335 research outputs found
The heart microbiome of insectivorous bats from Central and South Eastern Europe
No full textHost associated microbiome not only may affect the individual health-status or provide insights into the species- or group specific bacterial communities but may act as early warning signs in the assessment of zoonotic reservoirs, offering clues to predict, prevent and control possible episodes of emerging zoonoses. Bats may be carriers and reservoirs of multiple pathogens such as viruses, bacteria and parasites, showing in the same time robust immunity against many of them. The microbiota plays a fundamental role on the induction, training and function of the host immune system and the immune system has largely evolved in order to maintain the symbiotic relationship of the host with these diverse microbes. Thus, expanding our knowledge on bat-associated microbiome it can be usefully in understanding bats’ outstanding immune capacities. The aim of this study was to investigate the presence of different bacterial communities in heart tissue of insectivorous bats, Nyctalus noctula, Pipistrellus pipistrellus and Rhinoplophus hipposideros, from Central and Eastern Europe using high-throughput sequencing of variable regions of the 16S rRNA. In addition, species-specific PCRs were used to validate the presence of the vector-borne pathogens Bartonella spp. and Rickettsia spp. In this study we identified a wide variety of bacterial groups, with the most abundant phyla being Proteobacteria and Firmicutes. The results showed that at individual level, the year or location had no effect on the diversity and composition of the microbiome, however host species determined both structure and abundance of the bacterial community. We report the presence of vector-borne bacteria Bartonella spp. in samples of N. noctula and indications of Rickettsia spp. in R. hipposideros. Our results provide a first insight into the bacterial community found in heart tissue of bats from Central and South Eastern Europe.Instituto de BiotecnologíaFil: Corduneanu, Alexandra. University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca. Department of Parasitology and Parasitic Diseases; RumaniaFil: Mihalca, Andrei Daniel. University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca. Department of Parasitology and Parasitic Diseases; RumaniaFil: Sandor, Attila D. University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca. Department of Parasitology and Parasitic Diseases; RumaniaFil: Sandor, Attila D. University of Veterinary Medicine. Department of Parasitology and Zoology; HungríaFil: Hornok, Sándor. University of Veterinary Medicine. Department of Parasitology and Zoology; HungríaFil: Malmberg, Maja. Swedish University of Agricultural Sciences. Department of Biomedical Sciences and Veterinary Public Health. Section of Virology; SueciaFil: Malmberg, Maja. Swedish University of Agricultural Sciences. Department of Animal Breeding and Genetics. SLU Global Bioinformatics Centre; SueciaFil: Pin Viso, Natalia Daniela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Pin Viso, Natalia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bongcam-Rudloff, Erik. Swedish University of Agricultural Sciences. Department of Animal Breeding and Genetics. SLU Global Bioinformatics Centre; Sueci
Studies on glial fibrillary acidic protein (GFAP) in human glioma cells : in vitro and in vivo
No full textAdvancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
No full textThe rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices
Comparison of common adverse neonatal outcomes among preterm and term infants at the National Referral Hospital in Tanzania: a case-control study
No full textBackground: Neonatal period is a critical period in a child’s heath because it is associated with higher risk of adverse health outcomes. The objective of this study was to assess common adverse health outcomes and compare the risk of such outcomes between preterm and term neonates, in Tanzania. Methods: This was a case-control study involving infants admitted at Muhimbili National Hospital between August and October 2020. About 222 pairs of preterm and term infants were followed until discharge. Logistic regression was used to compare risk of health outcomes. Statistical sig-nificance was achieved at p–value < 0.05 and 95% confidence interval. Result: Preterm neonates had increased risk of mortality (OR = 7.2, 95% CI: 3.4----– 15.1), ap-nea (OR = 4.7, 95% CI: 3.4 – 15.1), respiratory distress syndrome (OR = 10.9, 95% CI: 6.1 – 19.6), necrotizing enterocolitis (OR = 5.5, 95% CI: 1.2 – 25.3), anemia (OR = 4.3, 95% CI: 2.8 – 6.6), pneumonia (OR = 2.7, 95% CI: 1.6 – 4.6) and sepsis (OR = 2.6, 95% CI: 1.7 – 3.9). No dif-ference in risk of intraventricular hemorrhage, patent ductus arteriosus and jaundice was ob-served. Conclusion: For promoting neonates' health, prevention and treatment of the higher risk adverse neonatal outcomes should be prioritized
“Biobanks, biomolecular resources and bioinformatics for health care and medical research in Europe”
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SNP and Structural Study of the Notch Superfamily Provides Insights and Novel Pharmacological Targets against the CADASIL Syndrome and Neurodegenerative Diseases
No full textThe evolutionary conserved Notch signaling pathway functions as a mediator of direct cell-cell communication between neighboring cells during development. Notch plays a crucial role in various fundamental biological processes in a wide range of tissues. Accordingly, the aberrant signaling of this pathway underlies multiple genetic pathologies such as developmental syndromes, congenital disorders, neurodegenerative diseases, and cancer. Over the last two decades, significant data have shown that the Notch signaling pathway displays a significant function in the mature brains of vertebrates and invertebrates beyond neuronal development and specification during embryonic development. Neuronal connection, synaptic plasticity, learning, and memory appear to be regulated by this pathway. Specific mutations in human Notch family proteins have been linked to several neurodegenerative diseases including Alzheimer's disease, CADASIL, and ischemic injury. Neurodegenerative diseases are incurable disorders of the central nervous system that cause the progressive degeneration and/or death of brain nerve cells, affecting both mental function and movement (ataxia). There is currently a lot of study being conducted to better understand the molecular mechanisms by which Notch plays an essential role in the mature brain. In this study, an in silico analysis of polymorphisms and mutations in human Notch family members that lead to neurodegenerative diseases was performed in order to investigate the correlations among Notch family proteins and neurodegenerative diseases. Particular emphasis was placed on the study of mutations in the Notch3 protein and the structure analysis of the mutant Notch3 protein that leads to the manifestation of the CADASIL syndrome in order to spot possible conserved mutations and interpret the effect of these mutations in the Notch3 protein structure. Conserved mutations of cysteine residues may be candidate pharmacological targets for the potential therapy of CADASIL syndrome
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