Evaluation of Parkinson's disease early diagnosis using single-channel EEG features and auditory cognitive assessment.

Background: Parkinson's disease (PD) often presents with subtle early signs, making diagnosis difficult. F-DOPA PET imaging provides a reliable measure of dopaminergic function and is a primary tool for early PD diagnosis. This study aims to evaluate the ability of machine-learning (ML) extracted EEG features to predict F-DOPA results and distinguish between PD and non-PD patients. These features, extracted using a single-channel EEG during an auditory cognitive assessment, include EEG feature A0 associated with cognitive load in healthy subjects, and EEG feature L1 associated with cognitive task differentiation. Methods: Participants in this study are comprised of cognitively healthy patients who had undergone an F-DOPA PET scan as a part of their standard care (n = 32), and cognitively healthy controls (n = 20). EEG data collected using the Neurosteer system during an auditory cognitive task, was decomposed using wavelet-packet analysis and machine learning methods for feature extraction. These features were used in a connectivity analysis that was applied in a similar manner to fMRI connectivity. A preliminary model that relies on the features and their connectivity was used to predict initially unrevealed F-DOPA test results. Then, generalized linear mixed models (LMM) were used to discern between PD and non-PD subjects based on EEG variables. Results: The prediction model correctly classified patients with unrevealed scores as positive F-DOPA. EEG feature A0 and the Delta band revealed distinct activity patterns separating between study groups, with controls displaying higher activity than PD patients. In controls, EEG feature L1 showed variations between resting state and high-cognitive load, an effect lacking in PD patients. Conclusion: Our findings exhibit the potential of single-channel EEG technology in combination with an auditory cognitive assessment to distinguish positive from negative F-DOPA PET scores. This approach shows promise for early PD diagnosis. Additional studies are needed to further verify the utility of this tool as a potential biomarker for PD.

Factor VII, EPCR, aPC Modulators: novel treatment for neuroinflammation.

BACKGROUND: Inflammation and coagulation are linked and pathogenic in neuroinflammatory diseases. Protease-activated receptor 1 (PAR1) can be activated both by thrombin, inducing increased inflammation, and activated protein C (aPC), inducing decreased inflammation. Modulation of the aPC-PAR1 pathway may prevent the neuroinflammation associated with PAR1 over-activation. METHODS: We synthesized a group of novel molecules based on the binding site of FVII/aPC to the endothelial protein C receptor (EPCR). These molecules modulate the FVII/aPC-EPCR pathway and are therefore named FEAMs-Factor VII, EPCR, aPC Modulators. We studied the molecular and behavioral effects of a selected FEAM in neuroinflammation models in-vitro and in-vivo. RESULTS: In a lipopolysaccharide (LPS) induced in-vitro model, neuroinflammation leads to increased thrombin activity compared to control (2.7 ± 0.11 and 2.23 ± 0.13 mU/ml, respectively, p = 0.01) and decreased aPC activity (0.57 ± 0.01 and 1.00 ± 0.02, respectively, p < 0.0001). In addition, increased phosphorylated extracellular regulated kinase (pERK) (0.99 ± 0.13, 1.39 ± 0.14, control and LPS, p < 0.04) and protein kinase B (pAKT) (1.00 ± 0.09, 2.83 ± 0.81, control and LPS, p < 0.0002) levels indicate PAR1 overactivation, which leads to increased tumor necrosis factor-alpha (TNF-α) level (1.00 ± 0.04, 1.35 ± 0.12, control and LPS, p = 0.02). In a minimal traumatic brain injury (mTBI) induced neuroinflammation in-vivo model in mice, increased thrombin activity, PAR1 activation, and TNF-α levels were measured. Additionally, significant memory impairment, as indicated by a lower recognition index in the Novel Object Recognition (NOR) test and Y-maze test (NOR: 0.19 ± 0.06, -0.07 ± 0.09, p = 0.03. Y-Maze: 0.50 ± 0.03, 0.23 ± 0.09, p = 0.02 control and mTBI, respectively), as well as hypersensitivity by hot-plate latency (16.6 ± 0.89, 12.8 ± 0.56 s, control and mTBI, p = 0.01), were seen. FEAM prevented most of the molecular and behavioral negative effects of neuroinflammation in-vitro and in-vivo, most likely through EPCR-PAR1 interactions. CONCLUSION: FEAM is a promising tool to study neuroinflammation and a potential treatment for a variety of neuroinflammatory diseases.

Recovery from trauma induced amnesia correlates with normalization of thrombin activity in the mouse hippocampus.

Transient amnesia is a common consequence of minimal traumatic brain injury (mTBI). However, while recent findings have addressed the mechanisms involved in its onset, the processes contributing to its recovery have not yet been addressed. Recently, we have found that thrombin is detected at high concentrations in the brain of mice after exposure to mTBI and that in such settings amnesia is rescued by either inhibiting thrombin activity or by blockade of PAR1. Here, we report that mice spontaneously recover from amnesia after two weeks from mTBI exposure. At this time point, long term potentiation was equally evoked in injured vs. control animals with thrombin concentration in the brain being normalized at this stage. These findings, which refer to the specific aspect of memory retrieval upon mTBI, together with our previous work, hint to a strong correlation between cognitive defects in the context of mTBI and thrombin concentrations in the brain. This may suggest that a possible scavenging of thrombin in the brain at early phases following mTBI may improve memory function.