Efferent compared to afferent neural substrates of the vergence eye movement system evoked via fMRI.

Introduction: The vergence neural system was stimulated to dissect the afferent and efferent components of symmetrical vergence eye movement step responses. The hypothesis tested was whether the afferent regions of interest would differ from the efferent regions to serve as comparative data for future clinical patient population studies.

Methods: Thirty binocularly normal participants participated in an oculomotor symmetrical vergence step block task within a functional MRI experiment compared to a similar sensory task where the participants did not elicit vergence eye movements.

SyncGenie: A programmable event synchronization device for neuroscience research.

In neuroscience, accurately correlating brain activity with stimuli and other events requires precise synchronization between neural data and event timing. To achieve this, purpose-built synchronization devices are often used to detect events. This paper introduces SyncGenie, a programmable synchronization device designed for a range of uses in neuroscience research-primarily as a "trigger box" to align neurophysiological data with physical stimulus events, among other possibilities.

BubbleCam: Engaging Privacy in Remote Sighted Assistance.

Remote sighted assistance (RSA) offers prosthetic support to people with visual impairments (PVI) through image- or video-based conversations with remote sighted assistants. While useful, RSA services introduce privacy concerns, as PVI may reveal private visual content inadvertently. Solutions have emerged to address these concerns on image-based asynchronous RSA, but exploration into solutions for video-based synchronous RSA remains limited.

Enhanced Stability and Sensitivity for CA-125 Detection Under Microfluidic Shear Flow Using Polyethylene Glycol-Coated Biosensor.

The microfluidic-based point-of-care (POC) diagnostic tool has garnered significant interest in recent years, offering rapid and cost-effective disease detection. There is a growing trend toward integrating microfluidic platforms with biosensors, aligning lab-on-a-chip technologies with POC diagnostic devices. Despite numerous efforts to incorporate biosensors into microfluidic systems, researchers have performed very limited investigations on the stability of biomarker detection when biosensors operate under microfluidic shear flow conditions.

PFAS Destruction and Near-Complete Defluorination of Undiluted Aqueous Film-Forming Foams at Ambient Conditions by Piezoelectric Ball Milling.

The nonthermal destruction of aqueous film-forming foam (AFFF) stockpiles, one of the major culprits responsible for water and soil contamination by per- and polyfluoroalkyl substances (PFAS), is extremely challenging because of the coexistence of mixed recalcitrant PFAS and complicated organic matrices at extremely high concentrations. To date, the complete defluorination of undiluted AFFF at ambient conditions has not been demonstrated. This study reports a novel piezoelectric ball milling approach for treating AFFF with a total organic fluorine concentration of 9080 mg/L and total organic carbon of 234 g/L.

Controlled ligation and elongation of uniformly truncated amyloid nanofibrils.

This study investigates the production and inter-fibril interactions of uniformly truncated amyloid nanofibrils. By varying extrusion cycles (0, 50, and 100) and using carbonate filters with 100 nm and 200 nm pore sizes, precise fibril length control was achieved. Atomic force microscopy (AFM) confirmed that the mean length of the truncated fibrils corresponded to the respective pore size as extrusion cycles increased.

Enhancing the Travel Experience for People with Visual Impairments through Multimodal Interaction: NaviGPT, A Real-Time AI-Driven Mobile Navigation System.

Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle detection, which can hinder a seamless and efficient user experience. In this paper, we present NaviGPT, a high-fidelity prototype that integrates LiDAR-based obstacle detection, vibration feedback, and large language model (LLM) responses to provide a comprehensive and real-time navigation aid for PVI.

Effects of maze appearance on maze solving.

As mazes are typically complex, cluttered stimuli, solving them is likely limited by visual crowding. Thus, several aspects of the appearance of the maze - the thickness, spacing, and curvature of the paths, as well as the texture of both paths and walls - likely influence the performance. In the current study, we investigate the effects of perceptual aspects of maze design on maze-solving performance to understand the role of crowding and visual complexity.

Micro-nanoscale polystyrene co-exposure impacts the uptake and translocation of arsenic and boscalid by lettuce (Lactuca sativa).

The influence of micro-nanoplastics (MNPs) on the fate and effects of other pollutants present in the environment is largely unknown. This study evaluated if the root exposure to MNPs (polystyrene, PS; 20 or 1000 nm) had an impact on the accumulation of arsenic and boscalid (As and Bos) in lettuce (Lactuca sativa). Under hydroponic conditions, plants were co-exposed to MNPs at 10 or 50 mg/L, and to 1 mg/L of each environmental pollutant (EP).

MO-GCN: A multi-omics graph convolutional network for discriminative analysis of schizophrenia.

The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these studies ignored the cooperative interactions and topological attributes of multi-omics networks. In this study, we constructed three types of brain graphs (BGs), three types of gut graphs (GGs), and nine types of brain-gut combined graphs (BGCGs) for each individual. We proposed a novel methodology of multi-omics graph convolutional network (MO-GCN) with an attention mechanism to construct a classification model by integrating all BGCGs.

Multifractal dynamic changes of spontaneous brain activity in psychiatric disorders: Adult attention deficit-hyperactivity disorder, bipolar disorder, and schizophrenia.

It is one of the strategies to study the complexity of spontaneous fluctuation of brain neurons based on resting-state functional magnetic resonance imaging (rs-fMRI), but the multifractal characteristics of spontaneous fluctuation of brain neurons in psychiatric diseases need to be studied. Therefore, this paper will study the multifractal spontaneous brain activity changes in psychiatric disorders using the multifractal detrended fluctuation analysis algorithm based on the UCLA datasets. Specifically: (1) multifractal characteristics in adult attention deficit-hyperactivity disorder (ADHD), bipolar disorder (BP), and schizophrenia (SCHZ); (2) the source of those multifractal characteristics.

Lurker: Backdoor attack-based explainable rumor detection on online media.

Because of their proficiency in capturing the category characteristics of graphs, graph neural networks have shown remarkable advantages for graph-level classification tasks, that is, rumor detection and anomaly detection. Due to the manipulation of special means (e.g.

Putative epicenters identified by transcriptome-neuromorphic interactions in attention-deficit/hyperactivity disorder biotypes.

Attention-deficit hyperactivity disorder (ADHD) is a heterogenous behavioral disorder with inattention, hyperactivity and impulsivity symptoms, indicating the important implication of identifying biotypes and its epicenters in understanding disease's pathogenesis. The study investigated the neuromorphic heterogeneity relating to transcriptional similarity architecture in ADHD, and further analyzed the epicenters of network-spreading in each ADHD biotype and their correlations with clinical characteristics. Individuals with ADHD could be identified into two discriminative biotypes that exhibited distinct neuromorphic aberrances.

Early detection of subjective cognitive decline from self-reported symptoms: An interpretable attention-cost fusion approach.

Background And Objective: Subjective cognitive decline (SCD) refers to self-reported difficulties in concentration, memory, and decision-making. Since SCD is based on subjective experiences, no specific medical test can definitively confirm its presence, making early detection challenging. Thus, it is advantageous to develop an AI model to capitalize on self-reported health complications, personality traits, and sociodemographic factors for early detection of SCD.

An Analysis of the Prevalence and Trends in Drug-Related Lyrics on Twitter (X): Quantitative Approach.

Background: The pervasiveness of drug culture has become evident in popular music and social media. Previous research has examined drug abuse content in both social media and popular music; however, to our knowledge, the intersection of drug abuse content in these 2 domains has not been explored. To address the ongoing drug epidemic, we analyzed drug-related content on Twitter (subsequently rebranded X), with a specific focus on lyrics.

Single cell RNA-seq reveals that granulosa cells are a target of phthalate toxicity in the ovary.

Phthalates are known endocrine disrupting chemicals and ovarian toxicants that are used widely in consumer products. Phthalates have been shown to exert ovarian toxicity on multiple endpoints, altering transcription of genes responsible for normal ovarian function. However, the molecular mechanisms by which phthalates act on the ovary are not well understood.

Incidental iron oxide nanoclusters drive confined Fenton-like detoxification of solid wastes towards sustainable resource recovery.

The unique properties of nanomaterials offer vast opportunities to advance sustainable processes. Incidental nanoparticles (INPs) represent a significant part of nanomaterials, yet their potential for sustainable applications remains largely untapped. Herein, we developed a simple strategy to harness INPs to upgrade the waste-to-resource paradigm, significantly reducing the energy consumption and greenhouse gas emissions.

Deciphering the N-substituent effects on biodegradation of sulfonamides: Novel insights revealed from molecular biology and computational chemistry approaches.

Elucidating biodegradation mechanisms and predicting pollutant reactivities are essential for advancing the application of biodegradation engineering to address the challenge of thousands of emerging contaminants. Molecular biology and computational chemistry are powerful tools for this purpose, enabling the investigation of biochemical reactions at both the gene and atomic levels. This study employs the biodegradation of ten sulfonamide antibiotics as a case study to demonstrate the integration of genomics and quantum chemistry approaches in exploring the biodegradation behavior of emerging contaminants.

Topological functional network analysis of cortical blood flow in hyperacute ischemic rats.

Acute cerebral ischemia alters brain network connectivity, leading to notable increases in both anatomical and functional connectivity while observing a reduction in metabolic connectivity. However, alterations of the cerebral blood flow (CBF) based functional connectivity remain unclear. We collected continuous CBF images using laser speckle contrast imaging (LSCI) technology to monitor ischemic occlusion-reperfusion progression through occlusion of the left carotid artery.

Expansion microscopy reveals neural circuit organization in genetic animal models.

Expansion microscopy is a super-resolution technique in which physically enlarging the samples in an isotropic manner increases inter-molecular distances such that nano-scale structures can be resolved using light microscopy. This is particularly useful in neuroscience as many important structures are smaller than the diffraction limit. Since its invention in 2015, a variety of expansion microscopy protocols have been generated and applied to advance knowledge in many prominent organisms in neuroscience, including zebrafish, mice, , and .

Comparative analysis of polystyrene versus zirconia beads on breakage kinetics, heat generation, and amorphous formation during wet bead milling.

This study determined process conditions under which polystyrene (CPS) and zirconia (YSZ) beads cause similar breakage kinetics and temperature rise during manufacturing of drug nanosuspensions via wet bead milling and explored relative advantages of CPS beads, particularly for stress-sensitive compounds. Besides temperature and particle size measurements, a microhydrodynamic-based kinetic model simulated the conditions for CPS to achieve breakage rates equivalent to those of YSZ. A power law correlation was applied to find conditions conducive to temperature equivalency.

Interfacial charge transfer in g-CN/FeVO/AgBr nanocomposite for efficient photodegradation of tetracycline antibiotic and Victoria blue dye.

The study presents the fabrication and superior photoactivity of a ternary g-CN/FeVO/AgBr heterojunction nanocomposite, synthesized via a chemical precipitation method for effective degradation of tetracycline (TC) and Victoria Blue (VB) dye under light illumination. The morphology and the crystal size of the synthesized nanocomposite were characterized by using FESEM and XRD and the calculated grain size (100.39 nm) is larger than the crystal size (48.

A bioinspired fish fin webbing for proprioceptive feedback.

The propulsive fins of ray-finned fish are used for large scale locomotion and fine maneuvering, yet also provide sensory feedback regarding hydrodynamic loading and the surrounding environment. This information is gathered via nerve cells in the webbing between their fin rays. A similar bioinspired system that can gather force feedback from fin motion could enable valuable insight into robotic underwater locomotion improving swimming efficiency and orientation.

Discrete element method model of soot aggregates.

Soot aerosols emitted during combustion can affect climate by scattering and absorbing the sunlight. Individual soot particles are fractal aggregates composed of elemental carbon. In the atmosphere, these aggregates acquire coatings by condensation and coagulation, resulting in significant compaction of the aggregates that changes the direct climate forcing of soot.