We aimed to explore the protective effects and potential treatment mechanism of Epigallocatechin-3-gallate (EGCG) in an animal model of chronic exposure in a natural high-altitude hypoxia (HAH) environment. Behavioral alterations were assessed with the Morris water maze test. Iron accumulation in the hippocampus was detected by using DAB enhanced Perls’ staining, MRI, qPCR and colorimetry, respectively. Oxidative stress (malondialdehyde, MDA), apoptosis (Caspase-3), and neural regeneration (brain-derived neurotrophic factor, BDNF) were detected by using ELISA and western blotting. Neural ultrastructural changes were evaluated by transmission electron microscopy (TEM). The results showed that learning and memory performance of rats decreased when exposure to HAH environment. It was followed by iron accumulation, dysfunctional iron metabolism, reduced BDNF and the upregulation of MDA and Caspase-3. TEM confirmed the ultrastructural changes in neurons and mitochondria. EGCG reduced HAH-induced cognitive impairment, iron deposition, oxidative stress, and apoptosis and promoted neuronal regeneration against chronic HAH-mediated neural injury.
Objective We used radiomics feature–based machine learning classifiers of apparent diffusion coefficient (ADC) maps to differentiate small round cell malignant tumors (SRCMTs) and non-SRCMTs of the nasal and paranasal sinuses. Materials A total of 267 features were extracted from each region of interest (ROI). Datasets were randomized into two sets, a training set (∼70%) and a test set (∼30%). We performed dimensional reductions using the Pearson correlation coefficient and feature selection analyses (analysis of variance [ANOVA], relief, recursive feature elimination [RFE]) and classifications using 10 machine learning classifiers. Results were evaluated with a leave-one-out cross-validation analysis. Results We compared the AUC for all the pipelines in the validation dataset using FeAture Explorer (FAE) software. The pipeline using RFE feature selection and Gaussian process classifier yielded the highest AUCs with ten features. When the “one-standard error” rule was used, FAE produced a simpler model with eight features, including Perc.01%, Perc.10%, Perc.90%, Perc.99%, S(1,0) SumAverg, S(5,5) AngScMom, S(5,5) Correlat, and WavEnLH_s-2. The AUCs of the training, validation, and test datasets achieved 0.995, 0.902, and 0.710, respectively. For ANOVA, the pipeline with the auto-encoder classifier yielded the highest AUC using only one feature, Perc.10% (training/validation/test datasets: 0.886/0.895/0.809, respectively). For the relief, the AUCs of the training, validation, and test datasets that used the LRLasso classifier using five features (Perc.01%, Perc.10%, S(4,4) Correlat, S(5,0) SumAverg, S(5,0) Contrast) were 0.892, 0.886, and 0.787, respectively. Compared with the RFE and relief, the results of all algorithms of ANOVA feature selection were more stable with the AUC values higher than 0.800. Conclusions We demonstrated the feasibility of combining artificial intelligence with the radiomics from ADC values in the differential diagnosis of SRCMTs and non-SRCMTs and the potential of this non-invasive approach for clinical applications. Key Points • The parameter with the best diagnostic performance in differentiating SRCMTs from non-SRCMTs was the Perc.10% ADC value. • Results of all the algorithms of ANOVA feature selection were more stable and the AUCs were higher than 0.800, as compared with RFE and relief. • The pipeline using RFE feature selection and Gaussian process classifier yielded the highest AUC.
Purpose Doxorubicin-induced cardiotoxicity (DIC) is a common side effect of doxorubicin chemotherapy, and a major mechanism of DIC is inflammation. However, no effective method exists to prevent DIC. In the present study, we investigated the cardioprotective effects of nicorandil against DIC using multiparametric cardiac magnetic resonance (CMR) imaging and elucidated the anti-inflammatory properties of nicorandil in rat models. Methods Male Sprague-Dawley rats received four weekly intraperitoneal doxorubicin doses (4 mg/kg/injection) to establish the DIC model. After treatment with or without nicorandil (3 mg/kg/day) or diazoxide (10 mg/kg/day) orally, all the groups underwent weekly CMR examinations, including cardiac function and strain assessment and T2 mapping, for 6 weeks. Additionally, blood samples and hearts were collected to examine inflammation and histopathology. Results According to our results, the earliest DIC CMR parameter in the doxorubicin group was T2 mapping time prolongation compared with the DIC rats treated with nicorandil (doxorubicin+nicorandil group) at week 2. Subsequently, the left ventricular ejection fraction (LVEF) and global peak systolic myocardial strain in the doxorubicin group were significantly reduced, and nicorandil effectively inhibited these effects at week 6. Our results were confirmed by histopathological evaluations. Furthermore, nicorandil treatment had a protective effect against the doxorubicin-induced inflammatory response. Interestingly, similar protective results were obtained using the KATP channel opener diazoxide. Conclusion Collectively, our findings indicate that nicorandil application ameliorates DIC in rats with significantly higher cardiac function and myocardial strain and less fibrosis, apoptosis and inflammatory cytokine production. Nicorandil prevents T2 abnormalities in the early stages of DIC, showing a high clinical value for early nicorandil treatment in chemotherapy patients.
AimsThis study aims to assess left ventricular (LV) function in hypertrophic cardiomyopathy (HCM) patients with preserved left ventricular ejection fraction (LVEF) by LV strain patterns based on cardiac magnetic resonance feature tracking (CMR-FT) and to explore the relationships between LV strain patterns and cardiac biomarkers in these patients, such as cardiac troponin (cTnT) and N-terminal prohormone of the brain natriuretic peptide (NT-proBNP).MethodsA total of 64 HCM patients with preserved LVEF and 33 healthy people were included in this study. All subjects underwent contrast-enhanced CMR, and all patients took blood tests for cTnT and NT-proBNP during hospitalization.ResultsDespite the absence of a significant difference in LVEF between HCM patients and healthy controls, almost all global and segmental strains in radial, circumferential, and longitudinal directions in the HCM group deteriorated significantly as compared to controls (p < 0.05). Moreover, some global and segmental strains correlated significantly with NT-proBNP and cTnT in HCM patients, and the best correlations were global radial strain (GRS) (r = −0.553, p < 0.001) and mid-ventricular radial strain (MRS) (r = −0.582, p < 0.001), respectively, with a moderate correlation. The receiver operating characteristic (ROC) results showed that among the LV deformation parameters, GRS [area under the curve (AUC), 0.76; sensitivity, 0.49; specificity, 1.00], MRS (AUC, 0.81; sensitivity, 0.77; specificity, 0.79) demonstrated greater diagnostic accuracy to predict elevated NT-proBNP, and abnormal cTnT, respectively. Their cut-off values were 21.17 and 20.94%, respectively. Finally, all global strains demonstrated moderate, good, and excellent intra- and inter-observer reproducibility.ConclusionLV strain patterns can be used to assess the subclinical cardiac function of HCM patients on the merit of being more sensitive than LVEF. In addition, LV strain patterns can detect serious HCM patients and may be helpful to non-invasively predict elevated NT-proBNP and cTnT.
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