Biological Fidelity Research Articles

Understanding the functional roles of modelling components in spiking neural networks

Abstract Spiking neural networks (SNNs), inspired by the neural circuits of the brain, are promising in achieving high computational efficiency with biological fidelity. Nevertheless, it is quite difficult to optimize SNNs because the functional roles of their modelling components remain unclear. By designing and evaluating several variants of the classic model, we systematically investigate the functional roles of key modelling components, leakage, reset, and recurrence, in leaky integrate-and-fire (LIF) based SNNs. Through extensive experiments, we demonstrate how these components influence the accuracy, generalization, and robustness of SNNs. Specifically, we find that the leakage plays a crucial role in balancing memory retention and robustness, the reset mechanism is essential for uninterrupted temporal processing and computational efficiency, and the recurrence enriches the capability to model complex dynamics at a cost of robustness degradation. With these interesting observations, we provide optimization suggestions for enhancing the performance of SNNs in different scenarios. This work deepens the understanding of how SNNs work, which offers valuable guidance for the development of more effective and robust neuromorphic models.

Designer cellular spheroids with DNA origami for drug screening.

Current in vitro models struggle to balance the complexity of human diseases with suitability for large-scale drug tests. While 3D cultures simulate human tissues, they lack cellular intricacy, and integrating these models with high-throughput drug screening remains a challenge. Here, we introduce a method that uses self-assembling nucleic acid nanostructures decorated living cells, termed NACs, to create spheroids with a customizable 3D layout. To demonstrate its uniqueness, our method effectively creates designer 3D spheroids by combining parenchymal cells, stromal cells, and immune cells, leading to heightened physiological relevance and detailed modeling of complex chronic diseases and immune-stromal interactions. Our approach achieves a high level of biological fidelity while being standardized and straightforward to construct with the potential for large-scale drug discovery applications. By merging the precision of DNA nanotechnology with advanced cell culture techniques, we are streamlining human-centric models, striking a balance between complexity and standardization, to boost drug screening efficiency.

Onion skin is not a universal firing pattern for spinal motoneurons: simulation study.

Muscle force is modulated by sequential recruitment and firing rates of motor units (MUs). However, discrepancies exist in the literature regarding the relationship between MU firing rates and their recruitment, presenting two contrasting firing-recruitment schemes. The first firing scheme, known as "onion skin," exhibits low-threshold MUs firing faster than high-threshold MUs, forming separate layers akin to an onion. This contradicts the other firing scheme, known as "reverse onion skin" or "afterhyperpolarization (AHP)," with low-threshold MUs firing slower than high-threshold MUs. To study this apparent dichotomy, we used a high-fidelity computational model that prioritizes physiological fidelity and heterogeneity, allowing versatility in the recruitment of different motoneuron types. Our simulations indicate that these two schemes are not mutually exclusive but rather coexist. The likelihood of observing each scheme depends on factors such as the motoneuron pool activation level, synaptic input activation rates, and MU type. The onion skin scheme does not universally govern the encoding rates of MUs but tends to emerge in unsaturated motoneurons (cells firing < their fusion frequency that generates peak force), whereas the AHP scheme prevails in saturated MUs (cells firing at their fusion frequency), which is highly probable for slow (S)-type MUs. When unsaturated, fast fatigable (FF)-type MUs always show the onion skin scheme, whereas S-type MUs do not show either one. Fast fatigue-resistant (FR)-type MUs are generally similar but show weaker onion skin behaviors than FF-type MUs. Our results offer an explanation for the longstanding dichotomy regarding MU firing patterns, shedding light on the factors influencing the firing-recruitment schemes.NEW & NOTEWORTHY The literature reports two contrasting schemes, namely the onion skin and the afterhyperpolarization (AHP) regarding the relationship between motor units (MUs) firing rates and recruitment order. Previous studies have examined these schemes phenomenologically, imposing one scheme on the firing-recruitment relationship. Here, we used a high-fidelity computational model that prioritizes biological fidelity and heterogeneity to investigate motoneuron firing schemes without bias toward either scheme. Our objective findings offer an explanation for the longstanding dichotomy on MU firing patterns.

Informing policy via dynamic models: Cholera in Haiti.

Public health decisions must be made about when and how to implement interventions to control an infectious disease epidemic. These decisions should be informed by data on the epidemic as well as current understanding about the transmission dynamics. Such decisions can be posed as statistical questions about scientifically motivated dynamic models. Thus, we encounter the methodological task of building credible, data-informed decisions based on stochastic, partially observed, nonlinear dynamic models. This necessitates addressing the tradeoff between biological fidelity and model simplicity, and the reality of misspecification for models at all levels of complexity. We assess current methodological approaches to these issues via a case study of the 2010-2019 cholera epidemic in Haiti. We consider three dynamic models developed by expert teams to advise on vaccination policies. We evaluate previous methods used for fitting these models, and we demonstrate modified data analysis strategies leading to improved statistical fit. Specifically, we present approaches for diagnosing model misspecification and the consequent development of improved models. Additionally, we demonstrate the utility of recent advances in likelihood maximization for high-dimensional nonlinear dynamic models, enabling likelihood-based inference for spatiotemporal incidence data using this class of models. Our workflow is reproducible and extendable, facilitating future investigations of this disease system.

An Overview of Advancements and Technologies in Vascularization Strategies for Tumor‐On‐A‐Chip Models

AbstractVascularized tumor on a chip (VToC) entail emulating intricate microvascular networks like those observed in tumors through microfluidic devices, which are meticulously designed to offer a faithful representation of cancer in vitro, exploration of tumor biology, evaluation of drug efficacy, and anticipation of patient responses to therapies. Compared to conventional ones, VToC systems hold advantages by creating a milieu where physiological conditions for investigating tumor–host interactions are pivotal in tumor advancement/therapy resilience. Nevertheless, VToC models confront limitations encompassing vascular network replication, biological fidelity, mechanical/chemical integrity, and intricacies of architectural design. Thus, drawbacks inherent to prevailing VToC models’ intricacies, attributes, and vascular network establishment are imperative. This systematic review focuses on the recent advancements, technologies explored for incorporating VToC models, and vascularization approaches for investigation, and factors/parameters affecting complex tumor microenvironments in VToC models, along with the futuristic approach for the design strategies, fabrication techniques, understanding of vascular network, also VToC models with spheroid. A comprehensive analysis of VToC based on their limitations for a practical approach highlights the promising strategies for possible applications. This will be essential regarding a complete overview of VToC models and the future direction toward developing efficient VToC models compared to the state‐of‐the‐art VToC.

Dynamic Reactive Spiking Graph Neural Network

Spiking Graph Neural Networks are emerging tools for analyzing graph data along with low energy consumption and certain biological fidelity. Existing methods directly integrate same-reactive spiking neurons into graph neural networks for processing propagated graphs. However, such same-reactive neurons are not biological-functionality enough compared to the brain's dynamic-reactive ones, limiting the model's expression. Meanwhile, insufficient long-range neighbor information can be excavated with the few-step propagated graph, restricting discrimination of graph spiking embeddings. Inspired by the dynamic cognition in the brain, we propose a Dynamic Reactive Spiking Graph Neural Network that can enhance model's expressive ability in higher biological fidelity. Specifically, we design dynamic reactive spiking neurons to process spiking graph inputs, which have unique optimizable thresholds to spontaneously explore dynamic reactive states between neurons. Moreover, discriminative graph positional spikes are learned and integrated adaptively into spiking outputs through our neurons, thereby exploring long-range neighbors more thoroughly. Finally, with the dynamic reactive mechanism and learnable positional integration, we can obtain a powerful and highly bio-fidelity model with low energy consumption. Experiments on various domain-related datasets can demonstrate the effectiveness of our model. Our code is available at https://github.com/hzhao98/DRSGNN.

Translational medical bioengineering research of traumatic brain injury among Chinese and American pedestrians caused by vehicle collision based on human body finite element modeling

Based on the average human body size in China and the THUMS AM50 finite element model of the human body, the Kriging interpolation algorithm was used to model the Chinese 50th percentile human body, and the biological fidelity of the model was verified. We built three different types of passenger vehicle models, namely, sedan, sports utility vehicle (SUV), and multi-purpose vehicle (MPV), and used mechanical response analysis and finite element simulation to compare and analyze the dynamic differences and head injury differences between the Chinese 50th percentile human body and the THUMS AM50 model during passenger vehicle collisions. The results showed that there are obvious differences between the Chinese mannequin and THUMS in terms of collision time, collision position, invasion speed, and angle. When a sedan collided with the mannequins, the skull damage to the Chinese human body model was more severe, and when a sedan or SUV collided, the brain damage to the Chinese human body was more severe. The abovementioned results suggest that the existing C-NCAP pedestrian protection testing regulations may not provide the best protection for Chinese human bodies, and that the regulations need to be improved by combining collision damage mechanisms and the physical characteristics of Chinese pedestrians. This thorough investigation is positioned to shed light on the fundamental biomechanics and injury mechanisms at play. Furthermore, the amalgamation of clinically rooted translational and engineering research in the realm of traumatic brain injury has the potential to establish a solid foundation for discerning preventive methodologies. Ultimately, this endeavor holds the potential to introduce effective strategies aimed at preventing and safeguarding against traumatic brain injuries.

Exploring fMRI RDMs: enhancing model robustness through neurobiological data

Artificial neural networks (ANNs) are sensitive to perturbations and adversarial attacks. One hypothesized solution to adversarial robustness is to align manifolds in the embedded space of neural networks with biologically grounded manifolds. Recent state-of-the-art works that emphasize learning robust neural representations, rather than optimizing for a specific target task like classification, support the idea that researchers should investigate this hypothesis. While works have shown that fine-tuning ANNs to coincide with biological vision does increase robustness to both perturbations and adversarial attacks, these works have relied on proprietary datasets—the lack of publicly available biological benchmarks makes it difficult to evaluate the efficacy of these claims. Here, we deliver a curated dataset consisting of biological representations of images taken from two commonly used computer vision datasets, ImageNet and COCO, that can be easily integrated into model training and evaluation. Specifically, we take a large functional magnetic resonance imaging (fMRI) dataset (BOLD5000), preprocess it into representational dissimilarity matrices (RDMs), and establish an infrastructure that anyone can use to train models with biologically grounded representations. Using this infrastructure, we investigate the representations of several popular neural networks and find that as networks have been optimized for tasks, their correspondence with biological fidelity has decreased. Additionally, we use a previously unexplored graph-based technique, Fiedler partitioning, to showcase the viability of the biological data, and the potential to extend these analyses by extending RDMs into Laplacian matrices. Overall, our findings demonstrate the potential of utilizing our new biological benchmark to effectively enhance the robustness of models.

A modified finite element dummy model of Chinese adult male used for train collision simulations

ABSTRACT This work established a modified finite element (FE) dummy model representing the Chinese 50th percentile males through the whole segment scaling method, referring to the Total Human Model for Safety (THUMS-AM50) of European and American 50th percentile males. The head, neck, chest, abdomen, and knee-thigh-hip (KTH) of the modified model were validated, respectively, by the cadaver experimental results. Integrating the dummy models with a four-car marshalling train collision FE model, we analysed the dynamic response in terms of human body posture, head, and neck injuries of the Chinese 50th percentile males and the European and American 50th percentile males during the frontal train collision process. The corresponding simulation results fitted well with the experimental tests, indicating that the established modified model exerted great biological fidelity. Compared with European-American 50th percentile males, the Von-Mises stress, shear stress, maximum principal strain (MPS), and the cumulative strain damage measure CSDM0.15 of the brain in the Chinese 50th percentile males were approximately higher by 22.21%, 19.85%, 36.58%, and 47.55%, respectively. That meant the Chinese males might be at a higher risk of brain contusion and diffuse axonal injury (DAI) during the train collision. Meanwhile, the Chinese 50th percentile males had more severe neck extension, especially the maximum cervical vertebrae Von-Mises stress and neck injury predictor (Nij) were increased by 30.3% and 50%, respectively. The established modified model could provide a more accurate simulation for predicting the Chinese body injury response during the train collision.

Footprints: Stamping hallmarks of lung cancer with patient-derived models, from molecular mechanisms to clinical translation.

The conventional two-dimensional (2D) tumor cell lines in Petri dishes have played an important role in revealing the molecular biological mechanism of lung cancer. However, they cannot adequately recapitulate the complex biological systems and clinical outcomes of lung cancer. The three-dimensional (3D) cell culture enables the possible 3D cell interactions and the complex 3D systems with co-culture of different cells mimicking the tumor microenvironments (TME). In this regard, patient-derived models, mainly patient-derived tumor xenograft (PDX) and patient-derived organoids discussed hereby, are with higher biological fidelity of lung cancer, and regarded as more faithful preclinical models. The significant Hallmarks of Cancer is believed to be the most comprehensive coverage of current research on tumor biological characteristics. Therefore, this review aims to present and discuss the application of different patient-derived lung cancer models from molecular mechanisms to clinical translation with regards to the dimensions of different hallmarks, and to look to the prospects of these patient-derived lung cancer models.

Neuromorphic behaviors of a symmetric LAM-based electronic neuron circuit: Numerical simulation and experimental measurement

Memristor-based neuromorphic computing can achieve the scalability and biological fidelity simultaneously by flexible applying the neuromorphic behaviors. The locally-active memristor (LAM) can work on the edge of chaos associating to stable yet excitable subdomain, which is regarded as a natural candidate in generating neuromorphic behaviors. This paper proposes a new LAM possessing origin symmetric DC characteristic and locally-active domains (LADs) is investigated in-depth and the edge of chaos in its LADs is explored. Afterwards, a second-order memristive circuit is built. Then, the Jacobi matrix-based stability and admittance function are theoretically and numerically analyzed, from which Hopf bifurcation is disclosed. The oscillating behaviors are revealed at neighborhood of the Hopf bifurcation. Then, a third-order electronic neuron circuit is built by parallel connecting a capacitor to the LAM, and a bipolar square-wave is applied to disclose the neuromorphic behaviors. Numerical results demonstrate that the electronic neuron circuit can generate neuromorphic behaviors of periodic/chaotic spiking. These spiking behaviors can be regulated by the period and duty ratio of the applied bipolar square-wave. Finally, FPGA-based experimental measurements validate the numerical simulations. What’s more, these numerical simulations and experimental measurements effectively show the feasibility of the LAM in constructing memristive circuit to generate neuromorphic behaviors.

Assessment of the physiological vulnerability of the endemic and critically endangered Daggernose Shark: A comparative approach to other Carcharhiniformes

IntroductionThe current Isogomphodon oxyrhynchus (Daggernose Shark) population status Q7points to 99% losses in the last decade due to certain biological traits, site fidelity, and historical high representativeness as bycatch in artisanal fisheries. This species is listed as Critically Endangered (CR), both in the IUCN and the Brazilian Red Lists. Its vulnerability is so high that its recovery potential requires protection from ongoing fishing pressure.ObjectiveIn this context, this study aimed to evaluate the health status of Daggernose sharks and their ability to cope with allostatic overload in a comparative analysis with other Carcharhinid and Sphyrnid sharks.MethodsSharks incidentally caught by the artisanal fleet in the state of Maranhão, on the Brazilian Amazon Coast, were sampled for blood, and serum was used to assess biochemical markers.ResultsThe findings indicate significant differences in Daggernose Shark homeostatic capacity for ALP, ALT/GTP, creatinine, lactate, urea, total cholesterol, and triglycerides, pointing to lower health scores and recovery capacity when compared to other Carcharhiniformes inhabiting the same region.Discussion and conclusionsIt is possible that such vulnerability is a result of fisheries-induced evolution, leading to remaining populations with very low chances of fully recovering. Conservation planning is thus urgent, as current legislation based on fishing bans does very little for the species. International collaboration and longterm recovery measures are necessary, including the creation of MPAs specially designed for the species and captive maintenance aiming to monitor health status and carry out breeding attempts.

Prolonged Maintenance of Ex Vivo Functional Vk*MYC Multiple Myeloma Cells Allows for in Vitro Manipulation and Subsequent In Vivo Analysis

Human multiple myeloma (MM) cell lines are easy to culture but only partially reflect the heterogeneity of primary MM samples as most cell lines are derived from primary human plasma-cell leukemia samples and have often lost their dependence on the marrow microenvironment. In contrast, maintaining primary human MM samples ex vivo and in vivo is very challenging. To bridge this gap, the immunocompetent Vk*MYC transgenic MM model was developed. It has high biological fidelity to the human disease characteristics and features easy in vivo engraftment and serial transplantation. However, Vk*MYC cells are considered notoriously difficult to grow and manipulate in vitro, limiting their usage for functional studies. Aim To overcome these limitations, we aimed to develop a robust culture system which promotes survival and function of primary Vk*MYC MM cells in culture as a research tool for in vitro manipulation and subsequent in vivo transplantation. Method Splenocytes from tVk*MYC (Vk12598 clone) engrafted mice were routinely maintained ex vivo and conditioned media collected for M-spike quantification. Analysis of cultures by flow cytometry allowed for Vk*MYC population quantification over time. Our novel plating method includes the following components to support Vk*MYC cell survival: 3D plating as hanging drops, low (6.5%) oxygen culture, high density cultures and a cytokine cocktail. Results The culture method described here routinely results in maintenance or slight enrichment of Vk*MYC (CD138+B220-) splenocyte fraction. Monoclonal immunoglobulin (M spike) accumulation in conditioned culture media was assessed after 7 days culture as a clinically relevant, functional output marker. Culture media displayed the same immunoglobulin isotype as parent Vk*MYC (Vk12598 clone). Figure 1 shows previously frozen donor Vk*MYC splenocytes (day 0) assessed by flow cytometry and either injected directly, or maintained 7 days ex vivo, prior to IV injection into naive C57BL/6 recipient mice. Culture-recipient mice developed Vk*MYC MM disease with the same serum M-spike isotype band, similar engraftment ratio, similar time to evidence of biochemical disease and similar overall survival time as mice transplanted with freshly defrosted Vk*MYC splenocytes. To exemplify in vitro manipulation, Vk*MYC splenocytes were cultured as described and treated with Cy3-labelled liposomal nanoparticles (LNP), a non-toxic way to deliver treatment loads e.g. siRNAs, then maintained in culture for up to 7 days after treatment. Flow analysis showed >95% of viable CD138+ cells were Cy3 positive as a marker of LNP uptake. In addition, Vk*MYC splenocytes were transduced with GFP-encoding lentivirus, then maintained in culture for up to 7 days. Flow analysis showed viable, CD138+B220- cells expressing GFP as a marker of lentiviral transduction, highlighting the potential of this culture method to allow manipulation of Vk*MYC cells in vitro. Discussion This innovative culture method allows for survival and enrichment, but not expansion of Vk*MYC splenocytes in culture. Our seven-day culture protocol allows in vitro manipulation with liposomal nanoparticles as well as viral vectors and subsequent in vivo investigations. Figure 1. Experimental setup. A) (Day 0) donor tVk*MYC spleen was defrosted and assessed for MM burden by flow (CD138+ B220-). Splenocytes were maintained for 7 days ex vivo in 3D hanging drop cultures. At day 7, conditioned media was assessed by modified SPEP method for evidence of biochemical disease, and cultured cells assessed by flow or injected into naive C57BL/6 recipient mice. B) After 4 weeks, evidence of biochemical disease (M-spike) was confirmed by SPEP and mouse spleen Vk*MYC burden assessed by flow cytometry. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Micropatterned Neurovascular Interface to Mimic the Blood-Brain Barrier's Neurophysiology and Micromechanical Function: A BBB-on-CHIP Model.

A hybrid blood–brain barrier (BBB)-on-chip cell culture device is proposed in this study by integrating microcontact printing and perfusion co-culture to facilitate the study of BBB function under high biological fidelity. This is achieved by crosslinking brain extracellular matrix (ECM) proteins to the transwell membrane at the luminal surface and adapting inlet–outlet perfusion on the porous transwell wall. While investigating the anatomical hallmarks of the BBB, tight junction proteins revealed tortuous zonula occludens (ZO-1), and claudin expressions with increased interdigitation in the presence of astrocytes were recorded. Enhanced adherent junctions were also observed. This junctional phenotype reflects in-vivo-like features related to the jamming of cell borders to prevent paracellular transport. Biochemical regulation of BBB function by astrocytes was noted by the transient intracellular calcium effluxes induced into endothelial cells. Geometry-force control of astrocyte–endothelial cell interactions was studied utilizing traction force microscopy (TFM) with fluorescent beads incorporated into a micropatterned polyacrylamide gel (PAG). We observed the directionality and enhanced magnitude in the traction forces in the presence of astrocytes. In the future, we envisage studying transendothelial electrical resistance (TEER) and the effect of chemomechanical stimulations on drug/ligand permeability and transport. The BBB-on-chip model presented in this proposal should serve as an in vitro surrogate to recapitulate the complexities of the native BBB cellular milieus.

Information theory entering soils and tissues.

For a long time, application of information theory for characterizing biological signaling fidelity was limited to "telegraph-like" situations, copying the classical scenario for which it was developed. A study published in this issue of Cell Systems applies this powerful framework to several distinct cases of dynamic signal sensing in complex geometries.

Organoid screening reveals epigenetic vulnerabilities in human colorectal cancer.

Precision oncology presumes an accurate prediction of drug response on the basis of the molecular profile of tumors. However, the extent to which patient-derived tumor organoids recapitulate the response of in vivo tumors to a given drug remains obscure. To gain insights into the pharmacobiology of human colorectal cancer (CRC), we here created a robust drug screening platform for patient-derived colorectal organoids. Application of suspension culture increased organoid scalability, and a refinement of the culture condition enabled incorporation of normal and precursor organoids to high-throughput drug screening. Drug screening identified bromodomain and extra-terminal (BET) bromodomain protein inhibitor as a cancer-selective growth suppressor that targets genes aberrantly activated in CRC. A multi-omics analysis identified an association between checkpoint with forkhead and ring finger domaines (CHFR) silencing and paclitaxel sensitivity, which was further validated by gene engineering of organoids and in xenografts. Our findings highlight the utility of multiparametric validation in enhancing the biological and clinical fidelity of a drug screening system.

Reformulated McNamara RBE-weighted beam orientation optimization for intensity modulated proton therapy.

Empirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework. Based on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE=1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness. Compared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses. The four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

BrainFreeze: Expanding the Capabilities of Neuromorphic Systems Using Mixed-Signal Superconducting Electronics.

Superconducting electronics (SCE) is uniquely suited to implement neuromorphic systems. As a result, SCE has the potential to enable a new generation of neuromorphic architectures that can simultaneously provide scalability, programmability, biological fidelity, on-line learning support, efficiency and speed. Supporting all of these capabilities simultaneously has thus far proven to be difficult using existing semiconductor technologies. However, as the fields of computational neuroscience and artificial intelligence (AI) continue to advance, the need for architectures that can provide combinations of these capabilities will grow. In this paper, we will explain how superconducting electronics could be used to address this need by combining analog and digital SCE circuits to build large scale neuromorphic systems. In particular, we will show through detailed analysis that the available SCE technology is suitable for near term neuromorphic demonstrations. Furthermore, this analysis will establish that neuromorphic architectures built using SCE will have the potential to be significantly faster and more efficient than current approaches, all while supporting capabilities such as biologically suggestive neuron models and on-line learning. In the future, SCE-based neuromorphic systems could serve as experimental platforms supporting investigations that are not feasible with current approaches. Ultimately, these systems and the experiments that they support would enable the advancement of neuroscience and the development of more sophisticated AI.

Evaluation method of training simulation on biological models for cardiovascular surgery residents.

The goal of this study was to describe and evaluate our simulation training program on biological models for the cardiovascular surgery residency program at our institution. Since 2016, with the purpose to develop better practical performance and evaluate the improvement of resident's surgical skills, a simulation training program was implemented, composed of some elemental procedures in cardiovascular surgery. It was established with one wet lab session weekly lasting 2 h, coached by two expert cardiovascular surgeons. Bovine and porcine hearts were used as biological models. At the end of the hands-on program, an objective assessment consisting of two practical modules was applied and performance was rated by way of a 5-point scale. In addition, to provide a subjective assessment, each resident filled out a questionnaire consisting of three items reviewing the overall quality of the workshops on a 10-point scale. The objective evaluation applied at the end of the training program consisted of valve replacement and coronary artery bypass grafting (CABG) modules. The mean performance rating scores for the valve replacement module ranged from 4.2 to 4.79, and CABG, from 4.33 to 4.87. Regarding subjective assessment, all items evaluated, such as expert's didactics, simulation performance, and biological simulator fidelity, received high grades (above 9 on a 10-point scale). Simulator training on biological models for cardiac surgery medical residents is a simple and effective learning method of surgical skills.

Unveiling Interindividual Variability of Human Fibroblast Innate Immune Response Using Robust Cell-Based Protocols.

The LabEx Milieu Interieur (MI) project is a clinical study centered on the detailed characterization of the baseline and induced immune responses in blood samples from 1,000 healthy donors. Analyses of these samples has lay ground for seminal studies on the genetic and environmental determinants of immunologic variance in a healthy cohort population. In the current study we developed in vitro methods enabling standardized quantification of MI-cohort-derived primary fibroblasts responses. Our results show that in vitro human donor cohort fibroblast responses to stimulation by different MAMPs analogs allows to characterize individual donor immune-phenotype variability. The results provide proof-of-concept foundation to a new experimental framework for such studies. A bio-bank of primary fibroblast lines was generated from 323 out of 1,000 healthy individuals selected from the MI-study cohort. To study inter-donor variability of innate immune response in primary human dermal fibroblasts we chose to measure the TLR3 and TLR4 response pathways, both receptors being expressed and previously studied in fibroblasts. We established high-throughput automation compatible methods for standardized primary fibroblast cell activation, using purified MAMPS analogs, poly I:C and LPS that stimulate TLR3 and TLR4 pathways respectively. These results were in turn compared with a stimulation method using infection by HSV-1 virus. Our “Add-only” protocol minimizes high-throughput automation system variability facilitating whole process automation from cell plating through stimulation to recovery of cell supernatants, and fluorescent labeling. Images were acquired automatically by high-throughput acquisition on an automated high-content imaging microscope. Under these methodological conditions standardized image acquisition provided for quantification of cellular responses allowing biological variability to be measured with low system noise and high biological signal fidelity. Optimal for automated analysis of immuno-phenotype of primary human cell responses our method and experimental framework as reported here is highly compatible to high-throughput screening protocols like those necessary for chemo-genomic screening. In context of primary fibroblasts derived from donors enrolled to the MI-clinical-study our results open the way to assert the utility of studying immune-phenotype characteristics relevant to a human clinical cohort.