ANN-based swarm intelligence for predicting expansive soil swell pressure and compression strength.

This research suggests a robust integration of artificial neural networks (ANN) for predicting swell pressure and the unconfined compression strength of expansive soils (PsUCS-ES). Four novel ANN-based models, namely ANN-PSO (i.e., particle swarm optimization), ANN-GWO (i.e., grey wolf optimization), ANN-SMA (i.e., slime mould algorithm) alongside ANN-MPA (i.e., marine predators' algorithm) were deployed to assess the PsUCS-ES. The models were trained using the nine most influential parameters affecting PsUCS-ES, collected from a broader range of 145 published papers. The observed results were compared with the predictions made by the ANN-based metaheuristics models. The efficacy of all these formulated models was evaluated by utilizing mean absolute error (MAE), Nash-Sutcliffe (NS) efficiency, performance index ρ, regression coefficient (R2), root mean square error (RMSE), ratio of RMSE to standard deviation of actual observations (RSR), variance account for (VAF), Willmott's index of agreement (WI), and weighted mean absolute percentage error (WMAPE). All the developed models for Ps-ES had an R significantly > 0.8 for the overall dataset. However, ANN-MPA excelled in yielding high R values for training dataset (TrD), testing dataset (TsD), and validation dataset (VdD). This model also exhibited the lowest MAE of 5.63%, 5.68%, and 5.48% for TrD, TsD, and VdD, respectively. The results of the UCS model's performance revealed that R exceeded 0.9 in the TrD. However, R decreased for TsD and VdD. Also, the ANN-MPA model yielded higher R values (0.89, 0.93, and 0.94) and comparatively low MAE values (5.11%, 5.67, and 3.61%) in the case of PSO, GWO, and SMA, respectively. The UCS models witnessed an overfitting problem because the aforementioned R values of the metaheuristics were 0.62, 0.56, and 0.58 (TsD), respectively. On the contrary, no significant observation was recorded in the VdD of UCS models. All the ANN-base models were also tested using the a-20 index. For all the formulated models, maximum points were recorded to lie within ± 20% error. The results of sensitivity as well as monotonicity analyses depicted trending results that corroborate the existing literature. Therefore, it can be inferred that the recently built swarm-based ANN models, particularly ANN-MPA, can solve the complexities of tuning the hyperparameters of the ANN-predicted PsUCS-ES that can be replicated in practical scenarios of geoenvironmental engineering.

Analyzing injury severity of three-wheeler motorized rickshaws: A correlated random parameters approach with heterogeneity in means.

Traffic crashes involving three-wheeler motorized rickshaw (3-WMR) are alarming public health and socioeconomic concerns in developing countries. While most of the earlier studies have dealt with safety analysis of four- and two-wheelers, there is a noticeable gap in understanding the safety dynamics, especially the risk factors affecting the crashes involving 3-WMR. The present study aims to address this gap by exploring potential risk factors influencing 3-WMR crashes, utilizing a correlated random parameters multinomial logit model with heterogeneity in means (CRPMNLMHM). This modeling framework advances the classic random parameters model by capturing associations among random parameters, providing a more comprehensive understanding of crash risks associated with 3-WMR. The empirical analysis draws on three years of traffic crash records (2017-2019) maintained by RESCUE 1122 in Rawalpindi city, Pakistan. A comparative assessment between the modeling frameworks demonstrated that CRPMNLMHM outperformed its counterparts. Model assessment for heterogeneity in the means identifies two significant variables, i.e., young age and nighttime, which yield statistically significant random parameters. In addition, the model's results suggest that fatal and severe injury outcomes in 3-WMR crashes are affected by several attributes related to temporal characteristics (weekend, nighttime, and off-peak indicators), driver profiles (young, older aged, and speeding), posted speed limits (>70 kmph), weather conditions (raining), and crash characteristics (collision with pedestrians, trucks, or 3-WMR overturning). The present study's findings offer invaluable insights, emphasizing the significance of considering for unobserved heterogeneity in variables contributing to the injury severity of 3-WMR crashes. Moreover, in light of the findings, a set of policy implications are suggested, which will guide safety practitioners to develop more effective countermeasures to address safety issues associated with 3-WMRs.

Effect of Mirabegron in Men With Overactive Bladder and Erectile Dysfunction: A Prospective Observational Study.

BACKGROUND: As it has been observed that the erect penis has been the epitome of virility for the male community for decades, it became necessary to search for alternative treatments for the cause. So, the study was performed to evaluate the potential impact of mirabegron in men with mild to moderate erectile dysfunction (ED) and overactive bladder (OAB). METHODS: It was a prospective, observational study that was carried out at the Department of Urology at Rajendra Institute of Medical Sciences, Ranchi, for a duration of two years and included a total of two hundred fifty patients. The individuals included had a diagnosis of mild to moderate erectile dysfunction (ED) along with symptoms of OAB. The overactive bladder questionnaire (OAB-q) score and the International Index of Erectile Dysfunction-5 (IIEF-5) score were used, respectively, to measure the impact of mirabegron on ED and OAB. Then, the changes in ED and OAB were evaluated at two, four, eight, and 12 weeks. RESULTS: Among the total 250 patients recruited, around 32.5% of them had mild ED, 17.5% were diagnosed with mild to moderate ED, and 50% suffered from moderate ED. The IIEF-5 scores improved by four points or more in 86.25%, 91.25%, and 71.25% of patients after four, eight, and 12 weeks, respectively. OAB-q scores were likewise shown to decline in the fourth (13.1 ± 4.3) and eighth (12.8 ± 4.2) weeks when compared to the baseline (17.4 ± 5.5). Also, adverse events reported did not hamper the progress of the study. CONCLUSION: The study concluded that mirabegron has a beneficial impact on controlling OAB symptoms among men diagnosed with mild to moderate ED. The effects last for only eight weeks, and then they decline. Furthermore, mirabegron was well-tolerated among patients and had no safety concerns with its use.

Identification of TBK1 inhibitors against breast cancer using a computational approach supported by machine learning.

Introduction: The cytosolic Ser/Thr kinase TBK1 is of utmost importance in facilitating signals that facilitate tumor migration and growth. TBK1-related signaling plays important role in tumor progression, and there is need to work on new methods and workflows to identify new molecules for potential treatments for TBK1-affecting oncologies such as breast cancer. Methods: Here, we propose the machine learning assisted computational drug discovery approach to identify TBK1 inhibitors. Through our computational ML-integrated approach, we identified four novel inhibitors that could be used as new hit molecules for TBK1 inhibition. Results and Discussion: All these four molecules displayed solvent based free energy values of -48.78, -47.56, -46.78 and -45.47 Kcal/mol and glide docking score of -10.4, -9.84, -10.03, -10.06 Kcal/mol respectively. The molecules displayed highly stable RMSD plots, hydrogen bond patterns and MMPBSA score close to or higher than BX795 molecule. In future, all these compounds can be further refined or validated by in vitro as well as in vivo activity. Also, we have found two novel groups that have the potential to be utilized in a fragment-based design strategy for the discovery and development of novel inhibitors targeting TBK1. Our method for identifying small molecule inhibitors can be used to make fundamental advances in drug design methods for the TBK1 protein which will further help to reduce breast cancer incidence.

Evaluating helmet-wearing of single-vehicle overspeeding motorcycle crashes: Insights from temporal instability in parsimonious pooled framework.

OBJECTIVE: A lower helmet-wearing rate and overspeeding in Pakistan are critical risk behaviors of motorcyclists, causing severe injuries. To explore the differences in the determinants affecting the injury severities among helmeted and non-helmeted motorcyclists in motorcycle crashes caused by overspeeding behavior, single-vehicle motorcycle crash data in Rawalpindi city for 2017-2019 is collected. Considering three possible crash injury severity outcomes of motorcyclists: fatal injury, severe injury and minor injury, the rider, roadway, environmental, and temporal characteristics are estimated. METHODS: To provide a mathematically simpler framework, the current study introduces parsimonious pooled random parameters logit models. Then, the standard pooled random parameters logit models without considering temporal effects are also simulated for comparison. By comparing the goodness of fit measure and estimation results, the parsimonious pooled random parameters logit model is suitable for capturing the temporal instability. Then, the non-transferability among helmeted and non-helmeted overspeeding motorcycle crashes is illustrated by likelihood ratio tests and out-of-sample prediction, and two types of models provide robust results. The marginal effects are also calculated. RESULTS: Several variables, such as age, cloudy and weekday indicators illustrate temporal instability. Moreover, several variables are observed to only show significance in non-helmeted models, showing non-transferability across helmeted and non-helmeted models. CONCLUSIONS: More educational campaigns, regulation and enforcement, and management countermeasures should be organized for non-helmeted motorcyclists and overspeeding behavior. Such findings also provide research reference for the risk-compensating behavior and self-selected group issues under overspeeding riding considering the usage of helmets.

Induced pluripotent stem cells (iPSCs): Where are we and where are we heading?

Induced Pluripotent Stem Cells (iPSCs) offer a unique therapeutic tool. The extent of the ongoing clinical studies substantiates the role of these cells in a highly promising area of personalized medicine. The employment of this technology in translational research is on the horizon. However, still, many questions remain unanswered. In this review, we discussed certain challenges and difficulties currently faced during the safe and stable clinical application of iPSCs. Furthermore, we describe the potential therapeutic scenarios employing iPSCs for the betterment of human health and the improvement of the health care sector.

Circular Penile Skin Fasciocutaneous Ventral Onlay Flap Urethroplasty as an Alternative to Dorsal Onlay Buccal Mucosal Graft Urethroplasty in Complex Long-Segment Urethral Stricture: A Retrospective Study.

Background A urethral stricture is the narrowing of the urethra that results in symptoms of obstruction. It can appear anywhere along the male urethra's length and has a variety of causes. The circular penile fasciocutaneous flap is employed in the successful single-stage reconstruction of long-segment complex anterior urethral strictures especially when the buccal mucosa is unavailable due to various reasons. The study has tried to identify a surgical technique that is more beneficial for the treatment of urethral strictures. Objective The objective of this research was to evaluate the outcomes of circular penile skin fasciocutaneous ventral onlay flap urethroplasty (group A) and the outcomes of dorsal onlay buccal mucosal graft urethroplasty (group B) in the management of complex long-segment penile urethral stricture. Methods In this retrospective study between December 2012 and December 2022, 60 patients with long-segment complex penile urethral stricture who underwent urethroplasty at our center were evaluated. Patients were divided into two groups according to the flap used (dorsal onlay buccal mucosal graft urethroplasty was used in 30 patients (group B), and circular penile fasciocutaneous flap (single stage) was used in 30 patients (group A)). The success rate and the mean peak flow rate were also calculated post-operation to identify the effectiveness of the surgical procedure used for urethral strictures. Results The study consisted of 60 patients in total. Group A's mean age was determined to be 51.2±16.2 years, whereas group B's mean age was determined to be 40.7±16.8 years. Preoperatively, the median urethral stricture length was 69 mm in group A (range: 20-100 mm) and 56 mm in group B (range: 30-110 mm). The intraoperative median length of the urethral stricture was 82 mm in group A (range: 20-120 mm) and 65 mm in group B (range: 40-140 mm). The mean peak flow rate was 30.9±6.8 mL/s in group A compared to 18.1±4.9 mL/s in group B. The success rate for group A was 89.7%, while the success rate for group B was 75.9%. Conclusion For complex long-segment urethral strictures, circular penile skin fasciocutaneous ventral onlay flap urethroplasty has a higher rate of success and fewer complications than dorsal onlay buccal mucosal graft urethroplasty. Along with success rate, it has a better mean peak flow rate and lower complications.

DISPEL: database for ascertaining the best medicinal plants to cure human diseases.

Medicinal plants are anticipated to be one of the most valuable resources for the remedial usage in the treatment of various ailments. The data on key medicinal plants and their therapeutic efficacy against various ailments are quite scattered and not available on a single platform. Moreover, currently there is no means/mechanism of finding the best medicinal plant(s) from numerous plants known to cure any disease. DISPEL (Diseases Plants Eliminate) is a compendium of medicinal plants available across the world that are used to cure infectious as well as non-infectious diseases in humans. The association of a medicinal plant with a disease it cures is hereby referred to as 'medicinal plant-disease cured' linkage. The DISPEL database hosts ∼60 000 'medicinal plant-disease cured' linkages encompassing ∼5500 medicinal plants and ∼1000 diseases. This platform provides interactive and detailed visualization of medicinal plants, diseases and their relations using comprehensible network graph representation. The user has the freedom to search the database by specifying the name of disease(s) as well as the scientific/common name(s) of plant. Each 'medicinal plant-disease cured' relation is scored based on the availability of any medicine/product derived from that medicinal plant, information about active compound(s), knowledge regarding the part of plant that is effective and number of distinct articles/books/websites confirming the effectiveness of the medicinal plant. The user can find the best plant(s) that can be used to cure any desired disease(s). The DISPEL database is the first step towards generating the 'most-effective' combination of plants to cure a disease since it delineates as well as ranks all the therapeutic medicinal plants for that disease. The combination of best medicinal plants can then be used to conduct clinical trials and thus pave the way for their use in clinics for treatment of diseases. Database URL https://compbio.iitr.ac.in/dispel.

Spices as Sustainable Food Preservatives: A Comprehensive Review of Their Antimicrobial Potential.

Throughout history, spices have been employed for their pharmaceutical attributes and as a culinary enhancement. The food industry widely employs artificial preservatives to retard the deterioration induced by microbial proliferation, enzymatic processes, and oxidative reactions. Nevertheless, the utilization of these synthetic preservatives in food products has given rise to significant apprehension among consumers, primarily stemming from the potential health risks that they pose. These risks encompass a spectrum of adverse effects, including but not limited to gastrointestinal disorders, the disruption of gut microbiota, allergic reactions, respiratory complications, and concerns regarding their carcinogenic properties. Consequently, consumers are displaying an increasing reluctance to purchase preserved food items that contain such additives. Spices, known for their antimicrobial value, are investigated for their potential as food preservatives. The review assesses 25 spice types for their inherent antimicrobial properties and their applicability in inhibiting various foodborne microorganisms and suggests further future investigations regarding their use as possible natural food preservatives that could offer safer, more sustainable methods for extending shelf life. Future research should delve deeper into the use of natural antimicrobials, such as spices, to not only replace synthetic preservatives but also optimize their application in food safety and shelf-life extension. Moreover, there is a need for continuous innovation in encapsulation technologies for antimicrobial agents. Developing cost-effective and efficient methods, along with scaling up production processes, will be crucial to competing with traditional antimicrobial options in terms of both efficacy and affordability.

A Study of Normal Renal Dimensions at Ultrasonography and Their Influencing Factors in an Indian Population.

Background: Kidney dimensions play one of the most vital roles in the diagnosis and identification of any renal disease. Renal dimensions are generally used in clinical practices to determine the size of the kidney as well as correlate with renal function to have a better understanding of acute and chronic renal diseases. This study aimed to find out the normal renal dimensions with the help of ultrasonography and their impact on the Indian population. Methods: Renal dimensions, which include parenchymatous thickness and length as well as the width of about 60 healthy adult Indian populations, were estimated with the help of sonography, and a detailed study has been performed on the difference observed based on age, sex, height, weight, body mass index, and body surface area. Results: There was no particular difference found on the basis of width and length between the left and right kidneys; however, the parenchymal thickness between the left and right has been shown to have a significant difference. The mean width, length, and parenchymal thickness were 4.6 ± 0.43, 9.64 ± 0.62, and 2.03 ± 0.1 cm, respectively. While doing estimation based on gender, it has been observed that there is a noticeable difference in width but no difference in height or parenchymal thickness. A significant diversity has been observed in patients in age groups above 49 compared to other age groups. A positive correlation with body weight, body height, and body mass index has also been observed in some cases. Conclusion: The given study has attempted to define the standard reference for renal dimension in the Indian census. The observations made in the given study demonstrated the possibility of renal dimensions being smaller in the Indian population in contrast to those of the Western population, which are much larger.

Association between 17q21 variants and asthma predisposition in Pashtun population from Pakistan.

OBJECTIVE: Asthma is a heterogeneous and genetically complex respiratory disease, and more than 300 million people are affected worldwide. In this study, frequencies of four SNPs (rs3816470, rs7216389, rs8067378, rs12603332) in chromosome 17q21 region were analyzed and their relationship with the asthma susceptibility, in the Pashtun population of Khyber Pakhtunkhwa province (KPK) of Pakistan were investigated. METHODS: DNA samples from 500 subjects (asthma cases/controls) were genotyped by Sanger sequencing. Chi-square tests, logistic regression analysis, linkage disequilibrium, and haplotype analysis techniques were applied to study the association of the SNPs with asthma. RESULTS: Genetic models, including recessive, dominant, co-dominant, over-dominant, and additive, were tested. The frequencies of alleles T/T at rs3816470 (OR = 1.91; 95%CI = 1.15-3.18; p = .011*) and rs7216389 (OR = 2.14; 95%CI = 1.21-3.79; p = .0076*), A/A at rs 8067378 (OR = 1.89; 95%CI = 1.17-3.06; p = .0081*), C/C at rs12603332 (OR = 1.97; 95%CI = 1.18-3.27; p = .008*), under recessive models, respectively, were significantly (p-values < .0125) associated with asthma susceptibility. The frequencies of T/T genotype in rs3816470 (OR = 6.01; 95%CI = 2.48-14.60; p = .000147*), and rs7216389 (OR = 5.05; 95%CI = 1.79-14.21; p = .003296*), and C/C at rs12603332 (OR = 2.64; 95%CI = 1.11-6.32; p = .019063*), were significantly (p-values < .0125) associated with asthma susceptibility in Pashtun women by stratified analysis based on age and gender. Similarly, three unique haplotypes were found associated with disease development and protective effect in female and male subjects. Linkage disequilibrium analysis presented a strong linkage (≥80%) between SNP variants and predicted their co-inheritance in the studied population. CONCLUSION: The 17q21 variants (rs3816470, rs7216389, rs12603332) were found significantly (p-values < .0125) associated with asthma predisposition in the Pashtun population of KPK exclusively in the female asthmatic cases.Supplemental data for this article can be accessed.

Optimization of laccase from Stenotrophomonas maltophilia E1 by submerge fermentation using coconut husk with its detoxification and biodecolorization ability of synthetic dyes.

Enzymatic degradation of synthetic dyes holds an immense promise for addressing the environmental concerns associated with the textile and dye industries. This study aimed to isolate bacteria capable of producing laccase enzymes from an anthropogenic environment. Subsequently, viability of utilizing cost-effective agricultural residues as substrates for laccase production was assessed. Response Surface Methodology (RSM) and the One Variable at a Time (OVAT) approach was pursued for the optimization of laccase production, followed by pH and temperature stability, dye degradation and decolorization experiments, toxicological studies on the degraded dye metabolites. In results, laccase-producing bacterial strain was identified as Stenotrophomonas maltophilia strain E1 (S. maltophilia). Among variety of substrates, coconut husk exhibited optimal efficacy. In a statistical optimization study, it was found that S. maltophilia was capable of producing laccase 51.38 IU/mL, i.e., three times higher than the amount of laccase produced by unoptimized medium (16.7 IU/mL), and the enzyme activity was found to be steady at an acidic pH, and a mesophilic temperature range. The laccase obtained from S. maltophilia E1 demonstrated proficient dye decolorization capabilities, achieving a notable 92.1% reduction in Malachite green dye coloration at a concentration of 500 ppm. Gas chromatography-mass spectrometry (GC-MS) analysis of the decolorized derivatives of Malachite green revealed a conversion into a distinct compounds. Moreover, after undergoing laccase treatment, Malachite green exhibited decreased phytotoxic effects on Oryza sativa, pointing to enzymatic detoxification. Collectively, insights gained from the present study will contribute to the development of efficient enzymatic approaches for addressing the environmental pollution caused by synthetic dyes.

Recent advances in applications of artificial intelligence in solid waste management: A review.

Efficient management of solid waste is essential to lessen its potential health and environmental impacts. However, the current solid waste management practices encounter several challenges. The development of effective waste management systems using advanced technologies is vital to overcome the challenges faced by the current approaches. Artificial Intelligence (AI) has emerged as a powerful tool for applications in various fields. Several studies also reported the applications of AI techniques in the management of solid waste. This article critically reviews the recent advancements in the applications of AI techniques for the management of solid waste. Various AI and hybrid techniques have been successfully employed to predict the performance of various methods used for the generation, segregation, storage, and treatment of solid waste. The key challenges that limit the applications of AI in solid waste are highlighted. These include the availability and selection of applicable data, poor reproducibility, and less evidence of applications in real solid waste. Based on identified gaps and challenges, recommendations for future work are provided. This review is beneficial for all stakeholders in the field of solid waste management, including policy-makers, governments, waste management organizations, municipalities, and researchers.

Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances.

Not wearing a helmet, not properly strapping the helmet on, or wearing a substandard helmet increases the risk of fatalities and injuries in motorcycle crashes. This research examines the differences in motorcycle crash injury severity considering crashes involving the compliance with and defiance of helmet use by motorcycle riders and highlights the temporal variation in their impact. Three-year (2017-2019) motorcycle crash data were collected from RESCUE 1122, a provincial emergency response service for Rawalpindi, Pakistan. The available crash data include crash-specific information, vehicle, driver, spatial and temporal characteristics, roadway features, and traffic volume, which influence the motorcyclist's injury severity. A random parameters logit model with heterogeneity in means and variances was evaluated to predict critical contributory factors in helmet-wearing and non-helmet-wearing motorcyclist crashes. Model estimates suggest significant variations in the impact of explanatory variables on motorcyclists' injury severity in the case of compliance with and defiance of helmet use. For helmet-wearing motorcyclists, key factors significantly associated with increasingly severe injury and fatal injuries include young riders (below 20 years of age), female pillion riders, collisions with another motorcycle, large trucks, passenger car, drivers aged 50 years and above, and drivers being distracted while driving. In contrast, for non-helmet-wearing motorcyclists, the significant factors responsible for severe injuries and fatalities were distracted driving, the collision of two motorcycles, crashes at U-turns, weekday crashes, and drivers above 50 years of age. The impact of parameters that predict motorcyclist injury severity was found to vary dramatically over time, exhibiting statistically significant temporal instability. The results of this study can serve as potential motorcycle safety guidelines for all relevant stakeholders to improve the state of motorcycle safety in the country.

Prediction Models for Estimating Compressive Strength of Concrete Made of Manufactured Sand Using Gene Expression Programming Model.

The depletion of natural resources of river sand and its availability issues as a construction material compelled the researchers to use manufactured sand. This study investigates the compressive strength of concrete made of manufactured sand as a partial replacement of normal sand. The prediction model, i.e., gene expression programming (GEP), was used to estimate the compressive strength of manufactured sand concrete (MSC). A database comprising 275 experimental results based on 11 input variables and 1 target variable was used to train and validate the developed models. For this purpose, the compressive strength of cement, tensile strength of cement, curing age, Dmax of crushed stone, stone powder content, fineness modulus of the sand, water-to-binder ratio, water-to-cement ratio, water content, sand ratio, and slump were taken as input variables. The investigation of a varying number of genetic characteristics, such as chromosomal number, head size, and gene number, resulted in the creation of 11 alternative models (M1-M11). The M5 model outperformed other created models for the training and testing stages, with values of (4.538, 3.216, 0.919) and (4.953, 3.348, 0.906), respectively, according to the results of the accuracy evaluation parameters root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The R2 and error indices values revealed that the experimental and projected findings are in extremely close agreement. The best model has 200 chromosomes, 8 head sizes, and 3 genes. The mathematical expression achieved from the GEP model revealed that six parameters, namely the compressive and tensile strength of cement, curing period, water−binder ratio, water−cement ratio, and stone powder content contributed effectively among the 11 input variables. The sensitivity analysis showed that water−cement ratio (46.22%), curing period (25.43%), and stone powder content (13.55%) were revealed as the most influential variables, in descending order. The sensitivity of the remaining variables was recorded as w/b (11.37%) > fce (2.35%) > fct (1.35%).

Attenuation of ovalbumin-induced inflammation and lung oxidative injury in asthmatic rats by Zingiber officinale extract: combined in silico and in vivo study on antioxidant potential, STAT6 and TNF-α pathways.

In the present study we focused on the anti-asthmatic and antioxidant effects of Zingiber officinalis roscoe L. (ZO) aqueous extract. This study includes 20 adult male rats, which were grouped into four; Group I: control group; Group II: asthmatic group (Ovalbumin sensitized/challenge model, Oval group); Group III: received ovalbumin sensitized/challenge associated a dose of 207 mg/kg body weight (BW) of ZO (Oval + D1 group); Group IV: received ovalbumin sensitized/challenge associated a dose of 414 mg/k BW of ZO (Oval + D2 group). After 21 days, blood and lung samples were collected for biochemical, hematological, and histopathological analyses. The ameliorative effect of ZO phytochemical compounds was also assessed by in silico approach on transducer and activator of transcription 6 (STAT6) and tumor necrosis factor-α (TNF-α) receptors. The oxidative/antioxidative status was evaluated in the lung tissues. Our results show that ZO extract alleviated the ovalbumin-induced hematological and biochemical disruptions associated oxidative injury. In fact, white and red blood cells (WBC and RBC, respectively), aspartate aminotransaminase (ASAT), malondialdehyde (MDA), glutathione (GSH), and glutathione peroxidase (GPx) were significantly disrupted (p < 0.05) in Oval group and alleviated following ZO treatment. Besides, several histopathological features were outlined in lung tissues of Oval group. Interestingly, ZO was found to exert ameliorative effects on tissue level. In silico analyses, particularly the binding affinities, the number of H-bonds, the embedding distance and the molecular interactions of ZO phytochemical compounds with either STAT6 or TNF-α supported the in vivo results. These findings confirm the potential ethno-pharmacological effects of ZO against asthma and its associated complications.

Modelling Compression Strength of Waste PET and SCM Blended Cementitious Grout Using Hybrid of LSSVM Models.

Nowadays, concretes blended with pozzolanic additives such as fly ash (FA), silica fume (SF), slag, etc., are often used in construction practices. The utilization of pozzolanic additives and industrial by-products in concrete and grouting materials has an important role in reducing the Portland cement usage, the CO2 emissions, and disposal issues. Thus, the goal of the present work is to estimate the compressive strength (CS) of polyethylene terephthalate (PET) and two supplementary cementitious materials (SCMs), namely FA and SF, blended cementitious grouts to produce green mix. For this purpose, five hybrid least-square support vector machine (LSSVM) models were constructed using swarm intelligence algorithms, including particle swarm optimization, grey wolf optimizer, salp swarm algorithm, Harris hawks optimization, and slime mold algorithm. To construct and validate the developed hybrid models, a sum of 156 samples were generated in the lab with varying percentages of PET and SCM. To estimate the CS, five influencing parameters, namely PET, SCM, FLOW, 1-day CS (CS1D), and 7-day CS (CS7D), were considered. The performance of the developed models was assessed in terms of multiple performance indices. Based on the results, the proposed LSSVM-PSO (a hybrid model of LSSVM and particle swarm optimization) was determined to be the best performing model with R2 = 0.9708, RMSE = 0.0424, and total score = 40 in the validation phase. The results of sensitivity analysis demonstrate that all the input parameters substantially impact the 28-day CS (CS28D) of cementitious grouts. Among them, the CS7D has the most significant effect. From the experimental results, it can be deduced that PET/SCM has no detrimental impact on CS28D of cementitious grouts, making PET a viable alternative for generating sustainable and green concrete. In addition, the proposed LSSVM-PSO model can be utilized as a novel alternative for estimating the CS of cementitious grouts, which will aid engineers during the design phase of civil engineering projects.

Predicting Bond Strength between FRP Rebars and Concrete by Deploying Gene Expression Programming Model.

Rebars made of fiber-reinforced plastic (FRP) might be the future reinforcing material, replacing mild steel rebars, which are prone to corrosion. The bond characteristics of FRP rebars differ from those of mild steel rebars due to their different stress-strain behavior than mild steel. As a result, determining the bond strength (BS) qualities of FRP rebars is critical. In this work, BS data for FRP rebars was investigated, utilizing non-linear capabilities of gene expression programming (GEP) on 273 samples. The BS of FRP and concrete was considered a function of bar surface (Bs), bar diameter (db), concrete compressive strength (fc'), concrete-cover-bar-diameter ratio (c/d), and embedment-length-bar-diameter ratio (l/d). The investigation of the variable number of genetic parameters such as number of chromosomes, head size, and number of genes was undertaken such that 11 different models (M1-M11) were created. The results of accuracy evaluation parameters, namely coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) imply that the M11 model outperforms other created models for the training and testing stages, with values of (0.925, 0.751, 1.08) and (0.9285, 0.802, 1.11), respectively. The values of R2 and error indices showed that there is very close agreement between the experimental and predicted results. 30 number chromosomes, 9 head size, and 5 genes yielded the optimum model. The parametric analysis revealed that db, c/d, and l/d significantly affected the BS. The FRP rebar diameter size is greater than 10 mm, whereas a l/d ratio of more than 12 showed a considerable decrease in BS. In contrast, the rise in c/d ratio revealed second-degree increasing trend of BS.

Lactiplantibacillus plantarum-Derived Biosurfactant Attenuates Quorum Sensing-Mediated Virulence and Biofilm Formation in Pseudomonas aeruginosa and Chromobacterium violaceum.

Quorum sensing (QS) controls the expression of diverse biological traits in bacteria, including virulence factors. Any natural bioactive compound that disables the QS system is being considered as a potential strategy to prevent bacterial infection. Various biological activities of biosurfactants have been observed, including anti-QS effects. In the present study, we investigated the effectiveness of a biosurfactant derived from Lactiplantibacillus plantarum on QS-regulated virulence factors and biofilm formation in Pseudomonas aeruginosa and Chromobacterium violaceum. The structural analogues of the crude biosurfactant were identified using gas chromatography-mass spectrometry (GC-MS). Moreover, the inhibitory prospects of identified structural analogues were assessed with QS-associated CviR, LasA, and LasI ligands via in silico molecular docking analysis. An L. plantarum-derived biosurfactant showed a promising dose-dependent interference with the production of both violacein and acyl homoserine lactone (AHL) in C. violaceum. In P. aeruginosa, at a sub-MIC concentration (2.5 mg/mL), QS inhibitory activity was also demonstrated by reduction in pyocyanin (66.63%), total protease (60.95%), LasA (56.62%), and LasB elastase (51.33%) activity. The swarming motility and exopolysaccharide production were also significantly reduced in both C. violaceum (61.13%) and P. aeruginosa (53.11%). When compared with control, biofilm formation was also considerably reduced in C. violaceum (68.12%) and P. aeruginosa (59.80%). A GC-MS analysis confirmed that the crude biosurfactant derived from L. plantarum was a glycolipid type. Among all, n-hexadecanoic acid, oleic acid, and 1H-indene,1-hexadecyl-2,3-dihydro had a high affinity for CviR, LasI, and LasA, respectively. Thus, our findings suggest that the crude biosurfactant of L. plantarum can be used as a new anti-QS/antibiofilm agent against biofilm-associated pathogenesis, which warrants further investigation to uncover its therapeutic efficacy.

GEP Tree-Based Prediction Model for Interfacial Bond Strength of Externally Bonded FRP Laminates on Grooves with Concrete Prism.

Reinforced concrete structures are subjected to frequent maintenance and repairs due to steel reinforcement corrosion. Fiber-reinforced polymer (FRP) laminates are widely used for retrofitting beams, columns, joints, and slabs. This study investigated the non-linear capability of artificial intelligence (AI)-based gene expression programming (GEP) modelling to develop a mathematical relationship for estimating the interfacial bond strength (IBS) of FRP laminates on a concrete prism with grooves. The model was based on five input parameters, namely axial stiffness (Eftf), width of FRP plate (bf), concrete compressive strength (fc'), width of groove (bg), and depth of the groove (hg), and IBS was considered the target variable. Ten trials were conducted based on varying genetic parameters, namely the number of chromosomes, head size, and number of genes. The performance of the models was evaluated using the correlation coefficient (R), mean absolute error (MAE), and root mean square error (RMSE). The genetic variation revealed that optimum performance was obtained for 30 chromosomes, 11 head sizes, and 4 genes. The values of R, MAE, and RMSE were observed as 0.967, 0.782 kN, and 1.049 kN for training and 0.961, 1.027 kN, and 1.354 kN. The developed model reflected close agreement between experimental and predicted results. This implies that the developed mathematical equation was reliable in estimating IBS based on the available properties of FRPs. The sensitivity and parametric analysis showed that the axial stiffness and width of FRP are the most influential parameters in contributing to IBS.