Biology subjects

Davila, A.

Publications and source records attributed to Davila, A..

7 recordsLinked to original sources

bioRxiv2026

An integrated synthetic biology and robotics approach for neutralising landmines in post-war communities

Unexploded ordnances (UX.Os) and landmines endanger lives and hinder the economic progress of communities living in post-conflict zones. Currently, the primary method for clearing UX.Os relies on metal detection and manual removal of UX.Os - an expensive, time-consuming, and hazardous process. This study, derived from the 2024 EPFL iGEM project SYNPLODE, presents a new approach that integrates synthetic biology and aerial drone robotics, proposing a novel, end-to-end, safe, and efficient solution to address UX.Os. Starting from bacteria engineered to detect and degrade 2,4,6-trinitrotoluene (TNT), a common explosive in landmines, our solution is designed for three main tasks: detecting TNT and RDX, breaking these compounds down into non-explosive byproducts, and confirming explosive neutralisation. To deploy this solution safely in UXO-contaminated areas, we designed, built, and tested an aerial drone capable of spraying explosive-degrading bacteria. Combining synthetic biology, robotics, mathematical modelling, and affected community engagement, our solution aims to improve UXO and landmine clearance by offering a scalable and cost-effective approach for deactivating UX.Os without risking human lives.

synthetic biology↗

bioRxiv2024

Assessing neuronal correlates of salience and their adaptability with naturalistic textures in macaque V1 and V2

Salience is critical to vision. It allows stimuli that are different from their surroundings to pop out, drawing our attention. Perceptual salience is postulated to be encoded via a saliency map, based on differences in neuronal responsivity to simple image features at different spatial locations. Simple image features such as luminance, orientation and color are known to affect saliency and many of these features are encoded in primary visual cortex (V1), which several influential theories propose instantiate a saliency map. However, the degree to which more complex image features can determine salience, and whether there are neural correlates of salience which are computed outside of V1, remains unclear. Here we use displays of naturalistic textures to test for neural correlates of salience--termed pop-out responses--in V1 and area V2 of anesthetized macaque monkeys. Sensitivity to higher-order texture statistics arises in V2, so pop-out responses for these displays, if they exist, would be expected to be computed after V1. We presented displays in which a target texture, presented within the neuronal receptive field, was surrounded by distractors. Distractors could differ from the target texture in either higher-order texture statistics only, or in both lower- and higher-order statistics. We found little evidence for pop-out signals in either V1 or V2, for either display type. However, brief periods of adaptation could induce pop-out responses in V2. This suggests that adaptation might define which features of the environment are most salient, even if those features would otherwise not evoke pop-out responses. Significance statementWe tested for neuronal correlates of salience--termed pop-out responses--using displays with multiple patches of naturalistic textures, whose higher-order statistics are encoded by neurons outside primary visual cortex. We found little evidence for pop-out responses in V1 or V2. However, brief periods of adaptation could induce pop-out responses in V2. Our results indicate that the computations that define bottom-up attention (i.e., salience) are malleable and continuously updated by our stimulus history.

neuroscience↗

bioRxiv2023

Adaptation with naturalistic textures in macaque V1 and V2

Adaptation affects neuronal responsivity and selectivity throughout the visual hierarchy. However, because most prior studies have tailored stimuli to a single brain area of interest, we have a poor understanding of how exposure to a particular image alters responsivity and tuning at different stages of visual processing. Here we assess how adaptation with naturalistic textures alters neuronal responsivity and selectivity in primary visual cortex (V1) and area V2 of macaque monkeys. Neurons in both areas respond to textures, but V2 neurons are sensitive to high-order statistics which do not strongly modulate V1 responsivity. We tested the specificity of adaptation in each area with textures and spectrally-matched noise stimuli. Adaptation reduced responsivity in both V1 and V2, but only in V2 was the reduction dependent on the presence of higher-order texture statistics. Despite this specificity, the texture information provided by single neurons and populations was reduced after adaptation, in both V1 and V2. Our results suggest that adaptation effects for a given feature are induced at the stage of processing that tuning for those features first arises and that stimulus-specific adaptation effects need not result in improved sensory coding. Significance statementNearly all sensory neurons adapt to recent input. However, how the adjustment triggered by a particular input is distributed across brain areas and how these changes contribute to sensory processing are poorly understood. Here we explore adaptation with naturalistic textures, for which neurons in primary visual cortex and area V2 have differing selectivity. Adaptation reduced responsivity in both areas, but the effects in V2 alone depended on the presence of the higher-level texture statistics to which V2 neurons are sensitive. Though prior work with simpler stimuli has argued that stimulus-specific adaptation improves visual encoding, we found adaptation reduced texture information. Thus, adaptation need not improve visual encoding, suggesting its effects may serve some other purpose.

neuroscience↗

bioRxiv2022

Improved antibody-specific epitope prediction using AlphaFold and AbAdapt

Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody-antigen specific features for epitope prediction. In this study, we assess the impact of integrating the state-of-the-art protein modeling method AlphaFold with the AbAdapt pipeline and demonstrate significant improvement in the prediction of antibody-specific epitope residues.

bioinformatics↗

bioRxiv2022

Adaptations of endolithic communities to abrupt environmental changes in a hyper-arid desert

The adaptation mechanisms of microbial communities to natural perturbations remain relatively unexplored, particularly in extreme environments. The extremophilic communities of halite (NaCl) nodules from the hyper-arid core of the Atacama Desert are self-sustained and represent a unique opportunity to study functional adaptations and community dynamics with changing environmental conditions. We transplanted halite nodules to different sites in the desert and investigated how their taxonomic, cellular, and biochemical changes correlated with water availability, using environmental data modeling and metagenomic analyses. Salt-in strategists, mainly represented by haloarchaea, significantly increased in relative abundance at sites characterized by extreme dryness, multiple wet/dry cycles, and colder conditions. The functional analysis of metagenome-assembled genomes (MAGs) revealed site-specific enrichments in archaeal MAGs encoding for the uptake of various compatible solutes and for glycerol utilization. These findings suggest that opportunistic salt-in strategists took over the halite communities at the driest sites. They most likely benefited from metabolites newly released in the environment by the death of microorganisms least adapted to the new conditions. The observed changes were consistent with the need to maximize cellular bioenergetics when confronted with lower water availability and higher salinity, providing valuable information on microbial community adaptations and resilience to climate change.

microbiology↗

bioRxiv2020

Neuronal variability reflects probabilistic inference tuned to natural image statistics

Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike-count variance and mean, and the modulation of V1 activity and variability by spatial context in images. Our results show that the properties of a basic aspect of cortical responses -- their variability -- can be explained by a probabilistic representation tuned to naturalistic inputs.

neuroscience↗

bioRxiv2018

Response of extremophile microbiome to a rare rainfall reveals a two-step adaptation mechanism

Understanding the mechanisms underlying microbial resistance and resilience to perturbations is essential to predict the impact of climate change on Earths ecosystems. However, the resilience and adaptation mechanisms of microbial communities to natural perturbations remain relatively unexplored, particularly in extreme environments. The response of an extremophile community inhabiting halite (salt rocks) in the Atacama Desert to a catastrophic rainfall provided the opportunity to characterize and de-convolute the temporal response of a highly specialized community to a major disturbance. With shotgun metagenomic sequencing, we investigated the halite microbiome taxonomic composition and functional potential over a 4-year longitudinal study, uncovering the dynamics of the initial response and of the recovery of the community after a rainfall event. The observed changes can be recapitulated by two general modes of community shifts - a rapid Type 1 shift and a more gradual Type 2 adjustment. In the initial response, the community entered an unstable intermediate state after stochastic niche re-colonization, resulting in broad predicted protein adaptations to increased water availability. In contrast, during recovery, the community returned to its former functional potential by a gradual shift in abundances of the newly acquired taxa. The general characterization and proposed quantitation of these two modes of community response could potentially be applied to other ecosystems, providing a theoretical framework for prediction of taxonomic and functional flux following environmental changes.

microbiology↗