Biology subjects

Russo, S.

Publications and source records attributed to Russo, S..

At least 19 recordsLinked to original sources

bioRxiv2026

PTP1B supports survival and regulates CFL1 and HSP90a abundance in trastuzumab-resistant HER2-positive breast cancer.

Trastuzumab resistance limits the treatment of HER2-positive breast cancer. Here, we identify protein tyrosine phosphatase 1B (PTP1B) as a survival dependency in models of intrinsic and acquired trastuzumab resistance, including cells with endogenous ERBB2 kinase domain mutations (L755S and V777L), a patient-derived tumor organoid model, and orthotopic xenografts. PTP1B expression was elevated in multiple trastuzumab-resistant models, accompanied by increased PI3K-AKT and ERK signaling in several of these. The PTP1B inhibitor DPM-1003 suppressed growth of trastuzumab-resistant cells and organoids, inhibited xenograft progression, and induced apoptosis. Genetic ablation of PTP1B reduced growth and restored trastuzumab responsiveness in multiple resistance models, although JIMT1 cells remained resistant. Quantitative phosphoproteomics, phosphotyrosine immunoprecipitation, and substrate-trapping assays identified cofilin-1 (CFL1) and HSP90 as substrates of PTP1B. Loss of PTP1B increased their tyrosine phosphorylation, reduced their abundance, and increased their recovery in ubiquitin pull-downs. Proteasome inhibition restored substrate abundance, and PTP1B re-expression restored protein levels in PTP1B-null cells. These findings support a model in which PTP1B-dependent dephosphorylation limits turnover of the substrates CFL1 and HSP90. Genetic or pharmacological targeting of PTP1B suppressed survival-associated signaling and increased apoptotic markers. Together, these results identify PTP1B as a therapeutic vulnerability in trastuzumab-resistant HER2-positive breast cancer and implicate regulation of CFL1 and HSP90 abundance in the accompanying signaling response.

cancer biology↗

bioRxiv2026

Simultaneous recordings link intracranial and scalp correlates of somatosensory awareness in humans

The electrophysiological events underlying the conscious perception of touch in humans remain elusive. Scalp-EEG studies have identified a negative deflection peaking 120-200 ms after stimulus onset, known as the N140. This component, recently reinterpreted as the somatosensory awareness negativity (N140/SAN), has been proposed as a putative marker of tactile awareness, but its underlying neuronal dynamics are still unknown. Intracranial studies have shown that responses to median nerve stimulation include, after an initial phasic activation mainly localized to primary somatosensory cortices, a predominantly insulo-opercular tonic broadband high-frequency activity (BHA; 50-150 Hz) that has been linked to tactile awareness. Yet these scalp and intracranial signatures have never been directly linked. Using simultaneous high-density scalp EEG and intracranial EEG recordings, we show that the N140/SAN is the scalp manifestation of the insulo-opercular local field potential that follows the BHA response to stimulation. By bridging invasive and non-invasive recordings our results identify the neural origins of the N140/SAN and connect scalp and intracranial correlates of somatosensory awareness.

neuroscience↗

bioRxiv2026

A proteomic feasibility study connecting metabolic and synaptic pathway alterations in serum and extracellular vesicles to characterize treatment-resistant depression

Treatment-resistant depression (TRD) remains a major clinical challenge, yet the biological processes distinguishing TRD from non-treatment-resistant depression (nTRD) are incompletely defined. While circulating serum proteomes reflect broad systemic alterations associated with depression, extracellular vesicles (EVs) could provide a more selective representation of intercellular signaling relevant to treatment resistance. Here, we carried out a pilot study to evaluate the extent that parallel proteomic profiling of serum and serum-derived EVs could distinguish healthy controls (CON), nTRD, and TRD individuals. In this exploratory and hypothesis-generating study, serum proteomes exhibited robust global differences between depression groups and controls, largely reflecting shared systemic biology across nTRD and TRD. In contrast, EV proteomes showed limited global separation but revealed subtype-associated pathway differences. Relative to controls, nTRD EVs were enriched for immune and inflammatory pathways. By contrast, TRD EVs were characterized by enrichment of mitochondrial metabolism, oxidative phosphorylation, translational initiation, and MYC-regulated pathways, together with depletion of synaptic signalling, membrane trafficking, and cytoskeletal pathways. Comparative analysis of pathways significant in both contrasts revealed that these bioenergetic and translational signatures were selectively amplified in TRD relative to nTRD. Our exploratory analyses identified that the circulating EV cargo may reflect a treatment-resistance-specific reorganization of biological pathways not apparent in bulk serum proteomics. This study highlights parallel serum and EV proteomics as a complementary approach for molecular stratification in antidepressant resistance.

neuroscience↗

bioRxiv2026

ZNF687 couples bone marrow myeloid progenitor dynamics toosteoclastogenesis in severe Paget's disease of bone

Pagets disease of bone (PDB) is a late-onset skeletal disorder characterized by excessive osteoclast-mediated bone remodelling and disorganized bone deposition. The P937R mutation in the ZNF687 gene causes a severe form of PDB complicated by giant cell tumour transformation. Although ZNF687 has been implicated in osteoclastogenesis, whether it regulates upstream haematopoietic progenitor dynamics and bone marrow myeloid output remains unclear. Using a constitutive Zfp687 knock-out mouse model, we showed that Zfp687 loss causes postnatal growth restriction, reduced bone marrow cellularity, impaired osteoclast differentiation in vitro and in vivo, and increased trabecular bone mass during adulthood. Flow cytometry revealed a marked reduction in osteoclast progenitors and macrophages in Zfp687-deficient bone marrow, whereas the pagetic P937R mutation promoted the expansion of the same myeloid populations in the Zfp687P937R knock-in mouse model. Single-cell RNA sequencing of bone marrow-derived c-Kit+ haematopoietic progenitors further demonstrated that Zfp687 loss selectively disrupted the myeloid progenitor compartment. This analysis identified 22 transcriptionally distinct populations and revealed a significant depletion of the early cycling granulocyte-monocyte progenitor cluster, without evidence of a global block in myeloid differentiation. Mechanistically, Zfp687 deficiency impaired the Brd4-c-Myc-NFATc1 axis in osteoclastogenic precursors and reduced Csf1 expression in bone marrow stromal and osteoblastic cells, linking intrinsic transcriptional competence to niche-derived M-CSF support. In pagetic patient iPSCs-derived haematopoietic progenitors, the P937R mutation enhanced clonogenic haematopoietic output, accelerated colony formation, and promoted the expansion of primitive/multipotent colony-forming progenitors, leading to hypercellular myeloid colonies. Together, our findings establish ZNF687 as a regulator of haematopoietic progenitor dynamics that couples bone marrow myeloid output to osteoclastogenesis, providing a progenitor-level mechanism for severe ZNF687-related PDB.

cancer biology↗

bioRxiv2026

Profilin 1 maintains cell cycle fidelity to prevent unscheduled genome doubling and polyploidy in cancer

Whole-genome doubling (WGD) represents a major route to genome instability and therapeutic resistance in cancer; yet, the mechanisms enabling genome duplication in p53-proficient cells remain poorly understood. Here, we identify Profilin 1 (PFN1) loss as a driver of WGD through impaired mitotic entry. Using FUCCI live-cell imaging and single-cell genomic profiling, we show that PFN1-deficient cells bypass mitosis and undergo endoreplication, generating tetraploid cells. Rather than undergoing stable arrest after mitotic bypass, these genome-doubled cells retain proliferative capacity and proceed through aberrant mitotic divisions, thereby amplifying genomic instability. Proteomic analyses reveal coordinated attenuation of late cell-cycle programs, including downregulation of key mitotic regulators such as CDK1, PLK1 and CKS2, consistent with impaired G2/M transition. Despite accumulating polyploidy, PFN1-knockout cells fail to activate an effective p53 tetraploidy checkpoint and display increased nuclear MDM2, promoting cell-cycle arrest evasion and chemotherapeutic resistance. We supported clinical relevance by an orthotopic osteosarcoma xenograft model, in which PFN1-deficient SaOS2 cells showed enhanced metastatic dissemination, and by pan-cancer TCGA analyses confirming a recurrent association between PFN1 loss and WGD. Together, these findings identify Profilin 1 as a safeguard of cell-cycle fidelity whose loss enables genome doubling, cellular plasticity and therapy tolerance.

cancer biology↗

bioRxiv2026

Patient-derived organoid xenografts reveal the multifaceted role of the lncRNA MALAT1 in breast cancer progression

Long non-coding RNAs (lncRNAs) have emerged as key regulators of tumor biology, however, thus far none have translated to cancer therapies. The lncRNA MALAT1 is overexpressed in more than 20 cancers, including breast cancer and has been shown to function via various mechanisms in a context-dependent manner, in 2D cell lines and mouse models. However, its functional role and therapeutic potential have not been evaluated in clinically relevant patient-derived models. We investigated the therapeutic potential of MALAT1-targeting antisense oligonucleotides (ASOs) for breast cancer, using clinically relevant 3D human patient-derived organoids (PDOs) and PDO-xenograft (PDO-X) models. We systematically evaluated the efficiency of MALAT1-targeting ASOs using a biobank of 28 PDO models. Across three independent PDO-X models of triple negative breast cancer (TNBC), MALAT1 depletion reproducibly drove widespread alternative splicing changes across all event types, with an enrichment of intron retention. Differentially spliced transcripts were enriched for targets of shared cancer-associated transcription factors, and MALAT1 knockdown specifically altered the relative abundance of previously unannotated splicing isoforms. Beyond tumor-intrinsic effects, tumor-specific MALAT1 depletion induced a consistent reduction in macrophage-associated gene signatures and reduced lung metastatic burden. Our data defines MALAT1s multifaceted role in TNBC, coordinating alternative splicing, tumor-stroma crosstalk, and metastatic progression. Our study provides strong preclinical evidence supporting MALAT1-targeted ASO therapy and establishes PDO-X models as a clinically relevant platform for functional interrogation of TNBC therapies. SignificanceUsing clinically relevant human PDO-X models, we show that MALAT1 influences alternative splicing, metastatic potential and the tumor microenvironment. These data support the potential of oncogenic lncRNA MALAT1 as a therapeutic target.

cancer biology↗

bioRxiv2026

A shared transcriptional network in the nucleus accumbens supports resilience to chronic stress across sex.

Although chronic stress increases the risk for depression, only a subset of exposed individuals develop psychiatric illness. The biological mechanisms that protect against depression remain incompletely understood, particularly at the molecular level. Here, we identify a transcriptional network in the nucleus accumbens (NAc), a central brain reward region, that supports stress resilience in both sexes and demonstrate the causal contribution of key hub genes. Using chronic social defeat stress, RNA-seq, and co-expression network analysis, we find sex-specific but overlapping gene modules linked to resilience, anchored by shared hub genes embedded within a common network architecture. Overexpression of these hub genes in stress-naive mice confers stress protection and induces a transcriptional state that is discrete from both susceptible and resilient profiles. These findings position resilience as a structured and targetable molecular phenotype and provide a basis for investigating sex-informed mechanisms of stress adaptation.

neuroscience↗

bioRxiv2025

Slow waves generation and propagation in a model of brain lesions

Slow waves (SWs), the hallmark of non-rapid eye movement (NREM) sleep, reflect the periodic occurrence of transient silent periods in cortical neurons (Down states). During NREM, SWs and Down states physiologically disrupt large-scale network interactions. Since early EEG studies, SWs have also been observed in awake patients after brain injury. Emerging evidence indicates that these intrusions of sleep-like activity interfere with ongoing network activity and contribute to motor and cognitive deficits; yet, the mechanisms governing the generation and spread of post-lesional SWs remain unclear. Here, we extend a neural mass model of EEG to capture transitions between wake-like and sleep-like dynamics and embed it in connectome-based networks with virtual lesions. This model supports that local disfacilitation, topology-dependent propagation, and synchrony-dependent amplification throughout the connectome are sufficient to produce post-lesional SWs. These mechanisms reproduce the spatial gradients of post-lesional SWs seen in patients and identify actionable targets for neuromodulation and rehabilitation.

neuroscience↗

bioRxiv2025

Sexual Dimorphism in c-Fos Networks Governing Aggression

Circuit based studies of aggression often focus on the activity of a small group of regions referred to as the "core aggression circuit," yet a whole-brain map of activity has yet to be produced. Using resident-intruder assays in male and female Swiss Webster mice, we combined iDISCO+ c-Fos imaging with a weighted co-expression network analyses to identify mesoscale co-activation modules in aggressive (AGG) and non-aggressive (NON) animals. We performed a module preservation analysis between each phenotype within each sex followed by differential correlation to localize edge-level changes. Behaviorally, AGG mice spent more time attacking, while females showed greater social investigation. When comparing activity changes in individual regions, male AGGs showed broad activation throughout the anteroposterior axis, while females preferentially activated anterior cortical regions. Network analyses revealed that NON networks often preserved density of AGG modules, but connectivity reorganized with aggression. In male AGGs there was large spread reorganization of numerous modules: a large sensorimotor-subcortical "blue" module, a pallidal/hypothalamic/brainstem "yellow" module, and a brainstem-heavy "green" module. Surprisingly the "brown" module, enriched for classic social-behavior regions was moderately preserved in male NONs. In females, the "turquoise" module spanning somatosensory/interoceptive cortex and midbrain regions and the "red" module spanning many anterior cortical and thalamic regions were the least preserved. These results indicate that aggression recruits distributed mesoscale communities via edge-specific gain, with males displaying broad strengthening throughout the brain and females showing more targeted potentiation within anterior cortical modules. This framework nominates candidate hubs and edges for causal manipulation.

neuroscience↗

bioRxiv2025

Electrical stimulation elicits space- and parameter-dependent spiking responses in human cortical organoids

Electrical stimulation (ES) is used to treat neuropsychiatric disorders and investigate brain dynamics, yet its effects on human cortical microcircuits remain poorly understood. Cortical organoids provide a unique platform to investigate these mechanisms in isolation from subcortical and long-range cortical inputs. Here we illustrate how cortical organoids respond to ES, identifying the response profiles of isolated cortical circuits while detailing a roadmap of how ES parameters affect the organoid spiking activity. We employed a high-density multielectrode array to record neuronal activity from cortical organoids (n=417 units in N=7 organoids) during ES, systematically varying stimulation frequency, intensity, pulse width, and charge density. By analyzing single unit spiking activity, we found that ES elicits excitatory, inhibitory, and mixed responses in 39%, 12%, and 17% of the units, respectively. On average, this response lasted 100 ms and became stable within 26 trials. The magnitude of both excitatory and inhibitory responses was maximal near the stimulation site and decayed with distance. The response magnitude was inversely correlated with pulse intensity and duration, but not with stimulation frequency and charge density. These findings demonstrate that local cortical circuits are sufficient to initiate the early excitatory phase of the canonical ES response, whose magnitude depends on ES parameters, and can sustain the excitatory phase for over 100 ms. The reduced late inhibitory phase, together with the absence of late excitatory components observed 200 ms after ES in intact adult brains in-vivo, suggests that these phases may depend on neuronal maturation or inter-area connections. Our work thus establishes cortical organoids as a framework for studying the local contributions to ES-induced activity in a developmental model of the human cortex.

neuroscience↗

bioRxiv2025

Evidence of Escherichia coli Regulating Drosophila melanogaster Behavior

Chemosensory systems are critical for insect survival, enabling host seeking, food acquisition, and oviposition site selection. While insect-associated microbes are known to influence host development and immunity, their role in modulating chemosensory behavior remains poorly understood. Here, we demonstrate that Escherichia coli, a bacterium identified in non-gut tissues of Aedes albopictus and experimentally reintroduced into axenic Drosophila melanogaster, alters both larval and adult sensory-driven behaviors. In larvae, E. coli infection modified phototaxis and mechanosensory responses across genotypes, while tunneling and thermosensory behaviors were specifically dependent on the ionotropic receptor co-receptor IR25a. In adults, E. coli increased attraction to fermentation cues (apple cider vinegar, ethanol) and enhanced sucrose consumption in wild-type and Orco-deficient flies, but not in IR25a-deficient mutants. Gas chromatography-mass spectrometry revealed that E. coli shifted cuticular hydrocarbon composition toward shorter-chain alkanes and increased the sex pheromone 9-tricosene in an IR25a-dependent manner. Together, these findings show that E. coli broadly reprograms insect sensory behavior, with IR25a serving as a critical mediator of microbial influence on chemosensory and physiological traits. This work identifies a previously unrecognized role for E. coli in shaping insect behavior and chemical ecology, providing a foundation for investigating microbial contributions to host-microbe coevolution and for exploring microbial cues as novel, environmentally sustainable tools for insect control. ImportanceInsects depend on their sense of smell and taste to find food, mates, and safe places to reproduce. These behaviors drive the spread of insect-borne diseases and cause major agricultural losses worldwide. Our work shows that a common bacterium, Escherichia coli, can reshape insect sensory behaviors, influencing how flies respond to light, temperature, food, and even the chemical signals on their outer surface that control mating. Importantly, these effects are linked to a specific sensory receptor, IR25a, which is conserved across many insect species. This finding reveals a previously unknown role for microbes in fine-tuning insect behavior. Understanding how bacteria influence insect sensory systems not only provides insight into host-microbe interactions but also opens the door to new, environmentally friendly ways of managing insect pests by targeting their behavior rather than killing them outright.

microbiology↗

bioRxiv2025

Recognizing EEG responses to active TMS vs. sham stimulations in different TMS-EEG datasets: a machine learning approach

BackgroundTranscranial Magnetic Stimulation (TMS) with simultaneous Electroencephalogram (TMS-EEG) allows assessing the neurophysiological properties of cortical neurons. However, TMS-evoked EEG potentials (TEPs) can be affected by components unrelated to TMS direct neuronal activation. Accurate, automatic tools are therefore needed to establish the quality of TEPs. ObjectiveTo assess the discriminability of EEG responses to TMS vs. EEG responses to sham stimulations using sequence-to-sequence machine learning (ML). MethodsTwo indipendent TMS-EEG datasets including TMS and several sham stimulation conditions were obtained from the left motor area of healthy volunteers (N=33 across datasets). A Bi-directional Long Short-Term Memory (BiLSTM) ML network was used to label each time point of the EEG signals as pertaining to TMS or sham conditions. Main outcome measures included accuracy at single-trial level and after averaging five to twenty trials. ResultsFor TMS conditions, post-stimulus vs. baseline/pre-stimulus EEG comparisons yielded moderate (60%-75%) single-trial accuracy and high-accuracy (>75%) for 20 trials across datasets, while for sham conditions post- vs. baseline/pre-stimulus EEG comparisons yielded lower accuracy rates than for TMS conditions, except for unmasked auditory stimulation. Furthermore, baseline/pre-stimulus TMS vs. baseline/pre-stimulus sham EEG comparisons showed chance-level accuracy, whereas post-stimulus TMS vs. post-stimulus sham EEG comparisons had moderate (single trial) to high (20 trial) accuracy, except for TMS with and without the click noise masking. Single-subject findings were comparable to group-level results across datasets. ConclusionsTEPs after active TMS are discernible from various sham stimulations even after a handful of trials and at the single-subject level using a BiLSTM ML approach.

neuroscience↗

bioRxiv2025

The specific spatiotemporal evolution of TMS-evoked potentials reflects the engagement of cortical circuits

Transcranial Magnetic Stimulation (TMS) evokes electroencephalographic (EEG) responses that can persist for hundreds of milliseconds. While the first 80 ms after the pulse are widely accepted to reflect genuine cortical responses to TMS, later components have mainly been attributed to the effects of sensory co-stimulations. Here we reappraise this view by investigating the target-specificity of the spatiotemporal evolution of TMS-evoked potentials (TEPs). To this end, we compared TEPs elicited by targeting the premotor and primary motor cortices in 16 healthy subjects, under conditions designed to optimize TMS effectiveness on the cortex while minimizing peripheral confounds. As a counterfactual, we conducted the same comparison on the EEG responses evoked by realistic sham TMS and high-intensity somatosensory scalp stimulation. We found that EEG responses to motor and premotor TMS can exhibit distinct spatiotemporal evolutions, lasting up to 300 ms, both at the group and single-subject levels. These differences were absent or marginally detectable in both realistic sham TMS and high-intensity somatosensory scalp stimulation. Our findings suggest that, when effectiveness is optimized and peripheral confounds are controlled, TMS elicits specific long-lasting genuine EEG responses that reflect the initial engagement of specific cortical targets. These results challenge previous assumptions and highlight how TMS-EEG can be reliably used to assess large-scale properties within corticothalamic networks.

physiology↗

bioRxiv2025

Extracting Reproducible Components from Electroencephalographic Responses to Transcranial Magnetic Stimulation with Group Task-Related Component Analysis

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is a powerful technique for investigating human cortical circuits. However, characterizing TMS-evoked potentials (TEPs) at the group level typically relies on grand averaging across stimulus repetitions (trials) and subjects - an approach that assumes a level of spatial and temporal consistency that is often lacking in TEPs. Here, we introduce an adaptation of Group Task-Related Component Analysis (gTRCA), a novel multivariate signal decomposition method, to automatically extract TEP components that are maximally reproducible across both trials and subjects. Following the validation of a new permutation-based statistical test for gTRCA using simulated data, the method was applied to two independent TMS-EEG datasets, in which stimulation was targeted to the primary motor cortex (M1) in cohorts of 16 and 22 healthy participants. We found that gTRCA reliably identified TEP components that were reproducible at the group level. Notably, the main gTRCA component captured the key spatial, temporal, and spectral features of motor TEPs, remained robust despite reduced number of stimuli and participants, and was consistent across different recordings. These findings demonstrate that gTRCA affords a more reliable characterization of TEPs at the group level, thereby facilitating the translation of TMS-EEG research into clinical practice.

neuroscience↗

bioRxiv2025

Transcranial magnetic vs intracranial electric stimulation: a direct comparison of their effects via scalp EEG recordings

BackgroundSingle-pulse Transcranial Magnetic Stimulation (TMS) and Intracranial Electrical Stimulation (IES) are widely used to probe cortical excitability and connectivity, but their electrophysiological effects have never been compared. ObjectiveThis study aims to fill this gap by using high-density scalp electroencephalogram (hd-EEG) as a common read-out to compare human brain responses to TMS and IES. MethodsThe dataset includes TMS-evoked potentials (TEPs) acquired from healthy subjects (n=22) and IES-evoked potentials (IEPs) recorded from drug-resistant epileptic patients (n=31) during wakefulness. In a subset of subjects TEPs (n=12) and IEPs (n=13) were also recorded during NREM sleep. Amplitude, spectral, and spatiotemporal features of TMS and IES responses, as well as their estimated electrical fields, were compared. ResultsWe observed marked differences between TMS and IES responses. During wakefulness, IEPs are considerably larger, slower and associated with a suppression of cortical activity, whereas TEPs are characterized by multiple waves of recurrent activation. These differences are attenuated during NREM, during which both TMS and IES elicit large EEG responses associated with a prominent suppression of cortical activity. At the global level, the spatiotemporal complexity of the responses to both TMS and IES decreases consistently following the transition from wakefulness to NREM sleep. ConclusionDespite the limitations due to different subject populations (healthy vs pathological), our findings provide a first reference to parallel non-invasive and invasive brain stimulation and to interpret their differential effects. They also offer important insight on how cortical responsiveness is shaped by inhibition and adaptation mechanisms depending on input parameters and brain states. Highlights- IES evokes higher signal-to-noise EEG responses than TMS. - IES responses are larger, slower, and lead to cortical suppression. - TMS elicits faster recurrent waves, with no suppression during wakefulness. - Both TMS and IES converge to similar patterns during NREM sleep.

neuroscience↗

bioRxiv2025

Statistical Characterization of Cortical-Thalamic Dynamics Evoked by Cortical Stimulation in Mice

ObjectiveStatistical models are powerful tools for describing biological phenomena such as neuronal spiking activity. Although these models have been widely used to study spontaneous and stimulated neuronal activity, they have not yet been applied to analyze responses to electrical cortical stimulation. In this study, we present an innovative approach to characterize neuronal responses to electrical stimulation in the mouse cortex, providing detailed insights into cortical-thalamic dynamics. ApproachOur method applies Mixture Models to analyze the Peri-Stimulus Time Histogram of each neuron, predicting the probability of spiking at specific latencies following the onset of electrical stimuli. By applying this approach, we investigated neuronal responses to cortical stimulation recorded from the motor cortex, somatosensory cortex, and sensorimotor-related thalamic nuclei in the mouse brain. Main resultsThe characterization approach achieved high goodness of fit, and the model features were leveraged by applying machine learning methods for stimulus intensity decoding and classification of brain regions to which a neuron belongs given its response to the stimulus. The Random Forest model demonstrated the highest F1 scores, achieving 92.86% for stimulus intensity decoding and 84.35% for brain zone classification. SignificanceThis study presents a novel statistical framework for characterizing neuronal responses to electrical cortical stimulation, providing quantitative insights into cortical-thalamic dynamics. Our approach achieves high accuracy in stimulus decoding and brain region classification, providing valuable contributions for neuroscience research and neuro-technology applications.

neuroscience↗

bioRxiv2025

Formyl-peptide receptor type 2 activation mitigates secondary organ damage in inflammatory arthritis

Rheumatoid arthritis (RA) is associated with heart and lung dysfunction. Current therapies fail to attenuate such complications. Here, we identify formyl-peptide receptor type 2 (FPR2) as therapeutic target to treat heart and lung dysfunction associated with inflammatory arthritis. Arthritic mice on high levels of dietary homocysteine develop cardiac diastolic dysfunction and reduced lung compliance, mirroring two comorbidities in RA. Therapeutic administration of a small molecule FPR2 agonist (BMS986235) to hyper-homocysteine arthritic mice prevented diastolic dysfunction (monitored by echocardiography) and restored lung compliance. These tissue-specific effects were secondary to reduced neutrophil infiltration, modulation of fibroblast activation and phenotype (in the heart) and attenuation of monocyte and macrophage numbers (in the lung). A dual FPR1/2 agonist (compound 43) failed to prevent the reduction in lung compliance of arthritic mice and promoted accumulation of inflammatory monocytes and pro-fibrotic macrophages in lung parenchyma. This cellular response lies downstream of FPR1-mediated potentiation of CCL2-dependent monocyte chemotaxis and activation. This finding supports therapeutic development of selective FPR2 agonists to mitigate two impactful comorbidities associated with inflammatory arthritides.

pharmacology and toxicology↗

bioRxiv2024

Astrocyte-derived extracellular matrix proteins regulate synapse remodeling in stress-induced depression

Major depressive disorder (MDD) is a common mood condition affecting multiple brain regions and cell types. Changes in astrocyte function contribute to depressive-like behaviors. However, while neuronal mechanisms driving MDD have been studied in some detail, molecular mechanisms by which astrocytes promote depression have not been extensively explored. To uncover astrocyte contributions to MDD, we subjected male mice to chronic social defeat stress precipitated by encounters with a dominant male. Animals exposed to this treatment exhibit symptoms indicative of MDD, including reduced social interactions, anxiety, despair, and anhedonia. We then measured astrocyte translating mRNA expression changes in mice that underwent chronic social defeat and control animals using ribosome affinity purification. Bioinformatic analyses reveal significant alterations in the prefrontal cortex (PFC), consistent with previous studies implicating this brain region in MDD. Expression of genes encoding extracellular matrix (ECM) proteins, cell-cell interaction proteins, and proteins controlling glutamatergic synaptic function are significantly altered. These changes correlate with perturbation of glutamatergic transmission, measured by electrophysiology, and increased synaptic cleft size. Among ECM genes, increased expression of mRNA encoding the synaptic remodeling protein secreted protein acidic and rich in cysteine (Sparc) correlates the most with the depressive phenotype. Furthermore, presence of SPARC and other ECM proteins in synaptosomes is also increased and overexpressing Sparc in PFC partially alleviates stress symptoms. Our results raise the possibility that increased expression of Sparc may be a natural protective mechanism against stress-induced synaptic dysfunction in depression.

neuroscience↗