Indian Institute of Technology Guwahati

About: Indian Institute of Technology Guwahati is a education organization based out in Guwahati, Assam, India. It is known for research contribution in the topics: Adsorption & Catalysis. The organization has 6933 authors who have published 17102 publications receiving 257351 citations.

Collagen Promotes Higher Adhesion, Survival and Proliferation of Mesenchymal Stem Cells

Abstract: Mesenchymal stem cells (MSC) can differentiate into several cell types and are desirable candidates for cell therapy and tissue engineering. However, due to poor cell survival, proliferation and differentiation in the patient, the therapy outcomes have not been satisfactory. Although several studies have been done to understand the conditions that promote proliferation, differentiation and migration of MSC in vitro and in vivo, still there is no clear understanding on the effect of non-cellular bio molecules. Of the many factors that influence the cell behavior, the immediate cell microenvironment plays a major role. In this context, we studied the effect of extracellular matrix (ECM) proteins in controlling cell survival, proliferation, migration and directed MSC differentiation. We found that collagen promoted cell proliferation, cell survival under stress and promoted high cell adhesion to the cell culture surface. Increased osteogenic differentiation accompanied by high active RHOA (Ras homology gene family member A) levels was exhibited by MSC cultured on collagen. In conclusion, our study shows that collagen will be a suitable matrix for large scale production of MSC with high survival rate and to obtain high osteogenic differentiation for therapy.

Green synthesis of gold nanoparticles using Nyctanthes arbortristis flower extract

Abstract: The present study explores the reducing and capping potentials of ethanolic flower extract of the plant Nyctanthes arbortristis for the synthesis of gold nanoparticles. The extract at different volume fractions were stirred with HAuCl4 aqueous solution at 80 °C for 30 min. The UV–Vis spectroscopic analysis of the reaction products confirmed successful reduction of Au3+ ions to gold nanoparticles. Transmission electron microscope (TEM) revealed dominant spherical morphology of the gold nanoparticles with an average diameter of 19.8 ± 5.0 nm. X-ray diffraction (XRD) study confirmed crystalline nature of the synthesized particles. Fourier transform infra-red (FTIR) and nuclear magnetic resonance (NMR) analysis of the purified and lyophilized gold nanoparticles confirmed the surface adsorption of biomolecules during preparation and caused long-term (6 months) stability. Low reaction temperature (25 °C) favored anisotropy. The strong reducing power of the flower extract can also be tested in the green synthesis of other metallic nanoparticles.

A review of deep learning with special emphasis on architectures, applications and recent trends

Abstract: Deep learning (DL) has solved a problem that a few years ago was thought to be intractable — the automatic recognition of patterns in spatial and temporal data with an accuracy superior to that of humans. It has solved problems beyond the realm of traditional, hand-crafted machine learning algorithms and captured the imagination of practitioners who are inundated with all types of data. As public awareness of the efficacy of DL increases so does the desire to make use of it. But even for highly trained professionals it can be daunting to approach the rapidly increasing body of knowledge in the field. Where does one start? How does one determine if a particular DL model is applicable to their problem? How does one train and deploy them? With these questions in mind, we present an overview of some of the key DL architectures. We also discuss some new automatic architecture optimization protocols that use multi-agent approaches. Further, since guaranteeing system uptime is critical to many applications, a section dwells on using DL for fault detection and mitigation. This is followed by an exploratory survey of several areas where DL emerged as a game-changer: fraud detection in financial applications, financial time-series forecasting, predictive and prescriptive analytics, medical image processing, power systems research and recommender systems. The thrust of this review is to outline emerging applications of DL and provide a reference to researchers seeking to use DL in their work for pattern recognition with unparalleled learning capacity and the ability to scale with data.

Chronic diseases, inflammation, and spices: how are they linked?

Abstract: Extensive research within the last several decades has revealed that the major risk factors for most chronic diseases are infections, obesity, alcohol, tobacco, radiation, environmental pollutants, and diet. It is now well established that these factors induce chronic diseases through induction of inflammation. However, inflammation could be either acute or chronic. Acute inflammation persists for a short duration and is the host defense against infections and allergens, whereas the chronic inflammation persists for a long time and leads to many chronic diseases including cancer, cardiovascular diseases, neurodegenerative diseases, respiratory diseases, etc. Numerous lines of evidence suggest that the aforementioned risk factors induced cancer through chronic inflammation. First, transcription factors NF-κB and STAT3 that regulate expression of inflammatory gene products, have been found to be constitutively active in most cancers; second, chronic inflammation such as pancreatitis, prostatitis, hepatitis etc. leads to cancers; third, activation of NF-κB and STAT3 leads to cancer cell proliferation, survival, invasion, angiogenesis and metastasis; fourth, activation of NF-κB and STAT3 leads to resistance to chemotherapy and radiation, and hypoxia and acidic conditions activate these transcription factors. Therefore, targeting these pathways may provide opportunities for both prevention and treatment of cancer and other chronic diseases. We will discuss in this review the potential of various dietary agents such as spices and its components in the suppression of inflammatory pathways and their roles in the prevention and therapy of cancer and other chronic diseases. In fact, epidemiological studies do indicate that cancer incidence in countries such as India where spices are consumed daily is much lower (94/100,000) than those where spices are not consumed such as United States (318/100,000), suggesting the potential role of spices in cancer prevention.