Biology subjects

Moro, A.

Publications and source records attributed to Moro, A..

10 recordsLinked to original sources

bioRxiv2026

golgi: an open-source graphical platform for image-to-recruitment modeling of peripheral nerve stimulation

Computational models of peripheral nerve stimulation--coupling finite-element bioelectric fields to biophysical axon models--have become essential for designing electrodes and waveforms for neuromodulation therapies. Yet the established open tools are code-first and assume substantial modeling expertise, and several depend on commercial finite-element solvers, placing realistic nerve modeling out of reach for many experimentalists and clinicians. We present golgi, an open-source platform that takes a peripheral nerve from image to stimulated fiber population through a single graphical interface, with an equivalent scriptable Python API and command-line interface for batch studies. golgi integrates the full pipeline: image segmentation (or import of surfaces or masks), automated multi-region tetrahedral meshing, anisotropic finite-element solution of the extracellular field with explicit perineurium contact impedance, generation of realistic fiber populations and their three-dimensional trajectories (straight, or curved via a quasi-static streamline solver), and biophysical activation thresholds through interchangeable NEURON and a GPU-accelerated surrogate backend. We demonstrate golgi on extruded multifascicular swine and human cervical vagus nerves and on real three-dimensional, branching human and rabbit vagus nerves reconstructed from micro-computed tomography. It reproduces the physiological fiber-diameter recruitment order, quantifies fascicular selectivity and current steering with a multi-contact cuff electrode, and resolves anatomically defined nerve branches. Using this branch resolution, we find that selectively engaging a vagal cardiac branch from a proximal cuff depends on anatomy. In the rabbit, whose cardiac fibers are predominantly small and whose superior cardiac branch forms a discrete, spatially segregated tract, current steering isolates even its small cardiac (B-type) fibers; in the human cervical vagus only the large myelinated fibers are separable, because the high thresholds of the small cardiac fibers force stimulus currents that also recruit off-target fibers. Every study can be exported as an integrity-hashed, self-contained bundle whose finite-element-to-recruitment provenance is verifiable byte-for-byte with a single command--a reproducibility guarantee absent from existing tools. By combining non-specialist usability, anatomical realism, and verifiable reproducibility in one open package, golgi lowers the barrier to in-silico peripheral nerve stimulation modeling. golgi is freely available as open-source software. Author summaryElectrical stimulation of peripheral nerves treats a growing range of conditions, from epilepsy to inflammatory and cardiovascular disease. Deciding where to place an electrode and how to shape the stimulus increasingly relies on computer models that combine the electric field around the electrode with detailed models of how individual nerve fibers respond. We found that existing software for this is powerful but primarily designed for expert modelers: it generally requires programming, substantial modeling expertise, and sometimes expensive commercial software, which can limit its adoption by experimentalists and clinicians. We built golgi to remove that barrier. With golgi, a user can go from a nerve image all the way to predicted fiber recruitment through a single point-and-click interface, while advanced users keep full scripting control. golgi builds anatomically realistic nerve models, simulates how different fiber types and fascicles are recruited, and lets users compare electrode designs. Using golgi, we also found that whether a small but clinically important nerve branch--such as the cardiac branch of the vagus nerve--can be selectively stimulated depends on its anatomy. In a rabbit nerve, where this branch forms a discrete, spatially separated bundle and its fibers are mostly small, even its small fibers can be targeted from a cuff on the main trunk; in the human, only the large fibers can be reached selectively, because the small cardiac fibers are harder to excite and the stronger currents needed to reach them also activate off-target fibers. Critically, every result can be packaged so that anyone else can verify it reproduces exactly--making peripheral nerve stimulation models easier to build, share, and trust.

bioengineering↗

bioRxiv2026

golgi: open-source software for automated nerve model generation and recruitment simulation

golgi is an open-source platform that takes a peripheral nerve from image to stimulated fiber population through a single graphical interface, with an equivalent scriptable Python API and command-line interface for batch and high-performance use. It integrates promptable image segmentation, automated multi-region tetrahedral meshing, anisotropic finite-element solution of the extracellular field with an explicit perineurium contact impedance, generation of realistic fiber populations and their three-dimensional trajectories, and biophysical activation thresholds through interchangeable backends-- NEURON (via PyFibers) and a GPU-accelerated surrogate (AxonML). Every study exports as an integrity-hashed bundle whose image-to-recruitment provenance is verifiable byte-for-byte. golgi lowers the barrier to in-silico peripheral nerve stimulation modeling for experimentalists and clinicians, using a fully open finite-element stack with no commercial dependencies.

bioengineering↗

bioRxiv2026

Optical flow reveals motility signatures for inferring pathogenic bacterial mixture compositions via temporal convolutional networks

With the rapid expansion of global food demand, aquaculture has become a critical pillar for future food security. However, aquaculture systems remain highly vulnerable to pathogenic bacteria, and rapid identification of antagonistic microbes is essential for sustainable disease control. Conventional evaluation approaches rely on fluorescence labeling or post-culture assays, limiting the ability to quantify dynamic interactions in mixed microbial populations in a real-time and label-free manner. Here, we propose a computational framework for classifying the mixing ratio of Vibrio harveyi and environmental bacteria using time-series motion features extracted from microscopy videos. We defined 24 interpretable motility descriptors and employed a Temporal Convolutional Network (TCN) to learn their temporal structure. The proposed method achieved a classification accuracy of 93.3%, outperforming conventional static statistical approaches and alternative machine learning models. These findings indicate that mixture discrimination in microbial communities is governed not by absolute motility magnitude, but by collective alignment and its temporal stability. Our study establishes a time-resolved computational framework for quantifying dynamic collective order in mixed microbial populations and highlights its potential for label-free automated screening and robotic microbiological applications. Author summaryBacterial infections pose a major threat to aquaculture, and rapid identification of antagonistic microbes is essential for sustainable disease management. Existing screening approaches often require fluorescent labeling or post-culture analysis, making real-time evaluation of mixed bacterial populations difficult. In this study, we show that mixture ratios of Vibrio harveyi and environmental bacteria can be accurately classified from time-series motion features extracted from microscopy videos. By applying TCN to 24 interpretable motility descriptors, we achieved high classification accuracy without relying on fluorescent markers. Our analysis demonstrates that collective directional alignment and its temporal stability, rather than absolute swimming speed, are the key determinants of mixture discrimination. This work introduces a computational strategy for quantifying dynamic collective order in microbial communities and supports the development of label-free, automated screening platforms for microbiological applications.

microbiology↗

bioRxiv2024

Brain and grammar: revealing electrophysiological basic structures with competing statistical models

Acoustic, lexical and syntactic information is simultaneously processed in the brain. Therefore, distinguishing the electrophysiological activity pertaining to these components requires complex and indirect strategies. Capitalizing on previous works which factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited EEG recordings and compared different surprisal models selectively involving lexical information, part of speech or syntactic structures in various combinations. EEG responses were recorded in 32 participants during listening to affirmative active declarative sentences and compared the activation corresponding to basic syntactic structures, such as noun phrases vs verb phrases. Lexical and syntactic processing activates different frequency bands, different time windows and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. Finally, we confirm previous measures obtained with intracortical recordings independently supporting the original hypothesis addressed here in a robust way.

neuroscience↗

bioRxiv2022

Event-related causality in Stereo-EEG discriminates syntactic processing of noun phrases and verb phrases

Syntax involves complex neurobiological mechanisms, which are difficult to disentangle for multiple reasons. Using a protocol able to separate syntactic information from sound information we investigated the neural causal connections evoked by the processing of homophonous phrases, either verb phrases (VP) or noun phrases (NP). We used event-related causality (ERC) from stereo-electroencephalographic (SEEG) recordings in 10 epileptic patients in multiple cortical areas, including language areas and their homologous in the non-dominant hemisphere. We identified the different networks involved in the processing of these syntactic operations (faster in the dominant hemisphere) showing that VPs engage a wider cortical network. We also present a proof-of-concept for the decoding of the syntactic category of a perceived phrase based on causality measures. Our findings help unravel the neural correlates of syntactic elaboration and show how a decoding based on multiple cortical areas could contribute to the development of speech prostheses for speech impairment mitigation.

neuroscience↗

bioRxiv2021

Distinct Hypoxia-induced Translational Profiles of Embryonic and Adult-derived Macrophages

Tissue homeostasis and repair are orchestrated by resident and newly recruited macrophages that alter their gene expression program in response to changes in tissue microenvironment. Embryonic macrophages, such as fetal liver derived macrophages (FLDM) seed the organs, including heart and lung during embryonic development and persist throughout the adult lifetime, while bone marrow-derived macrophages (BMDM) are recruited following an acute perturbation. Transcriptome analyses of FLDM and BMDM identified differences between them at the level of RNA expression, which correlates imperfectly with protein levels. Post-transcriptional regulation by microRNAs (miRNAs) and RNA-binding proteins determines mRNA stability and translation rate and may override transcriptional cues in response to environmental changes, such as hypoxia. To identify distinct features of FLDM and BMDM response to hypoxia at the level of translation, we employed translating ribosome affinity purification (TRAP) to isolate polysomal RNA. RNA-seq profiling of translated RNA identified distinct hypoxia-induced translational signature of BMDM (Ly6e, vimentin and glycolysis-associated enzymes Pgk1, Tpi1, Aldoa, Ldha) and FLDM (chemokines Ccl7 and Ccl2). By translational profiling of BMDM and FLDM with deletion of the RNA-binding protein HuR, we identified transcripts that were dependent on HuR. These findings highlight the importance of HuR and identify its distinct targets for post-transcriptional regulation of gene expression in embryonic vs. adult-derived macrophages.

cell biology↗

bioRxiv2020

A double negative post-transcriptional regulatory circuit mediates the virgin behavioral state

The survival and reproductive success of animals depends on the ability to harmonize their external behaviors with their internal states. For example, females conduct numerous social programs that are distinctive to virgins, compared to post-mated and/or pregnant individuals. In Drosophila, the fact that this post-mating switch is initiated by seminal factors implies that the default state is virgin. However, we recently showed that loss of miR-iab-4/8-mediated repression of the transcription factor Homothorax (Hth) within the abdominal ventral nerve cord (VNC) causes virgin females to execute mated behaviors. To elucidate new components of this post-transcriptional regulatory circuit, we used genomic analysis of mir-iab-4/8 deletion and hth-miRNA binding site mutants (hth[BSmut]) to elucidate doublesex (dsx) as a critical downstream factor. While Dsx has mostly been studied during sex-specific differentiation, its activities in neurons are little known. We find that accumulation of Dsx in the CNS is highly complementary to Hth, and downregulated in miRNA/hth[BSmut] mutants. Moreover, virgin behavior is highly dose-sensitive to developmental dsx function. Strikingly, depletion of Dsx in SAG-1 cells, a highly restricted set of abdominal neurons, abrogates female virgin conducts in favor of mated behavioral programs. Thus, a double negative post-transcriptional pathway in the VNC (miR-iab-4/8 -| Hth -| Dsx) specifies the virgin behavioral state.

neuroscience↗

bioRxiv2019

Disentangling sound from syntax: electrophysiological analysis of linguistics expressions

Syntax is a species-specific component of human language combining a finite set of words in a potentially infinite number of sentences. Since words are by definition expressed by sound, factoring out syntactic information is normally impossible. Here, we circumvented this problem in a novel way by designing phrases with exactly the same acoustic content but different syntactic structures depending on the other words they occur with. By performing stereo- electroencephalographic (SEEG) recordings in epileptic patients we measured a different electrophysiological correlate of verb phrases vs. noun phrases by analyzing the high gamma band activity (150-300Hz frequency), in multiple cortical areas in both hemispheres, including language areas and their homologous in the non-dominant hemisphere. Our findings contribute to the ultimate goal of a complete neural decoding of linguistic structures from the brain.

neuroscience↗

bioRxiv2019

Electrophysiological correlates of syntactic structures

Syntax is traditionally defined as a specifically human way to pair sound with meaning: words are assembled in a recursive way generating a potentially infinite set of sentences1,2. There can be different phrasal structures depending on the types of words involved, for example, \"noun phrases\" (NP), combining an article and a noun, vs. \"verb phrases\" (VP), combining a verb and a complement. Although it is known that the combination of an increasing number of words in sequences correlates with an increasing electrophysiological activity3,4, the specific electrophysiological correlates of the syntactic operation generating NPs vs. VPs remain unknown. A major confounding factor is the fact that syntactic information is inevitably intertwined with the acoustic information contained in words even during inner speech5. Here, we addressed this issue in a novel way by designing a paradigm to factor out acoustic information and isolate the syntactic component. In particular, we construed phrases that have exactly the same acoustic content but that are interpreted as NPs or VPs depending on their syntactic context (homophonous phrases). By performing stereo-electro-encephalographic (SEEG) recordings in epileptic patients6 we show that VPs are associated with a higher activity in the high gamma band (150-300Hz frequency), an index of cortical activity associated with linguistic processing, with respect to NPs in multiple cortical areas in both hemispheres, including language areas and their homologous in the non-dominant hemisphere. Our findings pave the way to a deeper understanding of the electrophysiological mechanisms underlying syntax and contribute to the ultimate far reaching goal of a complete neural decoding of linguistic structures from the brain2.

neuroscience↗

bioRxiv2018

microRNA-dependent regulation of biomechanical genes establishes tissue stiffness homeostasis

The mechanical properties of tissues, which are determined primarily by their extracellular matrix (ECM), are largely stable over time despite continual turnover of ECM constituents 1,2. These observations imply active homeostasis, where cells sense and adjust rates of matrix synthesis, assembly and degradation to keep matrix and tissue properties within the optimal range. However, the regulatory pathways that mediate this process are essentially unknown3. Genome-wide analyses of endothelial cells revealed abundant microRNA-mediated regulation of cytoskeletal, adhesive and extracellular matrix (CAM) mRNAs. High-throughput assays showed co-transcriptional regulation of microRNA and CAM genes on stiff substrates, which buffers CAM expression. Disruption of global or individual microRNA-dependent suppression of CAM genes induced hyper-adhesive, hyper-contractile phenotypes in multiple systems in vitro, and increased tissue stiffness in the zebrafish fin-fold during homeostasis and regeneration in vivo. Thus, a network of microRNAs and CAM mRNAs mediate tissue mechanical homeostasis.

cell biology↗