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862 results for “Capillary”
Longitudinal single-cell RNA sequencing of 55,260 capillary PBMCs from 2 donors with ME/CFS before, during, and after antibiotic treatment
<p><strong>Sample Procurement</strong></p> <p>Samples were self-collected directly from participants as part of <a href="https://www.remissionbiome.org/" target="_blank" rel="noopener">RemissionBiome</a>'s pilot study, and processed by <a href="https://www.imyoo.health/">ImYoo</a>. For additional details on the experiment, see <a href="https://www.imyoo.health/post/n-of-1-studies-are-scaling-and-they-re-making-discoveries-in-the-toughest-diseases" target="_blank" rel="noopener">ImYoo's blog post</a> and corresponding comments.</p> <p><strong>Sample Processing</strong></p> <p>Whole capillary blood samples were self-collected from participants using the <a href="https://yourbiohealth.com/en-us/virtually-painless-blood-collection-devices-for-clinical-trials-and-wellness-testing">TAP II</a> device. Samples were kept in a temperature stable thermos or styrofoam cooler with ice packs and shipped with overnight shipping to ImYoo labs. Cells were isolated using <a href="https://www.stemcell.com/products/easysep-direct-human-pbmc-isolation-kit.html">EasySep Direct Human PBMC Isolation Kit</a> (STEMCELL Technologies Catalog #19654) and cryopreserved using <a href="https://www.stemcell.com/cryostor-cs10.html">CryoStor CS10</a> (STEMCELL Technologies Catalog #07930). Upon thawing, samples were labeled in accordance with the MULTI-seq protocol (<a href="https://www.nature.com/articles/s41592-019-0433-8">https://www.nature.com/articles/s41592-019-0433-8</a>) and then processed on a 10X Genomics Chromium, using the Chromium Next GEM Single Cell 3’ HT Kit v3.1 (10X Genomics Product Code 1000370). DNA libraries were sequenced on a Complete Genomics DNBSEQ-G400 sequencer.</p> <p><strong>Data Processing</strong></p> <p>Transcriptomic sequencing data was processed using Cell Ranger v7.0.1 with default parameters. Multiplexing oligo sequencing data was processed through a custom python script that counts the number of occurrences of each sample barcode sequence and assigns it to the corresponding cell barcode. Samples were demultiplexed using a custom algorithm that estimates the background sample barcode counts, and assigns each cell a probability of belonging to each sample. Cell typing was done by training an <a href="https://scvi-tools.org/" target="_blank" rel="noopener">scVI model</a> on all cells with default parameters, and "library" as the batch_key. The latent space was then used to perform leiden clustering, and clusters were mapped to cell types based on common marker gene expression.</p> <p><strong>Differential Expression</strong></p> <p>Differential expression was calculated using DEseq2. For each cluster and cell type, cells from the same sample in the same participant were summed together to create a pseudocell, and passed as pseudobulked samples into DESeq2 to compare "Event" samples to "Baseline" samples.</p> <p><strong>Metadata Fields</strong></p> <ul> <li><strong>barcode:</strong> 10X cell barcode</li> <li><strong>sample_id:</strong> Unique ID for the experimental sample that was processed with 10x Chromium, could have come from the same biological sample (identified by <strong>source_sample_id</strong>)</li> <li><strong>condition</strong>: Whether this sample is before ("Baseline"), during ("Event"), or after ("New Baseline") the antibiotic intervention</li> <li><strong>participant_id:</strong> Unique ID for participant. There are two participants: P363, and P364. P363 experienced a full remission event, while P364 did not.</li> <li><strong>extracted_on</strong>: The date and time the blood was extracted</li> <li><strong>cell_barcoding_run_id:</strong> Unique ID for the 10x Chromium cell barcoding run in which that sample was processed. Multiple samples can be processed in a cell barcoding run.</li> <li><strong>extraction_type</strong>: Whether the PBMCs were isolated from Venous or Capillary blood</li> <li><strong>lane:</strong> ID of which Chromium chip lane the cell came from</li> <li><strong>sample_processing_delay_seconds:</strong> The amount of time (in seconds) between when the blood was extracted from the participant and when PBMC isolation + cryopreservation was performed</li> <li><strong>cell_barcoding_delay_days:</strong> How long PBMC samples were stored in liquid nitrogen prior to being thawed and processed on 10x</li> <li><strong>cell_barcoding_protocol</strong>: Which single cell RNA sequencing experimental protocol was used. Here all samples were processed with 10x v3.1 chemistry.</li> <li><strong>library:</strong> Concatenation of columns <strong>Cell Barcoding Runs</strong> and <strong>Lane</strong> to provide a unique ID for experimental processing batch (i.e. the DNA library)</li> <li><strong>leiden:</strong> The cluster this cell belongs to after automatic cell clustering</li> <li><strong>cell_type:</strong> Manually labeled cell type</li> <li><strong>source_sample_id:</strong> Some samples may be derived from the same originating whole blood sample. This field specifies the source of the whole blood sample.</li> </ul>
Dataset related to the article "Week to week variability of pulmonary capillary blood volume and alveolar membrane diffusing capacity in patients with heart failure"
<p>Abstract</p> <p><strong>Background: </strong>Alveolar-capillary membrane diffusing capacity for carbon monoxide (DMCO) and pulmonary capillary volume (Vcap) can be estimated by the multi-step Roughton and Foster (RF, original method from 1957) or the single-step NO-CO double diffusion technique (developed in the 1980s). The latter method implies inherent assumptions. We sought to determine which combination of the alveolar membrane diffusing capacity for nitric oxide (DMNO) to DMCO ratio, an specific conductance of the blood for NO (θ<sub>NO</sub>) and CO (θ<sub>CO</sub>) gave the lowest week-to-week variability in patients with heart failure.</p> <p><strong>Methods: </strong>44 heart failure patients underwent DMCO and Vcap measurements on three occasions over a ten-week period using both RF and double dilution NO-CO techniques.</p> <p><strong>Results: </strong>When using the double diffusing method and applying θ<sub>NO</sub> = infinity, the smallest week-to-week coefficient of variation for DMCO was 10 %. Conversely, the RF method derived DMCO had a much greater week-to-week variability (2x higher coefficient of variation) than the DMCO derived via the NO-CO double dilution technique. The DMCO derived from the double diffusion technique most closely matched the DMCO from the RF method when θ<sub>NO</sub> = infinity and DMCO = DLNO/2.42. The Vcap measured week-to-week was unreliable regardless of the method or constants used.</p> <p><strong>Conclusions: </strong>In heart failure patients, the week-to-week DMCO variability was lowest when using the single-step NO-CO technique. DMCO obtained from double diffusion most closely matched the RF DMCO when DMCO/2.42 and θ<sub>NO</sub> = infinity. Vcap estimation was unreliable with either method.</p>
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