Leveraging population information in brain connectivity via Bayesian ICA with a novel informative prior for correlation matrices.

Brain functional connectivity (FC), the temporal synchrony between brain networks, is essential to understand the functional organization of the brain and to identify changes due to neurological disorders, development, treatment, and other phenomena. Independent component analysis (ICA) is a matrix decomposition method used extensively for simultaneous estimation of functional brain topography and connectivity. However, estimation of FC via ICA is often sub-optimal due to the use of ad hoc estimation methods or temporal dimension reduction prior to ICA.

Sustainable Production of Bio-Based Geraniol: Heterologous Expression of Early Terpenoid Pathway Enzymes in .

Geraniol is a monoterpene alcohol with a rose-like aroma, used in food and cosmetics and for its anti-inflammatory, antibacterial, and insect-repellent properties. Geraniol is commonly chemically synthesized from petroleum-based sources in a highly energy-demanding process with a large carbon footprint. Alternatively, geraniol can be derived from plant-based essential oils but with relatively low yields and limitations from seasonal cultivation.

Photosensitized Decay of Levoglucosan in Biomass Burning Aerosol Particles.

Biomass burning (BB) is increasingly relevant to air quality as global warming intensifies wildfire activity. Levoglucosan (LEVO) is a widely used tracer for BB, but its oxidative decay is still less understood. While gas-phase hydroxyl radicals (•OH) have been considered the primary oxidants for LEVO decay in biomass burning organic aerosol (BBOA) particles, high particulate viscosity at low relative humidity (RH) limits •OH uptake.

GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis.

Background: Gene-Set Analysis (GSA) is commonly used to analyze high-throughput experiments. However, GSA cannot readily disentangle clusters or pathways due to redundancies in upstream knowledge bases, which hinders comprehensive exploration and interpretation of biological findings. To address this challenge, we developed GeneSetCluster, an R package designed to summarize and integrate GSA results.

A homochiral covalent organic framework membrane for the enantioseparation and fractionation of amino acids.

The separation of amino acids from complex mixtures remains an essential yet multi-step, energy-intensive process. Membrane separation technology offers a more energy-efficient alternative, but its effectiveness relies on achieving highly precise molecular recognition. Here, we report a homochiral covalent organic framework (COF) membrane with ordered ultra-microporous pore structures for targeted extraction of specific enantiomer from amino acid mixtures.

Long lifespan and substantial biomass production support stable high biomass of Ascophyllum nodosum under interannual climate fluctuations in Greenland.

The brown macroalga Ascophyllum nodosum is a foundation species on intertidal rocky shores, where its perennial canopy and high productivity support key ecological functions. However, its population dynamics near the northern edge, where low temperatures and sea ice may challenge stability, are largely unknown. We followed the population structure, dynamics, and nutrient status of A.

MolPrompt: Improving multi-modal molecular pre-training with knowledge prompts.

Motivation: Molecular pre-training has emerged as a foundational approach in computational drug discovery, enabling the extraction of expressive molecular representations from large-scale unlabeled datasets. However, existing methods largely focus on topological or structural features, often neglecting critical physicochemical attributes embedded in molecular systems.

Result: We present MolPrompt, a knowledge-enhanced multimodal pre-training framework that integrates molecular graphs and textual descriptions via contrastive learning.

A receptor antagonist counterbalances multiple systemin phytocytokines in tomato.

Tight regulation of immune activation is crucial for plant health. How plants control the actions of their immunostimulatory phytocytokines is largely unknown. Here, we identify antiSYS as a natural inhibitor of the tomato cytokine systemin.

Gabor-enhanced physics-informed neural networks for fast simulations of acoustic wavefields.

Physics-Informed Neural Networks (PINNs) have gained attention for solving partial differential equations, including the scattered Helmholtz equation, due to their flexibility and mesh-free formulation. However, their performance suffers from low-frequency bias, particularly in high-frequency wavefield simulations, limiting convergence speed and accuracy. To address this, we propose a novel and simplified PINN framework that incorporates explicit, trainable Gabor basis functions to efficiently capture the localized and oscillatory nature of wavefields.

Integrative molecular network analysis of genetic risk factors to infer biomarkers and therapeutic targets for rheumatoid arthritis.

Background: Understanding the interplay between genetic risk factors and molecular pathways in rheumatoid arthritis (RA) is essential for developing effective treatments. This study aims to utilize genetic risk factors of RA and identify their key pathways and potential therapeutic targets through an integrated multi-omics approach.

Methods: We developed a computational pipeline to construct a knowledge graph that combines genetic risk factor molecular networks with multi-omics enrichment analysis to estimate potential therapeutic target for RA.

Entropy-Regulated Selective Synthesis of Cyclic Polymers and Polycatenanes by Lewis Pair Polymerization.

While cyclic polymers offer a suite of unique material properties relative to their linear counterparts, their precision synthesis remains challenging and often relies on highly dilute reaction conditions to promote topological selectivity. Here, we unravel the nature of a Lewis pair polymerization (LPP) system that has demonstrated itself to be an exception to this general rule. To understand the unique, apparently concentration-independent, topological selectivity observed within this LPP system, we have paired specifically designed experimental studies with computational calculations to develop a mechanistic framework centered on an entropically driven dynamic equilibrium between intermolecular and intramolecular forms of electrostatic preorganization of polymer termini.

Integrated accuracy enhancement for the Fabry-Pérot interferometer: The multi-parameter approach series (MPAS).

Fabry-Pérot white light interferometry is at the heart of the surface force apparatus (SFA). One of the applications of SFA is the measurement of properties of sub-nanometer-confined fluids. For the determination of the properties of a confined fluid, the absolute accuracy of SFA is directly linked to the accuracy of the parameters describing the optical layers of the interferometer, particularly the micrometer thick mica spacer layers.

The Role of Random Texture Scattering on the Absorptance Enhancement in Halide Perovskite Layers.

Hybrid perovskites are a class of thin-film semiconductors with remarkably steep absorption edges and high absorption coefficient. In the case of solar cells, a film thickness of less than a micrometer is usually sufficient to absorb most of the light when combined with a back reflector. Otherwise, an efficient light trapping strategy may be desired, e.

SCRIPT: Predicting Single-Cell Long-Range Cis-Regulation Based on Pretrained Graph Attention Networks.

Single-cell cis-regulatory relationships (CRRs) are essential for deciphering transcriptional regulation and understanding the pathogenic mechanisms of disease-associated non-coding variants. Existing computational methods struggle to accurately predict single-cell CRRs due to inadequately integrating causal biological principles and large-scale single-cell data. Here, SCRIPT (Single-cell Cis-regulatory Relationship Identifier based on Pre-Trained graph attention networks) is presented for inferring single-cell CRRs from transcriptomic and chromatin accessibility data.

DFT Investigations and Molecular Docking as Potent Inhibitors of SARS-CoV-2 Main Protease of Novel Pyrimidine Dione Derivatives.

The global outbreak of SARS-CoV-2 has emerged as a major public health crisis due to its rapid transmission and significant morbidity and mortality rates. In response, there is an urgent need to discover novel antiviral agents targeting key viral proteins. In this study, a new series of pyrimidine-2,4-dione derivatives was synthesized from barbituric acid and its thio analog, aiming to explore their potential inhibitory activity against the SARS-CoV-2 main protease (Mpro).

High-Nuclearity Copper Molecular Catalysts for Electrocatalytic CO-to-Acetate Conversion.

Ligand-modified metal nanoclusters (NCs) have emerged as candidate materials for catalysis owing to their well-defined yet tunable structure and their metal centers' high nuclearity. We posited that NC-based catalytic behavior will depend on ligand properties, the accessibility of active sites, and their atomic configuration. We synthesized a series of Cu NC-based catalysts, tuned local hydrophobicity through ligand adjustment, balanced the ligand coverage and active site exposure, and found that we were, in this way, able to engender efficient electrosynthesis of acetate via CO electroreduction.

Adjustable SiC interfacial layers toward reliable Si-based anode applications.

The incorporation of a SiC interfacial layer has been recognized as an effective strategy to tackle the interface contact issue between Si and carbon, ensuring the structural integrity of Si-based anodes and thereby enhancing their cycling stability. However, its inherent low activity and poor conductivity pose a persistent challenge for maximizing capacity and facilitating ion and electron transport. Here, we present a thickness/content adjustable SiC interfacial layer in the Si-SiC-C heterostructure using a modified spark plasma sintering technique.

Warming climate and water withdrawals threaten river flow connectivity in China.

River flow connectivity, the continuity of fluvial discharge in space and time, provides a crucial lifeline for most biotic communities on Earth. Yet there is still limited understanding of the impacts of climate change and human water withdrawal on river connectivity. Here, we assess the river flow connectivity of 217,001 river reaches in mainland China from 1961 to 2020 and the impact of different climate warming trends and water withdrawals for different sectors.

Germline variants in are associated with multilocus imprinting disturbance in humans and mice.

The investigation of congenital imprinting disorders (CIDs) provides opportunities to elucidate the molecular mechanisms and role of genomic imprinting in development and human disease. Beckwith-Wiedemann spectrum (BWSp) is a prototypic CID resulting from genetic and epigenetic alterations of imprinted genes at chromosome 11p15.5.

Dengue nowcasting in Brazil by combining official surveillance data and Google Trends information.

Dengue is a mosquito-borne viral disease that poses significant public health challenges in tropical and sub-tropical regions worldwide. Surveillance systems are essential for dengue prevention and control. However, traditional systems often rely on delayed data, limiting their effectiveness.

Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation.

Common measures of brain functional connectivity (FC) including covariance and correlation matrices are symmetry-positive definite (SPD) matrices residing on a cone-shaped Riemannian manifold. Despite its remarkable success for Euclidean-valued data generation, the use of standard generative adversarial networks (GANs) to generate manifold-valued FC data neglects its inherent SPD structure and hence the inter-relatedness of edges in real FC. We propose a novel graph-regularized manifold-aware conditional Wasserstein GAN (GR-SPD-GAN) for FC data generation on the SPD manifold that can preserve the global FC structure.

Synthesis of Crystalline Covalent Organic Frameworks Crosslinked through Hydrogen Bonding.

Covalent organic frameworks crosslinked through hydrogen bonding (HcCOFs) exhibit considerable potential in combining the advantages of the stability of the covalent bonds with the flexibility and reversibility of the hydrogen bonds, creating a unique platform for assembling organic units into crystalline porous materials with unique properties and functions. In this work, a new crystalline HcCOF material is successfully synthesized for the first time via Schiff's base reaction and carboxylic acid self-assembly. This material exhibits a response to humidity and efficient atmospheric water-harvesting capabilities, showcasing its potential in materials science and providing a new path for future innovations in gas storage, catalysis, sensors, drug delivery, etc.

View Micronuclei in the Extent of Evolution: New Insight Into an Old Issue.

Micronuclei (MNs), once regarded as cellular debris or genotoxicity markers, can also be recognized as dynamic structures with potential evolutionary significance. In tumor models, MNs promote clonal diversification, mutagenesis, and adaptation. MNs' interaction with the conserved cGAS-STING pathway reflects dual roles in immune defense for the individual and adaptive response for cell under stress.

Characterization of nanoplastics and small-sized microplastics in sewage treatment.

The presence of nanoplastics (NPs) in sewage treatment plants (STPs) remains a critical yet underexplored environmental issue. Here, we present a novel investigation into the occurrence, recovery, and characterization of nanoplastics and small-size microplastics (50-2500 nm) in raw and treated sewage effluent from a full-scale STP (treating 4000 m/day) operating with activated sludge. To our knowledge, this research includes the first confirmed assessment of nanoplastics in such a system and applies nano-flow cytometry to wastewater analysis for the first time globally.