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.

To promote the standardization and normalization of perioperative care for follicular unit extraction(FUE) hair transplantation, ensure treatment efficacy, and align with advancements in the specialty, the Nursing Branch of the Chinese Association of Plastic and Aesthetics organized a panel of domestic experts. By integrating evidence-based medicine with clinical practice experience, and following thorough discussions, these experts developed the Clinical Practice Expert Consensus on Perioperative Nursing Care for Follicular Unit Extraction (2025). This consensus provides a comprehensive overview of hair transplantation, covering preoperative preparation, surgical procedures, intraoperative coordination, postoperative management, and complication prevention and treatment. It serves as a key reference and guide for implementing standardized perioperative nursing care in FUE hair transplantation.

Objective To develop an ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method to simultaneously determine 10 main components, including berberine, phellodendrine, specnuezhenide, mangiferin, loganin, paeoniflorin, geniposide, baicalin, and acteoside in Compound Dihuang oral solution. Methods An UPLC-MS/MS method was established with an ACQUITY UPLC BEH-C18 （2.1 mm×100 mm, 1.7 μm）column and mobile phase of 0.1% formic water（A）-methanol solution（B） in a gradient elution manner. The flow rate of mobile phase was 0.2 ml/min.The temperature of column was 30℃. The injection volume was 2 μl. The MS detection was in MRM mode. Results 10 components in Compound Dihuang oral solution had a good linear relationship within their concentration range,and the precision, repeatability, stability and recovery met the requirements. The contents of berberine, phellodendrine, specnuezhenide, mangiferin, loganin, paeoniflorin, geniposide, baicalin, and acteoside in 7 batches of samples were （89.7-95.6） μg/ml, （164.0-177.7） μg/ml, （540.0-610.0） μg/ml, （408.7-429.0） μg/ml, （726.0-825.0） μg/ml, （503.7-572.0） μg/ml, （1380.0-1540.0） μg/ml, （2596.7-2896.7) μg/ml, （4866.7-5520.0) μg/ml, （61.8-67.2) μg/ml, respectively. Conclusion The established method was easy to be repeated and operated. The contents of 10 components in Compound Dihuang oral solution could be determined quickly and accurately, which provided a reference for the quality control of hospital preparation.

Organophosphorus pesticide(OP)is one of the most widely used pesticides in the world with the largest dosage.Acute organophosphorus pesticide poisoning(AOPP)is a common clinical disease,and AOPP accounts for 20%-50%of poisoning cases in China every year,with case fatality rate of 3%-40%.Bromophos(BDF)is a long-acting anticoagulant rodenticide,which inhibits vitamin K epoxide reductase and interferes with the synthesis of coagulation factorsⅡ,Ⅶ,Ⅸ and Ⅹ,leading to coagulation dysfunction.This article discusses the multidisciplinary diagnosis and treatment(MDT)process of a patient with combined poisoning of dichlorvos and bromadiolone.The article explores blood purification,management of coagulation abnormalities,secondary infection,atropinization and altered consciousnes in patients with organophosphorus poisoning and anticoagulant rodenticide compound poisoning,with the aim of providing clinicians with references for early diagnosis and treatment.

Organophosphorus pesticide(OP)is one of the most widely used pesticides in the world with the largest dosage.Acute organophosphorus pesticide poisoning(AOPP)is a common clinical disease,and AOPP accounts for 20%-50%of poisoning cases in China every year,with case fatality rate of 3%-40%.Bromophos(BDF)is a long-acting anticoagulant rodenticide,which inhibits vitamin K epoxide reductase and interferes with the synthesis of coagulation factorsⅡ,Ⅶ,Ⅸ and Ⅹ,leading to coagulation dysfunction.This article discusses the multidisciplinary diagnosis and treatment(MDT)process of a patient with combined poisoning of dichlorvos and bromadiolone.The article explores blood purification,management of coagulation abnormalities,secondary infection,atropinization and altered consciousnes in patients with organophosphorus poisoning and anticoagulant rodenticide compound poisoning,with the aim of providing clinicians with references for early diagnosis and treatment.

BACKGROUND: Immunotherapy has been a standard treatment for the patients with advanced non-small cell lung cancer (NSCLC), however, reliable biomarkers for predicting the response remain unclear. This study explores the subpopulations of lymphocytes in bronchoalveolar lavage fluid (BALF) and combines clinical and laboratory examination indicators of NSCLC patients to identify potential biomarkers related to immunotherapy. METHODS: A retrospective analysis was conducted on 82 patients with locally advanced or metastatic NSCLC who underwent electronic bronchoscopy and received first-line immunotherapy at Beijing Chest Hospital, Capital Medical University between March 2020 and November 2022. Logistic regression and random forest models were employed to determine the correlation between immune cell subsets in BALF and response of immunotherapy. The predictive value was validated by the model. RESULTS: All patients enrolled received first-line immunotherapy, and the efficacy was evaluated according to clinical guidelines: among the 82 patients included, 48 patients got objective response and the other 34 did not achieve. The relationship between collected indicators and the best clinical treatment response was analyzed. The result shows that a higher percentage of total lymphocytes in BALF was associated with good response of first-line immunotherapy (P<0.05), while a higher percentage of T helper cells in BALF was associated with poor prognosis (P<0.05). CONCLUSIONS The proportions of total lymphocytes and T helper cells in BALF could be used as predictive biomarkers for first-line immunotherapy in late stage NSCLC. A multivariable model improves predictive accuracy.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Male ; Lung Neoplasms/pathology* ; Female ; Middle Aged ; Immunotherapy ; Retrospective Studies ; Aged ; Bronchoalveolar Lavage Fluid/cytology* ; Case-Control Studies ; Adult ; Treatment Outcome

Objective To establish an early prediction model for the diagnosis of severe acute pancreatitis based on the improved machine learning models,and to analyze its clinical value.Methods A case-control study was conducted on 352 patients with acute pancreatitis admitted to the Gastroenterology and Hepatobiliary Surgery Departments of the Army Medical Center of PLA and Emergency and Critical Care Medicine Department of No.945 Hospital of Joint Logistics Support Force of PLA from January 2014 to August 2023.According to the severity of the disease,the patients were divided into the severe group(n=88)and the non-severe group(n=264).The RUSBoost model and improved Archimead optimization algorithm was used to analyze 39 routine laboratory biochemical indicators within 48 h after admission to construct an early diagnosis and prediction model for severe acute pancreatitis.The task of feature screening and hyperparameter optimization was completed simultaneously.The ReliefF algorithm feature importance rank and multivariate logistic analysis were used to analyze the value of the selected features.Results In the training set,the area under curve(AUC)of the improved machine learning model was 0.922.In the testing set,the AUC of the improved machine learning model reached 0.888.The 4 key features of predicting severe acute pancreatitis based on the improved Archimedes optimization algorithm were C-reactive protein,blood chlorine,blood magnesium and fibrinogen level,which were consistent with the results of ReliefF algorithm feature importance ranking and multivariate logistic analysis.Conclusion The application of improved machine learning model analyzing the laboratory examination results can help to early predict the occurrence of severe acute pancreatitis.

Objectives:To investigate the clinical and genetic features of young Chinese patients with myeloproliferative neoplasms (MPN) .Methods:In this cross-sectional study, anonymous questionnaires were distributed to patients with MPN patients nationwide. The respondents were divided into 3 groups based on their age at diagnosis: young (≤40 years) , middle-aged (41-60 years) , and elderly (>60 years) . We compared the clinical and genetic characteristics of three groups of MPN patients.Results:1727 assessable questionnaires were collected. There were 453 (26.2%) young respondents with MPNs, including 274 with essential thrombocythemia (ET) , 80 with polycythemia vera (PV) , and 99 with myelofibrosis. Among the young group, 178 (39.3%) were male, and the median age was 31 (18-40) years. In comparison to middle-aged and elderly respondents, young respondents with MPN were more likely to present with a higher proportion of unmarried status (all P<0.001) , a higher education level (all P<0.001) , less comorbidity (ies) , fewer medications (all P<0.001) , and low-risk stratification (all P<0.001) . Younger respondents experienced headache (ET, P<0.001; PV, P=0.007; MF, P=0.001) at diagnosis, had splenomegaly at diagnosis (PV, P<0.001) , and survey (ET, P=0.052; PV, P=0.063) . Younger respondents had fewer thrombotic events at diagnosis (ET, P<0.001; PV, P=0.011) and during the survey (ET, P<0.001; PV, P=0.003) . JAK2 mutations were found in fewer young people (ET, P<0.001; PV, P<0.001; MF, P=0.013) ; however, CALR mutations were found in more young people (ET, P<0.001; MF, P=0.015) . Furthermore, mutations in non-driver genes (ET, P=0.042; PV, P=0.043; MF, P=0.004) and high-molecular risk mutations (ET, P=0.024; PV, P=0.023; MF, P=0.001) were found in fewer young respondents. Conclusion:Compared with middle-aged and elderly patients, young patients with MPN had unique clinical and genetic characteristics.

Objective:To retrieve, evaluate and summarize the best evidence of exercise reversal intervention in the elderly with cognitive frailty, and to provide evidence for guiding exercise in elderly patients.Methods:This study was a summary of evidence-based nursing evidence. Based on the PIPOST (P: Population; I: Intervention; P: Professional; O: Outcome; S: Setting; T: Type of evidence) mode, the evidence of exercise reversal intervention in the elderly with cognitive frailty in 25 relevant guideline network and association websites, Chinese and foreign language comprehensive databases such as PubMed, CINAHL, Web of Science, Embase, Chinese Biomedical Database, China National Knowledge Internet and others were searched, extracted and integrated. The retrieval time was from January 1, 2013 to February 14, 2022.Results:A total of 22 articles were included, including 3 guidelines, 2 expert consensuses, 1 clinical decision-making, 1 evidence summary, 9 Meta analysis, and 6 randomized controlled trials. Finally, 28 pieces of the best evidence including 7 dimensions were namely formulate principles,overall assessment, exercise mode, exercise intensity, exercise time and frequency, exercise management, health guidance.Conclusions:This study summarized the best evidence of exercise intervention in the elderly with cognitive frailty, which are systematic, comprehensive, rigorous, and reliable. It can provide references for healthcare administrators to dynamically evaluate patients′cognitive frailty status, formulate personalized exercise programs, and standardize exercise guidance for patients, so as to delay or even reverse cognitive frailty.

HIV infection is a serious challenge to global public health. Timely and accurate early diagnosis and early initiation of antiretroviral therapy can effectively resist the spread of the virus, and improve the immune function of HIV-infected patients, thereby improve patients′ outcomes and reduce patients′ hospitalization and mortality. Efficient and sensitive testing is a prerequisite for early diagnosis of HIV infection and is also a focus in the prevention and control of HIV epidemics. Serologic testing has been the most widely used HIV detection technology till now. However, it has been difficult for the traditional antibody detection technology to detect HIV acute infection in a timely and accurate manner and therefore restricted the early diagnosis of HIV infection. In recent years, a variety of new detection technologies, such as HIV antigen/antibody combined detection and biosensors, with their high sensitivity, have significantly shortened the window period for the diagnosis of HIV infection, bringing new hope for early diagnosis of HIV. This paper reviews the principle, scope of application, and application prospect of serological detection technology for HIV infection and provides a reference for the development of new HIV testing strategies.