International review of neurobiology最新文献

Alcohol, the most widely consumed substance globally, can lead to severe adverse effects for both users and those around them. Chronic ethanol consumption may lead to alcohol use disorder (AUD), a chronic relapsing condition characterized by compulsive drinking despite negative consequences. AUD is marked by a high relapse rate among individuals attempting abstinence. Currently, only a few medications, such as disulfiram, naltrexone, nalmefene, and acamprosate, are approved to treat AUD. Moreover, genetic factors and comorbid conditions can significantly influence both the development of AUD and the efficacy of its treatment. This chapter explores the genetic underpinnings of AUD and reviews the main pharmacological treatments available for managing this disorder.

Alcohol Use Disorder (AUD) is a highly prevalent medical condition characterized by impaired control over alcohol consumption, despite negative consequences on the individual's daily life and health. There is increasing evidence suggesting that chronic alcohol intake, like other addictive drugs, induces neuroinflammation and oxidative stress, disrupting glutamate homeostasis in the main brain areas related to drug addiction. This review explores the potential application of mesenchymal stem cells (MSCs)-based therapy for the treatment of AUD. MSCs secrete a broad array of anti-inflammatory and antioxidant molecules, thus, the administration of MSCs, or their secretome, could reduce neuroinflammation and oxidative stress in the brain. These effects correlate with an increase in the expression of the main glutamate transporter, GLT1, which, through the normalization of the extracellular glutamate levels, could mediate the inhibitory effect of MSCs' secretome on chronic alcohol consumption, thus highlighting GLT1 as a central target to reduce chronic alcohol consumption.

Pain is one of the key non-motor symptoms experienced by a large proportion of people living with Parkinson's disease (PD), yet the mechanisms behind this pain remain elusive and as such its treatment remains suboptimal. It is hoped that through the study of animal models of PD, we can start to unravel some of the contributory mechanisms, and perhaps identify models that prove useful as test beds for assessing the efficacy of potential new analgesics. However, just how far along this journey are we right now? Is it even possible to model pain in PD in animal models of the disease? And have we gathered any insight into pain mechanisms from the use of animal models of PD so far? In this chapter we intend to address these questions and in particular highlight the findings generated by others, and our own group, following studies in a range of rodent models of PD.

This chapter describes the role of neurophysiological techniques in diagnosing and monitoring amyotrophic lateral sclerosis (ALS). Despite many advances, electromyography (EMG) remains a keystone investigation from which to build support for a diagnosis of ALS, demonstrating the pathophysiological processes of motor unit hyperexcitability, denervation and reinnervation. We consider development of the different diagnostic criteria and the role of EMG therein. While not formally recognised by established diagnostic criteria, we discuss the pioneering studies that have demonstrated the diagnostic potential of transcranial magnetic stimulation (TMS) of the motor cortex and highlight the growing evidence for TMS in the diagnostic process. Finally, accurately monitoring disease progression is crucial for the successful implementation of clinical trials. Neurophysiological measures of disease state have been incorporated into clinical trials for over 20 years and we review prominent techniques for assessing disease progression.

The majority of amyotrophic lateral sclerosis (ALS) is caused by a complex gene-environment interaction. Despite high estimates of heritability, the genetic basis of disease in the majority of ALS patients are unknown. This limits the development of targeted genetic therapies which require an understanding of patient-specific genetic drivers. There is good evidence that the majority of these missing genetic risk factors are likely to be found within the non-coding genome. However, a major challenge in the discovery of non-coding risk variants is determining which variants are functional in which specific CNS cell type. We summarise current discoveries of ALS-associated genetic drivers within the non-coding genome and we make the case that improved cell-specific annotation of genomic function is required to advance this field, particularly via single-cell epigenetic profiling and spatial transcriptomics. We highlight the example of TBK1 where an apparent paradox exists between pathogenic coding variants which cause loss of protein function, and protective non-coding variants which cause reduced gene expression; the paradox is resolved when it is understood that the non-coding variants are acting primarily via change in gene expression within microglia, and the effect of coding variants is most prominent in neurons. We propose that cell-specific functional annotation of ALS-associated genetic variants will accelerate discovery of the genetic architecture underpinning disease in the vast majority of patients.

Chronic pain presents significant personal, psychological, and socioeconomic hurdles, impacting over 30% of adults worldwide and substantially contributing to disability. Unfortunately, current pharmacotherapy often proves inadequate, leaving fewer than 70% of patients with relief. This shortfall has sparked a drive to seek alternative treatments offering superior safety and efficacy profiles. Cannabinoid-based pharmaceuticals, notably cannabidiol (CBD), hold promise in pain management, driven by their natural origins, versatility, and reduced risk of addiction. As we navigate the opioid crisis, ongoing research plunges into CBD's therapeutic potential, buoyed by animal studies revealing its pain-relieving prowess through various system tweaks. However, the efficacy of cannabis in chronic pain management remains a contentious and stigmatized issue. The International Association for the Study of Pain (IASP) presently refrains from endorsing cannabinoid use for pain relief. Nevertheless, evidence indicates their potential in alleviating cancer-related, neuropathic, arthritis, and musculoskeletal pain, necessitating further investigation. Crucially, our comprehension of CBD's role in pain management is a journey still unfolding, with animal studies illustrating its analgesic effects through interactions with the endocannabinoid, inflammatory, and nociceptive systems. As the plot thickens, it's clear: the saga of chronic pain and CBD's potential offers a compelling narrative ripe for further exploration and understanding.

Parkinson's disease is a chronic neurodegenerative disorder with no known cure characterized by motor symptoms such as tremors, rigidity, bradykinesia (slowness of movement), and postural instability. Non-motor symptoms like cognitive impairment, mood disturbances, and sleep disorders often accompany the disease. Pharmacological treatments for these symptoms are limited and frequently induce significant adverse reactions, underscoring the necessity for appropriate treatment options. Cannabidiol is a phytocannabinoid devoid of the euphoric and cognitive effects of tetrahydrocannabinol. The study of cannabidiol's pharmacological effects has increased exponentially in recent years. Preclinical and preliminary clinical studies suggest that cannabidiol holds therapeutic potential for alleviating symptoms of Parkinson's disease, offering neuroprotective, anti-inflammatory, and antioxidant properties. However, knowledge of cannabidiol neuromolecular mechanisms is limited, and its pharmacology, which appears complex, has not yet been fully elucidated. By examining the evidence, this review aims to provide and synthesize scientifically proven evidence for the potential use of cannabidiol as a novel treatment option for Parkinson's disease. We focus on studies that administrated cannabidiol alone. The results of preclinical trials using cannabidiol in models of Parkinson's disease are encouraging. Nevertheless, drawing firm conclusions on the therapeutic efficacy of cannabidiol for patients is challenging. Cannabidiol doses, formulations, outcome measures, and methodologies vary considerably across studies. Though, cannabidiol holds promise as a novel therapeutic option for managing both motor and non-motor symptoms of Parkinson's disease, offering hope for improved quality of life for affected individuals.

Major depressive disorder (MDD) is a widespread and debilitating condition affecting a significant portion of the global population. Traditional treatment for MDD has primarily involved drugs that increase brain monoamines by inhibiting their uptake or metabolism, which is the basis for the monoaminergic hypothesis of depression. However, these treatments are only partially effective, with many patients experiencing delayed responses, residual symptoms, or complete non-response, rendering the current view of the hypothesis as reductionist. Cannabidiol (CBD) has shown promising results in preclinical models and human studies. Its mechanism is not well-understood, but may involve monoamine and endocannabinoid signaling, control of neuroinflammation and enhanced neuroplasticity. This chapter will explore CBD's effects in preclinical and clinical studies, its molecular mechanisms, and its potential as a treatment for MDD.

Animal models continue to be crucial to developing our understanding of the molecular, cellular, and neurophysiological mechanisms that lead to neuropathic pain. The overwhelming majority of animal studies use rodent models, ranging from surgical and trauma-induced models to those induced by metabolic diseases, genetic mutations, viruses, neurotoxic drugs, and cancer. We discuss the clinical relevance of the available models and the pain behavior tests commonly used as outcome measures. Finally, we summarize the refinements that have been proposed to improve the ability of animal model studies to predict clinical efficacy.