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Experimental evolution of extremotolerant and extremophilic fungi under osmotic stress.
Hariri Akbari, F, Song, Z, Turk, M, Gunde-Cimerman, N, Gostinčar, C
IUBMB life. 2024
Abstract
Experimental evolution was carried out to investigate the adaptive responses of extremotolerant fungi to a stressful environment. For 12 cultivation cycles, the halotolerant black yeasts Aureobasidium pullulans and Aureobasidium subglaciale were grown at high NaCl or glycerol concentrations, and the halophilic basidiomycete Wallemia ichthyophaga was grown close to its lower NaCl growth limit. All evolved Aureobasidium spp. accelerated their growth at low water activity. Whole genomes of the evolved strains were sequenced. No aneuploidies were detected in any of the genomes, contrary to previous studies on experimental evolution at high salinity with other species. However, several hundred single-nucleotide polymorphisms were identified compared with the genomes of the progenitor strains. Two functional groups of genes were overrepresented among the genes presumably affected by single-nucleotide polymorphisms: voltage-gated potassium channels in A. pullulans at high NaCl concentration, and hydrophobins in W. ichthyophaga at low NaCl concentration. Both groups of genes were previously associated with adaptation to high salinity. Finally, most evolved Aureobasidium spp. strains were found to have increased intracellular and decreased extracellular glycerol concentrations at high salinity, suggesting that the strains have optimised their management of glycerol, their most important compatible solute. Experimental evolution therefore not only confirmed the role of potassium transport, glycerol management, and cell wall in survival at low water activity, but also demonstrated that fungi from extreme environments can further improve their growth rates under constant extreme conditions in a relatively short time and without large scale genomic rearrangements.
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Epithelial barrier hypothesis: Effect of the external exposome on the microbiome and epithelial barriers in allergic disease.
Celebi Sozener, Z, Ozdel Ozturk, B, Cerci, P, Turk, M, Gorgulu Akin, B, Akdis, M, Altiner, S, Ozbey, U, Ogulur, I, Mitamura, Y, et al
Allergy. 2022;(5):1418-1449
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Abstract
Environmental exposure plays a major role in the development of allergic diseases. The exposome can be classified into internal (e.g., aging, hormones, and metabolic processes), specific external (e.g., chemical pollutants or lifestyle factors), and general external (e.g., broader socioeconomic and psychological contexts) domains, all of which are interrelated. All the factors we are exposed to, from the moment of conception to death, are part of the external exposome. Several hundreds of thousands of new chemicals have been introduced in modern life without our having a full understanding of their toxic health effects and ways to mitigate these effects. Climate change, air pollution, microplastics, tobacco smoke, changes and loss of biodiversity, alterations in dietary habits, and the microbiome due to modernization, urbanization, and globalization constitute our surrounding environment and external exposome. Some of these factors disrupt the epithelial barriers of the skin and mucosal surfaces, and these disruptions have been linked in the last few decades to the increasing prevalence and severity of allergic and inflammatory diseases such as atopic dermatitis, food allergy, allergic rhinitis, chronic rhinosinusitis, eosinophilic esophagitis, and asthma. The epithelial barrier hypothesis provides a mechanistic explanation of how these factors can explain the rapid increase in allergic and autoimmune diseases. In this review, we discuss factors affecting the planet's health in the context of the 'epithelial barrier hypothesis,' including climate change, pollution, changes and loss of biodiversity, and emphasize the changes in the external exposome in the last few decades and their effects on allergic diseases. In addition, the roles of increased dietary fatty acid consumption and environmental substances (detergents, airborne pollen, ozone, microplastics, nanoparticles, and tobacco) affecting epithelial barriers are discussed. Considering the emerging data from recent studies, we suggest stringent governmental regulations, global policy adjustments, patient education, and the establishment of individualized control measures to mitigate environmental threats and decrease allergic disease.
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Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.
Munjral, S, Maindarkar, M, Ahluwalia, P, Puvvula, A, Jamthikar, A, Jujaray, T, Suri, N, Paul, S, Pathak, R, Saba, L, et al
Diagnostics (Basel, Switzerland). 2022;(5)
Abstract
Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.
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Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.
Munjral, S, Ahluwalia, P, Jamthikar, AD, Puvvula, A, Saba, L, Faa, G, Singh, IM, Chadha, PS, Turk, M, Johri, AM, et al
Frontiers in bioscience (Landmark edition). 2021;(11):1312-1339
Abstract
Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.
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Wilson's disease: A new perspective review on its genetics, diagnosis and treatment.
Saba, L, Tiwari, A, Biswas, M, Gupta, SK, Godia-Cuadrado, E, Chaturvedi, A, Turk, M, Suri, HS, Orru, S, Sanches, JM, et al
Frontiers in bioscience (Elite edition). 2019;(1):166-185
Abstract
Wilson's disease (WD) is an autosomal recessive disorder which is caused by poor excretion of copper in mammalian cells. In this review, various issues such as effective characterization of ATP7B genes, scope of gene network topology in genetic analysis, pattern recognition using different computing approaches and fusion possibilities in imaging and genetic dataset are discussed vividly. We categorized this study into three major sections: (A) WD genetics, (B) diagnosis guidelines and (3) treatment possibilities. We addressed the scope of advanced mathematical modelling paradigms for understanding common genetic sequences and dominating WD imaging biomarkers. We have also discussed current state-of-the-art software models for genetic sequencing. Further, we hypothesized that involvement of machine and deep learning techniques in the context of WD genetics and image processing for precise classification of WD. These computing procedures signify changing roles of various data transformation techniques with respect to supervised and unsupervised learning models.
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Coenzyme Q10 supplementation decreases statin-related mild-to-moderate muscle symptoms: a randomized clinical study.
Skarlovnik, A, Janić, M, Lunder, M, Turk, M, Šabovič, M
Medical science monitor : international medical journal of experimental and clinical research. 2014;:2183-8
Abstract
BACKGROUND Statin use is frequently associated with muscle-related symptoms. Coenzyme Q10 supplementation has yielded conflicting results in decreasing statin myopathy. Herein, we tested whether coenzyme Q10 supplementation could decrease statin-associated muscular pain in a specific group of patients with mild-to-moderate muscle symptoms. MATERIAL/METHODS Fifty patients treated with statins and reporting muscle pain were recruited. The Q10 group (n=25) received coenzyme Q10 supplementation over a period of 30 days (50 mg twice daily), and the control group (n=25) received placebo. The Brief Pain Inventory (BPI) questionnaire was used and blood testing was performed at inclusion in the study and after 30 days of supplementation. RESULTS The intensity of muscle pain, measured as the Pain Severity Score (PSS), in the Q10 group was reduced from 3.9±0.4 to 2.9±0.4 (P<0.001). The Pain Interference Score (PIS) after Q10 supplementation was reduced from 4.0±0.4 to 2.6±0.4 (P<0.001). In the placebo group, PSS and PIS did not change. Coenzyme Q10 supplementation decreased statin-related muscle symptoms in 75% of patients. The relative values of PSS and PIS significantly decreased (-33.1% and -40.3%, respectively) in the Q10 group compared to placebo group (both P<0.05). From baseline, no differences in liver and muscle enzymes or cholesterol values were found. CONCLUSIONS The present results show that coenzyme Q10 supplementation (50 mg twice daily) effectively reduced statin-related mild-to-moderate muscular symptoms, causing lower interference of statin-related muscular symptoms with daily activities.