Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language models (LLMs) technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. The paper systematically analyzes that the exceptional potential of LLMs in lung cancer auxiliary diagnosis, tumor feature extraction, automatic staging, progression/outcome analysis, treatment recommendations, medical documentation generation, and patient education. However, they face critical technical and ethical challenges including inconsistent performance in complex integrated decision-making (e.g., TNM staging, personalized treatment suggestions) and "black box" opacity issues, along with dilemmas such as training data biases, model hallucinations, data privacy concerns, and cross-lingual adaptation challenges ("data colonization"). Future directions should prioritize constructing high-quality multimodal corpora specific to lung cancer, developing interpretable and compliant specialized models, and achieving seamless integration with existing clinical workflows. Through dual drivers of technological innovation and ethical standardization, LLMs should be prudently advanced for holistic lung cancer management processes, ultimately promoting efficient, standardized, and personalized diagnosis and treatment practices.

Background Amid global climate change, extreme environmental events are occurring more frequently, and it is imperative to investigate the impacts of combined exposure to fine particluate matter (PM_2.5) and cold spells (CS) on population mortality. Objective To analyze the association between sequential extreme PM_2.5-cold spell (EP-CS) events and non-accidental mortality among residents in Zigong City from 2016 to 2021. Methods Using time-series study design, meteorological data in Zigong were collected from the Zigong Meteorological Bureau for the period from January 1, 2016 to December 31, 2021, while daily non-accidental mortality data were obtained from the mortality surveillance system of the Zigong Center for Disease Control and Prevention. We adopted the percentile method to define extreme PM_2.5 events and cold spells. We analyzed the risk effect of EP-CS events on non-accidental mortality among residents in this city and explored the potential amplification of damage resulting from different patterns of consecutive extreme events by using distributed lag nonlinear model (DLNM). We also conducted stratified analyses based on age, gender, education level, and marital status. Results The EP-CS events demonstrated a significant impact on non-accidental mortality among the local residents, exhibiting a certain lagged effect. The effects on the overall residents lasted from lag0 (RR=1.030, 95%CI: 1.013, 1.048) to lag14 (RR=1.035, 95%CI: 1.019, 1.052). Notably, the effects were more pronounced among females, individuals aged 65 years and above, and those who were never married, divorced, or widowed. Different patterns of EP-CS events all associated with adverse effects, the health impact of EP-CS events was significantly greater than that of individual PM_2.5 pollution or CS events. The analysis of lag effects across different event patterns revealed that the overall effect of EP-CS events with shorter intervals (0–7 d) had a stronger effect compared to EP-CS with longer intervals (8–14 d), and the RR values of lag14 were 1.034 (95%CI: 1.015, 1.054) and 1.017 (95%CI: 1.007, 1.027), suggesting that the damaging effect of compound events occurring in the short term was more significant. Conclusion All sequential extreme EP-CS events have an impact on non-accidental mortality among residents in this city, with compound events demonstrating a stronger effect. Females, individuals aged ≥65 years, and those who were never married, divorced, or widowed are more sensitive to EP-CS events.

OBJECTIVE: Acupuncture therapies are known for their effectiveness in treating a variety of gastric diseases, although the mechanisms underlying these effects are not fully understood. This study tested the effectiveness of electroacupuncture (EA) at acupoints Zhongwan (RN12) and Weishu (BL21) for managing gastric motility disorder (GMD) and investigated the underlying mechanisms involved. METHODS: A GMD model was used to evaluate the impact of EA on various aspects of gastric function including the amplitude of gastric motility, electrogastrogram, food intake, and the rate of gastric emptying. Immunofluorescence techniques were used to explore the activation of spinal neurons by EA, specifically examining the presence of cholera toxin B subunit (CTB)-positive neurons and fibers emanating from acupoints RN12 and BL21. The stimulation of γ-aminobutyric acid (GABA)-ergic neurons in the spinal dorsal horn, the inhibition of sympathetic preganglionic neurons in the spinal lateral horn, and their collective effects on the activity of sympathetic nerves were examined. RESULTS: EA at RN12 and BL21 significantly improved gastric motility compromised by GMD. Notably, EA activated spinal neurons, with CTB-positive neurons and fibers from RN12 and BL21 being detectable in both the dorsal root ganglia and the spinal dorsal horn. Further analysis revealed that EA at these acupoints not only stimulated GABAergic neurons in the spinal dorsal horn but also suppressed sympathetic preganglionic neurons in the spinal lateral horn, effectively reducing excessive activity of sympathetic nerves triggered by GMD. CONCLUSION EA treatment at RN12 and BL21 effectively enhances gastric motility in a GMD model. The therapeutic efficacy of this approach is attributed to the activation of spinal neurons and the modulation of the spinal GABAergic-sympathetic pathway, providing a neurobiological foundation for the role of acupuncture in treating gastric disorders. Please cite this article as: Zhang MT, Liang YF, Dai Q, Gao HR, Wang H, Chen L, Huang S, Wang XY, Shen GM. A spinal neural circuit for electroacupuncture that regulates gastric functional disorders. J Integr Med. 2025; 23(1): 56-65.
Electroacupuncture ; Animals ; Male ; Acupuncture Points ; Stomach Diseases/physiopathology* ; Rats, Sprague-Dawley ; Gastrointestinal Motility ; Rats ; Gastric Emptying ; Neurons ; Spinal Cord ; Stomach/physiopathology*

ObjectiveTo investigate the potential mechanism of Liangxue Tuizi Formula （凉血退紫方， LXTZF） in treating Henoch-Schönlein Purpura （HSP） by examining its regulatory effect on neutrophil extracellular trap （NETs） dysregulation via the rapidly accelerated fibrosarcoma kinase （RAF）/mitogen-activated protein kinase （MEK）/extracellular signal-regulated kinase （ERK） signaling pathway. MethodsSeventy Wistar rats were randomly allocated into a blank control group （n=14） and a modeling group （n=56）. Rats in the modelling group underwent an eight-week modelling period to establish HSP rat models with blood-heat syndrome via modified ovalbumin （OVA） induction method combined with oral administration of heat-property Chinese herbal medicine. Fifty successfully modeled rats were subsequently randomly divided into five groups （n=10 per group）， model group， compound glycyrrhizin group， LXTZF group， RAF inhibitor group， and LXTZF + RAF agonist group. Additionally， 10 rats were selected from the original blank control group for the final experiment. From the 11th week of modelling， rats in the blank control group and the model group received 1 ml/（100 g·d） ultrapure water via oral administration， in addition to 0.5 ml/（kg·d） 0.9% sodium chloride solution via intraperitoneal injection. The LXTZF group and the compound glycyrrhizin group received 7.5 g/（kg·d） LXTZF granule suspension via gavage， 13.5 mg/（kg·d） compound glycyrrhizin suspension via gavage， respectively. The RAF inhibitor group received 1 mg/（kg·d） GW5074 suspension via intraperitoneal injection and ultrapure water via oral administration； the LXTZF + RAF agonist group received 7.5 g/（kg·d） LXTZF granule suspension via gavage and 1 mg/（kg·d） paclitaxel suspension via intraperitoneal injection. All administrations were performed once daily for 4 weeks. After intervention， skin tissue histopathology was examined by hematoxylin and eosin （H&E） staining， immunoglobulin A （IgA） deposition was assessed via immunofluorescence， serum levels of neutrophil elastase （NE）， tumor necrosis factor-α （TNF-α）， and vascular cell adhesion molecule-1 （VCAM-1） were measured using enzyme-linked immunosorbent assay （ELISA）， serum myeloperoxidase （MPO） level was determined by a colorimetric assay； the mRNA expression levels of RAF， MEK， and ERK in skin tissue were detected by real-time quantitative polymerase chain reaction （RT-qPCR）； and the protein expression of RAF， MEK， ERK， as well as phosphorylated MEK （p-MEK） and phosphorylated ERK （p-ERK）， were analyzed by Western Blot. ResultsSkin tissue in the blank control group rats remained normal， whereas the model group exhibited neutrophil infiltration and haemorrhage with red blood cell rupture. In all drug intervention groups， neutrophil infiltration and haemorrhagic exudation reduced markedly， with LXTZF group demonstrating the most pronounced improvement. Compared with the blank control group， rats in the model group exhibited enhanced IgA fluorescence intensity in skin tissue， elevated serum levels of NE， MPO， TNF-α and VCAM-1， increased mRNA expression of RAF， MEK， ERK1 and ERK2， as well as heightened RAF protein levels and p-MEK/MEK and p-ERK/ERK ratios （P＜0.05）. Compared with the model group， the drug intervention groups exhibited reduced IgA fluorescence intensity in skin tissue， along with decreased serum levels of NE， MPO， TNF-α， and VCAM-1 （P＜0.05）. In LXTZF group and RAF inhibition groups， reduced mRNA expression of RAF， MEK， ERK1， and ERK2 was observed in rat skin tissue， alongside decreased RAF protein levels and reduced p-MEK/MEK and p-ERK/ERK ratios （P＜0.05）. Compared with LXTZF + RAF agonist group， the compound glycyrrhizin group， LXTZF group， and RAF inhibitior group exhibited reduced IgA fluorescence intensity in skin tissue， decreased serum NE， MPO， TNF-α， and VCAM-1 levels， and decreased MEK mRNA expression and p-MEK/MEK ratio （P＜0.05）. ConclusionThe potential mechanism by which LXTZF treats Henoch-Schönlein purpura with blood heat syndrome may involve blocking the RAF/MEK/ERK signaling pathway in skin tissue， and suppressing excessive formation of NETs， thereby reducing IgA deposition in dermal microvessels and attenuating systemic inflammatory responses.

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

Objective:To construct the supportive care intervention scheme for breast cancer radiotherapy patients based on the empowerment theory and discuss its application effect, so as to provide the reference for the clinical nursing intervention.Methods:According to the investigation results of the current situation of supportive care needs of patients with breast cancer radiotherapy and the results of literature review, a supportive care intervention scheme for breast cancer radiotherapy patients based on the empowerment theory was constructed by Delphi expert consultation method.Adopting experimental research, breast cancer radiotherapy patients in General Hospital of Ningxia Medical University were selected by convenient sampling method. They were divided into the control group from April to May 2023 (40 cases) for routine nursing care, and the experimental group from August to September 2023 (40 cases) for the supportive care intervention scheme for breast cancer radiotherapy patients based on the empowerment theory on the basis of routine nursing care according to the admission time. The 34-item Short-Form Supportive Cancer Needs Survey (SCNS-SF34), Strategies Used by People to Promte Health (SUPPH), Cancer Fatigue Scale(CFS) and Function Assessment of Cancer Therapy-Breast (FACT-B) were collected on the day of admission, the end of radiotherapy and 3 months after radiotherapy to evaluate the effects before and after intervention.Results:After 1, 2 rounds of expert correspondence, the positivity of experts were 95.24%(20/21) and 100.00%(20/20), the expert authority coefficient was 0.804 and 0.825, and the Kendall harmony coefficient was 0.129 and 0.138 (both P<0.05). Finally, a supportive care intervention scheme for breast cancer radiotherapy patients based on the enabling theory was formed, which included 5 primary items, 11 secondary items and 32 tertiary items.The application results showed that there were 37 cases in the control group with an age of (48.16 ± 10.21) years, and 38 cases in the experimental group with an age of (44.50 ± 9.81) years. All patients were female. There was no statistically significant difference in the scores of SCNS-SF34, SUPPH, CFS, and FACT-B between the two groups on the day of admission(all P>0.05). Three months after the end of radiotherapy, the score of SCNS-SF34 in the experimental group was (73.24 ± 11.99) points, which was lower than (79.91 ± 14.79) points in the control group, and the difference was statistically significant ( t=4.43, P<0.05). At the end of radiotherapy and 3 months after the end of radiotherapy, the scores of SUPPH in the experimental group were (80.39 ± 8.55) and (92.37 ± 8.14) points, respectively, which were higher than (73.95 ± 9.86) and (86.24 ± 7.10) points in the control group, and the difference was statistically significant ( t=-3.03, -3.47, both P<0.05). At the end of radiotherapy and 3 months after the end of radiotherapy, the scores of CFS in the experimental group were 30.00 (28.75, 33.00) and (25.29 ± 3.26) points, respectively, which were lower than 34.00 (31.50, 35.00) and (27.59 ± 3.43) points in the control group, and the difference was statistically significant ( Z=-3.51, t=2.98, both P<0.05). At the end of radiotherapy and 3 months after the end of radiotherapy, the scores of FACT-B in the experimental group were (85.08 ± 12.74) and (105.53 ± 6.53) points, respectively, which were higher than (79.03 ± 7.90) and (95.73 ± 7.61) points in the control group, and the difference was statistically significant ( t=-2.48, -5.99, both P<0.05). Conclusions:The supportive care intervention scheme for patients with breast cancer radiotherapy based on the empowerment theory established in this study is scientific and feasible, which can reduce patients' needs for supportive care, alleviate cancer-related fatigue, and improve self-management efficacy and quality of life.