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Abstract Two major challenges need to be overcome to bridge the efficiency gap between small-area rigid organic solar cells (OSCs) and large-area flexible devices: the first challenge lies in preparing high-quality flexible transparent electrodes with low resistance, high transparency, smooth surface, and superior mechanical properties. Second, the scalable fabrication of thickness-insensitive photoactive layers with low-cost materials is also an essential task. In this review, recent progress and challenges of flexible large-area OSCs are summarized and analyzed. Based on our analysis, strategies and opportunities are proposed to promote the development of stable and efficient flexible large-area OSCs.

ABSTRACT Background: Predictors of outcomes following endovascular treatment (ET) for aneurysmal subarachnoid hemorrhage (aSAH) are not well-defined. Identifying them would be beneficial in determining which patients might benefit from ET. Objective: To identify the predictive factors for poor outcomes following ET for aSAH. Methods: 120 patients with ruptured cerebral aneurysms underwent endovascular embolization between January 2017 and December 2018. Blood pressure variability was examined using the standard deviation of the 24-hour systolic blood pressure (24hSSD) and 24-hour diastolic blood pressure (24hDSD). Predictors were identified through univariate and multivariate regression analysis. All patients were followed up for three months. Results: At follow-up, 86 patients (71.7%) had good outcomes and 34 (28.3%) had poor outcomes. Patients with poor outcomes had significantly higher 24hSSD than those with good outcomes (19.3 ± 5.5 vs 14.1 ± 4.8 mmHg; P < 0.001). The 24hDSD did not differ significantly between patients with good outcomes and those with poor outcomes (9.5 ± 2.3 vs 9.9 ± 3.5 mmHg; P = 0.464). The following were significant risk factors for poor outcomes after endovascular embolization: age ≥ 65 years (odds ratio [OR] = 23.0; 95% confidence interval [CI]: 3.0-175.9; P = 0.002); Hunt-Hess grade 3-4 (OR = 6.8; 95% CI: 1.1-33.7; P = 0.039); Fisher grade 3-4 (OR = 47.1; 95% CI: 3.8-586.5; P = 0.003); postoperative complications (OR = 6.1; 95% CI: 1.1-34.8; P = 0.042); and 24hSSD ≥ 15 mmHg (OR = 14.9; 95% CI: 4.0-55.2; P < 0.001). Conclusion: Elevated 24hSSD is a possibly treatable predictive factor for poor outcomes after ET for aSAH.

Abstract This paper is concerned with security problems for cyber‐physical systems (CPSs) under dynamic load altering attacks (DLAA) and false data injection attacks (FDIA). The smart grid, as a typical CPS system, is taken as an example in this paper. Since the communication channel is vulnerable to FDIA and DLAA, the stability of the smart grid may be influenced. For enhancing resilience and stability of smart grids, first of all, the power system model including both DLAA and FDIA is introduced. Second, an adaptive sliding mode controller is proposed. The controller can ensure the reliable operation of the power system in the case of unknown attack information by using the adaptive mechanism online estimating the upper bound of attack signal to automatically eliminate the effect of mixed attacks. Finally, a power system with three generators and six buses is taken as an illustrative example, and simulation and experiment results obtained by using MATLAB and Hardware‐in‐time platform built by Sartsim verify the effectiveness of the proposed resilient defense strategy.

A demodulation method based on liquid crystal spatial light modulator for space domain phase-shift-interferometry is proposed in this paper. In the method, the grating type with dual-image-element mode is used as the phase modulation mode, and the ρ-δ algorithm is proposed with which the interference image is recovered from the modulated image. Finally, the demodulation method is introduced by using the gradient projection algorithm and the arctangent operation. Simulation and experimental results show the effectiveness of the proposed method, in which the image recovery error can be reduced by 1.3 grayscales, and the improvement rate of recovery accuracy is 31.38%. In the 90pixels truncation interface, the effective demodulation pixels are 84 pixels, accounting for 93.33%.

BackgroundPrevious studies have demonstrated that inflammation-related interleukin-17 (IL-17) signaling plays a pivotal role in the pathogenesis of non-alcoholic steatohepatitis (NASH)- and alcoholic liver disease (ALD)-induced hepatocellular carcinoma (HCC). However, rare efforts have been intended at implementing the analysis of N6-methyladenosine (m6A) mRNA methylation to elucidate the underpinning function of the IL-17 receptor A (IL-17RA) during the inflammation-carcinogenesis transformation of HCC.MethodsWe performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) using normal, HCC tumor and paired tumor adjacent tissues from patients to investigate the dynamic changes of m6A mRNA methylation in the process of HCC. Additionally, murine non-alcoholic fatty liver disease (NAFLD) model and murine chronic liver injury model were utilized to investigate the role of IL-17RA regulated by m6A mRNA modulator fat mass and obesity-associated (FTO) in chronic hepatic inflammation.ResultsMeRIP-seq revealed the reduction of m6A mRNA methylation of IL-17RA in tumor adjacent tissues with chronic inflammation, suggesting the potential role of IL-17RA in the inflammation-carcinogenesis transformation of HCC. Besides, we demonstrated that FTO, rather than methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14), and alkB homolog 5 (ALKBH5) functions as a main modulator for the decrease of m6A mRNA methylation of IL-17RA via knockdown and overexpression of FTO in vitro and in vivo.ConclusionsOverall, we elaborated the underlying mechanisms of the increase of IL-17RA resulting in chronic inflammation via the demethylation of FTO in tumor adjacent tissues and demonstrated that targeting the specific m6A modulator FTO may provide an effective treatment for hepatitis patients to prevent the development of HCC.

Abstract In the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.