1.Three-dimensional Electrical Impedance Tomography for Monitoring Gastric Hemorrhage
Zi-Han ZHAO ; Bo SUN ; Jing-Shi HUANG ; Zhi-Wei LI ; Yang WU ; Nan LI ; Jia-Feng YAO ; Tong ZHAO
Progress in Biochemistry and Biophysics 2026;53(4):1062-1075
ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.
2.Olfactory Receptors Expressed in The Intestine and Their Functions
Pei-Wen YANG ; Meng-Meng YUAN ; Ying ZHOU ; Peng LI ; Gui-Hong QI ; Ying YANG ; Zhong-Yi MAO ; Meng-Sha ZHOU ; Xiao-Shuang MAO ; Jian-Ping XIE ; Yi-Nan YANG ; Shi-Hao SUN
Progress in Biochemistry and Biophysics 2026;53(3):534-549
Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.
3.Effect of sitravatinib on a mouse model of carbon tetrachloride-induced liver fibrosis and its mechanism
Huan ZHANG ; Xiangyu WU ; Qianwen ZHAO ; Fajuan RUI ; Nan GENG ; Rui JIN ; Jie LI
Journal of Clinical Hepatology 2026;42(3):600-607
ObjectiveTo investigate the therapeutic effect of sitravatinib on carbon tetrachloride (CCl4)-induced liver fibrosis in mice. MethodsA total of 30 male C57BL/6J mice, aged 8 weeks, were randomly divided into control group, CCl4 model group, and low- (5 mg/kg), middle- (10 mg/kg), and high-dose (20 mg/kg) sitravatinib groups. All mice except those in the control group were given intraperitoneal injection of CCl4 for 4 consecutive weeks to induce liver fibrosis, and since the first day of modeling, the mice in the low-, middle-, and high-dose sitravatinib groups were given sitravatinib at the corresponding dose by gavage every day. The serum levels of total cholesterol (TC), triglyceride (TG), and alanine aminotransferase (ALT) were measured for the mice in each group; hepatic hydroxyproline content was measured; HE staining, Masson staining, and Sirius Red staining were used to observe liver histopathological changes; quantitative real-time PCR and Western blot were used to measure the mRNA and protein expression levels of α-smooth muscle actin (α-SMA) and collagen type I alpha 1 (Col1a1) in liver tissue. The therapeutic effect of sitravatinib was assessed based on the above results. A one-way analysis of variance was used for comparison of continuous data between multiple groups, and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the control group, the model group had significant increases in the levels of TC, TG, and ALT (all P<0.05), and there were no significant differences in the levels of TC, TG, and ALT between the model group and the low-, middle-, and high-dose sitravatinib groups (all P>0.05). Hepatic hydroxyproline content decreased after sitravatinib intervention, with a significant difference between the middle-/high-dose sitravatinib groups and the CCl4 model group (both P<0.05). Histopathological staining showed that the sitravatinib treatment groups had a reduction in collagen deposition, along with thinning and fragmentation of fibrous septa, and in the high-dose sitravatinib group, 4 mice had a fibrosis stage of S0—S1 and 2 mice had a fibrosis stage of S2—S3, suggesting a certain degree of alleviation of liver fibrosis degree compared with the CCl4 model group (mainly S3—S4). The measurement of related molecules showed that sitravatinib downregulated the mRNA and protein expression levels of α-SMA and Col1a1 (all P<0.05). ConclusionSitravatinib can effectively alleviate CCl4-induced liver fibrosis in mice, possibly by inhibiting hepatic stellate cell activation and collagen synthesis.
4.From Gene Expression to Transcriptome-wide Association Study: Development and Comparison of Methodology
Kun FANG ; Guozhuang LI ; Linting WANG ; Qing LI ; Kexin XU ; Lina ZHAO ; Zhihong WU ; Jianguo ZHANG ; Nan WU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):223-229
Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.
5.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
6.LINC00657 Promotes Malignant Progression of Cervical Cancer by Sponging miR-30a-5p to Regulate Skp2 Expression
Changhui ZHOU ; Jingqin REN ; Zhen CHEN ; Qi YAN ; Nan YANG ; Jiaqi ZHAO ; Rong LI
Cancer Research on Prevention and Treatment 2026;53(2):103-111
Objective To investigate the role and regulatory mechanism of LINC00657 in the progression of cervical cancer. Methods Bioinformatics analysis predicted potential binding sites between LINC00657 and miR-30a-5p and between miR-30a-5p and Skp2. These sites were verified by using RNA immunoprecipitation and dual-luciferase reporter experiments. LINC00657, miR-30a-5p, and Skp2 mRNA expression levels in cervical cancer tissues and cell lines were assessed by utilizing RT-qPCR. Western blot analysis was employed to examine the protein levels of Skp2 in cells and subcutaneous xenograft tumor models in nude mice. Immunohistochemistry was applied to analyze Skp2 expression in animal tissues. The cellular processes of cervical cancer cell lines were evaluated through CCK-8, scratch, and Transwell assays. Results LINC00657 and Skp2 presented binding sites for miR-30a-5p. In cervical cancer, LINC00657 and Skp2 showed high expression levels (P<0.05), whereas miR-30a-5p displayed low expression (P<0.05). Functional experiments demonstrated that linc00657 upregulates Skp2 expression, a process that is dependent on its sequestration of miR-30a-5p. Conclusion LINC00657 promoted the malignant progression of cervical cancer by upregulating Skp2 expression through specifically sequestering miR-30a-5p, thereby relieving its inhibitory effect on the target gene Skp2.
7.Correlation Analysis of Huanglian Jiedu Wan on Syndrome Improvement and Clinical Biomarkers of "Excess Heat-Toxicity" Based on Machine Learning Model
Qi LI ; Keke LUO ; Baolin BIAN ; Hongyu YU ; Mengxiao WANG ; Mengyao TIAN ; Wen XIA ; Yuan MA ; Xinfang ZHANG ; Pengyue LI ; Nan SI ; Hongjie WANG ; Yanyan ZHOU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):162-173
ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally, the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome, such as oral ulcers, sore throat, and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation, oxidative stress, and energy metabolism in the early phase, Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting (XGBoost) algorithm was used to develop a prediction model for main symptom classification, with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers, sore throat, and overall symptoms, with significant effects observed especially in sore throat and overall symptom analyses (P<0.01). Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement, were also called "heat-related biomarkers", including succinic acid, α-ketoglutaric acid, glycine, lactic acid, adenosine monophosphate (AMP), tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin-1β (IL-1β), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), and so on. Conversely, clinical biomarkers negatively correlated with symptom severity, were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan, including malic acid, fumaric acid, cis-aconitic acid, adrenocorticotropic hormone (ACTH), IL-1β, IL-4, IL-8, succinic acid, and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables, with importance scores of 0.081 and 0.080, respectively. After screening out 14 key variables and optimizing the parameters, model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables, confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established, achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.
8.Correlation Analysis of Huanglian Jiedu Wan on Syndrome Improvement and Clinical Biomarkers of "Excess Heat-Toxicity" Based on Machine Learning Model
Qi LI ; Keke LUO ; Baolin BIAN ; Hongyu YU ; Mengxiao WANG ; Mengyao TIAN ; Wen XIA ; Yuan MA ; Xinfang ZHANG ; Pengyue LI ; Nan SI ; Hongjie WANG ; Yanyan ZHOU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):162-173
ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally, the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome, such as oral ulcers, sore throat, and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation, oxidative stress, and energy metabolism in the early phase, Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting (XGBoost) algorithm was used to develop a prediction model for main symptom classification, with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers, sore throat, and overall symptoms, with significant effects observed especially in sore throat and overall symptom analyses (P<0.01). Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement, were also called "heat-related biomarkers", including succinic acid, α-ketoglutaric acid, glycine, lactic acid, adenosine monophosphate (AMP), tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin-1β (IL-1β), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), and so on. Conversely, clinical biomarkers negatively correlated with symptom severity, were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan, including malic acid, fumaric acid, cis-aconitic acid, adrenocorticotropic hormone (ACTH), IL-1β, IL-4, IL-8, succinic acid, and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables, with importance scores of 0.081 and 0.080, respectively. After screening out 14 key variables and optimizing the parameters, model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables, confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established, achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.
9.Modified Morrow procedure for the treatment of hypertrophic obstructive cardiomyopathy: A single-center retrospective study in 318 patients
Jie LI ; Fan WENG ; Nan CHEN ; Yongxin SUN ; Changfa GUO ; Chunsheng WANG ; Yi LIN ; Wenjun DING
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(03):431-437
Objective To summarize the clinical efficacy of modified Morrow surgery in the treatment of hypertrophic obstructive cardiomyopathy. Methods A retrospective analysis was conducted on the clinical data of patients with hypertrophic obstructive cardiomyopathy treated with modified Morrow surgery at Zhongshan Hospital Affiliated to Fudan University from 2020 to 2023. Results A total of 318 patients were enrolled, including 156 males and 162 females, with an average age of (55.6±13.1) years. Preoperative echocardiography showed a mean interventricular septal thickness of (18.1±3.8) mm, peak left ventricular outflow tract pressure difference of (86.4±24.9) mm Hg. The surgery time was (162.3±51.0) min, extracorporeal circulation time was (80.9±31.0) min, and aortic occlusion time was (44.8±20.8) min. After the surgery, transesophageal echocardiography showed that the interventricular septal thickness was (11.0±1.8) mm and left ventricular outflow tract peak pressure difference was (9.4±5.1) mm Hg. The incidence rate of postoperative complete left bundle branch block was 45.3%, Ⅲ° atrioventricular block was 3.8%, and postoperative newly developed atrial fibrillation was 3.1%. The postoperative hospital stay was (6.6±4.9) days, and one perioperative death occurred, with a mortality rate of 0.3%. The follow-up time was (10.3±9.4) months, during which the transthoracic echocardiography revealed a ventricular septal thickness of (12.9±2.9) mm and a peak left ventricular outflow tract pressure difference of (13.9±10.0) mm Hg. Conclusion The modified Morrow procedure for the treatment of hypertrophic obstructive cardiomyopathy is safe and effective, with good results in the short and medium term.
10.Network analysis of basic psychological needs and psychological behavioral problems among junior and senior high school students in Taizhou City
LIN Nan, LI Li, FU Chaowei, LIN Haijiang, YANG Yuting, LIU Yixuan, WANG Tingting, WANG Jingyi
Chinese Journal of School Health 2026;47(3):388-393
Objective:
To explore the network structure of middle school students basic psychological needs and psychological behavioral problems, and identify the core nodes within the network, as well as examine demographic subgroup differences, so as to provide support for targeted mental health interventions for adolescents.
Methods:
In September and October of 2023, a total of 2 000 junior and senior high school students were selected with multistage cluster random sampling from 8 schools in Jiaojiang District and Tiantai County, Taizhou City. An online self administered questionnaire was used to assess emotional and behavioral problems, perceived autonomy, self awareness, loneliness, and social support. The instruments included the Strengths and Difficulties Questionnaire (SDQ), Perceived Choice and Awareness of Self Scale (PCASS), Mental Health Literacy Questionnaire (MHLQ), University of California,Los Angeles Loneliness Scale (UCLA-LS), and the Multidimensional Scale of Perceived Social Support (MSPSS). A network analysis approach was employed to construct a network representing adolescents basic psychological needs and psychological behavioral problems, focusing on centrality measures and demographic subgroup differences.
Results:
A total of 418 students (20.9%) reported abnormal emotional and behavioral problems. Perceived autonomy and competence were negatively correlated with emotional problems (weights: 0.12, 0.14) and hyperactivity (weights: 0.10, 0.16). Social support showed negative correlation with peer relationship issues, hyperactivity, and conduct problems (weights: 0.16, 0.13, 0.10). Loneliness was positively correlated with emotional symptoms and peer relationship problems (weights: 0.28, 0.18). In the overall network, perceived relationships (social support and loneliness), emotional symptoms, and hyperactivity emerged as central nodes. Significant differences in network structure were observed between gender subgroups ( P =0.02). Girls internalizing issues were more influenced by loneliness and perceived autonomy frustration, while social support exhibited higher centrality in boys.
Conclusions
Perceived relationships, emotional problems, and hyperactivity are key nodes in the network of adolescents basic psychological needs and psychological behavioral problems. Loneliness demonstrates a prominent influence within the network, and the overall network exhibits gender differences.


Result Analysis
Print
Save
E-mail