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Research on the form and formation mechanisms of Tujia traditional settlement in the Wuling Mountains, China
Impact of early and delayed azvudine administration on COVID-19 mortality: a retrospective study
Abnormal regulation of membrane-less organelles contributes to profilin1-associated ALS
Identification of plasma proteins associated with seizures in epilepsy: A consensus machine learning approach
Blood-based biomarkers in epilepsy could constitute important research tools advancing neurobiological understanding and valuable clinical tools for better diagnosis and follow-up. An interesting question is whether biomarker patterns could contribute additional understanding compared to individual marker values. We analyzed OLINK proteomics data from a large epilepsy cohort in which we have previously found four differentially expressed proteins (CDH15, PAEP, LTBP3, PHOSPHO1). Using two machine-learning techniques, we identified ten consensus candidate protein biomarkers (CDH15, PAEP, LTBP3, PHOSPHO1, NEFL, SFRP1, TDGF1, DUSP3, WWP2 and DSG3) that contributed to the classification of patients as being seizure-free or not. Six out of the ten consensus proteins were identified as differentially expressed in our previous study (although NEFL and TDGF1 not significantly so after multiple testing correction). The remaining four consensus proteins were newly identified by machine learning and were chosen for detailed analysis. In comparison to the four significantly differentially expressed proteins (CDH15, PAEP, LTBP3, PHOSPHO1), the newly identified consensus proteins (SFRP1, DSG3, DUSP3, and WWP2) and in particular a combination of all eight proteins, outperformed individual proteins in identifying individuals with recent seizures, highlighting the potential of multi-protein profiles. These findings emphasize the need for integrative bioinformatic approaches in epilepsy research and underscore the role of neuroinflammation and immune pathways in epileptogenesis. Our results support the applicability of plasma protein profiling for developing future blood-based tests for epilepsy seizure prediction, diagnosis, and treatment. Further validations in independent cohorts are required to establish these candidate biomarkers in clinical practice.
Restoration of authenticity in building insulation-and-decoration integrated board in cold regions
The platelet to high-density lipoprotein cholesterol ratio is associated with thyroid hormone abnormalities based on NHANES 2007 to 2012 data
Evaluating the Tree Drawing Test Depression Assessment Scale for adolescent depression screening
Biofunctionalization of chalcogenide glass fiber to enhance real time and label free detection by mid infrared spectroscopy
Abstract Bio-functionalized chalcogenide infrared optical glass fibers have been designed for evanescent wave mid-infrared spectroscopy. Surface biotinylation of the fiber tapered sensing zone has been achieved by reactivity of a maleimide function on sulfhydryl moieties of the glassy surface. Biotin-streptavidin interactions were studied by fiber evanescent wave spectroscopy. Kinetic measurement comparisons of functionalized and non-functionalized fiber surfaces for various protein concentrations have demonstrated the efficient bio-selectivity of the functionalized glass fibers. The protein enrichment of the functionalized glassy surface allows for a significant increase of the protein detection limit, greater than two orders of magnitude as compared to reference non-functionalized fibers. A detection of minute quantities at concentrations as low as 10 parts-per-billion is demonstrated. This study shows that bio-functionalized chalcogenide optical fibers allow to combine successfully surface bio-selectivity and infrared absorption fingerprints measurements to get a remarkable sensitivity enhancement of fiber evanescent wave detection methods in the mid infrared spectral range.
Bio-mediated CN cycling in serpentinites and the origin of life
Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis
Determinants of medical costs in patients with and without fractures using Korean Senior Cohort Study
Meta-analysis shows a malleable rightward bias in the expectations of objects in space
Live-cell imaging of DNA damage and cell cycle progression uncovers distinct responses during neural differentiation of hiPSCs
The relationship between teacher commitment, teacher self-efficacy, and work-related quality of life among science teachers
This study examines the validity and reliability of the Arabic versions of the Teacher Commitment Scale, Teacher Self-Efficacy Scale, and Work-Related Quality of Life Scale. It explores the relationships among these variables in Jordan. A total of 616 science teachers participated by completing the three scales. Exploratory factor analysis indicated that the Arabic version of the Teacher Commitment Scale comprised four factors explaining 62.49% of the variance; the Teacher Self-Efficacy Scale consisted of one factor accounting for 60.22% of the variance; and the Work-Related Quality of Life Scale included six factors explaining 74.14% of the variance. Results showed statistically significant relationships among teacher commitment, self-efficacy, and quality of life. Future research should explore additional variables influencing teacher commitment.
Lamina cribrosa morphology and clinical implications in glaucoma with thin central corneal thickness
Assessment of magnetism and magnetocrystalline anisotropy of (Mn$$_x$$Fe$$_{1-x}$$)$$_2$$P$$_{1-y}$$Si$$_y$$ (x,y = 0 or 1/3) compounds for permanent magnets
Causal links to persisting daytime equatorial plasma bubbles over Asia-Pacific region following the geomagnetic storm on 01 December 2023
Phenotypic yield-attributed traits and phytochemical composition of the flowers from Alcea species in Iran
Solvent free UV curable waterborne polyurethane acrylate coatings with enhanced hydrophobicity induced by a semi interpenetrating polymer network
Abstract This study presents the synthesis and characterization of solvent-free, UV-curable waterborne polyurethane-acrylate (WPUA) coatings using a semi-interpenetrating polymer network (sIPN) technique, aiming to develop durable, high-performance eco-friendly coatings. The WPUA formulations consisted of a urethane backbone created from polytetrahydrofuran (PTHF) and isophorone diisocyanate (IPDI), combined with urethane dimethacrylate (UDMA) to introduce acrylate functionality. The synthesized coatings were thoroughly analyzed to assess their morphology, thermal stability, spectroscopic characteristics, water absorption, adhesion strength, and mechanical properties. The design of experiments (DoE) approach was applied to optimize film characteristics, particularly tensile strength. Mechanical testing revealed that incorporating UDMA into the WPUA matrix significantly improved tensile strength, increasing from 4.1 MPa to 8.8 MPa in the optimized formulation. The increase in the cross-cut adhesion test rating from 3B to 5B demonstrates that UV curing significantly enhanced adhesion. Furthermore, the addition of UDMA increased hydrophobicity, reducing water absorption and raising the water contact angle from 67° to 83°.These results indicate that the UV-cured WPUA films possess superior mechanical properties, thermal stability, and water resistance, making them viable options for sustainable coating applications.