Biology subjects

Neri, P.

Publications and source records attributed to Neri, P..

17 recordsLinked to original sources

bioRxiv2026

Scene Structure Predicts Perceptual Decisions in Naturalistic Detection Tasks

The human visual system can identify objects in complex natural scenes, yet the mechanisms supporting robust perception under such variable conditions remain incompletely understood. Here, we investigate how the statistical structure of natural scenes shapes perceptual evidence formation and determines whether near-threshold stimuli are perceived correctly or incorrectly. We combine controlled psychophysics, outdoor augmented reality (AR), deep neural networks (DNNs), image-feature analysis, and EEG to examine how background context modulates perceptual decisions. Across multiple detection tasks, human performance was systematically influenced by probe-free background structure. DNNs trained on background images alone predicted correct and incorrect behavioral outcomes, with stronger effects in postcue conditions, suggesting that global scene context contributes to local perceptual decisions when spatial uncertainty is higher. AR experiments further showed that these context-driven effects persist in naturalistic viewing environments. To identify the visual information underlying these effects, we analyzed low-level image statistics. Texture entropy and edge density emerged as informative features, and conventional machine-learning models trained on these measures achieved meaningful correct/incorrect classification. Finally, EEG analyses revealed neural signatures of image-driven perceptual variability: activity during the probe-free preimage window distinguished later correct from incorrect trials, and combining EEG with image-derived features improved decoding performance. Together, these findings show that perception in natural scenes is not determined solely by the target, but is shaped by the statistical structure of the surrounding context. By linking psychophysics, AR, DNN modeling, image statistics, and EEG, this work provides a unified framework for understanding how environmental structure and neural dynamics jointly support perceptual decision-making.

neuroscience↗

bioRxiv2026

Visual detection of cryptic displays in jumping spiders

Most animals can segment camouflaged targets via static cues, such as luminance or contrast differences against a background. However, targets can be cryptic and merge with background clutter, making static cues unavailable until the camouflaged object starts moving: the target can then be segmented by identifying spatially coherent luminance changes over time. Jumping spiders represent a unique model for the study of spatiotemporal segmentation, as they process moving signals and static figures separately through distinct pathways associated with different pairs of eyes: the secondary eyes detect moving objects and trigger full body pivot responses, bringing the target within focused view of the principal eyes for subsequent figure processing. While secondary eyes can be selective for specific stimulus characteristics that cause the animal to pivot, it remains unclear whether their selectivity requires full motion segmentation or relies on simpler stimulus characteristics. Here, we tested whether the pivoting response triggered by secondary eyes is specifically linked to motion segmentation, or whether it is also elicited by less specific stimulus characteristics. We presented jumping spiders with several moving and non-moving stimuli, including clearly delineated objects, cryptic objects visible only through motion, and non-segmentable spatio-temporal luminance patterns. Based on the measured responses, we developed a computational model that captured all salient features of the pivoting behavior produced by the animal. We found that jumping spiders do not require a discrete, segmented object to trigger a pivoting response. Instead, they attend to luminance patterns that change across both time and space, while disregarding changes that repeat over the same spatial location. This mechanism constitutes an effective solution in terms of neural simplification: it offloads the task of complex motion segmentation from the secondary eyes, thus maximizing the efficiency of visual modularity--a unique evolutionary solution to the problem of brain miniaturization.

neuroscience↗

bioRxiv2026

Chiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping

MotivationThree-dimensional folding of the genome into structures such as chromatin loops is essential for gene regulation. Current experimental methods for mapping these structures, like Hi-C and HiChIP, are labor-intensive and require repeated assays to test hypothesized mutation effects. This motivates the need for predictive approaches that reveal the sequence determinants of chromatin loops. ResultsIn this work, we present a novel and interpretable computational pipeline for predicting CTCF-mediated chromatin loops. We propose Chiron3D, a DNA-only model trained in a cell-type specific manner to predict CTCF HiChIP contact maps. By leveraging pre-trained embeddings from a foundation model, our approach is competitive with baselines that take CTCF ChIP-seq as additional input, while enabling nucleotide-level attribution to the input DNA sequence. Using our framework, we provide likely mechanistic insights into the physical control of loop dynamics. Specifically, we find that the strength of the loop extrusion anchorage site is largely governed by the amount and binding affinity of CTCF sites at the boundaries. Furthermore, we reveal that loop stability is regulated by the amount of intra-loop CTCF binding sites, where fewer sites within the loop lead to a more stable domain. Using targeted, single-nucleotide edit simulations with Chiron3D, we show that both loop strength and stability can be precisely controlled. Together, these results provide novel mechanistic insights into the physical control of genome organization and highlight the potential of decoding the DNA sequence logic in silico. AvailabilityThe Chiron3D pipeline is made available at https://github.com/BoevaLab/Chiron3D. Supp. informationSupp. data are available at Journal Name online.

genomics↗

bioRxiv2025

Plasma cell identity escape drives resistance to anti-BCMA T-cell-redirecting therapy in multiple myeloma

Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell-associated transcriptional programs, a phenomenon we term "plasma cell identity escape." This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

cancer biology↗

bioRxiv2025

Perceptual processes as charting operators

Sensory operators are classically modelled using small circuits involving canonical computations, such as energy extraction and gain control. Notwithstanding their utility, circuit models do not provide a unified framework encompassing the variety of effects observed experimentally. We develop a novel, alternative framework that recasts sensory operators in the language of intrinsic geometry. We start from a plausible representation of perceptual processes that is akin to measuring distances over a sensory manifold. We show that this representation is sufficiently expressive to capture a wide range of empirical effects associated with elementary sensory computations. The resulting geometrical framework offers a new perspective on state-of-the-art empirical descriptors of sensory behavior, such as first-order and second-order perceptual kernels. For example, it relates these descriptors to notions of flatness and curvature in perceptual space.

neuroscience↗

bioRxiv2025

Cuttlefish interaction with multimodal arm wave signs displays

In addition to the well-known extraordinary changes in visual appearance they can generate at the level of their mantle, cuttle-fish can produce various body configurations combining chromatic, postural, and locomotion patterns, both for camouflaging and communication. We introduce a previously undescribed communication display in two cuttlefish species: Sepia officinalis and Sepia bandensis. The four "arm wave signs" are stereotyped arm movements consisting of long-lasting, expressive, and repeated sequences of undulations of the arms, which can be combined and expressed following specific patterns. Using non-invasive behavioral experiments, we tested the hypothesis that they represent multimodal communication displays. To assess the role of visual cues, we recorded videos of animals signing and played them back to individual cuttlefish participants. When seeing the movies, cuttlefish waved back at the display. Most importantly, they were more likely to wave back when the movie was in upright (original) configuration as opposed to flipped upside-down, similar to the manner in which humans perceive faces and other socially relevant displays. In addition to their visually striking display, arm wave signs produce mechanical waves in the water, prompting us to explore the possibility that they may also be perceived via mechanoreception. Using playback experiments similar to those adopted in vision, we obtained preliminary evidence to support this hypothesis, indicating that arm wave signs may represent multimodal signals involving vision and mechanoreception. Our new result on communication with arm wave signs opens up novel possibilities for understanding vibration-mediated communication through the lateral line and/or the statocysts in a cephalopod species as an example of convergent evolution with vertebrates.

animal behavior and cognition↗

bioRxiv2024

CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse following anti-CD38 antibodies. We report a loss of CD38 in 20% (10/50) of patients post-CD38 therapy, three of which exhibited a loss of both copies. Two of these cases showed convergent evolution where distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that two variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies Daratumumab and Isatuximab. However, a third mutation, R140G, conferred selective resistance to Daratumumab, while retaining sensitivity to Isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies following disease progression and these data support a role for next generation sequencing to guide treatment selection.

cancer biology↗

bioRxiv2024

Microbial metabolite-guided CAR T cell engineering enhances anti-tumor immunity via epigenetic-metabolic crosstalk

The microbiome is a complex host factor and key determinant of the outcome of antibody-based and cellular immunotherapy. Its postbiotics are a blend of soluble commensal byproducts that are released into the host environment and have been associated with the regulation of immune homeostasis, particularly through impacts on epigenetics and cell signaling. In this study, we show that the postbiotic pentanoate is metabolized to citrate within the TCA cycle via both the acetyl- and succinyl-CoA entry points, a feature uniquely enabled by the chemical structure of the C5 aliphatic chain. We identified ATP-citrate lyase as the crucial factor that redirects pentanoate-derived citrate from the succinyl-CoA route to the nucleus, thereby linking metabolic output and histone acetylation. This epigenetic-metabolic crosstalk mitigated T cell exhaustion and promoted naive-like differentiation in pentanoate-programmed chimeric antigen receptor (CAR) T cells. The predictive and therapeutic potential of pentanoate was corroborated in two independent patient cohorts and three syngeneic models of CAR T adoptive therapy. Our data demonstrate that postbiotics are integrated into mitochondrial metabolism and subsequently incorporated as epigenetic imprints. This bridge between microbial and mammalian interspecies communication can ultimately impact T cell differentiation and efficacy.

immunology↗

bioRxiv2024

EMMPRIN confers metabolic advantage for monocytes and macrophages to promote disease in a model of multiple sclerosis

Monocytes and monocyte-derived macrophages have important roles in the initiation and progression of multiple sclerosis (MS). These cells undergo metabolic reprogramming to generate immunophenotypes that promote leukocyte infiltration, axonal degeneration and demyelination, worsening MS pathology. The mechanisms that dictate metabolic programs in monocytes and macrophages in MS remain unclear. We previously reported that extracellular matrix metalloproteinase inducer (EMMPRIN, CD147), a glycoprotein that acts as a chaperone of monocarboxylate transporter 4 (MCT4), assisted with glycolysis-driven pro-inflammatory phenotype in macrophages in experimental autoimmune encephalomyelitis (EAE), an animal model of MS. Using newly-generated CCR2CreERT2:EMMPRINfl/fl (CCR2:EMMP) mice, we report that presymptomatic deletion of EMMPRIN in CCR2+ monocytes prevented or reduced clinical disability of EAE. This was correspondent with decreased infiltration of leukocytes into the CNS. Single cell RNA-seq of blood monocytes from EAE and proteomics analysis of macrophages from CCR2:EMMP-/- mice revealed significant alterations in metabolic programs, particularly reduced glycolysis and elevated mitochondrial electron transport and fatty acid oxidation, which were linked to their reduced pro-inflammatory traits. Our findings implicate EMMPRIN as a key regulator of metabolic pathways that exacerbate pro-inflammatory functions of monocytes in MS.

immunology↗

bioRxiv2024

Timing antigenic escape in multiple myeloma treated with T-cell redirecting immunotherapies

Recent data highlight genomic events driving antigen escape as a recurring cause of chimeric antigen receptor T-cell (CAR-T) and bispecific T-cell engager (TCE) resistance in multiple myeloma (MM). Yet, it remains unclear if these events, leading to clonal dominance at progression, result from acquisition under treatment selection or selection of pre-existing undetectable clones. This differentiation gains importance as these immunotherapies progress to earlier lines of treatment, prompting the need for innovative diagnostic testing to detect these events early on. By reconstructing phylogenetic trees and exploring chemotherapy mutational signatures as temporal barcodes in 11 relapsed refractory MM patients with available whole genome sequencing data before and after CART/TCE treatment, we demonstrated that somatic antigen escape mechanisms for BCMA- and GPRC5D-targeting therapies are acquired post-diagnosis, likely during CART/TCE treatment. Longitudinal tracking of these mutations using digital PCR in 4 patients consistently showed that genomic events promoting antigen escape were not detectable during the initial months of therapy but began to emerge nearly 1 year post therapy initiation. This finding reduces the necessity for a diagnostic panel to identify these events before CART/TCE. Instead, it underscores the importance of surveillance and identifying patients at higher risk of acquiring these events. KEY POINTSO_LIGenomic events driving antigen escape are recurrent mechanisms of resistance to CART and T-cell engagers in multiple myeloma. C_LIO_LIUsing chemotherapy mutational signatures, we demonstrated that these events are most likely acquired during treatment. C_LI

genomics↗

bioRxiv2023

Dynamic skin signatures of cuttlefish internal states

Cuttlefish skin is a powerful rendering device, capable of producing extraordinary changes in visual appearance over a broad range of temporal scales. This unique ability is typically associated with camouflage, however cuttlefish often produce skin patterns that do not appear connected with the surrounding environment, such as fast large-scale fluctuations with wave-like characteristics. Little is known about the functional significance of these dynamic patterns. In this study, we develop novel tools for analyzing pattern dynamics, and we demonstrate their utility for detecting changes in feeding state that occur without concomitant changes in sensory stimulation. Under these conditions, we find that the dynamic properties of specific pattern components differ for different feeding states, despite no measurable change in the overall expression of those components. These dynamic changes are therefore not detectable by conventional analyses focusing on pattern expression, requiring analytical tools specifically targeted to pattern dynamics.

animal behavior and cognition↗

bioRxiv2022

Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response

We performed the first integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, cellular compositions, and ligand-receptor interactions. We demonstrate that LE regions are conserved across multiple cancers while TC states are more tissue specific. Additionally, we found our LE gene signature is associated with worse clinical outcomes while the TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biologies, a platform for data exploration (http://www.pboselab.ca/spatial_OSCC/) and is foundational for developing novel targeted therapies.

cancer biology↗

bioRxiv2022

Deep networks may capture biological behaviour for shallow, but not deep, empirical characterizations

We assess whether deep convolutional networks (DCN) can account for a most fundamental property of human vision: detection/discrimination of elementary image elements (bars) at different contrast levels. The human visual process can be characterized to varying degrees of depth, ranging from percentage of correct detections to detailed tuning and operating characteristics of the underlying perceptual mechanism. We challenge deep networks with the same stimuli/tasks used with human observers and apply equivalent characterization of the stimulus-response coupling. In general, we find that popular DCN architectures do not account for signature properties of the human process. For shallow depth of characterization, some variants of network-architecture/training-protocol produce human-like trends; however, richer empirical descriptors expose glaring discrepancies. These results urge caution in assessing whether neural networks do or do not capture human behaviour: ultimately, our ability to assess success in this area can only be as good as afforded by the depth of behavioural characterization against which the network is evaluated. We propose a novel set of metrics/protocols that impose stringent constraints on the evaluation of DCN behaviour as adequate approximation of biological processes.

neuroscience↗

bioRxiv2020

Copy-scAT: An R package for detection of large-scale and focal copy number alterations in single-cell chromatin accessibility datasets

Single-cell epigenomic assays have tremendous potential to illuminate mechanisms of transcriptional control in functionally diverse cancer cell populations. However, application of these techniques to clinical tumor specimens has been hampered by the current inability to distinguish malignant from non-malignant cells, which potently confounds data analysis and interpretation. Here we describe Copy-scAT, an R package that uses single-cell epigenomic data to infer copy number variants (CNVs) that define cancer cells. Copy-scAT enables studies of subclonal chromatin dynamics in complex tumors like glioblastoma. By deploying Copy-scAT, we uncovered potent influences of genetics on chromatin accessibility profiles in individual subclones. Consequently, some genetic subclones were predisposed to acquire stem-like or more differentiated molecular phenotypes, reminiscent of developmental paradigms. Copy-scAT is ideal for studies of the relationships between genetics and epigenetics in malignancies with high levels of intratumoral heterogeneity and to investigate how cancer cells interface with their microenvironment.

bioinformatics↗

bioRxiv2020

Simultaneous Profiling of DNA Copy Number Variations and Transcriptional Programs in Single Cells using RNA-seq

Chromosome copy number variations (CNVs) are a near-universal feature of cancer however their effects on cellular function are incompletely understood. Single cell RNA sequencing (scRNA-seq) can reveal cellular gene expression however cannot directly link this to CNVs. Here we report new normalization methods (RTAM1 and -2) for scRNA-seq that improve gene expression alignment between cells, enhancing gene expression comparisons and the application of scRNA-seq to CNV detection. We also report sciCNV, a pipeline for inferring CNVs from RTAM-normalized data. Together, these tools provide dual profiling of transcriptomes and CNVs at single-cell resolution, enabling exploration of the effects of cancer CNVs on cellular programs. We apply these tools to multiple myeloma (MM) and examine the cellular effects of cancer CNVs +8q. Consistent with prior reports, MM cells with +8q22-24 upregulate MYC, MYC-target genes, mRNA processing and protein synthesis, verifying the approach. Overall, we provide new tools for scRNA-seq that enable matched profiling of the CNV landscape and transcriptome of single cells, facilitate deconstruction of the effects of cancer CNVs on cellular reprogramming within single samples.

genomics↗

bioRxiv2020

Mechanisms of spectrotemporal modulation detection for normal- and hearing-impaired listeners

Spectrotemporal modulations (STMs) offer a unified framework to probe suprathreshold auditory processing. Here, we introduce a novel methodological framework based on psychophysical reverse-correlation deployed in the modulation space to characterize how STMs are detected by the auditory system and how cochlear hearing loss impacts this processing. Our results show that young normal-hearing (NH) and older hearing-impaired (HI) individuals rely on a comparable non-linear processing architecture involving non-directional band-pass modulation filtering. We demonstrate that a temporal-modulation filter-bank model can capture the strategy of the NH group and that a broader tuning of cochlear filters is sufficient to explain the overall shift toward temporal modulations of the HI group. Yet, idiosyncratic behaviors exposed within each group highlight the contribution and the need to consider additional mechanisms. This integrated experimental-computational approach offers a principled way to assess supra-threshold auditory processing distortions of each individual.

neuroscience↗

bioRxiv2018

Multiple myeloma immunoglobulin lambda translocations portend poor prognosis

Multiple myeloma is a malignancy of antibody-secreting plasma cells. Most patients benefit from current therapies, however, 20% of patients relapse or die within two years and are deemed high-risk. To better understand and identify high-risk myeloma, we analyzed the translocation landscape of 826 newly-diagnosed patients by whole genome sequencing as part of the CoMMpass study. Translocations at the IgL locus were present in 10% of myeloma patients, and corresponded with poor prognosis. Importantly, 70% of IgL translocations co-occurred with hyperdiploid disease, a marker of standard risk, which is routinely diagnosed clinically whereas IgL-translocations are not. Thus, it is likely that the majority of IgL-translocated myeloma is being misclassified. The IgL enhancer is among the strongest in myeloma cells, indicating it can robustly drive oncogene expression when translocated. Consistent with this, IgL-translocated patients failed to benefit from immunomodulatory imide drugs (IMiDs), which target the lymphocyte-specific transcription factor Ikaros. These data implicate the IgL enhancer as resistant to IMiD-inhibition, and when translocated, as a driver of poor prognosis.

genomics↗