Biology subjects

Santoro, A.

Publications and source records attributed to Santoro, A..

17 recordsLinked to original sources

bioRxiv2026

The protective effect of NGF mutant CHF6467 in SH SY5Y cells exposed to Aβ(1-42): a pharmacometabolomic approach

Nerve Growth Factor (NGF) supports neuronal survival, plasticity, and growth by binding to p75NTR and TrkA receptors. There is a strong link between NGF and the cholinergic hippocampus, and changes in NGF pathways are observed in Alzheimer's disease (AD). Research shows NGF's neuroprotective and regenerative effects on cholinergic neurons, with positive results in AD models and clinical studies. However, NGF therapy faces challenges: limited blood-brain barrier crossing and dose-dependent pain. To address pain, a mutated NGF called CHF6467 was developed. Thanks to the R100E mutation, it prevents binding to p75NTR while maintaining TrkA affinity, which helps reduce pain side effects. Understanding CHF6467's mechanism remains a challenge. In this context, untargeted metabolomics is effective for uncovering unforeseen responses, making it suitable for assessing CHF6467's overall effects. Building on our previous research and recognizing the importance of amyloid-{beta} peptide as a critical pathological marker of AD, we used NMR-metabolomics to study the effect of CHF6467 on SH-SY5Y cells. The study examined metabolomic profiles of cells treated with CHF6467, with and without A{beta}(1-42), using NMR. Results show CHF6467 influences the metabolic changes caused by A{beta}(1-42), inducing biochemical effects consistent with the promotion of phospholipid precursors, reduced glutamate excitotoxicity, and restored energy metabolism.

cell biology↗

bioRxiv2026

Higher-order topology uncovers the multidimensional dynamics of naturalistic emotion

Emotions are thought to emerge from co-activation among distributed brain systems, yet traditional fMRI analyses typically examine localized responses and pairwise connections, potentially overlooking interactions among groups of regions. Here, we use time-resolved higher-order topology to characterize these group interactions during naturalistic viewing of 14 films totaling over 2.5 h, continuously annotated across 50 affective features. The homological scaffold, representing evolving group-level topology, most closely tracks recurrent emotional states and best predicts fine-grained affective profiles. This sensitivity diminishes when emotion is compressed into dimensions of valence, arousal, and power, where pairwise connectivity captures the dominant arousal signal. Across three independent datasets, arousal predictions transfer most robustly through pairwise connectivity, while the relative geometry of broad affective states remains conserved across film narratives despite poor valence generalization. These findings reveal complementary neural representations of emotion: higher-order topology captures fine-grained affective structure, whereas pairwise connectivity provides a portable readout of broad arousal.

neuroscience↗

bioRxiv2026

Sperm whale foraging combines persistent search with flexible prey-capture tactics

Predators searching patchy environments must coordinate movements across scales, yet this behavioural hierarchy is not yet technically possible to observe in the deep ocean. Here we show that sperm-whale foraging is organized across two nested levels: directionally persistent search paths and flexible prey-capture tactics. We combine acoustic recordings with reconstructed three-dimensional trajectories from 34 sensor-tag deployments on 20 individual whales in both the eastern Caribbean and the mid-Atlantic. Complete foraging paths exhibit heavy-tailed step lengths and superdiffusive displacement, consistent with Levy-like search. Within these paths, echolocation buzzes resolve into two recurrent acoustic-kinematic tactics. Type A involves brief ramp-ups, slower and more oscillatory movement, and longer post-buzz pauses. Type B involves prolonged ramp-ups, faster and vertically persistent movement, greater roll, slightly straighter approaches, and an energy-model estimate approximately seven times higher. Every sampled whale used both tactics and switched between them within dives, showing that the contrast is not driven by specialization among individuals. An Azorean deployment with prey-field echograms links the tactics to local prey conditions, while independent Dominica deployments recover their core kinematic contrast. Together, these results reveal a foraging hierarchy in which flexible capture actions unfold within persistent, deliberate large-scale search.

animal behavior and cognition↗

bioRxiv2026

Individual connectome fingerprints reveal early stabilization and long-term circuit remodeling after stroke

Stroke is one of the leading causes of global disability, yet the principles governing how focal brain injury disrupts large-scale neural connectivity over time remain poorly understood. Here, we leverage a longitudinal multimodal dataset to track the evolution of individual-specific connectivity patterns, or brain fingerprints, over the first year after stroke. Despite a persistent shift from healthy architecture, we demonstrate that each patients unique functional connectome fingerprint is remarkably resilient and stabilizes within three weeks. This early global stabilization masks a protracted system-specific reorganization of brain circuits, which is characterized by an initial increase in connectivity within sensory and attention systems, followed by a decline across higher-level association networks. A joint structure-function embedding further shows that recovery involves a gradual shift toward the normative healthy range, driven primarily by functional reconfiguration atop a stable structural lesion. Crucially, a multivariate prediction model reveals that early functional signatures selectively forecast long-term impairment in language, executive function, and attention. Together, our results define the post-stroke brain as a shifting but constrained dynamical system, identifying early-stabilized brain patterns as biomarkers for individual recovery profiles and targets for personalized neurorehabilitation.

neuroscience↗

bioRxiv2025

DNMT3A-R882 mutations intrinsically drive dysfunctional neutropoiesis from human haematopoietic stem cells

Clonal haematopoiesis (CH) arises from the expansion of hematopoietic stem cells (HSCs) carrying leukaemia-associated somatic mutations. CH is linked to pathological immune dysregulation and a greater risk of age-related inflammatory diseases. Yet, how CH mutations impact HSC differentiation into immune effector cells remains understudied. Here, we report a single-cell resolution functional and multi-omic investigation of HSC clonal and differentiation dynamics in individuals with DNMT3A-R882 CH. DNMT3A-R882 reshapes the clonal architecture of haematopoiesis towards an aged phylogenetic structure. Functionally, DNMT3A-R882 HSCs produce decreased monocytic output but more abundant and mature neutrophil progeny compared to WT HSCs in the same individual. Whereas DNMT3A-R882 myeloid progenitors display attenuated inflammatory transcriptional programmes, DNMT3A- R882 mature neutrophils acquire proinflammatory and immunomodulatory features typical of maladaptive immunity and CH co-morbidities. Our findings, validated in humanised mice, identify aberrant DNMT3A-R882 HSC-driven neutropoiesis as a key link between CH, immune dysregulation and risk of inflammatory disease.

cell biology↗

bioRxiv2025

Developmental vitamin A deficiency induces sex-specific reward processing alterations through a dysregulation of the mesolimbic dopamine transmission in mice

Neurodevelopmental psychiatric diseases such as schizophrenia or affective disorders share common symptomatic dimensions, in particular reward processing dysfunctions, associated with dysregulation of dopamine (DA) transmission. Retinoic acid (RA) homeostasis is altered across psychiatric disorders but whether impaired developmental RA signaling impacts the functionality of DA-related reward processing at adulthood remains poorly explored. Herein, we explored in male and female mice how developmental vitamin A deficiency (VAD), as a model of blunted RA signaling, could impact motivational processes through a modulation of mesolimbic DA transmission. Behavioral performances were evaluated using operant conditioning tasks, parallel with investigations of the integrity of DA transmission through biochemical analyses of markers of DA transmission and measures of DA dynamics using DA biosensor coupled with fiber photometry. Finally, chemogenetic manipulation of the mesolimbic DA pathway was used to normalize DA transmission and assess the effect on motivational performance in VAD offspring. Developmental VAD induced sex-specific alterations of reward-related processes at adulthood. Indeed, while female behavioral performances were spared, VAD males exhibited elevated instrumental performance and impulsivity. These behavioral alterations were coherent with reduced DA transporter (DAT) expression and increased DA dynamic in the mesolimbic pathway. Strikingly, chemogenetic inhibition of the mesolimbic DA pathway normalized motivational performance in VAD males. Our results show that developmental RA hyposignaling induces sex-specific reward processing alterations in adulthood through hyperactivity of the mesolimbic DA pathway. Our data support that developmental impairment in RA signaling might be at the core of reward-related symptoms across psychiatric disorders.

neuroscience↗

bioRxiv2025

Beyond Pairwise Interactions: Charting Higher-Order Models of Brain Function

Traditional models of brain connectivity have primarily focused on pairwise interactions, over-looking the rich dynamics that emerge from simultaneous interactions among multiple brain regions. Although a plethora of higher-order interaction (HOI) metrics have been proposed, a systematic evaluation of their comparative properties and utility is missing. Here, we present the first large-scale analysis of information-theoretic and topological HOI metrics, applied to both resting-state and task fMRI data from 100 unrelated subjects of the Human Connectome Project. We identify a clear taxonomy of HOI metrics -- redundant, synergistic, and topological--, with the latter acting as bridges along the redundancy-synergy continuum. Despite methodological differences, all HOI metrics align with the brains overarching unimodal-to-transmodal functional hierarchy. However, certain metrics show specific associations with the neurotransmitter receptor architecture. HOI metrics outperform traditional pairwise models in brain fingerprinting and perform comparably in task decoding, underscoring their value for characterizing individual functional profiles. Finally, multivariate analysis reveals that -- among all HOI metrics -- topological descriptors are key to linking brain function with behavioral variability, positioning them as valuable tools for linking neural architecture and cognitive function. Overall, our findings establish HOIs as a powerful framework for capturing the brains multidimensional dynamics, providing a conceptual map to guide their application across cognitive and clinical neuroscience.

neuroscience↗

bioRxiv2025

The Topological Architecture of Brain Identity

Accurately identifying individuals from brain activity--functional fingerprinting--is a powerful tool for understanding individual variability and detecting brain disorders. Most current approaches rely on functional connectivity (FC), which measures pairwise correlations between brain regions. However, FC is limited in capturing the higher-order, multiscale structure of brain organization. Here, we propose a novel fingerprinting method based on homological scaffolds, a topological repre-sentation derived from persistent homology of resting-state fMRI data. Using data from the Human Connectome Project (n = 100), we show that scaffold-based fingerprints achieve near-perfect identification accuracy ([~] 100%), outperforming FC-based methods (90%), and remain robust across preprocessing pipelines, atlas choices, and even with drastically shortened scan durations. Unlike FC, in which fingerprinting features localize within networks, scaffolds derive their discriminative power from inter-network connections, revealing the existence of individual mesoscale organizational signatures. Finally, we show that scaffolds bridge redundancy and synergy by balancing redundant information along high-FC border edges with synergistic interactions across the topological voids they enclose. These findings establish topological scaffolds as a powerful tool for capturing individual variability, revealing that unique signatures of brain organization are encoded in the interplay between mesoscale network integration and information dynamics.

neuroscience↗

bioRxiv2025

Spine-Prints: Transposing Brain Fingerprints to the Spinal Cord

Functional connectivity (FC) patterns in the human brain form a reproducible, individual-specific "fingerprint" that allows reliable identification of the same participant across scans acquired over different sessions. While brain fingerprinting is robust across healthy individuals and neuroimaging modalities, little is known about whether the fingerprinting principle extends beyond the brain. Here, we used multiple functional magnetic resonance imaging (fMRI) datasets acquired at different sites to examine whether a fingerprint can be revealed from FCs of the cervical region of the human spinal cord. Our results demonstrate that the functional organisation of this region also exhibits individual-specific properties, suggesting the potential existence of a spine-print within the same acquisition session. Although the spine-print scores are not directly comparable to those observed in the brain, this discrepancy may in part reflect the intrinsic limitations of imaging this region with fMRI, where where the signals are more susceptible to noise and effective resolution relative to structure size, and tSNR are markedly lower than in the brain.This study provides the first evidence of a spinal cord connectivity fingerprint, underscoring the importance of considering a more comprehensive view of the entire central nervous system. Eventually, these spine-specific signatures could contribute to identifying individualized biomarkers of neuronal connectivity, with potential clinical applications in neurology and neurosurgery.

neuroscience↗

bioRxiv2025

Small-world scale-free brain graphs from EEG

Developing individualized spatial models that capture the complex dynamics of multi-electrode EEG data is essential for accurately decoding global neural activity. A widely used approach is network modeling, where electrodes are represented as nodes. A key challenge lies in defining the network edges and weights, as precise connectivity estimation is critical for enhancing neural characterization and extracting discriminative features, such as those needed for task decoding. Traditional EEG-derived brain graphs often fail to capture biologically grounded organizational principles such as small-world structure and heavy-tailed (scale-free) connectivity patterns. To address this gap, we introduce a framework for inferring subject-specific EEG-based brain graphs that explicitly designed to exhibit small-world and scale-free properties. Our approach begins by computing phase-locking values (PLV) between EEG channel pairs to build a backbone graph, which is then refined into an individualized small-world and scale-free network. To reduce computational complexity while preserving subject-specific characteristics, we apply Kron reduction to the resulting graph. Using two public EEG datasets, we evaluate the proposed method on motor imagery (MI) decoding and brain fingerprinting tasks. Our approach improves MI classification accuracy by 4-7% compared to conventional PLV, small-world, and scale-free graph models, and enhances differential identifiability in fingerprinting by 8-20% across six canonical frequency bands. These gains were statistically significant in both applications. Moreover, integrating graph signal processing features derived from our constructed graphs with classical EEG features further boosts performance. Overall, our findings highlight the potential of the proposed graph construction framework to enhance EEG analysis. By jointly capturing local segregation, global integration, and hub-driven hierarchical organization, the method strengthens downstream decoding and identification tasks, with promising implications for a wide range of applications in cognitive neuroscience and brain-computer interface research.

neuroscience↗

bioRxiv2024

Detection of Echinococcus spp. and other taeniid species in lettuces and berries: two international multicenter studies from the MEmE project

Cystic and alveolar echinococcosis are severe zoonotic diseases characterized by long asymptomatic periods lasting months or years. Viable Echinococcus eggs released into the environment through the feces of canids can infect humans through accidental ingestion via hand-to-mouth contact or consumption of contaminated food or water. Both Echinococcus multilocularis and Echinococcus granulosus sensu lato are considered as foodborne parasites. However, when considering possible pathways of human infection, it appears that food and water-borne related variables do not significantly increase the risk of infection. Providing evidence-based data for the presence of DNA and, potentially, eggs in fresh produce is crucial in understanding foodborne transmission of Echinococcus spp. to humans. Two multicenter and multicountry studies were conducted within the One Health EJP framework to estimate the proportion of lettuces and berries contaminated by E. multilocularis, E. granulosus s.l., and other taeniid DNAs from 12 European countries, Tunisia and Pakistan. A total of 1,117 lettuces, 300 strawberries and 130 blueberries samples were collected and analyzed by washing, sequential sieving and real-time PCRs. Echinococcus multilocularis DNA was detected in 1.2% (7/570) of samples tested from the seven European endemic areas and in 2% (2/100) from Pakistan. In the five European endemic countries for E. granulosus s.l., E. granulosus sensu stricto DNA was identified in 1.3% of lettuces (9/695). The proportion of lettuces contaminated by E. granulosus sensu stricto DNA was 12% (9/75) in Tunisia and 4% (4/100) in Pakistan. Regarding berries, E. multilocularis DNA was detected in 5.4% of strawberries (n=11/202), 7.3% of blueberries (6/82) from the seven European endemic countries and 56% of blueberries (14/25) from Pakistan. High contamination rates of E. granulosus s.s were found outside of Europe, with 12.0% in blueberries (3/25) from Pakistan and 81.3%. DNA in strawberries (13/16) from Tunisia. The total contamination rate of all taeniid species DNA in lettuces (5.3%; 59/1,117) and berries (12.1%; 58/480) suggests that the transfer of taeniid eggs from carnivore feces to food is not uncommon. Although we assume that eggs are the source of the DNA detected in this study, the viability of such eggs is unknown. The detection of Echinococcus species in lettuces and berries suggests a potential risk of foodborne human infection. The relative contribution of this risk remains to be estimated. Further studies on food and environmental contamination are necessary to cover different epidemiological contexts and social habits, leading to a better understanding of human infections by Echinococcus eggs.

microbiology↗

bioRxiv2023

Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior

Traditional models of human brain activity often represent it as a network of pairwise interactions between brain regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order interactions from temporal brain signals involving three or more regions. However, to this day it remains unclear whether methods based on inferred higher-order interactions outperform traditional pairwise ones for the analysis of fMRI data. To address this question, we conducted a comprehensive analysis using fMRI time series of 100 unrelated subjects from the Human Connectome Project. We show that higher-order approaches greatly enhance our ability to decode dynamically between various tasks, to improve the individual identification of unimodal and transmodal functional subsystems, and to strengthen significantly the associations between brain activity and behavior. Overall, our approach sheds new light on the higher-order organization of fMRI time series, improving the characterization of dynamic group dependencies in rest and tasks, and revealing a vast space of unexplored structures within human functional brain data, which may remain hidden when using traditional pairwise approaches.

neuroscience↗

bioRxiv2023

A culture-based approach to study ecological interactions among the microbial species of the human scalp.

The human scalp hosts an unusually low diversity microbiota dominated by three species: Cutibacterium acnes, Staphylococcus epidermidis, and Malassezia restricta, where characteristic shifts in species frequencies are associated with seborrheic dermatitis and dandruff. In order to better understand this important community, here we study the ecological interactions between these scalp species. We establish a new experimental model system that supports the growth of all three species in vitro and allows one to selectively enumerate each species from co-culture. Our work reveals the potential for strong ecological interactions within the scalp community. In particular, C. acnes greatly benefits from the presence of M. restricta, but harms it in return (exploitation), while S. epidermidis suppresses both M. restricta and C. acnes. Our data suggest that the shifts in composition seen in compromised scalps are influenced by ecological interactions between species. We argue that the scalp microbiome should be viewed as an ecological system where species interactions have the potential to contribute to health outcomes. ImportanceOur bodies are home to diverse communities of microorganisms, our microbiome, which can be critical for health and wellbeing. The human scalp hosts a relatively simple community dominated by three species: two bacteria, Cutibacterium acnes and Staphylococcus epidermidis, and one fungus, Malassezia restricta. Both dandruff and seborrheic dermatitis are strongly associated with characteristic shifts in the frequencies of these three species. However, how these species affect one another and behave as a community remains poorly understood. Here, we develop a simple experimental system to empirically study how these three species interact and affect one another for the first time. We find that S. epidermidis greatly suppresses the growth of the other species, while C. acnes specifically exploits M. restricta. Our work suggests that the human scalp is an ecological system in which species interactions have the potential to affect health outcomes.

microbiology↗

bioRxiv2023

Inflammation causes insulin resistance via interferon regulatory factor 3 (IRF3)-mediated reduction in FAHFA levels

Obesity-induced inflammation causes metabolic dysfunction, but the mechanisms remain elusive. Here we show that the innate immune transcription factor interferon regulatory factor (IRF3) adversely affects glucose homeostasis through induction of the endogenous FAHFA hydrolase androgen induced gene 1 (AIG1) in adipocytes. Adipocyte-specific knockout of IRF3 protects mice against high-fat diet-induced insulin resistance, whereas overexpression of IRF3 or AIG1 in adipocytes promotes insulin resistance on a high-fat diet. Furthermore, pharmacological inhibition of AIG1 reversed obesity-induced insulin resistance and restored glucose homeostasis in the setting of adipocyte IRF3 overexpression. We, therefore, identify the adipocyte IRF3/AIG1 axis as a crucial link between obesity-induced inflammation and insulin resistance and suggest an approach for limiting the metabolic dysfunction accompanying obesity.

physiology↗

bioRxiv2022

Therapy-induced senescence upregulates antigen presentation machinery and triggers anti-tumor immunity in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematological malignancy often curable only by using intensive chemotherapy. Nonetheless, resistance/early relapses are frequent, underscoring the need to investigate the molecular events occurring shortly after chemotherapy. Therapy-induced senescence (TIS) is a fail-safe tumor suppressive mechanism that may elicit immune-mediated responses contributing to senescent cell clearance. Yet, TIS functional role in AML eradication and immune surveillance early post-chemotherapy remains ill-defined. By combining transcriptional and cellular-based evaluation of senescence markers in AML patient samples, we found upregulation of senescence-associated genes and interferon gene categories with concomitant induction of HLA class I and class II molecules, pointing to a causal link between TIS and leukemia immunogenicity. Consistently, senescence-competent AML samples activated autologous CD4+ and CD8+ T cells and improved leukemia recognition by both T-cell subsets. Lastly, the anti-leukemic activity of Immune Checkpoint Blockades (ICBs) was enhanced upon senescence engagement in AML. Altogether, our results identify senescence as a potent immune-related anti-leukemic mechanism that may rapidly translate into innovative senescence-based strategies to prevent AML relapse. STATEMENT OF SIGNIFICANCEOur findings uncover a novel link between senescence induction and leukemia immune recognition by T cells via upregulation of antigen presentation machinery components, providing the basis for conceptually novel senescence-based targeted immunotherapeutic regimens for AML patients.

cancer biology↗

bioRxiv2022

Can neurogenesis act as a neural regularizer?

New neurons are continuously generated in the subgranular zone of the dentate gyrus throughout adulthood. These new neurons gradually integrate into hippocampal circuits, forming new naive synapses. Viewed from this perspective, these new neurons may represent a significant source of wiring noise in hippocampal networks. In machine learning, such noise injection is commonly used as a regularization technique. Regularization techniques help prevent overfitting training data, and allow models to generalize learning to new, unseen data. Using a computational modeling approach, here we ask whether a neurogenesis-like process similarly acts as a regularizer, facilitating generalization in a category learning task. In a convolutional neural network (CNN) trained on the CIFAR-10 object recognition dataset, we modeled neurogenesis as a replacement/turnover mechanism, where weights for a randomly chosen small subset of neurons in a chosen hidden layer were re-initialized to new values as the model learned to categorize 10 different classes of objects. We found that neurogenesis enhanced generalization on unseen test data compared to networks with no neurogenesis. Moreover, neurogenic networks either outperformed or performed similarly to networks with conventional noise injection (i.e., dropout, weight decay, and neural noise). These results suggest that neurogenesis can enhance generalization in hippocampal learning through noise-injection, expanding on the roles that neurogenesis may have in cognition. Author SummaryIn deep neural networks, various forms of noise injection are used as regularization techniques to prevent overfitting and promote generalization on unseen test data. Here, we were interested in whether adult neurogenesis- the lifelong production of new neurons in the hippocampus- might similarly function as a regularizer in the brain. We explored this question computationally, assessing whether implementing a neurogenesis-like process in a hidden layer within a convolutional neural network trained in a category learning task would prevent overfitting and promote generalization. We found that neurogenesis regularization was as least as effective as, or more effective than, conventional regularizers (i.e., dropout, weight decay and neural noise) in improving model performance. These results suggest that optimal levels of hippocampal neurogenesis may improve memory-guided decision making by preventing overfitting, thereby promoting the formation of more generalized memories that can be applied in a broader range of circumstances. We outline how these predictions may be evaluated behaviorally in rodents with altered hippocampal neurogenesis.

neuroscience↗

bioRxiv2020

Quantitative and molecular differences distinguish adult human medullary and extramedullary haematopoietic stem and progenitor cell landscapes

In adults, the bone marrow (BM) is the main site of haematopoietic stem and progenitor cells (HSPCs) maintenance and differentiation. It is known that other anatomical sites can contribute significantly to blood production under stress conditions. However limited tissue availability restricts our knowledge on the cellular, molecular and functional composition of extramedullary HSPC pools in humans at steady state or under stress. Here we describe the landscape of human HSPC differentiation across the three major haematopoietic anatomical sites: BM, spleen and peripheral blood (PB), using matched tissues isolated from the same individuals. Single cell RNA-seq of 30,000 HSPCs and 700 phenotypic haematopoietic stem cells and multipotent progenitors (HSC/MPP) demonstrates significantly different dynamics of haematopoiesis between BM and extramedullary tissues. Lineage-committed progenitors of spleen and PB do not actively divide, whereas BM is the primary site of progenitor proliferation. The balance of differentiation in spleen and PB is skewed towards the lymphoid and erythroid lineages, whereas in BM it is tilted towards megakaryocytic and myeloid progenitors. Extramedullary tissues also harbour a molecularly defined subset of HSC/MPP not found in the BM, which is marked by a specific acto-myosin cytoskeletal signature and transcriptional priming for division and lineage differentiation. Collectively, our findings define a unique cellular and molecular structure of the haematopoietic landscape in extramedullary organs, positioned for rapid lineage-primed demand-adapted haematopoiesis. These data also provide a framework for better understanding of human extramedullary haematopoiesis in health and disease.

cell biology↗