With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective: To develop a quality appraisal tool for case reports in traditional Chinese medicine (TCM) based on their characteristics. [Methods]: An extensive literature search was conducted in Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), and China Science and Technology Journal Database (CSTJ), focusing on expert consensus statements and checklists for TCM case reports. Relevant items were extracted, and a Delphi method involving 34 experts was used in two rounds to rate each item on a 5-point Likert scale. Items were screened based on measures of central tendency and coordination (including total score, mean score, percentage of items rated as unimportant, and coefficient of variation). The weighted average method was used to determine item weights and construct the appraisal tool. Internal consistency was assessed using Cronbach’s α coefficient. The finalized tool was pilot-tested by two reviewers independently appraising 20 case reports, with an additional four reviewers evaluating 5 of these cases to compare inter-rater consistency. Results: A total of 9 513 articles were retrieved, and 96 items from 25 articles were extracted. After two rounds of the Delphi method, 27 items across 10 domains were retained. The Cronbach’s α coefficient was 0.72 in the first round (acceptable range), and 0.96 in the second round, indicating strong internal consistency. The tool was piloted by six reviewers, achieving a kappa value of 0.663 and a Kendall’s coefficient of concordance of 0.845, demonstrating high consistency among reviewers. Conclusion The developed TCM case report quality appraisal tool, consisting of 27 items in 10 domains, offers a scientific and reliable means of assessing the quality of TCM case reports. The tool showed high consistency and practical utility, and its application is expected to enhance the standardization, scientific rigor, and evidence quality of TCM case reports, facilitating the integration of traditional medical knowledge with modern evidence-based standards.

With the advancement of China's healthcare reform,enhancing the capacity of primary healthcare services has become a pivotal task.Colorectal cancer,one of the most prevalent malignancies in China,highlights the critical importance of early screening and diagnosis to improve patient survival rates.This study,guided by the principles of Party building and Xi Jinping Thought on Socialism with Chinese Characteristics,examines the implementation and outcomes of a rural outreach program focused on colorectal cancer screening and diagnostic technologies.By promoting the dissemination of colorectal cancer screening initiatives,the paper aims to provide empirical evidence to support the deepening of primary-care services,foster high-quality ad-vancement of grassroots health services,and align with the national Healthy China Initiative,thereby more effectively safeguarding population health.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.

Objective:To analyze the effect of precipitation on road traffic injuries (RTI) in Zhejiang Province.Methods:The RTI surveillance and meteorological data from 2009 to 2022 in Zhejiang Province were collected. Based on the time-stratified case-crossover design, the precipitation of case day and control day was compared, and the distributed lag nonlinear model was applied to analyze the correlation of precipitation and RTI. Stratified analyses were conducted to analyze the effect modification of gender, age, injury location, and temperature. An attributable fraction was used to assess the burden of RTI caused by precipitation.Results:A total of 239 970 RTIs were monitored in Zhejiang Province from 2009 to 2022, averaging 46 daily cases. The distributed lag nonlinear model showed that compared with no rain, the risk of RTI increased first and then decreased with the increase of precipitation. The risk of RTI was the highest when the precipitation was 30.99 mm ( OR=1.08, 95% CI: 1.05-1.11). The adverse effects on RTI mainly occurred on the day of precipitation, and it showed insignificant or protective effects with the extension of lag days. 1.34%(95% CI: 1.31%-1.36%) of RTI could be attributed to precipitation. Stratified analysis showed that gender, age, injury location, and temperature may modify the effect of precipitation on RTI. Precipitation caused a heavier burden on RTI in subgroups aged 18-64, females, and occurring on roads and in low temperatures. Conclusions:Precipitation can increase the risk of RTI. People aged 18-64 or females are the key groups for RTI prevention, and prevention and control efforts of precipitation-related RTI should be increased in road and low-temperature environments.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.

Diabetes is a very complex endocrine disease whose common feature is the increase in blood glucose concentration. Persistent hyperglycemia can lead to blindness, kidney and heart disease, neurodegeneration, and many other serious complications that have a significant impact on human health and quality of life. The number of people with diabetes is increasing yearly. The global diabetes prevalence in 20-79 year olds in 2021 was estimated to be 10.5% (536.6 million), and it will rise to 12.2% (783.2 million) in 2045. The main modes of intervention for diabetes include medication, dietary management, and exercise conditioning. Medication is the mainstay of treatment. Marketed diabetes drugs such as metformin and insulin, as well as GLP-1 receptor agonists, are effective in controlling blood sugar levels to some extent, but the preventive and therapeutic effects are still unsatisfactory. Peptide drugs have many advantages such as low toxicity, high target specificity, and good biocompatibility, which opens up new avenues for the treatment of diabetes and other diseases. Currently, insulin and its analogs are by far the main life-saving drugs in clinical diabetes treatment, enabling effective control of blood glucose levels, but the risk of hypoglycemia is relatively high and treatment is limited by the route of delivery. New and oral anti-diabetic drugs have always been a market demand and research hotspot. Inhibitor cystine knot (ICK) peptides are a class of multifunctional cyclic peptides. In structure, they contain three conserved disulfide bonds (C3-C20, C7-C22, and C15-C32) form a compact “knot” structure, which can resist degradation of digestive protease. Recent studies have shown that ICK peptides derived from legume, such as PA1b, Aglycin, Vglycin, Iglycin, Dglycin, and aM₁, exhibit excellent regulatory activities on glucose and lipid metabolism at the cellular and animal levels. Mechanistically, ICK peptides promote glucose utilization by muscle and liver through activation of IR/AKT signaling pathway, which also improves insulin resistance. They can repair the damaged pancrease through activation of PI3K/AKT/Erk signaling pathway, thus lowering blood glucose. The biostability and hypoglycemic efficacy of the ICK peptides meet the requirements for commercialization of oral drugs, and in theory, they can be developed into natural oral anti-diabetes peptide drugs. In this review, the structural properties, activity and mechanism of ICK pattern peptides in regulating glucose and lipid metabolism were summaried, which provided a reference for the development of new oral peptides for diabetes.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Objective To investigate the effect of ATP synthase inhibitory factor 1 (ATPIF1) on the antitumor activity of chimeric antigen receptor (CAR)-NK92 cells. Methods HER2-targeted CAR-NK92 cells with ATPIF1 overexpression or knockdown were constructed. CAR-positive expression rate was detected by flow cytometry. Cell proliferation capacity was measured using CCK-8 assay. Glycolytic capacity was analyzed by Seahorse metabolic analyzer. Mitochondrial membrane potential levels were detected using JC-1 probe. Target cell lysis rate was evaluated by firefly luciferase reporter assay. Expression levels of CD107a, natural-killer group 2 member D (NKG2D), granzyme B (GzmB), perforin, and interleukin 2 (IL-2) were detected via flow cytometry. Quantitative real-time PCR was used to measure the expression of interferon-induced protein with tetratricopeptide repeats 1 (IFIT1), tumor necrosis factor α (TNF-α), ATPIF1, and hexokinase 1 (HK1). The impact of glycolytic inhibition by 2-Deoxy-D-glucose (2-DG) on CAR-NK92 antitumor capacity was examined. Results Successfully generated HER2-targeting control CAR-NK92 cells, as well as ATPIF1-overexpressing and ATPIF1 knockdown CAR-NK92 cells. The ATPIF1-overexpressing CAR-NK92 cells showed significantly enhanced target cell lysis rate, elevated expression levels of NKG2D and CD107a, increased secretion capacities of Granzyme B (GzmB) and IL-2, and upregulated mRNA expression levels of IFIT1 and TNF-α, while ATPIF1-knockdown cells exhibited opposite effects. ATPIF1 overexpression induced metabolic reprogramming in CAR-NK92 cells, manifested by significantly decreased mitochondrial membrane potential (δpsim), markedly upregulated HK1 mRNA expression, and enhanced basal glycolysis and glycolytic capacity. After glycolysis inhibition with 2-DG (5 μmol/L), both ATPIF1-overexpressing and knockdown CAR-NK92 cells showed no significant differences in NKG2D and CD107a expression levels compared to control cells. Conclusion ATPIF1 regulates the antitumor activity of CAR-NK92 cells through modulating glycolytic metabolism. Overexpression of ATPIF1 can enhance the antitumor efficacy of CAR-NK92 cells.
Humans ; Glycolysis ; Killer Cells, Natural/metabolism* ; Receptors, Chimeric Antigen/immunology* ; Granzymes/genetics* ; Hexokinase/metabolism* ; Cell Line, Tumor ; Interleukin-2/genetics* ; Cell Proliferation ; NK Cell Lectin-Like Receptor Subfamily K/genetics* ; Membrane Potential, Mitochondrial