Purpose.: To determine the prevalence and associations of myopia in schoolchildren in provincial Western China. Methods.: In the school-based observational cross-sectional Gobi Desert Children Eye Study, cylcoplegic refractometry as part of a comprehensive ophthalmic examination was performed in all schools in the oasis region of Ejina. Out of 1911 eligible children, 1565 (81.9%) children with a mean age of 11.9 ± 3.5 years (range, 6–21 years) participated. Results.: The mean refractive error in the worse eye was −1.38 ± 2.04 diopters (D) (median, −0.88 D; range, −13.00 to +6.50 D). In multivariate analysis, more myopic refractive errors were associated with older age (P < 0.001; regression coefficient B: −0.26; 95% confidence interval [CI]: −0.28, −0.23), female sex (P = 0.005; B: −0.26; 95%CI: −0.43, −0.08), more myopic paternal refractive errors (P < 0.001; B: 0.20; 95%CI: 0.14, 0.27), more myopic maternal refractive errors (P < 0.001; B: 0.18; 95%CI: 0.12, 0.24), and fewer hours spent outdoors (P = 0.038; B: 0.18; 95%CI: 0.01, 0.35). The prevalence of myopia, defined as refractive errors (spherical equivalent) of ≤−0.50, ≤−1.00, and ≤−6.00 D in the worse eye, was 60.0 ± 1.2%, 48.0 ± 1.3%, and 2.9 ± 0.4%, respectively. The prevalence of high myopia (≤−6.00 D) was 2.9 ± 0.4% in the whole study population, and it was 9.9 ± 3.0% in 17-year-olds. It was not associated with time spent outdoors (P = 0.66). Conclusions.: Even in Western China, prevalence of myopia in schoolchildren is high. As in East China, low and medium myopia was associated with less time spent outdoors. High myopia was not significantly associated with outdoors time. Compared with the myopia prevalence in elderly Chinese populations, the relatively high myopia prevalence in schoolchildren in China predicts a marked increase in vision-threatening high myopia in future elderly populations in China.
Objectives . To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki‐67 expression in breast cancers. Methods . The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki‐67 were analysed using Spearman’s correlation analysis. Results . Of the 189 breast lesions included, there were significant differences in patient age ( P < 0.001) and lesion size ( P = 0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER‐2) status (both P = 0.001) and estrogen receptor (ER)/progesterone receptor (PR) status ( P = 0.020 and P = 0.041, respectively). Among all breast cancer lesions, 35 tumours in the low‐proliferation group (Ki − 67 < 14 % ) and 70 tumours in the high‐proliferation group (Ki − 67 ≥ 14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki‐67 status ( P = 0.007 and P < 0.001, respectively), and there were weak correlations between ADC entropy ( r = 0.383) and skewness ( r = 0.209) and the Ki‐67 index. Conclusion . The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.
Allicin, naturally present in the bulbs of the lily family, has anticancer, blood pressure lowering, blood fat lowering and diabetes improving effects. Recent studies have shown that allicin promotes the browning of white adipocytes and reduces the weight gain of mice induced by high-fat diet. While the gut microbiota has a strong relationship with obesity and energy metabolism, the effect of allicin on weight loss via gut microorganisms is still unclear. In this study, we treated obese mice induced by high-fat diet with allicin to determine its effects on fat deposition, blood metabolic parameters and intestinal morphology. Furthermore, we used high-throughput sequencing on a MiSeq Illumina platform to determine the gut microorganisms' species. We found that allicin significantly reduced the weight gain of obese mice by promoting lipolysis and thermogenesis, as well as blood metabolism and intestinal morphology, and suppressing hepatic lipid synthesis and transport. In addition, allicin changed the composition of the intestinal microbiota and increased the proportion of beneficial bacteria. In conclusion, our study showed that allicin improves metabolism in high-fat induced obese mice by modulating the gut microbiota. Our findings provide a theoretical basis for further elucidation of the weight loss mechanism of allicin.
Background: Atrial fibrillation (AF) is the most prevalent form of arrhythmia and poses significant health risks, of which the primary diagnostic tool is electrocardiogram (ECG); however, the manual review of ECG results is time-consuming and demands considerable effort from physicians.Methods: We collected ECG data from 6,590 heart failure patients as YY2023, classified as Normal, AF, and Other, and then preprocessed with mean normalization and wavelet transform, among others. Convolutional Neural Network (CNN), bidirectional Long Short-Term Memory (LSTM), and Attention construct the AF recognition model CNN LSTM Attention-Atrial Fibrillation (CLA-AF). The model performance is mainly evaluated using F1-score, Precision, and AUC. The generalization ability of the proposed model is then validated on public datasets CPSC2018, PhysioNet2017, and PTB-XL. Finally, the effects of oversampling, resampling, and hybrid datasets on model generalization performance are explored.Results: The F1-score, Precision, and AUC of the CLA-AF model on YY2023 are 0.956, 0.970, and 1.00, respectively. Similarly, the AUC on CPSC2018, PhysioNet2017, and PTB-XL reached above 0.95, demonstrating its strong generalization ability. After oversampling PhysioNet2017, F1-score and Recall improved by 0.156 and 0.260. The sampling frequency also has a significant influence on generalization ability. The model trained from the hybrid dataset has the most robust generalization ability, achieving an AUC of 0.96 or more on each test set.Conclusions: The developed CLA-AF model effectively identifies AF in ECG with robust generalization capabilities. This model serves as a valuable tool for AF detection in ECG and establishes an algorithmic framework and research avenues for precise treatment and risk prediction in patients with AF.
Background In the future, biochemical MRI might provide a valuable noninvasive quantitative analysis of the biochemical composition of cartilage in osteonecrosis of the femoral head (ONFH). Purpose To investigate the diagnostic performance of T 1 ρ and T 2 mapping in cartilage denaturalization with ONFH and to determine the correlation between T 1 ρ and T 2 mapping and the Association Research Circulation Osseous (ARCO) stage. Study Type Prospective. Subjects Forty‐seven patients with ONFH (stage I to III according to the ARCO criteria) and 24 volunteers (control group) were recruited for the prospective study. Sequence Conventional MRI, multiple echo recalled gradient echo (MERGE), and T 1 ρ and T 2 mapping sequences. Assessment Pseudocolor images and MERGE images were combined in the AW4.5 workstation. The region of interest (ROI) of the hip cartilage was 4–6 mm². The sagittal T 1 ρ and T 2 mapping values were calculated by the two first authors. Statistical Tests One‐way analysis of variance (ANOVA), LSD t ‐tests, Pearson correlation analysis, and receiver operator characteristic (ROC) curves. The significance level was set at P < 0.05. Results The T 1 ρ and T 2 mapping values of the ONFH group were significantly higher than the values of the control group ( P = 0.000). Regarding the assessment of the severity of ARCO staging, both T 1 ρ ( r = 0.66, P = 0.004) and T 2 mapping ( r = 0.501, P = 0.002) were positively associated with disease severity. The T 1 ρ values were positively correlated with the T 2 mapping values ( r = 0.381, P = 0.000). The areas under the curve (AUC) for the T 1 ρ and T 2 mapping values were 0.822 and 0.791, respectively. The diagnostic sensitivity and specificity were 72.34% and 70.83% for T 1 ρ mapping and 72.34% and 58.33%, respectively, for T 2 mapping. Data Conclusion Both T 1 ρ and T 2 mapping performed well in diagnosing the cartilage denaturalization in ARCO stage I‐III ONFH patients. T 1 ρ mapping had a higher diagnostic sensitivity and specificity than T 2 mapping. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:760–767.
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