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6,423 results for “biomarkers”
Two mosquito salivary antigens demonstrate promise as biomarkers of recent exposure to P. falciparum-infected mosquito bites
<p>Measuring malaria transmission intensity using the traditional entomological inoculation rate is difficult. Antibody responses to mosquito salivary proteins such as SG6 have previously been used as biomarkers of exposure to <em>Anopheles</em> mosquito bites. Here, we investigate four mosquito salivary proteins as potential biomarkers of human exposure to mosquitoes infected with <em>P. falciparum</em>: mosGILT, SAMPSP1, AgSAP, and AgTRIO. We tested population-level human immune responses in longitudinal and cross-sectional plasma samples from subjects with known <em>P. falciparum</em> infection from low and moderate transmission areas in Senegal using a multiplexed magnetic bead-based assay. AgSAP and AgTRIO were the best indicators of recent exposure to infected mosquitoes, with antibody responses to AgSAP in a moderate endemic area, and to AgTRIO in both low and moderate endemic areas, significantly higher than healthy non-endemic control cohort (p-values = 0.0245, 0.0064, and <0.0001 respectively). No antibody responses significantly differed between the low and moderate transmission area, or between equivalent groups during and outside the malaria transmission seasons. For AgSAP and AgTRIO, reactivity peaked 2-4 weeks after clinical <em>P. falciparum</em> infection and declined 3 months after infection. Reactivity to both AgSAP and AgTRIO peaked after infection and did not differ seasonally nor between areas of low and moderate transmission, suggesting reactivity is due to exposure to infectious mosquitos or recent biting rather than general mosquito exposure. Kinetics suggest reactivity is relatively short-lived. AgSAP and AgTRIO are promising candidates to incorporate into multiplexed assays for serosurveillance of population-level changes in <em>P. falciparum</em>-infected mosquito exposure.</p>
Soluble endoglin as a biomarker of successful rheopheresis treatment in patients with age-related macular degeneration
<p>Anonymous dataset from all patients included in the study</p>
Olink data for 'Identification of soluble biomarkers that associate with distinct manifestations of long COVID'
<p>Olink analysis output from plasma samples from healthy donors and donors with post-acute sequelae of SARS-CoV-2 infection. Data sourced from two cohorts - UK and Sweden based. UK patients with long covid start with CA. UK healthy controls start with CO. Swedish donors only include patients with long covid and start with KLIMP. Assays from the following panels were tested: Explore 384 Cardiometabolic, Explore 384 Cardiometabolic II, Explore 384 Inflammation, Explore 384 Inflammation II, Explore 384 Neurology, Explore 384 Neurology II, Explore 384 Oncology, Explore 384 Oncology II. </p> <p>Data relates to the manuscript titled 'Identification of soluble biomarkers that associate with distinct manifestations of long COVID'.</p>
Label-free multiplexed detection of diabetic retinopathy biomarkers using fiber optic biosensors: towards lab-in-the-tear
<p>Raw experimental data on label-free detection of diabetic retinopathy biomarkers using fiber optic biosensors. This data contains information on the multiplexed and separate detection of LCN1 and VEGF diabetic retinopathy biomarkers in artificial tears. </p>
Single Cell Phenotypic Profiling to Identify a Set of Immune Cell Protein Biomarkers for Relapsed and Refractory Diffuse Large B Cell Lymphoma: A Single-Center Study
<p>Diffuse large B-cell lymphoma (DLBCL) is the most common invasive type of non-Hodgkin lymphoma. Cell-of-origin (COO) classification is related to patients’ prognoses. Primary drug resistance in treatment for DLBCL has been observed. The specific serum biomarkers in these patients who suffer from relapsed and refractory (R/R)-DLBCL remains unclear. In the current study, using single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF), we determined and verified immune cell biomarkers at the mRNA and protein levels in single-cell resolution from 18 diagnostic peripheral blood mononuclear cell (PBMC) specimens collected from patients with R/R DLBCL. As controls, five PBMC specimens from healthy volunteers were obtained. We identified a panel of 35 surface marker genes for the features of R/R DLBCL unique cell cluster by scRNA-seq of eight R/R DLBCL patient samples and validated its efficiency in an external cohort consisting of 10 R/R DLBCL patients by CyTOF. The cell clustering and dimension reduction were compared among R/R DLBCL samples in CyTOF Space with COO as well as the C-MYC expression designation. Immune cells from each patient occupied unique regions in the 32-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Significant heterogeneity observed in subgroups was mainly attributed to individual differences among samples and not to expression differences in a single, homogeneous immune cell subpopulation. The marker panel showed reliability in labeling R/R DLBCL without any influence from COO stratification and C-MYC expression designation. Furthermore, we compared all the markers between R/R DLBCL and normal samples. A total of 12 biomarkers were significantly overexpressed in R/R DLBCL relative to the normal samples. Therefore, we further optimized the diagnostic biomarker panel of R/R DLBCL comprising CD82, CD55, CD36, CD63, CD59, IKZF1, CD69, CD163, CD14, CD226, CD84, and CD31. In summary, we developed a novel set of biomarkers for the diagnoses of patients with R/R DLBCL. Detections procedures at single-cell resolution provide precise biomarkers which may substantially overcome intertumoral and intratumoral heterogeneity among primary samples. The findings confirmed that each case was unique and may comprise multiple, genetically distinct subclones.</p> <p>Here we uploaded the dataset of CyTOF for external validation. For more detailed information, please contact Dr zheng (zenki_zheng@163.com)</p> <p> </p>
Comparative proteomic and metabolomic analyses of plasma reveal the novel biomarker panels for thyroid dysfunction
<p><strong>Abstract</strong><strong>:</strong></p> <p><em>Objectives: </em>Thyroid dysfunction such as hypothyroidism (THO) and hyperthyroidism (THE) are the disease caused by pathological processes in the thyroid. The current diagnosis of thyroid dysfunction is variable because of ages and genders. The aim of this study was to explore the novel candidate biomarker panels for hypothyroidism and hyperthyroidism screening with mass spectrometry and bioinformatics.</p> <p><em>Methods:</em> Plasma samples were collected from 15 THE patients, 9 THO patients, and 15 healthy controls. DIA-based proteomic and untargeted metabolomic analyses were performed to identify the novel biomarker panels for THO and THE. Finally, three candidate biomarkers were verified by ELISA in 34 samples.</p> <p><em>Results:</em> A total of 2738 proteins and 6103 metabolites were identified, and 173 proteins and 2487 metabolites were found to be differentially expressed among THE, THO and control groups. The results of the ensemble feature selection, K-means clustering and the least absolute shrinkage and selection operator (LASSO) regression model showed that four proteins (C4A, C3/C5 convertase, APOL1, and ITIH4) and four metabolites (L-arginine, L-proline, cortisol, and cortisone) identified by plasma proteomics and metabolomics could help distinguish THO and THE patients from healthy controls.</p> <p><em>Conclusions:</em> This study identified and verified two pairs of biomarker panels that can distinguish the THE and THO patients regardless of ages and genders. Consequently, our findings represent a comprehensive analyses of thyroid dysfunction plasma, which is significant for the clinical diagnosis.</p> <p> </p>
The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model
<p>This data is the raw data for the manuscript with titled The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model.</p>
Basophils as a predictive hematological biomarker of canine visceral leishmaniasis in the treatment with miltefosine
<p><strong>BACKGROUND:</strong> Basophils are initiators of the Th2 response related to the progression of canine visceral leishmaniasis (CanL). Miltefosine has been presented as an alternative in treatment due to its leishmanicide and immunomodulatory effects. Many blood cells have been used as predictive biomarkers, but none of them focused on the immunomodulatory action of miltefosine in the different stages of the disease.</p> <p><strong>OBJECTIVE:</strong> Identifying the predictive hematological biomarkers in dogs with visceral leishmaniasis treated with miltefosine.</p> <p><strong>METHODS:</strong> The animals were divided into three groups: sick dogs; infected dogs, dogs exposed. The animals were submitted to differential blood cell count and CanL diagnosis, through DPP, ELISA and qPCR. The groups were monitored from the time zero (T0) before treatment, and the times twenty (T20) and thirty (T30) days after the beginning of treatment using miltefosine at a dose of 1mL/10kg per day for 28 days.</p> <p><strong>FINDINGS:</strong> Basophils showed an exponential increase in the infected and sick group with an increase of IgG, suggesting a Th2 response. In the exposed group there was reduction of basophils with increase in monocytes and IgG reduction, suggesting a Th1 response.</p> <p><strong>CONCLUSIONS:</strong> We suggest basophils as a predictive biomarker of immunomodulation in the treatment of CanL with miltefosine.</p> <p><strong>BACKGROUND:</strong> Basophils are initiators of the Th2 response related to the progression of canine visceral leishmaniasis (CanL). Miltefosine has been presented as an alternative in treatment due to its leishmanicide and immunomodulatory effects. Many blood cells have been used as predictive biomarkers, but none of them focused on the immunomodulatory action of miltefosine in the different stages of the disease.</p> <p><strong>OBJECTIVE:</strong> Identifying the predictive hematological biomarkers in dogs with visceral leishmaniasis treated with miltefosine.</p> <p><strong>METHODS:</strong> The animals were divided into three groups: sick dogs; infected dogs, dogs exposed. The animals were submitted to differential blood cell count and CanL diagnosis, through DPP, ELISA and qPCR. The groups were monitored from the time zero (T0) before treatment, and the times twenty (T20) and thirty (T30) days after the beginning of treatment using miltefosine at a dose of 1mL/10kg per day for 28 days.</p> <p><strong>FINDINGS:</strong> Basophils showed an exponential increase in the infected and sick group with an increase of IgG, suggesting a Th2 response. In the exposed group there was reduction of basophils with increase in monocytes and IgG reduction, suggesting a Th1 response.</p> <p><strong>CONCLUSIONS:</strong> We suggest basophils as a predictive biomarker of immunomodulation in the treatment of CanL with miltefosine.</p>
An interactive meta-analysis of MRI biomarkers of myelin
Dataset provided for NeuroLibre preprint. Author repo: https://github.com/Notebook-Factory/myelin-meta-analysis NeuroLibre fork:https://github.com/roboneurolibre/myelin-meta-analysis<p>For details, please visit the corresponding <a href="https://github.com/neurolibre/neurolibre-reviews/issues/4">NeuroLibre technical screening.</a></p> <p><strong><a href="https://neurolibre.org">https://neurolibre.org</a></strong></p>
Evaluation of selected semen parameters and biomarkers of male infertility – preliminary study
<p>Visualization of sperm chromatin dispersion test (SCD). Micrographs obtained by light microscopy.</p>
Soil ecotoxicology needs robust biomarkers – a meta-analysis approach to test the robustness of gene expression-based biomarkers for measuring chemical exposure effects in soil invertebrates
<p>Gene expression-based biomarkers are regularly proposed as rapid, sensitive and mechanistically informative tools to identify whether soil invertebrates are experiencing adverse effects due to chemical exposure. However, before biomarkers could be deployed within diagnostic studies, systematic evidence of the robustness of such biomarkers to detect effects is needed. Here, we present an approach for conducting a systematic meta-analysis of the robustness of gene expression-based biomarkers in soil invertebrates.</p> <p>The approach was developed and trialled for two measurements of gene expression commonly proposed as biomarkers in soil ecotoxicology: metallothionein (MT) gene expression in earthworms for metals and heat shock protein 70 (HSP70) gene expression in earthworms for organic chemicals. From a systematic analysis of the published literature, we collected 294 unique gene expression data points and used linear mixed-effect models to assess concentration, exposure duration and species effects on the quantified response.</p> <p>This database provided contains gene-expression data from publications that have used gene expression-based biomakers to study effects of chemical pollutants on soil invertebrates. R scripts are provided that were used to study the patterns of gene expression as reported in accompanying publication. </p> <p>We encourage colleagues in the field to apply this approach to other biomarkers, as such quantitative assessment is a prerequisite to ensuring that the suitability and limitations of proposed biomarkers are known and stated.</p>
Tracking Global Invasion Pathways of the Spongy Moth (Lepidoptera: Erebidae) to the U.S. using Stable Isotopes as Endogenous Biomarkers
<p>The spread of invasive insect species causes enormous ecological damage and economic losses worldwide. A reliable method that tracks back an invaded insect's origin would be of great use to entomologists, phytopathologists and pest managers. The spongy moth (Lymantria dispar (L.d.), Linnaeus 1758) is a persistent invasive pest in the north-eastern United States (U.S.) and periodically causes major defoliations in temperate forests. We analysed field-captured (Europe, Asia, U.S.) and lab-reared L.d. specimens for their natal isotopic hydrogen and nitrogen signatures imprinted in their biological tissues (δ2H and δ15N) and compared these values to the long-term mean δ2H of regional precipitation (Global Network of Isotopes in Precipitation) and δ15N of regional plants at the capture site. We established the percentage of hydrogen-deuterium exchange for L.d. tissue (Pex=8.2%) using the comparative equilibration method and two-source-mixing-models, which allowed the extraction of the moth's natal δ2H value. We confirmed that the natal δ2H and δ15N values of our specimens are related to the environmental signatures at their geographic origins. With our regression models, we were able to isolate potentially invasive individuals and give estimations of their geographic origin. To enable the application of these methods on eggs, we established an egg-to-adult fraction factor for L.d. (Δegg-adult = 16.3‰ ± 4.3‰). Our models suggested that around 25% of the field-captured spongy moths worldwide were not native in the investigated capture sites. East Asia was the most frequently identified location of probable origin. Furthermore, our data suggested that eggs found on cargo ships in U.S. harbors in Alaska, California and Louisiana most probably originated from Asian L.d. in East Russia. These findings show that stable isotope biomarkers give a unique insight into invasive insect species pathways and thus, can be an effective tool to monitor the spread of insect pest epidemics.</p>
Association of Serum Biomarkers with Early Neurological Improvement after Intravenous Thrombolysis in Ischemic Stroke
<p><strong>Background:</strong> Early neurological improvement (ENI) after intravenous thrombolysis is associated with favorable outcome, but associated serum biomarkers were not fully determined. We aimed to investigate the issue in a prospective cohort.</p> <p><strong>Methods:</strong> In INTRECIS study, five centers were designed to consecutively collect the blood sample from enrolled patients. Enrolled patients with ENI and without ENI were matched by propensity score matching with the ratio of 1:1. Preset 49 biomarkers were measured through protein microarray analysis. Enrichment of Gene Ontology and pathway, and protein-protein interaction network were analyzed in the identified biomarkers.</p> <p><strong>Results:</strong> Of 358 patients, 19 occurred ENI, who were assigned as ENI group, while 19 matched patients without ENI were assigned as Non ENI group. A total of nine biomarkers were found different, among which levels of chemokine (C-C motif) ligand (CCL)-23, chemokine (C-X-C motif) ligand (CXCL)-12, insulin-like growth factor binding protein (IGFBP)-6, interleukin (IL)-5, lymphatic vessel endothelial hyaluronan receptor (LYVE)-1, plasminogen activator inhibitor (PAI)-1, platelet-derived growth factor (PDGF)-AA, suppression of tumorigenicity (ST)-2, and tumor necrosis factor (TNF)-α were higher in ENI group, compared with those in Non ENI group.</p> <p><strong>Conclusions:</strong> Our finding found that serum levels of CCL-23, CXCL-12, IGFBP-6, IL-5, LYVE-1, PAI-1, PDGF-AA, ST-2, and TNF-α at admission were associated with post-thrombolytic ENI in ischemic stroke. The role of these biomarkers warrant further investigation.</p>
oLIVER progress presentation 2022: Identifying biomarkers for diagnosis and treatment evaluation of NAFLD
<p>This is a recorded talk with head of the oLIVER project - Jørgen Kjems, where he presents the latest project progress.</p> <p>The talk was given at one of ODIN's (the Open Discovery Innovation Network) Knowledge Sharing Events in May 2022.</p>
BIOMETSCO progress presentation 2022: Identification of Novel Biomarkers and Drug Targets for the Detection and Elimination of Occult Metastases in Colon Cancer
<p>This is a recorded talk with head of the BIOMETSCO project - Lasse Sommer Kristensen - where he presents the latest project progress.</p> <p>The talk was given at one of ODIN's (the Open Discovery Innovation Network) Knowledge Sharing Events in May 2022.</p> <p> </p> <p> </p>
Decoding diabetes biomarkers and related molecular mechanisms using machine learning, text mining, and gene expression analysis
<p>The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA- DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top ten DEGs. These genes were enriched in aerobic respiration, T-Cell antigen receptor pathway, Tricarboxylic acid metabolic process, vitamin D receptor pathway, Toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for ML analysis . The "Decision tree", "Extra-tree regressor" and "Random forest" algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. ML algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes.</p>
Gene biomarkers for the assessment of thyroid-disrupting activity in zebrafish embryos
<p>We have conducted an exposure study on zebrafish embryos using thyroidal active compounds. Based on OECD guideline 236, freshly fertilized zebrafish embryos were exposed to two sublethal concentrations of triiodothyronine (T3), 6-Propyl-2-thiouracil (6-PTU), methimazole (MMI) and iopanoic acid (IOP) until 96 hours post fertilization. RNA was extracted and sequenced to identify thyroid-related gene expression patterns. .</p> <p>The uploaded data archive consists of three major data types:<br>1. MultiQC reports from raw RNA-Seq read processing and QC<br>2. Result tables from differential gene expression analysis (DGEA) with DESeq2 (apeglm shrunk results indicated by "reslfs")<br>3. Result tables from Overrespresentation Analysis (ORA) with clusterProfiler</p> <p>Gene count normalization and DGEA was conducted with DESeq2 (<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8">Love et al., 2014</a>, DOI 10.1186/s13059-014-0550-8). Three biological replicates per condition, exposure treatments were compared with respect to the control group in a pairwise fashion, applying Wald’s t-test. P values were corrected for multiple testing with independent hypothesis weighting (IHW) (<a href="https://www.nature.com/articles/nmeth.3885">Ignatiadis et al., 2016</a>, DOI 10.1038/nmeth.3885 ) after Benjamini-Hochberg (BH). To improve the signal to statistical noise ratio, the obtained log<sub>2</sub>-fold change (lfc) values were shrunk with the apeglm method described by Zhu and colleagues (<a href="https://academic.oup.com/bioinformatics/article/35/12/2084/5159452?login=true">2019</a>, DOI 10.1093/bioinformatics/bty895 ) before DGEA result tables were subjected to ORA via clusterProfiler (<a href="https://www.liebertpub.com/doi/10.1089/omi.2011.0118">Yu et al., 2012</a>, DOI 10.1089/omi.2011.0118).</p> <p>The ArrayExpress accession numbers E-MTAB-14185 (IOP), E-MTAB-14184 (MMI), E-MTAB-14183 (T3) and E-MTAB-9054 (6-PTU), provide access to the raw and DESeq2 normalized gene count matrices upon which these analysis were performed. Genes were annotated through the biomaRt package (<a href="https://www.nature.com/articles/nprot.2009.97.pdf?origin=ppub">Durinck et al., 2009</a>, DOI 10.1038/nprot.2009.97 ) in R (<a href="https://www.r-project.org/">R Core Team 2021</a>).</p>
Microbiome-based biomarkers to guide personalized microbiome-based therapies for Parkinson's disease
<p><strong>Abstract: </strong>We address an unmet challenge in Parkinson’s disease: the lack of biomarkers to identify the right patients for the right therapy, which is a main reason clinical trials for disease modifying treatments have all failed. The gut microbiome is a new target for treatment of neurodegenerative diseases. Our aim was to develop microbiome-based biomarkers to guide patient selection for microbiome-based clinical trials. We used microbial taxa that are robustly associated with PD across studies and at high significance as dysbiotic features of PD. Using individual-level taxonomic relative abundance data, we classified patients according to their dysbiotic features, effectively defining microbiome-based subtypes of PD. We show that not all persons with PD have a dysbiotic microbiome, and not all dysbiotic PD microbiomes have the same features. Grounded in robust and reproducible data from differential abundance studies, we propose an intuitive and easily modifiable method to identify the optimal candidates for microbiome-based clinical trials, and subsequently, for treatments that are personalized for each individual’s dysbiotic features. We demonstrate the method for PD. The concept, and the method, is generalizable for any disease with a microbiome component.</p> <p><strong>Zenodo</strong> <strong>content: </strong>In this Zenodo archive we provide (a) the method described step by step, which can be implemented in Microsoft Excel (we used v.16.84 (RRID:SCR_016137) <a href="https://www.microsoft.com/en-gb/">https://www.microsoft.com/en-gb/</a>) or in R (we used v4.3.3 (RRID:SCR_001905) <a title="https://www.r-project.org/ Cmd+Click or tap to follow the link" href="https://www.r-project.org/">https://www.r-project.org/</a>); and (b) data used to generate the results, tables and figures (except figure 2). Data for creating figure 2 can be found in source data (doi: 10.5281/zenodo.7246185) and the method is described by Wallen et al 2022 (DOI: <u><a href="https://doi.org/10.1038/s41467-022-34667-x" target="_blank" rel="noopener">10.1038/s41467-022-34667-x</a></u>). All data used here were extracted from the original source data reported by<strong> </strong>Wallen et. al. 2022 (DOI: <u><a href="https://doi.org/10.1038/s41467-022-34667-x" target="_blank" rel="noopener">10.1038/s41467-022-34667-x</a></u>) which can be found on Zenodo (DOI: 10.5281/zenodo.7246185).</p>
ddhN biomarkers NMR reference datasets
<p>To visualize the data please click on the following link: <a title="https://zenodo.nmrium.org/zenodo/v1/record/12806559" href="https://zenodo.nmrium.org/zenodo/v1/record/12806559" target="_blank" rel="noopener">https://zenodo.nmrium.org/zenodo/v1/record/12806559</a></p> <p>Reference 1D and 2D spectra from publication: <a href="https://doi.org/10.1021/acs.jproteome.3c00654" target="_blank" rel="noopener">10.1021/acs.jproteome.3c00654</a></p> <p>For further data, please also see zenodo entry: <a href="../doi/10.5281/zenodo.7906157">10.5281/zenodo.7906157</a></p>
Assessment of the association of new biomarkers (GDF15, ST2, galectin-3, TIMP-1, MMP-9, NfL) and plasma prothrombotic potential in the course of cardiac transthyretin amyloidosis.
<p><span>The development of cardiac amyloidosis (ATTR) is caused by the deposition of misfolded, insoluble proteins in the extracellular matrix of tissues. An important element of the clinical presentation of the disease is the increased risk of thromboembolic complications. Currently, there is limited published data on the potential role of new heart failure biomarkers in the assessment of ATTR cardiomyopathy, particularly in the assessment of asymptomatic carriers of pathogenic transthyretin (TTR) variants.</span></p> <p><span>Purpose of the study: To assess the diagnostic value of biomarkers related to heart failure (growth differentiation factor-15 (GDF15), soluble suppression of tumorigenicity-2 (ST2), galectin-3), amyloidosis ( retinol binding protein 4 (RBP4, transthyretin) , tissue inhibitor of metalloproteinase-1 (TIMP-1), matrix metalloproteinase-9 (MMP-9, matrix metalloproteinase-9), neurofilament light chain (NfL)) and the generation potential thrombin as a marker of the prothrombotic state in the course of ATTR.</span></p> <p><span>Methods: This prospective, single-center study included consecutive patients diagnosed with ATTR, asymptomatic carriers of pathogenic TTR variants, and a matched control group of healthy volunteers. The values of these biomarkers were evaluated using the ELISA method from peripheral blood (enzyme-linked immunosorbent assay) GDF15, ST2, RBP4 (TTR), TIMP-1, MMP-9, galectin-3, NfL. Additionally, the prothrombotic potential of plasma was tested using the calibrated automatic thrombogram (CAT) method. Results are presented in Table 1. </span><span>The demographic and clinical characteristics of the study population are presented in Table 2 and Table 3.</span></p> <p><span>Conclusions: The project provides information on the value of novel biomarkers in the assessment of ATTR cardiomyopathy, especially in the assessment of asymptomatic carriers of pathogenic TTR variants. Moreover, it evaluated prothrombotic state in the course of ATTR.</span></p>
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.