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In a significant academic achievement, the Department of Mathematics is proud to announce that Dr Koyel Chakravarty, an Assistant Professor, along with her diligent PhD Scholar, Ms Amrutha Sreekumar, has made a remarkable contribution to the field of biological mathematics. Their paper, titled “Exploring the Impact of PTH Therapy on Bone Remodeling: A Mathematical Investigation,” has been officially accepted for publication in the prestigious Journal of Biological Systems by World Scientific.

This paper presents a comprehensive mathematical model that investigates the effects of Parathyroid Hormone (PTH) therapy on bone remodelling processes. The research provides valuable insights that could potentially lead to more effective treatments for bone-related diseases and conditions.

The university community extends its heartfelt congratulations to Dr Chakravarty and Ms Sreekumar for their dedication and hard work.

Abstract

The regulatory role of parathyroid hormone (PTH) on bone, a crucial calcium reservoir, is influenced by sex steroids, notably estrogen. A mathematical model elucidates PTH-mediated bone remodeling mechanisms, examining plasma PTH effects and external dosages. Daily PTH injections, with their dual anabolic or catabolic action, offer a notable treatment for severe osteoporosis. This study predicts osteogenic responses to PTH, integrating factors like TGF-β, RANKL, and bisphosphonates in osteoblast-osteoclast signaling, alongside PTH’s effects on glands and regulatory molecules like Runx2, pCREB, and Bcl2. Using various methods, including simulations and sensitivity analysis, it aims to understand PTH therapy’s impact on bone volume, enhancing its clinical relevance.

Explanation of the Research in Layperson’s Terms

The role of parathyroid hormone (PTH) in calcium storage within bones is significant, with its regulation influenced by other hormones, notably estrogen. A mathematical model has been developed to comprehend the effects of PTH on bones, examining both endogenous levels in the blood and exogenous intake requirements. It has been observed that daily PTH injections can be beneficial in treating severe bone conditions like osteoporosis, as these injections can induce either bone formation or resorption, depending on their administration method. Additionally, the response of bones to PTH is under scrutiny in this study, considering various substances such as TGF-β, RANKL, and bisphosphonates, and their interplay in maintaining bone health. Through the utilization of different methodologies including computer simulations, efforts are being made to precisely understand how PTH injections influence bone health, thereby enhancing their efficacy in addressing bone-related ailments.

Title of the Research paper in the Citation Format

Exploring the Impact of PTH Therapy on Bone Remodeling: A Mathematical Investigation

Practical Implementation or the Social Implications Associated
Personalized Treatment Plans:
Mathematical modeling of bone remodeling can facilitate the development of personalized treatment plans for individuals with bone disorders such as osteoporosis. By considering factors like hormone levels, genetic predispositions, and lifestyle factors, healthcare providers can tailor treatment strategies to optimize bone health outcomes.
1. Drug Development:
Insights gained from mathematical models can aid in the development of new drugs for bone disorders. By simulating the effects of potential therapeutic agents on bone remodeling processes, researchers can identify promising candidates for further investigation, potentially accelerating the drug discovery process.
2. Improved Clinical Decision Making:
Healthcare professionals can use mathematical models to make more informed clinical decisions regarding the management of bone disorders. By integrating patient-specific data into predictive models, clinicians can better predict treatment outcomes and adjust therapeutic interventions accordingly.
3. Enhanced Surgical Planning:
Mathematical modeling can also be valuable in surgical planning for procedures such as bone grafting or joint replacement. By simulating the effects of surgical interventions on bone remodeling, surgeons can optimize surgical techniques to promote more effective healing and long-term outcomes for patients.
4. Public Health Interventions:
Understanding the factors influencing bone remodeling at a population level can inform public health interventions aimed at reducing the burden of bone disorders. By identifying modifiable risk factors and developing targeted prevention strategies, policymakers can promote bone health and reduce the incidence of conditions like osteoporosis on a larger scale.
5. Educational Tools:
Mathematical models of bone remodeling can serve as educational tools for healthcare professionals, students, and patients. By visualizing complex biological processes in a simplified manner, these models can enhance understanding of bone physiology and the mechanisms underlying bone disorders, ultimately improving patient care and outcomes.

Collaborators:
• Prof. D.C. Dalal, Professor, Department of Mathematics, IIT Guwahati
• Dr. L.N. Guin, Associate Professor, Department of Mathematics, Visva-Bharati

Future research plans.
a) Incorporating Multi-Scale Modeling: Future research could focus on integrating multi-scale modeling approaches to capture the intricate interactions occurring at different levels of bone structure, from the molecular to the tissue level. By incorporating information on cellular processes, tissue mechanics, and systemic factors, these models could provide a more comprehensive understanding of bone remodeling dynamics.
b) Accounting for Heterogeneity: There is a need to develop mathematical models that account for the heterogeneity observed in bone remodeling processes across individuals and within different anatomical sites. By considering factors such as age, sex, genetics, and bone quality, researchers can create more personalized and accurate models to predict individual responses to treatment and disease progression.
c) Integration of Advanced Imaging Techniques: Advances in imaging technologies such as micro-computed tomography (micro-CT) and magnetic resonance imaging (MRI) provide detailed insights into bone structure and function. Future research could focus on integrating data from these advanced imaging techniques into mathematical models to enhance their predictive capabilities and enable non-invasive monitoring of bone remodeling in clinical settings.
d) Exploring Therapeutic Interventions: Researchers could use mathematical modeling to explore the efficacy of novel therapeutic interventions for bone disorders, such as drug treatments, exercise regimens, and dietary interventions. By simulating the effects of these interventions on bone remodeling processes, researchers can identify optimal treatment strategies and accelerate the development of new therapies.

Link to the article

DOI: https://doi.org/10.1142/S021833902450027X

The Department of Civil Engineering is thrilled to host Er. Lakhwant Singh Khalsa for its 3rd Industry Guest Lecture Series. Mr Khalsa, Project Manager at Systra India, Haryana, will deliberate on “Railway Bridges and Track Structure – Practitioner Perspectives”. His lecture will offer deep insights into Railway Track Structure and Components and Railway Bridge Elements and Bridge Types. We Invite all civil engineering students and enthusiasts to join the insightful session on April 23, 2024.

About the Speaker:

Er. Lakhwant Singh Khalsa currently working as a project manager, Systra/PMC for RVNL Vijayawada 3rd line rail project. He has 41 years of rich & extensive experience in railway steel bridge structures, civil bridge works and project management. He is a Life Member of the Institution of Permanent Way Engineers (India)-IPWE and the Indian Institution of Bridge Engineers-IIBE. He holds several prestigious certifications, such as welding inspector from the welding research institute BHEL Trichy and Level II Certification in Non-Destructing Testing for DPT, MPT & UT as per SNT TC IA2006. He is familiar with IS, IRS, EN, and BS Codes, which are relevant to steel and concrete works. Also, he has experience working in hilly terrains in the Himalayan Ranges with critical environmental conditions.

Prof. Siva Sankar Yelampalli and Dr Ramesh Vaddi, Associate Professor, from the Department of Electronics and Communication Engineering, along with research scholars Mr Birudu Venu, Mr Tirumala Rao Kadiyam, and Mr Koteswara Rao Penumalli, have jointly published a paper titled “Computing in-memory reconfigurable (accurate/approximate) adder design with negative capacitance FET 6T-SRAM for energy efficient AI edge devices” The paper introduces Computing in-memory (CiM) as a promising alternative to traditional von-Neumann architectures, focusing on its potential for energy-efficient AI edge computing with CMOS scaling. Additionally, they have explored the advancements in approximate computing in-memory (ACiM) techniques, aiming to further enhance the energy efficiency of these innovative architectures.

Abstract:

Computing in-memory (CiM) is an alternative to von Neumann architectures for energy-efficient AI edge computing architectures with CMOS scaling. Approximate computing in-memory (ACiM) techniques have also been recently proposed to further increase the energy efficiency of such architectures. In the first part of the work, a negative capacitance FET (NCFET) based 6T-SRAM CiM accurate full adder has been proposed, designed and performance benchmarked with equivalent baseline 40 nm CMOS design. Due to the steep slope characteristics of NCFET, at an increased ferroelectric layer thickness, Tfe of 3 nm, the energy consumption of the proposed accurate NCFET-based CiM design is ∼82.48% lower in comparison to the conventional/Non CiM full adder design and ∼85.27% lower energy consumption in comparison to the equivalent baseline CMOS CiM accurate full adder design at VDD = 0.5 V. This work further proposes a reconfigurable computing in-memory NCFET 6T-SRAM full adder design (the design which can operate both in accurate and approximate modes of operation). NCFET 6T-SRAM reconfigurable full adder design in accurate mode has ∼4.19x lower energy consumption and ∼4.47x lower energy consumption in approximation mode when compared to the baseline 40 nm CMOS design at VDD = 0.5 V, making NCFET-based approximate CiM adder designs preferable for energy efficient AI edge CiM based computing architectures for DNN processing.

Future research plans: Implementing reconfigurable computing in-memory (CiM) MAC for energy-efficient AI edge devices.

Link to the article

The Department of Economics is thrilled to announce the publication of Assistant Professor Dr Ghanshyam Kumar Pandey’s research paper titled, “Bifurcation and Agricultural Development in Jharkhand,” in Economic and Political Weekly. The paper delves into the developmental trajectory of Jharkhand following its bifurcation from Bihar in 2000 and examines the intricacies of agricultural development and the key determinants that have shaped its evolution post-separation.

Abstract:

The cropping pattern in Jharkhand has significantly changed from 2000 to 2016, with shifts from the cultivation of cereals to non-cereals. An increase in the crop area and diversification towards high-value crops have accelerated overall agricultural growth. Capital formation and better infrastructure facilities, along with improved fertiliser consumption and irrigation, will foster agricultural development in Jharkhand

Practical implementation:

This study shows the development path of Jharkhand after bifurcation from Bihar in 2000. The study deals with the process of agricultural development and determinants of agricultural development after its bifurcation.

Link to the article