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December 20, 2019
12/10/2019
Conservation Science
Hinke and colleagues uncover chinstrap penguins migratory movements during their winter migration.
Image credit: Pixabay
12/13/2019
Global health
New investigations by Kaiser and colleagues into the market economics of treating diabetes in Zambia suggest that the vast majority of essential medications are not adequately available.
Image credit: stevepb
12/04/2019
Archaeology
Weniger and colleagues investigate the impacts of rapid climate change during the Late Glacial Maximum on human land use and mobility.
Image credit: Weniger G-C
12/05/2019
biofuels
Khalekuzzaman et al. produce low-cost algal bioful from wastewater using a Hybrid Anaerobic Baffled/Photobioreactor system.
Image credit: pone.0225458
12/02/2019
Proteomics
Takai and colleagues presented the applicability of the simulated spectral library searching approach to TripleTOF CID spectra.
Image credit: pone.0225885
11/20/2019
Cardiovascular Medicine
Hammad and colleagues explore the expression of sphingolipids in patients with systemic lupus erythematous and atherosclerosis, highlighting ethnicity-specific differences.
Image credit: Arek Socha
11/20/2019
EVERYONE
The year is almost over and here on the PLOS ONE team we’ve been reflecting on the tremendous impact our authors’ work has had in the community bu puitting together a collection of our most impactful work from 2015-2018.
12/13/2019
Biochemistry
Mestre-Fos and colleagues investigate rRNA G-quadruplex formation demonstrating that rRNA associated with small ribosomal subunit are able to form G-quadruplexes.
Image credit: pone.0226177
12/12/2019
Nutrition
Téllez-Rojo and colleagues study mother-child pairs from the (Early Life Exposure in Mexico to Environmental Toxicants) ELEMENT project in Mexico and find childhood diet and obesity to be strongly associated with the mother’s BMI.
Image credit: Free-Photos
12/02/2019
cognition
Tao et al. report multimodal perceptual differences associated with congenital amusia.
Image credit: Wikimedia Commons
12/02/2019
machine learning
Mayo and colleagues select the best machine learning technique for blood glucose level forecasting.
Image credit: xresch
To be considered for this Collection, articles must be submitted by February 7, 2020.
To be considered for this Collection, articles must be submitted by February 7, 2020.
To be considered for this Collection, articles must be submitted by January 21, 2020.
To be considered for this Collection, articles must be submitted by January 8, 2020.
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