Measuring the impact of suspending Umrah, a global mass gathering in Saudi Arabia on the COVID‑19 pandemic

This article uses a stratified SEIR epidemic model to evaluate the impact of Umrah, a global Muslim pilgrimage to Mecca, on the spread of the COVID-19 pandemic during the month of Ramadan, the peak of the Umrah season. The analyses provide insights into the effects of global mass gatherings on the progression of the COVID-19 pandemic locally and globally

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Deep learning-based approach for emotion recognition using electroencephalography (EEG) signals using bi-directional Long Short-Term Memory (Bi-LSTM)

Emotions are an essential part of daily human communication. The emotional states and dynamics of the brain can be linked by electroencephalography (EEG) signals that can be used by the Brain–Computer Interface (BCI), to provide better human–machine interactions. Several studies have been conducted in the field of emotion recognition. However, one of the most important issues facing the emotion recognition process, using EEG signals, is the accuracy of recognition. This paper proposes a deep learning-based approach for emotion recognition through EEG signals, which includes data selection, feature extraction, feature selection and classification phases. This research serves the medical field, as the emotion recognition model helps diagnose psychological and behavioral disorders. The research contributes to improving the performance of the emotion recognition model to obtain more accurate results, which, in turn, aids in making the correct medical decisions. A standard pre-processed Database of Emotion Analysis using Physiological signaling (DEAP) was used in this work. The statistical features, wavelet features, and Hurst exponent were extracted from the dataset. The feature selection task was implemented through the Binary Gray Wolf Optimizer. At the classification stage, the stacked bi-directional Long Short-Term Memory (Bi-LSTM) Model was used to recognize human emotions. In this paper, emotions are classified into three main classes: arousal, valence and liking. The proposed approach achieved high accuracy compared to the methods used in past studies, with an average accuracy of 99.45%, 96.87% and 99.68% of valence, arousal, and liking, respectively, which is considered a high performance for the emotion recognition mod

Green Synthesis and Anticancer Potential of 1,4-Dihydropyridines-Based Triazole Derivatives: In Silico and In Vitro Study

A library of 1,4-dihydropyridine-based 1,2,3-triazol derivatives has been designed, synthesized, and evaluated their cytotoxic potential on colorectal adenocarcinoma (Caco-2) cell lines. All compounds were characterized and identified based on their 1H and 13C NMR (Nuclear Magnetic Resonance) spectroscopic data. Furthermore, molecular docking of best anticancer hits with target proteins (protein kinase CK2α, tankyrase1, and tankyrase2) has been performed. Our results implicated that most of these compounds have significant antiproliferative activity with IC50 values between 0.63 ± 0.05 and 5.68 ± 0.14 µM. Moreover, the mechanism of action of most active compounds 13ab′ and 13ad′ suggested that they induce cell death through apoptosis in the late apoptotic phase as well as dead phase, and they could promote cell cycle arrest at the G2/M phase. Furthermore, the molecular docking study illustrated that 13ad′ possesses better binding interaction with the catalytic residues of target proteins involved in cell proliferation and antiapoptotic pathways. Based on our in vitro and in silico study, 13ad′ was found to be a highly effective anti-cancerous compound. The present data indicate that dihydropyridine-linked 1,2,3-triazole conjugates can be generated as potent anticancer agents

Surveillance and Testing for Middle East Respiratory Syndrome Coronavirus, Saudi Arabia, April 2015–February 2016

Saudi Arabia has reported >80% of the Middle East respiratory syndrome coronavirus (MERS-CoV) cases worldwide. During April 2015–February 2016, Saudi Arabia identified and tested 57,363 persons (18.4/10,000 residents) with suspected MERS-CoV infection; 384 (0.7%) tested positive. Robust, extensive, and timely surveillance is critical for limiting virus transmission

Burnout, Resilience, Supervisory Support, and Quitting Intention among Healthcare Professionals in Saudi Arabia: A National Cross-Sectional Survey

Although personal resilience and supervisory support are known to reduce the impact of burnout and quitting intention, there is limited data available to explore these relationships among healthcare professionals (HCPs) in Saudi Arabia. This study aimed to assess the prevalence of burnout and explore its association with resilience, supervisory support, and intention to quit among Saudi Arabian HCPs. Methods: A cross-sectional survey was distributed to a convenience sample of HCPs between April and November 2022. Participants responded to socio-demographic questions, the Maslach Burnout Inventory-Human Services Survey for Medical Personnel (MBI-HSS (MP)), the Connor-Davidson resilience scale 10 (CD-RISC 10), and the Perceived of Supervisor Support Scale (PSS). Descriptive, inferential, correlation, and logistic regression tests were performed for data analyses. Results: Of the 1174 HCPs included in the analysis, 77% were presented with high burnout levels: 58% with emotional exhaustion (EE), 72% with depersonalization (DP), and 66% with low personal accomplishment (PA). Females were associated with increased odds of burnout (OR: 1.47; 95% CI: 1.04–2.06) compared to males. Burnout and its subscales were associated with higher intention to leave practice, with 33% of HCPs considering quitting their jobs. Furthermore, HCPs reported a low resilience score overall, and negative correlations were found between EE (r = −0.21; p < 0.001) and DP (r = −0.12; p < 0.01), and positive correlation with low PA (r = 0.38; p < 0.001). In addition, most HCPs perceived supervisory support as low, and it is associated with increased burnout and quitting intention. Conclusion: Burnout is common among HCPs across all clinical settings and is associated with higher intention to quit and low resilience and supervisory support. Workplace management should provide a supportive workplace to reduce burnout symptoms and promote resiliency

Exploring the Binding Pattern of Geraniol with Acetylcholinesterase through In Silico Docking, Molecular Dynamics Simulation, and In Vitro Enzyme Inhibition Kinetics Studies

Acetylcholinesterase (AChE) inhibition is a key element in enhancing cholinergic transmission and subsequently relieving major symptoms of several neurological and neuromuscular disorders. Here, the inhibitory potential of geraniol and its mechanism of inhibition against AChE were elucidated in vitro and validated via an in silico study. Our in vitro enzyme inhibition kinetics results show that at increasing concentrations of geraniol and substrate, Vmax did not change significantly, but Km increased, which indicates that geraniol is a competitive inhibitor against AChE with an IC50 value 98.06 ± 3.92 µM. All the parameters of the ADME study revealed that geraniol is an acceptable drug candidate. A docking study showed that the binding energy of geraniol (−5.6 kcal mol−1) was lower than that of acetylcholine (−4.1 kcal mol−1) with AChE, which exhibited around a 12.58-fold higher binding affinity of geraniol. Furthermore, molecular dynamics simulation revealed that the RMSD of AChE alone or in complex with geraniol fluctuated within acceptable limits throughout the simulation. The mean RMSF value of the complex ensures that the overall conformation of the protein remains conserved. The average values of Rg, MolSA, SASA, and PSA of the complex were 3.16 Å, 204.78, 9.13, and 51.58 Å2, respectively. We found that the total SSE of AChE in the complex was 38.84% (α-helix: 26.57% and β-sheets: 12.27%) and remained consistent throughout the simulation. These findings suggest that geraniol remained inside the binding cavity of AChE in a stable conformation. Further in vivo investigation is required to fully characterize the pharmacokinetic properties, optimization of dose administration, and efficacy of this plant-based natural compound

Attitudes, confidence, barriers and current practice of managing depression in patients with COPD in Saudi Arabia: a national cross-sectional survey

Objective To investigate physicians’ perceptions and current practices of identifying and managing depression in patients with chronic obstructive pulmonary disease (COPD).Design A cross-sectional online survey was employed between March and September 2022.Settings Saudi Arabia.Participants 1015 physicians, including general practitioners and family, internal and pulmonary medicine specialists.Primary outcome measures Physicians’ perceptions, confidence, practices and barriers to recognising and managing depression in patients with COPD.Results A total of 1015 physicians completed to the online survey. Only 31% of study participants received adequate training for managing depression. While 60% of physicians reported that depression interferes with self-management and worsens COPD symptoms, less than 50% viewed the importance of regular screening for depression. Only 414 (41%) physicians aim to identify depression. Of whom, 29% use depression screening tools, and 38% feel confident in discussing patients’ feelings. Having adequate training to manage depression (OR: 2.89; 95% CI: 2.02 to 3.81; p<0.001) and more years of experience (OR: 1.25; 95% CI: 1.08 to 1.45; p=0.002) were associated with the intention to detect depression in COPD patients. The most common barriers linked to recognising depression are poor training (54%), absence of standard procedures (54%) and limited knowledge about depression (53%).Conclusion The prevalence of identifying and confidently managing depression in patients with COPD is suboptimal, owing to poor training, the absence of a standardised protocol and inadequate knowledge. Psychiatric training should be supported in addition to adopting a systematic approach to detect depression in clinical practice