Unlocking The Secrets Of Ones Cosmic Destiny With The Help Of AI, ML And Vedic Astro Science

The quest to understand the intricacies of human existence has long been a subject of fascination and inquiry. Among the diverse fields of study, astrology, rooted in ancient wisdom, offers a unique perspective on the cosmic forces that shape individual destinies. With the rapid advancements in Artificial Intelligence (AI) and Machine Learning (ML), there emerges an unprecedented opportunity to bridge the gap between ancient astrological knowledge and modern computational methods. This paper explores the convergence of AI, ML, and Vedic Astro Science based upon Lal Kitab Principles in unlocking the secrets of one's cosmic destiny

Immobilization of fibrinogen antibody on self-assembled gold monolayers for immunosensor applications

Self-assembled gold monolayers offer several advantages for the realization of novel modified electrodes for biosensor applications. This is due to their ability to decrease non-specific adsorption and provide for covalent attachment of biomolecules. Surfaces for these applications require the precise control of ligand density, the ability to immobilize ligands, and in situ-modulation of ligand activity. In this study, we focused our studies on the immobilization of antibody on a gold monolayer surface. We self-assembled thioctic acid onto the gold surface as an anchor point for the immobilization of anti-fibrinogen onto the surface. The modifications to the gold surface were characterized by ELISA, ellipsometry, and AFM

Genetic determinants of telomere length and risk of pancreatic cancer: A PANDoRA study

Telomere deregulation is a hallmark of cancer. Telomere length measured in lymphocytes (LTL) has been shown to be a risk marker for several cancers. For pancreatic ductal adenocarcinoma (PDAC) consensus is lacking whether risk is associated with long or short telomeres. Mendelian randomization approaches have shown that a score built from SNPs associated with LTL could be used as a robust risk marker. We explored this approach in a large scale study within the PANcreatic Disease ReseArch (PANDoRA) consortium. We analyzed 10 SNPs (ZNF676-rs409627, TERT-rs2736100, CTC1-rs3027234, DHX35-rs6028466, PXK-rs6772228, NAF1-rs7675998, ZNF208-rs8105767, OBFC1-rs9420907, ACYP2-rs11125529 and TERC-rs10936599) alone and combined in a LTL genetic score ("teloscore", which explains 2.2% of the telomere variability) in relation to PDAC risk in 2,374 cases and 4,326 controls. We identified several associations with PDAC risk, among which the strongest were with the TERT-rs2736100 SNP (OR = 1.54; 95%CI 1.35-1.76; p = 1.54 × 10-10 ) and a novel one with the NAF1-rs7675998 SNP (OR = 0.80; 95%CI 0.73-0.88; p = 1.87 × 10-6 , ptrend = 3.27 × 10-7 ). The association of short LTL, measured by the teloscore, with PDAC risk reached genome-wide significance (p = 2.98 × 10-9 for highest vs. lowest quintile; p = 1.82 × 10-10 as a continuous variable). In conclusion, we present a novel genome-wide candidate SNP for PDAC risk (TERT-rs2736100), a completely new signal (NAF1-rs7675998) approaching genome-wide significance and we report a strong association between the teloscore and risk of pancreatic cancer, suggesting that telomeres are a potential risk factor for pancreatic cancer