Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Objective:To describe epidemiological characteristics and their influencing factors of diabetes and pre-diabetes among adult residents in Hainan Province and provide a theoretical basis to develop epidemic prevention and control strategies for diabetes.Methods:This study used a two-stage unequal proportion cluster sampling method, and 32 857 subjects (≥18 years old) were collected from 24 cities/counties/districts in Hainan Province. All the subjects were investigated with questionnaires, physical examination, and laboratory tests from January to June 2023. The χ2 and Mantel-Haenszel trend χ2 tests were used to analyze the data. Multivariate logistic regression was used to analyze the factors influencing diabetes and pre-diabetes. SPSS 23.0 software was used to analyze the data. Results:The crude prevalence of diabetes and pre-diabetes in adult residents of Hainan Province were 18.1% and 22.8%, while the weighted rates were 13.7% and 20.7%, respectively. The results of multivariate logistic regression analysis showed that: aging (30-39 years old: OR=2.65, 95% CI: 2.06-3.41; 40-49 years old: OR=5.64, 95% CI: 4.40-7.24; 50- 59 years old: OR=9.88, 95% CI: 7.71-12.67; 60-69 years old: OR=18.34, 95% CI: 14.28-23.55; 70-79 years old: OR=21.30, 95% CI: 16.41-27.65; 80 years old and above: OR=24.13, 95% CI: 17.94-32.46), nationality (Li minority group: OR=1.50, 95% CI: 1.38-1.63; other ethnic groups: OR=1.53, 95% CI: 1.20-1.94), urban ( OR=1.12, 95% CI: 1.04-1.21), central obesity ( OR=2.14, 95% CI: 2.01-2.29), higher frequency of alcohol consumption (5-7 day/week: OR=1.24, 95% CI: 1.11-1.38), physical inactivity ( OR=1.09, 95% CI: 1.02-1.17) were risk factors for diabetes, while aging (30-39 years old: OR=1.53, 95% CI: 1.31-1.79; 40-49 years old: OR=2.36, 95% CI: 2.01-2.76; 50-59 years old: OR=3.03, 95% CI: 2.58-3.55; 60-69 years old: OR=4.22, 95% CI: 3.58-4.97; 70-79 years old: OR=5.05, 95% CI: 4.23-6.04; 80 years old and above: OR=6.08, 95% CI: 4.86-7.61), nationality: (Li minority group: OR=1.18, 95% CI: 1.10-1.28; other ethnic groups: OR=1.40, 95% CI: 1.14-1.71), urban ( OR=1.12, 95% CI: 1.04-1.19), central obesity ( OR=1.72, 95% CI: 1.62-1.83), higher frequency of alcohol consumption (1-4 day/week: OR=1.12, 95% CI: 1.01-1.23; 5-7 day/week: OR=1.35, 95% CI: 1.22-1.49) were risk factors for pre-diabetes. Conclusions:The epidemic situation of diabetes and pre-diabetes among adult residents in Hainan Province was not optimistic. In order to control the development of abnormal blood glucose, measures and targeted health education should be carried out to strengthen the screening, treatment, and management of people with abnormal blood glucose among different populations.

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 describe epidemiological characteristics and their influencing factors of diabetes and pre-diabetes among adult residents in Hainan Province and provide a theoretical basis to develop epidemic prevention and control strategies for diabetes.Methods:This study used a two-stage unequal proportion cluster sampling method, and 32 857 subjects (≥18 years old) were collected from 24 cities/counties/districts in Hainan Province. All the subjects were investigated with questionnaires, physical examination, and laboratory tests from January to June 2023. The χ2 and Mantel-Haenszel trend χ2 tests were used to analyze the data. Multivariate logistic regression was used to analyze the factors influencing diabetes and pre-diabetes. SPSS 23.0 software was used to analyze the data. Results:The crude prevalence of diabetes and pre-diabetes in adult residents of Hainan Province were 18.1% and 22.8%, while the weighted rates were 13.7% and 20.7%, respectively. The results of multivariate logistic regression analysis showed that: aging (30-39 years old: OR=2.65, 95% CI: 2.06-3.41; 40-49 years old: OR=5.64, 95% CI: 4.40-7.24; 50- 59 years old: OR=9.88, 95% CI: 7.71-12.67; 60-69 years old: OR=18.34, 95% CI: 14.28-23.55; 70-79 years old: OR=21.30, 95% CI: 16.41-27.65; 80 years old and above: OR=24.13, 95% CI: 17.94-32.46), nationality (Li minority group: OR=1.50, 95% CI: 1.38-1.63; other ethnic groups: OR=1.53, 95% CI: 1.20-1.94), urban ( OR=1.12, 95% CI: 1.04-1.21), central obesity ( OR=2.14, 95% CI: 2.01-2.29), higher frequency of alcohol consumption (5-7 day/week: OR=1.24, 95% CI: 1.11-1.38), physical inactivity ( OR=1.09, 95% CI: 1.02-1.17) were risk factors for diabetes, while aging (30-39 years old: OR=1.53, 95% CI: 1.31-1.79; 40-49 years old: OR=2.36, 95% CI: 2.01-2.76; 50-59 years old: OR=3.03, 95% CI: 2.58-3.55; 60-69 years old: OR=4.22, 95% CI: 3.58-4.97; 70-79 years old: OR=5.05, 95% CI: 4.23-6.04; 80 years old and above: OR=6.08, 95% CI: 4.86-7.61), nationality: (Li minority group: OR=1.18, 95% CI: 1.10-1.28; other ethnic groups: OR=1.40, 95% CI: 1.14-1.71), urban ( OR=1.12, 95% CI: 1.04-1.19), central obesity ( OR=1.72, 95% CI: 1.62-1.83), higher frequency of alcohol consumption (1-4 day/week: OR=1.12, 95% CI: 1.01-1.23; 5-7 day/week: OR=1.35, 95% CI: 1.22-1.49) were risk factors for pre-diabetes. Conclusions:The epidemic situation of diabetes and pre-diabetes among adult residents in Hainan Province was not optimistic. In order to control the development of abnormal blood glucose, measures and targeted health education should be carried out to strengthen the screening, treatment, and management of people with abnormal blood glucose among different populations.

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 analyze the MYH9 gene sequence of a patient with hereditary thrombocytopenia and diffuse large B-cell lymphoma and his family members,and to explore the relationship between MYH9 gene and tumors.Methods:Peripheral blood samples were collected from the patients and their family members for complete blood count analysis.The platelet morphology was observed under microscope.The MYH9 gene sequence was analyzed by Whole Exon Sequencing and Sanger Sequencing.Results:The mutation site c.279C＞A:p.(Asn93Lys)in exon 2 of the MYH9 gene were found in patient and his family members,both presenting as thrombocytopenia.The platelet count was significantly increased after the administration of Avatrombopag.Conclusion:A novel mutation of MYH9 was found in this study,and the case was sensitive to Avatrombopag,by exploring the relationship between the MYH9 gene and tumors,suggesting that the MYH9 gene may be associated with the development of diffuse large B-cell lymphoma.

The identification of the components absorbed in serum of platycosides in total saponins fraction of Platycodonis Radix is great significance, but there are still great challenges. In this study, 8 types of 44 primordial components from Platycodon saponins were firstly identified using the ultra-performance liquid chromatography-linear ion trap electrostatic field orbitrap high resolution mass spectrometry (UPLC-LTQ-Orbitrap-MS) equipped with the software of Compound Discoverer 3.2 and Trace finder 2.1. Then, the platycosides and their deglycosylated metabolites were used as the template molecules to construct the intestinal microbiota mediated method to identify the primary components and the prototypes in serum. As results, 57 components originating from 44 prototypes of platycosides were identified from drug-containing plasma. Those compounds consist of 12 prototypes of platycosides and 45 metabolites, while the prototypes in serum are also deglycosylated metabolites of other platycosides. The results showed that the intestinal microbiota mediated method could be applied to identify the metabolites of platycosides in total saponins fraction of Platycodonis Radix; and reveal the potential existing forms of prototypes of platycosides in plasma; In addition, it could clearly illustrate the one to many and many to one network of the prototypes and metabolites of platycosides. All animal protocols were approved by the Animal Ethics Committee of Jiangxi University of Traditional Chinese Medicine (No.JZLLSC-202100322).

Objective:To explore the plasma metabolomic characteristics of children with transfusion-dependent thalassemia(TDT),and reveal the changes of metabolic pattern in children with TDT.Methods:23 children with TDT who received regular blood transfusion in Ganzhou Women and Children's Health Care Hospital in 2021 were selected,and 11 healthy children who underwent physical examination during the same period were selected as the control group.The routine indexes between children with TDT and the control group were compared,and then the metabolic composition of plasma samples from children with TDT and the control group was detected by liquid chromatography-mass spectrometry.An OPLS-DA model was established to perform differential analysis on the detected metabolites,and the differential metabolic pathways between the two groups were analyzed based on the differential metabolites.Results:The results of routine testing showed that the indexes of ferritin,bilirubin,total bile acid,glucose and triglycerides in children with TDT were significantly higher than those in healthy controls,while hemoglobin and total cholesterol were significantly lower(all P＜0.05).However there was no significant difference in lactate dehydrogenase between the two groups(P＞0.05).Compared with the control group,190 differential metabolites(VIP＞1)were identified in TDT children.Among them,168 compounds such as arginine,proline and glycocholic acid were significantly increased,while the other 22 compounds such as myristic acid,eleostearic acid,palmitic acid and linoleic acid were significantly decreased.The metabolic pathway analysis showed that the metabolic impact of TDT on children mainly focused on the upregulation of amino acid metabolism and downregulation of lipid metabolism.Conclusion:The amino acid and lipid metabolism in children with TDT were significantly changed compared with the healthy control group.This finding is helpful to optimize the treatment choice for children with TDT,and provides a new idea for clinical treatment.

Objective To investigate the differences in visual perception between children with autism spectrum disorder(ASD)and typically developing(TD)children when watching different intention videos,and to explore the feasibility of machine learning algorithms in objectively distinguishing between ASD children and TD children.Methods A total of 58 children with ASD and 50 TD children were enrolled and were asked to watch the videos containing joint intention and non-joint intention,and the gaze duration and frequency in different areas of interest were used as original indicators to construct classifier-based models.The models were evaluated in terms of the indicators such as accuracy,sensitivity,and specificity.Results When using eight common classifiers,including support vector machine,linear discriminant analysis,decision tree,random forest,and K-nearest neighbors(with K values of 1,3,5,and 7),based on the original feature indicators,the highest classification accuracy achieved was 81.90% .A feature reconstruction approach with a decision tree classifier was used to further improve the accuracy of classification,and then the model showed the accuracy of 91.43% ,the specificity of 89.80% ,and the sensitivity of 92.86% ,with an area under the receiver operating characteristic curve of 0.909(P<0.001).Conclusions The machine learning model based on eye-tracking data can accurately distinguish ASD children from TD children,which provides a scientific basis for developing rapid and objective ASD screening tools.[Chinese Journal of Contemporary Pediatrics,2024,26(2):151-157]