What is she best known for?
The fields of study she is best known for:
- Gene
- Internal medicine
- Cancer
Her primary areas of investigation include Immunology, Inflammation, Genetics, microRNA and Internal medicine.
Her work carried out in the field of Immunology brings together such families of science as Alzheimer's disease and Disease.
The study incorporates disciplines such as Biomarker, Stressor, Circulating MicroRNA and Network theory of aging in addition to Disease.
Her Inflammation study combines topics from a wide range of disciplines, such as Phenotype, Senescence, Nutraceutical and Bioinformatics.
Her microRNA research incorporates elements of Regulation of gene expression, Lipotoxicity and Cancer research.
Her Internal medicine research focuses on Endocrinology and how it relates to Cytokine.
Her most cited work include:
- Inflamm‐aging: An Evolutionary Perspective on Immunosenescence (2549 citations)
- Inflammaging and anti-inflammaging: A systemic perspective on aging and longevity emerged from studies in humans (1335 citations)
- Human polymorphism at microRNAs and microRNA target sites. (1284 citations)
What are the main themes of her work throughout her whole career to date?
Fabiola Olivieri spends much of her time researching Internal medicine, microRNA, Endocrinology, Genetics and Inflammation.
Her Internal medicine research is multidisciplinary, incorporating perspectives in Diabetes mellitus, Type 2 diabetes and Cardiology.
Her microRNA study incorporates themes from Computational biology, Epigenetics, Bioinformatics and Cell biology.
Inflammation is the subject of her research, which falls under Immunology.
Her Allele research includes themes of Genetic variability, Genotype, Locus and Centenarian.
Her Senescence study integrates concerns from other disciplines, such as Cancer research, In vivo and Ageing.
She most often published in these fields:
- Internal medicine (39.83%)
- microRNA (26.84%)
- Endocrinology (21.65%)
What were the highlights of her more recent work (between 2018-2021)?
- Internal medicine (39.83%)
- microRNA (26.84%)
- Type 2 diabetes (11.69%)
In recent papers she was focusing on the following fields of study:
Her primary areas of study are Internal medicine, microRNA, Type 2 diabetes, Inflammation and Cell biology.
The concepts of her Internal medicine study are interwoven with issues in Diabetes mellitus and Endocrinology.
Her work deals with themes such as Myelodysplastic syndromes, Computational biology, Extracellular vesicles and Oncology, which intersect with microRNA.
Her studies in Inflammation integrate themes in fields like Interferon and Disease.
Her Cell biology study also includes
- Phenotype together with Telomere, Proinflammatory cytokine, Helicase, RNA and DNA,
- DNA damage and related Mitochondrion, Flux, Oxidative phosphorylation, Glycolysis and Bioenergetics.
Her study in the field of Inflamm aging is also linked to topics like Severe acute respiratory syndrome coronavirus 2.
Between 2018 and 2021, her most popular works were:
- Inflamm-aging: Why older men are the most susceptible to SARS-CoV-2 complicated outcomes. (59 citations)
- Small extracellular vesicles deliver miR-21 and miR-217 as pro-senescence effectors to endothelial cells (33 citations)
- Where Metabolism Meets Senescence: Focus on Endothelial Cells. (30 citations)
In her most recent research, the most cited papers focused on:
- Gene
- Internal medicine
- Cancer
The scientist’s investigation covers issues in Cell biology, Internal medicine, microRNA, Telomere and Senescence.
She interconnects Endocrinology and Type 2 diabetes in the investigation of issues within Internal medicine.
Her study in Endocrinology is interdisciplinary in nature, drawing from both Hemoglobin and Downregulation and upregulation.
Her microRNA research is multidisciplinary, relying on both Nutraceutical, Gut flora, Ruminococcus and NAD+ kinase.
The Telomere study combines topics in areas such as Phenotype, Inflammation, Computational biology and Telomerase.
Her Senescence research includes elements of Parabiosis, Healthy longevity, Extracellular vesicles and Ageing.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
