Search

Abstract Objectives We conducted this meta-analysis of randomized controlled trials (RCTs) to compare the efficacy of adding metformin to lifestyle interventions versus lifestyle interventions alone in individuals with prediabetes. Materials and methods We searched four databases from inception until March 20, 2024. Our primary outcomes included the incidence of type 2 diabetes, hemoglobin A1c (HbA1c), and fasting plasma glucose (FPG). Secondary outcomes included blood pressure, plasma lipids, and weight measurements. Dichotomous outcomes were pooled as the risk ratio (RR) and its 95% confidence interval (CI), while continuous outcomes were pooled as the standardized mean difference (SMD) and its 95% CI in the random effect model. All statistical analyses were conducted using the “meta” package of RStudio software. Results We included 12 RCTs, comprising 2720 patients. Adding metformin to lifestyle interventions significantly reduced HbA1c levels (SMD = -0.10, 95% CI [-0.19, -0.01], P = 0.03) and the incidence of type 2 diabetes (RR = 0.85, 95% CI [0.75, 0.97], P = 0.01). Interestingly, adding metformin to lifestyle interventions was comparable to lifestyle interventions alone in terms of FPG at both 3 and 6 months; however, it significantly reduced FPG at 12 months (SMD = -0.34, 95% CI [-0.59, -0.08], P = 0.01). There were no significant differences between the two groups in terms of all secondary outcomes. Conclusions Our findings suggest that adding metformin to lifestyle interventions may improve glycemic control in individuals with prediabetes and reduce their risk of progression to diabetes, compared to lifestyle interventions alone. A longer duration of this combined approach may be required to observe the desired effects.

Abstract Objective This study aimed to determine the prevalence of polypharmacy, comorbidities and to investigate factors associated with polypharmacy among adult patients with Chronic Obstructive Pulmonary Disease (COPD). Methods This was a retrospective single-centre cross-sectional study. Patients with a confirmed diagnosis of COPD according to the GOLD guidelines between 28 February 2020 and 1 March 2023 were included in this study. Patients were excluded if a pre-emptive diagnosis of COPD was made clinically without spirometry evidence of fixed airflow limitation. Population characteristics were presented as frequency for categorical variable. Logistic regression analysis was used to identify predictors of polypharmacy. Results The study sample included a total of 705 patients with COPD. Most of the study sample were males (60%). The mean age of the study population was 65 years old. The majority of the study population had comorbid diseases (68%), hypertension and diabetes were the most common co-existent diseases. Around 55% of the study sample had polypharmacy. Females were significantly less likely to be on polypharmacy compared to males (OR = 0.68, 95% CI = [0.50–0.92], P-value = 0.012)). On the other hand, older patients aged 65.4 or more (OR = 2.31, 95% CI = [1.71–3.14], P-value ≤ 0.001), those with high BMI (≥ 29.2) (OR = 1.42, 95% CI = [1.05–1.92], P-value = 0.024), current smokers (OR = 1.9, 95% CI = [1.39–2.62], P-value ≤ 0.001), those who are receiving home care (OR = 5.29, 95% CI = [2.46–11.37], P-value ≤ 0.001), those who have comorbidities (OR = 19.74, 95% CI = [12.70–30.68], P-value ≤ 0.001) were significantly more likely to be on polypharmacy (p ≤ 0.05). Conclusions Polypharmacy is common among patients with COPD. Patients with high BMI, previous ICU hospitalization and older age are more likely to have polypharmacy. Future analytical studies are warranted to investigate outcomes in patients with COPD and polypharmacy.

Abstract Background Advancements over the past decade in DNA sequencing technology and computing power have created the potential to revolutionize medicine. There has been a marked increase in genetic data available, allowing for the advancement of areas such as personalized medicine. A crucial type of data in this context is genetic variant data which is stored in variant call format (VCF) files. However, the rapid growth in genomics has presented challenges in analyzing and comparing VCF files. Results In response to the limitations of existing tools, this paper introduces a novel web application that provides a user-friendly solution for VCF file analyses and comparisons. The software tool enables researchers and clinicians to perform high-level analysis with ease and enhances productivity. The application’s interface allows users to conveniently upload, analyze, and visualize their VCF files using simple drag-and-drop and point-and-click operations. Essential visualizations such as Venn diagrams, clustergrams, and precision–recall plots are provided to users. A key feature of the application is its support for metadata-based file grouping, accomplished through flexible data matrix uploads, streamlining organization and analysis of user-defined categories. Additionally, the application facilitates standardized benchmarking of VCF files by integrating user-provided ground truth regions and variant lists. Conclusions By providing a user-friendly interface and supporting essential visualizations, this software enhances the accessibility of VCF file analysis and assists researchers and clinicians in their scientific inquiries.

Background: Acute poisoning is a major medical emergency that translates into morbidity and mortality across all age groups, it is a potentially preventable cause of illness and death. This study was carried out to assess the epidemiological information of acute poisoning among the general population presented to the three campuses of a private tertiary care teaching hospital in Karachi, Pakistan. Method: The cross-sectional study was conducted at three campuses of a private tertiary care teaching hospital, Dr. Ziauddin Hospital in Karachi, comprising of records from January 1, 2018, to December 31, 2022, of patients reporting acute poisoning. These records were accessed after getting approval from the Ethical review committee. Consecutive sampling technique was applied while data was collected. All cases of acute poisoning reporting to the emergency department with complete records were included. While data of those with any other diagnosis or incomplete record were excluded. Descriptive analysis was performed for quantitative variables. For categorical data frequency and percentages were extracted. The chi-square test was used to associate categorical variables. P value less than 0.05 was taken as statistically significant. Results: The total number of cases was n=518 out of which n=235 (45.4%) were males while n=283 (54.6%) were females and the maximum number of cases n=111 (21.4%) were associated with Benzodiazepines followed by insecticide poisoning and ingestion of rodenticides. Conclusions: The most susceptible groups to acute poisoning were found to be women and children. A prevalent agent that caused toxicity was benzodiazepines; the biggest number of cases occurred in April, while the lowest number occurred in December. The year 2020 was linked to the highest number of cases.

In non-English speaking developing countries, several debates have arisen over choosing the language of instruction in medical education, whether it should be one of the leading medical languages, such as English, or the mother tongue. In this article, we discuss this debate and provide a brief review of the pedagogical evidence supporting the superiority of the mother tongue as a language of instruction. We also highlight the academic challenges associated with second-language-based medical education and emphasize the impact of language of instruction on the doctor–patient relationship and health care. Finally, we examine the reasons or arguments for not including the mother tongue in medical education. In conclusion, the importance of English as a leading scientific and medical language should not overshadow the crucial role of the native language as the language of instruction in non-English speaking countries. Each country should develop strategies to include the mother tongue in medical education, following the example of developed countries.

Abstract Background Recent improvements in sequencing technologies enabled detailed profiling of genomic features. These technologies mostly rely on short reads which are merged and compared to reference genome for variant identification. These operations should be done with computers due to the size and complexity of the data. The need for analysis software resulted in many programs for mapping, variant calling and annotation steps. Currently, most programs are either expensive enterprise software with proprietary code which makes access and verification very difficult or open-access programs that are mostly based on command-line operations without user interfaces and extensive documentation. Moreover, a high level of disagreement is observed among popular mapping and variant calling algorithms in multiple studies, which makes relying on a single algorithm unreliable. User-friendly open-source software tools that offer comparative analysis are an important need considering the growth of sequencing technologies. Results Here, we propose Comparative Sequencing Analysis Platform (COSAP), an open-source platform that provides popular sequencing algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis and their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. COSAP is developed as a workflow management system and designed to enhance cooperation among scientists with different backgrounds. It is publicly available at https://cosap.bio and https://github.com/MBaysanLab/cosap/ . The source code of the frontend and backend services can be found at https://github.com/MBaysanLab/cosap-webapi/ and https://github.com/MBaysanLab/cosap_frontend/ respectively. All services are packed as Docker containers as well. Pipelines that combine algorithms can be customized and new algorithms can be added with minimal coding through modular structure. Conclusions COSAP simplifies and speeds up the process of DNA sequencing analyses providing commonly used algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis as well as their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. Standardized implementations of popular algorithms in a modular platform make comparisons much easier to assess the impact of alternative pipelines which is crucial in establishing reproducibility of sequencing analyses.

Abstract Introduction Rett syndrome is a rare genetic neurodevelopmental disorder that predominantly impacts females. It presents with loss of acquired skills, impaired communication, and stereotypic hand movements. Given the limited treatment options for Rett syndrome, there is a dire need for effective interventions. Objective To evaluate the safety and efficacy of trofinetide in Randomized Controlled Trials (RCTs) that report on Rett syndrome patients. Methods We identified 109 articles from four databases (Scopus, PubMed, Web of Science, and Cochrane CENTRAL). After removing the duplicates, we narrowed them down to 59 articles for further assessment. We included RCTs that evaluated the efficacy and safety of trofinetide in patients with Rett syndrome. Three studies were eligible for inclusion. Two independent reviewers evaluated the identified studies’ titles, abstracts, and full texts, extracting pertinent data. We assessed the quality of the studies using the Cochrane Risk of Bias (RoB) 2.0 tool. We then conducted a meta-analysis using the fixed effects model in the case of insignificant heterogeneity; otherwise, we used the random effects model. Based on the nature of the outcome, we analyzed the mean difference or the odds ratio. Analysis was conducted using RevMan version 5.3. Results Among the analyzed outcomes in 181 patients in the trofinetide group and 134 patients in the placebo group, significant improvement in Rett Syndrome Behavior Questionnaire (RSBQ) scores was observed at 200 mg dosage (overall mean difference: -3.53, p = 0.001). Clinical Global Impression-Improvement (CGI-I) scores improved considerably at 200 mg dosage (overall mean difference: -0.34, p

Background and Objectives Postpartum depression (PPD) is prevalent among women after childbirth, but accessing mental healthcare for PPD is challenging. This study aimed to assess the treatment gap and barriers to mental healthcare access for women with PPD symptoms living in Punjab, Pakistan. Methods A multicenter cross-sectional study was conducted in five populous cities of Punjab from January to June 2023 by administering the questionnaire to the women using stratified random sampling. A total of 3,220 women in first 6 months postpartum were screened using the Edinburgh Postnatal Depression Scale. Of them, 1,503 women scored thirteen or above, indicating potential depressive disorder. Interviews were conducted to explore help-seeking behavior and barriers to accessing mental healthcare. Descriptive statistics along with nonparametric tests (e.g., Kruskal–Wallis, Mann–Whitney U) were used and group differences were examined. Scatter plot matrices with fitted lines were used to explore associations between variables. Classification and regression tree methods were used to classify the importance and contribution of different variables for the intensity of PPD. Results Only 2% of women (n = 33) with high PPD symptoms sought mental healthcare, and merely 5% of women (n = 75) had been in contact with a health service since the onset of their symptoms. 92.80% of women with PPD symptoms did not seek any medical attention. The majority of women, 1,215 (81%), perceived the need for mental health treatment; however, 91.23% of them did not seek treatment from healthcare services. Women who recently gave birth to a female child had higher mean depression scores compared to those who gave birth to a male child. Age, education, and birth location of newborn were significantly associated (p

Background: In the Eastern Mediterranean region, Afghanistan ranks third for the world’s highest burden of malaria. The vast majority (95%) of malaria cases in Afghanistan are attributed to Plasmodium falciparum and 5% to Plasmodium vivax . Most cases occur in low-altitude regions, especially in the eastern province of Nangarhar, where agriculture and farming are predominant. To better understand the public sentiment toward malaria, this study aimed to understand the knowledge, attitude, and practice of patients toward malaria who visited public and private hospitals of Nangarhar province. Methods: A cross-sectional descriptive study was conducted on Nangarhar residents who visited the adult Outpatient departments of eight local public and private health facilities. Data collection took place from 1st August 2022 to 15th September 2022. Results: Of 700 participants, 37.9% ( n = 265) identified as male and 62.1% ( n = 435) identified as female. The majority of participants (84.6 %) were within the (18–40) age range, followed by 12.7% in the (41–60) age range, and 2.7% were aged 61 years or older. Moreover, 99.7% ( n = 698) of the participants had heard of malaria. The main sources of information about malaria were family members (31.3%, n = 219), television (32.6%, n = 228), Internet (12.6%, n = 88), school (11.3%, n = 79), and health facilities (31.4%, n = 220). Most respondents correctly identified mosquito bites as the primary mode of malaria transmission (72.6%, n = 508). Others suggested that transmission could occur by close contact with a malaria patient (14.0%, n = 98) and drinking contaminated water (17.3%, n = 121). The majority of participants (70.6%) agreed that malaria is a serious and life-threatening disease. A significant number of participants (96.6%) reported owning an insecticide-treated mosquito net at home, and 87.0% reported using the net. Conclusion: Overall, participants reported good knowledge, attitude, and practice toward malaria. This may be linked to the awareness campaigns and preventive programs in Nangarhar province that have contributed to participant’s willingness to prevent malaria and treat themselves if they get infected. Public health campaigns are difficult in Afghanistan with weak governance and conflict, and thus, populations may find themselves at risk if health promotion activities are stopped.

The prevalence of cyberbullying has reached an alarming rate, affecting approximately 54% of teenagers who experience various forms of cyberbullying, including offensive hate speech, threats, and racism. This research introduces a comprehensive dataset and system for cyberbullying detection in Urdu tweets, leveraging a spectrum of machine learning approaches including traditional models and advanced deep learning techniques. The objectives of this study are threefold. Firstly, a dataset consisting of 12,500 annotated tweets in Urdu is created, and it is made publicly available to the research community. Secondly, annotation guidelines for Urdu text with appropriate labels for cyberbullying detection are developed. Finally, a series of experiments is conducted to assess the performance of machine learning and deep learning techniques in detecting cyberbullying. The results indicate that fastText deep learning models outperform other models in cyberbullying detection. This study demonstrates its efficacy in effectively detecting and classifying cyberbullying incidents in Urdu tweets, contributing to the broader effort of creating a safer digital environment.

Abstract Background Creutzfeldt–Jakob disease (CJD), is a deadly degenerative condition of the central nervous system marked by rapidly progressive dementia. Magnetic resonance imaging (MRI) abnormalities in the cerebral cortex, basal ganglia, thalamus, and cerebellum could indicate severe acute diseases caused by a variety of factors. Although their MRI patterns may resemble those of CJD, clinical history, additional MRI findings, and laboratory testing are all necessary to provide a reliable difference. Here, we report a misdiagnosed case of probable VV1 subtype of sporadic CJD (sCJD) in which follow-up MRI supported the diagnosis. Case presentation A 41-year-old male patient attended the Neuropsychiatry Department with rapidly progressive dementia, akinetic mutism, and difficulty walking and speaking. His problem began with forgetfulness, disorganized behavior, and disorganized speech 7 months earlier which progressed rapidly and was accompanied by aphasia, apraxia, agnosia, and akinetic mutism in the last 2 months. On neurologic examination, hypertonia, hyperreflexia, frontal ataxia, bradykinesia, gait apraxia, and aphasia were noted. Based on clinical features and rapid symptoms progression the likely diagnosis of CJD was suspected. MRI and electroencephalography (EEG) were advised. MRI revealed features of diffuse cortical injury of both cerebral hemispheres also involving bilateral corpus striatum with evidence of cerebral volume loss. EEG showed lateralized periodic theta slow waves on the right side. According to the CDC’s diagnostic criteria for CJD, the diagnosis of probable sCJD was established. Supportive care and symptomatic treatment are provided for the patient. After a 1-month follow up the patient’s condition deteriorated significantly. The time-lapse from the first reported symptom to death was about 13 months. Conclusion The need of addressing CJD in patients presenting with rapidly progressive dementia is highlighted in this case report. In the early stages of the disease, interpretation of MRI results might cause diagnostic difficulties; therefore, follow-up MRI is critical in obtaining the correct diagnosis.

Background: Although the usefulness of the Modified Early Warning Score (MEWS) in predicting clinical deterioration or the need for intensive care unit (ICU) admission has been evaluated in several studies, only few reports have considered the immune status of the patient. Patients receiving chemotherapy for cancer are at risk of sepsis. This study aimed to assess the validity of MEWS in predicting clinical deterioration, ICU admission, and mortality among immunocompromised cancer patients on chemotherapy (CPOC). Methods: This retrospective cohort study was conducted at a tertiary care center in Jeddah, Saudi Arabia. Subjects aged>14 years with positive blood cultures, who were hospitalized between June 2016 and June 2017, were included. MEWS was calculated at different time intervals: before, after, and at the time (0-time) of positive blood culture. Results: Overall, 192 patients were enrolled, including 89 CPOC and 103 immunocompetent individuals (controls). ICU admission rate was significantly lower in the CPOC group than in the control group (21 % vs. 50 %, P

Herpes simplex encephalitis (HSVE) is a potentially fatal infectious central nervous system (CNS) disorder. Thus, early detection is critical in determining the case's fate. Clinical history and examination, brain computed tomography, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and lumbar puncture have been used to establish a diagnosis. This report describes a case of HSVE with hypocellular cerebrospinal fluid (CSF) and an uncommon form of memory impairment. However, MRI results were consistent with HSVE, and CSF PCR tested positive for HSV-1 DNA that responded to treatment. We routinely advise patients to begin antiviral therapy as soon as possible to avoid complications.

Abstract Background Chikungunya is an arboviral infection caused by the Chikungunya virus (CHIKV) transmitted to humans by mosquitoes of Aedes spp. CHIKV has been confined to African countries and South-East Asia up to 2004, but since then, the pathogen has become more global, and its high morbidity rate has become more visible. Saudi Arabia is not an endemic region of CHIKV, and the virus’s origin is not yet fully understood. This study aimed to characterize the genome of CHIKV from samples detected in Jeddah in 2018. Method Twenty-two sets of primers were designed to amplify near-full length genome of CHIKV. RT-PCR was conducted from clinical samples. Two samples were used for studying near complete genome sequence while the remaining samples were used to study the E1 gene. Different bioinformatics tools were utilized. Results Phylogenetic analysis showed that the CHIKV strains clustered with strains isolated from Kenya during 2017–2018 and belonged to ECSA genotype. E1: L136F, K211E and I317V mutations were identified in our strains. Also, E2: M74I, A76T, and V264A mutations were documented. Additionally, the capsid N79S substitution was also detected. Conclusion The genome of CHIKV was analyzed for the first time in Saudi Arabia to better understand the origin of the CHIKV and its genetic diversity, which showed high similarity with IE—a subclade of CHIKV strains detected in Mombasa (Kenya) indicating its possible origin.

Abstract Background Successful implementation of preventive measures and level of awareness in particular among university students in Afghanistan could play a crucial role in spreading the information for better control of the ongoing pandemic. Therefore, the aim of this study was to determine the level of knowledge, attitudes and practices (KAP) regarding COVID-19 among Kandahar university students. Methods A cross-sectional study conducted among undergraduate students to investigate their KAP regarding COVID-19 from January to March, 2021. The data were collected using a structured questionnaire (socio-demographic characteristics, KAP questionnaire) by phone call interviews. Results From 359 participants, 88.9% were males, 81.3% were single, 65.1% lived in urban areas, and more than 64% of the students were less than 23 years old. Overall, 86.6% of the study participants had adequate level of knowledge and 87.5% had positive attitudes toward COVID-19. Almost one-third of the participants had good practices regarding COVID-19. All KAP scores were higher in male students. Significant difference of good practice (p

This paper discusses the design of interactive gamified assessments for an introductory programming course based on the multimedia segmenting principle and gamification. The objective is to develop more engaging online programming assessments for low-achieving students. The general design follows Nielsen's design guidelines and incorporates Zaharias' usability evaluation framework with the motivation to learn. The methodology employed the Successive Approximation Model Version 2 (SAM2), comprising two key phases: preparation and iterative design. In the initial phase, a comparative analysis was performed to determine the design principles. The iterative design phase encompassed the application's design via storyboards, the development of the high-fidelity prototype, and users' reviews. A qualitative approach was adopted, involving a user-centred design (UCD) session through focus group discussions with 12 first-year students from the Diploma of Computer Science program, all of whom were low achievers in programming. The participants need to review and rate the prototype based on the scales of the usability recommendations, which are visual design, content design, navigation, interaction, gamification design, and multimedia design. The results from the UCD session revealed that all participants agreed with the usability recommendations integrated into the interactive gamified programming assessments, with the highest mean score of 5.00.

Abstract Previous studies investigated the frequency of different adverse events of COVID-19 vaccines. However, this study compares these adverse events between the two main COVID-19 vaccines used in Saudi Arabia (Pfizer-BioNTech and Oxford-AstraZeneca) using telemedicine technology. A cross-sectional study was conducted among 958 individuals, 7 days after receiving either Pfizer-BioNTech or Oxford-AstraZeneca vaccines during June 2021. Immediate adverse events were reported by 1.04% and 2.09% for Pfizer-BioNTech and Oxford-AstraZeneca vaccines, respectively, with no serious events. Recipients of Pfizer-BioNTech vaccine had a higher percentage of local adverse events (24.8% versus 9.8% in AstraZeneca vaccine). The most common reported systemic adverse events in both vaccines respectively were general fatigue (23.1% and 25.1%), fever (18.5% and 27.2%), myalgia (20.6% and 20.3%), and headache (15.2% and 17.2%). No significant difference was recorded between both vaccines regarding overall systemic adverse events; however, they were more frequent following the first dose of AstraZeneca vaccine compared to Pfizer-BioNTech vaccine, while the reverse was observed for the second dose. Adverse events were more frequent in females and younger age groups for both vaccines. Most of systemic and local adverse events were mild in nature. Further cohort studies are recommended to investigate the long-term adverse events of COVID-19 vaccines.

Sharks are predator species that play an important role in marine ecosystems and have high economic value. Exploiting shark parts, including fins, scales, teeth, cartilage, skin, liver, meat, and tails, is difficult to identify visually, necessitating molecular identification to determine traded shark products. This study aimed to design species-specific primers based on mitochondrial gene markers for shark species Isurus spp. and Lamna nasus, and their application in real-time PCR-based fisheries product authentication. The research was conducted in silico for specific primer design and in vitro for DNA sample isolation, DNA quantity and quality testing, DNA amplification, and real-time PCR analysis. The primer pairs of species included in the CITES II list with different genetic markers have been successfully created. The primers used were able to amplify DNA and showed a Ct difference between the target and non-target DNA, proving their ability to identify the target shark species.

Japanese threadfin bream (Nemipterus japonicus) contains highmyofibril protein which can be used as raw material in processing of surimi and kamaboko, however both of those products are able to cause allergies in people who have hypersensitivity to allergenic proteins. Parvalbumin is a sarcoplasmic protein which is the main source of allergies in fish. The washing process in surimi processing can remove sarcoplasmic proteins. Therefore, this research was conducted to determine the allergenic protein content in each processing process of surimi and kamaboko Japanese threadfin bream fish. The protein profiles of surimi and washingwater were visualized using sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and total parvalbumin protein was calculated using enzyme-linked immunosorbent assay (ELISA). The SDS-PAGE results showed that the washing process removed several allergens as indicated by a decrease in the protein band at a molecular weight of 10-13 kDa and for ELISA the absorbance value decreased with the number of washing processes in surimi processing. The content of parvalbumin and other allergycausing proteins such as aldolase A and β-enolase decreased after the meat underwent the washing process.

Seaweed is one of the highly commercial aquatic commodities, accounting for 51.3% of total marine and coastal aquaculture production. As much as 99.5% of seaweed production is concentrated in Asia, especially in East and Southeast Asian countries, one of which is Indonesia. The wide diversity of seaweeds has not been fully optimizing their potential to provide maximum economic benefits. This study aimed to determine the characteristics of crude extracts of fucoidan using two different solvents and to analyze the antioxidant activity of crude extracts of fucoidan using different solvents. The research method included the preparation of raw materials, extraction with distilled water and 2% CaCl2 at 85 °C for 4 h, followed by quality analyses. Total sugar using the phenol-sulphate method obtained higher results in distilled water (67.88%). The total sulphate analysis showed higher results with 2% CaCl2 (19.60%). The total phenol analysis yielded higher results with 2% CaCl2 (978.20%). The antioxidant activity of the crude fucoidan were 312.01 ppm (distilled water), 193.52 ppm (distilled water), 54.653 μg/mL ascorbic acid/g extract (CaCl2 2%, 128.38 mol Fe2+/g (CaCl2 2%).

International market demand for sharks is increasing, thus increasing the number of catches of several shark species that are included in the International Union for Conservation of Nature’s (IUCN) Red List and the Convention International Trade of Endangered Species (CITES) Appendix II. Authentication using biomoleculars by utilizing DNA is necessary. This study was aimed to design specific primers based on cytochrome c oxidase I and cytochrome b marker genes for endangered sharks (Prionace glauca and Carcharhinus spp.) and to apply them in vitro to identify fishery products using real-time PCR techniques. This research begins with designing target species-specific primers. Designing a specific primer using BioEdit software. The Oligo Evaluator and NCBI’s Blast (Basic Local Alignment Search Tool) web tool for performing primary specification validation. The next stage is the sample preparation, DNA isolation, DNA amplification, DNA quality and quantity testing, and realtime PCR analysis. Primer’s design of target species Prionace glauca using cyt b gene and degenerate primer for genus Carcharhinus spp. COI gene markers were successfully carried out in silico. Efficient real-time PCR conditions of Prionace glauca and Carcharhinus spp. complies with testing standards using the real-time PCR method.

This paper performed an investigation into the s-embedding of the Lie superalgebra (→S1∣1), a representation of smooth vector fields on a (1,1)-dimensional super-circle. Our primary objective was to establish a precise definition of the s-embedding, effectively dissecting the Lie superalgebra into the superalgebra of super-pseudodifferential operators ( SψD⊙) residing on the super-circle S1|1. We also introduce and rigorously define the central charge within the framework of (→S1∣1), leveraging the canonical central extension of SψD⊙. Moreover, we expanded the scope of our inquiry to encompass the domain of fuzzy Lie algebras, seeking to elucidate potential connections and parallels between these ostensibly distinct mathematical constructs. Our exploration spanned various facets, including non-commutative structures, representation theory, central extensions, and central charges, as we aimed to bridge the gap between Lie superalgebras and fuzzy Lie algebras. To summarize, this paper is a pioneering work with two pivotal contributions. Initially, a meticulous definition of the s-embedding of the Lie superalgebra (→S1|1) is provided, emphasizing the representationof smooth vector fields on the (1,1)-dimensional super-circle, thereby enriching a fundamental comprehension of the topic. Moreover, an investigation of the realm of fuzzy Lie algebras was undertaken, probing associations with conventional Lie superalgebras. Capitalizing on these discoveries, we expound upon the nexus between central extensions and provide a novel deformed representation of the central charge.

Abstract Severe Acute Respiratory Syndrome Corona Virus Type-2 (SARS-COV-2) was first detected in China and created a global pandemic rapidly. Subsequently after serious efforts different types of vaccines produced against the virus and recommended for all people including pregnant women. The aim of this study was to realize the willingness of pregnant women to accept the COVID-19 vaccine in Kabul Afghanistan. For this purpose, a cross-sectional study was conducted in gynecology wards of several hospitals in Kabul, Afghanistan from 10th of July to 20th of August 2021 through direct interview with the pregnant women who had come for prenatal care to the healthcare centers. The collected data were analyzed through Statistical Package for Social Studies (SPSS) version 25. Simple descriptive analysis computed for demographic characteristics and bi-variable (Chi-square) analysis was carried out to find out the associations of taking vaccine with demographic variables. A p-value of

BackgroundMeningiomas are mostly benign and slow-growing neoplasms of the central nervous system. Spinal meningiomas account for up to 45% of all intradural spinal tumors in adults and up to 25%–45% of all spinal tumors. Spinal extradural meningiomas are rare and may be easily confused with malignant neoplasms.Case descriptionA 24-year-old woman was presented to our hospital with paraplegia and loss of sensation in the T7 dermatome and lower body. MRI findings showed T6-T7 right-sided intradural extramedullary and extradural lesion, measuring 1.4 cm × 1.5 cm × 3 cm, extending to the right foramen, compressing the spinal cord, and displacing it to the left. Hyperintense lesion on T2 and hypointense lesion on T1 were observed. The patient reported improvement after surgery and during follow-up. We recommend maximizing the decompression during surgery to achieve better clinical outcome. Extradural meningiomas represent 5% of all meningiomas; therefore, having an intradural on top of extradural meningioma with extraforaminal extensions makes this a unique and rare case.ConclusionMeningiomas can be easily missed in diagnosis depending on imaging and the pathognomonic pattern it represents, which can mimic other pathologies, such as schwannomas. Therefore, surgeons should always suspect their patient having a meningioma even if the pattern is not typical. Moreover, preoperative preparation, such as navigation and defect closure, must be taken in case it turns out be a meningioma instead of the presumed pathology.

Background: The rapid increase in coronavirus disease 2019 (COVID-19) cases during the subsequent waves in Saudi Arabia and other countries prompted the Saudi Critical Care Society (SCCS) to put together a panel of experts to issue evidence-based recommendations for the management of COVID-19 in the intensive care unit (ICU). Methods: The SCCS COVID-19 panel included 51 experts with expertise in critical care, respirology, infectious disease, epidemiology, emergency medicine, clinical pharmacy, nursing, respiratory therapy, methodology, and health policy. All members completed an electronic conflict of interest disclosure form. The panel addressed 9 questions that are related to the therapy of COVID-19 in the ICU. We identified relevant systematic reviews and clinical trials, then used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach as well as the evidence-to-decision framework (EtD) to assess the quality of evidence and generate recommendations. Results: The SCCS COVID-19 panel issued 12 recommendations on pharmacotherapeutic interventions (immunomodulators, antiviral agents, and anticoagulants) for severe and critical COVID-19, of which 3 were strong recommendations and 9 were weak recommendations. Conclusion: The SCCS COVID-19 panel used the GRADE approach to formulate recommendations on therapy for COVID-19 in the ICU. The EtD framework allows adaptation of these recommendations in different contexts. The SCCS guideline committee will update recommendations as new evidence becomes available.

Background: Post-acute COVID-19 syndrome (PACS) is an important healthcare burden. We examined persistent symptoms in COVID-19 patients at least four weeks after the onset of infection, participants’ return to pre-COVID-19 health status and associated risk factors. Methods: Cross-sectional study was conducted (December 2020 to January 2021). A validated online questionnaire was sent to randomly selected individuals aged more than 14 years from a total of 1397,386 people confirmed to have COVID-19 at least 4 weeks prior to the start of this survey. This sample was drawn from the Saudi ministry of health COVID-19 testing registry system. Results: Out of the 9507 COVID-19 patients who responded to the survey, 5946 (62.5%) of them adequately completed it. 2895 patients (48.7%) were aged 35–44 years, 64.4% were males, and 91.5% were Middle Eastern or North African. 79.4% experienced unresolved symptoms for at least 4 weeks after the disease onset. 9.3% were hospitalized with 42.7% visiting healthcare facility after discharge and 14.3% requiring readmission. The rates of main reported persistent symptoms in descending order were fatigue 53.5%, muscle and body ache 38.2%, loss of smell 35.0%, joint pain 30.5%, and loss of taste 29.1%. There was moderate correlation between the number of symptoms at the onset and post-four weeks of COVID-19 infection. Female sex, pre-existing comorbidities, increased number of baseline symptoms, longer hospital-stay, and hospital readmission were predictors of delayed return to baseline health state (p

Determining students' language proficiency is essential for successful instruction and learning objectives in many educational settings. To this end, one of the most efficient assessment tools for measuring language proficiency is the C-test. Thus, the primary aim of this research is to assess the performance of university students through the C-Test and to analyze the extent to which this test is valid in measuring language ability. A standardized C-Test has been created with four brief passages, each containing 20 gaps. The length of each passage varied from 95 to 109 words. Throughout each passage, only the first and last sentences were not changed. The test was taken by 100 students; 39 were male and 61 were female at Al-Nisour University/Department of English in Baghdad, Iraq. The sample consists of two groups. Both groups come from the same school and would receive similar educational input in both cases based on their grade level. The validity and reliability of the C-Test were investigated using various techniques. The study analyzed the performance of fourth- and third-year students on the Common Language Proficiency Test in Iraq. The results showed that the test discriminates well between high-ability and low-ability examinees, with no significant difference between the two groups. The Rasch model separation reliability was relatively high, and the data were one-dimensional. The students faced difficulties in guessing the most appropriate words due to their limited English proficiency. The results suggest that developing and implementing this test could significantly improve students' academic achievements in basic foreign language classes in Iraq.

Deep learning has enabled a straightforward, convenient method of road pavement infrastructure management that facilitates a secure, cost-effective, and efficient transportation network. Manual road pavement inspection is time-consuming and dangerous, making timely road repair difficult. This research showcases You Only Look Once version 5 (YOLOv5), the most commonly employed object detection model trained on the latest benchmark Road Damage Dataset, Road Damage Detection 2022 (RDD 2022). The RDD 2022 dataset includes four common types of road pavement damage, namely vertical cracks, horizontal cracks, alligator cracks, and potholes. This paper presents an improved deep neural network model based on YOLOv5 for real-time road pavement damage detection in photographic representations of outdoor road surfaces, making it an indispensable tool for efficient, real-time, and cost-effective road infrastructure management. The YOLOv5 model has been modified to incorporate several techniques that improve its accuracy and generalization performance. These techniques include the Efficient Channel Attention module (ECA-Net), label smoothing, the K-means++ algorithm, Focal Loss, and an additional prediction layer. In addition, a 1.9% improvement in mean average precision (mAP) and a 1.29% increase in F1-Score were attained by the model in comparison to YOLOv5s, with an increment of 1.1 million parameters. Moreover, a 0.11% improvement in mAP and 0.05% improvement in F1 score was achieved by the proposed model compared to YOLOv8s while having 3 million fewer parameters and 12 gigabytes fewer Giga Floating Point Operation per Second (GFlops).

The surface quality of machine elements may deteriorate over time while operating under different conditions. This deterioration adversely affects the wear behavior in the contact areas, and these materials become unusable over time. In machine elements especially, the heat transfer, wear amount and surface roughness parameters in the contact area are very important in order for the system to work efficiently. In order to understand this change, composite materials were produced by adding spheroidal graphite cast iron (GGG40) with high lubricating properties at different rates to bronze (CuSn10), which is widely used as a self-lubricating bearing material. In this study, four different mixing ratios (B60D40, B70D30, B80D20 and B90D10) and B100, which is completely produced from bronze chips, were used for comparison purposes. In addition, these produced composite materials were compared with pure CuSn10 and pure GGG40 via double-acting isostatic hot pressing, and then the results were examined. The composite materials were made at two different temperatures (400 °C and 450 °C) and three different pressures (480 MPa, 640 MPa and 820 MPa) using recycled waste chips. Composites produced by recycling waste chips both reduce costs and make a positive contribution to the natural environment. Thus, more advantageous self-lubricating bearing materials will be produced, and the efficiency will be increased in these materials. The time-dependent variation in the friction coefficient observed after the wear tests performed under constant load is explained, and the resulting surface structures are presented with SEM images and EDS analyses. After the wear tests, it was observed that the process parameters used in production effectively influenced the wear behavior. In particular, when the production pressure was low (480 MPa), the wear behavior was adversely affected because sufficient bonding between the chips could not be achieved. In addition, as the amount of GGG40 used as a reinforcement material increased, the spheroidal graphite contained in it positively affected the wear behavior. The lubricating effect provided by this spheroidal graphite reduced wear in the contact area and the friction coefficient.

The field of mathematics that studies the relationship between algebraic structures and graphs is known as algebraic graph theory. It incorporates concepts from graph theory, which examines the characteristics and topology of graphs, with those from abstract algebra, which deals with algebraic structures such as groups, rings, and fields. If the vertex set of a graph G^ is fully made up of the zero divisors of the modular ring Zn, the graph is said to be a zero-divisor graph. If the products of two vertices are equal to zero under (modn), they are regarded as neighbors. Entropy, a notion taken from information theory and used in graph theory, measures the degree of uncertainty or unpredictability associated with a graph or its constituent elements. Entropy measurements may be used to calculate the structural complexity and information complexity of graphs. The first, second and second modified Zagrebs, general and inverse general Randics, third and fifth symmetric divisions, harmonic and inverse sum indices, and forgotten topological indices are a few topological indices that are examined in this article for particular families of zero-divisor graphs. A numerical and graphical comparison of computed topological indices over a proposed structure has been studied. Furthermore, different kinds of entropies, such as the first, second, and third redefined Zagreb, are also investigated for a number of families of zero-divisor graphs.

This paper explores the concept of Generalized Roughness in LA-Semigroups and its applications in various mathematical disciplines. We highlight the fundamental properties and structures of Generalized Roughness, examining its relationships with Fuzzy Lie Algebras, Order Theory, Lattice Structures, Algebraic Structures, and Categorical Perspectives. Moreover, we investigate the potential of mathematical modeling, optimization techniques, data analysis, and machine learning in the context of Generalized Roughness. Our findings reveal important results in Generalized Roughness, such as the preservation of roughness under the fuzzy equivalence relation and the composition of roughness sets. We demonstrate the significance of Generalized Roughness in the context of order theory and lattice structures, presenting key propositions and a theorem that elucidate its properties and relationships. Furthermore, we explore the applications of Generalized Roughness in mathematical modeling and optimization, highlighting the optimization of roughness measures, parameter estimation, and decision-making processes related to LA-Semigroup operations. We showcase how mathematical techniques can enhance understanding and utilization of LA-Semigroups in practical scenarios. Lastly, we delve into the role of data analysis and machine learning in uncovering patterns, relationships, and predictive models in Generalized Roughness. By leveraging these techniques, we provide examples and insights into how data analysis and machine learning can contribute to enhancing our understanding of LA-Semigroup behavior and supporting decision-making processes.

Trapped-ion (TI) quantum bits are a front-runner technology for quantum computing. TI systems with multiple interconnected traps can overcome the hardware connectivity issue inherent in superconducting qubits and can solve practical problems at scale. With a sufficient number of qubits on the horizon, the multi-programming model for Quantum Computers (QC) has been proposed where multiple users share the same QC for their computing. Multi-programming is enticing for quantum cloud providers as it can maximize device utilization, throughput, and profit for clouds. Users can also benefit from the short wait queue. However, shared access to quantum computers can create new security issues. This paper presents one such vulnerability in shared TI systems that require shuttle operations for communication among traps. Repeated shuttle operations increase quantum bit energy and degrade the reliability of computations (fidelity). We show adversarial program design approaches requiring numerous shuttles. We propose a random and systematic methodology for adversary program generation. Our analysis shows shuttle-exploiting attacks can substantially degrade the fidelities of victim programs by $\approx 2 \times $ to $\approx 63 \times $ . Finally, we present several countermeasures such as adopting a hybrid initial mapping policy, padding victim programs with dummy qubits, and capping maximum shuttles.

The advent of pre-trained language models has directed a new era of Natural Language Processing (NLP), enabling us to create powerful language models. Among these models, Transformer-based models like BERT have grown in popularity due to their cutting-edge effectiveness. However, these models heavily rely on resource-intensive languages, forcing other languages into multilingual models(mBERT). The two fundamental challenges with mBERT become significantly more challenging in a resource-constrained language like Bangla. It was trained on a limited and organized dataset and contained weights for all other languages. Besides, current research on other languages suggests that a language-specific BERT model will exceed multilingual ones. This paper introduces Bangla-BERT,a a monolingual BERT model for the Bangla language. Despite the limited data available for NLP tasks in Bangla, we perform pre-training on the largest Bangla language model dataset, BanglaLM, which we constructed using 40 GB of text data. Bangla-BERT achieves the highest results in all datasets and vastly improves the state-of-the-art performance in binary linguistic classification, multilabel extraction, and named entity recognition, outperforming multilingual BERT and other previous research. The pre-trained model is assessed against several non-contextual models such as Bangla fasttext and word2vec the downstream tasks. Finally, this model is evaluated by transfer learning based on hybrid deep learning models such as LSTM, CNN, and CRF in NER, and it is observed that Bangla-BERT outperforms state-of-the-art methods. The proposed Bangla-BERT model is assessed by using benchmark datasets, including Banfakenews, Sentiment Analysis on Bengali News Comments, and Cross-lingual Sentiment Analysis in Bengali. Finally, it is concluded that Bangla-BERT surpasses all prior state-of-the-art results by 3.52%, 2.2%, and 5.3%.

Background: The COVID-19 pandemic remains an immediate and present concern, yet as of now there is still no approved therapeutic available for the treatment of COVID-19.This study aimed to investigate and report evidence concerning demographic characteristics and currently-used medications that contribute to the ultimate outcomes of COVID-19 ICU patients. Methods: A retrospective cohort study was conducted among all COVID-19 patients in the Intensive Care Unit (ICU) of Asir Central Hospital in Saudi Arabia between the 1st and 30th of June 2020. Data extracted from patients’ medical records included their demographics, home medications, medications used to treat COVID-19, treatment durations, ICU stay, hospital stay, and ultimate outcome (recovery or death).Descriptive statistics and regression modelling were used to analyze and compare the results. The study was approved by the Institutional Ethics Committees at both Asir Central Hospital and King Khalid University. Results: A total of 118 patients with median age of 57 years having definite clinical and disease outcomes were included in the study. Male patients accounted for 87% of the study population, and more than 65% experienced at least one comorbidity. The mean hospital and ICU stay was 11.4 and 9.8 days, respectively. The most common drugs used were tocilizumab (31.4%), triple combination therapy (45.8%), favipiravir (56.8%), dexamethasone (86.7%), and enoxaparin (83%). Treatment with enoxaparin significantly reduced the length of ICU stay (p = 0.04) and was found to be associated with mortality reduction in patients aged 50−75 (p = 0.03), whereas the triple regimen therapy and tocilizumab significantly increased the length of ICU stay in all patients (p = 0.01, p = 0.02 respectively). Conclusion: COVID-19 tends to affect males more significantly than females. The use of enoxaparin is an important part of COVID-19 treatment, especially for those above 50 years of age, while the use of triple combination therapy and tocilizumab in COVID-19 protocols should be reevaluated and restricted to patients who have high likelihood of benefit.