Slice-Inference-Assisted Lightweight Small Object Detection Model for Holographic Digital Immunoassay Quantification.

Sensitive and cost-effective detection methods utilizing portable equipment are crucial for applications in food safety inspection, environmental monitoring, and clinical diagnosis. In this study, we propose a sliced inference-assisted lightweight small object detection model (SIALSO) holographic biosensor for digital immunoassay-based quantification of chloramphenicol in food samples. This innovative biosensor combines a lens-free holographic imaging system with a lightweight deep learning model, capitalizing on the extensive field of view (FOV) of holography to facilitate precise signal detection of microsphere probes.

Weight Differences-Based Multi-level Signal Profiling for Homogeneous and Ultrasensitive Intelligent Bioassays.

Current high-sensitivity immunoassay protocols often involve complex signal generation designs or rely on sophisticated signal-loading and readout devices, making it challenging to strike a balance between sensitivity and ease of use. In this study, we propose a homogeneous-based intelligent analysis strategy called Mata, which uses weight analysis to quantify basic immune signals through signal subunits. We perform nanomagnetic labeling of target capture events on micrometer-scale polystyrene subunits, enabling magnetically regulated kinetic signal expression.

Lens-Free Holographic Imaging-Based Immunosensor Using Unpaired Data Set Signal-to-Noise Ratio-Enhanced Modal Transformation for Biosensing.

Conventional microscopes have limited capacities to reconcile the trade-off between the lens and field of view (FOV). Thus, the imaging field and accuracy of immunosensors remain restricted. In this study, a holographic deep learning unpaired modal transformation-assisted immunosensor is presented, combining a portable lens-free holographic imaging device with a CuO@SiO nanoparticle-based click reaction signal amplification strategy for accurate antibiotic detection.

Leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples.

Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations.

Development of cyclopeptide inhibitors of cGAS targeting protein-DNA interaction and phase separation.

Cyclic GMP-AMP synthase (cGAS) is an essential sensor of aberrant cytosolic DNA for initiating innate immunity upon invading pathogens and cellular stress, which is considered as a potential drug target for autoimmune and autoinflammatory diseases. Here, we report the discovery of a class of cyclopeptide inhibitors of cGAS identified by an in vitro screening assay from a focused library of cyclic peptides. These cyclopeptides specifically bind to the DNA binding site of cGAS and block the binding of dsDNA with cGAS, subsequently inhibit dsDNA-induced liquid phase condensation and activation of cGAS.

Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples.

Magnetic resonance imaging (MRI) is a popular and useful non-invasive method to map patterns of brain structure and function to complex human traits. Recently published observations in multiple large scale studies cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional MRI, which seems to account for little behavioral variability. We leverage baseline data from thousands of children in the Adolescent Brain Cognitive Development (ABCD) Study to inform the replication sample size required with both univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations.

Magnetic relaxation switching immunoassay based on "limited-magnitude" particles for sensitive quantification of aflatoxin B.

Aflatoxin B (AFB) is a highly toxic and carcinogenic chemical substance that endangers food safety and human health. Magnetic relaxation switching (MRS) immunosensors are utilized in a variety of applications in food analysis due to its resistance to matrix interferences, but they often suffer from magnetic separation-based multi-washing steps and low sensitivity. Herein, we propose novel MRS strategy for the sensitive detection of AFB using "Limited-Magnitude" size particles: a single millimeter sized polystyrene spheres (PS) and 150 nm superparamagnetic nanoparticles (MNP).

Effects of superficial gas velocity on the performance of an air-lift internal circulation partial nitrification-anammox granular sludge reactor.

The airlift internal circulation reactor for partial nitrification-anammox (PNA-ALR) has the advantages of a small footprint, high mass transfer efficiency, and the ease of formation of granular sludge, thus making it an effective biological treatment for ammonia-containing wastewater. Although superficial gas velocity (SGV) is an essential parameter for PNA-ALR, it is unclear how the magnitude of SGV impacts nitrogen removal performance. In this study, the nitrogen removal efficiencies of five PNA-ALRs with different SGV were measured during feeding with synthetic municipal wastewater.

Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity.

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design.

Magnetic Relaxation Switching Immunosensors via a Click Chemistry-Mediated Controllable Aggregation Strategy for Direct Detection of Chlorpyrifos.

Chlorpyrifos (CPF) is the most frequently found organophosphate pesticide residue in solid food samples and can cause increasing public concerns about potential risks to human health. Traditional detection signals of such small molecules are mostly generated by target-mediated indirect conversion, which tends to be detrimental to sensitivity and accuracy. Herein, a novel magnetic relaxation switching detection platform was developed for target-mediated direct and sensitive detection of CPF with a controllable aggregation strategy based on a bioorthogonal ligation reaction between tetrazine (Tz) and trans-cyclooctene (TCO) ligands.

Artificial Intelligence-Assisted Digital Immunoassay Based on a Programmable-Particle-Decoding Technique for Multitarget Ultrasensitive Detection.

The development of a multitarget ultrasensitive immunoassay is significant to fields such as medical research, clinical diagnosis, and food safety inspection. In this study, an artificial intelligence (AI)-assisted programmable-particle-decoding technique (APT)-based digital immunoassay system was developed to perform multitarget ultrasensitive detection. Multitarget was encoded by programmable polystyrene (PS) microspheres with different characteristics (particle size and number), and subsequent visible signals were recorded under an optical microscope after the immune reaction.

Fine-tuning of mTOR signaling by the UBE4B-KLHL22 E3 ubiquitin ligase cascade in brain development.

Spatiotemporal regulation of the mechanistic target of rapamycin (mTOR) pathway is pivotal for establishment of brain architecture. Dysregulation of mTOR signaling is associated with a variety of neurodevelopmental disorders. Here, we demonstrate that the UBE4B-KLHL22 E3 ubiquitin ligase cascade regulates mTOR activity in neurodevelopment.

Generalization of cortical MOSTest genome-wide associations within and across samples.

Genome-Wide Association studies have typically been limited to univariate analysis in which a single outcome measure is tested against millions of variants. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci when compared to established approaches (min-P).

The ZSWIM8 ubiquitin ligase regulates neurodevelopment by guarding the protein quality of intrinsically disordered Dab1.

Protein quality control (PQC) is essential for maintaining protein homeostasis and guarding the accuracy of neurodevelopment. Previously, we found that a conserved EBAX-type CRL regulates the protein quality of SAX-3/ROBO guidance receptors in Caenorhabditis elegans. Here, we report that ZSWIM8, the mammalian homolog of EBAX-1, is essential for developmental stability of mammalian brains.

The philanthropic response of substantive and symbolic corporate social responsibility strategies to COVID-19 crisis: Evidence from China.

The COVID-19 epidemic broke out in China in January 2020, which triggered the largest wave of corporate philanthropic donations since the 2008 Sichuan earthquake. Based on A-share listed firms in the Shanghai and Shenzhen stock exchanges in 2020, we study whether substantive and symbolic corporate social responsibility (CSR) strategies affect corporate philanthropic responses during the COVID-19 crisis. We use the lagged annual donation and technical dimension scores (T scores) of rankins ratings (RKS) as proxies of CSR performance and CSR disclosure and then define the CSR gap as the gap between the two.

Board Network and CSR Decoupling: Evidence From China.

This paper investigates the influence of board network centrality on corporate social responsibility (CSR) decoupling. CSR decoupling refers to the gap between corporate internal and external actions in CSR practices. Specifically, we measure CSR decoupling as the difference between corporate social disclosure (CSD) and corporate social performance (CSP).

The anammox coupled partial-denitrification process in an integrated granular sludge and fixed-biofilm reactor developed for mainstream wastewater treatment: Performance and community structure.

This study describes an integrated granular sludge and fixed-biofilm (iGB) reactor innovatively designed to carry out the anammox/partial-denitrification (A/PD) process for nitrogen removal with mainstream municipal wastewater. The iGB-A/PD reactor consists of anammox granules inoculated in the lower region of reactor and an acclimated fixed-biofilm positioned in the upper region. Compared to the other reported A/PD systems for mainstream wastewater treatment, this iGB-A/PD reactor is notable due to its higher quality effluent with a total inorganic nitrogen (TIN) of ∼3 mg•L and operation at a high nitrogen removal rate (NRR) of 0.

Exploring the Influencing Factors of the Recreational Utilization and Evaluation of Urban Ecological Protection Green Belts for Urban Renewal: A Case Study in Shanghai.

With the continuous expansion of urban construction land, the green belts aiming for ecological protection have ensured a sustainable and effective function of regional ecosystem services. At the same time, these ecological green belts are expected to develop their compound service potentials with the development of cities. In order to meet the increasing demand of urban residents for the recreational utilization of urban green space, the primary function of the ecological green belts has transformed from being purely ecological to a combination of being ecological and recreational.

Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.

Despite its central role in revealing the neurobiological mechanisms of behavior, neuroimaging research faces the challenge of producing reliable biomarkers for cognitive processes and clinical outcomes. Statistically significant brain regions, identified by mass univariate statistical models commonly used in neuroimaging studies, explain minimal phenotypic variation, limiting the translational utility of neuroimaging phenotypes. This is potentially due to the observation that behavioral traits are influenced by variations in neuroimaging phenotypes that are globally distributed across the cortex and are therefore not captured by thresholded, statistical parametric maps commonly reported in neuroimaging studies.

Inter-character Orthographic Similarity Effects on the Recognition of Chinese Coordinative Compound Words.

Chinese coordinative compound words are common and unique in inter-character semantic and orthographic relationships. This study explored the inter-character orthographic similarity effects on the recognition of transparent two-morpheme coordinative compound words. Seventy-two native Chinese readers participated in a lexical decision task.

Artificial intelligence on diabetic retinopathy diagnosis: an automatic classification method based on grey level co-occurrence matrix and naive Bayesian model.

Aim: To develop an automatic tool on screening diabetic retinopathy (DR) from diabetic patients.

Methods: We extracted textures from eye fundus images of each diabetes subject using grey level co-occurrence matrix method and trained a Bayesian model based on these textures. The receiver operating characteristic (ROC) curve was used to estimate the sensitivity and specificity of the Bayesian model.

Comparison of ocular biometric measurements between a new swept-source optical coherence tomography and a common optical low coherence reflectometry.

The purpose of the current study was to compare the measurements between a new optical biometer based on swept-source optical coherence tomography (SS-OCT), the OA-2000 (Tomey, Japan), and an optical biometer based on optical low coherence reflectometry (OLCR), the Lenstar (Haag-Streit, Switzerland). Ninety-nine eyes of 99 healthy subjects were included. The axial length (AL), central corneal thickness (CCT), anterior chamber depth (ACD), aqueous depth (AD), lens thickness (LT), keratometry (K) readings, including flat K (Kf), steep K (Ks), mean K (Km), astigmatism vectors J, J at diameters of 2.

Axial Length Measurement Failure Rates With Biometers Using Swept-Source Optical Coherence Tomography Compared to Partial-Coherence Interferometry and Optical Low-Coherence Interferometry.

Purpose: To compare a new swept-source optical coherence tomography (SSOCT)-based biometer (OA-2000) with the IOLMaster v5.4 (partial-coherence interferometry) and Aladdin (optical low-coherence interferometry) biometers in terms of axial length measurement and failure rate in eyes with cataract.

Design: Reliability study.

Impaired downregulation of visual cortex during auditory processing is associated with autism symptomatology in children and adolescents with autism spectrum disorder.

Autism spectrum disorders (ASD) are pervasive developmental disorders characterized by impairments in language development and social interaction, along with restricted and stereotyped behaviors. These behaviors often include atypical responses to sensory stimuli; some children with ASD are easily overwhelmed by sensory stimuli, while others may seem unaware of their environment. Vision and audition are two sensory modalities important for social interactions and language, and are differentially affected in ASD.