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 explore the application effect of prone position ventilation combined with veno-venous extracorporeal membrane oxygenation (VV-ECMO) in the treatment of severe primary graft dysfunction (PGD) after lung transplantation. Methods The clinical data of 75 lung transplant recipients who developed severe PGD after lung transplantation and were treated with VV-ECMO from January 2021 to June 2024 at Wuxi People's Hospital Affiliated to Nanjing Medical University were collected. The patients with severe graft dysfunction after lung transplantation were divided into VV-ECMO group (control group, 45 cases) and prone position ventilation combined with VV-ECMO group (treatment group, 30 cases). The general data of the two groups of patients were compared, including the donors' clinical data (age, gender and oxygenation index, etc) and the recipients' clinical data [gender, age and body mass index (BMI), etc]. Cox regression analysis was used to analyze the influencing factors of the recipients' 30-day, 90-day and 180-day survival after surgery. The survival curves of the two groups of recipients were drawn using Kaplan-Meier method and compared using the log-rank test. Results The intensive care unit (ICU) stay time, ECMO application time and ventilator use time of control group were longer than those of treatment group. The proportion of male recipients and the BMI of control group were lower than those of treatment group. The 30-day, 90-day and 180-day survival of control group was worse than that of treatment group, and the differences were statistically significant (all P<0.05). The univariate Cox regression analysis of the recipients' 30-day survival after surgery showed that the recipients' BMI, history of diabetes, enlargement of the right atrium and right ventricle, intraoperative blood transfusion volume and intraoperative red blood cell transfusion volume were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes and enlargement of the right atrium and right ventricle were risk factors affecting the 30-day survival of lung transplant recipients (all P<0.05). The univariate Cox regression analysis of the recipients' 90-day survival after surgery showed that the recipients' BMI, history of diabetes, enlargement of the right atrium and right ventricle, intraoperative blood transfusion volume, intraoperative red blood cell transfusion volume and group variable were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes, enlargement of the right atrium and right ventricle and group variable were risk factors affecting the 90-day survival of lung transplant recipients (all P<0.05). The univariate Cox regression analysis of the recipients' 180-day survival after surgery showed that the recipients' BMI, history of diabetes, right atrium and right ventricle enlargement, intraoperative blood transfusion volume, intraoperative red blood cell transfusion volume and group variable were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes, enlargement of the right atrium and right ventricle and group variable were risk factors affecting the 180-day survival of lung transplant recipients (all P<0.05). The 30-day, 90-day and 180-day survival rates of control group were lower, and the differences between the two groups were statistically significant (all P<0.05), with a median survival time of 100 days in control group. Conclusions In the clinical treatment of severe PGD after lung transplantation, prone position ventilation combined with VV-ECMO may shorten ECMO application time, invasive ventilation time and ICU stay time, and improve the short-term prognosis of lung transplantation.

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: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.

Objective:To analyze the differentially expressed messenger RNA(mRNA), microRNA(miRNA), and long non-coding RNA(lncRNA)during the browning of mouse subcutaneous adipose tissue, construct a competitive endogenous RNA(ceRNA)network, and provide a theoretical basis for investigating the regulatory mechanisms of white adipose tissue browning.Methods:A cold-stimulated mouse model was established for transcriptome sequencing.Bioinformatics tools were employed to screen for differentially expressed mRNAs, miRNAs, and lncRNAs.An integrated mRNA-miRNA-lncRNA analysis was performed to construct a ceRNA network.Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes(KEGG), and Gene Set Enrichment Analysis(GSEA)were conducted on the differentially expressed mRNAs and ceRNA networks to explore transcriptional regulation during the cold-induced browning of subcutaneous adipose tissue.Results:Transcriptomic analysis of the cold-stimulated model identified 4, 256 differentially expressed RNAs, which include 3, 600 mRNAs, 588 lncRNAs, and 68 miRNAs.GO and KEGG analyses revealed that the browning of white adipose tissue involves immune-related processes, such as immune system processes, immune responses, adaptive and innate immune responses, and the positive regulation of T-cell activation.A ceRNA network associated with browning regulation was constructed, comprising 233 nodes(188 mRNAs, 34 miRNAs, and 11 lncRNAs)and 351 edges.Protein-protein interaction(PPI)analysis of the mRNAs within the ceRNA network highlighted pathways including apoptosis, intracellular signaling transduction, hypoxia-inducible factor-1(HIF-1), AMP-activated protein kinase(AMPK), Janus kinase-signal transducer and activators of transcription(JAK-STAT)signaling, carbon metabolism, glycolysis, and thyroid hormone pathways, all of which regulate lipid metabolism, hypoxia, and glycolysis.Cytohubba analysis identified the top 10 hub genes: Bcl2, Src, Cebpb, Creb1, Runx1, Foxo3, Ets1, Socs3, Slc2 a4, and Pkm. Conclusions:The ceRNA network that regulates the browning of white adipose tissue is involved in various pathways, including carbon metabolism, glycolysis, thyroid hormone signaling, growth hormone signaling, prolactin signaling, as well as the HIF-1, AMPK, and JAK-STAT pathways.Key regulatory miRNAs in this context include miR-30e-5p, miR-182-5p, miR-20b-5p, miR-144-3p, miR-363-3p, miR-141-3p, miR-203-3p, and miR-107-3p.These miRNAs may serve as critical targets for inducing browning in response to cold exposure.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.