Septic Cardiomyopathy.

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis-induced myocardial dysfunction represents reversible myocardial dysfunction which ultimately results in left ventricular dilatation or both, with consequent loss of contractility. Studies on septic cardiomyopathy report a wide range of prevalence ranging from 10% to 70%.

The Correlation of Serum Calpain 1 Activity and Concentrations of Interleukin 33 in COVID-19 Acute Respiratory Distress Syndrome.

Acute respiratory distress syndrome (ARDS) is one of the most severe complications of the COVID-19 disease. The role of IL-33 and calpain 1 was previously described in lung infections and lung tissue damage. Our study examined the association between serum calpain 1 activity and IL-33 concentration in patients with COVID-19 ARDS.

Fitts' Tapping Task as a New Test for Cognition and Manual Dexterity in Multiple Sclerosis: Validation Study.

Introduction. Studies suggest that people with multiple sclerosis (pwMS) experience continuous and subclinical physical worsening, even as early as their disease diagnosis. Validating sensitive and reproducible tests that can capture subclinical disease activity early in the disease are clinically useful and highly warranted.

VENOUS THROMBOEMBOLISM IN THE EMERGENCY DEPARTMENT - SINGLE-CENTER EXPERIENCE.

Given the importance of early recognition of acute venous thromboembolism (VTE) and the nonspecificity of its symptoms and signs, it is essential to follow the guidelines for diagnostic and therapeutic decisions. Ultrasound examination of the entire lower extremity is currently the standard diagnostic method for symptomatic patients with a clinical probability of deep vein thrombosis (DVT) according to the Wells scoring system. The aim of this study is to show the demographic structure and analyze the number of patients in the emergency department with suspected venous thrombosis.

Response of platelets to silver nanoparticles designed with different surface functionalization.

Despite increasing use of silver nanoparticles (AgNPs) in different medicinal products, knowledge about their effects on hemostasis and platelets functionality is still scarce. Published scientific reports provide neither data on oxidative stress response of platelets to AgNPs nor information about the effects of AgNPs physicochemical properties on functionality and activation of platelets. This study aimed to explore the role of AgNPs surface functionalization on cell viability, particle uptake, oxidative stress response, and activation of platelets.

Oxidative Stress in Ischemic Heart Disease.

One of the novel interesting topics in the study of cardiovascular disease is the role of the oxidation system, since inflammation and oxidative stress are known to lead to cardiovascular diseases, their progression and complications. During decades of research, many complex interactions between agents of oxidative stress, oxidation, and antioxidant systems have been elucidated, and numerous important pathophysiological links to na number of disorders and diseases have been established. This review article will present the most relevant knowledge linking oxidative stress to vascular dysfunction and disease.

Assessing the performance of a suite of machine learning models for daily river water temperature prediction.

In this study, different versions of feedforward neural network (FFNN), Gaussian process regression (GPR), and decision tree (DT) models were developed to estimate daily river water temperature using air temperature ( ), flow discharge (), and the day of year () as predictors. The proposed models were assessed using observed data from eight river stations, and modelling results were compared with the air2stream model. Model performances were evaluated using four indicators in this study: the coefficient of correlation (R), the Willmott index of agreement (d), the root mean squared error (RMSE), and the mean absolute error (MAE).

Two hybrid data-driven models for modeling water-air temperature relationship in rivers.

River water temperature (RWT) forecasting is important for the management of stream ecology. In this paper, a new method based on coupling of wavelet transformation (WT) and artificial intelligence (AI) techniques, including multilayer perceptron neural network (MLPNN) and adaptive neural-fuzzy inference system (ANFIS) for RWT prediction is proposed. The performances of the hybrid models are compared with regular MLPNN and ANFIS models and multiple linear regression (MLR) models for RWT forecasting in two river stations in the Drava River, Croatia.

Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network models (MLPNN), adaptive neuro-fuzzy inference systems (ANFIS) with fuzzy c-mean clustering algorithm (ANFIS_FC), ANFIS with grid partition method (ANFIS_GP), and ANFIS with subtractive clustering method (ANFIS_SC), were implemented to simulate daily river water temperature, using air temperature (T), river flow discharge (Q), and the components of the Gregorian calendar (CGC) as predictors. The proposed models were tested in various river systems characterized by different hydrological conditions.

Modelling daily water temperature from air temperature for the Missouri River.

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors.

Intake of some minerals in healthy adult volunteers from eastern Croatia.

Although minerals have important protective effects in human health, their role in nutrition is still underestimated and insufficiently investigated in Croatian population. The aim of this research was to examine sodium, potassium, magnesium, phosphorus, iron and copper intake in 120 adults, aged 18-54 years. The research was conducted using the 10 times repeated 24-h recall method during 1 year.