Aging disrupts the link between network centrality and functional properties of prefrontal neurons during memory-guided behavior.

The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with neuronal activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences in degree centrality-a measure of connectivity strength within local circuits-could explain this neuronal diversity and its functional implications. In young adults, neurons with high degree centrality, inferred from resting-state activity, exhibit reliable and stable action-plan selectivity during memory-guided tasks, suggesting that connectivity strength is closely linked to functional heterogeneity.

Investigating male factors and their relationships with reproductive health outcomes: a case-control study protocol for Towards Optimal Fertility, Fathering, and Fatherhood studY (TOFFFY) in Singapore.

Introduction: Despite the global prevalence of low fertility rates, male contributions to fertility and reproductive health outcomes have been understudied. This study aims to investigate the male contribution to fertility and explore the underlying biological mechanisms. Specifically, we aim to (1) identify male factors associated with successful pregnancy, (2) develop a fertility index incorporating modifiable factors for both males and females to predict pregnancy rate and (3) explore the relationship of male modifiable factors with semen parameters and molecular characteristics.

Taming Highly Enolizable Aldehydes via Enzyme Catalysis for Enantiocomplementary Construction of β-Hydroxyphosphonates.

Taming highly enolizable aldehydes for catalytic asymmetric C-C coupling with nucleophiles remains an elusive challenge compared to widely explored simple alkyl or aryl aldehydes. Herein, we use ThDP-dependent enzymes to realize the direct C-C coupling of highly enolizable 2-phosphonate aldehydes with in situ-generated dynamically reversible nucleophiles (acyl anions). Unlike NHC-mediated reactions that yield complex mixtures of multiple adducts, our enzymatic process selectively produces biologically active β-hydroxy phosphonates with high yields (up to 95%) and excellent enantioselectivities (up to 99% ee).

Rapid on-site determination of heavy metals and metalloids in contaminated biochar samples by accelerated leaching process coupled with voltammetric sensors.

Heavy metals and metalloids are the most common environmental pollutants. Toxicity characteristic leaching procedure (TCLP) is a standard operating procedure that is used to assess heavy metal and metalloid compositions, and evaluate the hazardous nature of waste and waste-derived materials for reuse or disposal, such as determining landfill suitability. However, TCLP and the following detections are time-consuming and require bulky laboratory-based instruments and trained personnel.

Defining the Critical Requisites for Accurate Simulation of SARS-CoV-2 Viral Dynamics: Patient Characteristics and Data Collection Protocol.

Mathematical models of viral dynamics are crucial in understanding infection trajectories. However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load data often includes limited sparse observations with significant heterogeneity. This study aims to: (1) understand the impact of patient characteristics in shaping the temporal viral load trajectory and (2) establish a data collection protocol (DCP) to reliably reconstruct individual viral load trajectories.

Crafting Hollow Spheres via Bulk Ice Melting with ppb-Level Gas Sensing Performance.

Ice melting, a common yet complex phenomenon, remains incompletely understood. While theoretical studies suggest that preexisting defects in ice generate "off-lattice" water molecules, triggering bulk ice melting, direct experimental evidence of their form has been lacking as the transparent and transient nature of ice poses significant challenges for observation with current techniques. Here, we introduce an ice-melting-induced lyophilization (IMIL) technique that employs graphene-based nanoprobes to replicate and track liquid evolution within melting bulk ice.

STDCformer: Spatial-temporal dual-path cross-attention model for fMRI-based autism spectrum disorder identification.

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique widely utilized in the research of Autism Spectrum Disorder (ASD), providing preliminary insights into the potential biological mechanisms underlying ASD. Deep learning techniques have demonstrated significant potential in the analysis of rs-fMRI. However, accurately distinguishing between healthy control group and ASD has been a longstanding challenge.

A comprehensive study of quantum arithmetic circuits.

In recent decades, the field of quantum computing has experienced remarkable progress. This progress is marked by the superior performance of many quantum algorithms compared with their classical counterparts, with Shor's algorithm serving as a prominent illustration. Quantum arithmetic circuits, which are the fundamental building blocks in numerous quantum algorithms, have attracted much attention.

Systematic bibliographic analysis of heavy metal remediation.

Heavy metals pose a significant threat to human health, with contaminated water sources linked to severe conditions, including gastric cancer. Consequently, the effective remediation of heavy metals is crucial. This study employs a bibliographic analysis to examine key methodologies, leading organizations, and prominent countries involved in heavy metal remediation.

Causality-driven candidate identification for reliable DNA methylation biomarker discovery.

Despite vast data support in DNA methylation (DNAm) biomarker discovery to facilitate health-care research, this field faces huge resource barriers due to preliminary unreliable candidates and the consequent compensations using expensive experiments. The underlying challenges lie in the confounding factors, especially measurement noise and individual characteristics. To achieve reliable identification of a candidate pool for DNAm biomarker discovery, we propose a Causality-driven Deep Regularization framework to reinforce correlations that are suggestive of causality with disease.

Additive Effects of Natural Plant Extracts/Essential Oils and Probiotics as an Antipathogenic Topical Skin Patch Solution for Acne and Eczema.

This work leverages the additive antipathogenic effects of natural extracts/essential oils (EOs) and probiotics for the treatment of acne vulgaris associated with () and eczema complicated by secondary infections with (). Six probiotic strains and various extracts/EOs were evaluated in a large screening to evaluate their potential against both pathogens. PCB003 was able to inhibit the growth of both pathogens.

Enhancing catalytic activity in MoC nanodots via nitrogen doping and graphene integration for efficient hydrogen evolution under alkaline conditions.

Due to its exceptional electronic properties and catalytic activity, MoC has garnered significant attention for its application in electrocatalysis, particularly for the hydrogen evolution reaction (HER). However, several critical challenges continue to impede its widespread use, especially under strongly alkaline conditions. A primary obstacle is the enhancement of its intrinsic activity through further modification strategies, which remains a key limitation for its broader utilization.

Metallic Electro-optic Effect in Gapped Bilayer Graphene.

Electro-optic (EO) modulation is a critical device action in photonics. Recently, the non-Drude dynamics induced by the Berry curvature dipole (BCD) in metals have attracted attention as a potential candidate for terahertz EO modulation. However, such BCD-induced EO effects can be challenging to realize, often requiring flat bands and complex materials such as a strained magic-angle twisted bilayer graphene on hexagonal boron nitride.

Utilizing deep learning to predict Alzheimer's disease and mild cognitive impairment with optical coherence tomography.

Introduction: Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. We aimed to develop a deep-learning algorithm using OCT to detect AD and MCI.

Methods: We performed a cross-sectional study involving 228 Asian participants (173 cases/55 controls) for model development and testing on 68 Asian (52 cases/16 controls) and 85 White (39 cases/46 controls) participants.

Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning.

The discovery of the optimal conditions for chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically, the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and through the design of experiments where reaction variables are modified one at a time to find the optimal conditions for a specific reaction outcome. Recently, a paradigm change in chemical reaction optimization has been enabled by advances in lab automation and the introduction of machine learning algorithms.

Robustness of machine learning predictions for Fe-Co-Ni alloys prepared by various synthesis methods.

Developing high-performance alloys is essential for applications in advanced electromagnetic energy conversion devices. In this study, we assess Fe-Co-Ni alloy compositions identified in our previous work through a machine learning (ML) framework, which used both multi-property ML models and multi-objective Bayesian optimization to design compositions with predicted high values of saturation magnetization, Curie temperature, and Vickers hardness. Experimental validation was conducted on two promising compositions synthesized using three different methods: arc melting, ball milling followed by spark plasma sintering (SPS), and chemical synthesis followed by SPS.

Roles for the long non-coding RNA / in pancreatic beta cell function.

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of beta cell function. Here, we show that an lncRNA-transcribed antisense to Pax6, annotated as Pax6os1/PAX6-AS1, was upregulated by high glucose concentrations in human as well as murine beta cell lines and islets. Elevated expression was also observed in islets from mice on a high-fat diet and patients with type 2 diabetes.

NIR-II photo-accelerated polymer nanoparticles boost tumor immunotherapy via PD-L1 silencing and immunogenic cell death.

Immune checkpoint blockade (ICB) therapy is a widely favored anti-tumor treatment, but it shows limited response to non-immunogenic "cold" tumors and suffers from drug resistance. Photodynamic therapy (PDT), as a powerful localized treatment approach, can convert a "cold tumor" into a "hot tumor" by inducing immunogenic cell death (ICD) in tumor cells, thereby enhancing tumor immunogenicity and promoting tumor immunotherapy. However, the effectiveness of PDT is largely hindered by the limited penetration depth into tumor tissues.

Effectiveness of Mobile Health Applications for Cardiometabolic Risk Reduction in Urban and Rural India: A Pilot, Randomized Controlled Study.

Introduction: mHealth technology has the potential to deliver personalized health care; however, data on cardiometabolic risk factors are limited. This study aims to assess the effectiveness of mobile health applications (apps) on cardiometabolic risk factor reduction in adults aged 25 to 60 years in urban and rural India.

Methods: The study design was a pilot randomized controlled trial conducted in Tamil Nadu, India.

Social Responsibility Appeal and Cross-Lagged Effects of Perceived Norms on Mask-Wearing Behavior During the COVID-19 Pandemic.

This study extends the Theory of Normative Social Behavior by examining the cross-lagged effects of perceived norms on mask-wearing intention and behavior during an evolving COVID-19 pandemic. We also investigate the normative mechanisms of how social responsibility appeals improve compliance with mask-wearing behavior. A two-wave panel survey ( = 767) was conducted in Singapore in March and April 2020.

Leveraging Iron in the Electrolyte to Improve Oxygen Evolution Reaction Performance: Fundamentals, Strategies, and Perspectives.

Electrochemical water splitting is a pivotal technology for storing intermittent electricity from renewable sources into hydrogen fuel. However, its overall energy efficiency is impeded by the sluggish oxygen evolution reaction (OER) at the anode. In the quest to design high-performance anode catalysts for driving the OER under non-acidic conditions, iron (Fe) has emerged as a crucial element.

Feasibility of long-range telesurgical robotic radical gastrectomy in a live porcine model.

Background: Telesurgery has been made increasingly possible with the advancements in robotic surgical platforms and network connectivity. However, long-distance transnational complex robotic surgeries such as gastrectomy have yet to be attempted.

Methods: Multiple transnational network connections by Science Innovation Network (SINET), Japan Gigabit Network (JGN), and Arterial Research and Education Network in Asia-Pacific (ARENA-PAC) were established and tested by multiple surgeons in a dry box model.

Ultimate water capillary evaporation in bamboo-inspired evaporator.

Bionic evaporators inspired by natural plants like bamboo and mushrooms have emerged as efficient generators through water capillary evaporation. However, primitive natural evaporators cannot currently meet growing demand, and their performance limitations remain largely unexplored, presenting a substantial challenge. Through extensive experimentation and detailed simulation analysis, this study presents a precisely engineered H-type bamboo steam generator.

Half a Century's Quest for Seasonal Hyperacute Panuveitis (SHAPU): From Academic Curiosity to Public Health Concern.

For the past 50 years, significant progress has been made in understanding Seasonal Hyperacute Panuveitis (SHAPU), a mysterious blinding disease first reported in Nepal in 1975. Predominantly affecting Nepalese children, SHAPU occurs cyclically every odd year from September to December. While initially misclassified as endophthalmitis, SHAPU is set apart by its lack of trauma or surgery, failure to grow organisms in most intraocular fluid cultures, and its hallmark presentation of a "white pupil in red eye" with an association with moth exposure.

Investigating frontoparietal networks and activation in children with mathematics learning difficulties: Cases with different deficit profiles.

Approximately 15%-20% of school-aged children suffer from mathematics learning difficulties (MLD). Most children with developmental dyscalculia (DD) or MLD also have comorbid cognitive deficits. Recent literature suggests that research should focus on uncovering the neural underpinnings of MLD across more inclusive samples, rather than limiting studies to pure cases of DD or MLD with highly stringent inclusion criteria.