Solution of Large Sparse System of Linear Equations over GF(2) on a Multi Node Multi GPU Platform

We provide an efficient multi-node, multi-GPU implementation of the Block Wiedemann Algorithm (BWA)to find the solution of a large sparse system of linear equations over GF(2). One of the important applications ofsolving such systems arises in most integer factorization algorithms like Number Field Sieve. In this paper, wedescribe how hybrid parallelization can be adapted to speed up the most time-consuming sequence generation stage of BWA. This stage involves generating a sequence of matrix-matrix products and matrix transpose-matrix products where the matrices are very large, highly sparse, and have entries over GF(2). We describe a GPU-accelerated parallel method for the computation of these matrix-matrix products using techniques like row-wise parallel distribution of the first matrix over multi-node multi-GPU platform using MPI and CUDA and word-wise XORing of rows of the second matrix. We also describe the hybrid parallelization of matrix transpose-matrix product computation, where we divide both the matrices row-wise into equal-sized blocks using MPI. Then after a GPU-accelerated matrix transpose-matrix product generation, we combine all those blocks using MPI_BXOR operation in MPI_Reduce to obtain the result. The performance of hybrid parallelization of the sequence generation step on a hybrid cluster using multiple GPUs has been compared with parallelization on only multiple MPI processors. We have used this hybrid parallel sequence generation tool for the benchmarking of an HPC cluster. Detailed timings of the complete solution of number field sieve matrices of RSA-130, RSA-140, and RSA-170 are also compared in this paper using up to 4 NVidia V100 GPUs of a DGX station. We got a speedup of 2.8 after parallelization on 4 V100 GPUs compared to that over 1 GPU

Down-regulation of miR-15a/b accelerates fibrotic remodelling in the Type 2 diabetic human and mouse heart

Correspondence: Rajesh Katare ([email protected]) Aim: Myocardial fibrosis is a well-established cause of increased myocardial stiffness and subsequent diastolic dysfunction in the diabetic heart. The molecular regulators that drive the process of fibrotic events in the diabetic heart are still unknown. We determined the role of the microRNA (miR)-15 family in fibrotic remodelling of the diabetic heart. Methods and results: Right atrial appendage (RAA) and left ventricular (LV) biopsy tissues collected from diabetic and non-diabetic (ND) patients undergoing coronary artery bypass graft surgery showed significant down-regulation of miR-15a and -15b. This was associated with marked up-regulation of pro-fibrotic transforming growth factor-β receptor-1 (TGFβR1) and connective tissue growth factor (CTGF), direct targets for miR-15a/b and pro-senescence p53 protein. Interestingly, down-regulation of miR-15a/b preceded the development of diastolic dysfunction and fibrosis in Type 2 diabetic mouse heart. Therapeutic restoration of miR-15a and -15b in HL-1 cardiomyocytes reduced the activation of pro-fibrotic TGFβR1 and CTGF, and the pro-senescence p53 protein expression, confirming a causal regulation of these fibrotic and senescence mediators by miR-15a/b. Moreover, conditioned medium (CM) collected from cardiomyocytes treated with miR-15a/b markedly diminished the differentiation of diabetic human cardiac fibroblasts. Conclusion: Our results provide first evidence that early down-regulation of miR-15a/b activates fibrotic signalling in diabetic heart, and hence could be a potential target for the treatment/prevention of diabetes-induced fibrotic remodelling of the heart

Cardiovascular microRNAs: early modulators in the pathogenesis of diabetic heart disease

Diabetic heart disease (DHD) is often unrecognized in the subclinical stage due to absence of pathognomonic signs, thereby restricting timely diagnosis and management of disease. Identifying early modulators of disease will not only help in early detection of disease, but also allow sufficient time for optimization of treatment. Recently, microRNAs (miRs) are gaining popularity as diagnostics and key regulators in the pathophysiology of several diseases including cardiovascular diseases. However, the diagnostic potential and pathophysiological role of miRs in DHD is still unrecognized. In the initial phase of my PhD, I carried out three pilot studies: 1) performing miR microarray using Taqman miR array cards using human diabetic myocardium; 2) identifying the onset alteration in pro-survival and 3) apoptosis pathways in human and type-2 diabetic mice. The outcomes of these pilot studies were that there was dysregulated expression of cardiovascular miRs (miR-1, miR-133a, miR-208a, miR-499, miR-126 and miR-132) in human diabetic heart compared to non-diabetic heart, suggesting these miRs as key players in pathogenesis of DHD. In addition to above mentioned miRs, I also included miR-15a and miR-15b into my study based on their cardio-enrichment and a recently published report showing their involvement in cardiac fibrosis. To further answer whether dysregulation of cardiovascular miRs has a correlation with aetiology of DHD, I carried out an animal study using db/db mice. Remarkably, all investigated miRs and their target proteins were dysregulated in diabetic myocardium, from the early stages of diabetes (8-12 weeks of age) vs age-matched non-diabetic control (p<0.05). Importantly, echocardiography and immunohistochemical analyses did not reveal any noticeable changes in diabetic mice until 20-weeks of age (p<0.001). These findings confirmed my hypothesis that miRs are early modulators of DHD and can be explored as therapeutic interventions for prompt management of DHD. In line with these results, I elicited in vitro modulation of some of my cardiovascular miRs (miR-1, miR-208a, miR-15a, miR-15b, miR-126, and miR-132) to explore their therapeutic potential in diabetic state. Using curative approach, I demonstrated that modulation of miRs in HL-1 cardiomyocytes (miR-1, miR-208a, miR-15a and miR-15b) and human umbilical vein endothelial cells (miR-126, and miR-132) abrogated the deleterious effects of high-glucose-induced impairment in cardiac/endothelial cell phenotype. Further, in order investigate their role as early modulators of DHD; it was essential to study the expression of cardiovascular miR at an early stage of diabetes. To address this, I recruited diabetic individuals from Dunedin and Christchurch Hospitals without any known history of cardiovascular disease. Quantitative real time PCR analyses revealed marked dysregulation of some of the circulating cardiovascular miRs (miR-1, miR-133a, miR-499, miR-126 and miR-132) in diabetic plasma samples at different duration of diabetes. I demonstrated a significant upregulation of miR-1, miR-126, miR-132 and miR-133 from early stage of diabetes (all p<0.05) while a significant downregulation of miR-499 in early (p<0.001) and later stage of diabetes (p<0.05). These findings were the first clinical evidence that miRs are modulated in DHD and lay a foundation for larger studies to establish miRs as valuable diagnostic biomarkers for detection of cardiovascular risk in diabetics Overall, my PhD work to date has provided first evidence that cardiovascular miRs can be used as potential diagnostic tools for early detection of DHD in at-risk diabetic individuals, and therefore, will provide sufficient time for clinicians to optimize and initiate the treatment. The findings of this study may ultimately encourage the clinical focus towards developing miR-based therapies for management of DHD. This, in the long-term will eventually improve the quality of life in people with diabetes

Cardiovascular microRNAs: early modulators in the pathogenesis of diabetic heart disease

Diabetic heart disease (DHD) is often unrecognized in the subclinical stage due to absence of pathognomonic signs, thereby restricting timely diagnosis and management of disease. Identifying early modulators of disease will not only help in early detection of disease, but also allow sufficient time for optimization of treatment. Recently, microRNAs (miRs) are gaining popularity as diagnostics and key regulators in the pathophysiology of several diseases including cardiovascular diseases. However, the diagnostic potential and pathophysiological role of miRs in DHD is still unrecognized. In the initial phase of my PhD, I carried out three pilot studies: 1) performing miR microarray using Taqman miR array cards using human diabetic myocardium; 2) identifying the onset alteration in pro-survival and 3) apoptosis pathways in human and type-2 diabetic mice. The outcomes of these pilot studies were that there was dysregulated expression of cardiovascular miRs (miR-1, miR-133a, miR-208a, miR-499, miR-126 and miR-132) in human diabetic heart compared to non-diabetic heart, suggesting these miRs as key players in pathogenesis of DHD. In addition to above mentioned miRs, I also included miR-15a and miR-15b into my study based on their cardio-enrichment and a recently published report showing their involvement in cardiac fibrosis. To further answer whether dysregulation of cardiovascular miRs has a correlation with aetiology of DHD, I carried out an animal study using db/db mice. Remarkably, all investigated miRs and their target proteins were dysregulated in diabetic myocardium, from the early stages of diabetes (8-12 weeks of age) vs age-matched non-diabetic control (p<0.05). Importantly, echocardiography and immunohistochemical analyses did not reveal any noticeable changes in diabetic mice until 20-weeks of age (p<0.001). These findings confirmed my hypothesis that miRs are early modulators of DHD and can be explored as therapeutic interventions for prompt management of DHD. In line with these results, I elicited in vitro modulation of some of my cardiovascular miRs (miR-1, miR-208a, miR-15a, miR-15b, miR-126, and miR-132) to explore their therapeutic potential in diabetic state. Using curative approach, I demonstrated that modulation of miRs in HL-1 cardiomyocytes (miR-1, miR-208a, miR-15a and miR-15b) and human umbilical vein endothelial cells (miR-126, and miR-132) abrogated the deleterious effects of high-glucose-induced impairment in cardiac/endothelial cell phenotype. Further, in order investigate their role as early modulators of DHD; it was essential to study the expression of cardiovascular miR at an early stage of diabetes. To address this, I recruited diabetic individuals from Dunedin and Christchurch Hospitals without any known history of cardiovascular disease. Quantitative real time PCR analyses revealed marked dysregulation of some of the circulating cardiovascular miRs (miR-1, miR-133a, miR-499, miR-126 and miR-132) in diabetic plasma samples at different duration of diabetes. I demonstrated a significant upregulation of miR-1, miR-126, miR-132 and miR-133 from early stage of diabetes (all p<0.05) while a significant downregulation of miR-499 in early (p<0.001) and later stage of diabetes (p<0.05). These findings were the first clinical evidence that miRs are modulated in DHD and lay a foundation for larger studies to establish miRs as valuable diagnostic biomarkers for detection of cardiovascular risk in diabetics Overall, my PhD work to date has provided first evidence that cardiovascular miRs can be used as potential diagnostic tools for early detection of DHD in at-risk diabetic individuals, and therefore, will provide sufficient time for clinicians to optimize and initiate the treatment. The findings of this study may ultimately encourage the clinical focus towards developing miR-based therapies for management of DHD. This, in the long-term will eventually improve the quality of life in people with diabetes

Bio-Nanocarriers for Lung Cancer Management: Befriending the Barriers

Abstract Lung cancer is a complex thoracic malignancy developing consequential to aberrations in a myriad of molecular and biomolecular signaling pathways. It is one of the most lethal forms of cancers accounting to almost 1.8 million new annual incidences, bearing overall mortality to incidence ratio of 0.87. The dismal prognostic scenario at advanced stages of the disease and metastatic/resistant tumor cell populations stresses the requisite of advanced translational interdisciplinary interventions such as bionanotechnology. This review article deliberates insights and apprehensions on the recent prologue of nanobioengineering and bionanotechnology as an approach for the clinical management of lung cancer. The role of nanobioengineered (bio-nano) tools like bio-nanocarriers and nanobiodevices in secondary prophylaxis, diagnosis, therapeutics, and theranostics for lung cancer management has been discussed. Bioengineered, bioinspired, and biomimetic bio-nanotools of considerate translational value have been reviewed. Perspectives on existent oncostrategies, their critical comparison with bio-nanocarriers, and issues hampering their clinical bench side to bed transformation have also been summarized

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Not Available102 Indian soybean varieties were surveyed using 10 SSR markers that were selected based upon high polymorphic information content (PIC) observed in the initial screening of 40 randomly selected genotypes using 58 SSR markers. The 10 selected primer pairs amplified 3-8 alleles in the 102 varieties. In total, 50 alleles with amplicon size ranging from 100 to 330 bp were observed with PIC value ranging from 0.4760 (primer pair Satt229) to 0.8123 (Sct_199). Once the amplicon profile of all the varieties was obtained, alleles were assigned a numerical number in the order of increasing size of amplicon. The numerical numbers were placed from left to right in alphabetical order of linkage group of the 10 SSR markers to construct a 10-digit barcode, which would serve as unique identification code for each of 102 soybean varieties released for commercial cultivation in India and would be useful in testing their genetic purity.Not Availabl

AI based strategies for Covid-19 drug repurposing.

Background: The novel coronavirus disease, COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused catastrophic effects resulting in over 5.6 million deaths worldwide as of February 2022 and approximately 3.6 million new cases have resulted. The traditional drug discovery methodology is a risky, lengthy and expensive process, and due to the urgency to discover new therapies and treatments, the drug repositioning strategy has been driven by its potential to identify compounds that could be used to treat the symptoms. Viral infection attracts attention. Method: It was discovered that the convolutional neural network (CNN) and its modified models were mainly used for COVID-19 pandemic prediction, whereas in the case of machine learning (ML), the support vector machine (SVM), and random forest (RF) was largely utilized for COVID-19 pandemic combat. Result: In the case of COVID-19, modern technologies such as AI and ML have been used effectively to identify remdesivir alongside other drugs to treat COVID-19. It has shown promise in treating COVID-19, prompting the FDA to issue emergency use authorization, although it is only limited to severe conditions. The FDA made this decision based on early research showing the drug could help speed recovery in hospitalized patients with COVID-19