Biology subjects

Testa, C.

Publications and source records attributed to Testa, C..

8 recordsLinked to original sources

bioRxiv2025

FREQ-NESS reveals age-related differences in frequency-resolved brain networks during auditory recognition and resting state

Understanding how brain networks operate across different frequencies during cognitive tasks, and how these dynamics change with age, remains a central challenge in cognitive neuroscience. While previous studies have focused on resting-state activity and passive listening, less is known about frequency-specific brain dynamics during event-related tasks that require active memory engagement. In this study, we extend the recently developed FREQ-NESS analytical pipeline by adapting it to event-related task and resting state source-reconstructed magnetoencephalography (MEG) data from 70 healthy participants. This method quantified the variance explained by frequency-specific brain networks, their spatial organization, and associated time-resolved power estimates. We found significant effects of age, condition, and their interaction in the variance explained by leading components at 1.07 Hz, 2.86 Hz, and 10.00 Hz. Younger adults exhibited stronger peaks at 1.07 and 2.86 Hz during the task and a more pronounced 10.00 Hz peak at rest, whereas older adults showed the opposite pattern. Time-frequency analysis revealed age- and condition-dependent desynchronization in the alpha and beta bands (7.10-22.90 Hz). These findings demonstrate the effectiveness of the adapted FREQ-NESS pipeline for event-related tasks and highlight the importance of frequency-resolved network analysis for characterizing age-related changes in active auditory memory processing.

neuroscience↗

bioRxiv2024

BROADband brain Network Estimation via Source Separation (BROAD-NESS)

Auditory memory enables the recognition of sound sequences by integrating sensory input with memory traces and predictive mechanisms. While predictive coding has been proposed as a key framework for this process, the large-scale brain networks supporting it remain poorly understood. Using BROADband brain Network Estimation via Source Separation (BROAD-NESS), we provide three fundamental insights into the neural organisation of auditory memory and predictive coding. First, auditory cortices participate in two distinct, orthogonal whole-brain networks, expanding on the conventional view focused on forward and backward information flow between single brain regions. One network involves the medial cingulate gyrus, while the other integrates prefrontal and hippocampal regions, inferior temporal cortex, and insula. Second, we present evidence for a dual-stream mechanism in auditory memory recognition, which both parallels and diverges from the well-established dual-stream hypothesis in vision. Third, predictive coding in conscious auditory memory is supported by large-scale networks generating confirmed predictions and prediction errors. While previous studies examined predictive coding in isolated regions or pairwise connections, our findings reveal how whole-brain networks coordinate these processes, highlighting fine-grained spatial gradients and distinct temporal dynamics. These findings enhance our understanding of auditory perception, memory, and prediction, as well as their underlying basis in whole-brain dynamical networks.

neuroscience↗

bioRxiv2024

A network based study of the dynamics of Aβ and {tau} proteins in Alzheimer's disease

Due to the extreme complexity of Alzheimers disease (AD), the aetiology of which is not yet known, nor are there any known effective treatments, mathematical modelling can be very useful. Indeed, mathematical models, if deemed reliable, can be used to test medical hypotheses that could be difficult to verify directly. In this context, it is important to understand how A{beta} and{tau} proteins, which in abnormal aggregate conformations are hallmarks of the disease, interact and spread. We are particularly interested in this paper in studying the spreading of misfolded{tau} . To this end, we present four different mathematical models, all on networks on which the protein evolves. The models differ in both the choice of network and diffusion operator. Through comparison with clinical data on{tau} concentration, that we carefully obtained with multimodal analysis techniques, we show that some models are more adequate than others to simulate the dynamics of the protein. This type of study may suggest that, when it comes to modelling certain pathologies, the choice of the mathematical setting must be made with great care if comparison with clinical data is considered decisive.

neuroscience↗

bioRxiv2024

The molecular basis of the anticancer effect of statins

Statins, one of the most used class of cardiovascular drugs with the primary function of reducing blood cholesterol levels, exert their effect by inhibiting the enzyme HMG-CoA reductase, the key player in cholesterol biosynthesis. While the primary indication for statins is the prevention of cardiovascular diseases, there has been growing interest in their potential anticancer effects. However, the current evidence on these effects is largely based on epidemiological observations and preclinical research, not yet substantiated by knowledge of the mechanisms behind it. Here we show that statins have an anticancer effect as they exploit the principle of Synthetic Lethality, a concept in which the combination of two non-lethal genetic or molecular events results in cell death or impairment. When either of these events occurs alone, it is not lethal, but when they happen coupled, they create a lethal condition for the cell. In this work we report that statins emerged from a computational data analysis that we performed on approximately 37,000 synthetic lethality couples. We performed this analysis to select repurposable drugs that could target genes involved in Synthetic Lethality couples with metastatic genes. We validated our discovery in vitro by drug tests performed on cell lines derived from cancers of the breast, ovary, and cervix. Our data-driven drug repurposing strategy allowed us to understand the molecular basis of the anticancer effect of statins, a discovery which can be directly translated into practical clinical applications in oncology.

cancer biology↗

bioRxiv2023

An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution

ImportanceDNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. ObjectiveOur study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. DesignA series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). SettingMBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. ParticipantsTwo population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). ExposuresEight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcomeGenome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. ResultsWe observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and RelevanceOverall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities. Key pointsO_ST_ABSQuestionC_ST_ABSCould DNAm be a mechanism by which adversity becomes embodied? FindingsTraffic-related air pollution exposure may induce epigenetic changes related to inflammatory processes and there are suggestive associations with measures of structural racism MeaningDNAm may be a biological mechanism through which structural racism and air pollution become biologically embodied

bioinformatics↗

bioRxiv2021

The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip

BackgroundDNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilising precious or limited DNA sources. Materials and methodsWe use a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip. ResultsData are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; however samples with a total input as low as 40ng pass standard quality control tests, and we observe little evidence that low input DNA obscures the associations between DNAm and two phenotypes, age and smoking status. ConclusionsDNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.

bioinformatics↗

bioRxiv2021

A Non-Negative Matrix Tri-Factorization based Method for Predicting Antitumor Drug Sensitivity

Large annotated cell line collections have been proven to enable the prediction of drug response in the preclinical setting. We present an enhancement of Non-Negative Matrix Tri-Factorization method, which allows the integration of different data types for the prediction of missing associations. To test our method we retrieved a dataset from CCLE, containing the connections among cell lines and drugs by means of their IC50 values. We performed two different kind of experiments: a) prediction of missing values in the matrix, b) prediction of the complete drug profile of a new cell line, demonstrating the validity of the method in both scenarios.

bioinformatics↗

bioRxiv2020

Melanopsin retinal ganglion cell-driven contribution to visual and cognitive brain responses in LHON

Melanopsin retinal ganglion cells (mRGCs) are intrinsically photosensitive photoreceptors contributing to visual and non-image-forming functions of the eye. Isolating mRGC roles in humans is challenging, therefore mRGCs functions remains to be fully characterized. We explored mRGCs contribution to light-driven visual and cognitive brain responses in Lebers Hereditary Optic Neuropathy (LHON), given mRGC relative sparing in LHON. Twelve patients and twelve matched healthy controls (HC) participated in an fMRI protocol including visual and visual-cognitive paradigms under blue (480nm) and red light (620nm). Higher occipital activation was found in response to sustained blue vs. red stimulation in LHON vs. HC. Similarly, brain responses to the executive task were larger under blue vs. red light in LHON over lateral prefrontal cortex. These findings are in line with LHON mRGCs relative sparing and support mRGCs contribution to non-visual and visual functions in humans, with potential implication for visual rehabilitation in optic neuropathy patients.

neuroscience↗