ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the "monarch, minister, assistant, envoy" compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.
Artificial Intelligence ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Drug Synergism

The rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that evade immunity elicited by vaccination has posed a global challenge to the control of the coronavirus disease 2019 (COVID-19) pandemic. Therefore, developing countermeasures that broadly protect against SARS-CoV-2 and related sarbecoviruses is essential. Herein, we have developed a lipid nanoparticle (LNP)-encapsulated mRNA (mRNA-LNP) encoding the full-length Spike (S) glycoprotein of SARS-CoV-2 (termed RG001), which confers complete protection in a non-human primate model. Intramuscular immunization of two doses of RG001 in Rhesus monkey elicited robust neutralizing antibodies and cellular response against SARS-CoV-2 variants, resulting in significantly protected SARS-CoV-2-infected animals from acute lung lesions and complete inhibition of viral replication in all animals immunized with low or high doses of RG001. More importantly, the third dose of RG001 vaccination elicited effective neutralizing antibodies against current epidemic XBB and JN.1 strains and similar cellular response against SARS-CoV-2 Omicron variants (BA.1, XBB.1.16, and JN.1) were observed in immunized mice. All these results together strongly support the great potential of RG001 in preventing the infection of SARS-CoV-2 variants of concern (VOCs).

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

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 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.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Objective:To explore the efficacy and safety of orelabrutinib combined with R-CHOP in patients with high-risk nongerminal center B-cell (non-GCB) diffuse large B-cell lymphoma (DLBCL) with extranodal involvement.Methods:This retrospective study was conducted on 35 patients who were seen at Guangxi Medical University Cancer Hospital and were immunohistochemically confirmed to have non-GCB DLBCL, had an International Prognostic Index score of 3 - 5, and confirmed to have ≥2 extranodal involvement on PET/CT. The treatment comprised the standard R-CHOP regimen combined with oral orelabrutinib (150 mg/day) for six cycles. In patients who developed neutropenia or grade 3 neutropenia with fever during treatment, administration of prophylactic pegylated granulocyte colony-stimulating factor 48 h after the end of chemotherapy was started on the next cycle. The endpoints included overall response rate (ORR), complete response (CR) rate, progression-free survival (PFS) time, overall survival (OS) time, and safety assessment.Results:The 35 eligible patients enrolled had a median age of 53 years (21 - 72 years) and a median follow-up time of 28 months (12 - 36 months) ; 19 patients had double-expressor (DE) status. The ORR was 88.6%, and the CR rate was 68.6%. The 2-year PFS and OS rates were 68.6% (95% CI 54.0% - 7.2%) and 87.5% (95% CI 76.7% - 100%), respectively. The 2-year PFS rate was significantly lower in patients with DE status than in those without DE status [54.4% (95% CI 35.4% - 84.2%) vs. 85.2% (95% CI 68.3% - 100%), P=0.048]. Serious adverse events included febrile neutropenia, pneumonia, and atrial flutter, but no treatment-related deaths. Conclusion:In patients with high-risk non-GCB DLBCL and extranodal involvement, the combination of orelabrutinib with R-CHOP regimen had good efficacy and manageable toxicity.

Objective:To analyze the clinical characteristics of a patient with Short rib-polydactyly syndrome type 6 (SRTD6) with long-term misdiagnosis, and improve its clinical recognition by reviewing the relevant literature.Methods:A patient presented at the Children′s Hospital Affiliated to Zhejiang University School of Medicine on August 19, 2024 for the discovery of liver dysfunction for 13 years and vision loss for 9 years was selected as the study subject. Her medical history, clinical data, laboratory findings and results of imaging examination were collected. High-throughput sequencing was carried out, and candidate variants were verified by Sanger sequencing. This study was approved by the Ethics Committee of the Hospital (Ethics No.: 2021-IRB-292).Results:The patient had long-term unexplained liver dysfunction, vision loss, and growth delay. Blood acylcarnitine and urinary organic acid analysis have failed to found any abnormality. Previous genetic testing revealed a homozygous c. 203A>C (p.Glu68Ala) missense variant in the ETFDH gene, leading to a misdiagnosis of various acyl-CoA dehydrogenase deficiencies. However, treatment with high-dose vitamin B2 showed a poor effect. Physical examination revealed small hands, short and stubby fingers, and a narrow chest. Medical imaging showed shortened bilateral ribs, a narrowed chest, and short, thick metacarpals. High-throughput sequencing has detected a pathogenic homozygous c. 1957C>T (p.R653*) nonsense variant in the NEK1 gene, confirming the diagnosis of SRTD6. Conclusion:SRTD6 is characterized by rib and sternum dysplasia as the primary skeletal deformities, which is often accompanied by multi-organ impairment. Genetic testing can facilitate the precise diagnosis.

Objective:To evaluate immunotherapy combined with neoadjuvant chemotherapy before radical total gastrectomy in microsatellite stable locally advanced gastric cancer in two cases.Methods:Two male patients with clinical stage cT3N 1M0 and microsatellite-stable locally advanced gastric cancer were treated with neoadjuvant chemotherapy with PD-1 inhibitor (Nivolumab) combined with SOX (Oxaliplatin+S-1) for 4 cycles before surgery. Standard laparoscopic assisted total gastrectomy with D 2 lymphadenectomy was performed on Feb 2023 and Oct 2023 respectively after the neoadjuvant treatment. Pathological tumor regression grade(TRG) was observed to assess the degree of tumor regression, and follow-up was conducted to monitor tumor markers and abdominal enhanced CT to detect recurrence. Results:Two patients achieved pathological complete response(TRG0). They were followed up until May 2024 and no recurrence was observed.Conclusion:Preoperative combination of chemotherapy and immunotherapy may provide survival benefit for microsatellite stable locally advanced gastric cancer patients.