What is he best known for?
The fields of study he is best known for:
- Gene
- Immune system
- Enzyme
Immunology, Influenza A virus, Inflammation, TLR3 and Proinflammatory cytokine are his primary areas of study.
His study in the field of Interleukin 21 is also linked to topics like FHL2.
His study in Influenza A virus is interdisciplinary in nature, drawing from both Innate immune system, Interleukin 22 and Cytokine.
Mustapha Si-Tahar interconnects CD8, Innate lymphoid cell and Pathogenesis in the investigation of issues within Inflammation.
His TLR3 research is multidisciplinary, relying on both RIG-I, T cell and Mitochondrial antiviral-signaling protein.
His work carried out in the field of Proinflammatory cytokine brings together such families of science as RAR-related orphan receptor gamma and Endocrinology.
His most cited work include:
- Involvement of Toll-like Receptor 3 in the Immune Response of Lung Epithelial Cells to Double-stranded RNA and Influenza A Virus * (587 citations)
- Detrimental contribution of the Toll-like receptor (TLR)3 to influenza A virus-induced acute pneumonia. (429 citations)
- Detrimental contribution of the Toll-like receptor (TLR)3 to influenza A virus-induced acute pneumonia. (429 citations)
What are the main themes of his work throughout his whole career to date?
Mustapha Si-Tahar mainly focuses on Immunology, Inflammation, Microbiology, Immune system and Signal transduction.
His research links Lung with Immunology.
Mustapha Si-Tahar focuses mostly in the field of Inflammation, narrowing it down to topics relating to Cystic fibrosis and, in certain cases, Pathology.
Mustapha Si-Tahar studied Immune system and Cell that intersect with Effector.
The Signal transduction study which covers Toll-like receptor that intersects with Aspergillus fumigatus.
His Influenza A virus research incorporates elements of Natural killer T cell, CD8, TLR3 and Viral replication.
He most often published in these fields:
- Immunology (73.51%)
- Inflammation (41.72%)
- Microbiology (35.76%)
What were the highlights of his more recent work (between 2018-2021)?
- Immunology (73.51%)
- Immune system (39.74%)
- Lung (22.52%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Immunology, Immune system, Lung, Inflammation and Pseudomonas aeruginosa.
Mustapha Si-Tahar works on Immunology which deals in particular with Interleukin.
His work deals with themes such as Receptor and Respiratory infection, which intersect with Interleukin.
His Immune system study incorporates themes from Regulator, Cell biology, Effector and Cytokine.
The study incorporates disciplines such as Cell activation, Cytotoxic T cell, Proinflammatory cytokine and Monocyte in addition to Cytokine.
Mustapha Si-Tahar has researched Pseudomonas aeruginosa in several fields, including Bronchoalveolar lavage, Cystic fibrosis and Microbiology.
Between 2018 and 2021, his most popular works were:
- Phenotypical and functional alteration of unconventional T cells in severe COVID-19 patients. (34 citations)
- Phenotypical and functional alteration of unconventional T cells in severe COVID-19 patients. (34 citations)
- Functional alteration of innate T cells in critically ill Covid-19 patients (19 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Immune system
- Enzyme
His main research concerns Immunology, Immune system, Lung, Inflammation and Pneumonia.
His Immunology study combines topics from a wide range of disciplines, such as ARDS and Airway.
His ARDS research is multidisciplinary, incorporating elements of T cell, Pathophysiology and Systemic inflammation.
His Airway research includes themes of Pseudomonas aeruginosa, Pharmacokinetics, Antibiotic resistance and Toxicity.
Mustapha Si-Tahar combines subjects such as Cell activation, Monocyte, Proinflammatory cytokine, Cytotoxic T cell and Macrophage with his study of Cytokine.
His Antibody study combines topics in areas such as Homeostasis, RAR-related orphan receptor gamma, Immunity, Neutrophilia and Interleukin.
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.
