In vitro model networks could provide cellular models of physiological relevance to reproduce and investigate the basic function of neural circuits on a chip in the laboratory. Several tools and methods have been developed since the past decade to build neural networks on a chip; among them, microfluidic circuits appear to be a highly promising approach. One of the numerous advantages of this approach is that it preserves stable somatic and axonal compartments over time due to physical barriers that prevent the soma from exploring undesired areas and guide neurites along defined pathways. As a result, neuron compartments can be identified and isolated, and their interconnectivity can be modulated to build a topological neural network (NN). Here, we have assessed the extent to which the confinement imposed by the microfluidic environment can impact cell development and shape NN activity. Toward that aim, microelectrode arrays have enabled the monitoring of the short- and mid-term evolution of neuron activation over the culture period at specific locations in organized (microfluidic) and random (control) networks. In particular, we have assessed the spike and burst rate, as well as the correlations between the extracted spike trains over the first stages of maturation. This study enabled us to observe intense neurite communications that would have been weaker and more delayed within random networks; the spiking rate, burst and correlations being reinforced over time in terms of number and amplitude, exceeding the electrophysiological features of standard cultures. Beyond the enhanced detection efficiency that was expected from the microfluidic channels, the confinement of cells seems to reinforce neural communications and cell development throughout the network.
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http://dx.doi.org/10.1038/s41598-023-39477-9 | DOI Listing |
Physiol Rev
January 2025
Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland.
Physical activity is a meaningful part of life, which starts before birth and lasts until death. There are many health benefits to be derived from physical activity, hence, regular engagement is recommended on a weekly basis. However, these recommendations are often not met.
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January 2025
Department of Computer Science, Khalifa University, Abu Dhabi, UAE.
A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in non-homogeneous temperature fields. The aim of this research is to explore the use of data-driven models in measuring temperature distributions in a spatially resolved manner using emission spectroscopy data. Two categories of data-driven methods are analyzed: (i) Feature engineering and classical machine learning algorithms, and (ii) end-to-end convolutional neural networks (CNN).
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January 2025
Data Management, Modelling and Geo-Information Unit, International Centre of Insect Physiology and Ecology, Kenya.
Organic fertilizers have been identified as a sustainable agricultural practice that can enhance productivity and reduce environmental impact. Recently, the European Union defined and accepted insect frass as an innovative and emerging organic fertilizer. In the wider domain of organic fertilizers, mathematical and computational models have been developed to optimize their production and application conditions.
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January 2025
Department of Zoology, University of Cambridge, Cambridge, UK.
The evolutionary origin of the vertebrate brain remains a major subject of debate, as its development from a dorsal tubular neuroepithelium is unique to chordates. To shed light on the evolutionary emergence of the vertebrate brain, we compared anterior neuroectoderm development across deuterostome species, using available single-cell datasets from sea urchin, amphioxus, and zebrafish embryos. We identified a conserved gene co-expression module, comparable to the anterior gene regulatory network (aGRN) controlling apical organ development in ambulacrarians, and spatially mapped it by multiplexed in situ hybridization to the developing retina and hypothalamus of chordates.
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January 2025
School of Information Science and Engineering, Xinjiang University, Urumqi, China.
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly detection methods overlook the importance of local density, limiting their effectiveness in detecting anomaly objects in complex data distributions. To address this challenge, we introduce a generative adversarial local density-based anomaly detection (GALD) method, which combines the data distribution modeling capabilities of GANs with local synthetic density analysis.
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