Objective: To explore the efficacy of a novel injectable hydrogel (GelMA/P11/IL4@LIP) loaded with P11 bacteriophages and interleukin-4 (IL-4) liposomes (LIP) in preventing relapse after maxillary expansion in mice, providing experimental evidence for its clinical application. Methods: This study was approved by the experimental animal ethics committee of our hospital. First, 15 7-week-old C57BL/6 mice were used to establish a maxillary expansion model and divided into 5 groups (3 mice in each group): a control group, post expansion day 3 group (PED3 group), post expansion day 7 group (PED7 group), retention for 14 days group (RET group), and relapse for 7 days group (REL group). The mice in each group were sacrificed at their designated time points (day 0, 3, 7, 21, 28), and their maxilla and anterior cranial regions were collected. Bone parameters and the inter-crestal distance (ICD) of maxillary incisor mesial alveolar ridge were measured using micro-computed tomography (micro-CT). Histological staining was performed to evaluate bone formation and resorption, while immunohistochemistry (IHC) was performed for macrophage markers (CD86 and CD206), mesenchymal stem cell markers (glioma-associated oncogene homolog 1 [Gli1]), and osteogenic markers (Runt-related transcription factor 2 [Runx2] and Osterix [OSX]). Next, GelMA/P11/IL4@LIP was synthesized and administered to mouse models of maxillary expansion. A total of 24 7-week-old C57BL/6 mice were divided into 4 groups (6 mice in each group): a blank control group, GelMA group, GelMA/P11 group, and GelMA/P11/IL4@LIP group. All mice underwent palatal expansion. On PED7, the expanders of all 24 mice were cemented with resin to initiate the 14-day retention period. On day 1 of the retention phase, the mice in each group received injections of saline, GelMA, GelMA/P11, or GelMA/P11/IL4@LIP at the midpalatal suture. After the 14-day retention period, three mice in each group were randomly selected and sacrificed, while the other three had their expanders removed and underwent a 7-day relapse before being sacrificed on day 28 (REL). Micro-CT, histological staining, and IHC were performed to evaluate the preventive effect of GelMA/P11/IL4@LIP on post-expansion relapse. Results: The mice maxillary expansion model exhibited a decreased ICD at REL compared to RET in micro-CT analysis (P = 0.008). IHC analysis demonstrated prolonged M1 macrophage infiltration, scarce Gli1+ mesenchymal stem cells, and insufficient expression of osteogenic markers (RUNX2 and OSX) (P < 0.001). Compared to the blank control and GelMA groups, GelMA/P11/IL4@LIP hydrogel injection in the midpalatal suture led to increased ICD at REL, promoted the timely M2 polarization of macrophages, recruited Gli1+ mesenchymal stem cells, and upregulated the expression of RUNX2 and OSX (P < 0.05). Conclusion The mechanism of relapse after maxillary expansion involves the persistent infiltration of M1 macrophages, as well as the inadequate recruitment and insufficient osteogenic differentiation of MSCs in the midpalatal suture. The GelMA/P11/IL4@LIP composite enhanced orofacial mesenchymal stem cell recruitment and promoted the M2 polarization of macrophages, thereby enhancing osteogenesis in the midpalatal suture and preventing post-expansion relapse.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

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 construct a combined prediction model based on dual-layer detector spectral CT radiomics features and quantitative parameters, and to evaluate its value in preoperative prediction of serosal invasion in gastric cancer.Methods:This case-control study retrospectively analyzed data from 253 gastric cancer patients confirmed by postoperative pathology at the First Affiliated Hospital of Soochow University (Center 1) and Changshu No.2 People′s Hospital (Center 2) from January 2022 to December 2023. Patients from Center 1 ( n=157) were randomly divided into training set ( n=110) and test set ( n=47) in a 7∶3 ratio, while patients from Center 2 ( n=96) served as an external validation set. Based on postoperative pathological serosal invasion status, patients were classified into serosal invasion group ( n=164) and non-serosal invasion group ( n=89), with distributions of 70/40, 30/17, and 64/32 in the training, test, and external validation sets, respectively. Spectral CT quantitative parameters, including arterial and venous phase iodine concentration (IC), normalized iodine concentration (NIC), arterial-venous IC differences, arterial-venous NIC differences (NIC pa), arterial enhancement fraction (AEF), and effective atomic number (Z eff), were measured. Radiomics features were extracted from venous-phase 40 keV monochromatic images. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature selection. The logistic regression classifier (LR-LASSO) was applied to construct the radiomics model. Univariate and multivariate logistic regression analyses identified independent risk factors for serosal invasion, including the radiomics signature (RadScore) and quantitative parameters. A clinical model was built using significant quantitative parameters, and a combined model integrated RadScore. An artificial model was based on cT4 staging assessed by two radiologists using venous-phase CT. The diagnostic performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). Results:A total of six radiomics features were selected to establish the radiomics model. RadScore ( OR=7.598, 95% CI 2.259-25.562, P=0.001) and NIC pa ( OR=4.598, 95% CI 1.404-15.050, P=0.012) served as independent risk factors. The NIC pa served as the clinical model. The AUCs (95% CI) of the combined model in the training, test, and external validation sets were 0.984 (0.969-1.000), 0.855 (0.728-0.982), and 0.773 (0.665-0.882), respectively. The AUCs of the artificial model were 0.741, 0.670, 0.644; of the clinical model were 0.709, 0.633, 0.626. The AUCs of the radiomics model were 0.963, 0.824, 0.741, respectively. Calibration curves showed good agreement between predicted probability and observed probability. The DCA confirmed higher clinical net benefits for the combined model. Conclusion:The combined model integrating dual-layer detector spectral CT radiomics features and quantitative parameters exhibits high efficacy for preoperative prediction of gastric cancer serosal invasion.

Obesity is the key factor leading to insulin resistance,cardiovascular disease,metabolic syndrome and tumor.Multimodal imaging technique,including dual-energy X-ray absorptiometry,ultrasound,CT,MRI and PET imaging could non-invasively quantify adipose tissue.The research progresses of multimodal imaging for quantifying adipose tissue were reviewed in this article.

Objective To observe the value of artificial intelligence iterative reconstruction(AIIR)combined with 60 kVp scanning in craniocervical CT angiography(CTA).Methods Eighty-six patients with suspected craniocervical vascular diseases were prospectively enrolled and randomly received routine-dose(120 kVp)or low-dose(60 kVp)scanning(each n=43),and contrast dosage and radiation dose were recorded.After scanning,hybrid iterative reconstruction(HIR)was used to reconstruct routine-dose images(group A),while HIR images(group B1)and AIIR images(group B2)were performed to reconstruct low-dose images,respectively.The overall imaging quality,visualization of targeted large and small vessels and diagnostic confidence scores,as well as image noise(SD),signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of targeted large vessels were compared among 3 groups.Results Contrast dosage and effective dose(ED)decreased by 36.52％ and 77.56％ in low-dose scanning compared with those in routine-dose scanning,respectively.No significant difference of subjective scoring of imaging quality indexes was found between groups B2 and A(all adjusted P＞0.05),which were both higher than those in group B1(all adjusted P＜0.05).SD of target large vessels in group B2 than that of most target large vessels in group A(all adjusted P＜0.05)except for aortic arch.SNR and CNR of target large vessels in group B2 were higher than those in group A and B1(all adjusted P＜0.05),while SD of target large vessels in group B2 were lower than in group B1.Conclusion AIIR combined with 60 kVp scanning in craniocervical CTA could meet diagnostic requirements of imaging quality and reduce contrast dosage and radiation dose.

Objective:To investigate the situation of computed tomography(CT)equipment and socio economic development of various grades and classifications of medical institutions in Jiangsu Province,and to analyze the interrelationship between them.Methods:From October 20,2023 to November 20,2023,a questionnaire survey was conducted on imported and domestic CT equipment of various grades and classifications of medical institutions in 13 prefecture-level cities in Jiangsu Province through online questionnaire survey of"questionnaire star".The gross domestic product(GDP)of each prefecture-level city in Jiangsu province was used as an indicator of measuring the level of socio-economic development in the region.The CT number,the row number of detector,quality of image,the total examination case number of daily average and the daily average case number of single machine examination of medical institutions of various grades and classifications of 13 prefecture-level cities were used to conduct correlation analysis with GDP values of various districts.Results:A total of 910 questionnaires were distributed,and 512 questionnaires were retrieved.There were 482 valid questionnaires in the 512 questionnaires,and the valid rate was 94.15,which involved to 482 various grade and classification institutions of 13 prefecture-level cities in Jiangsu province.The number of imported and domestic CT equipment in the 13 prefecture-level cities of Jiangsu Province positively correlated with the GDP of each city(r=0.882,0.880,P<0.001).The number of imported CT equipment with 64 rows and more than 64 rows,and with less than 64 rows,and the number of domestic CT equipment with 64 rows and more than 64 rows,and with less than 64 rows all positively correlated with the GDP of each city(r=0.880,0.881,0.736,0.897,P<0.05).The total number of daily average of examinations for imported and domestic CT equipment of 13 prefecture-level cities positively correlated with the GDP of each city(r=0.774,0.814,P<0.05).There were no significant difference in the image quality and the daily average case number of single machine examination between the domestic CT equipment and the imported CT equipment(P>0.05).Conclusion:The medical institutions of city with high level of economic development have more quantitative and more high-end CT equipment,and the quality of image of domestic CT equipment is equal to that of imported CT equipment regardless of the high and low level of economic development.

Objective:To investigate the pathogen distribution, temporal trends in the rates of antimicrobial resistance, and susceptibility of bloodstream isolates and comparatively explore the epidemiological characteristics of bloodstream infections in hematology departments across 56 healthcare facilities in Guangdong Province from 2020 to 2024.Methods:A multicenter analysis was conducted to evaluate the constituent ratio of different pathogens isolated from clinical isolate data from bloodstream specimens in hematology, respiratory, and intensive care unit (ICU) departments across 56 healthcare facilities in Guangdong Province (2020-2024), and antimicrobial resistance trends in pathogens with high-detection rate over 5 years were assessed. Carbapenem-resistant Gram-negative organisms (CRO) were randomly sampled for carbapenemase gene detection and in vitro antimicrobial susceptibility tests with novel antimicrobial agents.Results:From 2020 to 2024, a total of 8 968, 6 440, and 25 511 bloodstream isolates were identified in the hematology, respiratory, and ICU departments, respectively, across 56 participating facilities in Guangdong Province, with significant differences in the pathogen constituent ratio among departments ( P<0.001). Notably, the hematology department demonstrated a predominance of Escherichia coli (24.1%), Klebsiella pneumoniae (17.5%), Pseudomonas aeruginosa (11.7%), coagulase-negative Staphylococci (15.2%), and Staphylococcus aureus (5.1%). In the resistance analysis, the rates of meropenem resistance of Escherichia coli and Klebsiella pneumonia increased from 6.7% and 5.8% (2020) to 14.0% and 15.8% (2024), respectively. Conversely, Pseudomonas aeruginosa exhibited a declining trend in the rate of meropenem resistance (6.2% to 1.9%) and imipenem (10.2% to 6.1%) during the same period. Acinetobacter baumannii demonstrated a biphasic resistance pattern to common antimicrobial agents, characterized by an initial decline, followed by a rebound. In this study, the susceptibility rates to conventional antimicrobial agents were significantly higher in Staphylococcus aureus versus coagulase-negative Staphylococci, with no glycopeptide- or linezolid-resistant strains detected. Notably, the prevalence of vancomycin-resistant Enterococcus faecium increased from 0 in 2020 to 23.1% in 2024. CRO carbapenemase phenotypes through active surveillance revealed that 80% Escherichia coli isolates were carrying blaNDM, 90% Klebsiella pneumoniae isolates were carrying blaKPC, 10% Pseudomonas aeruginosa isolates were carrying blaVIM, and 100% Acinetobacter baumannii were carrying blaOXA-23. The results of the antimicrobial susceptibility test in CRO revealed that carbapenem-resistant Escherichia coli (CRECO) demonstrated a 0 resistance rate to tigecycline, polymyxin B, and aztreonam/avibactam, whereas carbapenem-resistant Klebsiella pneumoniae exhibited a 0 resistance rate to aztreonam/avibactam, ceftazidime/avibactam, and imipenem/relebactam. Carbapenem-resistant Pseudomonas aeruginosa exhibited a 95.0% susceptibility rate to amikacin and polymyxin B, with a 45.0% resistance rate to ceftazidime/avibactam. In contrast, carbapenem-resistant Acinetobacter baumannii demonstrated complete susceptibility (100.0%) to sulbactam/durlobactam (MIC90=2 μg/ml), whereas eravacycline showed MIC50 and MIC90 values of 1 and 2 μg/ml, respectively. Conclusion:The pathogen constituent ratio of bloodstream isolates differed significantly among hematology, respiratory, and ICU departments. Notably, although CRO exhibited an escalating prevalence, it sustained high susceptibility to novel antimicrobial agents.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

As a pivotal noninvasive diagnostic tool of coronary artery disease,coronary CT angiography(CCTA)has achieved remarkable advancements over the past four decades.From early electron beam CT to contemporary photon counting detector CT,CCTA technology has undergone continuous innovation,and its clinical applications expanded from pure anatomical assessment to a multidimensional comprehensive evaluation integrating anatomy,function and histology.The technological evolution clinical application status and future development directions of CCTA were reviewed in this article.