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12,346 results for “derivatives”
Supplementary material 1 from: Sivakumar B, Kaliappan I (2023) Lead drug discovery from imidazolinone derivatives with Aurora kinase inhibitors. Pharmacia 70(4): 1529-1540. https://doi.org/10.3897/pharmacia.70.e114935
Supplementary data
Figure 2 from: Mitkov J, Kondeva-Burdina M, Zlatkov A (2019) Synthesis and preliminary hepatotoxicity evaluation of new caffeine-8-(2-thio)-propanoic hydrazid-hydrazone derivatives. Pharmacia 66(3): 99-106. https://doi.org/10.3897/pharmacia.66.e37263
Figure 2 Effect of the hydrazid-hydrazones 6a–i, administered alone at concentration 100 µM, on isolated rat liver microsomes.
Dataset for "Label-free enrichment of human pluripotent stem cell-derived early retinal progenitor cells for cell-based regenerative therapies"
<p>The raw dataset for "Label-free enrichment of human pluripotent stem cell-derived early retinal progenitor cells for cell-based regenerative therapies"</p> <p><span>DOI:</span><a href="https://doi.org/10.1016/j.stemcr.2023.12.001">https://doi.org/10.1016/j.stemcr.2023.12.001</a></p>
Design and functional characterization of Salmo salar TLR5 agonist peptides derived from High Mobility Group B1 acidic tail.
<p>Based on the structural knowledge of TLR5 surface using blind docking platforms, a series of peptides derived from HMGB1 truncated acidic tail from Salmo salar was designed TLR5 agonistic. Also, a template peptide with the wild type C-terminal acidic tail sequence as reference was included (SsOri). Peptide binding poses complexed on TLR5 ectodomain model from each algorithm were filtrated based on docking scoring functions and predicted theoretical binding affinity of complex.</p>
Raw data of the article:Proof-of-Concept Study on the Use of Tangerine-Derived Nanovesicles as siRNA Delivery Vehicles toward Colorectal Cancer Cell Line SW480
<p>In the last years, the field of nanomedicine and drug delivery has grown exponentially, providing new platforms to carry therapeutic agents into the target sites. Extracellular vesicles (EVs) are ready-to-use, biocompatible, and non-toxic nanoparticles that are revolutionizing the field of drug delivery. EVs are involved in cell-cell communication and mediate many physiological and pathological processes by transferring their bioactive cargo to target cells. Recently, nanovesicles from plants (PDNVs) are raising the interest of the scientific community due to their high yield and biocompatibility. This study aims to evaluate whether PDNVs may be used as drug delivery systems. We isolated and characterized nanovesicles from tangerine juice (TNVs) that were comparable to mammalian EVs in size and morphology. TNVs carry the traditional EV marker HSP70 and, as demonstrated by metabolomic analysis, contain flavonoids, organic acids, and limonoids. TNVs were loaded with DDHD1-siRNA through electroporation, obtaining a loading efficiency of 13%. We found that the DDHD1-siRNA complex TNVs were able to deliver DDHD1-siRNA to human colorectal cancer cells, inhibiting the target expression by about 60%. This study represents a proof of concept for the use of PDNVs as vehicles of RNA interference (RNAi) toward mammalian cells.</p>
Parkinsonism Sac domain mutation in Synaptojanin-1 affects ciliary properties in iPSC-derived dopaminergic neurons
<p>The tabular dataset for all graphs in Rafiq et al 2024 can be found in the ASAP data repository</p>
Fig. 2 in Biotransformation of betulinic acid by Circinella muscae and Cunninghamella echinulata to discover anti-inflammatory derivatives
Fig. 2. Key COSY and HMBC correlations of metabolites 2, 4, and 8.
Fig. 1 in Biotransformation of betulinic acid by Circinella muscae and Cunninghamella echinulata to discover anti-inflammatory derivatives
Fig. 1. Biotransformation of betulinic acid by C. muscae and C. echinulata.
Fig. 3 in Biotransformation of betulinic acid by Circinella muscae and Cunninghamella echinulata to discover anti-inflammatory derivatives
Fig. 3. Key NOESY correlationships of metabolites 2 and 8.
Fig. 2 in Nine geranylgeranylated derivatives isolated from the roots of Rhus chinensis Mill.
Fig. 2. Key HMBC correlations of compounds 1–7.
Fig. 3. Key 1H–1H in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 3. Key 1H–1H COSYs and HMBCs of 3–8.
Fig. 6 in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 6. Experimental and calculated ECD spectra of 4, and 9–10.
Fig. 4. Key 1H–1H in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 4. Key 1H–1H COSYs and HMBCs of 9 and 10.
Fig. 2. Key 1H–1H in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 2. Key 1H–1H COSYs and HMBCs of 1 and 2.
Fig. 5 in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 5. Key NOESY correlations of 9 and 10.
Fig. 1 in Bioactive polyketide derivatives from the endophytic fungus Phaeosphaeriopsis musa
Fig. 1. Structures of compounds 1–10 isolated from Phaeosphaeriopsis musae.
Tracking gold mining derived mercury pollution into human diets in the Madre de Dios region of Peru
<p>Artisanal and small-scale gold mining (ASGM) is the largest global anthropogenic mercury (Hg) source and is widespread in the Peruvian Amazon. While numerous studies have examined fish Hg content near ASGM, Hg accumulation in other commonly consumed animal- and plant-based foods from terrestrial environments is often overlooked. These data were collected in 2018 and 2019 to understand Hg exposure from food staples in Peru's Madre de Dios region. This dataset contains measurements of total Hg and methyl Hg content in locally sourced crops, fish, chicken meat, chicken feathers, and eggs from ASGM-impacted and upstream reference communities. Stable carbon and nitrogen isotope signatures from fish and chicken were also measured to characterize trophic position and magnification.</p>
Psychochemical properties and bioactivity of biogenic nano-hydroxyapatite derived from scallop shell waste
Open the record for dataset details and reuse information.
ESA 4DMED-SEA - Mediterranean Sea Gridded L4 4DvarNET (1/8°) Sea Surface Heights And Derived Variables
<p>The gridded Sea Level Anomalies (SLA) presented here result from the application of the 4DVARNET algorithm, as described by <a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>. Here, the resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) is here downgraded to 1/8°. The algorithm takes as input Level-3 altimeter data distributed by the Copernicus Marine Service (<a href="https://doi.org/10.48670/moi-00139" target="_new">https://doi.org/10.48670/moi-00139</a>). This product provides additional variables such as Absolute Dynamic Topography and geostrophic currents (both absolute values and anomalies) at a resolution of 1/24° over the Mediterranean Sea and for the period from 2016 to 2022. It is intended for delayed-time applications.</p>
ESA 4DMED-SEA - Mediterranean Sea Gridded L4 4DvarNET (1/20°) Sea Surface Heights And Derived Variables
<p>The gridded Sea Level Anomalies (SLA) presented here result from the application of the 4DVARNET algorithm, as described by <a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>. Here, the resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) is here downgraded to 1/20°. The algorithm takes as input Level-3 altimeter data distributed by the Copernicus Marine Service (<a href="https://doi.org/10.48670/moi-00139" target="_new">https://doi.org/10.48670/moi-00139</a>). This product provides additional variables such as Absolute Dynamic Topography and geostrophic currents (both absolute values and anomalies) at a resolution of 1/24° over the Mediterranean Sea and for the period from 2016 to 2022. It is intended for delayed-time applications.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.