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1,218 results for “Vesicles”
Vesicles clustering around Wdr35-/- cilia lack electron dense decorations although electron-dense clathrin coated vesicles are still observed budding from the mutant plasma membrane (Figure 7- source data 1)
<p>Intraflagellar transport (IFT) is a highly conserved mechanism for motor-driven transport of cargo within cilia, but how this cargo is selectively transported to cilia is unclear. WDR35/IFT121 is a component of the IFT-A complex best known for its role in ciliary retrograde transport. In the absence of WDR35, small mutant cilia form but fail to enrich in diverse classes of ciliary membrane proteins. In <i>Wdr35 </i>mouse mutants, the non-core IFT-A components are degraded and core components accumulate at the ciliary base. We reveal deep sequence homology of WDR35 and other IFT-A subunits to α and ß' COPI coatomer subunits, and demonstrate an accumulation of 'coat-less' vesicles which fail to fuse with <i>Wdr35 </i>mutant cilia. We determine that recombinant non-core IFT-As can bind directly to<u> </u>lipids and provide the first <i>in-situ</i> evidence of a novel coat function for WDR35, likely with other IFT-A proteins, in delivering ciliary membrane cargo necessary for cilia elongation.</p>
Raw Data for the article: Extracellular Vesicle-Derived microRNAs of Human Wharton's Jelly Mesenchymal Stromal Cells May Activate Endogenous VEGF-A to Promote Angiogenesis
<p>Despite low levels of vascular endothelial growth factor (VEGF)-A, the secretome of human Wharton's jelly (WJ) mesenchymal stromal cells (MSCs) effectively promoted proangiogenic responses in vitro, which were impaired upon the depletion of small (~140 nm) extracellular vesicles (EVs). The isolated EVs shared the low VEGF-A profile of the secretome and expressed five microRNAs, which were upregulated compared to fetal dermal MSC-derived EVs. These upregulated microRNAs exclusively targeted the <em>VEGF-A</em> gene within 54 Gene Ontology (GO) biological processes, 18 of which are associated with angiogenesis. Moreover, 15 microRNAs of WJ-MSC-derived EVs were highly expressed (Ct value ≤ 26) and exclusively targeted the thrombospondin 1 (<em>THBS1</em>) gene within 75 GO biological processes, 30 of which are associated with the regulation of tissue repair. The relationship between predicted microRNA target genes and WJ-MSC-derived EVs was shown by treating human umbilical-vein endothelial cells (HUVECs) with appropriate doses of EVs. The exposure of HUVECs to EVs for 72 h significantly enhanced the release of VEGF-A and THBS1 protein expression compared to untreated control cells. Finally, WJ-MSC-derived EVs stimulated in vitro tube formation along with the migration and proliferation of HUVECs. Our findings can contribute to a better understanding of the molecular mechanisms underlying the proangiogenic responses induced by human umbilical cord-derived MSCs, suggesting a key regulatory role for microRNAs delivered by EVs.</p>
Pseudo-atomic model of a complete gas vesicle
<p>This pseudo-atomic model is shown in our preprint:</p> <p>Huber, S. T., Terwiel, D., Evers, W. H., Maresca, D. & Jakobi, A. J. Cryo-EM structure of gas vesicles for buoyancy-controlled motility.<em> BioRxiv (2022)</em></p> <p>(Update 26.04.2023), Now in:</p> <p>Huber, S. T., Terwiel, D., Evers, W. H., Maresca, D. & Jakobi, A. J. Cryo-EM structure of gas vesicles for buoyancy-controlled motility. <em>Cell </em>186, 975–986 (2023)</p> <p> </p> <p>We use the atomic model from our determined 3.2 Å cryo-EM structure of the <em>B.megaterium</em> gas vesicle (GV) wall and copy+place it on a helical path that narrows at the tips of the GVs. Placement at the seam in the GV center is informed by high-resolution 2D class averages. The helical arrangement is informed by the determined helical symmetry of this particular helical polymorph (92.93 units per helical turn) and the tip by measurement of the cone semi-angle.</p> <p>The pseudo-atomic model consists only of copies of the wall protein GvpA2. This is likely a simplification, and the homologous proteins GvpJ and GvpS might be involved in small parts of the assembly, such as the ends of the cones. The arrangement at the contact point of the two GV halves is informed only by high-resolution 2D data, therefore the 3D arrangement of these features is hypothetical.</p> <p>For display in ChimeraX I recommend this style:</p> <blockquote> <p>car style protein modeh default arrows f xsect oval width 3 thick 3 divisions 2 barSides 4</p> </blockquote> <p>The rainbow color scheme highlighting the main chain can be displayed:</p> <blockquote> <p>select :2-13; color sel #2c2a70; select :14-23; color sel #45639a; select :24-34; color sel #98b45a; select :35-39; color sel #abb24e; select :40-50; color sel #dddb20; select :51-61; color sel #e15a3d; select :62-66; color sel #ec1e24; ~sel;</p> </blockquote> <p>The color scheme for physico-chemical properties:</p> <blockquote> <p>select :Met,Ile,Leu,Ala,Val; color sel #e1b13e; select :Ser,Thr,Gln,Asn; color sel #49c2c6; select :Glu,Asp; color sel #cb2026; select :Lys,Arg,His; color sel #3e58a8; select :Phe,Trp,Tyr; color sel #715321; select :Gly,Pro; color sel #7b7b7b; ~sel;</p> </blockquote> <p>Python dictionary with color scheme:</p> <blockquote> <p>colorscheme = {'#e1b13e':'MILAV', '#49c2c6':'STNQ', '#cb2026':'DE', '#3e58a8':'KRH', '#715321':'FYW', '#7b7b7b':'GPC'}</p> </blockquote> <p>To highlight both halves in different colors in the full model:</p> <blockquote> <p>color #1.1-865 gray; color #1.866-1730 steel blue</p> </blockquote> <p>ChimeraX command to impose helical symmetry on a single GvpA monomer:</p> <blockquote> <p>sym #1 h,0.5257,-3.87399,500,-250 coordinateSystem #1 copies True</p> </blockquote> <p> </p>
All-atom molecular dynamics simulations of synaptic vesicle fusion I: a glimpse at the primed Synaptotagmin-SNARE-complexin complex
<p>Synaptic vesicles are primed into a state that is ready for fast neurotransmitter release upon Ca<sup>2+</sup>-binding to Syt1. This state likely includes trans-SNARE complexes between the vesicle and plasma membranes that are bound to Syt1 and complexins. However, the nature of this state and the steps leading to membrane fusion are unclear, in part because of the difficulty of studying this dynamic process experimentally. To shed light into these questions, we performed all-atom molecular dynamics simulations of systems containing trans-SNARE complexes between two flat bilayers or a vesicle and a flat bilayer with or without fragments of Syt1 and/or complexin-1. Our results need to be interpreted with caution because of the limited simulation times and the absence of key components, but suggest mechanistic features that may control release and help visualize potential states of the primed Syt1-SNARE-complexin-1 complex. In particular, the simulations suggest that SNAREs alone induce formation of extended membrane-membrane contact interfaces that may fuse slowly, and that the primed state contains macromolecular assemblies of trans-SNARE complexes bound to the Syt1 C<sub>2</sub>B domain and complexin-1 in a spring-loaded configuration that prevents premature membrane merger and formation of extended interfaces but keeps the system ready for fast fusion upon Ca<sup>2+</sup> influx.</p>
Raw datasets and media accompanying the manuscript: Extracellular Vesicles (EVs) Are Copurified with Feline Calicivirus, yet EV-Enriched Fractions Remain Infectious
<p>Raw datasets and media accompanying the manuscript: <strong>Extracellular Vesicles (EVs) Are Copurified with Feline Calicivirus, yet EV-Enriched Fractions Remain Infectious</strong></p>
Brain-Derived Neurotrophic Factor and extracellular vesicle-derived miRNAs in an Italian cohort of individuals with obesity: a key to explain the link between depression and atherothrombosis.
<p>This record contains raw data related to the article “Brain-Derived Neurotrophic Factor and Extracellular Vesicle-Derived miRNAs in an Italian Cohort of Individuals With Obesity: A Key to Explain the Link Between Depression and Atherothrombosis” </p> <p><em><strong>Abstract: </strong></em></p> <p><strong>Background</strong>: Obesity and depression are intertwined diseases often associated with an increased risk of cardiovascular (CV) complications. Brain-Derived Neurotrophic Factor (BDNF), altered in the brain both of subjects with depression and obesity, provides a potential link between depression and thrombosis. Since the relationship among peripheral BDNF, depression and obesity is not well-defined, the aim of the present report has been to address this issue taking advantage of the contribution played by extracellular vesicle (EV)-derived miRNAs. <strong>Research Process</strong>: Associations among circulating BDNF, depression and EVderived miRNAs related to atherothrombosis have been evaluated in a large Italian cohort of obese individuals (n = 743), characterized by the Beck Depression Inventory (BDI-II) score.<br> <strong>Results</strong>: BDI-II was negatively associated with BDNF levels without a significant impact of the rs6265 BDNF polymorphism; this association was modified by raised levels of IFN-g. BDNF levels were linked to an increase of 80 EV-derived miRNAs and a decrease of 59 miRNAs related to atherosclerosis and thrombosis. Network analysis identified at least 18 genes targeted by these miRNAs, 7 of which involved in depression and CV<br> risk. The observation of a possible link among BDNF, depression, and miRNAs related to atherothrombosis and depression in obesity is novel and may lead to a wider use of BDNF as a CV risk biomarker in this specific subject group.</p>
Bacteria-Derived Extracellular Vesicle Microbiome in NAFLD Patients With and Without Obstructive Sleep Apnea
<p>These are the supplementary figures.</p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction
<p>The data consists of Illumina raw reads obtained from prokaryotes from coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from prokaryotic metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial producers involved in the release of DNA packaged in EVs in our annual sampling.</p> <p>The samples are named according to the convention 'prokmeta[Month], where 'prokmeta' signifies prokaryotic metagenome, '[Month]' indicates the month of sampling, and "1" represents the forward , while (2) represent the reverse read. For instance, 'prokmetaDEC.1' denotes the prokaryotic metagenome for sample of December, with '1' indicating the forward read, while 'prokmetaDEC.2' represents the corresponding reverse read. This naming scheme is consistent across all samples in the dataset from sample of November 2021 to sample of June 2022.</p> <p> </p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction.
<p>The dataset consists of third part of data for the same paper " Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction." Data were uploaded separately due to the limited space available for uploading which is f 50.00 GB and since i have more I could not upload them together.</p> <p>The data are Illumina raw reads obtained from vesicle fractions of 20%, isolated from Coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from EVs 20% fraction metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial organisms involved in the production of EVs and packaging of DNA into those EVs in our annual sampling and the types of genes that were packaged in vessicles isolated from the Coastal Mediterranean seawaters (Functional annotation of genes packaged in vesicles).</p> <p> The data are labeled as "EVs_20_DEC_1.fastq" which denotes the vesicle 20% Optiprep fraction for sample collected in December, with "1" indicating the forward read, while "EVs_20_DEC_2.fastq" represents the corresponding reverse read. This naming scheme is consistent across all vesicle fraction samples in the dataset.</p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction
<p>The data consists second part of data for the same paper " Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction." Data were uploaded separately due to the limited space available for uploading.</p> <p>The data are Illumina raw reads obtained from vesicle fractions of 25%, isolated from coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from EVs fractions metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial organisms involved in the production of EVs and packaging of DNA into those EVs in our annual sampling and the types of genes that were packaged in vessicles isolated from the Coastal Mediterranean seawaters (Functional annotation of genes packaged in vesicles).</p> <p> The data are labeled as "EVs_25_DEC_1.fastq" which denotes the vesicle 25% Optiprep fraction for sample collected in December, with "1" indicating the forward read, while "EVs_25_DEC_2.fastq" represents the corresponding reverse read. This naming scheme is consistent across all vesicle fraction samples in the dataset. </p>
The effect of extracellular vesicles derived from oral squamous cell carcinoma on the metabolic profile of oral fibroblasts
<p><span>Oral cancer is one of the most common forms of head and neck cancers. Oral squamous cell carcinoma (OSCC) accounts for more than 90% of the oral malignancies. The molecular pathogenesis of OSCC is complex as it involves altered expression of specific genes and proteins, but also comprises changes in metabolic processes. It is suggested that extracellular vesicles (EVs) released by cancer cells may contribute to cancer development and metastasis by recruiting and changing phenotype of normal cells that surround the tumor. The aim of the project was to characterize the effect of OSCC EVs on the metabolic profile of normal oral fibroblasts (NOFs). Targeted </span><span>liquid chromatography-mass spectrometry metabolic profiling was performed on control cells and NOFs exposed to OSCC EVs for 24 and 48 h. Analysis of detected metabolites revealed that OSCC EVs affected NOFs the most after 24 h of exposure. Among metabolites that were significantly altered at 24 h, </span><span>pyruvate, ATP, UTP, coenzyme A, and dihydroxyacetone phosphate were upregulated, while fatty acids such as nervonic acid, linoleate, oleate, palmitoleic acid, and docosahexaenoic acid were downregulated. These findings were supported by Western blotting of pyruvate kinase M2 (PKM2). The metabolic pathways of glycolysis, </span><span>citric acid cycle, and </span><span>amino acid metabolism were enriched, suggesting that OSCC EVs cause phenotype switch in NOFs that may contribute to </span><span>acquiring</span><span> a pro-tumorigenic phenotype.</span></p>
Raw data for: Orthogonal analysis reveals inconsistencies in cargo loading of extracellular vesicles
<p>Raw datasets and media accompanying the manuscript: Orthogonal analysis reveals inconsistencies in cargo loading of extracellular vesicles, published in Journal of Extracellular Biology in 2024.</p>
Data from: Identifying extracellular vesicles from single cells
<p>Extracellular vesicles (EVs) are constantly secreted from both eukaryotic and prokaryotic cells. EVs, including those referred to as exosomes, may have an impact on cell signaling and an incidence in diseased cells. In this manuscript, a platform to capture, quantify, and phenotypically classify the EVs secreted from single cells is introduced. Microfluidic chambers of about 300 pL are employed to trap and isolate individual cells. The EVs secreted within these chambers are then captured by surface-immobilized monoclonal antibodies (mAbs), irrespectively of their intracellular origin. Immunostaining against both plasma-membrane and cytosolic proteins was combined with highly sensitive, multi-color total internal reflection fluorescence microscopy (TIRFM) to characterize the immobilized vesicles. The data analysis of high-resolution images allowed the assignment of each detected EV to one of 15 unique populations, and demonstrated the presence of highly-heterogeneous phenotypes even at the single-cell level. The analysis also revealed that each mAb isolates phenotypically-different EVs, and more vesicles were effectively immobilized when CD63 was targeted instead of CD81. Finally, we demonstrate how an heterogeneous suppression in the secreted vesicles is obtained when the enzyme neutral sphingomyelinase is inhibited.</p>
Tunable Resistive Pulse Sensing data of "The impact of storage on extracellular vesicles: a systematic study" experiments
<p>Raw data of Tunable Resistive Pulse Sensing (TRPS) of "The impact of storage on extracellular vesicles: a systematic study" experiments</p>
Flow cytometry data of "The impact of storage on extracellular vesicles: a systematic study" experiments
<p>Flow cytometry raw data acquired for the pubblication of "The impact of storage on extracellular vesicles: a systematic study"</p>
Raw data and media: Tetraspanins are unevenly distributed across single extracellular vesicles and bias sensitivity to multiplexed cancer biomarkers
<p>Raw datasets and media accompanying the manuscript: T<strong>etraspanins are unevenly distributed across single extracellular vesicles and bias sensitivity to multiplexed cancer biomarkers</strong>, published in the Journal of Nanobiotechnology </p>
Reassessment of the proteomic composition and function of extracellular vesicles in the seminal plasma
<p>Seminal plasma contains a high concentration of extracellular vesicles (EVs). The heterogeneity of small EVs or the presence of non-vesicular extracellular matter(NV) pose major obstacles in understanding the composition and function of seminal EVs. In this study, we employed high-resolution density gradient fractionation to accurately characterize the composition and function of seminal EVs and NV. We found that the seminal EVs could be divided into three different subtypes, namely high-density EV (EV-H), medium-density EV (EV-M), and low-density EV (EV-L) after purification using iodixanol,while NV was successfully isolated. EVs and NV display different features in size, shape and expression of some classic exosome markers. Both EV-H and NV could markedly promote sperm motility and capacitation compared with EV-M and EV-L, whereas only the NV fraction induced sperm acrosome reaction. Proteomic analysis results showed that EV-H, EV-M, EV-L, and NV had different protein components and were involved in different physiological functions. Further study showed that EV-M might reduce the production of sperm intrinsic reactive oxygen species (ROS) through Glutathione S-transferase Mu 2 (GSTM2).This study provides novel insights into important aspects of seminal EVs constituents and sounder footing to explore their functional properties in male fertility.</p>
The cellular response to extracellular vesicles is dependent on their cell source and dose
<p><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">Extracellular </span><span class="NormalTextRun SCXW24798733 BCX0">vesicles</span> <span class="NormalTextRun SCXW24798733 BCX0">(EV) </span><span class="NormalTextRun SCXW24798733 BCX0">have been </span><span class="NormalTextRun SCXW24798733 BCX0">established</span><span class="NormalTextRun SCXW24798733 BCX0"> to play important roles in cell-cell communication and have </span><span class="NormalTextRun SCXW24798733 BCX0">shown promise as therapeutic agents</span><span class="NormalTextRun SCXW24798733 BCX0">.</span><span class="NormalTextRun SCXW24798733 BCX0"> However</span><span class="NormalTextRun SCXW24798733 BCX0">, </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">we still lack a</span><span class="NormalTextRun SCXW24798733 BCX0"> basic</span><span class="NormalTextRun SCXW24798733 BCX0"> understanding of</span></span><span class="TextRun SCXW24798733 BCX0"> <span class="NormalTextRun SCXW24798733 BCX0">how cells respond </span><span class="NormalTextRun SCXW24798733 BCX0">upon exposure to </span><span class="NormalTextRun SCXW24798733 BCX0">EVs from different cell sources at </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">var</span><span class="NormalTextRun SCXW24798733 BCX0">ious</span> </span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">doses. </span><span class="NormalTextRun SCXW24798733 BCX0">Thus</span><span class="NormalTextRun SCXW24798733 BCX0">, </span><span class="NormalTextRun SCXW24798733 BCX0">we treated fibroblasts with EVs from twelve different cell </span><span class="NormalTextRun SCXW24798733 BCX0">sourc</span><span class="NormalTextRun SCXW24798733 BCX0">es at doses between </span><span class="NormalTextRun SCXW24798733 BCX0">2</span><span class="NormalTextRun SCXW24798733 BCX0">0</span><span class="NormalTextRun SCXW24798733 BCX0"> and </span><span class="NormalTextRun SCXW24798733 BCX0">2</span><span class="NormalTextRun SCXW24798733 BCX0">00,000 per cell, </span><span class="NormalTextRun SCXW24798733 BCX0">a</span><span class="NormalTextRun SCXW24798733 BCX0">nalyzed </span><span class="NormalTextRun SCXW24798733 BCX0">their transcript</span><span class="NormalTextRun SCXW24798733 BCX0">i</span><span class="NormalTextRun SCXW24798733 BCX0">onal effects, </span><span class="NormalTextRun SCXW24798733 BCX0">and functionally confirmed the findings</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> in various cell types</span><span class="NormalTextRun SCXW24798733 BCX0"> <em>in vitro</em></span><span class="NormalTextRun SCXW24798733 BCX0">,</span><span class="NormalTextRun SCXW24798733 BCX0"> and <em>in vivo</em> using single-cell RNA-sequencing</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Unbiased g</span><span class="NormalTextRun SCXW24798733 BCX0">lobal</span><span class="NormalTextRun SCXW24798733 BCX0"> analysis revealed EV dose to have </span><span class="NormalTextRun SCXW24798733 BCX0">a more significant effect than cell source, </span><span class="NormalTextRun SCXW24798733 BCX0">such that </span><span class="NormalTextRun SCXW24798733 BCX0">high doses downregulat</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span><span class="NormalTextRun SCXW24798733 BCX0"> exocytosis and upregulat</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span> <span class="NormalTextRun SCXW24798733 BCX0">lysozomal</span><span class="NormalTextRun SCXW24798733 BCX0"> act</span><span class="NormalTextRun SCXW24798733 BCX0">ivity. </span><span class="NormalTextRun SCXW24798733 BCX0">However, </span><span class="NormalTextRun SCXW24798733 BCX0">EV cell source-specific responses were </span><span class="NormalTextRun SCXW24798733 BCX0">observed</span><span class="NormalTextRun SCXW24798733 BCX0"> at low doses</span><span class="NormalTextRun SCXW24798733 BCX0">,</span><span class="NormalTextRun SCXW24798733 BCX0"> and </span><span class="NormalTextRun SCXW24798733 BCX0">these </span><span class="NormalTextRun SCXW24798733 BCX0">reflected the </span><span class="NormalTextRun SCXW24798733 BCX0">activities </span><span class="NormalTextRun SCXW24798733 BCX0">of the</span><span class="NormalTextRun SCXW24798733 BCX0"> EV</span><span class="NormalTextRun SCXW24798733 BCX0">'</span><span class="NormalTextRun SCXW24798733 BCX0">s</span><span class="NormalTextRun SCXW24798733 BCX0"> source cell</span><span class="NormalTextRun SCXW24798733 BCX0">s</span><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Finally, </span><span class="NormalTextRun SCXW24798733 BCX0">we </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">assess</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> EV</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">-derived</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> transcript abundance </span><span class="NormalTextRun SCXW24798733 BCX0">and foun</span><span class="NormalTextRun SCXW24798733 BCX0">d that immune cell</span><span class="NormalTextRun SCXW24798733 BCX0">-derived</span><span class="NormalTextRun SCXW24798733 BCX0"> EVs were </span><span class="NormalTextRun SCXW24798733 BCX0">most </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">associated with</span> <span class="NormalTextRun SCXW24798733 BCX0">recipient</span><span class="NormalTextRun SCXW24798733 BCX0"> cells</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Together, t</span><span class="NormalTextRun SCXW24798733 BCX0">his study </span><span class="NormalTextRun SCXW24798733 BCX0">provides</span><span class="NormalTextRun SCXW24798733 BCX0"> important insight into the </span><span class="NormalTextRun SCXW24798733 BCX0">cellular response to EVs.</span></span></p>
Efficacy of Platelet- and Extracellular Vesicle-rich Plasma in Chronic Postsurgical Temporal Bone Inflammations
ClinicalTrials.gov study NCT04281901. IPD Sharing: YES. Countries: 1. Publications: 2.
Extracellular Vesicle Infusion Treatment for COVID-19 Associated ARDS
ClinicalTrials.gov study NCT04493242. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
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.