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Fig. 1. Carpomyini. 1–2 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 1. Carpomyini. 1–2 — Carpomya pardalina, Kherson (1 — freshly emerged male; 2 — infested melon with holes in skin (cyan arrows) prepared by larvae for emerging of adults); 3 — Rhagoletis meigenii on Berberis fruit, Berlin; 4 — R. cerasi on Lonicera fruit, Kyiv, Grishko Botanical Gardens. Photos by R. I. Mishustin (1–2) and V. A. Korneyev (3–4).
Fig. 4 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 4. Carpomya spp. wings: 1 — C. (Goniglossum) wiedemanni; 2 — C. (Myiopardalis) pardalina; 3 — C. (s. str.) incompleta; 4 — C. (s. str.) schineri; 5 — C. (s. str.) vesuviana.
Fig. 3 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 3. Carpomya spp. mesonotums, dorsal view: 1 — C. (Goniglossum) wiedemanni; 2 — C. (G.) liat; 3 — C. (Myiopardalis) pardalina; 4 — C. (s. str.) incompleta; 5 — C. (s. str.) schineri.
Fig. 7 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 7. Rhagoletis spp. wings: 1 — R. obsoleta, Myhiia; 2 — R. sp. near obsoleta, Mt. Hermon; 3 — R. completa;
Fig. 4 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals
Fig. 4. Geographical and palaeogeographical locations of the studied area with arrows indicating dispersals of different species of the genus Praepusa from the Eastern Paratethys westward: 1 — Praepusa vindobonensis: Western Kazakhstan and Austria, Middle Miocene, early Sarmatian (16.5–11.2 Ma); 2 — Pr. vindobonensis (= tarchankutica): Ukraine and Moldova, Middle Miocene, middle Sarmatian (13.6–12.3 Ma); 3 — Pr. pannonica: Moldova and Hungary, Middle Miocene, early-middle Sarmatian (12.3–11.2 Ma). 4 — Pr. magyaricus: Vienna Basin, middle Sarmatian, Middle Miocene (13.6–12.3 Ma); 5 — Pr. boeska: The Netherlands and Belgium, Late Miocene — Early Pliocene (11.6–3.2 Ma).
Fig. 1 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals
Fig. 1. Sandpit de Kuilen, location of Mill-Langenboom, in the eastern Noord-Brabant, The Netherlands(Late Miocene).
Fig. 3 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals
Fig. 3. Sacrum of Praepusa boeska sp. n., RGM 629552, collection of the Naturalis Biodiversity Center in Leiden (NL). Zanclian–Piacenzian (Pliocene), Antwerp Basin, Belgium: A — ventral view; B — dorsal view; C — cranial view.
FIG. 1 in Three new species of Begonia sect. Erminea (Begoniaceae) from north-east Madagascar
FIG. 1. — Geographic distribution of Begonia ambanizanensis Scherber. & Duruiss., sp. nov., Begonia ambodiforahensis Scherber. & Duruiss., sp. nov. and Begonia harimalalae Scherber. & Duruiss., sp. nov. in north-east Madagascar.
Figs 62-67 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 62-67: Median lobe of aedoeagus, lateral aspect. Anthracus javaensis nov.sp. (62) HT and A. siamensis nov.sp. (63, 64, 67) PT, Laos, Pakkading, (65) HT, (66) Thailand, Ban Khoun.
Figs 74-79 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 74-79: Median lobe of aedoeagus, lateral and dorsal aspect. Anthracus skalei JAEGER (74) PT, Bangladesh, Nasirabad, (75) PT, India, Kurseong, A. spec. 1 near A. biplagiatus (BOHEMAN) (76, 77) Bangladesh, Nasirabad, A. spec. 2 near A. annamensis (BATES) (78,79) Myanmar, Pegu.
Figs 1-2 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 1-2: Anthracus nesophilus (ANDREWES, 1936). Habitus. (1) A. nesophilus, HT, (2) A. haemorrhous (LOUWERENS, 1952), HT.
Figs 50-55 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 50-55: Anthracus sumatraensis nov.sp. Median lobe of aedoeagus, lateral and dorsal aspect. (50, 52, 53, 55) PT, (51, 54) HT.
Figs 24-28 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 24-28: Anthracus nesophilus (ANDREWES, 1936). Median lobe of aedoeagus, lateral aspect. (24) Sulawesi, Ujung Pandang, (25) HT, A. haemorrhous, (26, 28) Java, Batavia, (27), HT, A. nesophilus.
Figs 56-61 in Revision of the maculate species of the Anthracus annamensis group from the East Palaearctic and Oriental Regions. Part 2. A redescription of Anthracus nesophilus (ANDREWES, 1936) and six new species from Nepal, India and SE Asia (Coleoptera, Carabidae, Harpalini, Stenolophina)
Figs 56-61: Anthracus hornburgi nov.sp. Median lobe of aedoeagus, lateral and dorsal aspect. (56, 59) HT, (57, 58, 60, 61) PT, Myanmar, Pegu, (61a) PT, Myanmar, Tharrawaddy.
Data set for the fauna material excavated at the Liang Abu site (East Kalimantan, Indonesia)
<p>Data set for the fauna material excavated at the Liang Abu site (East Kalimanta, Indonesia): count by subphylum, class, order, family, genus, and species for the squares 11Ec, 11Ed, and12Eb.</p>
Data set for the lithic material excavated at the Liang Abu site (East Kalimantan, Indonesia)
<p>Three tables describing the lithic material excavated at the Liang Abu site (East Kalimantan, Indonesia):</p> <ul> <li>abu-lithic-class.csv: count by class by stratigraphic layer</li> <li>abu-lithic-spatial-distribution.csv: count by square and stratigraphic layer</li> <li>abu-lithic-flakes.csv: morphometric values of the flakes</li> </ul>
Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and East Asian ancestries
<p><strong>Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions, and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Cross-tissue analyses indicated that over a third of effector genes most likely act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis, and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.</strong></p> <p><strong>The data submitted here are expression and methylation models with LD reference data for the transcriptome-wide (TWAS), methylome-wide (MWAS) and transcript isoform-wide association study (TIsWAS) as described in the manuscript "Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and East Asian ancestries". Details of the methods are presented in the method section and supplementary information file. </strong></p> <p><strong>TWAS analysis </strong></p> <p>Gene expression models for the six in-house expression datasets were generated using the PredictDB v7 pipeline for a total of 1,077 participants. Elastic net model building with 10-fold cross-validation was performed independently for each dataset. The elastic net models for GTEx v8 Colon Transverse were obtained from the PredictDB data repository (<a href="http://predictdb.org/">http://predictdb.org/</a>) and had been generated using the same pipeline. Models were computed using HapMap2 SNPs ±1Mb from each gene, together with covariate factors estimated using PEER32, clinical covariates when appropriate (age, sex and, where appropriate, case-control status, type of polyp and anatomic location in the colorectum), and three PCs from the individual dataset’s SNP genotype data.</p> <p>Transcript-based TWAS analyses (TIsWAS) were likewise performed by using transcript-level data from the SOCCS, BarcUVa-Seq and GTEx Colon Transverse datasets.</p> <p><strong>MWAS analysis </strong></p> <p>Methylation beta values were calculated based on the manufacturer’s standard, ranging from 0 to 1. Quality control and data normalization were performed in R using the ChAMP software pipeline for the EPIC and 450K arrays. Briefly, we filtered out failed probes with detection P > 0.02 in >5% of samples, probes with <3 reads in >5% of samples per probe and all non-CpG probes. Samples with failed probes >0.1 were also excluded from downstream analyses. We discarded all probes with SNPs within 10bp of the interrogated CpG (from 1,000 Genomes Project, CEU population)34, and probes that ambiguously mapped to multiple locations in the human genome with up to two mismatches33. We only considered probes mapping to autosomes and those overlapping between the EPIC and the 450K arrays. Normalization was achieved using the Beta MIxture Quantile (BMIQ) method. Per probe methylation models were created using the PredictDB pipeline on the normalized methylation matrix and the genotypes as per TWAS eQTL analysis. To optimize power, we restricted our analysis to 263,341-238,443 (for the 450K array) and 377,678 (for the EPIC array) probes annotated to Islands, Shores and Shelves, and discarded “Open Sea” regions. </p>
Stable Water Isotopes and Nutrients in the Changjiang (Yangtze River) Estuary and adjacent East China Sea shelf in Winter
<p>The dataset presented here includes the temperature, salinity, stable water isotopes, and nutrients of seawater from the Changjiang Estuary and adjacent East China Sea shelf in March 2013. </p>
Standardized Dataset of the Ecosystem's Water Use Efficiency, Gross Primary Productivity and the Evapotranspiration Deficit Index for 1982–2017 over the Middle East
<p>This data aimed to investigate the spatial-temporal variability of Standardized Actual Evapotranspiration (sAET), Gross Primary Productivity (sGPP) and Water Use Efficiency (WUE) anomalies series, and the Standardized Evapotranspiration Deficit Index (SEDI). The Middle East (ME), was selected as a case study to monitoring drought events as one of the major natural disasters for the ecosystem. To this end, the yearly gross primary production of GLASS, GIMMS, FloxCom, and VPM datasets for the study area spanning 1982–2017 was used to develop the sGPPR data. On the other hand, the Global Land Evaporation Amsterdam Model (GLEAM-version (v3.3a)), which estimated the several components of terrestrial evaporation (annual actual and potential evaporation (AET, PET)) was used for the same period this aimed to detect the variability of the SEDI.<br> This version of the yearly GLASS-sGPPR dataset (1982–2017) is available for the ME at 0.05° spatial resolution, as the original data of the GPP-GLASS products, While, sGPPR dataset of GIMMS, FloxCom, and VPM are also at annual temporal resolution, and at 0.5 degree spatial resolution spanning 1982–2016 for GIMMS, FloxCom, and 2000-2016 for VPM (Excel wrokbook .xlsx). The SEDI data are also available at 0.25 degree spatial resolution for 1980–2018 ( Raster files (TIFF)). For more details about Standardization of the GPP and evapotranspiration deficit data see: <strong>Alsafadi, K., Al-Ansari, N., Mokhtar, A., Mohammed, S., Elbeltagi, A., Sammen, S. S., & Bi, S. (2021). An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East. <em>Environmental Research Letters</em>. <a href="http://dx.doi.org/10.1088/1748-9326/ac4765">10.1088/1748-9326/ac4765</a></strong></p>
Data on the abundance of wild ungulates and large carnivores in the Roztocze National Park (south-east Poland), 2007-2022
<p>Data on the abundance of wild ungulates and large carnivores in the Roztocze National Park (south-east Poland), 2007-2022</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.