Applications of genome-scale metabolic models to the study of human diseases: A systematic review.

Background And Objectives: Genome-scale metabolic networks (GEMs) represent a valuable modeling and computational tool in the broad field of systems biology. Their ability to integrate constraints and high-throughput biological data enables the study of intricate metabolic aspects and processes of different cell types and conditions. The past decade has witnessed an increasing number and variety of applications of GEMs for the study of human diseases, along with a huge effort aimed at the reconstruction, integration and analysis of a high number of organisms.

Design and Experimental Validation of a 3D-Printed Embedded-Sensing Continuum Robot for Neurosurgery.

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles.

A General Approach for the Modelling of Negative Feedback Physiological Control Systems.

Mathematical models can improve the understanding of physiological systems behaviour, which is a fundamental topic in the bioengineering field. Having a reliable model enables researchers to carry out in silico experiments, which require less time and resources compared to their in vivo and in vitro counterparts. This work's objective is to capture the characteristics that a nonlinear dynamical mathematical model should exhibit, in order to describe physiological control systems at different scales.

Combined mechanistic modeling and machine-learning approaches in systems biology - A systematic literature review.

Background And Objective: Mechanistic-based Model simulations (MM) are an effective approach commonly employed, for research and learning purposes, to better investigate and understand the inherent behavior of biological systems. Recent advancements in modern technologies and the large availability of omics data allowed the application of Machine Learning (ML) techniques to different research fields, including systems biology. However, the availability of information regarding the analyzed biological context, sufficient experimental data, as well as the degree of computational complexity, represent some of the issues that both MMs and ML techniques could present individually.

CBRA: Cardiac biomarkers release analyzer.

Background And Objectives: The most advanced technologies and continuous innovations in the medical field require a necessary interaction between the clinical and the engineering world. In this context, software applications are proposed as a bridge between the two scientific fields and, therefore, as powerful tools, easy to use, and with great analytical skills. In this work, we propose CBRA as an innovative software platform, moving towards personalized medicine, which aims to simplify and speed up the triage of patients and support doctors in the diagnostic and prognostic phase.

SlicerArduino: A Bridge between Medical Imaging Platform and Microcontroller.

Interaction between medical image platform and external environment is a desirable feature in several clinical, research, and educational scenarios. In this work, the integration between 3D Slicer package and Arduino board is introduced, enabling a simple and useful communication between the two software/hardware platforms. The open source extension, programmed in Python language, manages the connection process and offers a communication layer accessible from any point of the medical image suite infrastructure.

Estimation of the Acute Myocardial Infarction Onset Time based on Time-Course Acquisitions.

Quantitative analysis of biochemical parameters is crucial for a correct diagnosis and prognosis of patients subject to acute myocardial infarction (AMI). In order to achieve a quantitative understanding of the dynamics of cardiac biomarkers, we have developed a mathematical model that can be exploited to extrapolate the release curve of cardiac troponin T (cTnT) into the plasma from few experimental acquisitions. The present work introduces a novel approach, based on the cTnT-release model, aimed at the identification of the infarct onset time.

Identification of the infarct time in patients with acute myocardial infarction.

In the present work, we introduce a novel technique to identify the infarct time from time-series meaurements of the cardiac troponin T (cTnT) into plasma. Although this information is extremely valuable from a clinical standpoint, it is not always possible to establish with certainty the exact infarct time. Here, we show how the infarct time can be reliably estimated from the cTnT release data in the first few hours after AMI, by using an optimization-based procedure and a model-based approach.

Validation of a model of the GAL regulatory system via robustness analysis of its bistability characteristics.

Background: In Saccharomyces cerevisiæ, structural bistability generates a bimodal expression of the galactose uptake genes (GAL) when exposed to low and high glucose concentrations. This indicates that yeast cells can decide between using either the limited amount of glucose or growing on galactose under changing environmental conditions. A crucial requirement for any plausible mechanistic model of this system is that it reproduces the robustness of the bistable response observed in vivo against inter-individual parametric variability and fluctuating environmental conditions.

Structural bistability of the GAL regulatory network and characterization of its domains of attraction.

Bistability is a system-level property, exploited by many biomolecular interaction networks as a key mechanism to accomplish different cellular functions (e.g., differentiation, cell cycle, switch-like response to external stimuli).