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1.
Physiological functions of ULK1/2.
Pareek, G, Kundu, M
Journal of molecular biology. 2024;:168472
Abstract
UNC-51-like kinases 1 and 2 (ULK1/2) are serine/threonine kinases that are best known for their evolutionarily conserved role in the autophagy pathway. Upon sensing the nutrient status of a cell, ULK1/2 integrate signals from upstream cellular energy sensors such as mTOR and AMPK and relay them to the downstream components of the autophagy machinery. ULK1/2 also play indispensable roles in the selective autophagy pathway, removing damaged mitochondria, invading pathogens, and toxic protein aggregates. Additional functions of ULK1/2 have emerged beyond autophagy, including roles in protein trafficking, RNP granule dynamics, and signaling events impacting innate immunity, axon guidance, cellular homeostasis, and cell fate. Therefore, it is no surprise that alterations in ULK1/2 expression and activity have been linked with pathophysiological processes, including cancer, neurological disorders, and cardiovascular diseases. Growing evidence suggests that ULK1/2 function as biological rheostats, tuning cellular functions to intra and extra-cellular cues. Given their broad physiological relevance, ULK1/2 are candidate targets for small molecule activators or inhibitors that may pave the way for the development of therapeutics for the treatment of diseases in humans.
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2.
AAA+ proteases: the first line of defense against mitochondrial damage.
Pareek, G
PeerJ. 2022;:e14350
Abstract
Mitochondria play essential cellular roles in Adenosine triphosphate (ATP) synthesis, calcium homeostasis, and metabolism, but these vital processes have potentially deadly side effects. The production of the reactive oxygen species (ROS) and the aggregation of misfolded mitochondrial proteins can lead to severe mitochondrial damage and even cell death. The accumulation of mitochondrial damage is strongly implicated in aging and several incurable diseases, including neurodegenerative disorders and cancer. To oppose this, metazoans utilize a variety of quality control strategies, including the degradation of the damaged mitochondrial proteins by the mitochondrial-resident proteases of the ATPase Associated with the diverse cellular Activities (AAA+) family. This mini-review focuses on the quality control mediated by the mitochondrial-resident proteases of the AAA+ family used to combat the accumulation of damaged mitochondria and on how the failure of this mitochondrial quality control contributes to diseases.
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3.
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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4.
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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5.
Pharmacologic treatment of kidney stone disease.
Eisner, BH, Goldfarb, DS, Pareek, G
The Urologic clinics of North America. 2013;(1):21-30
Abstract
This article reviews the data on pharmacologic treatment of kidney stone disease, with a focus on prophylaxis against stone recurrence. One of the most effective and important therapies for stone prevention, an increase in urine volume, is not discussed because this is a dietary and not a pharmacologic intervention. Also reviewed are medical expulsive therapy used to improve the spontaneous passage of ureteral stones and pharmacologic treatment of symptoms associated with ureteral stents. The goal is to review the literature with a focus on the highest level of evidence (ie, randomized controlled trials).
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6.
Expression of S100A4 in renal epithelial neoplasms.
Wang, LJ, Matoso, A, Sciandra, KT, Yakirevich, E, Sabo, E, Zhang, Y, Meitner, PA, Tavares, R, Noble, L, Pareek, G, et al
Applied immunohistochemistry & molecular morphology : AIMM. 2012;(1):71-6
Abstract
Expression of S100A4 has been associated with progression and poor clinical outcome in a variety of malignancies including those of the breast, pancreas, bladder, and thyroid. To date, the expression of S100A4 protein in renal epithelial neoplasms is poorly understood. In this study, we evaluated the expression of S100A4 protein and mRNA in the nontumoral kidney and renal epithelial neoplasms of different types and correlated its expression with patient outcome. The study population included 155 clear cell renal cell carcinomas (cRCC), 22 papillary renal cell carcinomas (pRCC), 13 chromophobe renal cell carcinomas and 13 oncocytomas. In nontumoral kidney, nuclear and cytoplasmic S100A4 staining was detected in the glomerular epithelium and endothelium, distal tubules and collecting ducts, and loops of Henle. A different expression pattern was noted in the various neoplasms. S100A4 expression was significantly increased in the stromal cells in cRCC (83%) and pRCC (73%) compared with paired nontumoral kidney tissue (P<0.001). There was no increased stromal cell expression of S100A4 in oncocytomas and chromophobe carcinomas. Positive epithelial staining was more common in pRCC (58%) than cRCC (11%) (P=0.01). The level of mRNA detected by reverse transcription-polymerase chain reaction was significantly higher in the tumor as opposed to normal tissue in cRCC but not in the other neoplasms (P=0.03). Multivariate analysis revealed that epithelial S100A4 protein expression is an independent poor prognostic factor along with grade and stage only in cRCC (P<0.01). Although S100A4 protein was expressed in a minority of cRCC, its expression was associated with shorter overall patient survival.