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Salvador, R.

Publications and source records attributed to Salvador, R..

At least 19 recordsLinked to original sources

cyto7: an open, vertex-level cortical type atlas of the human cortex

The cerebral cortex is organized along a gradient of laminar complexity, indexed principally by the emergence and granularity of layer IV and by the size of layer III neuron somata, and cortical types are the ordered categories along it. The Structural Model builds on that gradient to predict laminar connectivity, plasticity and disease vulnerability (Barbas and Rempel-Clower, 1997; Garcia-Cabezas et al., 2019). Existing digital cortical-type maps are area-level: they assign one type per classical area and cannot represent a type boundary that runs through an area. We release cyto7, an open, vertex-level, seven-type cortical-type atlas delineated on the fsaverage surface following the Garcia-Cabezas protocol and revised by the protocol's authors. We distribute the atlas with a reusable quality-control and support framework. A topological audit reports the map against four spatial rules that follow from cortical type analysis and the dual origin of the neocortex theory: neighbouring vertices differ by at most one type, the least complex cortex forms one continuous limbic belt, eulaminate II forms a single matrix enclosing a few holes, and eulaminate III and koniocortex form isolated islands. These were imposed during construction rather than tested, and the audit reports what imposing them cost. A vertex-wise benchmark against the existing area-level map, one type per von Economo-Koskinas area, shows exact agreement at 52.5% of vertices, with disagreement almost always a single level and concentrated inside the large, heterogeneous areas that a single areal label cannot resolve. Where the two maps disagree, cyto7's label better matches the independent multimodal profile in 60.1% of pooled feature-by-vertex comparisons, against 46% under a rotation null and 54% under granularity-matched alternative partitions (p = 0.020), the harder of the two. A per-vertex anatomical support score, computed from anatomy alone, states how strongly each hand-drawn label is backed by the anatomical evidence, and is deliberately not a calibrated error probability. We then validate cyto7 against independent brain measures not used to define it, under a spatial-autocorrelation (spin) null with FDR control. Intracortical myelin (T1w/T2w) increases, cortical thickness decreases, and the principal functional-connectivity gradient reverses along the type axis (all q of about 0.006 or less). Source-reconstructed resting-state MEG dynamics also track the axis: the intrinsic timescale shortens toward koniocortex (rho of about -0.46) and survives the null, as do the spectral centroid and the slow/fast band-power ratio, whereas the aperiodic 1/f exponent does not. The laminar marker genes are where cyto7 differs most from a quantisation of a continuous map: it shows a larger absolute correlation with the layer-IV marker RORB (rho = +0.78) and the layer-V marker FEZF2 (-0.59) than seven-level septiles of myelin, of the functional gradient or of a histological gradient, on four of five markers, while tying or losing to those septiles on the macroscale proxies. These are larger observed associations against three tested quantisations, not a test that the differences between maps are reliable, and they do not establish the accuracy of any individual boundary. Defined from anatomy alone, cyto7 recovers the sensorimotor-to-association hierarchy and, on these markers, some of the laminar signal underlying it. It is released with its full pipeline and an uncalibrated anatomical support score as a reusable substrate for structure-function and modelling studies.

neuroscience↗

CCR4+low-density neutrophils define a novel immunosuppressive subset associated with breast cancer progression and early mortality

Neutrophils are increasingly recognized as key players in cancer progression, yet their functional heterogeneity limits their therapeutic exploitation. In breast cancer (BC), elevated circulating and tumor-associated neutrophils have been associated with poor prognosis, and low-density neutrophils (LDN), particularly, have been linked to immunosuppression. However, the specific neutrophil subsets driving these effects remain undefined. Here, we identify a previously unrecognized CCR4-expressing neutrophil subset, strongly enriched among LDN, whose frequency rises with disease stage and correlates with faster progression and shorter survival. Serial blood sampling further showed that CCR4+LDN levels fluctuate in line with clinical course, with increases indicating near-term risk in metastatic patients. Our findings also reveal that this subset has an immunosuppressive signature more pronounced than that of the remaining LDN, migrates preferentially toward tumor-derived chemokines, and dampens T cell-driven tumor killing even when PD-1 is blocked. Additionally, in a pilot cohort of Triple-Negative BC patients on anti-PD-1 therapy, early changes in this population were associated with treatment outcome. Together, these results reveal a distinct neutrophil population that actively contributes to immune escape and tumor progression, establishing CCR4+LDN as a minimally invasive real-time biomarker of disease course and treatment response, and as a promising target for neutrophil-directed therapies in BC.

immunology↗

MicroRNAome of Spodoptera frugiperda in Response to SfMNPV Infection

Spodoptera frugiperda is one of the most important agronomical pests due to its migratory capacity and broad host range. Since it is resistant to several insecticides, novel control strategies are being explored to control it. In this way, Spodoptera frugiperda Multiple Nucleopolyhedrovirus, a natural pathogen, has been proposed for its biocontrol. In this work, we performed a small RNA-seq on uninfected larvae and larvae infected with SfMNPV to identify expressed miRNA, characterize them, and identify differentially expressed (DE) miRNA in the infected condition. We identified several known and putative novel miRNAs, some of which are encoded in multiple copies and may be expressed within miRNA clusters. We also found 13 DE miRNA, most of them previously reported, two of them are putative novel miRNAs identified in this work. We predicted miRNA targets and found that their putative biological role could be related with processes relevant to the infection such as proliferative and apoptotic pathways, cell cycle regulation, autophagy, DNA damage response (DDR), vesicle transport, cytoskeleton remodelling, JAK/STAT and Toll signaling pathway, and immune response activation, among others. Moreover, we observed that several of the putative targets were hub genes in a predicted protein - protein interaction network. Finally, we found DE miRNA putatively associated with the regulation of viral gene expression, suggesting they might have a role in modulating the infection. Our results contribute to better understanding the miRNA landscape in S. frugiperda, and their putative role upon SfMNPV infection.

molecular biology↗

Structural Brain Network Alterations in Relation to Treatment and Illness Severity in Bipolar Disorder

BackgroundLarge-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics. MethodsCross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7{+/-}12.6 years) and 510 controls (33.3{+/-}12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications. ResultsBD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged. ConclusionsAs the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

neuroscience↗

Incorporation of ChiA into AcMNPV occlusion bodies and its implications for oral infectivity

Baculoviruses are insect-specific viruses primarily employed in biological pest control and recombinant protein expression. As biopesticides, they offer numerous advantages over chemical pesticides and hold significant potential for application in integrated pest management (IPM). However, their slower action compared to conventional synthetic strategies has limited their widespread adoption. This study aimed to investigate the impact of incorporating a viral protein, AcChiA chitinase, which disrupts the gut peritrophic membrane of susceptible insects, into AcMNPV occlusion bodies in trans. This was achieved through the development of an insect cell line that facilitates the passive incorporation of this protein. The presence of ChiA was detected in dissolved occlusion bodies (OBs) preparations from infected transgenic lines, in a method-dependent manner, with the stronger signals observed in chimeric polyhedra. It is hypothesized that ChiA in OBs will increase peritrophic membrane permeability and facilitate primary infection. In bioassays, OBs produced in ChiA-expressing lines were associated with higher larval mortality than OBs produced in Sf9, consistent with a ChiA-mediated effect. Notably, the addition of ChiA proteins from stably transformed insect cell lines improved infection rates, particularly in recombinant baculoviruses, which exhibited a significant reduction in occlusion-derived virion (ODV) occlusion. This underscores the critical role of these proteins in the oral infection process. Consequently, it was possible to incorporate the ChiA protein from stably transformed insect cell lines into wild-type and recombinant baculovirus occlusion bodies, paving the way for potential applications in IPM with AcMNPV.

bioengineering↗

Neuroanatomical Correlates of Negative Symptoms in Schizophrenia

BackgroundSchizophrenia is characterized by widespread structural brain abnormalities, but associations between structural abnormalities and negative symptom severity are not well understood. Negative symptoms have been conceptualized in a hierarchical structure of two second-order dimensions--motivation and pleasure (MAP) and expression (EXP)--and five first-order domains: anhedonia, avolition, and asociality (MAP), and blunted affect and alogia (EXP). A better understanding of the neural circuitry underlying negative symptom dimensions and domains is important given their reported association with poor functional outcome and lack of available treatments. Study DesignThe meta-analysis included 1,591 individuals with schizophrenia across 16 samples with structural imaging and Scale for Assessment of Negative Symptoms data. The study generated correlations of cortical thickness and subcortical volumes with the negative symptom dimensions and domains. Study resultsNegative symptoms showed mainly negative associations with cortical thickness and subcortical volumes. The effect sizes were small but there was a pattern of associations in predominantly frontal lobe cortical thickness and limbic subcortical volumes. The regional correlation patterns of cortical thickness and subcortical volumes with symptom domains support the conceptualized hierarchical structure of negative symptoms: correlations of MAP domains were stronger with the MAP than EXP dimension, and vice versa. Exploratory analyses with receptor densities further supported the hierarchy. ConclusionOur findings reveal small but consistent associations between negative symptom dimensions and predominantly prefrontal region cortical thickness, and limbic region volumes. These findings advance our understanding of the network of anatomical regions that may contribute to the severity of negative symptoms in schizophrenia.

neuroscience↗

Control of fall armyworm with Spodoptera frugiperda multiple nucleopolyhedrovirus in sweet corn cultivated under agroecological conditions

The fall armyworm (FAW), Spodoptera frugiperda (JE Smith) is a polyphagous pest documented on more than 80 plant species. In vegetable production systems, sweet corn is their preferred host, but also infests other plants such as chilli, tomato, pumpkins, cucumber, beans and eggplant. Control strategies are commonly carried out by the use of chemical insecticides even though resistance of S. frugiperda populations to several insecticides has been reported. Last decades, have registered rapid adoption of organic and agroecological practices in horticulture, particularly those that rely on bioinputs such as biopesticides and biofertilizers. The baculovirus Spodoptera frugiperda Multiple Nucleopolyhedrovirus (SfMNPV) is a pathogenic agent for the fall armyworm and an alternative tool used for its control in sustainable pest management strategies. In this work, we evaluate two indigenous SfMNPV-based liquid formulations sprayed on sweet corn cultivated under agroecological conditions. Larvae fed with leaves treated with SfMNPV OBs showed mortality rates ranging from 55 to 68 %. Offspring from adult surviving to OBs treatments was analyzed by PCR and the results confirmed sublethal infections and vertical transmission in the fall armyworm. Corn ears harvested from each treatment were individually observed for insect presence, where the lowest rate of fall armyworm per corn ear was registered in plants treated with SfMNPV OBs. Analysis of secondary plagues in corn ears identified the sap beetle Carpophilus dimidiatus and the maize-infesting fly larvae Euxesta mazorca as the most abundant insect pests. These results show that indigenous isolates of SfMNPV produce a significant control on FAW under agroecological conditions, suggesting that the use of formulations including this virus might be a valuable tool for pest management in sustainable vegetable production systems. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/666974v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@12e8d59org.highwire.dtl.DTLVardef@1420401org.highwire.dtl.DTLVardef@11516b7org.highwire.dtl.DTLVardef@186750b_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Proteomic Characterization of Spodoptera frugiperda Granulovirus Occlusion Bodies

Lepidopteran-infecting baculoviruses represent one of the most promising alternatives for pest biocontrol. In particular, Spodoptera frugiperda granulovirus (SfGV) infects the fall armyworm Spodoptera frugiperda, an increasingly important pest for maize and other crops around the world. SfGV has been investigated due to its capacity to enhance other baculovirus infectivity and as a biopesticide itself. Although the proteome of SfGV occlusion bodies (OB) is fundamental for their infectivity properties, we still lack a detailed understanding of its protein components and how they compare with other baculoviruses. To tackle this problem, we performed mass spectrometry-based proteomics analysis on SfGV OB obtained from infected larvae. We could detect 72 proteins included in SfGV OB and confirm the presence of two enhancins. EmPAI-based semi-quantification highlighted the presence of two granulovirus proteins, ORF101 and ORF141, shared with other GV proteomic studies. ORF101 was shown to form aggregates in insect cells. Bioinformatic analysis determined that ORF101 is an Ac5 family protein and at the same time shares striking similarities with AcMNPV P10. Prediction and comparison of OB protein structures allowed the detection of a common structural fold among 6 proteins PEP-1, PEP-2, Pep-P10, ORF007, ORF025, and Bro-f. Finally, comparison of four reported ODV proteomic studies of different GVs indicated that ORF040, ORF101, ORF141 and Bro-f are common components in GV OBs.

molecular biology↗

Personalized whole-brain models of seizure propagation

Objective: Computational modeling has recently emerged as a powerful tool to better understand seizure dynamics and guide new treatment strategies. This work aims to develop and personalize whole-brain computational models in epilepsy using multimodal clinical data to simulate and evaluate individualized therapeutic strategies. Approach: We present a computational framework that constructs patient-specific whole-brain models of seizure propagation by integrating SEEG, MRI, and diffusion MRI data. The pipeline uses neural mass models for each node in the network, simulating whole-brain dynamics. Model personalization involves adjusting global and local parameters representing the excitability of individual brain areas, using an evolutionary algorithm that aims to maximize the correlation between empirical and synthetic functional connectivity matrices derived from SEEG data. Main results: The resulting personalized models successfully reproduce individual seizure propagation patterns and can be used to simulate therapeutic interventions like surgery, stimulation, or pharmacological interventions within a unified physiological framework. Notably, model predictions reveal distinct patient-specific responses across interventions, including variable sensitivity to different pharmacological agents and identification of critical regions whose removal or modulation reduced seizure spread. Significance: This framework provides a mechanistic, interpretable approach to simulate and compare individualized treatment strategies. By integrating multimodal data into a unified whole-brain model, it has the potential to improve clinical decision-making in epilepsy by identifying accessible and functionally relevant targets.

neuroscience↗

Neutrophils matter: New clinical insights on their role in the progression of metastatic breast cancer

BackgroundMetastatic breast cancer (BC) remains a significant clinical challenge, needing innovative strategies to improve disease management and extend patient survival. Increased neutrophil levels have been observed in both peripheral blood and tumor tissues of patients with different types of cancer, often being associated with poor clinical outcomes. These findings suggest a crucial role for neutrophils in tumor progression, raising interest in neutrophil-based therapies. However, the functional and phenotypic heterogeneity of neutrophils complicates their therapeutic targeting. This study aims to investigate the clinical impact of immunosuppressive, protumor low-density neutrophils (LDN) in metastatic BC, comparing them with normal high-density neutrophils (HDN) to better understand their role in disease progression. MethodsLDN and HDN subpopulations were isolated from the blood of 151 BC patients (72 metastatic, 79 non-metastatic) using density gradient centrifugation. Their frequency, phenotype, and function were analyzed by flow cytometry and in vitro experiments. Correlations between LDN levels and clinical data from metastatic BC patients were evaluated, alongside individual longitudinal assessments. ResultsLDN accumulated significantly in the blood of BC patients, particularly in those with metastatic disease. Elevated LDN levels in these patients were associated with faster disease progression and reduced life expectancy, regardless of metastatic site. Longitudinal analysis revealed that higher LDN percentages often correlated with adverse clinical events, whereas lower levels of LDN were linked to stable disease. Functionally, LDN exhibited protumor properties, including elevated expressions of PD-L1 and MMP-9, contributing to immunosuppression and metastasis. Unlike HDN, which demonstrated cytotoxicity against tumor cells, LDN failed to reduce BC cell line viability in 3D co-cultures. Notably, BC cell lines exposed to LDN-conditioned medium showed increased invasive capacity and proliferation, while T cells cultured in the same medium displayed impaired activation, likely due to the effect of arginase. ConclusionOur results highlighted LDN and their secreted factors as major drivers of BC progression and increased aggressiveness. These findings suggest that incorporating LDN assessment into clinical practice could aid in identifying high-risk patients and enable more personalized treatment approaches. Furthermore, our data strengthen the relevance of targeting specific neutrophil subsets or their functions to improve metastatic BC management and patient outcomes.

immunology↗

Group optimization methods for dose planning in transcranial electrical current stimulation (tES)

ObjectiveOptimizing transcranial electrical stimulation (tES) parameters--including stimulator settings and electrode placements--using magnetic resonance imaging-derived head models is essential for achieving precise electric field (E-field) distributions, enhancing therapeutic efficacy, and reducing inter-individual variability. However, the dependence on individually personalized MRI-based models limits their scalability in some clinical and research contexts. To overcome this limitation, we propose a novel group-level optimization framework employing multiple representative head models. ApproachThe proposed optimization approach utilizes computational modeling based on multiple representative head models selected to minimize group-level error compared to baseline (no stimulation). This method effectively balances focal stimulation intensity within targeted brain regions while minimizing off-target effects. We evaluated our method through computational modeling and leave-one-out cross-validation using data from 54 subjects and analyzed the effectiveness, generalizability, and predictive utility of anatomical characteristics. Main resultsOur approach demonstrated that group optimization significantly outperformed protocols derived from standard templates or randomly selected individual models, notably reducing variability in outcomes across participants. Additionally, correlations between anatomical features (e.g., head perimeter and tissue volumes) and E-field parameters revealed predictive relationships. This insight enables further optimization improvements through the strategic selection of representative head models that are electro-anatomically similar to the target subjects. SignificanceThe proposed group optimization framework provides a scalable and robust alternative to personalized approaches, substantially enhancing the feasibility and accessibility of model-driven tES protocols in diverse clinical and research environments. Data Access StatementThe data that support the findings of this study are available from the corresponding author, R.S., upon reasonable request.

biophysics↗

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples

Human social interactions rely on the ability to reflect on ones own and others internal states and traits--a process known as mentalizing. Impaired or altered mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total N=390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas, respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based mentalizing about self and others--present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions. Author NoteThis work was funded by a Starting Grant from the European Research Council (ERC, 101041087) to LKo, a German Academic Exchange Service (DAAD) doctoral grant and a Network of European Neuroscience Schools (NENS) exchange fellowship to DA, an R01 grant from the U.S. National Institutes of Mental Health (R01MH125414-01) to JAH and DAS, a Junior Leader Fellowship from "la Caixa" Foundation (LCF/BQ/PR22/11920017) to PFC, a Consolidator Grant from the European Research Council (ERC, 648082) to LKr, R37, R01 support from the U.S. National Institutes of Mental Health (R37MH076136 to TDW, MH116026 to TDW and L. Chang [PI], R01EB026549 to TDW and M. Lindquist [MPIs]), an NIMH grant (P50MH094258-01A1) to R. Adolphs, and a CIC Brain and Mental Health Chair from the Neurodis foundation to AT. LvdM acknowledges a European Science Foundation EURYI grant (044035001) that funded her doctoral studies (PI: A. Aleman). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. The funders had no role in study design, data analysis, manuscript preparation, or publication decisions.

neuroscience↗

Restoring Oscillatory Dynamics in Alzheimer's Disease: A Laminar Whole-Brain Model of Serotonergic Psychedelic Effects

Classical serotonergic psychedelics show promise in addressing neurodegenerative disorders such as Alzheimers disease by modulating pathological brain dynamics. However, the precise neurobiological mechanisms underlying their effects remain elusive. This study introduces a personalized whole-brain model built upon a laminar neural mass framework to elucidate these effects. Using multimodal neuroimaging data from thirty subjects diagnosed with mild to moderate Alzheimers disease, we simulate the impact of serotonin 2A receptor activation, characteristic of psychedelics, on cortical dynamics. By modulating the excitability of layer 5 pyramidal neurons, our models reproduce hallmark changes in EEG power spectra observed under psychedelics, including alpha power suppression and gamma power enhancement. These spectral shifts are shown to correlate strongly with the regional distribution of serotonin 2A receptors. Furthermore, simulated EEG reveals increased complexity and entropy, suggesting restored network function. These findings underscore the potential of serotonergic psychedelics to reestablish healthy oscillatory dynamics in the prodromal and early phases of Alzheimers disease and offer mechanistic insights into their potential therapeutic effects in neurodegenerative disorders.

neuroscience↗

Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working Group

BackgroundSchizophrenia (SCZ) is characterized by a disconnect from reality that manifests as various clinical and cognitive symptoms, and persistent neurobiological abnormalities. Sex-related differences in clinical presentation imply separate brain substrates. The present study characterized deep brain morphology using shape features to understand the independent effects of diagnosis and sex on the brain, and to determine whether the neurobiology of schizophrenia varies as a function of sex. MethodsThis study analyzed multi-site archival data from 1,871 male (M) and 955 female (F) participants with SCZ, and 2,158 male and 1,877 female healthy controls (CON) from twenty-three cross-sectional samples from the ENIGMA Schizophrenia Workgroup. Harmonized shape analysis protocols were applied to each sites data for seven deep brain regions obtained from T1-weighted structural MRI scans. Effect sizes were calculated for the following main contrasts: 1) Sex effects;2) Diagnosis-by-Sex interaction; 3) within sex tests of diagnosis; 4) within diagnosis tests of sex differences. Meta-regression models between brain structure and clinical variables were also computed separately in men and women with schizophrenia. ResultsMass univariate meta-analyses revealed more concave-than-convex shape differences in all regions for women relative to men, across diagnostic groups (d = -0.35 to 0.20, SE = 0.02 to 0.07); there were no significant diagnosis-by-sex interaction effects. Within men and women separately, we identified more-concave-than-convex shape differences for the hippocampus, amygdala, accumbens, and thalamus, with more-convex-than-concave differences in the putamen and pallidum in SCZ (d = -0.30 to 0.30, SE = 0.03 to 0.10). Within CON and SZ separately, we found more-concave-than-convex shape differences in the thalamus, pallidum, putamen, and amygdala among females compared to males, with mixed findings in the hippocampus and caudate (d = -0.30 to 0.20, SE = 0.03 to 0.09). Meta-regression models revealed similarly small, but significant relationships, with medication and positive symptoms in both SCZ-M and SCZ-F. ConclusionsSex-specific variation is an overriding feature of deep brain shape regardless of disease status, underscoring persistent patterns of sex differences observed both within and across diagnostic categories, and highlighting the importance of including it as a critical variable in studies of neurobiology. Future work should continue to explore these dimensions independently to determine whether these patterns of brain morphology extend to other aspects of neurobiology in schizophrenia, potentially uncovering broader implications for diagnosis and treatment. Key PointsO_LIStatistical analyses revealed significant main effects for diagnosis and sex in deep brain shape morphology. Among patients with schizophrenia, there was a pattern of thinning and surface contraction in the bilateral hippocampus, amygdala, accumbens, and thalamus, and a pattern of significant thickening and surface expansion in the bilateral putamen and pallidum compared to healthy control participants. Between males and females, there was a pattern of significant thinning and surface contraction in the bilateral thalamus, pallidum, putamen, and amygdala in females compared to males. C_LIO_LIThere was no significant interaction between diagnosis and biological sex, suggesting that sex differences in deep brain shape and asymmetry among patients with schizophrenia reflect those observed in healthy individuals. C_LIO_LISmall but statistically significant relationships exist between brain structure and clinical correlates of schizophrenia were similar for both men and women with the disease, such that higher CPZ was associated with shape-derived thinning and surface contraction in the caudate, accumbens, hippocampus, amygdala, and thalamus, and elevated positive symptoms were associated with shape-derived thinning and surface contraction in the bilateral caudate, right hippocampus, and right amygdala. C_LI

neuroscience↗

Enhancing HLA-DR in Cytotoxic T Lymphocytes is crucial for the development of efficient adoptive T cell Therapies for Breast Cancer

BackgroundDespite advances in breast cancer (BC) therapies, more effective interventions are needed, especially for chemotherapy-resistant tumors. Immune checkpoint inhibitors show promise for triple-negative breast cancer, but their effectiveness across all BC subtypes remains challenging. Therefore, novel strategies, including adoptive cellular therapy, employing patients own T lymphocytes expanded ex vivo, are under investigation. Previously, we demonstrated that cytotoxic T lymphocytes (CTLs) expressing high HLA-DR levels in the tumor microenvironment are associated with a good response to neoadjuvant chemotherapy (NACT), due to their pronounced anti-tumor properties compared to CTLs with low or no HLA-DR expression. In this paper, we demonstrated that HLA-DR expression in CTLs is crucial for efficient T lymphocytes-based therapies. MethodsTo clarify the role of HLA-DR in CTLs anti-tumor abilities, we performed in vitro and in vivo experiments. We also improved a protocol to expand ex vivo HLA-DR-expressing CTLs and employed a 3D co-culture platform to test the potential of different immune agents, namely an anti-PD1, anti-OX40, anti-VEGF and anti-CD137, on CTLs cytotoxicity against BC cells. Additionally, we conducted a bioinformatic analysis of scRNA-seq data of BC patients to better understand the modulation of HLA-DR expression in CTLs. ResultsOur findings revealed that CTLs require HLA-DR expression to eliminate tumor cells. Additionally, we unveiled that blocking HLA-DR or depleting CD4+ T cells compromised CTLs activation and cytotoxicity, suggesting antigen presentation by CTLs through HLA-DR, and CD4+ T cells, as probable mechanisms for CTLs increased anti-tumor immune response and treatment efficacy. We refined an ex vivo stimulation and cytokine supplementation protocol, observing that short-term stimulation increases HLA-DR expression while boosting CTLs functionality, unlike prolonged expansion. This result highlights the importance of prioritizing cell quality, over quantity, for therapy efficiency. Additionally, we verified that anti-PD-1 further increases HLA-DR levels in CTLs, enhancing their anti-tumor efficiency. Notably, an in silico analysis revealed that PD-1 in CTLs shares 34 co-expressed genes with HLA-DR, including several non-coding RNAs, suggesting a PD-1-mediated regulation of HLA-DR expression. ConclusionsGlobally, our findings underscore that heightening HLA-DR expression in CTLs, by combining anti-PD-1 with short-term stimulation, offers promise for improving T lymphocyte-based therapies for BC. Key MessageO_LIWhat is already known on this topic: While immunotherapy holds promise for breast cancer (BC), its success is still limited. Novel strategies are under investigation to improve outcomes across all BC subtypes. Previously we established a correlation between HLA-DR expression on CTLs and a positive response to neoadjuvant chemotherapy, likely due to enhanced anti-tumor properties of HLA-DR-expressing CTLs. However, the specific role of HLA-DR on CTLs and its implications for T lymphocyte-based therapies requires further investigation. C_LIO_LIWhat this study adds: This study revealed that HLA-DR expression is essential for CTLs to effectively eliminate tumor cells. Blocking HLA-DR or depleting CD4+ T cells impairs CTLs activation and cytotoxicity, indicating that HLA-DR-mediated antigen presentation and interaction with CD4+ T cell are crucial for CTLs function. The study also shows that combining ex vivo short-term stimulation and anti-PD-1 treatment increases HLA-DR levels in CTLs, enhancing their anti-tumor activity. C_LIO_LIHow this study might affect research, practice or policy: By emphasizing the importance of optimizing CTLs quality over quantity, this approach has the potential to improve the design of more efficient T lymphocyte-based therapies for BC. This could influence future research directions, clinical practices, and treatment policies, leading to improved therapeutic outcomes. C_LI

immunology↗

Estimating multimodal brain variability in schizophreniaspectrum disorders: A worldwide ENIGMA study

ObjectiveSchizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. MethodsThis meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. ResultsWe found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. ConclusionsHigher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

neuroscience↗

Connectome architecture shapes large-scale cortical reorganization in schizophrenia: a worldwide ENIGMA study

While schizophrenia is considered a prototypical network disorder characterized by widespread brain-morphological alterations, it still remains unclear whether distributed structural alterations robustly reflect underlying network layout. Here, we tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2,439 adults with schizophrenia and 2,867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n=207), we evaluated structural alterations of schizophrenia against two network susceptibility models: i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; ii) epicenter mapping, which identify regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Schizophrenia-related structural alterations co-localized with interconnected functional and structural hubs and harbored temporo-paralimbic and frontal epicenters. Findings were robust across sites and related to individual symptom profiles. We observed localized unique epicenters for first-episode psychosis and early stages, and transmodal epicenters that were shared across first-episode to chronic stages. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, yielding insights in pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work contributes to recognizing potentially common pathways to better understand macroscale structural alterations, and inter-individual variability in schizophrenia.

neuroscience↗

Biophysical modeling of the electric field magnitude and distribution induced by electrical stimulation with intracerebral electrodes

Intracranial electrodes are used clinically for diagnostic or therapeutic purposes, notably in drug-refractory epilepsy (DRE) among others. Visualization and quantification of the energy delivered through such electrodes is key to understanding how the resulting electric fields modulate neuronal excitability, i.e. the ratio between excitation and inhibition. Quantifying the electric field induced by electrical stimulation in a patient-specific manner is challenging, because these electric fields depend on a number of factors: electrode trajectory with respect to folded brain anatomy, biophysical (electrical conductivity / permittivity) properties of brain tissue and stimulation parameters such as electrode contacts position and intensity. Here, we aimed to evaluate various biophysical models for characterizing the electric fields induced by electrical stimulation in DRE patients undergoing stereoelectroencephalography (SEEG) recordings in the context of pre-surgical evaluation. This stimulation was performed with multiple-contact intracranial electrodes used in routine clinical practice. We introduced realistic 3D models of electrode geometry and trajectory in the neocortex. For the electrodes, we compared point (0D) and line (1D) sources approximations. For brain tissue, we considered three configurations of increasing complexity: a 6-layer spherical model, a toy model with a sulcus representation, replicating results from previous approaches; and went beyond the state-of-the-art by using a realistic head model geometry. Electrode geometry influenced the electric field distribution at close distances (~3 mm) from the electrode axis. For larger distances, the volume conductor geometry and electrical conductivity dominated electric field distribution. These results are the first step towards accurate and computationally tractable patient-specific models of electric fields induced by neuromodulation and neurostimulation procedures.

neuroscience↗