An Integrated Approach of the Potential Underlying Molecular Mechanistic Paradigms of SARS-CoV-2-Mediated Coagulopathy

Coronavirus disease 2019 (Covid-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pandemic disease which has affected more than 6.2 million people globally, with numbers mounting considerably daily. However, till date, no specific treatment modalities are available for Covid-19 and also not much information is known about this disease. Recent studies have revealed that SARS-CoV-2 infection is associated with the generation of thrombosis and coagulopathy. Fundamentally, it has been believed that a diverse array of signalling pathways might be responsible for the activation of coagulation cascade during SARS-CoV-2 infection. Henceforth, a detailed understanding of these probable underlying molecular mechanistic pathways causing thrombosis in Covid-19 disease deserves an urgent exploration. Therefore, in this review, the hypothetical crosstalk between distinct signalling pathways including apoptosis, inflammation, hypoxia and angiogenesis attributable for the commencement of thrombotic events during SARS-CoV-2 infection has been addressed which might further unravel promising therapeutic targets in Covid-19 disease.     

Expression of Telomere Binding Proteins (RAP1 and POT1) in Renal Cell Carcinoma and Their Correlation with Clinicopathological Parameters

Telomere stability is indispensable for continuous proliferation of cells. Telomere structure is maintained by group of six proteins termed as shelterin. RAP1 and POT1 proteins are significant members of shelterin complex. Expression of RAP1 and POT1 are crucial for telomere maintenance and hence uncontrolled division of cells. Notably, expression of RAP1 and POT1 is unknown in renal cell carcinoma (RCC). In view of these facts, the present study was initiated to investigate the expression of RAP1 and POT1 in RCC and their relationships with clinicopathological features. In total 65 histopathologically confirmed RCC cases and their adjacent normal renal parenchyma were analyzed for gene expression. The mRNA expression of telomere binding proteins RAP1 and POT1 were measured using RT-PCR. Expression of RAP1 was observed to be significantly increased in tumour tissues as compared to corresponding normal renal tissues (P = 0.004). The gene expression of RAP1 was documented to be related to grades of RCC (P = 0.002) and subtypes of RCC (P = 0.01). Although, POT1 expression was up-regulated in RCC tissue, however it was not statistically significant. Also, POT1 expression was not related to grades, stages and subtypes of RCC. This is the first study which shows correlation RAP1 with grades and subtypes of RCC.     

The logarithmic mean

The inequality between the arithmetic mean (AM) and geometric mean (GM) of two positive numbers is well known. This article introduces the logarithmic mean, shows how it leads to refinements of the AM-GM inequality. Some applications and properties of this mean are shown. Some other means and related inequalities are discussed. Rajendra Bhatia is a Professor at the Indian Statistical Institute, New Delhi. Some of his recent work is on means of matrices. But he is not a mean theorist.     

Integrating Internet, telephones, and call centers for delivering better quality e-governance to all citizens

This article examines the present approach of providing e-government services through the Internet. Since the Internet is not accessible to most of the populations of the world, the article advocates adopting a multi-platform approach in which mobile and fixed line phones can be used to enhance the Internet in the delivery of e-government services. The article also suggests the concept of Government Call Centers to overcome the limitations posed by the digital divide. The study concludes that integration of the Internet, phones, and call centers can enable governments to deliver e-government to every citizen of a nation. Finally, the article makes specific recommendations to spread e-government services to more citizens through the approach suggested in this paper.     

Vibrations and eigenvalues

The vibrating string problem is the source of much mathematics and physics. This article describes Lagrange’s formulation of a discretised version of the problem and its solution. This is also the first instance of an eigenvalue problem.     

Towards precision medicine: from quantitative imaging to radiomics

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.