Single-cell low-pass whole genome sequencing accurately detects circulating tumor cells for liquid biopsy-based multi-cancer diagnosis.

Accurate detection of circulating tumor cells (CTCs) in blood and non-blood body fluids enables generation of deterministic cancer diagnosis and represent a less invasive and safer liquid biopsy approach. Although genomic alternations have been widely used in circulating tumor DNA (ctDNA) analysis, studies on cell-based genomic alternations profiling for CTC detection are rare due to major technical limitations in single-cell whole genome sequencing (WGS) including low throughput, low accuracy and high cost. We report a single-cell low-pass WGS-based protocol (scMet-Seq) for sensitive and accurate CTC detection by combining a metabolic function-associated marker Hexokinase 2 (HK2) and a Tn5 transposome-based WGS method with improved cell fixation strategy. To explore the clinical use, scMet-Seq has been investigated with blood and non-blood body fluids in diagnosing metastatic diseases, including ascites-based diagnosis of malignant ascites (MA) and blood-based diagnosis of metastatic small-cell lung cancer (SCLC). ScMet-Seq shows high diagnostic sensitivity (MA: 79% in >10 cancer types; metastatic SCLC: 90%) and ~100% of diagnostic specificity and positive predictive value, superior to clinical cytology that exhibits diagnostic sensitivity of 52% in MA diagnosis and could not generate blood-based diagnosis. ScMet-Seq represents a liquid biopsy approach for deterministic cancer diagnosis in different types of cancers and body fluids.

Improved YOLOv7-based steel surface defect detection algorithm.

In response to the limited detection ability and low model generalization ability of the YOLOv7 algorithm for small targets, this paper proposes a detection algorithm based on the improved YOLOv7 algorithm for steel surface defect detection. First, the Transformer-InceptionDWConvolution (TI) module is designed, which combines the Transformer module and InceptionDWConvolution to increase the network's ability to detect small objects. Second, the spatial pyramid pooling fast cross-stage partial channel (SPPFCSPC) structure is introduced to enhance the network training performance. Third, a global attention mechanism (GAM) attention mechanism is designed to optimize the network structure, weaken the irrelevant information in the defect image, and increase the algorithm's ability to detect small defects. Meanwhile, the Mish function is used as the activation function of the feature extraction network to improve the model's generalization ability and feature extraction ability. Finally, a minimum partial distance intersection over union (MPDIoU) loss function is designed to locate the loss and solve the mismatch problem between the complete intersection over union (CIoU) prediction box and the real box directions. The experimental results show that on the Northeastern University Defect Detection (NEU-DET) dataset, the improved YOLOv7 network model improves the mean Average precision (mAP) performance by 6% when compared to the original algorithm, while on the VOC2012 dataset, the mAP performance improves by 2.6%. These results indicate that the proposed algorithm can effectively improve the small defect detection performance on steel surface defects.

DJ-1: A Potential Biomarker Related to Prognosis, Chemoresistance, and Expression of Microenvironmental Chemokine in HR-Positive Breast Cancer.

DJ-1 is significantly elevated in various malignancies. However, the clinical significance of DJ-1 in hormone receptor (HR)-positive (HR+) breast cancer remains unclear. We evaluated DJ-1 expression in different databases and validated in vitro assay by RT-PCR and western blot among HR+ breast cancer. The correlations between DJ-1 level and tumor-immune were calculated. Mutational landscape, enriched signaling pathways, and drug sensitivity analyses were also assessed between DJ-1 high and low-expression groups. DJ-1 was upregulated in HR+ breast cancer, and high DJ-1 expression was significantly linked with poor prognosis. DJ-1 was correlated with the expression and function of different immune cells. The low DJ-1 group showed sensitivity to paclitaxel and docetaxel, while the high-expression group showed sensitivity to doxorubicin. CTLA4 and PD-L1 were more sensitive in high-DJ-1 group. It is involved in a range of pathways and might behave as a novel biomarker of prognostic value for the immune environment and drug sensitivity in HR+ breast cancer.

RNA-Seq and 16S rRNA Reveals That Tian-Dong-Tang-Gan Powder Alleviates Environmental Stress-Induced Decline in Immune and Antioxidant Function and Gut Microbiota Dysbiosis in Litopenaeus vannami.

Ammonia stress and nitrite stress can induce immune depression and oxidative stress in Litopenaeus vannami (L. vannamei). Earlier reports showed that L. vannamei immunity, resistance to ammonia stress, and resistance to nitrite stress improved after Tian-Dong-Tang-Gan Powder (TDTGP) treatment, but the mechanism is not clear. In this study, three thousand L. vannamei were fed different doses of TDTGP for 35 days and then subjected to ammonia and nitrite stress treatments for 72 h. Transcriptome and 16-Seq ribosomal RNA gene sequencing (16S rRNA-seq) were used to analyze hepatopancreas gene expression and changes in gut microbiota abundance in each group. The results showed that after TDTGP treatment, hepatopancreas mRNA expression levels of immunity- and antioxidant-related genes were increased, the abundance of Vibrionaceae in the gut microbiota was decreased, and the abundance of Rhodobacteraceae and Flavobacteriaceae was increased. In addition, after TDTGP treatment, the effects of ammonia and nitrite stress on the mRNA expression of Pu, cat-4, PPAF2, HO, Hsp90b1, etc. were reduced and the disruption of the gut microbiota was alleviated. In short, TDTGP can regulate the immunity and antioxidant of L. vannamei by increasing the expression levels of immunity- and antioxidant-related genes and regulating the abundance of Rhodobacteraceae and Flavobacteriaceae in the gut microbiota.

Construction and verification of a prognostic risk model based on immunogenomic landscape analysis of bladder caner.

This study was designed to construct a prognostic risk model to predict prognosis and immunotherapy response of bladder cancer (BCa) patinets. 350 differential expressed immune-related genes (DEIRGs) were obtained according to the transcriptome profiling and immune-related genes from the Cancer Genome Atlas (TCGA) database and ImmPort database, respectively. A prognostic risk model was constructed based on 15 hub genes through univariate, multivariate, and LASSO Cox regression analyses. The area under the receiver operating characteristic (ROC) curve was 0.743, indicating the superiority of the model. The scatter plot showed that as the risk score increased, the overall survival decreased significantly. In addition, all results were internally verified by the TCGA cohort. The model showed that the higher the grade, clinical stage, and TNM stage of BCa, the higher the risk score of patients. The tumor mutation burden of the low-risk group was generally higher than that of the high-risk group. Immune cell infiltration analysis showed that CD8 T cells, naive CD4 T cells, follicular helper T cells and M0 Macrophage were significantly different between the two groups. Several key immune checkpoint genes were found to be significantly different between the two groups, such as CTLA4, PD-L1, CD47, CD276, CXCL8, and HAVCR2/TIM3. Finally, the analysis of immunotherapy revealed that the efficacy of CTLA4 or PD1 blockers alone was better in the low-risk group than in the high-risk group. Taken together, we developed and validated a prognostic risk model based on 15 hub genes, which performed well in predicting prognosis and immunotherapy response of BCa patients.

JWA suppresses proliferation in trastuzumab-resistant breast cancer by downregulating CDK12.

Breast cancer is the most common cancer worldwide. JWA is a microtubule-associated protein that has been identified as a tumor suppressor, and its downregulation in tumors is an independent adverse prognostic factor. The objective of this study was to explore the expression, regulation, and mechanism of JWA in trastuzumab-resistant breast cancers. In this study, we found that JWA expression was lower in trastuzumab-resistant breast cancers than that in trastuzumab-sensitive breast cancers. Furthermore, it was confirmed that overexpression of JWA inhibited proliferation and promoted apoptosis in trastuzumab-resistant breast cancers both in vitro and in vivo. In addition, the low expression of JWA in trastuzumab-resistant breast cancers is associated with a poor prognosis. Combining RNA-sequence datasets and next-generation sequencing, it was found that JWA negatively regulated CDK12, and was involved in the G1-to-S transition of the cell cycle. It has been reported that CDK12 drives breast cancer initiation and induces trastuzumab resistance. Taken together, high expression of JWA could inhibit the growth of trastuzumab-resistant breast cancer, and JWA is a potential predictive marker for trastuzumab resistance. In addition, targeted therapy with JWA may be a novel therapeutic strategy to improve the survival rate of trastuzumab-resistant breast cancer.

Comprehensive description of the current breast cancer microenvironment advancements via single-cell analysis.

Breast cancer is a heterogeneous disease with a complex microenvironment consisting of tumor cells, immune cells, fibroblasts and vascular cells. These cancer-associated cells shape the tumor microenvironment (TME) and influence the progression of breast cancer and the therapeutic responses in patients. The exact composition of the intra-tumoral cells is mixed as the highly heterogeneous and dynamic nature of the TME. Recent advances in single-cell technologies such as single-cell DNA sequencing (scDNA-seq), single-cell RNA sequencing (scRNA-seq) and mass cytometry have provided new insights into the phenotypic and functional diversity of tumor-infiltrating cells in breast cancer. In this review, we have outlined the recent progress in single-cell characterization of breast tumor ecosystems, and summarized the phenotypic diversity of intra-tumoral cells and their potential prognostic relevance.

Ethyl acetate fraction of flavonoids from Polygonum hydropiper L. modulates pseudorabies virus-induced inflammation in RAW264.7 cells via the nuclear factor-kappa B and mitogen-activated protein kinase pathways.

Pseudorabies virus (PRV) infection leads to severe inflammatory responses and tissue damage, and many natural herbs exhibit protective effects against viral infection by modulating the inflammatory response. An ethyl acetate fraction of flavonoids from Polygonum hydropiper L. (FEA) was prepared through ethanol extraction and ethyl acetate fractional extraction. An inflammatory model was established in RAW264.7 cells with PRV infection to evaluate the anti-inflammatory activity of FEA by measuring cell viability, nitric oxide (NO) production, reactive oxygen species (ROS) release, and mRNA expression of inflammatory factors, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2). Its functional mechanism was investigated by analyzing the phosphorylation and nuclear translocation of key proteins in the nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) signaling pathways. Our findings indicate that PRV induced inflammatory responses in RAW264.7 cells, and the responses were similar to that in lipopolysaccharide (LPS)-stimulated cells. FEA significantly suppressed NO synthesis and down-regulated both expression and secretion of COX-2, iNOS, and inflammatory cytokines (P<0.05 or P<0.01). FEA also reduced NF-κB p65 translocation into the nucleus and decreased MAPK phosphorylation, indicating that the NF-κB/MAPK signaling pathway may be closely related to the inflammatory response during viral infection. The findings suggested the potential pharmaceutical application of FEA as a natural product that can treat viral infections due to its ability to mitigate inflammatory responses.

An analysis of factors influencing drinking relapse among patients with alcohol-induced psychiatric and behavioral disorders.

BACKGROUND: Patients with alcohol-induced psychiatric and behavioral disorders have higher drinking relapse rates after treatment when compared to those without these disorders. AIM: To investigate factors influencing drinking relapse among patients with alcohol-induced psychiatric and behavioral disorders and provide guidance for rehabilitative intervention for those being treated for substance use disorders. METHODS: Patients were randomly assigned into either the study group or the control group. We used Chi-square test to analyze their general demographics, drinking history, and hospitalizations. Factors influencing the relapse were analyzed by logistic regression analyses. RESULTS: The univariate analysis showed that factors included ethnicity, level of education, occupation, marital status, duration of psychiatric symptoms and deception about alcohol use; multivariate analysis showed that marital status, duration of psychiatric symptoms, and deception about alcohol use were correlated with relapse among patients with psychiatric and behavioral disorders. CONCLUSIONS: For patients who were single, psychiatric symptoms were more likely to occur between the first and fifth year of alcohol consumption, and those who were deceptive about their alcohol use were more likely to have a relapse than those who were not.

Electric field-induced translocation of single-stranded DNA through a polarized carbon nanotube membrane.

Molecular dynamics simulations based on a novel polarizable nanotube model were performed to study the dynamics in translocation of a single-stranded deoxyribonucleic acid oligonucleotide through a polarized carbon nanotube membrane by an applied electric field. The study revealed a nonlinear dependence of translocation velocity and an inverse quadratic dependence of translocation time on the electric field strength, as well as a threshold electric field below which the translocation process becomes impossible. The translocation rate was found to be pore-size dependent. The polarizable nanotube model developed for this study provides a useful platform for investigating the dynamics of a range of bionanosystems.