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.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Objective To explore the relationship between the characteristics of X-ray and magnetic resonance imaging(MRI) and the expression level of estrogen receptor(ER),progesterone receptor(PR)and human epithelial factor receptor 2(HER2)in breast cancer patients.Methods 108 cases of breast cancer patients in the first 74 Hospital of the PLA from January 2013 to Janu-ary 2017 were selected as the research object.Clinical,pathological and imaging data of patients were collected.All patients were ex-amined by X-ray and MRI after admission.The expressions of ER,PR and HER2 in cancer cells were detected by immunohisto-chemical staining.Results The expression of ER,PR and HER2 was positive in 73 cases(67.59%),63 cases(58.33%)and 43 ca-ses(39.81%),respectively.The positive rate of HER2 in patients with calcification was higher than that in patients without calcifi-cation(P<0.05).The positive rate of PR in patients with calcification along the duct was lower than that in patients of whom the calcification was not along the duct,and the positive rate of PR in patients with glandular or mixed density was higher than that in patients with structural disorder(P< 0.05).The positive rate of ER was higher in patients with calcification,mass,spiculation signs,glandular or mixed density(P<0.05).There were significant differences in the positive rate of HER2 between patients with different shapes and different enhancement modes(P<0.05),and there was a significant difference in the positive rate of PR be-tween patients with different enhancement modes(P<0.05).Calcification displayed by X-ray mammography was positively corre-lated with HER2,calcification along the duct was negatively correlated with the expression of PR,calcification with mass was posi-tively correlated with ER and negatively correlated with PR,spiculation sign was positively correlated with ER,and structural disor-der was negatively correlated with ER and PR.Mass type and inhomogeneous enhancement of MRI signs were negatively correlated with HER2,irregular shape was positively correlated with HER2,and inhomogeneous enhancement was positively correlated with PR (r = 0 .363 ,- 0 .375 ,0 .368 ,- 0 .326 ,0 .426 ,- 0 .489 ,- 0 .373 ,- 0 .468 ,- 0 .403 ,0 .391 ,0 .425 ;P < 0 .05) .Conclusion There is a correlation of signs of X‐ray mammography and MRI signs with the expression of ER ,PR and HER2 .Imaging changes can predict the expression of some biological factors of breast cancer ,which is related to hormones ,chemotherapy sensitivity and the prognosis of patients.

Objective:To purify a kind of deoxyribonuclease from earthworm Eisenia foetida (named earthworm DNase, EDNase) and study its characteristics. Methods: Acetone precipitation, ion-exchange chromatography, high performance liquid chromatography, SDS-PAGE, CapiUary electrophoresis isoelectric focusing and MALDI-TOP MS were used for the study. Results: This purified protocol improved 137-fold purification and 45.6 % recovery of enzyme activity. The molecular mass of EDNase was estimated to be 63 000. Mg2+ , Mn2+ and Ca2+ were strong inhibitors of EDNase, while Na+ slightly increasd the enzyme activity. The enzyme was completely stable in the pH range from 4. 4 to 5.2 and had a pH optimum of 4.8. The optimum temperature was 37℃ and the enzyme was stable up to 40 ℃. The pI of the enzyme was 6. 20. Km and Vmax for the enzyme were 1.52 g/L and 4. 89 mg/(mL ·min), respectively, with calf thymus DNA as substrate. The enzyme was able to degrade chromosemal DNA, linear λbacteriophage DNA as well as supereoiled plasmid DNA, but didn' t display any RNase activity. Conclusion: This kind of deoxyribonuclease possesses unique characteristics, which is different from the deoxyribonucleases which we have known before.

AIM:To explore the production and cytotoxicity of the reactive oxygen species(ROS)induced by diallyl trisulfide(DATS)in HL-60 cells.METHODS:HL-60 cells were either treated with various doses of DATS alone,or DATS combination with apocynin,a specific NADPH oxidase inhibitor,or with antioxidant N-acetyl-L-cysteine(NAC)for 0,1,3,6,12 and 24 h,respectively.The intracellular ROS level was measured by flow cytometry.The activity of NADPH oxidase was evaluated by NBT reduction experiment.The content of both malondialdehyde(MDA)and the protein carbonyl were analyzed by spectrophotometer.RESULTS:The results from flow cytometry indicated that DATS significantly increased the intracellular ROS level in HL-60 cells(P