ObjectiveTo investigate the value of liver stiffness measurement （LSM） and spleen stiffness measurement （SSM） measured by two-dimensional shear wave elastography （2D-SWE） in the diagnosis of severe portal hypertension （SPH） and high-risk varices （HRV）， and to provide a basis for noninvasive assessment of portal hypertension. MethodsA prospective study was conducted among 78 patients with cirrhotic portal hypertension who were treated in Liver Research Center of Beijing Friendship Hospital， Capital Medical University， from December 2019 to April 2023. According to hepatic venous pressure gradient （HVPG）， the patients were divided into 6 mmHg≤HVPG<12 mmHg group， 12 mmHg≤HVPG<20 mmHg group， and HVPG ≥20 mmHg group. All patients underwent gastroscopy and 2D-SWE within 1 week after HVPG measurement， and SWE-LSM and SWE-SSM measured by 2D-SWE were recorded. A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between multiple groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. With HVPG and gastroscopy findings as the gold standard， the receiver operating characteristic （ROC） curve was plotted and the area under the ROC curve （AUC） was calculated to evaluate diagnostic performance， while the DeLong test was used for comparison of AUC. The Pearson or Spearman correlation analysis was used to investigate the correlation between variables， and the linear regression analysis and the Logistic regression analysis were used to investigate the influencing factors for HVPG and HRV. ResultsThe mean HVPG was 18.1±6.4 mmHg for the patients enrolled in this study， and HRV was observed in 62 patients （79.5%）. Both SWE-LSM and SWE-SSM were significantly positively correlated with HVPG （r=0.413 and 0.633， both P<0.001）， with an AUC of 0.812 and 0.902， respectively， in the diagnosis of HVPG≥12 mmHg and an AUC of 0.804 and 0.789， respectively， in the diagnosis of HVPG≥20 mmHg （all P>0.05）. The multivariate linear regression analysis showed that SWE-SSM was an independent influencing factor for HVPG （β=0.17， P<0.001）. In the diagnosis of HRV， only SWE-SSM showed a significant positive correlation with HRV （r=0.432， P<0.001）， with a better diagnostic performance than SWE-LSM in terms of AUC （0.808 vs 0.642， Z=2.775， P=0.006）. The multivariate Logistic regression analysis showed that platelet count was an independent influencing factor for HRV （odds ratio=0.97， P=0.014）. ConclusionSWE-SSM is closely correlated with both HVPG and HRV， showing a good performance in the diagnosis of SPH and HRV， and therefore， it is expected to become an effective noninvasive tool for assessing portal hypertension.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

BACKGROUND:In vitro construction of tissue-engineered intestinal models plays an important role in intestinal regeneration and intestinal disease research.The interaction of intestinal nervous system and intestinal epithelial barrier to maintain body homeostasis is a hot topic in the bionic construction of tissue-engineered intestinal tract.OBJECTIVE:To construct a bionic model that can mimic the enteric nervous system in vivo.METHODS:Using fibroin protein with villus structure as scaffold,human induced neural stem cells solidified with collagen were added to intestinal epithelial cells(Caco-2 and HT29-MTX-E12)for 3-day culture to construct a co-culture system of intestinal epithelial cells and nerve cells(co-culture group).Human induced neural stem cells or intestinal epithelial cells cultured alone that were inoculated with fibroin scaffolds were set as controls.Cell morphology was observed by scanning electron microscopy and hematoxylin-eosin staining.Cell activity was detected by Live/Dead cell staining.Human induced neural stem cell differentiation was detected by β-microtubulin immunofluorescence staining.Intestinal epithelial histological properties and barrier function were detected by microvillin,sucrase-isomaltase,tight junction protein 1,E-calmodulin,and mucin-2 immunofluorescence staining.The function of mucus secretion from intestinal epithelial cells was detected by Alcian blue staining.Alkaline phosphatase staining was performed to detect differentiation of intestinal epithelial cells,at the same time,sucrase-isomaltase,tight junction protein 1,and alkaline phosphatase mRNAs were detected by RT-qRCR.RESULTS AND CONCLUSION:The neuralized intestinal mucosal co-culture model with villi structure was successfully constructed,and neural stem cells and intestinal epithelial cells on the fibroin scaffold showed good cellular activities.After neuralization,the activity of alkaline phosphatase and sucrase-isomaltase in intestinal epithelial cells was enhanced,while the expression level of tight junction protein 1 was up-regulated.To conclude,the neuralized bionic intestinal epithelial model is beneficial to the maturation of intestinal mucosal epithelial cells and the formation of barrier function.

BACKGROUND:Plate fixation is the mainstream method for the surgical treatment of distal femoral fractures.The intramedullary nailing has the advantages of minimally invasive,such as less soft tissue injury and bone blood supply destruction.At the same time,it is a central fixation and has better biomechanical effect.Therefore,retrograde intramedullary nailing has become another option for the internal fixation of distal femoral fractures.OBJECTIVE:The biomechanical characteristics of new retrograde intramedullary nail on lateral femur condyle,common femoral retrograde intramedullary nail,and lateral femur condyle anatomical locking plate for the treatment of A2-type distal femoral fractures were compared using finite element analysis,and the advantages of new retrograde intramedullary nail on lateral femur condyle was studied.METHODS:A new retrograde intramedullary nail on lateral femur condyle was designed,which was inserted into the bone cortex in front of the insertion point of the lateral collateral ligament of the lateral femoral condyle.A CT scan was performed on the lower limb bone of a male volunteer,and a three-dimensional model of the femur was established.The model was then segmented to create a three-dimensional model of a femoral distal A2-type fracture,The three-dimensional models of small(small group),standard type retrograde intramedullary nail on the lateral femoral condyle(standard group),common retrograde intramedullary needle(common group),and lateral femur condyle anatomical locking plate(plate group)were established respectively.The axial stresses of 600,1 800 N and the torsional load of 4 000,8 000 N·mm were applied to the models,and the displacement and stress of femur and the displacement,stress and shear force of internal fixators were observed in each group.RESULTS AND CONCLUSION:(1)When subjected to axial load of 600 and 1 800 N,the femoral peak displacement,the femoral peak stress,and the peak stress of interal fixation in the standard group were the lowest among the four groups.(2)When subjected to torsional load of 4 000 and 8 000 N·mm,the femoral peak displacement and peak displacement of the internal fixation in the standard group were the lowest among the four groups.(3)Compared with femoral lateral condylar locking plate and common retrograde intramedullary needle,the new retrograde intramedullary needle on lateral femur condyle has mechanical advantages of reducing stress concentration and decreasing the risk of internal fixation failure.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective: To assess the clinical application value of a prediction model for red blood cell (RBC) demand in surgical procedures. Methods: Demographic data, laboratory parameters, anesthesia and transfusion records, and model prediction data were retrospectively collected from surgical patients at the First Medical Center of Chinese PLA General Hospital between 2018 and 2024. Statistical analysis was performed using the Chi-square test, t-test, and Mann-Kendall trend test. Results: From 2018 to 2024, the predictive model for RBC demand in surgical procedures was used to evaluate a total of 112 293 surgeries. During this period, the model call rate (77.49%-98.91%, P<0.05), compliance rate (56.81%-84.92%, P<0.05), and prediction accuracy rate (66.82%-94.17%, P<0.05) all showed significant upward trends. The total blood usage across the hospital (13645.4-7723.5 units, P<0.05) and the average blood usage per surgery (0.21-0.1 units, P<0.05) exhibited overall downward trends. Postoperative average hemoglobin levels in the non-compliance group (112.1-105.3 g/L in the non-compliance group vs 106.9-92.7 g/L in the compliance group, P<0.05) and the intraoperative excessive transfusion rate (5.06%-6.05% in the non-compliance group vs 0.09%-0.04% in the compliance group, P<0.05) were significantly higher in the non-compliance group compared to the compliance group. Conclusion: The predictive model for RBC demand in surgical procedures has played a positive role in conserving blood resources, optimizing blood resource allocation, and reducing intraoperative risks.