SMARTER-database: a tool to integrate SNP array datasets for sheep and goat breeds.

Unlabelled: Underutilized sheep and goat breeds can adapt to challenging environments due to their genetics. Integrating publicly available genomic datasets with new data will facilitate genetic diversity analyses; however, this process is complicated by data discrepancies, such as outdated assembly versions or different data formats. Here, we present the SMARTER-database, a collection of tools and scripts to standardize genomic data and metadata, mainly from SNP chip arrays on global small ruminant populations, with a focus on reproducibility.

Smartwatch interventions in healthcare: A systematic review of the literature.

Objective: The use of smartwatches has attracted considerable interest in developing smart digital health interventions and improving health and well-being during the past few years. This work presents a systematic review of the literature on smartwatch interventions in healthcare. The main characteristics and individual health-related outcomes of smartwatch interventions within research studies are illustrated, in order to acquire evidence of their benefit and value in patient care.

Extensive Countrywide Molecular Identification and High Genetic Diversity of spp. in Domestic Ruminants in Greece.

The gastrointestinal nematode parasite spp. is one of the most pathogenic parasites of ruminants, due to its blood-sucking activity, which causes large economic losses in the ruminant industry. The latest epizootiological data recorded an increase in the infection, not only in Greece but also in other countries, mainly attributed to climatic changes.

Methodological challenges in systematic reviews of mHealth interventions: Survey and consensus-based recommendations.

Objective: Mobile Health (mHealth) refers to using mobile devices to support health. This study aimed to identify specific methodological challenges in systematic reviews (SRs) of mHealth interventions and to develop guidance for addressing selected challenges.

Study Design And Setting: Two-phase participatory research project.

Investigating the role of genetic variation in and in the domestication of gilthead seabream ( Linnaeus) and European seabass ( Linnaeus).

Gene function conservation is crucial in molecular ecology, especially for key traits like growth and maturation in teleost fish. The and genes are known to influence age-at-maturity in Atlantic salmon, but their impact on other fish species is poorly understood. Here, we investigated the association of and in the domestication of gilthead seabream and European seabass, both undergoing selective breeding for growth-related traits in the Mediterranean.

Genetic Identification and Traceability of Insect Meals.

Insects have been proposed as a rich alternative source of protein for the partial or total replacement of fishmeal in aquaculture. For maximum safety and effectiveness of insect meals, control of the quality composition of these products is considered mandatory. The aim of this study was the genetic analysis of the composition of commercially available insect meals at the species level.

Prevalence of SOD1 allele associated with degenerative myelopathy in canine population in Greece.

Canine degenerative myelopathy (CDM) is a late-onset fatal disorder associated with a point mutation of the superoxide dismutase 1 (SOD1) gene (c.118G > A). The purpose of this study was to determine the genotype and allele frequencies of this mutation in 108 dogs, mainly in Belgian Malinois and German Shepherd dogs with (CDM-affected group) and without CDM clinical symptoms (control group) in Greece.

Promoting Obesity Prevention and Healthy Habits in Childhood: The OCARIoT Experience.

Objective: Long term behavioural disturbances and interventions in healthy habits (mainly eating and physical activity) are the primary cause of childhood obesity. Current approaches for obesity prevention based on health information extraction lack the integration of multi-modal datasets and the provision of a dedicated Decision Support System (DSS) for health behaviour assessment and coaching of children.

Methods: Continuous co-creation process has been applied in the frame of the Design Thinking Methodology, involving children, educators and healthcare professional in the whole process.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review.

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs.

Novel genomic markers and genes related to reproduction in prolific Chios dairy sheep: a genome-wide association study.

Genetic architecture of sheep reproduction is increasingly gaining scientific interest due to the major impact on sheep production systems. In the present study, we conducted pedigree-based analyses and genome-wide association studies using the Illumina Ovine SNP50K BeadChip to explore the genetic mechanisms underlying the reproduction of the highly prolific Chios dairy sheep. First lambing age, total prolificacy and maternal lamb survival were selected as representative reproductive traits and estimated as significantly heritable (h = 0.

Isolation of Listeria monocytogenes from poultry red mite (Dermanyssus gallinae) infesting a backyard chicken farm in Greece.

The poultry red mite (PRM), Dermanyssus gallinae, is arguably the most harmful, ubiquitous haematophagous ectoparasite infesting egg-laying hens. PRM is a vector of various microorganisms, with some being important for food microbiology and public health. The present study aimed to investigate the presence of specific pathogens, including Escherichia coli, Salmonella spp.

Indications, Safety, Efficacy and Survival Benefit of Intraperitoneal Chemotherapy in Patients With Advanced Gastric Cancer.

Background/aim: Advanced gastric cancer remains a significant concern for the medical community mostly due to the locoregional extension of the disease. Most commonly, stomach neoplasms are resectable, but not curable, due to the elevated percentage of peritoneal dissemination after gastrectomy and extensive lymph node dissection. Locoregional intraperitoneal chemotherapy plays a pivotal role in overall survival and prognosis of patients with advanced gastric cancer and shows a high probability of peritoneal dissemination after gastrectomy.

A social robot-based platform for health behavior change toward prevention of childhood obesity.

Childhood obesity is a major public health challenge which is linked with the occurrence of diseases such as diabetes and cancer. The COVID-19 pandemic has forced changes to the lifestyle behaviors of children, thereby making the risk of developing obesity even greater. Novel preventive tools and approaches are required to fight childhood obesity.

Bulgarian Medicinal Extracts as Natural Inhibitors with Antiviral and Antibacterial Activity.

Background: Bulgaria is a country with a wide range of medicinal plants, with uses in traditional medicine dating back for centuries.

Methods: Disc diffusion assay was used to evaluate the antimicrobial activity of the plant extracts. A cytopathic effect inhibition test was used for the assessment of the antiviral activity of the extracts.

Usability of the Virtual Supermarket Test for Older Adults with and without Cognitive Impairment.

This study conducted a preliminary usability assessment of the Virtual Supermarket Test (VST), a serious game-based self-administered cognitive screening test for mild cognitive impairment (MCI). Twenty-four healthy older adults with subjective cognitive decline and 33 patients with MCI self-administered the VST and then completed the System Usability Scale (SUS). The average SUS score was 83.

Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.

IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions.

The genus Diaphanosoma (Diplostraca: Sididae) in Greece: morphological and molecular assessment.

For the genus Diaphanosoma Fischer (Cladocera) the species name D. brachyurum has been widely used for many decades to identify other species belonging to this genus. To clarify the diversity of the genus in Greek lakes in the present study, we morphologically and genetically identified the Diaphanosoma species occurring in eight lakes.

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development of intelligent mobile health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere.

Objective: The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this rapidly developing field.

A Machine Learning Approach for Prediction of Sedentary Behavior Based on Daily Step Counts.

Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our work focuses on analyzing historical data from multiple users of wearable physical activity trackers and exploring the performance of four machine learning algorithms, i.