Chemical Papers最新文献

This study investigates the degradation of Ponceau S (PS), a commonly used azo dye, through the cobalt-catalyzed Co²⁺/H₂O₂/UV advanced oxidation process (AOP). Process optimization was performed using the Box–Behnken design (BBD) under the framework of response surface methodology (RSM). Key operational parameters, namely the Co(II) concentration, the hydrogen peroxide (H₂O₂) dosage, and the PS dye concentration, were evaluated to maximize degradation efficiency, as the chosen response, after one hour of irradiation. The statistical analysis of the experimental data produced a robust predictive model with a high coefficient of determination (R² = 0.9655), confirming the model’s reliability. The model F value of 21.79 indicates that the model is statistically significant, with only a 0.03% probability that such a high F value could result from random noise. Among the tested variables, the initial PS concentration and the H₂O₂ dose were found to have a highly significant impact on the degradation efficiency. In contrast, the Co(II) concentration showed no significant effect whether in its linear, interaction, or quadratic forms. Regarding interaction effects, only the interaction between dye concentration and H₂O₂ dose was significant, and among the quadratic terms, only the H₂O₂ dosage showed a notable influence. Optimal conditions for maximum PS degradation were determined to be 0.03 mM dye concentration, 0.55 mM H₂O₂, and 0.06 mM Co²⁺. These findings underscore the potential of the Co²⁺/H₂O₂/UV system as an effective method for azo dye wastewater treatment, with BBD proving to be a valuable tool for operational optimization.

Bread is a fundamental food staple providing essential energy for human consumption. The purpose of this study was to explore how targeted enzyme applications can enhance bread quality and shelf life, addressing a gap in optimizing traditional bread formulations for modern consumer demands. This study investigated the effects of α-amylase, transglutaminase, and xylanase enzymes on the properties of Barbari, Lavash, and Sangak bread. Optimal enzyme levels were determined from preliminary tests to ensure the best bread quality. Optimal enzyme levels were incorporated into different flour types, and the resulting breads were stored at room temperature for six days. Moisture content, specific volume, differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and sensory evaluation were conducted at 0, 2, 4, and 6 days of storage at room temperature. Statistical analysis was performed using one-way ANOVA followed by Tukey’s test, with significance considered at p < 0.05. DSC thermograms revealed the emergence of new peaks and altered thermal behavior in enzyme-treated breads. SEM images indicated a compact bread structure with starch granules encapsulated by gluten proteins. Results showed a decrease in moisture content over time for all bread samples, with significant statistical differences (p < 0.05). Control breads exhibited the lowest moisture content, while B1, L1, and S1 maintained the highest moisture content. Specific volume increased over time, with the control samples having the lowest specific volume. Enzyme application enhanced the sensory properties of all breads, especially with higher α-amylase and lower transglutaminase levels. The study recommends using 30 ppm glucose oxidase for producing bread with improved characteristics.

In this study, a reliable fluorescence nanoprobe utilizing bovine serum albumin-modified silver nanocrystals (BSA-modified Ag NCs) was developed for the sensitive quantification of hydrogen peroxide (H₂O₂) in the milk samples. The successful synthesis of BSA-modified Ag NCs was examined through transmission electron microscopy, scanning electron microscopy, fluorescence spectroscopy, energy-dispersive spectrometry, dynamic light scattering, X-ray powder diffraction, and attenuated total reflectance–Fourier transforms infrared. The probe exhibited a significant decrease in fluorescence intensity when exposed to H₂O₂, indicating an oxidative interaction between BSA-modified Ag NCs and H₂O₂. The proposed nanoprobe displayed a linear response toward H₂O₂ in the concentration range of 1.5–294 nmol/L, with a detection limit of 0.3 nmol/L. The intraday precision and inter-day precision which are percentages of relative standard deviation for five repetitive measurements of H₂O₂ at a concentration of 59 nmol/L, respectively, on the same day and different days were 3.4% and 6.8%. The validated method was successfully used for the determination of H₂O₂ in six milk samples obtained from the local market. This method exhibited high sensitivity and specificity, offering a sensing platform that is simple, convenient, and quick to implement.

Crease finishing has revolutionized cotton textiles by enhancing wrinkle resistance, durability, and aesthetic appeal, addressing the natural propensity of cotton to crease. This review comprehensively traces the evolution of crease-finishing techniques, from early starch-based methods to modern chemical, nano-based, and enzymatic treatments. Historically, formaldehyde-based resins like urea–formaldehyde and DMDHEU dominated, but health and environmental concerns have driven the adoption of non-formaldehyde alternatives such as polycarboxylic acids (e.g., BTCA) and bio-based agents like citric acid and chitosan. Current advancements include nanotechnology, plasma treatments, and enzymatic processes, which improve crease recovery angles (CRA, 250–300°) while minimizing environmental impact. Challenges persist, including wastewater generation, reduced fabric strength, and consumer demand for sustainable yet high-performance textiles. Future trends focus on green chemistry, smart textiles with self-ironing capabilities, and AI-driven finishing for precision and efficiency. By synthesizing past developments, present innovations, and emerging possibilities, this review provides a roadmap for researchers, manufacturers, and consumers navigating the dynamic landscape of textile finishing, emphasizing sustainability and performance.

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Chalenges in Crease Finishing of Cotton Textiles

We employ statistical and graph theoretical methods to explore the relationship between structural topology and information content in two dimension carbon nitride ((C_{2}N)) monolayers. To this end, we consider several degree-based Zagreb-type indices together with entropy measurement to investigate the inherent complexity and information encoding capacity of ((C_{2}N)) network. The quantification of the entropy and topological indices provide molecular connectivity and system disorder data. Logarithmic regression modeling is employed to determine nonlinear relationships between entropy and indices, and is also justified using Pearson correlation analysis. The strong correlation coefficients found in this work support these indices as reliable metrics for assessing the structure and complexity of ((C_{2}N)) materials, with potential applications in materials science and nanotechnology.

Medical textiles represent a rapidly growing segment within functional textiles, driven by the need for enhanced health protection. Herein, selenium nanoparticles (SeNPs) have emerged as promising agents due to their intrinsic antimicrobial, anti-inflammatory, and biocompatible properties. This study introduces a novel method for imparting multifunctional properties to cotton fabrics by embedding SeNPs using microwave-assisted deposition on both untreated and cationized cotton substrates. Air permeability and vapor permeability were non-observably decreased from 14.5 cm³/cm² s and 1766 g/m² day for cationized cotton to 12.3 cm³/cm² s and 1727 g/m² day for the sample prepared with higher Se concentration (Se@Q-Cotton (4)). Antimicrobial tests showed a reduction of 94.4–95.3% for Staphylococcus aureus and 86.0–86.4% for Escherichia coli, both before and after 10 washing cycles, indicating strong durability. Furthermore, Se@Q-Cotton (4) maintained significant anti-inflammatory efficacy, with cell viability measured at 76.9% before and 41.6% after repeated washing. UV protective properties were also enhanced, with an initial UPF of 55.5 that remained at a very good level (39.1) after washing. These findings confirm the potential of SeNPs-treated cotton fabrics as highly durable medical textiles with superior antimicrobial, anti-inflammatory, and UV protective functionalities, suitable for long-term clinical and protective applications.

Topological descriptors and Shannon entropy play significant roles in the account of structure and information characteristics of molecular networks. Various degree-based and distance-based topological descriptors are computed to understand the structural peculiarity of the terephthalic tetragonal network. The tetragonal terephthalic compound ((TI_4Te_3Pb)) is identified based on its distinctive tetragonal crystal structure, consisting of lead (Pb), tellurium (Te) and thallium (Tl). The optically isotropic tetragonal-shaped crystal lattice is axis-centric with a square base and two equal axes and a distinctive third axis (c-axis). Shannon entropy is computed to quantify the uncertainty and information content of the network. Logarithmic regression modeling identifies correlations between calculated indices and entropy, which reveals the mathematical dynamics of these descriptors. Observations are seen to exhibit remarkable connections, indicative of the applicability of logarithmic regression in predicting network attributes. This work adds to the cheminformatics and network theory literature in the suggestion of a systematic approach to the analysis of molecular structures through computation. Furthermore, this work adds to the quantitative structure–property relationship literature through the availability of a dependable computational platform for the analysis of novel nanomaterials, with potential applications in drug discovery, material science, and nanotechnology.

Prostate cancer (PC) is the second most diagnosed cancer and a significant cause of mortality among men globally. Castration-resistant prostate cancer (CRPC) poses a challenge due to its resistance to conventional androgen deprivation therapy (ADT). Targeting the bromodomain and extraterminal domain (BET) family proteins, particularly BRD4, has shown potential in treating CRPC. This study involves molecular docking of 54 molecules against the acetyl–lysine binding site of BRD4's first bromodomain (BD1) using PDB structure 5Y8Z. A pharmacophore model was generated and validated, followed by screening the NCI database. Concurrently, a 3D QSAR model predicted activity. Virtual screening, MM-GBSA analysis, and ADMET prediction were performed, with many discovered compounds showing improved G-scores (− 9.495 to − 8.002 kCal∙mol⁻¹) toward BRD4-BD1. Five promising compounds—NSC321246, NSC16725, NSC10021, NSC131751, and NSC40091—were subjected to MD simulations followed by MM-PBSA calculations. NSC40091 emerged as the most promising candidate, exhibiting high binding energy, moderate activity, and appropriate ADME characteristics. Despite NSC321246's highest Glide Gscore of − 9.495, it had the lowest ADME results. MD simulations confirmed NSC40091's stability, flexibility, and favorable hydrogen bonding, highlighting its potential as a therapeutic agent for CRPC. Further, experimental validation is necessary to develop selective BET inhibitors for CRPC treatment.

Point-of-care (POC) diagnostics is being revolutionized by smartphone-assisted biosensors, which combine cutting-edge sensing technologies with the computing power and connectivity of smartphones. These biosensors provide a portable and affordable substitute for conventional laboratory-based diagnostics by enabling the quick, real-time analysis of physiological parameters and biomarkers. Smartphone-assisted biosensors enable continuous health monitoring, enhanced patient engagement, and early disease detection by utilizing optical, electrochemical, and biomarker-based detection techniques. The development of smartphone-assisted biosensing platforms is reviewed in this article, along with their technological integration, detection methods, and medical applications. Sensor accuracy, data security, regulatory approval, and standardization continue to be challenges despite the progress. The impact of recent advancements on infectious disease management, chronic disease monitoring, and personalized medicine is highlighted in this review, which critically assesses wearable biosensors, AI-driven analytics, and smartphone-integrated disease detection systems.

Directly connected 1,3-azoles are identified as sub-structures in significant naturally occurring compounds with intriguing structures as well as interesting biological activities. Amidst them, bithiazole (BT) is an uncommon structural feature of many potent naturally and biologically active compounds with diversified therapeutic efficacy. BT-based organic moieties have strengthened the efficiency of solar devices and are a promising source of light harvesting. Also, BT-based medicinal chemistry is rapidly expanding and increasing activity due to associated research and advancements. To date, no review article has explored the captivating pharmacological potential of BT as a core structure. This review marks the author’s pioneering effort to conduct a critical analysis of both the synthesis and medicinal properties of BT derivatives. The aim is to underscore this heterocyclic compound’s profound significance and practical utility in the drug discovery continuum. An overview of natural compounds containing BT, several synthesis methods, and the biological activities of some novel derivatives of the BT moiety are presented in this report.

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