It is very limited that the benefit of perioperative chemotherapy in early non-small cell lung cancer (NSCLC), and the 5-year survival rate is only 5% higher than surgery. Antibodies that block programmed cell death protein 1/programmed death-ligand 1 significantly improve the survival of advanced NSCLC. The value of immunotherapy in early NSCLC is also being explored. This paper firstly summarized and analyzed the progress of immunotherapy in the perioperative period of NSCLC. Secondly, the safety and feasibility of surgical resection after neoadjuvant immunotherapy were discussed. Finally, the clinical value of different therapeutic efficacy prediction indicators was summarized, in order to clarify the current status of immunotherapy in the perioperative period, so as to improve the clinical benefits of early NSCLC patients.

Objective To explore the application value of three mainstream large language models in the diagnosis, differential diagnosis, and treatment decision support of the primary diseases related to pediatric liver transplantation. Methods Seventy-nine cases of pediatric liver transplantation-related diseases diagnosed through pathological or clinical follow-up data were collected from Renji Hospital, Shanghai Jiao Tong University School of Medicine or published high-quality case reports. These cases covered 25 types of primary diseases such as cholestatic liver disease, metabolic diseases, and tumors. Standardized prompts were used to input the case information into the DeepSeek-R1, ChatGPT-4o and Grok-3 models, and the accuracy of their preliminary diagnosis and differential diagnosis based on basic clinical data was evaluated. The final diagnosis accuracy and the response time after supplementary examination were also assessed, as well as the completeness and rationality of their analysis of disease treatment principles. Results In the initial diagnosis and differential diagnosis stage, the comprehensive accuracy of DeepSeek-R1 was the highest [72.1%, 95% confidence interval (CI) 61.4% - 80.8%], and there was a statistically significant difference in the comprehensive accuracy of the three models for initial diagnosis (P = 0.008). After adding further examination information, the final diagnosis accuracy of the three models increased, with DeepSeek-R1 at 88.6% (95% CI 79.7% - 93.9%), ChatGPT-4o at 87.3% (95% CI 78.2% - 93.0%), and Grok-3 at 78.5% (95% CI 68.2% - 86.1%). There was no statistically significant difference among the three models (P = 0.05). The scores given by experts for the treatment principles showed good consistency (Kappa = 0.769). In addition, the response time of ChatGPT-4o is shorter than that of the other two models [(24 ± 7) s]. Conclusions Large language models demonstrate good efficacy in the diagnosis and treatment decision-making process of various pediatric liver diseases, have a good application prospect for auxiliary diagnosis and decision support, and are expected to help improve the accuracy and efficiency of clinical diagnosis and treatment of pediatric liver transplantation-related primary diseases.

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.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

Objective To investigate the efficacy of subcutaneous flap and/or pedicled penile skin flap combined with advancement flap coverage technique in the treatment of urethrocutaneous fistula(UCF)secondary to failed repair and to improve the success rate. Methods The clinical data of 36 UCF patients after urethral repair admitted to our hospital during Jan. 2020 and Jan. 2024 were retrospectively analyzed. According to the location and surrounding condition of the fistula, the fistula was closed without tension, the subcutaneous flap and/or pedicled penile skin flap was combined with advancement flap coverage technique. The effects of the treatment were followed up. Successful repair was defined as unobstructed urination, no recurrence of fistula and no urethral stricture. Results The patients' age was(25.7±11.6)years, and the diameter of fistula was(8.1±2.2)mm. UCF occurred in 24 cases after hypospadias repair, and in 12 cases after the repair of other urethral injuries, including 2 cases of urethral compression injury after improper indwelling catheterization, 2 cases of urethral stone removal, 2 cases of urethral diverticulum repair, 2 cases of circumcision repair, 1 case of congenital anal atresia repair, and 3 cases of other urethral repair. The primary repair success rate was 83.3%(30/36). Among the 6 patients with unsuccessful primary repair, 3 were cured with a secondary repair, 1 was cured after wound dressing, and 2 were lost to follow-up. The primary repair success rates of penile shape, penile scrotal junction, and perineal urethral skin fistulas were 82.1%(23/28), 83.3%(5/6), and 100%(2/2), respectively. The primary repair success rates for fistulas with diameter ≤1.0 cm and＞1.0 cm were 85.2%(23/27)and 77.8%(7/9), respectively; for single and two urethrocutaneous fistulas, the success rates were 84.8%(28/33)and 66.7%(2/3); for patients with 1 and ≥2 previous repair attempts, the success rates were 87.5%(14/16)and 80.0%(16/20). During the follow-up of(15.1±3.5)months, no recurrence of fistula occurred, and all patients experienced unobstructed urination with a maximum urinary flow rate of(19.5±4.2)mL/s. Conclusion The failure rate of UCF repair is still high. Based on the location of the fistulas and the condition of the surrounding tissue, the surgical success rate can be improved by utilizing subcutaneous flap and/or pedicled penile skin flap combined with advancement flap coverage technique. This approach allows for tension-free suturing and multi-layer closure of the fistula.

Objective To examine the impact of climate, land use and their interaction effect on the population density of Oncomelania hupensis. Methods O. hupensis snail surveillance data in Yunnan Province from 2013 to 2022 were obtained from the National Information System for Parasitic Diseases Prevention and Control of Chinese Information System for Disease Control and Prevention, and the density of living snails was calculated in each county-level administrative district. Climate data were obtained from the China Meteorological Forcing Dataset version 2.0, and land use data were captured from the China Land Cover Dataset. The raster climate data and land use data were clipped to the administrative border of Yunnan Province in the R package version 4.5, and the climate data were resampled to a spatial resolution of 30 m × 30 m consistent with the land use data using bilinear interpolation. Annual meteorological indicators were extracted from each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022, including average temperature, maximum temperature, minimum temperature, temperature difference, average precipitation rate, maximum precipitation rate, minimum precipitation rate, downward shortwave radiation flux, downward longwave radiation flux, air pressure, wind speed, specific humidity and relative humidity. Annual land use structure and landscape pattern index in each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022 were extracted and calculated, including the proportion of areas occupied by each type of land use, patch density, largest patch index, landscape separation index, landscape fragmentation index, landscape segmentation index, contagion index, patch cohesion index, edge density, and shape index. Land use entropy index was introduced to represent the degree of habitat fragmentation and ecological niche breadth. The density of living snails and environmental factors were subjected to rank correlation analysis, and variables with no statistically significant correlation (P>0.1) were excluded. Then, a correlation coefficient matrix was constructed, and |r_s| of 0.85 and greater was defined as the threshold of high collinearity. For highly correlated variables in each group, indicators with a more biological explanatory power or a better statistical efficiency were retained. A generalized additive model (GAM) was constructed with O. hupensis snail density as a response variable and screened environmental variables as independent variables, and the model performance was evaluated using the variance explained. Results The area occupied by O. hupensis snail habitats was 1 056 to 1 680 hm² in Yunnan Province from 2013 to 2022, appearing an overall tendency towards a decline; however, the density of living snails appeared a tendency towards a slight rise. Based on the correlation coefficient matrix, 14 core explanatory variables were retained, including farmland, water bodies, bare land, impervious surface, landscape separation index, landscape fragmentation index, edge density, shape index, land use entropy index, downward longwave radiation flux, downward shortwave radiation flux, maximum temperature, minimum precipitation rate and specific humidity. Two types of GAM were constructed, including the main-effects model without interaction terms and the interaction model with interaction terms. The corrected Akaike information criterion (AICc) of the optimal main-effects model was −285.223, and the core variables included bare land, impervious surface, landscape separation index, edge density, shape index, land use entropy index and downward shortwave radiation flux. Following introduction of second-order interaction terms, the AICc value of the optimal interaction model was −345.526, and the significant interaction combinations included: farmland × impervious surface, farmland × landscape separation index, farmland × shape index, farmland × land use entropy index, impervious surface × landscape separation index, impervious surface × edge density, and shape index × downward shortwave radiation flux. The proportion of the main-effects model explaining the variation of O. hupensis snail density was 39.8%, and the explanatory power of GAM increased to 79.0% following introduction of interaction terms. Conclusion Landscape separation index, edge density, shape index and other landscape pattern indicators pose significant impacts on the intensity and direction of changes in O. hupensis snail density in Yunnan Province.

Objective: To analyze the epidemiological characteristics, associated factors, and vaccine effectiveness of two pertussis cluster outbreaks in two primary schools in Yangzhong City in 2025, so as to provide evidence for school based epidemic prevention and control. Methods: From August 26 to 30, 2025, a pertussis questionnaire was administered to the epidemic affected classes of two primary schools (school A and school B) in Yangzhong City. A descriptive epidemiological retrospective analysis was used to characterize the pertussis cluster outbreaks in Yangzhong City from March to July 2025. A 1∶5 matched case control study (79 cases, 395 controls) was performed. Multivariate Logistic regression was used to identify associated factors, and the clinical symptom incidence rates, types of pertussis containing vaccines, and timeliness of vaccination were compared between groups using Fisher s exact test. Results: From March to July 2025, a total of 79 pertussis cases were reported in the two schools, with attack rates of 1.33% and 1.01%, respectively. Cases were predominantly aged 7-8 years (85.37% in school A, 73.68% in school B), and the main clinical manifestation was productive cough (63.29%). The pneumonia incidence rate among hospitalized cases ( 57.14 %) was higher than that among nonhospitalized cases(4.17%)(Fisher s exact test, P <0.01). The interval from the last dose to onset was concentrated at 6 to <7 years (44 cases). Logistic regression showed that children exposed to secondhand smoke in daily life ( OR = 3.86 ), those whose desk mates or front/back desk mates took leave due to cough ( OR =4.67), and those whose dining table mates or front/back table mates took leave due to cough ( OR =3.67) had significantly higher risks of pertussis (all P <0.05). A high proportion of both the case group and the control group received the acellular DTaP vaccine (97.47% and 96.96%, respectively),while a low proportion received the pentavalent vaccine (1.27% and 3.04%, respectively). Additionally, one case received only three doses of the acellular DTaP vaccine.The difference in vaccine type distribution between the two groups was not statistically significant (Fisher s exact test, P =0.31). Conclusions The outbreaks represent breakthrough infections under high vaccine coverage. Close contact and secondhand smoke exposure are the main risk factors. A booster immunization strategy with diphtheria-tetanus-pertussis vaccine should be implemented for school aged children.

Objective To investigate the factors affecting the distribution of Pomacea and project the trends in the spread of suitable distribution areas of Pomacea in 2050 and 2070 in Dali Bai Autonomous Prefecture, so as to provide insights into Pomacea control in the prefecture. Methods The longitudes and latitudes of Pomacea sampling sites were captured based on Pomacea field survey data in 12 cities (counties) of Dali Bai Autonomous Prefecture from 2023 to 2024. A total of 19 climatic factors (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest month, mean temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, mean temperature of the warmest quarter, and mean temperature of the coldest quarter) and representative concentration pathways (RCPs) were retrieved from the world climate database (www.worldclim.org). All climatic variables were employed to create a maximum entropy (MaxEnt) model. The predictive accuracy of the model was assessed with the area under the receiver operating characteristic (ROC) curve (AUC), and the contributions of these 19 climatic factors to the distribution of Pomacea were analyzed in Dali Bai Autonomous Prefecture using Jackknife test. In addition, the suitable distribution areas of Pomacea were predicted with the MaxEnt model in Dali Bai Autonomous Prefecture in 2024 and in 2050 and 2070 under RCP4.5. Results Data pertaining to 91 Pomacea sampling sites were captured. ROC analysis revealed the MaxEnt model had an AUC value of 0.885 ± 0.088 for predicting the suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture. Of the 19 climatic factors, the maximum temperature of the warmest month had the highest contribution to the distribution of Pomacea in Dali Bai Autonomous Prefecture, followed by mean temperature of the driest quarter, mean temperature of the wettest quarter and minimum temperature of the coldest month. The suitable distribution area of Pomacea was predicted to be 14 555.69 km² in Dali Bai Autonomous Prefecture in 2024, and would expand gradually to the southeastern part of the prefecture in the future due to climatic factors. The suitable distribution areas of Pomacea were projected to expand to 21 475.61 km² in 2050 and 25 782.52 km² in 2070 in Dali Bai Autonomous Prefecture, respectively. Conclusions Temperature is an important contributor to the distribution of Pomacea in Dali Bai Autonomous Prefecture, and the suitable distribution area of Pomacea will gradually expand to the southeastern part of the prefecture in 2050 and 2070.

Objective To analyze the virus subtypes, molecular evolutional and molecular transmission network features of the first confirmed mpox case in Huai’an City, Jiangsu Province, so as to provide insights into understanding of the transmission and evolution dynamics of mpox virus and formulation of the mpox control strategy in the city. Methods Genomic DNA was extracted from swabs of the first confirmed mpox case’s skin lesions in Huai’an City, and the amplicon sequencing library was constructed using the hypersensitive mpox virus whole-genome capture kit. High-throughput sequencing was performed using the GridION X5 nanopore sequencer on the Nanopore sequencing platform, and single nucleotide polymorphism (SNP) analysis of mpox virus genome sequences was performed following sequence assembly. In addition, phylogenetic analysis, genetic genealogy and molecular traceability analysis were performed. Results The virus whole genome sequence of the first confirmed mpox case was successfully obtained by high-throughput sequencing, with a full length of 197 182 bp, and was named hMpxV/China/JS-HA01/2023, which belonged to the clade IIb (West African clade) lineage B.1.3. Compared with the mpox virus reference sequence MPXV-M5312_HM12_Rivers-001 (GenBank accession number: NC_063383), the genome sequence of the Huai’an virus isolate carried 86 SNPs, including 40 SNPs in the coding region as non-synonymous mutations and 73 SNPs as nucleotide mutations caused by APOBEC3 (APOBEC3). Of the 97 mpox virus gene sequences, 79 sequences were included in the molecular network (81.44%), and the threshold of the genetic distance accessed to the network was 0.35/10⁵. There were two large molecular transmission clusters and one scattered cluster in the molecular transmission network of the mpox virus, andthehMpxV/China/JS-HA01/2023 sequence was located in the large cluster. The 97 gene sequences formed 92 haplotypes, including three shared haplotypes Hap_4, Hap_6 and Hap_38, and an exclusive haplotype Hap_1 of hMpxV/China/JS-HA01/2023 generated from mutation of the exclusive haplotype Hap_43, while the exclusive haplotype Hap_43 was generated from mutation of the shared haplotype Hap_38. Conclusions The whole genome sequence of the mpox virus isolated from the first confirmed mpox case in Huai’an City has been successfully obtained, and the molecular evolutionary and molecular transmission network characteristics of the virus have been preliminarily understood.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.