Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

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 This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.

Since the birth of the first "test-tube baby" in Chinese mainland in 1988, assisted reproductive technology (ART) in China has matured significantly. The number of ART cycles has surpassed one million, and the number of assisted reproductive institutions and practitioners has attained a significant scale, contributing to the establishment of a fertility-friendly society. However, due to the complexity of the ART process, the diversity of personnel backgrounds, and the profound impact of any error that may occur, there is an urgent need to establish an efficient and effective safety management model for error prevention. This paper aims to outline the key processes and steps involved in the implementation of ART, explore control measures for these critical processes, and delve into error prevention strategies for gamete and embryo laboratories through the creation and utilization of a "gamete safety checklist".

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Background and purpose:Accurate preoperative differentiation between vagal nerve cervical schwannomas(SCCS)and sympathetic chain cervical schwannomas(SCCS)in the neck is crucial because of their different postoperative complication.This study aimed to construct and validate a Diagnosis Score and vascular displacement nomogram for the preoperative differentiation of VNCS from SCCS in the neck.Methods:This cross-sectional study retrospectively analyzed patients with pathologically confirmed VNCS and SCCS at Fudan University Shanghai Cancer Center from January 2017 to April 2022.This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center(approval number:1612167-18).Inclusion criteria:① histopathological diagnosis of VNCS or SCCS through biopsy or surgical resection;② patients with complete clinic data;③availability of preoperative contrast-enhanced computed tomography(CT)or magnetic resonance imaging(MRI)examinations.Patients were excluded for:① contrast agent contraindications;② poor image quality;③ severe artifacts;④ non-standard scanning protocols.The cohort was randomly divided into training and validation sets in a 7∶3 ratio.Two radiologists(one resident and one attending physician)independently evaluated tumor characteristics(location,size and vascular displacement patterns)on preoperative imaging.Independent predictors were selected using LASSO regression analysis to construct a diagnostic scoring system and nomogram,with model performance evaluated by the receiver operating characteristic(ROC)curve.Results:A total of 110 patients were enrolled,with 77 cases allocated to the training set and 33 cases to the validation set.The age range was 24-78 years,and the mean age was(51.22±12.36)years.There were no statistically significant differences in baseline characteristics including age,gender,tumor location and size between the two patient groups(P＞0.05).ICA/ECA splaying was significantly associated with SCCS(P＜0.001),while the ICA/IJV splaying was significantly associated with VNCS(P＜0.001).Lateral and posterior ICA displacement were significantly associated with SCCS(P＜0.001),and medial and anterior ICA displacement were significantly associated with VNCS(P＜0.001).Five features including tumor size,ICA displacement direction,IJV displacement direction,ICA/ECA splaying and ICA/IJV splaying were used to establish the Diagnosis Score and nomogram.The nomogram combined imaging features showed favorable preference value for differentiating VNCS from SCCS,with area under curve(AUC)values of 0.953(95%CI:0.912-0.994)and 0.939(95%CI:0.885-0.993)for the training and validation cohorts,respectively.Conclusion:The Diagnosis Score and vascular displacement nomogram showed favorable predictive efficacy for differentiating VNCS from SCCS in the neck,and might be useful for clinical decision-making.

Objective:To develop a risk prediction model for moderate to severe orthodontic-induced inflammatory root resorption (OIIRR) of maxillary incisors based on cone beam CT (CBCT) radiomics features and clinical characteristics of the orthodontic patients.Methods:Clinical and CBCT data from 101 orthodontic patients treated by the same attending orthodontist in the Department of Orthodontics, Stomatology Hospital of Tianjin Medical University from January 2019 to January 2024 were retrospectively collected. The sample included 42 class Ⅰ patients, 52 class Ⅱ patients and 7 class Ⅲ patients [age: (19.7±6.3) years], and a total of 394 maxillary incisors were analyzed. Potential influencing factors for moderate to severe OIIRR (root volume resorption rate≥10%) were collected from the patients′ CBCT and medical records, including initial age, gender, treatment duration, Angle′s classification, extraction or not, type of orthodontic appliance (fixed or clear aligner), changes in root inclination, root movement distance and direction, pre-treatment cephalometric measurements, pre-treatment root-bone relationship, pre-treatment root length, and pre-treatment radiomics features of the teeth. Univariate analysis was initially performed to screen for factors influencing moderate to severe OIIRR. Subsequently, least absolute shrinkage and selection operator (LASSO) regression, best subset regression, and random forest were used for feature selection to construct the OIIRR risk prediction model. The discrimination, calibration, and net benefit of the three risk prediction models were evaluated, and the optimal model was displayed using a nomogram.Results:LASSO regression identified clinical features including initial age (LASSO coefficient 0.052), treatment duration (LASSO coefficient 0.024), pre-treatment root length (LASSO coefficient -0.023), and vertical root movement distance (LASSO coefficient -0.029). Initial age and treatment duration were positively correlated with the severity of OIIRR, while root length and vertical root movement distance were negatively correlated. A total of 14 radiomics features were identified, including 2 original image features and 12 wavelet features. Best subset regression identified vertical root movement distance as the clinical feature and 7 radiomics features, including 1 original image feature and 6 wavelet features. The random forest model identified 8 wavelet features as important predictors, and all of which were radiomics features. Model performance evaluation showed that the random forest model had the highest discrimination, calibration, and net benefit, making it the optimal model, with radiomics features being the most important predictors.Conclusions:Based on the data from this study, radiomics features were identified as the most important predictors by the optimal model for OIIRR risk prediction. Predicting the occurrence of moderate to severe OIIRR before orthodontic treatment held potential clinical application value.

Objective:To investigate the association between different types of lung nodules and the risk of lung cancer in a population at high risk of lung cancer and to provide an epidemiologic basis for the comprehensive management of lung nodules.Methods:Using the free lung cancer screening program of low-dose CT (LDCT) in Wenling, Zhejiang Province, we collected baseline and imaging information of high-risk groups for lung cancer who underwent LDCT screening from April 2019 to October 2021 and patients with previous history of lung cancer, tuberculosis, pneumoconiosis, and silicosis were excluded. A total of 28 539 study subjects were included in the analysis, and the follow-up ended on 31 December 2023. Based on the characteristics of the detected pulmonary nodules, the study subjects were classified with no nodules, with solid nodules, with pure ground glass nodules, and with part solid nodules groups. The association between different characteristics of lung nodules and the risk of lung cancer development was analyzed using the Cox proportional hazard regression model with a new diagnosis of lung cancer during the follow-up period as the outcome.Results:The overall detection rate of lung nodules with a mean diameter of ≥3 mm was 76.5%, of which 53.7%, 18.2%, and 4.6% were detected in the solid nodule, pure ground glass nodule, and partially solid nodule groups, respectively. There were statistically significant differences between the different nodule groups in terms of age, gender, BMI, history of toxic exposure education level, smoking status, history of lung disease, and family history of lung cancer (all P<0.05). The median follow-up time of the study population was 3.4 years, and 485 new lung cancer cases were diagnosed during the follow-up period. After adjusting for covariates, the results of multifactorial Cox proportional hazard regression model analysis showed that the risk of lung cancer was higher in pure ground glass nodules and part solid nodules compared with solid nodules, with HR values (95% CI) of 1.89 (1.52-2.35) and 6.49 (5.18-8.14), respectively. The results of subgroup analysis showed that patients in the group of part solid nodules had the highest risk of lung cancer in all strata of the population, followed by patients with pure ground glass nodules. Patients in the solid nodule group who were older or had previous lung disease had a higher risk of lung cancer, and the risk of lung cancer in the part solid nodule group differed between genders. Conclusions:The proportion of lung nodules detected is high in the high-risk group of lung cancer, and among them, patients with pure ground glass and part solid nodules have a higher risk of developing lung cancer. Attention should be paid to the annual follow-up management for patients with solid nodules who are older or who have had lung diseases, as well as for female patients with part solid nodules.