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1,658 results for “sepsis”
Neutrophil and emergency granulopoietic drivers of sepsis immune suppression and an extreme response to infection
<p>The dysregulated host response to infection leading to organ dysfunction is highly heterogeneous. It is currently poorly delineated by sepsis as a clinical syndromic classification, thus confounding immunotherapy trials. Here we establish the pathophysiology and potential therapeutic targets of a specific extreme response to infection state (sepsis response signature SRS1), characterised by immune compromise and poor outcome. We first derive a whole blood single-cell multi-omic atlas of the sepsis response (2727,993 cells, n=39), finding an increase in IL1R2+ immature neutrophils in SRS1, which we confirmed by CyTOF and RNA-sequencing (n=53). We next uncovered high activity of neutrophil STAT3 gene expression programs in SRS1, which were shared across multiple infectioius disease settings (n=1044) irrespective of the clinical definition of the patient cohorts. We observed elevated plasma G-CSF and IL-6 in SRS1, suggesting heightened emergency granulopoiesis (EG). We therefore characterised patient and healthy control hematopoietic stem cells (HSCs) using single-cell RNA/chromatin accessibility multi-omics (29,366 cells, n=27), identifying SRS1-specific EG transcriptional skewing, together with STAT3 and EG master regulator CEBPB epigenetic signatures. Our findings establish a common cellular axis present across extreme responses to infection, reveal its hematopoietic origin, and nominate G-CSF and IL-6 as potential therapeutic targets for the SRS1 state.</p> <p> </p> <p>The present data deposit includes processed and quality-controlled data tables for:</p> <p>1. Whole blood leukocytes profiled with the BD Rhapsody platform in a cohort of 39 sepsis patients (RNA and protein count matrices, as well as their accompanying metadata table)</p> <p>2. Circulating HSCs in blood profiled with the 10X multiomics platform in a cohort of 27 sepsis patients (RNA and ATAC-seq count matrices, as well as their accompanying metadata tables)</p>
Incidences of community onset severe sepsis, Sepsis-3 sepsis, and bacteremia in Sweden – a prospective population-based study.
<p>Sepsis epidemiology study 2011-2012 Sweden</p> <p>Ljungström, Lars; Andersson, Rune; Jacobsson, Gunnar</p> <p> </p> <p>Data collected during the prospective "Sepsis Skaraborg study" performed 2011-2012 in the western region of Sweden. Adult patients admitted to the emergency department for suspicion of a community-onset sepsis were evaluated. The study was approved by the Regional Ethical Review Board of Gothenburg (376-11). The file includes data for patient characteristics, vital signs, biomarker measurements, cases of bacteremia, and patient classifications using Sepsis-2 and Sepsis-3 criteria.</p>
Genome Sizes of Bacterial Species Detected in Cell-Free DNA of Patients with Acute Leukemia and Sepsis, Including Those Undergoing Bone Marrow Transplantation
<p>Next Generation Sequencing (NGS) analysis of Cell-Free DNA provides valuable insights into a spectrum of pathogenic species (particularly bacterial) in blood. Patients with Sepsis often face problems like delays in treatment regimens (combination or cocktail of antibiotics) due to the long turnaround time (TAT) of classical and standard blood culture procedures. NGS gives results with lower TAT along with high-depth coverage. The use of NGS may be a possible solution to deciding treatment regimens for patients without losing precious time and more accurately possibly saving lives.</p> <p>Our curated dataset is of bacterial species or strains detected along with their genome size in 107 AML patients diagnosed with Sepsis clinically. Cell-free DNA profiles of patients were built and sequencing was done in Illumina (NovaSeq and NextSeq). Bioinformatic analysis was performed using two classification algorithms namely kraken2 and kaiju. For kraken2 based classification reference bacterial index developed by Carlo Ferravante et al (Zenodo 2020) (link: https://zenodo.org/records/4055180) was used, while for kaiju-based classification reference database named "nr_euk" dated "2023-05-10" (link: https://bioinformatics-centre.github.io/kaiju/downloads.html) was used.</p> <p>Genome size annotation is important in metagenomics since for the use of depth of coverage (abundance), genome size is required. In metagenomic classification algorithms like kraken/kraken2 and kaiju output computes reads assigned only and not abundance. In kaiju, the problem is more complicated since the reference database does not have a fasta file but only an index file from which alignment is done. </p> <p>To address the above challenges to compute "depth of coverage" or simply abundance, we build a Genome size annotator tool (https://github.com/patkarlab/Genome-Size-Annotation) which provides genome size for each species detected given its taxid is available. In this tool, the NCBI Datasets tool, NCBI Genome API check tool, and Data Mining from AI search engines like perplexity.ai are used. </p> <p>We have curated two datasets</p> <p>Kraken2 dataset named "FINAL METAGENOMIC DATA MASTERSHEET - kraken_genome_annotation"<br>Kaiju dataset named "FINAL METAGENOMIC DATA MASTERSHEET - kaiju_genome_annotation"</p> <p>*Please note that for kraken2 curated dataset, we used data mining from the AI search engine perplexity.ai while for kaiju we did not use perplexity, ai, and any species whose genome size was not found was labeled "NA"</p>
Detection of sepsis biomarkers
<p>Comparison of the working principles, advantages, and disadvantages of different types of sepsis sensors. Summary of the state-of-the-art electrochemical sensors used for the detection of sepsis biomarkers; limit of detection. </p>
Effects of Code Sepsis Implementation on Emergency Department (ED) Sepsis Care
ClinicalTrials.gov study NCT04148989. IPD Sharing: YES. Countries: 1. Publications: 1.
Effect of Emergency Department Care Reorganization on Door-to-antibiotic Times for Sepsis (LDS SWARM)
ClinicalTrials.gov study NCT03226366. IPD Sharing: YES. Countries: 1. Publications: 1.
Simplified Event Logs for Sepsis Patient Trajectories
<p>This dataset contains a simplified excerpt from a real event log that tracks the trajectories of patients admitted to a hospital to be treated for sepsis, a life-threatening condition. The log has been recorded by the Enterprise Resource Planning of the hospital. Additionally, the dataset contains three synthetic logs that increase the number of trajectories within the original log timespan, while maintaining other statistical characteristics.</p> <p>In total, the dataset contains four files in .zip format and a companion that describes the statistical method used to synthesize the logs as well as the dataset content in detail. The dataset can be used in testing the performance of event-based process-mining and log (runtime) monitoring tools against an increasing load of events.</p>
Myeloperoxidase can differentiate between sepsis and non-infectious SIRS and predicts mortality in intensive care patients with SIRS.
<p>Dataset of "Myeloperoxidase can differentiate between sepsis and non-infectious SIRS and predicts mortality in intensive care patients with SIRS."</p>
Sepsis biomarker study 2011-2012 Sweden
<p>Data collected during the prospective "Sepsis Skaraborg study" performed 2011-2012 in the western region of Sweden. Adult patients admitted to the emergency department for suspicion of a community-onset sepsis were asked to participate. Only those patients who gave their written informed consent were enrolled. The study was approved by the Regional Ethical Review Board of Gothenburg (376-11). The file includes data for patient characteristics, biomarker measurements, and patient classifications using Sepsis-2 and Sepsis-3 criteria.</p>
Dataset for "Takahama, M., Patil, A., Richey, G. et al. A pairwise cytokine code explains the organism-wide response to sepsis. Nat Immunol 25, 226–239 (2024)."
Open the record for dataset details and reuse information.
Supplement Tables of Recombinant Klotho protein protects pulmonary alveolar epithelial cells against sepsis-induced apoptosis by inhibiting the Bcl-2/Bax/caspase-3 pathway
<p>This is Supplement Tables of Recombinant Klotho protein protects pulmonary alveolar epithelial cells against sepsis-induced apoptosis by inhibiting the Bcl-2/Bax/caspase-3 pathway.</p>
Mass Cytometry (CyTOF) FCS files from Priest et al. 2024. Human PBMC from longitudinal analysis of COVID-19, Bacterial Sepsis, mRNA vaccination cohorts.
<p>Mass Cytometry (CyTOF) FCS files from Priest et al. "Non-classical CD45RB<sup>lo</sup> memory B-cells are the majority of circulating antigen-specific B-cells following mRNA vaccination and COVID-19 infection." Research Square 2024. </p> <p>Files are already normalised, debarcoded, gated, batch corrected and compensated as described in Priest et al. </p> <p>Data is from Human PBMCs of londitudanal cohorts of Severe COVID-19, Sepsis and mRNA vaccine recipients. </p> <p>Samples were barcoded, mixed and then split magnetically before staining with seperate antibody panels for CD3+ (CD4, Treg, Tfh, CD8, gdT) or CD3- (B cells, DC, NK, Monocytes) to give approximatly 1280 FCS files from 218 individuals. </p> <p>A follow up experiment with a B-cell specific panel and Tetramers is included. </p> <p>Patient level metadata and antibody panel details are included. </p> <p> </p>
Presence of the APOE4 allele is associated with an increased risk of sepsis progression
<p><strong>Supplementary Table 1. The Hardy-Weinberg equilibrium assay for APOE genotypes in healthy controls, sepsis, septic shock and all sepsis patients</strong>.</p>
Concentration of selected proteins in plasma of patient with soft tissue infections or sepsis
<p>The dataset includes two tabular sets of concentration measurements of selected proteins in plasma samples from patients with soft tissue infections or sepsis. Patients with soft tissue infections are classified into three groups: Patients with necrotizing soft tissue infections (NSTI), suspected NSTI cases but where no necrotic tissue was found during surgical exploration (Non-NSTI) and cellulitis. The sepsis patient cohort has heterogeneous etiologies and location of infection. Additionally, we included a group of patients that had surgery related to non-infectious conditions as a healthy cohort of patients (Surgical control).</p> <p>The measurements were performed by Luminex® multiplex immunoassay or ELISA. Each of the two sets were obtained from independent rounds of measurements and differ in the panel of analytes measured and samples included. The first set of measurements (Set01) covers 39 analytes measured in two sets of customized multiplex plates (32-plex and 5-plex), and two in independent ELISA assays. These analytes were measured in 251 NSTI samples, 20 Non-NSTI, 19 cellulitis and 20 surgical controls. The second set of measurements (Set02) consist of a subset of 10 analytes included in the first set and were measured in two multiplex plates (4-plex and 6-plex). The second round of measurements were carried out in 60 additional NSTI patients and 24 sepsis patients.</p> <p>Lastly, imputation of censored data was carried out only in the first set of measurements and the resulting data is also available in the current data set (Set01_imputed).</p>
Validation of Sepsis-3 using survival analysis and clinical evaluation of quick SOFA, SIRS, and burn-specific SIRS for sepsis in burn patients with suspected infection
<p><span><strong>Purpose</strong>: Sepsis-3 is a life-threatening organ dysfunction caused by dysregulated host responses to infection; and defined using the Sepsis-3 criteria, introduced in 2016, however, the criteria need to be validated in specific clinical fields. We investigated mortality prediction and compared the diagnostic performance of quick Sequential Organ Failure Assessment (qSOFA), systemic inflammatory response syndrome (SIRS), and burn-specific SIRS (bSIRS) in burn patients.</span></p> <p><span><strong>Methods</strong>: This single-center retrospective cohort study examined burn patients in Seoul, Korea during January 2010–December 2020. Overall, 1,391 patients with suspected infection were divided into four sepsis groups using SOFA, qSOFA, SIRS, and burn-specific SIRS. </span></p> <p><span><strong>Results</strong>: Hazard ratios (HRs) of all unadjusted models were statistically significant; however, the HR (0.726, p = 0.0080.001) in the SIRS ≥2 group is below 1. In the adjusted model, HRs of the SOFA ≥2 (2.426, p < 0.001), qSOFA ≥2 (7.198, p < 0.001), and SIRS ≥2 (0.575, p < 0.001) groups were significant. The diagnostic performance of dichotomized qSOFA, SIRS, and bSIRS for sepsis was defined by the Sepsis-3 criteria. The mean onset day was 4.13±2.97 according to Sepsis-3. The sensitivity of SIRS (0.989, 95% confidence interval [CI]: 0.982–0.994) was higher than that of qSOFA (0.841, 95% CI: 0.819–0.861) and bSIRS (0.803, 95% CI: 0.779–0.825). Specificities of qSOFA (0.929, 95% CI: 0.876–0.964) and bSIRS (0.922, 95% CI: 0.868–0.959) were higher than those of SIRS (0.461, 95% CI: 0.381–0.543).</span></p> <p><span><strong>Conclusion</strong>: Sepsis-3 is a good alternative diagnostic tool because it reflects sepsis severity without delaying diagnosis. SIRS showed higher sensitivity than qSOFA and bSIRS and may therefore more adequately diagnose sepsis.</span></p>
ANION GAP OR SERUM LACTATE-IN SEARCH OF A BETTER PROGNOSTIC MARKER IN SEPSIS A CROSS-SECTIONAL STUDY IN A RURAL TERTIARY CARE HOSPITAL
<p>master data sheet</p>
Data for: Weak sex-specific evolution of locomotor activity of Sepsis punctum (Diptera: Sepsidae) thermal experimental evolution lines
<p><span>Elevated temperatures are expected to rise beyond what the physiology of many organisms can tolerate. Behavioural responses facilitating microhabitat shifts may mitigate some of this increased thermal selection on physiology, but behaviours are themselves mediated by physiology, and any behavioural response may trade-off against other fitness-related activities. </span><span>We investigated whether experimental evolution in different thermal regimes (Cold: 15°C; Hot: 31°C; Intergenerational fluctuation 15/31°C; Control: 23°C) resulted in genetic differentiation of standard locomotor activity in the dung fly <em>Sepsis</em> <em>punctum</em>. We assessed individual locomotor performance, an integral part of most behavioral repertoires, across eight warm temperatures from 24°C to 45°C using an automated device. We found no evidence for generalist-specialist trade-offs (i.e. changes in the breadth of the performance curve) for this trait. Instead, at the warmest assay temperatures, hot-selected flies showed somewhat higher maximal performance than all others, especially cold-selected flies, overall more so in males than females. Yet, the flies' temperature optimum was not higher than that of the cold-selected flies, as expected under the 'hotter-is-better' hypothesis. Maximal locomotor performance merely weakly increased with body size. These results suggest that thermal performance curves are unlikely to evolve as an entity according to theory and that locomotor activity is a trait of limited use in revealing thermal adaptation.</span></p>
Utility of Ultrasound Assessment of the Inferior Vena Cava in Patients With Sepsis and Dehydration
ClinicalTrials.gov study NCT02568189. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Vitamin C Infusion for Treatment in Sepsis Induced Acute Lung Injury
ClinicalTrials.gov study NCT02106975. IPD Sharing: NO. Countries: 1. Publications: 1.
Vitamin C, Thiamine, and Steroids in Sepsis
ClinicalTrials.gov study NCT03509350. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.
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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.
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DANDI Archive for NWB datasets
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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.