Biology subjects

Villarreal, C.

Publications and source records attributed to Villarreal, C..

7 recordsLinked to original sources

bioRxiv2022

Speaker-induced suppression in EEG during a naturalistic reading and listening task

Speaking elicits a suppressed neural response when compared to listening to others speech, a phenomenon known as speaker-induced suppression (SIS). Previous research has focused on investigating SIS at constrained levels of linguistic representation, such as the individual phoneme and word level. Here we present scalp EEG data from a dual speech perception and production task where participants read sentences aloud then listened to playback of themselves reading those sentences. Playback was separated into predictable repetition of the previous trial and unpredictable, randomized repetition of a former trial to investigate the role predictive processing plays in SIS. Concurrent EMG was recorded to control for movement artifact during speech production. In line with previous research, event-related potential analyses at the sentence level demonstrated suppression of early auditory components of the EEG for production compared to perception. To evaluate whether specific neural representations contribute to SIS (in contrast with a global gain change), we fit linear encoding models that predicted scalp EEG based on phonological features, EMG activity, and task condition. We found that phonological features were encoded similarly between production and perception. However, this similarity was only observed when controlling for movement by using the EMG response as an additional regressor. Our results suggest SIS is at the representational level a global gain change between perception and production, not the suppression of specific characteristics of the neural response. We also detail some important considerations when analyzing EEG during continuous speech production.

neuroscience↗

bioRxiv2021

FEATURE DETECTION TO SEGMENT CARDIOMYOCYTE NUCLEI FOR INVESTIGATING CARDIAC CONTRACTILITY

In vivo quantitative assessment of structural and functional biomarkers is essential for understanding pathophysiology and identifying novel therapies for congenital heart disorders. Cardiac defect analysis through fixed tissue and histology has offered revolutionary insights into the tissue architecture, but section thickness limits the tissue penetration. This study demonstrated the potential of Light Sheet Fluorescence Microscopy (LSFM) for analyzing in vivo 4D (3d + time) cardiac contractility. Furthermore, we have described the utility of an improved feature detection framework for localizing cardiomyocyte nuclei in the zebrafish atrium and ventricle. Using the Hessian Difference of Gaussian (HDoG) scale space in conjunction with the watershed algorithm, we were able to quantify a statistically significant increase in cardiomyocyte nuclei count across different developmental stages. Furthermore, we assessed individual volumes and surface areas for the cardiomyocyte nuclei in the ventricles innermost and outermost curvature during cardiac systole and diastole. Using the segmented nuclei volumes from the feature detection, we successfully performed local area ratio analysis to quantify the degree of deformation suffered by the outermost ventricular region compared to the innermost ventricular region. This paper focuses on the merits of our segmentation and demonstrates its efficacy for cell counting and morphology analysis in the presence of anisotropic illumination across the field-of-view (FOV).

bioengineering↗

bioRxiv2021

Generalizable EEG encoding models with naturalistic audiovisual stimuli

In natural conversations, listeners must attend to what others are saying while ignoring extraneous background sounds. Recent studies have used encoding models to predict electroencephalography (EEG) responses to speech in noise-free listening situations, sometimes referred to as "speech tracking" in EEG. Researchers have analyzed how speech tracking changes with different types of background noise. It is unclear, however, whether neural responses from noisy and naturalistic environments can be generalized to more controlled stimuli. If encoding models for noisy, naturalistic stimuli are generalizable to other tasks, this could aid in data collection from populations who may not tolerate listening to more controlled, less-engaging stimuli for long periods of time. We recorded non-invasive scalp EEG while participants listened to speech without noise and audiovisual speech stimuli containing overlapping speakers and background sounds. We fit multivariate temporal receptive field (mTRF) encoding models to predict EEG responses to pitch, the acoustic envelope, phonological features, and visual cues in both noise-free and noisy stimulus conditions. Our results suggested that neural responses to naturalistic stimuli were generalizable to more controlled data sets. EEG responses to speech in isolation were predicted accurately using phonological features alone, while responses to noisy speech were more accurate when including both phonological and acoustic features. These findings may inform basic science research on speech-in-noise processing. Ultimately, they may also provide insight into auditory processing in people who are hard of hearing, who use a combination of audio and visual cues to understand speech in the presence of noise. Significance StatementUnderstanding spoken language in natural environments requires listeners to parse acoustic and linguistic information in the presence of other distracting stimuli. However, most studies of auditory processing rely on highly controlled stimuli with no background noise, or with background noise inserted at specific times. Here, we compare models where EEG data are predicted based on a combination of acoustic, phonetic, and visual features in highly disparate stimuli - sentences from a speech corpus, and speech embedded within movie trailers. We show that modeling neural responses to highly noisy, audiovisual movies can uncover tuning for acoustic and phonetic information that generalizes to simpler stimuli typically used in sensory neuroscience experiments.

neuroscience↗

bioRxiv2020

Isolation and characterization of Streptomyces bacteriophages and Streptomyces strains encoding biosynthetic arsenals

The threat to public health posed by drug-resistant bacteria is rapidly increasing, as some of healthcares most potent antibiotics are becoming obsolete. Approximately two-thirds of the worlds antibiotics are derived from natural products produced by Streptomyces encoded biosynthetic gene clusters. Thus, in order to identify novel gene clusters, we sequenced the genomes of four bioactive Streptomyces strains isolated from the soil in San Diego County and used Bacterial Cytological Profiling adapted for agar plate culturing in order to examine the mechanisms of bacterial inhibition exhibited by these strains. In the four strains, we identified 101 biosynthetic gene clusters. Some of these clusters were predicted to produce previously studied antibiotics; however, the known mechanisms of these molecules could not fully account for the antibacterial activity exhibited by the strains, suggesting that novel clusters might encode antibiotics. When assessed for their ability to inhibit the growth of clinically isolated pathogens, three Streptomyces strains demonstrated activity against methicillin-resistant Staphylococcus aureus. Additionally, due to the utility of bacteriophages for genetically manipulating bacterial strains via transduction, we also isolated four new phages (BartholomewSD, IceWarrior, Shawty, and TrvxScott) against S. platensis. A genomic analysis of our phages revealed nearly 200 uncharacterized proteins, including a new site-specific serine integrase that could prove to be a useful genetic tool. Sequence analysis of the Streptomyces strains identified CRISPR-Cas systems and specific spacer sequences that allowed us to predict phage host ranges. Ultimately, this study identified Streptomyces strains with the potential to produce novel chemical matter as well as integrase-encoding phages that could potentially be used to manipulate these strains.

microbiology↗

bioRxiv2019

Dynamic regulation of immunity through post-translational control of defense transcript splicing

Survival of all living organisms requires the ability to detect attack and swiftly counter with protective immune responses. Despite considerable mechanistic advances, interconnectivity of signaling circuits often remains unclear. A newly-characterized protein, IMMUNOREGULATORY RNA-BINDING PROTEIN (IRR), negatively regulates immune responses in both maize and Arabidopsis, with disrupted function resulting in enhanced disease resistance. IRR physically interacts with, and promotes canonical splicing of, transcripts encoding defense signaling proteins, including the key negative regulator of pattern recognition receptor signaling complexes, CALCIUM-DEPENDENT PROTEIN KINASE 28 (CPK28). Upon immune activation by Plant Elicitor Peptides (Peps), IRR is dephosphorylated, disrupting interaction with CPK28 transcripts and resulting in accumulation of an alternative splice variant encoding a truncated CPK28 protein with impaired kinase activity and diminished function as a negative regulator. We demonstrate a novel circuit linking Pep-induced post-translational modification of IRR with post-transcriptionally-mediated attenuation of CPK28 function to dynamically amplify Pep signaling and immune output.\n\nOne Sentence SummaryPlant innate immunity is promoted by post-translational modification of a novel RNA-binding protein that regulates alternative splicing of transcripts encoding defense signaling proteins to dynamically increase immune receptor signaling capacity through deactivation of a key signal-buffering circuit.

plant biology↗

bioRxiv2019

Characterisation of type 2 diabetes progression with regulatory network

Type 2 diabetes develops due to beta cell exhaustion with accompanying decrease in insulin secretion, leading to hyperglycemia and eventual damage of nerve, kidney, and eye tissues. It is usually preceded by metabolic alterations related to insulin signaling, inflammatory pathways, or intracellular glucose processing, encompassed as metabolic syndrome. We propose a regulatory network for components of pancreatic-beta cells playing an essential role in the disease. The network interactions are expressed as continuous fuzzy logic propositions. The dynamical modeling of the network allows to portray the disease progression as a transit between steady states associated to health, metabolic syndrome, and diabetes, each state defined by specific expression patterns of the network components. Transitions between equilibrium states are due to altered expression or functional exhaustion associated to modifications of characteristic decay rates of cellular components. This approach let us identify functional modules that may eventually drive the transit from health to diabetes. The analysis reveals that underexpression of protein kinase B and X-box binding protein 1, with concomitant overexpression of lipopolysaccharides and thioredoxin interacting protein are key factors in the transition from health to disease.

systems biology↗

bioRxiv2017

A biophysical dynamic module for the polarisation of auxin efflux carriers PIN-FORMED (PIN)

Intracellular polarisation of auxin efflux carriers is crucial for understanding how auxin gradients form in plants. The polarisation dynamics of auxin efflux carriers PIN-FORMED (PIN) depends on both biomechanical forces as well as chemical, molecular and genetic factors. Biomechanical forces have shown to affect the localisation of PIN transporters to the plasma membrane. We proposed a biophysical module of PIN polarisation that integrates biomechanical, molecular, and cellular processes as well as their non-linear interactions. The module was implemented as a discrete Boolean model and then approximated to a continuous dynamic system, in order to explore the relative contribution of the factors mediating PIN polarisation at the scale of single cell. Our models recovered qualitative behaviours that have been experimentally observed and enabled us to postulate that, in the context of PIN polarisation, the effects of the mechanical forces can predominate over the activity of molecular factors such as the GTPase ROP6 and the CRIB-motif CRIB-motif RIC1.

plant biology↗