Concanavalin-A displays leishmanicidal activity by inducing ROS production in human peripheral blood mononuclear cells.
Ana Paula Fortes Dos Santos ThomazelliFernanda Tomiotto-PellissierMilena Menegazzo Miranda-SaplaSuelen Santos da SilvaDaniele Sapede AlvarengaCarolina PanisAllan Henrique Depieri CataneoJuliano BordignonGuilherme Ferreira SilveiraLucy Megumi Yamauchi LioniJussevania Pereira Santos Rubro de SáIonice FelipeWander Rogério PavanelliIvete Conchon CostaPublished in: Immunopharmacology and immunotoxicology (2018)
The context of the article: Leishmania amazonensis has a wide geographical distribution throughout South American countries and can cause self-healing to severe cases as mucocutaneous or visceral forms. Leishmaniasis presents a balance of inflammatory and anti-inflammatory cytokines which is responsible for promoting the activation of phagocytes, essential to control the infection and lead to tissue repair/resolution of the disease, respectively. Results and discussion: Our model revealed that the treatment with Con-A was capable to stimulate human PBMC cells by increasing the phagocytic capacity and promoting parasite elimination. The pretreatment with Con-A promoted inflammatory (IFN-γ, TNF-α, IL-2 and IL-6) and anti-inflammatory (IL-4 and IL-10) cytokines production, increased the reactive oxygen species (ROS) sinthesys as well as the expression and presence of iNOS enzyme, but not nitric oxide production. Conclusion: Based on the data obtained, it was possible to infer that Con-A induces the ROS production, responsible for eliminating parasites in addition to regulatory cytokines synthesis which are important for disease resolution.
Keyphrases
- reactive oxygen species
- nitric oxide
- endothelial cells
- cell death
- dna damage
- oxidative stress
- anti inflammatory
- poor prognosis
- induced pluripotent stem cells
- induced apoptosis
- rheumatoid arthritis
- immune response
- transcription factor
- type diabetes
- plasmodium falciparum
- early onset
- hydrogen peroxide
- pluripotent stem cells
- big data
- electronic health record
- machine learning
- adipose tissue
- binding protein
- combination therapy
- endoplasmic reticulum stress
- drug induced