In order to improve the efficiency of the recycling of the electric vehicle power batteries and reduce the recycling cost, it is of great importance to select an optimal power battery recycling mode. In this paper, an extended MULTIMOORA (Multiobjective Optimization by Ratio Analysis plus full Multiplicative form) approach which combines with the two-dimension uncertain linguistic variables (TDULVs) and the regret theory, called TDUL-RT-MULTIMOORA method, is developed for solving the power battery recycling mode decision-making (PBRMDM) problem. Firstly, the evaluations of the power battery recycling modes over criteria are given by the experts using the TDULVs, and the evaluations of all experts are aggregated into a group linguistic decision matrix by the TDULDWA operator. On the basis of the regret theory, the perceived utility decision matrix is constructed. And then, in order to avoid the disadvantages of the subjective weighting methods, such as the deviation from the measured data and the dependence on the experience and knowledge of the experts, an objective entropy weighting method is applied. After that, the MULTIMOORA method is introduced to rank the power battery recycling modes. In the end, an illustrative example is given to verify the effectiveness and practicability of the proposed method.

Background Preeclampsia (PE) prediction has been shown to improve the maternal and fetal outcomes in pregnancy. We aimed to evaluate the PE prediction values of a series of serum biomarkers. Methods The singleton pregnant women (20–36 gestational weeks) with PE‐related clinical and/or laboratory presentations were recruited and had the blood drawn at their first visits. The following markers were tested with the collected serum samples: soluble fms‐like tyrosine kinase 1 (sFlt‐1), placental growth factor (PlGF), thrombomodulin (TM), tissue plasminogen activator inhibitor complex (tPAI‐C), complement factors C1q, B, H, glycosylated fibronectin (GlyFn), pregnancy‐associated plasma protein‐A2 (PAPP‐A2), blood urea nitrogen (BUN), creatinine (Cre), uric acid (UA), and cystatin C (Cysc). Results Of the 196 recruited subjects, 25% (n = 49) developed preeclampsia before delivery, and 75% remained preeclampsia negative (n = 147). The serum levels of sFlt‐1, BUN, Cre, UA, Cysc, and PAPP‐A2 were significantly elevated, and the PlGF level was significantly decreased in the preeclampsia‐positive patients. In the receiver operating characteristics (ROC) analyses, the area under the curves were listed in the order of decreasing values: 0.73 (UA), 0.67 (sFlt‐1/PlGF), 0.66 (Cysc), 0.65 (GlyFn/PlGF), 0.64 (PAPP‐A2/PlGF), 0.63 (BUN), 0.63 (Cre), and 0.60 (PAPP‐A2). The positive predictive values of these serum markers were between 33.1% and 58.5%, and the negative predictive values were between 80.9% and 89.5%. Conclusions The serum markers investigated in current study showed better performance in ruling out than ruling in PE. Absence of pre‐defined latency period between blood draw and the onset of PE limits the clinical utility of these markers.

Background Early preeclampsia (PE) prediction has been shown to improve the maternal and fetal outcomes in pregnancy. We aimed to evaluate the PE prediction values of a series of serum biomarkers. Methods The singleton pregnant women with PE-related clinical and/or laboratory presentations were recruited and had the blood drawn at their first visits. The prospective cohort was further divided into the PE-positive and PE-negative groups based on the follow-up results. The following markers were tested with the collected serum samples: sFlt-1, PlGF, M, tPAI-C, compliment factors C1q, B, H, BUN, GlyFn, PAPP-A2, BUN, Cre, UA and Cysc. Results Totally 196 women suspected for PE were recruited with follow-up medical records. Twenty-five percent of the recruited subjects developed PE before delivery and 75% remained PE-negative. The serum levels of sFlt-1, BUN, Cre, UA, Cysc and PAPP-A2 were significantly elevated and the PlGF was significantly decreased in the PE-positive patients. The AUCs were listed in the order of decreasing values: UA (AUC = 0.73), sFlt-1/PlGF (AUC = 0.67), Cysc (AUC = 0.66), GlyFn/PlGF (AUC = 0.65), PlGF (AUC = 0.64), PAPP-A2/PlGF (AUC = 0.64), sFlt-1 (AUC = 0.63), BUN (AUC = 0.63), Cre (AUC = 0.63), and PAPP-A2 (AUC = 0.60) in the ROC analyses. The Logistic regression analysis showed that UA and PAPP-A2 were independent risk factors for PE development with the odds ratios of 3.3 and 2.2 respectively. Moreover, the PPVs of UA and PAPP-A2 were 48.9%, and 40.4%; the NPVs of UA and PAPP-A2 were 82.1% and 81.9%. Conclusions Further studies are warranted to confirm the clinical utilities of the serum markers in PE prediction.

Objective The purpose of this study was to evaluate the diagnostic performance of the following hemostatic markers in hypertensive disorder of pregnancy (HDP): tissue-type plasminogen activator and inhibitor-1 complex (tPAI-C), thrombomodulin, thrombin-antithrombin complex, plasmin inhibitor-plasmin complex, D-dimer, and fibrinogen degradation products. Methods A total of 311 individuals diagnosed with HDP and 187 healthy controls (HC) of matched gestational age were admitted, including 175 subjects with gestational hypertension, 94 with mild preeclampsia, and 42 with severe preeclampsia. Results Compared with those of the HC group, the plasma concentrations of all the hemostatic markers continuously increased with the clinical severity of the hypertensive disorder, regardless of their statistical significance. In the receiver operating characteristic analysis, tPAI-C displayed the best discrimination performance. Conclusion The tPAI-C level was consistently and significantly elevated across the different HDP groups when compared with the HC group, suggesting aggravated fibrinolysis disorder increasing with the severity of the HDP.

Background: Coronary artery disease (CAD) is a common cardiovascular disease that has attracted attention worldwide due to its high morbidity and mortality. Recent studies have shown that abnormal microRNA (miRNA) expression is effective in CAD diagnoses and processes. However, the potential relationship between miRNAs and CAD remains unclear.Methods: Microarray datasets GSE105449 and GSE28858 were downloaded directly from the Gene Expression Omnibus (GEO) to identify miRNAs involved in CAD. Target gene prediction and enrichment analyses were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).Results: There were nine differentially expressed miRNAs in CAD patients compared to the controls. A total of 352 genes were predicted and subjected to GO analysis, which showed that differentially expressed genes (DEGs) were mainly associated with axon guidance, neuron projection guidance, neuron-to-neuron synapses, and postsynaptic density. According to the KEGG pathway analysis, the most enriched pathways were those involved in transcriptional misregulation in cancer, growth hormone synthesis, secretion and action, endocrine resistance, axon guidance, and Cushing syndrome. Pathway analysis was mainly involved in the HIPPO and prion disease signaling pathways. Furthermore, a competing endogenous RNA (ceRNA) interaction network centered on miR-22-3p revealed eight related transcription factors in the cardiovascular system. The receiver operating characteristic (ROC) curve analysis suggested that miR-22-3p may be a better CAD predictor.Conclusion: The results indicate that miR-22-3p may function in pathophysiological CAD processes. Our study potentiates miR-22-3p as a specific biomarker for diagnosing CAD.