Efficacy of a multicomponent binding agent against combined exposure to zearalenone and ochratoxin A in weaned pigs.

Introduction: The study aimed to evaluate the efficacy of a novel multicomponent substance against combined exposure to the mycotoxins zearalenone (ZEN) and ochratoxin A (OTA) in weaned piglets. Methods: In total, 60 piglets at the age of 28 days were equally allocated to four experimental groups (A-D), consisting of eight female and seven male piglets each (15 animals per group, for a total trial duration of 42 days). Animals from group A received typical weaner feed without mycotoxins or the test product [multicomponent mycotoxin detoxifying agent (MMDA)]. Group B animals received the same weaner feed contaminated with 0.992 mg ZEN/kg feed and 0.531 mg OTA/kg feed without the addition of the MMDA. Animals in group C received the same contaminated feed as group B with the addition of 1.5 g MMDA/kg feed, whereas group D received the same feed as group B with the inclusion of 3 g MMDA/kg feed. Clinical signs and performance parameters [body weight (BW), average daily weight gain (ADWG), and feed conversion ratio (FCR)] were evaluated, while mycotoxin residues were also assessed in the liver and kidney tissues. Results: Findings showed improved FCR in the group that received the greatest dose of the test product (3 g MMDA/kg feed) compared to the group that received the lower dose (1.5 g MMDA/kg feed). A few hematological and biochemical parameters were slightly altered, predominantly within normal limits. The residue analysis demonstrated a reduction of OTA in liver samples, a-ZEL in the liver and total tested samples, and a total of ZEN and metabolite contents in all samples of the group that received the greatest MMDA dose in comparison to the group that received the toxins without the addition of the test product. Discussion: Therefore, a positive effect of the MMDA at the greatest dosage regime on reducing bioavailability and tissue deposition of ZEN and OTA, with a particularly positive effect on FCR in weaned pigs, is suggested under concurrent ZEN and OTA exposure in vivo.

Bibliometric research analysis of molecularly imprinted polymers (MIPs): evidence and research activity dynamics.

The escalating issue of water pollution has become a worldwide issue that has captured the attention of numerous scientists. Molecularly imprinted polymers (MIPs) have emerged as adaptable materials with exceptional attributes, including easy synthesis, low cost, remarkable durability, long life, and accessibility. These attributes have motivated researchers to develop novel materials based on MIPs to tackle hazardous contaminants in environmental matrices. The purpose of this paper was to conduct a bibliometric analysis on MIPs' publications, in order to shed light on the developments and focus points of the field. The selected publications were obtained from Scopus database and subjected to a filtering process, resulting in 11,131 relevant publications. The analysis revealed that the leading publication source (journal) is Biosensors and Bioelectronics; the mostly employed keywords are solid-phase extraction, electrochemical sensor, and molecular recognition; and the top contributing countries are China, Iran, and the USA. The Latent Dirichlet Allocation (LDA) algorithm was used for extracting thematic axes from the textual content of the publications. The results of the LDA model showcase that the topic of synthesis and performance of MIPs for environmental applications can be considered as the most dominant topic with a share value of 72.71%. From the analysis, it can be concluded that MIPs are a cross-disciplinary research field.

Single Nucleotide Polymorphisms' Causal Structure Robustness within Coronary Artery Disease Patients.

An ever-growing amount of accumulated data has materialized in several scientific fields, due to recent technological progress. New challenges emerge in exploiting these data and utilizing the valuable available information. Causal models are a powerful tool that can be employed towards this aim, by unveiling the structure of causal relationships between different variables. The causal structure may avail experts to better understand relationships, or even uncover new knowledge. Based on 963 patients with coronary artery disease, the robustness of the causal structure of single nucleotide polymorphisms was assessed, taking into account the value of the Syntax Score, an index that evaluates the complexity of the disease. The causal structure was investigated, both locally and globally, under different levels of intervention, reflected in the number of patients that were randomly excluded from the original datasets corresponding to two categories of the Syntax Score, zero and positive. It is shown that the causal structure of single nucleotide polymorphisms was more robust under milder interventions, whereas in the case of stronger interventions, the impact increased. The local causal structure around the Syntax Score was studied in the case of a positive Syntax Score, and it was found to be resilient, even when the intervention was strong. Consequently, employing causal models in this context may increase the understanding of the biological aspects of coronary artery disease.

Comparative Effects of Deoxynivalenol, Zearalenone and Its Modified Forms De-Epoxy-Deoxynivalenol and Hydrolyzed Zearalenone on Boar Semen In Vitro.

Deoxynivalenol (DON) and zearalenone (ZEN) are described as detrimental factors to sow and boar fertility. In comparison, literature reports on the impact of modified forms of DON and ZEN, such as de-epoxy-DON (DOM-1) and hydrolyzed ZEN (HZEN), on swine reproduction are scarce. The aim of our study was to compare the effects of DON, DOM-1, ZEN and HZEN on boar semen in vitro. To this end, pooled boar semen ejaculates from two adult boars were treated with either 50.6 µM DON, 62.8 µM ZEN or equimolar concentrations of DOM-1 and HZEN, respectively (dilution volume of v/v 0.7% DMSO in all cases). Effects on semen motility, morphology, viability, hypo-osmotic swelling test reaction and DNA integrity were investigated hourly up to four hours of incubation. DON negatively affected particular parameters evaluated with a computer-assisted sperm analysis system (CASA), such as immotile spermatozoa and progressive motile spermatozoa, whereas those effects were absent in the case of DOM-1 treatment. In contrast to HZEN, ZEN affected almost all CASA parameters. Furthermore, only ZEN decreased the proportion of viable spermatozoa and increased the proportion of spermatozoa with abnormalities. In conclusion, DON and ZEN negatively affected boar semen in vitro, whereas equimolar concentrations of DOM-1 and HZEN did not induce harmful effects.

Dissecting miRNA-Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine.

MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems. In this article, the miRNA-gene networks and the genomic signatures resulting from the SNPs will be analyzed as a method of highlighting specific gene-signaling circuits as sources of molecular knowledge which is relevant to CVDs. In concordance with this concept, and as a case study, the design of the clinical trial GESS (NCT03150680) is referenced. The latter is presented in a manner to provide a direction for the improvement of the implementation of pharmacogenomics and precision cardiovascular medicine trials.

An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies.

The COVID-19 outbreak, also known as the coronavirus pandemic, has left its mark on every aspect of our lives and at the time of this writing is still an ongoing battle. Beyond the immediate global-wide health response, the pandemic has triggered a significant number of IT initiatives to track, visualize, analyze and potentially mitigate the phenomenon. For individuals or organizations interested in developing COVID-19 related software, knowledge-sharing communities such as Stack Overflow proved to be an effective source of information for tackling commonly encountered problems. As an additional contribution to the investigation of this unprecedented health crisis and to assess how fast and how well the community of developers has responded, we performed a study on COVID-19 related posts in Stack Overflow. In particular, we profiled relevant questions based on key post features and their evolution, identified the most prominent technologies adopted for developing COVID-19 software and their interrelations and focused on the most persevering problems faced by developers. For the analysis of posts we employed descriptive statistics, Association Rule Graphs, Survival Analysis and Latent Dirichlet Allocation. The results reveal that the response of the developers' community to the pandemic was immediate and that the interest of developers on COVID-19 related challenges was sustained after its initial peak. In terms of the problems addressed, the results show a clear focus on COVID-19 data collection, analysis and visualization from/to the web, in line with the general needs for monitoring the pandemic.

Investigation of a Novel Multicomponent Mycotoxin Detoxifying Agent in Amelioration of Mycotoxicosis Induced by Aflatoxin-B1 and Ochratoxin A in Broiler Chicks.

The present study was designed to determine the efficacy of a novel multicomponent mycotoxin detoxifying agent (MMDA) containing modified zeolite (Clinoptilolite), Bacillus subtilis, B. licheniformis, Saccharomyces cerevisiae cell walls and silymarin against the deleterious effects of Aflatoxin B1 (AFB1) and Ochratoxin A (OTA) in broiler chicks. A total of 160 one-day-old Ross 308® broiler chicks were randomly allocated in four treatment groups, with four replicates, according to the following experimental design for 42 days. Group A received a basal diet; Group B received a basal diet contaminated with AFB1 and OTA at 0.1 mg/kg and 1 mg/kg, respectively; Group C received a basal diet contaminated with AFB1 and OTA and MMDA at 1 g/kg feed, and Group D received a basal diet contaminated with AFB1 and OTA and MMDA at 3 g/kg feed. Results showed that ingested mycotoxins led to significant (p ≤ 0.05) reduction in body weight and feed conversion from 25 days of age, induced histopathological changes, increased the pH of the intestinal content, and altered the biochemical profile of birds with significantly (p ≤ 0.05) increased aspartate aminotransferase (AST) values (p ≤ 0.05). On the other hand, the supplementation of MMDA significantly (p ≤ 0.05) improved the feed conversion ratio (FCR) during the second part of the study, diminished biochemical alterations, reduced pH in jejunal and ileal content, and E. coli counts in the caeca of birds (p ≤ 0.05). It may be concluded that the dietary supplementation of the MMDA partially ameliorated the adverse effects of AFB1 and OTA in broilers and could be an efficient tool in a mycotoxin control program.

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease-rationale and design of the GESS study.

BACKGROUND: Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score-GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies. METHODS: GESS (ClinicalTrials.gov Identifier: NCT03150680) is a prospective, non-interventional clinical study designed to enroll 1080 consecutive patients with no prior history of coronary revascularization procedure, who undergo scheduled or emergency coronary angiography in AHEPA, University General Hospital of Thessaloniki. Next generation sequencing (NGS) technology will be used to genotype specific single-nucleotide polymorphisms (SNPs) across the genome of study participants, which were identified as clinically relevant to CAD after extensive bioinformatic analysis of literature-based SNPs. Enrichment analyses of Gene Ontology-Molecular Function, Reactome Pathways and Disease Ontology terms were also performed to identify the top 15 statistically significant terms and pathways. Furthermore, the SYNTAX score will be calculated for the assessment of CAD severity of all patients based on their angiographic findings. All patients will be followed-up for one-year, in order to record any major adverse cardiovascular events. DISCUSSION: A group of 228 SNPs was identified through bioinformatic and pharmacogenomic analysis to be involved in CAD through a wide range of pathways and was correlated with various laboratory and clinical parameters, along with the patients' response to clopidogrel and statin therapy. The annotation of these SNPs revealed 127 genes being affected by the presence of one or more SNPs. The first patient was enrolled in the study in February 2019 and enrollment is expected to be completed until June 2021. Hence, GESS is the first trial to date aspiring to develop a novel risk prediction algorithm, the GEnetic Syntax Score, able to identify patients at high risk for complex CAD based on their molecular signature profile and ultimately promote pharmacogenomics and precision medicine in routine clinical settings. Trial registration GESS trial registration: ClinicalTrials.gov Number: NCT03150680. Registered 12 May 2017- Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03150680 .

A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial.

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and (ii) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F-measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients.

Individual and Combined In Vitro Effects of Deoxynivalenol and Zearalenone on Boar Semen.

Mycotoxins deoxynivalenol (DON) and zearalenone (ZEN) can negatively affect pig health. However, little is known about their effects on boar semen. We assessed the individual and combined effects of DON and ZEN on boar semen in vitro. In a pretrial, we determined the minimum dose (MiD) of each mycotoxin that induces a significant alteration of sperm progressive motility, as investigated using computer-assisted semen analysis (CASA). In the main trial, the individual and combined effects of each mycotoxin's MiD on sperm motility and kinetics (CASA analysis), morphology (SpermBlue staining), viability (calcein-propidium iodide staining), membrane functional status (hypoosmotic swelling test), and chromatin integrity (acridine orange staining) were analyzed. Pretrial results suggested a MiD of 50.6 µM and 62.8 µM for DON and ZEN, respectively. In the main trial, DON and ZEN administered at MiD significantly affected CASA parameters (e.g., increase of immotile spermatozoa, reduction of progressive motile spermatozoa), decreased sperm viability, and affected sperm morphology (head abnormalities) and membrane functional status. DON and ZEN showed less than additive effects on most parameters tested and a synergistic effect on viability and on two CASA parameters. In conclusion, DON and ZEN showed individual and combined toxic effects on boar semen in vitro.