Objective To investigate the prevalence of cognitive frailty and its associated factors among middle-aged and elderly patients with chronic obstructive pulmonary disease (COPD) in Gusu District, Suzhou City, to provide a basis for intervention measures. Methods COPD patients managed at Pingjiang New Town Community Health Service Center in Gusu District from January to December 2024 were selected. Data were collected using the Fried Frailty Phenotype, Mini-Mental State Examination, and a general information questionnaire. Chi-square tests, one-way analysis of variance, and multivariate Logistic regression were used for data analysis. Results A total of 1 388 patients were included, with 916 males (65.99%) and 472 females (34.01%). Cognitive frailty was observed in 554 cases (prevalence: 39.91%). Univariate analysis showed significant differences in gender, education, visual impairment, hearing impairment, sleep disorders, and disease duration between the cognitive frailty and non-cognitive frailty groups (all P<0.05). Multivariate Logistic regression indicated that education was negatively associated with cognitive frailty (illiteracy OR=6.969, P<0.001; primary school OR=1.499, P=0.005), while visual impairment (OR=2.347, P<0.001), hearing impairment (OR=1.705, P<0.001), sleep disorders (OR=2.488, P<0.001), and disease duration (≤5 years OR=0.329, P<0.001; 6-10 years OR=0.487, P<0.001) were positively associated with cognitive frailty. Conclusion The prevalence of cognitive frailty among middle-aged and elderly COPD patients in Gusu District, Suzhou City, is high (39.91%). Epositively associated with cognitive frailtyducation, sensory impairments, sleep disorders, and disease duration are associated factors. Clinical attention to high-risk groups and implementation of early screening and targeted interventions are recommended.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To evaluate the predictive value of dose-surface histogram(DSH)for radiation proctitis(RP)in prostate cancer(PCa)patients undergoing radiotherapy.Methods This prospective randomized controlled clinical trial included 380 PCa patients who underwent image-guided radiotherapy in the First Affiliated Hospital of Hebei Northern University from January 2018 to January 2023.Patients were randomly divided into observation group(n=200)and control group(n=180).The rectal dose distribution of patients in the two groups was evaluated by using DSH and dose-volume histogram(DVH),respectively.The receiver operating characteristic(ROC)curve was utilized to evaluate the predictive value of DSH for acute RP,with DVH serving as a reference.Results The difference was not statistically significant in clinical information such as age,KPS score,and body mass index(BMI)between the observation and control groups(P＞0.05),as well as in acute RP incidence(P＞0.05).There were significant differences in S40 and V40,S50 and V50,S60 and V60,S70 and V70,and S78 and V78 between the two groups(P＜0.05).S40,S50,V40,and V50 showed low efficacy(P＜0.001)in predicting acute RP at each level,with AUC≤0.700.S60 and V60 showed moderate efficacy(P＜0.001)in predicting acute RP at each level,with AUC 0.700-0.900.S70,S78,V70 and V78 showed high efficacy(P＜0.001)in predicting acute RP at each level,with AUC＞0.900.Conclusions The predictive value of DSH for rectal toxicity in patients with PCa is basically consistent with that of DVH.It is expected to become a novel and valuable tool for evaluating radiotherapy plans in the future.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

OBJECTIVE: To observe the effects of electroacupuncture (EA) at changbing fang (prescription for intestinal disease) on autophagy of colonic cells and gut microbiota in rats with ulcerative colitis (UC), and to explore the mechanism of EA in the treatment of UC. METHODS: Thirty-two SD male rats were randomly divided into a control group, a model group, an EA group and a sham-EA group, with 8 rats in each group. Except the control group, the UC rat model was established by free drinking of 5% dextran sulfate sodium solution for 7 days in the other groups. In the EA group, changbing fang was adopted, in which, EA was applied at "Tianshu" (ST25) and "Shangjuxu" (ST37), at disperse-dense wave and frequency of 10 Hz/50 Hz, for 20 min in each intervention. In the sham-EA group, shallow transcutaneous puncture was performed at the sites, 5 mm away from the points as the EA group, with the same parameters as the EA group. The intervention was delivered once daily for 3 consecutive days. The body weight was measured daily and the disease activity index (DAI) score was calculated before and after intervention. After intervention completion, the colon length was measured. Using HE staining, the colon morphology was observed and the score of colonic pathology was assessed. With ELISA adopted, the contents of tumor necrosis factor (TNF-α), interleukin (IL)-1β, IL-2 and IL-10 in the serum of the rats were detected. The ultrastructure of the colon tissue was observed under electron microscopy. Using Western blotting, the protein expression was detected for microtubule-associated protein 1 light chain 3 (LC3)Ⅱ, LC3Ⅰ, autophagy-related genes (ATG) 5, ATG12, sequestosome 1 (p62), phosphatidylinositol 3-kinase (PI3K), phosphorylated protein kinase B (p-AKT), protein kinase B (AKT), and phosphorylated mammalian target of rapamycin (p-mTOR), mammalian target of rapamycin (mTOR) in the colon tissue. The mRNA expression of PI3K, AKT and m-TOR in the colon tissue was detected by real-time fluorescence quantitative PCR. The 16S rRNA gene sequencing was used to analyze the structure of gut flora in the feces of rats. RESULTS: From day 1 to day 7, compared with the control group, the body weight decreased in the model group, EA group, and SEA group (P<0.05, P<0.01). From day 9 to day 10, the EA group showed an increase in body weight compared with the model group and SEA group (P<0.05, P<0.01). Before intervention, the DAI score in the model group, EA group, and SEA group was higher than the score of the control group, respectively (P<0.01). After intervention, the DAI score in the EA group was reduced compared with the model group and SEA group (P<0.01). Compared with the control group, in the model group, the colon length of rats was shorter (P<0.01); it showed the distorted crypts, thinner mucosal layer, reduced goblet cells, inflammatory cell infiltration and the disarranged histological structure; and the pathological score of the colon tissue increased (P<0.01); the serum contents of TNF-α and IL-1β increased (P<0.01), and those of IL-2 and IL-10 decreased (P<0.01). The structure of colon epithelial cells was disarranged, with cilia pelt off, and a large number of vacuoles in the cytoplasm; the mitochondria were swollen, with unclear structure and cristae partially disappeared; and few autophagosomes were observed. The value of LC3Ⅱ/LC3Ⅰand the protein expression of ATG5 and ATG12 in the colon tissues were reduced (P<0.01), the protein expression of p62 and PI3K, and the values of p-AKT/AKT, and p-mTOR/mTOR increased (P<0.01), and mRNA expression of PI3K, AKT and mTOR was elevated (P<0.01). The indexes of Chao1, Ace and Shannon decreased (P<0.01). At the phylum level, the relative abundance of Firmicutes decreased (P<0.05), that of Bacteroidetes and Proteobacteria increased (P<0.05, P<0.01). At the genus level, the relevant abundance of Lactobacillus decreased (P<0.05), while that of Lachnospiraceae_NK4A136_group and Phascolarctobacterium increased (P<0.01, P<0.05 ). Compared with the model group and SEA group, in the EA group, the colon length increased (P<0.01), the infiltration of inflammatory cells was reduced, the arrangement of intestinal epithelial cells was arranged regularly, with a small amount of shedding, and the pathological score of the colon tissue decreased (P<0.01). The serum contents of TNF-α and IL-1β decreased (P<0.01), and those of IL-2 and IL-10 increased (P<0.01). The colonic epithelial cells were arranged relatively, the morphology of organelles was basically normal, and autophagosomes were visible. The value of LC3Ⅱ/LC3Ⅰand the protein expression of ATG5 and ATG12 in colon tissue increased (P<0.01, P<0.05), the protein expression of p62 and PI3K, and the values of p-AKT/AKT, and p-mTOR/mTOR decreased (P<0.01); and mRNA expression of PI3K, AKT, m-TOR was reduced (P<0.01). The indexes of Chao1, Ace and Shannon increased (P<0.01). At the phylum level, the relative abundance of Firmicutes increased (P<0.01), while that of Bacteroidetes decreased (P<0.01). At the genus level, the relative abundance of Lactobacillus increased (P<0.05), whereas that of Lachnospiraceae_NK4A136_group decreased (P<0.01). When compared with the model group, the relative abundance of Proteobacteria decreased (P<0.05), and that of Phascolarctobacterium was reduced (P<0.05) in the EA group. CONCLUSION EA at changbingfang alleviates UC symptoms probably through inhibiting the PI3K/AKT/mTOR signaling pathway to regulate colonic autophagy and improve the intestinal flora.
Animals ; Electroacupuncture ; Colitis, Ulcerative/metabolism* ; Male ; Rats ; Gastrointestinal Microbiome ; Rats, Sprague-Dawley ; Colon/metabolism* ; Humans ; Autophagy ; Acupuncture Points ; Tumor Necrosis Factor-alpha/genetics* ; Interleukin-10/genetics*

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective To investigate the detection rate and related influencing factors of gastrointestinal diseases in grass-roots personnel.Methods A total of 481 grass-roots personnel were enrolled and examined by magnetic-controlled capsule endoscopy(MCCE).Multivariate logistic regression were used to analyze the influencing factors of gastrointestinal diseases detected by MCCE.Results All personnel completed MCCE,and gastrointestinal diseases were detected in 154(32.0%)cases,including 106 cases of erosive gastritis,25 cases of chronic atrophic gastritis,17 cases of digestive tract polyp,16 cases of gastric ulcer,5 cases of reflux esophagitis,4 cases of cardia,1 case of duodenitis,and 1 case of enteritis.Gastrointestinal diseases was correlated with special operation posts,long-term tasks within recent 6 months,abdominal distension,belching,nausea and vomiting,diarrhea and other symptoms(all P＜0.05).Multivariate logistic regression analysis showed that the risk factors of gastrointestinal diseases were working in special operation posts,performing long tasks within 6 months,belching,nausea and vomiting symptoms(all P＜0.05).Conclusion The overall detection rate of gastrointestinal diseases(mainly acid related diseases)is relatively high,and its incidence is closely related to working in special operation posts and performing long-term tasks within recent 6 months.Personnel working in special operation posts should be more alert to gastrointestinal diseases.Gastrointestinal symptoms have reference value for the prediction of lesions,but more attention should be paid to the identification of functional gastrointestinal diseases with endoscopy.