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Butylated hydroxytoluene (BHT) induces zebrafish spinal cord defects and scoliosis by inhibiting the hedgehog pathway
A molecular cell atlas of mouse lemur, an emerging model primate
Abstract Mouse lemurs are the smallest and fastest reproducing primates, as well as one of the most abundant, and they are emerging as a model organism for primate biology, behaviour, health and conservation. Although much has been learnt about their ecology and phylogeny in Madagascar and their physiology, little is known about their cellular and molecular biology. Here we used droplet-based and plate-based single-cell RNA sequencing to create Tabula Microcebus, a transcriptomic atlas of 226,000 cells from 27 mouse lemur organs opportunistically obtained from four donors clinically and histologically characterized. Using computational cell clustering, integration and expert cell annotation, we define and biologically organize more than 750 lemur molecular cell types and their full gene expression profiles. This includes cognates of most classical human cell types, including stem and progenitor cells, and differentiating cells along the developmental trajectories of spermatogenesis, haematopoiesis and other adult tissues. We also describe dozens of previously unidentified or sparsely characterized cell types. We globally compare expression profiles to define the molecular relationships of cell types across the body, and explore primate cell and gene expression evolution by comparing lemur transcriptomes to those of human, mouse and macaque. This reveals cell-type-specific patterns of primate specialization and many cell types and genes for which the mouse lemur provides a better human model than mouse1. The atlas provides a cellular and molecular foundation for studying this model primate and establishes a general approach for characterizing other emerging model organisms.
CRxK dataset: a multi-view surveillance video dataset for re-enacted crimes in Korea
Mouse lemur cell atlas informs primate genes, physiology and disease
Abstract Mouse lemurs (Microcebus spp.) are an emerging primate model organism, but their genetics, cellular and molecular biology remain largely unexplored. In an accompanying paper1, we performed large-scale single-cell RNA sequencing of 27 organs from mouse lemurs. We identified more than 750 molecular cell types, characterized their transcriptomic profiles and provided insight into primate evolution of cell types. Here we use the generated atlas to characterize mouse lemur genes, physiology, disease and mutations. We uncover thousands of previously unidentified lemur genes and hundreds of thousands of new splice junctions including over 85,000 primate splice junctions missing in mice. We systematically explore the lemur immune system by comparing global expression profiles of key immune genes in health and disease, and by mapping immune cell development, trafficking and activation. We characterize primate-specific and lemur-specific physiology and disease, including molecular features of the immune program, lemur adipocytes and metastatic endometrial cancer that resembles the human malignancy. We present expression patterns of more than 400 primate genes missing in mice, many with similar expression patterns to humans and some implicated in human disease. Finally, we provide an experimental framework for reverse genetic analysis by identifying naturally occurring nonsense mutations in three primate immune genes missing in mice and by analysing their transcriptional phenotypes. This work establishes a foundation for molecular and genetic analyses of mouse lemurs and prioritizes primate genes, isoforms, physiology and disease for future study.
Astrocyte morphogenesis requires self-recognition
A comparative study of manifold learning methods for scRNA-seq with a trajectory-aware metric
The role of metabolism in shaping enzyme structures over 400 million years
Abstract Advances in deep learning and AlphaFold2 have enabled the large-scale prediction of protein structures across species, opening avenues for studying protein function and evolution 1 . Here we analyse 11,269 predicted and experimentally determined enzyme structures that catalyse 361 metabolic reactions across 225 pathways to investigate metabolic evolution over 400 million years in the Saccharomycotina subphylum 2 . By linking sequence divergence in structurally conserved regions to a variety of metabolic properties of the enzymes, we reveal that metabolism shapes structural evolution across multiple scales, from species-wide metabolic specialization to network organization and the molecular properties of the enzymes. Although positively selected residues are distributed across various structural elements, enzyme evolution is constrained by reaction mechanisms, interactions with metal ions and inhibitors, metabolic flux variability and biosynthetic cost. Our findings uncover hierarchical patterns of structural evolution, in which structural context dictates amino acid substitution rates, with surface residues evolving most rapidly and small-molecule-binding sites evolving under selective constraints without cost optimization. By integrating structural biology with evolutionary genomics, we establish a model in which enzyme evolution is intrinsically governed by catalytic function and shaped by metabolic niche, network architecture, cost and molecular interactions.
The effect of coadministration of D156844 and AR42 (REC-2282) on the survival and motor phenotype of mice with spinal muscular atrophy
Sparse transformer and multipath decision tree: a novel approach for efficient brain tumor classification
Synthesis and characterization of carbon based polymer composites reinforced with MWCNTs and graphite in PVDF matrix
Prediction of success of slings in female stress incontinence, statistical and AI modeling
Abstract Studies on predicting the outcome of sling surgery are limited. Most depend on analysis of multiple confounding factors using regression models. However, their prediction results are limited. In this study, we tested a statistical regression model and an AI model for the prediction of the outcome of mid-urethral sling. Data were collected from 151 patients who underwent MUS surgery in our center from 2002 to 2022 and confounding factors that affect the outcome of the surgery at a minimum of one year. The study was divided into two phases. Phase I included the construction of a prediction model using binomial logistic regression. In phase II, we applied AI techniques (Artificial neural network (ANN) and Support Vector Machines (SVM) trying to obtain better predictions. Phase I: The logistic regression model predicted the outcome of surgery with overall accuracy of 90.7% and positive predictive value of 61.5% [X 2 (11) = 46.24, P < 0.001]. Phase II: The data of the patients were entered as 10 features; 9 were predictors and the 10 th was the output. The output comprised 18 cases designated as ‘failure’ and 133 as ‘success’ output. The best model performance-wise was the (SVM) with 92% accuracy and 96% F1-score, which meets the industrial standards for predictive models. However, ANN produced 90% accuracy and 94% F1-score. However, our sample size is small. Prediction of the outcome of MUS surgery was achieved using different modalities with the best prediction of the outcome obtained by SVM method. This is helpful in future counseling of women undergoing sling surgery, whatever its type as to what to expect after surgery.
Beta cyclodextrin stabilized cupric oxide nanoparticles assisted thermal therapy for lung tumor and its effective in vitro anticancer activity
Abstract The unique physicochemical properties of cupric oxide nanoparticles (CuO NPs) make them suitable for a wide range of therapeutic applications. Here, we synthesized β-cyclodextrin (βCD) capped CuO NPs (CuONPs@βCD) using a simple reduction process. The formation and physicochemical characteristics were identified via different spectroscopic techniques. The CuONPs@βCD displayed antimicrobial activity as good as commercial drugs. Dimethyl thiazolyl tetrazolium bromide (MTT) assay was carried out to assess the anticancer properties of CuONPs@βCD against A549 lung cancer cells. The result demonstrated that the anticancer activity of CuONPs@βCD with IC50 values of 41.06 ± 0.05 and 19.46 µg/mL at 24 and 48-h incubation period, respectively. CuONPs@βCD exhibited anticancer activity on A549 lung cancer cells while having less adverse effects on normal cells. Annexin V-FITC/PI assay, reactive oxygen species (ROS) analysis, disruption of mitochondrial membrane potential (Δψm), and AO/EB apoptosis studies in A549 cells revealed significant apoptotic impact of CuONPs@βCD when compared to the control. Moreover, thermal therapy study of CuONPs@βCD in lung tumor using COMSOL Multiphysics has been reported. Our investigation revealed Case III, where the temperature distribution at the top surface of the tumor is best and may be the most effective way to treat lung cancer. It was found that an incident flux of 8000 Wm− 2 for 900 s and an extinction coefficient of 8.266 m− 1 for CuONPs@βCD were the best conditions for reaching a temperature of 43.63 °C across the whole tumor area. Thus, these findings open new research opportunities and potential use of CuONPs@βCD for biological applications.
Neuroprotective effect of Tozasertib in Streptozotocin-induced alzheimer’s mice model
Abstract Alzheimer’s disease (AD) is responsible for more than 80% of cases of dementia in senior individuals globally. In the current study, the role of modulation of the FGF1/PI3K/Akt pathway in the protective effect of tozasertib was evaluated. Experimental dementia was induced in mice by injecting streptozotocin (STZ) intracerebroventricularly. Various biochemical parameters for oxidative stress & lipid peroxidation (SOD, GSH, catalase, TBARS), neuroinflammation (MPO, IL-6, IL-1 β, TNF-α, NFκB), apoptotic markers (Bax, Bcl-2, Caspase-3), and memory parameters (AChE activity, β1–40 levels) were assessed. The behavioral parameters evaluated included the Morris Water Maze test and the step-down passive avoidance test. Histological changes were assessed using H&E staining. ICV STZ-induced AD resulted in increased oxidative stress, lipid peroxidation, neuroinflammation, apoptosis, and decreased learning and memory. The results showed that administration of tozasertib improved memory, decreased levels of oxidative stress, inflammatory parameters, and apoptotic markers, and improved histological parameters in a dose-dependent manner. Pre-administration of LY294002, a PI3K/Akt pathway inhibitor, partially reversed the protective effects of Tozasertib, suggesting possible involvement of this pathway. However, as the mechanism was inferred primarily through pharmacological antagonism, further studies including direct molecular assessments (e.g. p-Akt/t-Akt) are warranted to confirm the role of FGF1/PI3K/Akt signaling in Tozasertib’s action.
Homo sapiens adapted to diverse habitats before successfully populating Eurasia
Assessment of hybrid nanocomposite AFOs for pediatric cerebral palsy: mechanical, spectroscopic, and finite element analysis
Abstract Cerebral Palsy (CP) is a neurological disorder that affects motor function and causes gait abnormalities in children. Ankle–Foot Orthoses (AFOs) are external aiding devices that provide stability and improve mobility for pediatrics. However, conventional AFO materials often fail to achieve an optimal balance of strength, flexibility, and energy absorption for dynamic movements. This study introduces a novel composite material for pediatric ankle–foot orthoses (AFOs), based on Orthocryl and reinforced with multi-walled carbon nanotubes (MWCNTs) and polylactic acid (PLA). The proposed formulation is engineered to overcome the limitations of conventional materials by providing enhanced mechanical performance and improved functional suitability for clinical applications. Four composite concentrations were fabricated: pure Orthocryl, 0.5% MWCNTs, 0.5% MWCNTs/1.0% PLA, and 0.5% MWCNTs/1.5% PLA. Mechanical and morphological characterizations were performed using a universal testing machine for tensile, flexural, and impact testing, Fourier Transform Infrared Spectroscopy (FT-IR) for material composition analysis, and Field Emission Scanning Electron Microscopy (FE-SEM) for surface morphology examination. To simulate practical application, Finite Element Analysis was performed using ANSYS software, recognizing gait loading conditions. The experimental findings demonstrated that incorporating 0.5% MWCNT into Orthocryl significantly enhanced its mechanical properties, with a 12.5% increase in tensile strength (from 52.79 to 59.4 MPa), a 59.3% increase in flexural strength (from 52.08 to 82.93 MPa), and a 22% improvement in impact resistance (from 28.12 to 34.3 kJ/m2). These improvements confirm the effectiveness of MWCNT reinforcement. Additionally, FE-SEM and FT-IR analyses confirmed the uniform distribution of CNTs within the matrix and stronger interfacial bonding between the filler and polymer. Simulation results showed that the 0.5% MWCNT/1.5% PLA composite had the highest deformation (10.95 mm) with a safety factor of 1.12, indicating acceptable safety. In contrast, the 0.5% MWCNT composite showed the lowest deformation (4.17 mm), 12.6% less than pure Orthocryl, and the highest safety factor (3.2), reflecting an optimal balance of strength and flexibility for pediatric AFOs in CP patients.