Role for T-type Ca2+Ca 2+ channels in sleep waves

International audienceSince their discovery more than 30 years ago, low-threshold T-type $Ca 2+$ channels (T channels) have been suggested to play a key role in many EEG waves of non-REM sleep, which has remained exclusively linked to the ability of these channels to generate low-threshold $Ca 2+$ potentials and associated high-frequency bursts of action potentials. Our present understanding of the biophysics and physiology of T channels, however, highlights a much more diverse and complex picture of the pivotal contributions that they make to different sleep rhythms. In particular, recent experimental evidence has conclusively demonstrated the essential contribution of thalamic T channels to the expression of slow waves of natural sleep and the key role played by $Ca 2+$ entry through these channels in the activation or modulation of other voltage-dependent channels that are important for the generation of both slow waves and sleep spindles. However, the precise contribution to sleep rhythms of T channels in cortical neurons and other sleep-controlling neuronal networks remains unknown, and a full understanding of the cellular and network mechanisms of sleep delta waves is still lacking

Improved Positional Encoding for Implicit Neural Representation based Compact Data Representation

Positional encodings are employed to capture the high frequency information of the encoded signals in implicit neural representation (INR). In this paper, we propose a novel positional encoding method which improves the reconstruction quality of the INR. The proposed embedding method is more advantageous for the compact data representation because it has a greater number of frequency basis than the existing methods. Our experiments shows that the proposed method achieves significant gain in the rate-distortion performance without introducing any additional complexity in the compression task and higher reconstruction quality in novel view synthesis.Comment: Published at ICCV 2023 Workshop on Neural Fields for Autonomous Driving and Robotic

Toward laboratory blood test-comparable photometric assessments for anemia in veterinary hematology

Anemia associated with intestinal parasites and malnutrition is the leading cause of morbidity and mortality in small ruminants worldwide. Qualitative scoring of conjunctival redness has been developed so that farmers can gauge anemia in sheep and goats to identify animals that require treatment. For clinically relevant anemia diagnosis, complete blood count-comparable quantitative methods often rely on complicated and expensive optical instruments, requiring detailed spectral information of hemoglobin. We report experimental and numerical results for simple, yet reliable, noninvasive hemoglobin detection that can be correlated with laboratory-based blood hemoglobin testing for anemia diagnosis. In our pilot animal study using calves, we exploit the third eyelid (i.e., palpebral conjunctiva) as an effective sensing site. To further test spectrometer-free (or spectrometerless) hemoglobin assessments, we implement full spectral reconstruction from RGB data and partial least square regression. The unique combination of RGB-based spectral reconstruction and partial least square regression could potentially offer uncomplicated instrumentation and avoid the use of a spectrometer, which is vital for realizing a compact and inexpensive hematology device for quantitative anemia detection in the farm field

A model of the pre-assessment learning effects of summative assessment in medical education

It has become axiomatic that assessment impacts powerfully on student learning. However, surprisingly little research has been published emanating from authentic higher education settings about the nature and mechanism of the pre-assessment learning effects of summative assessment. Less still emanates from health sciences education settings. This study explored the pre-assessment learning effects of summative assessment in theoretical modules by exploring the variables at play in a multifaceted assessment system and the relationships between them. Using a grounded theory strategy, in-depth interviews were conducted with individual medical students and analyzed qualitatively. Respondents’ learning was influenced by task demands and system design. Assessment impacted on respondents’ cognitive processing activities and metacognitive regulation activities. Individually, our findings confirm findings from other studies in disparate non-medical settings and identify some new factors at play in this setting. Taken together, findings from this study provide, for the first time, some insight into how a whole assessment system influences student learning over time in a medical education setting. The findings from this authentic and complex setting paint a nuanced picture of how intricate and multifaceted interactions between various factors in an assessment system interact to influence student learning. A model linking the sources, mechanism and consequences of the pre-assessment learning effects of summative assessment is proposed that could help enhance the use of summative assessment as a tool to augment learning

Modelling the pre-assessment learning effects of assessment : evidence in the validity chain

Publication of this article was funded by the Stellenbosch University Open Access Fund.The original publication is available at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291365-2923/OBJECTIVES We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor–learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. METHODS A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. RESULTS There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. CONCLUSIONS For a subset of uncommon associations in the model, the role of most assessment factor–learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning.Stellenbosch UniversityPublishers' Versio

Modèle de comportement évolutif pour grave-émulsion, basé sur les décompositions spectrales des modèles de Boyce et Huet

Dans un contexte politique où les enjeux énergétiques et environnementaux deviennent de plus en plus forts, la communauté routière souhaite favoriser des techniques plus économes en énergie et plus respectueuses de l'environnement. Parmi celles-ci, l'enrobé bitumineux à l'émulsion de bitume apparaît comme une technique à déployer plus largement sur les réseaux routiers. En effet, cette technique utilise de l'émulsion de bitume qui, comparée aux enrobés à chaud, nécessite moins d'énergie et limite les rejets de GES lors de sa fabrication. Toutefois, la formulation du mélange ainsi que les approches des performances d'une chaussée intégrant une couche d'enrobé à l'émulsion restent empiriques et sont basées sur des savoir-faire locaux. Ceci qui entrave le développement de cette technique.   En règle générale, la première étape pour dimensionner une chaussée consiste à connaitre le comportement mécanique réversible de chacune des couches qui la composent afin de déterminer les champs de contrainte et de déformation de la chaussée au passage des charges roulantes. Dans un deuxième temps, ces valeurs sont comparées aux seuils des critères de durabilité mécanique de ces matériaux.   Le modèle pour enrobé à chaud utilisé jusqu'à présent pour dimensionner les enrobés à l'émulsion est inadéquat car le modèle pour enrobé ne prend pas en compte l'évolution de ce matériau de son état frais à son état mûri. Ce manque de connaissance peut expliquer pourquoi dimensionner une couche d'enrobé à l'émulsion est si complexe et explique le fait que ce matériau ne soit pratiquement pas utilisé dans les chaussées à fort trafic.   La première partie de cet article présente un modèle évolutif pour enrobé à l'émulsion qui prend en compte l'évolution de son état frais à son état mûri en utilisant les modèles de Boyce et de Huet. Ce modèle pour enrobé à l'émulsion est réalisé à partir de la décomposition spectrale des deux modèles puis par leur juxtaposition. L'évolution du comportement mécanique de ce matériau est due à la viscosité du modèle de Huet qui est considérée comme dépendant non seulement de la température mais aussi du vieillissement du matériau. La deuxième partie de cet article montre la réponse en déformation de ce modèle à la simulation de différents types de contraintes

Functional limb muscle innervation prior to cholinergic transmitter specification during early metamorphosis in Xenopus

In vertebrates, functional motoneurons are defined as differentiated neurons that are connected to a central premotor network and activate peripheral muscle using acetylcholine. Generally, motoneurons and muscles develop simultaneously during embryogenesis. However, during Xenopus metamorphosis, developing limb motoneurons must reach their target muscles through the already established larval cholinergic axial neuromuscular system. Here, we demonstrate that at metamorphosis onset, spinal neurons retrogradely labeled from the emerging hindlimbs initially express neither choline acetyltransferase nor vesicular acetylcholine transporter. Nevertheless, they are positive for the motoneuronal transcription factor Islet1/2 and exhibit intrinsic and axial locomotor-driven electrophysiological activity. Moreover, the early appendicular motoneurons activate developing limb muscles via nicotinic antagonist-resistant, glutamate antagonist-sensitive, neuromuscular synapses. Coincidently, the hindlimb muscles transiently express glutamate, but not nicotinic receptors. Subsequently, both pre- and postsynaptic neuromuscular partners switch definitively to typical cholinergic transmitter signaling. Thus, our results demonstrate a novel context-dependent re-specification of neurotransmitter phenotype during neuromuscular system development