Objective To evaluate the efficacy and safety of intraoperative pleural irrigation with Nocardia rubra cell-wall skeleton (N-CWS) for reducing pleural effusion drainage after radical surgery for lung cancer. Methods A retrospective analysis was conducted on the clinical data of lung cancer patients who underwent lobectomy and mediastinal lymph node dissection at the First Affiliated Hospital of Xiamen University between December 2024 and May 2025. Patients were divided into a control group and an irrigation group based on the intraoperative use of N-CWS. Patients in the irrigation group received pleural irrigation with 800 μg of N-CWS diluted in 10 mL of normal saline. The following outcomes were compared between the two groups: pleural effusion drainage volume at 0-24 h, 24-48 h, and 48-72 h postoperatively, degree of air leak, chest tube duration, postoperative length of stay, and the incidence of adverse events (fever, chest pain, and nausea and vomiting). Results A total of 245 patients were included (97 males, 148 females) with a mean age of (61.28±6.26) years, with 205 in the control group and 40 in the irrigation group. Compared to the control group, the irrigation group showed significantly lower pleural effusion drainage volumes at 0-24 h, 24-48 h, and 48-72 h, as well as shorter chest tube duration and postoperative length of stay (all P<0.05). There was no statistical difference in the degree of postoperative air leak (P=0.661). No significant differences were observed between the two groups regarding the highest body temperature within 72 h post-surgery (P=0.130), fever grade (P=0.196), severity of chest pain (P=0.105), or the incidence of nausea and vomiting (P=0.376). Conclusion Intraoperative pleural irrigation with N-CWS in patients undergoing lobectomy and mediastinal lymph node dissection for lung cancer can significantly reduce postoperative pleural effusion drainage volume, shorten chest tube duration and length of hospital stay. The procedure is safe and feasible.

Allergic rhinitis (AR), a globally prevalent immune-mediated inflammatory condition, is still an incurable disease. In the present study, we have validated the impact of the Kelch-like ECH associated protein 1 (Keap1)-related oxidative stress and inflammatory response in clinical AR patient peripheral blood and nasal swab samples, emphasizing the biological relevance of Keap1 and AR. Targeting Keap1 -nuclear factor erythroid 2-related factor 2 (Nrf2) related anti-oxidative stress may be effective for AR intervention. Drawing inspiration from the Keap1 homodimerization and the E3 ligase characteristics, we herein present a design of novel bivalent molecules for chemical knockdown of Keap1. For the first time, we characterized ternary complexes of Keap1 dimer and one molecule of bivalent compounds. The best bivalent molecule 8 encompasses robust capacity to degrade Keap1 as a homoPROTAC^KEAP1. It efficaciously suppresses inflammatory cytokines in extensively different cells, including human nasal epithelial cells. Moreover, in an AR mouse model, we confirmed that the chemical degradation induced by homoPROTAC^KEAP1 led to therapeutic benefits in managing AR symptoms, oxidative stress and inflammation. In summary, our findings underscore the efficacy of targeting the Keap1 system through the homoPROTAC-ing technology as an innovative and promising treatment strategy for the incurable allergic disorders.

OBJECTIVE: To investigate the clinical characteristics and related risk factors of Clostridium difficile infection (CDI) in intensive care unit (ICU). METHODS: A retrospective study was conducted. Patients with diarrhea admitted to the ICU of the General Hospital of Ningxia Medical University from May 1 to August 30, 2023 were selected. Patients were divided into CDI group and non-CDI group based on the presence or absence of CDI. Clinical data from two groups of patients meeting the criteria were collected and compared, including gender, age, acute physiology and chronic health evaluation II (APACHE II), length of hospital stay, serum lactic acid, parenteral nutrition time, white blood cell count (WBC), procalcitonin (PCT), C-reactive protein (CRP), coagulation indicators, albumin, antibiotic exposure, etc. Multivariate Logistic regression analysis was performed to analyze the risk factors for CDI in ICU diarrhea patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of each index for CDI in diarrhea patients. RESULTS: A total of 24 patients with diarrhea were enrolled, including 9 patients in the CDI group and 15 patients in the non-CDI group. The time of parenteral nutrition in the CDI group was significantly longer than that in the non-CDI group [days: 18.0 (13.5, 19.5) vs. 10.0 (4.0, 18.0)], the serum lactic acid level [mmol/L: 4.40 (3.00, 15.25) vs. 2.50 (1.90, 3.20)] and the ratio of serum lactic acid > 3.9 mmol/L [66.67% (6/9) vs. 6.67% (1/15)] were significantly higher than those in the non-CDI group, with statistical significance (all P < 0.05). Multivariate binary Logistic regression analysis showed that the serum lactic acid level of the patients was an independent risk factor for CDI [odds ratio (OR) = 3.193, 95% confidence interval (95%CI) was 1.011-10.080, P = 0.048]. ROC curve showed that serum lactic acid level had a high predictive value for CDI in ICU patients with diarrhea, and the area under the curve (AUC) was 0.815, respectively. When the cut-off value of serum lactic acid was 3.9 mmol/L, the sensitivity was 66.7% and the specificity was 93.3%. CONCLUSION Patients with diarrhea who have higher serum lactate levels (> 3.9 mmol/L) on admission are at increased risk of developing CDI.
Humans ; Retrospective Studies ; Risk Factors ; Intensive Care Units ; Clostridium Infections ; Clostridioides difficile ; Male ; Female ; Middle Aged ; Aged ; Diarrhea/microbiology* ; Logistic Models ; ROC Curve ; Adult

Aiming at the quality problem of preparing gut for patients in test and treatment with colonoscopy,this article involved in one kind of quality judgement system based on cloud processing,which composed of information collection module,cloud processing analysis module,and identification and judgment module for doctor.It could realize automatic interpretation and medication guidance for the quality of preparing gut.In the system,the obtained operation information of depending collection module,and the cloud processor with the ability of analyzing and processing data can judge the quality of preparing gut for patients,and effectively solve a series of problems such as inefficient judgment for preparing gut,and poor quality of preparation.It can help patients to adjust medication,and relieve the pressure of medical staffs in guideline and communication for preparing gut,and enhance the quality of preparing gut,and avoid the influence of insufficient preparation for gut on the test and treatment of colonoscopy,so as to provide more effective safety and guarantee for clinical practice.

Objective To explore the clinical efficacy and mechanism of FuKe Yangrong capsule(FKYRC)in treating anovulatory infertility(AI)using network pharmacology and clinical observation meth-ods.Methods A total of 110 AI patients who visited the hospital from January 2023 to July 2024 were select-ed as the research subjects.They were divided into three groups according to the treatment method:traditional Chinese medicine treatment group(n=30,treated only with FKYRC),western medicine treatment group(n=40,treated only with letrozole),and combination treatment group(n=40,treated only with FKYRC+letrozole).After 4 cycles of treatment,the total effective rate,maximum follicle diameter,pre-ovulation endo-metrial thickness,ovulation rate and pregnancy rate,and embryo survival rate of each group were compared af-ter treatment.Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and GeneCards database,the core active ingredients,target proteins,and AI related targets of FKYRC were obtained,and common targets were screened.Then,a protein-protein interaction(PPI)network was constructed,and gene ontology(GO)function and Kyoto Gene and Genome Database(KEGG)pathway enrichment analysis were performed using a bioinformatics platform for visualization.Finally,three-dimen-sional visualization analysis was performed.Results The total clinical efficacy of the traditional Chinese medi-cine group,western medicine group,and combination therapy group were 90.00％,92.50％,and 97.50％,re-spectively.The ovulation rates were 60.00％,70.00％,and 87.50％,respectively.The pregnancy rates were 33.33％,37.5％,and 60.00％,respectively.The survival rates of embryos were 60.00％,73.30％,and 95.80％,respectively,and the differences between the groups were statistically significant(P＜0.05).The maximum follicle diameter and pre-ovulation endometrial thickness in the combination therapy group were higher than those in the traditional Chinese medicine group and the western medicine group,and the difference was statistically significant(P＜0.05).Network pharmacology discovered 239 active ingredients and 3 977 target genes in FKYRC.After screening,200 active ingredients and 299 target genes were identified.A total of 478 disease target genes,38 potential interaction targets,and 19 core targets were obtained.Molecular func-tions,cellular components,and biological processes mainly involved steroid protein binding,estrogen response elements,estrogen receptor activity,nuclear chromatin,and other aspects.KEGG pathway enrichment analysis showed that FKYRC anti AI core targets were mainly enriched in estrogen signaling pathway,P53 signaling pathway,advanced glycation end product receptor(AGE-RAGE)of diabetes complications and other signaling pathways.The key targets of FKYRC against AI were two estrogen receptors(ESR1 and ESR2),steroid re-ceptor(AR),and peroxisome proliferator activated receptor-γ(PPARG).Conclusion The combined treat-ment of FKYRC and letrozole can improve AI patients' clinical symptoms,increase ovulation rate,pregnancy rate,and embryo survival rate.The active ingredients in FKYRC can comprehensively regulate the core targets of AI,and may promote follicular development and maturation in infertile patients with ovulation disorders through signaling pathways such as estrogen,P53,and AGE-RAGE,thereby increasing pregnancy rate.

Objective To explore the clinical application value of simple artery occlusion (SAO) in revealing intersegmental planes during thoracoscopic pulmonary segmentectomy. Methods A retrospective analysis was conducted on the clinical data of patients who underwent thoracoscopic pulmonary segmentectomy at the First Affiliated Hospital of Xiamen University from February 2022 to December 2023. Patients were divided into a conventional group and a SAO group based on the method used to reveal the intersegmental plane during surgery. The two groups were compared in terms of intraoperative blood loss, operation time, postoperative drainage volume, time to intubation, postoperative pulmonary air leakage, and conversion to open thoracotomy rate. Results A total of 318 patients were included. There were 181 patients in the conventional group, including 86 males and 95 females, with an average age (53.35±9.20) years, and there were 137 patients in the SAO group, including 58 males and 79 females, with an average age (55.26±11.46) years. There were no statistical differences in general patient information between the two groups (P>0.05). The SAO group had less intraoperative blood loss [MD=17.568, 95%CI (9.968, 25.168), P<0.001] and postoperative drainage volume [MD=275.587, 95%CI (188.999, 362.175), P<0.001], shorter drainage tube duration [MD=1.000, 95%CI (1.000, 2.000), P<0.001] and operation time [MD=20.709, 95%CI (16.258, 25.159), P<0.001]. The incidence of postoperative pulmonary air leakage complications in the SAO group was lower than that in the conventional group [RR=0.361, 95%CI (0.181, 0.722), P=0.003]. Conclusion SAO can reduce surgical difficulty, shorten operation time, decrease the incidence of postoperative pulmonary air leakage, and enhance the safety of anatomical pulmonary segmentectomy, making it worthy of clinical promotion and application.

Objective To discuss the main pathological types and imaging characteristics of pulmonary nodules that are highly suspected to be malignant in clinical practice but are pathologically confirmed to be benign. Methods A retrospective analysis was performed on the clinical data of patients with pulmonary nodules who were initially highly suspected of malignancy but were subsequently pathologically confirmed to be benign. These patients were treated at the First Affiliated Hospital of Xiamen University from December 2020 to April 2023. Based on the outcomes of preoperative discussions, the patients were categorized into a benign group and a suspicious malignancy group. The clinical data and imaging characteristics of both groups were compared. Results A total of 232 patients were included in the study, comprising 112 males and 120 females, with a mean age of (50.7±12.0) years. Among these, 127 patients were classified into the benign group, while 105 patients were categorized into the suspicious malignancy group. No statistically significant differences were observed between the two groups regarding age, gender, symptoms, smoking history, or tumor history (P>0.05). However, significant differences were noted in nodule density, CT values, margins, shapes, and malignant signs (P＜0.05). Further analysis revealed that in the suspicious malignancy group, solid nodules were predominantly characterized by collagen nodules and fibrous tissue hyperplasia (33.3%), followed by tuberculosis (20.4%) and fungal infections (18.5%). In contrast, non-solid nodules were primarily composed of collagen nodules and fibrous tissue hyperplasia (41.2%) and atypical adenomatous hyperplasia (17.7%). Conclusion Benign pulmonary nodules that are suspected to be malignant are pathologically characterized by the presence of collagen nodules, fibrous tissue hyperplasia, tuberculosis, atypical adenomatous hyperplasia, and fungal infections. Radiologically, these nodules typically present as non-solid lesions and may exhibit features suggestive of malignancy, including spiculation, lobulation, cavitation, and pleural retraction.

Glioma is the most common primary malignant brain tumor and its microenvironment exhibits immunosuppressive properties. Macrophages and T cells are the main immune cells of glioma, which engage in highly dynamic interactions. Cytokines such as interleukin-2 (IL-12), interleukin-10 (IL-10), interferon-γ (IFN-γ),and transforming growth factor-β (TGF-β) determine the direction and intensity of the anti-tumor immune response through finely regulating macrophage polarization and T cell subset differentiation. Co-stimulatory molecules on the surface of T cells are mostly members of the immunoglobulin superfamily (IgSF); in addition,co-stimulatory molecules including CD80/CD86, T cell inducible co-stimulatory molecule and its ligand (ICOS /ICOS-L),CD40L/CD40, OX40L/OX40 and glucocorticoid-induced tumor necrosis factor receptor related protein and its ligand (GITR /GITR-L) are involved in initiating,enhancing or inhibiting T cell activation,and collaboratively shape the overall tumor immune microenvironment. The in-depth understanding of these factors and molecular pathways can help optimize immunotherapeutic strategies for glioma and provide new therapeutic targets.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that seriously affects the health of the elderly, and the early diagnosis is crucial to slow down the progression of the disease. This review systematically examines the integrative applications of multimodal digital technologies in early AD identification, encompassing cognitive assessment, neuroimaging analysis, biomarker detection, and polygenic risk prediction, with the goal of enhancing diagnostic accuracy and operational efficiency. It was found that artificial intelligence-driven digital tools significantly improved screening efficiency by capturing subtle behavioral patterns and physiological signatures. Machine learning algorithms integrated with multimodal neuroimaging data optimize sensitivity in detecting structural brain abnormalities, while combinatorial analysis of digital biomarkers enables high-precision staging of AD pathology. Recent advancements highlight the critical role of digital technologies in facilitating multimodal biomarker integration and streamlining diagnostic workflows. The convergence of these innovative approaches provides a robust framework for early AD screening, offering patients accessible and efficient diagnostic pathways.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that seriously affects the health of the elderly, and the early diagnosis is crucial to slow down the progression of the disease. This review systematically examines the integrative applications of multimodal digital technologies in early AD identification, encompassing cognitive assessment, neuroimaging analysis, biomarker detection, and polygenic risk prediction, with the goal of enhancing diagnostic accuracy and operational efficiency. It was found that artificial intelligence-driven digital tools significantly improved screening efficiency by capturing subtle behavioral patterns and physiological signatures. Machine learning algorithms integrated with multimodal neuroimaging data optimize sensitivity in detecting structural brain abnormalities, while combinatorial analysis of digital biomarkers enables high-precision staging of AD pathology. Recent advancements highlight the critical role of digital technologies in facilitating multimodal biomarker integration and streamlining diagnostic workflows. The convergence of these innovative approaches provides a robust framework for early AD screening, offering patients accessible and efficient diagnostic pathways.