Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster.

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

Generating parallel representations of position and identity in the olfactory system.

In Drosophila, a dedicated olfactory channel senses a male pheromone, cis-vaccenyl acetate (cVA), promoting female courtship while repelling males. Here, we show that separate cVA-processing streams extract qualitative and positional information. cVA sensory neurons respond to concentration differences in a 5-mm range around a male. Second-order projection neurons encode the angular position of a male by detecting inter-antennal differences in cVA concentration, which are amplified through contralateral inhibition. At the third circuit layer, we identify 47 cell types with diverse input-output connectivity. One population responds tonically to male flies, a second is tuned to olfactory looming, while a third integrates cVA and taste to coincidentally promote female mating. The separation of olfactory features resembles the mammalian what and where visual streams; together with multisensory integration, this enables behavioral responses appropriate to specific ethological contexts.

Integration of Parallel Opposing Memories Underlies Memory Extinction.

Accurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment, a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.

Network statistics of the whole-brain connectome of Drosophila.

Brains comprise complex networks of neurons and connections, similar to the nodes and edges of artificial networks. Network analysis applied to the wiring diagrams of brains can offer insights into how they support computations and regulate the flow of information underlying perception and behaviour. The completion of the first whole-brain connectome of an adult fly, containing over 130,000 neurons and millions of synaptic connections1-3, offers an opportunity to analyse the statistical properties and topological features of a complete brain. Here we computed the prevalence of two- and three-node motifs, examined their strengths, related this information to both neurotransmitter composition and cell type annotations4,5, and compared these metrics with wiring diagrams of other animals. We found that the network of the fly brain displays rich-club organization, with a large population (30% of the connectome) of highly connected neurons. We identified subsets of rich-club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex ( https://codex.flywire.ai ) and should serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

The fly connectome reveals a path to the effectome.

A goal of neuroscience is to obtain a causal model of the nervous system. The recently reported whole-brain fly connectome1-3 specifies the synaptic paths by which neurons can affect each other, but not how strongly they do affect each other in vivo. To overcome this limitation, we introduce a combined experimental and statistical strategy for efficiently learning a causal model of the fly brain, which we refer to as the 'effectome'. Specifically, we propose an estimator for a linear dynamical model of the fly brain that uses stochastic optogenetic perturbation data to estimate causal effects and the connectome as a prior to greatly improve estimation efficiency. We validate our estimator in connectome-based linear simulations and show that it recovers a linear approximation to the nonlinear dynamics of more biophysically realistic simulations. We then analyse the connectome to propose circuits that dominate the dynamics of the fly nervous system. We discover that the dominant circuits involve only relatively small populations of neurons-thus, neuron-level imaging, stimulation and identification are feasible. This approach also re-discovers known circuits and generates testable hypotheses about their dynamics. Overall, we provide evidence that fly whole-brain dynamics are generated by a large collection of small circuits that operate largely independently of each other. This implies that a causal model of a brain can be feasibly obtained in the fly.

A Drosophila computational brain model reveals sensorimotor processing.

The recent assembly of the adult Drosophila melanogaster central brain connectome, containing more than 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain1,2. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity3, to study circuit properties of feeding and grooming behaviours. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation4. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing5-a testable hypothesis that we validate by optogenetic activation and behavioural studies. Activating different classes of gustatory neurons in the model makes accurate predictions of how several taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit, and accurately describes the circuit response upon activation of different mechanosensory subtypes6-10. Our results demonstrate that modelling brain circuits using only synapse-level connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can describe complete sensorimotor transformations.

Neuronal wiring diagram of an adult brain.

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative1-6, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 107 chemical synapses7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster8,9. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities10-12. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

Whole-brain annotation and multi-connectome cell typing of Drosophila.

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set.

We develop an automatic method for synaptic partner identification in insect brains and use it to predict synaptic partners in a whole-brain electron microscopy dataset of the fruit fly. The predictions can be used to infer a connectivity graph with high accuracy, thus allowing fast identification of neural pathways. To facilitate circuit reconstruction using our results, we develop CIRCUITMAP, a user interface add-on for the circuit annotation tool CATMAID.

Long-Term Trajectories of Biomarkers, Functional, and Echocardiographic Parameters in Patients with Chronic Heart Failure from Dilated or Ischaemic Cardiomyopathy.

INTRODUCTION: The long-term evolution of clinical, echocardiographic, and laboratory parameters of cardiac function in patients with chronic heart failure (HF) with either reduced (HFrEF) or mildly reduced (HFmrEF) left ventricular ejection fraction (LVEF) is incompletely characterised. METHODS: We identified patients with chronic stable HF who presented at least twice to a university HF outpatient clinic between 1995 and 2021. Trajectories of NYHA functional class, LVEF, left ventricular internal end-diastolic diameter (LVIDD), NT-proBNP concentrations, and HF treatment over 10 years of follow-up were analysed using fractional polynomials. Analyses were repeated after stratifying patients according to aetiology (ischaemic vs. dilated) or HF category (HFrEF vs. HFmrEF). RESULTS: A total of 2,132 patients were included, of whom 51% had ischaemic and 49% had dilated HF. Eighty six percent and 14% were classified as HFrEF and HFmrEF, respectively. Mean LVEF was 28 ± 10%, and median NT-proBNP and estimated glomerular filtration rate values were 1,170 (385-3,176) pmol/L and 81 (62-100) mL/min/1.73 m2, respectively. Median follow-up was 5.2 (2.6-9.2) years. Overall, NYHA functional class and LVIDD trajectories were U-shaped, whereas LVEF and NT-proBNP concentrations markedly improved during the first year and remained stable thereafter. However, the evolution of HF parameters significantly differed with respect to HF category and aetiology, with greater improvements seen in patients with HFrEF of non-ischaemic origin. Improvements in HF variables were associated with optimization of HF therapy, notably with initiation and up-titration of renin-angiotensin-system blockers. CONCLUSION: This study provides insights into the natural history of HF in a large cohort of well-treated chronic HF outpatients with respect to subgroups of HF and different aetiologists.

Ligand-activated RXFP1 gene therapy ameliorates pressure overload-induced cardiac dysfunction.

Recurrent episodes of decompensated heart failure (HF) represent an emerging cause of hospitalizations in developed countries with an urgent need for effective therapies. Recently, the pregnancy-related hormone relaxin (RLN) was found to mediate cardio-protective effects and act as a positive inotrope in the cardiovascular system. RLN binds to the RLN family peptide receptor 1 (RXFP1), which is predominantly expressed in atrial cardiomyocytes. We therefore hypothesized that ventricular RXFP1 expression might exert potential therapeutic effects in an in vivo model of cardiac dysfunction. Thus, mice were exposed to pressure overload by transverse aortic constriction and treated with AAV9 to ectopically express RXFP1. To activate RXFP1 signaling, RLN was supplemented subcutaneously. Ventricular RXFP1 expression was well tolerated. Additional RLN administration not only abrogated HF progression but restored left ventricular systolic function. In accordance, upregulation of fetal genes and pathological remodeling markers were significantly reduced. In vitro, RLN stimulation of RXFP1-expressing cardiomyocytes induced downstream signaling, resulting in protein kinase A (PKA)-specific phosphorylation of phospholamban (PLB), which was distinguishable from ß-adrenergic activation. PLB phosphorylation corresponded to increased calcium amplitude and contractility. In conclusion, our results demonstrate that ligand-activated cardiac RXFP1 gene therapy represents a therapeutic approach to attenuate HF with the potential to adjust therapy by exogenous RLN supplementation.

Selection of motor programs for suppressing food intake and inducing locomotion in the Drosophila brain.

Central mechanisms by which specific motor programs are selected to achieve meaningful behaviors are not well understood. Using electrophysiological recordings from pharyngeal nerves upon central activation of neurotransmitter-expressing cells, we show that distinct neuronal ensembles can regulate different feeding motor programs. In behavioral and electrophysiological experiments, activation of 20 neurons in the brain expressing the neuropeptide hugin, a homolog of mammalian neuromedin U, simultaneously suppressed the motor program for food intake while inducing the motor program for locomotion. Decreasing hugin neuropeptide levels in the neurons by RNAi prevented this action. Reducing the level of hugin neuronal activity alone did not have any effect on feeding or locomotion motor programs. Furthermore, use of promoter-specific constructs that labeled subsets of hugin neurons demonstrated that initiation of locomotion can be separated from modulation of its motor pattern. These results provide insights into a neural mechanism of how opposing motor programs can be selected in order to coordinate feeding and locomotive behaviors.

The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae.

Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva - because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour-taste associative learning, as well as light/dark-electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages.

AAV6.ßARKct cardiac gene therapy ameliorates cardiac function and normalizes the catecholaminergic axis in a clinically relevant large animal heart failure model.

AIMS: G protein-coupled receptor kinase 2 (GRK2), which is markedly upregulated in failing human myocardium, has been implicated as a contributing factor or consequence of heart failure (HF). Importantly, cardiac-specific GRK2 knockout mice have recently proved the pathological nature of GRK2 in HF. Targeted inhibition of GRK2 is possible using a peptide inhibitor known as the ßARKct, which has rescued several disparate small animal HF models. This study was designed to evaluate long-term ßARKct expression in a clinically relevant large animal HF model, using stable myocardial gene delivery with adeno-associated virus serotype 6 (AAV6). METHODS AND RESULTS: A porcine model of HF subsequent to left ventricular (LV) myocardial infarction (MI) was used to study the effects of retrograde injection into the anterior interventricular vein of either AAV6.ßARKct or AAV6.luciferase as a control 2 weeks after MI. Echocardiography and LV hemodynamics were performed before and 6 weeks after gene transfer. Robust and long-term ßARKct expression was found after AAV6-mediated delivery, leading to significant amelioration of LV haemodynamics and contractile function in HF pigs compared with AAV6.luciferase-treated control animals that showed a continued decline in cardiac function. Interestingly, the neurohormonal axis was virtually normalized in AVV6.ßARKct-treated HF animals, represented by reductions in plasma norepinephrine levels, whereas AAV6.luciferase-treated pigs showed further increases in plasma catecholamine levels. As a result, LV remodelling and foetal gene expression was reversed by AVV6.ßARKct gene therapy. CONCLUSION: These data--showing sustained amelioration of cardiac function in a post-MI pig HF model--demonstrate the therapeutic potential of ßARKct gene therapy for HF.

Serotonergic modulation of swallowing in a complete fly vagus nerve connectome.

How the body interacts with the brain to perform vital life functions, such as feeding, is a fundamental issue in physiology and neuroscience. Here, we use a whole-animal scanning transmission electron microscopy volume of Drosophila to map the neuronal circuits that connect the entire enteric nervous system to the brain via the insect vagus nerve at synaptic resolution. We identify a gut-brain feedback loop in which Piezo-expressing mechanosensory neurons in the esophagus convey food passage information to a cluster of six serotonergic neurons in the brain. Together with information on food value, these central serotonergic neurons enhance the activity of serotonin receptor 7-expressing motor neurons that drive swallowing. This elemental circuit architecture includes an axo-axonic synaptic connection from the glutamatergic motor neurons innervating the esophageal muscles onto the mechanosensory neurons that signal to the serotonergic neurons. Our analysis elucidates a neuromodulatory sensory-motor system in which ongoing motor activity is strengthened through serotonin upon completion of a biologically meaningful action, and it may represent an ancient form of motor learning.

Favorable safety profile of NOAC therapy in patients after tricuspid transcatheter edge-to-edge repair.

BACKGROUND: Transcatheter edge-to-edge repair for severe tricuspid regurgitation (TR) is a new treatment option (t-TEER). Data on optimal antithrombotic therapy after t-TEER in patients with an indication for anticoagulation are scarce and evidence-based guideline recommendations are lacking. We sought to investigate efficacy and safety of novel oral anticoagulation (NOAC) and vitamin-K-antagonists (VKA) in patients undergoing t-TEER. METHODS: Among 78 consecutive patients with t-TEER of severe TR, 69 patients were identified with concomitant indication for oral anticoagulation. Outcomes of these patients treated with NOAC or VKA were compared over a median follow-up period of 327 (177-460) days. RESULTS: Despite elevated thromboembolic and bleeding risk scores (CHA2DS2-VASc 4.2 ± 1.1, HEMORR2HAGES 3.0 ± 1.0 and HAS-BLED 2.1 ± 0.8), only one major bleeding incidence occurred under NOAC therapy. The risk for overall (NOAC 8% vs. VKA group 26%, p = 0.044) and major bleeding events (NOAC 2% vs. VKA 21%, p = 0.010) was significantly lower in the NOAC compared to the VKA group. No significant difference was found between NOAC and VKA treatment in terms of mortality (NOAC 18% vs. VKA 16%, p = 0.865) or the combined endpoint of death, heart failure hospitalization, stroke, embolism, thrombosis, myocardial infarction, and severe bleeding (NOAC 48% vs. VKA 42%, p = 0.801). A comparison between apixaban (n = 27) and rivaroxaban (n = 16) treated patients revealed no significant differences between NOAC substances (all bleeding events apixaban 7% vs. rivaroxaban 13%, p = 0.638). CONCLUSION: Results of this study indicate that NOACs may offer a favorable risk-benefit profile for patients with concomitant indication for anticoagulation therapy following t-TEER.

Increase of Cardiac Autoantibodies Against Beta-2-adrenergic Receptor During Acute Cellular Heart Transplant Rejection.

BACKGROUND: Acute cellular rejection (ACR) in heart transplant (HTx) recipients may be accompanied by cardiac cell damage with subsequent exposure to cardiac autoantigens and the production of cardiac autoantibodies (aABs). This study aimed to evaluate a peptide array screening approach for cardiac aABs in HTx recipients during ACR (ACR-HTx). METHODS: In this retrospective single-center observational study, sera from 37 HTx recipients, as well as age and sex-matched healthy subjects were screened for a total of 130 cardiac aABs of partially overlapping peptide sequences directed against structural proteins using a peptide array approach. RESULTS: In ACR-HTx, troponin I (TnI) serum levels were found to be elevated. Here, we could identify aABs against beta-2-adrenergic receptor (ß-2AR: EAINCYANETCCDFFTNQAY) to be upregulated in ACR-HTx (intensities: 0.80 versus 1.31, P = 0.0413). Likewise, patients positive for ß-2AR aABs showed higher TnI serum levels during ACR compared with aAB negative patients (10.0 versus 30.0 ng/L, P = 0.0375). Surprisingly, aABs against a sequence of troponin I (TnI: QKIFDLRGKFKRPTLRRV) were found to be downregulated in ACR-HTx (intensities: 3.49 versus 1.13, P = 0.0025). A comparison in healthy subjects showed the same TnI sequence to be upregulated in non-ACR-HTx (intensities: 2.19 versus 3.49, P = 0.0205), whereas the majority of aABs were suppressed in non-ACR-HTx. CONCLUSIONS: Our study served as a feasibility analysis for a peptide array screening approach in HTx recipients during ACR and identified 2 different regulated aABs in ACR-HTx. Hence, further multicenter studies are needed to evaluate the prognostic implications of aAB testing and diagnostic or therapeutic consequences.

Network Statistics of the Whole-Brain Connectome of Drosophila.

Brains comprise complex networks of neurons and connections. Network analysis applied to the wiring diagrams of brains can offer insights into how brains support computations and regulate information flow. The completion of the first whole-brain connectome of an adult Drosophila, the largest connectome to date, containing 130,000 neurons and millions of connections, offers an unprecedented opportunity to analyze its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We discovered that the network of the fly brain displays rich club organization, with a large population (30% percent of the connectome) of highly connected neurons. We identified subsets of rich club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex and will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

From connectome to effectome: learning the causal interaction map of the fly brain.

A long-standing goal of neuroscience is to obtain a causal model of the nervous system. This would allow neuroscientists to explain animal behavior in terms of the dynamic interactions between neurons. The recently reported whole-brain fly connectome [1-7] specifies the synaptic paths by which neurons can affect each other but not whether, or how, they do affect each other in vivo. To overcome this limitation, we introduce a novel combined experimental and statistical strategy for efficiently learning a causal model of the fly brain, which we refer to as the "effectome". Specifically, we propose an estimator for a dynamical systems model of the fly brain that uses stochastic optogenetic perturbation data to accurately estimate causal effects and the connectome as a prior to drastically improve estimation efficiency. We then analyze the connectome to propose circuits that have the greatest total effect on the dynamics of the fly nervous system. We discover that, fortunately, the dominant circuits significantly involve only relatively small populations of neurons-thus imaging, stimulation, and neuronal identification are feasible. Intriguingly, we find that this approach also re-discovers known circuits and generates testable hypotheses about their dynamics. Overall, our analyses of the connectome provide evidence that global dynamics of the fly brain are generated by a large collection of small and often anatomically localized circuits operating, largely, independently of each other. This in turn implies that a causal model of a brain, a principal goal of systems neuroscience, can be feasibly obtained in the fly.

An ex-vivo and in-vitro dynamic simulator for surgical and transcatheter mitral valve interventions.

PURPOSE: Minimally invasive mitral valve surgery (MIMVS) and transcatheter edge-to-edge repair (TEER) are complex procedures used to treat mitral valve (MV) pathologies, but with limited training opportunities available. To enable training, a realistic hemodynamic environment is needed. In this work we aimed to develop and validate a simulator that enables investigation of MV pathologies and their repair by MIMVS and TEER in a hemodynamic setting. METHODS: Different MVs were installed in the simulator, and pressure, flow, and transesophageal echocardiographic measurements were obtained. To confirm the simulator's physiological range, we first installed a biological prosthetic, a mechanical prosthetic, and a competent excised porcine MV. Subsequently, we inserted two porcine MVs-one with induced chordae tendineae rupture and the other with a dilated annulus, along with a patient-specific silicone valve extracted from echocardiography with bi-leaflet prolapse. Finally, TEER and MIMVS procedures were conducted by experts to repair the MVs. RESULTS: Systolic pressures, cardiac outputs, and regurgitations volumes (RVol) with competent MVs were 119 ± 1 mmHg, 4.78 ± 0.16 l min-1, and 5 ± 3 ml respectively, and thus within the physiological range. In contrast, the pathological MVs displayed increased RVols. MIMVS and TEER resulted in a decrease in RVols and mitigated the severity of mitral regurgitation. CONCLUSION: Ex-vivo modelling of MV pathologies and repair procedures using the described simulator realistically replicated physiological in-vivo conditions. Furthermore, we showed the feasibility of performing MIMVS and TEER at the simulator, also at patient-specific level, thus providing new clinical perspectives in terms of training modalities and personalized planning.