Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

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 construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

With the rapid advancement of medical technology and the increasing complexity of clinical environments, competence in clinical ethical decision-making has become an indispensable core competency for exemplary physicians. However, traditional medical ethics education has long been confronted with the persistent challenges of theory-practice dissociation and the disconnect between pedagogical settings and clinical realities. Thus, how to construct a "Clinical Ethics" curriculum that aligns with the objectives of training high-caliber medical professionals has emerged as a critical and challenging issue in current medical education reform. To effectively address this challenge, the Office of Education at Peking University Third Hospital, since 2021, has assembled a multidisciplinary "Clinical Ethics" teaching and management team comprising faculty from Peking University School of Humanities and key clinical specialists from the hospital. In 2022, the "Clinical Ethics" elective course was formally launched for fourth-year students in the eight-year MD program who had completed coursework in "Medical Ethics" and organ-system-based curricula, with the aim of exploring and operationalizing a pre-clinical ethics education model tailored for senior medical students. The course employs a modular instructional design encompassing "theoretical review-case-based deliberation-clinical workshop", which effectively facilitates the deep integration of medical humanities with clinical practice.Following four years of iterative refinement through the "plan-act-observe-reflect" cycle, the course has demonstrated positive outcomes in enhancing students' ethical awareness and decision-making capabilities, and has preliminarily established a sustainable collaborative mechanism among the multidisciplinary faculty team. This article systematically delineates the course development background, pedagogical model and methodological innovations, and the multidisciplinary collaborative framework, alongside reflections and summaries based on implementation outcomes, with the intent of providing references for the future development of "Clinical Ethics" curricula.

ObjectiveTo observe the clinical effect of modified Huanglian Wendantang on cardiovascular risk factors in patients with metabolic syndrome under the guidance of treating disease before its onset. MethodsA total of 82 patients with metabolic syndrome treated in the First Affiliated Hospital of Heilongjiang University of Chinese Medicine from July 2023 to July 2024 were selected and allocated into an observation group （41 cases） and a control group （41 cases） by the random number table method. The control group received routine treatment， and the observation group was treated with modified Huanglian Wendantang on the basis of routine treatment. Both groups were treated for 8 weeks. The therapeutic effects on TCM symptoms after treatment in the two groups were evaluated. The levels of obesity degree indicators， blood pressure indicators， glucose and lipid metabolism indicators， inflammatory factors， and vascular endothelial function indicators before and after treatment in the two groups were measured， and the treatment safety was evaluated. ResultsAfter treatment， the total response rate of TCM symptoms in the observation group was 97.56% （40/41）， which was higher than that （87.80%， 36/41） in the control group （χ²=5.205， P<0.05）. After treatment， both groups showed declines （P<0.05） in systolic blood pressure （SBD）， diastolic blood pressure （DBP）， triglyceride （TG）， total cholesterol （TC）， low density lipoprotein cholesterol （LDL-C）， fasting blood glucose， 2-hour postprandial blood glucose （2 h PG）， glycosylated hemoglobin （HbA1c）， fasting insulin （FINS）， Homeostatic Model Assessment for Insulin Resistance （HOMA-IR）， body mass index （BMI）， waist circumference （WC）， waist-to-hip ratio （WHR）， leptin （LEP）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， endothelin-1 （ET-1）， and inducible nitric oxide synthase （iNOS）. Moreover， the declines in the observation group were more obvious than those in the control group （P<0.05， P<0.01）. After treatment， both groups showed elevated levels of high density lipoprotein cholesterol （HDL-C）， adiponectin （ADP）， nitric oxide （NO）， and endothelial nitric oxide synthase （eNOS） （P<0.05）， and the above indexes in the observation group were higher than those in the control group （P<0.01）. ConclusionUnder the guidance of the thought of treating disease before its onset， modified Huanglian Wendantang was used to treat patients with metabolic syndrome. The decoction improved the clinical efficacy by ameliorating IR to improve insulin sensitivity， reducing inflammation， and protecting the vascular endothelial function. It inhibits cardiovascular risk factors without inducing adverse reactions， being worthy of clinical application and promotion.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

BACKGROUND: Arsenic trioxide (ATO) is indicated as a broad-spectrum medicine for a variety of diseases, including cancer and cardiac disease. While the role of ATO in hepatic ischemia/reperfusion injury (HIRI) has not been reported. Thus, the purpose of this study was to identify the effects of ATO on HIRI. METHODS: In the present study, we established a 70% hepatic warm I/R injury and partial hepatectomy (30% resection) animal models in vivo and hepatocytes anoxia/reoxygenation (A/R) models in vitro with ATO pretreatment and further assessed liver function by histopathologic changes, enzyme-linked immunosorbent assay, cell counting kit-8, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay. Small interfering RNA (siRNA) for extracellular signal-regulated kinase (ERK) 1/2 was transfected to evaluate the role of ERK1/2 pathway during HIRI, followed by ATO pretreatment. The dynamic process of autophagic flux and numbers of autophagosomes were detected by green fluorescent protein-monomeric red fluorescent protein-LC3 (GFP-mRFP-LC3) staining and transmission electron microscopy. RESULTS: A low dose of ATO (0.75 μmol/L in vitro and 1 mg/kg in vivo ) significantly reduced tissue necrosis, inflammatory infiltration, and hepatocyte apoptosis during the process of hepatic I/R. Meanwhile, ATO obviously promoted the ability of cell proliferation and liver regeneration. Mechanistically, in vitro  studies have shown that nontoxic concentrations of ATO can activate both ERK and phosphoinositide 3-kinase-serine/threonine kinase (PI3K-AKT) pathways and further induce autophagy. The hepatoprotective mechanism of ATO, at least in part, relies on the effects of ATO on the activation of autophagy, which is ERK-dependent. CONCLUSION Low, non-toxic doses of ATO can activate ERK/PI3K-AKT pathways and induce ERK-dependent autophagy in hepatocytes, protecting liver against I/R injury and accelerating hepatocyte regeneration after partial hepatectomy.
Animals ; Arsenic Trioxide ; Autophagy/physiology* ; Reperfusion Injury/prevention & control* ; Mice ; Male ; Proto-Oncogene Proteins c-akt/physiology* ; Arsenicals/therapeutic use* ; Oxides/therapeutic use* ; Liver/metabolism* ; Extracellular Signal-Regulated MAP Kinases/metabolism* ; Mice, Inbred C57BL

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*