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.

The Use of Terahertz Computed Tomography and Time Domain Spectroscopy to Evaluate Symmetry in 3D Printed Parts.

3D printing has become essential to many fields for its low-cost production and rapid prototyping abilities. As 3D printing becomes an alternative manufacturing tool, developing methods to non-destructively evaluate defects for quality control is essential. This study integrates the non-destructive terahertz (THz) analysis methods of terahertz time-domain spectroscopy (THz-TDS) and terahertz computed tomography (THz CT) to image and assess 3D printed resin structures for defects.

Comparing Intra- and Inter-individual Correlational Brain Connectivity from Functional and Structural Neuroimaging Data.

Inferring brain connectivity from inter-individual correlations has been applied to various neuroimaging modalities, such as glucose metabolic activity measured by positron emission tomography (PET) and brain structures assessed using MRI. The variability that drives these inter-individual correlations is generally attributed to individual differences, potentially influenced by factors like genetics, life experiences, and biological sex. However, it remains unclear whether long-term within-individual effects, such as aging, and state-like effects also contribute to the correlated structures, and how intra-individual correlations are compared to inter-individual correlations.

Enriching fluorotelomer carboxylic acids-degrading consortia from sludges and soils.

Fluorotelomer carboxylic acids (FTCAs) has drawn increasing attention due to their prevalent occurrence, high toxicity, and bioaccumulating effects. In this study, microbial consortia with sustainable FTCA removal abilities were enriched and characterized from two activated sludges and five soils when no external carbon sources were supplemented. After four generations of enrichment, stable 6:2 FTCA and 5:3 FTCA biodegradation were achieved, reaching 0.

Distinctive adsorption and transport behaviors of short-chain versus long-chain perfluoroalkyl acids in a river sediment.

Perfluoroalkyl acids (PFAAs) embrace perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and other concerning chemicals of different chain length and terminal moieties. PFAAs can leach from municipal wastewater facilities as point sources discharging into rivers and receiving streams. In this study, we investigated the adsorption and transport behaviors of six select PFAAs in a Hudson River (USA) sediment in both batch and mesocosm studies.

Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation.

As a fundamental mechanism for gene expression regulation, post-transcriptional RNA methylation plays versatile roles in various biological processes and disease mechanisms. Recent advances in single-cell technology have enabled simultaneous profiling of transcriptome-wide RNA methylation in thousands of cells, holding the promise to provide deeper insights into the dynamics, functions, and regulation of RNA methylation. However, it remains a major challenge to determine how to best analyze single-cell epitranscriptomics data.

Using Thermal Crowding to Direct Pattern Formation on the Nanoscale.

Metal films and other metal geometries of nanoscale thickness deposited on an insulating substrate, when exposed to laser irradiation, melt and evolve as fluids as long as their temperature is sufficiently high. This evolution often leads to pattern formation, which may be influenced strongly by material parameters that are temperature dependent. In addition, the laser heat absorption itself depends on the time-dependent metal thickness.

Prevent and Reverse Metabolic Dysfunction-Associated Steatohepatitis and Hepatic Fibrosis via mRNA-Mediated Liver-Specific Antibody Therapy.

Chronic exposure of the liver to multiple insults culminates in the development of metabolic dysfunctionassociated steatohepatitis (MASH), a complicated metabolic syndrome characterized by hepatic steatosis and inflammation, typically accompanied by progressive fibrosis. Despite extensive clinical evaluation, there remain challenges in MASH drug development, which are primarily due to unsatisfactory efficacy and limited specificity. Strategies to address the unmet medical need for MASH with fibrosis before it reaches the irreversible stage of decompensated cirrhosis are critically needed.

Transsynaptic modulation of cerebellar nuclear cells: theta AC-burst stimulation.

Transcranial alternating current stimulation (tACS) and its variants are being tested in clinical trials for treatment of neurological disorders, and cerebellar tACS (ctACS) in particular has garnered much interest because of the involvement of the cerebellum in these disorders. The main objective of this study was to investigate the frequency tuning curves for the entrainment of the Purkinje cells (PCs) and the cerebellar nuclear (CN) cells by their axonal projections. In addition, we aimed to investigate the temporal and steady-state characteristics of the PC-CN transsynaptic modulation under clinically relevant stimulation waveforms.

Enhancing groundwater quality prediction through ensemble machine learning techniques.

Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensemble learning model, for predicting groundwater quality in an unconfined aquifer located in northern Iran.

Fair and explainable Myocardial Infarction (MI) prediction: Novel strategies for feature selection and class imbalance correction.

The rising incidences of myocardial infarction (MI), often affecting individuals without traditional risk factors, highlight the urgent need for improved early detection using personal health data. However, health surveys and electronic health records (EHRs) frequently suffer from class imbalances, leading to prediction biases and differences between specificity and sensitivity, which hinder reliable model development despite the valuable insights contained in these datasets. To address this, we have introduced a novel approach to enhance MI risk prediction using self-reported attributes from the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) dataset.

Comparative evaluation of melt- solution-printed poly(ε-caprolactone)/hydroxyapatite scaffolds for bone tissue engineering applications.

Material extrusion-based three-dimensional (3D) printing is a widely used manufacturing technology for fabricating scaffolds and devices in bone tissue engineering (BTE). This technique involves two fundamentally different extrusion approaches: solution-based and melt-based printing. In solution-based printing, a polymer solution is extruded and solidifies solvent evaporation, whereas in melt-based printing, the polymer is melted at elevated temperatures and solidifies as it cools post-extrusion.

Transdiagnostic and Diagnosis-Specific Morphological Similarity Related Transcriptional Profile in Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder.

Objective: Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both highly heritable developmental psychiatric disorders and exhibit a high degree of comorbidity. Our objective is to enhance understanding of the transdiagnostic and diagnosis-specific structural alterations and related cellular and genetic pathophysiological mechanisms between ADHD and ASD.

Method: We used structural magnetic resonance imaging data of 247 subjects from the publicly available 1000 Functional Connectomes Project, including 91 individuals with ADHD, 49 individuals with ASD, and 107 age- and sex-matched controls.

Activation of PAA at the Fe-N Sites by Boron Nitride Quantum Dots Enhanced Charge Transfer Generates High-Valent Metal-Oxo Species for Antibiotics Degradation.

Advanced oxidation processes (AOPs) based on peracetic acid (PAA) offer a promising strategy to address antibiotic wastewater pollution. In this study, Fe-doped graphitic carbon nitride (g-CN) nanomaterials were used to construct Fe-N sites, and the electronic structure was tuned by boron nitride quantum dots (BNQDs), thereby optimizing PAA activation for the degradation of antibiotics. The BNQDs-modified Fe-doped g-CN catalyst (BNQDs-FCN) achieved an excellent reaction rate constant of 0.

Cerebellar transcranial AC stimulation produces a frequency-dependent bimodal cerebellar output pattern.

Transcranial alternating current stimulation (ctACS) has the potential to be an appealing, non-invasive treatment option for psychiatric and neurological disorders. However, its potential has been limited by significant knowledge gaps in the details and mechanisms of how ctACS affects cerebellar output on single cell and population levels. We investigated this issue by making single-unit recordings of Purkinje cells (PC) and lateral cerebellar nuclear (Lat CN) cells in response to ctACS in anesthetized adult female Sprague-Dawley rats.

Integrated analyses of multi-omic data derived from paired primary lung cancer and brain metastasis reveal the metabolic vulnerability as a novel therapeutic target.

Background: Lung cancer brain metastases (LC-BrMs) are frequently associated with dismal mortality rates in patients with lung cancer; however, standard of care therapies for LC-BrMs are still limited in their efficacy. A deep understanding of molecular mechanisms and tumor microenvironment of LC-BrMs will provide us with new insights into developing novel therapeutics for treating patients with LC-BrMs.

Methods: Here, we performed integrated analyses of genomic, transcriptomic, proteomic, metabolomic, and single-cell RNA sequencing data which were derived from a total number of 154 patients with paired and unpaired primary lung cancer and LC-BrM, spanning four published and two newly generated patient cohorts on both bulk and single cell levels.

Socially driven negative feedback regulates activity and energy use in ant colonies.

Despite almost a century of research on energetics in biological systems, we still cannot explain energy regulation in social groups, like ant colonies. How do individuals regulate their collective activity without a centralized control system? What is the role of social interactions in distributing the workload amongst group members? And how does the group save energy by avoiding being constantly active? We offer new insight into these questions by studying an intuitive compartmental model, calibrated with and compared to data on ant colonies. The model describes a previously unexplored balance between positive and negative social feedback driven by individual activity: when activity levels are low, the presence of active individuals stimulates inactive individuals to start working; when activity levels are high, however, active individuals inhibit each other, effectively capping the proportion of active individuals at any one time.

Explorations of using a convolutional neural network to understand brain activations during movie watching.

Background: Naturalistic stimuli, such as videos, can elicit complex brain activations. However, the intricate nature of these stimuli makes it challenging to attribute specific brain functions to the resulting activations, particularly for higher-level processes such as social interactions.

Objective: We hypothesized that activations in different layers of a convolutional neural network (VGG-16) would correspond to varying levels of brain activation, reflecting the brain's visual processing hierarchy.