Objective To explore the role of DNAJC5B in immunotherapy for esophageal squamous cell carcinoma (ESCC). Methods Using the ESCC dataset from The Cancer Genome Atlas (TCGA) database, genes correlated with DNAJC5B expression were identified through Pearson correlation analysis. Subsequently, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Additionally, single-cell RNA sequencing (scRNA-seq) data were utilized to analyze the expression of DNAJC5B in different T-cell subsets. The prognostic value of DNAJC5B was evaluated using Kaplan-Meier survival curves, receiver operating characteristic curves, and Cox proportional hazards models. Results DNAJC5B was highly expressed in patients with advanced-stage ESCC, particularly in males. GO and KEGG analyses revealed a significant correlation between DNAJC5B expression and immune-related processes, such as the adaptive immune response and cell surface receptor signaling pathways. Single-cell analysis results indicated that DNAJC5B expression was positively correlated with immune function, with DNAJC5B predominantly accumulating in CD8+ T cells. Kaplan-Meier survival curves showed that the median survival time for patients with high DNAJC5B expression was 681 days, significantly shorter than the 1 361 days for patients with low expression (P<0.05). Furthermore, univariate and multivariate independent prognostic analyses demonstrated that DNAJC5B was an independent risk factor, with hazard ratios (HRs) of 3.577 and 4.114, respectively (both P<0.05). Conclusion DNAJC5B may play a crucial immunomodulatory role in ESCC, particularly in regulating CD8+ T-cell function and tumor immune escape. These findings support the potential of DNAJC5B as a biomarker for the treatment and prognostic assessment of ESCC.

Accurate prediction of drug responses in cancer cell lines(CCLs)and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine.Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response(CDR)prediction,chal-lenges remain regarding the generalization of new drugs that are unseen in the training set.Herein,we propose a multimodal fusion deep learning(DL)model called drug-target and single-cell language based CDR(DTLCDR)to predict preclinical and clinical CDRs.The model integrates chemical descriptors,mo-lecular graph representations,predicted protein target profiles of drugs,and cell line expression profiles with general knowledge from single cells.Among these features,a well-trained drug-target interaction(DTI)prediction model is used to generate target profiles of drugs,and a pretrained single-cell language model is integrated to provide general genomic knowledge.Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods.Further ablation studies verified the effectiveness of each component of our model,highlighting the significant contribution of target information to generalizability.Subsequently,the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments,demonstrating its potential for real-world applications.Moreover,DTLCDR was transferred to the clinical datasets,demonstrating satisfactory performance in the clinical data,regardless of whether the drugs were included in the cell line dataset.Overall,our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

Immune dysregulation is a critical factor in the pathogenesis of inflammatory bowel disease (IBD), and numerous studies have focused on the impact of immune cell metabolic pathways. Immune system cells dynamically adapt to the microenvironment, regulating the body's response to external stimuli through intricate metabolic pathways. This review summarizes the mechanisms by which glycolysis, fatty acid and amino acid metabolisms influence immune metabolism and thereby modulate IBD progression, offering new perspectives for the diagnosis and treatment of IBD.

Objective:To evaluate the characteristics of neutrophil extracellular traps (NET) in children with inflammatory bowel disease (IBD) and its role in diagnosis and disease activity monitoring.Methods:A total of 66 IBD children admitted to Beijing Children′s Hospital from December 2017 to August 2024 were enrolled in this cross-sectional study, another 20 age-matched children who underwent gastrointestinal endoscopy during the same period in the same hospital and showed no abnormalities were selected as the controls. Clinical data of IBD and control group were collected. Children with IBD were divided into active group and remission group according to clinical score and endoscopic score. The peripheral blood of IBD and control group were collected, and the levels of NET markers, including neutrophil elastase (NE) and myeloperoxidase (MPO)-DNA were detected by enzyme-linked immunosorbent assay. The levels of NET markers in control group and different IBD groups were compared. Independent sample t-test or Mann-Whitney U test was used for group comparisons. Kruskal-Wallis H test was used for multiple group comparisons. Spearman correlation analysis was used to analyze the correlation between NET markers and IBD activity. The efficacy of laboratory indicators in diagnosing IBD and control group was evaluated using receiver operating characteristic (ROC) curve. Results:There were 66 children with IBD, including 36 in Crohn′s disease group with the age of (11.0±3.7) years, and 30 in ulcerative colitis (UC) group with the age of (8.3±5.0) years. The control group consisted of 20 children with the age of (10.1±3.5) years. Compared with control group, the levels of NE (958 (771, 1 328) vs. 303 (196, 501) μg/L) and MPO-DNA (0.11 (0.09, 0.18) vs. 0.09 (0.06, 0.12)) in peripheral blood of IBD group were significantly higher (both P<0.05). However, there was no significant difference in the levels of NE (1 008 (863, 1 301) vs. 807 (567, 1 535) μg/L) and MPO-DNA (0.11 (0.09, 0.21) vs. 0.12 (0.09, 0.14)) between Crohn′s disease and UC groups (both P>0.05). The NE levels in the endoscopic active group and remission group of Crohn's disease were higher than those in the control group (both P<0.05). The MPO-DNA level in the endoscopic active group of Crohn's disease was higher than that in the control group ( P<0.05), while the MPO-DNA level in the endoscopic remission group of Crohn's disease was lower than that in the control group ( P>0.05). The NE levels in the endoscopic activity group and remission group of UC were higher than those in control group (both P<0.05). NET markers were not correlated with the clinical activity and endoscopic activity of IBD (all P>0.05). ROC curve analysis showed that the area under the curve of NE combined with MPO-DNA for distinguishing IBD from controls was 0.95, with a sensitivity was 90.0% and a specificity was 89.4%. Conclusion:The combination of NE and MPO-DNA demonstrated high sensitivity and specificity for distinguishing pediatric IBD patients from healthy children, suggesting its potential as a diagnostic biomarker panel of IBD.

Objective To investigate the molecular targets and signaling pathways involved in the therapeutic effects of Lishukang Capsule(LSK)in a rat model of high-altitude pulmonary edema(HAPE)using a proteomics-based approach.Methods A total of 60 male Wistar rats were randomly assigned to a control group,a HAPE model group,3 LSK treatment groups receiving low-,medium-,and high-dose LSK,respectively,and a Rhodiola rosea(also known as Hongjitian[HJT]in pinyin,a Chinese Romanization system)control group.After HAPE modeling,the pharmacodynamic effects were assessed and the optimal LSK dose was determined using HE stains,inflammatory cytokine quantification,lung tissue water content,and the protein concentration in bronchoalveolar lavage.Label free quantitative proteomic profiling was then applied to identify differentially expressed proteins(DEPs)in the optimal dose group,using a screening threshold of over 1.5-fold change and P<0.05.The selected DEPs were validated with Western blotting,followed by Gene Ontology(GO)enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Results The medium-dose LSK group exhibited significant anti-HAPE effects.Findings from the proteomic analysis revealed,in the comparison with the control group,267 DEPs were identified in the HAPE group.In the comparison with the HAPE group,225 DEPs were identified in the medium-dose LSK group.A total of 112 DEPs in the control group were normalized following LSK treatment in the medium-dose LSK group.In addition,GO enrichment analysis of proteins differentially expressed between the HAPE and LSK group showed that these DEPs were mainly enriched in 12 biological processes,2 cellular components,and 5 molecular functions.KEGG pathway analysis showed that LSK activated pathways associated with cell adhesion molecules,glycosaminoglycan biosynthesis,DNA replication/nucleotide excision repair,transcriptional dysregulation in cancer,and Herpes simplex virus type 1(HSV-1)infection,while inhibiting pathways associated with glycerophospholipid metabolism.Some differentially expressed proteins with potential functions were verified by Western blotting,including AGPAT5,NCAM1,SRSF3,and PLA2.These differentially expressed proteins were significantly expressed in the normal group,HAPE group,and LSK group,and the validation results were consistent with proteomic findings,indicating the high reliability of the proteomic results.Conclusion LSK exerts a significant protective effect against HAPE.Proteomic analysis suggests that its therapeutic action may be mediated through activating pathways involved in cell adhesion molecules,glycosaminoglycan biosynthesis,DNA replication/nucleotide excision repair,transcriptional dysregulation in cancer,and HSV-1 infection,alongside inhibition of pathways associated with glycerophospholipid metabolism.The key DEPs identified in these pathways may play crucial roles in the preventive and therapeutic effects of LSK on HAPE.

Mitochondrial dysfunction in chondrocytes is a key pathogenic factor in osteoarthritis (OA), but directly modulating mitochondria in vivo remains a significant challenge. This study is the first to verify a correlation between mitochondrial dysfunction and the downregulation of the FOXO3 gene in the cartilage of OA patients, highlighting the potential for regulating mitophagy via FOXO3 gene modulation to alleviate OA. Consequently, we developed a chondrocyte-targeting CRISPR/Cas9-based FOXO3 gene-editing tool (FoxO3) and integrated it within a nanoengineered 'truck' (NETT, FoxO3-NETT). This was further encapsulated in injectable hydrogel microspheres (FoxO3-NETT@SMs) to harness the antioxidant properties of sodium alginate and the enhanced lubrication of hybrid exosomes. Collectively, these FoxO3-NETT@SMs successfully activate mitophagy and rebalance mitochondrial function in OA chondrocytes through the Foxo3 gene-modulated PINK1/Parkin pathway. As a result, FoxO3-NETT@SMs stimulate chondrocytes proliferation, migration, and ECM production in vitro, and effectively alleviate OA progression in vivo, demonstrating significant potential for clinical applications.

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

This study summarizes the nursing experience of an elderly patient who developed Takotsubo syndrome following mitral valve replacement surgery.Key nursing points include:close monitoring of electrocardiogram and myocardial enzyme spectrum changes for early identification of Takotsubo syndrome;implementation of a multi-dimensional collaborative circulatory support strategy;establishment of a triadic psychological intervention model comprising"environment-communication-family support"to prevent the exacerbation of Takotsubo syndrome based on stressor management;application of multimodal early rehabilitation interventions to shorten mechanical ventilation duration.After meticulous treatment and care,the left ventricular ejection fraction(LVEF)of the patient improved to 46％on postoperative day 12.There were no occurrences of malignant arrhythmias or multiple organ dysfunction.On postoperative day 16,the patient was transferred to a general ward for continued specialized treatment,and on postoperative day 22,the patient was successfully discharged after rehabilitation.

Inflammatory bowel disease（IBD）is a type of disease characterized by chronic intestinal inflammation，mainly including Crohn's disease，ulcerative colitis，and undifferentiated IBD. Its pathogenesis is very complex and involves multiple factors. In recent years，studies have shown that heat shock proteins（HSPs）and cell apoptosis play important roles in the occurrence and progression of IBD. HSPs not only participate in cellular stress response，but also play a crucial role in regulating cell apoptosis. The specific mechanism of the interaction between HSPs and apoptosis in IBD is currently unclear. This article reviews the relationship and mechanism between HSPs and apoptosis in the occurrence and development of IBD，explores the roles of HSPs and apoptosis in IBD，and proposes potential treatment strategies to provide more effective treatment options for IBD patients in the future.

Objective:To investigate the relationship between nerve growth factor (NGF) concentration in follicular fluid and abnormal menstrual cycle in infertile patients with polycystic ovary syndrome (PCOS).Methods:A retrospective cohort study was conducted on 100 infertile patients with PCOS who underwent in vitro fertilization and embryo transfer (IVF-ET) at Department of Obstetrics and Gynecology, Peking University Third Hospital from March 2017 to June 2019. For comparison, the 100 patients with PCOS were divided into low NGF group ( n=50) and high NGF group ( n=50) based on the median NGF concentration (1 644.03 ng/L) in follicular fluid. Baseline characteristics, menstrual status and clinical outcomes of assisted reproductive technology were compared. We performed multiple linear regression analysis to examine the effect of NGF in follicular fluid on menstrual cycle length for multivariate analysis. Results:1) PCOS patients in the low NGF group had significantly higher body mass index [(27.24±5.17) kg/m 2] and white blood cell count [7.31(5.99, 8.43)×10 9/L ] than those in the high NGF group [(25.03±4.46) kg/m 2, P=0.024; 5.95(5.08,7.01)×10 9/L, P=0.001], while high-density lipoprotein cholesterol [1.15 (0.98, 1.36) mmol/L] and basic follicle-stimulating hormone level [6.51 (5.10,7.95) U/L] in the low NGF group were significantly lower than those in the high NGF group [1.36 (1.09,1.52) mmol/L, P=0.039;6.51 (5.10,7.95)U/L, P=0.040]. 2) PCOS patients in the low NGF group had significantly higher menstrual cycle length [60.00 (35.00, 180.00) d] than the high NGF group [32.50 (27.00,67.50) d, P=0.001]. 3) Multiple linear regression analysis revealed that after adjustment for body mass index, age, infertility duration, infertility type, and glucose and lipid metabolic parameters, the NGF concentration in the follicular fluid independently and negatively correlated with menstrual cycle length ( P<0.05). 4) The NGF concentration in follicular fluid was not correlated with assisted reproductive outcomes. Conclusion:NGF concentration in follicular fluid is closely related to the degree of menstrual cycle abnormalities in patients with PCOS.