Biology subjects

Denis, J.

Publications and source records attributed to Denis, J..

6 recordsLinked to original sources

bioRxiv2026

XPO1 controls VDR localization and activity in triple-negative breast cancer cells

The association of cytoplasmic localization of VDR in TNBC tumors and disease aggressivity prompted investigation of its regulation by XPO1. In TNBC cell lines, the XPO1 inhibitors selinexor and eltanexor increased nuclear VDR localization. Their effects were particularly strong when combined with vitamin D treatment. Similarly, XPO1 knockdown increased nuclear VDR levels, both alone and in combination with vitamin D. These results identify XPO1 as an important regulator of VDR subcellular distribution. XPO1 inhibition also enhanced vitamin D-dependent VDR transcriptional activity. Indeed, selinexor, eltanexor, and XPO1 silencing increased vitamin D-dependent CYP24A1 reporter activity and the expression of genes such as CYP24A1 or CDH1. RNA sequencing showed that XPO1 modulation markedly reshaped the vitamin D transcriptional response. The affected genes were mainly involved in metabolism, cell-cycle regulation, protein localization, and cellular organization. Functional analyses demonstrated that cytoplasmic VDR promoted TNBC cell proliferation. Conversely, nuclear VDR was required for the antiproliferative effects of vitamin D. Accordingly, XPO1 inhibition or depletion potentiated vitamin D-mediated growth suppression. This finding suggested functional cooperation between XPO1-dependent export and VDR activity. Finally, high VDR expression was associated with poor disease-free or overall survival only in tumors with high XPO1 expression. Overall, XPO1 negatively regulates VDR nuclear localization and vitamin D responsiveness in TNBC. Targeting XPO1 may therefore enhance the therapeutic potential of vitamin D-based strategies in TNBC.

cell biology↗

bioRxiv2026

CICADA: A unified framework for NWB-based neurophysiological data analysis

Neurophysiology datasets are becoming increasingly complex, combining behavioral measurements with high-dimensional neuronal activity recordings coming from optical and/or electrophysiological measurements. The Neurodata Without Borders (NWB) standard has emerged in the community as the format of record. While standardized and widely used preprocessing tools generating NWB files have been developed, extensible frameworks for scientific analysis downstream of the NWB ecosystem are still under-represented. We present CICADA, a Python framework dedicated to analysis of neurophysiological data in the standardized NWB format. The toolbox is built as three hierarchically-organized packages: cicada-nwb (NWB access layer), cicada-analysis (plugin-based analysis engine and tool library), and cicada-gui (PyQt5 desktop application at the head of the pipeline). Beyond this architectural separation, CICADA is built around a central design principle: supporting a continuum from turnkey use to full modularity. Researchers can use the complete GUI-driven cicada-gui workflow without writing code, programmatically use existing analysis plugins from cicada-analysis, contribute to new analysis plugins, reuse utilities from cicada-tools, or build entirely custom pipelines on top of the cicada-nwb access layer alone. The same analysis plugin runs identically in interactive GUI and parameter-configured headless modes, enabling reproducible multi-session, multi-animal group analyses. We illustrate the versatility of CICADA with example analyses of behavioral, calcium imaging (two-photon and widefield) and extracellular electrophysiology datasets from rodent laboratories. CICADA is open source, actively maintained, and designed so that any laboratory can contribute at any level of the stack without modifying the core framework.

neuroscience↗

bioRxiv2026

Hydrogen metabolism shapes gut microbiome into health-associated configurations

The human gut microbiome exhibits reproducible configurations, yet the ecological forces connecting them to health remain unclear. Here, using enterosignature-based stratification of 5,170 individuals from the Le French Gut cohort, we identified hydrogen disposal as a key determinant of population-scale microbiome configurations, independently replicated in a meta-cohort (n = 5,107). Microbial configurations followed a continuum of hydrogen recycling capacity and redox-associated functions, aligned with dietary patterns and health indicators. Methanogenesis-dominant partitions were associated with more favorable health profiles, whereas acetogenesis-enriched partitions exhibited features of low-grade inflammation, and increased digestive symptoms, perceived stress and antidepressant use. Experimental characterization of mucin profiles highlighted differences across partitions and alterations in Bacteroides-enriched configurations. Together, our findings support an ecological host-microbiome framework linking hydrogen metabolism, redox ecology, and host health, offering microbiome-informed targets for precision intervention. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/722951v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@e7b8d1org.highwire.dtl.DTLVardef@116ab09org.highwire.dtl.DTLVardef@136f1f8org.highwire.dtl.DTLVardef@480097_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2021

The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion

Early electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly ignited by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas including the hippocampus, which in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within two days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal cognitive models.

neuroscience↗

bioRxiv2019

miRViz: a novel webserver application to visualize and interpret microRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in the regulation of major pathways in eukaryotic cells through repression of their target genes at the post-transcriptional level1. While high-throughput approaches are broadly used to decipher the biological relevance of miRNAs, extraction of significant information from large miRNA datasets remains challenging. For example, sequencing technologies can quantify the relative expression of up to thousands of mature miRNAs under various experimental conditions. However, in such datasets, small subsets of miRNAs can often show significant differential expression, and deciding which one(s) should be further analyzed can prove difficult. Thus, the current challenge resides in objective analysis, interpretation and visualization of these large datasets, for which specifically suited methods are lacking.

genomics↗

bioRxiv2019

DeepCINAC: a deep-learning-based Python toolbox for inferring calcium imaging neuronal activity based on movie visualization

Two-photon calcium imaging is now widely used to infer neuronal dynamics from changes in fluorescence of an indicator. However, state of the art computational tools are not optimized for the reliable detection of fluorescence transients from highly synchronous neurons located in densely packed regions such as the CA1 pyramidal layer of the hippocampus during early postnatal stages of development. Indeed, the latest analytical tools often lack proper benchmark measurements. To meet this challenge, we first developed a graphical user interface allowing for a precise manual detection of all calcium transients from imaged neurons based on the visualization of the calcium imaging movie. Then, we analyzed the movies using a convolutional neural network with an attention process and a bidirectional long-short term memory network. This method is able to reach human performance and offers a better F1 score (harmonic mean of sensitivity and precision) than CaImAn to infer neural activity in the developing CA1 without any user intervention. It also enables automatically identifying activity originating from GABAergic neurons. Overall, DeepCINAC offers a simple, fast and flexible open-source toolbox for processing a wide variety of calcium imaging datasets while providing the tools to evaluate its performance. Significance statementInferring neuronal activity from calcium imaging data remains a challenge due to the difficulty in obtaining a ground truth using patch clamp recordings and the problem of finding optimal tuning parameters of inference algorithms. DeepCINAC offers a flexible, fast and easy-to-use toolbox to infer neuronal activity from any kind of calcium imaging dataset through visual inspection.

neuroscience↗