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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.
Raw - EBV-specific CD8 T lymphocytes and B cells during glatiramer acetate therapy in patients with MS
<p>Intracellular staining overnight</p>
Figure 9 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 9 Chromatogram of carbohydrates formed as a result of enzymatic hydrolysis in the herbal mixture No. 19 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose).
Figure 8 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 8 Chromatogram of free carbohydrates in the herbal mixture No. 13 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose; 5 – sucrose).
Figure 7 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 7 Chromatogram of carbohydrates formed as a result of enzymatic hydrolysis in the herbal mixture No. 13 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose).
Figure 6 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 6 Chromatogram of free carbohydrates in the herbal mixture No. 7 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose; 5 – sucrose).
Figure 5 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 5 Chromatogram of carbohydrates formed as a result of enzymatic hydrolysis in the herbal mixture No. 7 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose).
Figure 10 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 10 Chromatogram of free carbohydrates in the herbal mixture No. 19 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose; 5 – sucrose).
Figure 3 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 3 Chromatogram of carbohydrates formed as a result of enzymatic hydrolysis in the herbal mixture No. 4 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose).
Figure 1 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 1 Chromatogram of carbohydrates formed as a result of enzymatic hydrolysis in the herbal mixture No. 3 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose).
Figure 2 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 2 Chromatogram of free carbohydrates in the herbal mixture No. 3 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose; 5 – sucrose).
Figure 4 from: Savych AO, Marchyshyn S, Kozyr H, Yarema N (2021) Determination of inulin in the herbal mixtures by GC-MS method. Pharmacia 68(1): 181-187. https://doi.org/10.3897/pharmacia.68.e55051
Figure 4 Chromatogram of free carbohydrates in the herbal mixture No. 4 (1 – arabinose, internal standard; 2 – glucose; 3–4 – fructose; 5 – sucrose).
Data from: Analysing small insect glands with UV-LDI MS: high-resolution spatial analysis reveals the chemical composition and use of the osmeterium secretion in Themira superba (Sepsidae: Diptera)
For many insect species, pheromones are important communication tools, but chemical analysis and experimental study can be technically challenging because they require the detection and handling of complex chemicals in small quantities. One drawback of traditional mass spectrometry methods such as gas chromatography mass spectrometry is that whole-body extractions from one to several hundred individuals are required, with the consequence that intra- and interindividual differences cannot be detected. Here, we used the recently introduced UV-LDI MS (ultraviolet laser desorption/ionization mass spectrometry) to profile the 'osmeterium' of the sepsid fly Themira superba that is located on the edge of the hind tibia of males. Based on analyses of individual legs, we established that the gland produced a secretion that consisted of oxygenated hydrocarbons and putative isoprenoids. The secretion was first detected 24 h after eclosion, and its transfer to the wings of females during mating was demonstrated using UV-LDI MS. We then tested whether the secretion had an anti-aphrodisiac function, but experimental transfer of the secretion to virgin females did not affect mating success or copulation duration. Throughout the study, UV-LDI MS proved invaluable, because it allowed tracking the natural and experimental transfer of small quantities of pheromones to specific body parts of small flies.
Data from: A highly sensitive LC-MS/MS method to determine novel Bruton's tyrosine kinase inhibitor spebrutinib: application to metabolic stability evaluation
Spebrutinib (SBT) is a Bruton's tyrosine kinase inhibitor. SBT is currently in phase II and phase I clinical trials for the management of rheumatoid arthritis and chronic lymphocytic leukaemia, respectively. We developed and validated a liquid chromatography tandem mass spectrometry analytical method to quantify SBT and investigate its metabolic stability. SBT and the naquotinib as internal standard were isocratically eluted on a C18 column. The linearity of the developed method is 5-500 ng/mL (r2≥ 0.9999) in the human liver microsomes (HLMs) matrix. Good sensitivity was approved by the very low limit of detection (0.39 ng/mL). Inter- and intra- assay accuracy values of -1.41 to 12.44 and precision values of 0.71 to 4.78%, were obtained. SBT was found to have an in vitro half-life (82.52 min) and intrinsic clearance (8.4 µL/min/mg) as computed following its incubation with HLMs. The latter finding, hypothesize that SBT could be deliberately expelled from the body unlike other related tyrosine kinase inhibitors. So, drug plasma level and kidney function should be monitored because of potential bioaccumulation. To the best of our knowledge, this is considered the first analytical method for SBT quantification using LC-MS/MS with application to metabolic stability evaluation.
Data from: Metabolism studies of paeoniflorin in rat liver microsomes by ultra-performance liquid chromatography coupled with hybrid quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS)
To explore metabolism mechanism of paeoniflorin in the liver and further understand intact metabolism process of paeoniflorin, a rapid, convenient and effective assay is described using ultra-performance liquid chromatography coupled with hybrid quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS). The strategy was confirmed in the following primary processes: firstly, different concentration of paeoniflorin, rat liver microsomes, coenzymes and different incubated conditions were optimized to build a biotransformation model of rat liver microsomes in vitro by high performance liquid chromatography with diode array detection (HPLC-DAD); secondly, the metabolites of paeoniflorin in rat liver microsomes were detected and screened using UPLC-Q-TOF-MS/MS by comparing the total ion chromatogram (TIC) of the experimental group with those of control groups; finally, the molecular formulae and corresponding chemical structures of paeoniflorin metabolites were identified by comparing the MS and MS/MS spectra with the self-constructed database and simulation software. Based on this analytical strategy, 20 metabolites of paeoniflorin were found and 6 metabolites (including four new compounds) were tentatively identified. It was shown that hydrolysis and oxidation were the major metabolic pathways of paeoniflorin in rat liver microsomes, and the main metabolic sites were the structures of pinane and the ester bond. These findings were significant for a better understanding of the metabolism of paeoniflorin in rat liver microsomes and the proposed metabolic pathways of paeoniflorin might provide fundamental support for the further research in the pharmacological mechanism of Paeoniae Radix Rubra (PRR).
Data from: Comparative authentication of Hypericum perforatum herbal products using DNA metabarcoding, TLC and HPLC-MS
Many herbal products have a long history of use, but there are increasing concerns over product efficacy, safety and quality in the wake of recent cases exposing discrepancies between labeling and constituents. When it comes to St. John's wort (Hypericum perforatum L.) herbal products, there is limited oversight, frequent off-label use and insufficient monitoring of adverse drug reactions. In this study, we use amplicon metabarcoding (AMB) to authenticate 78 H. perforatum herbal products and evaluate its ability to detect substitution compared to standard methods using thin-layer chromatography (TLC) and high performance liquid chromatography coupled with mass spectrometry (HPLC-MS). Hypericum perforatum was detected in 68% of the products using AMB. Furthermore, AMB detected incongruence between constituent species and those listed on the label in all products. Neither TLC nor HPLC-MS could be used to unambiguously identify H. perforatum. They are accurate methods for authenticating presence of the target compounds, but have limited efficiency in detecting infrageneric substitution and do not yield any information on other plant ingredients in the products. Random post-marketing AMB of herbal products by regulatory agencies could raise awareness among consumers of substitution and would provide an incentive to manufacturers to increase quality control from raw ingredients to commercialized products.
Figure 9 from: Kokhia MS, Golovatch SI (2020) Diversity and distribution of the millipedes (Diplopoda) of Georgia, Caucasus. In: Korsós Z, Dányi L (Eds) Proceedings of the 18th International Congress of Myriapodology, Budapest, Hungary. ZooKeys 930: 199-219. https://doi.org/10.3897/zookeys.930.47490
Figure 9 Map of Abkhazia showing the distributions of some endemic or subendemic species. Designations: red triangle (Brachychaetosoma turbanovi), blue square (Caucaseuma kelasuri), orange star (Archileucogeorgia abchasica), pink star (Omobrachyiulus implicitus), orange square (Cylindroiulus olgainna), blue ring (Paranotosoma subrotundatum), yellow star (Julus lindholmi), green star (Leucogeorgia rediviva), green ring (Dentatosoma magnum), pink ring (Heterocaucaseuma deprofundum), orange diamond (Metamastigophorophyllon giljarovi), white ring (Kubaniulus gracilis), blue star (Metamastigophorophyllon hamatum), red ring (Pseudoflagellophorella mirabilis), red diamond (Megaphyllum dioscoriadis), yellow square (Nopoiulus brevipilosus), yellow triangle (Archileucogeorgia satunini), orange ball (Heterocaucaseuma longicorne), red ball (Omobrachyiulus hortensis), blue ball (Brachydesmus furcatus), green ball (Brachydesmus simplex), yellow ball (Polydesmus lignaui), green square (Heterocaucaseuma mauriesi).
Figure 4 from: Kokhia MS, Golovatch SI (2020) Diversity and distribution of the millipedes (Diplopoda) of Georgia, Caucasus. In: Korsós Z, Dányi L (Eds) Proceedings of the 18th International Congress of Myriapodology, Budapest, Hungary. ZooKeys 930: 199-219. https://doi.org/10.3897/zookeys.930.47490
Figure 4 Map of central Georgia with its transect (light blue), Roki Tunnel – Tskhinvali – Tbilisi – Tsalka Reservoir – Ninotsminda – Javakheti National Park, and its macro relief (bottom).
Figure 7 from: Kokhia MS, Golovatch SI (2020) Diversity and distribution of the millipedes (Diplopoda) of Georgia, Caucasus. In: Korsós Z, Dányi L (Eds) Proceedings of the 18th International Congress of Myriapodology, Budapest, Hungary. ZooKeys 930: 199-219. https://doi.org/10.3897/zookeys.930.47490
Figure 7 Map of western Georgia (= Colchis) showing the distributions of some endemic or subendemic species. Designations: orange ball (Hyleoglomeris awchasica), red ball (Nopoiulus golovatchi), green triangle (Cylindroiulus pterophylacum), red ring (Cylindroiulus ruber), white ball (Polydesmus abchasius), blue ball (Trachysphaera fragilis), green star (Trachysphaera radiosa), pink ring (Cylindroiulus schestoperovi), yellow ring (Hirudicryptus abchasicus).
Figure 2 from: Kokhia MS, Golovatch SI (2020) Diversity and distribution of the millipedes (Diplopoda) of Georgia, Caucasus. In: Korsós Z, Dányi L (Eds) Proceedings of the 18th International Congress of Myriapodology, Budapest, Hungary. ZooKeys 930: 199-219. https://doi.org/10.3897/zookeys.930.47490
Figure 2 Map of Georgia with three transects (light blue), one each in the western, central and eastern parts of the country, to crudely show both horizontal and vertical distributions of millipedes endemic or subendemic to the country.
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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.