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.     

A novel approach for part family formation using K-means algorithm

The reconfigurable manufacturing system （RMS） is the next step in manufacturing, allowing the production of any quantity of highly customized and complex parts together with the benefits of mass production. In RMSs, parts are grouped into families, each of which requires a specific system configuration. Initially system is configured to produce the first family of parts. Once it is finished, the system will be reconfigured in order to produce the second family, and so forth. The effectiveness of a RMS depends on the formation of the optimum set of part families addressing various recon figurability issues. The aim of this work is to establish a methodology for grouping parts into families for effective working of RMS. The methodology carried out in two phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, agglomerative hier archical Kmeans algorithm is used for the parts family for mation resulting in an optimum set of part families for reconfigurable manufacturing system.     

Engagement and learning through social software in finance: a retrospective on the Trading Room experience

The introduction of a social software blog space called the Trading Room in an undergraduate finance unit generated a great deal of activity to support student learning. A subsequent evaluation of this innovation, viewed through the lens of Activity Theory, demonstrated that students perceived high value in the opportunity it provided for them to reaffirm theories, obtain individualised feedback and benchmark their work against others. While assessment is generally seen as the carrot and the stick of learning; students in the study reported that they would still participate in reading and posting to the Trading Room even if there was no assessment requirement. Students did not see any value in the environment as a purely social space, reporting that they saw it primarily as a professional educational community. It would appear that just as there are different communities in the real world social space, there are also different types of communities in the online space.     

Negotiating meanings of gender justice: Critical reflections on dialogs and debates in a non-governmental organization (NGO)

In this paper, we reflect upon how dialogs and debates in a non-governmental organization (NGO) – CARE India in the context of a girls’ education project shaped staff members’ understandings of gender justice. As CARE India staff shared their experiences in the field, in the organization, and in domestic spaces during gender training sessions and other forums, their different politics in these spaces shaped how they translated global discourses of gender justice to produce fluid, contested, and contextual understandings. While these dialogs included the voices of diverse social actors in identifying the capabilities needed for gender justice in education, they were often reframed by local NGO actors.     

Indian Council of Social Science Research (ICSSR) Maintained Research Institutes’ Libraries in India: Towards Digitization and Networking

The Indian Council of Social Science Research (ICSSR) was established for development of social science research in India. It provides grants to 27 research institutes and six regional centers in India. These institutes have established close links with scholars in the region through activities such as seminars, workshops, training, and consultancy programs. Some of the institutes are closely associated with national and state level planning development agencies and have thereby strengthened the links between research and policy-making. The present study includes 22 institute libraries and three regional libraries in different Indian states. The study analyses their annual acquisition of books; periodicals; CD-ROMs; annual budgets; computerization; hardware and software; Internet; library network; and interlibrary loan and photocopy facilities available in these libraries. Digitization provides a solution to traditional library problems such as conservation, preservation, multimedia documents, and remote access to information, collection, and storage space. ICSSR institute libraries are replacing conventional storage and network systems with digital systems. The progress is a bit slow. Only a few ICSSR institute libraries are subscribing to electronic journals and having electronic documents. ICSSR institute libraries have started computerized operations and are making vigorous attempts to have digitized collections. However, these libraries are required to understand literature growth and use patterns in the social sciences.     

A survey towards an integration of big data analytics to big insights for value-creation

Big Data Analytics (BDA) is increasingly becoming a trending practice that generates an enormous amount of data and provides a new opportunity that is helpful in relevant decision-making. The developments in Big Data Analytics provide a new paradigm and solutions for big data sources, storage, and advanced analytics. The BDA provide a nuanced view of big data development, and insights on how it can truly create value for firm and customer. This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies. It provides an overview of the architecture of BDA including six components, namely: (i) data generation, (ii) data acquisition, (iii) data storage, (iv) advanced data analytics, (v) data visualization, and (vi) decision-making for value-creation. In this paper, seven V's characteristics of BDA namely Volume, Velocity, Variety, Valence, Veracity, Variability, and Value are explored. The various big data analytics tools, techniques and technologies have been described. Furthermore, it presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city. This paper also highlights the previous research, challenges, current status, and future directions of big data analytics for various application platforms. This overview highlights three issues, namely (i) concepts, characteristics and processing paradigms of Big Data Analytics; (ii) the state-of-the-art framework for decision-making in BDA for companies to insight value-creation; and (iii) the current challenges of Big Data Analytics as well as possible future directions.     

Study of Oxidative Stress in Vitiligo

Vitiligo is an idiopathic, acquired, circumscribed, hypomelanotic skin disorder, characterized by milky white patches of different sizes and shapes. It is due to the destruction of melanocytes resulting in the absence of pigment production of the skin and mucosal surfaces. Oxidative stress has been implicated in pathophysiology of vitiligo. To study the activity of blood Superoxide dismutase (SOD) and Glutathione peroxidase (GPx) in vitiligo patients. A case–control study was conducted in which 100 patients were enrolled after written consent. 50 cases were of active vitiligo and 50 served as control (25 healthy control and 25 with stable vitiligo). SOD—In our study, among the active vitiligo cases 90% had high level of SOD and 10% had normal level of SOD. Among the stable vitiligo controls, 92% had normal level of SOD and 8% had low levels of SOD.The difference between active vitiligo cases and stable vitiligo control as well as with healthy control was statistically significant (P value < 0.05). GPx—Among the active vitiligo cases 74% had normal GPx levels, 22% had low and only 4% had high levels of GPx. Among the stable vitiligo controls, 64% had normal GPx levels, 16% had low, and 20% had high levels of GPx. The difference between active vitiligo cases and stable vitiligo control as well as with healthy control was statistically not significant (P value > 0.05). Our study shows that oxidative stress is involved in the pathophysiology of vitiligo, as indicated by the high levels of serum superoxide dismutase activity.     

Correlation of Adiponectin and Leptin with Insulin Resistance: A Pilot Study in Healthy North Indian Population

The increasing incidence of obesity, leading to metabolic complications is now recognized as a major public-health problem. Insulin resistance is a central abnormality of the metabolic syndrome, or syndrome X, originally hypothesized by Reaven Insulin resistance is more strongly linked to intra abdominal fat than to fat in other depots. Adipose tissue secretes numerous factors (adipokines) known to markedly influence lipid and glucose/insulin metabolism, oxidative stress, and cardiovascular integrity. Some of these adipokines have been shown to directly or indirectly affect insulin sensitivity through modulation of insulin signaling and the molecules involved in glucose and lipid metabolism. A pilot study was conducted with 80 healthy subjects who were non diabetic, non hypertensive and having no family history of hypertension, the aim was to evaluate the correlation of adiponectin and leptin levels with obesity and insulin resistance markers in healthy north Indian adult population. Serum leptin, adiponectin and insulin was estimated by sandwich ELISA method. In our study, Leptin correlated significantly with BMI (P value of 0.0000), WC (P value = 0.007), and HC (P value = 0.000). leptin showed significant positive correlation with fasting insulin (P value 0.002), post prandial insulin (P value = 0.000) and HOMA-IR (P value = 0.002). Adiponectin showed significant positive correlation with triglycerides (P value = 0.038), strong negative correlation with HDL-cholesterol (P value = 0.017). Serum concentrations of leptin are associated with central body fat distribution. Insulin resistance and adiponectin is associated with dyslipidemia and these all disorders may ultimately lead to metabolic syndrome.     

Interpreting HbA1c in Presence of Deficiency Anemias

HbA1c is used extensively for the diagnosis and management of diabetes mellitus. It constitutes 80% of glycated HbA1(Glycated haemoglobin(GHb)A), and depends upon blood glucose and RBC life span. RBC life span varies with anemia, leading to a consequent alteration in the HbA1c value irrespective of the circulating blood glucose concentration. But to the best of our knowledge no Hb cut offs have been derived for appropriate interpretation of HbA1c. The prevalence of anemia in Indian population is nearly 40% as per its definition by WHO—Hb < 12 g/dL in females and < 13 g/dL in males—with most cases attributable to nutritional deficiencies. Hence, we aimed to identify Hb cut-off for accurate interpretation of HbA_1c in presence of deficiency anemias. Partial correlation between random blood glucose (RBG) and HbA_1c was studied in 1312 subjects, 470 of whom had deficiency-related anemia]. The data was adjusted for age, sex and Hb. Partial correlation between RBG and HbA1c was highly significant (p < 0.0001) till Hb of 8.1 gm/dL. Significance reduced to p = 0.003 and p = 0.006 as the cut off of Hb reduced to 7.1 gm/dL and 5.0 gm/dL, respectively, but was not lost. Hence, caution in interpretation of HbA_1c is not required till an Hb of 5 g/dL.