The Association between Lifestyle Factors and COVID-19: Findings from Qatar Biobank.

Coronavirus Disease 2019 (COVID-19) manifestations range from mild to severe life-threatening symptoms, including death. COVID-19 susceptibility has been associated with various factors, but studies in Qatar are limited. The objective of this study was to investigate the correlation between COVID-19 susceptibility and various sociodemographic and lifestyle factors, including age, gender, body mass index, smoking status, education level, dietary patterns, supplement usage, physical activity, a history of bariatric surgery, diabetes, and hypertension. We utilized logistic regression to analyze these associations, using the data of 10,000 adult participants, aged from 18 to 79, from Qatar Biobank. In total, 10.5% (n = 1045) of the participants had COVID-19. Compared to non-smokers, current and ex-smokers had lower odds of having COVID-19 (odds ratio [OR] = 0.55; 95% CI: 0.44-0.68 and OR = 0.70; 95% CI: 0.57-0.86, respectively). Vitamin D supplement use was associated with an 18% reduction in the likelihood of contracting COVID-19 (OR = 0.82; 95% CI: 0.69-0.97). Obesity (BMI ≥ 30 kg/m2), a history of bariatric surgery, and higher adherence to the modern dietary pattern-characterized by the consumption of foods high in saturated fat and refined carbohydrates-were positively associated with COVID-19. Our findings indicate that adopting a healthy lifestyle may be helpful in the prevention of COVID-19 infection.

The Parkinson's disease risk gene cathepsin B promotes fibrillar alpha-synuclein clearance, lysosomal function and glucocerebrosidase activity in dopaminergic neurons.

Background: Variants in the CTSB gene encoding the lysosomal hydrolase cathepsin B (catB) are associated with increased risk of Parkinson's disease (PD). However, neither the specific CTSB variants driving these associations nor the functional pathways that link catB to PD pathogenesis have been characterized. CatB activity contributes to lysosomal protein degradation and regulates signaling processes involved in autophagy and lysosome biogenesis. Previous in vitro studies have found that catB can cleave monomeric and fibrillar alpha-synuclein, a key protein involved in the pathogenesis of PD that accumulates in the brains of PD patients. However, truncated synuclein isoforms generated by catB cleavage have an increased propensity to aggregate. Thus, catB activity could potentially contribute to lysosomal degradation and clearance of pathogenic alpha synuclein from the cell, but also has the potential of enhancing synuclein pathology by generating aggregation-prone truncations. Therefore, the mechanisms linking catB to PD pathophysiology remain to be clarified. Methods: Here, we conducted genetic analyses of the association between common and rare CTSB variants and risk of PD. We then used genetic and pharmacological approaches to manipulate catB expression and function in cell lines and induced pluripotent stem cell-derived dopaminergic neurons and assessed lysosomal activity and the handling of aggregated synuclein fibrils. Results: We first identified specific non-coding variants in CTSB that drive the association with PD and are linked to changes in brain CTSB expression levels. Using iPSC-derived dopaminergic neurons we then find that catB inhibition impairs autophagy, reduces glucocerebrosidase (encoded by GBA1) activity, and leads to an accumulation of lysosomal content. Moreover, in cell lines, reduction of CTSB gene expression impairs the degradation of pre-formed alpha-synuclein fibrils, whereas CTSB gene activation enhances fibril clearance. Similarly, in midbrain organoids and dopaminergic neurons treated with alpha-synuclein fibrils, catB inhibition or knockout potentiates the formation of inclusions which stain positively for phosphorylated alpha-synuclein. Conclusions: The results of our genetic and functional studies indicate that the reduction of catB function negatively impacts lysosomal pathways associated with PD pathogenesis, while conversely catB activation could promote the clearance of pathogenic alpha-synuclein.

Qatar's Silent Epidemic: A Comprehensive Meta-analysis on the Prevalence of Metabolic Syndrome.

BACKGROUND: Metabolic syndrome comprises various conditions like abdominal obesity, insulin resistance, elevated triglyceride levels, reduced HDL, and high blood pressure, which pose significant health challenges globally. It's imperative to determine its prevalence in specific populations to formulate effective preventive measures. OBJECTIVE: This systematic review and meta-analysis aimed to determine the prevalence of metabolic syndrome in the Qatari population. METHODS: Using the PRISMA guidelines, a systematic search was executed on PubMed until July 2023 with keywords "Metabolic syndrome" and "Qatar." Eligibility criteria included human subjects, studies assessing metabolic syndrome components, and research conducted in Qatar or on Qatari subjects. The quality of the studies was evaluated using the Newcastle-Ottawa Scale (NOS). Pooled prevalence rates were calculated using the inverse variance weighting metaanalysis. RESULTS: Out of 237 studies, 14 met our inclusion criteria, with a combined sample size of 14,772 from the Qatari population. The overall pooled prevalence of metabolic syndrome was 26%. The ATP III and IDF criteria exhibited significant differences in prevalence rates, with the IDF criteria showing a higher prevalence. Age ≥ 40 years demonstrated a higher prevalence compared to the younger group. Studies post-2018 reported a decreasing trend in metabolic syndrome prevalence. CONCLUSION: The prevalence of metabolic syndrome in the Qatari population is comparable to rates in the Middle East. The study underscores the need for tailored interventions and strategies, especially targeting the older age group. Continuous research and monitoring are essential to track and understand the disease's progression in Qatar.

Development and Evaluation of a High-Fidelity Rhinoplasty Simulator.

SUMMARY: Rhinoplasty is a challenging procedure with a steep learning curve. Surgical simulators provide a safe platform to gain hands-on experience without compromising patient outcomes. Therefore, rhinoplasty is an ideal procedure to benefit from an effective surgical simulator. A high-fidelity rhinoplasty simulator was developed using three-dimensional computer modeling, three-dimensional printing, and polymer techniques. The simulator was tested by six surgeons with experience in rhinoplasty to assess realism, anatomic accuracy, and value as a training tool. The surgeons performed common rhinoplasty techniques and were provided a Likert-type questionnaire assessing the anatomic features of the simulator. A variety of surgical techniques were performed successfully using the simulator, including open and closed approaches. Bony techniques performed included endonasal osteotomies and rasping. Submucous resection with harvest of septal cartilage, cephalic trim, and tip suturing, as well as grafting techniques including alar rim, columellar strut, spreader, and shield grafts, were performed successfully. Overall, there was agreement on the simulator's anatomic accuracy of bony and soft-tissue features. There was strong agreement on the simulator's overall realism and value as a training tool. The simulator provides a high-fidelity, comprehensive training platform to learn rhinoplasty techniques to augment real operating experience without compromising patient outcomes.

Urolithiasis-related ureteric intussusception: A rare case report.

Ureteral intussusception is a rare condition that historically occurs as a complication of ureteral neoplasms or iatrogenic endoscopic procedures. Although the exact mechanism of ureteral intussusception is unclear, most reported cases are due to leading points as malignant or benign masses. Urolithiasis related is rarely reported and can be challenging in stone management as it might decrease the spontaneous stone passage rate. In addition, it will increase the complexity of the endoscopic stone management. We present the second reported case of urolithiasis-related ureteric intussusception presented with urosepsis due to obstructive uropathy, successfully managed by an endourological approach.

A Meta Modeling-Based Interoperability and Integration Testing Platform for IoT Systems.

The rapid growth of the Internet of Things (IoT) and its integration into various industries has made it extremely challenging to guarantee IoT systems' dependability and quality, including scalability, dynamicity, and integration with existing IoT frameworks. However, the essential principles, approaches, and advantages of model-driven IoT testing indicate a promising strategy for overcoming these. This paper proposes a metamodeling-based interoperability and integration testing approach for IoT systems that automates the creation of test cases and the assessment of system performance by utilizing formal models to reflect the behavior and interactions of IoT systems. The proposed model-based testing enables the systematic verification and validation of complex IoT systems by capturing the essential characteristics of IoT devices, networks, and interactions. This study describes the key elements of model-driven IoT testing, including the development of formal models, methods for generating test cases, and the execution and assessment of models. In addition, it examines various modeling formalisms and their use in IoT testing, including state-based, event-driven, and hybrid models. This study examines several methods for creating test cases to ensure thorough and effective testing, such as constraint-based strategies and model coverage requirements. Model-driven IoT testing improves defect detection, expands test coverage, decreases testing effort, and increases system reliability. It also offers an organized and automated method to confirm the efficiency and dependability of IoT systems.

The Parkinson's disease risk gene cathepsin B promotes fibrillar alpha-synuclein clearance, lysosomal function and glucocerebrosidase activity in dopaminergic neurons.

Variants in the CTSB gene encoding the lysosomal hydrolase cathepsin B (catB) are associated with increased risk of Parkinson's disease (PD). However, neither the specific CTSB variants driving these associations nor the functional pathways that link catB to PD pathogenesis have been characterized. CatB activity contributes to lysosomal protein degradation and regulates signaling processes involved in autophagy and lysosome biogenesis. Previous in vitro studies have found that catB can cleave monomeric and fibrillar alpha-synuclein, a key protein involved in the pathogenesis of PD that accumulates in the brains of PD patients. However, truncated synuclein isoforms generated by catB cleavage have an increased propensity to aggregate. Thus, catB activity could potentially contribute to lysosomal degradation and clearance of pathogenic alpha synuclein from the cell, but also has the potential of enhancing synuclein pathology by generating aggregation-prone truncations. Therefore, the mechanisms linking catB to PD pathophysiology remain to be clarified. Here, we conducted genetic analyses of the association between common and rare CTSB variants and risk of PD. We then used genetic and pharmacological approaches to manipulate catB expression and function in cell lines and induced pluripotent stem cell-derived dopaminergic neurons and assessed lysosomal activity and the handling of aggregated synuclein fibrils. We find that catB inhibition impairs autophagy, reduces glucocerebrosidase (encoded by GBA1) activity, and leads to an accumulation of lysosomal content. In cell lines, reduction of CTSB gene expression impairs the degradation of pre-formed alpha-synuclein fibrils, whereas CTSB gene activation enhances fibril clearance. In midbrain organoids and dopaminergic neurons treated with alpha-synuclein fibrils, catB inhibition potentiates the formation of inclusions which stain positively for phosphorylated alpha-synuclein. These results indicate that the reduction of catB function negatively impacts lysosomal pathways associated with PD pathogenesis, while conversely catB activation could promote the clearance of pathogenic alpha-synuclein.

Artificial Intelligence and Machine Learning Applications in Sudden Cardiac Arrest Prediction and Management: A Comprehensive Review.

PURPOSE OF REVIEW: This literature review aims to provide a comprehensive overview of the recent advances in prediction models and the deployment of AI and ML in the prediction of cardiopulmonary resuscitation (CPR) success. The objectives are to understand the role of AI and ML in healthcare, specifically in medical diagnosis, statistics, and precision medicine, and to explore their applications in predicting and managing sudden cardiac arrest outcomes, especially in the context of prehospital emergency care. RECENT FINDINGS: The role of AI and ML in healthcare is expanding, with applications evident in medical diagnosis, statistics, and precision medicine. Deep learning is gaining prominence in radiomics and population health for disease risk prediction. There's a significant focus on the integration of AI and ML in prehospital emergency care, particularly in using ML algorithms for predicting outcomes in COVID-19 patients and enhancing the recognition of out-of-hospital cardiac arrest (OHCA). Furthermore, the combination of AI with automated external defibrillators (AEDs) shows potential in better detecting shockable rhythms during cardiac arrest incidents. AI and ML hold immense promise in revolutionizing the prediction and management of sudden cardiac arrest, hinting at improved survival rates and more efficient healthcare interventions in the future. Sudden cardiac arrest (SCA) continues to be a major global cause of death, with survival rates remaining low despite advanced first responder systems. The ongoing challenge is the prediction and prevention of SCA. However, with the rise in the adoption of AI and ML tools in clinical electrophysiology in recent times, there is optimism about addressing these challenges more effectively.

The gut microbiome in the fight against obesity: The potential of dietary factors.

Obesity as a global public health burden has experienced a drastic growing trend recently. The management of obesity is challenging because of its complex etiology, and various factors are involved in its development, such as genetic and environmental factors. Different approaches are available to treat and/or manage obesity, including diet, physical activity, lifestyle changes, medications, and surgery. However, some of these approaches have inherent limitations and are closely associated with adverse effects. Therefore, probing into a novel/safe approach to treat and/or manage obesity is of fundamental importance. One such approach gaining renewed interest is the potential role of gut microbiota in obesity and its effectiveness in treating this condition. However, there is a dearth of comprehensive compilation of data on the potential role of the gut microbiome in obesity, particularly regarding dietary factors as a therapeutic approach. Therefore, this review aims to provide an updated overview of the role of gut microbiota in obesity, further highlighting the importance of dietary factors, particularly diet, prebiotics, and probiotics, as potential complementary and/or alternative therapeutic options. Moreover, the association of gut microbiota with obese or lean individuals has also been discussed.

Modelling and analysis of the complement system signalling pathways: roles of C3, C5a and pro-inflammatory cytokines in SARS-CoV-2 infection.

The complement system is an essential part of innate immunity. It is activated by invading pathogens causing inflammation, opsonization, and lysis via complement anaphylatoxins, complement opsonin's and membrane attack complex (MAC), respectively. However, in SARS-CoV-2 infection overactivation of complement system is causing cytokine storm leading to multiple organs damage. In this study, the René Thomas kinetic logic approach was used for the development of biological regulatory network (BRN) to model SARS-CoV-2 mediated complement system signalling pathways. Betweenness centrality analysis in cytoscape was adopted for the selection of the most biologically plausible states in state graph. Among the model results, in strongly connected components (SCCs) pro-inflammatory cytokines (PICyts) oscillatory behaviour between recurrent generation and downregulation was found as the main feature of SARS-CoV-2 infection. Diversion of trajectories from the SCCs leading toward hyper-inflammatory response was found in agreement with in vivo studies that overactive innate immunity response caused PICyts storm during SARS-CoV-2 infection. The complex of negative regulators FI, CR1 and DAF in the inhibition of complement peptide (C5a) and PICyts was found desirable to increase immune responses. In modelling role of MAC and PICyts in lowering of SARS-CoV-2 titre was found coherent with experimental studies. Intervention in upregulation of C5a and PICyts by C3 was found helpful in back-and-forth variation of signalling pattern linked with the levels of PICyts. Moreover, intervention in upregulation of PICyts by C5a was found productive in downregulation of all activating factors in the normal SCCs. However, the computational model predictions require experimental studies to be validated by exploring the activation role of C3 and C5a which could change levels of PICyts at various phases of SARS-CoV-2 infection.

Migrated Hem-o-lok clip in the bladder: A rare cause of bladder stone for cystolitholapaxy.

The bladder is the most common site of foreign bodies in the urinary tract. Most foreign bodies are self-inserted via the urethra due to exotic impulses, psychometric problems, or sexual curiosity. Here we present a rare case of bladder stones due to the migration of the Heme-o-lok clip. We present a case of a 76-year-old male with hematuria for 4 days. An abdominal computed tomography (CT) scan showed a 15 mm calculus noted in the urinary bladder. The patient underwent cystolitholapaxy which was successful. Foreign bodies inserted in the bladder pose a significant challenge and require timely intervention.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm.

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable. To address this issue, this study proposes a novel approach for aneurysm segmentation and multidisciplinary rupture prediction using 2D Digital Subtraction Angiography (DSA) images. The proposed method involves training a fully connected convolutional neural network (CNN) to segment aneurysm regions in DSA images, followed by extracting and fusing different features using a multidisciplinary approach, including deep features, geometrical features, Fourier descriptor, and shear pressure on the aneurysm wall. The proposed method also adopts a fast correlation-based filter approach to drop highly correlated features from the set of fused features. Finally, the selected fused features are passed through a Decision Tree classifier to predict the rupture severity of the associated aneurysm into four classes: Mild, Moderate, Severe, and Critical. The proposed method is evaluated on a newly developed DSA image dataset and on public datasets to assess its generalizability. The system's performance is also evaluated on DSA images annotated by expert neurosurgeons for the rupture risk assessment of the segmented aneurysm. The proposed system outperforms existing state-of-the-art segmentation methods, achieving an 85 % accuracy against annotated DSA images for the risk assessment of aneurysmal rupture.

Association of Rare Variants in ARSA with Parkinson's Disease.

BACKGROUND: Several lysosomal genes are associated with Parkinson's disease (PD), yet the association between PD and ARSA remains unclear. OBJECTIVES: To study rare ARSA variants in PD. METHODS: To study rare ARSA variants (minor allele frequency < 0.01) in PD, we performed burden analyses in six independent cohorts with 5801 PD patients and 20,475 controls, followed by a meta-analysis. RESULTS: We found evidence for associations between functional ARSA variants and PD in four cohorts (P ≤ 0.05 in each) and in the meta-analysis (P = 0.042). We also found an association between loss-of-function variants and PD in the United Kingdom Biobank cohort (P = 0.005) and in the meta-analysis (P = 0.049). These results should be interpreted with caution as no association survived multiple comparisons correction. Additionally, we describe two families with potential co-segregation of ARSA p.E382K and PD. CONCLUSIONS: Rare functional and loss-of-function ARSA variants may be associated with PD. Further replications in large case-control/familial cohorts are required. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prognosis Prediction in COVID-19 Patients through Deep Feature Space Reasoning.

The COVID-19 pandemic has presented a unique challenge for physicians worldwide, as they grapple with limited data and uncertainty in diagnosing and predicting disease outcomes. In such dire circumstances, the need for innovative methods that can aid in making informed decisions with limited data is more critical than ever before. To allow prediction with limited COVID-19 data as a case study, we present a complete framework for progression and prognosis prediction in chest X-rays (CXR) through reasoning in a COVID-specific deep feature space. The proposed approach relies on a pre-trained deep learning model that has been fine-tuned specifically for COVID-19 CXRs to identify infection-sensitive features from chest radiographs. Using a neuronal attention-based mechanism, the proposed method determines dominant neural activations that lead to a feature subspace where neurons are more sensitive to COVID-related abnormalities. This process allows the input CXRs to be projected into a high-dimensional feature space where age and clinical attributes like comorbidities are associated with each CXR. The proposed method can accurately retrieve relevant cases from electronic health records (EHRs) using visual similarity, age group, and comorbidity similarities. These cases are then analyzed to gather evidence for reasoning, including diagnosis and treatment. By using a two-stage reasoning process based on the Dempster-Shafer theory of evidence, the proposed method can accurately predict the severity, progression, and prognosis of a COVID-19 patient when sufficient evidence is available. Experimental results on two large datasets show that the proposed method achieves 88% precision, 79% recall, and 83.7% F-score on the test sets.

Aesthetic Refinements in Male Chest Lifting.

The authors describe aesthetic refinements to the approach for male chest lifting in male patients with grade 3 gynecomastia and/or significant chest skin excess. An inferior pedicle is used to transpose the nipple-areolar complex allowing preservation of pigment and sensation, liposuction and direct excision are used to reduce volume and excess skin, and the resulting curvilinear scar along the inferior and lateral border of the chest provide a more masculine appearance. Early experience with this technique has shown it to be safe and effective. Perioperative management and the detailed steps of the procedure are outlined.

NPC1 variants are not associated with Parkinson's disease, REM-sleep behavior disorder or dementia with Lewy bodies in European cohorts.

NPC1 encodes a lysosomal protein involved in cholesterol transport. Biallelic mutations in this gene may lead to Niemann-Pick disease type C (NPC), a lysosomal storage disorder. The role of NPC1 in alpha synucleinopathies is still unclear, as different genetic, clinical, and pathological studies have reported contradictory results. This study aimed to evaluate the association of NPC1 variants with the synucleinopathies Parkinson's disease (PD), dementia with Lewy bodies (DLB), and rapid eye movement-sleep behavior disorder (RBD). We analyzed common and rare variants from 3 cohorts of European descent: 1084 RBD cases and 2945 controls, 2852 PD cases and 1686 controls, and 2610 DLB cases and 1920 controls. Logistic regression models were used to assess common variants while optimal sequence Kernel association tests were used to assess rare variants, both adjusted for sex, age, and principal components. No variants were associated with any of the synucleinopathies, supporting that common and rare NPC1 variants do not play an important role in alpha synucleinopathies.

Association of rare variants in ARSA with Parkinson's disease.

Background: Several lysosomal genes are associated with Parkinson's disease (PD), yet the association between PD and ARSA , which encodes for the enzyme arylsulfatase A, remains controversial. Objectives: To evaluate the association between rare ARSA variants and PD. Methods: To study possible association of rare variants (minor allele frequency<0.01) in ARSA with PD, we performed burden analyses in six independent cohorts with a total of 5,801 PD patients and 20,475 controls, using optimized sequence Kernel association test (SKAT-O), followed by a meta-analysis. Results: We found evidence for an association between functional ARSA variants and PD in four independent cohorts (P≤0.05 in each) and in the meta-analysis (P=0.042). We also found an association between loss-of-function variants and PD in the UKBB cohort (P=0.005) and in the meta-analysis (P=0.049). However, despite replicating in four independent cohorts, these results should be interpreted with caution as no association survived correction for multiple comparisons. Additionally, we describe two families with potential co-segregation of the ARSA variant p.E384K and PD. Conclusions: Rare functional and loss-of-function ARSA variants may be associated with PD. Further replication in large case-control cohorts and in familial studies is required to confirm these associations.

GALC variants affect galactosylceramidase enzymatic activity and risk of Parkinson's disease.

The association between glucocerebrosidase, encoded by GBA, and Parkinson's disease (PD) highlights the role of the lysosome in PD pathogenesis. Genome-wide association studies in PD have revealed multiple associated loci, including the GALC locus on chromosome 14. GALC encodes the lysosomal enzyme galactosylceramidase, which plays a pivotal role in the glycosphingolipid metabolism pathway. It is still unclear whether GALC is the gene driving the association in the chromosome 14 locus and, if so, by which mechanism. We first aimed to examine whether variants in the GALC locus and across the genome are associated with galactosylceramidase activity. We performed a genome-wide association study in two independent cohorts from (i) Columbia University; and (ii) the Parkinson's Progression Markers Initiative study, followed by a meta-analysis with a total of 976 PD patients and 478 controls with available data on galactosylceramidase activity. We further analysed the effects of common GALC variants on expression and galactosylceramidase activity using genomic colocalization methods. Mendelian randomization was used to study whether galactosylceramidase activity may be causal in PD. To study the role of rare GALC variants, we analysed sequencing data from 5028 PD patients and 5422 controls. Additionally, we studied the functional impact of GALC knockout on alpha-synuclein accumulation and on glucocerebrosidase activity in neuronal cell models and performed in silico structural analysis of common GALC variants associated with altered galactosylceramidase activity. The top hit in PD genome-wide association study in the GALC locus, rs979812, is associated with increased galactosylceramidase activity (b = 1.2; SE = 0.06; P = 5.10 × 10-95). No other variants outside the GALC locus were associated with galactosylceramidase activity. Colocalization analysis demonstrated that rs979812 was also associated with increased galactosylceramidase expression. Mendelian randomization suggested that increased galactosylceramidase activity may be causally associated with PD (b = 0.025, SE = 0.007, P = 0.0008). We did not find an association between rare GALC variants and PD. GALC knockout using CRISPR-Cas9 did not lead to alpha-synuclein accumulation, further supporting that increased rather than reduced galactosylceramidase levels may be associated with PD. The structural analysis demonstrated that the common variant p.I562T may lead to improper maturation of galactosylceramidase affecting its activity. Our results nominate GALC as the gene associated with PD in this locus and suggest that the association of variants in the GALC locus may be driven by their effect of increasing galactosylceramidase expression and activity. Whether altering galactosylceramidase activity could be considered as a therapeutic target should be further studied.