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Abstract This research aimed to enhance emotional awareness and engender empathy among primary school students in Pakistan through education, ultimately fostering emotional regulation and preventing disruptive behaviors. While emotional intelligence (EI) is increasingly recognized as a vital component in counter-terrorism efforts, it is seldom emphasized by young primary school students. Research suggests that educational programs based on videos and cartoons can help children retain information effectively over time. Therefore, an educational program was designed around a video/animated cartoon series focusing on EI themes of developing empathy and emotional awareness. This program included teaching aids, worksheets, and activity-based learning. It was conducted using a mixed methods approach within a quasi-experimental design in two primary schools in Pakistan’s Rawalpindi/Islamabad region. Pre- and post-test assessments revealed that students initially lacked awareness of core EI concepts and had limited prior knowledge of empathy. However, significant improvements were observed in their post-test scores across all EI-related areas. The findings suggest that incorporating EI training into school curricula could help nurture emotional resilience and mitigate extremist tendencies among children in the future.

Abstract Introduction The Medication Home Delivery (MHD) service from community pharmacies involves the safe and efficient delivery of pharmaceuticals (prescription and non-prescription medications), and health products directly to the patient’s/consumer’s home. There are several issues encountered by the users of the MHD service that have an impact on their satisfaction with the service. The study aimed to assess the public’s perceptions of the MHD service in the United Arab Emirates (UAE), their willingness to utilize it, and the practical use of the service. Method A cross-sectional exploratory study was conducted in the UAE using a validated online survey. The inclusion criteria were adults residing in the UAE. Statistical analysis was performed to identify the association between the variables, the service use, and the level of service efficiency. Results A total of 556 participants filled out the survey, with 69.4% of them using the service. The majority of participants were females (75.9%) and aged less than 40 years old (71.6%). Three variables showed a statistically significant association with the use of the MHD service (P

Locusts and grasshoppers (Orthoptera: Acrididae) are pests of agricultural importance, devastating crops and pastures. This group includes hundreds of pest species and affects the livelihoods of one in every ten people worldwide. Their outbreaks can be chronic or episodic, with alternating periods of invasion and recession. Here, we review the natural enemies of locusts and grasshoppers in both their native and invaded ranges across the globe to assess the need for their conservation and maintenance as part of the natural suppression of outbreaks and to augment outbreak suppression as potential biological control agents. More than 70 natural enemies have been reported to attack locusts and grasshoppers, including entomopathogenic fungi, bacteria, nematodes, predatory insects, birds, reptiles, and mammals. Particular attention is given to the well-studied species of locusts and grasshoppers for which more information is available and to natural enemies in the locust-affected countries as part of the recent trend of looking for indigenous natural enemies. Such organisms can play a vital role in integrated pest management strategies for locusts and grasshoppers, particularly entomopathogens that can be incorporated with chemical pesticides into the management system. Among the organisms considered, Metarhizium acridum is noteworthy for inclusion in integrated pest management programs.

Abstract Background The ongoing armed conflict in Sudan has caused mass displacement, affecting mental health. This study aimed to assess the prevalence of posttraumatic stress disorder (PTSD) and trauma among refugees, internally displaced, and nondisplaced people, while also examining the link between displacement type, PTSD severity, and associated factors. Methods This cross-sectional study used the Posttraumatic Stress Disorder Checklist for DSM-5 to assess PTSD symptoms and the General Health Questionnaire-28 to evaluate depression. Data were collected from 642 participants, targeting general social media groups for those within Sudan and specific groups for refugees outside the country. Sociodemographic and trauma event data were also gathered. Data analysis was conducted using SPSS, applying one-way ANOVA and independent t-tests to compare PTSD and depression. Binary logistic regression identified associations between sociodemographic factors and PTSD symptoms. Results Among the 642 participants, 46.3% were internally displaced people (IDP), 42.1% were refugees, and 11.7% were non-displaced individuals. Clinically significant PTSD symptoms were identified in 36.6% of the participants. Refugees had a significantly greater percentage of traumatic events (M = 4.31, SD = 2.605, p

Wheat yellow rust disease poses a significant threat to global wheat yield and grain quality. Early detection of this disease will help to minimize the loss caused by its effects. Existing models work well on images taken in a controlled environment, whereas a uniform background is placed behind the leaf, but these models fail to produce good results in natural settings. Previous research also involves manual interventions in the pipeline to achieve good classification results such as cropping the images, using uniform backgrounds, etc. These systems are not practical to use in natural environments where there will be a lot of background noise to the image and manual cropping becomes an extra step for the farmer. Moreover, the unavailability of the dataset in which images of leaves are taken in a natural setting became another challenge. In this research, a dataset is curated and leaves are annotated for object detection, object segmentation further the leaves are classified into 3 classes ie healthy, resistant, and susceptible. A novel unsupervised image rotation algorithm is proposed that takes input from YOLOv8 to align the leave in such a way that maximum background can be removed by a rectangular bounding box . Then the comparison between multiple state-of-the-art segmentation models ie. UNET, Segment-Anything (SAM), Segnet, LinkNet, PSPNet, FPN, Deep-Labv3+ (Xception), and DeepLabv3+ (Mo-bileNet) has shown that UNET has outperformed all the other segmentation models with an IOU score of 0.9563. Lastly for classification, the performance of multiple convolution neural networks ie. VGG16, Resnet 101(v2), Xception, Mo-bileNetV2, and Transformer-based models ie. Swin trans-former and MobileVit have been compared. Swin transformer has outperformed the state-of-the-art CNN models with an accuracy of 95.8%. This paper proposes a complete robust pipeline that can be deployed in natural environment and does not need any manual intervention to produce good results. This research shows that good localization of leaves and removal of unwanted background noise at the earliest stage of the pipeline will assist the segmentation model to effectively segment the leaf from the background which will enable classification models to achieve high classification accuracy, even when dealing with very small datasets.

The functional and structural features of microbial load in soil are influenced by the presence of insecticides. This study examined the impact of two organophosphorus insecticides, dimethoate and parathion on the microbial load of soil. The colony count of fungi, actinomycetes, bacteria, and nitrogen fixing bacteria was reduced after insecticides application at 7 and 14 days, but at 28 days the colony count began to increase. The growth of two white rot fungi including Pleurotus sajor-caju and Phanerochaete chrysosporium was affected by parathion, which was reflected by a decrease in colony radius to 1.85±0.05 and 0.75±0.06 cm, respectively, and by dimethoate, reflected by a decrease in colony radius to 3.33±0.12 and 1.85±0.05 cm, respectively at 40 mg/L compared to colony radius at control 7.90±0.12 and 7.50±0.06 cm, respectively. The applied low concentration (10 mg/L) encouraged P. sajor-caju and P. chrysosporium to remove up to 87.7% and 81.8% of dimethoate, respectively, and 69.20 and 68.30% of parathion, respectively compared with the decomposition at high dose (40 mg/L) at 28 days. The presence of insecticides induced the production of ligninolytic enzymes lignin peroxidase, laccase, and manganase peroxidase.

Water pollution has become a worldwide issue, particularly in developing countries. This study aimed to cleanse water contaminated with reactive red (RR-198) and reactive blue (RB-19) dyes via adsorption onto nonliving white rot fungal biomass Phanerochaete chrysosporium under different operational conditions. It was found that P. chrysosporium removed more of RB-19 than RB-198. The conditions of pH 3, temperature 50 °C, adsorbent dosage 0.6 g, particle sizes of adsorbent (0.25 mm), and contact time (30 min) were optimum for removal of the dyes. RR-198 and RB-19 were removed with levels of 78.4% and 86.4%, respectively at pH 3; 79.6% and 90.0%, respectively using 0.6 g of adsorbent dosage; 82.0% and 87.0%, respectively at 30 min; and 82.0% and 87.2%, respectively at 50 °C. Thus, dead P. chrysosporium biomass was shown to be a biosorbent for the uptake of RB-19 and RR-198 dyes.

Abstract This research addresses the critical need to optimize the Energy Efficiency (EE) for Ultra-Dense HetNets amid the ever-increasing demands for high-speed data networks. The rapid increase in high-speed devices highlights the urgent necessity for a transformative change in upcoming 5G cellular networks. According to Ericsson's 2022 report, mobile data traffic volume is expected to double by 2027, with mobile video traffic anticipated to rise by nearly 30% each year. In response to these challenges, researchers have identified essential technologies that facilitate 5G networks, including massive Multiple-input-Multiple-output (m-MIMO) systems and HetNets. Although both promise enhanced coverage and throughput, HetNets emerges as a cost-effective solution, surpassing m-MIMO in implementation cost and coverage. However, achieving maximum EE in HetNets necessitates careful consideration of various constraints, including delay, coverage probability, and Signal-to-Interference-plus-Noise Ratio (SINR) thresholds. This research marks a significant milestone in adopting the Distributed Dynamic Opportunistic Sleep Strategy (D-DOSS) approach. The D-DOSS method organizes small clusters throughout the network and evaluates key Quality of Service (QoS) parameters including Energy Utilization Efficiency (EUE), Coverage Probability, Data Throughput, and Success Probability using Monte Carlo simulations. This research analyzes Distributed Sleep (DS) and Centralized Schemes (CS) concerning given QoS parameters. While DS methodologies often exhibit performance trade-offs compared to CS, they provide significant advantages in terms of ease of implementation and management. CS, though representing the most commonly used method in ultra-dense HetNets involves high computational costs that complicate its management. By integrating the D-DOSS and addressing various constraints, this research not only advances HetNet technologies but also makes a significant contribution to optimizing EE while preserving network performance and QoS. The innovative D-DOSS approach offers a promising solution to the challenges of energy efficiency in wireless communication networks and paves the way for future advancements in HetNet deployments. The results and analysis show that D-DOSS effectively addresses the limitations of DS and outperforms existing CS techniques.

Abstract This study investigates the projected impact of air pollution on mortality and Disability-Adjusted Life Years (DALYs) across SAARC countries. Utilizing Time Series and Machine Learning methodologies such as Autoregressive Integrated Moving Average, Exponential Smoothing, and Neural Network, the research aims to accurately forecast the mortality and DALYs attributed to air pollution from 2020 to 2030. Statistical analyses reveal a consistent upward trend in deaths and DALYs during the forecasting period, primarily driven by Ambient Particulate Matter Pollution (APM) and Ambient Ozone Pollution (AOP). Comparing the predictive accuracy of the models, Neural Network outperformed other methods, as indicated by Root Mean Square Error (RMSE) values. Specifically, the study finds that deaths and DALYs due to Ambient Particulate Matter pollution are least prevalent in the Maldives, while India and Pakistan exhibit the highest rates, and deaths and DALYs due to Ambient Ozone pollution are lowest in the Maldives and highest in Bangladesh and Pakistan. Moreover, deaths and DALYs attributed to Household Air Pollution (HAP) are lowest in Pakistan and highest in Nepal. These findings underscore the urgent need for air pollution control measures and informed policymaking in SAARC countries to mitigate the escalating health burden associated with air pollution.

Abstract Septins are a family of cytokinesis-related proteins involved in regulating cytoskeletal design, cell morphology, and tissue morphogenesis. Apart from cytokinesis, as a fourth component of cytoskeleton, septins aid in forming scaffolds, vesicle sorting and membrane stability. They are also known to be involved in the regulation of intracellular calcium (Ca2+) via the STIM/Orai complex. Infertility affects ~ 15% of couples globally, while male infertility affects ~ 7% of men. Global pregnancy and live birth rates following fertility treatment remain relatively low, while there has been an observable decline in male fertility parameters over the past 60 years. Low fertility treatment success can be attributed to poor embryonic development, poor sperm parameters and fertilisation defects. While studies from the past few years have provided evidence for the role of septins in fertility related processes, the functional role of septins and its related complexes in cellular processes such as oocyte activation, fertilization, and sperm maturation are not completely understood. This review summarizes the available knowledge on the role of septins in spermatogenesis and oocyte activation via Ca2+ regulation, and cytoskeletal dynamics throughout pre-implantation embryonic development. We aim to identify the currently less known mechanisms by which septins regulate these immensely important mechanisms with a view of identifying areas of investigation that would benefit our understanding of cell and reproductive biology, but also provide potential avenues to improve current methods of fertility treatment.

Abstract Smartphones store valuable personal information, necessitating robust authentication methods to protect user data. This research proposes a lightweight bi-model fallback authentication technique that combines dynamic security questions and finger pattern recognition using inertial measurement units. The dynamic security questions are generated based on the smartphone’s usage behavior, while the owner’s finger movements are captured using four different inertial sensors: accelerometer, gyroscope, gravity sensor, and magnetometer. By combining the answers to the questions and the owner’s finger movements, the user can be authenticated even if the primary authentication method fails. In this study, data was collected from 24 participants, including 12 primary phone users and 12 close adversaries, over a span of 28 days. The dynamic security questions, derived from call, SMS, battery charging events, application usage, location, and physical activity categories, achieved high accuracy rates, with call, SMS, and application usage surpassing $$90\%$$ 90 % . Incorporating the inertial measurement units significantly improved the accuracy of all question types, increasing from a maximum of $$76\%$$ 76 % to $$90.99\%$$ 90.99 % , while also enhancing the True Positive Rate from 0.79 to 0.99 compared to a previous study. This research presents a promising lightweight bi-model fallback authentication technique that leverages dynamic security questions and inertial measurement units data, demonstrating its effectiveness for enhancing smartphone security.

Abstract Background Hepatocellular carcinoma (HCC) is a global health concern. Due to late diagnosis and limited therapeutic strategies, HCC based mortality rate is exponentially increasing globally. Genetic predisposition is a non-avoidable intrinsic factor that could alter the genome sequence, ultimately leading to HCC. Protein kinase C eta (PKCη) is involved in key physiological roles, hence alteration in PKCη could aid in cancer progression. Research indicates association between non-synonymous (ns) SNPs and HCC onset. However, effect of nsSNP variants of PKCη on HCC development has not been explored yet. Hence, this study aimed to investigate the association between pathogenic nsSNPs of PKCη with HCC. Methods Non-synonymous (missense) variants of PKCη were obtained from Ensembl genome browser. These variants were filtered out to obtain pathogenic nsSNPs of PKCη. Genotyping of nsSNPs was done through Tetra ARMS PCR. For that, blood samples of 348 HCC patients and 337 controls were collected. The clinical factors that influence HCC were studied. Relative risk (RR) and Odds Ratio (OR) with 95% confidence interval was calculated by Chi-square test and P-value

Abstract Robots support and facilitate tasks in all life fields. Soft robots specifically have the advantages of inherent compliance, safe interaction and flexible deformability. Soft pneumatic network (Pneu-Net) is a soft pneumatic actuator (SPA) composed of network of chambers that is actuated by pneumatic power. Soft Pneu-Net fits the human interface applications perfectly. In this paper, a bio-inspired modular based design for Pneu-Net actuator is developed. The actuator mimics the elephant trunk curling to be employed for rehabilitation of human hand fingers. The actuator is an integrated four Pneu-Net modules actuator which is attached to hand’s finger. The main introduced advantages in the new developed actuator are: providing four degrees of freedom (DoF) essential for finger’s motion by single compound actuator and developing a methodology for a modular soft Pneu-Net actuator that is efficiently reproducible. The actuator’s design is developed using computer aided design (CAD) software SOLIDWORKS. The design is simulated using finite element modeling (FEM) software ABAQUS. Fabrication process uses 3D printed molds. Soft material is molded in the 3D printed molds, forming actuator’s modules. Actuator’s modules are integrated by adhesion using the soft material. A proposed non-standard hyper-elastic material biaxial tension test is introduced as a quick material properties identification method that can produce a test table used for material identification in the FEM. Enhanced version for the actuator uses reinforcement fibers. Results show advances for the reinforced actuator, as it limits the unwanted actuator’s strain and deformation. The reinforced actuator shows improved energy efficiency reaches to 46%.

Abstract This study reported the synthesis and characterization of chitosan-copper nanoparticles (Ch-CuNPs) using a 1% copper sulfate solution in 0.2% w/v chitosan. The Ch-CuNPs, displaying a stable brick-red hue, showed an absorption peak at 572 nm, indicative of monodisperse nanoparticle formation and surface plasmon resonance. X-ray diffraction confirmed the face-centered cubic structure with peaks at 36.78°, 43.38°, 50.56°, and 74.26°, and an average particle size of 87–89 nm. FTIR analysis showed interactions between chitosan and copper, particularly around 3370 –3226 cm⁻¹, 1633 cm⁻¹, and 680 cm⁻¹. In vitro assays revealed that Ch-CuNPs inhibited Macrophomina phaseolina growth by 18–71% at 0.03–0.09% concentrations, achieving complete inhibition at 0.12–0.15%, with PCA analysis confirming that growth peaked at lower concentrations and sharply declined at higher levels. Ch-CuNPs also altered fungal morphology and enzyme activity, with notable degradation at higher concentrations. The Cu uptake by the fungus peaked at 29.9% with 0.03% Ch-CuNPs and decreased at higher concentrations. FTIR analysis showed shifts and disappearance of peaks in fungal biomass treated with Ch-CuNPs, indicating molecular interactions and potential structural changes. This study underscores the potential of Ch-CuNPs as an effective antifungal agent and elucidates their interaction mechanisms.

Abstract Background Copeptin is an immediate biomarker of individual stress response; many life-threatening diseases are causing a high elevation of its concentration in plasma, such as myocardial infarction and cardiovascular shock. Moreover, copeptin is a promising marker in sepsis. We aimed to evaluate copeptin as a diagnostic and prognostic marker in neonatal sepsis for the early initiation of appropriate therapy and the prediction of mortality. A prospective case-control study involved 237 neonates (165 cases had neonatal sepsis, and 72 served as controls). Cases were admitted to the neonatal intensive care unit (NICU) and followed up for symptoms and signs of sepsis confirmed by laboratory data: complete blood count (CBC), c-reactive protein (CRP), and cultures. Serum copeptin level by the enzyme-linked immunosorbent assay (ELISA) was measured for all included neonates. We observed that the copeptin level was significantly higher in cases than control (3.51 ± 1.4, 1.61 ± 0.51 pmol/liter, respectively). The cut-off value of copeptin at which we can discriminate between cases and controls was above 2.065 pmol/liter. Among cases, copeptin was higher in early-onset sepsis (EOS) than late-onset sepsis (LOS) neonates, and there was a significant correlation between its level and all the following: age at admission, birth weight, gestational age, history of perinatal asphyxia, maternal chorioamnionitis, and premature rupture of membrane (PROM). Also, copeptin was strongly associated with CRP level and the poor prognosis of patients. Copeptin can predict the death of cases at a cut-off value above 2.995 pmol/liter. Conclusion Serum copeptin level can be used as a diagnostic and prognostic marker in neonatal sepsis.

Abstract Background: Total hip arthroplasty (THA) by using ceramic-on-ceramic (CoC) implants has emerged as a promising solution to mitigate wear debris-related complications, such as osteolysis, specifically in younger patients. This study aims to investigate the functional outcomes after total hip replacement by CoC in patients less than 30 years old, conducted within the hospitals of Khartoum, Sudan. Methods: A descriptive, cross-sectional, hospital-based study was carried out across the major healthcare institutions in Khartoum state from October 2021 to April 2022. A cohort of 32 patients, all aged 30 or below, who underwent total hip replacement were included. Thorough data analysis was conducted using advanced statistical techniques. Results: The average age of included patients was 25.69 ± 2.7 years, among them, males had a slight predominance (56.3%) with a male-to-female ratio of 1.3:1. Most patients had a secondary school level of education (37.5%), while workers constituted the largest group (34.4%). The included patients were followed-up for more than six months. The mean visual analog scale (VAS) score was 7.91 ± 0.893. Additionally, the mean modified Harris hip score was 83.03 ± 4.9 (range: 72–91), highlighting the enhanced hip function achieved through the procedure. The majority of patients (65.6%) reported good functional outcomes, followed by 28.1% who attained fair outcomes and 25.8% who reported excellent outcomes. Conclusion: The study demonstrates that CoC THA yields optimal functional outcomes among patients aged 30 years and below. The procedure exhibits remarkable potential to improve hip function and alleviate pain in this specific patient population. These findings highlight the efficacy and viability of CoC implants in younger patients, contributing to the advancement of hip arthroplasty techniques.

Abstract Introduction Colorectal cancer (CRC) constitutes around 10% of global cancer diagnoses and death due to cancer. Treatment involves the surgical resection of the tumor and regional lymph nodes. Assessment of multiple lymph node demands meticulous examination by skilled pathologists, which can be arduous, prompting consideration for an artificial intelligence (AI)-supported workflow due to the growing number of slides to be examined, demanding heightened precision and the global shortage of pathologists. Method This was a retrospective cross-sectional study including digital images of glass slides containing sections of positive and negative lymph nodes obtained from radical resection of primary CRC. Lymph nodes from 165 previously diagnosed cases were selected from Agha Khan University Hospital, from Jan 2021 to Jan 2022. The images were prepared at 10X and uploaded into an open source software, Q path and deep learning model Ensemble was applied for the identification of tumor deposits in lymph node. Results Out of the 87 positive lymph nodes detected by AI, 73(84%) were true positive and 14(16%) were false positive. The total number of negative lymph nodes detected by AI was 78. Out of these, 69(88.5%) were true negative and 9 (11.5%) were false negative. The sensitivity was 89% and specificity 83.1%. The odds ratio was 40 with a confidence interval of 16.26–98.3. P-value was

Background: Tear production increases ocular surface health and improves visual clarity. Which facilitates the physical activity comfortably. Different dosages of glucose intake had a significantly varying impact on tear production in euglycemic, initially decreasing followed by an increase. Objective: to compare the effect of 0.5% and 1% glucose intake on tear production in euglycemic. Methodology: A quasi-experimental study was conducted with n=200 participants at Irfan Eye Care Hospital Peshawar, from September 2022 to May 2023. The participants were euglycemic without any ocular and systemic pathology and determined its effect on tear production. The participants were divided into two groups equally for 0.5% and 1% glucose intake. Tear production was measured at baseline, after 60 minutes, 90 minutes, 120 minutes, and 150 minutes with the Schirmer test. Results: There was a significant reduction of tear production from baseline to 120 minutes (p

Objective: To determine the seroprevalence of Varicella-zoster virus (VZV) in females of childbearing age. Study Design: Cross-sectional study. Place and Duration of Study: Virology Department, tertiary care hospital, Rawalpindi, from August 2022 to December 2022. Materials and Methods: A total of 200 females, aged 15-49 years, were included in the study. Data of the participants regarding age, socioeconomic status, marital status, and previous history of VZV infection was collected by a predesigned questionnaire. Blood samples were tested for the detection of VZV IgG by Enzyme Linked Immunosorbent Assay (ELISA) of Ratio Diagnostic, Germany. SPSS version 25 was used to analyze the data. Results: Out of total 200 samples, 163 (81.5%) were positive for VZV IgG and 37 (18.5%) were negative. The positivity of VZV IgG was highest in age group 2 (20-29 years) with 87 (43.5%) positive cases, followed by 54 (27%) in age group 3 (30-39 years) and 11 (5.5%) in both age group 1 (< 20 years) and age group 4 (40-49 years). Out of 200 participants, 158 (79.0%) were married and 42 (21.0%) were unmarried. Among total, 107 (53.5%) had history of previous VZV infection while 93 (46.5%) had no significant history. Conclusions: This study showed significant exposure of VZV in females of childbearing age and subsequent development of immunity. However, a substantial proportion of females were susceptible to VZV infection. This susceptibility in females could potentially pose a future risk of infection during pregnancy, resulting in severe complications and congenital abnormalities.

Abstract Purpose The antibacterial properties of silver nanoparticles (AgNPs) are extensively identified. In large quantities, they might be harmful. So many fields of nanotechnology have shown a great deal of interest in the development of an environmentally friendly, efficient method for synthesizing metal nanoparticles. Because of its antibacterial and antifungal properties toward a wide range of microbes, chitosan silver nanoparticles (AgNPs@Cs) constitute a newly developing class of bio-nanostructured hybrid materials. Furthermore, the use of photothermal therapy (PTT) has been suggested as a means of elimination of germs. These light-stimulated treatments are minimally invasive and have a few side effects. In the present work, the antibacterial effect of AgNPs at low concentrations; prepared by chemical and green methods as antimicrobial and photothermal agents in photothermal therapy; with laser irradiation were explored as combined treatment against MRSA, Pseudomonas aeruginosa, and Klebsiella pneumoniae. Methods Silver nanoparticles were produced in two ways. First, by sodium borohydrides, second, by chitosan (as a natural eco-friendly reducing, and capping agent). The nanostructure of AgNPs and AgNPs@Cs was confirmed by UV–visible spectrometer, transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIRs), and direct light scattering (DLS). The antibacterial activity of the prepared nanoparticles and the laser irradiation was tested against three bacterial species of zoonotic importance; MRSA, Pseudomonas aeruginosa, and Klebsiella pneumoniae; and was evaluated by measuring their minimum inhibitory concentrations (MIC). Results Silver nanoparticles produced by the two methods had spherical shapes with nearly the same particle size. The analysis of DLS showed that AgNPs were very stable with zeta potential − 28.8 mv, and 47.7 mv by chemical and chitosan synthesis, respectively. Furthermore, AgNPs@Cs showed higher antibacterial activity toward the tested bacterial species than AgNPs by chemical method. Additionally, the bacterial viability using photothermal laser therapy was reduced compared to laser and AgNPs alone. The bactericidal activities were higher when laser diode was coupled with AgNPs@Cs than by chemical reduction. Conclusion The laser combined treatment had a higher antimicrobial effect than AgNPs alone or laser irradiation alone.

In this article, we study the convergence behavior of G-nonexpansive mappings for three-step iterations in convex metric space along with the directed graph. We demonstrate the Δ-convergence as well as the strong convergence results for these mappings. For supporting our main results we presented a numerical example and convergence comparison of modified Thianwan iteration with SP iteration scheme and Noor iteration scheme.

AbstractMost fungal bone and joint infections (arthritis) are caused by Mucormycosis (Mucor indicus). These infections may be difficult to treat and may lead to chronic bone disorders and disabilities, thus the use of new antifungal materials in bone disorders is vital, particularly in immunocompromised individuals, such as those who have contracted coronavirus disease 2019 (COVID-19). Herein, we reported for the first time the preparation of nitrogen-doped carbon quantum dots (N/CQDs) and a nitrogen-doped mesoporous carbon (N/MC) using a quick micro-wave preparation and hydrothermal approach. The structure and morphology were analysed using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and surface area analyser. Minimum inhibitory concentration (MIC), disc diffusion tests, minimum fungicidal concentration (MFC) and antifungal inhibitory percentages were measured to investigate the antifungal activity of N/CQDs and N/MC nanostructures. In addition to the in vivo antifungal activity in rats as determined by wound induction and infection, pathogen count and histological studies were also performed. According to in vitro and in vivo testing, both N/CQDs with small size and N/MC with porous structure had a significant antifungal impact on a variety of bone-infecting bacteria, including Mucor infection. In conclusion, the present investigation demonstrates that functional N/CQDs and N/MC are effective antifungal agents against a range of microbial pathogenic bone disorders in immunocompromised individuals, with stronger and superior fungicidal activity for N/CQDs than N/MC in vitro and in vivo studies.

ABSTRACTThe present research investigated the effectiveness of cumin and black cumin extracts as natural antioxidants in uncooked chicken nuggets stored at refrigeration temperature (4°C) for 12 days and compared the results with a control treatment. Seven treatments were formulated, including a control group (Tc), T1 (0.5% cumin), T2 (1% cumin), T3 (1.5% cumin), T4 (0.5% black cumin), T5 (1% black cumin), and T6 (1.5% black cumin). The product was evaluated for several physicochemical parameters on days 0, 3, 6, 9, and 12 of storage. The data was analyzed using a two-way factorial design under a completely randomized (CRD) design. Results showed that both treatments and storage significantly impacted all physicochemical properties, including DPPH, TPC, pH, POV, and TBARS (p 0.05). Sensory evaluation showed that T3 (1.5% cumin) was the most pleasant and preferred treatment. Conclusively, both cumin and black cumin have good antioxidant properties and can be used as natural antioxidants to increase the shelf life of food products.

Background and objective: Increased blood sugar levels (hyperglycemia) and lack of insulin are a hallmark of Type 1 diabetes mellitus (T1DM), which is a chronic autoimmune illness results from the destruction of pancreatic beta –cells. The most common causes of hypothyroidism and hyperthyroidism are autoimmune diseases Hashimoto's thyroiditis and Graves’ disease, respectively. Because type 1 diabetes includes autoimmunity as a pathophysiological trigger, it is not uncommon to investigate patients with both diabetes and thyroid problems. The aim of the study is to evaluate serum thyroid hormones in patients with type1 diabetes mellitus. Methods: In this study 104 participants were included, 52 patients with type1 diabetes, and 52 healthy individuals. Blood samples were taken, and serum thyroid hormones levels were measured and the results of cases and controls were analyzed and compared using SPSS program. Results: It was found that the levels of T4 among non- diabetic participants were higher than those of diabetic patients. (P

Abstract Background A paradigm shift in nursing education is required to prepare Z generation of nursing students through integrated innovative technologies as teaching strategies such as immersive virtual reality in several bioscience and main courses to facilitate and enhance learning process. Aim/objective Examine the effect of utilizing an immersive virtual reality application on students’ perceptions, knowledge, and satisfaction in an anatomy course. Methods A quasi-experimental (pre-post test, one group) design was conducted among 1st year nursing students (N = 138) enrolled in an anatomy course in the spring semester of 2023–2024 in the nursing program in the health professions faculty at Al-Quds University. The technology acceptance model (TAM) was used for data collection. Results The results showed that 96% of participants were satisfied with using the VR application, and it retains their knowledge in the human anatomy course. 92% of the total, were under the age of twenty, and 84% were females. 80.1% (2.99 ± 0.58) of those students had more positive perspectives of VR applications in the nursing courses. Additionally, there were significant differences in students’ satisfaction and knowledge toward using VR applications after the anatomy lecture (p = 0.029, p = 0.05, respectively). Conclusion Virtual reality is a supplemental innovative tool for promoting learning. Nursing students perceive immersive virtual reality technologies positively and prefer using three-dimensional images in their anatomy courses, which helps them recall their knowledge, understand concepts of educational content, identify learning objectives, and improve learning outcomes. This study found that virtual reality can improve nursing students’ understanding, satisfaction, and knowledge of anatomy.

Abstract Meaningful communication between health service users and providers is essential. However, when stakeholders are unfamiliar with new health services, innovative communication methods are necessary to engage them. The aim of the study was to create, validate, and evaluate a video-vignette to enhance stakeholders’ (physicians, pharmacists, and laypeople) engagement and understanding of an innovative pharmacy-based diabetes screening and prevention program. Also, to assess the video-vignette’s capacity to measure appetite and appeal for such preventive programs. This mixed-methods study consisted of two phases. In phase one, a video-vignette depicting the proposed screening and prevention program was developed and validated following established international guidelines (n = 25). The video-vignette was then evaluated by stakeholders (n = 99). In phase two, the video-vignette’s capacity as a communication tool was tested in focus groups and interviews to explore stakeholders’ perspectives and engagement on the proposed service (n = 22). Quantitative data were analyzed descriptively, while qualitative data underwent thematic analysis. In total, 146 stakeholders participated. The script was well-received, deemed credible, and realistic. Furthermore, the video-vignette received high ratings for its value, content, interest, realism, and visual and audio quality. The focus groups and interviews provided valuable insights into the design and delivery of the new service. The video-vignette compellingly portrayed the novel pharmacy-based diabetes screening and prevention service. It facilitated in-depth discussions among stakeholders and significantly enhanced their understanding and appreciation of such health services. The video-vignette also generated significant interest in pharmacy-based diabetes screening and prevention programs, serving as a powerful tool to promote enrollment in these initiatives.

Clinical trials, the empirical discipline of medical experimentation conducted on human subjects, have engendered a paradigm shift in medical research. The need for new clinical studies is paramount in the Middle East and North Africa (MENA) region, with its rising cancer incidence and demand for efficient oncology treatments. This paper comprehensively reviews the challenges, opportunities, and future directions of phase I oncology clinical trials in the MENA region. Early-phase trials are vital in determining drug dosage and assessing toxicity, bridging the gap between preclinical research and clinical practice. Considering the unique landscape of MENA, this review explores regulatory aspects, specific hurdles faced, potential advantages, and areas for improvement in conducting these trials. Various future directions can be pursued to maximize the potential of phase I oncology trials in MENA. While regulatory bodies like the Ministry of Health adhere to the International Conference on Harmonization–Good Clinical Practice guidelines, a unified system meeting high standards would yield better results. Strengthening research infrastructure, establishing research centers, incorporating clinical trial education into the curriculum, and improving access to medical facilities are crucial. Enhancing consumer understanding of research would facilitate increased participation and promote sustainability in trial recruitment. Navigating various funding sources would open the door for more funding opportunities. Collaborations between academia, industry, and regulatory bodies, both international and local, should be fostered to promote knowledge sharing, resource pooling, and harmonization of standards. Such collaborations would contribute to the sustainability of clinical trial activities by leveraging collective expertise, sharing research infrastructure, and distributing the burden of regulatory compliance. By adopting these strategies, the MENA region can advance its capacity to conduct early phases of oncology trials and contribute significantly to the global medical research landscape.

Abstract Background Jigsaw method is a structured cooperative-learning technique that lays the groundwork towards achieving collective competence, which forms the core of effective clinical practice. It promotes deep learning and effectively enhances team-work among students, hence creating a more inclusive environment. Objective Present study was designed to introduce jigsaw model of cooperative learning to early-year undergraduate medical students, measure its effectiveness on their academic performance, and evaluate the perspectives of both students and faculty members regarding the same. Methods It was a mixed method research, involving eighty second-year undergraduate medical students. The jigsaw cooperative learning approach was introduced in two themes within neurosciences module. Students were divided into two equal groups, with one group experiencing typical small-group discussions (SGDs) in first theme and other group exposed to jigsaw approach. The groups were then reversed for second theme. Following the activity, an assessment comprising multiple-choice-questions was conducted to evaluate the impact of jigsaw technique on students’ academic performance, with scores from both groups compared. Student perspectives were gathered through self-designed and validated questionnaire, while faculty perceptions were obtained through focus group discussions. Quantitative data were analyzed using SPSS v22, while thematic analysis was performed for qualitative data. Results The students of jigsaw group displayed significantly higher median assessment score percentage compared to control group (p = 0.003). Moreover, a significantly greater number of students achieved scores ≥ 60% in jigsaw group compared to control group (p = 0.006). The questionnaire responses indicated a favorable perception of this technique among students, in terms of acceptance, positive interdependence, improvement of interpersonal skills, and comparison with typical SGDs. This technique was also well-perceived within the educational context by faculty members. Conclusion The jigsaw method is associated with higher levels of academic performance among students when compared to typical small-group discussion. The students and faculty perceived this technique to be an effective cooperative learning strategy in terms of enhanced student engagement, active participation, and a sense of inclusivity.

Primary ovarian insufficiency (POI) is the development of primary hypogonadism before the age of 40 years in women with normal karyotypes. Patients present with symptoms that are similar to those of menopause, including irregular periods, reduced fertility, and climacteric symptoms due to hypoestrogenism, such as hot flashes, vaginal dryness, dyspareunia, irritability, and night sweats. The incidence of spontaneous POI is approximately 1 in 250 by 35 years of age and 1 in 100 by 40 years of age. Genetic, inflammatory, metabolic, autoimmune, and idiopathic factors contribute to POI. POI pathophysiology is explained by the presence of fewer primordial follicles and their rapid degeneration. Detailed history and examination are important for diagnosis. Diagnosis requires biochemical evidence and laboratory testing, including measurements of follicle-stimulating hormone, thyroid-stimulating hormone, prolactin, and estradiol (E2) levels. In addition, transvaginal ultrasound is preferred to evaluate ovarian reserve. POI should be managed through a multidisciplinary approach involving gynecologists, endocrinologists, and psychologists. Hormonal replacement therapy is the mainstay treatment for all women with POI. Lifestyle modifications such as weight-bearing exercises, smoking cessation, and Vitamin D and calcium supplementation are highly recommended to improve bone density and reduce fractures. Psychological care has been suggested to improve self-esteem and social support, along with family planning guidance. Despite recent discoveries, additional screening techniques are needed.

Abstract Background Pulmonary arteriovenous malformations are a relatively uncommon medical condition, affecting roughly 1 in every 2500 individuals. Of those suffering from pulmonary arteriovenous malformations, 80% have an underlying genetic condition: hereditary hemorrhagic telangiectasia. Case presentation We present the case of a 20-year-old Pakistani male with a history of persistent slower-onset frontal headaches that increased in severity within the course of the day. His hemoglobin was 18 g/dl, indicating polycythemia, for which he had undergone seven venesections in a month previously. His physical examination was unremarkable. His computed tomography scan depicted multiple dilated tortuous vessels with branching linear opacities in the right lower lobe of the lungs. The multiple feeding arteries were supplied by the right main pulmonary artery, and the large draining veins led to the right inferior pulmonary vein. This was identified as a diffuse pulmonary arteriovenous malformation. He was recommended for a right pulmonary artery angiogram. It showed multiple tortuous vessels with a nidus and large draining veins—features of a diffuse arteriovenous malformation in the right lower lobe of the lung consistent with the computed tomography scan. Embolization of two of these vessels feeding the arteriovenous malformation was conducted, using Amplatzer Vascular plug 2, whereas multiple pushable coils (five coils) were used for embolizing the third feeding vessel. This achieved 70–80% successful embolization of right pulmonary AVM; however, some residual flow was still seen in the arteriovenous malformation given the complexity of the lesion. Immediately after, his oxygen saturation improved from 78% to 96%. Conclusion Diffuse pulmonary arteriovenous malformations, as seen in this patient, are rare, accounting for less than 5% of total pulmonary arteriovenous malformations diagnosed. The patient presented with a complaint of progressive frontal headaches, which can be attributed to low oxygen saturation or the presence of a cerebral arteriovenous malformation. There was no history of hereditary hemorrhagic telangiectasia in the patient’s family. Furthermore, although most patients with hereditary hemorrhagic telangiectasia and hence pulmonary arteriovenous malformation have complaints of iron-deficiency anemia, our patient in contrast was suffering from polycythemia. This can be explained as a compensatory mechanism in hypoxemic conditions. Moreover, the patient had no complaint of hemoptysis or epistaxis, giving a varied presentation in comparison with a typical pulmonary arteriovenous malformation.

Abstract Background Quality sleep is vital for well-being, especially for healthcare workers facing high risks of fatigue and burnout. Sleep deprivation impairs cognitive and motor functions, contributing to medical errors. Addressing sleep disorders among healthcare professionals is crucial for enhancing patient care. Tailored interventions are needed to support their well-being and improve healthcare outcomes. Objective To evaluate the effect of Sleep Quality and its Deprivation on Sudanese Healthcare Professionals amidst conflict in Sudan. Methods A cross-sectional online survey of Sudanese doctors was conducted using convenience sampling. The questionnaire covered sleep quality, daytime sleepiness, and psychological well-being. Pilot testing ensured questionnaire clarity. Data collection utilized Google Forms distributed through social media and professional networks. A minimum sample size of 384 was calculated. Statistical analysis included descriptive statistics and various tests for significance. Data were securely stored and analyzed using SPSS and R software. Results Among 649 participants, 404 (62.2%) were women, with a mean age of 30.34 years. Most were single (434, 66.9%). General practitioners constituted the largest professional group (267, 41.1%), followed by registrars/residents (142, 21.9%). Participants took an average of 43.70 minutes to fall asleep and slept an average of 5.90 hours per night. According to the PSQI, 300 (46.2%) reported mild sleep disturbance, 287 (44.2%) moderate, 42 (6.5%) severe, and only 20 (3.1%) normal sleep. The ESS revealed 285 (43.9%) with lower normal daytime sleepiness, 188 (29.0%) with higher normal, and various levels of excessive daytime sleepiness. Stress levels varied, with 398 (61.3%) reporting normal stress, while anxiety ranged from 248 (38.2%) normal to 148 (22.8%) extremely severe. Conclusion This study emphasizes the importance of addressing sleep quality, mental health, and performance challenges among Sudanese healthcare professionals. It highlights the need for hospitals to implement measures enabling more time off, adequate sleep, and reduced on-call service days. Healthcare workers must recognize the significance of these factors for their well-being and patient care quality. The research outcomes can raise awareness about the necessity of regulating healthcare practitioners' working hours and ensuring adequate sleep.

Rainfall has a huge impact on agriculture because it's one of the key causes of crops devastation. Farmers face a slew of issues when unexpected heavy rains fall, as their planted crops are washed away or damaged. Pakistan is an agricultural country where new methods and techniques are needed to improve the traditional farming methods. This research intends to provide aid in the protection of crops from severe rains using machine learning to accurately anticipate the possibility of rainfall, which is a well-known agricultural problem. Various weather factors such as temperature, humidity, and atmospheric pressure can be used to predict rainfall patterns. Rainfall prediction can be used to identify and furnish future rainfall descriptions for agricultural planning for food security, allowing farmers to take precautionary measures to safeguard rice fields. Naïve Bayes, LogitBoost, RIPPER, Decision Stump, AdaBoost, Random Forest, Artificial Neural network, and K* were evaluated for rainfall prediction based on accuracy, precision, recall, F1-measure, Root Mean Squared Error, area under receiver operating characteristic curve, elapsed training time and elapsed testing time. The results obtained indicate that the best performance is achieved by Random forest with maximum accuracy of 83.2%, followed by ANN (82.5%), LogitBoost (82.2%), RIPPER (82%), naïve Bayes (80.3%), AdaBoost (80.2%), and K*(79.2%) respectively. K* The lazy approach involved a minimum of training time and a maximum of test time. Maximum training time was consumed by Random Forest and minimum testing time was taken by Decision Stump.

Abstract Background NAXE‐encephalopathy or early‐onset progressive encephalopathy with brain edema and/or leukoencephalopathy‐1 (PEBEL‐1) and NAXD‐encephalopathy (PEBEL‐2) have been described recently as mitochondrial disorders causing psychomotor regression, hypotonia, ataxia, quadriparesis, ophthalmoparesis, respiratory insufficiency, encephalopathy, and seizures with the onset being usually within the first three years of life. It usually leads to rapid disease progression and death in early childhood. Anecdotal reports suggest that niacin, through its role in nicotinamide adenine dinucleotinde (NAD) de novo synthesis, corrects biochemical derangement, and slows down disease progression. Reports so far have supported this observation. Methods We describe a patient with a confirmed PEBEL‐1 diagnosis and report his clinical response to niacin therapy. Moreover, we systematically searched the literature for PEBEL‐1 and PEBEL‐2 patients treated with niacin and details about response to treatment and clinical data were reviewed. Furthermore, we are describing off‐label use of a COX2 inhibitor to treat niacin‐related urticaria in NAXE‐encephalopathy. Results So far, seven patients with PEBEL‐1 and PEBEL‐2 treated with niacin were reported, and all patients showed a good response for therapy or stabilization of symptoms. We report a patient exhibiting PEBEL‐1 with an unfavorable outcome despite showing initial stabilization and receiving the highest dose of niacin reported to date. Niacin therapy failed to halt disease progression or attain stabilization of the disease in this patient. Conclusion Despite previous positive results for niacin supplementation in patients with PEBEL‐1 and PEBEL‐2, this is the first report of a patient with PEBEL‐1 who deteriorated to fatal outcome despite being started on the highest dose of niacin therapy reported to date.

Objectives: The research aims to study documentary archives from important departments, given that they contain important data, information and documents about events and general conditions. One of the countries that has been interested in archival work is Iraq because of the desire of many Iraqi historians to keep pace with those countries, as Iraq is the main homeland. For documentary archives, due to the ancient civilization and its cultural heritage since ancient times and in its contemporary history. Methodology: The research includes a brief historical study that gives a clear picture of the historical roots of archival work in Iraq by relying on Iraqi documents, sources, and newspapers that were considered the scientific sources of the research, then focusing on the role of Iraqi historians in collecting, classifying, and archiving documents and making them scientific material to draw from. Researchers and graduate students such as Abdul Razzaq Al-Hassani, Salem Al-Alusi, Saleh Ahmed Al-Ali, Yassin Abdul Karim, and others who later became founders and workers at the Iraqi Center for Document Preservation. Result: The archive constituted a source of various information related to the development of the features of political, social, intellectual, economic and cultural life, from the formation of the Iraqi state, and for this reason the state faced the problem of how to deal with the huge amount of these papers, records and files that are issued daily, but it did not receive any attention from anyone. In order to preserve documents and the necessity of securing them, or to establish an independent department to take care of their preservation and facilitate access to them by historians and researchers, until the destruction law was issued in 1942 AD, to which several amendments were made. Conclusion: A country that does not have an archive is like a patient who has lost his memory. Preserving documents goes back to the University of Baghdad and the urgent need for sources and references that they rely on in historical studies and research and their sense of the importance of documents in historical writings. They also drew attention to the necessity of making use of old papers. preserved in the state ministries and departments, and thus the responsible authorities at the University of Baghdad made unremitting efforts to contact government departments and institutions, urging them to pay attention to old records and files that contain various important information.

Wastewater from industries contributes significantly to pollution. Adsorption of acidic dye using nanohybrid biopolymeric hydrogels has evolved as one of the viable techniques. Graphene oxide (GO)/chitosan (CS)–polyvinyl alcohol (PVA), GO/starch–PVA, and GO/agar–PVA hydrogels were synthesized. The results revealed that the following are the ideal values: GO/CS–PVA: 3 pH (8.251 mg g−1), 0.05 g/50mL dosage (8.251 mg g−1), 90 min (8.251 mg g−1), 12 ppm dye concentration (8.251 mg g−1), and 30 °C (8.251 mg g−1); for GO/starch–PVA: 2 pH (7.437 mg g−1), 0.05 g/50 mL dosage (7.437 mg g−1), 90 min (7.437 mg g−1), 12 ppm dye concentration (7.437 mg g−1), and 30 °C (7.437 mg g−1); and for GO/agar–PVA; 3 pH (6.142 mg g−1), 0.05 g/50 mL dosage (6.142 mg g−1), 90 min (6.142 mg g−1), 12 ppm dye concentration (6.142 mg g−1), 30 °C (6.142 mg g−1). GO/CS–PVA outperformed the other hydrogels. The Langmuir model suited GO/CS–PVA data, while GO/starch–PVA and GO/agar–PVA hydrogels followed Freundlich isotherm models. The adsorption capacity data followed a pseudo-second-order model. Negative value of Gibbs free energy and enthalpy showed that the reactions were spontaneous and exothermic in nature. The presence of heavy metals, electrolytes, and detergents/surfactants affected the dye adsorption. Entropy changes positive values implied randomness at the solid/solution contact. The desorption (60, 55, and 58%) of GO/CS–PVA, GO/starch–PVA, and GO/agar–PVA hydrogels was obtained using 0.5 N NaOH. Scanning electron microscope, X-ray diffraction, and Fourier transform infrared (FT-IR) were used for characterization. HIGHLIGHTS Nanohybrid biopolymeric hydrogels are effective for textile wastewater treatment.; Prepared hydrogels are based on graphene oxide (GO) and biopolymers. GO was made using Hummer's technique.; Synthesized GO/chitosan–polyvinyl alcohol (PVA), GO/starch–PVA, and GO/agar–PVA nanohybrid biopolymeric hydrogels.; Physiochemical and postexperimental analysis were performed to determine efficient elimination of Acid Red 97 dye.;

Background: Balance problems and falls are prevalent issues, especially among older adults. Otago exercise is one of the interventions applied to the geriatric population to prevent falls and balance problems, The Action observation therapy with the Otago exercise program can be a more beneficial intervention method to decrease the prevalence of falls and balance issues among older people. Objective: to evaluate the effectiveness of Otago exercise in combination with action observation training (AOT) on balance and quality of life among the elderly. Methods: A randomized clinical trial was conducted on n=54 elderly between 60-80 years and moderate risk of fall Berge balance scale from May 2022 to July 2023. The participants were included in the study after fulfilling the selection criteria. Then the participants were randomly assigned into two AOT plus Otago (n= 27) groups and Otago exercise alone group (n= 27). The static and dynamic balance were assessed with the Berg Balance Scale (BBS), Timed Up and Go (TUG) test, and Functional Reach Test (FRT) respectively. Additionally, quality of life was measured with the SF-36 questionnaire among older adults. The data was collected at baseline, 6th week, and 12th week. Results: Significant improvements (p

Background: Athletes have general complaints about sleep disturbance which is important for body recovery, healthy brain and body functions, tissue wear and tear, and the body's immune system. Objective: To determine the effectiveness of Progressive Muscle Relaxation (PMR) on sleep disturbance in athletes. Methodology: N=24 athletes aged 18 to 36 years participating in a competition were included in a randomized controlled trial. Athletes who were training for a competition, aged between 18 -and 36 years, and athletes with sleep disturbance score (SDS) falling above 4 on the Athletic Sleep Screening Questionnaire were included. Athlete sleep screening questionnaire (ASSQ) was used to assess sleep disturbance score (SDS). Athletes were randomly assigned to the experimental (n=12) and control (n=12) groups. The experimental group was given progressive muscle relaxation and re-assessed the next day for SDS. Results: The pre-post analysis showed that progressive muscle relaxation reduced the athletes' sleep disturbance score significantly one day after the intervention with a large effect size (p=0.006 Cohen's d= 1.44) in the experimental group. The mean of the mean differences of SDS of both groups were compared which showed a group had a significantly improved sleep disturbance score compared to a control group with a large effect size. (Mean= 1.41 ±1.44 v/s 0.00±1.85, p≤ 0.01, Cohen's d= 1.66). Conclusion: Progressive Muscle Relaxation exercises can be a non-pharmacological method to help athletes sleep by simple head-to-toe muscles contract and relax technique. Clinical Trail No: NCT05695092

Abstract Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases.

Abstract Stevia rebaudiana (stevia) is a plant in the Asteraceae that contains several biologically active compounds including the antidiabetic diterpene glycosides (e.g. stevioside, rebaudioside and dulcoside) that can serve as zero-calorie sugar alternatives. In this study, an elicitation strategy was applied using 5% polyethylene glycol (PEG), sodium chloride (NaCl; 50 and 100 mM) and gibberellic acid (2.0 and 4.0 mg/L GA3) to investigate their effect on shoot morphogenesis, and the production of phenolics, flavonoids, total soluble sugars, proline and stevioside, as well as antioxidant activity, in shoot cultures of S. rebaudiana. Herewith, the media supplemented with 2 mg/L and 4 mg/L GA3 exhibited the highest shooting response (87% and 80%). The augmentation of lower concentrations of GA3 (2 mg/L) in combination with 6-benzylaminopurine (BAP) resulted in the maximum mean shoot length (11.1 cm). The addition of 100 mM NaCl salts to the media led to the highest observed total phenolics content (TPC; 4.11 mg/g-DW compared to the control 0.52 mg/g-DW), total flavonoids content (TFC; 1.26 mg/g-DW) and polyphenolics concentration (5.39 mg/g-DW) in shoots cultured. However, the maximum antioxidant activity (81.8%) was observed in shoots raised in media treated with 50 mM NaCl. The application of 2 mg/L of GA3 resulted in the highest accumulation of proline (0.99 μg/mL) as compared to controls (0.37 μg/mL). Maximum stevioside content (71 µL/mL) was observed in cultures supplemented with 100 mM NaCl and 5% PEG, followed by the 4 mg/L GA3 treatment (70 µL/mL) as compared to control (60 µL/mL). Positive correlation was observed between GA3 and stevioside content. Notably, these two compounds are derived from a shared biochemical pathway. These results suggest that elicitation is an effective option to enhance the accumulation of steviosides and other metabolites and provides the groundwork for future industrial scale production using bioreactors.

Abstract Microplastic particles have been discovered in virtually all ecosystems worldwide, yet they may only represent the surface of a much larger issue. Nanoplastics, with dimensions well below 1 µm, pose an even greater environmental concern. Due to their size, they can infiltrate and disrupt individual cells within organisms, potentially exacerbating ecological impacts. Moreover, their minute dimensions present several hurdles for removal, setting them apart from microplastics. Here, we describe a process to remove colloidally stable nanoplastics from wastewater, which synergistically combines electrophoretic deposition and the formation of particle-stabilized foam. This approach capitalizes on localized changes in particle hydrophilicity induced by pH fluctuations resulting from water electrolysis at the electrode surface. By leveraging these pH shifts to enhance particle attachment to nascent bubbles proximal to the electrode, separation of colloidal particles from aqueous dispersions is achieved. Using poly(methyl methacrylate) (PMMA) colloidal particles as a model, we gain insights into the separation mechanisms, which are subsequently applied to alternative model systems with varying surface properties and materials, as well as to real-world industrial wastewaters from dispersion paints and PMMA fabrication processes. Our investigations demonstrate removal efficiencies surpassing 90%.

Abstract Chronic lower respiratory disease (CLRD) related mortality has decreased in the United States due to increasing awareness in the general population and advancing preventative efforts, diagnostic measures, and treatment. However, demographic and regional differences still persist throughout the United States. In this study, we analyzed the temporal trends of demographic and geographical differences in CLRD-related mortality. Data was extracted from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database. Using this data, age-adjusted mortality rates per 100,000 people (AAMR), annual percentage change (APC), and average annual percentage changes with 95% confidence intervals (CIs) were assessed. The Joinpoint Regression Program was used to determine mortality trends between 1999 and 2020 based on demographic and regional groups. During this study period, there were 3,064,049 CLRD-related deaths, with most demographics and regional areas showing an overall decreasing trend. However, higher mortality rates were seen in the non-Hispanic White population and rural areas. Interestingly, mortality rates witnessed a decreasing trend for males throughout the study duration compared to females, who only began to show decreases in mortality during the latter half of the 2010s. Using these results, one can target efforts and build policies to improve CLRD-related mortality and reduce disparities in the coming decades.

Objective: Evaluation of the clinical outcome of inguinal herniotomy in children at a single center. Study Design: Retrospective cross-sectional study. Place and Duration of Study: Department of surgery, Northern Area Armed Forces Hospital Hafer al Batin, Saudi Arabia, from July 10, 2011, to Oct. 10, 2021. Materials and Methods: A total of 256 patients admitted with inguinal hernia underwent inguinal herniotomy. All the patients were treated by single senior pediatric surgeon. The age ranged from 2 months to 13 years. The data was collected regarding age at operation, gender, location, investigations performed, operative procedure, and complications of the surgical intervention. The follow up was also done in the outpatient clinic for 12 months to assess the complications and outcome of the procedure. The data was analyzed by IBM SPSS version 26.0. The Fischer exact test was applied to evaluate the association of site of inguinal hernia with gender. The p value less than 0.05 was considered statistically significant. Results: One hundred and seventeen (46%) patients had right sided inguinal hernia, 124 (48%) had left sided and 15 (6%) were having bilateral inguinal hernia. There was no per-operative and post-operative complication. There was no testicular atrophy. There was no recurrence of inguinal hernia during follow up of 12 months after surgery. All the children had successful clinical outcome on follow up of 12 months period. Fischer exact test was applied to find the association of type of inguinal hernia with gender and the p value was 0.166 which is considered statistically nonsignificant. Conclusion: Early inguinal herniotomy on next available elective list is safe, effective and feasible procedure to treat children with inguinal hernia.

Abstract Background Chronic liver disease (CLD) is one of the leading disease burdens in Pakistan. Until now, there has only been limited focus in the country on providing health services through tertiary services in urban cities, whereas there is almost no research in Pakistan on the mental health and quality of life of CLD patients. This study aimed to understand which predictors influence the mental health and quality of life of CLD patients in order to advise better policy protection. Methods Data was collected from CLD patients at the Pakistan Kidney and Liver Institute and Research Centre, Lahore, Pakistan. A total of 850 respondents were part of the final sample. The age of respondents ranged from 18 to 79 years and included the following diagnosis: (i) Chronic Viral Hepatitis (n = 271), (ii) Cirrhosis (n = 259), (iii) Hepatocellular Carcinoma (n = 193), and (iv) Non-viral Liver Disease (n = 127). Results Mean results reveal that females as well as illiterate patients need more support for mental health and communication with their physician; whereas men need more support to develop coping strategies. Structural equation modelling results reveal that the severity of symptoms (β = 0.24, p

Abstract Background Dynamical mathematical models defined by a system of differential equations are typically not easily accessible to non-experts. However, forecasts based on these types of models can help gain insights into the mechanisms driving the process and may outcompete simpler phenomenological growth models. Here we introduce a friendly toolbox, SpatialWavePredict, to characterize and forecast the spatial wave sub-epidemic model, which captures diverse wave dynamics by aggregating multiple asynchronous growth processes and has outperformed simpler phenomenological growth models in short-term forecasts of various infectious diseases outbreaks including SARS, Ebola, and the early waves of the COVID-19 pandemic in the US. Results This tutorial-based primer introduces and illustrates a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using an ensemble spatial wave sub-epidemic model based on ordinary differential equations. Scientists, policymakers, and students can use the toolbox to conduct real-time short-term forecasts. The five-parameter epidemic wave model in the toolbox aggregates linked overlapping sub-epidemics and captures a rich spectrum of epidemic wave dynamics, including oscillatory wave behavior and plateaus. An ensemble strategy aims to improve forecasting performance by combining the resulting top-ranked models. The toolbox provides a tutorial for forecasting time-series trajectories, including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. Conclusions We have developed the first comprehensive toolbox to characterize and forecast time-series data using an ensemble spatial wave sub-epidemic wave model. As an epidemic situation or contagion occurs, the tools presented in this tutorial can facilitate policymakers to guide the implementation of containment strategies and assess the impact of control interventions. We demonstrate the functionality of the toolbox with examples, including a tutorial video, and is illustrated using daily data on the COVID-19 pandemic in the USA.

An ensemble n-sub-epidemic modeling framework that integrates sub-epidemics to capture complex temporal dynamics has demonstrated powerful forecasting capability in previous works. This modeling framework can characterize complex epidemic patterns, including plateaus, epidemic resurgences, and epidemic waves characterized by multiple peaks of different sizes. In this tutorial paper, we introduce and illustrate SubEpiPredict, a user-friendly MATLAB toolbox for fitting and forecasting time series data using an ensemble n-sub-epidemic modeling framework. The toolbox can be used for model fitting, forecasting, and evaluation of model performance of the calibration and forecasting periods using metrics such as the weighted interval score (WIS). We also provide a detailed description of these methods including the concept of the n-sub-epidemic model, constructing ensemble forecasts from the top-ranking models, etc. For the illustration of the toolbox, we utilize publicly available daily COVID-19 death data at the national level for the United States. The MATLAB toolbox introduced in this paper can be very useful for a wider group of audiences, including policymakers, and can be easily utilized by those without extensive coding and modeling backgrounds.

Background: Polycystic ovarian syndrome (PCOS) is an endocrinological disease of women of the reproductive age group. The study aimed to compare the efficacy of Myo-inositol and folic acid with and without D-chiro-inositol in the improvement of symptoms of PCOS within 4 months for the evaluation of the most effective therapeutic regimen. Methods: This Quasi-experimental study was conducted at Gynecology & Obstetrics OPD of two Private Healthcare Hospitals in Sialkot from February 2024-June 2024. The Rotterdam criteria (2003) was used for diagnosis of PCOS in non-pregnant women aged between 18-35 years. A total of 90 PCOS patients (45 in each group) were enrolled using a purposive sampling technique and distributed into two treatment groups. Group A received MI 2000 mg + DCI 50 mg + FA 200 mcg while Group B received MI 2000 mg + FA 200 mcg BD, after meal, for 17-18 weeks. Patients’ menstrual cycle history, BMI, transabdominal-ultrasonographic picture, and serum total testosterone levels were evaluated at Day 0, 60, and 120 to compare these measurements before and after initiation of treatment. SPSS was used to analyze the data. Independent samples t-test and Repeated measures ANOVA were used to analyze the data. P-value ≤ 0.05 was considered statistically significant. Results: After the intervention, body mass index (kg/m²), serum total testosterone levels (ng/dl), and follicular number per ovary decreased, with Group A demonstrating better performance with p-values 0.03, 0.04, and < 0.001 respectively. Both groups exhibited increased follicular size in both ovaries and decreased ovarian volumes. By Day 120, menstrual cycle regularity was more pronounced in Group A than in Group B (1.00 ± 0.00 and 1.13 ± 0.34 respectively, p-value

The desert locust is one of the most destructive locusts recorded in human history, and it has caused significant food shortages, monetary losses, and environmental calamities. Prediction of locust attacks is complicated as it depends on various environmental and geographical factors. This research aims to develop a machine-learning model for predicting desert locust attacks in 42 countries that considers three predictors: soil moisture, maximum temperature, and precipitation. We developed the Global Locust Attack Database for 42 countries (GLAD42) by integrating TerraClimate’s environmental data with locust swarm attack data from the Food and Agriculture Organization (FAO). To improve the usability of spatial data, reverse geocoding which is the process of converting geographic coordinates (longitude and latitude) into human-readable location names (such as countries and regions) was employed. This step enhances the clarity and interpretability of the data by providing meaningful geographic context. This study’s initial dataset focused on instances where locust attacks were recorded (positive class). To ensure a comprehensive analysis, we also incorporated negative class instances, representing periods (specific years and months) in the same countries and regions where locust attacks did not occur. This research utilizes the benefits of lazy learners by employing the K-nearest neighbor algorithm (K-NN), which provides high accuracy and the benefit of no time-consuming retraining even if real-time updated data is periodically added to the system. This research also focuses on building an eco-friendly machine learning model by evaluating carbon emissions from ML models. The results obtained from LocustLens are compared with other machine learning models, including baseline–K-NN, decision trees (DT), Logistic regression (LR), AdaBoost Classifier, BaggingClassifier, and support vector classifier (SVC). LocustLens outperformed all competitors with an accuracy of 98%, while baseline-K-NN achieved 96%, SVC gave 91%, DT gave 97%, AdaBoost has accuracy of 91%, BaggingClassifier gave 94% and LR gave 83%, respectively. Carbon emissions from RAM and CPU electricity consumption are measured in kg gCO2. They are a minimum for AdaBoost Classifier equal to 0.02 and 0.07 for DT and a maximum of 9.03 for SVC. The carbon footprint of LocustLens is 4.87 kg gCO2.