Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project.

Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines.

Differentially expressed long non-coding RNAs and mRNAs of cadmium exposure on learning disability of offspring rats.

BACKGROUND: Cadmium (Cd) exposure has been found to have detrimental effects on the development of the central nervous system and cognitive ability in children. However, there is ongoing debate regarding the impact of maternal Cd exposure on the cognitive ability of offspring. In this study, we aimed to investigate the mechanisms underlying the influence of maternal Cd exposure on the cognitive ability of offspring rats. METHODS: Here, we constructed a model of cadmium poisoning in first-generation rats through gavage. The cognitive and memory abilities of its offspring were evaluated by water maze experiment. Then, we used the gene chip to find out the key genes, and we performed qRT-PCR detection of these genes. Subsequently, enrichment analysis was employed to identify pathways. Finally, we constructed a co-expression network consisting of LncRNAs and mRNAs to elucidate the biological functions and regulatory mechanisms of LncRNAs. RESULTS: The results of the water maze trial demonstrated that the offspring of rats exposed to cadmium in the first generation had reduced cognitive and memory abilities. Through an analysis of gene expression in the hippocampus of the cadmium-treated rats' offspring and the control group, we identified a correlation between the islet secretion pathway and the cognitive impairment observed in the offspring. Utilizing various algorithms, we identified Cpa1 and Prss1 as potential key genes associated with the cognitive impairment caused by cadmium. The results of qRT-PCR demonstrated a decrease in the expression levels of these genes in the hippocampus of the cadmium-treated rats' offspring. In addition, in the co-expression network, we observed that Cpa1 was co-expressed with 11 LncRNAs, while Prss1 was associated with 4 unexplored LncRNAs. Furthermore, we conducted an analysis to examine the relationship between Cpa1, Prss1-related transcription factors, and LncRNAs. CONCLUSION: Overall, this study provides novel insights into the molecular effects of first generation Cd exposure on the cognitive ability of offspring. The target genes and signaling pathways investigated in this study could serve as potential targets for improving neurodevelopment and cognitive ability in children.

Study of compaction tools and parameters on critical quality attributes of high drug load minitablets.

Minitablets are prepared using multiple die openings and multi-tip punches for greater productivity. With multiple tips on the punch barrel, the overall compaction force to be applied is commonly estimated by multiplying the desired compaction force per tip by the number of punch tips. Few researchers have however examined this proportionality and the effects of the number of punch tips and punch face geometry on the critical quality attributes (CQAs) of high drug load minitablets. In this study, the minitablets prepared by multi-tip tools exhibited greater weight variation than those prepared by single-tip tools. Their compaction was accompanied by a longer dwell time that led to a higher minitablet tensile strength and consequently a longer disintegration time. The compaction forces required to achieve a consistent set of minitablet CQAs were not directly proportional to the number of punch tips used. In comparison, the effect of punch face geometry was negligible. Increasing concentration of magnesium stearate (as lubricant) from 0.75 to 1.25 %, w/w reduced weight variation, especially of minitablets prepared by the multi-tip tools. It also increased the disintegration time but had no significant effect on the tensile strength of the minitablets regardless of type of tools used. The adjustment of compaction speed was an effective compensatory method to mitigate the differences in dwell time and tensile strength between minitablets prepared by single-tip and multi-tip standard concave tools. A larger reduction in compaction speed of the single-tip tools was required at higher compaction pressures.

Inhibitory effect of acarbose on tyrosinase: application of molecular dynamics integrating inhibition kinetics.

Due to its clinical and cosmetic applications, investigators have paid attention to tyrosinase (TYR) inhibitor development. In this study, a TYR inhibition study with acarbose was investigated to gain insights into the regulation of the catalytic function. Biochemical assay results indicated that acarbose was turned to be an inhibitor of TYR in a reversible binding manner and probed as a distinctive mixed-type inhibitor via measurement of double-reciprocal kinetic (Ki = 18.70 ± 4.12 mM). Time-interval kinetic measurement indicated that TYR catalytic function was gradually inactivated by acarbose in a time-dependent behavior displaying with a monophase process that was evaluated by semi-logarithmic plotting. Spectrofluorimetric measurement by integrating with a hydrophobic residue detector (1-anilinonaphthalene-8-sulfonate) showed that the high dose of acarbose derived a conspicuous local structural deformation of the TYR catalytic site pocket. Computational docking simulation showed that acarbose bound to key residues such as HIS61, TYR65, ASN81, HIS244, and HIS259. Our study extends an understanding of the functional application of acarbose and proposes that acarbose is an alternative candidate drug for a whitening agent via direct retardation of TYR catalytic function and it would be applicable for the relevant skin hyperpigmentation disorders concerning the dermatologic clinical purpose.Communicated by Ramaswamy H. Sarma.

Joint L2,p-norm and random walk graph constrained PCA for single-cell RNA-seq data.

The development and widespread utilization of high-throughput sequencing technologies in biology has fueled the rapid growth of single-cell RNA sequencing (scRNA-seq) data over the past decade. The development of scRNA-seq technology has significantly expanded researchers' understanding of cellular heterogeneity. Accurate cell type identification is the prerequisite for any research on heterogeneous cell populations. However, due to the high noise and high dimensionality of scRNA-seq data, improving the effectiveness of cell type identification remains a challenge. As an effective dimensionality reduction method, Principal Component Analysis (PCA) is an essential tool for visualizing high-dimensional scRNA-seq data and identifying cell subpopulations. However, traditional PCA has some defects when used in mining the nonlinear manifold structure of the data and usually suffers from over-density of principal components (PCs). Therefore, we present a novel method in this paper called joint L2,p-norm and random walk graph constrained PCA (RWPPCA). RWPPCA aims to retain the data's local information in the process of mapping high-dimensional data to low-dimensional space, to more accurately obtain sparse principal components and to then identify cell types more precisely. Specifically, RWPPCA combines the random walk (RW) algorithm with graph regularization to more accurately determine the local geometric relationships between data points. Moreover, to mitigate the adverse effects of dense PCs, the L2,p-norm is introduced to make the PCs sparser, thus increasing their interpretability. Then, we evaluate the effectiveness of RWPPCA on simulated data and scRNA-seq data. The results show that RWPPCA performs well in cell type identification and outperforms other comparison methods.

Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance.

BACKGROUND: Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome. RESULTS: We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data. CONCLUSIONS: The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.

The Quartet Data Portal: integration of community-wide resources for multiomics quality control.

The Quartet Data Portal facilitates community access to well-characterized reference materials, reference datasets, and related resources established based on a family of four individuals with identical twins from the Quartet Project. Users can request DNA, RNA, protein, and metabolite reference materials, as well as datasets generated across omics, platforms, labs, protocols, and batches. Reproducible analysis tools allow for objective performance assessment of user-submitted data, while interactive visualization tools support rapid exploration of reference datasets. A closed-loop "distribution-collection-evaluation-integration" workflow enables updates and integration of community-contributed multiomics data. Ultimately, this portal helps promote the advancement of reference datasets and multiomics quality control.

Development and validation of a differentiation-related signature based on single-cell RNA sequencing data of immune cells in spinal cord injury.

Background: After spinal cord injury (SCI), the native immune surveillance function of the central nervous system is activated, resulting in a substantial infiltration of immune cells into the affected tissue. While numerous studies have explored the transcriptome data following SCI and revealed certain diagnostic biomarkers, there remains a paucity of research pertaining the identification of immune subtypes and molecular markers related to the immune system post-spinal cord injury using single-cell sequencing data of immune cells. Methods: The researchers conducted an analysis of spinal cord samples obtained at three time points (3,10, and 21 days) following SCI using the GSE159638 dataset. The SCI subsets were delineated through pseudo-time analysis, and differentiation related genes were identified after principal component analysis (PCA), cell clustering, and annotation techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were employed to assess the differentiation-related genes (DRGs) across different subsets. The molecular subtypes of SCI were determined using consensus clustering analysis. To further explore and validate the correlation between the molecular subtypes and the immune microenvironment, the CIBERSORT algorithm was employed. High-value diagnostic gene markers were identified using LASSO regression, and their diagnostic sensitivity was assessed using receiver operating characteristic curves (ROC) and quantitative real-time polymerase chain reaction (qRT-PCR). Results: Three SCI subsets were obtained, and differentiation-related genes were characterized. Within these subsets, two distinct molecular subtypes, namely C1 and C2, were identified. These subtypes demonstrated significant variations in terms of immune cell infiltration levels and the expression of immune checkpoint genes. Through further analysis, three candidate biomarkers (C1qa, Lgals3 and Cd63) were identified and subsequently validated. Conclusions: Our study revealed a diverse immune microenvironment in SCI samples, highlighting the potential significance of C1qa, Lgals3 and Cd63 as immune biomarkers for diagnosing SCI. Moreover, the identification of immune checkpoints corresponding to the two molecular subtypes suggests their potential as targets for immunotherapy to enhance SCI repair in future interventions.

Wearing individualized 3D printed oral stent to protect normal tissues in patients with nasopharyngeal carcinoma during radiotherapy.

PURPOSE: To demonstrate a new individualized 3D printed oral stent in radiotherapy of nasopharyngeal carcinoma (NPC) patients and carry out a comparative analysis combining with clinical case. MATERIAL AND METHODS: Thirty NPC patients treated in our institution from September 2021 to October 2022 were prospectively enrolled. An individualized 3D printed oral stent was designed for each patient, and one set of computed tomography (CT) slices were obtained with /without wearing the oral stent, respectively. After delineation of target volumes and organs at risk (OARs) on the two CT slices, we finished two treatment plans by using the same target objectives, critical constraints and plan setup for each patient. Finally, the dose distribution and other dosimetric parameters of target volumes and OARs between the two plans were compared. RESULTS: Tongue volume and tongue length outside of mouth was 10.4 ± 2.5 cm3 and 2.8 ± 0.6 cm, respectively, distance between dorsal surface of oral tongue and plate increased from 0.3 ± 0.3 cm to 2.2 ± 0.5 cm by wearing the oral stent. For the target volume, there was no significant difference. However, Dmax of tongue, tongue tip and periglottis decreased significantly from 6352.6 ± 259.9 cGy to 5994.9 ± 478.9 cGy, 3499.8 ± 250.6 cGy to 3357.7 ± 158.0 cGy and 6345.5 ± 171.0 cGy to 6133.4 ± 263.3 cGy, respectively (p = 0.000); Dmean of tongue, tongue tip and periglottis decreased significantly from 3714.7 ± 204.2 cGy to 3169.7 ± 200.9 cGy, 3060.8 ± 216.2 cGy to 2509.6 ± 196.7 cGy and 3853.3 ± 224.9 cGy to 3079.3 ± 222.0 cGy, respectively (p = 0.000). CONCLUSION: The individualized 3D printed oral stent can reduce the dose of oral tissues and organs, so as to reduce the oral adverse reactions and improve the compliance of patients and the quality of their life. The technique can be used in radiotherapy of NPC patients.

Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling.

Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect intrinsically small biological differences in clinical settings, such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multi-omics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two samples, providing cross-platform and cross-laboratory 'ground truth'. Investigation of the intrinsically subtle biological differences among the Quartet samples enables sensitive assessment of cross-batch integration of transcriptomic measurements at the ratio level. The Quartet RNA reference materials, combined with the ratio-based reference datasets, can serve as unique resources for assessing and improving the quality of transcriptomic data in clinical and biological settings.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials.

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Comparison of efficacy between unilateral biportal endoscopic lumbar fusion versus minimally invasive transforaminal lumbar fusion in the treatment of lumbar degenerative diseases: A systematic review and meta-analysis.

BACKGROUND: To evaluate the clinical efficacy and prognosis of unilateral biportal endoscopic lumbar fusion (ULIF) and minimally invasive transforaminal lumbar fusion (MIS-TLIF) for lumbar degenerative diseases. METHODS: Chinese and English databases were retrieved for the period from database creation to December 31, 2022. Case-control studies on unilateral biportal endoscopic lumbar fusion were collected. The observation indexes consisted of operation times, intraoperative blood loss, postoperative drainage volume, length of hospital stay, postoperative pain score, postoperative oswestry disability index score, postoperative MacNab excellent and good rate, imaging fusion rate at the last follow-up, and complications. The NO rating table was employed to assess the quality of the included literature, and a meta-analysis was conducted using Revman5.4.1 and Stata17. RESULTS: Ten studies with 738 surgical patients were considered, including 347 patients in the ULIF group and 391 in the MIS-TLIF group. This Meta-analysis demonstrated statistically significant differences in mean operation duration, intraoperative blood loss, postoperative drainage volume, length of hospital stay, and early postoperative (1-2W) visual analogue scale/score (VAS) scores for back pain. No significant differences were observed in the final follow-up postoperative VAS scores for back pain, postoperative leg VAS score, postoperative oswestry disability index score, excellent and good rate of postoperative modified MacNab, imaging fusion rate, and complications. CONCLUSION: Compared with the MIS-TLIF group, the ULIF group had longer operation time, lower intraoperative blood loss and postoperative drainage volume, lower lumbar VAS score in the early postoperative period, and shorter hospital stay. ULIF is less invasive than traditional MIS-TLIF, making it a trustworthy surgical option for lumbar degenerative diseases with comparable fusion efficiency, superior MacNab rate, and complication rate.

Predictive factors for cerebrocardiac syndrome in patients with severe traumatic brain injury: a retrospective cohort study.

Background and objective: Cerebrocardiac syndrome (CCS) is a severe complication of severe traumatic brain injury (sTBI) that carries high mortality and disability rates. Early identification of CCS poses a significant clinical challenge. The main objective of this study was to investigate potential risk factors associated with the development of secondary CCS in patients with sTBI. It was hypothesized that elevated right heart Tei index (TI), lower Glasgow Coma Scale (GCS) scores, and elevated cardiac troponin-I (cTnI) levels would independently contribute to the occurrence of CCS in sTBI patients. Methods: A retrospective cohort study was conducted to identify risk factors for CCS secondary to sTBI. One hundred and fifty-five patients were enrolled with sTBI admitted to the hospital between January 2016 and December 2020 and divided them into a CCS group (n = 75) and a non-CCS group (n = 80) based on the presence of CCS. This study involved the analysis and comparison of clinical data from two patient groups, encompassing demographic characteristics, peripheral oxygen saturation (SPO2), neuron-specific enolase (NSE), cardiac troponin-I (cTnI), N-terminal pro-brain natriuretic peptide (NT-proBNP), optic nerve sheath diameter (ONSD), cardiac ultrasound, acute physiology and chronic health evaluation (APACHE II) scores, and GCS scores and so on. Multivariate logistic regression was employed to identify independent risk factors for CCS, and receiver operating characteristic (ROC) curves were used to assess their predictive value for CCS secondary to sTBI. Results: The study revealed that 48.4% of sTBI patients developed secondary CCS. In the multivariate analysis model 1 that does not include NT-proBNP and cTnI, ONSD (OR = 2.582, 95% CI: 1.054-6.327, P = 0.038), right heart Tei index (OR = 2.81, 95% CI: 1.288-6.129, P = 0.009), and GCS (OR = 0.212, 95% CI: 0.086-0.521, P = 0.001) were independent risk factors for secondary CCS in sTBI patients. In multivariate analysis model 2 that includes NT-proBNP and cTnI, cTnI (OR = 27.711, 95%CI: 3.086-248.795, P = 0.003), right heart Tei index (OR = 2.736, 95% CI: 1.056-7.091, P = 0.038), and GCS (OR = 0.147, 95% CI: 0.045-0.481, P = 0.002) were independent risk factors for secondary CCS in sTBI patients. The area under the ROC curve for ONSD, Tei index, GCS, and cTnI were 0.596, 0.613, 0.635, and 0.881, respectively. ONSD exhibited a positive predictive value (PPV) of 0.704 and a negative predictive value (NPV) of 0.634. The Tei index demonstrated a PPV of 0.624 and an NPV of 0.726, while GCS had a PPV of 0.644 and an NPV of 0.815. On the other hand, cTnI exhibited a significantly higher PPV of 0.936 and an NPV of 0.817. These findings indicate that the Tei index, GCS score, and cTnI possess certain predictive value for secondary CCS in patients with sTBI. Conclusions: The study provides valuable insights into the identification of independent risk factors for CCS secondary to sTBI. The findings highlight the significance of right heart Tei index, GCS score, and cTnI as potential predictive factors for CCS in sTBI patients. Further larger-scale studies are warranted to corroborate these findings and to provide robust evidence for the development of early intervention strategies aimed at reducing the incidence of CCS in this patient population.

NLRRC: A Novel Clustering Method of Jointing Non-Negative LRR and Random Walk Graph Regularized NMF for Single-Cell Type Identification.

The development of single-cell RNA sequencing (scRNA-seq) technology has opened up a new perspective for us to study disease mechanisms at the single cell level. Cell clustering reveals the natural grouping of cells, which is a vital step in scRNA-seq data analysis. However, the high noise and dropout of single-cell data pose numerous challenges to cell clustering. In this study, we propose a novel matrix factorization method named NLRRC for single-cell type identification. NLRRC joins non-negative low-rank representation (LRR) and random walk graph regularized NMF (RWNMFC) to accurately reveal the natural grouping of cells. Specifically, we find the lowest rank representation of single-cell samples by non-negative LRR to reduce the difficulty of analyzing high-dimensional samples and capture the global information of the samples. Meanwhile, by using random walk graph regularization (RWGR) and NMF, RWNMFC captures manifold structure and cluster information before generating a cluster allocation matrix. The cluster assignment matrix contains cluster labels, which can be used directly to get the clustering results. The performance of NLRRC is validated on simulated and real single-cell datasets. The results of the experiments illustrate that NLRRC has a significant advantage in single-cell type identification.

Differences of molecular events driving pathological and radiological progression of lung adenocarcinoma.

BACKGROUND: Ground-glass opacity (GGO)-like lung adenocarcinoma (LUAD) has been detected increasingly in the clinic and its inert property and superior survival indicate unique biological characteristics. However, we do not know much about them, which hampers identification of key reasons for the inert property of GGO-like LUAD. METHODS: Using whole-exome sequencing and RNA sequencing, taking into account both radiological and pathological classifications of the same 197 patients concomitantly, we systematically interrogate genes driving the progression from GGO to solid nodule and potential reasons for the inertia of GGO. Using flow cytometry and IHC, we validated the abundance of immune cells and activity of cell proliferation. FINDINGS: Identifying the differences between GGO and solid nodule, we found adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA) and GGO-like LUAD exhibited lower TP53 mutation frequency and less active cell proliferation-related pathways than solid nodule in LUAD. Identifying the differences in GGO between AIS/MIA and LUAD, we noticed that EGFR mutation frequency and CNV load were significantly higher in LUAD than in AIS/MIA. Regulatory T cell was also higher in LUAD, while CD8+ T cell decreased from AIS/MIA to LUAD. Finally, we constructed a transcriptomic signature to quantify the development from GGO to solid nodule, which was an independent predictor of patients' prognosis in 11 external LUAD datasets. INTERPRETATION: Our results provide deeper insights into the indolent nature of GGO and provide a molecular basis for the treatment of GGO-like LUAD. FUNDING: This study was supported in part by the National Natural Science Foundation of China (32170657), the National Natural Science Foundation of China (82203037), and Shanghai Sailing Program (22YF1408900).

LC/MS- and GC/MS-based metabolomic profiling to determine changes in flavor quality and bioactive components of Phlebopus portentosus under low-temperature storage.

Introduction: Low temperature is the most common method used to maintain the freshness of Phlebopus portentosus during long-distance transportation. However, there is no information regarding the nutritional changes that occur in P. portentosus preserved postharvest in low temperature. Methods: In this study, the changes in flavor quality and bioactive components in fruiting bodies stored at 4 °C for different storage periods were determined through LC/MS and GC/MS analyses. Sampling was performed at 0, 3, 5, 7, and 13 days storage. Results and Discussion: Based on the results, the metabolites present in caps and stipes were different at the same period and significantly different after 7 days of storage. A total of 583 and 500 different metabolites were detected in caps and stipes, respectively, and were mainly lipids and lipid-like molecules, organic acids and derivatives, organic oxygen compounds and others. Except for prenol lipids and nucleotides, the expression levels of most metabolites increased with longer storage time. In addition, geosmin was identified as the major contributor to earthy-musty odors, and the level of geosmin was increased when the storage time was short. Conclusion: The variations in these metabolites might cause changes in flavor quality and bioactive components in P. portentosus. Variations in these metabolites were thoroughly analyzed, and the results revealed how storage processes affect the postharvest quality of P. portentosus for the first time.

ARGLRR: A Sparse Low-Rank Representation Single-Cell RNA-Sequencing Data Clustering Method Combined with a New Graph Regularization.

The development of single-cell transcriptome sequencing technologies has opened new ways to study biological phenomena at the cellular level. A key application of such technologies involves the employment of single-cell RNA sequencing (scRNA-seq) data to identify distinct cell types through clustering, which in turn provides evidence for revealing heterogeneity. Despite the promise of this approach, the inherent characteristics of scRNA-seq data, such as higher noise levels and lower coverage, pose major challenges to existing clustering methods and compromise their accuracy. In this study, we propose a method called Adjusted Random walk Graph regularization Sparse Low-Rank Representation (ARGLRR), a practical sparse subspace clustering method, to identify cell types. The fundamental low-rank representation (LRR) model is concerned with the global structure of data. To address the limited ability of the LRR method to capture local structure, we introduced adjusted random walk graph regularization in its framework. ARGLRR allows for the capture of both local and global structures in scRNA-seq data. Additionally, the imposition of similarity constraints into the LRR framework further improves the ability of the proposed model to estimate cell-to-cell similarity and capture global structural relationships between cells. ARGLRR surpasses other advanced comparison approaches on nine known scRNA-seq data sets judging by the results. In the normalized mutual information and Adjusted Rand Index metrics on the scRNA-seq data sets clustering experiments, ARGLRR outperforms the best-performing comparative method by 6.99% and 5.85%, respectively. In addition, we visualize the result using Uniform Manifold Approximation and Projection. Visualization results show that the usage of ARGLRR enhances the separation of different cell types within the similarity matrix.

Genetic diversity, antibiotic resistance, and virulence characteristics of Staphylococcus aureus from raw milk over 10 years in Shanghai.

Staphylococcus aureus (S. aureus) is a major cause of foodborne infections and its persistence in raw milk is a multifaceted phenomenon that poses a considerable public health challenge. Our study investigated the prevalence, virulence genes, antibiotic resistance, and genetic characterization of S. aureus in raw milk in six Shanghai districts from 2013 to 2022. At 18 dairy farms, a total of 704 S. aureus strains were isolated from 1799 samples tested for drug sensitivity. The highest rates of antibiotic resistance were ampicillin (96.7 %), sulfamethoxazole (65 %), and erythromycin (21.6 %). Between 2018 and 2022, there was a significant decrease in the resistance rates of ceftiofur, ofloxacin, tilmicosin, erythromycin, clindamycin, amoxicillin-clavulanic acid, and sulfamethoxazole in comparison to the period from 2013 to 2017. There were 205 S. aureus strains chosen for whole genome sequencing (WGS), with no more than 2 strains of the same resistance phenotype from each farm per year. The prevalence of mecA-positive strains was 14.15 %, while other antibiotic resistance-associated genes were observed as follows: blaI (70.21 %), lnu(B) (5.85 %), lsa(E) (5.75 %), fexA (6.83 %), erm(C) (4.39 %), tet(L) (9.27 %), and dfrG (5.85 %). Isolates harboring the immune evasion cluster (IEC) genes (scn, chp, and sak) were predominantly categorized as sequence types (STs) 7, 188, 15, 59, and 398. The predominant cluster complexes were CC97, CC1, CC398, and CC1651. In 2017-2022, there was a transition in CC1 from the highly antibiotic-resistant ST9 strain that emerged between 2013 and 2018 to the low-resistant but highly virulent ST1 strain. Retrospective phylogenetic analysis elucidated the evolutionary history of the isolates and demonstrated that the human-animal host transition of S. aureus was linked to the genesis of MRSA CC398. The implementation of extended surveillance will aid in the development of innovative strategies to avoid the transmission of S. aureus along the dairy food chain and the occurrence of public health events.

Comprehensive analysis of a pyroptosis-related gene signature of clinical and biological values in spinal cord injury.

Background: Since some of the clinical examinations are not suitable for patients with severe spinal cord injury (SCI), blood biomarkers have been reported to reflect the severity of SCI. The objective of this study was to screen out the potential biomarkers associated with the diagnosis of SCI by bioinformatics analysis. Methods: The microarray expression profiles of SCI were obtained from the Gene Expression Omnibus (GEO) database. Core genes correlated to pyroptosis were obtained by crossing the differential genes, and module genes were obtained by WGCNA analysis and lasso regression. The immune infiltration analysis and GSEA analysis revealed the essential effect of immune cells in the progression of SCI. In addition, the accuracy of the biomarkers in diagnosing SCI was subsequently evaluated and verified using the receiver operating characteristic curve (ROC) and qRT-PCR. Results: A total of 423 DEGs were identified, among which 319 genes were upregulated and 104 genes were downregulated. Based on the WGCNA analysis, six potential biomarkers were screened out, including LIN7A, FCGR1A, FGD4, GPR27, BLOC1S1, and GALNT4. The results of ROC curves demonstrated the accurate value of biomarkers related to SCI. The immune infiltration analysis and GSEA analysis revealed the essential effect of immune cells in the progression of SCI, including macrophages, natural killer cells, and neutrophils. The qRT-PCR results verified that FGD4, FCAR1A, LIN7A, BLOC1S1, and GPR27 were significantly upregulated in SCI patients. Conclusion: In this study, we identified and verified five immune pyroptosis-related hub genes by WGCNA and biological experiments. It is expected that the five identified potential biomarkers in peripheral white blood cells may provide a novel strategy for early diagnosis.