Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights

The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, addresses this imperative using machine learning techniques and investigating different class balancing methods for pediatric ICU mortality prediction. This study employs the publicly accessible "Paediatric Intensive Care database" to train, validate, and test a machine learning model for predicting pediatric patient mortality. Features were ranked using three machine learning feature selection techniques, namely Random Forest, Extra Trees, and XGBoost, resulting in the selection of 16 critical features from a total of 105 features. Ten machine learning models and ensemble techniques are used to make accurate mortality predictions. To tackle the inherent class imbalance in the dataset, we applied a unique data partitioning technique to enhance the model's alignment with the data distribution. The CatBoost machine learning model achieved an area under the curve (AUC) of 72.22%, while the stacking ensemble model yielded an AUC of 60.59% for mortality prediction. The proposed subdivision technique, on the other hand, provides a significant improvement in performance metrics, with an AUC of 85.2% and an accuracy of 89.32%. These findings emphasize the potential of machine learning in enhancing pediatric mortality prediction and inform strategies for improved ICU readiness.

Ensemble technique of intrusion detection for IoT-edge platform

Internet of Things (IoT) technology has revolutionized modern industrial sectors. Moreover, IoT technology has been incorporated within several vital domains of applicability. However, security is overlooked due to the limited resources of IoT devices. Intrusion detection methods are crucial for detecting attacks and responding adequately to every IoT attack. Conspicuously, the current study outlines a two-stage procedure for the determination and identification of intrusions. In the first stage, a binary classifier termed an Extra Tree (E-Tree) is used to analyze the flow of IoT data traffic within the network. In the second stage, an Ensemble Technique (ET) comprising of E-Tree, Deep Neural Network (DNN), and Random Forest (RF) examines the invasive events that have been identified. The proposed approach is validated for performance analysis. Specifically, Bot-IoT, CICIDS2018, NSL-KDD, and IoTID20 dataset were used for an in-depth performance assessment. Experimental results showed that the suggested strategy was more effective than existing machine learning methods. Specifically, the proposed technique registered enhanced statistical measures of accuracy, normalized accuracy, recall measure, and stability.

Harmonics management and hosting capacity enhancement: Optimal double-resistor damped double-tuned power filter with artificial hummingbird optimization

This paper introduces a novel and improved double-resistor damped double-tuned passive power filter (DR-DDTF), designed using multi-objective optimization algorithms to mitigate harmonics and increase the hosting capacity of distribution systems with distributed energy resources. Although four different topologies of single-resistor damped double-tuned filters (DDTFs) have been studied before in the literature, the effectiveness of two different DR-DDTF configurations has not been examined. This work redresses this gap by demonstrating that via comprehensive simulations on two power systems, DR-DDTF provides better harmonic suppression and resonance mitigation than single-resistor alternatives. When it comes to optimizing the DR-DDTF for maximum hosting capacity and minimum system active power losses, the multi-objective artificial hummingbird outperformed six other algorithms in the benchmark. To allow for higher penetration of distributed generation without requiring grid upgrades, this newly developed harmonic mitigation filter provides a good alternative.

Tailoring of Bilosomal Nanogel for Augmenting the Off-Label Use of Sildenafil Citrate in Pediatric Pulmonary Hypertension

Pediatric pulmonary hypertension is a serious syndrome with significant morbidity and mortality. Sildenafil is widely used off-label in pediatric patients with pulmonary arterial hypertension. In this study, bile salt-stabilized nanovesicles (bilosomes) were screened for their efficacy to enhance the transdermal delivery of the phosphodiesterase type 5 inhibitor, sildenafil citrate, in an attempt to augment its therapeutic efficacy in pediatric pulmonary hypertension. A response surface methodology was implemented for fabricating and optimizing a bilosomal formulation of sildenafil (SDF-BS). The optimized SDF-BS formulation was characterized in terms of its entrapment efficiency (EE), zeta potential, vesicle size, and in vitro release profile. The optimized formula was then loaded onto hydroxypropyl methyl cellulose (HPMC) hydrogel and assessed for skin permeation, in vivo pharmacokinetics, and pharmacodynamic studies. The optimized SDF-BS showed the following characteristic features; EE of 88.7 ± 1.1%, vesicle size of 185.0 + 9.2 nm, zeta potential of -20.4 ± 1.1 mV, and efficiently sustained SDF release for 12 h. Skin permeation study revealed a remarkable improvement in SDF penetration from bilosomal gel compared to plain SDF gel. In addition, pharmacokinetic results revealed that encapsulating SDF within bilosomal vesicles significantly enhanced its systemic bioavailability (∼3 folds), compared to SDF oral suspension. In addition, pharmacodynamic investigation revealed that, compared to plain SDF gel or oral drug suspension, SDF-BS gel applied topically triggered a significant elevation (p < 0.05) in cGMP serum levels, underscoring the superior therapeutic efficacy of SDF-BS gel. Conclusively, bilosomes can be viewed as a promising nanocarrier for transdermal delivery of SDF that would grant higher therapeutic efficiency while alleviating the limitations encountered with SDF oral administration.

Mistreatment of nurses by patients and its impact on their caring behaviors: The roles of psychological detachment and supervisor positive gossip

BACKGROUND

Mistreatment by patients is a detrimental phenomenon predominant in healthcare organizations. However, there is a lack of nursing literature regarding the underlying mechanisms and boundary conditions that exist between mistreatment by patients and its detrimental consequences.

AIM

By integrating the Job Demands-Resources Model and the Conservation of Resources Theory, the study aimed to unveil the mediating role of psychological detachment from work in the relationship between mistreatment by patients and nurses' caring behaviors, as well as the moderating effect of supervisor positive gossip.

METHODS

This multicenter, cross-sectional study involved 341 nurses from five hospitals across two cities in Egypt. Data were collected using an introductory information form, the Mistreatment by Patients Scale, the Psychological Detachment Scale, the Caring Behaviors Scale, and the Supervisor Positive Gossip Scale. The study's hypotheses were tested using the PROCESS macro.

RESULTS

The results showed that mistreatment by patients was negatively related to nurses' caring behaviors via an increased psychological detachment. Further, higher levels of supervisor positive gossip were shown to weaken the direct effect of mistreatment by patients in increasing nurses' psychological detachment, as well as the indirect negative effect of mistreatment by patients on nurses' caring behaviors via psychological detachment.

CONCLUSIONS

Mistreatment by patients contributes to nurses' psychological detachment and decreased caring behaviors; however, these negative outcomes can be mitigated by supervisor positive gossip.

IMPLICATION FOR NURSING POLICYMAKING

Nursing managers should adopt strategies to deter the rise of mistreatment by patients, and utilize positive gossip to support nurses exposed to such mistreatment to alleviate its consequences.

Geochemistry and the optics of geospatial analysis as a preposition of water quality on a macroscale

The water treatment depends exclusively on the identification of residues containing toxic chemical elements accumulated in NPs (nanoparticles), and ultrafine particles sourced from waste piles located at old, abandoned sulfuric acid factories containing phosphogypsum requires global attention. The general objective of this study is to quantify and analyze the hazardous chemical elements present in the leachate of waste from deactivated sulfuric acid factories, coupled in NPs and ultrafine particles, in the port region of the city of Imbituba, Santa Catarina, Brazil. Samples were collected in 2020, 2021, and 2022. Corresponding images from the Sentinel-3B OLCI satellite, taken in the same general vicinity, detected the levels of absorption coefficient of Detritus and Gelbstoff (ADG443_NN) in 443 m-1, chlorophyll-a (CHL_NN (m-3)), and total suspended matter (TSM_NN (g m-3) at 72 points on the marine coast of the port region. The results of inductively coupled plasma atomic-emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS) demonstrate that the leaching occurring in waste piles at the port area of Imbituba was the likely source of hazardous chemical elements (e.g., Mg, Sr, Nd, and Pr) in the environment. These leachates were formed due to the presence of coal pyrite and Fe-acid sulfates in said waste piles. The mobility of hazardous chemical elements potentiates changes in the marine ecosystem, in relation to ADG443_NN (m-1), CHL_NN (m-3), and TSM NN (g m-3), with values greater than 20 g m-3 found in 2021 and 2022. This indicated changes in the natural conditions of the marine ecosystem up to 30 km from the coast in the Atlantic Ocean, justifying public initiatives for water treatment on a global scale.

Repositioning of anti-infective compounds against monkeypox virus core cysteine proteinase: a molecular dynamics study

Monkeypox virus (MPXV) core cysteine proteinase (CCP) is one of the major drug targets used to examine the inhibitory action of chemical moieties. In this study, an in silico technique was applied to screen 1395 anti-infective compounds to find out the potential molecules against the MPXV-CCP. The top five hits were selected after screening and processed for exhaustive docking based on the docked score of ≤ -9.5 kcal/mol. Later, the top three hits based on the exhaustive-docking score and interaction profile were selected to perform MD simulations. The overall RMSD suggested that two compounds, SC75741 and ammonium glycyrrhizinate, showed a highly stable complex with a standard deviation of 0.18 and 0.23 nm, respectively. Later, the MM/GBSA binding free energies of complexes showed significant binding strength with ΔGTOTAL from -21.59 to -15 kcal/mol. This report reported the potential inhibitory activity of SC75741 and ammonium glycyrrhizinate against MPXV-CCP by competitively inhibiting the binding of the native substrate.

Computational and stability analysis of Ebola virus epidemic model with piecewise hybrid fractional operator

In this manuscript, we developed a nonlinear fractional order Ebola virus with a novel piecewise hybrid technique to observe the dynamical transmission having eight compartments. The existence and uniqueness of a solution of piecewise derivative is treated for a system with Arzel'a-Ascoli and Schauder conditions. We investigate the effects of classical and modified fractional calculus operators, specifically the classical Caputo piecewise operator, on the behavior of the model. A model shows that a completely continuous operator is uniformly continuous, and bounded according to the equilibrium points. The reproductive number R0 is derived for the biological feasibility of the model with sensitivity analysis with different parameters impact on the model. Sensitivity analysis is an essential tool for comprehending how various model parameters affect the spread of illness. Through a methodical manipulation of important parameters and an assessment of their impact on Ro, we are able to learn more about the resiliency and susceptibility of the model. Local stability is established with next Matignon method and global stability is conducted with the Lyapunov function for a feasible solution of the proposed model. In the end, a numerical solution is derived with Newton's polynomial technique for a piecewise Caputo operator through simulations of the compartments at various fractional orders by using real data. Our findings highlight the importance of fractional operators in enhancing the accuracy of the model in capturing the intricate dynamics of the disease. This research contributes to a deeper understanding of Ebola virus dynamics and provides valuable insights for improving disease modeling and public health strategies.

The role of psychological ownership in linking decent work to nurses' vigor at work: A two-wave study

INTRODUCTION

Nurses' vigor at work profoundly impacts the quality of patient care. However, the determinants of nurses' vigor remain underexplored in the current nursing literature, and the mechanism through which these determinants exert their effects remains unclear.

AIM

This study aimed to elucidate the mediating role of psychological ownership in linking decent work to nurses' vigor at work.

METHODS

A two-wave, time-lagged study was conducted to collect data from 289 nurses working across three hospitals in Port Said, Egypt, between March and June 2023. Data were collected using the Decent Work Scale, the Psychological Ownership Scale, the Shirom-Melamed Vigor Measure, on an Introductory Information Form. Mediation testing was performed using structural equation modeling.

RESULTS

Decent work was significantly associated with psychological ownership and vigor at work. Psychological ownership partially mediated the relationship between decent work and nurses' vigor at work.

CONCLUSION

Decent work practices are critical in fostering nurses' vigor while working, and psychological ownership plays a mediating role in this relationship.

CLINICAL RELEVANCE

Hospital administrators should value decent work practices, which could enhance psychological ownership, resulting in a potential improvement in nurses' vigor at work.

Sequential mediation analysis of physical activity, healthy diet, BMI, and academic burnout in the Pakistani educational landscape

Research has indicated a negative impact of physical activity on academic burnout among students, however, there is a paucity of evidence about the underlying mechanism of this association in Pakistani students. The present research seeks to investigate the relationship between physical activity and academic burnout by investigating the potential mediating effects of adherence to the Mediterranean diet (MD) and body mass index (BMI). A sample of 596 students using a cross-sectional survey design was gathered from two public universities (Riphah International University and Mohammed Ali Jinnah University) in Rawalpindi, Pakistan from June to July 2022. The study participants were asked to fill out the Physical Activity Rating Scale-3, the Learning Burnout Scale, and the Test of Adherence to MD questionnaires. The study employed descriptive, bivariate, and path analysis through regression utilizing the SPSS software version 27. The findings demonstrated a negative correlation between academic burnout and BMI, physical activity, and adherence to the MD. The relationship between physical activity and academic burnout was mediated by BMI. Physical activity and academic burnout were inversely correlated, with adherence to the MD and BMI interacting as sequential mediators. The outcomes of this research have expanded our knowledge of the association between physical activity and academic burnout and have suggested crucial and appropriate strategies for addressing student academic burnout.

An Insight on Microfluidic Organ-on-a-Chip Models for PM2.5-Induced Pulmonary Complications

Pulmonary diseases like asthma, chronic obstructive pulmonary disorder, lung fibrosis, and lung cancer pose a significant burden to global human health. Many of these complications arise as a result of exposure to particulate matter (PM), which has been examined in several preclinical and clinical trials for its effect on several respiratory diseases. Particulate matter of size less than 2.5 μm (PM2.5) has been known to inflict unforeseen repercussions, although data from epidemiological studies to back this are pending. Conventionally utilized two-dimensional (2D) cell culture and preclinical animal models have provided insufficient benefits in emulating the in vivo physiological and pathological pulmonary conditions. Three-dimensional (3D) structural models, including organ-on-a-chip models, have experienced a developmental upsurge in recent times. Lung-on-a-chip models have the potential to simulate the specific features of the lungs. With the advancement of technology, an emerging and advanced technique termed microfluidic organ-on-a-chip has been developed with the aim of identifying the complexity of the respiratory cellular microenvironment of the body. In the present Review, the role of lung-on-a-chip modeling in reproducing pulmonary complications has been explored, with a specific emphasis on PM2.5-induced pulmonary complications.

Automated detection and recognition system for chewable food items using advanced deep learning models

Identifying and recognizing the food on the basis of its eating sounds is a challenging task, as it plays an important role in avoiding allergic foods, providing dietary preferences to people who are restricted to a particular diet, showcasing its cultural significance, etc. In this research paper, the aim is to design a novel methodology that helps to identify food items by analyzing their eating sounds using various deep learning models. To achieve this objective, a system has been proposed that extracts meaningful features from food-eating sounds with the help of signal processing techniques and deep learning models for classifying them into their respective food classes. Initially, 1200 audio files for 20 food items labeled have been collected and visualized to find relationships between the sound files of different food items. Later, to extract meaningful features, various techniques such as spectrograms, spectral rolloff, spectral bandwidth, and mel-frequency cepstral coefficients are used for the cleaning of audio files as well as to capture the unique characteristics of different food items. In the next phase, various deep learning models like GRU, LSTM, InceptionResNetV2, and the customized CNN model have been trained to learn spectral and temporal patterns in audio signals. Besides this, the models have also been hybridized i.e. Bidirectional LSTM + GRU and RNN + Bidirectional LSTM, and RNN + Bidirectional GRU to analyze their performance for the same labeled data in order to associate particular patterns of sound with their corresponding class of food item. During evaluation, the highest accuracy, precision,F1 score, and recall have been obtained by GRU with 99.28%, Bidirectional LSTM + GRU with 97.7% as well as 97.3%, and RNN + Bidirectional LSTM with 97.45%, respectively. The results of this study demonstrate that deep learning models have the potential to precisely identify foods on the basis of their sound by computing the best outcomes.

Not a passive learner but an active one: a focus on the efficacy of philosophy-based language instruction and its consequences on EFL learners' critical thinking, engagement, and academic achievement

This study investigates the impact of Philosophy-Based Language Teaching (PBLT) on the critical thinking skills and learner engagement of English as a Foreign Language (EFL) students. A concurrent mixed-methods approach, including semi-structured interviews, document analysis, and academic achievement tests, was employed with an experimental group (EG) exposed to PBLT and a control group (CG) receiving traditional instruction. The results reveal a substantial positive effect of PBLT on the critical thinking abilities of EFL learners, as evidenced by thematic analyses of interviews and document content. Themes include heightened critical thinking awareness, collaborative knowledge construction, and increased learner engagement. Academic achievement tests further demonstrate significant improvement in the experimental group's performance. A comparison with existing literature underscores the novelty of our mixed-methods approach. Implications for language teachers, materials developers, syllabus designers, and policy-makers are discussed, highlighting the potential of PBLT in cultivating critical thinking and learner engagement.

Understanding the Modulation of α-Synuclein Fibrillation by N-Acetyl Aspartate: A Brain Metabolite

α-Synuclein (α-Syn) fibrillation is a prominent contributor to neuronal deterioration and plays a significant role in the advancement of Parkinson's Disease (PD). Considering this, the exploration of novel compounds that can inhibit or modulate the aggregation of α-Syn is a topic of significant research. This study, for the first time, elucidated the effect of N-acetyl aspartate (NAA), a brain osmolyte, on α-Syn aggregation using spectroscopic and microscopic approaches. Thioflavin T (ThT) assay revealed that a lower concentration of NAA inhibits α-Syn aggregation, whereas higher concentrations of NAA accelerate the aggregation. Further, this paradoxical effect of NAA was complemented by ANS, RLS, and the turbidity assay. The secondary structure transition was more pronounced at higher concentrations of NAA by circular dichroism, corroborating the fluorescence spectroscopic observations. Confocal microscopy also confirmed the paradoxical effect of NAA on α-Syn aggregation. Interaction studies including fluorescence quenching and molecular docking were employed to determine the binding affinity and critical residues involved in the α-Syn-NAA interaction. The explanation for this paradoxical nature of NAA could be a solvophobic effect. The results offer a profound understanding of the modulatory mechanism of α-Syn aggregation by NAA, thereby suggesting the potential role of NAA at lower concentrations in therapeutics against α-Syn aggregation-related disorders.

Knowledge, Perception, and Self-Confidence of Antibiotic Resistance, Appropriate Antibiotic Therapy, and Antibiotic Stewardship Among Undergraduate Pharmacy Students in Sudan

Background

Adequate training in infectious diseases and antibiotic resistance is crucial for pharmacy students to participate in antibiotic stewardship programs and understand microbiology careers.

Aim

The study was carried out to assess the knowledge and self-reported confidence in antibiotic resistance, antibiotic therapy, and antimicrobial stewardship (AMS) among final-year undergraduate pharmacy students in Sudan.

Methods

A cross-sectional study was conducted in three universities using a 57-item online questionnaire between April and May 2022.

Results

A total of 109 students (response rate 36%) participated and showed average knowledge scores of 5.6±1.7 (out of 10.0) for antibiotic resistance, 4.9±2.0 (out of 5.0) for appropriate antibiotic therapy, and 3.1±1.4 (out of 5.0) for AMS. No significant differences were observed among schools. Some students reported poor knowledge about antibiotic therapy and the consequences of resistance. One-third of students lacked confidence in interpreting microbiological results. Knowledge of antibiotic resistance among students' practice area after graduation was higher (p=0.017) and those interested in ID careers (5.8 vs 4.8) (p=0.037). Male students (5.6 vs 4.5) and those interested in ID careers (4.3 vs 3.4) (p<0.001) had higher scores of appropriate antibiotic therapy. Students attended antibiotic resistance courses (51.5 vs 45.2), and those interested in ID significantly had higher self-confidence (55.3 vs 45.8) (p=0.008).

Conclusion

Pharmacy students in Sudan have substantial knowledge of AMS and antibiotic resistance with poor knowledge of antibiotic therapy. Adequate training about infectious diseases and related topics is recommended to improve pharmacy students' understanding of microbiological findings, other competencies, and skills to incorporate in antimicrobial stewardship.

Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer

Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives. Deep learning models have uplifted the medical sector by providing promising results in diagnosing, detecting, and classifying diseases. This paper explores the role of deep learning techniques in detecting and classifying various parasitic organisms. The research works on a dataset consisting of 34,298 samples of parasites such as Toxoplasma Gondii, Trypanosome, Plasmodium, Leishmania, Babesia, and Trichomonad along with host cells like red blood cells and white blood cells. These images are initially converted from RGB to grayscale followed by the computation of morphological features such as perimeter, height, area, and width. Later, Otsu thresholding and watershed techniques are applied to differentiate foreground from background and create markers on the images for the identification of regions of interest. Deep transfer learning models such as VGG19, InceptionV3, ResNet50V2, ResNet152V2, EfficientNetB3, EfficientNetB0, MobileNetV2, Xception, DenseNet169, and a hybrid model, InceptionResNetV2, are employed. The parameters of these models are fine-tuned using three optimizers: SGD, RMSprop, and Adam. Experimental results reveal that when RMSprop is applied, VGG19, InceptionV3, and EfficientNetB0 achieve the highest accuracy of 99.1% with a loss of 0.09. Similarly, using the SGD optimizer, InceptionV3 performs exceptionally well, achieving the highest accuracy of 99.91% with a loss of 0.98. Finally, applying the Adam optimizer, InceptionResNetV2 excels, achieving the highest accuracy of 99.96% with a loss of 0.13, outperforming other optimizers. The findings of this research signify that using deep learning models coupled with image processing methods generates a highly accurate and efficient way to detect and classify parasitic organisms.

Recent advances in mRNA-based vaccine for cancer therapy; bench to bedside

The messenger RNA (mRNA) vaccines have progressed from a theoretical concept to a clinical reality over the last few decades. Compared to conventional vaccination methods, these vaccines have a number of benefits, such as substantial potency, rapid growth, inexpensive production, and safe administration. Nevertheless, their usefulness was restricted up to now due to worries about the erratic and ineffective circulation of mRNA in vivo. Thankfully, these worries have largely been allayed by recent technological developments, which have led to the creation of multiple mRNA vaccination platforms for cancer and viral infections. The mRNA vaccines have been demonstrated as a powerful alternative to traditional conventional vaccines because of their high potency, safety and efficacy, capacity for rapid clinical development, and potential for rapid, low-cost manufacturing. The paper will examine the present status of mRNA vaccine technology and suggest future paths for the advancement and application of this exciting vaccine platform as a common therapeutic choice.

Overview of reemerging mpox infection with a focus on neurological manifestations

Mpox, a reemerging zoonotic disease caused by the mpox virus, has garnered increasing attention due to its potential for severe clinical manifestations. While the cutaneous and systemic presentations of mpox have been well-documented, its neurological complications have recently emerged as an area of concern. This review provides a brief overview of the neurological aspects of mpox infection, highlighting the key findings and challenges in understanding and managing these complications. Neurological manifestations in mpox patients range from mild symptoms such as headaches and dizziness to more severe conditions, including encephalitis and seizures. The pathogenesis of neurological involvement is not yet fully elucidated but is thought to involve viral dissemination to the central nervous system. This dissemination may occur through haematogenous or neuronal routes, contributing to the diverse clinical spectrum observed. Early recognition and diagnosis of neurological complications in mpox are crucial for implementing appropriate therapeutic interventions and improving patient outcomes.

Optimal and total controllability approach of non-instantaneous Hilfer fractional derivative with integral boundary condition

The focus of this work is on the absolute controllability of Hilfer impulsive non-instantaneous neutral derivative (HINND) with integral boundary condition of any order. Total controllability refers to the system's ability to be controlled during the impulse time. Kuratowski measure and semigroup theory in Banach space yield the results. Furthermore, we talked about optimal controllability in conjunction with appropriate limitations. Our established outcomes are described using an example.

Telehealth-Enabled In-Home Elbow Rehabilitation for Brachial Plexus Injuries Using Deep-Reinforcement-Learning-Assisted Telepresence Robots

Due to damage to the network of nerves that regulate the muscles and feeling in the shoulder, arm, and forearm, brachial plexus injuries (BPIs) are known to significantly reduce the function and quality of life of affected persons. According to the World Health Organization (WHO), a considerable share of global disability-adjusted life years (DALYs) is attributable to upper limb injuries, including BPIs. Telehealth can improve access concerns for patients with BPIs, particularly in lower-middle-income nations. This study used deep reinforcement learning (DRL)-assisted telepresence robots, specifically the deep deterministic policy gradient (DDPG) algorithm, to provide in-home elbow rehabilitation with elbow flexion exercises for BPI patients. The telepresence robots were used for a six-month deployment period, and DDPG drove the DRL architecture to maximize patient-centric exercises with its robotic arm. Compared to conventional rehabilitation techniques, patients demonstrated an average increase of 4.7% in force exertion and a 5.2% improvement in range of motion (ROM) with the assistance of the telepresence robot arm. According to the findings of this study, telepresence robots are a valuable and practical method for BPI patients' at-home rehabilitation. This technology paves the way for further research and development in telerehabilitation and can be crucial in addressing broader physical rehabilitation challenges.

Perceived stress among dental students and the role of parental influence in career decision-making

OBJECTIVES

The current study aimed to assess perceived stress levels among dental students at Riyadh, Saudi Arabia, and to explore the influence of parental roles in their decision to pursue dentistry as a potential source of social stress.

METHODS

This cross-sectional study employed the validated Dental Environmental Stress (DES) Scale to evaluate perceived stress, and incorporated additional questions to fulfill the research aim. We approached all undergraduate dental students at King Saud University, both male and female, across all academic years, using online channels (such as emails, WhatsApp, Twitter, etc.) and hard copy distribution. Data collected were analyzed using SPSS version 20, utilizing descriptive and correlation statistics.

RESULTS

A total of 326 students participated in the study, with an even distribution of male and female students. Female students reported higher levels of stress compared to their male counterparts across most DES domains. A notable correlation emerged between mean DES scores in certain domains and influence of parents in the decision to pursue dentistry.

CONCLUSION

Our findings indicate that female dental students experience higher stress levels than males in all examined areas, barring social stressors. Furthermore, the study underscores the significant impact of parental involvement in choosing dentistry as a career on students' stress level.

Gold Fluorescence Nanoparticles for Enhanced SERS Detection in Biomedical Sensor Applications: Current Trends and Future Directions

Nanotechnology has emerged as a pivotal tool in biomedical research, particularly in developing advanced sensing platforms for disease diagnosis and therapeutic monitoring. Since gold nanoparticles are biocompatible and have special optical characteristics, they are excellent choices for surface-enhanced Raman scattering (SERS) sensing devices. Integrating fluorescence characteristics further enhances their utility in real-time imaging and tracking within biological systems. The synergistic combination of SERS and fluorescence enables sensitive and selective detection of biomolecules at trace levels, providing a versatile platform for early cancer diagnosis and drug monitoring. In cancer detection, AuNPs facilitate the specific targeting of cancer biomarkers, allowing for early-stage diagnosis and personalized treatment strategies. The enhanced sensitivity of SERS, coupled with the tunable fluorescence properties of AuNPs, offers a powerful tool for the identification of cancer cells and their microenvironment. This dual-mode detection not only improves diagnostic accuracy but also enables the monitoring of treatment response and disease progression. In drug detection, integrating AuNPs with SERS provides a robust platform for identifying and quantifying pharmaceutical compounds. The unique spectral fingerprints obtained through SERS enable the discrimination of drug molecules even in complex biological matrices. Furthermore, the fluorescence property of AuNPs makes it easier to track medication distribution in real-time, maximizing therapeutic effectiveness and reducing adverse effects. Furthermore, the review explores the role of gold fluorescence nanoparticles in photodynamic therapy (PDT). By using the complementary effects of targeted drug release and light-induced cytotoxicity, SERS-guided drug delivery and photodynamic therapy (PDT) can increase the effectiveness of treatment against cancer cells. In conclusion, the utilization of gold fluorescence nanoparticles in conjunction with SERS holds tremendous potential for revolutionizing cancer detection, drug analysis, and photodynamic therapy. The dual-mode capabilities of these nanomaterials provide a multifaceted approach to address the challenges in early diagnosis, treatment monitoring, and personalized medicine, thereby advancing the landscape of biomedical applications.

Investigation of Zika virus methyl transferase inhibitors using steered molecular dynamics

Zika virus (ZIKV) spread is considered a major public health threat by the World Health Organization (WHO). There are no vaccines or drugs available to control the infection of the Zika virus, therefore a highly effective medicinal molecule is urgently required. In this study, a computationally intensive investigation was performed to identify a potent natural compound that could inhibit the ZIKV NS5 methyltransferase. This research approach is based on target-based drug identification principles where the native inhibitor SAH (S-adenosylhomocysteine) of ZIKV NS5 methyltransferase was selected as a reference. High-throughput virtual screening and tanimoto similarity coefficient were applied to the natural compound library for ranking the potential candidates. The top five compounds were selected for interaction analysis, MD simulation, total binding free energy through MM/GBSA, and steered MD simulation. Among these compounds, Adenosine 5'-monophosphate monohydrate, Tubercidin, and 5-Iodotubercidin showed stable binding to the protein compared to the native compound, SAH. These three compounds also showed less fluctuations in RMSF in contrast to native compound. Additionally, the same interacting residues observed in SAH also made strong interactions with these three compounds. Adenosine 5'-monophosphate monohydrate and 5-Iodotubercidin had greater total binding free energies than the reference ligand. Moreover, the dissociation resistance of all three compounds was equivalent to that of the reference ligand. This study suggested binding properties of three-hit compounds that could be used to develop drugs against Zika virus infections.Communicated by Ramaswamy H. Sarma.

Slipped capital femoral epiphysis in a 5-year-old boy with cerebral palsy on valproic acid and levetiracetam for epilepsy: a case report

This study presents a rare case of unilateral slipped capital femoral epiphysis treated surgically in a 5-year-old boy with cerebral palsy who was born at 27 weeks' gestation and developed grade III intraventricular haemorrhage and periventricular leucomalacia and was on antiepileptic drugs, including valproic acid and levetiracetam for >3 years. The patient had no history of endocrine, renal, and significant familial diseases.

Semi-synthesis, α-amylase inhibition, and kinetic and molecular docking studies of arylidene-based sesquiterpene coumarins isolated from Ferula tunetana Pomel ex Batt

Despite all the significant progresses made to enhance the efficacy of the existing bank of drugs used to manage and cure type II diabetes mellitus, there is still a need to search and develop novel bioactive compounds with superior efficacy and minimal adverse effects. This study describes the valorization of the natural bioactive sesquiterpene coumarin via the semi-synthesis of new analogs and the study of their α-amylase inhibition activity. The sesquiterpene coumarin named coladonin (1) was quantitatively isolated from the chloroform extract of endemic Ferula tunetana roots. Subsequently, the oxidation of 1via the Jones oxidation reaction, used as a key reaction, afforded precursor 2. The condensation of oxidized coladonin (2) with various aryl aldehydes provided a series of new arylidene-based sesquiterpene coumarin derivatives (3a-m), which were characterized by NMR and ESI-HRMS experiments. All derivatives evaluated in vitro for their α-amylase inhibitory potential showed interesting α-amylase inhibition with IC50 values ranging from 7.24 to 28.98 μM. Notably, compounds 3k and 3m exhibited lower IC50 values (7.24 μM and 8.38 μM, respectively) compared to the standard (acarbose: IC50 = 9.83 μM). In addition, the structure-activity relationship (SAR) for all the compounds was studied. The most active compounds were found to be mixed-type inhibitors, which was revealed by kinetic studies. Furthermore, molecular in silico docking studies were established for all synthesized analogs with the binding site for the α-amylase enzyme.

Exact solutions of the (3+1)-generalized fractional nonlinear wave equation with gas bubbles

In this manuscript, we implement the travelling wave solutions of the fractional (3+1) generalized computational nonlinear wave equation with gas bubbles via application of five mathematical methods. Liquids with gas bubbles primarily arise in various applications like science, engineering, and mathematical physics. The obtained solitary waves solutions have fruitful applications in engineering, science, life, nature and physics. Several novel soliton solutions of concerned model are established in the form of hyperbolic, trigonometric, exponential and rational functions. To handle all calculations and verification of obtained results, computational software Mathematica 12.1 is used. For the demonstration of the physical behaviour of concern model, some solutions are plotted graphical in 2-dimensional and 3-dimensional by imparting specific values to the parameters under constrain conditions. Finally, we intrigue both two and three dimensional to explain the physical behavior of the model.

Recent Progress in Prompt Molecular Detection of Exosomes Using CRISPR/Cas and Microfluidic-Assisted Approaches Toward Smart Cancer Diagnosis and Analysis

Exosomes are essential indicators of molecular mechanisms involved in interacting with cancer cells and the tumor environment. As nanostructures based on lipids and nucleic acids, exosomes provide a communication pathway for information transfer by transporting biomolecules from the target cell to other cells. Importantly, these extracellular vesicles are released into the bloodstream by the most invasive cells, i. e., cancer cells; in this way, they could be considered a promising specific biomarker for cancer diagnosis. In this matter, CRISPR-Cas systems and microfluidic approaches could be considered practical tools for cancer diagnosis and understanding cancer biology. CRISPR-Cas systems, as a genome editing approach, provide a way to inactivate or even remove a target gene from the cell without affecting intracellular mechanisms. These practical systems provide vital information about the factors involved in cancer development that could lead to more effective cancer treatment. Meanwhile, microfluidic approaches can also significantly benefit cancer research due to their proper sensitivity, high throughput, low material consumption, low cost, and advanced spatial and temporal control. Thereby, employing CRISPR-Cas- and microfluidics-based approaches toward exosome monitoring could be considered a valuable source of information for cancer therapy and diagnosis. This review assesses the recent progress in these promising diagnosis approaches toward accurate cancer therapy and in-depth study of cancer cell behavior.

Progress and Perspectives on Promising Covalent-Organic Frameworks (COFs) Materials for Energy Storage Capacity

In recent years, a new class of highly crystalline advanced permeable materials covalent-organic frameworks (COFs) have garnered a great deal of attention thanks to their remarkable properties, such as their large surface area, highly ordered pores and channels, and controllable crystalline structures. The lower physical stability and electrical conductivity, however, prevent them from being widely used in applications like photocatalytic activities and innovative energy storage and conversion devices. For this reason, many studies have focused on finding ways to improve upon these interesting materials while also minimizing their drawbacks. This review article begins with a brief introduction to the history and major milestones of COFs development before moving on to a comprehensive exploration of the various synthesis methods and recent successes and signposts of their potential applications in carbon dioxide (CO2 ) sequestration, supercapacitors (SCs), lithium-ion batteries (LIBs), and hydrogen production (H2 -energy). In conclusion, the difficulties and potential of future developing with highly efficient COFs ideas for photocatalytic as well as electrochemical energy storage applications are highlighted.

Chemistry Aspects and Designing Strategies of Flexible Materials for High-Performance Flexible Lithium-Ion Batteries

In recent years, flexible and wearable electronics such as smart cards, smart fabrics, bio-sensors, soft robotics, and internet-linked electronics have impacted our lives. In order to meet the requirements of more flexible and adaptable paradigm shifts, wearable products may need to be seamlessly integrated. A great deal of effort has been made in the last two decades to develop flexible lithium-ion batteries (FLIBs). The selection of suitable flexible materials is important for the development of flexible electrolytes self-supported and supported electrodes. This review is focused on the critical discussion of the factors that evaluate the flexibility of the materials and their potential path toward achieving the FLIBs. Following this analysis, we present how to evaluate the flexibility of the battery materials and FLIBs. We describe the chemistry of carbon-based materials, covalent-organic frameworks (COFs), metal-organic frameworks (MOFs), and MXene-based materials and their flexible cell design that represented excellent electrochemical performances during bending. Furthermore, the application of state-of-the-art solid polymer and solid electrolytes to accelerate the development of FLIBs is introduced. Analyzing the contributions and developments of different countries has also been highlighted in the past decade. In addition, the prospects and potential of flexible materials and their engineering are also discussed, providing the roadmap for further developments in this fast-evolving field of FLIB research.

Drug Polymeric Carrier of Aceclofenac Based on Amphiphilic Chitosan Micelles

Amphiphilic micelles based on chitosan (CS) were applied as drug carriers of aceclofenac (ACF) as a potential method to induce its bioavailability and therapeutic efficiency. N-octyl-N,O-succinyl CS (OSCS), an amphiphilic CS derivative, was successfully synthesized and loaded physically by ACF at different pH values and using different dosages of ACF, forming ACF-loaded polymeric micelles (PMs). The obtained PMs and ACF-loaded PMs were characterized by different analytical techniques, including AFM, TEM, DLS, UV-vis spectrophotometry, 1H NMR spectroscopy, and FT-IR spectroscopy. The pH 5 sample with a 30% ACF/polymer ratio showed the highest ACF loading capacity (LC) and entrapment efficiency (EE). In vitro release behaviors of pure ACF and ACF-loaded PMs at each release point indicated that the release profile of pH-responsive PMs loaded with ACF demonstrated quicker release rates (94% after 480 min) compared to the release behavior noticed for free ACF (59.56% after 480 min). Furthermore, the release rates exhibit a notable rise when the pH is increased from 1.2 to 4.7. In the carrageenan-induced inflammation model of paw edema in rats, it has been demonstrated that the injection of ACF-loaded PMs (at a dose of 10 mg/kg) resulted in a strengthened inflammatory activity compared to the injection of free ACF at equivalent dosages as well as at time intervals. However, the use of ACF-loaded PMs for a duration of 6 h displayed a notable reduction of paw edema, with an inhibition percentage of 85.09%, in contrast to the 74.9% inhibition percentage observed for the free ACF medication.

Emerging Role of Long Noncoding RNAs in Regulating Inflammasome-Mediated Neurodegeneration in Parkinson's Disease

Parkinson's disease (PD) is one of the complex neurodegenerative disorders, primarily characterized by motor deficits, including bradykinesia, tremor, rigidity, and postural instability. The underlying pathophysiology involves the progressive loss of dopaminergic neurons within the substantia nigra pars compacta, leading to dopamine depletion in the basal ganglia circuitry. While motor symptoms are hallmark features of PD, emerging research highlights a wide range of non-motor symptoms, including cognitive impairments, mood disturbances, and autonomic dysfunctions. Inflammasome activation is pivotal in inducing neuroinflammation and promoting disease onset, progression, and severity of PD. Several studies have shown that long noncoding RNAs (lncRNAs) modulate inflammasomes in the pathogenesis of neurodegenerative diseases. Dysregulation of lncRNAs is linked to aberrant gene expression and cellular processes in neurodegeneration, causing the activation of inflammasomes that contribute to neuroinflammation and neurodegeneration. Inflammasomes are cytosolic proteins that form complexes upon activation, inducing inflammation and neuronal cell death. This review explores the significance of lncRNAs in regulating inflammasomes in PD, primarily focusing on specific lncRNAs such as nuclear paraspeckle assembly transcript 1 (NEATNEAT1), X-inactive specific transcript (XIST), growth arrest-specific 5 (GAS5), and HOX transcript antisense RNA (HOTAIR), which have been shown to activate or inhibit the NLRP3 inflammasome and induce the release of proinflammatory cytokines. Moreover, some lncRNAs mediate inflammasome activation through miRNA interactions. Understanding the roles of lncRNAs in inflammasome regulation provides new therapeutic targets for controlling neuroinflammation and reducing the progression of neurodegeneration. Identifying lncRNA-mediated regulatory pathways paves the way for novel therapies in the battle against these devastating neurodegenerative disorders.

On estimation of P(Y < X) for inverse Pareto distribution based on progressively first failure censored data

The stress-strength reliability (SSR) model ϕ = P(Y < X) is used in numerous disciplines like reliability engineering, quality control, medical studies, and many more to assess the strength and stresses of the systems. Here, we assume X and Y both are independent random variables of progressively first failure censored (PFFC) data following inverse Pareto distribution (IPD) as stress and strength, respectively. This article deals with the estimation of SSR from both classical and Bayesian paradigms. In the case of a classical point of view, the SSR is computed using two estimation methods: maximum product spacing (MPS) and maximum likelihood (ML) estimators. Also, derived interval estimates of SSR based on ML estimate. The Bayes estimate of SSR is computed using the Markov chain Monte Carlo (MCMC) approximation procedure with a squared error loss function (SELF) based on gamma informative priors for the Bayesian paradigm. To demonstrate the relevance of the different estimates and the censoring schemes, an extensive simulation study and two pairs of real-data applications are discussed.

Radix-4 CORDIC algorithm based low-latency and hardware efficient VLSI architecture for Nth root and Nth power computations

In this article, a low-complexity VLSI architecture based on a radix-4 hyperbolic COordinate Rotion DIgital Computer (CORDIC) is proposed to compute the [Formula: see text] root and [Formula: see text] power of a fixed-point number. The most recent techniques use the radix-2 CORDIC algorithm to compute the root and power. The high computation latency of radix-2 CORDIC is the primary concern for the designers. [Formula: see text] root and [Formula: see text] power computations are divided into three phases, and each phase is performed by a different class of the proposed modified radix-4 CORDIC algorithms in the proposed architecture. Although radix-4 CORDIC can converge faster with fewer recurrences, it demands more hardware resources and computational steps due to its intricate angle selection logic and variable scale factor. We have employed the modified radix-4 hyperbolic vectoring (R4HV) CORDIC to compute logarithms, radix-4 linear vectoring (R4LV) to perform division, and the modified scaling-free radix-4 hyperbolic rotation (R4HR) CORDIC to compute exponential. The criteria to select the amount of rotation in R4HV CORDIC is complicated and depends on the coordinates [Formula: see text] and [Formula: see text] of the rotating vector. In the proposed modified R4HV CORDIC, we have derived the simple selection criteria based on the fact that the inputs to R4HV CORDIC are related. The proposed criteria only depend on the coordinate [Formula: see text] that reduces the hardware complexity of the R4HV CORDIC. The R4HR CORDIC shows the complex scale factor, and compensation of such scale factor necessitates the complex hardware. The complexity of R4HR CORDIC is reduced by pre-computing the scale factor for initial iterations and by employing scaling-free rotations for later iterations. Quantitative hardware analysis suggests better hardware utilization than the recent approaches. The proposed architecture is implemented on a Virtex-6 FPGA, and FPGA implementation demonstrates [Formula: see text] less hardware utilization with better error performance than the approach with the radix-2 CORDIC algorithm.

Cobalt and Titanium Alleviate the Methylglyoxal-Induced Oxidative Stress in Pennisetum divisum Seedlings under Saline Conditions

Salinity is considered to be a global problem and a severe danger to modern agriculture since it negatively impacts plants' growth and development at both cellular- and whole-plant level. However, cobalt (Co) and titanium (Ti), multifunctional non-essential micro-elements, play a crucial role in improving plant growth and development under salinity stress. In the current study, Co and Ti impact on the morphological, biochemical, nutritional, and metabolic profile of Pennisetum divisum plants under three salinity levels which were assessed. Two concentrations of Co (Co-1; 15.0 mg/L and Co-2; 25.0 mg/L), and two concentrations of Ti (Ti-1; 50.0 mg/L and Ti-2; 100.0 mg/L) were applied as foliar application to the P. divisum plants under salinity (S1; 200 mM, S2; 500 mM, and S3; 1000 mM) stress. The results revealed that various morphological, biochemical, and metabolic processes were drastically impacted by the salinity-induced methylglyoxal (MG) stress. The excessive accumulation of salt ions, including Na+ (1.24- and 1.21-fold), and Cl- (1.53- and 1.15-fold) in leaves and roots of P. divisum, resulted in the higher production of MG (2.77- and 2.95-fold) in leaves and roots under severe (1000 mM) salinity stress, respectively. However, Ti-treated leaves showed a significant reduction in ionic imbalance and MG concentrations, whereas considerable improvement was shown in K+ and Ca2+ under salinity stress, and Co treatment showed downregulation of MG content (26, 16, and 14%) and improved the antioxidant activity, such as a reduction in glutathione (GSH), oxidized glutathione (GSSG), Glutathione reductase (GR), Glyoxalase I (Gly I), and Glyoxalase II (Gly II) by up to 1.13-, 1.35-, 3.75-, 2.08-, and 1.68-fold under severe salinity stress in P. divisum roots. Furthermore, MG-induced stress negatively impacted the metabolic profile and antioxidants activity of P. divisum's root and leaves; however, Co and Ti treatment considerably improved the biochemical processes and metabolic profile in both underground and aerial parts of the studied plants. Collectively, the results depicted that Co treatment showed significant results in roots and Ti treatment presented considerable changes in leaves of P. divism under salinity stress.

Electrochemical Detection of 4-Nitrophenol Using a Novel SrTiO3/Ag/rGO Composite

In this study, an eco-friendly strategy was used to prepare a novel SrTiO3/Ag/rGO composite. A SrTiO3/Ag/rGO composite-modified screen-printed carbon electrode (SPCE) was applied for the electrochemical detection of 4-nitrophenol. A simple ultrasonic method with an ultrasonic frequency of 20 kHz was used for the synthesis of SrTiO3/Ag/rGO composite material. The obtained SrTiO3/Ag/rGO composite was characterized by X-ray diffraction, Fourier transform infrared, Raman spectroscopy, field emission electron microscopy, and UV-visible spectroscopy. Electrochemical impedance spectroscopy was used to determine the electrical conductivity of the SrTiO3/Ag/rGO composite. The electrochemical properties of the modified electrode were studied using cyclic voltammetry as well as linear sweep voltammetry techniques. In comparison to SrTiO3/SPCE, SrTiO3/Ag/SPCE, and SrTiO3/rGO/SPCE electrodes, SrTiO3/Ag/rGO/SPCE demonstrates a considerable increase in 4-nitrophenol redox peak current. At optimum conditions, a large linear response range of 0.1-1000 M, with a relatively low limit of detection (0.03 M), outperforms the previously published modified electrode for 4-nitrophenol. Moreover, the SrTiO3/Ag/rGO/SPCE electrode-based 4-nitrophenol sensor is distinguished by good selectivity, high stability, and repeatability. Furthermore, SrTiO3/Ag/rGO/SPCE contributed to the detection of 4-nitrophenol in river water and drinking water with the recovery range from 97.5 to 98.7%. The experimental finding was supported by density functional theory calculation.

Exploration of phytochemical compounds against Marburg virus using QSAR, molecular dynamics, and free energy landscape

Marburg virus disease (MVD) is caused by the Marburg virus, a one-of-a-kind zoonotic RNA virus from the genus Filovirus. Thus, this current study employed AI-based QSAR and molecular docking-based virtual screening for identifying potential binders against the target protein (nucleoprotein (NP)) of the Marburg virus. A total of 2727 phytochemicals were used for screening, out of which the top three compounds (74977521, 90470472, and 11953909) were identified based on their predicted bioactivity (pIC50) and binding score (< - 7.4 kcal/mol). Later, MD simulation in triplicates and trajectory analysis were performed which showed that 11953909 and 74977521 had the most stable and consistent complex formations and had the most significant interactions with the highest number of hydrogen bonds. PCA (principal component analysis) and FEL (free energy landscape) analysis indicated that these compounds had favourable energy states for most of the conformations. The total binding free energy of the compounds using the MM/GBSA technique showed that 11953909 (ΔGTOTAL = - 30.78 kcal/mol) and 74977521 (ΔGTOTAL = - 30 kcal/mol) had the highest binding affinity with the protein. Overall, this in silico pipeline proposed that the phytochemicals 11953909 and 74977521 could be the possible binders of NP. This study aimed to find phytochemicals inhibiting the protein's function and potentially treating MVD.

Development of Gefitinib-Loaded Solid Lipid Nanoparticles for the Treatment of Breast Cancer: Physicochemical Evaluation, Stability, and Anticancer Activity in Breast Cancer (MCF-7) Cells

In the current study, the toxic effects of gefitinib-loaded solid lipid nanoparticles (GFT-loaded SLNs) upon human breast cancer cell lines (MCF-7) were investigated. GFT-loaded SLNs were prepared through a single emulsification-evaporation technique using glyceryl tristearate (Dynasan™ 114) along with lipoid® 90H (lipid surfactant) and Kolliphore® 188 (water-soluble surfactant). Four formulae were developed by varying the weight of the lipoid™ 90H (100-250 mg), and the GFT-loaded SLN (F4) formulation was optimized in terms of particle size (472 ± 7.5 nm), PDI (0.249), ZP (-15.2 ± 2.3), and EE (83.18 ± 4.7%). The optimized formulation was further subjected for in vitro release, stability studies, and MTT assay against MCF-7 cell lines. GFT from SLNs exhibited sustained release of the drug for 48 h, and release kinetics followed the Korsmeyer-Peppas model, which indicates the mechanism of drug release by swelling and/or erosion from a lipid matrix. When pure GFT and GFT-SLNs were exposed to MCF-7 cells, the activities of p53 (3.4 and 3.7 times), caspase-3 (5.61 and 7.7 times), and caspase-9 (1.48 and 1.69 times) were enhanced, respectively, over those in control cells. The results suggest that GFT-loaded SLNs (F4) may represent a promising therapeutic alternative for breast cancer.

Thermally tunable electromagnetic surface waves supported by graphene loaded indium antimonide (InSb) interface

The thermal agitation plays a vital role in tunability of optoelectronic, structural and chemical characteristics of the temperature sensitive materials. Graphene enables the THz optics, due to its unprecedent controlling characteristics over the traditional materials. The influence of temperature on the monolayer graphene is very negligible due to its low free charge carrier density, to enhance the thermal sensitivity of graphene, the graphene loaded temperature sensitive material interface has been proposed. A theoretical analysis has been carried out on temperature dependent propagation characteristics of electromagnetic surface waves supported by the graphene loaded semi-infinite indium antimonide (InSb). The InSb has been taken as temperature sensitive material. The Drude model has been used for the modeling of InSb in the THz region while the modeling of the graphene has been done by random phase approximation-based Kubo's formulism. To realize the graphene loaded indium antimonide interface, the impedance boundary conditions (IBCs) have been employed. The numerical analysis has been conducted to analyze the influence of temperature on the characteristics of electromagnetic surface waves i.e., dispersion curve, effective mode index (Neff), penetration depth (δ), propagation length (Lp), phase speed (Vp) and field profile, propagating along the graphene loaded InSb. In all the numerical results, the temperature variation has been considered from 200 to 350 K. It has been concluded that the graphene-InSb interface provides more temperature assisted tunability to the interfacial surface modes, commonly known as surface waves, as compared to monolayer graphene. Further, the graphene parameters can play a vital role in the dynamical tuning of electromagnetic surface waves in THz to IR frequency range. The numerically computed results have potential applications in designing of thermo-optical waveguides, temperature assisted communication devices, thermo-optical sensors and near field thermal imaging platforms.

Quantification of Suvorexant in Human Urine Using a Validated HPTLC Bioanalytical Method

Suvorexant (SUV) is a new sedative/hypnotic medicine that is recommended to treat insomnia. It is an important medicine from a forensic point of view due to its sedative/hypnotic and depressant effects. To the best of our knowledge, high-performance thin-layer chromatography (HPTLC) bioanalytical methods have not been published to measure SUV in human urine and pharmaceutical samples. Accordingly, this study was designed and validated a sensitive and rapid bioanalytical HPTLC method to determine SUV in human urine samples for the very first time. The densitometric measurement of SUV and the internal standard (IS; sildenafil) was performed on glass-coated silica gel normal-phase-60F254S TLC plates using a mixture of chloroform and methanol (97.5:2.5 v/v) as the eluent system. Both the SUV and IS were detected at a wavelength of 254 nm. Both analytes were extracted using the protein precipitation technique utilizing methanol as the solvent. For the IS and SUV, the Rf values were 0.09 and 0.45, respectively. The proposed bioanalytical method for SUV was linear in the 50-1600 ng/band range. The current bioanalytical technique was linear, precise (% RSD = 3.28-4.20), accurate (% recovery = 97.58-103.80), robust (% recovery = 95.31-102.34 and % RSD = 2.81-3.15), rapid, and sensitive (LOD = 3.73 ng/band and LOQ = 11.20 ng/band). These findings suggested that the current bioanalytical method can be regularly used to determine SUV in wide varieties of urine samples.

Synthesis, biological activities, and future perspectives of steroidal monocyclic pyridines

Steroidal pyridines are a class of compounds that have been the subject of extensive research in recent years due to their potential biological activities. The introduction of a pyridine ring into the steroid skeleton can significantly alter the chemical and biological properties of the compound, making it more potent and/or selective for a particular target. Different synthetic methods have been developed for the preparation of steroidal pyridines. This review provides an overview of the synthesis, biological activities, and future perspectives of steroidal monocyclic dihydropyridines, tetrahydropyridines, and pyridines from 2005 to the present. The different synthetic methods that have been developed for the preparation of these steroids are discussed, as well as the proposed mechanisms and the biological activities that have been reported. Finally, the potential of steroidal monocyclic pyridines for the development of new drugs is discussed. This review is intended to provide a comprehensive overview of the field of steroidal monocyclic pyridines for researchers and scientists who are interested in this area of research. It is also hoped that this review will stimulate further research into the synthesis and biological activities of steroidal pyridines to develop new and improved drugs for the treatment of diseases.

Inquiring asymmetric effects of oil prices, money supply, and domestic debt on consumer prices: an empirical evidence from Pakistan

Oil prices (OP) may play a significant role in determining inflation in any oil-importing economy and could have an asymmetrical effect as well. Thus, this paper aims to explore the asymmetric influence of OP, broad money supply (BMS), and domestic debt (DD) on the Consumer Price Index (CPI) in the oil-importing economy of Pakistan using the nonlinear autoregressive distributive lag (NARDL) methodology on an annual sample from 1980 to 2021. The long-run results show that increasing OP and BMS have a positive effect on CPI. Similarly, decreasing OP and BMS have a positive effect on CPI. So, increasing OP and BMS is raising price levels, and decreasing OP and BMS is reducing price levels. OP has a positive and symmetrical effect on CPI. However, the BMS has a positive but asymmetrical effect on CPI. Furthermore, the effect of decreasing BMS is found greater than increasing BMS. Moreover, the effect of DD on CPI is also found asymmetrical. The increasing DD has a positive effect, and decreasing DD has a negative effect on CPI. The most of short-run results follow the long-run results. However, energy usage shows a negative effect on CPI in the short run, which is insignificant in the long-run results. This study recommends controlling the money supply and oil prices to reduce consumer prices.

Potential role of tocopherol in protecting crop plants against abiotic stresses

The changing global climate have given rise to abiotic stresses that adversely affect the metabolic activities of plants, limit their growth, and agricultural output posing a serious threat to food production. The abiotic stresses commonly lead to production of reactive oxygen species (ROS) that results in cellular oxidation. Over the course of evolution, plants have devised efficient enzymatic and non-enzymatic anti-oxidative strategies to counteract harmful effects of ROS. Among the emerging non-enzymatic anti-oxidative technologies, the chloroplast lipophilic antioxidant vitamin A (Tocopherol) shows great promise. Working in coordination with the other cellular antioxidant machinery, it scavenges ROS, prevents lipid peroxidation, regulates stable cellular redox conditions, simulates signal cascades, improves membrane stability, confers photoprotection and enhances resistance against abiotic stresses. The amount of tocopherol production varies based on the severity of stress and its proposed mechanism of action involves arresting lipid peroxidation while quenching singlet oxygen species and lipid peroxyl radicals. Additionally, studies have demonstrated its coordination with other cellular antioxidants and phytohormones. Despite its significance, the precise mechanism of tocopherol action and signaling coordination are not yet fully understood. To bridge this knowledge gap, the present review aims to explore and understand the biosynthesis and antioxidant functions of Vitamin E, along with its signal transduction and stress regulation capacities and responses. Furthermore, the review delves into the light harvesting and photoprotection capabilities of tocopherol. By providing insights into these domains, this review offers new opportunities and avenues for using tocopherol in the management of abiotic stresses in agriculture.

Reinvigorating the environmental Kuznets curve hypothesis in the context of highly polluted nations: evidence using advanced panel estimation techniques

China, United States, India, Russia, and Japan are regarded as the top five carbon dioxide-emitting nations in the world. These countries altogether account for more than half of the global annual discharges of carbon dioxide. Consequently, impeding the carbon emission-led environmental adversities in these countries is of critical emphasis for establishing environmental sustainability worldwide. In this regard, this study checks how economic progress, energy use intensification, and renewable energy use affect the annual growth rates of per capita carbon dioxide emission in these highly-polluted economies considering the study period from 1990 to 2021. Besides, for analytical purposes, advanced panel data estimation techniques have been utilized for detecting and neutralizing the impacts of cross-sectional dependency and slope heterogeneity-related problems in the data. Overall, the findings endorse that economic progress deteriorates environmental quality both in the short and long run. However, since the long-run unfavorable environmental impacts of economic growth are relatively lower compared with the short-run impacts, the environmental Kuznets curve hypothesis can be deemed valid. Besides, more intensive use of energy resources is witnessed to impose negative long-run environmental consequences while the adoption of renewable energy instead of fossil fuels is found to improve environmental well-being, both in the short and long run. Furthermore, the results affirm that economic progress and energy use intensification jointly degrade environmental conditions. By contrast, economic progress alongside greater adoption of renewable energy is observed to inflict an environmental quality-improving effect. Considering these findings, a couple of carbon dioxide mitigating policies are suggested to the concerned highly polluted developed and developing nations.

Potential impacts of Russo-Ukraine conflict and its psychological consequences among Ukrainian adults: the post-COVID-19 era

Background

Since February 2022, the nation of Ukraine has become entangled in an escalating conflict that erupted after coronavirus outbreak fostering a situation of indeterminacy and precariousness, which adversely affected several facets, especially psychological well-being. However, there is a lack of empirical evidence on the psychological well-being of Ukrainians during the Russo-Ukraine war, as well as their coping strategies in response to the war's repercussions. Consequently, this investigation endeavors to explore the prevalence of symptoms associated with depression, anxiety, stress, and insomnia and to correlate these symptoms with Ukrainians' effective coping mechanisms during the ongoing war.

Methods

An online survey was administered in Ukraine from June to August 2022 due to the ongoing Russo-Ukraine conflict. The survey employed a quota sampling technique, targeting 2,664 individuals (≥18 years). Out of the total sample, 1,833 valid responses were obtained, yielding a response rate of 68. 81%. Depression, anxiety, and stress were measured using the depression, anxiety, and stress scale-21 (DASS-21), while the Pittsburgh sleep quality index (PSQI) was utilized to evaluate insomnia symptoms. In addition, Brief-COPE was adopted to evaluate the coping mechanisms of the selected study participants.

Results

Of 1,833 Ukrainian adults, 60.5% had symptoms of stress; 62.4% of them reported symptoms of anxiety; and 58.2% reported symptoms of depression. Symptom criteria for insomnia were found in about 21.8% of the study sample. The factors of sex, living area, area occupied by Russian forces, and having older adults and children in the house were statistically significant with symptoms of depression, anxiety, stress, and insomnia. The productive coping strategies of self-distraction, using instrumental support, planning, and behavioral disengagement, were observed as statistically significant with four psychological constructs.

Conclusion

The study outcomes highlight a substantial prevalence of symptoms related to depression, anxiety, stress, and insomnia attributed to the accumulated consequences of ongoing conflict and the COVID-19 outbreak. The aforementioned findings emphasize the imperative of providing healthcare services and facilitating effective coping strategies among Ukrainians amid the ongoing war.

Seroprevalence, Risk Factors and Maternal-Fetal Outcomes of Toxoplasma gondii in Pregnant Women from WHO Eastern Mediterranean Region: Systematic Review and Meta-Analysis

BACKGROUND

The protozoan parasite Toxoplasma gondii may cause serious illness in the immunocompromised. The Toxoplasma gondii seropositive prevalence in pregnant women in WHO Eastern Mediterranean Region countries is inconsistent in the literature and it is associated with outcomes that have not be fully elucidated, hence the need for a better understanding of the pooled seroprevalence and associated maternal and fetal outcomes.

OBJECTIVE

The objective was to conduct a systematic literature review and determine the pooled prevalence of WHO Eastern Mediterranean Regional countries' pregnant women's seroprevalence of Toxoplasma gondii and the maternal-fetal outcomes.

METHODS

This quantitative study examined WHO Eastern Mediterranean countries' maternal-fetal outcomes and Toxoplasma gondii prevalence in pregnant women. The targeted population was pregnant women, while the primary outcome was seropositivity of Toxoplasma gondii, while other outcomes such as maternal and fetal associations and risk factors were determined PubMed, SCOPUS, MEDLINE, and Index Medicus for the Eastern Mediterranean Region (IMEMR) databases were searched up until 30 January 2023. The search terms used were "Toxoplasma gondii" OR "Toxoplasma infection" AND "Pregnant woman" or pregnan* OR Antenatal OR Prenatal OR Gravidity OR Parturition OR Maternal AND WHO Eastern Mediterranean Region). OpenMeta-Analyst and Jamovi were used to analyze the generated data.

RESULTS

In total, 95 of 2947 articles meeting the inclusion criteria examined Toxoplasma gondii prevalence in pregnant women from WHO Eastern Mediterranean countries. The pooled prevalence of Toxoplasma gondii in pregnant women was 36.5% (95%CI: 32.6-40.4) with a median value of 35.64%, range values of 1.38-75.30%, with 99.61% heterogeneity. The pooled seroprevalence of IgG of Toxoplasma gondii was 33.5% (95%CI: 29.8-37.2) with a median value of 33.51%, and a range values of 1.38-69.92%; the pooled seroprevalence of IgM was 3.6% (95%CI: 3.1-4.1)) with a median value of 3.62 and range values of 0.20-17.47%, while cases of pooled seroprevalence of both IgG and IgM positivity was 3.0% (95%CI: 1.9-4.4) with a median value of 2.05 and a range values of 0.05-16.62%. Of the Toxoplasma gondii seropositive women, 1281/3389 (34.8%) 174/1765 (32.9%), 1311/3101 (43.7%), and 715/1683 (40.8%) of them had contact with cats, drank unprocessed milk, ate raw or undercooked meat and ate unwashed raw vegetables, respectively. The maternal-fetal outcomes associated with Toxoplasma gondii seropositivity were a history of abortions, miscarriage, stillbirth, intrauterine fetal death, and premature birth, which were found in 868/2990 (32.5%), 112/300 (36.1%), 111/375 (25.7%), 3/157 (1.9%) and 96/362 (20.1%) of women who tested positive for Toxoplasma gondii antibodies.

CONCLUSION

The study found a high proportion of Toxoplasma gondii seroprevalence in pregnant women in the WHO Eastern Mediterranean Region, which may be linked to poor outcomes for mothers and their babies. Thus, pregnant women require monitoring and comprehensive prevention strategies for Toxoplasma gondii infection.

Impact of forestry on environment and human health: an evidence-based investigation

There is an increasing interest in the health effects of the forest. Without active participation in forestry, conflicts between the various stakeholders are foreseeable. The impact of forests on human life is unforgettable, and everyone gets enormous benefits from trees and greenery. COVID-19 has caused many changes in human behavior, which needs much attention. Environmental change's impact is considered a better solution and influences human behavior. Scientists around the globe are conducting research experiments on trees and the effect of forestry on human health, which is increasing in terms of social, ecological, and economic services. Trees provide full support to enhance the quality of life and minimize air pollution. Forests must be noticed to get benefits (e.g., carbon storage, fruits, human health considerations, economic benefits, and biodiversity). This research aims to explain the area of forest and health from the perspective of Saudi Arabian forestry and develop strategic measures for the proactive design of this topic. The research entailed expert interviews with forestry representatives and a quantitative survey of medical students. Our findings show that implementing strategic measures, such as establishing a forest and health, improves health and eliminates air pollution. It shows many other establishment and planning strategies, such as the use of professional visitor monitoring, the development of product innovations, the use of digitalization, and the development of integrated forest management.

The effects of Capsicum annuum supplementation on lipid profiles in adults with metabolic syndrome and related disorders: A systematic review and meta-analysis of randomized controlled trials

The electiveness of Capsicum annuum supplementation in controlling dyslipidemia in adults has been unclear. Therefore, this meta-analysis focuses on the relationship between C. annuum supplementation and lipid profile in adults with metabolic syndrome (MetS) and related disorders. PubMed, Scopus, ISI Web of Science, and the Cochrane Library were searched up to March 2021. Only randomized controlled trials (RCTs) studying the administration of C. annuum compared to control on lipid markers in adults with MetS and related disorders were examined. Pooled effect sizes were reported as weighted mean differences (WMDs) and 95% confidence intervals (CIs). The results of four eligible RCTs showed that C. annuum supplementation could significantly reduce total cholesterol (TC) (WMD: -4.98 mg/dL, 95% CI: -7.08 to -2.88, p ≤ 0.001) levels, but did not regulate triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol concentrations. In summary, the present findings suggest the beneficial effects of C. annuum supplementation on the reduction of plasma levels of TC. However, to draw a firm link between C. annuum supplementation and lipid profile, more trials with adequate sample sizes, specifically in subjects with dyslipidemia are warranted.

LEO satellite assisted UAV distribution using combinatorial bandit with fairness and budget constraints

In this paper, an integration between a low earth orbit satellite (LEO-Sat) and unmanned aerial vehicle (UAV) is proposed to assist users in post-disaster areas. In this scenario, multiple UAVs will be distributed to fully cover the victims and provide rescue services, while LEO-Sat provides backhaul links for UAVs to the ground base station (GBS). In this regard, we consider the problem of efficient UAVs distribution to maximize the total sum rate of the victims while assuring fairness in their coverage within the limited resources of UAVs batteries and LEO-Sat bandwidth. In this paper, UAV distribution problem is considered as a combinatorial multi-armed bandit (MAB) with arms' fairness and limited UAVs battery budget (CMAB-FB) constraints. Additionally, the utilization of LEO-Sat bandwidth resources is optimized based on the average traffic demands of the LEO-UAV links by means of gradient decent algorithm. The results of numerical analysis indicate that the proposed approach outperforms other naïve ben chmarks.

Quantification of Pomalidomide Using Conventional and Eco-Friendly Stability-Indicating HPTLC Assays: A Contrast of Validation Parameters

High-performance thin-layer chromatographic (HPTLC) assays for pomalidomide (PMD) measurement are lacking in the published database. Furthermore, eco-friendly stability-indicating analytical assays for PMD measurement are also lacking in the published database. In order to detect PMD in commercial products more accurately and sustainably than the conventional normal-phase HPTLC (NP-HPTLC) assay, an effort was made to design and verify a sensitive and eco-friendly reversed-phase HPTLC (RP-HPTLC) assay. The silica gel 60 NP-18F254S and 60 RP-18F254S plates were used as the stationary phases for NP-HPTLC and RP-HPTLC methods, respectively. The solvent system for NP-HPTLC was chloroform-methanol (90:10 v/v). However, the solvent system for RP-HPTLC was ethanol-water (75:25 v/v). The greenness scores for both assays were measured by AGREE approach. PMD measurement was performed for both assays at 372 nm. In the 50-600 and 20-1000 ng/band ranges, the NP-HPTLC and RP-HPTLC methods were linear for PMD measurement. The RP-HPTLC assay was superior to the NP-HPTLC method for measuring PMD in terms of sensitivity, accuracy, precision, and robustness. The ability of both methods to identify PMD in the presence of its degradation products suggests that both methods have stability-indicating features. When employing the NP-HPTLC and RP-HPTLC assays, respectively, the assay for PMD in commercial capsules was 88.68 and 98.83%. The AGREE scores for NP-HPTLC and RP-HPTLC assays were calculated to be 0.44 and 0.82, respectively, suggesting an outstanding greenness characteristic of the RP-HPTLC method than the NP-HPTLC method. The RP-HPTLC method was found to be superior to the NP-HPTLC method based on these findings. Therefore, the RP-HPTLC method could be successfully applied for the determination of PMD in pharmaceutical products.

A new statistical methodology using the sine function: Control chart with an application to survival times data

Statistical methodologies have a wider range of practical applications in every applied sector including education, reliability, management, hydrology, and healthcare sciences. Among the mentioned sectors, the implementation of statistical models in health sectors is very crucial. In the recent era, researchers have shown a deep interest in using the trigonometric function to develop new statistical methodologies. In this article, we propose a new statistical methodology using the trigonometric function, namely, a new trigonometric sine-G family of distribution. A subcase (special member) of the new trigonometric sine-G method called a new trigonometric sine-Weibull distribution is studied. The estimators of the new trigonometric sine-Weibull distribution are derived. A simulation study of the new trigonometric sine-Weibull distribution is also provided. The applicability of the new trigonometric sine-Weibull distribution is shown by considering a data set taken from the biomedical sector. Furthermore, we introduce an attribute control chart for the lifetime of an entity that follows the new trigonometric sine-Weibull distribution in terms of the number of failure items before a fixed time period is investigated. The performance of the suggested chart is investigated using the average run length. A comparative study and real example are given for the proposed control chart. Based on our study of the existing literature, we did not find any published work on the development of a control chart using new probability distributions that are developed based on the trigonometric function. This surprising gap is a key and interesting motivation of this research.