| 1. |
- Mallhi, Tauqeer Hussain, et al.
(författare)
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Estimation of Psychological Impairment and Coping Strategies during COVID-19 Pandemic among University Students in Saudi Arabia : A Large Regional Analysis
- 2022
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 19:21
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Tidskriftsartikel (refereegranskat)abstract
- Background: The COVID-19 pandemic and associated restrictive measures have substantially affected educational processes around the globe, resulting in psychological distress among students. The mental health of students in higher education is of paramount importance, and the COVID-19 pandemic has brought this vulnerable population into renewed focus. In this context, the evaluation of students' mental health at educational institutes has gained invaluable popularity during the COVID-19 pandemic. This study aimed to ascertain the psychological health and coping strategies among students from a higher education institute in Saudi Arabia.Methods: An online study instrument was used to assess anxiety (Generalized Anxiety Disorder-7, GAD-7), depression (Patient Health Questionnaire-9, PHQ-9), post-traumatic stress disorder-PTSD (Impact of Event Scale-Revised, IES-R) and coping strategies (Brief-COPE). The severity of the psychological distress was classified as per the scoring criteria and correlated with demographics using appropriate statistical methods.Results: Of 1074 students (age 21.1 +/- 2.1 years), 12.9% and 9.7% had severe anxiety and depression, respectively. The mean anxiety and depression scores were 7.50 +/- 5.51 and 9.31 +/- 6.72, respectively. About one-third (32%) of students reported suicidal ideation, with 8.4% students having such thoughts nearly every day. The average PTSD score was 21.64 +/- 17.63, where avoidance scored higher (8.10 +/- 6.94) than intrusion and hyperarousal. There was no association of anxiety, depression and PTSD score with the demographics of the study participants. Religious/spiritual coping (5.43 +/- 2.15) was the most adoptive coping mechanism, followed by acceptance (5.15 +/- 2.10). Male students were significantly (p < 0.05) associated with active copings, instrumental support, planning, humor, acceptance and religious coping. Substance use was the least adopted coping strategy but practiced by a considerable number of students.Conclusions: The long-lasting pandemic situation, onerous protective measures and uncertainties in educational procedures have resulted in a high prevalence of psychological ailments among university students, as indicated in this study. These findings accentuate the urgent need for telepsychiatry and appropriate population-specific mental health services to assess the extent of psychological impairment and to leverage positive coping behaviors among students.
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| 2. |
- Pompermaier, Laura, et al.
(författare)
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Impact of COVID-19 on global burn care
- 2022
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Ingår i: Burns. - : Elsevier Science Ltd. - 0305-4179 .- 1879-1409. ; 48:6, s. 1301-1310
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Tidskriftsartikel (refereegranskat)abstract
- Background: Worldwide, different strategies have been chosen to face the COVID-19-patient surge, often affecting access to health care for other patients. This observational study aimed to investigate whether the standard of burn care changed globally during the pan-demic, and whether country acute accent s income, geographical location, COVID-19-transmission pat-tern, and levels of specialization of the burn units affected reallocation of resources and access to burn care.Methods: The Burn Care Survey is a questionnaire developed to collect information on the capacity to provide burn care by burn units around the world, before and during the pandemic. The survey was distributed between September and October 2020. McNemar`s test analyzed differences between services provided before and during the pandemic, chi 2 or Fishers exact test differences between groups. Multivariable logistic regression analyzed the independent effect of different factors on keeping the burn units open during the pandemic.Results: The survey was completed by 234 burn units in 43 countries. During the pandemic, presence of burn surgeons did not change (p = 0.06), while that of anesthetists and dedi-cated nursing staff was reduced (< 0.01), and so did the capacity to manage patients in all age groups (p = 0.04). Use of telemedicine was implemented (p < 0.01), collaboration be-tween burn centers was not. Burn units in LMICs and LICs were more likely to be closed, after adjustment for other factors.Conclusions: During the pandemic, most burn units were open, although availability of standard resources diminished worldwide. The use of telemedicine increased, suggesting the implementation of new strategies to manage burns. Low income was independently associated with reduced access to burn care.(c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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| 3. |
- Arshed, Muhammad Asad, et al.
(författare)
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Chem2Side : A Deep Learning Model with Ensemble Augmentation (Conventional + Pix2Pix) for COVID-19 Drug Side-Effects Prediction from Chemical Images
- 2023
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Ingår i: Information (Switzerland). - 2078-2489. ; 14:12
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Tidskriftsartikel (refereegranskat)abstract
- Drug side effects (DSEs) or adverse drug reactions (ADRs) are a major concern in the healthcare industry, accounting for a significant number of annual deaths in Europe alone. Identifying and predicting DSEs early in the drug development process is crucial to mitigate their impact on public health and reduce the time and costs associated with drug development. Objective: In this study, our primary objective is to predict multiple drug side effects using 2D chemical structures, especially for COVID-19, departing from the conventional approach of relying on 1D chemical structures. We aim to develop a novel model for DSE prediction that leverages the CNN-based transfer learning architecture of ResNet152V2. Motivation: The motivation behind this research stems from the need to enhance the efficiency and accuracy of DSE prediction, enabling the pharmaceutical industry to identify potential drug candidates with fewer adverse effects. By utilizing 2D chemical structures and employing data augmentation techniques, we seek to revolutionize the field of drug side-effect prediction. Novelty: This study introduces several novel aspects. The proposed study is the first of its kind to use 2D chemical structures for predicting drug side effects, departing from the conventional 1D approaches. Secondly, we employ data augmentation with both conventional and diffusion-based models (Pix2Pix), a unique strategy in the field. These innovations set the stage for a more advanced and accurate approach to DSE prediction. Results: Our proposed model, named CHEM2SIDE, achieved an impressive average training accuracy of 0.78. Moreover, the average validation and test accuracy, precision, and recall were all at 0.73. When evaluated for COVID-19 drugs, our model exhibited an accuracy of 0.72, a precision of 0.79, a recall of 0.72, and an F1 score of 0.73. Comparative assessments against established transfer learning and machine learning models (VGG16, MobileNetV2, DenseNet121, and KNN) showcased the exceptional performance of CHEM2SIDE, marking a significant advancement in drug side-effect prediction. Conclusions: Our study introduces a groundbreaking approach to predicting drug side effects by using 2D chemical structures and incorporating data augmentation. The CHEM2SIDE model demonstrates remarkable accuracy and outperforms existing models, offering a promising solution to the challenges posed by DSEs in drug development. This research holds great potential for improving drug safety and reducing the associated time and costs.
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| 4. |
- Arshed, Muhammad Asad, et al.
(författare)
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Multiclass AI-Generated Deepfake Face Detection Using Patch-Wise Deep Learning Model
- 2024
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Ingår i: Computers. - 2073-431X. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- In response to the rapid advancements in facial manipulation technologies, particularly facilitated by Generative Adversarial Networks (GANs) and Stable Diffusion-based methods, this paper explores the critical issue of deepfake content creation. The increasing accessibility of these tools necessitates robust detection methods to curb potential misuse. In this context, this paper investigates the potential of Vision Transformers (ViTs) for effective deepfake image detection, leveraging their capacity to extract global features. Objective: The primary goal of this study is to assess the viability of ViTs in detecting multiclass deepfake images compared to traditional Convolutional Neural Network (CNN)-based models. By framing the deepfake problem as a multiclass task, this research introduces a novel approach, considering the challenges posed by Stable Diffusion and StyleGAN2. The objective is to enhance understanding and efficacy in detecting manipulated content within a multiclass context. Novelty: This research distinguishes itself by approaching the deepfake detection problem as a multiclass task, introducing new challenges associated with Stable Diffusion and StyleGAN2. The study pioneers the exploration of ViTs in this domain, emphasizing their potential to extract global features for enhanced detection accuracy. The novelty lies in addressing the evolving landscape of deepfake creation and manipulation. Results and Conclusion: Through extensive experiments, the proposed method exhibits high effectiveness, achieving impressive detection accuracy, precision, and recall, and an F1 rate of 99.90% on a multiclass-prepared dataset. The results underscore the significant potential of ViTs in contributing to a more secure digital landscape by robustly addressing the challenges posed by deepfake content, particularly in the presence of Stable Diffusion and StyleGAN2. The proposed model outperformed when compared with state-of-the-art CNN-based models, i.e., ResNet-50 and VGG-16.
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| 5. |
- Harhash, Ahmed A., et al.
(författare)
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Risk Stratification Among Survivors of Cardiac Arrest Considered for Coronary Angiography
- 2021
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Ingår i: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 77:4, s. 360-371
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe American College of Cardiology Interventional Council published consensus-based recommendations to help identify resuscitated cardiac arrest patients with unfavorable clinical features in whom invasive procedures are unlikely to improve survival.ObjectivesThis study sought to identify how many unfavorable features are required before prognosis is significantly worsened and which features are most impactful in predicting prognosis.MethodsUsing the INTCAR (International Cardiac Arrest Registry), the impact of each proposed “unfavorable feature” on survival to hospital discharge was individually analyzed. Logistic regression was performed to assess the association of such unfavorable features with poor outcomes.ResultsSeven unfavorable features (of 10 total) were captured in 2,508 patients successfully resuscitated after cardiac arrest (ongoing cardiopulmonary resuscitation and noncardiac etiology were exclusion criteria in our registry). Chronic kidney disease was used in lieu of end-stage renal disease. In total, 39% survived to hospital discharge. The odds ratio (OR) of survival to hospital discharge for each unfavorable feature was as follows: age >85 years OR: 0.30 (95% CI: 0.15 to 0.61), time-to-ROSC >30 min OR: 0.30 (95% CI: 0.23 to 0.39), nonshockable rhythm OR: 0.39 (95% CI: 0.29 to 0.54), no bystander cardiopulmonary resuscitation OR: 0.49 (95% CI: 0.38 to 0.64), lactate >7 mmol/l OR: 0.50 (95% CI: 0.40 to 0.63), unwitnessed arrest OR: 0.58 (95% CI: 0.44 to 0.78), pH <7.2 OR: 0.78 (95% CI: 0.63 to 0.98), and chronic kidney disease OR: 0.96 (95% CI: 0.70 to 1.33). The presence of any 3 or more unfavorable features predicted <40% survival. Presence of the 3 strongest risk factors (age >85 years, time-to-ROSC >30 min, and non-ventricular tachycardia/ventricular fibrillation) together or ≥6 unfavorable features predicted a ≤10% chance of survival to discharge.ConclusionsPatients successfully resuscitated from cardiac arrest with 6 or more unfavorable features have a poor long-term prognosis. Delaying or even forgoing invasive procedures in such patients is reasonable.
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| 6. |
- Mahmood, Rashid, et al.
(författare)
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Assessment of antidiabetic potential and phytochemical profiling of Rhazya stricta root extracts
- 2020
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Ingår i: BMC Complementary Medicine and Therapies. - : Springer Nature. - 2662-7671. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Diabetes mellitus is a chronic disease characterized by hyperglycemia that may occur due to genetic, environmental or lifestyle factors. Natural remedies have been used to treat diabetes since long and many antidiabetic compounds of varied efficacies have been isolated from medicinal plants. Rhazya stricta has been used for decades for the treatment of diabetes mellitus and associated ailments. Considering the folkloric use of R. stricta against diabetes, it was aimed to investigate the effectiveness of its root extracts against diabetes through in vitro assays and in vivo studies using animal model along with phytochemical profiling through GCMS. Methods: Various fractions of Rhazya stricta obtained through column chromatography were evaluated for a variety of assays including a-glucosidase, Dipeptidyl peptidase-IV (DPP-IV), beta-secretase and Glucagon-like peptide-1 (GLP-1) secretion studies. For the in vivo studies the alloxan-induced diabetic mice were treated with root extracts and blood glucose levels, HbA1C, and other biochemical markers along with the histological study of the liver were done. The phytochemical identification was performed using an Agilent 7890B GC coupled to a 7010 Triple Quadrupole (MS/MS) system. GraphPad Prism software version 5.01 was used for statistical analysis. Results: Majority of the extract fractions showed excellent results against diabetes by inhibiting enzymes DPP-IV (Up to 61%) and beta-secretase (Up to 83%) with IC50s 979 pg/ml and 169 mu g/ml respectively with increase in the GLP1 secretion. The results of in vivo studies indicated a marked reduction in blood glucose and HbA1c levels along with positive effects on other parameters like lipid profile, liver functions and renal functions of extract-treated mice as compared to control. The histological examination of the liver demonstrated hepatoprotective effects against diabetes led changes and various classes of phytochemicals were also identified through GCMS in different fractions. Conclusion: The results revealed strong antidiabetic activity of R. stricta root with the potential to protect body organs against diabetic changes. Moreover, a variety of phytochemicals has also been identified through GCMS that might be responsible for the antidiabetic potential of Rhazya stricta root.
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| 7. |
- Muhammad, Imran, et al.
(författare)
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3D porous sulfur-graphdiyne with splendid electrocatalytic and energy storage application
- 2023
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Ingår i: Materials Today Chemistry. - : Elsevier. - 2468-5194. ; 34
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Tidskriftsartikel (refereegranskat)abstract
- The blooming emergence of graphdiyne featuring embellished sp-hybridized carbons has been highly alluring for electrocatalysis and ion storage. Here, a porous 3D material sulfur-graphdiyne (3D-SGDY) is theoretically designed comprising butadiyne chains and sulfur as a heteroatom, owing a stable cubic skeleton and an atypical tuneable indirect bandgap. Compared to sp2-bonded carbon materials, the existence of sp-bonded carbon in 3D-SGDY tuned the direction of organic reactions leading to a single carbon product with numerous storage sites for the metal ions. Anchoring a single Cu atom in 3D-SGDY, we realize the unique Cu–C (3D-SGDY) chemical bonds exhibiting unconventional selectivity for CO2 reduction. The Cu–C bond in 3D-SGDY predominantly forms the *OCHO intermediates in lieu of *COOH and provides an active charge deportation channel during the reduction process of CO2 into CH4 product. Additionally, the porous structure reveals its astounding potential as an anode material by facilitating rapid transportation with a very low diffusion barrier of 0.06 eV and an ultrahigh capacity of 1826.4 mAhg−1 for Ca-ions. This work not only provides the 3D prototype of GDY but also administers the atomic level selectivity for CO2RR and high-performance Ca-ion batteries.
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| 8. |
- Salman, Muhammad, et al.
(författare)
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Evaluation of Conspiracy Beliefs, Vaccine Hesitancy, and Willingness to Pay towards COVID-19 Vaccines in Six Countries from Asian and African Regions : A Large Multinational Analysis
- 2022
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Ingår i: Vaccines. - : MDPI. - 2076-393X. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Vaccination protects people from serious illness and associated complications. Conspiracy theories and misinformation on vaccines have been rampant during the COVID-19 pandemic and are considered significant drivers of vaccine hesitancy. Since vaccine hesitancy can undermine efforts to immunize the population against COVID-19 and interferes with the vaccination rate, this study aimed to ascertain the COVID-19-vaccine-related conspiracy beliefs, vaccine hesitancy, views regarding vaccine mandates, and willingness to pay for vaccines among the general population. A web-based, cross-sectional survey was conducted (April-August 2021) among the adult population in six countries (Pakistan, Saudi Arabia, India, Malaysia, Sudan, and Egypt). Participants were recruited using an exponential, non-discriminate snowball sampling method. A validated self-completed electronic questionnaire was used for the data collection. All the participants responded to questions on various domains of the study instrument, including conspiracy beliefs, vaccine hesitancy, and willingness to pay. The responses were scored according to predefined criteria and stratified into various groups. All data were entered and analyzed using SPSS version 22. A total of 2481 responses were included in the study (Pakistan 24.1%, Saudi Arabia 19.5%, India 11.6%, Malaysia 8.1%, Sudan 19.3%, and Egypt 17.3%). There was a preponderance of participants <= 40 years old (18-25 years: 55.8%, 26-40 years: 28.5%) and females (57.1%). The average score of the COVID-19 vaccine conspiracy belief scale (C19V-CBS) was 2.30 +/- 2.12 (median 2; range 0-7). Our analysis showed that 30% of the respondents were found to achieve the ideal score of zero, indicating no conspiracy belief. The mean score of the COVID-19 vaccine hesitancy scale (C19V-HS) was 25.93 +/- 8.11 (range: 10-50). The majority (45.7%) had C19V-HA scores of 21-30 and nearly 28% achieved a score greater than 30, indicating a higher degree of hesitancy. There was a significant positive correlation between conspiracy beliefs and vaccine hesitancy (Spearman's rho = 0.547, p < 0.001). Half of the study population were against the vaccine mandate. Respondents in favor of governmental enforcement of COVID-19 vaccines had significantly (p < 0.001) lower scores on the C19V-CBS and C19V-HS scale. Nearly 52% reported that they would only take vaccine if it were free, and only 24% were willing to pay for COVID-19 vaccines. A high prevalence of conspiracy beliefs and vaccine hesitancy was observed in the targeted countries. Our findings highlight the dire need for aggressive measures to counter the conspiracy beliefs and factors underlying this vaccine hesitancy.
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