Background A diverse cohort of patients and susceptible individuals congregate in healthcare facilities, where exposure to pathogenic microorganisms associated with respiratory infectious diseases constitutes a significant risk factor for cross-infection. Central air-conditioning ventilation systems improve some indoor environment indicators while exacerbating the risk of transmission of respiratory infectious diseases. Objective To investigate the distribution characteristics of microbial communities in the central air-conditioning ventilation systems of hospitals, providing a scientific basis for the selection of microbial indicators in hygiene standards for hospital central air-conditioning ventilation systems and for hospital risk early warning systems. Methods In October 2023, two central air-conditioning ventilation systems were selected from a Grade 3A hospital in Shanghai: one was an all-air air-conditioning system serving the waiting area on the ground floor, and the other was a fan coil plus fresh air system serving the outpatient area on the third floor. Samples from four different components of the ventilation systems—air outlets, filters, surface coolers, and condensate trays—were collected for high-throughput sequencing of the 16S rRNA gene to analyze bacterial communities. Alpha-diversity and beta-diversity analyses were performed to investigate the microbial community composition and diversity characteristics of the hospital central air-conditioning ventilation systems. Functional analysis was conducted to determine the relative abundance of bacterial functions in these systems.Results A total of 528 operational taxonomic units (OTUs) were identified, encompassing 20 bacterial phyla, 37 classes, 79 orders, 123 families, and 240 genera. The analysis revealed that the bacterial community was predominantly composed of Proteobacteria, Gemmatimonadates, Bacteroidetes, and Actinobacteria. The diversity analysis indicated that bacterial community richness and diversity were highest in the condensate trays, while no statistically significant differences (P > 0.05) were observed in the bacterial community composition among the air outlets, filters, and surface coolers. The functional analysis showed that the bacterial communities in the central air-conditioning ventilation systems primarily exhibited chemoheterotrophic, oxidative energy-dependent heterotrophic, and ureolytic functional characteristics. Conclusion The dominance of Proteobacteria suggests that this phylum exhibits strong adaptability in the central air-conditioning ventilation systems, possibly related to its ability to survive and reproduce under varying environmental conditions. The diversity analysis indicates that the condensate tray is a critical area for bacterial proliferation in the central air-conditioning ventilation systems. The similarity in environmental conditions among the air outlets, filters, and surface coolers result in similar bacterial community structures. The functional analysis reveals that the bacterial communities possess robust energy conversion and metabolic capabilities, potentially contributing to processes such as organic matter decomposition and nitrogen cycling within the central air-conditioning ventilation systems.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

Background and objective Lung cancer is the cancer with the highest incidence and mortality rates in China,and non-small cell lung cancer(NSCLC)accounts for 80％-85％of all malignant lung tumors.Currently,surgical treat-ment remains the primary treatment modality for lung cancer.In recent years,the effectiveness of immune checkpoint inhibi-tors for NSCLC has become a consensus,and neoadjuvant immunochemotherapy(nICT)has shown promising efficacy and safety in early to intermediate stage NSCLC.However,there are fewer studies related to nICT for locally advanced NSCLC.This study aims to evaluate the efficacy and safety of nICT therapy in locally advanced resectable NSCLC.Methods 85 con-firmed resectable stage ⅢA and ⅢB patients treated in the Department of Thoracic Surgery,Second Hospital of Lanzhou University,from January 2021 to April 2024,were divided into the nICT group(n=32)and the surgery alone group(n=53).Clinical baseline data,perioperative indicators,postoperative complications,imaging response rate,pathological response rate,incidence of adverse events,and quality of life were compared between the two groups.Results There were no statisti-cally significant differences in clinical baseline data between the two groups(P＞0.05).Incidence of choosing thoracotomy was higher in the nICT group than in the surgery alone group(P=0.002).There were no significant differences in surgical time,intraoperative blood loss,number of dissected lymph nodes,duration of chest tube placement,postoperative hospital stay,and R0 resection rate between the two groups(P＞0.05).The overall incidence of postoperative complications was 31.25％in the nICT group and 22.64％in the surgery alone group,with no statistically significant difference(P=0.380).In the nICT group,the objective response rate(ORR)was 84.38％,with 5 cases of complete response(CR)(15.63％),22 cases of partial response(PR)(68.75％),15 cases of pathological response rate(pCR)(46.88％),and 11 cases of major pathological reaponse(MPR)(34.38％).During nICT treatment,12 cases(37.50％)experienced grade 3 treatment-related adverse events,no death induced by adverse events or immune related adverse events.Moreover,the symptoms of the patients were improved after nICT treat-ment.Conclusion Neoadjuvant immunochemotherapy shows promising efficacy in locally advanced resectable NSCLC,with manageable treatment-related adverse events.It is a safe and feasible neoadjuvant treatment modality for locally advanced resectable NSCLC.

Objective Chlorination is often used to disinfect recreational water in large amusement parks;however,the health hazards of chlorination disinfection by-products(DBPs)to occupational populations are unknown.This study aimed to assess the exposure status of chlorinated DBPs in recreational water and the health risks to employees of large amusement parks. Methods Exposure parameters of employees of three large amusement parks in Shanghai were investigated using a questionnaire.Seven typical chlorinated DBPs in recreational water and spray samples were quantified by gas chromatography,and the health risks to amusement park employees exposed to chlorinated DBPs were evaluated according to the WHO's risk assessment framework. Results Trichloroacetic acid,dibromochloromethane,bromodichloromethane,and dichloroacetic acid were detected predominantly in recreational water.The carcinogenic and non-carcinogenic risks of the five DBPs did not exceed the risk thresholds.In addition,the carcinogenic and non-carcinogenic risks of mixed exposure to DBPs were within the acceptable risk limits. Conclusion Typical DBPs were widely detected in recreational water collected from three large amusement parks in Shanghai;however,the health risks of DBPs and their mixtures were within acceptable limits.

Objective To investigate the effect of dexmedetomidine on renal function in patients with septic-associated acute kidney injury(SAKI).Methods A prospective cohort study was conducted in 180 patients with sepsis admitted to ICU in the Second Affiliated Hospital of Guangdong Medical University from October 2021 to April 2023.According to the principle of randomized controlled trials,60 non-acute kidney injury(AKI)patients were divided into S-D group(n = 30,dexmedetomidine + conventional treatment)and S group(n = 30,conventional treatment),and the occurrence and disease score of AKI after treatment were compared between the two groups.A total of 120 AKI patients were divided into SA-D-RT group(n = 30,dexmedetomidine + blood purification + conven-tional treatment),SA-D group(n = 30,dexmedetomidine + conventional treatment),SA-RT group(n = 30,blood purification + conventional treatment)and SA group(n = 30,conventional treatment).Renal function,inflammatory factor level and disease change of the four groups were compared after treatment.Results After treatment,the inci-dence of AKI in S-D group was lower than that in S group,and the APACHEII score and SOFA score in S-D group were lower than those in S group on the 7th day after treatment(P<0.05).After 7 days of treatment,the level of Scr,BUN and CysC in the 4 groups was significantly lower than that on the 1st and 3rd day,and those in the SA-D-RT group were lower than those in the SA-D group,SA-RT group and SA group(P<0.05).After 7 days of treatment,the level of CRP,PCT,TNF-α,IL-6 and IL-1β in four groups was significantly decreased compared with on the 1st and 3rd day,and the level of CRP,PCT,TNF-α,IL-6 and IL-1β in SA-D-RT group was lower than that in SA-D group,SA-RT group and SA group(P<0.05).After 7 days of treatment,the APACHEII score and SOFA score of the four groups were significantly lower than on the 1st and 3rd day,and the scores of the SA-D group were lower than those of the SA-D group,the SA-RT group and the SA group(P<0.05).Conclusion Dexmedetomidine can effectively reduce the incidence of AKI,affect the expression level of renal function markers and inflammatory factors in serum of SAKI patients,and improve the condition of patients.

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

Objective:To assess the feasibility of using the posterosuperior tetralogy (PS-Tetra) score for predicting the prognosis of repair of posterosuperior massive rotator cuff tears.Methods:Data were retrospectively reviewed for patients who underwent repair of posterosuperior massive rotator cuff tears from February 2016 to June 2020. A total of 95 (male 48, female 47) shoulders with an average age of 58.52±8.33 years (range, 27-76 years) were included. The American Shoulder and Elbow Surgeons (ASES) scores and shoulder range of motions (ROM) were used to evaluate shoulder function. MRI was used to assess preoperative fatty infiltration (FI), atrophy, modified Patte's classification, PS-Tetra score and postoperative tendon integrity. The shoulder function was compared between groups of different PS-Tetra scores. The binary logistic regression was used to determine the risk factors of irreparability and retear.Results:83 cases of repair of posterosuperior massive rotator cuff tears were finally included. Complete repairs were performed in 83 cases, and partial repairs were performed in 12 cases. Retear was observed in 17 (20%) cases. The ASES scores (postoperative 58.52±8.33 vs. preoperative 47.30±17.40, t=-19.642, P<0.001), ROM of forward flexion (postoperative 157.60°±13.85° vs. preoperative 116.88°±50.89°, t=-7.272, P<0.001), external rotation (postoperative 45.26°±14.69° vs. preoperative 37.34°±18.65°, t=-4.043, P<0.001) and internal rotation [postoperative L 1 (T 7-buttock) vs. preoperative L 2 (T 7-buttock), Z=-2.737, P=0.006] were significantly improved postoperatively in the group with PS-Tetra score between 0 and 2. In the group with PS-Tetra score of 3 and 4, the ASES scores (postoperative 69.17±15.91 vs. preoperative 46.85±20.73, t=-11.167, P=0.001) were significantly improved postoperatively, while the ROMs were not. Modified Patte stageⅢ[ OR=26.827, 95% CI (2.089, 344.500), P=0.012] was the risk factor of irreparability. Dominant side involvement [ OR=9.407, 95% CI (1.044, 84.784), P=0.046) and PS-Tetra score of 3 and 4 [ OR=5.037, 95% CI (1.028, 26.623), P=0.046] were risk factors of retear. Conclusions:For repair of posterosuperior massive rotator cuff tears, preoperative PS-Tetra score of 3 and 4 was the risk factors of poor postoperative shoulder functions and retear.