Biology, Engineering, Medicine and Science Reports

Optimization of Cancer Treatment: A Control Theory Approach

Utpal Mishra — 2026-01-23

In medical diagnostics and treatment, precise administration and monitoring are essential, especially in cancer therapy, where personalized drug dosage becomes critical due to varying patient responses. Human demographics exhibit diverse reactions to drug administration, necessitating individualized treatment regimens for cancer patients. The effects of drugs on cancer cells vary based on dosage, highlighting the need for a mathematical framework to model drug intake, absorption in the gastrointestinal tract, and eventual circulation in the bloodstream. For physicians, initial drug dosing and administration schedules-typically spanning a week-are observed before adjustment. This study mirrors this practical approach by proposing an optimal control therapy for cancer treatment, explicitly using chemotherapy. Through Pharmacokinetics (PK) modelling, one can explore dose optimization strategies to provide patient-specific, optimal drug regimens tailored to individual cancer patients. The research emphasizes the critical role of prior knowledge and control therapy in enhancing treatment outcomes.

Energy Forecasting and Time Series Analysis Using Machine Learning

Utpal Mishra — 2026-01-23

We have moved from lacking a sufficient supply of electricity/power to producing it in abundance, so it is paramount to decipher how to bring it to optimal usage. This research lays a hand on forecasting energy, bringing in the consumption of electricity and city across the households, enabling stakeholders to accurately predict future energy consumption and generation and meet the demand to enhance sustainable practices. This research examines various Machine Learning algorithms and the very essence of Time Series Forecasting. Forecasting can be done in different span/time intervals as required but eventually depends on factors such as managing the load, trading electricity, and optimizing energy storage, which is crucial for strategic planning and helps to identify trends influenced by economic and social factors. Considering how we are moving forward, having Power System Forecasting is essential to make the optimal use of our resources, and with the generated data, using the approach of Machine Learning and Forecasting to understand the pattern can make a difference.

Remote Ischemic Preconditioning in Noncardiac Surgery: The End of a Promising Hypothesis?

Arun HS Kumar — 2026-01-23

Postoperative myocardial injury remains a major determinant of morbidity and mortality after noncardiac surgery, prompting sustained interest in preventive strategies such as Remote Ischemic Preconditioning (RIPC). Initially supported by compelling experimental data and numerous small-randomized trials, RIPC has been widely perceived as a low-cost, low-risk intervention with potential systemic organ-protective effects. The PRINCE randomized clinical trial represents the most rigorous and definitive evaluation of RIPC in this setting to date. Conducted across 25 centres in eight countries and enrolling more than 1,200 high-risk patients, PRINCE used a double-blind, sham-controlled design, avoided propofol anaesthesia, and selected postoperative myocardial injury, defined by troponin elevation as a clinically meaningful primary endpoint. The trial demonstrated no reduction in myocardial injury or secondary outcomes, including myocardial infarction, stroke, acute kidney injury, or mortality, with RIPC compared with sham treatment. Moreover, modest safety signals, including increased limb petechiae and hospital readmissions, further weaken the rationale for routine use. This editorial place PRINCE in the broader context of perioperative research, highlighting the recurrent discordance between small, single-centre trials and large multicentre randomized studies. The findings decisively challenge the clinical utility of RIPC in noncardiac surgery and underscore the importance of adequately powered methodologically robust trials before adopting biologically appealing interventions into standard perioperative practice.

Harnessing AI Technologies for Sustainable Agricultural Practices: Innovations in Soil Analysis and Crop Management

Utpal Mishra — 2026-01-23

Challenges in agriculture sector are becoming significant a rapidly growing population and declining agricultural productivity. Despite the rigorous efforts of the farmers to cultivate crops, they encounter numerous obstacles stemming from insufficient knowledge about soil characteristics across the demographics of the farmers stacked with uncertain and fluctuating weather patterns. This research highlights the use of Machine Learning (ML) and Computer Vision (CV) to simplify and automate the process with higher yields. Moreover, this study also touches the inclusion of Unmanned Aerial Vehicles (UAVs) to drastically reduce the intense physical work with technology and bring out advancement in agriculture. With the live status update across soil-understanding and nourishment - and soil parameters, forecasting weather features-sunlight rain, wind, etc. Farmers can optimize the crop growth with optimized decision-making and promoting sustainability.

The Vanguard of Paediatric Protection: Innovation, Vigilance, and the Oral Frontier

Arun HS Kumar — 2026-01-23

The 43rd Annual Meeting of the European Society of Paediatric Infectious Diseases (ESPID), held in the historic and vibrant city of Bucharest from May 26th to 30th, 2025, convened at a watershed moment for global child health. As the world moves further away from the acute disruptions of the COVID-19 pandemic, the landscape of paediatric infections has not simply returned to its prior state; rather, it has transformed into a complex arena defined by technological breakthroughs in vaccine delivery, the aggressive re-emergence of classic pathogens, and a deepening understanding of the host-pathogen interface at the mucosal level. This year’s proceedings in Bucharest have underscored a fundamental truth: while our technological toolkit is expanding at an unprecedented rate, our success in protecting the world’s most vulnerable population, its children, depends entirely on our ability to integrate high-tech precision with old-school clinical vigilance.