Scaling relations of CO hydrogenation and dissociation on single metal atom doped InO catalysts with promoted oxygen vacancy sites.

In this work, we conducted a computational study on single atom doped InO catalysts with 12 transition metals (Fe-Cu, Ru-Ag, Os-Au) through density functional theory (DFT) calculations, by investigating the dissociation of H, and the dissociation and hydrogenation of CO. From the thermodynamic-kinetic scaling relationships such as Brønsted-Evans-Polanyi (BEP) and transition-state scaling (TSS) relations, we establish the descriptors for the energy barriers and improve our understanding of the synergistic catalytic effect of oxygen vacancies and single atoms. We find that the adsorption energy of the H adatom on the perfect surface can serve as an effective descriptor for the dissociation energy barrier of H on this surface, and the formation energy of the oxygen vacancy can serve as an effective descriptor for the energy barrier of CO hydrogenation to HCOO as well as the energy barrier of CO direct dissociation.

Relationship of OCT-Based Diabetic Retinal Neurodegeneration to the Development and Progression of Diabetic Retinopathy: A Cohort Study.

Purpose: To evaluate the relationship between diabetic retinal neurodegeneration (DRN), as quantified by optical coherence tomography (OCT), to the development of diabetic retinopathy (DR), progression of DR, and development of proliferative DR (PDR).

Methods: This was a prospective cohort study, including 385 eyes with no DR or nonproliferative DR at baseline. The thicknesses of the macular ganglion cell-inner plexiform layer (m-GCIPL), macular retinal nerve fiber layer, and peripapillary RNFL (p-RNFL) were measured using Cirrus OCT (Carl Zeiss Meditec, Dublin, CA, USA).

Uncertainty-aware genomic deep learning with knowledge distillation.

Deep neural networks (DNNs) have advanced predictive modeling for regulatory genomics, but challenges remain in ensuring the reliability of their predictions and understanding the key factors behind their decision making. Here we introduce DEGU (Distilling Ensembles for Genomic Uncertainty-aware models), a method that integrates ensemble learning and knowledge distillation to improve the robustness and explainability of DNN predictions. DEGU distills the predictions of an ensemble of DNNs into a single model, capturing both the average of the ensemble's predictions and the variability across them, with the latter representing epistemic (or model-based) uncertainty.

Environmental Stability Determines the Cytotoxicity of Metal-Organic Frameworks to a Nitrogen-Fixing Bacterium .

During widespread applications of metal-organic frameworks (MOFs), the environmental hazards and risks of MOFs have aroused great concerns. In this study, we aimed to reveal the importance of the environmental stability of MOFs on their toxicity. Two Zn-MOFs, namely, ZIF-8 with high aqueous stability and Zn-BDC with low aqueous stability, were compared directly in the toxicological evaluations of a nitrogen-fixing bacterium .

Reference-Based OCT Angiogram Super-Resolution With Learnable Texture Generation.

Optical coherence tomography angiography (OCTA) can visualize retinal microvasculature and is important to qualitatively and quantitatively identify potential biomarkers for different retinal diseases. However, the resolution of optical coherence tomography (OCT) angiograms inevitably decreases when increasing the field-of-view (FOV) given a fixed acquisition time. To address this issue, we propose a novel reference-based super-resolution (RefSR) framework to preserve the resolution of the OCT angiograms while increasing the scanning area.

The WAVE complex forms linear arrays at negative membrane curvature to instruct lamellipodia formation.

Cells generate a wide range of actin-based membrane protrusions for various cell behaviors. These protrusions are organized by different actin nucleation promoting factors. For example, N-WASP controls finger-like filopodia, whereas the WAVE complex controls sheet-like lamellipodia.

Pan-cancer analysis identifies olfactory receptor family 7 subfamily A member 5 as a potential biomarker for glioma.

Background: Human olfactory receptors (ORs) account for approximately 60% of all human G protein-coupled receptors. The functions of ORs extend beyond olfactory perception and have garnered significant attention in tumor biology. However, a comprehensive pan-cancer analysis of ORs in human cancers is lacking.

Environmental Toxicant Exposure and Depressive Symptoms.

Importance: Recognizing associations between exposure to common environmental toxicants and mental disorders such as depression is crucial for guiding targeted mechanism research and the initiation of disease prevention efforts.

Objectives: To comprehensively screen and assess the associations between potential environmental toxicants and depressive symptoms and to assess whether systemic inflammation serves as a mediator.

Design, Setting, And Participants: A total of 3427 participants from the 2013-2014 and 2015-2016 waves of the National Health and Nutrition Examination and Survey who had information on blood or urine concentrations of environmental toxicants and depression scores assessed by the 9-item Patient Health Questionnaire (PHQ-9) were included.

Efficient and Stable CuSCN-based Perovskite Solar Cells Achieved by Interfacial Engineering with Amidinothiourea.

Cuprous thiocyanate (CuSCN) emerges as a prime candidate among inorganic hole-transport materials, particularly suitable for the fabrication of perovskite solar cells. Nonetheless, there is an Ohmic contact degradation between the perovskite and CuSCN layers. This is induced by polar solvents and undesired purities, which reduce device efficiency and operational stability.

LRP1 facilitates hepatic glycogenesis by improving the insulin signaling pathway in HFD-fed mice.

Background: LDL receptor-related protein-1 (LRP1) is a cell-surface receptor that functions in diverse physiological pathways. We previously demonstrated that hepatocyte-specific LRP1 deficiency (hLRP1KO) promotes diet-induced insulin resistance and increases hepatic gluconeogenesis in mice. However, it remains unclear whether LRP1 regulates hepatic glycogenesis.

4'--MethylbavachalconeB Targeted 14-3-3ζ Blocking the Integrin β3 Early Outside-In Signal to Inhibit Platelet Aggregation and Thrombosis.

14-3-3ζ protein, the key target in the regulation and control of integrin β3 outside-in signaling, is an attractive new strategy to inhibit thrombosis without affecting hemostasis. In this study, 4'--methylbavachalconeB (4--MB) in Psoraleae Fructus was identified as a 14-3-3ζ ligand with antithrombosis activity by target fishing combined with ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) analysis. The competitive inhibition analysis showed that 4--MB targeted 14-3-3ζ and blocked the 14-3-3ζ/integrin β3 interaction with inhibition constant () values of 9.

Mudanpioside C Discovered from Andr. Acts as a Protein Disulfide Isomerase Inhibitor with Antithrombotic Activities.

Andr. is a well-known landscape plant worldwide and also holds significant importance in China due to its medicinal and dietary properties. Previous studies have found that Cortex Moutan (CM), the dried root bark of , showed antiplatelet and cardioprotective effects, although the underlying mechanism and active compounds remain to be revealed.

Evaluating the representational power of pre-trained DNA language models for regulatory genomics.

The emergence of genomic language models (gLMs) offers an unsupervised approach to learning a wide diversity of -regulatory patterns in the non-coding genome without requiring labels of functional activity generated by wet-lab experiments. Previous evaluations have shown that pre-trained gLMs can be leveraged to improve predictive performance across a broad range of regulatory genomics tasks, albeit using relatively simple benchmark datasets and baseline models. Since the gLMs in these studies were tested upon fine-tuning their weights for each downstream task, determining whether gLM representations embody a foundational understanding of -regulatory biology remains an open question.

Continuous synthesis of high-entropy alloy nanoparticles by in-flight alloying of elemental metals.

High-entropy alloy (HEA) nanoparticles (NPs) exhibit unusual combinations of functional properties. However, their scalable synthesis remains a significant challenge requiring extreme fabrication conditions. Metal salts are often employed as precursors because of their low decomposition temperatures, yet contain potential impurities.

SnO-Perovskite Interface Engineering Based on Bifacial Passivation via Multifunctional -(2-Acetamido)-2-aminoethanesulfonic Acid toward Efficient and Stable Solar Cells.

Bifacial passivation on both electron transport materials and perovskite light-absorbing layers as a straightforward technique is used for gaining efficient and stable perovskite solar cells (PSCs). To develop this strategy, organic molecules containing multiple functional groups can maximize the effect of defect suppression. Based on this, we introduce -(2-acetamido)-2-aminoethanesulfonic acid (ACES) at the interface between tin oxide (SnO) and perovskite.

PM constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study.

Background: The association of specific PM chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM exposure on the trajectory of children's body mass index (BMI) have not been explored.

Methods: We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM and its chemical constituents with incident OWOB risk.

A deep learning system for predicting time to progression of diabetic retinopathy.

Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images.

The impact of short-term exposures to ambient NO, O, and their combined oxidative potential on daily mortality.

It is widely recognized that air pollution exerts substantial detrimental effects in human health and the economy. The potential for harm is closely linked to the concentrations of pollutants like nitrogen dioxide (NO) and ozone (O), as well as their collective oxidative potential (O). Yet, due to the challenges of directly monitoring O as an independent factor and the influences of different substances' varying ability to contain or convey O, uncertainties persist regarding its actual impact.

Association of Short-Term Co-Exposure to Particulate Matter and Ozone with Mortality Risk.

A complex regional air pollution problem dominated by particulate matter (PM) and ozone (O) needs drastic attention since the levels of O and PM are not decreasing in many parts of the world. Limited evidence is currently available regarding the association between co-exposure to PM and O and mortality. A multicounty time-series study was used to investigate the associations of short-term exposure to PM, PM, PM, and O with daily mortality from different causes, which was based on data obtained from the Mortality Surveillance System managed by the Jiangsu Province Center for Disease Control and Prevention of China and analyzed via overdispersed generalized additive models with random-effects meta-analysis.

Expanding the toolset of fluorescent covalent staining of biological samples by labeling carboxylate and phosphate groups.

Recently, fluorescent covalent staining methods have been developed for visualization of anatomical structures in cells and tissues. Coupled with expansion microscopy, these stains revealed various ultrastructural details. However, the covalently stainable chemical groups have been limited to amines, carbohydrates, and thiols.

Simulation Optimization of AlGaN/GaN SBD with Field Plate Structures and Recessed Anode.

This study investigated several AlGaN/GaN Schottky Barrier Diodes (SBDs) with different designs to achieve device optimization. First, the optimal electrode spacing, etching depth, and field plate size of the devices were measured using Technology Computer-Aided Design (TCAD) software by Silvaco, and analysis of the electrical behavior of the device was based on the simulation results, and several AlGaN/GaN SBD chips were designed and prepared. The experimental results revealed that the recessed anode can increase the forward current and reduce the on-resistance.