Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy

Detalhes bibliográficos
Autor(a) principal: Gonçalves, Rafaela de Sousa
Data de Publicação: 2020
Outros Autores: Alves de Pinho, Flaviane, Dinis-Oliveira, Ricardo Jorge, Azevedo, Rui, Gaifem, Joana, Farias Larangeira, Daniela, Ramos-Sanchez, Eduardo Milton, Goto, Hiro, Silvestre, Ricardo, Barrouin-Melo, Stella Maria
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/65507
Resumo: Prediction parameters of possible outcomes of canine leishmaniasis (CanL) therapy might help with therapeutic decisions and animal health care. Here, we aimed to develop a diagnostic method with predictive value by analyzing two groups of dogs with CanL, those that exhibited a decrease in parasite load upon antiparasitic treatment (group: responders) and those that maintained high parasite load despite the treatment (group: non-responders). The parameters analyzed were parasitic load determined by q-PCR, hemogram, serum biochemistry and immune system-related gene expression signature. A mathematical model was applied to the analysis of these parameters to predict how efficient their response to therapy would be. Responder dogs restored hematological and biochemical parameters to the reference values and exhibited a Th1 cell activation profile with a linear tendency to reach mild clinical alteration stages. Differently, non-responders developed a mixed Th1/Th2 response and exhibited markers of liver and kidney injury. Erythrocyte counts and serum phosphorus were identified as predictive markers of therapeutic response at an early period of assessment of CanL. The results presented in this study are highly encouraging and may represent a new paradigm for future assistance to clinicians to interfere precociously in the therapeutic approach, with a more precise definition in the patient’s prognosis.
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spelling Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapymathematical modeltreatmenthematological parametersbiochemical parametersLeishmaniaCiências Médicas::Ciências da SaúdeScience & TechnologyPrediction parameters of possible outcomes of canine leishmaniasis (CanL) therapy might help with therapeutic decisions and animal health care. Here, we aimed to develop a diagnostic method with predictive value by analyzing two groups of dogs with CanL, those that exhibited a decrease in parasite load upon antiparasitic treatment (group: responders) and those that maintained high parasite load despite the treatment (group: non-responders). The parameters analyzed were parasitic load determined by q-PCR, hemogram, serum biochemistry and immune system-related gene expression signature. A mathematical model was applied to the analysis of these parameters to predict how efficient their response to therapy would be. Responder dogs restored hematological and biochemical parameters to the reference values and exhibited a Th1 cell activation profile with a linear tendency to reach mild clinical alteration stages. Differently, non-responders developed a mixed Th1/Th2 response and exhibited markers of liver and kidney injury. Erythrocyte counts and serum phosphorus were identified as predictive markers of therapeutic response at an early period of assessment of CanL. The results presented in this study are highly encouraging and may represent a new paradigm for future assistance to clinicians to interfere precociously in the therapeutic approach, with a more precise definition in the patient’s prognosis.This work was funded by the Brazilian agencies Bahia Research Foundation—FAPESB (Grant nº PRONEM 498/2011-PNE 0002/2011 to S.M.B-M), National Council for Scientific and Technological Development —CNPq (PQ scholarship nº 307813/2018-5 to SMBM, and nº 303621/2015-0 to HG) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior —CAPES (PDSE scholarship nº 88881.189587/2018-01 to R.S.G; Finance Code 001 and PV scholarship nº 23066.033859/2018-73 to R.S.). This work was supported by grants from CESPU (TramTap-CESPU-2016, Chronic-TramTap_CESPU_2017 and TraTapMDMA-CESPU-2018), from the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013), funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and the Fundação para a Ciência e Tecnologia (FCT) (contract IF/00021/2014 to R.S.), Infect-Era (project INLEISH to R.S.) and Proyecto SNIP N◦ 292900 “Creación del Servicio de Laboratorio de Enfermedades Infecciosas y Parasitarias de Animales Domésticos de la Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas.Instituto de Investigación en Ganadería y Biotecnología-IGBI. Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas.Multidisciplinary Digital Publishing InstituteUniversidade do MinhoGonçalves, Rafaela de SousaAlves de Pinho, FlavianeDinis-Oliveira, Ricardo JorgeAzevedo, RuiGaifem, JoanaFarias Larangeira, DanielaRamos-Sanchez, Eduardo MiltonGoto, HiroSilvestre, RicardoBarrouin-Melo, Stella Maria2020-05-152020-05-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/65507engde Sousa Gonçalves, R.; Alves de Pinho, F.; Dinis-Oliveira, R.J.; Azevedo, R.; Gaifem, J.; Farias Larangeira, D.; Ramos-Sanchez, E.M.; Goto, H.; Silvestre, R.; Barrouin-Melo, S.M. Mathematical Modelling Using Predictive Biomarkers for the Outcome of Canine Leishmaniasis upon Chemotherapy. Microorganisms 2020, 8, 745.2076-260710.3390/microorganisms8050745https://www.mdpi.com/2076-2607/8/5/745info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:48:41Zoai:repositorium.sdum.uminho.pt:1822/65507Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:46:59.633796Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
title Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
spellingShingle Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
Gonçalves, Rafaela de Sousa
mathematical model
treatment
hematological parameters
biochemical parameters
Leishmania
Ciências Médicas::Ciências da Saúde
Science & Technology
title_short Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
title_full Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
title_fullStr Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
title_full_unstemmed Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
title_sort Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy
author Gonçalves, Rafaela de Sousa
author_facet Gonçalves, Rafaela de Sousa
Alves de Pinho, Flaviane
Dinis-Oliveira, Ricardo Jorge
Azevedo, Rui
Gaifem, Joana
Farias Larangeira, Daniela
Ramos-Sanchez, Eduardo Milton
Goto, Hiro
Silvestre, Ricardo
Barrouin-Melo, Stella Maria
author_role author
author2 Alves de Pinho, Flaviane
Dinis-Oliveira, Ricardo Jorge
Azevedo, Rui
Gaifem, Joana
Farias Larangeira, Daniela
Ramos-Sanchez, Eduardo Milton
Goto, Hiro
Silvestre, Ricardo
Barrouin-Melo, Stella Maria
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Gonçalves, Rafaela de Sousa
Alves de Pinho, Flaviane
Dinis-Oliveira, Ricardo Jorge
Azevedo, Rui
Gaifem, Joana
Farias Larangeira, Daniela
Ramos-Sanchez, Eduardo Milton
Goto, Hiro
Silvestre, Ricardo
Barrouin-Melo, Stella Maria
dc.subject.por.fl_str_mv mathematical model
treatment
hematological parameters
biochemical parameters
Leishmania
Ciências Médicas::Ciências da Saúde
Science & Technology
topic mathematical model
treatment
hematological parameters
biochemical parameters
Leishmania
Ciências Médicas::Ciências da Saúde
Science & Technology
description Prediction parameters of possible outcomes of canine leishmaniasis (CanL) therapy might help with therapeutic decisions and animal health care. Here, we aimed to develop a diagnostic method with predictive value by analyzing two groups of dogs with CanL, those that exhibited a decrease in parasite load upon antiparasitic treatment (group: responders) and those that maintained high parasite load despite the treatment (group: non-responders). The parameters analyzed were parasitic load determined by q-PCR, hemogram, serum biochemistry and immune system-related gene expression signature. A mathematical model was applied to the analysis of these parameters to predict how efficient their response to therapy would be. Responder dogs restored hematological and biochemical parameters to the reference values and exhibited a Th1 cell activation profile with a linear tendency to reach mild clinical alteration stages. Differently, non-responders developed a mixed Th1/Th2 response and exhibited markers of liver and kidney injury. Erythrocyte counts and serum phosphorus were identified as predictive markers of therapeutic response at an early period of assessment of CanL. The results presented in this study are highly encouraging and may represent a new paradigm for future assistance to clinicians to interfere precociously in the therapeutic approach, with a more precise definition in the patient’s prognosis.
publishDate 2020
dc.date.none.fl_str_mv 2020-05-15
2020-05-15T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/65507
url http://hdl.handle.net/1822/65507
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv de Sousa Gonçalves, R.; Alves de Pinho, F.; Dinis-Oliveira, R.J.; Azevedo, R.; Gaifem, J.; Farias Larangeira, D.; Ramos-Sanchez, E.M.; Goto, H.; Silvestre, R.; Barrouin-Melo, S.M. Mathematical Modelling Using Predictive Biomarkers for the Outcome of Canine Leishmaniasis upon Chemotherapy. Microorganisms 2020, 8, 745.
2076-2607
10.3390/microorganisms8050745
https://www.mdpi.com/2076-2607/8/5/745
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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