Efficacy of invasive and non-invasive methods for the treatment of Parkinson's disease: Nanodelivery and enriched environment.

Parkinson's disease (PD) is the second most common neurodegenerative disorder characterised by the loss of dopaminergic neurons in the substantia nigra pars compacta and the subsequent motor disability. The most frequently used treatments in clinics, such as L-DOPA, restore dopaminergic neurotransmission in the brain. However, these treatments are only symptomatic, have temporary efficacy, and produce side effects. Part of the side effects are related to the route of administration as the consumption of oral tablets leads to unspecific pulsatile activation of dopaminergic receptors. For this reason, it is necessary to not only find alternative treatments, but also to develop new administration systems with better security profiles. Nanoparticle delivery systems are new administration forms designed to reach the pharmacological target in a highly specific way, leading to better drug bioavailability, efficacy and safety. Some of these delivery systems have shown promising results in animal models of PD not only when dopaminergic drugs are administered, but even more when neurotrophic factors are released. These latter compounds promote maturation and survival of dopaminergic neurons and can be exogenously administered in the form of pharmacological therapy or endogenously generated by non-pharmacological methods. In this sense, experimental exposure to enriched environments, a non-invasive strategy based on the combination of social and inanimate stimuli, enhances the production of neurotrophic factors and produces a neuroprotective effect in parkinsonian animals. In this review, we will discuss new nanodelivery systems in PD with a special focus on therapies that increase the release of neurotrophic factors.

Sexual differences in locus coeruleus neurons and related behavior in C57BL/6J mice.

BACKGROUND: In addition to social and cultural factors, sex differences in the central nervous system have a critical influence on behavior, although the neurobiology underlying these differences remains unclear. Interestingly, the Locus Coeruleus (LC), a noradrenergic nucleus that exhibits sexual dimorphism, integrates signals that are related to diverse activities, including emotions, cognition and pain. Therefore, we set-out to evaluate sex differences in behaviors related to LC nucleus, and subsequently, to assess the sex differences in LC morphology and function. METHODS: Female and male C57BL/6J mice were studied to explore the role of the LC in anxiety, depressive-like behavior, well-being, pain, and learning and memory. We also explored the number of noradrenergic LC cells, their somatodendritic volume, as well as the electrophysiological properties of LC neurons in each sex. RESULTS: While both male and female mice displayed similar depressive-like behavior, female mice exhibited more anxiety-related behaviors. Interestingly, females outperformed males in memory tasks that involved distinguishing objects with small differences and they also showed greater thermal pain sensitivity. Immunohistological analysis revealed that females had fewer noradrenergic cells yet they showed a larger dendritic volume than males. Patch clamp electrophysiology studies demonstrated that LC neurons in female mice had a lower capacitance and that they were more excitable than male LC neurons, albeit with similar action potential properties. CONCLUSIONS: Overall, this study provides new insights into the sex differences related to LC nucleus and associated behaviors, which may explain the heightened emotional arousal response observed in females.

Exploring sex differences in the brain is important to understand the impact of such differences in pathological conditions characterized by gender bias, as well as their therapeutic implications. In this manuscript, we examined sex differences in the mouse locus coeruleus (LC) and how this might affect related behaviours. The LC is a sexually dimorphic nucleus that integrates signals associated with attention, anxiety, stress, arousal, pain, memory and learning. Our findings reveal that female mice exhibit more intense anxiety-related behaviors but that they perform better than males in recognizing small differences between objects. Additionally, we found pronounced sex differences in the LC, which contained fewer noradrenergic cells in females, with a larger dendritic volume and displaying enhanced cell excitability. These differences in the LC, a nucleus that fulfils a pivotal role in stress and pain, could be important for understanding the higher prevalence of stress-related disorders in women, such as anxiety and depression, but also of chronic pain. Hence, it is clearly important to consider sex differences in both preclinical and clinical research studies that attempt to understand pathologies related to these phenomena.

Review of Technological Challenges in Personalised Medicine and Early Diagnosis of Neurodegenerative Disorders.

Neurodegenerative disorders are characterised by progressive neuron loss in specific brain areas. The most common are Alzheimer's disease and Parkinson's disease; in both cases, diagnosis is based on clinical tests with limited capability to discriminate between similar neurodegenerative disorders and detect the early stages of the disease. It is common that by the time a patient is diagnosed with the disease, the level of neurodegeneration is already severe. Thus, it is critical to find new diagnostic methods that allow earlier and more accurate disease detection. This study reviews the methods available for the clinical diagnosis of neurodegenerative diseases and potentially interesting new technologies. Neuroimaging techniques are the most widely used in clinical practice, and new techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have significantly improved the diagnosis quality. Identifying biomarkers in peripheral samples such as blood or cerebrospinal fluid is a major focus of the current research on neurodegenerative diseases. The discovery of good markers could allow preventive screening to identify early or asymptomatic stages of the neurodegenerative process. These methods, in combination with artificial intelligence, could contribute to the generation of predictive models that will help clinicians in the early diagnosis, stratification, and prognostic assessment of patients, leading to improvements in patient treatment and quality of life.