Multicultural personality traits of Chinese university students and their effects on the psychological adjustment in the aftermath of COVID-19 in Shanghai: a scale validation.

Objective: This study aims to explore Chinese university students' multicultural personalities and examine how they predict the psychological adjustment of students in Shanghai. In addition, the validation of Multicultural Personality Questionnaire Short Form (MPQ-SF) scale developed to assess the multicultural personality traits of individuals is also aimed in Chinese context. Data were collected after the psychological stresses from restrictions imposed by COVID-19 in China that influenced life adjustments for nearly three years. Method: A total of 1,099 university students participated in this multi-stage study. First, the Chinese version of MPQ-SF (MPQ-SF-C) was developed and validated. The impact of MPQ-SF-C dimensions was then tested through path analysis to establish the effects of Chinese university students' multicultural personality traits on their psychological adjustment using the Schwartz Outcome Scale (SOS-10). Results: The MPQ-SF-C yielded a five-factor solution which accounted for 60.14% of the common variance. The findings indicated that cultural empathy (ß = 0.23, p < 0.05), certainty seeking (ß = 0.13, p < 0.05), open-mindedness (ß = 0.48, p < 0.05), and emotional stability (ß = 0.24, p < 0.05) had significant influences on adjustment. Only flexibility was found to have a statistically insignificant impact on adjustment at this time in this context. MPQ-SF-C and SOS-10 scales represented very good psychometric properties in terms of their reliability and validity. Conclusion: The MPQ-SF-C shows good psychometric properties and appropriateness for evaluating multicultural personalities in Chinese contexts. The multicultural personality characteristics of university students using this scale well predicted their psychological adjustment.

Analyzing the dynamical sensitivity and soliton solutions of time-fractional Schrödinger model with Beta derivative.

In physical domains, Beta derivatives are necessary to comprehend wave propagation across various nonlinear models. In this research work, the modified Sardar sub-equation approach is employed to find the soliton solutions of (1+1)-dimensional time-fractional coupled nonlinear Schrödinger model with Beta fractional derivative. These models are fundamental in real-world applications such as control systems, processing of signals, and fiber optic networks. By using this strategy, we are able to obtain various unique optical solutions, including combo, dark, bright, periodic, singular, and rational wave solutions. In addition, We address the sensitivity analysis of the proposed model to investigate the truth that it is extremely sensitive. These studies are novel and have not been performed before in relation to the nonlinear dynamic features of these solutions. We show these behaviors in 2-D, contour 3-D structures across the associated physical characteristics. Our results demonstrate that the proposed approach offers useful results for producing solutions of nonlinear fractional models in application of mathematics and wave propagation in fiber optics.

Analytical solution of fuzzy heat problem in two-dimensional case under Caputo-type fractional derivative.

This work aims to investigate the analytical solution of a two-dimensional fuzzy fractional-ordered heat equation that includes an external diffusion source factor. We develop the Sawi homotopy perturbation transform scheme (SHPTS) by merging the Sawi transform and the homotopy perturbation scheme. The fractional derivatives are examined in Caputo sense. The novelty and innovation of this study originate from the fact that this technique has never been tested for two-dimensional fuzzy fractional ordered heat problems. We presented two distinguished examples to validate our scheme, and the solutions are in fuzzy form. We also exhibit contour and surface plots for the lower and upper bound solutions of two-dimensional fuzzy fractional-ordered heat problems. The results show that this approach works quite well for resolving fuzzy fractional situations.

Quality and antioxidant potential of goat's milk paneer prepared from different citrus juices and its whey.

The experiments reported in this research paper aimed to evaluate the physico-chemical and sensory characteristics, microbial quality and antioxidant potential of goat's milk paneer during storage (0-12 d, 4 ± 1°C). The juices from five different citrus fruits were used as coagulant (treatments) to make goat's milk paneer. The pH of all paneer samples decreased during storage whereas titratable acidity increased. Ash (%) fat (%) and protein (%) of paneer increased slightly during storage, whereas sensory perception decreased. The juices from all the citrus fruit varieties showed high contents of total phenolics and total flavonoids which ultimately influenced ferric reducing antioxidant power, total antioxidant capacity and radical scavenging activities. As the contents of different juices were also retained in the paneer matrix, so paneer coagulated with citrus juices also showed encouraging results in terms of total phenolic and flavonoid contents, ferric reducing antioxidant power and radical scavenging activities. Amongst all the paneers, the most promising was that coagulated by kinnow juice. In addition, the whey obtained from paneer coagulated by citrus juices also showed appreciable quantities of total phenolic and flavonoid contents, thereby beneficially influencing ferric reducing antioxidant power andradical scavenging activities. It is concluded that citrus juices improve the sensorial quality and antioxidant potential of goat's milk paneer and its whey.

Topological Insights into Nanostar Dendrimers by Computing the Augmented Zagreb Index.

BACKGROUND: The field of nanobiotechnology uses precise nanofabrication techniques to advance our understanding and control of biological systems. Due to their remarkable properties, dendrimers, which are hyperbranched macromolecular structures with distinct and well-defined architectures, have emerged as pivotal entities within this field. They are gaining increasing attention for their potential to catalyze a paradigm shift in medical therapeutics, biotechnological applications, and advanced material sciences. OBJECTIVE: This paper focuses on a novel analytical expression and determines the precise value of the augmented Zagreb index, a topological descriptor, for eight classes of nanostar dendrimers. METHODS: The Zagreb index is a topological invariant to predict molecular behaviour and reactivity. In this paper, we have explored its application in characterizing the branching of nanostar dendrimers through computational modelling and mathematical rigor. RESULTS: Our research has measured the augmented Zagreb index for nanostar dendrimers, which fall into eight distinct classes. The results better explain the relationship between the dendrimers' topology and chemical properties. This correlation has implications for their structural stability and reactivity, potentially leading to new applications. CONCLUSION: Developing the augmented Zagreb index for nanostar dendrimers is a significant breakthrough in nanobiotechnology. Based on the correlation between the calculated topological index and the corresponding molecular attributes, our analytical approach has opened up new possibilities for designing and synthesizing dendrimers tailored to specific functions in medical and material science applications. This precise topological quantification could significantly enhance the utility and functionalization of dendrimers in cutting-edge nanotechnological applications.

Co-exposure to tire wear particles and nickel inhibits mung bean yield by reducing nutrient uptake.

Soil and terrestrial contamination with microplastics and nanoplastics has been discussed extensively, while tire wear particles (TWPs) have been largely overlooked. We investigated the root-surface interactions and growth response of mung bean (Vigna radiata L.) plants exposed to tire wear particles (TWPs) (0.05, 0.1, and 0.25% w/w) and nickel sulfate (50 and 100 mg kg-1 NiSO4) alone and in co-exposure scenarios for the full life cycle (105 days) under soil conditions. The results show that TWPs adhered to the root surface and reduced the water and nutrient uptake by the plant, particularly at higher concentrations of TWPs (0.25% w/w), without any observed organic contaminant accumulation in the root tissue. TWPs alone at 0.01, 0.1, and 0.25% (w/w) decreased mung bean yield by 11, 28, and 52%, respectively. Co-exposure to TWPs at 0.01, 0.1 and 0.25% w/w with 100 mg kg-1 NiSO4 decreased yield by 73, 79 and 88%, respectively. However, co-exposure to TWPs at 0.01 and 0.1% w/w with 50 mg kg-1 NiSO4 enhanced the yield by 32% and 7%, respectively. These changes in yield and nutritional aspects appear to be linked to Ni's regulatory influence on mineral homeostasis. Moreover, exposure to NiSO4 at 100 mg kg-1 increased Ni uptake in the root, shoot, and grain by 9, 26, and 20-fold, respectively as compared to the unamended control; this corresponded to increased antioxidant enzyme activity (10-127%) as compared to the control. TWPs caused blockages, significantly reducing plant yield and altering nutrient dynamics, highlighting emerging risks to plant health.

High performance electrochemical CO2 reduction over Pd decorated cobalt containing nitrogen doped carbon.

Efficient electrocatalytic CO2 reduction reaction (eCO2RR) to various products, such as carbon monoxide (CO), is crucial for mitigating greenhouse gas emissions and enabling renewable energy storage. In this article, we introduce Pd nanoparticles which are deposited over in-house synthesized nitrogen doped tubular carbon (NC) whose ends are blocked with cobalt oxide (CoOx). This composite material is denoted as Pd@CoOx/NC. Among the series of synthesized electrocatalysts, the optimum ratio (Pd@CoOx/NC1) within this category exhibits exceptional performance, manifesting an 81% faradaic efficiency (FE) for CO generation which was quantitatively measured using a gas chromatograph. This remarkable efficiency can be attributed to several scientific factors. Firstly, the presence of Pd nanoparticles provides active sites for CO2 reduction. Secondly, the NC offer enhanced electrical conductivity and facilitate charge transfer during the reaction. Thirdly, the CoOx capping at the ends of the NC serves to stabilize the catalyst, favoring the formation of CO. The remarkable selectivity of the catalyst is further confirmed by the qualitative CO detection method using PdCl2 strips. Pd@CoOx/NC1 exhibits a high current density of 55 mA cm-2 and a low overpotential of 251 mV, outperforming Pd decorated multiwalled carbon nanotubes (Pd@MWCNTs) which shows a higher overpotential of 481 mV. Pd@CoOx/NC1 shows long-term stability at different potentials and rapid reaction kinetics. These findings highlight Pd@CoOx/NC1 as promising CO2 reduction catalysts, with implications for sustainable energy conversion techniques.

The dynamical perspective of soliton solutions, bifurcation, chaotic and sensitivity analysis to the (3+1)-dimensional Boussinesq model.

In this study, we examine multiple perspectives on soliton solutions to the (3+1)-dimensional Boussinesq model by applying the unified Riccati equation expansion (UREE) approach. The Boussinesq model examines wave propagation in shallow water, which is derived from the fluid dynamics of a dynamical system. The UREE approach allows us to derive a range of distinct solutions, such as single, periodic, dark, and rational wave solutions. Furthermore, we present the bifurcation, chaotic, and sensitivity analysis of the proposed model. We use planar dynamical system theory to analyze the structure and characteristics of the system's phase portraits. The current study depends on a dynamic structure that has novel and unexplored results for this model. In addition, we display the behaviors of associated physical models in 3-dimensional, density, and 2-dimensional graphical structures. Our findings demonstrate that the UREE technique is a valuable mathematical tool in engineering and applied mathematics for studying wave propagation in nonlinear evolution equations.

Molecular identification of different toxinogenic strains of Clostridium perfringens and histo-pathological observations of camels died of per-acute entero-toxaemia.

Enterotoxaemia is a severe disease caused by Clostridium perfringens and render high mortality and huge economic losses in livestock. However, scanty information and only few cases are reported about the presence and patho-physiology of enterotoxaemia in camels. The bacterium induces per-acute death in animals due to rapid production of different lethal toxins. The necropsy of camels (per-acute = 15, acute = 3) was conducted at 18 outbreaks of enterotoxaemia in camels in the desert area of Bahawalpur region. At necropsy, the serosal surfaces of visceral organs in the abdominal, peritoneal and thoracic cavities were found to have petechiation with severe congestion. Moreover, both the cut-sections of different visceral organs and the histo-pathological analysis revealed the pathological lesions in heart, lungs, kidneys, spleen, small and large intestines. Grossly, the kidneys were severely congested, hyperemic, swollen and softer in consistency. Under the microscope, different sections of kidneys indicated that the convulated and straight tubules were studded with erythrocytes. In the intestines, there were stunting fusion of crypts and villi. Similarly, various histo-pathological ailments were also observed in the heart, lungs and spleen. At blood agar, the collected samples showed beta hemolytic colonies of C. perfringens that appeared as medium sized rods microscopically and stained positively on Gram staining. Multiplex PCR revealed C. perfringens type A (α and ß2 genes) and D (epsilon gene) and the deaths were found to be significantly higher due to C. perfringens type D compared to those by C. perfringens type A. Hence, it has been concluded that enterotoxaemia in camel affects multiple organs and becomes fatal, if occurred due to C. perfringens type D.

Vulnerability detection in Java source code using a quantum convolutional neural network with self-attentive pooling, deep sequence, and graph-based hybrid feature extraction.

Software vulnerabilities pose a significant threat to system security, necessitating effective automatic detection methods. Current techniques face challenges such as dependency issues, language bias, and coarse detection granularity. This study presents a novel deep learning-based vulnerability detection system for Java code. Leveraging hybrid feature extraction through graph and sequence-based techniques enhances semantic and syntactic understanding. The system utilizes control flow graphs (CFG), abstract syntax trees (AST), program dependencies (PD), and greedy longest-match first vectorization for graph representation. A hybrid neural network (GCN-RFEMLP) and the pre-trained CodeBERT model extract features, feeding them into a quantum convolutional neural network with self-attentive pooling. The system addresses issues like long-term information dependency and coarse detection granularity, employing intermediate code representation and inter-procedural slice code. To mitigate language bias, a benchmark software assurance reference dataset is employed. Evaluations demonstrate the system's superiority, achieving 99.2% accuracy in detecting vulnerabilities, outperforming benchmark methods. The proposed approach comprehensively addresses vulnerabilities, including improper input validation, missing authorizations, buffer overflow, cross-site scripting, and SQL injection attacks listed by common weakness enumeration (CWE).

Predicting current and future habitat of Indian pangolin (Manis crassicaudata) under climate change.

Climate change is among the greatest drivers of biodiversity loss, threatening up to 15-30% of described species by the end of the twenty-first century. We estimated the current suitable habitat and forecasted future distribution ranges of Indian pangolin (Manis crassicaudata) under climate change scenarios. We collected occurrence records of Indian pangolin using burrow counts, remote camera records and previously published literature in Pakistan during 2021-2023. We downloaded bioclimatic data for current (1970-2000) and future (2041-2060, 2061-2080, 2081-2100) climate scenarios from the WorldClim database using the Hadley Global Environment Model (HadGEM3-GC31-LL). We used MaxEnt software to predict current and future distributions of Indian pangolin, then computed the amount of habitat lost, gained, and unchanged across periods. We obtained 560 Indian pangolin occurrences overall, 175 during the study, and 385 from our literature search. Model accuracy was very good (AUC = 0.885, TSS = 0.695), and jackknife tests of variable importance showed that the contribution of annual mean temperature (bio1) was greatest (33.4%), followed by the mean temperature of the coldest quarter (bio-12, 29.3%), temperature seasonality (bio 4, 25.9%), and precipitation seasonality (bio 15, 11.5%). The maxent model predicted that during the current time period (1970-2000) highly suitable habitat for Indian pangolin was (7270 km2, 2.2%), followed by moderately suitable (12,418 km2, 3.7%), less suitable (49,846 km2, 14.8%), and unsuitable habitat (268,355 km2, 79.4%). Highly suitable habitat decreased in the western part of the study area under most SSPs and in the central parts it declined under all SSPs and in future time periods. The predicted loss in the suitable habitat of the Indian pangolin was greatest (26.97%) under SSP 585 followed by SSP 126 (23.67%) during the time 2061-2080. The gain in suitable habitat of Indian pangolin was less than that of losses on average which ranged between 1.91 and 13.11% under all SSPs during all time periods. While the stable habitat of the Indian pangolin ranged between 64.60 and 83.85% under all SSPs during all time periods. Our study provides the current and future habitat ranges of Indian pangolin in the face of a changing climate. The findings of our study could be helpful for policymakers to set up conservation strategies for Indian pangolin in Pakistan.

Artificial intelligence models for validating and predicting the impact of chemical priming of hydrogen peroxide (H2O2) and light emitting diodes on in vitro grown industrial hemp (Cannabis sativa L.).

Industrial hemp (Cannabis sativa L.) is a highly recalcitrant plant under in vitro conditions that can be overcome by employing external stimuli. Hemp seeds were primed with 2.0-3.0% hydrogen peroxide (H2O2) followed by culture under different Light Emitting Diodes (LEDs) sources. Priming seeds with 2.0% yielded relatively high germination rate, growth, and other biochemical and enzymatic activities. The LED lights exerted a variable impact on Cannabis germination and enzymatic activities. Similarly, variable responses were observed for H2O2 × Blue-LEDs combination. The results were also analyzed by multiple regression analysis, followed by an investigation of the impact of both factors by Pareto chart and normal plots. The results were optimized by contour and surface plots for all parameters. Response surface optimizer optimized 2.0% H2O2 × 918 LUX LEDs for maximum scores of all output parameters. The results were predicted by employing Multilayer Perceptron (MLP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Moreover, the validity of these models was assessed by using six different performance metrics. MLP performed better than RF and XGBoost models, considering all six-performance metrics. Despite the differences in scores, the performance indicators for all examined models were quite close to each other. It can easily be concluded that all three models are capable of predicting and validating data for cannabis seeds primed with H2O2 and grown under different LED lights.

Cryptic footprint of thallium in soil-plant systems; A review.

The current review highlights the complex behavior of thallium (Tl) in soil and plant systems, offering insight into its hazardous characteristics and far-reaching implications. The research investigates the many sources of Tl, from its natural existence in the earth crust to its increased release through anthropogenic activities such as industrial operations and mining. Soil emerges as a significant reservoir of Tl, with diverse physicochemical variables influencing bioavailability and entrance into the food chain, notably in Brassicaceae family members. Additionally, the study highlights a critical knowledge gap concerning Tl influence on legumes (e.g., soybean), underlining the pressing demand for additional studies in this crucial sector. Despite the importance of leguminous crops in the world food supply and soil fertility, the possible impacts of Tl on these crops have received little attention. As we traverse the ecological complexity of Tl, this review advocates the collaborative research efforts to eliminate crucial gaps and provide solutions for reducing Tl detrimental impacts on soil and plant systems. This effort intends to pave the path for sustainable agricultural practices by emphasizing the creation of Tl-tolerant legume varieties and revealing the complicated dynamics of Tl-plant interactions, assuring the long-term durability of our food systems against the danger of Tl toxicity.

Consanguineous Marriages and the Perception of Wife-Beating Justification in Pakistan: An Application of Fairlie Decomposition Analysis.

Pakistan has a significant occurrence of both consanguineous marriages and intimate partner violence (IPV), which may be interlinked. The practice of consanguineous marriages could potentially influence women to rationalize and accept instances of IPV. Such attitudes perpetuate a culture of violence against women, creating difficulties for victims to reject or escape from it. Pakistan has high prevalence rate of consanguineous marriages and IPV. However, no research has been done to explain the difference in acceptance of IPV between women in consanguineous and non-consanguineous marriages. This study used Pakistan Demographic and Health Survey data and applied association tests, logistic regression, and the Fairlie decomposition analysis. The Fairlie decomposition helps us identify the relative contribution of different socioeconomic factors in the inequalities in IPV between the two types of marriages. Five dimensions of wife-beating justification are used as outcome variables. Age, education, and empowerment of women, husband education, woman witness parental violence, region, place of residence, and household wealth status are used as independent variables. The logistic regression results indicated that women in consanguineous marriages of younger age and who witnessed parental violence are more likely to justify wife-beating than those who belong to wealthy households and enjoy more empowerment. Compared to the Punjab province, women residing in Sindh and Baluchistan are less likely and in the Khyber Pakhtunkhwa province are more likely to justify wife-beating. The Fairlie decomposition analysis shows that household wealth status, woman education, and empowerment are the main contributors in explaining the gap between the wife-beating justification of the two groups. The IPV gap can be reduced up to 77% if the distribution of women in different wealth quantiles of the consanguineous marriage group is identical to the non-consanguineous marriage group. Furthermore, woman education level is the second highest contributor. Consanguineous marriages are a prevalent cultural practice in Pakistan and are associated with several negative health and social outcomes. Addressing this issue requires a sustained and comprehensive effort by the government, civil society, and international partners, with a particular focus on women from poor households with less education.

Boosted charge separation via Ce2S3 over dual Z-scheme ZnO-Ce2S3-MnO2 core double-shell nanocomposite for the degradation of diverse dye pollutants.

Herein, core double-shell direct dual Z-scheme ZnO-Ce2S3-MnO2 nanocomposite was synthesized via a hydrothermal route along with pure ZnO, Ce2S3, MnO2, and characterized by numerous characterization tools for application in synthetic dyes degradation. The XRD, Raman, and FTIR analyses have confirmed the nanocomposite formation. TEM images exhibited the core double-shell morphology with an average particle diameter of 81 nm and stacking of ZnO, Ce2S3, and MnO2. EDX confirmed the existence of desired elements in the grown composition. The varied oxidation states, presence of defects, and fast charge transfer were also revealed from XPS, PL, and EIS. The ZnO-Ce2S3-MnO2 nanocomposite has an optical energy bandgap of 2.84 eV, capable of decomposing harmful dyes with excellent efficiency, 99.81% MB, 97.62% MO, 88.5% MR, and 58.9% EY in 40 min sunlight exposure. The effect of several operating parameters is also observed and obtained results showed the optimal catalyst dose was 20 mg, pH of 8, and dye concentration of 10 ppm. The scavenger's experiment suggests that •O2- and •OH are the main active radicals in the photodegradation reaction which is also evident in the dual Z-scheme formation. The MnO2 and ZnO layers covered the Ce2S3 (core) and dual Z-scheme formation allows rapid kinetics of redox reaction and provides plenteous channels for transfer of photo-generated charge carriers during photocatalysis. Thus, core double-shell direct dual Z-scheme photocatalysts having inorganic components could be an excellent choice for photocatalysis at the industrial level, particularly for water purification.

Hybrid Rice Production: A Worldwide Review of Floral Traits and Breeding Technology, with Special Emphasis on China.

Rice is an important diet source for the majority of the world's population, and meeting the growing need for rice requires significant improvements at the production level. Hybrid rice production has been a significant breakthrough in this regard, and the floral traits play a major role in the development of hybrid rice. In grass species, rice has structural units called florets and spikelets and contains different floret organs such as lemma, palea, style length, anther, and stigma exsertion. These floral organs are crucial in enhancing rice production and uplifting rice cultivation at a broader level. Recent advances in breeding techniques also provide knowledge about different floral organs and how they can be improved by using biotechnological techniques for better production of rice. The rice flower holds immense significance and is the primary focal point for researchers working on rice molecular biology. Furthermore, the unique genetics of rice play a significant role in maintaining its floral structure. However, to improve rice varieties further, we need to identify the genomic regions through mapping of QTLs (quantitative trait loci) or by using GWAS (genome-wide association studies) and their validation should be performed by developing user-friendly molecular markers, such as Kompetitive allele-specific PCR (KASP). This review outlines the role of different floral traits and the benefits of using modern biotechnological approaches to improve hybrid rice production. It focuses on how floral traits are interrelated and their possible contribution to hybrid rice production to satisfy future rice demand. We discuss the significance of different floral traits, techniques, and breeding approaches in hybrid rice production. We provide a historical perspective of hybrid rice production and its current status and outline the challenges and opportunities in this field.

Impact of construction parameters on ergonomic and thermo-physiological comfort performance of knitted occupational compression stocking materials.

This work investigates the effect of varying the knitting structure and stitch length (SL) on various thermo-physiological and ergonomic comfort properties of the occupational graduated compression socks. Thermo-physiological comfort, ergonomic comfort and dimensional stability of theses stockings were analysed in a comparative manner. Obtained results were evaluated statistically using the technique of analysis of variance (ANOVA). A Fisher's multiple comparison test was commissioned to analyze the relationship between the alteration of stitch length (SL) on various utility functions and properties desired in the occupational compression socks. In order to examine whether the difference of stitch length is significant, p values were determined. Further the influence of knitting structures e.g., plain, 2 × 2 Rib and 1 × 3 Rib was analysed on the selected properties. The interactive effect of both stitch length (SL) and knitting structure was studied using statistical techniques. It was concluded that knitting structure has a stronger impact on thermo-physiological and ergonomic comfort properties. Results showed a significant variation in thermo-physiological and ergonomic comfort by altering stitch length by means of the statistical analysis. An innovative approach for the manufacturers has been developed for optimizing performance in compression stockings. The construction of the compression socks can thus be optimized in terms of constructional parameters to provide optimum comfort to the users.

Study of multi-dimensional problems arising in wave propagation using a hybrid scheme.

Many scientific phenomena are linked to wave problems. This paper presents an effective and suitable technique for generating approximation solutions to multi-dimensional problems associated with wave propagation. We adopt a new iterative strategy to reduce the numerical work with minimum time efficiency compared to existing techniques such as the variational iteration method (VIM) and homotopy analysis method (HAM) have some limitations and constraints within the development of recurrence relation. To overcome this drawback, we present a Sawi integral transform ( S T) for constructing a suitable recurrence relation. This recurrence relation is solved to determine the coefficients of the homotopy perturbation strategy (HPS) that leads to the convergence series of the precise solution. This strategy derives the results in algebraic form that are independent of any discretization. To demonstrate the performance of this scheme, several mathematical frameworks and visual depictions are shown.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets.

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Fabrication of an affordable and sensitive corticosteroid-binding globulin immunosensor based on electrodeposited gold nanoparticles modified glassy carbon electrode.

Herein, we fabricated an ultrasensitive electrochemical immunosensor for the quantitative detection of corticosteroid-binding globulin (CBG). CBG is a protein that regulates glucocorticoid levels and is an important biomarker for inflammation. A decrease in CBG levels is a key biomarker for inflammatory diseases, such as septic shock. To enhance the electrochemical performance and provide a large surface area for anti-CBG immobilization, we functionalized the glassy carbon electrode surface with AuNPs. Electrochemical characterization methods including cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to examine the construction of the fabricated immunosensor. The electrochemical signal demonstrated a remarkable sensitivity to the CBG antigen, with a detection range from 0.01 to 100 µg/mL and a limit of detection of 0.012 µg/mL, making it suitable for both clinical and research applications. This label-free immunosensor offers significant advantages, including high sensitivity, low detection limits and excellent selectivity, making it a promising tool for detecting CBG in complex biological samples. Its potential applications include early disease diagnosis, treatment monitoring and studying CBG-related physiological processes.