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Rosa, M.

Publications and source records attributed to Rosa, M..

16 recordsLinked to original sources

Rev-erbα inhibits vascular calcification by repressing osteogenic reprogramming in atherosclerosis

Background: Atherosclerotic plaque rupture is the most deleterious atherogenic event, responsible for the majority of fatal acute atherothrombotic and myocardial infarctions. Intimal microcalcification is a major cause of atherosclerotic plaque instability. Yet, a thorough characterization of the mechanisms controlling intimal calcification is needed to develop innovative therapeutic strategies to treat high risk patients. The nuclear receptor Rev-erb regulates lipoprotein metabolism and exerts anti-inflammatory activities. Here, we hypothesized that Rev-erb modulates atherogenesis by regulating arterial calcification processes. Methods: We used a multi-omics approach in the ANGIOSAFE and the ATHEROPORTAL human cohort to identify pathways and factors associated with vascular calcification in diabetic patients. We then compared REV-ERB expression between calcified and non-calcified areas of human endarterectomies using laser capture microdissection assays (n=11-22/group). We assessed the role of Rev-erb on calcium deposition and expression of osteoblast markers in aortic roots of 18-month-old Ldlr-/-Rev-erb-/- and Ldlr-/-Rev-erb+/+ mice (n=10/group). Rev-erb-dependent molecular pathways that drive calcification were identified using gene expression profiling in aortic plaques from Ldlr-/-Rev-erb-/- and Ldlr-/-Rev-erb+/+ mice (n=8-10/group). We then confirmed omics data using primary aortic smooth muscle cells (SMCs) (n=3-6) in vitro assessing inflammation-driven calcification process as well as Rev-erb-dependent transcriptional mechanisms. Results: REV-ERB expression is significantly lower in circulating anti-inflammatory classical CD14+CD16- monocytes from diabetic patients with low coronary artery calcium (CAC) compared to those exhibiting high CAC scores while its expression is lower in highly calcified plaques from patients with diabetes mellitus compared to those with no diabetes or no calcification. Consistently, REV-ERB is markedly downregulated in calcified areas of human endarterectomy samples, while remaining higher in non-calcified regions. Rev-erb deficient Ldlr-/- mice exhibit accelerated atherogenesis and vascular calcification, and aortic smooth muscle cells (SMCs) exhibit a reprogramming toward an osteochondroblastic phenotype. Functional in vitro studies show that Rev-erb maintains SMC identity by preventing their IL-1{beta}-driven transdifferentiation into osteochondroblast-like cells, notably through the repression of key osteogenic regulators. Finally, while hyaluronic acid degradation is known to promote intimal calcification, we demonstrate that Rev-erb represses the hyaluronidase Cemip expression during SMC transdifferentiation. Conclusions: Rev-erb is identified as an important brake on SMC-driven vascular calcification, suppressing both osteogenic reprogramming and matrix-remodeling pathways. Thus, this study opens new avenues for developing novel therapeutic tools targeting Rev-erb to reduce vascular calcification and associated cardiovascular risk in high-risk patients.

pathology↗

Automatic computational classification of bone marrow cells for B cell pediatric leukemia using UMAP

B Acute Lymphoblastic Leukemia (B-ALL) accounts for approximately 80% of pediatric leukemia cases. Despite treatment advances, 15-20% of children experience relapse, highlighting the need of improved monitoring of patients and novel strategies leading to successful therapies. Flow Cytometry is an essential technique for measuring residual disease and guiding treatment. However, traditional manual gating limits its efficiency. In recent years, computational tools have been integrated to enhance these clinical processes but many mathematical techniques are underexploited. Particularly, Uniform Manifold Approximation and Projection (UMAP), together with Machine Learning, provide promising approaches for analyzing large datasets. Mathematical tools and artificial intelligence offer new perspectives on these health problems, beyond the usual approach in biomedicine. We have exploited 234 samples from 75 B-ALL patients to develop an artificial intelligence-based algorithm that can improve patient classification and therapy decisions in different patient cohorts. This implies an advancement on the routine manual analysis of the disease progression, as we identify key subpopulations automatically, distinguishing patients bone marrow regeneration patterns, thus improving the prediction and prognosis of the disease. MSC Classification: 68-04, 68T09, 90C90, 92B05 Abbreviations: A list of abbreviations used throughout this work can be found in Appendix A.

cancer biology↗

Automated Collective Variable Discovery for MFSD2A transporter from molecular dynamics simulations

Biomolecules often exhibit complex free energy landscapes in which long-lived metastable states are separated by large energy barriers. Overcoming these barriers to robustly sample transitions between the metastable states with classical molecular dynamics (MD) simulations presents a challenge. To circumvent this issue, collective variable (CV)-based enhanced sampling MD approaches are often employed. Traditional CV selection relies on intuition and prior knowledge of the system. This approach introduces bias, which can lead to incomplete mechanistic insights. Thus, automated CV detection is desired to gain a deeper understanding of the system/process. Analysis of MD data with various machine learning algorithms, such as Principal Component Analysis (PCA), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA)-based approaches have been implemented for automated CV detection. However, their performance has not been systematically evaluated on structurally and mechanistically complex biological systems. Here, we applied these methods to MD simulations of the MFSD2A (Major Facilitator Superfamily Domain 2A) lysolipid transporter in multiple functionally relevant metastable states with the goal of identifying optimal CVs that would structurally discriminate these states. Specific emphasis was on the automated detection and interpretive power of LDA-based CVs. We found that LDA methods, which included a novel gradient descent-based multiclass harmonic variant, termed GDHLDA, we developed here, outperform PCA in class separation, exhibiting remarkable consistency in extracting CVs critical for distinguishing metastable states. Furthermore, the identified CVs included features previously associated with conformational transitions in MFSD2A. Specifically, conformational shifts in transmembrane helix 7 and in residue Y294 on this helix emerged as critical features discriminating the metastable states in MFSD2A. This highlights the effectiveness of LDA-based approaches in automatically extracting from MD trajectories CVs of functional relevance that can be used to drive biased MD simulations to efficiently sample conformational transitions in the molecular system. STATEMENT OF SIGNIFICANCETo elucidate the biological mechanisms of pertinent biomolecules, it is crucial to understand their complex free energy landscapes. Such landscapes are often constructed from molecular dynamics (MD) simulations using collective variable (CV)-guided enhanced sampling methods. Identifying proper CVs for this task is critical but can be challenging with traditional intuition-based approaches. Here we propose an automated protocol for CV discovery which is based on linear discriminant analysis (LDA) for dimensionality reduction of MD data. By applying the protocol to MD simulations of the MFSD2A lysolipid transporter, a structurally and mechanistically complex biological system, we show that LDA-based methods efficiently detect system-specific CVs that accurately classify different metastable states of MFSD2A and are highly interpretable in a detailed structural context.

biophysics↗

Faecal microbiota transplantation from Alzheimer's participants induces impairments in neurogenesis and cognitive behaviours in rats

The gut microbiome is emerging as an important susceptibility factor in Alzheimers disease (AD) possibly due to the increased prevalence of pro-inflammatory genera in gut microbiota of AD participants. Microbiota-mediated changes in cognition and adult hippocampal neurogenesis (AHN), an important process for memory which is altered in AD, position the microbiota-gut-brain axis as a key regulator of AD. However, it is unknown whether gut microbiota alterations are the cause or consequence of AD symptoms. We transplanted faecal microbiota from AD participants and age-matched controls into microbiota-depleted naive adult rats and found impairments in AHN and associated memory tasks, which correlated with clinical cognitive scores. Discrete changes in the rat caecal and hippocampal metabolome were evident. Serum from AD participants also decreased neurogenesis in vitro and correlated with cognitive scores and pro-inflammatory genera. Our results reveal that the cognitive symptoms in AD may be due to alterations in gut microbiota, and that impaired neurogenesis may be a mechanistic link between altered gut microbiota and cognitive impairment in AD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=191 SRC="FIGDIR/small/515189v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@143263forg.highwire.dtl.DTLVardef@1842a23org.highwire.dtl.DTLVardef@1ea8aaborg.highwire.dtl.DTLVardef@135e5a3_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Cancer-Associated Mutations Enhance The Sensitivity Of The Trupath GαQ/11 System

G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors and are a common drug target. They can be stabilised in different conformational states by ligands to activate multiple transducers and effectors leading to a variety of cellular responses. The potential of agonists to activate select pathways has important implications for drug discovery. Thus, there is a clear need to profile the initial GPCR signal transduction event, activation of G proteins, to enhance understanding of receptor coupling and guide drug design. The BRET-based biosensor suite, TRUPATH, was recently developed to enable quantification of the activation profiles of all non-visual G proteins (excluding Golf and G14) and has since been utilised in numerous studies. However, it fails to detect Gq/11 activation for a number of GPCRs previously reported to display promiscuous secondary coupling to Gq/11. Here we report modifications to the Gq and G11 biosensors in the switch I region that prevent intrinsic GTPase activity (R183C/Q). Except for the PAC1R, substitution with cancer-associated mutations, Cys or Gln, significantly increased sensitivity to allow detection of robust, reliable, and representative Gq/11 responses to Class B1 GPCRs. We also demonstrate the utility of these modified biosensors for promiscuously coupled class A GPCR that have primary Gs-coupling. Thus, we propose that modification to Gq/11 may also be necessary in other biosensor systems to enable detection of Gq/11 activation.

pharmacology and toxicology↗

Breast Cancer Reaction-Diffusion from Spectral-Spatial Analysis in Immunohistochemistry

Cancer is a prevalent disease, and while many significant advances have been made, the ability to accurately predict how an individual tumor will grow - and ultimately respond to therapy - remains limited. We use spatial-spectral analysis of 20 patients accrued to a phase II study of preoperative SABR with 9.5 x 3 Gy for early-stage breast cancer whose tissues were stained with multiplex immunofluorescence. We employ the reaction-diffusion framework to compare the data-deduced two-point correlation function and the corresponding spatial power spectral distribution with the theoretically predicted ones. A single histopathological slice suffices to characterize the reaction-diffusion equation dynamics through its power spectral density giving us an interpretative key in terms of infiltration and diffusion of cancer on a per-patient basis. This novel approach tackles model-parameter-inference problems for tumor infiltration and can immediately inform clinical treatments.

cancer biology↗

Structural dynamics of the β-coronavirus Mpro protease ligand binding sites

{beta}-coronaviruses alone have been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a back-up against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensible role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all non-redundant ligand-binding sites available for SARS-CoV2, SARS-CoV and MERS-CoV Mpro. Extensive adaptive sampling has been used to explore conformational dynamics employing convolutional variational auto encoder-based deep learning, and investigates structural conservation of the ligand binding sites using Markov state models across {beta}-coronavirus homologs. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across {beta}-coronavirus homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.

biophysics↗

A collaborative resource platform for non-human primate neuroimaging

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.

neuroscience↗

A \"twisted\" visual field map in the primate cortex predicted by topographic continuity

Adjacent neurons in visual cortex have overlapping receptive fields within and across area boundaries, an arrangement which is theorized to minimize wiring cost. This constraint is thought to create retinotopic maps of opposing field sign (mirror and non-mirror representations of the visual field) in adjacent visual areas, a concept which has become central in current attempts to subdivide the cortex. We modelled a realistic developmental scenario in which adjacent areas do not mature simultaneously, but need to maintain topographic continuity across their borders. This showed that the same mechanism that is hypothesized to maintain topographic continuity within each area can lead to a more complex type of retinotopic map, consisting of sectors with opposing field sign within a same area. Using fully quantitative electrode array recordings, we then demonstrate that this type of map exists in the primate extrastriate cortex.

neuroscience↗

Different Whole-Brain Functional Connectivity Correlates of Reactive-Proactive Aggression and Callous-Unemotional Traits in Disruptive Children and Adolescents

BackgroundDisruptive behavior in children and adolescents can manifest itself in reactive (RA) and proactive (PA) aggression and is modulated by callous-unemotional (CU) traits and comorbidity. Research on aggression subtype-specific neural correlates is limited and the role of comorbid symptoms largely neglected.\n\nMethodsThe current multi-center study extended previous efforts by investigating unrestricted resting state functional connectivity (rsFC) alterations. The large sample (n = 207) of children and adolescents aged 8 - 18 years (mean age = 13.30 {+/-} 2.60 years) included 118 cases with disruptive behavior (80 diagnosed with Oppositional Defiant Disorder and/or Conduct Disorder) and 89 controls. Attention-deficit/hyperactivity disorder (ADHD) and anxiety symptoms were added as covariates. We measured changes in global and local voxel-to-voxel rsFC using functional magnetic resonance imaging at 3T (mean acquisition time = 8 min 25 sec).\n\nResultsCompared to controls, cases demonstrated altered rsFC including frontal areas when anxiety but not ADHD symptoms were considered. Within cases, RA and PA scores related to changes in global and local rsFC in central gyrus and precuneus previously linked to aggression-related impairments. CU trait severity correlated with global rsFC alterations including inferior and middle temporal gyrus implicated in empathy, emotion, and reward-related activity. Importantly, most observed aggression subtype-specific patterns could only be identified when ADHD and anxiety problems were also accounted for.\n\nConclusionsThe current study clarifies that distinct though overlapping brain connectivity measures can disentangle differing manifestations of aggressive behavior. Moreover, our results highlight the importance of considering comorbid symptoms for detecting aggression-related rsFC alterations.

neuroscience↗

Tetraploidy in rodent cardiac stem cells confers enhanced biological properties

Ploidy for cardiomyocytes is well described but remains obscure in cardiac interstitial cells (CICs). Ploidy of c-kit+CICs were assessed using a combination of confocal, karyotypic, and flow cytometric assessments coupled with molecular and bioinformatic analyses. Fundamental differences were found between cultured rodent (rat, mouse) c-kit+CICs possessing mononuclear tetraploid (4n) content versus large mammal (human, swine) with mononuclear diploid (2n) content. In-situ analysis, confirmed with fresh isolates, revealed diploid content in c-kit+CICs from human and a mixture of diploid and tetraploid nuclei in mouse. Molecular assessment of the p53 signaling pathway provides a plausible explanation for escape from replicative senescence in rodent but not human ckit+CICs. Single cell transcriptional profiling reveals distinctions between diploid versus tetraploid populations in mouse ckit+CICs, alluding to functional divergences. Collectively, these data reveal fundamental species-specific biological differences in c-kit+CICs that could account for challenges in extrapolation of myocardial preclinical studies from rodent to large animal models.

cell biology↗

Topographic organization of the third tier dorsomedial visual cortex in the macaque

The boundaries of the visual areas located anterior to V2 in the dorsomedial region of the macaque cortex remain contentious. This region is usually conceptualized as including two functional subdivisions: the dorsal component of area V3 (V3d), laterally, and another area, named the parietooccipital area (PO) or V6, medially. However, the nature of the putative border between V3d and PO/V6 has remained undefined. We recorded the receptive fields of multiunit clusters in adult male macaques, and reconstructed the locations of recording sites using histological sections and \"unfolded\" cortical maps. Immediately adjacent to dorsomedial V2 we observed a representation of the lower contralateral quadrant, which represented the vertical meridian at its rostral border. This region, corresponding to V3d of previous studies, formed a simple eccentricity gradient, from approximately <5{degrees} in the annectant gyrus, to >60{degrees} in the parietooccipital sulcus. However, there was no topographic reversal where one would expect to find the border between V3d and PO/V6. Rather, near the midline, this lower quadrant map continued directly into a representation of the peripheral upper visual field, without an intervening lower quadrant representation that could be unambiguously assigned to PO/V6. Thus, V3d and PO/V6 form a continuous topographic map, which includes parts of both quadrants. Together with previous observations that V3d and PO/V6 are both densely myelinated relative to adjacent cortex, and share similar input from V1, these results suggest that they are parts of a single area, which is distinct from the one forming the ventral component of the third tier complex.\n\nSignificance statementThe primate visual cortex has a large number of areas. Knowing the extent of each visual area, and how they can be distinguished from each other, are essential for the interpretation of experiments aimed at understanding visual processing. Currently, there are conflicting models of the organization of the dorsomedial visual cortex rostral to area V2 (one of the earliest stages of cortical processing of vision). By conducting large-scale electrophysiological recordings, we found that what were originally thought to be distinct areas in this region (dorsal V3, and the parietooccipital area [PO/V6]), together form a single map the visual field. These results will help guide future functional studies, and the interpretation of the outcomes of lesions involving the dorsal visual cortex.

neuroscience↗

Reactive/proactive aggression specific cortical and subcortical alterations in children and adolescents with disruptive behavior

ObjectiveMaladaptive aggression, as present in conduct disorder (CD) and, to a lesser extent, oppositional defiant disorder (ODD), has been associated with structural alterations in various brain regions, such as ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), amygdala, insula and ventral striatum. Although aggression can be subdivided into reactive and proactive subtypes, no neuroimaging studies have yet investigated if any structural brain alterations are associated with either of the subtypes specifically. Here we investigated this association in predefined regions of interest.\n\nMethodT1-weighted magnetic resonance images were acquired from 158 children and adolescents with aggressive behavior (ODD/CD) and 96 controls in a multi-centre study. Aggression subtypes were assessed by questionnaires. Cortical volume and subcortical volumes and shape were determined using Freesurfer and the FMRIB integrated registration and segmentation tool. Associations between volumes and continuous measures of aggression were established using multilevel linear mixed effects models.\n\nResultsIn cases only proactive aggression was negatively associated with amygdala volume (b=-11.82, p=0.05), while reactive aggression was negatively associated with insula volume (b=-46.41, p=0.01). Classical group comparison showed that children and adolescents with aggressive behavior had smaller volumes than controls in (bilateral) ventral striatum (p=0.003), ACC (p=0.01), and vmPFC (p=0.003) with modest effect sizes.\n\nConclusionsAggression was associated with reduced volume in brain regions involved in decision making. Negative associations were found between reactive aggression and volumes in regions involved in threat responsivity and between proactive aggression and regions linked to empathy. This provides evidence for aggression subtype-specific alterations in brain structure.

neuroscience↗

Aggression Subtypes Relate to Distinct Resting State Functional Connectivity in Disruptive Children and Adolescents

ObjectiveThere is increasing evidence to suggest altered resting state functional connectivity (rsFC) in adolescents with conduct problems. However, no rsFC studies have addressed the effects of reactive and proactive aggression. Herein, we examined the associations between these aggression subtypes along with subdimensions of callous-unemotional (CU) traits and rsFC using predefined seeds in aggression-related salience network (SN) and default mode network (DMN).\n\nMethodAggression subtype-specific whole-brain rsFC of SN and DMN seeds was investigated in a resting state sequence (mean acquisition time = 8 min 25 sec) acquired from 207 children and adolescents of both sexes aged 8 - 18 years (mean age (SD) = 13.30 (2.60) years; range = 8.02 - 18.35) in a multi-center study. One hundred eighteen individuals exhibited disruptive behavior (conduct disorder/oppositional defiant disorder) with different levels of comorbid ADHD symptoms, 89 were healthy.\n\nResultsCompared to healthy controls, cases demonstrated reduced DMN and - after controlling for ADHD scores - SN seed-based rsFC with left hemispheric frontal clusters. We found increased and distinct aggression-subtype specific rsFC patterns in brain regions linked to processes like emotion, empathy, moral, cognitive control, and decision-making. Specifically, reactive and proactive aggression correlated with distinct SN and DMN seed-based rsFC patterns. CU dimensions led to different DMN and SN rsFC with clusters including frontal, parietal, and cingulate areas, with uncaring-related clusters extended to cerebellar regions.\n\nConclusionsThis first study investigating reactive and proactive aggression along with CU dimensions reveals new subtype-specific whole-brain rsFC patterns, extending the knowledge of neural networks to further distinct forms of disruptive behavior.

neuroscience↗

Continuity between koniocellular layers of dorsal lateral geniculate and inferior pulvinar nuclei in common marmosets

In primates, the koniocellular (K) layers of the dorsal lateral geniculate nucleus (LGN) and the calbindin-rich subdivisions of the inferior pulvinar (IPul) nucleus are considered part of a thalamic matrix system which projects diffusely to superficial cortical layers. Activity in the matrix system is proposed to coordinate oscillatory activity in thalamocortical loops. Further, since both K cells and IPul are involved in visual processing pathways, especially in alternative pathways to visual cortex after V1 lesion in early life (\"blindsight\"), their functional similarities have been strongly implicated. Here we tested the hypothesis that calbindin-positive K cells and IPul cells constitute a continuous group of cells. By combining immunohistochemistry and a high-throughput neuronal tracing method, we found that both K cells and IPul form reciprocal connections with striate and extrastriate cortices; whereas principal laminae of LGN do not receive inputs from extrastriate cortex and only project sparsely to these areas. Retrograde labelled cells in lateral division of IPul merged seamlessly into the retrograde labelled cells in K layers. These results supported the continuity between LGN K layers and IPul, providing the anatomical basis for functional congruity of this part of dorsal thalamic matrix.

neuroscience↗

Classification and characterisation of brain network changes in chronic back pain: a multicenter study.

Chronic pain is a common and often disabling condition, and is thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. Here, we investigated brain network architecture using resting state fMRI data collected from chronic back pain patients in UK and Japan (41 patients, 56 controls). Using a machine learning approach (support vector machine), we found that brain network patterns reliably classified chronic pain patients in a third, independent open data set with an accuracy of 63%, whilst 68% was attained in cross validation of all data. We then developed a deep learning classifier using a conditional variational autoencoder, which also yield yielded 63% generalisation and 68% cross-validation accuracy. Given the existence of reliable network changes, we next studied the graph topology of the network, and found consistent evidence of hub disruption based on clustering and betweenness centrality of brain nodes in pain patients. To examine this in more detail, we developed a multislice modularity algorithm to identify a consensus pattern of modular reorganisation of brain nodes across the entire data set. This revealed evidence of significant changes in the modular identity of several brain regions, most notably including broad regions of bilateral sensorimotor cortex, subregions of which also contributed to classifier performance. These results provide evidence of consistent and characteristic brain network changes in chronic pain, and highlight extensive reorganisaton of the network architecture of sensorimotor cortex.

neuroscience↗