1.Guidelines for the perioperative diagnosis and treatment of oncogene-driven non-small cell lung cancer (2026)
Weidong WANG ; Yongbin LIN ; Hui TIAN ; Gaofeng LI ; Shun XU ; Yongde LIAO ; Haitao MA ; Junfeng LIU ; Chundong GU ; Xiaolong YAN ; Shumin WANG ; Daqiang SUN ; Jianyang LIU ; Tao XUE ; Shaohua MA ; Zhigang LI ; Shuanghu YUAN ; Gen LIN ; Ling CAI ; Jianping ZHOU ; Wenzhao ZHONG ; Naixin LIANG ; Yi HAN ; Junfeng WANG ; Weidong ZHANG ; Xin WANG ; Lianjuan CHEN ; Lunxu LIU ; Xiuyi ZHI ; Lanjun ZHANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(09):1337-1353
Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.
2.Clinical effects of Supplemented Buyang Huanwu Decoction on postoperative patients with lumbar vertebral fracture complicated with spinal cord injury due to Qi Deficiency and Blood Stasis Pattern
Jia-man YANG ; Tong LIU ; De-hui FAN ; Mei-yi SU ; Ying LIN ; Man-guang LIANG ; Zhi-wen OU ; Shun-cong ZHANG
Chinese Traditional Patent Medicine 2025;47(11):3630-3634
AIM To explore the clinical effects of Supplemented Buyang Huanwu Decoction on postoperative patients with lumbar vertebral fracture complicated with spinal cord injury due to Qi Deficiency and Blood Stasis Pattern.METHODS One hundred and twenty patients were randomly assigned into control group(60 cases)for 6-week intervention of conventional treatment,and observation group(60 cases)for 6-week intervention of both Supplemented Buyang Huanwu Decoction and conventional treatment.The changes in clinical effects,TCM syndrome scores,spinal cord conduction signals(SEP amplitude,MEP amplitude),serum neurotrophic factors(NGF,IGF-1,BDNF),coagulation and inflammatory indices(PT,APTT,TNF-α,IL-1 β)and incidence of adverse reactions were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P<0.05).After the treatment,the two groups displayed decreased TCM syndrome scores,TNF-α,IL-1β(P<0.05),increased spinal cord conduction signals,coagulation and inflammatory indices(P<0.05),and shortened PT,APTT(P<0.05),especially for the observation group(P<0.05).No significant difference in incidence of adverse reactions was found between the two groups(P>0.05).CONCLUSION For the patients with lumbar vertebral fracture complicated with spinal cord injury due to Qi Deficiency and Blood Stasis Pattern,Supplemented Buyang Huanwu Decoction can safely and effectively promote neurological function recovery.
3.Predictive model for intra-abdominal pressure in critically ill patients based on multiple regression and variational auto-encoders
Yi ZHANG ; Zhi-qin ZHU ; Wen-lin LI ; Dong-chu ZHAO ; Chang LIU ; Zhi-wei FAN ; Zhen WANG ; Lian-yang ZHANG ; Hao TANG
Chinese Medical Equipment Journal 2025;46(11):10-17
Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.
4.Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine.
Xin-Ran DU ; Meng-Yi WU ; Mao-Can TAO ; Ying LIN ; Chao-Ying GU ; Min-Feng WU ; Yi CAO ; Da-Can CHEN ; Wei LI ; Hong-Wei WANG ; Ying WANG ; Yi WANG ; Han-Zhi LU ; Xin LIU ; Xiang-Fei SU ; Fu-Lun LI
Journal of Integrative Medicine 2025;23(6):641-653
Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy*
;
Humans
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Medicine, Chinese Traditional/methods*
;
Integrative Medicine
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Drugs, Chinese Herbal/therapeutic use*
;
Practice Guidelines as Topic
5.Inflammatory Bowel Disease and Dementia: Evidence Triangulation from a Meta-Analysis of Observational Studies and Mendelian Randomization Study.
Di LIU ; Mei Ling CAO ; Shan Shan WU ; Bing Li LI ; Yi Wen JIANG ; Teng Fei LIN ; Fu Xiao LI ; Wei Jie CAO ; Jin Qiu YUAN ; Feng SHA ; Zhi Rong YANG ; Jin Ling TANG
Biomedical and Environmental Sciences 2025;38(1):56-66
OBJECTIVE:
Observational studies have found associations between inflammatory bowel disease (IBD) and the risk of dementia, including Alzheimer's dementia (AD) and vascular dementia (VD); however, these findings are inconsistent. It remains unclear whether these associations are causal.
METHODS:
We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia. Mendelian randomization (MR) analysis based on summary genome-wide association studies (GWASs) was performed. Genetic correlation and Bayesian co-localization analyses were used to provide robust genetic evidence.
RESULTS:
Ten observational studies involving 80,565,688 participants were included in this meta-analysis. IBD was significantly associated with dementia (risk ratio [ RR] =1.36, 95% CI = 1.04-1.78; I 2 = 84.8%) and VD ( RR = 2.60, 95% CI = 1.18-5.70; only one study), but not with AD ( RR = 2.00, 95% CI = 0.96-4.13; I 2 = 99.8%). MR analyses did not supported significant causal associations of IBD with dementia (dementia: odds ratio [ OR] = 1.01, 95% CI = 0.98-1.03; AD: OR = 0.98, 95% CI = 0.95-1.01; VD: OR = 1.02, 95% CI = 0.97-1.07). In addition, genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.
CONCLUSION
Our study did not provide genetic evidence for a causal association between IBD and dementia risk. The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
Humans
;
Mendelian Randomization Analysis
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Inflammatory Bowel Diseases/complications*
;
Dementia/etiology*
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Observational Studies as Topic
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Genome-Wide Association Study
6.Analysis of Tongue and Face Image Features of Anemic Women and Construction of Risk-Screening Model.
Hong Yuan FU ; Yi CHUN ; Ya Han ZHANG ; Yu WANG ; Yu Lin SHI ; Tao JIANG ; Xiao Juan HU ; Li Ping TU ; Yong Zhi LI ; Jia Tuo XU
Biomedical and Environmental Sciences 2025;38(8):935-951
OBJECTIVE:
To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance.
METHODS:
A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated.
RESULTS:
Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818].
CONCLUSION
Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans
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Female
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Tongue/diagnostic imaging*
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Adult
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Anemia/diagnosis*
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Middle Aged
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Face/diagnostic imaging*
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Young Adult
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Machine Learning
7.Molecular Characterization of New Recombinant Human Adenoviruses Detected in Children with Acute Respiratory Tract Infections in Beijing, China, 2022-2023.
Yi Nan GUO ; Ri DE ; Fang Ming WANG ; Zhen Zhi HAN ; Li Ying LIU ; Yu SUN ; Yao YAO ; Xiao Lin MA ; Shuang LIU ; Chunmei ZHU ; Dong QU ; Lin Qing ZHAO
Biomedical and Environmental Sciences 2025;38(9):1071-1081
OBJECTIVE:
Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control.
METHODS:
Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes.
RESULTS:
Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16.
CONCLUSION
A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans
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Adenoviruses, Human/isolation & purification*
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Respiratory Tract Infections/epidemiology*
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Child, Preschool
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Child
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Recombination, Genetic
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Male
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Beijing/epidemiology*
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Infant
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Female
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Phylogeny
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Adenovirus Infections, Human/epidemiology*
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Acute Disease
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Genome, Viral
8.Human Cytomegalovirus Infection and Embryonic Malformations: The Role of the Wnt Signaling Pathway and Management Strategies.
Xiao Mei HAN ; Bao Yi ZHENG ; Zhi Cui LIU ; Jun Bing CHEN ; Shu Ting HUANG ; Lin XIAO ; Dong Feng WANG ; Zhi Jun LIU
Biomedical and Environmental Sciences 2025;38(9):1142-1149
Human cytomegalovirus (HCMV) poses a significant risk of neural damage during pregnancy. As the most prevalent intrauterine infectious agent in low- and middle-income countries, HCMV disrupts the development of neural stem cells, leading to fetal malformations and abnormal structural and physiological functions in the fetal brain. This review summarizes the current understanding of how HCMV infection dysregulates the Wnt signaling pathway to induce fetal malformations and discusses current management strategies.
Humans
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Cytomegalovirus Infections/virology*
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Wnt Signaling Pathway
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Pregnancy
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Female
;
Cytomegalovirus/physiology*
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Pregnancy Complications, Infectious/virology*
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Congenital Abnormalities/virology*
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Animals
9.Associations of Genetic Risk and Physical Activity with Incident Chronic Obstructive Pulmonary Disease: A Large Prospective Cohort Study.
Jin YANG ; Xiao Lin WANG ; Wen Fang ZHONG ; Jian GAO ; Huan CHEN ; Pei Liang CHEN ; Qing Mei HUANG ; Yi Xin ZHANG ; Fang Fei YOU ; Chuan LI ; Wei Qi SONG ; Dong SHEN ; Jiao Jiao REN ; Dan LIU ; Zhi Hao LI ; Chen MAO
Biomedical and Environmental Sciences 2025;38(10):1194-1204
OBJECTIVE:
To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease.
METHODS:
This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used.
RESULTS:
During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity.
CONCLUSION
Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans
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Pulmonary Disease, Chronic Obstructive/epidemiology*
;
Exercise
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Male
;
Female
;
Middle Aged
;
Prospective Studies
;
Aged
;
Genetic Predisposition to Disease
;
Risk Factors
;
United Kingdom/epidemiology*
;
Incidence
;
Adult
10.Predictive model for intra-abdominal pressure in critically ill patients based on multiple regression and variational auto-encoders
Yi ZHANG ; Zhi-qin ZHU ; Wen-lin LI ; Dong-chu ZHAO ; Chang LIU ; Zhi-wei FAN ; Zhen WANG ; Lian-yang ZHANG ; Hao TANG
Chinese Medical Equipment Journal 2025;46(11):10-17
Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

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