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  • Public Library of Science  (155)
  • PANGAEA  (89)
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  • 1
    Publication Date: 2020-12-10
    Description: The biggest nationwide COVID-19 pandemic lockdown worldwide was enforced in India for an initial period of 21-days. Emerging evidence suggests that pandemic situations and associated lockdowns have an adverse impact on sleep and mental health. However, prediction of sleep health from sociodemographic characteristics and the public’s worry during the initial stages of the COVID-19 pandemic has not been extensively explored so far. It’s also unclear whether sleep outcomes mediate the association between worry and mental health during pandemic situations. A web-survey (N = 391) on sociodemographic characteristics, COVID-19 related worry, sleep health (insomnia and daytime sleepiness), and depression was conducted during the initial 21-days of the COVID-19 stringent lockdown in India. Multiple regression analyses showed that variables, including sex, age, income level, and worry score, contributed to the significant regression equation for insomnia but not for daytime sleepiness. Specifically, the female, younger, lower income, and highly worried populations contributed significantly more than the male, elderly, higher income, and less worried populations, respectively, to the prediction of insomnia. Mediation analyses showed that insomnia, but not daytime sleepiness, fully mediated the relationship between worry score and severity of depressive symptoms. We provide evidence that the female, younger, lower income, and worried populations may be at higher risk for insomnia during pandemic situations. Current evidence gives hope that improving sleep may reduce depressive symptoms during a pandemic situation. This underscores the importance of the implementation of effective public health policies in conjunction with strategical responses to the COVID-19 pandemic.
    Electronic ISSN: 1932-6203
    Topics: Medicine , Natural Sciences in General
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  • 2
  • 3
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 12 (2017): e0188257, doi:10.1371/journal.pone.0188257.
    Description: Preservation of three-dimensional structure in the gut is necessary in order to analyze the spatial organization of the gut microbiota and gut luminal contents. In this study, we evaluated preparation methods for mouse gut with the goal of preserving micron-scale spatial structure while performing fluorescence imaging assays. Our evaluation of embedding methods showed that commonly used media such as Tissue-Tek Optimal Cutting Temperature (OCT) compound, paraffin, and polyester waxes resulted in redistribution of luminal contents. By contrast, a hydrophilic methacrylate resin, Technovit H8100, preserved three-dimensional organization. Our mouse intestinal preparation protocol optimized using the Technovit H8100 embedding method was compatible with microbial fluorescence in situ hybridization (FISH) and other labeling techniques, including immunostaining and staining with both wheat germ agglutinin (WGA) and 4', 6-diamidino-2-phenylindole (DAPI). Mucus could be visualized whether the sample was fixed with paraformaldehyde (PFA) or with Carnoy’s fixative. The protocol optimized in this study enabled simultaneous visualization of micron-scale spatial patterns formed by microbial cells in the mouse intestines along with biogeographical landmarks such as host-derived mucus and food particles.
    Description: Funding provided by National Science Foundation (www.nsf.gov) grant 1650141 to J.L.M.W. and National Institutes of Health National Institute of Dental and Craniofacial Research (www.nidcr.nih.gov) grant DE022586 to G.G.B.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2023-01-13
    Keywords: Buoy; BUOY; Chlorophyll a; Conductivity; DATE/TIME; Day of the year; Density, sigma-theta (0); DEPTH, water; Pressure, water; Radiation, photosynthetically active; Salinity; Scotian Shelf; SeaHorse_2007_ScotiaShelf; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 1883875 data points
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  • 5
    Publication Date: 2023-01-13
    Keywords: Buoy; BUOY; Carbon dioxide, partial pressure; CARIOCA_2014_ScotiaShelf; DATE/TIME; Day of the year; DEPTH, water; Fluorescence; Fugacity of carbon dioxide in seawater; LATITUDE; LONGITUDE; Pressure, atmospheric; Salinity; Scotian Shelf; Temperature, water; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 67815 data points
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  • 6
    Publication Date: 2023-01-13
    Description: The understanding of the seasonal variability of carbon cycling on the Scotian Shelf in the NW Atlantic Ocean has improved in recent years; however, very little information is available regarding its short-term variability. In order to shed light on this aspect of carbon cycling on the Scotian Shelf we investigate the effects of Hurricane Arthur, which passed the region on 5 July 2014. The hurricane caused a substantial decline in the surface water partial pressure of CO2 (pCO2), even though the Scotian Shelf possesses CO2-rich deep waters. High-temporal-resolution data of moored autonomous instruments demonstrate that there is a distinct layer of relatively cold water with low dissolved inorganic carbon (DIC) slightly above the thermocline, presumably due to a sustained population of phytoplankton. Strong storm-related wind mixing caused this cold intermediate layer with high phytoplankton biomass to be entrained into the surface mixed layer. At the surface, phytoplankton begin to grow more rapidly due to increased light. The combination of growth and the mixing of low DIC water led to a short-term reduction in the partial pressure of CO2 until wind speeds relaxed and allowed for the restratification of the upper water column. These hurricane-related processes caused a (net) CO2 uptake by the Scotian Shelf region that is comparable to the spring bloom, thus exerting a major impact on the annual CO2 flux budget.
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 7
    Publication Date: 2023-01-13
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 11.7 kBytes
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  • 8
    Publication Date: 2023-02-07
    Keywords: Analyst; Braarudosphaera bigelowii; Calcidiscus fuscus; Calcidiscus leptoporus; Calcidiscus radiatus; Calcidiscus tropicus; Camuralithus pelliculatus; Clausicoccus fenestratus; Clausicoccus obrutus; Coccolithus crassipons; Coccolithus formosus; Coccolithus miopelagicus; Coccolithus pelagicus; Coccolithus pliopelagicus; Comment; Coronocyclus nitescens; Cruciplacolithus flavius; Cyclicargolithus abisectus; Cyclicargolithus bukryi; Cyclicargolithus floridanus; DEPTH, sediment/rock; Depth, sediment revised; Dictyococcites albitectus; Dictyococcites antarcticus; Dictyococcites bisectus; Dictyococcites filewiczii; Dictyococcites hesslandii; Dictyococcites onustus; Dictyococcites productellus; Dictyococcites scrippsae; Dictyococcites stavensis; Discoaster adamanteus; Discoaster aulakos; Discoaster calculosus; Discoaster deflandrei; Discoaster druggii; Discoaster durioi; Discoaster nephados; Discoaster obtusus; Discoaster salomonii; Discoaster saundersii; Discoaster shumnykii; Discoaster trinidadensis; Discoaster woodringii; Ericsonia detecta; Hayella gauliformis; Helicosphaera bipuncta; Helicosphaera carteri; Helicosphaera compacta; Helicosphaera disrupta; Helicosphaera elongata; Helicosphaera euphratis; Helicosphaera intermedia; Helicosphaera obliqua; Helicosphaera perch-nielseniae; Helicosphaera recta; Helicosphaera rhomba; Helicosphaera truncata; Helicosphaera zeta; Horizon; Hughesius gizoensis; Hughesius tasmaniae; Ilselithina fusa; Italy; Lemme-Carrioso_Section; Nannofossils; Nannofossils, reworked fossil; Orthozygus aureus; OUTCROP; Outcrop sample; Pontosphaera desueta; Pontosphaera elliptica; Pontosphaera enormis; Pontosphaera latelliptica; Pontosphaera latoculata; Pontosphaera longiforaminis; Pontosphaera multipora; Pontosphaera segmenta; Pontosphaera trematotes; Reticulofenestra amplus; Reticulofenestra celtica; Reticulofenestra francofurtana; Reticulofenestra haqii; Reticulofenestra hillae; Reticulofenestra inclinata; Reticulofenestra kahniae; Reticulofenestra minuta; Reticulofenestra perforata; Rhabdosphaera clavigera; Sample code/label; Sample ID; Sphenolithus akropodus; Sphenolithus apoxis; Sphenolithus bipedis; Sphenolithus calyculus; Sphenolithus capricornutus; Sphenolithus ciperoensis; Sphenolithus compactus; Sphenolithus conicus; Sphenolithus delphix; Sphenolithus disbelemnos; Sphenolithus dissimilis; Sphenolithus distentus; Sphenolithus microdelphix; Sphenolithus moriformis; Sphenolithus multispinatus; Sphenolithus pacificus; Sphenolithus paratintinnabulum; Sphenolithus peartiae; Sphenolithus predistentus; Sphenolithus procerus; Sphenolithus puniceus; Sphenolithus spinula; Sphenolithus truaxii; Sphenolithus umbrellus; Syracosphaera lamina; Transversopontis lata; Traverse; Triquetrorhabdulus carinatus; Triquetrorhabdulus challengeri; Triquetrorhabdulus milowii; Umbilicosphaera jafari; Zygrhablithus bijugatus
    Type: Dataset
    Format: text/tab-separated-values, 5820 data points
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  • 9
    Publication Date: 2023-05-12
    Keywords: ALTITUDE; DATE/TIME; ERA-CLIM; ERA-CLIM_4845; ERA-CLIM Quality flag; European Reanalysis of Global Climate Observations; Humidity, relative; Mount Weather; Pressure, at given altitude; Quality flag, air temperature; Quality flag, altitude; Quality flag, time; Temperature, air; United States of America; Weather station/meteorological observation; Wind direction; Wind speed; WST
    Type: Dataset
    Format: text/tab-separated-values, 97240 data points
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  • 10
    Publication Date: 2023-05-12
    Keywords: ALTITUDE; DATE/TIME; ERA-CLIM; ERA-CLIM_4846; ERA-CLIM Quality flag; European Reanalysis of Global Climate Observations; Humidity, relative; Mount Weather; Pressure, at given altitude; Quality flag, air temperature; Quality flag, altitude; Temperature, air; United States of America; Weather station/meteorological observation; Wind direction; Wind speed; WST
    Type: Dataset
    Format: text/tab-separated-values, 6731 data points
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