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.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

To analyze the distribution of serotypes and antimicrobial resistance of clinical Salmonella isolates from multiple centers across China.

OBJECTIVE To provide standardized whole-process guidance on drug traceability codes for medical institutions in Sichuan province， ensuring medication safety and compliance with medical insurance supervision requirements. METHODS Based on evidence-based principles and expert consensus， Expert Consensus on Whole-process Management of Drug Traceability Codes in Medical Institutions of Sichuan Province （hereinafter referred to as the Consensus） was formulated through systematic literature review， field investigations， establishment of a multidisciplinary expert committee and multiple rounds of questionnare consultation via the modified Delphi method， and finalized through consensus meetings. RESULTS & CONCLUSIONS The Consensus clarifies key operating procedures for code verification， code assignment and code return， whole-process operational standards for drug warehouse acceptance and storage， drug warehouse outbound delivery and pharmacy acceptance check， drug distribution and dispensing in pharmacy and intravenous admixture center， medication administration in nursing units and examination departments， as well as drug return process. Key recommendations are proposed such as improving the core functions of the drug traceability system， unifying the hospital-wide traceability code database， strengthening the management of traceability codes for backup medications， establishing a management organization and institutional framework， and optimizing the architectural design and data governance requirements of the drug traceability system. The release of the Consensus will provide scientific， standardized and implementable practical guidelines for medical institutions of Sichuan province， helping to improve closed-loop management of the drug traceability system， strengthen medication safety and fulfil medical insurance fund supervision.

Intestinal microecological changes are closely related to liver cirrhosis and cirrhosis-related sarcopenia.Studies has demonstrated that interventions targeting the intestinal microbiota could contribute to the treatment of cirrhosis and cirrhosis-related sarcopenia.Here we reviewed the research progress on the alterations in intestinal microbiota during liver cirrhosis and the underlying mechanisms by which these changes impacted the development of the disease.The potential of microbiota-targeted interventions in both preventing and treating liver cirrhosis and related sarcopenia was also discussed,which might provide valuable insights into clinical diagnosis and management of the disease.

Objective:To investigate the prevalence of adult skeletal fluorosis caused by drinking tea-type endemic fluorosis in Yushu Tibetan Autonomous Prefecture (hereinafter referred to as Yushu Prefecture), Qinghai Province, and provide scientific basis for prevention and control of the disease.Methods:In August 2021, one village was selected as a survey site in six counties (cities) in Yushu Prefecture, including Nangqian, Chindu, Yushu, Zadoi, Qumarlêb, and Zhiduo. Drinking water samples and 10 brick tea samples were collected from each village to determine the fluoride content in water and brick tea; at least 100 permanent residents aged ≥ 25, who had a habit of drinking brick tea and had lived in the local area for more than 5 years, were selected for X-ray imaging to examine the prevalence of adult skeletal fluorosis.Results:A total of 75 samples of residential drinking water were collected, with a fluoride content of (0.21 ± 0.05) mg/L, ranging from 0.11 to 0.34 mg/L; 60 samples of brick tea, with a fluoride content of (626.70 ± 157.27) mg/kg, ranging from 324.00 to 2 102.00 mg/kg. A total of 1 136 adults were examined, and 318 cases of skeletal fluorosis were diagnosed, with a detection rate of 27.99%. Among them, the detection rates of mild, moderate, and severe skeletal fluorosis were 20.95% (238/1 136), 6.07% (69/1 136), and 0.97% (11/1 136), respectively, with mild symptoms being the main. The detection rates of skeletal fluorosis in males and females were 29.09% (121/416) and 27.36% (197/720), respectively, with no statistically significant difference between the gender (χ 2 = 0.39, P = 0.533). Comparison of the skeletal fluorosis in different gender, the differences were statistically significant (χ 2 = 22.31, P < 0.001). The detection rates of skeletal fluorosis in the age groups of 25 - 35, 36 - 45, 46 - 55, 56 - 65, 66 - 75, and ≥76 years old were 6.86% (7/102), 22.37% (51/228), 24.02% (92/383), 37.44% (73/195), 43.48% (70/161), and 37.31% (25/67), respectively. The differences between the groups were statistically significant (χ 2 = 59.84, P < 0.001). Moreover, there was a statistically significant difference in the composition of skeletal fluorosis among different age groups ( H = 37.66, P < 0.001). The Spearman correlation analysis results showed that the severity of adult skeletal fluorosis was positively correlated with age ( r = 0.34, P < 0.001). Conclusions:There is a certain degree of prevalence of adult skeletal fluorosis in Yushu Prefecture. And as age increases, the condition of skeletal fluorosis becomes more severe.

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
Male ; Humans ; Prostate/pathology* ; Prostate-Specific Antigen/analysis* ; Prostatic Neoplasms/diagnostic imaging* ; Biopsy ; Nomograms ; Retrospective Studies

Uncontrolled and persistent inflammation is closely related to numerous acute and chronic diseases. However, effective targeting delivery systems remain to be developed for precision therapy of inflammatory diseases. Herein we report a novel strategy for engineering inflammation-accumulation nanoparticles via phenolic functionalization. Different phenol-functionalized nanoparticles were first developed, which can undergo in situ aggregation upon triggering by the inflammatory/oxidative microenvironment. Phenolic compound-decorated poly (lactide-co-glycolide) nanoparticles, in particular tyramine (Tyr)-coated nanoparticles, showed significantly enhanced accumulation at inflammatory sites in mouse models of colitis, acute liver injury, and acute lung injury, mainly resulting from in situ cross-linking and tissue anchoring of nanoparticles triggered by local myeloperoxidase and reactive oxygen species. By combining a cyclodextrin-derived bioactive material with Tyr decoration, a multifunctional nanotherapy (TTN) was further developed, which displayed enhanced cellular uptake, anti-inflammatory activities, and inflammatory tissue accumulation, thereby affording amplified therapeutic effects in mice with colitis or acute liver injury. Moreover, TTN can serve as a bioactive and inflammation-targeting nanoplatform for site-specifically delivering a therapeutic peptide to the inflamed colon post oral administration, leading to considerably potentiated in vivo efficacies. Preliminary studies also revealed good safety of orally delivered TTN. Consequently, Tyr-based functionalization is promising for inflammation targeting amplification and therapeutic potentiation of nanotherapies.

The number of investigator initiated research (IIR) is increasing. But the recognition and management of IIR in China is still in its infancy, and there is a lack of specific and operable guidance for the implementation process. Based on our practical experiences, previous literature reports, and current policy regulations, the authors took prospective IIR as an example to summarize the implementation process of IIR into 14 steps, which are as the following: study initiation, ethical review, study registration, study filing, case report form design, database establishment, standard operating procedure making, investigator training, informed consent, data collection, data entry, data verification, data locking and data archiving.