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Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors.

ABSTRACT: Sensors for monitoring biomolecular dynamics in biological systems and biotechnological processes in real time, need to accurately and precisely reconstruct concentration-time profiles. This requirement becomes challenging when transport processes and biochemical kinetics are important, as is typically the case for biomarkers at low concentrations. Here, we present a comprehensive methodology to study the concentration-time profiles generated by affinity-based sensors that continuously interact with a biological system of interest. Simulations are performed for sensors with diffusion-based sampling (e.g., a sensor patch on the skin) and advection-based sampling (e.g., a sensor connected to a catheter). The simulations clarify how transport processes and molecular binding kinetics result in concentration gradients and time delays in the sensor system. Using these simulations, measured and true concentration-time profiles of insulin were compared as a function of sensor design parameters. The results lead to guidelines on how biomolecular monitoring sensors can be designed for optimal bioanalytical performance in terms of concentration and time properties.

SUBMITTER: Lubken RM

PROVIDER: S-EPMC8805115 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors.

Lubken Rafiq M RM de Jong Arthur M AM Prins Menno W J MWJ

ACS sensors 20220103 1

Sensors for monitoring biomolecular dynamics in biological systems and biotechnological processes in real time, need to accurately and precisely reconstruct concentration-time profiles. This requirement becomes challenging when transport processes and biochemical kinetics are important, as is typically the case for biomarkers at low concentrations. Here, we present a comprehensive methodology to study the concentration-time profiles generated by affinity-based sensors that continuously interact ...[more]

PMID: 34978190

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Project description:Health care is one of the least funded sectors in Bangladesh and many other similar developing countries. People living in rural and remote areas do not have access to proper health care, and when they do, it is too expensive. This research aimed to develop a real-time health monitoring system that is cheap, easy to use, and accessible by doctors and patients. The system consists of several Internet of Things (IoT)-based sensors connected to an Arduino microprocessor, which thus measures the vital body signs of the patients. The measured readings are then transmitted to an Android application on a smartphone via a Bluetooth module. The sensors are connected to analog inputs. These sensors measure analog data, which is amplified by the microprocessor after being sorted. Doctors can also carry out the diagnosis of ailments using the data collected remotely from the patient. An Android-based mobile application that interfaces with a web-based application is implemented for efficient patients-doctors dual real-time communication. The Android application, which is connected to a MySQL database, updates the said database, which updates and displays the readings on a website accessible by both doctors and patients. Initially, the health monitor was tested using an Arduino Integrated Development Environment (IDE) monitor and a single user. Once initial simulations were successful, the proposed system was tested on five different real-human test subjects. The testing of the wireless health monitor produced successful results that measured patient vitals with a high level of accuracy. The proposed IoT-based system monitors vital signs such as the patient's body temperature, heart rate, ECG, SpO2 levels, blood pressure, and glucose levels. This system also includes a medical treatment plan by the doctors. The proposed system is novel as it integrates the IoT-based patient monitoring system with telemedicine. This proposed system has different sensors for real-time measuring the vital signs of the human body. A mobile and web application have also been integrated with this system for real-time remote patient monitoring and treatment plan. There are now systems available that only offer a telemedicine facility, where patients and doctors can have discussions, but do not have an IoT-based patient vital sign monitoring system integrated with telemedicine. The proposed system in this paper has the facility of IoT-based patient vital signs monitoring integrated with telemedicine, which makes this research work novel. The proposed system will increase the life expectancy of people throughout the world.

Dataset Information

Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors.

Publications

Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors.

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