Differential effects of statins on the anti-dyskinetic activity of sub-anesthetic ketamine.

Sub-anesthetic ketamine has been demonstrated to reduce abnormal involuntary movements (AIMs) in preclinical models of L-DOPA-induced dyskinesia (LID) and retrospective Parkinson's disease (PD) case reports. In this study, we examined the effects on LID of two different statins alone and in combination with ketamine in unilateral 6-hydroxydopamine-lesioned male rats, the standard model for preclinical LID studies. Ketamine attenuated the development of AIMs, while the non-polar lovastatin only showed anti-dyskinetic activity early in the priming period but did not prevent the development of LID, and the polar pravastatin showed no anti-dyskinetic activity.

Extrasinusoidal macrophages are a distinct subset of immunologically active dural macrophages.

Although macrophages in the meningeal compartments of the central nervous system (CNS) have been comprehensively characterized under steady state, studying their contribution to physiological and pathological processes has been hindered by the lack of specific targeting tools in vivo. Recent findings have shown that the dural sinus and its adjacent lymphatic vessels act as a neuroimmune interface. However, the cellular and functional heterogeneity of extrasinusoidal dural macrophages outside this immune hub is not fully understood.

Differential effects of statins on the anti-dyskinetic activity of sub-anesthetic ketamine.

Sub-anesthetic ketamine has been demonstrated to reduce abnormal involuntary movements (AIMs) in preclinical models of L-DOPA-induced dyskinesia (LID) and retrospective Parkinson's disease case reports. In this study, we examined the effects on L-DOPA-induced dyskinesia of two statins alone and in combination with ketamine in unilateral 6-hydroxydopamine-lesioned male rats, the standard preclinical LID model. Sub-anesthetic ketamine attenuated the development of AIMs, while lovastatin only showed anti-dyskinetic activity at the beginning of the priming but did not prevent the development of LID.

Decoupling of motor cortex to movement in Parkinson's dyskinesia rescued by sub-anaesthetic ketamine.

Gamma band and single-unit neural activity in primary motor cortex (M1) are involved in the control of movement. This activity is disrupted in Parkinson's disease (PD) and levodopa-induced dyskinesia (LID), a debilitating consequence of dopamine replacement therapy for PD. Physiological features of LID include pathological narrowband gamma oscillations, finely tuned gamma (FTG), and altered M1 firing activity.

WavRx: a Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model.

Speech is known to carry health-related attributes, which has emerged as a novel venue for remote and long-term health monitoring. However, existing models are usually tailored for a specific type of disease, and have been shown to lack generalizability across datasets. Furthermore, concerns have been raised recently towards the leakage of speaker identity from health embeddings.

The angiotensin (1-7) glycopeptide PNA5 improves cognition in a chronic progressive mouse model of Parkinson's disease through modulation of neuroinflammation.

Cognitive decline in Parkinson's Disease (PD) is a prevalent and undertreated aspect of disease. Currently, no therapeutics adequately improve this aspect of disease. It has been previously shown that MAS receptor agonism via the glycosylated Angiotensin (1-7) peptide, PNA5, effectively reduces cognitive decline in models of vascular contributions to cognitive impairment and dementia (VCID).

MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees.

We present a one-year-long multi-sensor dataset collected from honey bee colonies (Apis mellifera) with rich phenotypic measurements. Data were collected non-stop from April 2020 to April 2021 from 53 hives located at two apiaries in Québec, Canada. The sensor data included audio features, temperature, and relative humidity.

PACAP glycosides promote cell outgrowth in vitro and reduce infarct size after stroke in a preclinical model.

Pituitary Adenylate Cyclase Activating Polypeptide (PACAP) is a pleiotropic peptide known to promote many beneficial processes following neural damage and cell death after stroke. Despite PACAP's known neurotrophic and anti-inflammatory properties, it has not realized its translational potential due to a poor pharmacokinetic profile (non-linear PK/PD), and limited Blood-Brain Barrier Penetration (BBB) permeability. We have previously shown that glycosylation of PACAP increases stability and enhances BBB penetration.

Differential effects of opioid receptor antagonism on the anti-dyskinetic and anti-parkinsonian effects of sub-anesthetic ketamine treatment in a preclinical model.

Sub-anesthetic ketamine treatment has been shown to be an effective therapy for treatment-resistant depression and chronic pain. Our group has previously shown that sub-anesthetic ketamine produces acute anti-parkinsonian, and acute anti-dyskinetic effects in preclinical models of Parkinson's disease (PD). Ketamine is a multifunctional drug and exerts effects through blockade of N-methyl-d-aspartate receptors but also through interaction with the opioid system.

Secondary Sites of the C-type Lectin-Like Fold.

C-type lectins are a large superfamily of proteins involved in a multitude of biological processes. In particular, their involvement in immunity and homeostasis has rendered them attractive targets for diverse therapeutic interventions. They share a characteristic C-type lectin-like domain whose adaptability enables them to bind a broad spectrum of ligands beyond the originally defined canonical Ca-dependent carbohydrate binding.

Enhancing motor imagery detection efficacy using multisensory virtual reality priming.

Brain-computer interfaces (BCI) have been developed to allow users to communicate with the external world by translating brain activity into control signals. Motor imagery (MI) has been a popular paradigm in BCI control where the user imagines movements of e.g.

Quantifying time perception during virtual reality gameplay using a multimodal biosensor-instrumented headset: a feasibility study.

We have all experienced the sense of time slowing down when we are bored or speeding up when we are focused, engaged, or excited about a task. In virtual reality (VR), perception of time can be a key aspect related to flow, immersion, engagement, and ultimately, to overall quality of experience. While several studies have explored changes in time perception using questionnaires, limited studies have attempted to characterize them objectively.

EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs.

Brain-computer interface (BCI) technology has emerged as an influential communication tool with extensive applications across numerous fields, including entertainment, marketing, mental state monitoring, and particularly medical neurorehabilitation. Despite its immense potential, the reliability of BCI systems is challenged by the intricacies of data collection, environmental factors, and noisy interferences, making the interpretation of high-dimensional electroencephalogram (EEG) data a pressing issue. While the current trends in research have leant towards improving classification using deep learning-based models, our study proposes the use of new features based on EEG amplitude modulation (AM) dynamics.

Automated system for training and assessing reaching and grasping behaviors in rodents.

Background: Reaching, grasping, and pulling behaviors are studied across species to investigate motor control and problem solving. String pulling is a distinct reaching and grasping behavior that is rapidly learned, requires bimanual coordination, is ethologically grounded, and has been applied across species and disease conditions.

New Method: Here we describe the PANDA system (Pulling And Neural Data Analysis), a hardware and software system that integrates a continuous string loop connected to a rotary encoder, feeder, microcontroller, high-speed camera, and analysis software for the assessment and training of reaching, grasping, and pulling behaviors and synchronization with neural data.

Neuromorphic Computing via Fission-based Broadband Frequency Generation.

The performance limitations of traditional computer architectures have led to the rise of brain-inspired hardware, with optical solutions gaining popularity due to the energy efficiency, high speed, and scalability of linear operations. However, the use of optics to emulate the synaptic activity of neurons has remained a challenge since the integration of nonlinear nodes is power-hungry and, thus, hard to scale. Neuromorphic wave computing offers a new paradigm for energy-efficient information processing, building upon transient and passively nonlinear interactions between optical modes in a waveguide.

Antagonism of kappa opioid receptors accelerates the development of L-DOPA-induced dyskinesia in a preclinical model of moderate dopamine depletion.

Levels of the opioid peptide dynorphin, an endogenous ligand selective for kappa-opioid receptors (KORs), its mRNA and pro-peptide precursors are differentially dysregulated in Parkinson's disease (PD) and following the development of l-DOPA-induced dyskinesia (LID). It remains unclear whether these alterations contribute to the pathophysiological mechanisms underlying PD motor impairment and the subsequent development of LID, or whether they are part of compensatory mechanisms. We sought to investigate nor-BNI, a KOR antagonist, 1) in the dopamine (DA)-depleted PD state, 2) during the development phase of LID, and 3) via measuring of tonic levels of striatal DA.

piRNA processing by a trimeric Schlafen-domain nuclease.

Transposable elements are genomic parasites that expand within and spread between genomes. PIWI proteins control transposon activity, notably in the germline. These proteins recognize their targets through small RNA co-factors named PIWI-interacting RNAs (piRNAs), making piRNA biogenesis a key specificity-determining step in this crucial genome immunity system.

Antagonism of kappa opioid receptors accelerates the development of L-DOPA-induced dyskinesia in a preclinical model of moderate dopamine depletion.

Levels of the opioid peptide dynorphin, an endogenous ligand selective for kappa-opioid receptors (KORs), its mRNA and pro-peptide precursors are differentially dysregulated in Parkinson disease (PD) and following the development of L-DOPA-induced dyskinesia (LID). It remains unclear, whether these alterations contribute to the pathophysiological mechanisms underlying PD motor impairment and the subsequent development of LID, or whether they are part of compensatory mechanisms. We sought to investigate nor-BNI, a KOR antagonist, 1) in the dopamine (DA)-depleted PD state, 2) during the development phase of LID, and 3) with measuring tonic levels of striatal DA.

Automated Multi-Wavelength Quality Assessment of Photoplethysmography Signals Using Modulation Spectrum Shape Features.

Photoplethysmography (PPG) is used to measure blood volume changes in the microvascular bed of tissue. Information about these changes along time can be used for estimation of various physiological parameters, such as heart rate variability, arterial stiffness, and blood pressure, to name a few. As a result, PPG has become a popular biological modality and is widely used in wearable health devices.

Using CNN Saliency Maps and EEG Modulation Spectra for Improved and More Interpretable Machine Learning-Based Alzheimer's Disease Diagnosis.

Biomarkers based on resting-state electroencephalography (EEG) signals have emerged as a promising tool in the study of Alzheimer's disease (AD). Recently, a state-of-the-art biomarker was found based on visual inspection of power modulation spectrograms where three "patches" or regions from the modulation spectrogram were proposed and used for AD diagnostics. Here, we propose the use of deep neural networks, in particular convolutional neural networks (CNNs) combined with saliency maps, trained on power modulation spectrogram inputs to find optimal patches in a data-driven manner.