Source Data for EMBOR-2023-58131V2
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus (mouse)
SUBMITTER:
PROVIDER: S-BSST1371 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Understanding of TMZ therapy during and after treatment in a mouse model
2023-08-10 | GSE227348 | GEO
Project description:DrugCentral monitors new drug approvals and standardizes drug information. The current update contains 285 drugs (131 for human use). New additions include: (i) the integration of veterinary drugs (154 for animal use only), (ii) the addition of 66 documented off-label uses and iii) the identification of adverse drug events from pharmacovigilance data for pediatric and geriatric patients. Additional enhancements include chemical substructure searching using SMILES and 'Target Cards' based on UniProt accession codes. Statistics of interests include the following: (i) 60% of the covered drugs are on-market drugs with expired patent and exclusivity coverage, 17% are off-market, and 23% are on-market drugs with active patents and exclusivity coverage; (ii) 59% of the drugs are oral, 33% are parenteral and 18% topical, at the level of the active ingredients; (iii) only 3% of all drugs are for animal use only; however, 61% of the veterinary drugs are also approved for human use; (iv) dogs, cats and horses are by far the most represented target species for veterinary drugs; (v) the physicochemical property profile of animal drugs is very similar to that of human drugs. Use cases include azaperone, the only sedative approved for swine, and ruxolitinib, a Janus kinase inhibitor.
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Project description:Given trained models from multiple source domains, how can we predict the labels of unlabeled data in a target domain? Unsupervised multi-source domain adaptation (UMDA) aims for predicting the labels of unlabeled target data by transferring the knowledge of multiple source domains. UMDA is a crucial problem in many real-world scenarios where no labeled target data are available. Previous approaches in UMDA assume that data are observable over all domains. However, source data are not easily accessible due to privacy or confidentiality issues in a lot of practical scenarios, although classifiers learned in source domains are readily available. In this work, we target data-free UMDA where source data are not observable at all, a novel problem that has not been studied before despite being very realistic and crucial. To solve data-free UMDA, we propose DEMS (Data-free Exploitation of Multiple Sources), a novel architecture that adapts target data to source domains without exploiting any source data, and estimates the target labels by exploiting pre-trained source classifiers. Extensive experiments for data-free UMDA on real-world datasets show that DEMS provides the state-of-the-art accuracy which is up to 27.5% point higher than that of the best baseline.
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Project description:Olympic Coast National Marine Sanctuary (OCNMS), which was established in 1994 and covers an area of 8257 km2, is located along Washington State's remote and rugged outer coast towards the northernmost extent of the California Current System (CCS). In this region, summertime equatorward winds drive seasonal upwelling of cold, nutrient rich waters onto the continental shelf. These waters help fuel a highly diverse and productive ecosystem that includes marine mammal and seabird communities as well as commercially and culturally important fisheries. The sanctuary is located within the boundaries of the legally defined Usual and Accustomed (U&A) fishing grounds of four Coastal Treaty Tribes, the Hoh Tribe, Makah Tribe, Quileute Tribe, and the Quinault Indian Nation, which hold treaty fishing rights and co-manage fisheries and other natural resources within the sanctuary through state, federal, and international partnerships and agreements. This data article describes shipboard hydrographic Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected within the sanctuary at fourteen locations during mooring deployment, recovery, and maintenance cruises between the months of May and October from 2005-2023. The 792 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed using Sea-Bird Scientific's SBE Data Processing application. These data are needed for improving our understanding of subsurface oceanographic conditions - including marine heat waves, changes in timing of spring transition to upwelling, seasonal hypoxia, and ocean acidification - in this important but undersampled region, and can be used to help improve the management of marine resources regionally and within the sanctuary. The CTD cast data are available via Zenodo at https://doi.org/10.5281/zenodo.10466124.
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