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.

Myofascial trigger points， as hyperirritable spots within taut bands of skeletal muscle， can induce local or referred pain， and show a high degree of similarity to acupoints in traditional Chinese medicine （TCM）， particularly the so-called sinew knot lesion point. From the perspective of channel sinew theory， and by examining the correlations of myofascial trigger points with acupoints and channel sinew disorders， this study aims to compare the similarities and differences between MTrPs and sinew knot lesion points in terms of pathological mechanisms， needling analgesic mechanisms， and therapeutic approaches. The goal is to deepen the understanding of MTrPs and dry needling， and provide a modern scientific perspective on channel sinew theory and the sinew knot lesion point.

Myofascial trigger points， as hyperirritable spots within taut bands of skeletal muscle， can induce local or referred pain， and show a high degree of similarity to acupoints in traditional Chinese medicine （TCM）， particularly the so-called sinew knot lesion point. From the perspective of channel sinew theory， and by examining the correlations of myofascial trigger points with acupoints and channel sinew disorders， this study aims to compare the similarities and differences between MTrPs and sinew knot lesion points in terms of pathological mechanisms， needling analgesic mechanisms， and therapeutic approaches. The goal is to deepen the understanding of MTrPs and dry needling， and provide a modern scientific perspective on channel sinew theory and the sinew knot lesion point.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Objective To construct a nursing follow-up checklist for patients undergoing autologous hematopoietic stem cell transplantation,providing a basis for postoperative follow-up care.Methods Using evidence-based methods,the literature from major guide websites and databases using Chinese and English search terms was retrieved,and their quality was evaluated.The relevant items were extracted,and a first draft was formed.15 experts were selected in relevant fields from 14 tertiary hospitals in 13 provinces,cities,and autonomous regions across the country for Delphi inquiry.The nursing follow-up checklist was revised again based on expert opinions and clinical practice.The nursing follow-up checklist was initially applied and then revised again to form the final draft.Results 15 experts include 12 undergraduate and 3 master's degree holders.The positivity coefficients of the 2 rounds of inquiry were 100％;the authority coefficients of the experts were 0.815;the Kendall coefficients were 0.119 and 0.144,respectively;the differences were statistically significant(P＜0.001).The final nursing follow-up checklist was formed,which includes 6 primary indicators,including physiological status,psychological status,social and family support,living conditions,disease knowledge,and laboratory tests.19 patients(95％)found the follow-up content to be comprehensive.The follow-up nurses's satisfaction rate exceeded 85％.There were 27 secondary indicators and 61 tertiary indicators,with coefficients of variation of all indicators less than 0.25.Conclusion The nursing follow-up checklist is scientific,reliable,and practical,which can provide a basis for clinical nursing staff to follow up and comprehensively manage patients after autologous hematopoietic stem cell transplantation.

To investigate the protective effect of Lycium barbarum glycopeptide(LbGp)on testicu-lar injury induced by D-galactose(D-gal)in aging rats,male SD rats were randomly divided into 6 groups:the blank control group(Control),aging model group(Model),positive control group(β-nicotinamide mononucleotide,NMN),low dose LbGp group(LLbGp),medium dose LbGp group(MLbGp)and high dose LbGp group(HLbGp).The testicular mass of rats was counted,the morphological changes of testicular tissue were observed by hematoxylin-eosin(HE)staining,the testicular senescence was detected by β-galactosidase(SA-β-gal)staining,and the levels of testos-terone(T),luteinizing hormone(LH)and follicle stimulating hormone(FSH)in serum were de-tected.The levels of oxidative factors such as glutathione peroxidase(GSH-Px),superoxide dis-mutase(SOD),malondialdehyde(MDA),catalase(CAT)and inflammatory factors such as tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β)and interleukin-6(IL-6)in rat tissues were measured.TUNEL staining was used to detect the apoptosis of testicular cells,epididymal sperm quality,and the expression of Keap1,Nrf2 and Nqo1 mRNA were analyzed.The results showed that compared with the Model group,the testicular coefficient of Lycium barbarum glycopeptide rats in MLbGp and HLbGp groups increased(P＜0.01),the level of T in serum and sperm quality increased(P＜0.05),the structural degeneration and aging of testicular tissue decreased(P＜0.01),the level of antioxidant factors increased,and the levels of inflammatory factors and apopto-sis decreased(P＜0.05).The expression of Keap1 decreased significantly(P＜0.01),while the ex-pression of Nrf2 and Nqo1 mRNA increased(P＜0.05).The above results indicate that Lycium barbarum glycopeptide can improve D-gal-induced testicular senescence,attenuate oxidative stress,reduce inflammatory response,decrease apoptosis,and exert a protective effect on testicular injury in rats due to senescence through the Keap1-Nrf2 signaling pathway.

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.

Butylated hydroxytoluene (BHT) is a synthetic phenolic antioxidant widely used in food additives, pharmaceuticals, personal care products, and other industries. It has been frequently detected in various environmental media, including oceans, soils, and the atmosphere. Human exposure to BHT can occur through multiple routes, and it has the potential to accumulate in the body while being readily transformed into several metabolites that are often more toxic than the parent compound. In recent years, numerous studies have investigated the levels of BHT and its metabolites in human populations and their potential health risks. Most current research on BHT exposure and its metabolites has focused on vulnerable groups such as pregnant women and children. These compounds have been detected in various biological samples—including human serum, urine, cerebrospinal fluid, and placenta—with relatively high frequencies.The metabolites of BHT demonstrate greater toxicity than BHT itself and have been implicated in pathological processes such as diminished ovarian reserve and miscarriage. Potential mechanisms include endocrine disruption, oxidative stress, and DNA damage. This article reviews current research on human exposure to BHT and its metabolites, as well as their potential health effects, aiming to provide a scientific basis for establishing usage standards and assessing health risks associated with BHT.