Objective:To construct a model of mitochondria-related genes (Mito-RGs) in hepatocellular carcinoma (HCC), and predict the immune, prognostic and therapeutic characteristics of HCC based on the model, so as to provide a new idea for the diagnosis and treatment of HCC.Methods:The expression profiles of HCC and corresponding clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression were used to construct a prognostic model of HCC based on Mito-RGs, and the International Cancer Genome Consortium-Liver Cancer-RIKEN-Japan ICGC-LIRI-JP dataset were used for validation. GO and KEGG analyses were performed to investigate the signaling pathways enriched for differentially expressed genes in the high- and low-risk groups. Immune infiltration was assessed using CIBERSORT. Single-cell data were used to study the proportion of immune cells in high- and low-risk groups of HCC samples and the relationship with cell proliferation. Cellminer was used to assess the relationship between risk score models and drug sensitivity.Results:A risk-prognostic model of HCC containing seven Mito-RGs ( DTYMK, ACADS, HMGCS2, CYP27A1, TOMM40L, STOM, and AKR1B10) was constructed. High-risk HCC patients had a worse prognosis. Genes upregulated in the high- and low-risk groups of differentially expressed genes were enriched in cell cycle and metabolism-related pathways. Single-cell data showed higher proportions of CD8 + T cells, macrophages and monocytes, and proliferating cells in the high-risk group. CIBERSORT analysis suggested that Treg cells and M0 macrophages were more abundant in the high-risk group, whereas CD8 + T cells and CD4 + memory T cells were less abundant. Patients in the high-risk group were more sensitive to myeloid cell leukemia sequence 1 inhibitor, vincristine, phosphatidylinositol kinase beta subunit inhibitor, and aurora kinase A, while trametinib, selumetinib, extracellular regulated protein kinase, and mitogen-activated extracellular signal-regulated kinase were more effective in the low-risk group. Conclusion:The constructed Mito-RGs model is capable of providing a more accurate assessment of the prognosis and the degree of immune cell infiltration in HCC patients.

Objective:To investigate the temporal expression of Growth Differentiation Factor-15 (GDF15) in the serum of patients with Acute Coronary Syndrome (ACS) and explore the clinical significance of GDF15 in protecting cardiomyocytes in ACS.Methods:A retrospective study was conducted on 289 ACS patients admitted to the emergency departments from February to October 2023. Data on gender, age, troponin T (TnT), creatine kinase isoenzyme (CK-MB), GDF15, and B-type natriuretic peptide (BNP) within 30 minutes of admission were recorded. Differences in these indicators among different groups were compared. Receiver Operating Characteristic (ROC) curves were plotted to evaluate the diagnostic value of GDF15, TnT, and BNP for ACS. Among the patients, 15 exhibited a temporal expression pattern of GDF15, and their blood samples were re-measured using a GDF15 fluorescent quantitative immunochromatographic assay kit. Fifteen patients without temporal expression were randomly selected as controls, and their samples were also re-measured to exclude detection errors. Fifteen patients with temporal expression were included in the temporal expression group, and 15 without temporal expression were included in the non-temporal expression group. Laboratory indicators such as fasting blood glucose, glycated hemoglobin, triglycerides, creatinine, and uric acid were compared between the groups. Additionally, patient age, gender, body mass index (BMI), coronary angiography results, echocardiography, Gensini score, left ventricular ejection fraction (LVEF), and GRACE risk score were recorded to assess their correlation with GDF15 temporal expression. Statistical analysis was performed using SPSS 27 software, with continuous data expressed as mean ± standard deviation (Mean ± SD) and compared using t-tests and χ2 tests. Results:The overall trend in ACS patients showed a higher proportion of males than females (73.36% vs. 26.64%). The oldest group was the Unstable Angina (UA) group, with a mean age of (63.98 ± 15.19) years, while the youngest group was the non-ACS chest pain group, with a mean age of (54.29 ± 16.39) years. A higher proportion of patients in the UA, ST-segment elevation myocardial infarction (STEMI), and non-ST-segment elevation myocardial infarction (NSTEMI) groups had a history of smoking. The combination of GDF15 and TnT showed high diagnostic value for ACS, with an area under the ROC curve (AUC) of 0.843, consistent with previous studies. Among all ACS patients, 15 exhibited a temporal expression pattern of GDF15, where GDF15 levels peaked at 4 hours, gradually decreased, and peaked again at 24 hours. Patients in the temporal expression group had higher LVEF and left ventricular end-systolic diameter compared to the non-temporal expression group. The Gensini score was lower in the temporal expression group, and the GRACE risk score was significantly lower in the temporal expression group (00.7±14.72) compared to the non-temporal expression group (116.1±23.46), with a statistically significant difference ( P = 0.0115). There were no significant differences in general characteristics (age, gender, BMI) or clinical biochemical indicators (fasting blood glucose, glycated hemoglobin, triglycerides, total cholesterol, high-density lipoprotein, low-density lipoprotein, creatinine, uric acid) between the temporal and non-temporal expression groups ( P > 0.05). Conclusions:GDF15 demonstrates significant diagnostic and prognostic predictive value in ACS. Patients with temporally dynamic expression of serum GDF15 exhibit milder myocardial injury and a lower probability of mortality. These findings provide novel therapeutic targets and research directions for further exploring the role of GDF15 in ACS management.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Purpose To develop a nomogram based on contrast-enhanced CT and habitat analysis for predicting early recurrence after thermal ablation in hepatocellular carcinoma,enabling risk stratification and personalized patient management.Materials and Methods This retrospective study included 107 patients with hepatocellular carcinoma treated with thermal ablation from Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital from January 2016 to March 2022.Tumor lesions were manually segmented on preoperative contrast-enhanced CT images.Habitat encoding was performed on volumes of interest using K-means clustering.Radiomic features were extracted from each phase and habitat subregion.Machine learning algorithms were used to construct phase-specific models,with performance compared to select the optimal model.A combined model integrating optimal radiomic features and independent clinical risk factors was developed and evaluated.Results The Adaboost algorithm yielded the optimal model for the arterial phase,Naive Bayes for the venous phase,and MLP for the combined arterial-venous phase.The combined model demonstrated superior performance,achieving concordance indices of 0.711(training cohort)and 0.709(validation cohort)for predicting early recurrence.Significant differences in recurrence-free survival were observed between high-risk group and low-risk group(log-rank P<0.05).Conclusion Habitat imaging derived from contrast-enhanced CT effectively and noninvasively assesses recurrence-free survival after thermal ablation for hepatocellular carcinoma,demonstrating potential for guiding clinical treatment and decision-making.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Purpose To develop a nomogram based on contrast-enhanced CT and habitat analysis for predicting early recurrence after thermal ablation in hepatocellular carcinoma,enabling risk stratification and personalized patient management.Materials and Methods This retrospective study included 107 patients with hepatocellular carcinoma treated with thermal ablation from Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital from January 2016 to March 2022.Tumor lesions were manually segmented on preoperative contrast-enhanced CT images.Habitat encoding was performed on volumes of interest using K-means clustering.Radiomic features were extracted from each phase and habitat subregion.Machine learning algorithms were used to construct phase-specific models,with performance compared to select the optimal model.A combined model integrating optimal radiomic features and independent clinical risk factors was developed and evaluated.Results The Adaboost algorithm yielded the optimal model for the arterial phase,Naive Bayes for the venous phase,and MLP for the combined arterial-venous phase.The combined model demonstrated superior performance,achieving concordance indices of 0.711(training cohort)and 0.709(validation cohort)for predicting early recurrence.Significant differences in recurrence-free survival were observed between high-risk group and low-risk group(log-rank P<0.05).Conclusion Habitat imaging derived from contrast-enhanced CT effectively and noninvasively assesses recurrence-free survival after thermal ablation for hepatocellular carcinoma,demonstrating potential for guiding clinical treatment and decision-making.

Objective:To construct a model of mitochondria-related genes (Mito-RGs) in hepatocellular carcinoma (HCC), and predict the immune, prognostic and therapeutic characteristics of HCC based on the model, so as to provide a new idea for the diagnosis and treatment of HCC.Methods:The expression profiles of HCC and corresponding clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression were used to construct a prognostic model of HCC based on Mito-RGs, and the International Cancer Genome Consortium-Liver Cancer-RIKEN-Japan ICGC-LIRI-JP dataset were used for validation. GO and KEGG analyses were performed to investigate the signaling pathways enriched for differentially expressed genes in the high- and low-risk groups. Immune infiltration was assessed using CIBERSORT. Single-cell data were used to study the proportion of immune cells in high- and low-risk groups of HCC samples and the relationship with cell proliferation. Cellminer was used to assess the relationship between risk score models and drug sensitivity.Results:A risk-prognostic model of HCC containing seven Mito-RGs ( DTYMK, ACADS, HMGCS2, CYP27A1, TOMM40L, STOM, and AKR1B10) was constructed. High-risk HCC patients had a worse prognosis. Genes upregulated in the high- and low-risk groups of differentially expressed genes were enriched in cell cycle and metabolism-related pathways. Single-cell data showed higher proportions of CD8 + T cells, macrophages and monocytes, and proliferating cells in the high-risk group. CIBERSORT analysis suggested that Treg cells and M0 macrophages were more abundant in the high-risk group, whereas CD8 + T cells and CD4 + memory T cells were less abundant. Patients in the high-risk group were more sensitive to myeloid cell leukemia sequence 1 inhibitor, vincristine, phosphatidylinositol kinase beta subunit inhibitor, and aurora kinase A, while trametinib, selumetinib, extracellular regulated protein kinase, and mitogen-activated extracellular signal-regulated kinase were more effective in the low-risk group. Conclusion:The constructed Mito-RGs model is capable of providing a more accurate assessment of the prognosis and the degree of immune cell infiltration in HCC patients.

Objective To explore the application effect of family-community-hospital linked care in patients with chronic hepatitis B. Methods A total of 118 patients with chronic hepatitis B were selected and randomly divided into control group and observation group using a random number table method, with 59 patients in each group. The control group received routine health education, while the observation group received family-community-hospital ternary linked care on the basis of the control group received family-community-hospital linked care. The social support, treatment adherence, quality of life, and fear of disease progression between the two groups were compared before intervention and 2 months after the intervention. Results Two months after the intervention, the scores of the Social Support Rating Scale (SSRS), the Treatment Adherence Scale for chronic hepatitis B patients, and the Chronic Liver Disease Questionnaire (CLDQ) increased in both groups compared with those before the intervention, and the above scores were higher in the observation group than in those in the control group (P < 0.05). The scores of social family and physical health on the Fear of Progression Questionnaire-Short Form (FoP-Q-SF) decreased in both groups compared with those before the intervention, and the scores were lower in the observation group than those in the control group (P < 0.05). Conclusion Family-community-hospital linked care can improve social support, treatment adherence, and quality of life in patients with chronic hepatitis B and alleviate their fear of the disease.

Objective:To compare the image quality and the diagnostic efficiency for breast malignant lesions using simultaneous multi-slice single shot echo planar imaging (SMS+SS-EPI) and readout segment of long variable echo trains (RESOLVE) for breast diffusion-weighted imaging (DWI).Methods:This study was a cross-sectional study. Clinical and imaging data of 102 patients with breast lesion from March 2021 to February 2023 in the First Hospital Affiliated to Ningbo University were prospectively analyzed. All patients underwent routine breast MRI scans and cross-sectional RESOLVE and SMS+SS EPI sequence DWI, and the image quality of 2 types sequences of DWI was evaluated. The subjective evaluation was based on a 5-point scale, including geometric distortion, artifact blurring, fat suppression, overall image quality, and lesion conspicuity of the breast. The objective evaluation included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) value of the lesion. Wilcoxon signed rank sum test was used to compare the subjective and objective parameters between the two sequences. Finally, the receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the effectiveness of ADC values for diagnosing breast malignant lesions based on two sequence images.Results:All 102 female patients had single lesions, aged from 25 to 68 years and 60 lesions were malignant and 42 were benign. The acquisition time for SMS+SS-EPI sequence imaging was 1 min 50 s, and the acquisition time for RESOLVE sequence imaging was 3 min 43 s.The subjective scores from both SMS+SS-EPI and RESOLVE sequence were over than 3 points. The geometric distortion, artifact blurring, and overall image quality scores of RESOLVE sequence images were higher than those of SMS+SS-EPI (all P<0.001). The overall lesion conspicuity score, malignant lesion conspicuity score, and benign lesion conspicuity score of DWI and ADC images combined with SMS+SS-EPI sequence were higher than those of the RESOLVE sequence (all P<0.05). There were no statistically difference in SNR, CNR, overall ADC value, malignant ADC value, and benign ADC value between SMS+SS-EPI and RESOLVE sequence DWI images of breast lesions (all P>0.05). The AUC of RESOLVE sequence ADC value in diagnosis of breast cancer was 0.973, the sensitivity was 0.929, and the specificity was 0.915; The AUC of SMS+SSC-EPI sequence ADC value in diagnosis of breast cancer was 0.956, the sensitivity was 0.977, and the specificity was 0.850. Conclusions:In breast DWI, the subjective score of SMS+SS EPI image quality can basically meet the diagnostic requirements and the conspicuity of lesions is better than that of the RESOLVE sequence. Both have good diagnostic efficacy for malignant breast lesions.

Endo-periodontal lesions(EPLs)involve both the periodontium and pulp tissue and have complicated etiologies and pathogenic mechanisms,including unique anatomical and microbiological characteristics and multiple contributing factors.This etiological complexity leads to difficulties in determining patient prognosis,posing great challenges in clinical practice.Furthermore,EPL-affected teeth require multidisciplinary therapy,including periodontal therapy,endodontic therapy and others,but there is still much debate about the appropriate timing of periodontal therapy and root canal therapy.By compiling the most recent findings on the etiology,pathogenesis,clinical characteristics,diagnosis,therapy,and prognosis of EPL-affected teeth,this consensus sought to support clinicians in making the best possible treatment decisions based on both biological and clinical evidence.