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COLSCREEN: 16S-sequencing of fecal microbiota from a population-based CRC screening program
<p><span>The research cohort (COLSCREEN study) was recruited among individuals that participated during 2016-2020 in the ongoing population-based CRC screening program overseen by the Catalan Institute of Oncology in L’Hospitalet del Llobregat, Barcelona, Spain. This program invites men and women between the ages of 50 and 69 to partake in the immunochemical fecal occult blood test (FIT). In the event of a positive FIT result (≥ 20 μg Hb/g feces), the participants are then recommended to undergo colonoscopy. Participants of the COLSCREEN study (N=997) were invited to participate after receiving a positive FIT result. Since CRC diagnosis is rare in screening, this cohort includes patients diagnosed clinically from the CRC Functional Unit (N=45). Furthermore, a subset of participants with a negative FIT is also included (N=140). All of them underwent a colonoscopy and participants were categorized based on the risk stratification proposal by Castells et al. after careful review of the colonoscopy and histopathology reports. All participants who agreed to take part of the COLSCREEN study provided written informed consent and donated a fecal and blood sample at recruitment (samples obtained before colonoscopy) and answered an epidemiological questionnaire. Clinically diagnosed CRC patients usually underwent a colonoscopy before recruitment, and the fecal samples were obtained prior surgery. In the present study, we excluded those participants that reported having used antibiotics or probiotics one month before sampling. </span></p>
Supplementary material 1 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Supplementary material 1 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Supplementary material 2 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Supplementary material 2 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Blood-based epigenome–wide analyses of chronic low–grade inflammation across diverse population cohorts
<p>Authors: Robert F. Hillary, Hong Kiat Ng, Daniel L. McCartney, Hannah R. Elliott, Rosie M. Walker, Archie Campbell, Felicia Huang, Kenan Direk, Paul Welsh, Naveed Sattar, Janie Corley, Caroline Hayward, Andrew M. McIntosh, Cathie Sudlow, Kathryn L. Evans, Simon R. Cox, John C. Chambers, Marie Loh, Caroline L. Relton, Riccardo E. Marioni, Paul D. Yousefi, Matthew Suderman</p> <p>Epigenome-wide association studies were performed on log-transformed blood C-reactive protein levels in Generation Scotland. Log-transformed CRP was the outcome. CpG beta-values were the exposure and were measured using the EPIC array (n=752,722 sites). </p> <p>A basic model adjusted for age, sex, experimental batch and Houseman-estimated white blood cell proportions. A fully-adjusted model further adjusted for alcohol consumption (units/week), log-transformed body mass index (kg/m2), education (11-category ordinal variable), deprivation (Scottish Index of Multiple Deprivation), EpiSmokEr (a methylation-based surrogate score for cigarette smoking) and 20 genetic principal components (to control for population structure).</p>
Figure 3 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 3. Ultrametric tree for Lyponiini. Branches marked by solid lines originate from continental Asia; those by dashed lines from Taiwan, Okinawa, and Japan. The grey dots/squares designate putative species identified using the general mixed Yule-coalescent model and the barcoding threshold, respectively. Terminals without designation were recovered as independent species-level entities.
Figure 2 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 2. Phylogenetic hypothesis on Lyponiini inferred from the maximum likelihood (ML) analysis. Numbers at the branches indicate maximum parsimony and ML bootstrap values, and Bayesian posterior probabilities (left to right).
Figure 7 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 7. The number of DNA diagnostic characters as a function of time since the split from the closest relative. The black-rimmed dots designate splits supported also by morphological characters, simple dots designate splits within morphologically defined clades.
Figure 1 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 1. Sampling sites of Lyponiini in (A) Continental East Asia, Taiwan and Okinawa and (B) Honshu and Shikoku.
Figure 6 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 6. Density plots of genetic distances of Lyponiini for (A) intra- and interspecific diversity of Lyponiini (B) intraspecific diversity for species as listed.
Figure 5 in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 5. Relationships between Kimura-two-parameter genetic and geographical distances of Lyponiini. A–E, interspecific and intraspecific species pairs for five clades; F, intraspecific pairs of Ponyalis quadricollis. The parameters and P-values are listed in Table 1.
Figure 4. A in DNA-based species delimitation separates highly divergent populations within morphologically coherent clades of poorly dispersing beetles
Figure 4. A, intraspecific relationships between maximum genetic and geographical distances of Lyponiini for the Chinese species pairs (blue) and Japanese species pairs (red). B, intraspecific maximum genetic divergence and geographical distances in Lyponiini (red) and Agabini (blue). The data on Agabini diving beetles are from Bergsten et al. (2012).
Fig. 8 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 8. Myosotis antarctica subsp. traillii photographs and distribution map. (a) Habit. (b, d) Rosette leaf tips: (b) adaxial and (d) abaxial sides. (c) Flower. (e) Nutlets. (f) Map of georeferenced herbarium specimens observed by J. M. Prebble (35). Whie scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, e by J. M. Prebble (a: WELT SP100487, Tiwai Point, Southland, South Island; e: WELT SP104518, cultivated ex Mason Bay, Stewart Island). b, c © Te Papa by H. M. Meudt (b: WELT SP090544, Manihi Rd, Taranaki, North Island; c: WELT SP090629, Hukanui, Gisborne, North Island; d: WELT SP090631, Waipuna, Gisborne, North Island).
Fig. 2 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 2. Maps of MaxEnt niche models for pygmy Myosotis in New Zealand and southern South America. (a) Myosotis glauca (light blue circles). (b) M. pygmaea (green circles). (c, h) M. "Volcanic Plateau" (grey triangles). (d) M. brevis (yellow cir-cles). (e) M. drucei (dark blue circles; excluding individuals identified as M. "Volcanic Plateau"). (f) M. drucei (dark blue circles) + M. pygmaea (green circles) + M. "Volcanic Plateau" (grey triangles) (g) M. antarctica (pink circles; Chilean locations), note scale is the same as for maps of New Zealand. a–f use models based on the nine-layer model (see Table 1), whereas g and h are based on the sevenlayer model.
Fig. 5 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 5. Myosotis glauca photographs and distribution map. (a) Habit. (b) Rosette leaves, adaxial and abaxial sides. (c) Calyces, left to right most to least mature. (d) Nutlets. (e) Map of georeferenced herbarium specimens observed by J. M. Prebble (16). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: all by J. M. Prebble (WELT SP093285, Nevis Valley, Otago).
Fig. 4 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 4. Myosotis brevis photographs and distribution map. (a) Habit. (b) Inflorescence showing cauline leaf abaxial side. (c) Inflorescence showing cauline leaf adaxial side, calyces, and flower. (d) Rosette leaf adaxial side showing colour morphs. (e) Flower. (f) Nutlet. (g) Map of georeferenced herbarium specimens observed by J. M. Prebble (25). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: a–e © Te Papa by H. M. Meudt (a: WELT SP090549, Te Ikaamaru Bay, Wellington; b, c: WELT SP090545, Ngawi, Wairarapa; d: WELT SP090543, Stent Road, Taranaki; e: WELT SP090550, Ohau Bay, Wellington); f by J. M. Prebble (WELT SP090543, cultivated ex Stent Road, Taranaki).
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I. (Fl. Antarct.) Part I, plate 38 (Hooker 1844). Illustration by W. H. Fitch. This image is in the public domain, downloaded from the Biodiversity Heritage Library (https:// www.biodiversitylibrary.org/page/13448452#page/81/ mode/1up, accessed 8 June 2021). Draft pencil drawings for this figure are attached to the type specimen of M. antarctica (K0007878799; visible online at http:// apps.kew.org/herbcat/getImage.do?imageBarcode= K000787899, accessed 8 June 2021), which was collected by J. D. Hooker from Campbell Island.
Fig. 6 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 6. Myosotis antarctica subsp. antarctica photographs and distribution maps. (a, b) Habit. (c) Rosette leaves abaxial and adaxial sides. (d) Flower. (e) Nutlets. (f) Map of mainland New Zealand distribution based on georeferenced herbarium specimens observed by J. M. Prebble (163). (g) Map of Campbell Island distribution based on georeferenced herbarium specimens observed by J. M. Prebble (14). (h) Map of Chilean distribution based on georeferenced herbarium specimens observed by J. M. Prebble (2). White scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, c, e by J. M. Prebble (a: WELT SP102777, Mt Azimuth, Campbell Island; c: WELT SP093293, Port Hills, Canterbury, South Island E: WELT SP100466, cultivated ex Mt Peel, Western Nelson. South Island). b, d © Te Papa by H. M. Meudt (b: WELT SP106592, Matiri Range, Western Nelson, South Island; d: WELT SP107322, Mt Starveall, Western Nelson, South Island).
Fig. 3 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 3. Plots displaying (a, c) omission and commission values and (b, d) area under the receiving operating characteristic curve (AUC) for two pygmy forget-me-not taxa: (a, b) M. "Volcanic Plateau" and (c, d) M. drucei, modelled using MaxEnt and all nine environmental layers for the New Zealand extent.
Fig. 1. Maps displaying all 290 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 1. Maps displaying all 290 occurrence points used for Myosotis pygmy species group niche modelling (Supplementary Table S1). Maps, clockwise from top: World, New Zealand, Campbell Island, and southern South America. Colour represents a priori species: M. antarctica (pink circles); M. drucei (dark blue circles); M. pygmaea (green circles); M. brevis (yellow circles); M. glauca (light blue circles); M. "Volcanic Plateau" (grey triangles).
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.