UV-OZONE Treatment for Suppressing Surface Damages on Silicon Solar Cells.

In the preparation process of c-Si solar cells, qualified Si wafers must be processed through mechanical processing during manufacturing. Most of these processes involve mechanical processing, which inevitably results in severe mechanical damage layers and a wafer surface with large roughness. The current industry practice involves etching of the damage layer using an acid/alkali solution, and it is usually followed by deposition of additional passivation layers in the subsequent processes. However, even with these treatments, there still remain non-negligible microscopic saw damage and scratches on the wafer surface, which hinder the urgent development of a higher conversion efficiency of solar cells. Here, we provide a simple method to effectively suppress the impact of this surface damage. UV-OZONE treatment, which involves generation of an oxide layer and subsequent cleaning with hydrofluoric acid, leads to the effective regain of solar cell performance due to the passivation of dangling bonds and removal of sharp microstructures based on the creation of mechanical scratches. In addition, PEDOT:PSS/n-Si solar cells were prepared to exploit their strong surface dependence to investigate the effect of scratches on the overall performance. These results further validate the impact of scratches on solar cells, and a simple and effective method for surface damage suppression is provided.

miR-541 is associated with the prognosis of liver cirrhosis and directly targets JAG2 to inhibit the activation of hepatic stellate cells.

BACKGROUND: The activation of hepatic stellate cells (HSCs) has been emphasized as a leading event of the pathogenesis of liver cirrhosis, while the exact mechanism of its activation is largely unknown. Furthermore, the novel non-invasive predictors of prognosis in cirrhotic patients warrant more exploration. miR-541 has been identified as a tumor suppressor in hepatocellular carcinoma and a regulator of fibrotic disease, such as lung fibrosis and renal fibrosis. However, its role in liver cirrhosis has not been reported. METHODS: Real-time PCR was used to detect miR-541 expression in the liver tissues and sera of liver cirrhosis patients and in the human LX-2. Gain- and loss-of-function assays were performed to evaluate the effects of miR-541 on the activation of LX-2. Bioinformatics analysis and a luciferase reporter assay were conducted to investigate the target gene of miR-541. RESULTS: miR-541 was downregulated in the tissues and sera of patients with liver cirrhosis, which was exacerbated by deteriorating disease severity. Importantly, the lower expression of miR-541 was associated with more episodes of complications including ascites and hepatic encephalopathy, a shorter overall lifespan, and decompensation-free survival. Moreover, multivariate Cox's regression analysis verified lower serum miR-541 as an independent risk factor for liver-related death in cirrhotic patients (HR = 0.394; 95% CI: 0.164-0.947; P = 0.037). miR-541 was also decreased in LX-2 cells activated by TGF-ß and the overexpression of miR-541 inhibited the proliferation, activation and hydroxyproline secretion of LX-2 cells. JAG2 is an important ligand of Notch signaling and was identified as a direct target gene of miR-541. The expression of JAG2 was upregulated in the liver tissues of cirrhotic patients and was inversely correlated with miR-541 levels. A rescue assay further confirmed that JAG2 was involved in the function of miR-541 when regulating LX-2 activation and Notch signaling. CONCLUSIONS: Dysregulation of miR-541/JAG2 axis might be a as a new mechanism of liver fibrosis, and miR-541 could serve as a novel non-invasive biomarker and therapeutic targets for liver cirrhosis.

An interval-valued carbon price forecasting method based on web search data and social media sentiment.

Accurate carbon price prediction is a crucial task for the carbon trading market. Previous studies have ignored the impact of online data and are limited to point predictions, which brings challenges to the accurate forecasting of carbon prices. To address those issues, this paper proposes an interval-valued carbon price forecasting method based on web search data and social media sentiment. First, we collect web search data and social media sentiment to improve prediction performance by synthesizing multiple types of data information. Second, we employ principal component analysis (PCA) to preprocess high-dimensional web search data, and utilize BosonNLP for quantifying social media information, thereby enhancing the predictability of the dataset. Subsequently, a variational mode decomposition (VMD) is applied to the carbon price and online data, followed by utilizing particle swarm optimization support vector regression (PSO-SVR) to predict each sub-modes and summing them up to obtain the ultimate forecasting outcome. Finally, using carbon prices in Guangdong and Hubei provinces as case studies, the experimental results demonstrate that web search data and social media sentiment significantly enhance the predictive accuracy of interval-valued carbon prices. Furthermore, the proposed VMD-PSO-SVR outperforms other comparative models in the accuracy and reliability of interval-valued forecasting.

The next bastion to be conquered in immunotherapy: microsatellite stable colorectal cancer.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide, and its incidence continues to rise, particularly in developing countries. The advent of immune checkpoint inhibitors (ICIs) has represented a significant advancement in CRC treatment. Deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H) serves as a biomarker for immunotherapy, with dMMR/MSI-H CRC exhibiting significantly better response rates to immunotherapy compared to proficient mismatch repair (pMMR)or microsatellite stable (MSS) CRC. While some progress has been made in the treatment of pMMR/MSS CRC in recent years, it remains a challenging issue in clinical practice. The tumor microenvironment (TME) plays a crucial role not only in the development and progression of CRC but also in determining the response to immunotherapy. Understanding the characteristics of the TME in pMMR/MSS CRC could offer new insights to enhance the efficacy of immunotherapy. In this review, we provide an overview of the current research progress on the TME characteristics and advancements in immunotherapy for pMMR/MSS CRC.

Beam Wander Restrained by Nonlinearity of Femtosecond Laser Filament in Air.

The filamentation process under atmospheric turbulence is critical to its remote-sensing application. The effects of turbulence intensity and location on the spatial distribution of femtosecond laser filaments in the air were studied. The experimental results show that the nonlinear effect of the filament can restrain the beam wander. When the turbulence intensity was 3.31×10−13 cm−2/3, the mean deviation of the wander of the filament center was only 27% of that of the linear transmitted beam. The change in turbulence location would lead to a change in the standard deviation of the beam centroid drift. Results also show that the filament length would be shortened, and that the filament would end up earlier in a turbulent environment. Since the filamentation-based LIDAR has been highly expected as an evolution multitrace pollutant remote-sensing technique, the study promotes our understanding of how turbulence influences filamentation and advances atmospheric remote sensing by applying a filament.

Consensus-Based Linguistic Distribution Large-Scale Group Decision Making Using Statistical Inference and Regret Theory.

Large-scale group decision-making (LSGDM) deals with complex decision- making problems which involve a large number of decision makers (DMs). Such a complex scenario leads to uncertain contexts in which DMs elicit their knowledge using linguistic information that can be modelled using different representations. However, current processes for solving LSGDM problems commonly neglect a key concept in many real-world decision-making problems, such as DMs' regret aversion psychological behavior. Therefore, this paper introduces a novel consensus based linguistic distribution LSGDM (CLDLSGDM) approach based on a statistical inference principle that considers DMs' regret aversion psychological characteristics using regret theory and which aims at obtaining agreed solutions. Specifically, the CLDLSGDM approach applies the statistical inference principle to the consensual information obtained in the consensus process, in order to derive the weights of DMs and attributes using the consensus matrix and adjusted decision-making matrices to solve the decision-making problem. Afterwards, by using regret theory, the comprehensive perceived utility values of alternatives are derived and their ranking determined. Finally, a performance evaluation of public hospitals in China is given as an example in order to illustrate the implementation of the designed method. The stability and advantages of the designed method are analyzed by a sensitivity and a comparative analysis.

miR-541 potentiates the response of human hepatocellular carcinoma to sorafenib treatment by inhibiting autophagy.

OBJECTIVE: Autophagy participates in the progression of hepatocellular carcinoma (HCC) and the resistance of HCC cells to sorafenib. We investigated the feasibility of sensitising HCC cells to sorafenib by modulating miR-541-initiated microRNA-autophagy axis. DESIGN: Gain- and loss-of-function assays were performed to evaluate the effects of miR-541 on the malignant properties and autophagy of human HCC cells. Autophagy was quantified by western blotting of LC3, transmission electron microscopy analyses and confocal microscopy scanning of mRFP-GFP-LC3 reporter construct. Luciferase reporter assays were conducted to confirm the targets of miR-541. HCC xenograft tumours were established to analyse the role of miR-541 in sorafenib-induced lethality. RESULTS: The expression of miR-541 was downregulated in human HCC tissues and was associated with malignant clinicopathologic phenotypes, recurrence and survival of patients with HCC. miR-541 inhibited the growth, metastasis and autophagy of HCC cells both in vitro and in vivo. Prediction software and luciferase reporter assays identified autophagy-related gene 2A (ATG2A) and Ras-related protein Rab-1B (RAB1B) as the direct targets of miR-541. Consistent with the effects of the miR-541 mimic, inhibition of ATG2A or RAB1B suppressed the malignant phenotypes and autophagy of HCC cells. Furthermore, siATG2A and siRAB1B partially reversed the enhancement of the malignant properties and autophagy in HCC cells mediated by the miR-541 inhibitor. More interestingly, higher miR-541 expression predicted a better response to sorafenib treatment, and the combination of miR-541 and sorafenib further suppressed the growth of HCC cells in vivo compared with the single treatment. CONCLUSIONS: Dysregulation of miR-541-ATG2A/RAB1B axis plays a critical role in patients' responses to sorafenib treatment. Manipulation of this axis might benefit survival of patients with HCC, especially in the context of the highly pursued strategies to eliminate drug resistance.

An Approach to Linguistic Multiple Attribute Decision-Making Based on Unbalanced Linguistic Generalized Heronian Mean Aggregation Operator.

This paper proposes an approach to linguistic multiple attribute decision-making problems with interactive unbalanced linguistic assessment information by unbalanced linguistic generalized Heronian mean aggregation operators. First, some generalized Heronian mean aggregation operators with unbalanced linguistic information are proposed, involving the unbalanced linguistic generalized arithmetic Heronian mean operator and the unbalanced linguistic generalized geometric Heronian mean operator. For the situation that the input arguments have different degrees of importance, the unbalanced linguistic generalized weighted arithmetic Heronian mean operator and the unbalanced linguistic generalized weighted geometric Heronian mean operator are developed. Then we investigate their properties and some particular cases. Finally, the effectiveness and universality of the developed approach are illustrated by a low-carbon tourist instance and comparison analysis. A sensitivity analysis is performed as well to test the robustness of proposed methods.

SHP-1 Acts as a Tumor Suppressor in Hepatocarcinogenesis and HCC Progression.

Src homology region 2 (SH2) domain-containing phosphatase 1 (SHP-1, also known as PTPN6) is a nonreceptor protein tyrosine phosphatase that acts as a negative regulator of inflammation. Emerging evidence indicates that SHP-1 plays a role in inhibiting the progression of hepatocellular carcinoma (HCC). However, the role of SHP-1 in hepatocarcinogenesis remains unknown. Here, we find that levels of SHP-1 are significantly downregulated in human HCC tissues compared with those in noncancerous tissues (P < 0.001) and inversely correlate with tumor diameters (r = -0.4130, P = 0.0002) and serum α-fetoprotein levels (P = 0.047). Reduced SHP-1 expression was associated with shorter overall survival of patients with HCC with HBV infection. Overexpression of SHP-1 suppressed proliferation, migration, invasion, and tumorigenicity of HCC cells, whereas knockdown of SHP-1 enhanced the malignant phenotype. Moreover, knockout of Ptpn6 in hepatocytes (Ptpn6HKO ) enhanced hepatocarcinogenesis induced by diethylnitrosamine (DEN) as well as metastasis of primary liver cancer in mice. Furthermore, systemic delivery of SHP-1 by an adenovirus expression vector exerted a therapeutic effect in an orthotopic model of HCC in NOD/SCID mice and DEN-induced primary liver cancers in Ptpn6HKO mice. In addition, SHP-1 inhibited the activation of JAK/STAT, NF-κB, and AKT signaling pathways, but not the MAPK pathway in primary hepatocytes from DEN-treated mice and human HCC cells. Together, our data implicate SHP-1 as a tumor suppressor of hepatocarcinogenesis and HCC progression and propose it as a novel prognostic biomarker and therapeutic target of HCC.Significance: The nonreceptor protein tyrosine phosphatase SHP-1 acts as a tumor suppressor in hepatocellular carcinoma. Cancer Res; 78(16); 4680-91. ©2018 AACR.

The HNF1α-regulated lncRNA HNF1A-AS1 reverses the malignancy of hepatocellular carcinoma by enhancing the phosphatase activity of SHP-1.

BACKGROUND: Our previous study has demonstrated that hepatocyte nuclear factor 1α (HNF1α) exerts potent therapeutic effects on hepatocellular carcinoma (HCC). However, the molecular mechanisms by which HNF1α reverses HCC malignancy need to be further elucidated. METHODS: lncRNA microarray was performed to identify the long noncoding RNAs (lncRNAs) regulated by HNF1α. Chromatin immunoprecipitation and luciferase reporter assays were applied to clarify the mechanism of the transcriptional regulation of HNF1α to HNF1A antisense RNA 1 (HNF1A-AS1). The effect of HNF1A-AS1 on HCC malignancy was evaluated in vitro and in vivo. RNA pulldown, RNA-binding protein immunoprecipitation and the Bio-Layer Interferometry assay were used to validate the interaction of HNF1A-AS1 and Src homology region 2 domain-containing phosphatase 1 (SHP-1). RESULTS: HNF1α regulated the expression of a subset of lncRNAs in HCC cells. Among these lncRNAs, the expression levels of HNF1A-AS1 were notably correlated with HNF1α levels in HCC cells and human HCC tissues. HNF1α activated the transcription of HNF1A-AS1 by directly binding to its promoter region. HNF1A-AS1 inhibited the growth and the metastasis of HCC cells in vitro and in vivo. Moreover, knockdown of HNF1A-AS1 reversed the suppressive effects of HNF1α on the migration and invasion of HCC cells. Importantly, HNF1A-AS1 directly bound to the C-terminal of SHP-1 with a high binding affinity (KD = 59.57 ± 14.29 nM) and increased the phosphatase activity of SHP-1. Inhibition of SHP-1 enzymatic activity substantially reversed the HNF1α- or HNF1A-AS1-induced reduction on the metastatic property of HCC cells. CONCLUSIONS: Our data revealed that HNF1A-AS1 is a direct transactivation target of HNF1α in HCC cells and involved in the anti-HCC effect of HNF1α. HNF1A-AS1 functions as phosphatase activator through the direct interaction with SHP-1. These findings suggest that regulation of the HNF1α/HNF1A-AS1/SHP-1 axis may have beneficial effects in the treatment of HCC.