Ti3C2 mediates the NiFe-LDH layered electrocatalyst to enhance the OER performance for water splitting.

Oxygen evolution reaction (OER) is a very complex process with slow reaction kinetics and high overpotential, which is the main limitation for the commercial application of water splitting. Thus, it is of necessary to design high-performance OER catalysts. NiFe based layered double hydroxides (NiFe-LDHs) have recently gained a lot of attention due to their high reaction activity and simple manufacturing process. In this study, a novel electrocatalyst based on NiFe-LDH was constructed by introducing Ti3C2, which was utilized to modulate the structural and electronic properties of the electrocatalysts. Structural examinations reveal that the Ti3C2 of 2D structure successfully dope the NiFe-LDHs nanosheets, forming NiFe-LDH/Ti3C2 heterojunctions. Firstly, the heterojunction substantially reduces the charge transfer resistance, promoting the electron migration between the LDH nanosheets. Secondly, theoretical calculations demonstrate that the energy barrier between the rate-determining step from *OH to *O is lowered, favoring the formation of the reaction intermediates and thus the occurrence of OER. As a result, the composite electrocatalyst exhibits a low overpotential of 334 mV at a current density of 10 mA/cm2 and a small Tafel slope of 55 mV/dec, which are superior to those of the NiFe-LDH by 11.2 % and 38.5 %, respectively. This study provides inspiration for promoting the performances of NiFe based electrocatalysts by utilizing 2D materials.

Two-Dimensional SnS Mediates NiFe-LDH-Layered Electrocatalyst toward Boosting OER Activity for Water Splitting.

NiFe-layered double hydroxides (NiFe-LDHs), as promising electrocatalysts, have received significant research attention for hydrogen and oxygen generation through water splitting. However, the slow oxidation kinetics of NiFe-LDH, due to the limited number of active sites and the low conductivity, hinders the improvement of the water-splitting efficiency. Therefore, to overcome the obstacles, two-dimensional (2D) SnS was first explored to tailor the prepared NiFe-LDH via the hydrothermal method. A NiFe-LDH/SnS heterojunction is built, which is observed from the microstructural investigations. SnS incorporation could greatly improve the conductivity of the NiFe-LDH sheets, which was reflected by the reduced charge transfer resistance. Moreover, SnS layers modulated the electronic environment around the active sites, favoring the adsorption of intermediates during the oxygen evolution reaction (OER) process, which was verified by density functional theory calculations. A synergistic effect induced by the NiFe-LDH/SnS heterostructure promoted the OER activities in electrical, electronic, and energetic aspects. Consequently, the as-prepared NiFe-LDH/SnS electrocatalyst greatly improved the electrocatalytic performance, exhibiting 20% and 27% reductions in the overpotential and Tafel slope compared with those of pristine NiFe-LDH, respectively. The results provide a strategy for regulating NiFe-based electrocatalysts by using emerging 2D materials to enhance water-splitting efficiency.

CloudMix: Dual Mixup Consistency for Unpaired Point Cloud Completion.

Due to the unsatisfactory performance of supervised methods on unpaired real-world scans, point cloud completion via cross-domain adaptation has recently drawn growing attention. Nevertheless, previous approaches only focus on alleviating the distribution shift through domain alignment, resulting in massive information loss of real-world domain data. To tackle this issue, we propose a dual mixup-induced consistency regularization to integrate both source and target domain to improve robustness and generalization capability. Specifically, we mix up virtual and real-world shapes in the input and latent feature space respectively, and then regularize the completion network by forcing two kinds of mixed completion predictions to be consistent. To further adapt to each instance within the real-world domain, we design a novel density-aware refiner to utilize local context information to preserve the fine-grained details and remove noise or outliers for coarse completion. Extensive experiments on real-world scans and our synthetic unpaired datasets demonstrate the superiority of our method over existing state-of-the-art approaches.

Self-Adversarial Disentangling for Specific Domain Adaptation.

Domain adaptation aims to bridge the domain shifts between the source and the target domain. These shifts may span different dimensions such as fog, rainfall, etc. However, recent methods typically do not consider explicit prior knowledge about the domain shifts on a specific dimension, thus leading to less desired adaptation performance. In this article, we study a practical setting called Specific Domain Adaptation (SDA) that aligns the source and target domains in a demanded-specific dimension. Within this setting, we observe the intra-domain gap induced by different domainness (i.e., numerical magnitudes of domain shifts in this dimension) is crucial when adapting to a specific domain. To address the problem, we propose a novel Self-Adversarial Disentangling (SAD) framework. In particular, given a specific dimension, we first enrich the source domain by introducing a domainness creator with providing additional supervisory signals. Guided by the created domainness, we design a self-adversarial regularizer and two loss functions to jointly disentangle the latent representations into domainness-specific and domainness-invariant features, thus mitigating the intra-domain gap. Our method can be easily taken as a plug-and-play framework and does not introduce any extra costs in the inference time. We achieve consistent improvements over state-of-the-art methods in both object detection and semantic segmentation.

A network analysis of anxiety and depression symptoms in Chinese disabled elderly.

BACKGROUND: Mental health is an essential dimension of healthy aging. The number and severity of disabled elderly in China show an increasing tendency year by year. Due to their impaired ability of daily activities, reduced social participation and reduced self-care ability, they are more prone to depression and anxiety. METHOD: We included 2131 individuals aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2017-2018). We used the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. The structure of depressive and anxiety symptoms was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed by gender. RESULTS: Network analysis revealed that nodes CESD3 (Felt sadness), GAD2 (Uncontrollable worry), and GAD4 (Trouble relaxing) were the primary symptoms of the anxiety-depression network. Anxiety and depression were united by the symptoms of CESD9 (Could not get going), GAD1 (Nervousness or anxiety), CESD10 (Sleep quality), and GAD4 (Trouble relaxing). Additionally, Gender did not significantly affect the network structure. CONCLUSION: Central symptoms (e.g., felt sadness, uncontrollable worry and trouble relaxing) and key bridge symptoms (e.g., could not get going, nervousness and anxiety) in the depressive and anxiety symptoms network may be used as potential targets for intervention among disabled elderly who is at risk for or suffer from depressive and anxiety symptoms.

The interaction effect of transfusion history and previous stroke history on the risk of venous thromboembolism in stroke patients: a prospective cohort study.

BACKGROUND: Blood transfusion and previous stroke history are two independent risk factors of venous thromboembolism (VTE) in stroke patients. Whether the potential interaction of transfusion history and previous stroke history is associated with a greater risk of VTE remains unclear. This study aims to explore whether the combination of transfusion history and previous stroke history increases the risk of VTE among Chinese stroke patients. METHODS: A total of 1525 participants from the prospective Stroke Cohort of Henan Province were enrolled in our study. Multivariate logistic regression models were used to explore the associations among transfusion history, previous stroke history and VTE. The interaction was evaluated on both multiplicative and additive scales. The odds ratio (95% CI), relative excess risk of interaction (RERI), attributable proportion (AP), and synergy index (S) of interaction terms were used to examine multiplicative and additive interactions. Finally, we divided our population into two subgroups by National Institutes of Health Stroke Scale (NIHSS) score and re-evaluated the interaction effect in both scales. RESULTS: A total of 281 (18.4%) participants of 1525 complicated with VTE. Transfusion and previous stroke history were associated with an increased risk of VTE in our cohort. In the multiplicative scale, the combination of transfusion and previous stroke history was statistically significant on VTE in both unadjusted and adjusted models (P<0.05). For the additive scale, the RERI shrank to 7.016 (95% CI: 1.489 ~ 18.165), with the AP of 0.650 (95% CI: 0.204 ~ 0.797) and the S of 3.529 (95% CI: 1.415 ~ 8.579) after adjusting for covariates, indicating a supra-additive effect. In subgroups, the interaction effect between transfusion history and previous stroke history was pronouncedly associated with the increased risk of VTE in patients with NIHSS score > 5 points (P<0.05). CONCLUSIONS: Our results suggest that there may be a potential synergistic interaction between transfusion history and previous stroke history on the risk of VTE. Besides, the percentage of VTE incidence explained by interaction increased with the severity of stroke. Our findings will provide valuable evidence for thromboprophylaxis in Chinese stroke patients.

The effects of capsaicin intake on weight loss among overweight and obese subjects: a systematic review and meta-analysis of randomised controlled trials.

Animal studies have shown that capsaicin plays a positive role in weight management. However, the results in human research are controversial. Therefore, the present systematic review and meta-analysis aimed to evaluate the effect of capsaicin on weight loss in adults. We searched PubMed, Embase, China Biomedical Literature Database (CBM), Cochrane library and clinical registration centre, identifying all randomised controlled trials (RCT) published in English and Chinese to 3 May 2022. A random-effect model was used to calculate the weighted mean difference (WMD) and 95 % CI. Heterogeneity between studies was assessed by the Cochran Q statistic and I-squared tests (I 2 ). Statistical analyses were performed using STATA version 15.1. P-values < 0·05 were considered as statistically significant. From 2377 retrieved studies, fifteen studies were finally included in the meta-analyses. Fifteen RCT with 762 individuals were included in our meta-analysis. Compared with the control group, the supplementation of capsaicin resulted in significant reduction on BMI (WMD: -0·25 kg/m2, 95 % CI = -0·35, -0·15 kg/m2, P < 0·05), body weight (BW) (WMD: -0·51 kg, 95 % CI = -0·86, -0·15 kg, P < 0·05) and waist circumference (WC) (WMD: -1·12 cm, 95 % CI = -2·00, -0·24 cm, P < 0·05). We found no detrimental effect of capsaicin on waist-to-hip ratio (WMD: -0·05, 95 % CI = -0·17, 0·06, P > 0·05). The current meta-analysis suggests that capsaicin supplementation may have rather modest effects in reducing BMI, BW and WC for overweight or obese individuals.

TransVOD: End-to-End Video Object Detection With Spatial-Temporal Transformers.

Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous complex hand-crafted detectors. However, their performance on Video Object Detection (VOD) has not been well explored. In this paper, we present TransVOD, the first end-to-end video object detection system based on simple yet effective spatial-temporal Transformer architectures. The first goal of this paper is to streamline the pipeline of current VOD, effectively removing the need for many hand-crafted components for feature aggregation, e.g., optical flow model, relation networks. Besides, benefited from the object query design in DETR, our method does not need post-processing methods such as Seq-NMS. In particular, we present a temporal Transformer to aggregate both the spatial object queries and the feature memories of each frame. Our temporal transformer consists of two components: Temporal Query Encoder (TQE) to fuse object queries, and Temporal Deformable Transformer Decoder (TDTD) to obtain current frame detection results. These designs boost the strong baseline deformable DETR by a significant margin (3 %-4 % mAP) on the ImageNet VID dataset. TransVOD yields comparable performances on the benchmark of ImageNet VID. Then, we present two improved versions of TransVOD including TransVOD++ and TransVOD Lite. The former fuses object-level information into object query via dynamic convolution while the latter models the entire video clips as the output to speed up the inference time. We give detailed analysis of all three models in the experiment part. In particular, our proposed TransVOD++ sets a new state-of-the-art record in terms of accuracy on ImageNet VID with 90.0 % mAP. Our proposed TransVOD Lite also achieves the best speed and accuracy trade-off with 83.7 % mAP while running at around 30 FPS on a single V100 GPU device. Code and models are available at https://github.com/SJTU-LuHe/TransVOD.

Causal relationships between birth weight, childhood obesity and age at menarche: A two-sample Mendelian randomization analysis.

OBJECTIVES: Observational studies suggest birth weight and childhood obesity are closely associated with age at menarche. However, the relationships between them are currently inconsistent and it remains elusive whether such associations are causal. Therefore, the aim of the study was to investigate whether there existed causal relationships between birth weight, childhood obesity and age at menarche. DESIGN, PATIENTS AND MEASUREMENTS: A two-sample Mendelian randomization (MR) study. The standard inverse variance weighted MR analyses were adopted to evaluate the causal effects of birth weight (n = 143,677), childhood body mass index (BMI) (n = 39,620) on age at menarche (n = 182,416) with summary statistics from large-scale genome-wide association studies (GWASs). Meanwhile, we validated our MR results with some sensitivity analyses including maximum likelihood, weighted-median and MR pleiotropy residual sum and outlier methods. RESULTS: The present study showed that each one standard deviation (1-SD) lower birth weight was predicted to result in a 0.1479 years earlier of age at menarche (ß = .1479, 95% confidence interval [CI] = 0.0422-0.2535; p = 0.0061). We also found that genetically predicted 1-SD increase in childhood BMI was causally associated with early age at menarche (ß = -.3966, 95% CI = -0.5294 to -0.2639; p = 4.73E-09). CONCLUSIONS: Our MR study suggests the causal effect of lower birth weight and higher childhood BMI on the increased risk of earlier menarche. It may be the opportune time to carry out weight control intervention in prenatal and early childhood development periods to prevent early menarche onset, thus decreasing the future adverse consequences.

Identification of potentially common loci between childhood obesity and coronary artery disease using pleiotropic approaches.

Childhood obesity remains one of the most important issues in global health, which is implicated in many chronic diseases. Converging evidence suggests that a higher body mass index during childhood (CBMI) is significantly associated with increased coronary artery disease (CAD) susceptibility in adulthood, which may partly arise from the shared genetic determination. Despite genome-wide association studies (GWASs) have successfully identified some loci associated with CBMI and CAD individually, the genetic overlap and common biological mechanism between them remains largely unexplored. Here, relying on the results from the two large-scale GWASs (n = 35,668 for CBMI and n = 547,261 for CAD), linkage disequilibrium score regression (LDSC) was used to estimate the genetic correlation of CBMI and CAD in the first step. Then, we applied different pleiotropy-informed methods including conditional false discovery rate ([Formula: see text]) and genetic analysis incorporating pleiotropy and annotation (GPA) to detect potentially common loci for childhood obesity and CAD. By integrating the genetic information from the existing GWASs summary statistics, we found a significant positive genetic correlation ([Formula: see text] = 0.127, p = 2E-4) and strong pleiotropic enrichment between CBMI and CAD (LRT = 79.352, p = 5.2E-19). Importantly, 28 loci were simultaneously discovered to be associated with CBMI, and 13 of them were identified as potentially pleiotropic loci by [Formula: see text] and GPA. Those corresponding pleiotropic genes were enriched in trait-associated gene ontology (GO) terms "amino sugar catabolic process", "regulation of fat cell differentiation" and "synaptic transmission". Overall, the findings of the pleiotropic loci will help to further elucidate the common molecular mechanisms underlying the association of childhood obesity and CAD, and provide a theoretical direction for early disease prevention and potential therapeutic targets.

Early memory impairment is accompanied by changes in GluA1/p-GluA1 in APP/PS1 mice.

AIMS: Exploring the neurobiological mechanisms of early AD damage Background: The early diagnosis of Alzheimer's disease (AD) has a very important impact on the prognosis of AD. However, the early symptoms of AD are not obvious and difficult to diagnose. Existing studies have rarely explored the mechanism of early AD. AMPARs are early important learning memory-related receptors. However, it is not clear how the expression levels of AMPARs change in early AD. OBJECTIVE: We explored learning memory abilities and AMPAR expression changes in APP/PS1 mice at 4 months, 8 months, and 12 months. METHOD: We used the classic Morris water maze to explore the learning and memory impairment of APP/PS1 mice and used western blotting to explore the changes in AMPARs in APP/PS1 mice. RESULT: We found that memory impairment occurred in APP/PS1 mice as early as 4 months of age, and the impairment of learning and memory gradually became serious with age. The changes in GluA1 and p-GluA1 were most pronounced in the early stages of AD in APP/PS1 mice. CONCLUSION: Our study found that memory impairment in APP/PS1 mice could be detected as early as 4 months of age, and this early injury may be related to GluA1.

NiFeMn-Layered Double Hydroxides Linked by Graphene as High-Performance Electrocatalysts for Oxygen Evolution Reaction.

Currently, precious metal group materials are known as the efficient and widely used oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) catalysts. The exorbitant prices and scarcity of the precious metals have stimulated scale exploration of alternative non-precious metal catalysts with low-cost and high performance. Layered double hydroxides (LDHs) are a promising precursor to prepare cost-effective and high-performance catalysts because they possess abundant micropores and nitrogen self-doping after pyrolysis, which can accelerate the electron transfer and serve as active sites for efficient OER. Herein, we developed a new highly active NiFeMn-layered double hydroxide (NFM LDH) based electrocatalyst for OER. Through building NFM hydroxide/oxyhydroxide heterojunction and incorporation of conductive graphene, the prepared NFM LDH-based electrocatalyst delivers a low overpotential of 338 mV at current density of 10 mA cm-2 with a small Tafel slope of 67 mV dec-1, which are superior to those of commercial RuO2 catalyst for OER. The LDH/OOH heterojunction involves strong interfacial coupling, which modulates the local electronic environment and boosts the kinetics of charge transfer. In addition, the high valence Fe3+ and Mn3+ species formed after NaOH treatment provide more active sites and promote the Ni2+ to higher oxidation states during the O2 evolution. Moreover, graphene contributes a lot to the reduction of charge transfer resistance. The combining effects have greatly enhanced the catalytic ability for OER, demonstrating that the synthesized NFM LDH/OOH heterojunction with graphene linkage can be practically applied as a high-performance electrocatalyst for oxygen production via water splitting.

Combined lifestyle factors on mortality among the elder population: evidence from a Chinese cohort study.

BACKGROUND: Numerous studies have suggested that lifestyle-related factors are associated with mortality, however limited evidence is available for the Chinese elder population. METHODS: The data of this study was obtained from the Chinese Longitudinal Health Survey (CLHLS) during 2008 - 2018, lifestyle-related factors including body mass index (BMI), smoking, drinking, consumption of vegetables and fruits, physical activity and sleep duration were included as dependent variables in the analysis. A lifestyle risk score was created using six unhealthy behaviors: smoking, drinking, unhealthy weight, physical inactivity, not eat vegetables or fruits and short or prolonged sleep. The Kaplan-Meier curves were used to illustrate the cumulative effect of lifestyle factors on mortality and cox regression models were conducted to estimate the combined effects of lifestyle-related factors on total mortality. RESULTS: The results illustrated that low BMI, smoking, no fruit eating, and no physical inactivity were risk factors for total mortality. KM curves showed significant cumulative effect of unhealthy lifestyle factors on mortality. Compared with participants without any unhealthy factors, the hazard ratio (HR) for participants with six unhealthy factors was 1.335 (1.015,1.757) for all-cause mortality. CONCLUSIONS: This study demonstrated poor adherence to a healthy lifestyle may increase all-cause mortality and specific combinations of lifestyle related factors have different effects on mortality among Chinese elderly population.

Microtubule depolymerization limits porcine betacoronavirus PHEV replication.

Porcine hemagglutinating encephalomyelitis virus (PHEV) is a typical neurotropic betacoronavirus causing digestive disease and/or neurological dysfunction in neonatal pigs. Actin filaments have been identified to implicate in PHEV invasion, but the effects of viral infection on microtubules (MTs) cytoskeleton are unknown. Here, we observed that PHEV infection induced MT depolymerization and was accompanied by the disappearance of microtubule organizing centers. Depolymerization of MTs induced by nocodazole significantly inhibited viral RNA replication, but over-polymerization of MTs induced by paclitaxel did not substantially affect PHEV infection. The expression of histone deacetylase 6 (HDAC6), an important regulator of MT acetylation, progressively increased during PHEV infection. Tramstatin A could alter HDAC6 deacetylase activity to enhance the acetylation of the substrate α-tubulin and MT polymerization, but does not increase PHEV proliferation. These findings suggest that PHEV could subvert host MT cytoskeleton to facilitate infection, and that MT depolymerization negatively affects viral replication independently of HDAC6 activity.

Development of Fixed-Wing UAV 3D Coverage Paths for Urban Air Quality Profiling.

Due to the ever-increasing industrial activity, humans and the environment suffer from deteriorating air quality, making the long-term monitoring of air particle indicators essential. The advances in unmanned aerial vehicles (UAVs) offer the potential to utilize UAVs for various forms of monitoring, of which air quality data acquisition is one. Nevertheless, most current UAV-based air monitoring suffers from a low payload, short endurance, and limited range, as they are primarily dependent on rotary aerial vehicles. In contrast, a fixed-wing UAV may be a better alternative. Additionally, one of the most critical modules for 3D profiling of a UAV system is path planning, as it directly impacts the final results of the spatial coverage and temporal efficiency. Therefore, this work focused on developing 3D coverage path planning based upon current commercial ground control software, where the method mainly depends on the Boustrophedon and Dubins paths. Furthermore, a user interface was also designed for easy accessibility, which provides a generalized tool module that links up the proposed algorithm, the ground control software, and the flight controller. Simulations were conducted to assess the proposed methods. The result showed that the proposed methods outperformed the existing coverage paths generated by ground control software, as it showed a better coverage rate with a sampling density of 50 m.

The PERK/PKR-eIF2α Pathway Negatively Regulates Porcine Hemagglutinating Encephalomyelitis Virus Replication by Attenuating Global Protein Translation and Facilitating Stress Granule Formation.

The replication of coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and the recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is closely associated with the endoplasmic reticulum (ER) of infected cells. The unfolded protein response (UPR), which is mediated by ER stress (ERS), is a typical outcome in coronavirus-infected cells and is closely associated with the characteristics of coronaviruses. However, the interaction between virus-induced ERS and coronavirus replication is poorly understood. Here, we demonstrate that infection with the betacoronavirus porcine hemagglutinating encephalomyelitis virus (PHEV) induced ERS and triggered all three branches of the UPR signaling pathway both in vitro and in vivo. In addition, ERS suppressed PHEV replication in mouse neuro-2a (N2a) cells primarily by activating the protein kinase R-like ER kinase (PERK)-eukaryotic initiation factor 2α (eIF2α) axis of the UPR. Moreover, another eIF2α phosphorylation kinase, interferon (IFN)-induced double-stranded RNA-dependent protein kinase (PKR), was also activated and acted cooperatively with PERK to decrease PHEV replication. Furthermore, we demonstrate that the PERK/PKR-eIF2α pathways negatively regulated PHEV replication by attenuating global protein translation. Phosphorylated eIF2α also promoted the formation of stress granules (SGs), which in turn repressed PHEV replication. In summary, our study presents a vital aspect of the host innate response to invading pathogens and reveals attractive host targets (e.g., PERK, PKR, and eIF2α) for antiviral drugs. IMPORTANCE Coronavirus diseases are caused by different coronaviruses of importance in humans and animals, and specific treatments are extremely limited. ERS, which can activate the UPR to modulate viral replication and the host innate response, is a frequent occurrence in coronavirus-infected cells. PHEV, a neurotropic betacoronavirus, causes nerve cell damage, which accounts for the high mortality rates in suckling piglets. However, it remains incompletely understood whether the highly developed ER in nerve cells plays an antiviral role in ERS and how ERS regulates viral proliferation. In this study, we found that PHEV infection induced ERS and activated the UPR both in vitro and in vivo and that the activated PERK/PKR-eIF2α axis inhibited PHEV replication through attenuating global protein translation and promoting SG formation. A better understanding of coronavirus-induced ERS and UPR activation may reveal the pathogenic mechanism of coronavirus and facilitate the development of new treatment strategies for these diseases.

Preparation of Ag3PO4/TiO2(B) Heterojunction Nanobelt with Extended Light Response and Enhanced Photocatalytic Performance.

Photocatalytic degradation, as an emerging method to control environmental pollution, is considered one of the most promising environmental purification technologies. As Tibet is a region with some of the strongest solar radiation in China and even in the world, it is extremely rich in solar energy resources, which is ideal for applying photocatalytic technology to its ecological environment protection and governance. In this study, Na2Ti3O7 nanobelts were prepared via a hydrothermal method and converted to TiO2∙xH2O ion exchange, which was followed by high-temperature calcination to prepare TiO2(B) nanobelts ("B" in TiO2(B) means "Bronze phase"). A simple in situ method was used to generate Ag3PO4 particles on the surface of the TiO2 nanobelts to construct a Ag3PO4/TiO2(B) heterojunction composite photocatalyst. By generating Ag3PO4 nanoparticles on the surface of the TiO2(B) nanobelts to construct heterojunctions, the light absorption range of the photocatalyst was successfully extended from UV (ultraviolet) to the visible region. Furthermore, the recombination of photogenerated electron-hole pairs in the catalyst was inhibited by the construction of the heterojunctions, thus greatly enhancing its light quantum efficiency. Therefore, the prepared Ag3PO4/TiO2(B) heterojunction composite photocatalyst greatly outperformed the TiO2(B) nanobelt in terms of photocatalytic degradation.

Detection of average methylation level of specific genes by binary-probe hybridization.

We developed a simple and highly-selective method for 5-methylcytosine detection of specific gene sequence based on binary-probe DNA hybridization. The sequence complementary to the target was designed into two probes, and each fragment of binary probes bound to a relatively short sequence of the target, which made it sensitive to the base mismatches introduced by bisulfite treatment. The advantages of a low detection limit of methylation abundance of 0.1% for the fully methylated target and high sensitivity of 10 pM have been proved by the successful design of binary-probe hybridization. The successful design of the binary probes makes it possible to quantify the average methylation levels of five CpG sites. Thirty-two DNA strands containing 5, 4, 3, 2, 1 and 0 CpG sites were successfully analyzed with the same pair of binary probes. The higher the average methylation level of the target was, the higher the degree of the hybridization reaction. Based on the simple construction of the binary-probe hybridization, the developed biosensor exhibited signals proportional to the average methylation level of the vimentin gene and could evaluate the average methylation level of artificial mixtures. Furthermore, the method has been used to detect vimentin methylation in a genomic context with good specificity, which indicated its potential in the pre-diagnosis of methylation related disease.

Fabrication of Highly Textured 2D SnSe Layers with Tunable Electronic Properties for Hydrogen Evolution.

Hydrogen is regarded to be one of the most promising renewable and clean energy sources. Finding a highly efficient and cost-effective catalyst to generate hydrogen via water splitting has become a research hotspot. Two-dimensional materials with exotic structural and electronic properties have been considered as economical alternatives. In this work, 2D SnSe films with high quality of crystallinity were grown on a mica substrate via molecular beam epitaxy. The electronic property of the prepared SnSe thin films can be easily and accurately tuned in situ by three orders of magnitude through the controllable compensation of Sn atoms. The prepared film normally exhibited p-type conduction due to the deficiency of Sn in the film during its growth. First-principle calculations explained that Sn vacancies can introduce additional reactive sites for the hydrogen evolution reaction (HER) and enhance the HER performance by accelerating electron migration and promoting continuous hydrogen generation, which was mirrored by the reduced Gibbs free energy by a factor of 2.3 as compared with the pure SnSe film. The results pave the way for synthesized 2D SnSe thin films in the applications of hydrogen production.

Multi-omics analysis of the prognosis and therapeutic significance of circadian clock in ovarian cancer.

Ovarian cancer (OV) is one of the most common female malignancies with high morbidity and mortality, but its mechanism is not fully understood. The circadian clock is involved in the regulation of the immune system and the tumor microenvironment, regulating biological processes and behaviors in multiple ways. Circadian rhythm disorders are considered a risk factor for tumorigenesis. Multi-omics analysis was performed to comprehensively illustrate the roles of circadian clock genes in OV, we found that most of circadian clock genes undergo epigenetic alterations in OV and are strongly correlated with overall and progression-free patient survival. These clock genes are mainly involved in the inhibition of Apoptosis pathway, Cell Cycle pathway and DNA Damage Response pathway, as well as the activation of RAS/MAPK pathway and RTK pathway. Drug sensitivity model indicate that the expression of core clock genes may associate with drug resistance. Further, immune infiltrates analysis shows that different mutant forms of core genes can not only suppress immune infiltration, but also affect clinical outcome of ovarian cancer patients. Overall, our results may provide novel insights for the potential selection of immunotherapeutic targets.