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 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.

Parathyromegaly refers to chronic enlargement of the parathyroid glands caused by multiple etiological factors. Pathological conditions, such as hyperparathyroidism, parathyroid hyperfunction, parathyroid adenoma, parathyroid cysts, and parathyroid carcinoma may all lead to parathyromegaly. Notably, calcium intake insufficiency and/or vitamin D insufficiency (CVI), which is the predominant etiology of parathyromegaly, now has been recognized as a global public health challenge. Chronic CVI induces negative calcium balance and relative low serum calcium level, stimulating compensatory parathyroid hyperplasia and enlargement. This progression triggers parathyroid hyperfunction and secondary hyperparathyroidism, resulting in bone mass loss, height reduction, kyphosis, osteoporosis, pathological fractures, metastatic vascular calcification and systemic abnormal calcium migration and calcinosis (such as urolithiasis). During the early stages of parathyromegaly, the condition remains preventable and treatable; However, delayed intervention may lead to irreversible tertiary hyperparathyroidism. CVI-associated parathyromegaly exhibits high prevalence and heterogeneous clinical manifestations, representing a critically underrecognized clinical entity. This article will systematically discuss the etiology, pathological characteristics, clinical consequences, and prevention and control strategies for CVI-related parathyromegaly.

Patients with initially diagnosed breast cancer and uncontrolled hyperthyroidism are at high risk of perioperative thyroid crisis. This article reports two cases of early-stage breast cancer initially diagnosed concurrently with uncontrolled primary hyperthyroidism. In Case 1, the patient received neoadjuvant chemotherapy to control breast cancer progression while concurrently taking antithyroid drugs to manage hyperthyroidism. Hyperthyroidism was controlled during chemotherapy, and the patient successfully underwent surgery after neoadjuvant chemotherapy. Case 2 involved recurrent primary hyperthyroidism with leukopenia after antithyroid drug therapy. Since leukopenia is a relative contraindication for antithyroid drugs, the patient underwent radioactive iodine therapy (iodine-131) and endocrine therapy for one month before proceeding with breast cancer surgery. Through a literature review, this article analyzes preoperative management strategies for uncontrolled hyperthyroidism in initially diagnosed breast cancer patients, emphasizing the importance of normalizing thyroid function to prevent thyroid crisis and reduce perioperative risks.

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.

Iodine is an indispensable trace element in the human body and its intake level is closely related to thyroid function. Iodine deficiency or iodine excess will lead to iodine-related diseases. The implementation of the universal salt iodization policy of China has achieved remarkable results, yet it is still facing the problems of iodine deficiency and iodine excess at present. Since iodine in the human body is mainly metabolized by the kidneys and excreted in urine, urinary iodine test has become an effective way to reflect the recent iodine nutrition status of the body. This article will discuss the current iodine nutrition status of the population in China, the hazards of iodine deficiency and iodine excess, as well as the clinical application of urinary iodine test.

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.

Parathyromegaly refers to chronic enlargement of the parathyroid glands caused by multiple etiological factors. Pathological conditions, such as hyperparathyroidism, parathyroid hyperfunction, parathyroid adenoma, parathyroid cysts, and parathyroid carcinoma may all lead to parathyromegaly. Notably, calcium intake insufficiency and/or vitamin D insufficiency (CVI), which is the predominant etiology of parathyromegaly, now has been recognized as a global public health challenge. Chronic CVI induces negative calcium balance and relative low serum calcium level, stimulating compensatory parathyroid hyperplasia and enlargement. This progression triggers parathyroid hyperfunction and secondary hyperparathyroidism, resulting in bone mass loss, height reduction, kyphosis, osteoporosis, pathological fractures, metastatic vascular calcification and systemic abnormal calcium migration and calcinosis (such as urolithiasis). During the early stages of parathyromegaly, the condition remains preventable and treatable; However, delayed intervention may lead to irreversible tertiary hyperparathyroidism. CVI-associated parathyromegaly exhibits high prevalence and heterogeneous clinical manifestations, representing a critically underrecognized clinical entity. This article will systematically discuss the etiology, pathological characteristics, clinical consequences, and prevention and control strategies for CVI-related parathyromegaly.