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Influence of pulverization on the micropore structure of coal and its fractal characteristics
Ultra-rapid preparation of large-area high-crystallinity covalent organic framework membranes
Design a model to predict incomplete immunization among Ethiopian children using ensemble machine learning algorithms
Abstract Immunization is a cost-effective public health intervention globally, including in Ethiopia. However, the study focused on children aged 0–59 months and analyzed factors influencing incomplete immunization using ensemble machine learning techniques. A total of 16,394 EDHS datasets were used, with 80% for training and 20% for testing sets. Accordingly, the training set consisted of 13,115 samples, while the testing set contained 3,279 samples. Ensemble learning algorithms were employed, including Bagging methods (Bagging meta-estimator, Random Forest), Boosting methods (Gradient Boosting, XGBoost, LightGBM, AdaBoost, and CatBoost), and Voting ensembles combining both bagging and boosting models. Additionally, Stacking was performed using XGBoost and CatBoost as base models, with other machine learning algorithms such as Random Forest, K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Logistic Regression as meta-models. All models were implemented using the Python programming language. On the tested data, bagging meta-estimator + XGBoost voting model executed the highest performance result of accuracy (95.94%), f1-score (95.89%), recall (94.81%), and precision (97.07%), for visualizing using a confusion matrix and AUC-ROC value of 96%, and the cross-validation score of 95.75% for its reliability. Also, the most influential factors for incomplete immunization include marital status, residence, and others. This study aims to identify key factors influencing immunization coverage among Ethiopian children under the age of five and improve with ensemble machine learning algorithms. The findings provide valuable insights for targeted interventions, supporting improved immunization practices and contributing to better child health outcomes.
Revealing the topological nature of entangled orbital angular momentum states of light
A novel ZnO-MgO-Gd₂O₃ nanocomposite synthesized with Ocimum basilicum seed extract for enhanced photocatalysis
GlyContact analyzes glycan 3D structures at scale
Abstract Glycans are branched, structurally diverse, and highly flexible biomolecules. These characteristics make glycoanalytics and structural characterization challenging, resulting in often unclear structure-to-function relationships. GlycoShape, currently the largest open-access database of glycan 3D structures from molecular dynamics (MD) simulations, provides an opportunity to fill this information gap. Here, we present GlyContact, an open-source Python package designed and developed to retrieve, process, and analyze glycan 3D structures, from MD, NMR, or X-ray crystallography. We demonstrate that GlyContact can (i) unveil the impact of sequence context on glycan motif structure, (ii) yield a predictive understanding of motif flexibility and surface accessibility on lectin-glycan binding, which improved lectin-binding prediction by ~ 7%, and (iii) accurately predict torsion angle distribution between disaccharides using von Mises graph neural networks. We envision that GlyContact will allow researchers to explore glycan structures within their 3D space, obtaining insights into their biological functions. GlyContact is available open-access at https://github.com/lthomes/glycontact .
Impact of pancreatic proenzymes on pancreatic ductal adenocarcinoma associated fibroblasts
Mitochondria are absent from microglial processes performing surveillance, chemotaxis, and phagocytic engulfment
A mathematical formulation and computational exploration of Yayoi Kusama’s tentacle artworks
Functionally diversified Caenorhabditis elegans BiP orthologs control body growth, reproduction, stress resistance, aging, and autophagy
Synergistic antibiofilm activity of methylene blue and silver nanoparticle-mediated photothermal therapy against Enterococcus faecalis biofilm
Abstract Biofilm formation by Enterococcus faecalis ( E. faecalis) in root canals is a significant challenge in endodontic therapy, often leading to persistent infections and treatment failures. This research paper investigates the antibiofilm efficacy of methylene blue mediated photothermal treatment (MB-PTT), as compared to the sole effect of diode laser, PTT, and sodium hypochlorite (NaOCl) on E. faecalis biofilms. 45 maxillary central incisors were decoronated, prepared and infected by E faecalis for seven days. Forty samples were randomly allocated as follows; GI; irrigated with 2.6% NaOCl, GII; irradiated with 660 nm diode laser (250 mW) for 180 s. GIII; Silver nanoparticles (AgNPs) with diode laser application at same parameters (AgNPs-PTT), GIV: accompanied MB and AgNPs-PTT, while 5 samples were kept as control for biofilm formation. The antibiofilm effect was demonstrated both by bacterial colonies counting (CFU/ml) and scanning electron microscope images. The results highlight the potential of all experimental treatment modalities ( P < 0.01), However complete absence of detactable bacterial colonies was only evident when MB was coupled with AgNPs-PTT. Accompanied MB with PTT is a promising approach with effective antibiofilm activity against E. faecalis biofilms.
Histone acetylation homeodynamics navigates cell survival and apoptosis
Abstract The balance between inhibitor of apoptosis proteins (IAPs) and pro-apoptotic proteins (PAPs) tightly and precisely regulates cellular homeostasis. However, the epigenetic mechanism by which this balance is maintained in vivo remains largely unknown. Here we show that in various Drosophila tissues, the homeodynamics of H3K14ac/H3K27ac/H4K8ac on the promoters/enhancers of E93 and PAPs ( rpr / hid ), modulated by P300-CtBP/HDAC3, directs the decision between cell survival and the activation of hormone-induced developmental apoptosis. Concurrently, the homeodynamics of H3K14ac/H3K27ac/H4K8ac in IAPs ( Diap1 ) promoters, modulated by Tip60/P300-CtBP/HDAC3, sustains cellular homeostasis by antagonizing the activities of PAPs. Notably, the epigenetic mechanism revealed in Drosophila is partially conserved in mammals. Moreover, disrupting the histone acetylation homeodynamics attenuates tumorigenesis through altering the balances between IAPs and PAPs in Drosophila and mice. In conclusion, histone acetylation homeodynamics navigates cell survival and apoptosis, suggesting potential epigenetic targets for the treatment of diseases or tumors caused by the imbalance between IAPs and PAPs.
Elucidating the molecular compatibility mechanism to guide the optimization of Straw-Derived asphalt
Tunable Octdong and Spindle-Torus Fermi Surfaces in Kramers Nodal Line Metals
Abstract Kramers nodal lines are doubly degenerate band crossings in achiral non-centrosymmetric crystals, arising from spin-orbit coupling and connecting time-reversal invariant momenta. When intersecting the Fermi level, they generate exotic three-dimensional Fermi surfaces, in some cases described by two-dimensional massless Dirac fermions, enabling enhanced graphene-like physics such as quantized optical conductivity and large anomalous Hall effects. However, no experimental realization of such materials has been reported. Here, we identify Kramers nodal line metals beyond the case of Fermi surfaces enclosing a single time-reversal invariant momentum. Using angle-resolved photoemission spectroscopy and first-principles calculations, we show that 3R-TaS 2 and 3R-NbS 2 host open Octdong and Spindle-torus Fermi surfaces, respectively. We observe a filling-controlled transition between these configurations and evidence of size quantization in 3R-TaS 2 inclusions within 2H-TaS 2 . We further predict a strain- or pressure-driven transition to a conventional metal. Our results establish 3R transition-metal dichalcogenides as a tunable platform for Kramers nodal line physics.
Time-series analysis of vitiligo-related online search behavior in response to ambient air pollutants
Chiral multi-curved shell metamaterials integrating compression-torsion and buckling mechanisms for ideal energy absorption
Abstract Metamaterials with compression-torsion or buckling mechanism have demonstrated significant potential for energy absorption. However, compression-torsion metamaterials easily trigger deformation, resulting in low load-bearing capacity, and buckling ones have high peak load with fluctuations, accompanying severe localized deformations. Here, we propose chiral multi-curved shell (CMCS) metamaterials that synergistically couple compression-torsion and buckling mechanisms, achieving high and smooth load curves. The compression-torsion mechanism enables metamaterials to convert compressive deformation into torsional deformation, preventing abrupt changes in local geometry. Simultaneously, the synergy of compression-torsion and curved shell ensures that the buckling provides high load-bearing capacity and avoids localized deformation. This coupled compression-torsion-buckling deformation enables the material to achieve high energy storage. Characterized by tests, the CMCS metamaterials exhibit enhanced energy absorption and tuneability. Compared with Kresling and hexagon metamaterials, the proposed design achieves a 20-fold higher specific energy absorption (SEA) and a 50% higher efficiency of energy absorption (EEA) owing to its higher and gentler plateau phase, respectively. Multiple drop tests demonstrate their reliable impact protection and reusability. CMCS metamaterials provide a novel concept for lightweight and high-strength protective structures or materials.