Knockdown of long non-coding RNA SBF2-AS1 inhibits calcium oxalate-induced HK-2 cell injury by regulating the miR-302e/NLRP3 pathway.

Long non-coding ribose nucleic acids (lncRNAs) have been implicated in the development of nephrolithiasis. The study aims to investigate the interplay of lncRNA SBF2-AS1 (SETbinding factor 2 antisense RNA 1) and NLR family pyrin domain containing 3 (NLRP3) in regulating the calcium oxalate monohydrate (COM)-induced human kidney HK-2 cell injury. HK-2 cells were treated with COM (100 µg/mL) to create a cellular model of kidney injury. Gene and protein expression was assessed by quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and Western blot. Proliferation and apoptosis rates, as well as levels of malondialdehyde (MDA), lactate dehydrogenase (LDH), superoxide dismutase (SOD), tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6 were measured. Additionally, potential miRNAs interacting with SBF2-AS1 and NLRP3 were predicted utilizing the starBase and TargetScan databases. The interference of SBF2-AS1 resulted in increased cell proliferation and SOD levels in HK-2 cells after COM induction. SBF2-AS1 silencing also reduced COM-induced cell death and inflammatory cytokine production by down-regulating NLRP3 protein expression. Conversely, forced upregulation of NLRP3 abrogated the effect of SBF2-AS1 interference. Notably, SBF2-AS1 interference on COM-induced oxidative stress and COM-induced cellular damage was rescued by antioxidant, indicating the involvement of oxidative burden in COM-induced damage. miR-302e acted as a mediator miRNA linking the functional association of SBF2-AS1 and NLRP3. Silencing SBF2-AS1 promoted miR-302e level and miR-302e reduced NLRP3 expression in HK-2 cells to protect against COM-induced damage. In summary, these findings suggest that downregulation of lncRNA SBF2-AS1 can potentially protect HK-2 cells from COM-induced injury by modulating the miR-302e/NLRP3 pathway.

Consumers' Behavioral Willingness to Use Green Financial Products: An Empirical Study within a Theoretical Framework.

In an era marked by the expansion of the Internet economy and the intensification of environmental concerns, the convergence of digital finance and green finance has emerged as a significant global trend. China's Alipay Ant Forest, an innovative green financial product, has successfully quantified carbon emission reductions resulting from users' green consumption patterns, establishing the first carbon account-based green financial product and pioneering an innovative "green finance plus gamification" model. However, the academic literature has not fully explained the underlying mechanisms that drive consumer engagement with such green financial products. This study, motivated by the academic question of what factors influence consumers' willingness to use green financial products, employs Ant Forest as a case study and develops a novel structural equation model based on self-determination theory, customer-perceived value, and the technology acceptance model. The model incorporates user type as a control variable and considers autonomy, gamification, and bonuses as key independent variables, with customer-perceived value serving as a mediating variable. Data collection involved 606 participants, enabling a comprehensive analysis of the factors influencing users' willingness to engage with green financial products. The findings support the proposed hypothesis, identifying several significant predictors of users' willingness to use green financial products, with the exception of age. This study advances the theoretical understanding of consumer behavior towards green financial products by integrating self-determination theory, customer-perceived value, and the technology acceptance model, while also offering practical insights for marketing strategies. It explores the interface between digital finance, environmental sustainability, and consumer behavior, highlighting opportunities for financial institutions to leverage Internet applications to promote green financial services and enhance their marketing approaches to influence consumer adoption.

A Reconfigurable energy-resolving method for a layered edge-on detector.

Currently, most of the x-ray spectral detectors can extract signals in a set number of energy bins, that inevitably reduces the dynamic range and energy resolution of the imaging system. Inspired by the idea of dynamic thresholding, we previously proposed a pixel architecture and an energy-resolving method for layered edge-on detector. However, the complicated energy exchange mechanism of x-rays in the detector that ultimately affects the practical applications of the layered detectors had not been previously considered. In this study, we modify the energy-depositing model of x-ray photons and propose a reconfigurable energy-resolving method to improve the spectral performance of a layered energy integrating detector. We analyze the errors associated with the energy-resolving process and present our numerical simulation results obtained with energy bins and dynamically changed detection layers to demonstrate the utility and reliability of the proposed method.

Thermal Conductivity of Two Types of 2D Carbon Allotropes: a Molecular Dynamics Study.

The thermal properties of the two novel 2D carbon allotropes with five-five-eight-membered rings are explored using molecular dynamics simulations. Our results reveal that the thermal conductivity increases monotonically with increasing size. The thermal conductivities of infinite sizes are obtained by linear relationships of the inverse length and inverse thermal conductivity. The converged thermal conductivity obtained by extrapolation in the reverse non-equilibrium molecular dynamics method is found to be in reasonable agreement with that in the equilibrium molecular dynamics method. The much lower thermal conductivity, compared with graphene, is attributed to the lower phonon group velocity and phonon mean free path. Temperature and strain effects on thermal conductivity are also explored. The thermal conductivity decreases with increasing temperature and it can also be tuned through strain engineering in a large range. The effect of strain on TC is well explained by spectra analysis of phonon vibration. This study provides physical insight into thermal properties of the two carbon allotropes under different conditions and offers design guidelines for applications of novel two-dimensional carbon allotropes related devices.

RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.

Prostate cancer (PCa) is the most commonly diagnosed cancer in males in the Western world. Although prostate-specific antigen (PSA) has been widely used as a biomarker for PCa diagnosis, its results can be controversial. Therefore, new biomarkers are needed to enhance the clinical management of PCa. From publicly available microarray data, differentially expressed genes (DEGs) were identified by meta-analysis with RankProd. Genetic algorithm optimized artificial neural network (GA-ANN) was introduced to establish a diagnostic prediction model and to filter candidate genes. The diagnostic and prognostic capability of the prediction model and candidate genes were investigated in both GEO and TCGA datasets. Candidate genes were further validated by qPCR, Western Blot and Tissue microarray. By RankProd meta-analyses, 2306 significantly up- and 1311 down-regulated probes were found in 133 cases and 30 controls microarray data. The overall accuracy rate of the PCa diagnostic prediction model, consisting of a 15-gene signature, reached up to 100% in both the training and test dataset. The prediction model also showed good results for the diagnosis (AUC = 0.953) and prognosis (AUC of 5 years overall survival time = 0.808) of PCa in the TCGA database. The expression levels of three genes, FABP5, C1QTNF3 and LPHN3, were validated by qPCR. C1QTNF3 high expression was further validated in PCa tissue by Western Blot and Tissue microarray. In the GEO datasets, C1QTNF3 was a good predictor for the diagnosis of PCa (GSE6956: AUC = 0.791; GSE8218: AUC = 0.868; GSE26910: AUC = 0.972). In the TCGA database, C1QTNF3 was significantly associated with PCa patient recurrence free survival (P < .001, AUC = 0.57). In this study, we have developed a diagnostic and prognostic prediction model for PCa. C1QTNF3 was revealed as a promising biomarker for PCa. This approach can be applied to other high-throughput data from different platforms for the discovery of oncogenes or biomarkers in different kinds of diseases.

Improving Charge Injection via a Blade-Coating Molybdenum Oxide Layer: Toward High-Performance Large-Area Quantum-Dot Light-Emitting Diodes.

A solution-processed molybdenum oxide (MoO x) as the hole injection layer (HIL) by doctor-blade coating was developed to improve the efficiency and lifetime of red-emitting quantum-dot light-emitting diodes (QD-LEDs). It has been demonstrated that by adding isopropyl alcohol into the MoO x precursor during the doctor-blade coating process, the morphology, composition, and the surface electronic structure of the MoO x HIL could be tailored. A high-quality MoO x film with optimized charge injection was obtained, based on which all-solution-processed highly efficient red-emitting QD-LEDs were realized by using a low-cost doctor-blade coating technique under ambient conditions. The red QD-LEDs exhibited the maximum current efficiency and external quantum efficiency of 16 cd/A and 15.1%, respectively. Moreover, the lifetime of red devices initializing at 100 cd/m2 was 3236 h under ambient conditions, which is about twice as long as those with a conventional poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) HIL. Large-area QD-LEDs with 4 in. emitting areas were fabricated with blade coating as well, which exhibit a high efficiency of 12.1 cd/A for red emissions. Our work paves a new way to the realization of efficient large-area QD-LEDs, and the processing and findings from this work can be expanded into next-generation lighting and flat-panel displays.

Efficient All-Solution Processed Quantum Dot Light Emitting Diodes Based on Inkjet Printing Technique.

Quantum dot light emitting diodes (QLEDs) are increasingly attractive owing to their compatibility with the inkjet printing process and potential application in low-cost large-area full-color pixelated display. The strategy for controlling the morphology of the quantum dot layer is definitely critical for realizing all-solution processed QLEDs with high performance, which certainly requires in-depth thinking regarding the design of ink composition and their optimization in the printing process. Herein, by carefully controlling the quantum dot ink composition and physicochemical properties, we demonstrate that the viscosity, contact angle, and the three-phase contact line moving would affect the final morphology of the quantum dot film formed by inkjet printing. We achieved coffee ring-free and low-roughness quantum dot film, and all-solution processed QLEDs with normal structure were fabricated for the first time. The devices have a low turn-on voltage of 2.0 V, a luminance of 12100 cd/m2 at the voltage of 12 V, and a maximum current efficiency of 4.44 cd/A at the luminance of 1974 cd/m2, which is the best result to date for inkjet-printed red QLEDs. The results will pave the way for future application of inkjet printing in solution processed pixelated QLED display.

GSTM1 and GSTT1 polymorphisms contribute to renal cell carcinoma risk: evidence from an updated meta-analysis.

Emerging evidences suggest that GSTM1 and GSTT1 are involved in the detoxification of carcinogens, and polymorphisms in this gene that result in a loss of enzyme activity may increase the risk of renal cell carcinoma (RCC). Thus, to evaluate the association of GSTM1 and GSTT1 polymorphisms and RCC, we performed an updated meta-analysis of 10 case-control studies by RevMan 5.2, and the publication bias was tested using STATA 11.0. The meta-analysis showed that the single locus GSTM1 and GSTT1 polymorphisms were not significantly associated with a risk of RCC in a recessive model. However, that wild-type genotype versus the dual null genotype of GSTM1-GSTT1 showed a positive association with RCC risk (OR = 0.70; 95% CI = 0.51-0.98; P = 0.04). In another analysis of subjects exposed to pesticides, we found that the GSTM1 wild-type genotype was associated with increased RCC risk in Europeans (OR = 2.72; 95% CI = 1.54-4.82; P = 0.0006). We also identified an association between the GSTT1 wild-type and lower RCC TNM staging (I + II versus III + IV: OR = 1.88; 95% CI = 1.09-3.26; P = 0.02). This meta-analysis suggests that there may be a relationship between the GSTM1 and GSTT1 wild-type genotype and RCC.