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Machine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors' intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806-0.811), accuracy: 0.815 (0.812-0.818), precision: 0.840 (0.835-0.845), and F1 score of XGBoost: 0.843 (0.840-0.845) and recall of SVM: 0.991 (0.988-0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies., (© 2022. The Author(s).)

Bushen-Tiaojing-Fang (BSTJF) is commonly used to treat infertility. This study investigated the effects of BSTJF on the pregnancy outcomes of patients with repeated controlled ovarian stimulation (COS), on mitochondrial function, and on oxidative stress in ovarian granulosa cells (GCs) and follicular fluid (FF). The samples and clinical data of 97 patients, including 35 in the control group, 29 in the placebo group and 33 in the BSTJF group, were collected for this study. The mitochondrial ultrastructure, ATP content, mitochondrial DNA (mtDNA) number, 8-hydroxy-2-deoxyguanosine (8-OHdG), Mn-superoxide dismutase (Mn-SOD), glutathione peroxidase (GSH-Px) activity levels, and mRNA expression levels of Mn-SOD, GSH-Px, and nuclear factor erythroid-derived factor 2-related factor 2 (Nrf2) were analyzed. The high-grade embryo (P < 0.001), implantation (P = 0.033), and clinical pregnancy (P = 0.031) rates, as well as the ATP content (P = 0.014), mtDNA number (P = 0.035), GSH-Px activity (P = 0.004 in GCs and P = 0.008 in FF) and mRNA expression levels (P = 0.019), were significantly lower in the placebo group than in the control group, whereas the 8-OHdG content was significantly (P = 0.006 in FF) higher in the placebo group than in the control group. Compared with those in the placebo group, the high-grade embryo rate (P = 0.007), antioxidant enzyme activity (P = 0.037 and 0.036 in Mn-SOD; P = 0.047 and 0.030 in GSH-Px) and mRNA level (P < 0.001 in Nrf2, P = 0.039 in Mn-SOD and P = 0.002 in GSH-Px) were significantly higher in the BSTJF group, as were changes in mitochondrial ultrastructure, ATP (P = 0.040) and mtDNA number (P = 0.013). In conclusion, BSTJF can improve oxidative stress in patients with repeated COS and pregnancy outcomes., (© 2021. The Author(s).)

The clinical epidemiological features of cognitive impairment in Chinese older adult patients undergoing hemodialysis are not clear, we aimed to identify the extent and patterns of cognitive impairment among those patients. We conducted a cross-sectional study of 613 hemodialysis patients aged 50 to 80 from 11 centers in Beijing. A neuropsychological battery of 11 tests covering domains of attention/processing speed, executive function, memory, language, and visuospatial function was applied, patients were classified as none, mild, or major cognitive impairment according to the fifth version of the Diagnostic and Statistical Manual of Mental Disorders criteria for cognitive impairment. Compared with Chinese population norms, 37.2% of the participants had mild cognitive impairment, 43.7% had major cognitive impairment. Memory and language were the most severe impaired domains in the mild cognitive impairment group, attention and visuospatial function domains were the most serious impaired domains in the major cognitive impairment group. Concomitant impairment across multiple cognitive domains was common. Factors associated with major cognitive impairment included age, education level, history of stroke and hypertension, dialysis vintage, and single-pool Kt/V. There is a high frequency of cognitive impairment in Chinese older adult hemodialysis patients, with varying severity and concomitant impairment across multiple domains.

Metabolic disorders, such as obesity and type 2 diabetes, are associated with an increased risk of cardiomyopathy. To date, microRNA (miRNAs) functions in cardiac remodeling induced by obesity remain to be elucidated. We found that rats fed a high fat diet (HFD) manifested cardiac fibrosis and LV dysfunction. In the heart of rats fed HFD, the phosphorylation levels of Smad 2 and the expression of fibrotic genes, such as connective tissue growth factor, collagen-1α1 (Col1α1), Col3α1, and Col4α1, were up-regulated, which accompanied by an increase in Smad 7 protein levels, but not its mRNA levels. Using miRNA microarray analysis, we showed that the miRNA miR-410-5p inhibited the protein expression of Smad 7, thus increasing the phosphorylation levels of Smad 2. Overexpression of miR-410-5p promoted cardiac fibrosis in rats fed normal diet, whereas inhibition of miR-410-5p by way of miR-410-5p antimiR suppressed cardiac fibrosis in rats fed HFD. Finally, our data revealed that miR-410-5p from the kidney and adipose tissues was probably transferred to heart to induce cardiac fibrosis. Taken together, our study characterizes an endocrine mechanism in which adipose- or kidney-derived circulating miR-410-5p regulates metabolic disorders-mediated cardiac remodeling by activating the TGFβ/Smad signaling in heart.

Animals often experience periods of nutrient deprivation; however, the molecular mechanisms by which animals survive starvation remain largely unknown. In the nematode Caenorhabditis elegans, the nuclear receptor DAF-12 acts as a dietary and environmental sensor to orchestrate diverse aspects of development, metabolism, and reproduction. Recently, we have reported that DAF-12 together with co-repressor DIN-1S is required for starvation tolerance by promoting fat mobilization. In this report, we found that genetic inactivation of the DAF-12 signaling promoted the production of reactive oxygen species (ROS) during starvation. ROS mediated systemic necrosis, thereby inducing organismal death. The DAF-12/DIN-1S complex up-regulated the expression of antioxidant genes during starvation. The antioxidant enzyme GST-4 in turn suppressed ROS formation, thereby conferring worm survival. Our findings highlight the importance of antioxidant response in starvation tolerance and provide a novel insight into multiple organisms survive and adapt to periods of nutrient deprivation.