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.

Objective To evaluate the associations between carbapenem-resistant Acinetobacter baumannii (CRAb) detected from any respiratory specimens within 0-7 days after lung transplantation and all-cause mortality at 30-day, 90-day and 1-year post-transplantation. Methods Recipients undergoing lung transplantation at Lung Transplant Center of Wuxi People’s Hospital Affiliated to Nanjing Medical University from January 1, 2020 to December 31, 2022 were retrospectively enrolled. Patients were divided into the CRAb-positive group (n=126) and CRAb-negative group (n=299) according to culture results of respiratory samples collected within postoperative days 0-7. Baseline characteristics were compared between the two groups. Univariate and multivariate Cox regression models were performed to identify risk factors for 30-day mortality and analyse the correlation of CRAb detection with 30-day, 90-day and 1-year all-cause mortality. Sensitivity analyses and subgroup analyses were subsequently conducted. Results Compared with the CRAb-negative group, recipients in the CRAb-positive group presented higher ratios of preoperative invasive mechanical ventilation and extracorporeal membrane oxygenation (ECMO), a higher CRAb-positive rate in donor pharyngeal swabs, and elevated proportions of bilateral lung transplantation, Shell-shaped incision, peri-operative ECMO application. Moreover, the CRAb-positive group had longer pulmonary cold-ischemia time, intensive care unit stay duration and operation time (all P<0.05). Multivariate Cox regression demonstrated that positive CRAb isolation from respiratory samples within postoperative days 0-7 and preoperative coronary stent implantation were independently associated with 30-day mortality (all P<0.001). The CRAb-positive group exhibited significantly higher mortality risks at 30 days, 90 days and 1 year after surgery (all P<0.001). After adjusting for confounders, early CRAb detection remained an independent predictor of elevated mortality (all P<0.05). Consistent results were obtained when stratifying cases by detection timing (0-3 days vs. 4-7 days), excluding patients with co-detection of other multidrug-resistant bacteria, and applying inverse probability of treatment weighting, and the direction of association remained consistent. Conclusions CRAb detected from respiratory specimens within postoperative days 0-7 is independently correlated with increased 30-day, 90-day and 1-year all-cause mortality among lung-transplant recipients. Early CRAb detection may serve for risk stratification. Nevertheless, such finding does not confirm that CRAb infection directly causes death, and the conclusion cannot be generalized to deaths occurring within the initial postoperative 7-day period.

Objective To analyze the characteristics of postoperative hospital-acquired infections and drug sensitivity in lung transplant recipients over the past 5 years in a single center. Methods A total of 724 lung transplant recipients at Wuxi People's Hospital from January 2019 to December 2023 were selected. Based on the principles of hospital-acquired infection diagnosis, a retrospective analysis was conducted on the hospital infection situation and infection sites of lung transplant recipients, and an analysis of the distribution of hospital-acquired infection pathogens and their antimicrobial susceptibility test status was performed. Results Among the 724 lung transplant recipients, 275 cases of hospital-acquired infection occurred, with an infection rate of 38.0%. The case-time infection rate decreased from 54.2% in 2019 to 22.8% in 2023, showing a downward trend year by year (Z=30.98, P<0.001). The main infection site was the lower respiratory tract, accounting for 73.6%. The pathogens were mainly Gram-negative bacteria, with the top four being Acinetobacter baumannii (37.1%), Pseudomonas aeruginosa (17.3%), Klebsiella pneumoniae (13.7%), and Stenotrophomonas maltophilia (13.4%), with imipenem resistance rates of 89%, 53%, 58% and 100%, respectively. Gram-positive bacteria were mainly Staphylococcus aureus (3.6%), with a methicillin resistance rate of 67%. Conclusions Over the past 5 years, the hospital-acquired infections in lung transplant recipients have shown a downward trend, mainly involving lower respiratory tract infections, with the main pathogens being Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae, all of which have high resistance rates to imipenem.

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.

Objective:Utilizing the principles of mechanical vibrations dissections and low-temperature coagulation of harmonic scalpel, and combining the magnifying effect of 3D thoracoscopy and the advantage of low trauma, we used harmonic scalpel to harvest the left internal mammary artery (LIMA) under thoracoscopy, and explored the feasibility and early effect of harmonic scalpel in minimally invasive coronary artery bypass grafting (MICABG).Methods:A total of 488 patients who underwent MICABG from July 2021 to December 2023 in Dong E Hospital were collected. Among them, 347 patients was harvested using harmonic scalpel under thoracoscopy. Following anastomosis, the blood flow and pulsatility index (PI) from the graft to the target vessel were determined using a transit time flow meter (MiraQ, Medistim, Norway), and patency was checked. Data from 347 patients were analyzed.Results:All 347 patients were performed under non-extracorporeal circulation and successful graft patency was achieved in all patients. Analysis of 79 patients revealed a median time to LIMA acquisition of 32 min and a median length of acquisition of 15 cm. No graft-related events or complications occurred in any of the patients, and 2 patients died postoperatively. During a median follow-up of 12.1 months, only one patient experienced graft occlusion necessitating intervention.Conclusion:The utilization of harmonic scalpel for LIMA harvesting in MICABG is feasible and yields stable early results.

Objective:To investigate the optimization of inferior vena cava imaging using dual-layer spectral detector CT (DLCT) virtual monoenergetic images (VMI) combined with multiphase scanning.Methods:A retrospective analysis was conducted on the imaging data of 184 patients who underwent inferior vena cava imaging using dual-layer detector spectral CT at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2021 to October 2024. Each patient underwent multiphase scanning (60, 80, and 120 s after contrast injection were referred to as the first, second, and third phases, respectively). The images were reconstructed into conventional 120 kVp polyenergetic image (PI) and VMIs at 40, 50, 60, 70, and 80 keV. Image quality of 120 kVp PI and VMI for each phase was evaluated. The objective image quality indicators included CT value, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and noise. Comparisons of the above indictors within the same phase were performed using repeated measures ANOVA or the Friedman test, while comparisons between different phases were conducted using one-way ANOVA or the Kruskal-Wallis test.Results:At the same phase, the CT value, SNR, and CNR of the 40 keV VMI were higher than those of other energy level VMIs and PI (all P<0.001). The SNR of the 40 keV VMI in the third phase was significantly higher than in the first phase ( P<0.05), while there was no significant difference between the first and second phases ( P>0.05). The standard deviation (SD) of the 40 keV VMI in the third phase was significantly lower than that in the first and second phases (all P<0.05). The subjective scores for the 40 keV VMI were higher than those for other energy level VMIs and PI at the same phase ( P<0.001). The subjective scores for the 40 keV VMI in the third phase were higher than those in the second and first phases ( P<0.001). The percentage of scores≥4 in the third phase (77.17%,142/184) was significantly higher than those in the first phase (28.26%,52/184) and second phase (61.96%,114/184) ( P<0.001). Conclusion:In inferior vena cava imaging, the 40 keV VMI, combined with the optimal phase (120 s delay), effectively optimizes image quality.

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.

Objective To analyze the acupoint selection law of acupuncture and moxibustion for postherpetic neuralgia(PHN)with R language data mining technology.Methods The clinical research literature on acupuncture and moxibustion treatment of PHN included in CNKI,Wanfang Data,VIP and CBM from January 1,2010 to July 1,2023 was retrieved,and the database was established by Excel 2016.R language was used to statistically analyze the frequency of acupoint usage,meridians,locations,specific acupoints,etc.Through association rule analysis and clustering analysis,the characteristics and law of acupoint selection for acupuncture and moxibustion treatment of PHN were obtained.Results A total of 198 articles were included,including 83 acupoints,with a total frequency of 714 times.The high-frequency acupoints include Ashi acupoint,Jiaji acupoint and Yanglingquan.The commonly used meridians were gallbladder meridian,spleen meridian and large intestine meridiam.The acupoints were mostly in the upper and lower limbs,with the Wushu acupoints,Yuan acupoints and Xiahe acupoints being the most common.The core acupoint was Ashi acupoint,Jiaji acupoint,Hegu,Quchi,and 9 sets of association rules and 5 effective clusters were obtained.Conclusion The most commonly used acupoints for acupuncture and moxibustion treatment of PHN are Ashi acupoint,Jiaji acupoint,Hegu and Quchi,which mainly follow the principle of combining local acupoint selection with distal acupoint selection.

Objective To observe the efficacy of nomogram model based on enhanced MRI radiomics,deep learning(DL)and clinical features for differentiating spinal tuberculosis and pyogenic spondylitis.Methods Totally 59 cases of spinal tuberculosis and 66 of pyogenic spondylitis were retrospectively enrolled.Radiomics,DL and clinical features relevant to differentiating spinal tuberculosis and pyogenic spondylitis were selected.Then a predictive model was constructed using logistic regression based on the selected optimal features,and a comprehensive nomogram model was developed through combination of the above features.The effectiveness of these models for distinguishing spinal tuberculosis from pyogenic spondylitis were visualized based on receiver operating characteristic curves,calidration curves and decision curves.Results The nomogram model demonstrated the highest area under the curve(AUC)in both training set and test set,with AUC of 0.997 and 0.920,respectively.In test set,DeLong test indicated that the difference of AUC between the nomogram model and clinical model was significant(P=0.002),while no significant difference was observed between the nomogram model and the other models(all P＞0.05).The nomogram model provided the highest overall net benefit and exhibited good calibration for distinguishing spinal tuberculosis from pyogenic spondylitis.Conclusion Nomogram model based on enhanced MRI radiomics,DL and clinical features demonstrated high efficacy for differentiating spinal tuberculosis from pyogenic spondylitis.