Application of green synthesized silver nanoparticles in Burn therapy: a review.

Silver nanoparticles (AgNPs), owing to their unusual characteristics, have been used in various pharmaceutical, cosmetic, and healthcare products. AgNPs, with their exceptional biological potential, exhibit antibacterial, antifungal, antiviral, anti-inflammatory, anticancer, and wound healing properties and have been extensively used in burn therapy. Several studies have established the use of silver nanoparticles in the treatment of burn injuries, resulting in reduced inflammation, quick tissue regeneration, and the remarkable creation of collagen fibers. Conventional physical and chemical techniques have synthesized AgNPs, but they appear to be highly costly and hazardous. Recently, there has been considerable interest in the synthesis of AgNPs using the green chemistry approach because of its tremendous benefits, including being non-toxic, low energy consumption, pollution-free, economical, environmentally friendly, and more sustainable. This review emphasizes the green synthesis of AgNPs using bacteria, fungi, plants, and other microorganisms and the current research related to the application of green synthesized AgNPs in burn therapy, including the biological aspects of AgNPs, their mode of action, and any possible detrimental effects.

A new label free spiral sensor using impedance spectroscopy to characterize hepatocellular carcinoma in tissue and serum samples.

Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer, predominantly affecting patients with chronic liver diseases such as hepatitis B or C-induced cirrhosis. Diagnosis typically involves blood tests (assessing liver functions and HCC biomarkers), imaging procedures such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and liver biopsies requiring the removal of liver tissue for laboratory analysis. However, these diagnostic methods either entail lengthy lab processes, require expensive imaging equipment, or involve invasive techniques like liver biopsies. Hence, there exists a crucial need for rapid, cost-effective, and noninvasive techniques to characterize HCC, whether in serum or tissue samples. In this study, we developed a spiral sensor implemented on a printed circuit board (PCB) technology that utilizes impedance spectroscopy and applied it to 24 tissues and sera samples as proof of concept. This newly devised circuit has successfully characterized HCC and normal tissue and serum samples. Utilizing the distinct dielectric properties between HCC cells and serum samples versus the normal samples across a specific frequency range, the differentiation between normal and HCC samples is achieved. Moreover, the sensor effectively characterizes two HCC grades and distinguishes cirrhotic/non-cirrhotic samples from tissue specimens. In addition, the sensor distinguishes cirrhotic/non-cirrhotic samples from serum specimens. This pioneering study introduces Electrical Impedance Spectroscopy (EIS) spiral sensor for diagnosing HCC and liver cirrhosis in clinical serum-an innovative, low-cost, rapid (< 2 min), and precise PCB-based technology without elaborate sample preparation, offering a novel non-labeled screening approach for disease staging and liver conditions.

Cross vision transformer with enhanced Growth Optimizer for breast cancer detection in IoMT environment.

The recent advances in artificial intelligence modern approaches can play vital roles in the Internet of Medical Things (IoMT). Automatic diagnosis is one of the most important topics in the IoMT, including cancer diagnosis. Breast cancer is one of the top causes of death among women. Accurate diagnosis and early detection of breast cancer can improve the survival rate of patients. Deep learning models have demonstrated outstanding potential in accurately detecting and diagnosing breast cancer. This paper proposes a novel technology for breast cancer detection using CrossViT as the deep learning model and an enhanced version of the Growth Optimizer algorithm (MGO) as the feature selection method. CrossVit is a hybrid deep learning model that combines the strengths of both convolutional neural networks (CNNs) and transformers. The MGO is a meta-heuristic algorithm that selects the most relevant features from a large pool of features to enhance the performance of the model. The developed approach was evaluated on three publicly available breast cancer datasets and achieved competitive performance compared to other state-of-the-art methods. The results show that the combination of CrossViT and the MGO can effectively identify the most informative features for breast cancer detection, potentially assisting clinicians in making accurate diagnoses and improving patient outcomes. The MGO algorithm improves accuracy by approximately 1.59% on INbreast, 5.00% on MIAS, and 0.79% on MiniDDSM compared to other methods on each respective dataset. The developed approach can also be utilized to improve the Quality of Service (QoS) in the healthcare system as a deployable IoT-based intelligent solution or a decision-making assistance service, enhancing the efficiency and precision of the diagnosis.

Understanding the awareness of antimicrobial resistance amongst commercial poultry farmers in northwestern Nigeria.

The emergence of antimicrobial resistance (AMR) in both humans and animals is a growing health threat worldwide. Significant quantities of antibiotics are used in the livestock production sector, particularly in poultry farming to enhance growth and productivity. A cross-sectional study was conducted in three states of northwestern Nigeria to understand the level of knowledge, attitude, and practice of commercial poultry farmers on antimicrobial resistance. A total of 247 poultry farmers enrolled in the study comprising 100 (40.5 %) from Sokoto, 68 from Kebbi (27.5 %) and 79 (32.0 %) from Zamfara States. A significant number of the farmers have good knowledge of antimicrobial use (94.74 %), and the potential emergence of antimicrobial resistant bacteria due to irrational administration of antibiotics (83.0 %). Kruskal-Wallis test showed a significant difference in farmers' knowledge of AMR based on their educational qualification (p < 0.001) as farmers with bachelor's degree (BSc) being more knowledgeable than those with Ordinary National Diploma (OND) and those who only completed primary or secondary education. A statistically significant difference was also observed in the attitude of the participants based on State (p < 0.001) and educational qualification (p = 0.013). The study provided valuable insight into the understanding of antimicrobial resistance amongst commercial poultry farmers in the region. The findings necessitate the need for educational interventions and initiatives through enlightenment campaigns and deployment of extension workers to reach farmers with low level of education to further improve their attitudes and practice towards responsible use of antibiotics.

Design, synthesis and bioactivity study on oxygen-heterocyclic-based pyran analogues as effective P-glycoprotein-mediated multidrug resistance in MCF-7/ADR cell.

P-glycoprotein (P-gp) imparts multi-drug resistance (MDR) on the cancers cell and malignant tumor clinical therapeutics. We report a class of newly designed and synthesized oxygen-heterocyclic-based pyran analogues (4a-l) bearing different aryl/hetaryl-substituted at the 1-postion were synthesized, aiming to impede the P-gp function. These compounds (4a-l) have been tested against cancerous PC-3, SKOV-3, HeLa, and MCF-7/ADR cell lines as well as non-cancerous HFL-1 and WI-38 cell lines to determine their anti-proliferative potency.The findings demonstrated the superior potency of 4a-c with 4-F, 2-Cl, and 3-Cl derivatives and 4h,g with 4-NO2, 4-MeO derivatives against PC-3, SKOV-3, HeLa, and MCF-7/ADR cell lines.Compounds 4a-c were tested for P-gp inhibition and demonstrated significant vigour against MCF-7/ADR cells with IC50 = 5.0-10.7 µM. The Rho123 accumulation assay showed that compounds 4a-c adequately inhibited P-gp function, as predicted. Furthermore, 4a or 4b administration resulted in MCF-7/ADR cell accumulation in the S phase, while compound 4c induced apoptosis by causing cell cycle arrest at G2/M. The molecular docking was applied to understand the likely modes of action and guide us in the rational design of more potent analogs. The investigate derivatives showed their good binding potential for p-gp active site with excellent docking scores and interactions. Finally, the majority of investigated derivatives 4a-c derivatives showed high oral bioavailability, but they did not cross the blood-brain barrier. These results suggest that they have favorable pharmacokinetic properties. Therefore, these compounds could serve as leads for designing more potent and stable drugs in the future.

Molecular characterization of Aeromonas hydrophila isolates from diseased fishes in district Kasur, Punjab, Pakistan

Abstract Pakistan is an agricultural country and fisheries play a very important role in the economic development of the country. Different diseases are prevalent in Pakistani fish but information related to the causative agents is not well-known. Keeping in view the significance of bacterial pathogens as the causative agents of multiple fish diseases, the present study was conducted for identification, characterization and analysis of virulence genes of Aeromonas spp. isolated from diseased fishes. A total of fifty fish samples having multiple clinical indications were collected from different fish farms of district Kasur, Punjab Pakistan. For isolation of Aeromonas spp. samples were enriched and inoculated on Aeromonas isolation medium. Isolates were identified and characterized by different biochemical tests, Analytical Profile Index (API) 20E kit and Polymerase Chain Reaction (PCR) assays. All isolates were screened for three putative virulence genes including aerolysin (aer), haemolysin (hyl) and heat labile cytotonic enterotoxin (alt). Seven isolates of Aeromonas (A.) hydrophila were retrieved and identified based on API 20E. These isolates were further confirmed as A. hydrophila on the basis of PCR assays. Three isolates were detected positive for the presence of virulence genes (alt and hyl). Whereas aerolysin (aer) gene was not present in any of A. hydrophila isolates. The present study confirmed A. hydrophila as the causative agent of epizootic ulcerative syndrome and motile Aeromonas septicemia in fish farms of district Kasur, Punjab Pakistan. Moreover, detection of two virulence genes (alt and hyl) in A. hydrophila isolates is a threat for fish consumers of study area.

Resumo O Paquistão é um país agrícola, onde a pesca desempenha um papel muito importante para o desenvolvimento econômico. Diferentes doenças são prevalentes em peixes do Paquistão, mas as informações relacionadas aos agentes causadores não são bem conhecidas. Tendo em vista a importância dos patógenos bacterianos como agentes causadores de múltiplas doenças em peixes, o presente estudo foi conduzido para identificação, caracterização e análise de genes de virulência de isolados de Aeromonas spp. de peixes doentes. Foram coletadas 50 amostras de peixes com múltiplas indicações clínicas em diferentes fazendas do distrito de Kasur, Punjab, Paquistão. Para isolar Aeromonas spp., as amostras foram enriquecidas e inoculadas em meio de isolamento. Os isolados foram identificados e caracterizados por diferentes testes bioquímicos, kit Analytical Profile Index (API) 20E, e ensaios de reação em cadeia da polimerase (PCR). Todos os isolados foram selecionados para três genes de virulência putativos, incluindo aerolisina (aer), hemolisina (hyl) e enterotoxina citotônica termolábil (alt). Sete isolados de Aeromonas hydrophila foram recuperados e identificados com base no API 20E. Esses isolados foram posteriormente confirmados como A. hydrophila de acordo com ensaios de PCR. Três isolados indicaram a presença de genes de virulência (alt e hyl), enquanto o gene aerolisina (aer) não esteve presente em nenhum dos isolados de A. hydrophila. O presente estudo confirmou A. hydrophila como o agente causador da síndrome ulcerativa epizoótica e septicemia móvel por Aeromonas em fazendas de peixes, no distrito de Kasur, Punjab, Paquistão. Além disso, a detecção de dois genes de virulência (alt e hyl) em isolados de A. hydrophila é uma ameaça para os consumidores de peixes da área de estudo.

Molecular characterization of Aeromonas hydrophila isolates from diseased fishes in district Kasur, Punjab, Pakistan / Caracterização molecular de isolados de Aeromonas hydrophila de peixes doentes no distrito de Kasur, Punjab, Paquistão

Abstract Pakistan is an agricultural country and fisheries play a very important role in the economic development of the country. Different diseases are prevalent in Pakistani fish but information related to the causative agents is not well-known. Keeping in view the significance of bacterial pathogens as the causative agents of multiple fish diseases, the present study was conducted for identification, characterization and analysis of virulence genes of Aeromonas spp. isolated from diseased fishes. A total of fifty fish samples having multiple clinical indications were collected from different fish farms of district Kasur, Punjab Pakistan. For isolation of Aeromonas spp. samples were enriched and inoculated on Aeromonas isolation medium. Isolates were identified and characterized by different biochemical tests, Analytical Profile Index (API) 20E kit and Polymerase Chain Reaction (PCR) assays. All isolates were screened for three putative virulence genes including aerolysin (aer), haemolysin (hyl) and heat labile cytotonic enterotoxin (alt). Seven isolates of Aeromonas (A.) hydrophila were retrieved and identified based on API 20E. These isolates were further confirmed as A. hydrophila on the basis of PCR assays. Three isolates were detected positive for the presence of virulence genes (alt and hyl). Whereas aerolysin (aer) gene was not present in any of A. hydrophila isolates. The present study confirmed A. hydrophila as the causative agent of epizootic ulcerative syndrome and motile Aeromonas septicemia in fish farms of district Kasur, Punjab Pakistan. Moreover, detection of two virulence genes (alt and hyl) in A. hydrophila isolates is a threat for fish consumers of study area.

Resumo O Paquistão é um país agrícola, onde a pesca desempenha um papel muito importante para o desenvolvimento econômico. Diferentes doenças são prevalentes em peixes do Paquistão, mas as informações relacionadas aos agentes causadores não são bem conhecidas. Tendo em vista a importância dos patógenos bacterianos como agentes causadores de múltiplas doenças em peixes, o presente estudo foi conduzido para identificação, caracterização e análise de genes de virulência de isolados de Aeromonas spp. de peixes doentes. Foram coletadas 50 amostras de peixes com múltiplas indicações clínicas em diferentes fazendas do distrito de Kasur, Punjab, Paquistão. Para isolar Aeromonas spp., as amostras foram enriquecidas e inoculadas em meio de isolamento. Os isolados foram identificados e caracterizados por diferentes testes bioquímicos, kit Analytical Profile Index (API) 20E, e ensaios de reação em cadeia da polimerase (PCR). Todos os isolados foram selecionados para três genes de virulência putativos, incluindo aerolisina (aer), hemolisina (hyl) e enterotoxina citotônica termolábil (alt). Sete isolados de Aeromonas hydrophila foram recuperados e identificados com base no API 20E. Esses isolados foram posteriormente confirmados como A. hydrophila de acordo com ensaios de PCR. Três isolados indicaram a presença de genes de virulência (alt e hyl), enquanto o gene aerolisina (aer) não esteve presente em nenhum dos isolados de A. hydrophila. O presente estudo confirmou A. hydrophila como o agente causador da síndrome ulcerativa epizoótica e septicemia móvel por Aeromonas em fazendas de peixes, no distrito de Kasur, Punjab, Paquistão. Além disso, a detecção de dois genes de virulência (alt e hyl) em isolados de A. hydrophila é uma ameaça para os consumidores de peixes da área de estudo.

Investigating the Chemical Composition of Lepidium sativum Seeds and Their Ability to Safeguard against Monosodium Glutamate-Induced Hepatic Dysfunction.

Monosodium glutamate (MSG) is one of the most frequently used food additives that endanger public health. The antioxidant, hyperlipidemic, and cytoprotective properties of Lepidium sativum seeds (LSS) as a natural remedy can minimize the harmful effects of MSG. This study investigated the potential protective effect of LSS against MSG-induced hepatotoxicity in rats. Male albino Sprague Dawley rats (n = 24) were equally divided into four groups for 30 days: the control group (G1) received a basal diet without supplement, group (G2) was fed a basal diet + MSG (30 g/kg b.w.) as a model group, group (G3) was fed a basal diet + MSG (30 g/kg b.w.) + LSS (30 g/kg b.w.), and group (G4) was fed a basal diet + MSG (30 g/kg b.w.) + LSS (60 g/kg b.w.). LSS enhanced serum alkaline phosphatase activity as well as total cholesterol, triglyceride, and glucose levels. It can decrease peroxide content in serum lipids and inhibit glutathione reductase and superoxide dismutase in hepatic cells. The dietary supplementation with LSS provided cytoprotection by enhancing the histoarchitecture of the liver and decreasing the number of apoptotic cells. Due to their antioxidant and anti-apoptotic properties, LSS effectively protect against the hepatotoxicity of MSG. These findings are of the highest significance for drawing attention to incorporating LSS in our food industry and as a health treatment in traditional medicine to combat MSG-induced hepatic abnormalities.

DIETARY LIFESTYLE, HYPOALBUMINAEMIA AND ANAEMIA AMONG OLDER ADULTS ATTENDING A PRIMARY CARE CLINIC IN NIGERIA: A CROSS-SECTIONAL STUDY.

Introduction: Anaemia has been extensively studied in children and women of reproductive age. However, there are few data on anaemia and related conditions in the elderly from developing countries. Objectives: To determine the prevalence and severity pattern of anaemia, and assess the relationship between dietary lifestyle, hypoalbuminaemia, and anaemia in older persons. Methodology: A cross-sectional study involving 378 patients aged≥60 years who presented at the General Outpatient Clinic. Dietary lifestyle was assessed using a structured questionnaire. Samples were collected for packed cell volume and serum albumin. Inferential statistical analyses were used to determine the associations between variables. Results: A total of 348 respondents completed the study. The mean age of respondents was 67.83 ±7.53 years with female (60.9%) predominance. The prevalence of anaemia and hypoalbuminaemia were 42.2% and 17.8% respectively. Hypoalbuminaemia (ß=0.335, 95%CI=0.131-0.229, P<0.001), long duration of co-morbidities (ß= - 0.179, 95%CI= -0.165-0.047, P<0.001), one full meal/day (ß=0.130, 95%CI=0.224-1.879, P=0.013), and low monthly income (ß=0.122, 95%CI=0.179-1.543, P=0.026) were the predictors of anaemia among the elderly in this study. Conclusion: Data on the predictors of anaemia from this study will be useful in developing guidelines and strategies for managing the condition in primary care settings and other similar sites.

Effect of dietary supplementation of betaine and organic minerals on growth performance, serum biochemical parameters, nutrients digestibility, and growth-related genes in broilers under heat stress.

Global warming and climate changes have a detrimental impact on poultry production, causing substantial economic losses. This study investigated the effects of incorporating dietary betaine (BT) and organic minerals (OMs) on broilers' performance as well as their potential to mitigate the negative impacts of heat stress (HS). Six hundred 1-day-old Ross 308 chicks were randomly allocated to 12 experimental treatments with 5 replicates of 10 birds each (5 male + 5 female). The birds were provided with diets containing BT (0 and 2,000 ppm) and OMs (0, 250, and 500 ppm), either individually or in combination, under both thermoneutral and HS-inducing temperatures. The HS conditions involved exposing the birds to cyclic periods of elevated temperature (35°C ± 2°C) for 6 h daily, from 10:00 am to 4:00 pm, starting from d 10 and continuing until d 35. The exposure to HS deteriorated birds' growth performance; however, dietary BT and OMs inclusion improved the growth performance parameters bringing them close to normal levels. Carcass traits were not affected by dietary supplementation of BT, OMs, HS, or their interaction. Interestingly, while HS led to increased (P < 0.05) levels of total cholesterol, LDL-cholesterol, and hepatic malondialdehyde (MDA), these adverse effects were mitigated (P < 0.05) by the addition of BT and OMs. Moreover, dietary BT supplementation led to elevated serum total protein and globulin concentrations. Cyclic HS did not alter Mn, Zn, and Cu contents in the pectoral muscle. However, the incorporation of OMs at both levels increased concentrations of these minerals. Notably, the combination of 500 ppm OMs and 2,000 ppm BT improved Mn, Zn, Cu, and Fe digestibility, which has been compromised under HS conditions. Cyclic HS upregulated gene expression of interleukin-1ß, heat shock protein 70, and Toll-like receptor-4 while downregulated the expression of claudin-1, uncoupling protein, growth hormone receptor, superoxide dismutase 1, glutathione peroxidase 1 and insulin-like growth factor 1. The aforementioned gene expressions were reversed by the combination of higher dietary levels of BT and OMs. In conclusion, the dietary supplementation of 500 ppm OMs along with 2,000 ppm BT yielded significant improvements in growth performance and mineral digestibility among broiler chickens, regardless of thermal conditions. Moreover, this combination effectively restored the expression of growth-related genes even under heat-stress conditions.

Exploring Salinity Tolerance Mechanisms in Diverse Wheat Genotypes Using Physiological, Anatomical, Agronomic and Gene Expression Analyses.

Salinity is a widespread abiotic stress that devastatingly impacts wheat growth and restricts its productivity worldwide. The present study is aimed at elucidating biochemical, physiological, anatomical, gene expression analysis, and agronomic responses of three diverse wheat genotypes to different salinity levels. A salinity treatment of 5000 and 7000 ppm gradually reduced photosynthetic pigments, anatomical root and leaf measurements and agronomic traits of all evaluated wheat genotypes (Ismailia line, Misr 1, and Misr 3). In addition, increasing salinity levels substantially decreased all anatomical root and leaf measurements except sclerenchyma tissue upper and lower vascular bundle thickness compared with unstressed plants. However, proline content in stressed plants was stimulated by increasing salinity levels in all evaluated wheat genotypes. Moreover, Na+ ions content and antioxidant enzyme activities in stressed leaves increased the high level of salinity in all genotypes. The evaluated wheat genotypes demonstrated substantial variations in all studied characters. The Ismailia line exhibited the uppermost performance in photosynthetic pigments under both salinity levels. Additionally, the Ismailia line was superior in the activity of superoxide dismutase (SOD), catalase activity (CAT), peroxidase (POX), and polyphenol oxidase (PPO) enzymes followed by Misr 1. Moreover, the Ismailia line recorded the maximum anatomical root and leaf measurements under salinity stress, which enhanced its tolerance to salinity stress. The Ismailia line and Misr 3 presented high up-regulation of H+ATPase, NHX2 HAK, and HKT genes in the root and leaf under both salinity levels. The positive physiological, anatomical, and molecular responses of the Ismailia line under salinity stress were reflected on agronomic performance and exhibited superior values of all evaluated agronomic traits.

Antimicrobial Resistance: A Growing Serious Threat for Global Public Health.

Antibiotics are among the most important discoveries of the 20th century, having saved millions of lives from infectious diseases. Microbes have developed acquired antimicrobial resistance (AMR) to many drugs due to high selection pressure from increasing use and misuse of antibiotics over the years. The transmission and acquisition of AMR occur primarily via a human-human interface both within and outside of healthcare facilities. A huge number of interdependent factors related to healthcare and agriculture govern the development of AMR through various drug-resistance mechanisms. The emergence and spread of AMR from the unrestricted use of antimicrobials in livestock feed has been a major contributing factor. The prevalence of antimicrobial-resistant bacteria has attained an incongruous level worldwide and threatens global public health as a silent pandemic, necessitating urgent intervention. Therapeutic options of infections caused by antimicrobial-resistant bacteria are limited, resulting in significant morbidity and mortality with high financial impact. The paucity in discovery and supply of new novel antimicrobials to treat life-threatening infections by resistant pathogens stands in sharp contrast to demand. Immediate interventions to contain AMR include surveillance and monitoring, minimizing over-the-counter antibiotics and antibiotics in food animals, access to quality and affordable medicines, vaccines and diagnostics, and enforcement of legislation. An orchestrated collaborative action within and between multiple national and international organizations is required urgently, otherwise, a postantibiotic era can be a more real possibility than an apocalyptic fantasy for the 21st century. This narrative review highlights on this basis, mechanisms and factors in microbial resistance, and key strategies to combat antimicrobial resistance.

Using the LeiCNS-PK3.0 Physiologically-Based Pharmacokinetic Model to Predict Brain Extracellular Fluid Pharmacokinetics in Mice.

INTRODUCTION: The unbound brain extracelullar fluid (brainECF) to plasma steady state partition coefficient, Kp,uu,BBB, values provide steady-state information on the extent of blood-brain barrier (BBB) transport equilibration, but not on pharmacokinetic (PK) profiles seen by the brain targets. Mouse models are frequently used to study brain PK, but this information cannot directly be used to inform on human brain PK, given the different CNS physiology of mouse and human. Physiologically based PK (PBPK) models are useful to translate PK information across species. AIM: Use the LeiCNS-PK3.0 PBPK model, to predict brain extracellular fluid PK in mice. METHODS: Information on mouse brain physiology was collected from literature. All available connected data on unbound plasma, brainECF PK of 10 drugs (cyclophosphamide, quinidine, erlotonib, phenobarbital, colchicine, ribociclib, topotecan, cefradroxil, prexasertib, and methotrexate) from different mouse strains were used. Dosing regimen dependent plasma PK was modelled, and Kpuu,BBB values were estimated, and provided as input into the LeiCNS-PK3.0 model to result in prediction of PK profiles in brainECF. RESULTS: Overall, the model gave an adequate prediction of the brainECF PK profile for 7 out of the 10 drugs. For 7 drugs, the predicted versus observed brainECF data was within two-fold error limit and the other 2 drugs were within five-fold error limit. CONCLUSION: The current version of the mouse LeiCNS-PK3.0 model seems to reasonably predict available information on brainECF from healthy mice for most drugs. This brings the translation between mouse and human brain PK one step further.

A robust algorithmic cum integrated approach of interval-valued fuzzy hypersoft set and OOPCS for real estate pursuit.

Due to the vast variety of aspects that must be made-many of which are in opposition to one another-choosing a home can be difficult for those without much experience. Individuals need to spend more time making decisions because they are difficult, which results in making poor choices. To overcome residence selection issues, a computational approach is necessary. Unaccustomed people can use decision support systems to help them make decisions of expert quality. The current article explains the empirical procedure in that field in order to construct decision-support system for selecting a residence. The main goal of this study is to build a weighted product mechanism-based decision-support system for residential preference. The said house short-listing estimation is based on several key requirements derived from the interaction between the researchers and experts. The results of the information processing show that the normalized product strategy can rank the available alternatives to help individuals choose the best option. The interval valued fuzzy hypersoft set (IVFHS-set) is a broader variant of the fuzzy soft set that resolves the constraints of the fuzzy soft set from the perspective of the utilization of the multi-argument approximation operator. This operator maps sub-parametric tuples into a power set of universe. It emphasizes the segmentation of every attribute into a disjoint attribute valued set. These characteristics make it a whole new mathematical tool for handling problems involving uncertainties. This makes the decision-making process more effective and efficient. Furthermore, the traditional TOPSIS technique as a multi-criteria decision-making strategy is discussed in a concise manner. A new decision-making strategy, "OOPCS" is constructed with modifications in TOPSIS for fuzzy hypersoft set in interval settings. The proposed strategy is applied to a real-world multi-criteria decision-making scenario for ranking the alternatives to check and demonstrate their efficiency and effectiveness.

Enhancing Intrusion Detection Systems for IoT and Cloud Environments Using a Growth Optimizer Algorithm and Conventional Neural Networks.

Intrusion detection systems (IDS) play a crucial role in securing networks and identifying malicious activity. This is a critical problem in cyber security. In recent years, metaheuristic optimization algorithms and deep learning techniques have been applied to IDS to improve their accuracy and efficiency. Generally, optimization algorithms can be used to boost the performance of IDS models. Deep learning methods, such as convolutional neural networks, have also been used to improve the ability of IDS to detect and classify intrusions. In this paper, we propose a new IDS model based on the combination of deep learning and optimization methods. First, a feature extraction method based on CNNs is developed. Then, a new feature selection method is used based on a modified version of Growth Optimizer (GO), called MGO. We use the Whale Optimization Algorithm (WOA) to boost the search process of the GO. Extensive evaluation and comparisons have been conducted to assess the quality of the suggested method using public datasets of cloud and Internet of Things (IoT) environments. The applied techniques have shown promising results in identifying previously unknown attacks with high accuracy rates. The MGO performed better than several previous methods in all experimental comparisons.

Genetic Diversity Analysis of Banana Cultivars (Musa sp.) in Saudi Arabia Based on AFLP Marker.

Banana plantation has been introduced recently to a temperate zone in the southeastern parts of Saudi Arabia (Fifa, Dhamadh, and Beesh, located in Jazan province). The introduced banana cultivars were of a clear origin without a recorded genetic background. In the current study, the genetic variability and structure of five common banana cultivars (i.e., Red, America, Indian, French, and Baladi) were analyzed using the fluorescently labeled AFLP technique. Nine different primer pairs combinations yielded 1468 loci with 88.96% polymorphism. Among all locations, high expected heterozygosity under the Hardy-Weinberg assumption was found (0.249 ± 0.003), where Dhamadh was the highest, followed by Fifa and Beesh, respectively. Based on the PCoA and Structure analysis, the samples were not clustered by location but in pairs in accordance with the cultivar's names. However, the Red banana cultivar was found to be a hybrid between the American and Indian cultivars. Based on ΦST, 162 molecular markers (i.e., loci under selection) were detected among cultivars. Identifying those loci using NGS techniques can reveal the genetic bases and molecular mechanisms involved in the domestication and selection indicators among banana cultivars.

Discovery of benzochromene derivatives first example with dual cytotoxic activity against the resistant cancer cell MCF-7/ADR and inhibitory effect of the P-glycoprotein expression levels.

A series of 1H-benzo[f]chromene moieties (4a-z) were synthesised under Ultrasonic irradiation and confirmed with spectral analyses. Derivative 4i solely possessed an X-ray single crystal. The anti-proliferative efficacy of the desired molecules has been explored against three cancer cells: MCF-7, HCT-116, and HepG-2 with the cytotoxically active derivatives screened against MCF-7/ADR and normal cells HFL-1 and WI-38. Furthermore, compounds 4b-d, 4k, 4n, 4q, and 4w, which possessed good potency against MCF-7/ADR, were tested as permeability glycoprotein (P-glycoprotein [P-gp]) expression inhibitors. The attained data confirmed that 4b-d, 4q, and 4w exhibited strong expression inhibition against the P-gp alongside its cytotoxic effect on MCF-7/ADR. The western blot results and Rho123 accumulation assays showed that compounds 4b-d, 4q, and 4w effectively inhibited the P-gp expression and efflux function. Meanwhile, 4b-d, 4q, and 4w induced apoptosis and accumulation of the treated MCF-7/ADR cells in the G1 phase and 4k and 4n in the S phase of the cell cycle.

A descriptive study of inflammatory bowel disease at an Egyptian tertiary care center.

INTRODUCTION AND AIMS: Inflammatory bowel disease (IBD) is a group of chronic intestinal disorders that trigger prolonged inflammation of the digestive tract. Its incidence and prevalence appear to be increasing in the African population and in Egypt. The present study aims to highlight the pattern and management of IBD in Egyptian patients. MATERIALS AND METHODS: Two hundred patients with IBD were assessed for ulcerative colitis (UC), through the Mayo score, and for Crohn's disease (CD), with the Crohn's disease activity index (CDAI). RESULTS: Median patient age was 35 years, with a predominance of females. UC was more common than CD (88% and 12%, respectively) and severity was moderate, in the majority of cases. Most UC patients had left-sided lesions, whereas ileitis was the most common finding (37.5%) in the CD patients. Proctitis was the least common finding in both diseases and Crohn's fistulizing disease was detected in 4.1% of the patients. Interestingly, peripheral arthropathy was the most common extraintestinal manifestation in the IBD patients (70%) and axial arthropathy was the least common (6%). Severe ocular or mucocutaneous involvement was very rare. Finally, biologic treatment was prescribed to 15.4% of the UC patients and 20.8% of the CD patients. CONCLUSIONS: Although the clinical presentation of IBD in Egypt is comparable to that reported worldwide, diagnoses were found to be delayed. There were fewer cases of CD than UC, but more mild-to-moderate disease severity. The surveillance of patients with IBD must continue and awareness of the disease in the Egyptian medical community needs to increase. A national registry must be established, multicenter studies need to be conducted, and molecular diagnostics is recommended.

The PBPK LeiCNS-PK3.0 framework predicts Nirmatrelvir (but not Remdesivir or Molnupiravir) to achieve effective concentrations against SARS-CoV-2 in human brain cells.

SARS-CoV-2 was shown to infect and persist in the human brain cells for up to 230 days, highlighting the need to treat the brain viral load. The CNS disposition of the antiCOVID-19 drugs: Remdesivir, Molnupiravir, and Nirmatrelvir, remains, however, unexplored. Here, we assessed the human brain pharmacokinetic profile (PK) against the EC90 values of the antiCOVID-19 drugs to predict drugs with favorable brain PK against the delta and the omicron variants. We also evaluated the intracellular PK of GS443902 and EIDD2061, the active metabolites of Remdesivir and Molnupiravir, respectively. Towards this, we applied LeiCNS-PK3.0, the physiologically based pharmacokinetic framework with demonstrated adequate predictions of human CNS PK. Under the recommended dosing regimens, the predicted brain extracellular fluid PK of only Nirmatrelvir was above the variants' EC90. The intracellular levels of GS443902 and EIDD2061 were below the intracellular EC90. Summarizing, our model recommends Nirmatrelvir as the promising candidate for (pre)clinical studies investigating the CNS efficacy of antiCOVID-19 drugs.

Predicting CO2 trapping in deep saline aquifers using optimized long short-term memory.

A sustainable environment by decreasing fossil fuel utilization and anthropogenic greenhouse gases is a globally main goal due to climate change and serious air pollution. Carbon dioxide (CO2) is a heat-trapping (greenhouse) that is released into the earth's atmosphere from natural processes, such as volcanic respiration and eruptions, as well as human activities, such as burning fossil fuels and deforestation. Due to this fact, underground carbon storage (UCS) is a promising technology to cut carbon emissions. However, there are some barriers to prevent UCS from applying globally. One of them is evaluating the feasibility of storage projects. Thus, the prediction accuracy of CO2 storage efficiencies may promote the attention of the community for UCS. In this study, we utilize the recent advances of swarm intelligence to develop a hybrid algorithm called AOSMA, employed to train the long short-term memory (LSTM). The developed swarm intelligence method (AOSMA) is an enhanced Aquila optimizer (AO) using the search mechanism of the slime mould algorithm (SMA). It is used to boost the prediction capability of the LSTM by optimizing its parameters. We considered two CO2 trapping indices, called residual trapping index (RTI) and solubility trapping index (STI). The evaluation experiments have shown that the AOSMA achieved significant results compared to the original AO and SMA and several swarm intelligence and optimization algorithms. The developed smart tools could use as a game changer to provide fast and accurate storage efficiency for projects that have similar parameters falling within the range of the database.