Intracoronary trimetazidine does not improve recovery of regional function in a porcine model of repeated ischemia

We evaluated the effect of trimetazidine (TMZ) on recovery of regional cardiac function in anesthetized open-chest pigs, subjected to fifteen 2-minute occlusions of the left anterior descending coronary artery, separated by 2 minutes of reperfusion and a 120-minute recovery period. Regional myocardial function was evaluated by sonomicrometry-derived segment lengthening and the area enclosed by the left ventricular pressure-segment length loop (external work, EW) in animals, which received either an intracoronary infusion of TMZ (33 μg/kg/min, n=6) or saline (1 ml/min, n=7), starting 15 minutes before the first occlusion and ending 2 minutes after the 15th occlusion. In addition, myocardial malondialdehyde production to evaluate oxygen free radical production, oxygen consumption, and the ATP, ADP, and AMP content, as well as the energy charge, were determined at regular time intervals. In control pigs the sequences of occlusion-reperfusion did not affect systemic hemodynamics, except for the LVdP/dtmax, which decreased by 11% during the interventions and did not recover during the following reperfusion period of 2 hours (78% of baseline, p<0.05). Systolic segment length shortening and EW were increased at the end of the first occlusion-reperfusion cycle, decreased gradually during the remainder of the occlusion-reperfusion periods, and did not improve during the recovery period. Energy charge and myocardial blood flow were not impaired, but oxygen consumption was decreased during the recovery period. The malondialdeyde data did not provide evidence for production of oxygen free radicals. TMZ decreased LVdP/dtmax by 6% (p<0.05) and caused a twofold increase in postsystolic segment shortening (p<0.05) before the first occlusion, but did not influence the hemodynamic responses, the changes in regional cardiac function, and the metabolic events produced by repetitive regional ischemia

Preferential substrate use decreases priming effects in contrasting treeline soils

This is the final version. Available on open access from Springer via the DOI in this recordData availability: All data generated during the current study are presented in the manuscript and available from the authors.Climate change currently manifests in upward and northward shifting treelines, which encompasses changes to the carbon (C) and nitrogen (N) composition of organic inputs to soils. Whether these changed inputs will increase or decrease microbial mineralisation of native soil organic matter remains unknown, making it difficult to estimate how treeline shifts will affect the C balance. Aiming to improve mechanistic understanding of C cycling in regions experiencing treeline shifts, we quantified priming effects in soils of high altitudes (Peruvian Andes) and high latitudes (subarctic Sweden), differentiating landcover types (boreal forest, tropical forest, tundra heath, Puna grassland) and soil horizons (organic, mineral). In a controlled laboratory incubation, soils were amended with substrates of different C:N, composed of an organic C source at a constant ratio of 30% substrate-C to microbial biomass C, combined with different levels of a nutrient solution neutral in pH. Substrate additions elicited both positive and negative priming effects in both ecosystems, independent from substrate C:N. Positive priming prevailed above the treeline in high altitudes and in mineral soils in high latitudes, where consequently climate change-induced treeline shifts and deeper rooting plants may enhance SOM-mineralisation and soil C emissions. However, such C loss may be compensated by negative priming, which dominated in the other soil types and was of larger magnitude than positive priming. In line with other studies, these results indicate a consistent mechanism linking decreased SOM-mineralisation (negative priming) to increased microbial substrate utilisation, suggesting preferential substrate use as a potential tool to support soil C storage. Graphical abstract: [Figure not available: see fulltext.]Natural Environment Research Council (NERC

Phase Space Analysis of Chaotic Neural Networks

We analytically determine the distribution of fixed points in a canonical model of a chaotic neural network. This distribution reveals that fixed points and dynamics are confined to separate shells in phase space. Furthermore, the distribution enables us to determine the eigenvalue spectra of the Jacobian at the fixed points. Perhaps counter-intuitively, the velocity of the dynamics is strongly correlated with the direction imposed by the nearest fixed point despite the spatial separation. We propose that this influence of the fixed points is mediated by tangentially fixed lines

Erector spinae plane block improves postoperative recovery after laminectomy and discectomy surgery: a retrospective cohort study

Abstract Background There is still room for improvement of pain management after spinal surgery. The goal of this study was to evaluate adding the erector spinae block to the standard analgesia regimen. Our hypothesis was that the erector spinae plane block will decrease length of hospital stay, reduce opioid need and improve numeric rating scale pain scores. Methods This was a single center retrospective cohort study. We included 418 patients undergoing laminectomy or discectomy from January 2019 until December 2021. The erector spinae plane block was introduced in 2016 by Forero and colleagues and added to our clinical practice in October 2020. Patients who did not receive an erector spinae plane block prior to its implementation in October 2020 were used as control group. The primary outcome measure was functional recovery, measured by length of hospital stay. Secondary outcome measures were perioperative opioid consumption, need for patient-controlled analgesia and numeric rating scale pain scores. Postoperative data collection time points were: at the PACU and after 3, 6, 12 and 24 h postoperatively. Results There was a significant shorter length of hospital stay in patients undergoing single level laminectomy (with erector spinae plane block 29 h (IQR 27–51), without block 53 h (IQR 51–55), p < .001), multiple level laminectomy (with erector spinae plane block 49 h (IQR 31–54), without block 54 h (IQR 52–75), p < .001) and discectomy (with erector spinae plane block 27 h (IQR 25–30), without block 29 h (IQR 28–49), p = .04). Conclusions Erector spinae plane block reduces length of stay after laminectomy surgery

Multi-Scale Spiking Network Model of Human Cerebral Cortex

Background: The structure of the brain plays a crucial role in shaping its activity. However, the link between structural connectivity and observed neuronal activity remains incompletely understood. Previous research utilizing a large-scale spiking network model of leaky integrate-and-fire neurons has addressed this question for macaque cortex [1,2]. Here, a similar framework is employed to investigate human cortex in a model that links the cortical network structure to the resting-state activity of neurons, populations, layers, and areas.Objectives: The objective of this study is to investigate the link between structural connectivity and observed neuronal activity in human cortex using a large-scale spiking network model, and to create a platform for multi-scale in silico studies of human cortex.Materials and Methods: The model includes all 34 areas in a single hemisphere of human cortex according to the Desikan-Killiany parcellation. Our approach integrates cortical data on architecture, morphology, and connectivity into a multi-scale framework for predicting neuron connections. Each cortical area is represented by a 1 $mm^2$ layered microcircuit adapted from [3] with the full density of neurons and synapses. Inter-area connectivity relies on diffusion tensor imaging data [4] and the determination of laminar patterns of synaptic connectivity takes into account human neuron morphology data [5]. The model comprises 4 million neurons and 50 billion synapses, simulated with the NEST simulator on the supercomputer JURECA-DC. Results and Conclusions: Simulations of the model with uniform synaptic weights reveal a state with asynchronous and irregular activity that deviates from experimental recordings in terms of spiking activity and inter-area functional connectivity. Increasing inter-area synapse strength enables the model to capture both microscopic and macroscopic resting-state activity of human cortex measured via electrophysiological recordings and fMRI [6]. Furthermore, the model reveals rapid propagation of the effects of a single-spike perturbation across the entire network. This suggests individual spikes play a role in fast sensory processing and behavioral responses in the cortical network. Overall, the model serves as a basis for the investigation of multi-scale structure-dynamics relationships in human cortex

Multi-Scale Spiking Network Model of Human Cerebral Cortex

The structure of the brain plays a crucial role in shaping its activity. However, the link between structural connectivity and observed neuronal activity remains not fully understood. Previous research utilizing a large-scale spiking network model of leaky integrate-and-fire neurons has addressed this question for macaque cortex [1,2]. In this study, we employ the same framework to investigate human cortex and present a large-scale spiking network model that links the cortical network structure to the resting-state activity of neurons, populations, layers, and areas.Our approach integrates data on cortical architecture, cellular morphologies, and local and cortico-cortical connectivity into a multi-scale framework to predict connection probabilities between neurons based on their types and locations within areas and layers. We represent each cortical area with a 1 mm2 area-specific microcircuit incorporating the full density of neurons and synapses. For this first model version, the laminar thicknesses and neuron densities are derived from the von Economo and Koskinas atlas [3]. The connectivity on the area level is informed by diffusion tensor imaging (DTI) data [4], while predictions on laminar connectivity patterns are derived from predictive connectomics based on macaque data that express regularities of laminar connectivity patterns as a function of cortical architecture. We use the Potjans and Diesmann [5] model as a basis for the local connectivity, scaling it according to cytoarchitectonic data. To map inter-area synapses to target cells, which may have their cell body in a different layer compared to the synapse location, we assign synapses in proportion to the layer- and cell-type-specific dendritic lengths determined from human neuron morphologies [6]. The model contains approximately 4 million neurons and 50 billion synapses and is simulated on JURECA-DC using the NEST simulator.Simulations of the model reveal a state with asynchronous and irregular activity that deviates from experimental recordings in terms of spiking activity and inter-area functional connectivity. By increasing the strength of the inter-area synapses, a state is reached that captures aspects of both microscopic and macroscopic resting-state activity of human cortex measured via electrophysiological recordings from medial frontal cortex and fMRI [7]. Furthermore, we used our model to track the effect of a single additional spike through the large-scale network. We find that a single-spike perturbation spreads rapidly across the entire network within 50-75 ms, comparable to visual response latencies in macaque cortex [8], suggesting that the cortical network allows individual spikes to play a role in fast sensory processing and behavioral responses. Overall, the model serves as a basis for the investigation of multi-scale structure-dynamics relationships in human cortex