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.

ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point， this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding， 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups （10 mice per group）： The 12-month-old control group （12MCON）， the 15-month-old control group （15MCON）， and the 15-month-old group with a high-fat diet （15MHFD）. The 12MCON and 15MCON groups were continuously fed a standard diet， while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups （10 mice per group）： the 20-month-old control group （20MCON）， the model group， and the low-， medium-， and high-dose Liangyi Paste groups （2.91 ， 5.82 ， 11.64 g·kg^-1·d^-1， respectively）. The 20MCON group was continuously fed a standard diet， while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age， the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage， while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage （when the mice reached 20 months of age）， tissue samples were collected. Hepatic TG levels were measured using assay kits； liver histology and lipid deposition were observed via hematoxylin-eosin （HE） and oil red O staining； reactive oxygen species （ROS） were detected by enzyme-linked immunosorbent assay （ELISA）； Cu²⁺， superoxide dismutase （SOD）， and malondialdehyde （MDA） levels were measured by colorimetry； mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction（Real-time PCR） and Wes automated protein expression system. ResultsCompared with 12MCON， the 15MCON group showed significantly increased hepatic TG， Cu²⁺， ROS， and MDA levels （P<0.01）， decreased SOD （P<0.01）， hepatocyte swelling， and disordered arrangement. The mRNA and protein levels of ferredoxin 1 （FDX1）， dihydrolipoamide S-acetyltransferase （DLAT）， heat shock protein 70 （HSP70）， dihydrolipoamide dehydrogenase （DLD）， pyruvate dehydrogenase E1 subunit-β （PDHB）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and peroxisome proliferator-activated receptor γ （PPARγ） were significantly elevated （P<0.05， P<0.01）. Compared with 15MCON group， the 15MHFD and 20MCON groups exhibited further increases in TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group， and no significant lipid deposition was observed in the 20MCON group. FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and protein levels were significantly increased （P<0.05， P<0.01）. Compared with 20MCON group， the model group demonstrated markedly elevated TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， severe hepatic steatosis， and upregulated expression of FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and proteins （P<0.05， P<0.01）. All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.

To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework.

OBJECTIVE To systematically evaluate the effects of oral non-peptidic thrombopoietin receptor agonists （TPO-RAs） on hepatic enzyme in adult patients with immune thrombocytopenia. METHODS A comprehensive literature search was conducted in PubMed， Web of Science， CNKI， Wanfang database and the Chinese Medical Association Journal Full-Text Database to collect randomized controlled trials （RCTs） comparing oral non-peptidic TPO-RAs （intervention group） with placebo or conventional therapy （control group）. All databases were searched from their inception to June 2025. After literature screening， data extraction and quality assessment of the included studies， meta-analysis was conducted using RevMan 5.4.1 software. RESULTS Twelve RCTs comprising 1 388 patients were included， with 971 in the intervention group and 417 in the control group. Meta-analysis results showed that there were no significant differences between the two groups in terms of the incidence of hepatic enzyme elevation[OR＝1.24， 95%CI （0.77， 1.99）， P ＝0.37 ] ， the incidence of hepatic enzyme elevation in patients treated for ≥6 weeks[OR＝1.21， 95%CI （0.73， 1.99）， P ＝0.46 ] ， and the incidence of severe hepatic enzyme elevation[OR＝1.39， 95%CI（0.46， 4.20）， P ＝0.55 ] . Subgroup analysis showed that there were no significant differences in the incidence of hepatic enzyme elevation between the intervention group and control group among patients using eltrombopag[OR＝1.57，95%CI（0.85，2.87）， P ＝0.15 ] ， avatrombopag[OR＝0.88，95%CI （0.09，8.46）， P ＝0.91 ] ， and hetrombopag[OR＝1.04，95%CI（0.30，3.65）， P ＝0.95 ] ， respectively. CONCLUSIONS Oral non-peptidic TPO-RAs do not significantly increase the risk of hepatic enzyme elevation in adult patients with immune thrombocytopenia， and show an overall favorable hepatic safety profile.

ObjectiveTo investigate the effects of modified Ditan tang on genes related to the transcription-translation feedback loop （TTFL） of biorhythm in the rat model of non-alcoholic fatty liver disease （NAFLD） and its mechanism for prevention and treatment of NAFLD. MethodsSixty-five healthy SPF male SD rats were randomly assigned into blank （n=20）， model （n=15）， and low-， medium-， and high-dose （2.68， 5.36， and 10.72 g·kg^-1·d^-1， respectively） modified Ditan tang （n=10） groups. Other groups except the blank group were fed a high-fat diet for 12 weeks. The modified Ditan tang groups were treated with the decoction at corresponding doses by gavage， and the blank and model groups were treated with an equal volume of normal saline from the 9th week for 4 weeks. The levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） in the serum were measured by an automatic biochemical analyzer. TG and non-esterified fatty acid （NEFA） assay kits were used to measure the levels of TG and NEFA in the liver. The pathological changes in the hypothalamus and liver were observed by hematoxylin-eosin staining， and the lipid deposition in the liver was observed by oil red O staining. The levels of brain-muscle ARNT-like protein 1 （BMAL1/ARNTL） in the hypothalamus and liver were determined by immunohistochemical staining. The mRNA and protein levels of BMAL1， circadian locomotor output cycles kaput （CLOCK）， period circadian clock 2 （PER2）， and cryptochrome1 （Cry1） in the hypothalamus and liver were determined by Real-time PCR and Western blot， respectively. ResultsCompared with the blank group， the model group showed elevated levels of TG， TC， LDL-C， AST， and ALT （P<0.01） and a lowered level of HDL-C （P<0.05） in the serum， elevated levels of TG and NEFA in the liver （P<0.01）， pyknosis and deep staining of hypothalamic neuron cells， and a large number of vacuoles in the brain area. In addition， the model group showed lipid deposition in the liver， up-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.01）， and down-regulated mRNA and protein levels of Cry1 and PER2 （P<0.01） in the hypothalamus and liver. Compared with the model group， all the three modified Ditan tang groups showed lowered levels of TG， TC， LDL-C， ALT， and AST （P<0.05， P<0.01） and an elevated level of HDL-C （P<0.05） in the serum， and lowered levels of TG and NEFA （P<0.05， P<0.01） in the liver. Furthermore， the three groups showed alleviated pyknosis and deep staining of hypothalamic neuron cells， reduced lipid deposition in the liver， down-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.05， P<0.01）， and up-regulated mRNA and protein levels of Cry1 and PER2 （P<0.05， P<0.01） in the hypothalamus and liver. ConclusionModified Ditan tang can reduce lipid deposition in the liver and regulate the expression of CLOCK， BMAL1， Cry1， and PER2 in the TTFL of NAFLD rats.

Background Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants widely distributed in the environment. Epidemiological studies have shown that PFAS exposure is closely associated with liver dysfunction and an increased risk of liver cancer. Some animal and cell experiments have also revealed its hepatotoxicity and potential carcinogenicity; however, the related carcinogenic mechanism has not yet been fully elucidated. Objective To explore the potential molecular mechanism of PFAS-induced liver cancer, identify the key causal genes, and specifically evaluate the causal association and expression changes of KMT2C in this process, as well as the binding stability between KMT2C and PFAS, and to provid a theoretical basis for mechanistic studies and molecular target discovery in PFAS-related liver cancer. Methods Toxicity prediction was performed on six representative PFAS. Potential target genes of PFAS were identified by integrating results from SwissTargetPrediction, STITCH, and TargetNet databases. Liver cancer-related genes were retrieved from GeneCards, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). The intersection of PFAS targets and liver cancer-related genes was used to obtain core genes. A compound-gene-disease regulatory network was constructed, and a protein–protein interaction network was established using STRING database. A core gene network was visualized based on node degree values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore biological functions and enriched signaling pathways. Subsequently, two-sample Mendelian randomization was employed to assess potential causal relationships between candidate genes and hepatocellular carcinoma, enabling the identification of key genes. Molecular docking analysis using AutoDock was conducted to evaluate the binding stability between KMT2C and PFAS, and TCGA data were used to validate the differential expression of KMT2C between hepatocellular carcinoma and adjacent normal tissues. Results PFAS exhibited multisystem toxicity and posed significant risks of liver injury and carcinogenesis. A total of 266 PFAS target genes and 2923 liver cancer-related genes were identified, with 61 intersecting genes obtained. The enrichment analysis revealed that these intersecting genes were primarily involved in epigenetic regulation, nuclear receptor signaling pathways, and apoptosis-related pathways including TGF-β FoxO and Notch, suggesting their roles in diverse tumor-related biological processes. The two-sample Mendelian randomization results showed a significant negative causal association between KMT2C and hepatocellular carcinoma (OR=0.68, P <0.05). The molecular docking results demonstrated that all tested PFAS exhibited favorable binding to the KMT2C protein, with binding energies below –5.0 kcal·mol⁻¹. KMT2C was significantly upregulated in hepatocellular carcinoma tissues (unpaired P=0.025; paired P=8.38 × 10⁻⁴). Conclusion The KMT2C protein is found to stably bind with all six PFAS, exhibiting strong structural affinity. A causal relationship is identified between KMT2C and the development of hepatocellular carcinoma. TCGA data indicate that KMT2C is significantly upregulated in hepatocellular carcinoma tissues, and it may serve as a key regulatory target in PFAS-related liver cancer.

Cancer is characterized by abnormal cell proliferation. Cyclins and cyclin-dependent kinases (CDKs) have been recognized as essential regulators of the intricate cell cycle, orchestrating DNA replication and transcription, RNA splicing, and protein synthesis. Dysregulation of the CDK pathway is prevalent in the development and progression of human cancers, rendering cyclins and CDKs attractive therapeutic targets. Several CDK4/6 inhibitors have demonstrated promising anti-cancer efficacy and have been successfully translated into clinical use, fueling the development of CDK-targeted therapies. With this enthusiasm for finding novel CDK-targeting anti-cancer agents, there have also been exciting advances in the field of targeted protein degradation through innovative strategies, such as using proteolysis-targeting chimera, heat shock protein 90 (HSP90)‍-mediated targeting chimera, hydrophobic tag-based protein degradation, and molecular glue. With a focus on the translational potential of cyclin- and CDK-targeting strategies in cancer, this review presents the fundamental roles of cyclins and CDKs in cancer. Furthermore, it summarizes current strategies for the proteasome-dependent targeted degradation of cyclins and CDKs, detailing the underlying mechanisms of action for each approach. A comprehensive overview of the structure and activity of existing CDK degraders is also provided. By examining the structure‍‒‍activity relationships, target profiles, and biological effects of reported cyclin/CDK degraders, this review provides a valuable reference for both CDK pathway-targeted biomedical research and cancer therapeutics.
Humans ; Neoplasms/metabolism* ; Cyclin-Dependent Kinases/antagonists & inhibitors* ; Cyclins/metabolism* ; Proteolysis ; Antineoplastic Agents/pharmacology* ; Molecular Targeted Therapy ; Proteasome Endopeptidase Complex/metabolism* ; Animals

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*