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.

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.

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.

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.

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.

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.

Analysis of the Insulation Characteristics of Hexafluorobutene (C4H2F6) Gas and Mixture with CO2/N2 as an Alternative to SF6 for Medium-Voltage Applications

This paper investigates C4H2F6, a promising environmentally friendly insulating gas that possesses high dielectric strength and a low global warming potential. The study focuses on examining the insulation properties of C4H2F6 when combined with CO2/N2, aiming to assess its suitability as a substitute for SF6 in gas-insulated applications. Finite element analyses are performed to evaluate the field utilization factor and electric field distribution in the proposed mixture. The properties of liquefaction temperature were examined in this study to determine the optimal mixing ratio for applications that require a minimum working temperature. Extensive experimental investigations were carried out to assess the dielectric strength characteristics of the gas mixture in both uniform and quasi-uniform electric fields. It was found that pure HFO-1336mzz (E) exhibits a dielectric strength approximately 1.2–1.6 times higher than SF6. Experimental results have revealed that the insulation performance of a 30% HFO-1336mzz (E)/CO2 mixture closely resembles that of SF6, with a matching efficiency of up to 90% in a weakly uniform electric field. This remarkable performance can be attributed to a positive synergistic effect between HFO-1336mzz (E) and CO2, combined with the gas mixture’s excellent self-recoverability property. These experimental findings are further supported by finite element analysis, which confirms the observed results. The 30% HFO-1336mzz (E)/CO2 gas mixture at 0.15–0.20 MPa pressure and constant 0.6 mm air gap reveal superior insulation tolerance and less sensitivity to the electric field, confirming its promising medium-voltage engineering applications. The associated results of this research provide a critical reference for the engineering application of the alternating (AC) and direct current (DC) insulation characteristics of the HFO-1336mzz (E)/CO2 gas mixture.

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.

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.

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.

Identification of Causative agents associated with decay of Trees Twig and Orchards Die-back and their Impacts on Vessels of Citrus, Date Palm and Ficus

The present work is concerned with the studies of the organism causing wood decay of twigs and branches of citrus orchards, date palm Phoenix dactylifera L, and ficus trees. A survey for the occurrence of this disease in the main growing areas was achieved by the researchers. The following species of citrus orchards [lime (C. aurantifolia), sweet orange (C. sinensis), and mandarin (C. reticulate)] were surveyed, and so date palm and ficus trees. However, the results showed that the incidence of this disease was about 100%. Laboratory examinations data revealed mainly two fungal species causing the disease: Physalospora rhodina (P.rhodina)  and Diaporthe citri (D. citri). In addition that, both fungi, which are P. rhodina and D. citri affected the vessels of tree tissues. According to the pathogenicity test, the fungus P. rhodina caused a breakdown of parenchyma cells, and the fungus D. citri caused the darkening of the xylem.

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%).

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 (E_ft_f), width of FRP plate (b_f), concrete compressive strength (f_c′), width of groove (b_g), and depth of the groove (h_g), 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.

Kidney injury and oxidative damage alleviation by Zingiber officinale: pharmacokinetics and protective approach in a combined murine model of osteoporosis

Ginger (Zingiber officinale) is considered as a nutraceutical spice, which possesses several health promotion and benefits. This study was carried out to investigate the phyto-chemical composition, the antioxidant capacities, the drug-likeness, and pharmacokinetic properties of ginger extract on kidney injury-associated osteoporosis in rats. Phenolic and flavonoid contents were assessed by standard chemical analysis methods and HPLC. In vivo protective effect was based on the use of female rats to evaluate the effect on renal injury as a result of combined osteoporosis using biochemical markers, oxidative status, and histological analyses. Results showed that ZO contained appreciable amounts of phenolics and flavonoids and it exhibited high scavenging activity. Ovariectomy-associated corticotherapy induced severe renal injury marked by altered biochemical markers (creatinine, urea, and uric acid), reduced GFR, significative oxidative damage signs, and disrupted antioxidant status in the combined osteoporotic rats. The histopathological examination revealed structural modifications of kidney tissues. However, all these changes were reversed following the use of ZO. These results confirm the renoprotective and antioxidant potential of ginger against renal injuries in osteoporotic rats.

Enhancement of Confinement in Scaled RC Columns using Steel Fibers Extracted from Scrap Tyres

Steel fibers are widely extracted from scrap tyres, causing environmental concerns. This paper presents the use of steel fibers in variable proportions extracted from scrap tyres. The enhancement of the confinement was envisaged through the addition of steel fibers obtained from scrap tyres. The study included an experimental program for the development of constitutive material models for ordinary Portland cement (OPC) concrete and concrete with added steel fibers. A mix design was carried out for OPC, targeting a compressive strength of 3000 psi. Steel fibers were added to OPC in ratios of 1.0% to 3.0%, with an increment of 0.5%. Concrete columns, with cross-sectional dimensions of 6 × 6 inches and a length of 30 inches, were cast with both OPC and fiber-reinforced concrete. The column confinement was evaluated with a different spacing of ties (3- and 4-inch center-to-center). Compression tests on the concrete columns indicate that the addition of steel fibers to a concrete matrix results in an appreciable increase in strength and ductility. Overall, increasing the percentage of steel fibers increased the compression strength and the ductility of concrete. The maximum strain in the concrete containing 2.5% steel fibers increased by 285% as compared to the concrete containing 1% of steel fibers. An optimum percentage of 2.5% steel fibers added to the concrete resulted in a 39% increase in compressive strength, accompanied by a significant improvement in ductility. The optimum content of steel fibers, when used in confined columns, showed that confined compression strength increased with the addition of steel fibers. However, it is recommended that additional columns on the basis of the optimum steel fiber content shall be tested to evaluate their effectiveness in reducing the stirrup spacing.

Impact of chemoprophylaxis immunisation under halofantrine (CPS-HF) drug cover in Plasmodium yoelii Swiss mice malaria model

In the present study, we have investigated the role of antimalarial drug halofantrine (HF) in inducing the sterile protection against challenges with sporozoites of the live infectious Plasmodium yoelii (Killick-Kendrick, 1967) in Swiss mice malaria model. We observed that during the first to third sequential sporozoite inoculation cycles, blood-stage patency remains the same in the control and chemoprophylaxis under HF drug cover (CPS-HF) groups. However, a delayed blood-stage infection was observed during the fourth and fifth sporozoite challenges and complete sterile protection was produced following the sixth sporozoite challenge in CPS-HF mice. We also noticed a steady decline in liver stage parasite load after 3th to 6th sporozoite challenge cycle in CPS-HF mice. CPS-HF immunisation results in a significant up-regulation of pro-inflammatory cytokines (IFN-γ, TNF-α, IL-12 and iNOS) and down-regulation of anti-inflammatory cytokines (IL-10 and TGF-β) mRNA expression in hepatic mononuclear cells (HMNC) and spleen cells in the immunised CPS-HF mice (after 6th sporozoite challenge) compared to control. Overall, our study suggests that the repetitive sporozoite inoculation under HF drug treatment develops a strong immune response that confers protection against subsequent challenges with sporozoites of P. yoelii.

Recent Developments in the Removal of Dyes from Water by Starch-Based Adsorbents

Starch-based adsorbents have demonstrated excellent potential for the removal of various noxious dyes from wastewater. This review critically evaluates the recent progress in applications of starch-based adsorbents for the removal of dyes from water. The synthesis methods of starch-based composites and their effects on physicochemical characteristics of produced adsorbents are discussed. The removal of various dyes by starch-based adsorbents are described in detail, with emphasis on the effect of key parameters, adsorption mechanism and their reusability potential. The key challenges related to the synthesis and applications of starch-based adsorbents in water purification are highlighted. Based on the research gaps, recommendations for future research are made. The evaluation of starch-based adsorbents would contribute to the development of sustainable water treatment options in near future.

Experimental Investigation of the Stress–Strain Behavior and Strength Characterization of Rubberized Reinforced Concrete

Due to the rapid increase in population, the use of automobile vehicles increases day by day, which causes a considerable increase in the waste tires produced worldwide. Research studies are in progress to utilize scrap tires and waste rubber material in several fields to cater the pollution problems in a sustainable and environmentally friendly manner. In this research, the shredded waste tires were used in concrete to replace fine aggregates in different percentages. The fine aggregates in the rubberized concrete were replaced 10%, 15%, and 20% by rubber. The stress–strain behavior of the concrete models is then determined and compared with the already established analytical models, i.e., Modified Kent and Park Model, Mander’s model, and Razvi and Saatcioglu Model. A total of 12 standard concrete cylinders and 18 models of each type of concrete, i.e., normal concrete, reinforced rubberized concrete with 10%, 15%, and 20% addition of rubber, were fabricated. Specimens fabricated in each replacement of rubber were laterally confined, employing 3 in (76 mm) and 6 in (152 mm) c/c tie spacing. The model and cylinders were subjected to uni-axial compression tests using Universal Testing Machine (UTM). The drop in compressive strength, stress–strain constitutive law, strain limits, and overall behavior of the rubberized reinforced concrete were explored experimentally. The results were then compared with the analytical results of the established models. The research can help explore the possible future for the use of rubberized concrete for the potential application as a structural material.

Performance Evaluation of Cementitious Composites Incorporating Nano Graphite Platelets as Additive Carbon Material

Nano graphite platelets (NGPs) belong to the carbon family and have a huge impact on the construction industry. NGPs are used as multi-functional fillers and have the potential to develop reinforcing within cementitious composites. In this paper, NGPs were incorporated in cementitious composites to investigate the effects of NGPs on the fresh, mechanical, durability, and microstructural properties of concrete. Five mixes were prepared with intrusion of NGPs (0%, 0.5%, 1.5%, 3%, and 5% by weight of cement). The properties studied involved workability, air content, hardened density, compressive strength, tensile strength, flexural strength, sorptivity, ultrasonic pulse velocity (UPV), water absorption, and external sulfate attack. The workability and percent air content decrease by 22.5% and 33.8%, respectively, for concrete with 5% NGPs compared to the control mix. The specimens containing 5% of NGPs revealed the hardened density, compressive, tensile, and flexural strength to increase by 11.4%, 38.5%, 31.6%, and 44.34%, respectively, compared to the control mix. The results revealed that the incorporation of 5%NGPs in cementitious composites reduces the sorptivity and water absorption by 32.2% and 73.9%, respectively, whereas, it increases the UPV value by 7.5% compared to the control mix. Furthermore, the incorporation of NGPs provided better resistance against external sulfate attacks. SEM–EDX spectroscopy was carried out to investigate its microstructural analysis.

Inhibition of Bacterial Adhesion and Antibiofilm Activities of a Glycolipid Biosurfactant from Lactobacillus rhamnosus with Its Physicochemical and Functional Properties

Biosurfactants derived from different microbes are an alternative to chemical surfactants, which have broad applications in food, oil, biodegradation, cosmetic, agriculture, pesticide and medicine/pharmaceutical industries. This is due to their environmentally friendly, biocompatible, biodegradable, effectiveness to work under various environmental conditions and non-toxic nature. Lactic acid bacteria (LAB)-derived glycolipid biosurfactants can play a major role in preventing bacterial attachment, biofilm eradication and related infections in various clinical settings and industries. Hence, it is important to explore and identify the novel molecule/method for the treatment of biofilms of pathogenic bacteria. In the present study, a probiotic Lactobacillus rhamnosus (L. rhamnosus) strain was isolated from human breast milk. Firstly, its ability to produce biosurfactants, and its physicochemical and functional properties (critical micelle concentration (CMC), reduction in surface tension, emulsification index (% EI24), etc.) were evaluated. Secondly, inhibition of bacterial adhesion and biofilm eradication by cell-bound biosurfactants from L. rhamnosus was performed against various biofilm-forming pathogens (B. subtilis, P. aeruginosa, S. aureus and E. coli). Finally, bacterial cell damage, viability of cells within the biofilm, exopolysaccharide (EPS) production and identification of the structural analogues of the crude biosurfactant via gas chromatography-mass spectrometry (GC-MS) analysis were also evaluated. As a result, L. rhamnosus was found to produce 4.32 ± 0.19 g/L biosurfactant that displayed a CMC of 3.0 g/L and reduced the surface tension from 71.12 ± 0.73 mN/m to 41.76 ± 0.60 mN/m. L. rhamnosus cell-bound crude biosurfactant was found to be effective against all the tested bacterial pathogens. It displayed potent anti-adhesion and antibiofilm ability by inhibiting the bacterial attachment to surfaces, leading to the disruption of biofilm formation by altering the integrity and viability of bacterial cells within biofilms. Our results also confirm the ability of the L. rhamnosus cell-bound-derived biosurfactant to damage the architecture of the biofilm matrix, as a result of the reduced total EPS content. Our findings may be further explored as a green alternative/approach to chemically synthesized toxic antibiofilm agents for controlling bacterial adhesion and biofilm eradication.

Functional and Structural Characterization of Pediococcus pentosaceus-Derived Biosurfactant and Its Biomedical Potential against Bacterial Adhesion, Quorum Sensing, and Biofilm Formation

Biosurfactants are surface-active molecules of microbial origin and alternatives to synthetic surfactants with various applications. Due to their environmental-friendliness, biocompatibility, biodegradability, effectiveness to work under various environmental conditions, and non-toxic nature, they have been recently recognized as potential agents with therapeutic and commercial importance. The biosurfactant produced by various probiotic lactic acid bacteria (LAB) has enormous applications in different fields. Thus, in vitro assessment of biofilm development prevention or disruption by natural biosurfactants derived from probiotic LAB is a plausible approach that can lead to the discovery of novel antimicrobials. Primarily, this study aims to isolate, screen, and characterize the functional and biomedical potential of biosurfactant synthesized by probiotic LAB Pediococcus pentosaceus (P. pentosaceus). Characterization consists of the assessment of critical micelle concentration (CMC), reduction in surface tension, and emulsification index (% EI24). Evaluation of antibacterial, antibiofilm, anti-QS, and anti-adhesive activities of cell-bound biosurfactants were carried out against different human pathogenic bacteria (B. subtilis, P. aeruginosa, S. aureus, and E. coli). Moreover, bacterial cell damage, viability of cells within the biofilm, and exopolysaccharide (EPS) production were also evaluated. As a result, P. pentosaceus was found to produce 4.75 ± 0.17 g/L biosurfactant, which displayed a CMC of 2.4 ± 0.68 g/L and reduced the surface tension from 71.11 ± 1.12 mN/m to 38.18 ± 0.58 mN/m. P. pentosaceus cells bound to the crude biosurfactant were found to be effective against all tested bacterial pathogens. It exhibited an anti-adhesion ability and impeded the architecture of the biofilm matrix by affecting the viability and integrity of bacterial cells within biofilms and reducing the total EPS content. Furthermore, the crude biosurfactant derived from P. pentosaceus was structurally characterized as a lipoprotein by GC-MS analysis, which confirms the presence of lipids and proteins. Thus, our findings represent the potent anti-adhesion and antibiofilm potential of P. pentosaceus crude biosurfactant for the first time, which may be explored further as an alternative to antibiotics or chemically synthesized toxic antibiofilm agents.

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP-BWM Model

Frequent lane changes cause serious traffic safety concerns for road users. The detection and categorization of significant factors affecting frequent lane changing could help to reduce frequent lane-changing risk. The main objective of this research study is to assess and prioritize the significant factors and sub-factors affecting frequent lane changing designed in a three-level hierarchical structure. As a multi-criteria decision-making methodology (MCDM), this study utilizes the analytic hierarchy process (AHP) combined with the best–worst method (BWM) to compare and quantify the specified factors. To illustrate the applicability of the proposed model, a real-life decision-making problem is considered, prioritizing the most significant factors affecting lane changing based on the driver’s responses on a designated questionnaire survey. The proposed model observed fewer pairwise comparisons (PCs) with more consistent and reliable results than the conventional AHP. For level 1 of the three-level hierarchical structure, the AHP–BWM model results show “traffic characteristics” (0.5148) as the most significant factor affecting frequent lane changing, followed by “human” (0.2134), as second-ranked factor. For level 2, “traffic volume” (0.1771) was observed as the most significant factor, followed by “speed” (0.1521). For level 3, the model results show “average speed” (0.0783) as first-rank factor, followed by the factor “rural” (0.0764), as compared to other specified factors. The proposed integrated approach could help decision-makers to focus on highlighted significant factors affecting frequent lane-changing to improve road safety.

830 A Case of Colo-Colonic Intussusception Secondary to A Large Lipoma in An Adult

Colonic lipomas are benign tumours, most commonly in the right colon or caecum, usually detected incidentally at colonoscopy and are often asymptomatic not requiring treatment. Lipomas leading to intussusception have previously been described in case reports, but it remains a rare occurrence, no specific incidence data has been documented. We present the case of a patient with a 7cm colonic lipoma that developed an intussusception.

This patient suffered non-specific pulling pain along the right and upper abdomen for many years. A distal ascending colonic lipoma was identified, on repeated imaging and colonoscopy and biopsied. It was concluded that the abdominal pain was due to gallstones, diverticulitis and adhesions from previous pelvic surgery. In early December 2020, the patient was reviewed and listed for elective cholecystectomy. Later the same month, the patient was admitted with severe abdominal pain, watery and bloody diarrhoea. CT scan showed the colonic lipoma had acted as the lead point for an intussusception, with the lipoma and surrounding colon having intussuscepted into the transverse colon. Patient had an open right hemicolectomy and anastomosis for colo-colic intussusception secondary to the lipoma. Subsequently, the patient developed anastomotic breakdown requiring relook laparotomy with resection of ileo-colic anastomosis and end ileostomy formation.

Adults presenting with intussusception is rare and associated with nonspecific signs and symptoms. Variability in clinical presentation highlights the need for a low index of suspicion in people with known colonic masses. In addition, early surgical intervention should be considered in masses &gt;4cm as previously suggested in the literature.

Molecular Docking and Dynamics Simulation Revealed Ivermectin as Potential Drug against Schistosoma-Associated Bladder Cancer Targeting Protein Signaling: Computational Drug Repositioning Approach

Urogenital schistosomiasis is caused by Schistosoma haematobium (S. haematobium) infection, which has been linked to the development of bladder cancer. In this study, three repurposing drugs, ivermectin, arteether and praziquantel, were screened to find the potent drug-repurposing candidate against the Schistosoma-associated bladder cancer (SABC) in humans by using computational methods. The biology of most glutathione S-transferases (GSTs) proteins and vascular endothelial growth factor (VEGF) is complex and multifaceted, according to recent evidence, and these proteins actively participate in many tumorigenic processes such as cell proliferation, cell survival and drug resistance. The VEGF and GSTs are now widely acknowledged as an important target for antitumor therapy. Thus, in this present study, ivermectin displayed promising inhibition of bladder cancer cells via targeting VEGF and GSTs signaling. Moreover, molecular docking and molecular dynamics (MD) simulation analysis revealed that ivermectin efficiently targeted the binding pockets of VEGF receptor proteins and possessed stable dynamics behavior at binding sites. Therefore, we proposed here that these compounds must be tested experimentally against VEGF and GST signaling in order to control SABC. Our study lies within the idea of discovering repurposing drugs as inhibitors against the different types of human cancers by targeting essential pathways in order to accelerate the drug development cycle.

A New Pedestrian Crossing Level of Service (PCLOS) Method for Promoting Safe Pedestrian Crossing in Urban Areas

Crosswalks are critical locations in the urban transport network that need to be designed carefully as pedestrians are directly exposed to vehicular traffic. Although various methods are available to evaluate the level of service (LOS) at pedestrian crossings, pedestrian crossing facilities are frequently ignored in assessing crosswalk conditions. This study attempts to provide a comprehensive framework for evaluating crosswalks based on several essential indicators adopted from different guidelines. A new pedestrian crossing level of service (PCLOS) method is introduced in this research, with an aimto promote safe and sustainable operations at such locations. The new PCLOS employs an analytical point system to compare existing street crossing conditions to the guidelines' standards, taking into account the scores and coefficients of the indicators. The quantitative scores and coefficients of indicators are assigned based on field observations and respondent opinions. The method was tested to evaluate four pedestrian crosswalks in the city of Putrajaya, Malaysia. A total of 17 indicators were selected for the study after a comprehensive literature review. Survey results show that the provision of a zebra crossing was the most critical indicator at the pedestrian crossings, while drainage near crosswalks was regarded as the least important. Four indicators had a coefficient value above 4, indicating that these are very critical pedestrian crossing facilities and significantly impact the calculation of LOS for pedestrian crossings. Four crosswalks were evaluated using the proposed method in Putrajaya, Malaysia. The crosswalk at the Ministry of Domestic Trade Putrajaya got the "PCLOS A". In contrast, the midblock crossing in front of the Putrajaya Corporation was graded "PCLOS C". While the remaining two crosswalks were graded as "PCLOS B" crosswalks. Based on the assigned PCLOS grade, the proposed method could also assist in identifying current design and operation issues in existing pedestrian crossings and providing sound policy recommendations for improvements to ensure pedestrian safety.

Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study

A better understanding of injury severity risk factors is fundamental to improving crash prediction and effective implementation of appropriate mitigation strategies. Traditional statistical models widely used in this regard have predefined correlation and intrinsic assumptions, which, if flouted, may yield biased predictions. The present study investigates the possibility of using the eXtreme Gradient Boosting (XGBoost) model compared with few traditional machine learning algorithms (logistic regression, random forest, and decision tree) for crash injury severity analysis. The data used in this study was obtained from the traffic safety department, ministry of transport (MOT) at Riyadh, KSA, and contains 13,546 motor vehicle collisions along 15 rural highways reported between January 2017 to December 2019. Empirical results obtained using k-fold (k = 10) for various performance metrics showed that the XGBoost technique outperformed other models in terms of the collective predictive performance as well as injury severity individual class accuracies. XGBoost feature importance analysis indicated that collision type, weather status, road surface conditions, on-site damage type, lighting conditions, and vehicle type are the few sensitive variables in predicting the crash injury severity outcome. Finally, a comparative analysis of XGBoost based on different performance statistics showed that our model outperformed most previous studies.

Deciphering the Molecular Mechanism Responsible for Efficiently Inhibiting Metastasis of Human Non-Small Cell Lung and Colorectal Cancer Cells Targeting the Matrix Metalloproteinases by Selaginella repanda

Selaginella species are known to have antimicrobial, antioxidant, anti-inflammatory, anti-diabetic as well as anticancer effects. However, no study has examined the cytotoxic and anti-metastatic efficacy of Selaginella repanda (S. repanda) to date. Therefore, this study aimed to evaluate the potential anti-metastatic properties of ethanol crude extract of S. repanda in human non-small-cell lung (A-549) and colorectal cancer (HCT-116) cells with possible mechanisms. Effect of S. repanda crude extract on the growth, adhesion, migration and invasion of the A-549 and HCT-116 were investigated. We demonstrated that S. repanda crude extract inhibited cell growth of metastatic cells in a dose and time dependent manner. Incubation of A-549 and HCT-116 cells with 100-500 µg/mL of S. repanda crude extract significantly inhibited cell adhesion to gelatin coated surface. In the migration and invasion assay, S. repanda crude extract also significantly inhibited cellular migration and invasion in both A-549 and HCT-116 cells. Moreover, reverse transcription-polymerase chain reaction, and real-time PCR (RT-PCR) analysis revealed that the activity and mRNA level of matrix metalloproteinase-9 (MMP-9), matrix metalloproteinase-2 (MMP-2) and membrane type 1-matrix metalloproteinase (MT1-MMP) were inhibited. While the activity of tissue inhibitor matrix metalloproteinase 1 (TIMP-1); an inhibitor of MMPs was stimulated by S. repanda crude extract in a concentration-dependent manner. Therefore, the present study not only indicated the inhibition of motility and invasion of malignant cells by S. repanda, but also revealed that such effects were likely associated with the decrease in MMP-2/-9 expression of both A-549 and HCT-116 cells. This further suggests that S. repanda could be used as a potential source of anti-metastasis agent in pharmaceutical development for cancer therapy.

A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw

Motorcycles and motorcyclists have a variety of attributes that have been found to be a potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road Users (VRUs) that include pedestrians, bicyclists, cycle-rickshaw occupants, and motorcyclists constitute by far the highest share of road traffic accidents in developing countries. Motorized three-wheeled Rickshaws (3W-MR) is a popular public transport mode in almost all Pakistani cities and is used primarily for short trips to carry passengers and small-scale goods movement. Despite being an important mode of public transport in the developing world, little work has been done to understand the factors affecting the injury severity of three-wheeled motorized vehicles. Crash injury severity prediction is a promising research target in traffic safety. Traditional statistical models have underlying assumptions and predefined associations, which can yield misleading results if flouted. Machine learning(ML) is an emerging non-parametric method that can effectively capture the non-linear effects of both continuous and discrete variables without prior assumptions and achieve better prediction accuracy. This research analyzed injury severity of three-wheeled motorized rickshaws (3W-MR) using various machine learning-based identification algorithms, i.e., Decision jungle (DJ), Random Forest (RF), and Decision Tree (DT). Three years of crash data (from 2017 to 2019) was collected from Provincial Emergency Response Service RESCUE 1122 for Rawalpindi city, Pakistan. A total of 2,743 3W-MR crashes were reported during the study period that resulted in 258 fatalities. The predictive performance of proposed ML models was assessed using several evaluation metrics such as overall accuracy, macro-average precision, macro-average recall, and geometric means of individual class accuracies. Results revealed that DJ with an overall accuracy of 83.7 % outperformed the DT and RF-based on a stratified 10-fold cross-validation approach. Finally, Spearman correlation analysis showed that factors such as the lighting condition, crashes involving young drivers (aged 20-30 years), facilities with high-speed limits (over 60 mph), weekday, off-peak, and shiny weather conditions were more likely to worsen injury severity of 3W-MR crashes. The outcomes of this study could provide necessary and essential guidance to road safety agencies, particularly in the study area, for proactive implementation of appropriate countermeasures to curb road safety issues pertaining to three-wheeled motorized vehicles.

Thymic Stromal Lymphopoietin (TSLP) gene variant rs1837253 is significantly associated with Asthma prevalence in Pakistani Pashtun women

Asthma is a chronic inflammatory disease of the airways characterized by airway hyperresponsiveness and remodeling. Thymic stromal lymphopoietin (TSLP), a member of the interleukin-2 family of cytokines, is produced by activated lung and intestinal epithelial cells, mast, and other immune cells. Population-based studies identified associations between SNPs in the TSLP promoter region and asthma pathogenesis. In this study, we analyzed the genotypic association of TSLP rs1837253 with asthma predisposition in the Pashtun population of Khyber Pakhtunkhwa, Pakistan. Target DNA sequence of 250 asthmatics and an equal number of healthy individuals was PCR amplified, and allelic determination was performed by Sanger sequencing. Statistical analysis was conducted using chi-square tests and logistic regression analysis. Homozygous T/T genotype was frequent in the asthmatic subjects with a statistically significant level (P<0.05). Genetic models, including recessive, dominant, co-dominant, over-dominant, and additive were tested while adjusting allele frequencies with covariates (gender and age). Combined C/T and T/T individuals had higher odds ratios of 3.00, 1.91, and 1.73 in co-dominant, dominant, and additive models with statistically significant P-values of 0.029*, 0.022*, and 0.02*, respectively. T allele of rs1837253 was associated with increased susceptibility to asthma among Pashtuns, particularly in females, and we corroborate rs1837253 as a SNP of interest with a potential functional role.

Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study

Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pedestrians, and property. This study is aimed to investigate different traffic violations (overspeeding, wrong-way driving, illegal parking, non-compliance traffic control devices, etc.) using spatial analysis and different machine learning methods. Georeferenced violation data along two expressways (S308 and S219) for the year 2016 was obtained from the traffic police department, in the city of Luzhou, China. Detailed descriptive analysis of the data showed that wrong-way driving was the most common violation type observed. Inverse Distance Weighted (IDW) interpolation in the ArcMap Geographic Information System (GIS) was used to develop violation hotspots zones to guide on efficient use of limited resources during the treatment of high-risk sites. Lastly, a systematic Machine Learning (ML) framework, such as K Nearest Neighbors (KNN) models (using k = 3, 5, 7, 10, and 12), support vector machine (SVM), and CN2 Rule Inducer, was utilized for classification and prediction of each violation type as a function of several explanatory variables. The predictive performance of proposed ML models was examined using different evaluation metrics, such as Area Under the Curve (AUC), F-score, precision, recall, specificity, and run time. The results also showed that the KNN model with k = 7 using manhattan evaluation had an accuracy of 99% and outperformed the SVM and CN2 Rule Inducer. The outcome of this study could provide the practitioners and decision-makers with essential insights for appropriate engineering and traffic control measures to improve the safety of road-users.

Predicting Risky and Aggressive Driving Behavior among Taxi Drivers: Do Spatio-Temporal Attributes Matter?

Risky and aggressive driving maneuvers are considered a significant indicator for traffic accident occurrence as well as they aggravate their severity. Traffic violations caused by such uncivilized driving behavior is a global issue. Studies in existing literature have used statistical analysis methods to explore key contributing factors toward aggressive driving and traffic violations. However, such methods are unable to capture latent correlations among predictor variables, and they also suffer from low prediction accuracies. This study aimed to comprehensively investigate different traffic violations using spatial analysis and machine learning methods in the city of Luzhou, China. Violations committed by taxi drivers are the focus of the current study since they constitute a significant proportion of total violations reported in the city. Georeferenced violation data for the year 2016 was obtained from the traffic police department. Detailed descriptive analysis is presented to summarize key statistics about various violation types. Results revealed that over-speeding was the most prevalent violation type observed in the study area. Frequency-based nearest neighborhood cluster methods in Arc map Geographic Information System (GIS) were used to develop hotspot maps for different violation types that are vital for prioritizing and conducting treatment alternatives efficiently. Finally, different machine learning (ML) methods, including decision tree, AdaBoost with a base estimator decision tree, and stack model, were employed to predict and classify each violation type. The proposed methods were compared based on different evaluation metrics like accuracy, F-1 measure, specificity, and log loss. Prediction results demonstrated the adequacy and robustness of proposed machine learning (ML) methods. However, a detailed comparative analysis showed that the stack model outperformed other models in terms of proposed evaluation metrics.

A novel nonsense mutation in the STS gene in a Pakistani family with X-linked recessive ichthyosis: including a very rare case of two homozygous female patients

Background

X-linked ichthyosis (XLI; OMIM# 308100) is a recessive keratinization disorder characterized by the presence of dark brown, polygonal, adherent scales on different parts of the body surface. It almost exclusively affects males and the estimated prevalence ranges from 1:2000–6000 in males worldwide. Extracutaneous manifestations are frequent including corneal opacities, cryptorchidism, neuropsychiatric symptoms or others. Up to 90% of XLI cases are caused by recurrent hemizygous microdeletion encompassing entire STS gene on chromosome Xp22.3, while only a minority of patients shows partial deletions or loss of function point mutations in STS. Larger deletions also involving contiguous genes are identified in syndromic patients.

Methods

Here, we report clinical and genetic findings of a large Pakistani family having 16 affected individuals including 2 females with XLI. Molecular karyotyping and direct DNA sequencing of coding region of the STS gene was performed.

Results

The clinical manifestations in affected individuals involved generalized dryness and scaling of the skin with polygonal, dark scales of the skin on scalp, trunk, limbs, and neck while sparing face, palms and soles. There were no associated extra-cutaneous features such as short stature, cryptorchidism, photophobia, corneal opacities, male baldness, and behavioral, cognitive, or neurological phenotypes including intellectual disability, autism or attention deficit hyperactivity disorder. Molecular karyotyping was normal and no copy number variation was found. Sanger sequencing identified a novel hemizygous nonsense mutation (c.287G > A; p.W96*), in exon 4 of STS gene in all affected male individuals. In addition, two XLI affected females in the family were found to be homozygous for the identified variant.

Conclusions

This study is useful for understanding the genetic basis of XLI in the patients studied, for extending the known mutational spectrum of STS, diagnosis of female carriers and for further application of mutation screening in the genetic counseling of this family.

Short Term Traffic State Prediction via Hyperparameter Optimization Based Classifiers

Short-term traffic state prediction has become an integral component of an advanced traveler information system (ATIS) in intelligent transportation systems (ITS). Accurate modeling and short-term traffic prediction are quite challenging due to its intricate characteristics, stochastic, and dynamic traffic processes. Existing works in this area follow different modeling approaches that are focused to fit speed, density, or the volume data. However, the accuracy of such modeling approaches has been frequently questioned, thereby traffic state prediction over the short-term from such methods inflicts an overfitting issue. We address this issue to accurately model short-term future traffic state prediction using state-of-the-art models via hyperparameter optimization. To do so, we focused on different machine learning classifiers such as local deep support vector machine (LD-SVM), decision jungles, multi-layers perceptron (MLP), and CN2 rule induction. Moreover, traffic states are evaluated using traffic attributes such as level of service (LOS) horizons and simple if–then rules at different time intervals. Our findings show that hyperparameter optimization via random sweep yielded superior results. The overall prediction performances obtained an average improvement by over 95%, such that the decision jungle and LD-SVM achieved an accuracy of 0.982 and 0.975, respectively. The experimental results show the robustness and superior performances of decision jungles (DJ) over other methods.

A prospective study of tea drinking temperature and risk of esophageal squamous cell carcinoma

Previous studies have reported an association between hot tea drinking and risk of esophageal cancer, but no study has examined this association using prospectively and objectively measured tea drinking temperature. We examined the association of tea drinking temperature, measured both objectively and subjectively at study baseline, with future risk of esophageal squamous cell carcinoma (ESCC) in a prospective study. We measured tea drinking temperature using validated methods and collected data on several other tea drinking habits and potential confounders of interest at baseline in the Golestan Cohort Study, a population-based prospective study of 50,045 individuals aged 40-75 years, established in 2004-2008 in northeastern Iran. Study participants were followed-up for a median duration of 10.1 years (505,865 person-years). During 2004-2017, 317 new cases of ESCC were identified. The objectively measured tea temperature (HR 1.41, 95% CI 1.10-1.81; for ≥60°C vs. <60°C), reported preference for very hot tea drinking (HR 2.41, 95% CI 1.27-4.56; for "very hot" vs. "cold/lukewarm"), and reported shorter time from pouring tea to drinking (HR 1.51, 95% CI 1.01-2.26; for <2 vs. ≥6 min) were all associated with ESCC risk. In analysis of the combined effects of measured temperature and amount, compared to those who drank less than 700 ml of tea/day at <60°C, drinking 700 mL/day or more at a higher-temperature (≥60°C) was consistently associated with an about 90% increase in ESCC risk. Our results substantially strengthen the existing evidence supporting an association between hot beverage drinking and ESCC.

The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies

Road traffic crashes (RTCs) are one of the most critical public health problems worldwide. The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per 100,000 people) due to RTCs in the Kingdom of Saudi Arabia (KSA) has increased from 17.4 to 27.4 over the last decade, which is an alarming situation. This paper presents an overview of RTCs in the Eastern Province, KSA, from 2009 to 2016. Key descriptive statistics for spatial and temporal distribution of crashes are presented. Statistics from the present study suggest that the year 2012 witnessed the highest number of crashes, and that the region Al-Ahsa had a significantly higher proportion of total crashes. It was concluded that the fatality rate for the province was 25.6, and the mean accident to injury ratio was 8:4. These numbers are substantially higher compared to developed countries and the neighboring Gulf states. Spatial distribution of crashes indicated that a large proportion of severe crashes occurred outside the city centers along urban highways. Logistic regression models were developed to predict crash severity. Model estimation analysis revealed that crash severity can be attributed to several significant factors including driver attributes (such as sleep, distraction, overspeeding), crash characteristics (such as sudden deviation from the lane, or collisions with other moving vehicles, road fences, pedestrians, or motorcyclists), and rainy weather conditions. After critical analysis of existing safety and infrastructure situations, various suitable crash prevention and mitigation strategies, for example, traffic enforcement, traffic calming measures, safety education programs, and coordination of key stakeholders, have been proposed.

Predictive value of IL-28B rs12979860 variants for peg-IFN, sofosbuvir plus ribavirin treatment of HCV infection in Pakistani population

AIM

The correlation of IL28-B genetic variants (rs12979860) with combinational therapy (peg-interferon, sofosbuvir plus ribavirin) of hepatitis C virus infection were studied in 154 chronic hepatitis C patients.

METHODS & RESULTS

The sustained virological response for efficient antiviral regimen was achieved in 75.32% treated individuals. Three genotypes of rs12979860 (CC, CT and TT) were compared both in sustained virological response and nonresponders groups (p = 0.25, p ≤ 0.001, p = 0.10, respectively). CT genotype demonstrated a significant correlation (p ≤ 0.001) in both groups with higher positive predictive value (81.55%).

CONCLUSION

IL28 polymorphism and positive predictive value may be considered as the markers for the evaluation of the effectiveness of the treatment regimen. Further clinical trials are recommended to verify the role of IL28-B in hepatitis C virus treatment.

Correlation of IL28B rs12979860 genotype and gender with spontaneous clearance of HCV infection: a Pakistani cross-section study

AIM

There is a strong correlation of IL28B rs12979860 genetic variations and gender with spontaneous clearance of hepatitis C virus (HCV) infection.

MATERIALS & METHODS

HCV-infected subjects were categorized into HCV spontaneous clearance (SC) group and chronic hepatitis C (CHC) group on the basis of anti-HCV antibodies and HCV RNA level and follow-up of 6 months. 35 subjects were classified in SC group and 165 subjects were classified in CHC group. IL28B rs12979860 genotypes were determined by allele-specific PCR.

RESULTS & CONCLUSION

Multinominal logistic regression analyses revealed that both genders favor IL28B rs12979860 CT genotype (OR: 4.80; CI: 2.22-10.35; p = 0.0005) and (OR: 3.47; CI: 1.63-7.43; p = 0.001) for male and female, respectively, are significant in spontaneous clearance of HCV infection.

Microwave-assisted synthesis and in vitro osteogenic analysis of novel bioactive glass fibers for biomedical and dental applications

Glass fiber-based materials have gained interest for use in biomedical and dental applications. The aim of this study was to make E-glass fiber bioactive by a novel method using the microwave irradiation technique. Industrial E-glass fibers were used after surface activation with the hydrolysis method. The ratio of calcium and phosphorous precursors was set at 1.67. After maintaining the pH of the calcium solution, E-glass fibers in two ratios, i.e. 30% (nHA/E30) and 50% (nHA/E50) wt/wt, were added. The phosphorous precursor was added later and the solution was irradiated in a microwave to obtain nano-hydroxyapatite (nHA) particles on E-glass fibers. The structural, physical and in vitro biocompatibility analyses of the resulting materials were conducted. The expression of osteopontin (OPN) and collagen (Col) type 1 was measured by reverse transcription polymerase chain reaction (RT-PCR) and comparison was made between all the groups. Fourier transform infrared spectroscopy and x-ray diffraction showed characteristic peaks of nHA, and a change in the peak intensities was observed with an increase in the concentration of E-glass fibers. Scanning electron microscopic (SEM) images confirmed the homogenous adhesion of nHA spherical particles all over the fibers. Cell viability with mesenchymal stem cells showed growth, proliferation, and adhesion. All the materials were able to upregulate the expression of the OPN and Col, where gene expression was highest in nHA followed by nHA/E30 and nHA/E50. The bioactive glass fibers were synthesized in the shortest time and showed osteogenic properties. These materials have the potential for use in bone tissue engineering, dental prosthesis, and tooth restoration.

Eugenia jambolana extract reduces the systemic exposure of Sitagliptin and improves conditions associated with diabetes: A pharmacokinetic and a pharmacodynamic herb-drug interaction study

Eugenia jambolana (EJ) is an Indian traditional herb widely used for the treatment of diabetes mellitus. This herb is globally marketed as single or multi herb formulations. Many diabetes patients consume EJ extract oral hypoglycemic drugs together. This calls for a need to assess risks versus benefit of this co-administration.

In present investigation, pharmacodynamic and pharmacokinetic interactions of aqueous extract of EJ seeds at the dose of 400 mg/kg are studied with 10 mg/kg of oral hypoglycaemic drug sitagliptin (SITA) by co-administrating them for 28 days in streptozotocin (STZ) induced diabetic rats. The pharmacokinetic parameters of SITA were determined using HPLC-ESI-MS/MS and it was found that the combination treatment reduces the systemic exposure of SITA by showing 38.70% reduction in concentration maximum (Cmax) and 22.40% reduction in area under curve (AUC). Despite low levels of SITA, the combination demonstrated a significant reduction in blood glucose level when compared with individual drug and individual extract administered groups during pharmacodynamic study. In addition, the liver function, the kidney function and the lipid parameters were found to be significantly improved and beneficial effects were found with respect to food intake and water intake and urine output in case of combination treatment groups when compared with individual treatment groups. Histopathological examination of pancreatic tissue suggests its significant recovery of having normal acinus with better cell protection in combination treatment. In conclusion, the combination treatment demonstrated reduced systemic exposure of SITA without compromising on its antihyperglycemic activity and improvement in conditions associated with diabetes.

Users’ perceptions of e-learning environments and services effectiveness

Purpose

E-learning environments and services (ELES) adoption and success rates challenge ELES designers, practitioners and organisations. Enterprise decision makers continue to seek effective instruments in launching such systems. The purpose of this paper is to understand users’ perceptions of ELES effectiveness and develop a theoretical framework which improves understanding of success factors for adoption.

Design/methodology/approach

Grounded theory method is used to reflect on the relationships between changing users’ requirements and expectations, technological advances and ELES effectiveness models. A longitudinal study collecting data from social media blogs over four years was authenticated based on the context evaluation, language structure and conversational constructs.

Findings

Identification of a new core dimension named “Concept Functionality” which can be used to understand the relationships between e-learning effectiveness factors including the relationships with other domains such as security. The findings are also used to validate major existing models for the success of ELES.

Practical implications

The new framework potentially improves system design process in the fields of education technology, enterprise systems, etc.

Originality/value

Concept functionality dimension can offer more insights to understand ELES effectiveness and further improve system design process in a variety of domains including enterprise systems, process modelling and education technology.

A survey of ward round practice

Aims and Method

A postal questionnaire was sent to consultant psychiatrists in the West Midlands to establish their current ward round practice. This questionnaire addressed ward round etiquette, practical issues and educational function. Consultants received only one mailing.

Results

A total of 96 (out of 139) consultants replied (69% response rate). The majority of consultants saw patients on the ward round (97%) and all consultants introduced both themselves and team members to the patient; 72% explained the purpose of the ward round. A median of seven professionals attended the ward round with psychology (6.5%) and pharmacy services (0%) being underrepresented. When consultants added comments, the recurrent themes were that ward rounds were an effective use of professional time but were often daunting for patients.

Clinical Implications

Our results indicate some uniformity in the conduct of ward rounds. The lack of representation at ward rounds for certain professional groups may adversely affect the range of opinions and therapies for patients. Changes could be made to incorporate the views of users, which would make ward rounds more productive for users and professionals.