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221 results for “structural biology”
Fig. 10 in Progress in structure, synthesis and biological activity of natural cephalotane diterpenoids
Fig. 10. Cytotoxicity of compounds 2, 20, 21, and 25 against A-549, KB, HL-60 and HT-29 cells (IC50 in μM).
Fig. 14 in Progress in structure, synthesis and biological activity of natural cephalotane diterpenoids
Fig. 14. Brief summary of the antitumor structure–activity relationships (SARs) of cephalotane diterpenoids.
Fig. 1 in Progress in structure, synthesis and biological activity of natural cephalotane diterpenoids
Fig. 1. Distributions of reported cephalotane diterpenoids in the different species of the Cephalotaxus genus.
Data from: Warming reduces the growth and diversity of biological soil crusts in a semi-arid environment: implications for ecosystem structure and functioning
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Inelastic scattering of electrons in water from first principles: Cross sections and inelastic mean free path for use in Monte Carlo track-structure simulations of biological damage
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Species diversity and food web structure jointly shape natural biological control in agricultural landscapes
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Figure 6 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 6 A–C Minimum spanning networks of COI haplotypes, color-coded for each hypothesis of structure. A Four faunal regions of hypothesis I B ten watersheds of hypothesis II C five genetic clusters of hypothesis III D A split network of 85 COI sequences revealing the five genetically distinct clusters of hypothesis III.
Figure 7 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 7 Representative male genitalia from 17 of the sampled caves: 1 Wells Cave; 2 Pine Hill Cave; 3–5 Wind Cave; 6 Richardson's Cave; 7, 8 Lainhart #1 Cave; 9, 10 and 15, 16 Pourover Cave; 11, 12 John Griffin Cave; 13 Climax Cave; 14 Hicksey Cave; 17, 18 Stab Cave; 19, 20 Piney Grove Cave; 21, 22 Dykes Bridge Cave; 23 Great Saltpeter Cave; 24 Teamers Cave; 25 Mullins Spring Cave; 26 Jesse Cave; 27 Steel Hollow Cave. Note that Wells and Dykes Bridge Caves were not included in the genetic study.
Figure 1 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 1 (Adapted from Barr 1985, Figure 3) Map showing the major geologic features important for cave development in the southeastern United States: MP-I and MP-II (green) are western and eastern bands of the Mississippian Plateau. Dots indicate collecting records (see Figure 3).
Figure 5 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 5 Frequencies of COI haplotypes and their proportions, color coded for each hypothesis of structure; circle area corresponds to number of individuals assigned to each group. Overlain transparent dots show collecting localities. A Four faunal regions of hypothesis I (fifth region unsampled in this study: see discussion and Barr 1985, Kane et al. 1992) B ten minor watersheds of hypothesis II C five genetic clusters of hypothesis III.
Figure 4 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 4 Distribution of cave collection sites and proportions of haplotypes from 27 populations of Darlingtonea kentuckensis in eastern Kentucky, USA. Circle area corresponds to number of individuals sampled per locality. Different colors indicate different haplotypes; similarity in hue qualitatively indicates sequence similarity. KR: Kentucky River; RR: Rockcastle River; CR: Cumberland River; MVF: Mount Vernon Fault; DD = drainage divide between Kentucky and Rockcastle rivers.
Figure 3 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 3 Cave localities of currently known sites for Darlingtonea kentuckensis. White dots were the caves sampled for this study while black dots represent caves unsampled.
Figure 2 from: Boyd OF, Philips TK, Johnson JR, Nixon JJ (2020) Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechini). Subterranean Biology 34: 1-23. https://doi.org/10.3897/subtbiol.34.46348
Figure 2 Gravid female Darlingtonea kentuckensis photographed in Fletcher Spring Cave, Rockcastle County, Kentucky. Photo courtesy of Dr. Matthew Niemiller, University of Alabama, Huntsville.
Biological productivity and community structure of phytoplankton in the oligotrophic Philippine Sea
<p>In the Philippine Sea, mesoscale eddies have been frequently observed, but little is known about their contributions to the biological productivity and community structure of phytoplankton in the region. In situ carbon and nitrogen uptake rates and phytoplankton community structure were investigated in the Philippine Sea based on the 13C-15N dual-tracer technique and photosynthetic pigment analysis from late August to September 2018. Based on the comparison of the phytoplankton community structure among the cold eddy, warm eddy, and outer area, we found that the phytoplankton composition was different in the warm eddy with relatively lower contributions of large phytoplankton. However, a distinct enhancement in phytoplankton biomass over the euphotic zone was not detected even in eddy occurrence. In terms of community, the picoplankton Prochlorococcus was persistently dominant, which was attributed to a low supply and chemical composition of nutrients. The average integrated primary productions (IPP) were 80.4, 75.9, and 76.3 mg C m−2 d−1 for the cold eddy, warm eddy, and outer area, respectively. The IPP under the eddy condition was not largely different from that in reference sites, even though the vertical distribution of productivity maximum was found to be different depending on eddy condition. These weak biological responses to mesoscale eddies might be attributed to the sustaining picoplankton-dominant community structure and no substantial upward inputs of nutrients to the euphotic zone. Our findings represent an important contribution to understanding the biological response of mesoscale eddies in the oligotrophic Philippine Sea.</p>
Fig. 9 in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 9. Experimental ECD spectra of 5 and 6 in MeCN.
Fig. 7. Proposed biosynthetic relationships between compounds 7 and 1–3 in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 7. Proposed biosynthetic relationships between compounds 7 and 1–3.
Fig. 4 in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 4. ORTEP drawing of 1.
Fig. 5 in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 5. Experimental and calculated ECD spectra of 2 in MeCN.
Fig. 2. 1H–1H in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 2. 1H–1H COSY (for 2–4, and 6) and selected HMBC correlations (for 1–6).
Fig. 3 in Phytochemical and biological studies on rare and endangered plants endemic to China. Part XXII. Structurally diverse diterpenoids from the leaves and twigs of the endangered conifer Torreya jackii and their bioactivities
Fig. 3. Key NOE correlations of 1–6.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.