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Figure 3 from: Al-Rafyai HM, Alwash MS, Al-Khafaji NS (2021) Quinolone resistance (qnrA) gene in isolates of Escherichia coli collected from the Al-Hillah River in Babylon Province, Iraq. Pharmacia 68(1): 1-7. https://doi.org/10.3897/pharmacia.68.e57819
Figure 3 Distribution of the qnrA gene among quinolone-resistant E. coli isolates in the three sampling sites along the Al-Hillah River.
Figure 2 from: Al-Rafyai HM, Alwash MS, Al-Khafaji NS (2021) Quinolone resistance (qnrA) gene in isolates of Escherichia coli collected from the Al-Hillah River in Babylon Province, Iraq. Pharmacia 68(1): 1-7. https://doi.org/10.3897/pharmacia.68.e57819
Figure 2 Agarose gel electrophoresis of PCR products derived from amplifying the qnrA gene of 61 E. coli isolates (516-bp). Lane M is a 1-kb DNA Ladder, and lanes 1 to 61 are E. coli isolates. Samples were amplified on 1.5% agarose gel, and isolates are labelled at the top of the figure.
Figure 5 from: Al-Rafyai HM, Alwash MS, Al-Khafaji NS (2021) Quinolone resistance (qnrA) gene in isolates of Escherichia coli collected from the Al-Hillah River in Babylon Province, Iraq. Pharmacia 68(1): 1-7. https://doi.org/10.3897/pharmacia.68.e57819
Figure 5 Distribution of the qnrA gene among phylogenetic subgroups of quinolone-resistant E. coli isolates recovered from the three sampling sites.
Figure 4 from: Al-Rafyai HM, Alwash MS, Al-Khafaji NS (2021) Quinolone resistance (qnrA) gene in isolates of Escherichia coli collected from the Al-Hillah River in Babylon Province, Iraq. Pharmacia 68(1): 1-7. https://doi.org/10.3897/pharmacia.68.e57819
Figure 4 Distribution of the qnrA gene among phylogenetic groups of quinolone-resistant E. coli isolates recovered from the three sampling sites.
Microsatellite genotype data from seven loci for a phylogeographic/population genetic study of the South African endemic freshwater crab Potamonautes lividus sampled from eight localities in the KwaZulu-Natal and Eastern Cape provinces in South Africa
<ol> <li>During the present study, the phylogeography of the only southern African IUCN Red Listed vulnerable (VU) freshwater crab, <i>Potamonautes lividus</i> was investigated by surveying several localities in the Eastern Cape and KwaZulu-Natal provinces in South Africa. Both nuclear and mitochondrial DNA markers were used, and it was hypothesized, that marked genetic differentiation should be present, while niche modeling was undertaken to explore the distribution of the species along the east coast of South Africa. <span><span>Further, the shortfalls in the present approach to IUCN Red Listing, as illustrated by a vulnerable species of crabs are discussed</span></span>.</li> <li>Results from the mtDNA revealed the presence of two haploclades confined to specimens from the two provinces respectively and the general absence of maternal dispersal; a fact that was further validated by the marked <i>F</i><sub>ST</sub> data and high F<sub>ST</sub>. Within the Eastern Cape haploclade, low frequency maternal dispersal occurred, corroborated by the low F<sub>ST</sub>. In contrast, no haplotypes were shared in the KwaZulu-Natal haploclade a fact corroborated by marked F<sub>ST</sub> differences. </li> <li>The microsatellite data demonstrated the presence of higher frequency, possibly paternally biased dispersal of specimens between the Eastern Cape and KwaZulu-Natal provinces. Our results suggest that presence of two distinct management units within <i>P. lividus</i>. Divergence time estimation suggest a late Pleistocene cladogenesis between the Eastern Cape and KwaZulu-Natal haploclades. </li> <li>Considering the presence of <i>P. lividus</i> in several newly collected nature conservation areas in both provinces, and its potential presence in the intermediary area based on the MAXENT niche modeling, our data suggest the species IUCN Red Listing status should be downgraded to LC.</li> <li>A comparison of all the EN, VU and CR IUCN Red Listed freshwater crabs for the entire Afrotropical region reveals the lack of recent sampling in the three biodiversity hotspots in West, Central and East Africa, with mountainous areas containing a disproportionate number of species with most species being devoid of phylogeographic study. </li> </ol>
Figure 6 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 6 Diaporthe multiguttulata on Citrus maxima (BJFC-S1614) a, b habit of conidiomata on twig c conidiomata on PDAd transverse section through conidiomata e longitudinal section through conidiomata f conidiogenous cells attached with alpha conidia g alpha conidia h the colony on PDA. Scale bars: 200 μm (b, d, e); 10 μm (f, g).
Figure 4 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 4 Diaporthe citri on Citrus sinensis (BJFC-S1658) a, b symptoms on leaves of host plant c culture on PDA (30d) d conidiomata e alpha conidia f conidiophores and alpha conidia. Scale bars: 10 μm (e, f).
Figure 3 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 3 Diaporthe bauhiniae on Bauhinia purpurea (BJFC-S1621) a habit of conidiomata in wood b transverse section of conidiomata c longitudinal section through conidiomata d the colony on PDAe conidiogenous cells attached with alpha conidia f Alpha conidia g Beta conidia. Scale bars: 100 μm (b, c); 10 μm (e–h).
Figure 7 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 7 Diaporthe schimae on Schima superba (BJFC-S1661) a symptoms on leaves of host plant b the colony on PDAc conidiomata on PDAd conidiophores cells attached with beta conidia e Alpha conidia. Scale bars: 10 μm (d, e).
Figure 1 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 1 Phylogram of Diaporthe from a Maximum Likelihood analysis based on combined ITS, cal, his3, tef1 and tub2. Values above the branches indicate Maximum Likelihood bootstrap (left, ML BP ≥ 50%) and Bayesian probabilities (right, BI PP ≥ 0.90). The tree is rooted with Diaporthella corylina. Strains in current study are in blue font and the ex-type cultures are in bold font.
Figure 9 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 9 Diaporthe xunwuensis on unknown host (BJFC-S1679) a the colony on PDA and conidiomata b alpha conidia c conidiogenous cells attached with alpha conidia. Scale bars: 10 μm (a–c).
Figure 8 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 8 Diaporthe verniciicola on Vernicia montana (BJFC-S1622) a, b habit of conidiomata on twig c transverse section through conidiomata d longitudinal section through conidiomata e alpha conidia f conidiophores g culture on PDA (30d). Scale bars: 500 μm (b); 200 μm (c); 10 μm (e, f).
Figure 5 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 5 Diaporthe ganzhouensis on unknown host (BJFC-S1678) a the colony on PDA and conidiomata b alpha and beta conidia c conidiogenous cells and alpha conidia. Scale bars: 10 μm (b, c).
Figure 2 from: Yang Q, Jiang N, Tian C-M (2021) New species and records of Diaporthe from Jiangxi Province, China. MycoKeys 77: 41-64. https://doi.org/10.3897/mycokeys.77.59999
Figure 2 Diaporthe apiculatum on Rhus chinensis (BJFC-S1680) a, b habit of conidiomata in wood c transverse section of conidiomata d longitudinal section through conidiomata e conidiogenous cells attached with beta conidia f the colony on PDA. Scale bars: 200 μm (b–d); 10 μm (e).
Data from: Spatial-temporal variability and related factors of soil organic carbon in Henan province
Spatial variability and influence factors are important to evaluate soil organic carbon(SOC) and the carbon pool in large areas. In the present study, sampling was conducted from May to November 2011 in Henan province, a typical agricultural region of central China, to study the effects of soil properties and anthropogenic factors on SOC variability in cropland. Physicochemical properties of soil samples were analyzed, which were collected at 280 sites from the surface layer (at a depth of 0–20 cm), and related data about the sampling sites were also collected from the Second State Soil Survey of China (SSSSC), conducted in 1981. The main results were as follows: 1) Increasing trends in soil organic carbon density (SOCD) and soil organic carbon pool (SOCP) were obvious from 1981 to 2011, and we conclude that cropland presents great carbon sequestration potential for the future. Carbon pool ability varied with soil properties: the order of fixed carbon amount in different soil types was found to be Inceptisols > Luvisols > Semi-hydromorphic soil > Anthrosols, and the average SOCP increased significantly from 1981 to 2011. 2) Soil bulk density, pH and returning straw are the key influence factors for SOCD in the past 30 years. 3) Although random factors (returning straw) only explain 29.1% of SOCD variability, the factor should be paid more attention, because application of returning strawwas the most dominant anthropogenic factors, which can be used to improve cropland productivity and carbon sink capacity within a short period if they are properly managed in the future.
FIGURE 1 in A new fossil mordellid (Coleoptera: Tenebrionoidea: Mordellidae) from the Yixian Formation of Western Liaoning Province, China
FIGURE 1. Praemordella martynovi redrawn from Scegoleva-Barovskaja (1929).
FIGURE 1 in The checkered beetles (Coleoptera: Cleridae) of the Maritime Provinces of Canada
FIGURE 1. Distribution of Zenodosus sanguineus in the Maritime Provinces.
FIGURE 2 in The checkered beetles (Coleoptera: Cleridae) of the Maritime Provinces of Canada
FIGURE 2. Distribution of Phyllobaenus humeralis and P. lecontei in the Maritime Provinces.
FIGURE 4 in The checkered beetles (Coleoptera: Cleridae) of the Maritime Provinces of Canada
FIGURE 4. Distribution of Thanasimus dubius in the Maritime Provinces.
FIGURE 3 in The checkered beetles (Coleoptera: Cleridae) of the Maritime Provinces of Canada
FIGURE 3. Distribution of Phyllobaenus verticalis and P. pallipennis in the Maritime Provinces.
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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.