Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

With the latest development of information and communication technology, mobile applications for health care have attracted much attention to help cancer patients better manage their diseases. Digital therapeutics is an evidence-based intervention driven by high-quality software programs that prevent, manage, or treat medical disorders or diseases. This paper summarizes the origin, concept and characteristics of digital therapeutics and the application form, effect, challenge and opportunity of symptom management in cancer patients, in order to provide reference for the scientific and efficient application of Digital therapeutics to cancer patients.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Objective:Non-targeted metabolomics based on ultra-performance liquid chromatography mass spectrometry(UPLC-MS)platform was used to study the metabolic characteristics of multiple myeloma(MM)patients,and explore potential new metabolic mechanisms affecting the occurrence and development of MM.Methods:The study enrolled 42 MM patients,including 21 newly diagnosed(ND)patients and 21 relapsed patients(RP),and 21 age-sex matched healthy controls(HC)as subjects.UPLC-MS analysis platform was used to detect small molecule metabolites in serum of the subjects.Principal component analysis(PCA),orthogonal partial least-squared discriminant analysis(OPLS-DA)and 200 random permutations were used to analyze the differences of metabolic profiles among groups.Identification of differential metabolites was completed in the Human Metabolome Database(HMDB)and abnormal metabolic pathway analysis was performed using the KEGG database.Results:The metabolic profiles of MM patients and healthy controls were significantly separated in both PCA and OPLS-DA models,while the metabolic profiles of newly diagnosed and relapsed MM patients were significantly separated only in OPLS-DA model.In ND vs HC,RP vs HC and RP vs ND cohorts,19,24 and 18 differential metabolites were identified respectively,mainly sphingolipids,glycerophospholipids and fatty acyl amino acids.The metabolic pathway abnormalities in newly diagnosed and relapsed MM patients were mainly manifested in sphingolipid metabolism and glycerophospholipid metabolism compared to healthy controls.Compared with newly diagnosed MM patients,relapsed MM patients were mainly manifested in sphingolipid metabolism and ether-lipid metabolism.Conclusion:The metabolic profiles of MM patients are significantly different from those of healthy people.Relapsed MM patients and newly diagnosed MM patients have similar metabolic profiles,but there are still some differences.Glycerophospholipid metabolism,sphingolipid meta-bolism and ether-lipid metabolism may play important biological roles in the occurrence and development of MM.

This article systematically reviews the characteristics and trends of the writing, editing, publication and promotion of physiology textbooks in China from the late 19th century to the present, focusing on the introduction, development and innovation of Chinese physiology textbooks. The development of physiology textbooks in China is divided into four main stages: the introduction and initial development of physiology textbooks from the late 19th century to 1925; the localization and diversification of textbooks from 1926 to 1949, after the establishment of the Chinese Physiological Society; the exploratory phase of textbook construction after the founding of the People's Republic of China from 1949 to 1976; the formation and innovation of the textbook development process from 1977 to the present, following the restoration of the college entrance examination. For each phase, the article not only records the historical development of physiology textbooks, but also analyzes the evolution of their content, writing styles and the interaction with the social and political contexts. The article summarizes the characteristics and experiences of all these four phases. Special attention is given to the comprehensive statistical analysis of physiology textbooks published since the restoration of the college entrance examination and Economic Reform and Opening-up in 1977, revealing the changes in the number, publication trends and academic features of textbooks during this period. Finally, the article presets the future development of physiology textbooks in China, proposing that textbook writing should integrate aspects such as ideological and political education, medical humanities, basic and clinical medicine, health education, scientific research and international exchange and collaboration. The article also advocates for the application of new technologies and methods, such as artificial intelligence, virtual teaching models and knowledge graphs, to support "personalized learning". This research provides a systematic reference for the study of the history of medical education and offers theoretical support for the future innovation of physiology textbook in China.
Humans ; China ; History, 19th Century ; History, 20th Century ; History, 21st Century ; Physiology/education* ; Textbooks as Topic/history*

OBJECTIVE: To explore the clinical efficacy of conventional transforaminal endoscopic technique and I See transforaminal endoscopic technique in the treatment of recurrent L₅S₁ lumbar disc herniation with high iliac crest. METHODS: A total of 36 patients with recurrent L5S1 lumbar disc herniation with high iliac crest after posterior small-incision discectomy, admitted from May 2016 to May 2023, were selected. They were divided into the conventional transforaminal endoscopy group and the I See transforaminal endoscopy group according to the different transforaminal endoscopic techniques adopted, and all patients in both groups underwent lateral transforaminal spinal canal decompression and discectomy. There were 18 patients in the conventional transforaminal endoscopy group, including 11 males and 7 females, with an age of (52.24±6.68) years;the I See transforaminal endoscopy group also had 18 patients, including 12 males and 6 females, with an age of (50.75±7.79) years. The perioperative indicators (operation time, number of intraoperative radiographs, and length of hospital stay) were compared between two groups. The clinical efficacy was evaluated using the visual analogue scale(VAS) for pain, the Japanese Orthopaedic Association(JOA) low back pain score, and the modified MacNab criteria before and after surgery. RESULTS: All patients achieved gradeⅠincision healing, with no infection cases. The operation time of the I See group was (64.25±16.67) minutes, which was significantly shorter than that of the conventional transforaminal endoscopy group (89.11±17.24) minutes, and the difference was statistically significant(P<0.05). The number of intraoperative radiographs in the I See group was (5.20±2.29) times, which was significantly less than that in the conventional transforaminal endoscopy group(19.16±3.68) times, and the difference was statistically significant(P<0.05). The VAS and total JOA scores of both groups at the 3rd day, the 3rd month after surgery, and the last follow-up were significantly lower than those before surgery, with statistically significant differences(P<0.05);however, there were no statistically significant differences in VAS and total JOA scores between two groups at the 3rd day, the 3rd month after surgery, and the last follow-up (P>0.05). According to the modified MacNab criteria for efficacy evaluation:in the conventional transforaminal endoscopy group, 14 cases were excellent and 4 cases were good;in the I See transforaminal endoscopy group, 15 cases were excellent and 3 cases were good;there was no statistically significant difference in efficacy between two groups(Z=0.177, P=0.674). CONCLUSION Both transforaminal endoscopic techniques have good clinical effects in the treatment of recurrent L₅S₁ lumbar disc herniation with high iliac crest, resulting in significant improvement of postoperative symptoms, and they are safe, reliable, and minimally invasive surgical methods. Compared with the conventional transforaminal endoscopy, the I See transforaminal endoscopic technique has shorter operation time and fewer intraoperative radiographs, so it is generally the first choice.
Humans ; Male ; Female ; Intervertebral Disc Displacement/surgery* ; Endoscopy/methods* ; Middle Aged ; Lumbar Vertebrae/surgery* ; Ilium/surgery* ; Adult ; Diskectomy/methods*

Objectives:To explore the predictive value of residual Murray's law-based quantitative flow ratio(μQFR)on long-term vessel-oriented composite endpoints(VoCE).Methods:This retrospective study included 3 510 patients from the FAVOR Ⅲ China trial.Offline residual μQFR analysis was performed on all vessels(diameter≥2.5 mm)with 50%-90%stenotic lesions.Patients were stratified into high-,intermediate-,and low-risk groups based on residual μQFR tertiles.The primary endpoint was 3-year VoCE,defined as a composite of cardiac death related to the target vessel,target vessel-related spontaneous myocardial infarction,and ischemia-driven target vessel revascularization.Results:Offline analysis was performed on 5 256 vessels from 3 510 patients.The mean residual μQFR was 0.92±0.75.The high-risk group(residual μQFR≤0.91)with 1 554 patients(1 958 vessels);the intermediate-risk group(residual μQFR 0.92-0.96)with 1 211 patients(1 906 vessels);and the low-risk group(residual μQFR>0.96)with 745 patients(1 392 vessels).Over 3-year follow-up,VoCE occurred in 227 vessels(4.3%).The 3-year VoCE incidence was significantly higher in the high-risk group compared to the intermediate-and low-risk groups(6.2%vs.4.1%vs.2.5%,log-rank P<0.001),primarily driven by ischemia-driven target vessel revascularization(5.0%vs.3.0%vs.1.6%,log-rank P<0.001).Hypertension(OR=0.83,95%CI:0.72-0.96),hypercholesterolemia(OR=0.84,95%CI:0.73-0.97),bifurcation lesions(OR=0.72,95%CI:0.63-0.83),moderate/severe calcification(OR=0.70,95%CI:0.57-0.84),and tandem lesions(OR=0.59,95%CI:0.47-0.75)were independent predictors of lower residual μQFR values.Conclusions:Lower residual μQFR is significantly associated with increased VoCE risk during the 3-year follow up period.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]