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.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

OBJECTIVE To provide a reference for revising the safety content of traditional Chinese medicine（TCM） instructions. METHODS A systematic analysis was conducted on the relevant announcements on the revision of TCM instruction from 2013 to 2024， including the year of publication， drug name， drug formulation， announcement release time， and the average number of revisions made to three safety contents （contraindication， adverse drug reaction， and precaution）. According to the report data of national adverse drug reaction monitoring from 2013 to 2024， analyze the proportion of TCM in all adverse drug reactions， the composition ratio of adverse drug reaction of different dosage forms of drugs [TCM injection， oral TCM， other （topical） TCM]. RESULTS From 2013 to 2024， the National Medical Products Administration issued a total of 101 notices on the revision of TCM instruction， involving 241 types of TCM. Among them， there were 163 types of oral TCM， 25 types of TCM injection， and 53 types of other （topical） TCM. There were 3， 10 and 0 types of TCM injection， oral TCM， and other （topical） TCM with missing safety content， respectively. The main source of adverse drug reaction data for TCM injections was post- marketing monitoring data （accounting for 48.00%）； the main source of adverse drug reaction data for oral TCM was monitoring data （accounting for 71.17%）； 73.58% of other （topical） TCM did not mention the source of adverse drug reaction data. The report on national adverse drug reaction monitoring showed that the proportion of all adverse drug reactions of TCM had decreased from 17.3% in 2013 to 12.1% in 2024. Among them， the proportion of adverse drug reaction of TCM injection in the three dosage forms of TCM had decreased from 61.3% in 2015 to 24.6% in 2024， while the proportion of adverse drug reaction of oral TCM in the three dosage forms of TCM had increased from 34.7% in 2015 to 64.0% in 2024. CONCLUSIONS The risk management of TCM safety content has achieved results in China， but still faces three major challenges： strongdependence on passive monitoring， insufficient data traceability， and missing key content. It is urgent to improve safety content by dosage form， optimize data sources， and fully utilize real-world evidence to supplement safety content.

Jiaxing city is one of the pilot cities for the Long-term Care Insurance(LTCI)policy in Zhejiang Province.This study examines the current implementation status of Jiaxing's LTCI policy in terms of financing(including financing targets,channels,methods,and standards)and benefit payments(including payment forms,contents,standards,and levels).It summarizes the experiences and challenges encountered during the pilot process.Currently,Jiaxing's LTCI policy has undergone continuous improvement in financing and benefit payment mechanisms.The financing targets now cover both urban and rural residents,and the coverage has expanded from individuals with severe disabilities to include those with severe dementia.The benefit content has been refined,with the introduction of a detailed service project directory and service pricing.For the future,it is recommended to expand the coverage to individuals with moderate disabilities,based on the fund's capacity and sustainability,and to differentiate benefit standards according to the severity of disability.Furthermore,it is suggested to strengthen the responsibilities of employers and individuals,diversify financing channels,and gradually explore an independent financing mechanism for LTCI.A combination of fixed-amount and proportional financing methods should be considered,alongside factors such as intergenerational equity and population aging trends,to establish a scientific and dynamic premium adjustment mechanism.

Six compounds were isolated from the ethyl acetate fraction of Citri Sarcodactylis Fructus by using various column chromatographic methods, such as MCI Gel CHP-20, ODS, Sephadex LH-20, silica gel and semipreparative HPLC. Their structures were identified to be citrusin G (1), citrusin H (2), citrusin E (3), syringin (4), coniferin (5), methylconiferin (6) by NMR, HR-ESI-MS, UV, IR spectra. Compounds 1 and 2 were new secondary metabolism products and 3-6 were obtained from the titled material for the first time. Compound 1 showed anti-renal fibrosis activity in TGF-β1-induced kidney proximal tubular cells.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

Objective To analyze the distribution characteristics of the single nucleotide polymorphism (SNP) site rs76206423 in the promoter region of the interleukin-2 receptor (IL-2R) β gene among Han males in a high radiation background area (HBRA) in Yangjiang City. Methods A total of 48 male participants from Tangkou Town, Yangxi County, Yangjiang City (HBRA group), and 51 male participants from Hengpo Town, Enping City (control group) were selected as the research subjects using the random number table method. Peripheral venous blood samples of participants from both groups were collected, and genomic DNA was extracted. The genotyping and allele frequency distribution of the rs76206423 (A/G) site in the IL-2R β promoter region was detected among the participants in both groups using the SNP detection method. The difference of allele frequencies between population in HBRA group and five area of East Asia, South Asia, Africa, Europe, and the Americas published in the Human Genome Project database from National Center for Biotechnology Information were analyzed. Results The allele frequencies of rs76206423 of population in both groups conformed to Hardy-Weinberg equilibrium (P>0.05). In the HBRA group, the AA genotype was predominant (64.6%), while the AG genotype was the most common in the control group (51.0%), with a significant difference (P<0.05). Population in both groups showed a predominance of the variant allele A (78.1% and 72.5%, respectively), with no significant difference (P>0.05). The frequency of the G allele of rs76206423 in the population in HBRA group was higher than those in South Asian, African, European, and American populations (all P<0.01), but showed no significant difference compared with East Asian populations (P>0.05). Conclusion In the Han male population from the HBRA in Yangjiang City, the rs76206423 site in the IL-2R β gene promoter region is predominantly composed of the wild-type A allele and AA genotype, indicating genetic stability and a relatively high degree of variation at this locus.

The Expert Consensus on the Deployment of DeepSeek in Medical Institutions serves as a detailed guideline for the deployment of DeepSeek in medical institutions. It was developed by experts in the fields of healthcare， hospital management， medical information， health policy， law， and medical ethics from nearly 30 leading domestic medical and academic research institutions， based on relevant domestic and international laws and regulations as well as the practices of medical institutions. It aims to provide medical institutions with a scientific， standardized， and secure deployment guideline to ensure that the application of artificial intelligence （AI） technologies in healthcare， including but not limited to DeepSeek， conforms to the unique characteristics of the healthcare industry and effectively promotes the improvement of medical service levels. From the three aspects of pre-deployment evaluation， deployment implementation， and post-deployment management and monitoring， the key factors that medical institutions should consider when introducing DeepSeek were elaborated in detail， including medical demand compatibility， technical capabilities and infrastructure， legal and ethical risks， data preparation and management， model selection and optimization， system integration and training， performance monitoring and continuous optimization， risk management and emergency response， as well as compliance review and evaluation. This provides a comprehensive deployment framework for medical institutions to ensure the safety and effectiveness of technology applications.

Objective: To prepare platelet membrane biomimetic liposomes loaded with vincristine sulfate (VCR) for targeted delivery to tumor. Methods: Vincristine sulfate liposomes (LIPO) were prepared using the pH-gradient method, followed by the fusion of platelet membranes and subsequent drug loading to obtain platelet membrane biomimetic liposomes (PLM-LIPO). The particle size, polydispersity index (PDI), Zeta potential, and drug encapsulation efficiency (EE%) of both liposomes were characterized. The tumor-targeting capability was evaluated through in vitro cellular experiments and in vivo biodistribution studies. Results: The optimal preparation conditions for LIPO were determined as follows: DPPC-to-cholesterol molar ratio of 1∶1, internal aqueous phase of 0.3 M pH 4.0 citrate buffer, external aqueous phase of 1 M Na HPO solution, drug-to-lipid ratio of 1∶10, drug loading temperature of 60℃, and loading time of 10 minutes. The LIPO exhibited a mean particle size of (147.3±2.24) nm, PDI of 0.078±0.014, Zeta potential of (-3.54±0.75) mV, and EE% of 91.37±0.47. For PLM-LIPO, prepared via membrane fusion followed by drug loading, the mean particle size was (185.3±3.61) nm, PDI was 0.075±0.022, Zeta potential was (-18.91±1.54) mV, and EE% was 63.36±2.45. In the CD62P validation experiment, the fluorescence intensity of PLM-LIPO was five times higher than that of LIPO. In vitro cellular uptake experiments revealed that PLM-LIPO showed 1.3-fold and 1.2-fold higher uptake rates compared to LIPO at 6 h and 12 h, respectively. In vivo experiments demonstrated that 1h after administration, the accumulation of PLM-LIPO at tumor sites was 4-fold higher than that of LIPO and 6-7 times higher than that in healthy mice. Conclusion: The platelet membrane biomimetic liposomes loaded with vincristine sulfate were successfully developed. Both cellular uptake and tissue distribution studies confirmed the PLM-LIPO enhanced tumor-targeting capability.

Image 1.