Background: Sex-based differences often influence the therapeutic efficacy and safety of medications. Semen Cuscutae is a traditional tonic botanical drug with sex-specific characteristics, traditionally indicated for conditions such as impotence (exclusive to males) and restless fetus (exclusive to pregnant females). However, most existing studies have focused on a single sex. Objective: To evaluate the sex-specific biological effects of Semen Cuscutae in rats and explore its molecular mechanisms, with the aim of uncovering its pharmacological characteristics through a multiomics approach. Methods: A traditional aqueous extract of Semen Cuscutae (SCA) was used as the experimental material. Forty adult Sprague-Dawley rats (equal numbers of males and females) were randomly divided into 4 groups: male control, male SCA treatment (240 mg/kg), female control, and female SCA treatment (240 mg/kg), with 10 rats in each group. The biological effects were comprehensively evaluated using a combination of open field test, biochemical analyses, proteomics, and gut microbiota profiling. Results: As a tonic botanical drug, SCA appeared to directly affect the mental and behavioral state of rats. It significantly altered the time spent by rats in the center area during the open field test, showing a sex-dependent reversal of behaviors. Proteomic analysis of brain tissue identified 624 differentially expressed proteins across the groups, with 10 key differentially expressed proteins related to sex differences, including fibroblast growth factor receptor 3, transcription elongation factor A protein-like 1, 40S ribosomal protein S25, neural cell adhesion molecule, and anion exchange protein 2 (SLC4A2). Enrichment analysis revealed that in male rats, SCA upregulated proteins involved in biological processes such as ribosome function and energy derivation, supporting protein synthesis and enhancing energy supply, showing an overall gain effect. In contrast, in female rats, SCA downregulated proteins associated with processes such as positive regulation of target of rapamycin (TOR) signaling and vesicle transport, suggesting suppression of neuronal signaling and material transport, indicative of a shift toward a more restrained physiological state. Furthermore, SCA reduced gut microbiota diversity in female rats but increased it in males, including the abundance of Akkermansia, which may serve as a crucial mediator. Conclusion: Overall, the biological effects of SCA differ significantly between male and female rats, with evidence suggesting greater health benefits in males. These findings help elucidate the scientific basis of its traditional applications and provide guidance for the precise application of SCA as a functional health food.

With the integration of 5G communication technology and robotic surgical systems, remote robot-assisted thoracic surgery is overcoming geographical barriers, offering an innovative approach to addressing the uneven distribution of medical resources. This study conducted a systematic literature review—using databases such as PubMed and CNKI, with the search period extending up to 2025—incorporating clinical studies, case reports, and review articles to comprehensively evaluate the clinical efficacy and safety of 5G-enabled remote robot-assisted thoracic surgery (5G-RRATS). The analysis also examined current technological limitations and potential future development trajectories. Existing evidence indicates that, given adequate technical support, 5G-RRATS can achieve perioperative outcomes comparable to those of conventional local robotic surgeries across procedures including pulmonary wedge resection, lobectomy, and esophagectomy. Furthermore, it demonstrates potential advantages in minimizing surgical incisions and reducing intraoperative blood loss. Nevertheless, challenges related to network stability, latency control, interdisciplinary collaboration between medical and engineering teams, and legal, regulatory, and ethical considerations continue to hinder widespread clinical adoption. Looking ahead, the emergence of a "one-to-many" remote surgical model, combined with the integration of artificial intelligence and augmented reality technologies, as well as advancements in low-orbit satellite communications, may enable 5G-RRATS to further advance precision and efficiency in thoracic surgery, thereby facilitating equitable access to high-quality care for a broader patient population.

Objective To analyze the monitoring data of cardio-cerebrovascular diseases prevention and control system in Yichang in 2022, and to provide data support and experience for the precise prevention and treatment of cardio-cerebrovascular diseases. Methods Acute cardiovascular and cerebrovascular event data were collected from the Yichang Cardio-cerebrovascular Events Monitoring System from January 1, 2022 to December 31, 2022. Descriptive analysis was conducted for the data collected. Statistical analysis was performed using SPSS 20.0 software, and a chi-square test was used to analyze the count data. Results A total of 37,217 cases of cardio-cerebrovascular events were monitored in Yichang in 2022. The crude incidence and the standardized incidence were 983.84/100,000 and 541.55/100,000, respectively. The incidence in males was higher than females (554.93/100,000 vs 428.91/100,000，χ² =464.52，P＜0.05). The top three diseases were cerebral infarction, acute myocardial infarction, and cerebral hemorrhage. The incidence of events increased with age, and 79.80% of the cases were over 60 years old. The main onset time was from May to August. Conclusion The use of the cardio-cerebrovascular events monitoring system in Yichang and the implementation of ^“mandatory reporting card^” monitoring can timely obtain the epidemic characteristics of the diseases, provide support for the precise formulation of prevention and control strategies and measures, reduce underreporting rates, and improve the monitoring system, which is worthy of reference and promotion.

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed

Objective:To investigate the incidence of collateral circulation in high-risk patients with sleep apnea and stroke treated by continuous positive airway pressure （CPAP） ventilation and to analyze the influencing factors. Methods:A total of 152 patients diagnosed with obstructive sleep apnea-hypopnea syndrome （OSAHS） combined with acute ischemic stroke （AIS） who were admitted to our hospital from January 2020 to June 2022 were selected for this study. Based on the apnea-hypopnea index （AHI）, the patients were divided into three groups: mild （n=44）, moderate （n=72）, and severe （n=36）. After treatment, the patients were further classified into a group without collateral circulation （n=30） and a group with collateral circulation （n=26）, which included those with moderate collateral circulation （n=69） and good collateral circulation （n=27）. Clinical data across the different groups were compared, and multiple factor analysis was performed to identify factors affecting the occurrence of collateral circulation. Results:The AHI and IL-6 levels in the severe group were significantly higher than those in the mild and moderate groups, while the levels of NO and PO2 were significantly lower in the severe group compared to the mild and moderate groups, with statistically significant differences among the three groups （P<0.05）. After treatment, all groups showed improvement, and the proportion of patients with collateral circulation was 84.09% in the mild group, 81.94% in the moderate group, and 72.22% in the severe group. Significant differences in age, AHI, NIHSS, NO, MoCA, and MMSE scores were observed between the groups with and without collateral circulation （P<0.05）. In the group with collateral circulation, the scores for age, AHI, and NIHSS in the good collateral circulation subgroup were significantly lower than those in the poor collateral circulation and moderate collateral circulation subgroups, while the scores for NO, MoCA, and MMSE were significantly higher in the good collateral circulation subgroup. Multi-factor analysis revealed that age, AHI, and NIHSS were independent risk factors for collateral circulation, whereas NO, MoCA, and MMSE served as protective factors that were negatively correlated with collateral circulation. Classification tree model results indicated that AHI had the greatest influence on the occurrence of collateral circulation among the five influencing factors, demonstrating good predictive capability. Conclusion:Most high-risk patients with sleep apnea and stroke are likely to develop collateral circulation following continuous positive airway pressure ventilation. Factors such as age, AHI, NIHSS, NO, MoCA, and MMSE are important determinants affecting the occurrence of collateral circulation.
Humans ; Collateral Circulation ; Continuous Positive Airway Pressure ; Stroke/physiopathology* ; Sleep Apnea, Obstructive/physiopathology* ; Risk Factors ; Male ; Incidence ; Female ; Middle Aged ; Aged ; Sleep Apnea Syndromes/physiopathology* ; Interleukin-6/blood*

OBJECTIVES: To explore the effects of cannabidiol on endoplasmic reticulum stress and neuronal apoptosis in rats with multiple concussions (MCC). METHODS: SD rats were randomized into sham group, MCC group, 1% tween20 (TW) treatment group, and low-dose (10 mg/kg) and high-dose (40 mg/kg) cannabidiol treatment groups. In all but the sham group, MCC models were established using a metal pendulum percussion device, after which the rats received daily intraperitoneal injections of the corresponding agents for 2 weeks. The expressions of PERK, eIF2α, ATF4, CHOP, TRIB3, p-Akt and pro-caspase-3 in the brain tissue of the rats were detected with qRT-PCR, Western blotting and immunofluorescence staining. The core targets of cannabidiol in treatment of traumatic brain injury (TBI) were identified by network pharmacology analysis, and molecular docking was carried out to simulate the interaction of cannabidiol with the factors related to endoplasmic reticulum stress and apoptosis. RESULTS: Compared with the sham-operated rats, the rat models of MCC showed significantly increased mRNA expressions of PERK, eIF2α and CHOP and protein expressions of PERK, eIF2α, ATF4, CHOP, TRIB3, p-AKT and pro-caspase-3 in the cerebral cortex. CBD treatment, especially at the high dose, obviously increased the expression of p-Akt and lowered the expression levels of the other factors tested in the rat models. Network pharmacology analysis indicated interactions of the core targets of CBD with the factors related to endoplasmic reticulum stress and TBI, and molecular docking study showed a high binding energy of CBD with multiple factors pertaining to endoplasmic reticulum stress and apoptosis. CONCLUSIONS MCC induce endoplasmic reticulum stress and apoptosis in rat brain tissues, for which CBD, especially at a high dose, provides neuroprotective effects by inhibiting endoplasmic reticulum stress and cell apoptosis.
Animals ; Endoplasmic Reticulum Stress/drug effects* ; Apoptosis/drug effects* ; Rats, Sprague-Dawley ; Activating Transcription Factor 4/metabolism* ; Transcription Factor CHOP/metabolism* ; Rats ; Eukaryotic Initiation Factor-2/metabolism* ; Signal Transduction/drug effects* ; eIF-2 Kinase/metabolism* ; Cannabidiol/pharmacology* ; Neurons/metabolism* ; Brain Concussion/metabolism* ; Male ; Molecular Docking Simulation

The quality of traditional Chinese medicine (TCM) prescriptions (TCMPs) is critical to clinical efficacy; however, evaluating their consistency and identifying sources of variability remain challenging. This study proposes an integrated strategy to assess the quality of 100 widely sold TCMPs. A "one-for-all" chromatographic method was employed to analyze 645 sample batches. This large-scale data collection enabled statistical evaluations, such as hierarchical cluster analysis (HCA) and similarity heatmap, to identify quality inconsistencies. The introduction of a TCM-specific mass spectrometry (MS) database allowed for rapid, automated annotation of chemicals across 100 prescriptions and facilitated the tracing of raw material sources. Results indicate that 19% of prescriptions exhibited chemical inconsistencies, which are associated with high market value, low pricing, and substantial price disparities. The MS database allowed rapid annotation of 761 and 673 compounds in positive and negative modes, respectively, in 100 TCMPs, with 73 prescriptions reported for the first time. The tracing efforts succeeded in identifying >40% of the raw material sources for 51 prescriptions. P93 (Yinianjin (YNJ)) is a case in which the chromatographic profiles from three manufacturers displayed inconsistencies. Analysis using the database traced divergent peaks to Rhei Radix et R hizoma (RRER). Verification with self-prepared samples confirmed that manufacturers utilized three distinct botanical sources. This integrated strategy provides a scalable framework for quality control in TCMPs.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Background: The global rise in visual impairment, driven by population aging, the increasing prevalence of lifestyle-related chronic diseases, and environmental factors, has made it a critical public health concern, highlighting the urgent need for effective preventive strategies and eye health maintenance. Cuscutae Semen (CS), a traditional Chinese herbal medicine long regarded for its vision-enhancing properties, has been widely used to support ocular health. However, its underlying molecular mechanisms and bioactive constituents remain poorly understood, limiting its modernization and broader clinical application. Objective: This study aims to investigate the restorative effects of CS on visual impairment, elucidate its underlying mechanisms, and identify potential active components. Methods: A zebrafish model of visual impairment was established using mepanipyrim to simulate retinal structural damage and visual dysfunction. The therapeutic effects of CS were systematically evaluated through behavioral analyses and histomorphological observations. To elucidate the underlying mechanisms, an integrated approach was employed, combining transcriptome sequencing (RNA-seq), reverse transcription quantitative polymerase chain reaction validation, and immunofluorescence staining to identify critical genes and pathways involved. Furthermore, macroporous resin column chromatography was employed for the fractionation and screening of potential active components. Results: CS treatment significantly alleviated mepanipyrim-induced ocular abnormalities in zebrafish, restoring approximately 82% of the observed morphological defects. Behavioral assessments revealed that CS-treated zebrafish exhibited markedly increased swimming speed and distance, indicating enhanced visual light sensitivity. Histopathological analysis demonstrated that CS effectively repaired the structure of retinal cell layers. RNA-seq revealed that CS broadly reversed mepanipyrim-induced gene expression disturbances, suggesting a restorative effect on transcriptomic homeostasis. Gene Ontology enrichment analysis identified the phototransduction pathway as a key mediator of CS’s therapeutic effects. This was further supported by reverse transcription quantitative polymerase chain reaction validation of critical genes and immunofluorescence staining, which confirmed the restored expression of Pde6a and Gnat2, key proteins involved in photic signal transmission. Active component screening indicated that high-polar constituents, including chlorogenic acid, may constitute one of the major bioactive fractions responsible for the observed therapeutic effects. Conclusion: This study provides evidence of the vision-protective effects of CS in a zebrafish model, demonstrating that its therapeutic mechanism involves modulation of the phototransduction pathway. Chlorogenic acid was identified as one of the key bioactive constituents contributing to this effect. These findings not only provide scientific validation for the traditional use of CS in ocular protection but also present promising therapeutic prospects for the prevention and treatment of visual impairment.