Effect of nanoparticle macroalgae in the treatment of fatty liver disease using logistic regression, and support vector machine.

One of the major health issues facing people worldwide is liver fibrosis. Liver fibrosis may be brought on by long-term exposure to harmful substances, medicines, and microorganisms. The development of liver fibrosis in children was particularly worrying due to their longer life-span, which was possibly related to a great risk of developing long-term complications. Marine algae species have provided a biological variety in the research phase of novel approaches to the treatment of numerous ailments. Marine macroalgae have recently been the subject of research due to their rich bioactive chemical composition and potential for the production of various nutraceuticals. Macroalgae are potentially excellent sources of bioactive substances with particular and distinct biological activity when compared to their terrestrial equivalents. Macroalgae in diverse marine cases offer a few biologically active metabolites, comprising sterols, polyunsaturated fatty acids, carotenoids, oligosaccharides, polysaccharides, proteins, polyphenols, vitamins, and minerals. Accordingly, there is great interest in their high potential for supporting immunomodulatory, antimicrobial, antidiabetic, antitumoral, anti-inflammatory, antiangiogenic, and neuroprotective properties. Using an experimental model, the current research intends to collect data on the therapeutic value of macroalgae nanoparticles for fatty liver disease. The researchers' goal of predicting illnesses from the extensive medical datasets is quite difficult. The purpose of this research is to assess the protective effects of a seaweed, Padina pavonia (PP), on liver fibrosis caused by carbon tetrachloride (CCl4). This research presents two models of logistic regression (LR) and support vector machines (SVM) for predicting the likelihood of liver disease incidence. The performance of the model was evaluated using a dataset. PP macro-algae considerably reduce the high blood concentrations of aminotransferases, alkaline phosphatases, and lactate dehydrogenases, as well as causing a considerable (p < 0.05) decrease in serum bilirubin levels. In addition to improving kidney function (urea and creatinine), algal extracts enhance fat metabolism (triglycerides and cholesterol). With an accuracy rate of 70.2%, a sensitivity of 92.3%, a specificity of 74.7%, a type I error of 9.1%, and a type II error of 21.0%, the predictive model has demonstrated excellent performance. The model validated laboratory tests' ability to predict illness (age; direct bilirubin (DB), total proteins (TP), and albumin (ALB). These classifier methods are compared on the basis of their execution time and classification accuracy.

Application of aluminum oxide nanoparticles in asphalt cement toward non-polluted green environment using linear regression.

In order to decrease the greenhouse gas emissions generated by regular Portland cement (OPC), additional cementitious ingredients have been frequently employed, even while building road bases. OPC's susceptibility to moisture and lack of flexibility make it ineffective for stabilizing road bases. This research used alkali-activated materials (AAM) with fly ash to investigate the mechanical properties of cold asphalt binder (freeze-thaw cycles) including the compressive, flexural strength, workability and porosity of cement. Dry specimens and specimens in distilled water have both been used in the experiments to study these temperature correlations. One sample was tested at 20 °C, and the other was frozen and thawed five times at a temperature of -5 °C (cold region environment). The resulting mixtures' morphologies and microstructures were analyzed via SEM images. During the 7 to 28-day curing period, the mixture's growth ratio rose. The combination registered both the greatest and lowest robust elastic modulus. The total compressive strength of the material decreased as the water-to-cement ratio increased due to the greater amount of free water accessible with a higher cationic asphalt emulsion (CAE) content. The moderate loss of flexural strength with increasing CAE concentration after 7 and 28 days of curing was seen. There is not a major impact on flexural strength in the materials by looking at the very modest gaps in flexural strength between 7 and 28 days curing periods. Due to the particle shape and size of this precursor, FA's inclusion allowed for a lower water to binder rate while maintaining a similar level of workability. The porosity and water absorption values rose with FA substitutions. Further studies might clarify the lower flexural strength observed in this study by adding other hybrids plus fly ash such as lime or nanoparticles.

Enhanced artificial intelligence for electrochemical sensors in monitoring and removing of azo dyes and food colorant substances.

It is necessary to determine whether synthetic dyes are present in food since their excessive use has detrimental effects on human health. For the simultaneous assessment of tartrazine and Patent Blue V, a novel electrochemical sensing platform was developed. As a result, two artificial azo colorants (Tartrazine and Patent Blue V) with toxic azo groups (-NN-) and other carcinogenic aromatic ring structures were examined. With a low limit of detection of 0.06 µM, a broad linear concentration range 0.09µM to 950µM, and a respectable recovery, scanning electron microscopy (SEM) was able to reveal the excellent sensing performance of the suggested electrode for patent blue V. The electrochemical performance of an electrode can be characterized using cyclic and differential pulse voltammetry, and electrochemical impedance spectroscopy. Moreover, the classification model was created by applying binary classification assessment using enhanced artificial intelligence comprises of support vector machine (SVM) and Genetic Algorithm (GA), respectively, a support vector machine and a genetic algorithm, which was then validated using the 50 dyes test set. The best binary logistic regression model has an accuracy of 83.2% and 81.1%, respectively, while the best SVM model has an accuracy of 90.3% for the training group of samples and 81.1% for the test group (RMSE = 0.644, R2 = 0.873, C = 205.41, and = 5.992). According to the findings, Cu-BTC MOF (copper (II)-benzene-1,3,5-tricarboxylate) has a crystal structure and is tightly packed with hierarchically porous nanomaterials, with each particle's edge measuring between 20 and 37 nm. The suggested electrochemical sensor's analytical performance is suitable for foods like jellies, condiments, soft drinks and candies.

Risk assessment of organophosphorus pesticide residues in drinking water resources: Statistical and Monte-Carlo approach.

A large part of the world's agricultural production, despite its adverse effects on human health and water resources, depends on the use of pesticides. Despite strict regulations, the use of pesticides continues around the world. This study aimed to determine the residual concentrations of malathion and diazinon in samples of drinking water resources. To achieve this goal, 384 samples from 8 various sites from January to December 2020 were analyzed using gas chromatography (GC) with an electron capture detector (ECD) and liquid-liquid extraction technique. Besides, statistical analysis and a risk-modeling approach supported by an automatic Monte-Carlo procedure were applied. The results showed that there is a high carcinogenic risk regarding malathion and that the low age population is at the most non-carcinogenic risk regarding diazinon.

Electrochemical monitoring sensors of water pollution systems.

Analytical techniques as strong, precise, and expensive are necessary for monitoring food and water safety for contaminants, microorganisms, and allergies that might be harmful if used. Sudan dyes are commonly utilized as an ingredient in food dye substances and a variety of industrial items. These colors are classified as three carcinogens and are linked to liver and bladder cancers. They are not authorized for human consumption by the International Agency for Research on Cancer (IARC) and are not permitted to be used by the Food Standards Agency or the European Union. This article describes electrochemical dye analysis beside the numerous electrochemical sensors utilized to identify these dyes as a food colorant and water. As a result, the qualities, chemistry, and toxicity of dyes as food colorants and industrial goods in Sudan have been investigated in this study. Sudan dyes have been thoroughly studied, and many electrochemical sensors have been developed to define and monitor these dyes in food colorants. As a result, current electrochemical sensors have been found to be neither mass-production nor cost-effective. Mostly, the synthesis of high-performance materials needs high knowledge, and the production of electrode surfaces is remained difficult due to labor-intensive and time-consuming activities.

Investigation of the interaction mechanism of 3-allyl-2-hydantoin anti-cancer on the pristine and functionalized BC2N nanotubes as an effective drug delivery nanocarriers.

One of the exciting aspects of different nanomaterials in biomedical applications is the delivery of a wide range of anti-cancer drugs to mitigate their negative side effects via precise targeting of the tumor cells. In the present study, the DFT B3LYP/6-31G (d, p) level of theory was used to evaluate the capabilities of raw BC2N nanotubes (BC2NNTs) and functionalized BC2NNTs nanostructures as a carrier for an anti-cancer drug (i.e., 3-allyl-2-hydantoin (3-ASH)). It was specified that the existing interaction between 3-ASH and BC2N nanotubes is weak (-10.97 kcal mol-1). Therefore, the functionalized BC2NNTs were investigated for 3-ASH interaction. According to our computations, compared with raw BC2NNTs, the role of hydrogen bonds between 3-ASH molecules' active sites and carboxyl-functionalized BC2NNTs in the complexes' fixation, adsorption, and thermodynamic energy is of great importance. A considerable transfer of charge between 3-ASH molecule to the functionalized BC2NNTs was detected via MEP, NBO, and fractional charge transfer analysis. Also, it was found that these nanostructures have high stability on the water medium while their solvation energies have negative values. This negative value is beneficial for the applications of 3-ASH drug delivery. The present work proposes a new method to load 3-ASH drugs with a high density on BC2NNTs' surfaces.