Archive for the ‘Stell Cell Research’ Category

Pathways to Stem Cell Science | Methods in Stem Cell …

Stell Cell Research | Posted by admin
Mar 18 2019

Methods in Stem Cell Engineering is a four-session afterschool program exploring the science of gene modulation in stem cells. Participating students learn basic hands-on lab skills, using RNA interference (RNAi) to silence the expression of an oncogene in human cancer stem cells.

RNAi is a sophisticated technique that scientists use to inhibit the expression of specific genes in order to study their function. During Methods in Stem Cell Engineering, students learn bioinformatical approaches to designing an RNAi experiment and measure the effect of inhibiting the gene oct-4 in stem cells derived from testicular cancers. They also explore the real-world applications of RNAi technology, hearing from guest speakers and experts in the field of stem cell engineering.

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Pathways to Stem Cell Science | Methods in Stem Cell ...

Perception of Depth by Michael Kalloniatis and Charles Luu …

Stell Cell Research | Posted by admin
Mar 18 2019

Michael Kalloniatis and Charles Luu

Stereopsis

Stereopsis refers to our ability to appreciate depth, that is the ability to distinguish the relative distance of objects with an apparent physical displacement between the objects. It is possible to appreciate the relative location of objects using one eye (monocular cues). However, it is the lateral displacement of the eyes that provides two slightly different views of the same object (disparate images) and allow acute stereoscopic depth discrimination.

Monocular Cues

Several strong monocular cues allow relative distance and depth to be judged. These monocular cues include:

Relative Size: Retinal image size allow us to judge distance based on our past and present experience and familiarity with similar objects. As the car drives away, the retinal image becomes smaller and smaller. We interpret this as the car getting further and further away. This is referred to as size constancy. A retinal image of a small car is also interpreted as a distant car (figure 1).

Figure 1. Relative size. A retinal image of a small car is considered to be distant

Interposition: Interposition cues occur when there is overlapping of objects. The overlapped object is considered further away (figure 2).

Figure 2. Interposition. The blue circle is reported to be closer since it overlaps the red circle

Linear Perspective: When objects of known distance subtend a smaller and smaller angle, it is interpreted as being further away. Parallel lines converge with increasing distance such as roads, railway lines, electric wires, etc (figure 3).

Figure 3. Linear perspective. Parallel lines such as railway lines converge with increasing distance

Aerial Perspective: Relative colour of objects give us some clues to their distance. Due to the scattering of blue light in the atmosphere, creating wall of blue light, distance objects appear more blue (figure 4). Thus distant mountains appear blue. Contrast of objects also provide clues to their distance. When the scattering of light blurs the outlines of objects, the object is perceived as distant. Mountains are perceived to be closer when the atmosphere is clear.

Figure 4. Aerial perspective. Mountains in the distance appear more blue

Light And Shade: Highlights and shadows can provide information about an objects dimensions and depth (figure 5). Because our visual system assumes the light comes from above, a totally different perception is obtained if the image is viewed upside down.

Figure 5. Highlights and shadows provide information about depth

Monocular Movement Parallax: When our heads move from side to side, objects at different distances move at a different relative velocity. Closer objects move against the direction of head movement and farther objects move with the direction of head movement.

Binocular Cues

Stereopsis is an important binocular cue to depth perception. Stereopsis cannot occur monocularly and is due to binocular retinal disparity within Panums fusional space. Stereopsis is the perception of depth produced by binocular retinal disparity. Therefore, two objects stimulates disparate (non-corresponding) retinal points within Panums fusional area.

Fusion describes the neural process that brings the retinal images in the two eyes to form one single image. Fusion occurs to allow single binocular vision. Fusion takes place when the objects are the same. When the objects are different, suppression, superimposition or binocular (retinal) rivalry may occurs. Suppression occurs to eliminate one image to prevent confusion. Superimposition results in one image presented on top of the other image. Binocular rivalry describes alternating suppression of the two eyes resulting in alternating perception of the two images. This usually occurs when lines are presented to the two eyes differ in orientation, length or thickness. An example of binocular rivalry occurs when one eye is presented with a horizontal line and the other eye is presented with a vertical line. Binocular rivalry occurs at the intersection of the lines and some suppression also exists (figure 6)

Figure 6. (a) Binocular rivalry can be demonstrated by placing a pen between yourself and the screen. Keep you eye on the tip of the pen and notice the two bars merge. You may need to slowly move the pen from the screen towards you. (b) Result of (a)

Panums fusional area is the region of binocular single vision. Outside Panums fusional area, physiological diplopia occurs. Using the haplopic method of determining the horopter, Panums area can be determined (figure 7).

Figure 7. Haplopic method of determining the horopter involves locating the region of single binocular vision at a distance of 40cm.Panums fusional area lies between the outer and inner limits of the region of single binocular vision

Retinal disparity: Retinal disparate points are retinal points that give rise to different principal visual direction and diplopia. However, retinal disparity within Panums fusional area (zone of single binocular vision) can be fused resulting in single vision. Retinal disparity is essential for stereoscopic depth perception as stereoscopic depth perception results from fusion of slightly dissimilar images. Due to the lateral displacement of our eyes, slightly dissimilar retinal images result from the different perception of the same object from each eye.

Clinical Tests used to measure Stereopsis

There are two groups of clinical tests used to measure stereopsis. These are the contour stereotests and the random-dot stereotest. Random-dot stereograms were first used by Julesz (1960) to eliminate monocular cues. As there are no contours, depth perception (stereopsis) can only be appreciated when binocular fusion occurs. Two process of stereopsis are used and these are local and global stereopsis. Local stereopsis exists to evaluate the two horizontally disparate stimuli. This process is sufficient for contour stereotests. Global stereopsis is required in random-dot stereogram when the evaluation and correlation of corresponding points and disparate points are needed over a large retinal area.

An example of a contour stereotest used in the clinic is the Titmus Fly Stereotest. In the Titmus Fly Stereotest, horizontal disparity is presented via the vectographic technique (Fricke and Siderov, 1997). When tested a 40 cm the fly has a disparity of 3,600 sec of arc; the disparity of the animals range from 400 100 sec of arc and the disparity of the Wirt rings range from 800 40 sec of arc (figure 8).

Figure 8. Titmus Fly Stereotest

Examples of random-dot stereotests used in the clinic are the Frisby Stereotest, the Randot Stereotest, the Random-dot E Stereotest and the Lang Stereotest. The Frisby Stereotest (figure 9) uses real depth to determine stereoacuity. Three perspex of different thicknesses are used. Four squares of geometric shapes are painted on one side of the perspex. In one of the squares, a circle of these geometric shape is painted on the other side of the perspex. Both the Randot (figure 10) and the Random-dot E uses crossed polarised filters. Disparity is also constructed vectographically. The Randot Stereotest uses modified animals and ring designs with random dot backgrounds to eliminate monocular cues. The Lang Stereotest uses a panographic technique (Fricke and Siderov, 1997) to present disparity, therefore, no filters are required. Patients are required to identify pictures on the Lang Stereotest. The Lang II Stereotest has a monocularly visible shape on it (figure 11).

Figure 11. The Lang II

All the tests provides a measure of stereoacuity by asking the patient to identify the correct target that has stereoscoptic depth (target with disparity). The working distance and interpupillary distance will need to be taken into consideration when calculating stereoacuity. Patients with disturbed binocular vision or different refractive error in one eye, will perform poorly on depth discrimination tests.

Acknowlegements

We like to thank Tim Fricke for providing Figures 8-11.

References.

Fricke TR and Siderov J (1997) Stereopsis, stereotest and their relation to vision screening and clinical practice.Clin Exp Optom. 80: 165-172.

Julesz B. Binocular depth perception of computer generated patterns.Bell Syst Tech J.1960;39:11251162.2.

Moses RA and Hart WM (1987)Adlers Physiology of the eye, Clinical Application, 8th ed. St. Louis: The C. V. Mosby Company.

Ogle KN (1950)Researches in Binocular Vision. London: Saunders. 1950

Schwartz SH (1999)Visual Perception, 2nd ed. Connecticut: Appleton and Lange.

Last Update: June 6, 2007.

The author

Michael Kalloniatiswas born in Athens Greece in 1958. He received his optometry degree and Masters degree from the University of Melbourne. His PhD was awarded from the University of Houston, College of Optometry, for studies investigating colour vision processing in the monkey visual system. Post-doctoral training continued at the University of Texas in Houston with Dr Robert Marc. It was during this period that he developed a keen interest in retinal neurochemistry, but he also maintains an active research laboratory in visual psychophysics focussing on colour vision and visual adaptation. He was a faculty member of the Department of Optometry and Vision Sciences at the University of Melbourne until his recent move to New Zealand. Dr. Kalloniatis is now the Robert G. Leitl Professor of Optometry, Department of Optometry and Vision Science, University of Auckland.e-mail:m.kalloniatis@unsw.edu.au

The author

Charles Luuwas born in Can Tho, Vietnam in 1974. He was educated in Melbourne and received his optometry degree from the University of Melbourne in 1996 and proceeded to undertake a clinical residency within the Victorian College of Optometry. During this period, he completed post-graduate training and was awarded the post-graduate diploma in clinical optometry. His areas of expertise include low vision and contact lenses. During his tenure as a staff optometrist, he undertook teaching of optometry students as well as putting together the Cyclopean Eye, in collaboration with Dr Michael Kalloniatis. The Cyclopean Eye is a Web based interactive unit used in undergraduate teaching of vision science to optometry students. He is currently in private optometric practice as well as a visiting clinician within the Department of Optometry and Vision Science, University of Melbourne.

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Perception of Depth by Michael Kalloniatis and Charles Luu ...

Why does my DAB signal disappear so quickly?

Stell Cell Research | Posted by admin
Mar 10 2019

Hi everyone,

Great suggestions, thanks for sharing your thoughts. I have tried using fresh dehydrating alcohols, but still got the same results. I may try some of the different mounting media you suggested and a different source of DAB. I have not tried leaving out the differentiation step with acid alcohol. Is there a particular bluing reagent that works best?

The details of my protocol are as follows:

The sections were fixed in Modified Davidsons solution, paraffin embedded, re-hydrated, underwent sodium citrate heat-mediated antigen retrieval for 20 minutes, rinsed in PBS, incubated with 10% normal goat serum in PBS for 1 hour at room temperature, incubated with primary antibody in PBS overnight at 4 degrees C, rinsed in PBS, quenched for endogenous peroxidase in 3% hydrogen peroxidase for 15 minutes, rinsed in PBS, incubated with biotinylated secondary antibody in PBS for 1 hour at room temperature, rinsed in PBS, incubated with avidin and biotinylated horseradish peroxidase complex for 30 minutes, rinsed in PBS, developed with DAB (Invitrogen) for 1-2 minutes, counterstained with hematoxylin, rinsed in water, differentiated in acid alcohol, rinsed in water, blued in 0.2% ammonia water, rinsed in water, dehydrated in three changes of isopropanol, cleared through three changes of xylene, and mounted using Cytoseal XYL.

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Why does my DAB signal disappear so quickly?

Atmospheric & Environmental Chemistry | Aerodyne Research …

Stell Cell Research | Posted by admin
Mar 06 2019

Development of a NOx chemistry module for EDMS/AEDT to predict NO2 concentrations, R. Miake-Lye, S. Herndon, M. Kenney, ACRP, National Academy of Sciences, 2017.

Revisiting global fossil fuel and biofuel emissions of ethane, Z. A. Tzompa-Sosa, E. Mahleu, B. Franco, C. A. Keller, A. J. Turner, D. Helmig, A. Fried, D. Richter, P. Welbring, J. Walega, T. L. Yacovitch, S. C. Herndon, D. R. Blake, F. Hase, J. W. Hannigan, S. Conway, K. Strong, M. Schnelder, E. V. Fischer,J. Geophys. Atmos,, 122, 2493-2512, 2017.

Dynamics of canopy stomatal conductance, transpiration, and evaporation in a temperate decidious forest, validated by carbonyl sulfide uptake, R. Wehr, R. Commane, J. Munger, J. B. McManus, D. Nelson, M. Zahniser, S. Saleska, S. Wofsy, Biogeosciences,14, 389-401, 2017.

Interannual variability of ammonia concentrations over the United States: sources and implications, L. D. Schiferl, C. L. Heald, M. Van Damme, L. Clarisse, C. Clerbaux, P. Coheur, J. B. Nowak, J. A. Neuman, S. C. Herndon, J. R. Roscioli, S. J. Ellerman, Atmos. Chem. Phys., 16, 12305-12328, 2016.

Using airborne technology to quantify and apportion emissions of CH4 and NH3 from feedlots, J. M. Hacker, D. Chen, M. Bai, C. Ewenz, W. Junkermann, W. Lieff, B. McManus, B. Neininger, J. Sun, T. Coates, T. Denmead, T. Flesch, S. McGinn, J. Hill, Animal Production Science, 56, 190-203, 2016.

Exhaust emissions from in-use general aviation aircraft, T. I. Yacovitch, Z. Yu, S. C. Herndon, R. Miake-Lye, D. Liscinsky, W. B. Knighton, M. Kenney, C. Schoonard, P. Pringle, Airport Cooperative Research Program, 2016.

Continuous and high-precision atmospheric concentration measurements of COS, CO2, CO and H2O using a quantum cascade laser specrometer (QCLS), L. M. J. Kooijmans, N. A. M. Uitslag, M. S. Zahniser, D. D. Nelson, S. A. Montzka, H. Chen, Amos. Meas. Tech., 9, 5293-5314, 2016.

Characterization of ammonia, methane, and nitrous oxide emissions from concentrated animal feeding operations in northeastern colorado, S. J. Eilerman, J. Peischl, J. A. Neuman, T. B. Ryerson, K. C. Aikin, M. W. Holloway, M. A. Zondlo, L. M. Golston, D. Pan, C. Floerchinger, S. Herndon, Env. Sci. & Technol., 50, 10885-10903, 2016.

Impacts of the Denver Cyclone on regional air quality and aerosol formation in the Colorado Front Range during FRAPPE 2014, K. T. Vu, J. H. Dingle, R. Bahreini, P. J. Reddy, E. C. Apel, T. L. Campos, J. P. DiGangi, G. S. Diskin, A. Freid, S. C. Herndon, A. J. Hills, R. S. Hornbrook, G. Huey, L. Kaser, D. D. Montzka, J. B. Nowak, S. E. Pusede, D. Richter, J. R. Roscioli, G. W. Sachse, S. Shertz, M. Stell, D. Tanner, G. S. Tyndall, J. Walega, P. Weibring, A. J. Weinheimer, G. Pfister, F. Flocke, Atmos. Chem. Phys., 16, 12039-12058, 2016.

Seasonal and diurnal variation in CO fluxes from an agricultural bioenergy crop, M. Pihlatie, U. Rannik, S. Haapanala, O. Peltola, N. Shurpali, P. J. Martikainen, S. Lind, N. Hyvonen, P. Virkajarvi, M. Zahniser, I. Mammarella, Biogeosciences, 13, 5471-5485, 2016.

Surface-atmosphere exchange of ammonia over peatland using QCL-based eddy-covariance measurements and inferential modeling, U. Zoll, C. Brummer, F. Shcrader, C. Ammann, A. Ibrom, C. R. Flechard, D. D. Nelson, M. Zahniser, W. L. Kutsh, Atmos. Chem. Phys. 16, 11283-11299, 2016.

Aerosol optical extinction during the Front Range Air Pollution and Photochemistry Experiment (FRAPPE) 2014 summertime field campaign, Colorado, USA, J. H. Dingle, K. Vu, R. Bahreini, E. C. Apel, T. L. Campos, F. FLocke, A. Fried, S. Herndon, A. J. Hills, R. S. Hornbrook, G. Huey, L. Kaser, D. D. Montzka, J. B. Nowak, M. Reeves, D. Richter, J. R. Roscioli, S. Shertz, M. Stell, D. Tanner, G. Tyndall, J. Walega, P. Weibring, A. Weinheimer, Atmos. Chem. Phys., 16, 11207-11217, 2016.

Direct and indirect measurements and modeling of methane emissions in Indianapolis, Indiana, B. K. Lamb, M. Cambaliza, K. J. Davis, S. L. Edburg, T. W. Ferrara, C. Floerchinger, A. M. Heimburger, S. Herndon, T. Lauvaux, T. Lavoie, D. R. Lyon, N. Miles, K. R. Prasad, S. Richardson, J. R. Roscioli, O. E. Salmon, P. B. Shepson, B. H. Stirm, J. Whetstone, Environ. Sci. Technol, 16, 8910-7, 2016.

Seasonality of temperate forest photosynthesis and daytime respiration, R. Wehr, J.W. Munger, J. B. McManus, D. D. Nelson, M. S. Zahniser, E. A. Davidson, S. C. Wofsy, S. R. Saleska, Nature Letter, 534, 680-683, 2016.

Dynamics of Ammonia Volatilisation Measured by Eddy Covariance During Slurry Spreading in North Italy, Rossana Monica Ferrara, Marco Carozzi, Paul Di Tommasi, David D. Nelson, Gerardo Fratini, Teresa Bertolini, Vincenzo Magliulo, Marco Acutis, Gianfranco Rana, Agriculture, Ecosystems & Environment, 219, 1-13, 2016.

The Development and Evaluation of Airborne in Situ N2O and CH4 Sampling Using a Quantum Cascade Laser Absorption Spectrometer (QCLAS) J. R. Pitt, M. LeBreton, G. Allen, C. J. Percival, M. W. Gallagher, S. J.-B. Bauguitte, S. J. O'Shea, J. B. A. Muller, M. S. Zahniser, J. Pyle, P. I. Palmer, Atmos. Meas. Tech., 9, 63-77, 2016.

Reconciling Divergent Estimates of Oil and Gas Methane Emissions, Daniel Zavala-Araizaa, David R. Lyona, Ramn A. Alvareza, Kenneth J. Davisb, Robert Harrissa, Scott C. Herndon, Anna Kariond, Eric Adam Kortf, Brian K. Lambg, Xin Lanh, Anthony J. Marchesei, Stephen W. Pacalaj, Allen L. Robinsonk, Paul B. Shepsonl, Colm Sweeneyd, Robert Talboth, Amy Townsend-Smallm, Tara I. Yacovitchc, Daniel J. Zimmerlei, Steven P. Hamburg, PNAS, 112, 1559715602, 2015.

Air Pollutant Mapping with a Mobile Laboratory During the BEE-TEX Field Study, Tara I. Yacovitch1, Scott C. Herndon, Joseph R. Roscioli1, Cody Floerchinger,W. Berk Knighton, Charles E. Kolb, Supplementary Issue: Ambient Air Quality (B), Environmental Health Insights, 9, 7-13, 2015.

New Approaches to Measuring Sticky Molecules: Improvement of Instrumental Response Times Using Active Passivation, J. R. Roscioli, M. S. Zahniser, D. D. Nelson, S. C. Herndon, C. E. Kolb, J. Phys. Chem. A, (Web): June 24, 2015.

Seasonal fluxes of carbonyl sulfide in a midlatitude forest, R. Commanea, L. K. Meredith, I. T. Baker, J. A. Berry, J. W. Munger, S. A. Montzka, P. H. Templer, S. M. Juice, M. S. Zahniser, S. C. Wofsy, PNAS, 112, 14162-14167, 2015.

Recent progress in laser-based trace gas instruments: performance and noise analysis, J. B. McManus, M. S. Zahniser, D. D. Nelson, J. H. Shorter, S. C. Herndon, D. Jervis, M. Agnese, R. McGovern, T. I. Yacovitch, J. R.Roscioli, Appl. Phys. B: Lasers Opt., 119, 203-218, 2015.

Methane Emissions from United States Natural Gas Gathering and Processing, A. J. Marchese, T. L. Vaughn, D. J. Zimmerle, D. M. Martinez, L. L. Williams, A. L. Robinson, A. L. Mitchell, R. Subramanian, D. S. Tkacik, J. R. Roscioli, S. C. Herndon, Environ. Sci. Technol., 49, 10718-10727, 2015.

Methane emissions from natural gas infrastructure and use in the urban region of Boston, Massachusetts, K. McKain, A. Down, S. M. Raciti, J. Budney, L. R. Hutyra, C. Floerchinger, S. C. Herndon, T. Nehrkorn, M. S. Zahniser, R. B. Jackson, N. Phillips, S. C. Wofsy PNAS, 112, 1941-1946, 2015.

Meteorology, Air Quality, and Health in London: The ClearfLo Project, S. I. Bohnenstengel, S. E. Belcher, A. Aiken, J. D. Allan, G. Allen, A. Bacak, T. J. Bannan, J. F. Barlow, D. C. S. Beddows, W. J. Bloss, A. M. Booth, C. Chemel, O. Coceal, C. F. Di Marco, M. K. Dubey, K. H. Faloon, Z. L. Fleming, M. Furger, J. K. Gietl, R. R. Graves, D. C. Green, C. S. B. Grimmond, C. H. Halios, J. F. Hamilton, R. M. Harrison, M. R. Heal, D. E. Heard, C. Helfter, S. C. Herndon, R. E. Holmes, J. R. Hopkins, A. M. Jones, F. J. Kelly, S. Kotthaus, B. Langford, J. D. Lee, R. J. Leigh, A. C. Lewis, R. T. Lidster, F. D. Lopez-Hilfiker, J. B. McQuaid, C. Mohr, P. S. Monks, E. Nemitz, N. L. Ng, C. J. Percival, A. S. H. Prvt, H. M. A. Ricketts, R. Sokhi, D. Stone, J. A. Thornton, A. H. Tremper, A. C. Valach, S. Visser, L. K. Whalley, L. R. Williams, L. Xu, D. E. Young, P. Zotter, Bull. Amer. Meteor. Soc., 96, 779804, 2015.

Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region, D. R. Lyon, D. Zavala-Araiza, R. A. Alvarez, R. Harriss, V. Palacios, X. Lan, R. Talbot, T. Lavoie, P. Shepson, T. I. Yacovitch, S. C. Herndon, A. J. Marchese, D. Zimmerle, A. L. Robinson, S. P. Hamburg, Environ. Sci. Technol., 49, 81478157, 2015.

Mobile Laboratory Observations of Methane Emissions in the Barnett Shale Region, T. I. Yacovitch, S. C. Herndon, G. Ptron, J. Kofler, D. Lyon, M. S. Zahniser, C. E. Kolb, Environ. Sci. Technol., 49, 78897895, 2015.

Airborne Ethane Observations in the Barnett Shale: Quantification of Ethane Flux and Attribution of Methane Emissions, M. L. Smith, E. A. Kort, A. Karion, C. Sweeney, S. C. Herndon, T. I. Yacovitch, Environ. Sci. Technol., 49, 81588166, 2015.

Aircraft-Based Estimate of Total Methane Emissions from the Barnett Shale Region, A. Karion, C. Sweeney, E. A. Kort, P. B. Shepson, A. Brewer, M. Cambaliza, S. A. Conley, K. Davis, A. Deng, M. Hardesty, S. C. Herndon, T. Lauvaux, T. Lavoie, D. Lyon, T. Newberger, G. Ptron, C. Rella, M. Smith, S. Wolter, T. I. Yacovitch, P. Tans, Environ. Sci. Technol., 49, 81248131, 2015.

Aircraft-Based Measurements of Point Source Methane Emissions in the Barnett Shale Basin, T. N. Lavoie, P. B. Shepson, M. O. L. Cambaliza, B. H. Stirm, A. Karion, C. Sweeney, T. I. Yacovitch, S. C. Herndon, X. Lan, D. Lyon, Environ. Sci. Technol., 49, 79047913, 2015.

Atmospheric Emission Characterization of Marcellus Shale Natural Gas Development Sites, J. D. Goetz, C. Floerchinger, E. C. Fortner, J. Wormhoudt, P. Massoli, W. B. Knighton, S. C. Herndon, C. E. Kolb, E. Knipping, S. L. Shaw, P. F. DeCarlo, Environ. Sci. Technol., 49, 70127020, 2015.

Vehicle emissions of radical precursors and related species observed in the 2009 SHARP campaign, J. Wormhoudt, E. C. Wood, W. B. Knighton, C. E. Kolb, S. C. Herndon, E. P. Olague, J. Air Waste Manage. Assoc., 65, 699-706, 2015.

Airborne in situ vertical profiling of HDO/H216O in the subtropical troposphere during the MUSICA remote sensing validation campaign, C. Dyroff, S. Sanati, E. Christner, A. Zahn, M. Balzer, H. Bouquet, J. B. McManus, Y. Gonzlez-Ramos, M. Schneider, Atmos. Meas. Tech. Discuss., 8, 121155, 2015.

Design and performance of a dual-laser instrument for multiple isotopologues of carbon dioxide and water, J. B. McManus, D. D. Nelson, M. S. Zahniser, Opt. Express, 23, 6569-6586, 2015.

Intercomparison of fast response commercial gas analysers for nitrous oxide flux measurements under field conditions, . Rannik, S. Haapanala, N. J. Shurpali, I. Mammarella, S. Lind, N. Hyvnen, O. Peltola, M. Zahniser, P. J. Martikainen, T. Vesala, Biogeosciences, 12, 415-431, 2015.

Development and field testing of a rapid and ultra-stable atmospheric carbon dioxide spectrometer, B. Xiang, D. D. Nelson, J. B. McManus, M. S. Zahniser, R. A. Wehr, S. C. Wofsy, Atmos. Meas. Tech., 7, 4445-4453, 2014.

Feasibility and Potential Utility of Multicomponent Exhaled Breath Analysis for Predicting Development of Radiation Pneumonitis after Stereotactic Ablative Radiotherapy, J. M. Mor, N. C.W. Eclov, M. P. Chung, J. F. Wynne, J. H. Shorter, D. D. Nelson, A. L. Hanlon, R. Burmeister, P. Banos, P. G. Maxim, B. W. Jr Loo, M. Diehn, J. Thorac. Oncol., 9, 957-964, 2014.

Demonstration of an Ethane Spectrometer for Methane Source Identification, T. I. Yacovitch, S. C. Herndon, J. R. Roscioli, C. Floerchinger, R. M. McGovern, M. Agnese, G. Ptron, J. Kofler, C. Sweeney, A. Karion, S. A. Conley, E. A. Kort, L. Nhle, M. Fischer, L. Hildebrandt, J. Koeth, J. B. McManus, D. D. Nelson, M. S. Zahniser, C. E. Kolb, Environ. Sci. Technol., 48, 8028-8034, 2014.

Sources and sinks of carbonyl sulfide in an agricultural field in the Southern Great Plains, K. Maseyk, J. A. Berry, D. Billesbach, J. E. Campbell, M. S. Torn, M. Zahniser, U. Seibt, PNAS, 111, 9064-9069, 2014.

Measurement of a doubly substituted methane isotopologue, 13CH3D, by tunable infrared laser direct absorption spectroscopy, S. Ono, D. T. Wang, D. S. Gruen, B. S. Lollar, M. S. Zahniser, B. J. McManus, D. D. Nelson, Anal. Chem., 86, 64876494, 2014.

Greenhouse gas budget (CO2, CH4 and N2O) of intensively managed grassland following restoration, L. Merbold, W. Eugster, J. Stieger, M. Zahniser, D. Nelson, N. Buchmann, Global Change Biol., 20, 19131928, 2014.

Simulation of semi-explicit mechanisms of SOA formation from glyoxal in a 3-D model, C. Knote, A. Hodzic, J. L. Jimenez, R. Volkamer, J. J. Orlando, S. Baidar, J. Brioude, J. Fast, D. R. Gentner, A. H. Goldstein, P. L. Hayes, W. B. Knighton, H. Oetjen, A. Setyan, H. Stark, R. Thalman, G. Tyndall, R. Washenfelder, E. Waxman, Q. Zhang, Atmos. Chem. Phys., 14, 6213-6239, 2014.

Evaluation of the airborne quantum cascade laser spectrometer (QCLS) measurements of the carbon and greenhouse gas suite CO2, CH4, N2O, and CO during the CalNex and HIPPO campaigns, G. W. Santoni, B. C. Daube, E. A. Kort, R. Jimnez, S. Park, J. V. Pittman, E. Gottlieb, B. Xiang, M. S. Zahniser, D. D. Nelson, J. B. McManus, J. Peischl, T. B. Ryerson, J. S. Holloway, A. E. Andrews, C. Sweeney, B. Hall, E. J. Hintsa, F. L. Moore, J. W. Elkins, D. F. Hurst, B. B. Stephens, J. Bent, and S. C. Wofsy, Atmos. Meas. Tech., 7, 1509-1526, 2014.

Measurement of a doubly substituted methane isotopologue, 13CH3D, by tunable infrared laser direct absorption spectroscopy, S. Ono, D. T. Wang, D. S. Gruen, B. S. Lollar, M. S. Zahniser, B. J. McManus, D. D. Nelson, Anal.Chem, (Web): June 4, 2014.

Intercomparison of field measurements of nitrous acid (HONO) during the SHARP campaign, J. P. Pinto, J. Dibb, B. H. Lee, B. Rappenglck, E. C. Wood, M. Levy, R.-Y. Zhang, B. Lefer, X.-R. Ren, J. Stutz, C. Tsai, L. Ackermann, J. Golovko, S. C. Herndon, M. Oakes, Q.-Y. Meng, J. W. Munger, M. Zahniser,J. Zheng, J. Geophys. Res. Atmos., 119, 55835601, DOI: 10.1002/2013JD020287, 2014.

Development of a Spectroscopic Technique for Continuous Online Monitoring of Oxygen and Site-Specific Nitrogen Isotopic Composition of Atmospheric Nitrous Oxide, E. Harris, D. D. Nelson, W. Olszewski, M. Zahniser, K. E. Potter, B. J. McManus, A. Whitehill, R. G. Prinn, S. Ono, Anal. Chem., 86, 17261734, 2014.

Urban measurements of atmospheric nitrous acid: A caveat on the interpretation of the HONO photostationary state, B. H. Lee, E. C. Wood, S. C. Herndon, B. L. Lefer, W. T. Luke, W. H. Brune, D. D. Nelson, M. S. Zahniser, J. W. Munger, J. Geophys. Res. Atmos., 118, 12,27412,281, doi:10.1002/2013JD020341 2013.

Carbonyl sulfide in the planetary boundary layer: Coastal and continental influences, R. Commane, S. C. Herndon, M. S. Zahniser, B. M. Lerner, J. B. McManus, J. W. Munger, D. D. Nelson, S. C. Wofsy, JGR, Atmos. 118, Issue 14, 80018009, DOI:10.1002/jgrd.5058, 2013.

Measurements of methane emissions at natural gas production sites in the United States, D. T. Allen, V. M. Torres, J. Thomas, D. W. Sullivan, M. Harrison, A. Hendler, S. C. Herndon, C. E. Kolb, M. P. Fraser, A. D. Hill, B. K. Lamb, J. Miskimins, R. F. Sawyer, J. H. Seinfeld, PNAS, 110, 17768-17773, 2013.

Contribution of Nitrated Phenols to Wood Burning Brown Carbon Light Absorption in Detling, United Kingdom during Winter Time, C. Mohr, F. D. Lopez-Hilfiker, P. Zotter, A. S. H. Prvt, L. Xu, N. L. Ng, S. C. Herndon, L. R. Williams, J. P. Franklin, M. S. Zahniser, D. R. Worsnop, W. B. Knighton, A. C. Aiken, K. J. Gorkowski, M. K. Dubey, J. D. Allan, J. A. Thornton, Environ. Sci. Technol., 47, 63166324, 2013.

Long-term eddy covariance measurements of the isotopic composition of the ecosystematmosphere exchange of CO2 in a temperate forest, R. Wehr, J. W. Munger, D. D. Nelson, J. B. McManus, M. S. Zahniser, S. C. Wofsy, S. R. Saleska, Agric. For. Meteorol., 181, 69-84, 2013.

Online measurements of the emissions of intermediate-volatility and semi-volatile organic compounds from aircraft, E. S. Cross, J. F. Hunter, A. J. Carrasquillo, J. P. Franklin, S. C. Herndon, J. T. Jayne, D. R. Worsnop, R. C. Miake-Lye, and J. H. Kroll, Atmos. Chem. Phys., 13, 7845-7858, 2013.

Towards a stable and absolute atmospheric carbon dioxide instrument using spectroscopic null method, B. Xiang, D. D. Nelson, J. B. McManus, M. S. Zahniser, S. C. Wofsy, Atmos. Meas. Meas. Tech., 6, 1611-1621, 2013.

Selective measurements of NO, NO2 and NOy in the free troposphere using quantum cascade laser spectroscopy, B. Tuzson, K. Zeyer, M. Steinbacher, J. B. McManus, D. D. Nelson, M. S. Zahniser, L. Emmenegger, Atmos. Meas. Tech. Discuss., 5, 89698993, 2012.

Detecting fugitive emissions of 1,3-butadiene and styrene from a petrochemical facility: An application of a mobile laboratory and a modified proton transfer reaction mass spectrometer, W. B. Knighton, S. C. Herndon, E. C. Wood, E. C. Fortner, T. B. Onasch, J. Wormhoudt, C. E. Kolb, B. H. Lee, M. Zavala, L. Molina, M. Jones, Industrial & Engineering Chemistry Research, 51, 1267412684, 2012.

Direct measurement of volatile organic compound emissions from industrial flares using real-time online techniques: Proton transfer reaction mass spectrometry and tunable infrared laser differential absorption spectroscopy, W. B. Knighton, S. C. Herndon, J. F. Franklin, E. C. Wood, J. Wormhoudt, W. Brooks, E. C. Fortner, D. T. Allen, Industrial & Engineering Chemistry Research, 51, 1267412684, 2012.

Industrial flare performance at low flow conditions. 1. Study overview, V. M. Torres, S. Herndon, Z. Kodesh, D. T. Allen, Ind. Eng. Chem. Res., 51, 12559-12568, 2012.

Industrial flare performance at low flow conditions. 2. Steam- and air-assisted flares, V. M. Torres, S. Herndon, D. T. Allen, Ind. Eng. Chem. Res., 51, 12569-12576, 2012.

Application of the carbon balance method to flare emissions characteristics, S. C. Herndon, D. D. Nelson, Jr., E. C. Wood, W. B. Knighton, C. E. Kolb, Z. Kodesh, V. M. Torres, D. T. Allen, Ind. Eng. Chem. Res., 51, 12577-12585, 2012.

Emissions of nitrogen oxides from flares operating at low flow conditions, V. M. Torres, S. Herndon, E. Wood, F. M. Al-Fadhli, D. T. Allen, Ind. Eng. Chem. Res., 51, 12600-12605, 2012.

Effective line strengths of trans-nitrous acid near 1275 cm-1 and cis-nitrous acid at 1660 cm-1 , B. H. Lee, E. C. Wood, J. Wormhoudt, J. H. Shorter, M. S. Zahniser, J. W. Munger, J. Quant. Spectrosc. Radiat. Transfer, 113, 1905-1912, 2012.

Mass fluxes and isofluxes of methane (CH4) at a New Hampshire fen measured by a continuous wave quantum cascade laser spectrometer. G. W. Santoni, B. H. Lee, J. P. Goodrich, R. K. Varner, P. M. Crill, J. Barry McManus, D. D. Nelson, M. S. Zahniser, S. C. Wolfsy, JGR 117, D10301, doi:10.1029/2011JD016960, 15pp., 2012.

Modelled and measured concentrations of peroxy radicals and nitrate radical in the US Gulf Coast region during TexAQS 2006, R. Sommariva, T. S. Bates, D. Bon, D. M. Brookes, J. A. de Gouw, S. C. Herndon, W. C. Kuster, B. M. Lerner, P. S. Monks, H. D. Osthoff, A. E. Parker, J. M. Roberts, S. C. Tucker, C. Warneke, E. J. Williams, M. S. Zahniser, S. S. Brown, J. Atmos. Chem. 68, 331-362, 2012.

Primary and secondary sources of formaldehyde in urban atmospheres: Houston Texas region, D. D. Parrish, T. B. Ryerson, J. Mellqvist, J. Johansson, A. Fried, D. Richter, J. G. Walega, R. A. Washenfelder, J. A. de Gouw, J. Peischl, K. C. Aikin, S. A. McKeen, G. J. Frost, F. C. Fehsenfeld, S. C. Herndon, Atmos. Chem. Phys. 12, 3273-3288, 2012.

Establishing Policy Relevant Background (PRB) Ozone Concentrations in the United States, E. C. McDonald-Buller, D. T Allen, N. Brown, D. J. Jacob, D. Jaffe, C. E. Kolb, A. S. Lefohn, S. Oltmans, D. D. Parrish, G. Yarwood, L. Zhang, Environ. Sci. Tech. 45, 9484-9497, 2011.

Measurements of nitrous acid in commercial aircraft exhaust at the alternative aviation fuel experiment, B. H. Lee, G. W. Santoni, E. C. Wood, S. C. Herndon, R. C. Miake-Lye, M. S. Zahniser, S. C. Wofsy, J. W. Munger, Environ. Sci. Tech. 45, 7648-7651, 2011.

Monomer, clusters, liquid: an integrated spectroscopic study of methanol condensation, H. Laksmono, S.Tanimura, H. C. Allen, G. Wilemski, M. S. Zahniser, J. H. Shorter, D. D. Nelson, J. B. McManus, B. E. Wyslouzil, Phys. Chem. Chem. Phys., 13, 5855-5871, 2011.

Measurements of volatile organic compounds at a suburban ground site (T1) in Mexico City during the MILAGRO 2006 campaign: measurement comparison, emission ratios, and source attribution, D. M. Bon, I. M. Ulbrich, J. A. de Gouw, C. Warneke, W. C. Kuster, M. L. Alexander, A. Baker, A. J. Beyersdorf, D. Blake, R. Fall, J. L. Jimenez, S. C. Herndon, L. G. Huey, W. B. Knighton, J. Ortega, S. Springston, O. Vargas, Atmos. Chem. Phys., 11, 2399-2421, 2011.

Ozone production in remote oceanic and industrial areas derived from ship based measurements of peroxy radicals TexAQS 2006, R. Sommariva, S. S. Brown, J. M. Roberts, D. M. Brookes, A. E. Parker, P. S. Monke, T. S. Bates, D. Bon, J. A. De Gouw, G. .J. Frost, J. B. Gilman, P. D. Goldan, S. C. Herndon, W. C. Kuster, B. M. Lerner, H. D. Osthuff, S. C. Tucker, C. Warneke, E. J. Williams, M. S. Zahniser, Atmos. Chem. Phys., 11, 2471-2485, 2011.

Dual quantum cascade laser trace gas instrument with astigmatic Herriott cell at high pass number, J. B. McManus, M. S. Zahniser, D. D. Nelson, Appl. Opt., 50, A74-A84, 2011.

Investigation of the correlation between odd oxygen and secondary organic aerosol in Mexico City and Houston, E. C. Wood, M. R. Canagaratna, S. C. Herndon, T. B. Onasch, C. E. Kolb, D. R. Worsnop, J. H. Kroll, W. B. Knighton, R. Seil, M. Zavala, L. T. Molina, P. F. DeCarlo, J. L. Jimenez, A. J. Weinheimer, D. J. Knapp, B. T. Jobson, J. Stutz, W. C. Kuster, and E. J. Williams, Atmos. Chem. Phys 10, 8947-8968, 2010.

Application of quantum cascade lasers to high-precision atmospheric trace gas measurements, J. B. McManus, M. S. Zahniser, D. D. Nelson Jr., J. H. Shorter, S. Herndon, E. Wood, F. Wehr, Opt. Eng. 49, 111124, 2010.

Gas turbine engine emissions - Part I: Volatile organic compounds and nitrogen oxides, M. T. Timko, S. C. Herndon, E. C. Wood, T. B. Onasch, M. J. Northway, J. T. Jayne, M. R. Canagaratna, R. C. Miake-Lye, W. B. Knighton, J. Eng. Gas Turb. Power, 132, 06154 (14 pages), 2010.

Gas turbine engine emissions - Part II: Chemical properties of particulate matter, M. T. Timko, T. B. Onasch, M. J. Northway, J. T. Jayne, M. R. Canagaratna, S. C. Herndon, E. C. Wood, R. C. Miake-Lye, W. B. Knighton, J. Eng. Gas Turb. Power, 132, 061505 (15 pages), 2010.

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City, D. A. Thornhill, A. E. Williams, T. B. Onasch, E. Wood, S. C. Herndon, C. E. Kolb, W. B. Knighton, M. Zavala, L. T. Molina, L. C. Marr, Atmos. Chem. Phys. 10, 3629-3644, 2010.

Characterizing a quantum cascade tunable infrared laser differential absorption spectrometer (QC-TILDAS) for measurements of atmospheric ammonia, R. A. Ellis, J. G. Murphy, E. Pattey, R. van Haarlem, J. M. O'Brien, S. C. Herndon, Atmos. Meas. Tech. 3, 397-406, 2010.

Multicomponent breath analysis with infrared absorption using room-temperature quantum cascade lasers, J. H. Shorter, D. D. Nelson, J. Barry McManus, M. S. Zahniser, D. K. Milton, IEEE Sensors J., 10, 76-84, 2010.

Quantum cascade lasers in chemical physics, R. F. Curl, F. Capasso, C. Gmachl, A. A. Kosterev, B. McManus, R. Lewicki, M. Pusharsky, G. Wysocki, F. K. Tittel, Chem. Phys. Lett. 487, 1-18, 2010.

Long-term continuous sampling of 12CO2, 13CO2 and 12C18O16O in ambient air with a quantum cascade laser spectrometer, J. B. McManus, D. D. Nelson, M. S. Zahniser, Isot. Environ. Health Stu. 46, 49-63, 2010.

Adaptation of a proton transfer reaction mass spectrometer instrument to employ NO+ as reagent ion for the detection of 1,3-butadiene in the ambient atmosphere, W. B. Knighton, E. C. Fortner, S. C. Herndon, E. C. Wood, R. C. Miake-Lye, Rapid Commun. Mass Spectrom., 23, 3301-3308, 2009.

Hit from both sides: tracking industrial and volcanic plumes in Mexico City with surface measurements and OMI SO2 retrievals during the MILAGRO field campaign, B.deFoy, N.A.Krotkov, N.Bei, S.C.Herndon, L.G.Huey, A.-P.Martnez, L.G.Ruiz-Surez, E.C.Wood, M.Zavala, L.T.Molina, Atmos. Chem. Phys. 9, 9599-9617, 2009.

High precision measurements of atmospheric concentrations and plant exchange rates of carbonyl sulfide using mid-IR quantum cascade laser, K. Stimler, D. Nelson, D. Yakir, Glob. Change Biol. 16, 2496-2503, 2010.

HCN detection with a proton transfer reaction mass spectrometer, W. B. Knighton, E. C. Fortner, A. J. Midley, A. A. Viggiano, S. C. Herndon, E. C. Wood, C. E. Kolb, Int. J. Mass. Spectrom. 283, 112-121, 2009.

Emissions of NOx SO2, CO, and HCHO from commercail marine shipping during Texas Air Quality Study (TEXAQS) 2006, E. J. Williams, B. M. Lerner, P. C. Herndon, M. S. Zahniser, JGR, 114, D21306, doi:10.1029/2009JD012094, 2009.

Measurements of volatile organic compounds during the 2006 TexAQS/GoMACCS campaign: Industrial influences, regional characteristics, and diurnal dependencies of the OH reactivity, J. B. Gilman, W. C. Kuster, P. D. Goldan, S. C. Herndon, M. S. Zahniser, S. C. Tucker, W. A. Brewer, B. M. Lerner, E. J. Williams, R. A. Harley, F. C. Fehsenfeld, C. Warneke, J. A. de Gouw, JGR, 114, D00F06, doi:10.1029/2008JD011525, 2009.

Aircraft hydrocarbon emissions at Oakland International Airport, S. C. Herndon, E. C. Wood, M. J. Northway, R. Miake-Lye, L. Thornhill, A. Beyersdorf, B. E. Anderson, R. Dowlin, W. Dodds, W. B. Knighton, Environ. Sci. Technol., 43, 1730-1736, 2009.

Comparison of emissions from on-road sources using a mobile laboratory under various driving and operational sampling modes, M.Zavala, S.C.Herndon, E.C.Wood, J.T.Jayne, D.D.Nelson, A.M.Trimborn, E.Dunlea, W.B.Knighton, A.Mendoza, D.T.Allen, C.E.Kolb, M.J.Molina, and L.T.Molina, Atmos. Chem. Phys.,9,1-14,2009.

ACRP Report 7: Aircraft and Airport-Related Hazardous Air Pollutants: Research Needs and Analysis, E. Wood, S. Herndon, R. C. Miake-Lye, D. Nelson, M. Seeley, 65p. (2008). Airport Cooperative Research Program, Transportation Research Board, Washington, DC

Correlation of secondary organic aerosol with odd oxygen in Mexico City, S. C. Herndon, T. B. Onasch, E. C. Wood, J. H. Kroll, M. R. Canagaratna, J. T. Jayne, M. A. Zavala, W. B. Knighton, C. Mazzoleni, M. K. Dubey, I. M. Ulbrich, J. L. Jimenez, R. Seila, J. A. de Gouw, B. de Foy, J. Fast, L. T. Molina, C. E. Kolb, doi:10.1029/2008GL034058, 2008.

Spatial and temporal variability of particulate polycyclic aromatic hydrocarbons in Mexico City, D. A. Thornhill, B. de Foy, S. C. Herndon, T. B. Onasch, E. C. Wood, M. Zavala, L. T. Molina, J. S. Gaffney, N. A. Marley, L. C. Marr1, Atmos. Chem. Phys., 8, 3093-3105, 2008.

High precision and continuous field measurements of 13C and 18O in carbon dioxide with a cryogen-free QCLAS, B. Tuzson, J. Mohn, M. J. Zeeman, R. A. Werner, W. Eugster, M. S. Zahniser, D. D. Nelson, J. B. McManus, L. Emmenegger, Appl. Phys. B, DOI: 10.1007/s00340-008-3085-4, 2008.

Pulsed quantum cascade laser instrument with compact design for rapid, high sensitivity measurements of trace gases in air, J. B. McManus, J. H. Shorter, D. D. Nelson, M. S. Zahniser, D. E. Glenn, R. M. McGovern, Appl. Phys. B., 92, 387-392, 2008.

Development of negative-ion proton-transfer chemical-ionization mass spectrometry (NI-PT-CIMS) for the measurement of gas-phase organic acids in the atmosphere, P. Veres, J. M. Roberts, C. Warneke, D. Welsh-Bon, M. Zahniser, S. Herndon, R. Fall, J. de Gouw, Int. J. Mass Spectrom., 274, 48-55, 2008.

New method for isotopic ratio measurements of atmospheric carbon dioxide using a 4.3 m pulsed quantum cascade laser, D. D. Nelson, J. B. McManus, S. C. Herndon, M. S. Zahniser, B. Tuzson, L. Emmenegger, Appl. Phys. B, 90, 301-310, 2008. Special Issue: 6th International Conference on tunable laser spectroscopy.

Quantum cascade laser based spectrometer for in situ stable carbon dioxide isotope measurements, B. Tuzson, M. J. Zeeman, M. S. Zahniser, L. Emmenegger, Infrared Physics & Technology, 51, (1), 198-206, 2008.

Suitability of quantum cascade laser spectroscopy for CH4 and N2O eddy covariance flux measurements, P. S. Kroon, A. Hensen, H. J. J. Jonker, M. S. Zahniser, W. H. van't Veen, A. T. Vermeulen, Biogeosciences, 4, Special issue, 715-728, 2007.

Laboratory evaluation of an aldehyde scrubber system specifically for the detection of acrolein, W. B. Knighton, S. C. Herndon, J. H. Shorter, R. C. Miake-Lye, M. S. Zahniser, K. Akiyama, A. Shimono, K. Kitasaka, H. Shimajiri, K. Sugihara, J. Air & Waste Manage. Assoc. 57,, 1370-1378, 2007.

Tunable diode laser absorption spectroscopy study of CH3CH2OD/D2O binary condensation in a supersonic Laval nozzle, S. Tanimura, B. E. Wyslouzil, M. S. Zahniser, J. H. Shorter, D. D. Nelson, J. B. McManus, J. Chem.Phys. 127, 034305 (13), 2007.

Towards realization of reactive gas amount of substance standards through spectroscopic measurements, P. M. Chu, D. D. Nelson, Jr., M. S. Zahniser, J. B. McManus, Q. Shi, J. C. Travis, IEEE T. Instrum. Meas., 56, 305-308, 2007.

Evaluation of nitrogen dioxide chemiluminescence monitors in a polluted urban environment, E. J. Dunlea, S. C. Herndon, D. D. Nelson, R. M. Volkamer, F. San Martini, P. M. Sheehy, M. S. Zahniser, J. H. Shorter, J. C. Wormhoudt, B. K. Lamb, E. J. Allwine, J. S. Gaffney, N. A. Marley, M. Grutter, C. Marquez, S. Blanco, B. Cardenas, A. Retama, C. R. Ramos Villegas, C. E. Kolb, L. T. Molina1, M. J. Molina, Atmos. Chem. Phys., 7, 26912704, 2007.

Airborne measurements of HCHO and HCOOH during the New England Air Quality Study 2004 using a pulsed quantum cascade laser spectrometer, S.C. Herndon, M.S. Zahniser, D.D. Nelson Jr., J. Shorter, J.B. McManus, R. Jimnez, C. Warneke, J.A. DeGouw, J. Geophys. Res., 112, D10S03, doi:10.1029/2006JD007600, 2007.

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Atmospheric & Environmental Chemistry | Aerodyne Research ...

Anyone have objective data on the effectiveness of the …

Stell Cell Research | Posted by admin
Feb 09 2019

@StemCellPioneers I think you raise an interesting argument, but not for the reasons you list. The FDA is at least trying to base decisions on ACTUAL DATA, whereas there IS NO VERIFIABLE DATA on the therapeutic use of stem cells. What the FDA is saying is that the study is limited, and thus should be interpreted with caution. Therefore, they are being CONSISTENT. Flawed or limited data does not equal legitimate data on which to base decisions. So yes, if a study is limited, according to the FDA, then it is acceptable that a potentially dangerous drug should be continued to be given to children.

I dont have access to this particular study from home, but I can already tell you that retrospective case control studies can have significant problems with bias and confounding. See, this study states in the methods The primary exposure measure was the presence of amphetamine, dextroamphetamine, methamphetamine, or methylphenidate according to informant reports or as noted in medical examiner records, toxicology results, or death certificates. Now, even without reading the paper, which I will, I can already identify a potential source of bias. Kids who experienced sudden death were probably a lot more likely to have an autopsy, where drugs would be found by toxicology, whereas the kids who died in auto accidents probably were less likely to have autopsies, and the investigators likely relied on interviews with the family (less reliable). Thus, I predict that when I read the study tomorrow, I will find more autopsies in the sudden death group, and thus a greater association of sudden death with stimulants (because they were found more frequently by a better method). We shall see.

In any event, at least the FDA is weighing DATA, pros and cons, etc. There have been many cases of the FDA pulling medications and-or issuing black box warnings (for example, the diet drug fen-phen). This is how the system works. No drug is perfect, and as such needs to be approved through prospective studies, and constantly reviewed via aftermarket analysis. If more proof accumulates indicating that stimulants are harmful in ADHD, you can be sure the FDA will pull the drugs from the market. In contrast, the stem cell pioneers are just pushing forward, without so much as a hint that there could be some benefit (save lots and lots of anecdotal stories, which could easily be attributed to placebo affects).

I will say this again (perhaps for the 5th or 6th time). As a physician-scientist I truly believe in the promise of stem cells. I really, really do. However, no one will ever know if stem cell treatments are effective if they arent studied in rigorous, well-controlled clinical trials. This is true of all new treatments. And I would ask, why are the purveyors of this treatment not the leaders in the field of stem cell research? You talk about reputable stem cell clinic or doctor, but I consider that a misnomer. No reputable doctor would perform these infusions without it being part of a clinical trial or as an already verified procedure. Furthermore, this thread has piqued my interest in this area, and Ive been doing a lot of web research over the past few days. Interestingly, quite a few of the doctors and clinics discussed on your very site have had major legal and ethical issues (including doctors that are heavily promoted), which argues against them being reputable. The doctors who run these clinics may claim to be scientists, but in reality, the bulk of cutting edge stem cell work is going on in major academic hospitals, not small, private clinics run by doctors with little to no scientific training.

Finally, I really hope you find what you are looking for in stem cell infusions. Neither I nor any doctor wants patients to suffer needlessly, but apparently the majority of the medical community views the current status of stem cell treatments to be in its infancy. Many of us are concerned that the quixotic pursuit of highly experimental stem cell treatments could be detrimental on an emotional, financial, and possibly biologic level.

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Anyone have objective data on the effectiveness of the ...

Learn Zone – VetCompass – Royal Veterinary College, RVC

Stell Cell Research | Posted by admin
Feb 09 2019

Veterinary Epidemiology in Practice - The VetCompass Programme

Dr. Dan O'Neill (VetCompass, RVC)

In this e-lecture, recorded as part of the VET Talks series hosted by the RVC, Dr Dan O'Neill gives an overview of practice-based veterinary epidemiological research and describes the important role of VetCompass in pushing the boundaries of this exciting new field.

Dr. Dan O'Neill (VetCompass, RVC) & Dr. Katy Evans (University of Nottingham) British Small Animal Veterinary Association Annual Congress, 2015

This talk was delivered at BSAVA Congress 2015 and addresses the importance of generating high quality evidence to inform decision-making for the improvement of canine welfare. Dr. Dan ONeill and Dr. Katy Evans discuss the importance of evidence-based veterinary advice when aiming to improve dog health at a population level, highlighting how large-scale, ongoing health surveillance projects such as VetCompass are vital in providing relevant, representative findings for practical use by clinicians.

This audio recording is shared by kind permission of the UK Kennel Club.

Dr. Dan O'Neill (VetCompass, RVC) & Aimee Llewellyn (Geneticist & Health Information Manager, UK Kennel Club)British Small Animal Veterinary Association Annual Congress, 2015

This talk was delivered as part of the first ever BSAVA lecture stream on Practical aspects of dog breeding. Dr. Dan ONeill and Aimee Llewellyn (of the Royal Veterinary College & UK Kennel Club respectively) presented information on the practical approaches veterinary practices can take to improve the advice they give to breeder clients. Bothspeakers emphasised the vital role that veterinary practitioners can play in improving dog health at a population level and highlighted the importance of large-scale, ongoing health surveillance projects such as VetCompass.

This audio recording is shared by kind permission of the UK Kennel Club.

Discussinghowwe canuse the information contained in veterinary clinical records to better understand pain-related welfare in companion animals

A short video about VetCompass with examples of evidence generated, with musical accompaniment (no speaker)

Information on the expected lifespan and causes of death in dogs in England based on a VetCompass Programme study

Find out how common epilepsy is in dogs and which breeds are affected

McGreevy, PD, Wilson BJ, Mansfield, CS.Church DB, Brodbelt DC, Dhand, N,Soares Magalhaes, RJ and O'Neill DG. (2018)Canine Genetics and Epidemiology

O'Neill DG, Baral L, Church DB, Brodbelt DC and Packer RMA (2018) Canine Genetics and Epidemiology 5:3.

O'Neill DG, Darwent EC, Church DB and Brodbelt DC (2017) Canine Genetics and Epidemiology 4:15

O'Neill DG, Yin Seah W, Church DB and Brodbelt DC (2017) Canine Genetics and Epidemiology 4:13

O'Neill DG, Coulson NR, Church DB and Brodbelt DC (2017) Canine Genetics and Epidemiology 4:7

O'Neill DG, Darwent EC, Church DB andBrodbelt DC (2016) Canine Genetics and Epidemiology, 3(1):1-12.

Summers JF, ONeill DG, Church DB, Thomson PC, McGreevy PD and Brodbelt DC. (2015) Canine Genetics and Epidemiology.

Boyd, C., Jarvis, S., McGreevy, P., Heath, S., Church, D., Brodbelt, D., and O'Neill, DG. (2018)Animal Welfare

Conroy, M., O'Neill, DG., Boag, A., Church, DB., and Brodbelt, DC. (2018). Journal of Small Animal Practice.

McDonald JL, Cleasby LR, Brodblet DC, Church DB and O'Neill DG (2017) Journal of Small Animal Practice DOI: 10.1111/jsap.12716, n/a-n/a. (Early view)

O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC (2014) Veterinary Journal.

O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC (2014) Journal of Feline Medicine and Surgery.

O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC(2014) PLoS One,9(3).

O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC(2013) The Veterinary Journal,198,638-643.

Mattin MJ, Boswood A, Church DB, Brodbelt DC (2018) Journal of Veterinary Internal Medicine

Mattin MJ, Boswood A, Church DB, McGreevy PD, O'Neill DG, Thomson PC, Brodbelt DC. (2015; Epub ahead of print) Preventive Veterinary Medicine

Mattin MJ, Boswood A, Church DB, Lpez-Alvarez J, McGreevy PD, O'Neill DG, Thomson PC, Brodbelt DC. (2015) Journal of Veterinary Internal Medicine

O'Neill DG, Gostelow R, Orme C, Church D., Niessen SJM, Verheyen K & Brodbelt DC (2016) Journal of Veterinary Internal Medicine

O'Neill DG, Scudder C, Faire JM, Church DB, McGreevy PD, Thomson PC andBrodbelt DC(2016)Journal of Small Animal Practice2016

Mattin MJ, O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC (2014) The Veterinary Record,174(14), 349.

Stephens MJ, O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC (2014) The Veterinary Record.

O'Neill DG, Case J, Boag AK, Church DB, McGreevy PD, Thomson PC & Brodbelt DC (2017) Journal of Small Animal Practice, DOI: 10.1111/jsap.12723, n/a-n/a

Erlen A, Potschka H, Volk HA, Sauter-Louis C, O'Neill DG, (2018) Journal of Veterinary Internal Medicine.

Kearsley-Fleet L, O'Neill DG, Volk HA, Chursh DB, Brodbelt DC (2013) The Veterinary Record;30;172

O'Neill, DG., Corah, CH., Church, DB., Brodbelt, DC., and Rutherford, L. (2018).Canine Genetics and Epidemiology

Shoop SJ,Marlow S,Church DB,English K,McGreevy PD,Stell AJ,Thomson PC,O'Neill DGandBrodbelt DC (2014) Canine Genetics and Epidemiology.

O'Neill, D.G., Lee, M.M, Brodbelt, D.C., Church, D.B. & Sanchez, R.F. (2017) Canine Genetics and Epidemiology 4:5

Anderson KL, O'Neill DG, Brodbelt DC, Church DB, Meeson RL, Sargan D, Summers JF, Zulch H & Collins LM(2018)Scientific Reports

O'Neill DG, Meeson RL, Sheridan A, Church DB andBrodbelt DC (2016) Canine Genetics and Epidemiology

Taylor-Brown FE, Meeson RL, Brodbelt DC, Church DB, McGreevy PD, Thomson PC & O'Neill DG. (2015) Veterinary Surgery

O'Neill D, Jackson C, Guy J, Church D, McGreevy P, Thomson P. & Brodbelt D.(2015) Canine Genetics and Epidemiology

O'Neill, D.G., O'Sullivan, A.M., Manson, E.A., Church, D.B., McGreevy, P.D., Boag, A.K. and Brodbelt, D.C. (2019) Veterinary Record

Stevens K.B., O'Neill D.G., Jepson R., Holm L.P., Walker D.J., andCardwell J.M.(2018) Veterinary Record

Hall, J.L., Owen, L., Riddell, A., Church, D.B., Brodbelt, D.C., and O'Neill D.G., (2018)Journal of Small Animal Practice.

O'Neill D.G., O'Sullivan AM, Manson EA, Church DB, Boag AK, McGreevy PD and Brodbelt D.C. and (2017)VeterinaryRecordDOI:10.1136/vr.104108 DOI:10.1111/jsap.12731

O'Neill D.G., Riddell A., Church D.B., Owen L., Brodbelt D.C. and Hall J.L. (2017) Journal of Small Animal Practice DOI:10.1111/jsap.12731

O'Neill DG, Elliott J, Church DB, McGreevy PD, Thomson PC, Brodbelt DC(2013) Journal of Veterinary Internal Medicine;27(4):814-21

Buckland, E., O'Neill, D., Summers, J., Mateus, A., Church, D., Redmond, L. and Brodbelt, D. Veterinary Record (2016) doi:10.1136/vr.103830

Summers JF, Hendricks A, Brodbelt DC (2014) BMC Veterinary Research.

O'Neill DG, Hendricks A, Summers JF,Brodbelt DC(2012) J Small Anim Pract;53(4): 217-22

Muellner, P., Muellner, U., Gates, M. C., Pearce, T., Ahlstrom, C., O'Neill, D., Brodblet, D. & Cave, N. J. (2016) Frontiers in Veterinary Science, 3.

O'Neill DG, Church DB, McGreevy PD, Thomson PC, Brodbelt DC (2014) Canine Genetics and Epidemiology,1:2.

Hoffman, J.M., Creevy, K.E., Franks, A., O'Neill, D.G. and Promislow, D.E.L. (2018) Aging Cell.

Hoffman, J.M., O'Neill, D.G., Creevy, K.E., & Austad, S.N.(2018)The Journals of Gerontology: Series A, 73, 150-156.

Jin, K., Hoffman, J.M., Creevy, K.E., O'Neill, D.G. and Promislow, D.E.L. (2016) Pathobiology of Aging and Age-related Diseases6:33276

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Retinitis Pigmentosa – The Foundation Fighting Blindness

Stell Cell Research | Posted by admin
Feb 06 2019

Overview

Retinitis pigmentosa (RP) describes a group of genetic disorders that damage light-sensitive cells in the retina, leading to gradual vision loss over time as the cells die off. While the condition is classified as a rare disease, it is one of the most common inherited diseases of the retina, affecting between 1 in 3500 to 1 in 4000 Canadians.[1]RP is often referred to as an inherited retinal disease, meaning that it is passed along genetic lines and inherited from ones parents. Though it is usually diagnosed during childhood or adolescence, a minority of patients report symptoms later in life.

Specialized cells called photoreceptors are responsible for absorbing light and translating it into signals that are interpreted by the brainit is these essential cells that gradually die off as a result of RP. The cells come in two varieties: rod cells and cone cells. Rod photoreceptors are responsible for peripheral and night vision, while cone photoreceptors are responsible for central, high-acuity vision as well as detail and colour. Since it is the rod cells that are first damaged by RP, peripheral and night vision are affected during the early stages of the disease, followed by a narrowing of the visual field, often referred to as a progressive form of tunnel vision. The death of rod cells eventually affects the cone cells as well, leading to the loss of central vision and often resulting, during the later stages of the disease, in near or total blindness. The length of this process varies from individual to individual.

RP was originally considered a single disease, but after decades of researchincluding research funded by the FFBwe now know that there are several forms of RP, and that these forms involve mutations in any one of more than 64 different genes. The gene or genes affected determine the disease type and symptoms.

There are several different ways that RP can be inherited, which is usually described as the inheritance pattern. The different RP inheritance patterns include: autosomal dominant, autosomal recessive, and x-linked recessive. A genetic counsellor can talk with you about your family history and determine which of these patterns is associated with your vision loss. With this information, the genetic counsellor may be able to tell you more about how your condition will progress, and give you and your family information about the risks of vision loss for other family members. To learn more about genetic testing for RP, please consult the FFB resource Everything You Need to Know about Genetic Testing.

Typically, each person with RP only has damage in one pair of genes. Scientists have now identified more than 64 genes that can have mutations that cause RP. It is likely that mutations in more than 100 different genes will eventually be identified. Because so many RP-causing gene mutations are still unknown, there is about a 50:50 chance that genetic testing will provide a definitive result. Given your family history and the inheritance pattern of your RP, your genetic counsellor will be able to advise you about the likelihood that a genetic test will provide a definitive result.

Different genetic mutations can damage the retina or impair its function in different ways; for example, some mutations affect how the retina processes nutrients, while others damage the photoreceptors. Its important to identify the specific gene and mutation, because many treatments being developed for RP will be for particular genetic types.

Content on this page was written by Dr. Chad Andrews and Dr. Mary Sunderland, and was most recently updated on August 23, 2018. An earlier version of the content was approved by Dr. Jane Green and Dr. Bill Stell.

The most common early symptom of RP is difficultly seeing at night and in low-light conditionsthis is called nyctalopia or night blindness. The loss of peripheral vision is also a common first symptom, and is often experienced alongside nyctalopia. As RP progresses, peripheral vision slowly diminishes, resulting in a narrow field of view or tunnel vision. By age 40, many people with RP are legally blind, with a severely constricted field of vision, although many may retain the ability to read and recognize faces. Uncomfortable sensitivity to light and glare is common, as is photopsia (seeing flashes of light or shimmering). RP can also cause a loss of visual acuity (the ability to see clearly), but the onset is more variable. Some patients retain normal visual acuity, even when their vision is reduced to a small central island; others lose acuity much earlier in the course of disease. Eventually, however, most people with RP will begin to lose central vision and some will lose all light perception.

An ophthalmologist may suspect RP on the basis of a persons symptoms and the findings of a simple eye examination. Two tests are used to clarify the diagnosis:

Currently, there is only a single approved treatment for a very rare form of RP on the market in the United States: a gene therapy called Luxturna, which can halt vision loss and even restore some sight in individuals with a biallelic mutation of their RPE65 gene (manifesting as either RP or Leber congenital amaurosis). Though the number of patients with this mutation is small, the medical effectiveness of Luxturna and its materialization as a pharmaceutical product demonstrate that there is significant potential for gene therapy to treat other forms of RP in the future.

Read Our Story About The Approval of Luxturna

Clinical trials are essential to the scientific process of developing new treatments: they test the viability and safety of experimental drugs and techniques, called interventions, on human beings. While there is no guarantee that enrolling in a clinical trial will provide any medical benefit, some patients do experience positive results after receiving an experimental therapy.

Read Our Clinical Trials Guide

The website clinicaltrials.gov is a centralized database of clinical trials that are offered globally. But as the disclaimer on the sites home page states, there is no guarantee that a listed trial has been evaluated or approvedthe National Institutes of Health runs the site but does not vet its content. This means that there could be bogus or dangerous trials listed that are preying on patients. It is essential that you discuss a clinical trial with your ophthalmologist before enrolling, and that you pay close attention to enrollment criteria.

If you are interested in exploring what is available on the site you can click on the button below, which will take you to clinicaltrials.gov and initiate a search for trials relevant for patients living with RP.

CLINICAL TRIALS FOR Retinitis Pigmentosa

For individuals living with an inherited retinal disease (a disease caused by a genetic mutation), participation in a clinical trial could be a logical next-step (for a description of clinical trials, see above). But in Canada there is no centralized, guided mechanism for enrolling in a trial; with this in mind, the Foundation Fighting Blindness has developed a secure medical database of Canadian patients living with inherited retinal diseases: we call it the Patient Registry.

By enrolling in the Patient Registry, your information will become a part of this essential Canadian database that can be used to help connect you to a relevant clinical trial. The availability of relevant trials depends on a number of factors, so this tool provides no guarantees, but signing onto it will put you in a position to be connected to something appropriate. It is also a way of standing up and being counted: the more individuals enrolled in the Patient Registry, the better our chances of showing policymakers that there is a significant need for new treatments for inherited retinal diseases. The Patient Registry also helps to drive more sight-saving research!

You can begin the process of enrolling in the Patient Registry by clicking the button below.

Patient Registry Enrollment

The Foundation Fighting Blindness is committed to advancing the most promising sight-saving research, and has invested over $33 million into cutting-edge science since the organization was founded. Recognizing that science is tied to policy frameworks, the Foundation is also actively involved in health policy activities across Canada.

Many research groups are working to develop treatments and cures for RP. Experimental treatments can be divided into three broad categories:

Protective therapies aim to stop (or at least slow) the damage caused by genetic mutations. Often protective therapies are not specific to one mutation, but may benefit people with many types of RP. These include treatments to stop the process of photoreceptor death (apoptosis), as well as cell-derived therapies that aim to help photoreceptors survive.

Some protective therapies aim specifically to prevent the death of cone cells in RP and thus, the loss of central vision in later stages of the disease.

Corrective therapies aim to reverse the underlying genetic defect that causes vision loss. If these therapies are successful they might prevent a person who is treated when first diagnosed, from ever developing vision loss. Corrective therapies might also help slow the disease in people whose vision has already been affected, especially in the earlier stages. The corrective therapies being developed now are specific to certain forms of recessively inherited RP. Gene therapies, which replace a non-functioning gene, are one type of corrective therapy. Clinical trials of gene therapies for several types of RP are underway, and the results so far are encouraging.

Sight-restoring therapies are also a growing area of research success. These therapies are intended for people who have already lost all, or much, of their vision. Stem cell therapies aim to replace the retinas lost photoreceptors. There are promising early results with stem cell trials involving other retinal degenerative diseases; trials with RP are on the horizon. Retinal prosthetics, such as the Arugus II or Bionic Eye, use computer technology to generate vision. The Foundation Fighting Blindness helped to support the first Canadian trial of the Argus II and continues to work closely with health policy experts across Canada to ensure that patients who could benefit from the Argus II device have access to this innovative treatment. Drug and gene therapies are also being developed that may give non-photoreceptor nerve cells in the retina the capacity to sense light.

Thanks to our generous donors, we are funding ground-breaking research in these areas. Click on the button below to review the full list of FFB-funded projects:

FFB-FUNDED RESEARCH

On the right side of this webpage, you will find an updating list of stories that detail new research and health policy developments relevant for individuals affected by RP.

The page you are now on provides information on RP, but the Foundation Fighting Blindness has developed additional resources that can be helpful in plotting an optimal path through vision care. Below is a list of such resources, including information on genetic testing, clinical trials, Vision Quest (the FFBs in-person educational events), and more. The list will update as new resources are added.

Must-Read Resources Vision Quest Educational Series

We know that helpful resources related to your eye disease can be difficult to find. Vision care in Canada entails a complex web of services, programs, and instructions, and little of it is centralized. The information on this site represents our attempt at providing a comprehensive, centralized resource that offers guidance and information specific to your eye disease. Our goal is to help you find your optimal path through vision care in Canada, which is why we call this initiative Vision Care Pathways.

December 12th, 2018 by FFB Canada

Right now, over 1 million Canadians are living with blinding eye diseases and as vision fades, so too can hope. To date, donors of the Foundation Fighting Blindness (FFB) have contributed more than $32 million for vision research. And now, until the end of 2018, a generous supporter will match your gift up to a

Read More

November 13th, 2018 by FFB Canada

On Saturday, October 20, 2018, family and friends of the Celebres came together in support of one very special little boy. Nicholas Celebre was born with Usher syndrome,a condition that causes deaf-blindness and often balance issues. Born profoundly deaf, he was fortunate enough to get cochlear implants when he was 12 months old. He also

Read More

November 13th, 2018 by FFB Canada

Guest-written by Deborah Scott. Our daughter, Olivia was 5 years old when she was diagnosed with a blinding eye disease called retinitis pigmentosa (RP). It was difficult for us to comprehend what that diagnosis really meant. As a parent, you never get over the impact of learning that there is so much more to vision

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Retinitis Pigmentosa - The Foundation Fighting Blindness

Everything You Need To Know About The Bionic Eye – The …

Stell Cell Research | Posted by admin
Feb 06 2019

May 18th, 2016 by FFB Canada

Click here to download a printable version this article/fact sheet: PDF/Word.

What is a retinal prosthesis? A retinal prosthesis is a non-living, electronic substitute for the retina. Popular and brand names for retinal prostheses are the Bionic Eye and the Argus II. The aim is to restore vision to someone blinded by retinal eye disease. A retinal prosthesis is different from an implanted lens or a low-vision device, which works to maximize a persons existing vision.

What does it do? In people with advanced retinal disease, the light-capturing cells of the retina, called photoreceptors, have been lost, but the network of nerves that sends visual information to the brain often is intact. A retinal prosthesis bypasses the photoreceptors and sends visual signals to the brain.

Will it restore my vision? The prostheses that have been tested so far do not provide natural sight. For example, people who are using them are able to recognize a doorway or the shape of a person, or in some cases can make finer distinctions, such as the difference between a fork and a spoon. These retinal prostheses provide a simulation of sight which means that the users have to re-learn how to see. Their brains need to learn how to interpret this new kind of information.

Who could use it? Retinal prostheses are intended for people who are blind or have only minimal light perception, but who once had sight. With prostheses, the brain must interpret the devices signals. Someone blind from birth never developed this capacity, and therefore it might not benefit them.

Are any approved in Canada? Yes. The Argus II Retinal Prosthesis is approved by Health Canada. It is also approved in Europe and the USA. The Foundation Fighting Blindness played a key role in bringing the Argus II (sometimes called the Bionic Eye) to Canada by helping to fund an observational clinical trial of the device at the Toronto Western Hospital led by Dr. Robert Devenyi.

What will it cost? The Argus II Retinal Prosthesis is now being marketed in Europe for about $100,000 USD, plus the cost of the surgery to implant it. Second Sight (the manufacturer) is actively seeking coverage of the device through public insurance or government subsidies. The costs of other retinal prostheses are not yet known.

How does it work? Just as there are multiple kinds of smart phones, there are different approaches to this technology.

Camera + Epi-Retinal Chip The Argus II by Second Sight is the leader in this category. It captures images with a mini-camera embedded in glasses that also carry a batterypack. A 2D array of many tiny electrodes is implanted surgically on the front surface of the retina (epi-retinal). Images from the camera are converted into electrical pulses sent wirelessly to the implant. The pulses stimulate the retinas remaining cells to send patterns of nerve impulses, representing the images, along the optic nerve to the brain. Patients can learn to interpret the patterns and regain some functional vision. Most of the people who have received an Argus II implant have had some visual perception restored, allowing them to better orient themselves in a room or negotiate daily tasks. There appear to be significant variations in results between users.

The Intelligent Retinal Implant System is another camera/chip combo, similar to the Argus II. It is in clinical trials in Germany and the UK. Bionic Vision Australia is also working on a similar product.

Sub-Retinal Chip Retinal Implant AG has created a sub-retinal implant, which sits behind the retina instead of in front of it. This electronic chip contains tiny photocells to capture light, amplifiers to boost their signal, and electrodes to stimulate retinal nerve cells. Since photocells are part of the chip, the device does not need an external camera, and the sub-retinal placement should be more secure and stable than the epi-retinal option; but morecomplicated surgery is required to implant it. Clinical trials of this device are ongoing in Germany, Italy and the UK, and in the USA.

Other groups developing chips include Artificial Silicon Retina Microchip, the Boston Retinal Implant Project, and Nano Vision although the later two are not yet at the human trial stage.

Sub-retinal chips may allow somewhat higher resolution images than epi-retinal chips. However, since even the tiniest electrodes in these prostheses are bound to stimulate more than one retinal cell, so the wearers visual acuity may never approach normal sight. This limitation has led to hybrid strategies, in which remaining retinal nerve cells are made light-sensitive andthen stimulated by patterns of light instead of electricity.

Encoding Neural Signals Dr. Sheila Nirenberg of Cornell University is one of several researchers, who are developing this new hybrid approach to prosthetics. In Dr. Nirenbergs studies, a camera sends images to a computer, which measures local differences in intensity across the image and encodes this information in pulses of light that mimic the natural language of the central nervous system. The size of these pulses of light can be smaller than the smallest retinal nerve cells; they can be projected through the pupil onto individual retinal cells. Using a new approach called optogenetics, a form of gene therapy endows these nerve cells with the ability to respond directly to light, so that the computer-generated light pulses stimulate them to send high-resolution, realistic image representations to the brain. This approach is being tested in animals. If it proves to be effective, it should provide much higher-quality images and a more natural visual experience. Dr. Gautam Awatramani at the University of Victoria is one scientist funded by the Foundation Fighting Blindness donors to study similar therapies.

Direct to Brain Prothesis Scientists at the Monash Vision Group in Australia have developed a different type of vision prosthesis. It avoids the retina altogether. This device uses a video camera to capture images and send its electronic signals directly to the visual cortex of the brain.

While brain surgery sounds like a more difficult, and risky option, the surgery required is relatively straightforward. More importantly, if it is successful, the device could have some important advantages. For example, it could help people with retinal degenerative disease, but it might also help people whose optic nerve has been damaged due to glaucoma or injury

As well, this prosthesis would not be implanted into the retina and thus would not block or damage retinal tissue. So the prosthetic could be used to augment vision for people with some remaining sight, and would not impair their remaining vision. The Monash Vision Group and its partners have committed to having their direct to brain bionic eye ready for first patient tests very soon.

Updated May 18, 2016: Dr. Mary Sunderland, Director of Research & Education, Foundation Fighting Blindness. Initially reviewed by Dr. Bill Stell, Professor of Cell Biology and Anatomy, at the University of Calgary and Dr. Gautam Awatramani, University of Victoria.

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Everything You Need To Know About The Bionic Eye - The ...

Menstrual cycle – Wikipedia

Stell Cell Research | Posted by admin
Feb 02 2019

The menstrual cycle is the regular natural change that occurs in the female reproductive system (specifically the uterus and ovaries) that makes pregnancy possible.[1][2] The cycle is required for the production of oocytes, and for the preparation of the uterus for pregnancy.[1] Up to 80% of women report having some symptoms during the one to two weeks prior to menstruation.[3] Common symptoms include acne, tender breasts, bloating, feeling tired, irritability and mood changes.[4] These symptoms interfere with normal life and therefore qualify as premenstrual syndrome in 20 to 30% of women. In 3 to 8%, they are severe.[3]

The first period usually begins between twelve and fifteen years of age, a point in time known as menarche.[5] They may occasionally start as early as eight, and this onset may still be normal.[6] The average age of the first period is generally later in the developing world and earlier in developed world. The typical length of time between the first day of one period and the first day of the next is 21 to 45 days in young women and 21 to 35 days in adults (an average of 28 days[6][7][8]). Menstruation stops occurring after menopause which usually occurs between 45 and 55 years of age.[9] Bleeding usually lasts around 2 to 7 days.[6]

The menstrual cycle is governed by hormonal changes.[6] These changes can be altered by using hormonal birth control to prevent pregnancy.[10] Each cycle can be divided into three phases based on events in the ovary (ovarian cycle) or in the uterus (uterine cycle).[1] The ovarian cycle consists of the follicular phase, ovulation, and luteal phase whereas the uterine cycle is divided into menstruation, proliferative phase, and secretory phase.

Stimulated by gradually increasing amounts of estrogen in the follicular phase, discharges of blood (menses) flow stop, and the lining of the uterus thickens. Follicles in the ovary begin developing under the influence of a complex interplay of hormones, and after several days one or occasionally two become dominant (non-dominant follicles shrink and die). Approximately mid-cycle, 2436 hours after the luteinizing hormone (LH) surges, the dominant follicle releases an ovocyte, in an event called ovulation. After ovulation, the ovocyte only lives for 24 hours or less without fertilization while the remains of the dominant follicle in the ovary become a corpus luteum; this body has a primary function of producing large amounts of progesterone. Under the influence of progesterone, the uterine lining changes to prepare for potential implantation of an embryo to establish a pregnancy. If implantation does not occur within approximately two weeks, the corpus luteum will involute, causing a sharp drop in levels of both progesterone and estrogen. The hormone drop causes the uterus to shed its lining in a process termed menstruation. Menstruation also occurs in closely related primates (apes and monkeys).[11]

The average age of menarche is 1215.[5][12] They may occasionally start as early as eight, and this onset may still be normal.[6] This first period often occurs later in the developing world than the developed world.[8]

The average age of menarche is approximately 12.5 years in the United States,[13] 12.7 in Canada,[14] 12.9 in the UK[15] and 13.1 years in Iceland.[16] Factors such as genetics, diet and overall health can affect timing.[17]

The cessation of menstrual cycles at the end of a woman's reproductive period is termed menopause. The average age of menopause in women is 52 years, with anywhere between 45 and 55 being common. Menopause before age 45 is considered premature in industrialised countries.[18] Like the age of menarche, the age of menopause is largely a result of cultural and biological factors;[19] however, illnesses, certain surgeries, or medical treatments may cause menopause to occur earlier than it might have otherwise.[20]

The length of a woman's menstrual cycle typically varies somewhat, with some shorter cycles and some longer cycles. A woman who experiences variations of less than eight days between her longest cycles and shortest cycles is considered to have regular menstrual cycles. It is unusual for a woman to experience cycle length variations of more than four days. Length variation between eight and 20 days is considered as moderately irregular cycles. Variation of 21 days or more between a woman's shortest and longest cycle lengths is considered very irregular. [21]

The average menstrual cycle lasts 28 days. The variability of menstrual cycle lengths is highest for women under 25 years of age and is lowest, that is, most regular, for ages 25 to 39.[7] Subsequently, the variability increases slightly for women aged 40 to 44.[7]

The luteal phase of the menstrual cycle is about the same length in most individuals (mean 14.13 days, standard deviation 1.41 days)[22] whereas the follicular phase tends to show much more variability (log-normally distributed with 95% of individuals having follicular phases between 10.3 and 16.3 days).[23] The follicular phase also seems to get significantly shorter with age (geometric mean 14.2 days in women aged 1824 vs. 10.4 days in women aged 4044).[23]

Some women with neurological conditions experience increased activity of their conditions at about the same time during each menstrual cycle. For example, drops in estrogen levels have been known to trigger migraines,[24] especially when the woman who suffers migraines is also taking the birth control pill. Many women with epilepsy have more seizures in a pattern linked to the menstrual cycle; this is called "catamenial epilepsy".[25] Different patterns seem to exist (such as seizures coinciding with the time of menstruation, or coinciding with the time of ovulation), and the frequency with which they occur has not been firmly established. Using one particular definition, one group of scientists found that around one-third of women with intractable partial epilepsy has catamenial epilepsy.[25][26][27] An effect of hormones has been proposed, in which progesterone declines and estrogen increases would trigger seizures.[28] Recently, studies have shown that high doses of estrogen can cause or worsen seizures, whereas high doses of progesterone can act like an antiepileptic drug.[29] Studies by medical journals have found that women experiencing menses are 1.68 times more likely to attempt suicide.[30]

Mice have been used as an experimental system to investigate possible mechanisms by which levels of sex steroid hormones might regulate nervous system function. During the part of the mouse estrous cycle when progesterone is highest, the level of nerve-cell GABA receptor subtype delta was high. Since these GABA receptors are inhibitory, nerve cells with more delta receptors are less likely to fire than cells with lower numbers of delta receptors. During the part of the mouse estrous cycle when estrogen levels are higher than progesterone levels, the number of delta receptors decrease, increasing nerve cell activity, in turn increasing anxiety and seizure susceptibility.[31]

Estrogen levels may affect thyroid behavior.[32] For example, during the luteal phase (when estrogen levels are lower), the velocity of blood flow in the thyroid is lower than during the follicular phase (when estrogen levels are higher).[33]

Among women living closely together, it was once thought that the onsets of menstruation tend to synchronize. This effect was first described in 1971, and possibly explained by the action of pheromones in 1998.[34] Subsequent research has called this hypothesis into question.[35]

Research indicates that women have a significantly higher likelihood of anterior cruciate ligament injuries in the pre-ovulatory stage, than post-ovulatory stage.[36]

The most fertile period (the time with the highest likelihood of pregnancy resulting from sexual intercourse) covers the time from some 5 days before until 1 to 2 days after ovulation.[38] In a 28day cycle with a 14day luteal phase, this corresponds to the second and the beginning of the third week. A variety of methods have been developed to help individual women estimate the relatively fertile and the relatively infertile days in the cycle; these systems are called fertility awareness.

There are many fertility testing methods, including urine test kits that detect the LH surge that occurs 24 to 36 hours before ovulation; these are known as ovulation predictor kits (OPKs).[39] Computerized devices that interpret basal body temperatures, urinary test results, or changes in saliva are called fertility monitors. Fertility awareness methods that rely on cycle length records alone are called calendar-based methods.[40] Methods that require observation of one or more of the three primary fertility signs (basal body temperature, cervical mucus, and cervical position)[41] are known as symptoms-based methods.[40]

A woman's fertility is also affected by her age.[42] As a woman's total egg supply is formed in fetal life,[43] to be ovulated decades later, it has been suggested that this long lifetime may make the chromatin of eggs more vulnerable to division problems, breakage, and mutation than the chromatin of sperm, which are produced continuously during a man's reproductive life. However, despite this hypothesis, a similar paternal age effect has also been observed.

As measured on women undergoing in vitro fertilization, a longer menstrual cycle length is associated with higher pregnancy and delivery rates, even after age adjustment.[44]Delivery rates after IVF have been estimated to be almost doubled for women with a menstrual cycle length of more than 34 days compared with women with a menstrual cycle length shorter than 26 days.[44] A longer menstrual cycle length is also significantly associated with better ovarian response to gonadotropin stimulation and embryo quality.[44]

The different phases of the menstrual cycle correlate with women's moods. In some cases, hormones released during the menstrual cycle can cause behavioral changes in females; mild to severe mood changes can occur.[45] The menstrual cycle phase and ovarian hormones may contribute to increased empathy in women. The natural shift of hormone levels during the different phases of the menstrual cycle has been studied in conjunction with test scores. When completing empathy exercises, women in the follicular stage of their menstrual cycle performed better than women in their midluteal phase. A significant correlation between progesterone levels and the ability to accurately recognize emotion was found. Performances on emotion recognition tasks were better when women had lower progesterone levels. Women in the follicular stage showed higher emotion recognition accuracy than their midluteal phase counterparts. Women were found to react more to negative stimuli when in midluteal stage over the women in the follicular stage, perhaps indicating more reactivity to social stress during that menstrual cycle phase.[46] Overall, it has been found that women in the follicular phase demonstrated better performance in tasks that contain empathetic traits.

Fear response in women during two different points in the menstrual cycle has been examined. When estrogen is highest in the preovulatory stage, women are significantly better at identifying expressions of fear than women who were menstruating, which is when estrogen levels are lowest. The women were equally able to identify happy faces, demonstrating that the fear response was a more powerful response. To summarize, menstrual cycle phase and the estrogen levels correlates with womens fear processing.[47]

However, the examination of daily moods in women with measuring ovarian hormones may indicate a less powerful connection. In comparison to levels of stress or physical health, the ovarian hormones had less of an impact on overall mood.[48] This indicates that while changes of ovarian hormones may influence mood, on a day-to-day level it does not influence mood more than other stressors do.

Sexual feelings and behaviors change during the menstrual cycle. Before and during ovulation, high levels of estrogen and androgens result in women having an increased interest in sexual activity.[49] Unlike other animal species, women show interest in sex across all days of the menstrual cycle, regardless of fertility.[50]

Behavior towards potential mating partners changes during different phases of the menstrual cycle.[51][52][53] Near ovulation, women may have increased physical attraction and interest in attending social gatherings with men.[54] During the fertile phase of the cycle, women appear to prefer males who are more masculine.[55] The intensity of mate guarding differs across the phases of the cycle, with increased mate guarding occurring when women are fertile.[53][56][57]

During the fertile phase, many women experience more attraction, fantasies and sexual interest for extra pair men but not for the primary partner.[54][53][58] They also engage in extra-pair flirtations and demonstrate a preference for extra pair copulation.[54][58]

Preferences for voice pitch change across the cycle.[58] When seeking a short term mating partner, women may prefer a male with a low voice pitch, particularly during the fertile phase.[58] During the late follicular phase, it is common for women demonstrate a preference for mates with a masculine, deep voice.[59] Research has also been conducted on the attractiveness of the female voice throughout the cycle.[60] During their most fertile phase of the menstrual cycle, there is some evidence that female voices are rated as significantly more attractive.[60] This effect is not found with women on the birth control pill.[60]

Women's preference for male's body odor can change across the menstrual cycle.[61] Males who score highly on dominance have been rated as sexier by females during the fertile phase of the menstrual cycle. Additionally, during their most fertile phase of the menstrual cycle, women may show preference for the odor of symmetrical men.[53] This effect is not found for women on the birth control pill.[62] Also, during the late follicular and ovulatory phases, women prefer the scent of masculine men.[58] The scent of androsterone (responsible for testosterone levels) is highly preferred by women during the peak of their fertility in the menstrual cycle.[58] Moreover, women may demonstrate preference for men with a scent that indicates developmental stability.[58]

With regard to women's smell across the cycle, some evidence indicates that men use olfactory cues in order to know if a woman is ovulating.[61] Using a rating of women's odors, women who are ovulating have been rated as more attractive by men.[61] Men demonstrate preferences for the scent of fertile women.[61]

Preferences for facial features in mates can also change across the cycle.[58] There has been no difference found in preference for long-term mating partners during the menstrual cycle; however, those seeking a short-term relationship were more likely to choose a partner with more masculine features than usual.[54][59] This was found to be the case especially during the woman's high conception risk stage and when salivary testosterone was high.[63] However, when women are in the luteal (non-fertile) phase, they tend to prefer men (and females) with more feminine faces.[59] A preference is also shown for self-resembling faces and apparent health in faces during the luteal phase of the cycle.[64] Apparent health preferences were found to be strongest when progesterone levels were high.[64] Additionally, during the fertile phase, many women show a preference for men with darker skin pigmentation.[58] Research on facial symmetry is mixed.[65]

Preferences for body features can change during the fertile phase of the cycle. Women seeking a short-term partner demonstrate a preference for taller and muscular males.[58] Women also show preferences of males with masculine bodies at peak fertility.[58][63] Mixed research has been found regarding body symmetry preferences throughout different phases of the cycle.[58]

In short term mates, during the fertile phase, women may show more attraction to dominant men who display social presence.[58] For long-term mates, shifts in desired trait preferences do not occur throughout the cycle.[58]

Females have been found to experience different eating habits at different stages of their menstrual cycle, with food intake being higher during the luteal phase than the follicular phase.[66][67] Food intake increases by approximately 10% during the luteal phase compared to the follicular phase.[67]

Various studies have shown that during the luteal phase woman consume more carbohydrates, proteins and fats and that 24-hour energy expenditure shows increases between 2.5-11.5%.[68] The increasing intake during the luteal phase may be related to higher preferences for sweet and fatty foods, which occurs naturally and is enhanced during the luteal phases of the menstrual cycle.[68] This is due to the higher metabolic demand during this phase.[69] In particular, women tend to show a cravings for chocolate, with higher cravings during the luteal phase.[68]

Females with premenstrual syndrome (PMS) report changes in appetite across the menstrual cycle more than non-sufferers of PMS, possibly due to their oversensitivity to changes in hormone levels.[67] In women with PMS, food intake is higher in the luteal phase than follicular.[70] The remaining symptoms of PMS, including mood changes and physical symptoms, also occur during the luteal phase. No difference for preference of food types has been found between PMS sufferers and non-sufferers.[66]

The different levels of ovarian hormones at different stages of the cycle have been used to explain eating behaviour changes. Progesterone has been shown to promote fat storage, causing a higher intake of fatty foods during the luteal phase when progesterone levels are higher.[67] Additionally, with a high estrogen level dopamine is ineffective in converting to noradrenaline, a hormone which promotes eating, therefore decreasing appetite.[67] In humans, the level of these ovarian hormones during the menstrual cycle have been found to influence binge eating.[71]

It is theorized that the use of birth control pills should affect eating behaviour as they minimise or remove the fluctuations in hormone levels.[66] The neurotransmitter serotonin is also thought to play a role in food intake. Serotonin is responsible for inhibiting eating and controlling meal size,[72] among other things, and is modulated in part by ovarian hormones.[73]

A number of factors affect whether dieting will affect these menstrual processes: age, weight loss and the diet itself. First, younger women are likely to experience menstrual irregularities due to their diet. Second, menstrual abnormalities are more likely with more weight loss. For example, anovulatory cycles can occur as a result of adopting a restricted diet, as well as engaging in a high amount of exercise.[67] Finally, the cycle is affected more by a vegetarian diet compared to a non-vegetarian diet.[74]

Studies investigating effects of the menstrual cycle on alcohol consumption have found mixed evidence.[75] However, some evidence suggests that individuals consume more alcohol during the luteal stage, especially if these individuals are heavy drinkers or have a family history of alcohol abuse.[69]

The level of substance abuse increases with PMS, mostly with addictive substances such as nicotine, tobacco and cocaine.[69] One theory behind this suggests this higher level of substance abuse is due to decreased self-control as a result of the higher metabolic demands during the luteal phase.[69]

Infrequent or irregular ovulation is called oligoovulation.[76] The absence of ovulation is called anovulation. Normal menstrual flow can occur without ovulation preceding it: an anovulatory cycle. In some cycles, follicular development may start but not be completed; nevertheless, estrogens will be formed and stimulate the uterine lining. Anovulatory flow resulting from a very thick endometrium caused by prolonged, continued high estrogen levels is called estrogen breakthrough bleeding. Anovulatory bleeding triggered by a sudden drop in estrogen levels is called withdrawal bleeding.[77] Anovulatory cycles commonly occur before menopause (perimenopause) and in women with polycystic ovary syndrome.[78]

Very little flow (less than 10 ml) is called hypomenorrhea. Regular cycles with intervals of 21 days or fewer are polymenorrhea; frequent but irregular menstruation is known as metrorrhagia. Sudden heavy flows or amounts greater than 80 ml are termed menorrhagia.[79] Heavy menstruation that occurs frequently and irregularly is menometrorrhagia. The term for cycles with intervals exceeding 35 days is oligomenorrhea.[80]Amenorrhea refers to more than three[79] to six[80] months without menses (while not being pregnant) during a woman's reproductive years. The term for painful periods is Dysmenorrhea.

The menstrual cycle can be described by the ovarian or uterine cycle. The ovarian cycle describes changes that occur in the follicles of the ovary whereas the uterine cycle describes changes in the endometrial lining of the uterus. Both cycles can be divided into three phases. The ovarian cycle consists of the follicular phase, ovulation, and the luteal phase, whereas the uterine cycle consists of menstruation, proliferative phase, and secretory phase.[1]

The follicular phase is the first part of the ovarian cycle. During this phase, the ovarian follicles mature and get ready to release an egg.[1] The latter part of this phase overlaps with the proliferative phase of the uterine cycle.

Through the influence of a rise in follicle stimulating hormone (FSH) during the first days of the cycle, a few ovarian follicles are stimulated.[81] These follicles, which were present at birth[81] and have been developing for the better part of a year in a process known as folliculogenesis, compete with each other for dominance. Under the influence of several hormones, all but one of these follicles will stop growing, while one dominant follicle in the ovary will continue to maturity. The follicle that reaches maturity is called a tertiary or Graafian follicle, and it contains the ovum.[81]

Ovulation is the second phase of the ovarian cycle in which a mature egg is released from the ovarian follicles into the oviduct.[82] During the follicular phase, estradiol suppresses release of luteinizing hormone (LH) from the anterior pituitary gland. When the egg has nearly matured, levels of estradiol reach a threshold above which this effect is reversed and estrogen stimulates the production of a large amount of LH. This process, known as the LH surge, starts around day12 of the average cycle and may last 48 hours.[83]

The exact mechanism of these opposite responses of LH levels to estradiol is not well understood.[84] In animals, a gonadotropin-releasing hormone (GnRH) surge has been shown to precede the LH surge, suggesting that estrogen's main effect is on the hypothalamus, which controls GnRH secretion.[84] This may be enabled by the presence of two different estrogen receptors in the hypothalamus: estrogen receptor alpha, which is responsible for the negative feedback estradiol-LH loop, and estrogen receptor beta, which is responsible for the positive estradiol-LH relationship.[85] However, in humans it has been shown that high levels of estradiol can provoke 32 increases in LH, even when GnRH levels and pulse frequencies are held constant,[84] suggesting that estrogen acts directly on the pituitary to provoke the LH surge.

The release of LH matures the egg and weakens the wall of the follicle in the ovary, causing the fully developed follicle to release its secondary oocyte.[81] If it is fertilized by a sperm, the secondary oocyte promptly matures into an ootid and then becomes a mature ovum. If it is not fertilized by a sperm, the secondary oocyte will degenerate. The mature ovum has a diameter of about 0.2mm.[86]

Which of the two ovariesleft or rightovulates appears essentially random; no known left and right co-ordination exists.[87] Occasionally, both ovaries will release an egg;[87] if both eggs are fertilized, the result is fraternal twins.[88]

After being released from the ovary, the egg is swept into the fallopian tube by the fimbria, which is a fringe of tissue at the end of each fallopian tube. After about a day, an unfertilized egg will disintegrate or dissolve in the fallopian tube.[81]

Fertilization by a spermatozoon, when it occurs, usually takes place in the ampulla, the widest section of the fallopian tubes. A fertilized egg immediately begins the process of embryogenesis, or development. The developing embryo takes about three days to reach the uterus and another three days to implant into the endometrium.[81] It has usually reached the blastocyst stage at the time of implantation.

In some women, ovulation features a characteristic pain called mittelschmerz (German term meaning middle pain).[89] The sudden change in hormones at the time of ovulation sometimes also causes light mid-cycle blood flow.[90]

The luteal phase is the final phase of the ovarian cycle and it corresponds to the secretory phase of the uterine cycle. During the luteal phase, the pituitary hormones FSH and LH cause the remaining parts of the dominant follicle to transform into the corpus luteum, which produces progesterone. The increased progesterone in the adrenals starts to induce the production of estrogen. The hormones produced by the corpus luteum also suppress production of the FSH and LH that the corpus luteum needs to maintain itself. Consequently, the level of FSH and LH fall quickly over time, and the corpus luteum subsequently atrophies.[81] Falling levels of progesterone trigger menstruation and the beginning of the next cycle. From the time of ovulation until progesterone withdrawal has caused menstruation to begin, the process typically takes about two weeks, with 14 days considered normal. For an individual woman, the follicular phase often varies in length from cycle to cycle; by contrast, the length of her luteal phase will be fairly consistent from cycle to cycle.[91]

The loss of the corpus luteum is prevented by fertilization of the egg. The syncytiotrophoblast, which is the outer layer of the resulting embryo-containing structure (the blastocyst) and later also becomes the outer layer of the placenta, produces human chorionic gonadotropin (hCG), which is very similar to LH and which preserves the corpus luteum. The corpus luteum can then continue to secrete progesterone to maintain the new pregnancy. Most pregnancy tests look for the presence of hCG.[81]

The uterine cycle has three phases: menses, proliferative, secretory.[92]

Menstruation (also called menstrual bleeding, menses, catamenia or a period) is the first phase of the uterine cycle. The flow of menses normally serves as a sign that a woman has not become pregnant. (However, this cannot be taken as certainty, as a number of factors can cause bleeding during pregnancy; some factors are specific to early pregnancy, and some can cause heavy flow.)[93][94][95]

Eumenorrhea denotes normal, regular menstruation that lasts for a few days (usually 3 to 5 days, but anywhere from 2 to 7 days is considered normal).[89][96] The average blood loss during menstruation is 35 milliliters with 1080 ml considered normal.[97] Women who experience Menorrhagia are more susceptible to iron deficiency than the average person.[98] An enzyme called plasmin inhibits clotting in the menstrual fluid.[99]

Painful cramping in the abdomen, back, or upper thighs is common during the first few days of menstruation. Severe uterine pain during menstruation is known as dysmenorrhea, and it is most common among adolescents and younger women (affecting about 67.2% of adolescent females).[100] When menstruation begins, symptoms of premenstrual syndrome (PMS) such as breast tenderness and irritability generally decrease.[89] Many sanitary products are marketed to women for use during their menstruation.

The proliferative phase is the second phase of the uterine cycle when estrogen causes the lining of the uterus to grow, or proliferate, during this time.[81] As they mature, the ovarian follicles secrete increasing amounts of estradiol, and estrogen. The estrogens initiate the formation of a new layer of endometrium in the uterus, histologically identified as the proliferative endometrium. The estrogen also stimulates crypts in the cervix to produce fertile cervical mucus, which may be noticed by women practicing fertility awareness.[101]

The secretory phase is the final phase of the uterine cycle and it corresponds to the luteal phase of the ovarian cycle. During the secretory phase, the corpus luteum produces progesterone, which plays a vital role in making the endometrium receptive to implantation of the blastocyst and supportive of the early pregnancy, by increasing blood flow and uterine secretions and reducing the contractility of the smooth muscle in the uterus;[102] it also has the side effect of raising the woman's basal body temperature.[103]

While some forms of birth control do not affect the menstrual cycle, hormonal contraceptives work by disrupting it. Progestogen negative feedback decreases the pulse frequency of gonadotropin-releasing hormone (GnRH) release by the hypothalamus, which decreases the release of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) by the anterior pituitary. Decreased levels of FSH inhibit follicular development, preventing an increase in estradiol levels. Progestogen negative feedback and the lack of estrogen positive feedback on LH release prevent a mid-cycle LH surge. Inhibition of follicular development and the absence of a LH surge prevent ovulation.[104][105][106]

The degree of ovulation suppression in progestogen-only contraceptives depends on the progestogen activity and dose. Low dose progestogen-only contraceptivestraditional progestogen only pills, subdermal implants Norplant and Jadelle, and intrauterine system Mirenainhibit ovulation in about 50% of cycles and rely mainly on other effects, such as thickening of cervical mucus, for their contraceptive effectiveness.[107] Intermediate dose progestogen-only contraceptivesthe progestogen-only pill Cerazette and the subdermal implant Nexplanonallow some follicular development but more consistently inhibit ovulation in 9799% of cycles. The same cervical mucus changes occur as with very low-dose progestogens. High-dose, progestogen-only contraceptivesthe injectables Depo-Provera and Noristeratcompletely inhibit follicular development and ovulation.[107]

Combined hormonal contraceptives include both an estrogen and a progestogen. Estrogen negative feedback on the anterior pituitary greatly decreases the release of FSH, which makes combined hormonal contraceptives more effective at inhibiting follicular development and preventing ovulation. Estrogen also reduces the incidence of irregular breakthrough bleeding.[104][105][106] Several combined hormonal contraceptivesthe pill, NuvaRing, and the contraceptive patchare usually used in a way that causes regular withdrawal bleeding. In a normal cycle, menstruation occurs when estrogen and progesterone levels drop rapidly.[103] Temporarily discontinuing use of combined hormonal contraceptives (a placebo week, not using patch or ring for a week) has a similar effect of causing the uterine lining to shed. If withdrawal bleeding is not desired, combined hormonal contraceptives may be taken continuously, although this increases the risk of breakthrough bleeding.

Breastfeeding causes negative feedback to occur on pulse secretion of gonadotropin-releasing hormone (GnRH) and luteinizing hormone (LH). Depending on the strength of the negative feedback, breastfeeding women may experience complete suppression of follicular development, but no ovulation, or normal menstrual cycle may resume.[108] Suppression of ovulation is more likely when suckling occurs more frequently.[109] The production of prolactin in response to suckling is important to maintaining lactational amenorrhea.[110] On average, women who are fully breastfeeding whose infants suckle frequently experience a return of menstruation at fourteen and a half months postpartum. There is a wide range of response among individual breastfeeding women, however, with some experiencing return of menstruation at two months and others remaining amenorrheic for up to 42 months postpartum.[111]

The word "menstruation" is etymologically related to "moon". The terms "menstruation" and "menses" are derived from the Latin mensis (month), which in turn relates to the Greek mene (moon) and to the roots of the English words month and moon.[112]

Even though the average length of the human menstrual cycle is similar to that of the lunar cycle, in modern humans there is no relation between the two.[113] The relationship is believed to be a coincidence.[114][115] Light exposure does not appear to affect the menstrual cycle in humans.[11] A meta-analysis of studies from 1996 showed no correlation between the human menstrual cycle and the lunar cycle[116], nor did data analysed by period-tracking app Clue, submitted by 1.5m women, of 7.5m menstrual cycles[117].

Dogon villagers did not have electric lighting and spent most nights outdoors, talking and sleeping, so they were apparently an ideal population for detecting a lunar influence; none was found.[118]

In a number of countries, mainly in Asia, legislation or corporate practice has introduced formal menstrual leave to provide women with either paid or unpaid leave of absence from their employment while they are menstruating.[119] Countries with policies include Japan, Taiwan, Indonesia, and South Korea.[119] The practice is controversial due to concerns that it bolsters the perception of women as weak, inefficient workers,[119] as well as concerns that it is unfair to men.[120][121]

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Cigarette lighter using rechargeable AA batteries …

Stell Cell Research | Posted by admin
Jan 28 2019

NiCads have a lower internal resistance than NiMH. SLA even lower.

Having said that, I'd approach this as an academic exercise rather than as a practical project opportunity

This page http://www.buchmann.ca/article4-page1.asp (and I think they mean milliohms rather than milliwatts in the table) gives you some indication of internal resistances for cell types. (remember to divide these figures by the number of cells to get the per-cell internal resistance)

I think you'd have a better chance with D cells (certainly SLA cells are available in that size)

A major issue would be the connection to the cells. You would have to use cells that are terminated with solder tags rather than bare cells -- the connection resistance would be far too high.

You would need to look at the datasheets on individual cells to determine if the discharge rates are possible for the cell.

Another issue would be that you would almost certainly need to generate another higher voltage source to power your regulator. It is difficult to imagine any of the more efficient designs starting up on their own from 1.5V. You might need a more specialised "joule thief" type of inverter to generate an initial 12V rail to power the main inverter before using the generated 12V rail for continuous operation (or not -- you could use 2 regulators, it's not like a bit of inefficiency here would be a real issue).

More practically, you may be better off creating your own specialised "cigarette lighter" from a coil of nichrome wire of sufficient length to glow red hot from just a 1.2V supply. Since this device would be small enough to turn on when brought to the cigarette, it need not require the relatively large thermal mass of a conventional car cigarette lighter.

I would estimate that you could probably create a device that used perhaps only 10W (i.e. 8A) and would only need to be operated for a couple of seconds. The major issue here would be the contact resistance and the switch. It may be sensible to use a small inverter to provide gate voltage for a high current mosfet that has a very low RDSon.

At a minimum, I think you'd still be looking at a sub-C sized cell.

OK, here's the specs I found on a sub-C cell. It is rated for up to 30A discharge. http://www.gpbatteries.com/pic/330SCH-ZRS1161rev2.pdf Note the voltage at 30A, also note that the effective capacity is much lower, still it looks like you'd get 6 minutes use at 30A which is pretty good.

This page has more battery types listed: http://www.rechargeable-battery-review.com/data-sheets/battery-specs/gp-battery-data-sheets.html

From a quick look, it appears that the AA sized cells top out at a recommended max of 6.6A. (D cells go to 50A)

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Cigarette lighter using rechargeable AA batteries ...