Biology subjects

Nieto, N.

Publications and source records attributed to Nieto, N..

4 recordsLinked to original sources

bioRxiv2024

Voxel-wise or Region-wise Nuisance Regression for Functional Connectivity Analyses: Does it matter?

Removal of nuisance signals (such as motion) from the BOLD time series is an important aspect of preprocessing to obtain meaningful resting-state functional connectivity (rs-FC). The nuisance signals are commonly removed using denoising procedures at the finest resolution, i.e. the voxel time series. Typically the voxel-wise time series are then aggregated into predefined regions or parcels to obtain a rs-FC matrix as the correlation between pairs of regional time series. Computational efficiency can be improved by denoising the aggregated regional time series instead of the voxel time series. However, a comprehensive comparison of the effects of denoising on these two resolutions is missing. In this study, we systematically investigate the effects of denoising at different time series resolutions (voxel- and region-level) in 370 unrelated subjects from the HCP-YA dataset. Alongside the time series resolution, we considered additional factors such as aggregation method (Mean and first eigenvariate [EV]) and parcellation granularity (100, 400, and 1,000 regions). To assess the effect of those choices on the utility of the resulting whole-brain rs-FC, we evaluated the individual specificity (fingerprinting) and the capacity to predict age and three cognitive scores. Our findings show generally equal or better performance for region-level denoising with notable differences depending on the aggregation method. Using mean aggregation yielded equal individual specificity and prediction performance for voxel- and region-level denoising. When EV was employed for aggregation, the individual specificity of voxel-level denoising was reduced compared to region-level denoising. Increasing parcellation granularity generally improved individual specificity. For the prediction of age and cognitive test scores, only fluid intelligence indicated worse performance for voxel-level denoising in the case of aggregating with the EV. Based on these results, we recommend the adoption of region-level denoising for brain-behavior investigations when using mean aggregation. This approach offers equal individual specificity and prediction capacity with reduced computational resources for the analysis of rs-FC patterns.

neuroscience↗

bioRxiv2022

Promising Antimalarials targeting Apicoplast DNA Polymerase from Plasmodium falciparum

Malaria is caused by the parasite Plasmodium falciparum, which contains an essential non-photosynthetic plastid called the apicoplast. A single DNA polymerase, apPOL, is targeted to the apicoplast, where it replicates and repairs the genome. apPOL has no direct orthologs in mammals and is considered a promising drug target for the treatment and/or prevention of malaria. We previously reported screening the Malaria Box to identify MMV666123 as an inhibitor of apPOL. Herein we extend our studies and report structure-activity relationships for MMV666123 and identify key structural motifs necessary for inhibition. Although attempts to crystallize apPOL with the inhibitor were not fruitful, kinetic analysis and crystal structure determinations of WT and mutant apo-enzymes, facilitated model building and provided insights into the putative inhibitor binding site. Our results validate apPOL as an antimalarial target and provide an avenue for the design of high potency, specific inhibitors of apPOL and other A-family DNA polymerases.

biochemistry↗

bioRxiv2022

Discovery of small molecule inhibitors of Plasmodium falciparum apicoplast DNA polymerase

Malaria is caused by infection with protozoan parasites of the Plasmodium genus, which is part of the phylum Apicomplexa. Most organisms in this phylum contain a relic plastid called the apicoplast. The apicoplast genome is replicated by a single DNA polymerase (apPOL), which is an attractive target for anti-malarial drugs. We screened small-molecule libraries (206,504 compounds) using a fluorescence-based high-throughput DNA polymerase assay. Dose/response analysis and counter-screening identified 186 specific apPOL inhibitors. Toxicity screening against human HepaRG human cells removed 84 compounds and the remaining were subjected to parasite killing assays using chloroquine resistant P. falciparum parasites. Nine compounds were potent inhibitors of parasite growth and may serve as lead compounds in efforts to discover novel malaria drugs.

biochemistry↗

bioRxiv2021

"Thinking out loud": an open-access EEG-based BCI dataset for inner speech recognition

Surface electroencephalography is a standard and noninvasive way to measure electrical brain activity. Recent advances in artificial intelligence led to significant improvements in the automatic detection of brain patterns, allowing increasingly faster, more reliable and accessible Brain-Computer Interfaces. Different paradigms have been used to enable the human-machine interaction and the last few years have broad a mark increase in the interest for interpreting and characterizing the "inner voice" phenomenon. This paradigm, called inner speech, raises the possibility of executing an order just by thinking about it, allowing a "natural" way of controlling external devices. Unfortunately, the lack of publicly available electroencephalography datasets, restricts the development of new techniques for inner speech recognition. A ten-subjects dataset acquired under this and two others related paradigms, obtained with an acquisition system of 136 channels, is presented. The main purpose of this work is to provide the scientific community with an open-access multiclass electroencephalography database of inner speech commands that could be used for better understanding of the related brain mechanisms.

neuroscience↗