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.

ObjectiveTo analyze the potential risk of infection sources during the consolidation phase of schistosomiasis elimination in Lushan County (a mountainous region) of Sichuan Province, and to provide prevention and control strategies for the consolidation of schistosomiasis elimination achievements in mountainous areas. MethodsIn 2024, one to two villages with historically severe epidemics were selected in the heavily endemic townships of Lushan County as monitoring sites to carry out monitoring for wild animal feces, domestic animals, wild rats, free-roaming dogs, local residents, and mobile populations. Follow-up monitoring for previously infected individuals was carried out in Caoping Village of Siyan Town. Statistical analyses were performed to assess the risks associated with infection sources. ResultsA total of 115 fecal samples from 13 species of wildlife were incubated, with all negative. Blood tests were conducted on 492 cattle, 34 sheep, and 261 dogs, with all negative. A total of 2 520 rodent traps were set, capturing 67 wild rats with a capture rate of 2.66%, and no positive wild rats were found upon dissection. The activity track of 25 loose dogs was 2 212 meters at the farthest, 236 meters at the nearest, and 744 meters on average. a total of 68 wild droppings (all dog feces) were picked up along the way, with all negative. Blood tests were performed on 3 540 local population, yielding 39 blood-positive cases with a blood positive rate of 1.1%. Fecal examinations were conducted on 193 individuals, with all negative. A total of 315 blood tests were performed on the mobile population, identifying 1 positive case with a blood-positive rate of 0.32%. One person received a fecal examination, with zero positive. A follow-up survey of 505 previously infected individuals revealed 5 blood-positive cases, with a positive rate of 0.99%. Fecal examinations were conducted on 15 individuals, with all negative. ConclusionIn this investigation, no local or imported sources of schistosomiasis transmission were found. However, there was a wide variety and a large number of potential sources of infection in the local area. It is necessary to actively explore regional monitoring models for schistosomiasis elimination flexibly adjust prevention and control strategies according to local conditions, achieve precise prevention and control, and consolidate the achievements of elimination.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

Multibody dynamics simulation of the musculoskeletal system is an essential tool for analyzing the biomechanical mechanisms underlying human motion.Recent research trends have shifted from traditional physics-based models toward data-driven or data-physics hybrid frameworks.This review presents the latest developments in these areas.Physics-based multibody dynamics simulations have undergone significant progress in terms of simulation fidelity,optimization algorithms,and software tools.However,their practical implementation remains constrained by the need for complex experimental data and the computational expense of solving differential equations.Conversely,data-driven method bolstered by advancements in deep learning have demonstrated remarkable efficiency in predicting joint angles,postures,ground reaction forces,joint torques,and muscle forces,as well as developing control algorithms for exoskeletons.However,despite these advantages,data-driven approaches face challenges such as limited generalizability and potential violation of biomechanical principles.To address these limitations,data-physics hybrid approaches(e.g.,physics-informed neural network,PINN)which integrate physical constraints(e.g.,Newton-Euler equations,muscle constitutive laws)with data-driven architectures have been developed.This synergy enhances prediction accuracy while preserving the biological plausibility of solutions.Nevertheless,critical challenges persist,including the integration of multi-scale physical equations and the modeling of multi-joint coordination dynamics.Future research should prioritize:optimizing hybrid model architectures to balance computational efficiency and mechanistic accuracy,incorporating markerless motion capture techniques to improve real-world applicability,exploiting multi-scale physics and personalized parameter inversion to advance precision rehabilitation and motion analysis.These efforts will foster innovations in intelligent rehabilitation systems,clinical motion assessment,and related translational fields.

Objective:To investigate the value of 24 h urinary aldosterone(24 h-UAC) measurement by liquid chromatography-tandem mass spectrometry(LC-MS/MS) in the subtype classification of primary aldosteronism(PA).Methods:A total of 86 patients with PA, including 51 with unilateral primary aldosteronism(UPA) and 35 with bilateral primary aldosteronism(BPA), were enrolled in the Department of Endocrinology and Metabolism at West China Hospital between January 2018 and December 2022. Plasma aldosterone concentration(PAC), plasma renin concentration(PRC) and 24 h-UAC were measured by LC-MS/MS. 24-hour urinary electrolytes and 24-hour urinary creatinine(24 h-UCR) were also measured. The diagnostic value of 24 h-UAC in PA subtype classification was evaluated using receiver operating characteristic(ROC) curve analysis. Multivariate logistic regression analysis was conducted with PA subtypes as the dependent variable(UPA=1, BPA=0) to establish a diagnostic model for differentiating unilateral from bilateral lesions, and its performance was compared with published Chinese classification models. Results:There were no statistical differences between the UPA and BPA groups in terms of age, gender, BMI, systolic and diastolic blood pressure, 24 h urinary potassium, sodium, chloride, 24 h-UCR and PRC( P<0.05). The lowest plasma potassium level was significantly lower in the UPA group than in the BPA group, while PAC, 24 h-UAC, aldosterone-renin ratio(ARR), and 24 h-UAC/UCR were significantly higher( P<0.05). The detection rate of typical adenomas on imaging also showed a significant difference between the two groups( P<0.05). The area under the ROC curve(AUC) of 24 h-UAC for differentiating UPA from BPA was 0.829(95% CI 0.733-0.902), with an optimal cut-off value of 15.4 μg/24 h, yielding a sensitivity of 68.63% and a specificity of 88.57%( P<0.001). At a cut-off value of 24.5 μg/24 h, specificity reached 100%, with a sensitivity of 27.45%. Multivariate analysis indicated that a combined model incorporating 24 h-UAC, the lowest plasma potassium level, and imaging findings of typical adenomas significantly improved diagnostic accuracy for PA subtyping, achieving a specificity of 91.43%. Compared with the existing Chinese modified Küpers scoring model and CONPASS prediction model, this model demonstrated higher diagnostic efficiency, a lower missed diagnosis rate, and a misdiagnosis rate intermediate between the two. Conclusion:The 24 h-UAC in UPA patients is significantly higher than in BPA patients, making it a valuable marker for PA subtype classification. A predictive model combining 24 h-UAC, the lowest plasma potassium level, and imaging evidence of typical adenomas demonstrated high diagnostic accuracy for PA subtype classification and may provide valuable guidance for clinical decision-making.

mRNA therapy is an emerging treatment that has become a frontier and hot topic in the field of biomedicine.To explore the trend in the development of mRNA therapy,this paper conducts an analysis from the perspectives of papers and patents,examining multiple dimensions including development trend,research areas,and high-value research.The study reveals the following findings:Global research in mRNA therapy is growing rapidly.Basic research mainly focuses on oncology,chemistry-multidisciplinary,biochemistry and molecular biology,while applied research centers on mRNA concerning genetic engineering,isolation,synthesis,purification,and the development of medicines.High-value research mainly centers on topics such as mRNA delivery,composition,manufacture,modification,and the development of various mRNA-based therapies.

Objective:To investigate the value of 24 h urinary aldosterone(24 h-UAC) measurement by liquid chromatography-tandem mass spectrometry(LC-MS/MS) in the subtype classification of primary aldosteronism(PA).Methods:A total of 86 patients with PA, including 51 with unilateral primary aldosteronism(UPA) and 35 with bilateral primary aldosteronism(BPA), were enrolled in the Department of Endocrinology and Metabolism at West China Hospital between January 2018 and December 2022. Plasma aldosterone concentration(PAC), plasma renin concentration(PRC) and 24 h-UAC were measured by LC-MS/MS. 24-hour urinary electrolytes and 24-hour urinary creatinine(24 h-UCR) were also measured. The diagnostic value of 24 h-UAC in PA subtype classification was evaluated using receiver operating characteristic(ROC) curve analysis. Multivariate logistic regression analysis was conducted with PA subtypes as the dependent variable(UPA=1, BPA=0) to establish a diagnostic model for differentiating unilateral from bilateral lesions, and its performance was compared with published Chinese classification models. Results:There were no statistical differences between the UPA and BPA groups in terms of age, gender, BMI, systolic and diastolic blood pressure, 24 h urinary potassium, sodium, chloride, 24 h-UCR and PRC( P<0.05). The lowest plasma potassium level was significantly lower in the UPA group than in the BPA group, while PAC, 24 h-UAC, aldosterone-renin ratio(ARR), and 24 h-UAC/UCR were significantly higher( P<0.05). The detection rate of typical adenomas on imaging also showed a significant difference between the two groups( P<0.05). The area under the ROC curve(AUC) of 24 h-UAC for differentiating UPA from BPA was 0.829(95% CI 0.733-0.902), with an optimal cut-off value of 15.4 μg/24 h, yielding a sensitivity of 68.63% and a specificity of 88.57%( P<0.001). At a cut-off value of 24.5 μg/24 h, specificity reached 100%, with a sensitivity of 27.45%. Multivariate analysis indicated that a combined model incorporating 24 h-UAC, the lowest plasma potassium level, and imaging findings of typical adenomas significantly improved diagnostic accuracy for PA subtyping, achieving a specificity of 91.43%. Compared with the existing Chinese modified Küpers scoring model and CONPASS prediction model, this model demonstrated higher diagnostic efficiency, a lower missed diagnosis rate, and a misdiagnosis rate intermediate between the two. Conclusion:The 24 h-UAC in UPA patients is significantly higher than in BPA patients, making it a valuable marker for PA subtype classification. A predictive model combining 24 h-UAC, the lowest plasma potassium level, and imaging evidence of typical adenomas demonstrated high diagnostic accuracy for PA subtype classification and may provide valuable guidance for clinical decision-making.

Objective:To discuss the role of M2 macrophages in epithelial-mesenchymal transition(EMT)and cisplatin(DDP)resistance in the non-small cell lung cancer(NSCLC),and to clarify the regulatory mechanism of nuclear factor κB(NF-κB)signaling pathway.Methods:The human monocytic leukemia THP-1 cells were selected and differentiated into M0 macrophages by phorbol myristate acetate(PMA)induction,followed by M2 macrophage polarization through interleukin(IL)-4 and IL-13 stimulation.Western blotting and immunofluorescence methods were used to detect the protein expression levels of CD163,CD86,and arginase-1(Arg-1)in M0 and M2 macrophages.The human NSCLC A549 cells were co-cultured non-contactly with M0 or M2 macrophages in Transwell chambers,and the cells were divided into A549+M0 group(A549 cells co-cultured with M0 macrophages),A549+M2 group(A549 cells co-cultured with M2 macrophages),and A549+M2+BAY11-7082 group(A549 cells co-cultured with M2 macrophages and treated with 10 mmol·L-1 NF-κB inhibitor BAY11-7082).Wound healing assay was used to detect the wound healing rate of the A549 cells in various groups;Transwell assay was used to detect the number of invasion A549 cells in various groups;cell counting kit-8(CCK-8)assay was used to detect the inhibitory rate of proliferation and half maximal inhibitory concentration(IC50)value of the A549 cells after treated with DDP in the co-culture system;Western blotting method was used to detect the expression levels of vimentin,E-cadherin,N-cadherin,transcription factor Snail,phosphorylated P65(p-P65),P-glycoprotein(P-gp),and programmed death-ligand 1(PD-L1)proteins in the A549 cells in various groups.Results:The Western blotting results showed that compared with M0 group,the expression levels of CD163 and Arg-1 proteins in the macrophages in M2 group were significantly increased(P<0.05),while the expression level of CD86 protein was significantly decreased(P<0.05).The immunofluorescence results showed that compared with M0 group,the expression of CD163 protein in the macrophages in M2 group was enhanced and the expression of CD86 protein was weakened.The wound healing assay results showed that at 24 and 48 h of culture,compared with A549+M0 group,the wound healing rate of the A549 cells in A549+M2 group was significantly increased(P<0.05);in the co-culture system,compared with A549+M0 group,the wound healing rate of the A549 cells in A549+M2 group was significantly increased(P<0.05);compared with A549+M2 group,the wound healing rate of the A549 cells in A549+M2+BAY11-7082 group was significantly decreased(P<0.05).The Transwell assay results showed that compared with A549+M0 group,the number of invasion A549 cells in A549+M2 group was significantly increased(P<0.05);compared with A549+M2 group,the number of invasion A549 cells in A549+M2+BAY11-7082 group was significantly decreased(P<0.05);in the co-culture system,compared with A549+M0 group,the number of invasion A549 cells in A549+M2 group was significantly increased(P<0.05).The CCK-8 assay results showed that after treated with 2.50,5.00,10.00,20.00,and 40.00 mg·L-1 DDP,compared with A549+M0 group,the inhibitory rate of proliferation of the A549 cells in A549+M2 group was significantly decreased(P<0.05 or P<0.01),and the IC50 value was significantly increased(P<0.01);in the co-culture system,compared with A549+M0 group,the inhibitory rate of proliferation of the A549 cells in A549+M2 group was significantly decreased(P<0.05 or P<0.01),and the IC50 value was significantly increased(P<0.01);compared with A549+M2 group,the inhibitory rate of proliferation of the A549 cells in A549+M2+BAY11-7082 group was significantly increased(P<0.05),and the IC50 value was significantly decreased(P<0.05).The Western blotting results showed that compared with A549+M0 group,the expression level of E-cadherin proteins in the A549 cells in A549+M2 group was significantly decreased(P<0.05),while the expression levels of N-cadherin,vimentin,and Snail proteins were significantly increased(P<0.05);in the co-culture system,compared with A549+M0 group,the expression levels of vimentin,Snail,N-cadherin,and p-P65 proteins in the A549 cells in A549+M2 group were significantly increased(P<0.05),while the expression level of E-cadherin proteins was significantly decreased(P<0.05);compared with A549+M2 group,the expression levels of vimentin,N-cadherin,and p-P65 proteins in the A549 cells in A549+M2+BAY11-7082 group were significantly decreased(P<0.05),while the expression level of E-cadherin proteins was significantly increased(P<0.05);compared with A549+M0 group,the expression levels of P-gp and PD-L1 proteins in the A549 cells in A549+M2 group were significantly increased(P<0.05);in the co-culture system,compared with A549+M0 group,the expression levels of P-gp and PD-L1 proteins in the A549 cells in A549+M2 group were significantly increased(P<0.05);compared with A549+M2 group,the expression levels of P-gp and PD-L1 proteins in the A549 cells in A549+M2+BAY11-7082 group were significantly decreased(P<0.05).Conclusion:The M2 macrophages can regulate EMT in the NSCLC cells to promote the invasion and metastasis of tumor,and modulate the expressions of P-gp and PD-L1 to enhance DDP resistance,which is associated with the NF-κB signaling pathway.

mRNA therapy is an emerging treatment that has become a frontier and hot topic in the field of biomedicine.To explore the trend in the development of mRNA therapy,this paper conducts an analysis from the perspectives of papers and patents,examining multiple dimensions including development trend,research areas,and high-value research.The study reveals the following findings:Global research in mRNA therapy is growing rapidly.Basic research mainly focuses on oncology,chemistry-multidisciplinary,biochemistry and molecular biology,while applied research centers on mRNA concerning genetic engineering,isolation,synthesis,purification,and the development of medicines.High-value research mainly centers on topics such as mRNA delivery,composition,manufacture,modification,and the development of various mRNA-based therapies.