LitCovid-sentences  

PMC:7417788 / 58243-78417 JSONTXT 14 Projects

Annnotations TAB TSV DIC JSON TextAE Lectin_function IAV-Glycan

Id Subject Object Predicate Lexical cue
T303 0-21 Sentence denotes MATERIALS AND METHODS
T304 23-37 Sentence denotes Human subjects
T305 38-180 Sentence denotes The study was approved by the Ethics Committee of Zhongshan Ophthalmic Center, China and the Ethics Committee of Wuhan Hankou Hospital, China.
T306 181-368 Sentence denotes A written informed consent was routinely obtained from all individuals participating in the study and all relevant ethical regulations regarding human research participants were followed.
T307 369-537 Sentence denotes Healthy non-frail individuals were recruited in the Zhongshan Ophthalmic Center, and divided by age into two groups in cohort-1: young adults (YA) and aged adults (AA).
T308 538-640 Sentence denotes The YA group ranged from ages 20 to 45 years old and the AA group ranged from ages 60 to 80 years old.
T309 641-829 Sentence denotes COVID-19 patients diagnosed by real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR) and CT images were enrolled in the Wuhan Hankou Hospital, China.
T310 830-1106 Sentence denotes Based on their clinical history, patients were divided into incipient and recovered groups in cohort-2 and cohort-3 respectively, and the incipient hospitalized patients were further divided by age into young COVID-19 patient onset (YCO) and aged COVID-19 patient onset (ACO).
T311 1107-1293 Sentence denotes Enrolled patients that tested negative with nucleic acid transfer in 7–14 days were further divided into young COVID-19 patient recovered (YCR) and aged COVID-19 patient recovered (ACR).
T312 1294-1434 Sentence denotes Individuals with comorbid conditions including cancer, immunocompromising disorders, hypertension, diabetes and steroid usage were excluded.
T313 1435-1657 Sentence denotes No significant gender differences were detected between YA group and AA group in cohort-1 (Table S1C–E), between YH, AH, YCO and ACO group in cohort-2 (Table S1F), between YH, AH, YCR and ACR group in cohort-3 (Table S1G).
T314 1659-1682 Sentence denotes Antibodies and reagents
T315 1683-1836 Sentence denotes Antibodies against the following markers in flow cytometric analysis were purchased from Biolegend, BD biosciences and Abcam: CD3 (clone SK7) BV785 (Cat.
T316 1837-1873 Sentence denotes 344842), CD19 (clone HB19) APC (Cat.
T317 1874-1913 Sentence denotes 302212), CD88 (clone S5/1) PE/Cy7 (Cat.
T318 1914-1952 Sentence denotes 344307), CD89 (clone A59) PE/Cy7 (Cat.
T319 1953-1992 Sentence denotes 354107), HLA-DR (clone L243) FITC (Cat.
T320 1993-2031 Sentence denotes 307604), CD11c (clone 3.9) BV421 (Cat.
T321 2032-2080 Sentence denotes 301627), FcεRIa (clone AER-37) PercP/Cy5.5 (Cat.
T322 2081-2119 Sentence denotes 334622), CD1c (clone L161) BV650 (Cat.
T323 2120-2166 Sentence denotes 331541), CD371 (CLEC12A) (clone 50C1) PE (Cat.
T324 2167-2233 Sentence denotes 353603) were purchased from Biolegend, CD147 (clone HIM6) PE (Cat.
T325 2234-2276 Sentence denotes 562552) was purchased from BD biosciences.
T326 2277-2307 Sentence denotes Fetal bovine serum (FBS) (Cat.
T327 2308-2349 Sentence denotes 10270-106), penicillin/streptomycin (Cat.
T328 2350-2392 Sentence denotes 15140-122), and Trypsin-EDTA (0.25%) (Cat.
T329 2393-2430 Sentence denotes 25200-072) were purchased from GIBCO.
T330 2431-2448 Sentence denotes RT-qPCR kit (Cat.
T331 2449-2486 Sentence denotes 25200-072) was purchased from TaKaRa.
T332 2488-2524 Sentence denotes Detection of SARS-Cov-2 with RT-qPCR
T333 2525-2680 Sentence denotes Samples used for RT-qPCR were blood, upper respiratory tract sputum and throat swab obtained from patients at specified time-points during hospitalization.
T334 2681-2786 Sentence denotes The patient samples were collected, processed and analyzed following the guideline stipulated by the WHO.
T335 2787-2932 Sentence denotes To extract viral RNA, the specimens were treated with the QIAamp RNA Viral Kit (Qiagen, Heiden, Germany) following the manufacturer’s guidelines.
T336 2933-3148 Sentence denotes The presence of SARS-CoV-2 infection was confirmed with a China CDC recommended RT-qPCR kit (TaKaRa, Dalian, China). qPCR was performed as previously described (Zhang et al., 2019; Bi et al., 2020; Li et al., 2020).
T337 3150-3213 Sentence denotes Isolation of PBMCs for mass cytometry, scRNA-seq and scATAC-seq
T338 3214-3445 Sentence denotes For pipeline analysis, venous blood samples were derived from each healthy donor or patient using Ficoll-Hypaque density solution, heparinized and then processed by standard density gradient centrifugation methods to isolate PBMCs.
T339 3446-3543 Sentence denotes The viability and quantity of PBMCs in single-cell suspensions were determined using Trypan Blue.
T340 3544-3593 Sentence denotes For each sample, the cell viability exceeded 90%.
T341 3594-3773 Sentence denotes For each sample with more than 1 × 107 viable cells, a fraction of PBMCs was extracted for scRNA-seq analysis, a fraction of PBMCs was allocated for scATAC-seq and mass cytometry.
T342 3775-3799 Sentence denotes Flow cytometric analysis
T343 3800-4010 Sentence denotes PBMCs suspended in phosphate buffered saline (PBS) were cultured with Live/Dead yellow dye (Invitrogen) at 4 °C for 30 min and then washed once with 1 mL of PBS containing 1% FBS (GIBCO, Grand Island, NY, USA).
T344 4011-4079 Sentence denotes Subsequently, cells were treated with antibodies for 30 min at 4 °C.
T345 4080-4486 Sentence denotes These antibodies included: CD3-BV785 (clone SK7, Biolegend), CD19-APC (clone HB19, Biolegend), CD88-PE/Cy7 (clone S5/1, Biolegend), CD89-PE/Cy7 (clone A59, Biolegend), HLA-DR-FITC (clone L243, Biolegend), CD11c-BV421 (clone 3.9, Biolegend), FcεRIa- PercP/Cy5.5 (clone AER-37, Biolegend), CD1c-BV650 (clone L161, Biolegend), CD147-PE (clone HIM6, BD biosciences), CD371 (CLEC12A)-PE (clone 50C1, Biolegend).
T346 4487-4662 Sentence denotes Analysis of PBMCs with flow cytometry was conducted with BD Fortessa (BD Biosciences) and the results were evaluated with FlowJo (version 10.0.7, Tree Star, Ashland, OR, USA).
T347 4664-4719 Sentence denotes Mass cytometry live cell barcoding and surface staining
T348 4720-4859 Sentence denotes We made use of a live cell barcoding approach to minimize inter-sample staining variability, sample handling time and antibody consumption.
T349 4860-5018 Sentence denotes After incubating with anti-human CD45 loaded with different isotopes (89Y, 162Dy, 165Ho, 169Tm, 175Lu), all the samples were then pooled for surface staining.
T350 5019-5187 Sentence denotes The Maxpar Direct Immune Profiling Assay (Fluidigm) was used for cell surface staining and the monoclonal anti-human antibodies in the assay kit are listed as Table S2.
T351 5188-5610 Sentence denotes Barcoded and combined samples were washed and stained with viability dyes cisplatin-195pt (0.5 μmolL) (Fluidigm, 201064) and vortexed to mix thoroughly for 2 min at room temperature for cell viability, terminated with Maxpar Cell Staining buffer at room temperature (400 rcf.), washed, fixed with 1.6% paraformaldehyde (PFA; Electron Microscopy Sciences) in PBS for 10 min at room temperature on a rotary shaker (500 rpm).
T352 5611-5701 Sentence denotes The fixed cells were resuspended in pre-cooling Maxpar Cell Staining to slow fix reaction.
T353 5702-5858 Sentence denotes Fixed samples were washed twice with PBS/bovine serum albumin and once with double-distilled water before resuspended in 400 μL of surface-antibody mixture.
T354 5859-5941 Sentence denotes Surface staining was performed for 30 min at 37 °C on a rotating shaker (500 rpm).
T355 5942-6129 Sentence denotes The samples then stored in freshly diluted 2% formaldehyde (Electron Microscopy Sciences) in PBS containing 0.125 nmol/L iridium 191/193 intercalator (Fluidigm, 201192) at 4 °C overnight.
T356 6131-6190 Sentence denotes scRNA-seq data alignment, processing and sample aggregation
T357 6191-6426 Sentence denotes The Chromium Single Cell 5′ Library (the 10x Genomics chromium platform Illumina NovaSeq6000), Gel Bead and Multiplex Kit, and Chip Kit (10x Genomics) were used to convert single-cell suspension samples to barcoded scRNA-seq libraries.
T358 6427-6575 Sentence denotes Single-cell RNA libraries were prepared using the Chromium Single Cell 5′ v2 Reagent (10x Genomics, 120237) kit as per the manufacturer’s protocols.
T359 6576-6643 Sentence denotes The quality of the libraries was checked using the FastQC software.
T360 6644-6774 Sentence denotes Initial processing of the sequenced data was performed using CellRanger software (https://support.10xgenomics.com, version 3.1.0).
T361 6775-6958 Sentence denotes The command Cell Ranger count in CellRanger Software Suite (10x Genomics) was used to demultiplex and barcode the sequences derived from the 10x Genomics single-cell RNA-seq platform.
T362 6959-7263 Sentence denotes The data was filtered, normalized, dimensionality was reduced, clustered, and differential gene expression analysis were performed after calculation of the single-cell expression matrix by CellRanger using Python (version 3.7.7) Scanpy (https://scanpy.readthedocs.io/en/stable/index.html, version 1.4.6).
T363 7264-7403 Sentence denotes Data collection and the subsequent analyses were performed in an unsupervised manner, but not blinded to the conditions of the experiments.
T364 7404-7605 Sentence denotes For quality control, the filtered cell population was mainly those cells that express HBB, HBA1, and several light and heavy chain transcripts, which identified as the RBC-contaminated cell population.
T365 7606-7751 Sentence denotes Likewise, several clusters expressing genes has no significance (P ≥ 0.1, calculate by 10x genomics Loupe Cell Browser with it default algorithm.
T366 7752-7847 Sentence denotes P values are adjusted using the Benjamini-Hochberg correction for multiple tests) were removed.
T367 7848-7989 Sentence denotes A total of 16 libraries were sequenced, and 166,609 cells (YA 77,652 cells, AA 88,957 cells) were analyzed after quality control in cohort-1.
T368 7990-8148 Sentence denotes For cohort-3, 22 libraries and 205,434 cells (YH 79,039 cells, AH 88,750 cells, YCR 19,533 cells, ACR 18,112 cells) were remained for the subsequent analysis.
T369 8149-8448 Sentence denotes The genes used in principal component analysis (PCA) analysis have eliminated mitochondria (MT), and ribosomes (RPL and RPS) genes with 50 principal components, and then aligned together, followed by t-distributed stochastic neighbor embedding (t-SNE) are both used after the results of the aligned.
T370 8449-8631 Sentence denotes And using the run_harmony function (in pyharmony package, version 1.0.7) and combat function (in Scanpy) methods to deal with batch effect issues if batch effect existing in dataset.
T371 8632-8701 Sentence denotes Genes not detected in any cell were removed from subsequent analysis.
T372 8703-8773 Sentence denotes Dimensionality reduction and clustering analysis of scRNA-seq datasets
T373 8774-9020 Sentence denotes To analyze the scRNA-seq data, we log normalized data (1 + counts per 10,000) with the ‘‘sc.pp.normalize_total’’ function before clustering, reduction and performing 2-dimensional t-SNE algorithm clustering with the first 50 principal components.
T374 9021-9168 Sentence denotes This was done following PCA on top 5,000 most variable genes by using “sc.pp.highly_variable_genes” function in Scanpy with the default parameters.
T375 9169-9375 Sentence denotes Dimensionality method and identification of significant clusters and was performed using Leiden clustering algorithm which uses a shared nearest neighbour modularity optimization-based clustering algorithm.
T376 9376-9496 Sentence denotes Marker genes for each significant cluster were found using the function sc.tl.rank_genes_groups with default parameters.
T377 9498-9530 Sentence denotes Differential expression analysis
T378 9531-9780 Sentence denotes Differential expression analysis for each cell type between different groups (YA and AA in cohort-1 and YH, AH, YCR and ACR in cohort-3) was performed using the t-test as implemented in the ‘‘sc.tl.rank_genes_groups’’ function of the Scanpy package.
T379 9781-9918 Sentence denotes For each cluster, differentially-expressed genes (DEGs) were performed using the t-test and generated relative to all of the other cells.
T380 9919-10078 Sentence denotes Before executing the differential expression analysis, we filtered out the cell types that were missing or had fewer than three cells in the comparison groups.
T381 10079-10348 Sentence denotes An aging-associated and disease-related DEG dataset was established (adjusted P value < 0.05, |Log2FC| > 0.25) after identification of DEGs between AA and YA groups in cohort-1, AH and YH groups in cohort-3, ACR and AH groups in cohort-3, YCR and YH groups in cohort-3.
T382 10349-10465 Sentence denotes The ‘‘upregulated DEGs during aging’’ were defined as the DEGs that increased in AA group and decreased in YA group.
T383 10466-10580 Sentence denotes The ‘‘downregulated DEGs in aging’’ were defined as the DEGs that decreased in AA group and increased in YA group.
T384 10582-10608 Sentence denotes Gene functional annotation
T385 10609-10829 Sentence denotes The Metascape webtool (www.metascape.org) (Zhou et al., 2019) that allow visualization of functional patterns of gene clusters and statistical analysis was used to conduct DEGs gene ontology, pathway enrichment analyses.
T386 10830-10993 Sentence denotes Among the top 30 enriched GO terms or pathways across various types of cells and tissues, 10 GO terms or pathways which were associated with aging were visualized.
T387 10994-11169 Sentence denotes Gene expression profile cluster plots and heatmaps were established using the pheatmap R package (https://cran.r-project.org/web/packages/pheatmap/index.html, version 1.0.12).
T388 11171-11191 Sentence denotes Aging score analysis
T389 11192-11335 Sentence denotes To assess the impact of aging in circulating immune cells, we selected the top 20 genes out of 60 common upregulated genes in all immune cells.
T390 11336-11458 Sentence denotes Aging scores were estimated for all cells as the average of the scaled (Z-normalized) expression of the genes in the list.
T391 11459-11587 Sentence denotes The score of aging for all immune cell types can be used to predict the effect of aging on single cells and cell subtype levels.
T392 11588-11855 Sentence denotes Calculation of the scores was done as follows: the score of the aging gene set in the given cell-subset (named as X) was computed as the sum of all UMI for all the aging genes expressed in X cell, divided by the sum of all UMI expressed by X cell (Pont et al., 2019).
T393 11857-11901 Sentence denotes Sequencing and analysis of TCR and BCR V(D)J
T394 11902-12082 Sentence denotes PCR amplification was done to enrich the full-length TCR/BCR V(D)J segments for the amplified cDNA from 5′ libraries with a Chromium Single-Cell V(D)J Enrichment kit (10 Genomics).
T395 12083-12260 Sentence denotes The TCR/BCR sequences of each T/B cell were clustered using the CellRanger vdj pipeline (version 3.1.0, allowing identification of CDR3 sequence and the rearranged TCR/BCR gene.
T396 12261-12372 Sentence denotes Analysis was performed using Loupe V(D)J Browser version 2.0.1 (https://support.10xgenomics.com, 10x Genomics).
T397 12373-12481 Sentence denotes In summary, barcode information a containing clonotype frequency and TCR/BCR diversity metric were obtained.
T398 12482-12600 Sentence denotes We projected T /B cells with dominant TCR/BCR clonotypes on a t-SNE plot using barcode information (Wen et al., 2020).
T399 12602-12640 Sentence denotes Determination of cell-cell interaction
T400 12641-12763 Sentence denotes We employed the expression of immune-related ligands and receptors to assess the cell-cell interactions (Ma et al., 2020).
T401 12764-13034 Sentence denotes The possible ligand-receptor interactions between one set of receptor-expressing cells and then next ligand-expressing cells were determined as the average of the product of receptor and ligand expression (respectively from set one and two) across all single-cell pairs:
T402 13035-13783 Sentence denotes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$I = \mathop \sum \limits_{i}^{n} I_{i} \times \mathop \sum \limits_{j}^{m} r_{j} \left(\frac{1}{m*n}\right)$$\end{document}I=∑inIi×∑jmrj1m∗nwhere I refers to the interaction score between receptor expressing cells in set one and ligand-expressing cells in set two, Ii stands for the ligand expression of cell i in cell set one, rj represents the receptor expression of cell j in cell set two, n stands for the number of cells in set one and m denotes the number of cells in set two.
T403 13784-13922 Sentence denotes In the gene list, there were 168 pairs of well-annotated ligands and receptors, among which were co-stimulators, chemokines and cytokines.
T404 13923-14145 Sentence denotes The possible interactions between two cell types were orchestrated by receptor-ligand pairs by the product of the average expression levels of the ligand in one cell type and the respective receptor in the other cell type.
T405 14147-14192 Sentence denotes Mass cytometry processing and quality control
T406 14193-14416 Sentence denotes CyTOF data were acquired with a CyTOF2 system using a SuperSampler fluidics system (Victorian Airships) at an event rate of < 400 events per second and normalized with Helios normalizer software (Fluidigm version 6.7.1016).
T407 14417-14550 Sentence denotes Acquisitions from different days (three independent acquisitions were performed) were normalized using five-element beads (Fluidigm).
T408 14551-14653 Sentence denotes Barcoded samples were deconvoluted and cross-sample doublets were filtered using cytobank application.
T409 14654-14939 Sentence denotes CyTOF data was pre-processed with Cytobank (https://mtsinai.cytobank.org; Cytobank, 7.0) to sequentially remove calibration beads, dead cells, debris and barcodes for CD45+ PBMCs based on event length, DNA (191Ir and 193Ir) and live cell (195Pt) channels and then export the FCS files.
T410 14940-15051 Sentence denotes We analyzed 200,000 PBMCs in cohort-1 and 160,000 PBMC in cohort-2, with an average of 20,000 cells per sample.
T411 15053-15094 Sentence denotes Mass cytometry visualizing and clustering
T412 15095-15206 Sentence denotes We created mass cytometry datasets for analysis by concatenating cells from all individuals for each cell type.
T413 15207-15418 Sentence denotes In this way, we created downsampled datasets of 95,316 TCs, 35,254 NKs, 22,042 BCs, 39,144 MCs and 8,244 DCs in cohort-1 and 57,910 TCs, 34,857 NKs, 13,812 BCs, 45,431 MCs and 7,990 DCs in cohort-2 for analysis.
T414 15419-15449 Sentence denotes We used FlowCore (65 flowCore:
T415 15450-15544 Sentence denotes Basic structures for flow cytometry data.) to read and process FCS files for further analysis.
T416 15545-15667 Sentence denotes For sample with more than 20,000 cells, we randomly selected 20,000 cells to ensure that samples were equally represented.
T417 15668-15866 Sentence denotes At last, we run the t-SNE dimensionality reduction algorithm on a combined data sample using the Seurat package based on harmony embedding (https://github.com/immunogenomics/harmony, version 1.0.0).
T418 15868-15907 Sentence denotes Batch correction of mass cytometry data
T419 15908-16049 Sentence denotes PBMC mass cytometry data from 10 subjects of cohort-1 or 8 subjects of cohort-2 was combined and batch normalized using harmony respectively.
T420 16050-16142 Sentence denotes First, mass cytometry data from each cohort all subjects was combined into a single dataset.
T421 16143-16215 Sentence denotes Second, harmony batch correction was performed using one of the samples.
T422 16216-16331 Sentence denotes Third, mass cytometry data were lognormalized in the Seurat’s NormalizeData function across the aggregated dataset.
T423 16333-16411 Sentence denotes Single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq)
T424 16412-16551 Sentence denotes scATAC-seq targeting 4,000 cells per sample was performed using Chromium Single Cell ATAC Library and Gel Bead kit (10x Genomics, 1000110).
T425 16552-16620 Sentence denotes Each sample library was uniquely barcoded and quantified by RT-qPCR.
T426 16621-16854 Sentence denotes Libraries were then pooled and loaded on an Illumina Novaseq 6000 sequencer (3.5 pmol/L loading concentration, 50 + 8 + 16 + 49 bp read configuration) and sequenced to either 90% saturation or 30,000 unique reads per cell on average.
T427 16855-17086 Sentence denotes All protocols to generate scATAC-seq data on the 10x Chromium platform, including sample preparation, library preparation and instrument and sequencing settings, are available here: https://support.10xgenomics.com/single-cell-atac.
T428 17088-17114 Sentence denotes scATAC-seq data processing
T429 17116-17137 Sentence denotes scATAC-seq processing
T430 17138-17273 Sentence denotes scATAC-seq reads were aligned to the GRCh38 (hg38) reference genome and quantified using CellRanger-ATAC count (10x Genomics, v.1.0.0).
T431 17275-17301 Sentence denotes scATAC-seq quality control
T432 17302-17483 Sentence denotes To ensure that each cell was both adequately sequenced and had a high signal-to-background ratio, we filtered cells with less than 1,000 unique fragments and enrichment at TSSs < 8.
T433 17484-17632 Sentence denotes To calculate TSS enrichment > 2, genome-wide Tn5-corrected insertions were aggregated ± 2,000 bp relative (TSS-strand-corrected) to each unique TSS.
T434 17633-17806 Sentence denotes This profile was normalized to the mean accessibility ± 1,900–2,000 bp from the TSS, smoothed every 51 bp and the maximum smoothed value was reported as TSS enrichment in R.
T435 17807-17937 Sentence denotes To construct a counts matrix for each cell by each feature (peaks), we read each fragment.tsv.gz fill into a GenomicRanges object.
T436 17938-18107 Sentence denotes For each Tn5 insertion, which can be thought of as the “start” and “end” of the ATAC fragments, we used findOverlaps to find all overlaps with the feature by insertions.
T437 18108-18234 Sentence denotes Then we added a column with the unique id (integer) cell barcode to the overlaps object and fed this into a sparseMatrix in R.
T438 18235-18416 Sentence denotes To calculate the fraction of reads/insertions in peaks, we used the colSums of the sparseMatrix and divided it by the number of insertions for each cell id barcode using table in R.
T439 18418-18461 Sentence denotes scATAC-seq visualization in genomic regions
T440 18462-18547 Sentence denotes To visualize scATAC-seq data, we read the fragments into a GenomicRanges object in R.
T441 18548-18676 Sentence denotes We then computed sliding windows across each region we wanted to visualize for every 100 bp “slidingWindows (region, 100, 100)”.
T442 18677-18784 Sentence denotes We computed a counts matrix for Tn5-corrected insertions as described above and then binarized this matrix.
T443 18785-18930 Sentence denotes We then returned all non-zero indices (binarization) from the matrix (cell × 100-bp intervals) and plotted them in ggplot2 in R with “geom_tile”.
T444 18931-19027 Sentence denotes For visualizing aggregate scATAC-seq data, the binarized matrix above was summed and normalized.
T445 19028-19137 Sentence denotes Scale factors were computed by taking the binarized sum in the global peak set and normalizing to 10,000,000.
T446 19138-19460 Sentence denotes Tracks were then plotted in Loupe Cell Browser, an interactive visualization software that shows scATAC-seq peak profiles for scATAC-seq cell clusters, similar to the analysis done in this manuscript and described at https://support.10xgenomics.com/single-cellatac/software/visualization/latest/what-is-loupe-cell-browser.
T447 19462-19470 Sentence denotes chromVAR
T448 19471-19519 Sentence denotes We measured global TF activity using chromVAR15.
T449 19520-19701 Sentence denotes We used the cell-by-peaks and the Catalog of Inferred Sequence Binding Preferences (CIS-BP) motif (from chromVAR motifs “human_pwms_v1”) matches within these peaks from motifmatchr.
T450 19702-19804 Sentence denotes We then computed the GC-bias-corrected deviation scores using the chromVAR “deviationScores” function.
T451 19806-19826 Sentence denotes Statistical analysis
T452 19827-19919 Sentence denotes The GraphPad Prism Software (version 8.0.2) was employed for data analysis and presentation.
T453 19920-19961 Sentence denotes All results are presented as means ± SEM.
T454 19962-20088 Sentence denotes Groups were compared with two-tailed Mann-Whitney-Wilcoxon tests and FDR was corrected using the Benjamini-Hochberg procedure.
T455 20089-20174 Sentence denotes P value was derived by a hypergeometric test in representative GO terms and pathways.