Dataset Information

Human liver LC-MSMSProteomic research on new urinary biomarkers of renal disease in canine leishmaniosis: survival and monitoring response to treatment

ABSTRACT: The objective of our study was to search for survival biomarkers (SB) and treatment response monitoring biomarkers (TRMB) in the urinary proteome of dogs with renal disease secondardy to canine leishmaniosis (CanL),

INSTRUMENT(S): 6550A iFunnel Q-TOF LC/MS

ORGANISM(S): Canis Familiaris (dog) (canis Lupus Familiaris)

TISSUE(S): Urine

DISEASE(S): Leishmaniasis

SUBMITTER: FERNANDO JUAN PEÑA VEGA

LAB HEAD: Javier Duque

PROVIDER: PXD042578 | Pride | 2023-07-20

REPOSITORIES: Pride

ACCESS DATA

Publications

Proteomic research on new urinary biomarkers of renal disease in canine leishmaniosis: Survival and monitoring response to treatment.

González Mario A MA Barrera-Chacón Rafael R Peña Fernando J FJ Belinchón-Lorenzo Silvia S Robles Nicolás R NR Pérez-Merino Eva M EM Martín-Cano Francisco E FE Duque Francisco J FJ

Research in veterinary science 20230622

The objective of our study was to search for survival biomarkers (SB) and treatment response monitoring biomarkers (TRMB) in the urinary proteome of dogs with renal disease secondary to canine leishmaniosis (CanL), using UHPLC-MS/MS. The proteomic data are available via ProteomeXchange with identifier PXD042578. Initially, a group of 12 dogs was evaluated and divided into survivors (SG; n = 6) and nonsurvivors (NSG; n = 6). A total of 972 proteins were obtained from the evaluated samples. Then, ...[more]

PMID: 37419051

Similar Datasets

Project description:Adverse outcome pathways (AOP) contain summarizing sequences of key events (KE) relating toxicant exposures to specific adverse outcomes (AO) observed in exposed populations. Quantitative AOPs (qAOP) provide frameworks to assess AO risks based on KE quantification and the modeling of their relationships. This work aimed to develop the quantitative component of AOP 411 <Oxidative stress leading to decreased lung function>. To examine the pertinence of the resulting qAOP-based risk assessment approach, we applied it to predict the medium-term lung function evolution after switching from combustible cigarettes (CC) to heated tobacco products (HTP). We used publicly available data for oxidative stress (in vitro), ciliary beating frequency (in vitro), mucociliary clearance (human), and lung function (human). Following the course of smoking-related lung function decline (Fletcher and Peto, 1977, PMID 871704), we assumed a non-monotonic time evolution where the risk of the AO <decreased lung function> begins to decline after quitting smoking CC or switching to HTP use. Consequently, we designed our qAOP to evaluate the relative reduction (RR) of AO risk for HTP switching compared to the two scenarios of continuing or quitting CC consumption. We developed both data- and physiology-based KE relationship (KER) models. Despite sparse data with respect to dose- and time-response relationships, we successfully connected the measured KEs through in silico KER models. We then used the resulting qAOP to evaluate the exposure effects of switching from CC smoking to HTP use along AOP 411. This approach enabled in silico prediction of the AO RR for which in vivo data were not yet available. In summary, our qAOP provides a multiscale mechanistic approach to evaluate medium-term lung function evolution for the use case of switching from CC smoking to HTP use. The presented approach demonstrates how 21st Century Toxicology principles such as in vitro testing and in silico predictions can be integrated to achieve a meaningful risk assessment approach. It also represents a starting point for integrating additional AOP into an extended AOP network that includes other mechanisms leading to decreased lung function.

Dataset Information

Human liver LC-MSMSProteomic research on new urinary biomarkers of renal disease in canine leishmaniosis: survival and monitoring response to treatment

Publications

Proteomic research on new urinary biomarkers of renal disease in canine leishmaniosis: Survival and monitoring response to treatment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure