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Biology subjects

Magri, C.

Publications and source records attributed to Magri, C..

3 recordsLinked to original sources

The contribution of object size, manipulability, and stability on neural responses to inanimate objects

In human occipitotemporal cortex, brain responses to depicted inanimate objects have a large-scale organization by real-world object size. Critically, the size of objects in the world is systematically related to behaviorally-relevant properties: small objects are often grasped and manipulated (e.g., forks), while large objects tend to be less motor-relevant (e.g., tables), though this relationship does not always have to be true (e.g., picture frames and wheelbarrows). To determine how these two dimensions interact, we measured brain activity with functional magnetic resonance imaging while participants viewed a stimulus set of small and large objects with either low or high motor-relevance. The results revealed that the size organization was evident for objects with both low and high motor-relevance; further, a motor-relevance map was also evident across both large and small objects. Targeted contrasts revealed that typical combinations (small motor-relevant vs. large non-motor-relevant) yielded more robust topographies than the atypical covariance contrast (small non-motor-relevant vs. large motor-relevant). In subsequent exploratory analyses, a factor analysis revealed that the construct of motor-relevance was better explained by two underlying factors: one more related to manipulability, and the other to whether an object moves or is stable. The factor related to manipulability better explained responses in lateral small-object preferring regions, while the factor related to object stability (lack of movement) better explained responses in ventromedial large-object preferring regions. Taken together, these results reveal that the structure of neural responses to objects of different sizes further reflect behavior-relevant properties of manipulability and stability, and contribute to a deeper understanding of some of the factors that help the large-scale organization of object representation in high-level visual cortex. Highlights- Examined the relationship between real-world size and motor-relevant properties in the structure of responses to inanimate objects. - Large scale topography was more robust for contrast that followed natural covariance of small motor-relevant vs. large non-motor-relevant, over contrast that went against natural covariance. - Factor analysis revealed that manipulability and stability were, respectively, better explanatory predictors of responses in small- and large-object regions.

neuroscience↗

Investigating an in-silico approach for prioritizing antidepressant drug prescription based on drug-induced expression profiles and predicted gene expression

In clinical practice, antidepressant prescription is a trial and error approach, which is time consuming and discomforting for patients. This study investigated an in-silico approach for ranking antidepressants based on their hypothetical likelihood of efficacy. We determined the transcriptomic profile of citalopram remitters by performing a transcriptomic-wide association study on STAR*D data (N =1163). The transcriptional profile of remitters was compared with 21 antidepressant-induced gene expression profiles in five human cell lines available in the connectivity map database. Spearman correlation, Pearson correlation, and the Kolmogorov Smirnov test were used to determine the similarity between antidepressant-induced profiles and remitter profiles, subsequently calculating the average rank of antidepressants across the three methods and a p-value for each rank by using a permutation procedure. The drugs with the top ranks were those having high positive correlation with the expression profiles of remitters and they may have higher chances of efficacy in the tested patients. In MCF7 (breast cancer cell line), escitalopram had the highest average rank, with an average rank higher than expected by chance (p=0.0014). In A375 (human melanoma) and PC3 (prostate cancer) cell lines, escitalopram and citalopram emerged as the second highest ranked antidepressants, respectively (p=0.0310 and 0.0276, respectively). In HA1E (kidney) and HT29 (colon cancer) cell types, citalopram and escitalopram did not fall among top antidepressants. The correlation between citalopram remitters and (es)citalopram-induced expression profiles in three cell lines suggests that our approach may be useful and with future improvements it can be applicable at the individual level to tailor treatment prescription.

bioinformatics↗

Genome-wide analysis of RNA editing levels in human blood identified interactions with mRNA processing genes and suggested correlations with biological and drug-related variables

BackgroundA-to-I RNA editing is a co-/post-transcriptional modification catalyzed by ADAR enzymes, that deaminates Adenosines (A) into Inosines (I). Most of known editing events are located within inverted ALU repeats, but they also occur in coding sequences and may alter the function of encoded proteins. RNA editing contributes to generate transcriptomic diversity and it is found altered in cancer, autoimmune and neurological disorders. Emerging evidences indicate that editing process could be influenced by genetic variations, biological and environmental variables.\n\nResultsWe analyzed RNA editing levels in human blood using RNA-seq data from 459 healthy individuals and identified 2,079 sites consistently edited in this tissue. As expected, analysis of gene expression revealed that ADAR is the major contributor to editing on these sites, explaining [~]13% of observed variability. After removing ADAR effect, we found significant associations for 1,122 genes, mainly involved in RNA processing. These genes were significantly enriched in genes encoding proteins interacting with ADARs, including 276 potential ADARs interactors and 9 ADARs direct partners. In addition, our analysis revealed several factors potentially influencing RNA editing in blood, including cell composition, age, Body Mass Index, smoke and alcohol consumption. Finally, we identified genetic loci associated with editing levels, including known ADAR eQTLs and a small region on chromosome 7, containing LOC730338, a lincRNA gene that appears to modulate ADARs mRNA expression.\n\nConclusionsOur data provides a detailed picture of the most relevant RNA editing events and their variability in human blood, giving interesting insights on potential mechanisms behind this post-transcriptional modification and its regulation in this tissue.

genomics↗