Neurotherapeutics最新文献

Migraine is one of the leading causes of disability globally. Despite advances in the available pharmacological options for its management, many patients still show a lack of response to these current therapeutics. As a consequence, it is important to explore new targets for the management of migraine and related headache disorders. In this review, we discuss evidence related to various novel targets that are in different stages of development as part of the current therapeutic pipeline in migraine management. These include recent studies that report the role of specific ion channels in migraine pathophysiology, including ATP-sensitive potassium channels (K_ATP), large conductance calcium- and voltage-activated potassium channels (BK_Ca), and transient receptor potential melastatin (TRPM) channels, specifically TRPM3 and TRPM8. Additionally, peptides secreted endogenously by hypothalamic nuclei have drawn attention, for example, oxytocin, orexins and prolactin have been signaled as possible systems for modulation with therapeutics. Here, we will assess preclinical validation studies, as well as clinical experimental and clinical trial data, and we will discuss some of the potential challenges with these targets and the future perspectives of these pipeline targets.

Biomarkers are essential to guide decision making in Alzheimer's disease (AD) clinical trials where they have a variety of contexts of use (COUs) including diagnosis, risk, pharmacodynamic response, prognosis, prediction, monitoring, and safety. The COU of biomarkers may differ by phase of drug development with Phase 1, 2, and 3 emphasizing different types of information for decision making. A variety of biomarkers are currently serving as pharmacodynamic outcomes in clinical trials including amyloid and tau PET and fluid measures of amyloid, tau, neurodegeneration, inflammation, and synaptic plasticity. Biomarker strategies are integrated throughout drug development programs from collection and assay performance to statistical analysis and data interpretation. Data interrogation approaches using artificial intelligence and machine learning may enhance the value of biomarker observations through integration of multimodal data. Emerging biomarkers that may play a role in future AD trials include proteomics, exosome assays of co-pathology occurring in AD, EEG, ocular measures, and digital biomarkers. Biomarkers inform drug development decision-making including termination of candidate agents without sufficient biomarker effects, resourcing of promising therapies impacting the fundamental features of AD, and accelerating the development of new therapies for those with or at risk for AD.

Migraine is among the most dynamic and disabling neurological disorders, affecting over one billion people globally. Attacks demonstrate rhythmic patterns of onset across the day and seasonally, highlighting that attack onset is influenced by an individual's biological rhythms. Indeed, an individual's chronotype (their endogenous circadian clock rhythm) predicts when they are most likely to have an attack. These biological rhythms are regulated by an endogenous master biological clock in the hypothalamus that coordinates the function of peripheral clocks, aligning biological processes and behaviours to environmental cues (e.g. daily rhythms in light-dark cycles). As such, circadian rhythms are essential to maintain normal neurological function and health, regulating the expression of approximately 50 % of all protein coding genes in mammals. Importantly, the majority of the World Health Organisations essential medicines and several migraine-related therapeutics directly target the products of these rhythmic genes or influence circadian-related genes directly. Therefore, the current review will focus on the potential for chronotherapy in migraine. Highlighting its potential to optimise the chronopharmacokinetic profile, therapeutic efficacy and reduce potential side effects of anti-migraine therapies. A greater understanding of which has the potential for significant impact, representing a low cost, scalable method to improve therapeutic response and inform a personalized therapeutic strategy.

α-Synuclein is a small presynaptic protein whose aggregation is one of the hallmarks of Parkinson's disease (PD). In our quest to identify novel preventive or therapeutic treatments for PD, we collected 60 Italian plant species, representative of part of the Mediterranean flora, which were screened by a phylogenetic analysis in conjunction with a high-throughput screening in a yeast model of PD expressing human α-synuclein. The integration of these approaches led to the identification of four plants, Allium lusitanicum, Salvia pratensis, Verbascum thapsus and Glaucium flavum, whose extracts, characterized by a metabolomic analysis, exhibit robust inhibitory activity against the amyloid aggregation of α-synuclein in vitro, as well as in neuroblastoma cells overexpressing the protein. By employing a size exclusion chromatography affinity approach coupled to mass spectrometry, we identified the phenylpropanoid glycoside acteoside from the extract of the edible plant V. thapsus as the metabolite that directly binds α-synuclein and effectively inhibits its fibril formation. In addition, acteoside reduces oxidative stress in neuroblastoma cells exposed to α-synuclein fibrils and activates the NRF2 pathway. Notably, acteoside improves motor performance in a Drosophila model of PD and exhibits a significant reduction of protein carbonyl groups, suggesting that this compound may mitigate oxidative stress-induced protein damage. Our findings could pave the way for the development of new strategies aimed at discovering novel neuroprotective agents targeting PD-related diseases.

The aim of this study was to evaluate the feasibility of low-density (LD) interictal (IIC) and ictal (IC) electrical source imaging (ESI), and to assess their individual and combined diagnostic accuracy and predictive value in a cohort of children with drug-resistant epilepsy (DRE) who underwent resective surgery before the age of 7. Retrospective analysis was conducted on de-identified EEG and MRI data, which were (semi)-automatically processed, blinded to clinical information, to compute both IIC and IC-ESI. The concordance of ESI localizations with the resection cavity at sublobar level, and the association with surgical outcome were assessed. Thirty-two children were included. IIC- and IC-ESI showed an accuracy of 66 ​% (CI 95 ​% 47-81 ​%) and 72 ​% (CI 95 ​% 53-86 ​%) and a diagnostic odds ratio (DOR) of 3.0 (CI 95 ​% 0,66-13,69; p ​= ​0,15) and 5.0 (CI 95 ​% 0,91-27,47; p ​= ​0,06), respectively. The combined approach increased diagnostic performance, achieving an overall accuracy of 75 ​% and a DOR of 11.4 (CI 95 ​% 1.08-120,35; p ​= ​0,042). In multivariate logistic regression analysis, the combined IIC/IC ESI result emerged as the strongest predictor of postsurgical seizure freedom (OR: 222,28; p ​= ​0,0262; AUC: 0.87). These findings demonstrate that combined (semi)-automated LD-IIC and IC-ESI is feasible and can accurately localize the epileptogenic zone and predict postsurgical seizure freedom in children under 7 years of age. ESI may support earlier surgical referral, reduce the time from epilepsy onset to surgery, and ultimately improve long-term outcomes.

Infantile epileptic spasms syndrome (IESS) is a developmental and. epileptic encephalopathy with unique clinical and electrographic features, including seizure semiology (spasms), numerous and diverse etiologies spanning structural, genetic and metabolic causes, characteristic interictal (hypsarrhythmia) and ictal (electrodecrement) electroencephalogram (EEG) patterns, and responsiveness to "standard" pharmacological therapies (adrenocorticotrophic hormone, high-dose corticosteroids, vigabatrin) that are not commonly used in other epilepsy syndromes. Despite these long-recognized clinical features and laboratory investigations using a multiplicity of animal models with different epileptogenic mechanisms, the neurobiological underpinnings of IESS remain poorly understood, hampering the development of alternative treatments. This commentary discusses three aspects of IESS intended to raise fundamental clinical and mechanistic issues to afford greater understanding of the syndrome - nomenclature, EEG findings, and selected emerging animal models that might shed light on IESS pathophysiology and guide therapy development.

Alzheimer's disease (AD), closely associated with mitochondrial dysfunction, currently lacks convenient and non-invasive biomarkers for mitochondrial assessment. In this study, we developed an artificial intelligence framework leveraging live urine-derived stem cell (USC) mitochondrial fluorescence imaging to investigate differences between cognitively impaired individuals (AD and mild cognitive impairment (MCI)) and cognitively normal (CN) subjects. Mitochondrial fluorescence images from living HeLa cells were first segmented, and two binary classification models based on the ResNet-18 convolutional neural network were trained to identify mitochondrial hyperfission and hyperfusion relative to normal morphology. The models demonstrated robust performance in detecting intermediate mitochondrial states during validation. When applied to USCs, the system effectively distinguished mitochondrial patterns associated with cognitive impairment, highlighting its potential for the early detection of Alzheimer's disease and merits further validation in larger, independent cohorts.

More than half of subarachnoid hemorrhage (SAH) survivors develop delayed cognitive dysfunction, but the underlying mechanisms remain elusive. This study investigated the role of meningeal lymphatic vessels (mLVs) in this complication by examining their structural integrity, drainage capacity, and association with cognitive deficits post-SAH. In adult male C57BL/6J mice in which SAH was induced by intracisternal injection of autologous blood, spatial learning and memory, and hippocampal CA1 neuronal activity were impaired as early as 1 month post-surgery, with a marked exacerbation of these deficits at 2 months. SAH induced mLV fragmentation and atrophy, subsequent cerebrospinal and interstitial fluid drainage impairment, metabolite accumulation, and ultimately delayed cognitive dysfunction. Notably, lymphatic vessel ablation exacerbated these pathologies. In vitro experiments confirmed that vascular endothelial growth factor C (VEGF-C) reduced oxyhemoglobin-induced lymphatic endothelial cell apoptosis. Furthermore, in vivo studies demonstrated that VEGF-C therapy inhibited amyloid-β (Aβ) deposition in the hippocampal CA1 region and ameliorated cognitive dysfunction. Additional studies revealed that VEGF-C's protective effect on mLVs may be mediated via PI3K-AKT pathway activation. Collectively, these findings indicate that disrupted mLV integrity and drainage contribute to post-SAH cognitive impairment. Activation of VEGF-C-mediated PI3K-AKT signaling may preserve mLV function and represent a potential therapeutic strategy for preventing delayed cognitive impairment after SAH.

Several studies show that neurosteroids currently play a significant role in autism spectrum disorders (ASD). However, the pathway of neurosteroid synthesis involved in ASD remains unclear. This study aimed to investigate the crosstalk between autism and neurosteroids, focusing on the mechanism of allopregnanolone production. We used the BTBR T+ tf/J (BTBR) mouse, a well-established animal model of ASD that exhibits typical autism-like behaviors along with neuroinflammation. In the hippocampus of BTBR mice, we observed a marked overexpression of pregnenolone and a related reduction in allopregnanolone levels. This neurosteroid imbalance also appears to be associated with an inflammatory pattern and the manifestation of repetitive and asocial behaviors. The combination of low doses of ultramicronized palmitoylethanolamide (PEA-um) and docosahexaenoic acid (DHA) restores allopregnanolone production modulating neurosteroidogenesis. In association with neurosteroid modulation, this restoration reduces repetitive behaviors and improves social interactions in BTBR mice, also modulating the inflammatory profile with a significant reduction in proinflammatory cytokines and brain-derived neurotrophic factor (BDNF) levels in the hippocampus. These effects demonstrate an important role of the peroxisome proliferator-activated receptor alpha (PPAR-α), whose expression is particularly reduced in BTBR mice. In addition, the pivotal involvement of PPAR-α was further supported by administering a specific antagonist that abolished the advantageous effects of PEA-um ​+ ​DHA. Overall, our findings demonstrate the potential synergistic effect of the low-dose combination of PEA-um and DHA, confirming their therapeutic effect in ASD and the involvement of neurosteroids in their mechanism of action.