Objective To investigate the impact of intraoperative red blood cell (RBC) transfusion volume on the postoperative oxygenation index in lung transplant recipients. Methods This retrospective study analyzed the clinical data of patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from 2021 to 2023. Patients were divided into a non-severe primary graft dysfunction (PGD) group and a severe PGD group based on whether their postoperative oxygenation index was>200 mm Hg at 0, 24, and 48 h. General patient data and intraoperative RBC transfusion volumes were compared between the two groups. A binary logistic regression model was constructed to explore the effect size (OR and its 95%CI) of RBC transfusion volume on postoperative oxygenation status at different time points (0, 24, and 48 h). The area under the receiver operating characteristic curve was calculated to evaluate the model's diagnostic performance. Results A total of 351 patients were included (260 males, 91 females), with ages ranging from 20 to 77 years. The OR for the effect of intraoperative RBC transfusion on poor oxygenation was 1.486 (95%CI 0.982 to 2.248, P=0.061) at 0 h postoperatively, 3.111 (95%CI 1.793 to 5.399, P<0.001) at 24 h, and 1.583 (95%CI 1.026 to 2.442, P=0.038) at 48 h. This indicated that as time progressed, the postoperative oxygenation status of lung transplant recipients was affected by the intraoperative transfusion volume. Furthermore, an RBC transfusion volume>975 mLhad a significant impact on patient oxygenation at 24 and 48 h postoperatively. Conclusion The volume of intraoperative RBC transfusion has a significant impact on the oxygenation status at 24 and 48 h postoperatively. Intraoperative RBC transfusion volume is associated with the occurrence of severe PGD after lung transplantation. Controlling the volume of RBC transfusion during lung transplantation may help reduce the incidence of severe PGD.

In 2022， Hainan provincial government launched the project for the prevention and control of viral hepatitis with the goals of a hepatitis B screening rate of 90%， a diagnostic rate of 90%， and a treatment rate of 80% among people aged 18 years and above by the year 2025， and the main intervention measures include population-based prevention， case screening， antiviral therapy， and health management. As of December 31， 2024， a total of 6.875 million individuals in the general population had been screened for hepatitis B， with a screening rate of 95.6%. A total of 184 710 individuals with positive HBsAg were identified， among whom 156 772 were diagnosed through serological reexamination， resulting in a diagnostic rate of 84.9%. A total of 50 742 patients with chronic hepatitis B were identified， among whom 42 921 had hepatitis B-specific health records established for health management， with a file establishment rate of 84.6%. A total of 31 553 individuals received antiviral therapy， with a treatment rate of 62.2%. A total of 2.503 million individuals at a high risk of hepatitis C were screened， among whom 4 870 tested positive for HCV antibody and 3 858 underwent HCV RNA testing， resulting in a diagnostic rate of 79.2%， and 1 824 individuals with positive HCV RNA were identified， among whom 1 194 received antiviral therapy， with a treatment rate of 65.5%. In addition， 159 301 individuals with negative HBsAg and anti-HBs and an age of 20 — 40 years were inoculated with hepatitis B vaccine free of charge. Through the implementation of the project for the prevention and control of viral hepatitis， a large number of hepatitis patients have been identified， treated， and managed in the province within a short period of time， which significantly accelerates the efforts to eliminate the crisis of viral hepatitis.

Human carboxylesterase 2A (hCES2A) plays pivotal roles in prodrug activation and hydrolytic metabolism of ester-bearing chemicals. Targeted inhibition of intestinal hCES2A represents a feasible strategy to mitigate irinotecan-triggered gut toxicity (ITGT), but the orally active, selective, and efficacious hCES2A inhibitors are rarely reported. Here, a novel drug-like hCES2A inhibitor was developed via three rounds of structure-based drug design (SBDD) and structural optimization. Initially, donepezil was identified as a moderate hCES2A inhibitor from 2000 US Food and Drug Administration (FDA)-approved drugs. Following two rounds of SBDD and structural optimization, a donepezil derivative (B7) was identified as a strong reversible hCES2A inhibitor. Subsequently, nine B7 carbamates were rationally designed, synthesized and biologically assayed. Among all synthesized carbamates, C3 showed the most potent time-dependent inhibition on hCES2A (IC₅₀ = 0.56 nmol/L), excellent specificity and favorable drug-like properties. C3 could covalently modify the catalytic serine of hCES2A with high selectivity, while this agent also showed favorable safety profiles, high intestinal exposure, and impressive effects for ameliorating ITGT in both human intestinal organoids and tumor-bearing mice. Collectively, this study showcases a rational strategy for developing drug-like and serine-targeting covalent inhibitors against target serine hydrolase(s), while C3 emerges as a promising orally active drug candidate for ameliorating ITGT.

Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal disease, and has become a major global health issue. Individuals with IBD face an elevated risk of developing colorectal cancer (CRC), and recent studies have indicated that mitochondrial dysfunction plays a pivotal role in the pathogenesis of both IBD and CRC. This review covers the pathogenesis of IBD and CRC, focusing on mitochondrial dysfunction, and explores pharmacological targets and strategies for addressing both conditions by modulating mitochondrial function. Additionally, recent advancements in the pharmacological modulation of mitochondrial dysfunction for treating IBD and CRC, encompassing mitochondrial damage, release of mitochondrial DNA (mtDNA), and impairment of mitophagy, are thoroughly summarized. The review also provides a systematic overview of natural compounds (such as flavonoids, alkaloids, and diterpenoids), Chinese medicines, and intestinal microbiota, which can alleviate IBD and attenuate the progression of CRC by modulating mitochondrial function. In the future, it will be imperative to develop more practical methodologies for real-time monitoring and accurate detection of mitochondrial function, which will greatly aid scientists in identifying more effective agents for treating IBD and CRC through modulation of mitochondrial function.

Liraglutide (Lira), a glucagon-like peptide-1 (GLP-1) receptor agonist approved for diabetes and obesity, has shown significant potential in treating metabolic dysfunction-associated steatotic liver disease (MASLD). However, its systematic molecular regulation and mechanisms remain underexplored. In this study, a mouse model of MASLD was developed using a high-fat diet (HFD), followed by Lira administration. Proteomics and glycoproteomics were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS), while potential molecular target analysis was conducted via quantitative real-time polymerase chain reaction (qPCR) and Western blotting. Our results revealed that Lira treatment significantly reduced liver weight and serum markers, including alanine aminotransferase (ALT) and others, with glycosylation changes playing a more significant role than overall protein expression. The glycoproteome identified 255 independent glycosylation sites, emphasizing the impact of Lira on amino acid, carbohydrate metabolism, and ferroptosis. Simultaneously, proteomic analysis highlighted its effects on lipid metabolism and fibrosis pathways. 21 signature molecules, including 7 proteins and 14 N-glycosylation sites (N-glycosites), were identified as potential targets. A Lira hydrogel formulation (Lira@fibrin (Fib) Gel) was developed to extend drug dosing intervals, offering enhanced therapeutic efficacy in managing chronic metabolic diseases. Our study demonstrated the importance of glycosylation regulation in the therapeutic effects of Lira on MASLD, identifying potential molecular targets and advancing its clinical application for MASLD treatment.

Background and Aims:Medullary thyroid carcinoma(MTC)is an aggressive malignancy that is frequently associated with cervical lymph node metastasis,significantly affecting patient prognosis.However,the risk factors for lateral cervical lymph node metastasis(LLNM)in MTC remain inconclusive.This study aims to identify the risk factors associated with LLNM in MTC patients,in order to inform individualized surgical decision-making.Methods:The clinicopathologic data of 242 patients with MTC who underwent surgical treatment at Tianjin Medical University Cancer Institute and Hospital from 2011 to 2019 were retrospectively collected.The relationships between preoperative tumor markers,including calcitonin and carcinoembryonic antigen(CEA),and LLNM were evaluated.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for LLNM.Results:Preoperative calcitonin level was significantly associated with tumor diameter,the number of lymph node metastases,and the extent of lymph node involvement,while preoperative CEA level was significantly associated with tumor diameter(all P<0.05).The area under the ROC curve for preoperative calcitonin in diagnosing LLNM was 0.750(P=0.000),with an optimal cutoff value of 266.00 ng/L(sensitivity 0.854,specificity 0.577).The diagnostic value of preoperative CEA for LLNM was limited.Univariate analysis showed that sex,extracapsular extension,T stage,central lymph node metastasis(CLNM),bilateral lesions,preoperative calcitonin,tumor diameter,and multifocality were significantly associated with LLNM in MTC patients(all P<0.05).Multivariate analysis revealed that CLNM(OR=17.645,95%CI=7.728-40.290)and preoperative calcitonin≥266.00 ng/L(OR=7.832,95%CI=3.132-19.582)were independent risk factors for LLNM.Conclusion:CLNM and elevated preoperative calcitonin level are closely associated with LLNM in patients with MTC.The combination of these two indicators may help identify high-risk patients for LLNM,thereby and promoting individualized and precise treatment strategies for MTC.

Over the past two decades,the field of thyroid oncology in China has undergone rapid development.Through improvements in standardization processes,continuous innovations in treatment methods,and in-depth basic research,the 5-year survival rate of thyroid cancer has significantly increased from 67.5%to 92.9%.In diagnostics,advancements in color Doppler ultrasound technology,the establishment of the TI-RADS classification system,and innovations in fine-needle aspiration biopsy methods,particularly the integration of molecular diagnostics,have greatly improved the accuracy of preoperative diagnosis.In terms of treatment,there has been a gradual shift from traditional surgery to individualized precision therapy.Combined with radioactive iodine therapy,endocrine regulation,targeted therapy,and immunotherapy,a multidisciplinary comprehensive diagnosis and treatment system has been formed,providing patients with more precise and effective treatment options.Significant progress has also been made in the treatment of advanced thyroid cancer,with the application of targeted drugs bringing new hope to patients.In research,Chinese scholars have greatly increased their publications in the field of thyroid cancer,with high-quality studies emerging continuously,reflecting China's rapid rise in this area.Meanwhile,the establishment of academic organizations and the promotion of professional guidelines have substantially enhanced the diagnostic and treatment capabilities of primary care physicians.Looking ahead,efforts will continue to focus on the development of next-generation targeted drugs,the application of artificial intelligence and intelligent decision-making systems in diagnosis and treatment,the construction of prognosis prediction models based on big data,and the popularization of 5G-enabled remote medical care.These advances will drive the development of thyroid oncology toward more precise,minimally invasive,and personalized directions,creating new brilliance once again.

Inflammatory bowel disease(IBD)is a chronic and recurrent intestinal disease,and has become a major global health issue.Individuals with IBD face an elevated risk of developing colorectal cancer(CRC),and recent studies have indicated that mitochondrial dysfunction plays a pivotal role in the pathogenesis of both IBD and CRC.This review covers the pathogenesis of IBD and CRC,focusing on mitochondrial dysfunction,and explores pharmacological targets and strategies for addressing both conditions by modulating mitochondrial function.Additionally,recent advancements in the phar-macological modulation of mitochondrial dysfunction for treating IBD and CRC,encompassing mitochondrial damage,release of mitochondrial DNA(mtDNA),and impairment of mitophagy,are thoroughly summarized.The review also provides a systematic overview of natural compounds(such as flavonoids,alkaloids,and diterpenoids),Chinese medicines,and intestinal microbiota,which can alleviate IBD and attenuate the progression of CRC by modulating mitochondrial function.In the future,it will be imperative to develop more practical methodologies for real-time monitoring and accurate detection of mitochondrial function,which will greatly aid scientists in identifying more effective agents for treating IBD and CRC through modulation of mitochondrial function.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.