Search Results (1,068)

Currently, only a limited number of Mark–Houwink–Sakurada (MHS) equations are available for chitin, and their applicability is constrained by the narrow range of suitable solvent systems. The Mark–Houwink–Sakurada (MHS) equation is a widely used and practical approach for estimating polymer molecular weight from intrinsic viscosity measurements, particularly when chromatographic techniques are not readily accessible. This study aimed to establish new MHS equations for chitin to facilitate reliable molecular weight determination across different solvents and temperatures. Chitin samples with varying molecular weights were prepared via H₂O₂ degradation, and their weight-average molecular weights (Mw) were determined by high-performance size-exclusion chromatography (HPSEC). Intrinsic viscosity ([η]) was measured using a capillary viscometer at 25 and 30 °C in three solvent systems: 5% LiCl/N,N-dimethylacetamide (LiCl/DMAc), 8% NaOH/4% urea, and 10% NaOH/0.3% tannic acid (w/w). Double-logarithmic plots of Mw versus [η] were constructed to derive the corresponding MHS equations. At identical molecular weights and temperatures, intrinsic viscosity followed the order: LiCl/DMAc > NaOH/urea > NaOH/tannic acid. Increasing temperature led to higher intrinsic viscosity and conformation parameter (a) values. Chitin dissolved in LiCl/DMAc and NaOH/urea exhibited rod-like conformations, with a values ranging from 0.79 to 0.97, whereas chitin in NaOH/tannic acid displayed random coil behavior (a = 0.56–0.69). These established MHS equations expand the solvent applicability for chitin molecular weight determination and provide insights into its solution conformation under different chemical environments. Full article

Background/Objectives: The tumor suppressor gene TP53 is one of the most frequently mutated genes in human cancers, with alterations predominantly affecting its DNA-binding domain (DBD). However, the mutational landscape and functional consequences of TP53 variants remain poorly characterized in African populations. This study aimed to characterize mutations in exons 5–6 of TP53 in oral cavity cancer (OCC), prostate cancer (PC), and breast cancer (BC) in a Senegalese population, and to assess their structural effects, functional consequences, and impact on protein–protein interactions with BCL-2. Methods: Seventy-eight archived tumor DNA samples from Senegalese patients with OCC, PC, and BC were analyzed. Variants were annotated using COSMIC and dbSNP databases. Functional impact was evaluated with PolyPhen-2. Structural stability changes ($\Delta \Delta G$) were predicted using FoldX, conformational dynamics ($\Delta \Delta S_{vib}$) were assessed with ENCoM, and effects on the p53–BCL-2 interaction were analyzed using DDMut-PPI. Statistical analyses were also performed. Results: BC exhibited the highest TP53 mutation frequency, whereas OCC showed greater mutational diversity. Exon-level analysis revealed a significant enrichment of exon 6 mutations in BC. Structural analyses indicated that exon 5 mutations across all cancers and mutations in OCC were predominantly destabilizing and associated with loss-of-function effects. In contrast, recurrent exon 6 mutations in PC and BC, particularly V217L and V218M, were predicted to stabilize the p53 structure. Conformational dynamics differences between exons were significant only in PC. All analyzed mutations were predicted to stabilize the p53–BCL-2 interaction. Conclusions: This integrative in silico study identified cancer and exon-specific TP53 mutation patterns in a Senegalese population, highlighting exon 6 as a context-dependent hotspot with potential oncogenic implication in PC and BC. Despite its computational nature, the study provides valuable insights that merit further investigation. Full article

Background: The human gut microbiota plays a central role in host physiology by influencing digestion, immune function, and metabolism. Characterizing age-associated differences in the organization of microbial metabolism may provide insights into functional variation in the gut microbiome across the human lifespan. Methods: Gut microbiota metabolic organization was analyzed in a cohort of 30 individuals spanning three age groups (infants, adults, and elderly individuals) and comprising 156 stool samples. Community metabolic networks were reconstructed using the metabolic Directed Acyclic Graph (m-DAG) framework derived from KEGG Ortholog annotations. Network topology was characterized to assess whether the resulting networks conform to previously described global structural patterns and to examine age-associated variability. Pairwise m-DAG dissimilarities were computed, and hierarchical clustering was applied to evaluate similarities among samples. Results: All samples revealed a conserved global network organization, alongside marked variability in specific structural features. Hierarchical clustering did not strictly reflect chronological age. A homogeneous cluster composed exclusively of adult samples was identified, whereas elderly samples were distributed across two clusters, one grouping with adults and the other with infants. Exploratory discriminative analyses identified functional reactions contributing to the separation between the adult cluster and the remaining samples, indicating age-associated differences in metabolic network organization. Conclusions: Gut microbiota metabolic networks in adults tend to exhibit lower redundancy and structural complexity, whereas those in infant and elderly samples display more heterogeneous network configurations. This network-based analysis provides a functional perspective on age-associated variation in gut microbiota metabolism and offers a framework for future integrative studies. Full article

The application of natural polysaccharides and their sulfated derivatives have already been successfully implemented in the pharmaceutical and food industries, in particular. The present study is concerned with modifying a predominant polysaccharide in the composition of spruce wood, galactoglucomannan (GGM), by sulfation via a urea˗sulfamic acid complex in a 1,4-dioxane medium. By varying the sulfation process duration from 30 to 180 min, six novel GGM sulfate samples with different degrees of substitution (DS) of 0.4–1.2 were obtained and studied with a combination of modern physicochemical methods: elemental analysis, Fourier transform infrared (FTIR) spectroscopy, and gel permeation chromatography (GPC). It has been revealed that the sulfation of GGM proceeds without degradation of the main polymer chain, as evidenced by the shift in the main peak toward the high-molecular-weight region in the GPC curves. Moreover, modification of the polysaccharide leads to a significant transformation of the molecular conformation from a dense sphere to a random coil (α from 0.30 to 0.76). Furthermore, it has been determined that sulfate-substituted groups of the GGM tended to decrease the scavenging capacity of the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radicals. However, the 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) assay showed an increase in the free radical inhibitory capacity of sulfated polysaccharides. This is attributed to the structural and conformational properties of the polysaccharide sulfate derivatives. The maximum anticoagulant activity (ACA) of sulfated GGM (SGGM) is 21.19 ± 2.89 IU/mg and increases with increasing sulfation duration. Full article

Understanding interactions between cations and DNA is essential for elucidating the structural dynamics of this fundamental biomolecule. While B-DNA is well known to dominate in long genomic DNA under physiological ionic conditions, its stability in very short DNA fragments—particularly in dilute solutions and in crude oligonucleotide preparations—has remained largely unexplored. Previous spectroscopic studies have primarily focused on long DNA, highly purified oligonucleotides, or high-salt environments, where collective polyion effects dominate. In contrast, the present results demonstrate that even in the absence of chain overlap and under low-salt conditions, Mg²⁺ ions efficiently stabilize the B-form by screening phosphate–phosphate electrostatic repulsion at the intrachain level. The ability to induce an A-to-B transition in crude, ultra-short DNA fragments highlights the fundamental role of divalent counterions in governing DNA conformation and establishes a lower bound for the length scale at which B-DNA can be stabilized. These findings are particularly relevant for dilute biological systems, fragmented DNA samples, and analytical protocols where short DNA fragments and low ionic strength are unavoidable. Full article

Constrained by the low grade and poor floatability of the run-of-mine ore, the beneficiation of porphyry-type copper–molybdenum sulfide ores generates large quantities of molybdenum tailings, leading to significant environmental risks and resource losses and necessitating urgent recovery and reutilization. In this study, a representative sample of molybdenum tailings with a Mo grade of 0.354% was investigated to analyze its process mineralogy. The results show that molybdenite predominantly exists as fine, flaky particles intimately intergrown with quartz, pyrite, and aluminosilicate minerals, exhibiting an extremely low degree of liberation and an overall ultrafine particle size. Laboratory flotation tests show that the flotation kinetics conform to a first-order model; however, a considerable amount of molybdenum remains in the tailings, indicating that the mineralization process needs to be intensified. Through structural optimization and confined-space design, a vortex-based mineralization reactor was developed. Computational fluid dynamics simulations demonstrate that the mineralizer can generate flow fields with high turbulence intensity and dissipation rates and can induce high-energy, small-scale micro-vortices. On this basis, a semi-industrial rougher flotation system was established by coupling the developed mineralizer with a flotation column. Under optimized operating conditions, namely a feed pressure of 0.06 MPa and an impeller frequency of 20 Hz, single-stage treatment of the tailings produced molybdenum concentrates with a grade of 1.90% and a recovery of 81.29%, while the Mo grade of the tailings was reduced to 0.08%. The results are markedly superior to those obtained using a conventional laboratory flotation cell, demonstrating a substantial enhancement in mineralization efficiency and molybdenum recovery. The proposed approach, therefore, provides a practical reference for the flotation recovery of molybdenum tailings as well as other micro-fine, low-grade metal tailings. Full article

Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, peptidomic profiles were established on wort fermentation day 0, day 1, day 3, and day 9. A total of 25,592 peptides were identified by reversed-phase liquid chromatography–quadrupole time-of-flight mass spectrometry (RPLC-QTOF-MS). Molecular informatics screening was performed using UMPred-FRL (a feature representation learning-based meta-predictor for umami peptides) and TastePeptides-Meta (a one-stop platform for taste peptides and prediction models), yielding 7255 potential umami peptides. From these, 145 peptides were further selected for molecular docking. In addition, 6 representative umami peptides were selected for receptor-level validation and structural analysis. Mechanistically, the umami receptor taste receptor type 1 member 1/taste receptor type 1 member 3 (T1R1/T1R3) belonged to class C G protein-coupled receptor (GPCR) and relied on the extracellular Venus flytrap (VFT) domain for ligand capture. Ligand-induced VFT conformational convergence transmitted changes to the transmembrane region and triggered signal transduction. Docking and energy decomposition indicated that the ionic group primarily contributed to orientation and anchoring. Salt-bridge or hydrogen-bond networks were formed around Lys228, Arg240, Glu206, Asp210, Asn141, and Gln138, thereby reducing conformational freedom. Meanwhile, hydrophobic side chains obtained major binding gains within a hydrophobic microenvironment formed by Val135, Ile137, Leu165, Tyr166, Trp78, and His79. These results reflected a synergistic mode in which charge pairing enabled positioning and hydro-phobic complementarity promoted VFT closure. To experimentally confirm sensory relevance, 6 representative peptides were individually spiked into 4 brewing-stage beer samples, which produced a clear stratification pattern across stages. Notably, peptides with favorable docking-derived binding propensity did not necessarily enhance umami perception, and several longer peptides showed persistent negative sensory shifts, supporting that binding affinity alone could not be treated as a proxy for perceived umami in the beer matrix. At the node level, the cumulative abundance of umami peptides showed a significant positive correlation with umami scores, with a Pearson correlation coefficient of r = 0.963 and p = 0.037. This result indicated good linear consistency between umami peptide content and the upward shift in umami taste in lager beer. Umami peptide clusters were further proposed as a more appropriate functional unit, and an umami peptide cluster database spanning the full process was constructed. This database provided a reusable resource for process control and flavor prediction. Full article

Bamboo powder waste generated from bamboo processing serves as an ideal feedstock for biochar (BC). This study employed potassium hydroxide (KOH) to modify biochar derived from bamboo powder waste, activating it at different temperatures (700 °C, 800 °C, and 900 °C) to yield samples designated KBC-700, KBC-800, and KBC-900, respectively. The physicochemical properties and pore structures of the modified biochar were characterized using SEM, specific surface area and pore size analysis, FT-IR, Raman spectroscopy, XRD, and zeta potential measurements. The adsorption performance of the modified biochar toward PFOA was investigated using kinetic and thermodynamic models, examining the effects of the solution pH, adsorbent dosage, and temperature. Results indicate that KBC-900 exhibits a significantly enhanced specific surface area (up to 2924.7 m² g⁻¹), reduced surface oxygen-containing functional groups, increased carbon skeleton aromatization, and expanded mesoporous channels. Under initial conditions of pH = 3 and reaction temperature of 298 K, KBC-900 achieved a PFOA adsorption capacity of 366.7 mg g⁻¹ with a removal efficiency of 91.67%. The adsorption process conformed to pseudo-first-order and pseudo-second-order kinetic models as well as the Freundlich model. The adsorption equilibrium was reached within 12 h, indicating multi-layer adsorption dominated by chemisorption on a heterogeneous surface. Thermodynamic parameters indicate the adsorption reaction is an exothermic process. After five cycles of regeneration, KBC-900 maintained a removal efficiency of 75.69%. This study provides an efficient and reliable solution for removing PFOA from water. Full article

This study develops a mathematical optimization framework to determine optimal inspection policies for imperfect production systems subject to stochastic deterioration. System degradation is modeled using a Weibull power law process, which captures the increasing likelihood of transitions from in-control to out-of-control states over time. When deterioration occurs, a reverse-order inspection strategy based on negative binomial sampling is employed, wherein an inspection continues until a predefined number of conforming items is obtained. The proposed model integrates inspection decisions with production learning effects and Bayesian demand updating. Learning-by-doing is incorporated through an experience-dependent production cost function, while demand uncertainty is addressed using Bayesian posterior estimation. A comprehensive expected total cost function is formulated, including production, inspection, inventory holding, warranty, and rework costs. The analytical properties of the model are examined, demonstrating that the expected total cost function is strictly convex with respect to the inspection decision variable. This convexity guarantees the existence and uniqueness of the optimal solution. Numerical experiments and sensitivity analyses illustrate the effects of defect rates, learning parameters, warranty periods, and demand uncertainty on the optimal inspection policy. The results show that jointly optimizing inspection intensity, learning effects, and demand information leads to significant cost reductions and robust decision-making in deteriorating production systems. Full article

The conformation of a glycosaminoglycan (GAG) carbohydrate biopolymer is dependent upon the ring puckering states of its constituent monosaccharide residues and the dihedral angles (φ, ψ) of the glycosidic linkages connecting these residues. In the context of GAGs, the monosaccharide residue iduronate (IdoA; the conjugate base of iduronic acid) is able to take on both chair and boat-like ring pucker states. All-atom explicit-solvent molecular dynamics simulations were applied to determine the extent to which IdoA ring pucker state affects the conformational preferences of (φ, ψ) in 16 different IdoA-containing disaccharides derived from the GAGs heparin/heparan sulfate and dermatan sulfate. Using the extended-system adaptive biasing force (eABF) method, the complete free-energy surface ΔG(φ, ψ) was computed for each disaccharide with its IdoA ring restrained separately to the ¹C₄, ²S_O, B_3,O, or ⁴C₁ ring pucker state. Global-minimum ΔG(φ, ψ) values resided within broad ΔG(φ, ψ) basins, and both ring pucker state and sulfation status influenced basin shape and size. Various sulfoforms of the disaccharide IdoAα1–4GlcNS had prominent secondary-minimum basins distinct from the global-minimum basins, and these secondary-minimum basins may manifest as metastable states in standard (nonbiased) molecular dynamics simulations on the 1-microsecond timescale. As such, the present results provide a reference for assessing (φ, ψ) sampling in nonbiased molecular dynamics simulations of GAGs and demonstrate the interplay between IdoA ring puckering, glycosidic linkage dihedral rotation, and sulfation status in contributing to GAG conformational preferences. Full article

Excessive molybdenum (VI) (Mo (VI)) in water threatens environmental safety and human health, yet rapid on-site methods for Mo (VI) determination remain limited. Here, we propose a rapid method for Mo (VI) determination using phenylfluorone (PF)-modified test strips with dual readouts: visual colorimetry and image-based analysis in the CIELAB (Lab*) color space, and demonstrate its applicability using urban park water samples. Based on visual colorimetry, a standard color card was established, providing a screening range of 0.08 to 0.8 mg L⁻¹ (A blank (0 mg L⁻¹) was used as the baseline reference). Moreover, by the LAB color space, the linear relationship between the color development results of the PF-modified test strip and the A channel conforms to y = 21.08 + 8.82x (R² = 0.992), with a detection range of 0–0.8 mg L⁻¹. The total detection time was reduced to 2.5 min. To evaluate accuracy in real matrices, influent, midstream, and effluent samples from Chengdu Living Water Park were analyzed, with UV-vis spectrophotometry used as the reference method. The test-strip results agreed well with UV-vis spectrophotometry, with relative errors below 5%. Overall, this study provides a portable, rapid, and accurate method for the detection of Mo (VI) in water, and has potential application prospects in the field of water environment detection in the future. Full article

This study introduces a framework for estimating the optical scattering properties of thin-film phantoms using a custom-built Spectral-Domain Dental Optical Coherence Tomography (DEN-OCT) system operating within the 780–900 nm spectral range. The purpose of this work was to assess the performance of this system. The system exhibited high depth-resolved imaging performance with an axial resolution of approximately 16.30 µm, a signal-to-noise ratio of about 32.4 dB, and a 6 dB sensitivity roll-off depth near 2 mm, yielding an effective imaging range of 2.5 mm. Thin-film phantoms with controlled optical characteristics were fabricated and analyzed using Beer–Lambert and diffusion approximation models to evaluate attenuation behavior. Samples representing different tissue analogs demonstrated distinct scattering responses: one sample showed strong scattering similar to hard tissues, while the others exhibited lower scattering and higher transmission, resembling soft-tissue properties. Spectrophotometric measurements at 840 nm supported these trends through characteristic transmittance and reflectance profiles. While homogeneous samples conformed to analytical models, the highly scattering sample deviated due to structural non-uniformity, requiring Monte Carlo simulation to accurately describe photon transport. OCT A-scan analyses fitted with exponential decay models produced attenuation coefficients consistent with spectrophotometric data, confirming the dominance of scattering over absorption. The integration of OCT imaging, optical modeling, and Monte Carlo simulation establishes a reliable methodology for quantitative scattering estimation and demonstrates the potential of the developed DEN-OCT system for advanced dental and biomedical imaging applications. The innovation of this work lies in the integration of phantom-based optical calibration, multi-model scattering analysis, and depth-resolved OCT signal modeling, providing a validated pathway for quantitative parameter extraction in dental OCT applications. Full article

Wee1-like protein kinase 2 (WEE2) is an oocyte-specific kinase that regulates meiotic arrest and fertilization. Its largely restricted expression in female germ cells and absence in somatic tissues make it a highly selective target for reproductive health interventions. Despite its central role in human fertility, no clinically approved WEE2 modulator is available. In this study, we employed an integrated in silico approach that combines structure-based virtual screening, molecular dynamics (MD) simulations, and MM-PBSA free-energy calculations to identify repurposed drug candidates with potential WEE2 inhibitory activity. Screening of ~3800 DrugBank compounds against the WEE2 catalytic domain yielded ten high-affinity hits, from which Midostaurin and Nilotinib emerged as the most mechanistically relevant based on kinase-targeting properties and pharmacological profiles. Docking analyses revealed strong binding affinities (−11.5 and −11.3 kcal/mol) and interaction fingerprints highly similar to the reference inhibitor MK1775, including key contacts with hinge-region residues Val220, Tyr291, and Cys292. All-atom MD simulations for 300 ns demonstrated that both compounds induce stable protein–ligand complexes with minimal conformational drift, decreased residual flexibility, preserved compactness, and stable intramolecular hydrogen-bond networks. Principal component and free-energy landscape analyses further indicate restricted conformational sampling of WEE2 upon ligand binding, supporting ligand-induced stabilization of the catalytic domain. MM-PBSA calculations confirmed favorable binding free energies for Midostaurin (−18.78 ± 2.23 kJ/mol) and Nilotinib (−17.47 ± 2.95 kJ/mol), exceeding that of MK1775. To increase the translational prioritization of candidate hits, we place our structure-based pipeline in the context of modern machine learning (ML) and deep learning (DL)-enabled virtual screening workflows. ML/DL rescoring and graph-based molecular property predictors can rapidly re-rank docking hits and estimate absorption, distribution, metabolism, excretion, and toxicity (ADMET) liabilities before in vitro evaluation. Full article

Accurate prediction of individual treatment effects in survival analysis is often complicated by the presence of competing risks and the inherent unobservability of counterfactual outcomes. While machine learning models offer improved discriminative power, they typically lack rigorous guarantees for uncertainty quantification, which are essential for safety-critical clinical decision-making. In this paper, we introduce CONFIDE (CONFormal Inference for Distribution-free Estimation), a novel framework that bridges causal inference and conformal prediction to construct valid prediction sets for cause-specific cumulative incidence functions. Unlike traditional confidence intervals for population-level parameters, CONFIDE provides individual-level prediction sets for time-to-event outcomes, which are more clinically actionable for personalized treatment decisions by directly quantifying uncertainty in future patient outcomes rather than uncertainty in population averages. By integrating semi-parametric hazard estimation with targeted bias correction strategies, CONFIDE generates calibrated prediction sets that cover the true potential outcome with a user-specified probability, irrespective of the underlying data distribution. We empirically validate our approach on four diverse medical datasets, demonstrating that CONFIDE achieves competitive discrimination (C-index up to 0.83) while providing robust finite-sample marginal coverage guarantees (e.g., 85.7% coverage on the Bone Marrow Transplant dataset). We note two key limitations: (1) coverage may degrade under heavy censoring (>40%) unless inverse probability of censoring weighted (IPCW) conformal quantiles are used, as demonstrated in our sensitivity analysis; (2) while the method guarantees marginal coverage averaged over the covariate distribution, conditional coverage for specific covariate values is theoretically impossible without structural assumptions, though practical approximations via locally-adaptive calibration can improve conditional performance. Our framework effectively enables trustworthy personalized risk assessment in complex survival settings. Full article

In freeform optical metrology, wavefront fitting over non-circular apertures is hindered by the loss of Zernike polynomial orthogonality and severe sampling grid distortion inherent in standard conformal mappings. To address the resulting numerical instability and fitting bias, we propose a unified framework curve-shortening flow (CSF)-guided progressive quasi-conformal mapping (CSF-QCM), which integrates geometric boundary evolution with topology-aware parameterization. CSF-QCM first smooths complex boundaries via curve-shortening flow, then solves a sparse Laplacian system for harmonic interior coordinates, thereby establishing a stable diffeomorphism between physical and canonical domains. For doubly connected apertures, it preserves topology by computing the conformal modulus via Dirichlet energy minimization and simultaneously mapping both boundaries. Benchmarked against state-of-the-art methods (e.g., Fornberg, Schwarz–Christoffel, and Ricci flow) on representative irregular apertures, CSF-QCM suppresses area distortion and restores discrete orthogonality of the Zernike basis, reducing the Gram matrix condition number from >900 to <8. This enables high-precision reconstruction with RMS residuals as low as $3\times {10}^{-3}\lambda$ and up to 92% lower fitting errors than baselines. The framework provides a unified, computationally efficient, and numerically stable solution for wavefront reconstruction in complex off-axis and freeform optical systems. Full article