Different fates between extracellular and intracellular antimicrobial resistome in full-scale activated sludge and membrane bioreactor processes.

Treated effluent of wastewater treatment plants (WWTPs) are major sources of extracellular antimicrobial resistance genes (eARGs) into aquatic environments. This study aimed to clarify the fate and origins of eARGs from influent to treated effluent at a full-scale WWTP. The compositions of eARG and intracellular ARG (iARG) were acquired via shotgun metagenomic sequencing in influent wastewater, activated sludge, and treated effluent of the target WWTP, where identical wastewater was treated by conventional activated sludge (CAS) and membrane bioreactor (MBR) processes.

Significant Impact of a Daytime Halogen Oxidant on Coastal Air Quality.

Chlorine radicals (Cl) are highly reactive and affect the fate of air pollutants. Several field studies in China have revealed elevated levels of daytime molecular chlorine (Cl), which, upon photolysis, release substantial amounts of Cl but are poorly represented in current chemical transport models. Here, we implemented a parametrization for the formation of daytime Cl through the photodissociation of particulate nitrate in acidic environments into a regional model and assessed its impact on coastal air quality during autumn in South China.

Direct Frequency Comb Cavity Ring-Down Spectroscopy Using Vernier Filtering.

We present direct frequency comb cavity ring-down spectroscopy with Vernier filtering as a straightforward approach to sensitive and multiplexed trace gas detection. The high finesse cavity acts both to extend the interaction length with the sample and as a spectral filter, alleviating the need for dispersive elements or an interferometer. In this demonstration, a free running interband cascade laser was used to generate a comb centered at 3.

Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques.

Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. The technique leverages a feature extraction method called Derivative Level Thresholding to pinpoint suspicious regions within an image.

Dynamic emotion intensity estimation from physiological signals facilitating interpretation via appraisal theory.

Appraisal models, such as the Scherer's Component Process Model (CPM), represent an elegant framework for the interpretation of emotion processes, advocating for computational models that capture emotion dynamics. Today's emotion recognition research, however, typically classifies discrete qualities or categorised dimensions, neglecting the dynamic nature of emotional processes and thus limiting interpretability based on appraisal theory. In our research, we estimate emotion intensity from multiple physiological features associated to the CPM's neurophysiological component using dynamical models with the aim of bringing insights into the relationship between physiological dynamics and perceived emotion intensity.

Genome-wide identification and characterization of cation-proton antiporter (CPA) gene family in rice (Oryza sativa L.) and their expression profiles in response to phytohormones.

The cation-proton antiporter (CPA) superfamily plays pivotal roles in regulating cellular ion and pH homeostasis in plants. To date, the regulatory functions of CPA family members in rice (Oryza sativa L.) have not been elucidated.

Ascertaining the Environmental Advantages of Pavement Designs Incorporating Recycled Content through a Parametric and Probabilistic Approach.

Reclaimed asphalt pavement (RAP) is a widely used end-of-life (EoL) material in asphalt pavements to increase the material circularity. However, the performance loss due to using RAP in the asphalt binder layer often requires a thicker layer, leading to additional material usage, energy consumption, and transportation effort. In this study, we developed a parametric and probabilistic life cycle assessment (LCA) framework to robustly compare various pavement designs incorporating recycled materials.

Secondary metabolites of Alternaria alternate appraisal of their SARS-CoV-2 inhibitory and anti-inflammatory potentials.

This study identifies the secondary metabolites from Alternaria alternate and evaluates their ACE-2: Spike RBD (SARS-CoV-2) inhibitory activity confirmed via immunoblotting in human lung microvascular endothelial cells. In addition, their in vitro anti-inflammatory potential was assessed using a cell-based assay in LPS-treated RAW 264.7 macrophage cells.

The global convergence of some self-scaling conjugate gradient methods for monotone nonlinear equations with application to 3DOF arm robot model.

Conjugate Gradient (CG) methods are widely used for solving large-scale nonlinear systems of equations arising in various real-life applications due to their efficiency in employing vector operations. However, the global convergence analysis of CG methods remains a significant challenge. In response, this study proposes scaled versions of CG parameters based on the renowned Barzilai-Borwein approach for solving convex-constrained monotone nonlinear equations.

Low-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources.

Modern dialogue systems rely on emotion recognition in conversation (ERC) as a core element enabling empathetic and human-like interactions. However, the weak correlation between emotions and semantics poses significant challenges to emotion recognition in dialogue. Semantically similar utterances can express different types of emotions, depending on the context or speaker.

A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution.

Petroleum hydrocarbon pollution causes significant damage to soil, so accurate prediction and early intervention are crucial for sustainable soil management. However, traditional soil analysis methods often rely on statistical methods, which means they always rely on specific assumptions and are sensitive to outliers. Existing machine learning based methods convert features containing spatial information into one-dimensional vectors, resulting in the loss of some spatial features of the data.

Exploiting the similarity of dissimilarities for biomedical applications and enhanced machine learning.

The "similarity of dissimilarities" is an emerging paradigm in biomedical science with significant implications for protein function prediction, machine learning (ML), and personalized medicine. In protein function prediction, recognizing dissimilarities alongside similarities provides a more detailed understanding of evolutionary processes, allowing for a deeper exploration of regions that influence biological functionality. For ML models, incorporating dissimilarity measures helps avoid misleading results caused by highly correlated or similar data, addressing confounding issues like the Doppelgänger Effect.

Exploring effector protein dynamics and natural fungicidal potential in rice blast pathogen Magnaporthe oryzae.

Rice blast, caused by Magnaporthe oryzae, is one of the most destructive fungal diseases in rice, resulting in major economic losses worldwide. Genetic and genomic studies have identified key genes and proteins, such as AvrPik variants and MAX proteins, that are crucial for the pathogen's virulence. These effector proteins interact with specific alleles of the Pik gene family on rice chromosome 11, modulating the host's immune response.

Reference Values for Water-Specific T1, Intermuscular and Intramuscular Fat Content in Skeletal Muscle at 2.89 T.

Background: MRI offers quantification of proton density fat fraction (PDFF) and tissue characteristics with T1 mapping. The influence of age, sex, and the potential confounding effects of fat on T1 values in skeletal muscle in healthy adults are insufficiently known.

Purpose: To determine the accuracy and repeatability of a saturation-recovery chemical-shift encoded multiparametric approach (SR-CSE) for quantification of T1 and muscle fat content, and establish normative values (age, sex) from a healthy cohort.

Structure-guided engineering of a mutation-tolerant inhibitor peptide against variable SARS-CoV-2 spikes.

Pathogen mutations present an inevitable and challenging problem for therapeutics and the development of mutation-tolerant anti-infective drugs to strengthen global health and combat evolving pathogens is urgently needed. While spike proteins on viral surfaces are attractive targets for preventing viral entry, they mutate frequently, making it difficult to develop effective therapeutics. Here, we used a structure-guided strategy to engineer an inhibitor peptide against the SARS-CoV-2 spike, called CeSPIACE, with mutation-tolerant and potent binding ability against all variants to enhance affinity for the invariant architecture of the receptor-binding domain (RBD).

Analysis of Drug Molecules in Living Cells.

Cells are the fundamental units of life, comprising a highly concentrated and complex assembly of biomolecules that interact dynamic ally across spatial and temporal scales. Living cells are constantly undergoing dynamic processes, therefore, to understand the interactions between drug molecules and living cells is of paramount importance in the biomedical sciences and pharmaceutical development. Compared with traditional end-point assays and fixed cell analysis, analysis of drug molecules in living cells can provide more insight into the effects of drugs on cells in real-time and allowing for a better understanding of drug mechanisms and effects, which will contribute to the development of drug developing and testing and personalize medicine.

Isolation and Total Synthesis of Ukabamide, an Antitrypanosomal Lipopeptide from a Marine sp. Cyanobacterium.

Human African trypanosomiasis (HAT) is one of the most lethal of the neglected tropical diseases. While the discovery of a novel antitrypanosomal drug is highly desired, the creation of a superior lead compound is challenging. Herein we report ukabamide (), which was isolated from a marine sp.

Multifunctional Microflowers for Precise Optoacoustic Localization and Intravascular Magnetic Actuation In Vivo.

Efficient drug delivery remains a significant challenge in modern medicine and pharmaceutical research. Micrometer-scale robots have recently emerged as a promising solution to enhance the precision of drug administration through remotely controlled navigation within microvascular networks. Real-time tracking is crucial for accurate guidance and confirmation of target arrival.

Innovative Method for Reliable Measurement of PEM Water Electrolyzer Component Resistances.

Understanding the sheet resistance of porous electrodes is essential for improving the performance of polymer electrolyte membrane (PEM) water electrolyzers and related technologies. Despite its importance, existing methods often fail to provide reliable and comprehensive data, especially for porous materials with complex morphologies and non-uniform thicknesses. This study introduces a robust and straightforward method for determining the sheet resistance of porous electrodes using a novel probe concept based on industrial printed circuit board (PCB) technology.

Integrative Transcriptome-Wide Association Study With Expression Quantitative Trait Loci Colocalization Identifies a Causal VAMP8 Variant for Nasopharyngeal Carcinoma Susceptibility.

Nasopharyngeal carcinoma (NPC) is an Asia-prevalent malignancy, yet its genetic underpinnings remain incompletely understood. Here, a transcriptome-wide association study (TWAS) is conducted on NPC, leveraging gene expression prediction models based on epithelial tissues and genome-wide association study (GWAS) summary statistics from 1577 NPC cases and 6359 controls of southern Chinese descent. The TWAS identifies VAMP8 on chromosome 2p11.

Effect of human myoblasts on tenogenic progression in 2D and 3D culture models.

Tendon injuries and disorders associated with mechanical tendon overuse are common musculoskeletal problems. Even though tendons play a central role in human movement, the intrinsic healing process of tendon is very slow. So far, it is known that tendon cell activity is supported by several interstitial cells within the tendon.

Decoding Plant-Pathogen Interactions: A Comprehensive Exploration of Effector-Plant Transcription Factor Dynamics.

In the coevolutionary process between plant pathogens and hosts, pathogen effectors, primarily proteinaceous, engage in interactions with host proteins, such as plant transcription factors (TFs), during the infection process. This review delves into the intricate interplay between TFs and effectors, a key aspect in the prolonged and complex battle between plants and pathogens. Effectors strategically manipulate TFs using diverse tactics.

3D Mechanical Response Stem Cell Complex Repairs Spinal Cord Injury by Promoting Neurogenesis and Regulating Tissue Homeostasis.

Spinal cord injury (SCI) leads to acute tissue damage that disrupts the microenvironmental homeostasis of the spinal cord, inhibiting cell survival and function, and thereby undermining treatment efficacy. Traditional stem cell therapies have limited success in SCI, due to the difficulties in maintaining cell survival and inducing sustained differentiation into neural lineages. A new solution may arise from controlling the fate of stem cells by creating an appropriate mechanical microenvironment.

Operando Synchrotron X-Ray Absorption Spectroscopy: A Key Tool for Cathode Material Studies in Next-Generation Batteries.

Rechargeable batteries are central to modern energy storage systems, from portable electronics to electric vehicles. The cathode material, a critical component, largely dictates a battery's energy density, capacity, and overall performance. This review focuses on the application of operando X-ray absorption spectroscopy (XAS) to study cathode materials in Li-ion, Na-ion, Li-S, and Na-S batteries.

Achieving Ultralow Lattice Thermal Conductivity and High Thermoelectric Performance in BiTeSe Alloys via Introducing Organic & Inorganic Nanoparticles.

N-type BiTeSe(BTS) is a state-of-the-art thermoelectric material owing to its excellent thermoelectric properties near room temperatures for commercial applications. However, its performance is restricted by its comparatively low figure of merit ZT. Here, it is shown that a 14% increase in power factor (PF) (at 300 K) can be reached through incorporation of inorganic GaAs nanoparticles due to enhanced thermopower originating from the energy-dependent carrier scattering.