MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.
The mouse mammary gland is an excellent model system with which to study both the regulation of development and the functional differentiation of an organ. Most of the development occurs postnatally, when the gland undergoes a highly regulated cascade of invasive growth, branching, differentiation, secretion, apoptosis and remodelling during each pregnancy cycle [1,2]. Terminal differentiation of the alveolar epithelium is completed at the end of gestation with the onset of milk secretion (lactation). APR = acute-phase response; C/EBP = CCAAT/enhancer-binding protein; H&E = haematoxylin and eosin; IHC = immunohistochemistry; IL = interleukin; LIF = leukaemia inhibitory factor; LPS = lipopolysaccharide; OSM = oncostatin M; RT-PCR = reverse transcriptase polymerase chain reaction; SOM = self-organising map; TNF = tumour necrosis factor; WAP = whey acidic protein. Abstract Introduction: Involution of the mammary gland is a complex process of controlled apoptosis and tissue remodelling. The aim of the project was to identify genes that are specifically involved in this process.
Reducing insulin/IGF signaling allows for organismal survival during periods of inhospitable conditions by regulating the diapause state, whereby the organism stockpiles lipids, reduces fertility, increases stress resistance, and has an increased lifespan. The Target of Rapamycin (TOR) responds to changes in growth factors, amino acids, oxygen tension, and energy status; however, it is unclear how TOR contributes to physiological homeostasis and disease conditions. Here, we show that reducing the function of Drosophila TOR results in decreased lipid stores and glucose levels. Importantly, this reduction of dTOR activity blocks the insulin resistance and metabolic syndrome phenotypes associated with increased activity of the insulin responsive transcription factor, dFOXO. Reduction in dTOR function also protects against age-dependent decline in heart function and increases longevity. Thus, the regulation of dTOR activity may be an ancient "systems biological" means of regulating metabolism and senescence, that has important evolutionary, physiological, and clinical implications.
Marine ecosystems are changing rapidly as the oceans warm and become more acidic. The physical factors and the changes to ocean chemistry that they drive can all be measured with great precision. Changes in the biological composition of communities in different ocean regions are far more challenging to measure because most biological monitoring methods focus on a limited taxonomic or size range. Environmental DNA (eDNA) analysis has the potential to solve this problem in biological oceanography, as it is capable of identifying a huge phylogenetic range of organisms to species level. Here we develop and apply a novel multi-gene molecular toolkit to eDNA isolated from bulk plankton samples collected over a five-year period from a single site. This temporal scale and level of detail is unprecedented in eDNA studies. We identified consistent seasonal assemblages of zooplankton species, which demonstrates the ability of our toolkit to audit community composition. We were also able to detect clear departures from the regular seasonal patterns that occurred during an extreme marine heatwave. The integration of eDNA analyses with existing biotic and abiotic surveys delivers a powerful new long-term approach to monitoring the health of our world’s oceans in the context of a rapidly changing climate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.