Single-cell and spatial atlases of spinal cord injury in the Tabulae Paralytica.

Here, we introduce the Tabulae Paralytica-a compilation of four atlases of spinal cord injury (SCI) comprising a single-nucleus transcriptome atlas of half a million cells, a multiome atlas pairing transcriptomic and epigenomic measurements within the same nuclei, and two spatial transcriptomic atlases of the injured spinal cord spanning four spatial and temporal dimensions. We integrated these atlases into a common framework to dissect the molecular logic that governs the responses to injury within the spinal cord1. The Tabulae Paralytica uncovered new biological principles that dictate the consequences of SCI, including conserved and divergent neuronal responses to injury; the priming of specific neuronal subpopulations to upregulate circuit-reorganizing programs after injury; an inverse relationship between neuronal stress responses and the activation of circuit reorganization programs; the necessity of re-establishing a tripartite neuroprotective barrier between immune-privileged and extra-neural environments after SCI and a failure to form this barrier in old mice. We leveraged the Tabulae Paralytica to develop a rejuvenative gene therapy that re-established this tripartite barrier, and restored the natural recovery of walking after paralysis in old mice. The Tabulae Paralytica provides a window into the pathobiology of SCI, while establishing a framework for integrating multimodal, genome-scale measurements in four dimensions to study biology and medicine.

The neurons that restore walking after paralysis.

A spinal cord injury interrupts pathways from the brain and brainstem that project to the lumbar spinal cord, leading to paralysis. Here we show that spatiotemporal epidural electrical stimulation (EES) of the lumbar spinal cord1-3 applied during neurorehabilitation4,5 (EESREHAB) restored walking in nine individuals with chronic spinal cord injury. This recovery involved a reduction in neuronal activity in the lumbar spinal cord of humans during walking. We hypothesized that this unexpected reduction reflects activity-dependent selection of specific neuronal subpopulations that become essential for a patient to walk after spinal cord injury. To identify these putative neurons, we modelled the technological and therapeutic features underlying EESREHAB in mice. We applied single-nucleus RNA sequencing6-9 and spatial transcriptomics10,11 to the spinal cords of these mice to chart a spatially resolved molecular atlas of recovery from paralysis. We then employed cell type12,13 and spatial prioritization to identify the neurons involved in the recovery of walking. A single population of excitatory interneurons nested within intermediate laminae emerged. Although these neurons are not required for walking before spinal cord injury, we demonstrate that they are essential for the recovery of walking with EES following spinal cord injury. Augmenting the activity of these neurons phenocopied the recovery of walking enabled by EESREHAB, whereas ablating them prevented the recovery of walking that occurs spontaneously after moderate spinal cord injury. We thus identified a recovery-organizing neuronal subpopulation that is necessary and sufficient to regain walking after paralysis. Moreover, our methodology establishes a framework for using molecular cartography to identify the neurons that produce complex behaviours.

Neuroprosthetic baroreflex controls haemodynamics after spinal cord injury.

Spinal cord injury (SCI) induces haemodynamic instability that threatens survival1-3, impairs neurological recovery4,5, increases the risk of cardiovascular disease6,7, and reduces quality of life8,9. Haemodynamic instability in this context is due to the interruption of supraspinal efferent commands to sympathetic circuits located in the spinal cord10, which prevents the natural baroreflex from controlling these circuits to adjust peripheral vascular resistance. Epidural electrical stimulation (EES) of the spinal cord has been shown to compensate for interrupted supraspinal commands to motor circuits below the injury11, and restored walking after paralysis12. Here, we leveraged these concepts to develop EES protocols that restored haemodynamic stability after SCI. We established a preclinical model that enabled us to dissect the topology and dynamics of the sympathetic circuits, and to understand how EES can engage these circuits. We incorporated these spatial and temporal features into stimulation protocols to conceive a clinical-grade biomimetic haemodynamic regulator that operates in a closed loop. This 'neuroprosthetic baroreflex' controlled haemodynamics for extended periods of time in rodents, non-human primates and humans, after both acute and chronic SCI. We will now conduct clinical trials to turn the neuroprosthetic baroreflex into a commonly available therapy for people with SCI.

Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting.

Many connected devices are expected to be deployed during the next few years. Energy harvesting appears to be a good solution to power these devices but is not a reliable power source due to the time-varying nature of most energy sources. It is possible to harvest energy from multiple energy sources to tackle this problem, thus increasing the amount and the consistency of harvested energy. Additionally, a power management system can be implemented to compute how much energy can be consumed and to allocate this energy to multiple tasks, thus adapting the device quality of service to its energy capabilities. The goal is to maximize the amount of measured and transmitted data while avoiding power failures as much as possible. For this purpose, an industrial sensor node platform was extended with a multi-source energy-harvesting circuit and programmed with a novel energy-allocation system for multi-task devices. In this paper, a multi-source energy-harvesting LoRaWAN node is proposed and optimal energy allocation is proposed when the node runs different sensing tasks. The presented hardware platform was built with off-the-shelf components, and the proposed power management system was implemented on this platform. An experimental validation on a real LoRaWAN network shows that a gain of 51% transmitted messages and 62% executed sensing tasks can be achieved with the multi-source energy-harvesting and power-management system, compared to a single-source system.

How Can Wake-up Radio Reduce LoRa Downlink Latency for Energy Harvesting Sensor Nodes?

LoRa is popular for internet of things applications as this communication technology offers both a long range and a low power consumption. However, LoRaWAN, the standard MAC protocol that uses LoRa as physical layer, has the bottleneck of a high downlink latency to achieve energy efficiency. To overcome this drawback we explore the use of wake-up radio combined with LoRa, and propose an adequate MAC protocol that takes profit of both these heterogeneous and complementary technologies. This protocol allows an opportunistic selection of a cluster head that forwards commands from the gateway to the nodes in the same cluster. Furthermore, to achieve self-sustainability, sensor nodes might include an energy harvesting sub-system, for instance to scavenge energy from the light, and their quality of service can be tuned, according to their available energy. To have an effective self-sustaining LoRa system, we propose a new energy manager that allows less fluctuations of the quality of service between days and nights. Latency and energy are modeled in a hybrid manner, i.e., leveraging microbenchmarks on real hardware platforms, to explore the influence of the energy harvesting conditions on the quality of service of this heterogeneous network. It is clearly demonstrated that the cooperation of nodes within a cluster drastically reduces the latency of LoRa base station commands, e.g., by almost 90% compared to traditional LoRa scheme for a 10 nodes cluster.

Leveraging Energy Harvesting and Wake-Up Receivers for Long-Term Wireless Sensor Networks.

Wireless sensor nodes are traditionally powered by individual batteries, and a significant effort has been devoted to maximizing the lifetime of these devices. However, as the batteries can only store a finite amount of energy, the network is still doomed to die, and changing the batteries is not always possible. A promising solution is to enable each node to harvest energy directly in its environment, using individual energy harvesters. Moreover, novel ultra-low power wake-up receivers, which allow continuous listening of the channel with negligible power consumption, are emerging. These devices enable asynchronous communication, further reducing the power consumption related to communication, which is typically one the most energy-consuming tasks in wireless sensor networks. Energy harvesting and wake-up receivers can be combined to significantly increase the energy efficiency of sensor networks. In this paper, we propose an energy manager for energy harvesting wireless sensor nodes and an asynchronous medium access control protocol, which exploits ultra-low power wake-up receivers. The two components are designed to work together and especially to fit the stringent constraints of wireless sensor nodes. The proposed approach has been implemented on a real hardware platform and tested in the field. Experimental results demonstrate the benefits of the proposed approach in terms of energy efficiency, power consumption and throughput, which can be up to more than two-times higher compared to traditional schemes.

Prediction of all-cause mortality from gated-SPECT global myocardial wall thickening: comparison with ejection fraction and global longitudinal 2D-strain.

BACKGROUND: The aim of this study was to assess the correlation between global wall thickening (GWT) obtained by gated-single photon emission computed tomography (SPECT) and echocardiographic measures [ejection fraction (EF), global longitudinal strain (GLS), and strain rate (GLSR)] and to compare their prognostic value for all-cause mortality. METHODS AND RESULTS: Seventy-four patients with referral for dipyridamole myocardial perfusion SPECT were prospectively included and underwent transthoracic echocardiography to measure left ventricular EF, GLS, and GLSR. The strongest correlation with GWT was for EF (R = 0.63, P < .001), followed by GLSR (R = -0.57, P < .001) and GLS (R = -0.53, P < .001). There were ten deaths over a period of 14.6 ± 5.7 months. Using the multivariate Cox analysis, summed stress score (HR 1.108; P = .023), EF (HR 1.01, P = .031), GLS (HR 1.593, P = .001), and GWT (HR 0.898, P = .034) remained independent predictors of mortality. Mean survival rate evaluated by Kaplan-Meier analysis was longer in patients with GWT ≥ 24% (21.9 ± 0.6 months) than those with GWT < 24% (13.6 ± 2.7 months; P < .001). CONCLUSIONS: GWT assessed is a highly sensitive tool to detect early myocardial systolic dysfunction and may bring additional prognostic information.

New concept of myocardial longitudinal strain reserve assessed by a dipyridamole infusion using 2D-strain echocardiography: the impact of diabetes and age, and the prognostic value.

AIMS: Although dipyridamole is a widely used pharmacological stress agent, the direct effects on myocardium are not entirely known. Diabetic cardiomyopathy can be investigated by 2D-strain echocardiography. The aim of this study was to assess myocardial functional reserve after dipyridamole infusion using speckle-tracking echocardiography. METHODS: Seventy-five patients referred for dipyridamole stress myocardial perfusion gated SPECT (MPGS) were examined by echocardiography to assess a new concept of longitudinal strain reserve (LSR) and longitudinal strain rate reserve (LSRR) respectively defined by the differences of global longitudinal strain (GLS) and longitudinal strain rate between peak stress after dipyridamole and rest. Twelve patients with myocardial ischemia were excluded on the basis of MPGS as gold standard. RESULTS: Mean LSR was -2.28±2.19% and was more important in the 28 (44%) diabetic patients (-3.27±1.93%; p=0.001). After multivariate analyses, only diabetes improved LSR (p=0.011) after dipyridamole infusion and was not associated with glycaemic control (p=0.21), insulin therapy (p=0.46) or duration of the disease (p=0.80). Conversely, age (p=0.002) remained associated with a decrease in LSR. LSSR was also correlated to age (p=0.005). Patients with a LSR<0% have a better survival after 15 months (log-rank p=0.0012). CONCLUSION: LSR explored by 2D speckle-tracking echocardiography after dipyridamole infusion is a simple and new concept that provides new insights into the impact of diabetes and age on the myocardium with a potential prognostic value.

Longitudinal interrogation of sympathetic neural circuits and hemodynamics in preclinical models.

Neurological disorders, including spinal cord injury, result in hemodynamic instability due to the disruption of supraspinal projections to the sympathetic circuits located in the spinal cord. We recently developed a preclinical model that allows the identification of the topology and dynamics through which sympathetic circuits modulate hemodynamics, supporting the development of a neuroprosthetic baroreflex that precisely controls blood pressure in rats, monkeys and humans with spinal cord injuries. Here, we describe the continuous monitoring of arterial blood pressure and sympathetic nerve activity over several months in preclinical models of chronic neurological disorders using commercially available telemetry technologies, as well as optogenetic and neuronal tract-tracing procedures specifically adapted to the sympathetic circuitry. Using a blueprint to construct a negative-pressure chamber, the approach enables the reproduction, in rats, of well-controlled and reproducible episodes of hypotension-mimicking orthostatic challenges already used in humans. Blood pressure variations can thus be directly induced and linked to the molecular, functional and anatomical properties of specific neurons in the brainstem, spinal cord and ganglia. Each procedure can be completed in under 2 h, while the construction of the negative-pressure chamber requires up to 1 week. With training, individuals with a basic understanding of cardiovascular physiology, engineering or neuroscience can collect longitudinal recordings of hemodynamics and sympathetic nerve activity over several months.

Feasibility and early toxicity of intraoperative radiotherapy for breast cancer using the papillon + system: First results.

Background and Purpose: Breast intra operative radiation therapy has been evaluated with different systems delivering 20-21 Gy with treatment times around 30 min. Papillon + TM Contact X-ray machine was designed to produce a 50 kVp beam with a high dose rate ≥ 15 Gy/minute. A pilot study with the first prototype was conducted in Nice. Materials and methods: The inclusion criteria were age ≥ 60 years, unifocal ductal breast adenocarcinoma ≤ 2.5 cm, grade 1-2. Surgical local excision with sentinel node dissection was performed and the applicator was placed in the tumor bed after excision with a prescribed dose of 20 Gy. The main end point of the study was the doses measured with the Gafchromic films; two were located at the skin surface and two in the excision cavity. Secondary endpoints were early toxicity and relapse free survival. Results: Between 10/2018 and 09/2019, 26 patients were included. Mean Gafchromic doses were 18.8 Gy ± 2 Gy at the south pole, 15.6 Gy ± 2.81 Gy at the equator and 2.5 Gy ± 1.67 Gy at the skin. With a median follow-up time of 12 months, no skin or subcutaneous toxicity > grade 2, no local relapse and no metastasis were observed. Conclusion: This is the first phase II study testing the Papillon + tm system for breast IORT with in vivo dosimetry measurements and reassuring clinical data.

Recovery of walking after paralysis by regenerating characterized neurons to their natural target region.

Axon regeneration can be induced across anatomically complete spinal cord injury (SCI), but robust functional restoration has been elusive. Whether restoring neurological functions requires directed regeneration of axons from specific neuronal subpopulations to their natural target regions remains unclear. To address this question, we applied projection-specific and comparative single-nucleus RNA sequencing to identify neuronal subpopulations that restore walking after incomplete SCI. We show that chemoattracting and guiding the transected axons of these neurons to their natural target region led to substantial recovery of walking after complete SCI in mice, whereas regeneration of axons simply across the lesion had no effect. Thus, reestablishing the natural projections of characterized neurons forms an essential part of axon regeneration strategies aimed at restoring lost neurological functions.

Natural and targeted circuit reorganization after spinal cord injury.

A spinal cord injury disrupts communication between the brain and the circuits in the spinal cord that regulate neurological functions. The consequences are permanent paralysis, loss of sensation and debilitating dysautonomia. However, the majority of circuits located above and below the injury remain anatomically intact, and these circuits can reorganize naturally to improve function. In addition, various neuromodulation therapies have tapped into these processes to further augment recovery. Emerging research is illuminating the requirements to reconstitute damaged circuits. Here, we summarize these natural and targeted reorganizations of circuits after a spinal cord injury. We also advocate for new concepts of reorganizing circuits informed by multi-omic single-cell atlases of recovery from injury. These atlases will uncover the molecular logic that governs the selection of 'recovery-organizing' neuronal subpopulations, and are poised to herald a new era in spinal cord medicine.

Engineering spinal cord repair.

Neurological damage caused by spinal cord injury in humans has been observed for over three thousand years and impacts the lives of several hundred thousand people worldwide. Despite this prevalence and its associated consequences, there is no treatment to repair the injured spinal cord. Evidence gathered over the last several decades has provided mechanistic information on the complex cascade of events following traumatic spinal cord injury and this is paving the way towards mechanism based repair strategies. In this review, we summarize state-of-the-art biological and engineering repair strategies and posit that complete repair will be dependent on cataloguing the molecular signatures and growth requirements of the different neuron subpopulations in the brain and spinal cord.

Prioritization of cell types responsive to biological perturbations in single-cell data with Augur.

Advances in single-cell genomics now enable large-scale comparisons of cell states across two or more experimental conditions. Numerous statistical tools are available to identify individual genes, proteins or chromatin regions that differ between conditions, but many experiments require inferences at the level of cell types, as opposed to individual analytes. We developed Augur to prioritize the cell types within a complex tissue that are most responsive to an experimental perturbation. In this protocol, we outline the application of Augur to single-cell RNA-seq data, proceeding from a genes-by-cells count matrix to a list of cell types ranked on the basis of their separability following a perturbation. We provide detailed instructions to enable investigators with limited experience in computational biology to perform cell-type prioritization within their own datasets and visualize the results. Moreover, we demonstrate the application of Augur in several more specialized workflows, including the use of RNA velocity for acute perturbations, experimental designs with multiple conditions, differential prioritization between two comparisons, and single-cell transcriptome imaging data. For a dataset containing on the order of 20,000 genes and 20 cell types, this protocol typically takes 1-4 h to complete.

Confronting false discoveries in single-cell differential expression.

Differential expression analysis in single-cell transcriptomics enables the dissection of cell-type-specific responses to perturbations such as disease, trauma, or experimental manipulations. While many statistical methods are available to identify differentially expressed genes, the principles that distinguish these methods and their performance remain unclear. Here, we show that the relative performance of these methods is contingent on their ability to account for variation between biological replicates. Methods that ignore this inevitable variation are biased and prone to false discoveries. Indeed, the most widely used methods can discover hundreds of differentially expressed genes in the absence of biological differences. To exemplify these principles, we exposed true and false discoveries of differentially expressed genes in the injured mouse spinal cord.

Cell type prioritization in single-cell data.

We present Augur, a method to prioritize the cell types most responsive to biological perturbations in single-cell data. Augur employs a machine-learning framework to quantify the separability of perturbed and unperturbed cells within a high-dimensional space. We validate our method on single-cell RNA sequencing, chromatin accessibility and imaging transcriptomics datasets, and show that Augur outperforms existing methods based on differential gene expression. Augur identified the neural circuits restoring locomotion in mice following spinal cord neurostimulation.