Acute ischemic stroke (AIS) is the leading cause of disability and one of the top causes of mortality worldwide. The current standard of care is reperfusion therapy including intravenous thrombolysis (IVT) and thrombectomy. However, these treatments have limitations as they have a limited therapeutic window. Hence, there is a vital need to develop neuroprotective agents to prevent brain injury, extend the reperfusion window, improve mortality, and reduce disability in AIS patients. Neuroprotective agents work by counteracting the detrimental biochemical and molecular events that result in irreversible ischemic damage. Numerous preclinical studies and clinical trials have been done on different agents. Thus far, all have been definitively unsuccessful in large trials. Currently, there are several challenges in translation from animal studies to human trials. It is important to understand the current evidence as well as past challenges in the development of neuroprotective strategies in AIS in order for a more strategic selection of agents to be studied, improve study designs and thus contribute to the development of effective neuroprotective agents. Newer agents have shown promise in neuroprotection, and human trials are ongoing. In this review, the mechanisms of action of different families of neuroprotective agents were discussed. The evidence for the efficacy of different drugs in each family of neuroprotective agents was also evaluated and the current research landscape in neuroprotection for AIS was summarized. The past challenges and limitations in clinical trials and proposed possible ways to address these issues were highlighted.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder affecting 1% of the population above sixty years. It is caused by an interaction between genetic and environmental risk factors. Loss of dopaminergic neurons in substantia nigra pars compacta (SNpc) is pathologically characterizing the disease and responsible for the cardinal motor symptoms, most notably, bradykinesia, rest tremors, rigidity, and loss of postural reflexes. Non-motor signs such as olfactory deficits, cognitive impairment, sleep behavior disorders, and gastrointestinal disturbances are reflecting disturbances in the non-dopaminergic system. They precede dopaminergic neuronal degenerations by 5–10 years and are considered the main contributors to patients’ disability, particularly after the successful implementation of levodopa (L-dopa) treatment of motor symptoms. The present general review aimed to briefly update non-motor signs and their underlying pathophysiology in PD.

There is no approved drug capable of halting the progression of the most prevalent neurodegenerative disorders, namely Alzheimer’s disease (AD) and Parkinson’s disease (PD). Current therapeutic strategies focus mainly on the inhibition of the formation of protein aggregates and their deposition in the central nervous system. However, after almost a hundred years, proper management of the disease is still lacking. The fact of not finding effective management tools in the various clinical trials already carried out suggests that new hypotheses and strategies should be explored. Although vast resources have been allocated to the investigation of protein aggregates and the pathophysiology is now better understood, clues to the actual etiology are lacking. It is well known that brain homeostasis is of paramount importance for the survival of neurons. Drugs that target the periphery are often not subject to evaluation for their potential effect on the central nervous system. While acute treatments may be irrelevant, pills used for chronic conditions can be detrimental to neurons, especially in terms of progressive damage leading to a long-term decline in neuronal survival. Due to the lack of advances in the search for a curative treatment for neurodegenerative diseases, and the lack of new hypotheses about their etiology, a novel hypothesis is here proposed. It consists of assuming that the effects of the drugs most commonly used by the elderly, such as antihypertensive, hypoglycemic, and hypocholesterolemic, could have a negative impact on neuronal survival.

More than 600 different neurological diseases affect the human population. Some of these are genetic and can emerge even before birth, and some are caused by defects, infections, trauma, degeneration, inflammation, and cancer. However, they all share disabilities caused by damage to the nervous system. In the last decades, the burden of almost all neurological disorders has increased in terms of absolute incidence, prevalence, and mortality, largely due to the population’s growth and aging. This represents a dangerous trend and should become our priority for the future. But what new goals are we going to set and reach now, and how will we exploit thought-provoking technological skills for making these goals feasible? Machine learning can be at the root of the problem. Indeed, most recently, there has been a push towards medical data analysis by machine learning, and a great improvement in the training capabilities particularly of artificial deep neural networks (DNNs) inspired by the biological neural networks characterizing the human brain. This has generated competitive results for applications such as biomolecular target and protein structure prediction, structure-based rational drug design, and repurposing, all exerting a major impact on neuroscience and human well-being. By approaching early risks for diseases, non-invasive diagnosis, personalized treatment assessment, drug discovery, and automated science, the machine learning arena has thus the potential of becoming the new frontier for empowering neuroscience research and clinical practice in the years ahead.