Association of Predisposing Factors of Diabetes with six Stages of Disease Progression in Ayurveda (Shatkriyakala): A Cross-Sectional Pilot Study

Introduction: Diabetes has emerged as a global health crisis. It not only causes morbidity and mortality figures but deteriorates quality of life, national productivity and economic burden too. Besides this, no major advancement has been made for early diagnosis and prevention of diabetes. Clinical Staging of morbidity has been depicted in classical texts of Ayurveda modelled on pathogenesis.) This type of classification can serve as the basis of levelled and precise preventive interventions.  Thus, identification of cases pertaining to each stage of pathogenesis based on validated parameters is a prerequisite. This research is a preliminary work on validation of clinical staging. This Ayurveda system of staging method can serve as a holistic model of prevention as it includes variable responsible host factors, etiology, risk factor stratification and grading of pathological state. Aim: The present study aimed to explore the six stage pathogonomic model SKK (Shat kriyakala and its relevance in tracking pathogenesis at preclinical stages. Materials and methods: A cross-sectional trial was conducted in forty- two subjects. Study participants were subjected to a questionnaire (Q2) to assess clinical features in latent and clinical stages of Prameha (~ Diabetes Mellitus) and biomarkers (CRP and Serum cortisol).Result: The mean score of SKK questionnaire was found maximum with the corresponding stages designed on the basis of predisposing factors and laboratory parameters.Conclusion: It can be inferred from the study that SKK may act as a tool to check pathogenesis at an early stage. The model may act as a potential paradigm for preventing diabetes risk as well as preventive care from a public health perspective

Electrohydrodynamics Analysis of Dielectric 2D Nanofluids

The purpose of this present study is to prepare a stable mineral-oil (MO)-based nanofluid (NF) for usage as a coolant in a transformer. Nanoparticles (NPs) such as hexagonal boron nitride (h-BN) and titanium oxide (TiO2) have superior thermal and electrical characteristics. Their dispersion into MO is likely to elevate the electrothermal properties of NFs. Therefore, different batches of NFs are prepared by uniformly dispersing the insulating h-BN and semiconducting TiO2 NP of different concentrations in MO. Bulk h-BN NP of size 1μm is exfoliated into 2D nanosheets of size 150–200 nm, subsequently enhancing the surface area of exfoliated h-BN (Eh-BN). However, from the zeta-potential analysis, NP concentration of 0.01 and 0.1 wt.% are chosen for further study. The thermal conductivity and ACBDV studies of the prepared NF are performed to investigate the cooling and insulation characteristics. The charging-dynamics study verifies the enhancement in ACBDV of the Eh-BN NF. Weibull statistical analysis is carried out to obtain the maximum probability of ACBDV failure, and it is observed that 0.01 wt.% based NF has superior cooling and insulation properties than MO and remaining batches of NFs