Effect of Myosin Isoforms on Cardiac Muscle Twitch of Mice, Rats and Humans.

To understand how pathology-induced changes in contractile protein isoforms modulate cardiac muscle function, it is necessary to quantify the temporal-mechanical properties of contractions that occur under various conditions. Pathological responses are much easier to study in animal model systems than in humans, but extrapolation between species presents numerous challenges. Employing computational approaches can help elucidate relationships that are difficult to test experimentally by translating the observations from rats and mice, as model organisms, to the human heart.

Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation.

In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g.

Epidemiological Predictive Modeling of COVID-19 Infection: Development, Testing, and Implementation on the Population of the Benelux Union.

Since the outbreak of coronavirus disease-2019 (COVID-19), the whole world has taken interest in the mechanisms of its spread and development. Mathematical models have been valuable instruments for the study of the spread and control of infectious diseases. For that purpose, we propose a two-way approach in modeling COVID-19 spread: a susceptible, exposed, infected, recovered, deceased (SEIRD) model based on differential equations and a long short-term memory (LSTM) deep learning model.

Improved predictive performance of prostate biopsy collaborative group risk calculator when based on automated machine learning.

Background: The Prostate Biopsy Collaborative Group risk calculator (PBCG RC) has a moderate discriminatory capability. This study aimed to create automated machine learning (AutoML) PBCG RC for predicting the probability of any-grade and high-grade prostate cancer (PCa).

Methods: This retrospective, single-center study was carried out using the database with 832 patients who were subject to transrectal ultrasound-guided prostate biopsy with prostate-specific antigen (PSA) values from 2 to 50 ng/ml.

An Corrosion Model for Biomedical Applications for Coupling With Biocompatibility Tests for Estimation of Long-Term Effects.

The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in body-like environments for long time periods and their coupling with long-term experiments are not practical.

Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression.

Background And Objectives: Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-19, there is a noticeable shortage of literature dealing with ML usage in prediction of disease severity changes through the course of the disease. In that way, predicting disease progression from mild towards moderate, severe and critical condition, would help not only to respond in a timely manner to prevent lethal results, but also to minimize the number of patients in hospitals where this is not necessary.

Methods: We present a methodology for the classification of patients into 4 distinct categories of the clinical condition of COVID-19 disease.

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy.

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM.

A study on the accuracy and efficiency of the improved numerical model for stent implantation using clinical data.

Background And Objectives: Stent implantation procedure should be carefully planned and adapted to the particular patient in order to minimize possible complications. Numerical simulations can provide useful quantitative data about the state of the artery after the implantation, as well as information about the benefits of the intervention from the hemodynamical point of view.

Methods: In this paper, a numerical model for stent implantation is presented.

Attenuated Microcirculation in Small Metastatic Tumors in Murine Liver.

Metastatic cancer disease is the major cause of death in cancer patients. Because those small secondary tumors are clinically hardly detectable in their early stages, little is known about drug biodistribution and permeation into those metastatic tumors potentially contributing to insufficient clinical success against metastatic disease. Our recent studies indicated that breast cancer liver metastases may have compromised perfusion of intratumoral capillaries hindering the delivery of therapeutics for yet unknown reasons.

Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.

COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been made by researchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets mostly used in research in the field of COVID-19 regression modeling as well as present current literature based on Artificial Intelligence (AI) methods for regression tasks, like disease spread.

An Early Stage Researcher's Primer on Systems Medicine Terminology.

Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields.

The effect of variable troponin C mutation thin filament incorporation on cardiac muscle twitch contractions.

One of the complexities of understanding the pathology of familial forms of cardiac diseases is the level of mutation incorporation in sarcomeres. Computational models of the sarcomere that are spatially explicit offer an approach to study aspects of mutational incorporation into myofilaments that are more challenging to get at experimentally. We studied two well characterized mutations of cardiac TnC, L48Q and I61Q, that decrease or increase the release rate of Ca from cTnC, k, resulting in HCM and DCM respectively [1].

Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm.

Estimation of the epidemiology curve for the COVID-19 pandemic can be a very computationally challenging task. Thus far, there have been some implementations of artificial intelligence (AI) methods applied to develop epidemiology curve for a specific country. However, most applied AI methods generated models that are almost impossible to translate into a mathematical equation.

Automatic Evaluation of the Lung Condition of COVID-19 Patients Using X-ray Images and Convolutional Neural Networks.

COVID-19 represents one of the greatest challenges in modern history. Its impact is most noticeable in the health care system, mostly due to the accelerated and increased influx of patients with a more severe clinical picture. These facts are increasing the pressure on health systems.

In vitro and in silico testing of partially and fully bioresorbable vascular scaffold.

Coronary artery disease (CAD), one of the leading causes of death globally, occurs due to the growth of atherosclerotic plaques in the coronary arteries, causing lesions which restrict the flow of blood to the myocardium. Percutaneous transluminal coronary angioplasty (PTCA), including balloon angioplasty and coronary stent deployment is a standard clinical invasive treatment for CAD. Coronary stents are delivered using a balloon catheter inserted across the lesion.

Salivary Gland Ultrasonography in Sjögren's Syndrome: A European Multicenter Reliability Exercise for the HarmonicSS Project.

Salivary gland ultrasonography (SGUS) is increasingly applied for the management of primary Sjögren's syndrome (pSS). This study aims to: (i) compare the reliability between two SGUS scores; (ii) test the reliability among sonographers with different levels of experience. In the reliability exercise, two four-grade semi-quantitative SGUS scoring systems, namely De Vita et al.

Genetic determinants of clinical phenotype in hypertrophic cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease that affects approximately one in 500 people. HCM is a recognized genetic disorder most often caused by mutations involving myosin-binding protein C (MYBPC3) and β-myosin heavy chain (MYH7) which are responsible for approximately three-quarters of the identified mutations.

Methods: As a part of the international multidisciplinary SILICOFCM project ( www.

Abrupt Deterioration of COVID-19 Patients and Spreading of SARS COV-2 Virions in the Lungs.

A unique feature of COVID-19 interstitial pneumonia is an abrupt progression to respiratory failure. Our calculation shows that this abrupt deteriorate may be caused by a sudden shift in the spread of virus-laden bioaerosols through the airways to many different regions of the lungs from the initial site of infection.

Synthesis, Characterization and Biological Studies of Organoselenium trans-Palladium(II) Complexes.

Background: Over the years, transition metal complexes have exhibited significant antimicrobial and antitumor activity. It all started with cisplatin discovery, but due to the large number of side effects it shows, there is a growing need to find a new metal-based compound with higher selectivity and activity on more tumors.

Objectives: Two novel trans-palladium(II) complexes with organoselenium compounds as ligands, [Pd(L1)Cl] (L1 = 5-(phenylselanylmethyl)-dihydrofuran-2(3H)-one) and [Pd(L2)Cl] (L2 = 2- methyl-5-(phenylselanylmethyl)- tetrahydrofuran) were synthesized, in the text referred to as Pd-Se1 and Pd-Se2.

The TAXINOMISIS Project: A multidisciplinary approach for the development of a new risk stratification model for patients with asymptomatic carotid artery stenosis.

Introduction: Asymptomatic carotid artery stenosis (ACAS) may cause future stroke and therefore patients with ACAS require best medical treatment. Patients at high risk for stroke may opt for additional revascularization (either surgery or stenting) but the future stroke risk should outweigh the risk for peri/post-operative stroke/death. Current risk stratification for patients with ACAS is largely based on outdated randomized-controlled trials that lack the integration of improved medical therapies and risk factor control.

A comparison of classifiers in biomedical signal processing as a decision support system in disc hernia diagnosis.

The aim of this research was to investigate the best methodology for disc hernia diagnosis using foot force measurements from the designed platform. Based on the subjective neurological examination that examines muscle weakness on the nerve endings of the skin area on feet and concludes about origins of nerve roots between spine discs, a platform for objective recordings of the aforementioned muscle weakness has been designed. The dataset included 33 patients with pre-diagnosed L4/L5 and L5/S1 disc hernia on the left or the right side, confirmed with the MRI scanning and neurological exam.

Preparation and modeling of three-layered PCL/PLGA/PCL fibrous scaffolds for prolonged drug release.

The authors present the preparation procedure and a computational model of a three-layered fibrous scaffold for prolonged drug release. The scaffold, produced by emulsion/sequential electrospinning, consists of a poly(D,L-lactic-co-glycolic acid) (PLGA) fiber layer sandwiched between two poly(ε-caprolactone) (PCL) layers. Experimental results of drug release rates from the scaffold are compared with the results of the recently introduced computational finite element (FE) models for diffusive drug release from nanofibers to the three-dimensional (3D) surrounding medium.

Smeared Multiscale Finite Element Models for Mass Transport and Electrophysiology Coupled to Muscle Mechanics.

Mass transport represents the most fundamental process in living organisms. It includes delivery of nutrients, oxygen, drugs, and other substances from the vascular system to tissue and transport of waste and other products from cells back to vascular and lymphatic network and organs. Furthermore, movement is achieved by mechanical forces generated by muscles in coordination with the nervous system.