Objective Determining the prognoses of patients with acute ischemic stroke is difficult. Therefore, the aim of this study was to evaluate whether the combined assessment of plasma N-terminal pro-brain natriuretic peptide (NT-pro-BNP) and the National Institutes of Health Stroke Scale (NIHSS) variables is relevant to the prognosis of patients with acute cerebral ischemic infarction in-hospital. Methods We enrolled 122 patients who were within three days of onset of acute ischemic stroke. We measured the plasma NT-pro-BNP level of each patient within 72 hours and recorded the NIHSS score on admission. The factors associated with death were investigated using a multivariate logistic regression analysis. Results Twenty-three patients (18.85%) died during hospitalization. The frequency of atrial fibrillation (AF), the NIHSS score on admission (8.69±4.87 in the survival group vs. 14.48±2.54 in the deceased group, p<0.001) and the plasma NT-pro-BNP level (median: 926.30 pg/mL in the survival group vs. 3,280 pg/mL in the deceased group, p<0.001; Lg NT-pro-BNP 2.82±0.66 in the survival group vs. 3.46±0.52 in the deceased group, p<0.001) were each significantly higher in the deceased group than in the survival group. The optimal cut-off levels for the NT-pro-BNP level and NIHSS score to distinguish the deceased group from the survival group were 1,583.50 pg/mL and 12.5, respectively. Patients with both elevated NT-pro-BNP levels (>1,583.50 pg/mL) and NIHSS scores on admission (NIHSS >12.5) had a substantially higher mortality rate than those without elevated NT-pro-BNP levels and NIHSS scores (89.47% vs. 9.84%, p<0.001). A multivariate logistic regression analysis demonstrated that a NT-pro-BNP level >1,583.50 pg/mL (OR, 5.001; 95% CI, 1.233 to 20.287, p=0.024) and a NIHSS score >12.5 (OR, 1.465; 95% CI, 1.191 to 1.801, p<0.001) were each independent factors associated with in-hospital death. Conclusion The plasma NT-pro-BNP level and the NIHSS score added independent and incremental contributions to the prognostic stratification of patients with acute ischemic stroke.

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IntroductionCurrently, the design of extracellular matrix (ECM) with nanoscale properties in bone tissue engineering is challenging. For bone tissue engineering, the ECM must have certain properties such as being nontoxic, highly porous, and should not cause foreign body reactions.Materials and methodsIn this study, the hybrid scaffold based on polyvinyl alcohol (PVA) blended with metallocene polyethylene (mPE) and plectranthus amboinicus (PA) was fabricated for bone tissue engineering via electrospinning. The fabricated hybrid nanocomposites were characterized by scanning electron microscopy (SEM), Fourier transform and infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), contact angle measurement, and atomic force microscopy (AFM). Furthermore, activated partial thromboplastin time (APTT), prothrombin time (PT), and hemolytic assays were used to investigate the blood compatibility of the prepared hybrid nanocomposites.ResultsThe prepared hybrid nanocomposites showed reduced fiber diameter (238±45 nm) and also increased porosity (87%) with decreased pore diameter (340±86 nm) compared with pure PVA. The interactions between PVA, mPE, and PA were identified by the formation of the additional peaks as revealed in FTIR. Furthermore, the prepared hybrid nanocomposites showed a decreased contact angle of 51°±1.32° indicating a hydrophilic nature and exhibited lower thermal stability compared to pristine PVA. Moreover, the mechanical results revealed that the electrospun scaffold showed an improved tensile strength of 3.55±0.29 MPa compared with the pristine PVA (1.8±0.52 MPa). The prepared hybrid nanocomposites showed delayed blood clotting as noted in APTT and PT assays indicating better blood compatibility. Moreover, the hemolysis assay revealed that the hybrid nanocomposites exhibited a low hemolytic index of 0.6% compared with pure PVA, which was 1.6% suggesting the safety of the developed nanocomposite to red blood cells (RBCs).ConclusionThe prepared nanocomposites exhibited better physico-chemical properties, sufficient porosity, mechanical strength, and blood compatibility, which favors it as a valuable candidate in bone tissue engineering for repairing the bone defects.

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Remaining useful life (RUL) prediction of lithium‐ion batteries (LIBs) plays a very important role in the prognostics and health management (PHM). Accurately predicting RUL of batteries can maintain and replace the batteries in advance to guarantee the safety and stability of the energy storage system (ESS). A method based on improved ant lion optimization and support vector regression (IALO‐SVR) is proposed to accurately predict RUL of LIBs. The ALO algorithm easily falls into the local optimal solution, the levy flight algorithm is utilized to improve the shortcoming of the ALO algorithm. With the mathematical comparison of particle swarm optimization (PSO), differential evolution (DE), and ALO algorithms, the results indicate that the IALO algorithm has higher convergence accuracy. Experimental data simulations were performed using the battery datasets of NASA Prognostics Center of Excellence (PCoE) and the Center for Advanced Life Cycle Engineering (CALCE) to verify the proposed method. Through comparison with SVR, PSO‐LSSVM, and ALO‐SVR methods, the results indicate that the RUL prediction is more accurate based upon the IALO‐SVR method. Therefore, the proposed method can provide high prediction accuracy in battery health prognosis.

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