Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

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 This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

In recent years,the incidence and mortality of heatstroke have been increasing annually alongside global warming,with a marked rise in cases exhibiting atypical symptoms.To address the increasingly complex challenges in heatstroke prevention and treatment,Heatstroke Prevention and Treatment Research Center of Chinese PLA,Expert Group of Heatstroke Prevention and Treatment of Chinese PLA,and Chinese PLA Professional Committee of Critical Care Medicine have jointly developed this guideline(2025 edition).Utilizing the Grading of Recommendations Assessment,Development and Evaluation(GRADE)system,Appraisal of Guidelines for Research and Evaluation(AGREE)criteria,and Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards,and based on the 2015 draft"Expert Consensus on the Standardized Diagnosis and Treatment of Heatstroke"and the 2019"Chinese Expert Consensus on the Diagnosis and Treatment of Heatstroke",this guideline has been crafted.This guideline provides 25 evidence-based recommendations to guide the prevention,treatment and research of heatstroke,which thoroughly covers 8 critical domains:clinical classification,pathophysiological mechanisms,clinical manifestations,diagnostic criteria,differential diagnosis,treatment protocols,rehabilitation and return to work,and prevention.

BACKGROUND:Knee osteoarthritis is a common degenerative disease that significantly impacts patients'quality of life and increases the societal healthcare burden.Early and accurate diagnosis of knee osteoarthritis is crucial for the treatment and prognosis of patients.Traditional diagnostic methods are not only subjective and time-consuming but also do not guarantee consistently high accuracy.OBJECTIVE:To develop an automatic diagnostic method for knee osteoarthritis based on deep learning,utilizing deep learning networks to improve diagnostic accuracy and efficiency.METHODS:A new network model,YOLOV8-ViT,was proposed by replacing the backbone network of YOLOv8n with the Efficient-ViT network and incorporating attention mechanisms for the automatic identification and classification of X-ray images of knee osteoarthritis.The experimental dataset included 5 078 X-ray images of patients with knee osteoarthritis obtained from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine.Three imaging physicians annotated the sites of knee osteoarthritis and classified them according to the Kellgren-Lawrence grading standard using Labelme software,and the results were combined.The evaluation indicators used in this study included Precision,F1 score,mean average precision(mAP),Recall,val/box_loss,val/cls_loss,and val/dfl_loss.RESULTS AND CONCLUSION:The experimental results showed that the YOLOV8-ViT model outperformed the YOLOv5n,YOLOv8n,and YOLOv9n models in terms of precision,mAP50,mAP50-95,F1 score,and Recall,while lowering val/box_loss,val/cls_loss,and val/dfl_loss by 0.496,0.45,and 0.523;1.037,0.305,and 0.728;and 0.267,0.654,and 0.854,respectively.These experimental data validate that this model has high detection accuracy.

Purpose To investigate the role of ultrasound-guided fine needle aspiration cytology(US-FNAC)in the diagnosis of breast cancer.Methods Fine needle aspiration cytology(FNAC)samples of 203 patients with breast cancer were selected and prepared by liquid-based cytology.The results of histopathology after neoadjuvant therapy were used as the gold standard to compare with the diagnostic results of FNAC samples,and then evaluated the diagnos-tic coincidence rate of FNAC samples.Results Of 203 axillary lymph node FNAC samples,111 cases were diagnosed as positive,38 cases were diagnosed as suspicious for positivity,and 54 cases were diagnosed as negative.The diag-nostic accuracy of FNAC was 85.2％,the sensitivity of FNAC was 98.0％,and the specificity of FNAC was 90.0％.Conclusion FNAC has high sensitivity and accuracy in the diagnosis of axillary lymph node metastasis.Sentinel lymph node biopsy is recommended for patients with negative FNAC but clinically and radiographically suspected lymph node metastasis.

Aim To elucidate the molecular mecha-nism underlying the inhibitory effect of liquidambaric acid(LDA)targeting TNF receptor associated factor 6(TRAF6)in colorectal cancer.Methods This study employed microscale thermophoresis(MST),drug af-finity responsive target stability assay(DARTS)and cellular thermal shift assay(CETSA)to confirm the direct binding of LDA to TRAF6.Additionally,we generated TRAF6 knockout colorectal cancer HCT116 cells using CRISPR/Cas9 technology,and assessed the impact of LDA on TRAF6-regulated Hippo/YAP and Wnt signaling pathways through immunofluorescence a-nalysis and TOPFlash/Renilla luciferase reporter sys-tem.Co-IP and proximity ligation assays(PLA)were conducted to investigate LDA-regulated TRAF6 pro-tein-protein interactions and elucidate molecular mech-anisms.Results The direct binding of LDA to TRAF6 was confirmed in cell lysates and living cells.LDA promoted TRAF6-dependent nuclear translocation of YAP in colorectal cancer cells,and inhibited Wnt signaling by overexpressing TRAF6.Co-IP and PLA revealed that TRAF6 formed a tripartite complex with YAP and β-catenin in colon cancer cells,where TRAF6 was a key scaffolding protein of the tripartite complex.LDA disrupted the interactions between the TRAF domain of TRAF6 and YAP,as well as YAP and β-catenin.Conclusion LDA regulates Hippo/YAP signaling pathway by targeting TRAF6 and inhib-its colorectal cancer.

his study was aimed at understanding the drug resistance of Acinetobacter baumannii,exploring the consistency between resistance genes and resistance phenotypes,and providing a basis for the rational use of antibiotics in clinical practice.A total of 88 strains of Acinetobacter baumannii were isolated from hospitals at tertiary level or above within the jurisdiction from 2021 to 2023,and subjected to drug resistance testing and whole genome sequencing.The original data were analyzed for the entire genome process with a Microobench pathogenic microorganism analysis workstation(without reference splicing),and resistance genes were predicted and annotated.The strains were subjected to multi-point sequence analysisand minimum spanning tree construction.Among 88 strains of Acinetobacter baumannii,carbapenem resistant strains(CRAB)accounted for 72.73%,and 98.44%of CRAB showed multidrug resistance.In the past three years,the resistance to multiple drugs has increased.The cgMLST analysis showed that the ST2 type accounted for 89.77%,and a new ST type was discovered.After cgMLST analysis,the minimum spanning tree was generated,and the genetic relationship of the same ST type was closer.The same ST2 type was further divided into four clusters.Binary logistic regression analysis conducted on resistance genes and resistance phenotypes revealed that resistance genes APH(3″)-Ib,armA,ADC-73,sul1,and sul2 positively correlated with resistance phenotypes.The ST2 type was the main Acinetobacter baumannii type,and showed high rates of multidrug resistance and carriage of multiple resistance genes.The drug resistance situation is severe.The consistency between common resistance genes and resistance phenotypes is good.Clinical management of Acinetobacter baumannii infection must be strengthened to prevent outbreaks and transmission.

OBJECTIVE: To investigate the predictive value of the prognostic nutritional index (PNI) and systemic inflammatory response index (SIRI) for short-term efficacy and prognosis in newly treated patients with peripheral T-cell lymphoma (PTCL). METHODS: The general data, laboratory indicators, disease stage and other clinical data of 91 newly treated PTCL patients admitted to the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2023 were retrospectively analyzed. The optimal cutoff values for PNI and SIRI were determined using receiver operating characteristic (ROC) curves, and the patients were stratified into groups based on these cutoffs to compare clinical features and short-term efficacy between the different groups. Kaplan-Meier method was used to plot survival curves, and univariate and multivariate analyses were performed to identify the factors affecting overall survival (OS). RESULTS: The optimal cutoff values for PNI and SIRI were 45.30 and 1.74×10⁹/L, respectively. Patients in different PNI groups showed statistically significant differences in age, Ann Arbor stage, lactate dehydrogenase (LDH) level, international prognostic index (IPI), prognostic index for PTCL-not otherwise specified (PIT), pathological subtypes, and complete response (CR) rate (P < 0.05). PTCL patients in different SIRI groups exhibited significant differences in Ann Arbor stage, LDH level, IPI score, PIT score, and CR rate (P < 0.05). Logistic regression analysis showed that age ≥60 years old (OR =2.750), Ann Arbor stage Ⅲ-Ⅳ (OR =5.200), IPI score ≥2 (OR =7.650), low PNI (OR =3.296), and high SIRI (OR =3.130) were independent risk factors affecting treatment efficacy in PTCL patients (P < 0.05). Cox proportional hazards regression model analysis showed that low PNI and elevated β₂-microglobulin (β₂-MG) levels were independent risk factors affecting OS (P < 0.05). CONCLUSION PNI and SIRI have certain application value in evaluating short-term efficacy and prognosis in patients with PTCL. Compared with SIRI, PNI demonstrates greater predictive value for patient prognosis.
Humans ; Prognosis ; Lymphoma, T-Cell, Peripheral/therapy* ; Retrospective Studies ; Nutrition Assessment ; Male ; Female ; Middle Aged ; ROC Curve ; Inflammation

OBJECTIVE: To study the clinical efficacy of Wenyang Lishui Formula (WYLSF) in preventing ovarian hyperstimulation syndrome (OHSS) and explore the suitable range of estradiol (E₂) on the human chorionic gonadotropin (HCG) day in patients with OHSS using WYLSF. METHODS: Part I: eligible patients at high risk for OHSS undergoing ovulation induction between January and December, 2023 were randomized into 2 groups based on the actual treatment. The treatment group received 200 mL WYLSF formula twice daily for 5 days after oocyte retrieval in a combination of lifestyle coaching (LC) intervention including regular diet and exercise, whereas the LC group received LC intervention alone. The incidence of OHSS, OHSS self-assessment scales, changes in E₂ levels on HCG day and 5 days after oocyte retrieval, ovarian morphology changes, and menstrual recovery were compared between the two groups. Part II: patients at high risk for OHSS treated with WYLSF were studied. The optimal E₂ threshold on the HCG day was determined using the maximum selection test, and a multivariate analysis was adopted to compare the relationship between different E₂ levels on HCG day and hospitalization rate, incidence of moderate to severe OHSS, and self-assessment scales, to explore the preventive effect of WYLSF on OHSS in patients with varying E₂ levels. RESULTS: A total of 120 patients were included in the Part I analysis. The treatment group (60 cases) showed a significant reduction in the incidence, duration, and severity of abdominal distension, as well as the incidence of vomiting compared with the LC group (P<0.05). The post-retrieval E₂ levels in the treatment group decreased significantly more (P=0.032). Among 1,652 patients treated with WYLSF in the Part II, 90 patients with ⩽ 10092 pmol/L, 159 with >31074 pmol/L, and 1,403 in the middle range group were formed based on E₂ levels on HCG day in Part two analysis. Univariate and regression analyses showed that patients with E₂ levels >31073 pmol/L had a significantly higher incidence of moderate to severe OHSS compared to those with E₂ levels ⩽ 10092 pmol/L (P<0.05). CONCLUSIONS WYLSF can effectively reduce specific symptoms in high-risk OHSS patients after ovulation induction and significantly lower E₂ levels. It may be more suitable for high-risk OHSS patients with E₂ levels <31073 pmol/L on HCG day. (Registration No. MR-11-23-032493, https://www.medicalresearch.org.cn/login ).
Humans ; Ovarian Hyperstimulation Syndrome/blood* ; Female ; Adult ; Prospective Studies ; Drugs, Chinese Herbal/pharmacology* ; Estradiol/blood* ; Ovulation Induction ; Chorionic Gonadotropin