Background: Chinese herbal pieces are an essential component of traditional Chinese medicine. Accurate identification and classification of these materials are crucial in clinical practice. Objective: This study aims to enhance the recognition efficiency of Chinese herbal pieces using deep learning technology, while addressing the limitations of traditional manual classification methods in terms of both quality and efficiency. Methods: A comprehensive dataset containing 201 types of Chinese herbal pieces was established. Based on Real-time Detection Transformer (RT-DETR), we designed and integrated a Feature-focused Diffusion Network (FDN), resulting in an improved model termed RT-DETR-FDN. The proposed FDN includes a Feature-focus Module and a feature diffusion mechanism, enabling the model to capture more extensive feature information from Chinese herbal pieces and diffuse it across multiple detection scales. Results: Experimental results show that RT-DETR-FDN achieved a precision of 0.925, a recall of 0.943, and an mAP50-95 of 0.851. In addition, the model was compared with representative You Only Look Once series models commonly used in object detection. Compared with these models, RT-DETR-FDN achieved higher recognition accuracy while maintaining a lightweight architecture. Conclusion: This study integrates deep learning with traditional Chinese medicine, providing a more effective solution for the recognition of Chinese herbal pieces.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective To identify the key biomarkers for diagnosing chronic obstructive pulmonary disease(COPD)complicated with pulmonary arterial hypertension(PAH)using bioinformatics,and validate their clinical significance.Methods High-throughput sequencing data analysis was employed to identify differentially expressed genes(DEGs)in COPD-PAH.Functional enrichment analysis was then conducted to explore the biological functions of these DEGs.Machine learning methods,including least absolute shrinkage and selection operator(LASSO),random forest(RF),and support vector machine-recursive feature elimination(SVM-RFE),were utilized to screen 5 potential biomarkers.Single-cell analysis was performed to reveal the expression patterns of these key genes in macrophages.The clinical significance of these biomarkers was further validated using peripheral blood mononuclear cells(PBMC)data.A mouse model of COPD-PAH was established using hypoxia exposure.Sixteen mice(either sexes,8 weeks old,weighing 20～22 g)were randomly divided into a hypoxia group[O2(10.0±0.5)%,COPD-PAH,n=8]and a normoxia group(COPD,n=8).Immunofluorescence assay was used to label the key biomarkers,and their expression levels were quantified.Results A total of 28 DEGs(|Log2FC|≥2,P<0.05)were identified in COPD-PAH patients.Functional enrichment analysis indicated that DEGs in COPD were primarily associated with major histocompatibility complex(MHC)Ⅱ and cell division,and involved in lysosomes,oxidative phosphorylation,and cell cycle pathways(P<0.05).Machine learning identified 5 potential biomarkers(GRN,KLF4,SHTN1,LRP1,and GPNMB),and subsequent single-cell analysis revealed that these markers exhibited reverse expression patterns during disease progression.A nomogram model constructed based on PBMC data yielded an area under the curve(AUC)of 0.907 in diagnosing COPD-PAH.GRN,KLF4,SHTN1,LRP1 and GPNMB were significantly upregulated in the COPD-PAH group(P<0.05).Conclusion GRN,KLF4,SHTN1,LRP1 and GPNMB are identified as key biomarkers for the prediction and diagnosis of COPD-PAH,which providing new insights for the clinical and treatment of the condition.

Objective To evaluate the effectiveness of the integrated schistosomiasis control programme in Wuhan City from 2005 to 2023, so as to provide insights into precision control and elimination of schistosomiasis. Methods The integrated measures for schistosomiasis control implemented by health, agriculture, water resources, and forestry departments of Wuhan City, and the epidemiological data of schistosomiasis in Wuhan City were collected from 2005 to 2023, and the prevalence of human schistosomiasis, prevalence of Schistosoma japonicum infections in humans and bovines, areas of S. japonicum-infected snail habitats, areas of snail habitats in inner embankments, and actual areas of snail habitats were retrieved. In addition, the trends in prevalence of schistosomiasis in humans and livestock and snail status were evaluated in Wuhan City from 2005 to 2023 using Mann-Kendall test and a Joinpoint regression model. Results Mann-Kendall test revealed a tendency towards a decline in the prevalence of human schistosomiasis (Z = -4.41, P < 0.01), prevalence of S. japonicum infections in humans (Z = -4.89, P < 0.01) and bovines (Z = -4.50, P < 0.01), areas of S. japonicum-infected snail habitats (Z = -3.91, P < 0.01), areas of snail habitats in inner embankments (Z = -2.28, P = 0.02), and actual areas of snail habitats (Z = -5.95, P < 0.01) in Wuhan City from 2005 to 2023. Joinpoint regression analysis showed an average annual reduction of 8.58% in the prevalence of human schistosomiasis in Wuhan City from 2005 to 2023 [average annual percent change (AAPC) = -8.58%, 95% confidence interval (CI): (-10.02%, -6.65%), P < 0.01], with two joinpoints in 2013 and 2016, respectively, and the tendency towards a decline showed statistical significance during the period from 2013 through 2016 [annual percent change (APC) = -34.41%, 95% CI: (-40.36%, -20.01%), P < 0.01]. The prevalence of S. japonicum human infections appeared an average annual reduction of 51.91% in Wuhan City from 2005 to 2023 [AAPC = -51.91%, 95% CI: (-58.12%, -44.25%), P < 0.01], with two joinpoints in 2014 and 2017, respectively, and the tendency towards a decline showed statistical significance during the period from 2014 through 2017 [APC = -98.17%, 95% CI: (-99.17%, -90.87%), P < 0.01]. The prevalence of S. japonicum infections in bovines appeared an average annual reduction of 53.12% in Wuhan City from 2005 to 2023 [AAPC = -53.12%, 95% CI: (-59.65%, -42.44%), P < 0.01], with two joinpoints in 2011 and 2014, respectively, and the tendency towards a decline showed statistical significance during the period from 2014 through 2017 [APC = -98.63%, 95% CI: (-99.44%, -90.93%), P < 0.01]. The areas of S. japonicum-infected snail habitats appeared an average annual reduction of 47.09% in Wuhan City from 2005 to 2023 [AAPC = -47.09%, 95% CI: (-52.92%, -38.26%), P < 0.01], with two joinpoints in 2011 and 2014, respectively, and the tendency towards a decline showed statistical significance during the period from 2011 through 2014 [APC = -97.27%, 95% CI: (-98.65%, -88.06%), P < 0.01]. The areas of snail habitats in inner embankments appeared an average annual reduction of 4.45% in Wuhan City from 2005 to 2023 [AAPC = -4.45%, 95% CI: (-5.18%, -3.82%), P < 0.01], with three joinpoints in 2011, 2015 and 2018, respectively, and statistical significance was seen in the tendency towards a decline during the period from 2005 through 2011 [APC = -16.38%, 95% CI: (-20.15%, -14.25%), P < 0.01]. In addition, the actual areas of snail habitats appeared an average annual reduction of 2.65% in Wuhan City from 2005 to 2023 [AAPC = -2.65%, 95% CI: (-2.89%, -2.40%), P < 0.01], with a joinpoint in 2013, and the tendency towards a decline showed statistical significance during the period from 2013 through 2023 [APC = -4.06%, 95% CI: (-4.66%, -3.58%), P < 0.01]. Conclusions The integrated schistosomiasis control programme achieved significant effectiveness in Wuhan City from 2005 to 2023, with a tendency towards a decline in morbidity due to schistosomiasis in humans and livestock and snail status. The integrated schistosomiasis control strategy with emphasis on management of the source of S. japonicum infections should continue to be implemented to consolidate the schistosomiasis control achievements and achieve the goal of schistosomiasis elimination in the city.

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

The aim of this study was to investigate the trend in testicular volume changes after orchiopexy in children with cryptorchidism. The clinical data of 854 children with cryptorchidism who underwent orchiopexy between January 2013 and December 2016 in Shenzhen Children's Hospital (Shenzhen, China) were retrospectively analyzed. The mean (standard deviation) age of the patients was 2.8 (2.5) years, and the duration of follow-up ranged from 1 year to 5 years. Ultrasonography was conducted preoperatively and postoperatively. The variables analyzed included age at the time of surgery, type of surgical procedure, laterality, preoperative testicular position, preoperative and postoperative testicular volumes, and the testicular volume ratio of them. The average testicular volumes preoperatively and at 1 year, 2 years, 3 years, and 5 years postoperatively were 0.27 ml, 0.38 ml, 0.53 ml, 0.87 ml, and 1.00 ml, respectively ( P < 0.001). The corresponding testicular volume ratios were 0.67, 0.76, 0.80, 0.83, and 0.84 ( P < 0.001). The mean volume of the undescended testes was significantly smaller than the mean normative value ( P < 0.001, lower than the 10 th percentile). The postoperative testicular volumes in children with cryptorchidism were generally lower than those in healthy boys but were still greater than the 10 th percentile and exhibited an increasing trend. The older the child is at the time of surgery, the larger the gap in volume between the affected and normal testes. Although testicular volume tends to gradually increase after orchiopexy for cryptorchidism, it could not normalizes. Earlier surgery results in affected testicular volumes closer to those of healthy boys.
Humans ; Male ; Cryptorchidism/diagnostic imaging* ; Orchiopexy ; Child, Preschool ; Testis/surgery* ; Retrospective Studies ; Organ Size ; Ultrasonography ; Infant ; Child ; Postoperative Period ; Follow-Up Studies

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

Immunotherapy has emerged as a revolutionary approach to treat immune-related diseases. Dendritic cells (DCs) play a pivotal role in orchestrating immune responses, making them an attractive target for immunotherapeutic interventions. Modulation of gene expression in DCs using genome editing techniques, such as the CRISPR-Cas system, is important for regulating DC functions. However, the precise delivery of CRISPR-based therapies to DCs has posed a significant challenge. While lipid nanoparticles (LNPs) have been extensively studied for gene editing in tumor cells, their potential application in DCs has remained relatively unexplored. This study investigates the important role of cholesterol in regulating the efficiency of BAMEA-O16B lipid-assisted nanoparticles (BLANs) as carriers of CRISPR/Cas9 for gene editing in DCs. Remarkably, BLANs with low cholesterol density exhibit exceptional mRNA uptake, improved endosomal escape, and efficient single-guide RNA release capabilities. Administration of BLAN_mCas9/gPD-L1 results in substantial PD-L1 gene knockout in conventional dendritic cells (cDCs), accompanied by heightened cDC1 activation, T cell stimulation, and significant suppression of tumor growth. The study underscores the pivotal role of cholesterol density within LNPs, revealing potent influence on gene editing efficacy within DCs. This strategy holds immense promise for the field of cancer immunotherapy, offering a novel avenue for treating immune-related diseases.

Coronavirus-related diseases pose a significant challenge to the global health system. Given the diversity of coronaviruses and the unpredictable nature of disease outbreaks, the traditional "one bug, one drug" paradigm struggles to address the growing number of emerging crises. Therefore, there is an urgent need for therapeutic agents with broad-spectrum anti-coronavirus activity. Here, we provide evidence that ATV006, an anti-SARS-CoV-2 nucleoside analog targeting RNA-dependent RNA polymerase (RdRp), has broad antiviral activity against human and animal coronaviruses. Using mouse hepatitis virus (MHV) and human coronavirus NL63 (HCoV-NL63) as a model, we show that ATV006 has potent prophylactic and therapeutic activity against murine coronavirus infection in vivo. Remarkably, ATV006 successfully inhibits viral replication in mice even when administered 96 h after infection. Due to its oral bioavailability and potency against multiple coronaviruses, ATV006 has the potential to become a useful antiviral agent against SARS-CoV-2 and other circulating and emerging coronaviruses in humans and animals.