Nimodipine is a 1,4-dihydropyridine-derivative Ca(2+)-channel blocker developed approximately 30 years ago. It is highly lipophilic, crosses the blood-brain barrier, and reaches brain and cerebrospinal fluid. Early treatment with nimodipine reduces the severity of neurological deficits resulting from vasospasm in subarachnoid haemorrhage (SAH) patients. In SAH, nimodipine reduced spasm-related deficits of all severities, but no spasm-unrelated deficits. This paper has reviewed preclinical studies on the influence of nimodipine in various animal models of cerebral ischemia, with particular attention toward investigations published in the last 10 years. These studies further support the main indication of nimodipine, by clarifying some mechanisms of the anti-ischemic activity of the compound. Papers reporting a possible role of nimodipine in epileptogenesis were also examined. Clinical studies on nimodipine were grouped into subarachnoid hemorrhage, acute ischemic stroke, cerebral ischemia without stroke, dementia disorders, and migraine. Clinical investigations have shown that the drug improves neurological outcome by reducing the incidence and severity of ischemic deficits in patients with SAH from ruptured intracranial berry aneurysms regardless of their post-ictus neurological condition. No relevant effects of treatment with nimodipine were reported for acute ischemic stroke, cerebral ischemia without stroke, and migraine, except than for cluster headache. The less pronounced cardiovascular effects of nimodipine compared to other dihydropyridine-type Ca(2+)-channel blockers probably accounts for its use out of label for treating patients affected by chronic cerebral ischemia and vascular cognitive impairment. However, the blood pressure-lowering effects of nimodipine should not be minimized, as clinical studies have documented lowering blood pressure in small groups of patients, including cases of withdrawn due to pronounced hypotension induced by nimodipine administration. In the area of vascular cognitive impairment, short-term benefits of nimodipine do not justify its use as a long-term anti-dementia drug, and benefits obtained in elderly patients affected by subcortical vascular dementia require to be confirmed by other groups and in larger scale trials. In conclusion, nimodipine is a safe drug with an important place in pharmacotherapy and with the main documentation for reduction in the severity of neurological deficits resulting from vasospasm in SAH patients.

Adult-onset dementia disorders represent a challenge for modern medicine. Alzheimer’s disease (AD) represents the most diffused form of adult-onset dementias. For half a century, the diagnosis of AD was based on clinical and exclusion criteria, with an accuracy of 85%, which did not allow for a definitive diagnosis, which could only be confirmed by post-mortem evaluation. Machine learning research applied to Magnetic Resonance Imaging (MRI) techniques can contribute to a faster diagnosis of AD and may contribute to predicting the evolution of the disease. It was also possible to predict individual dementia of older adults with AD screening data and ML classifiers. To predict the AD subject status, the MRI demographic information and pre-existing conditions of the patient can help to enhance the classifier performance. In this work, we proposed a framework based on supervised learning classifiers in the dementia subject categorization as either AD or non-AD based on longitudinal brain MRI features. Six different supervised classifiers are incorporated for the classification of AD subjects and results mentioned that the gradient boosting algorithm outperforms other models with 97.58% of accuracy.

Increasing evidence suggests the utility of magnetic resonance imaging (MRI) as an important technique for the diagnosis of Alzheimer’s disease (AD) and for predicting the onset of this neurodegenerative disorder. In this study, we present a sophisticated machine learning (ML) model of great accuracy to diagnose the early stages of AD. A total of 373 MRI tests belonging to 150 subjects (age ≥ 60) were examined and analyzed in parallel with fourteen distinct features related to standard AD diagnosis. Four ML models, such as naive Bayes (NB), artificial neural networks (ANN), K-nearest neighbor (KNN), and support-vector machines (SVM), and the receiver operating characteristic (ROC) curve metric were used to validate the model performance. Each model evaluation was done in three independent experiments. In the first experiment, a manual feature selection was used for model training, and ANN generated the highest accuracy in terms of ROC (0.812). In the second experiment, automatic feature selection was conducted by wrapping methods, and the NB achieved the highest ROC of 0.942. The last experiment consisted of an ensemble or hybrid modeling developed to combine the four models. This approach resulted in an improved accuracy ROC of 0.991. We conclude that the involvement of ensemble modeling, coupled with selective features, can predict with better accuracy the development of AD at an early stage.

Cholinergic precursors have represented the first approach to counter cognitive impairment occurring in adultonset dementia disorders. These compounds were early leaved because their clinical efficacy was not clearly demonstrated. This is probably not true for some choline-containing phospholipids including choline alphoscerate. Choline alphoscerate increases the release of acetylcholine in rat hippocampus, facilitates learning and memory in experimental animals, improves brain transduction mechanisms and decreases age-dependent structural changes occurring in rat brain areas involved in learning and memory. The compound exerts neuroprotective effects in models of altered cholinergic neurotransmission and of brain vascular injury. In clinical studies choline alphoscerate improved memory and attention impairment, as well as affective and somatic symptoms in dementia disorders. An ongoing trial indicates that association between the acetylcholinesterase inhibitor donepezil and choline alphoscerate is accompanied by an improvement in several cognitive tests superior to that induced by donepezil alone. It is suggested that this association may represent a therapeutic option to prolong beneficial effects of cholinergic therapies in Alzheimer’s disease patients with concomitant ischemic cerebrovascular disorders. In summary, choline alphoscerate has significant effects on cognitive function with a good safety profile and tolerability. Although limited both in terms of size of the samples investigated and of the length of treatment, preclinical and clinical results presented suggest that cognitive enhancing capabilities of choline alphoscerate merit of being further investigated in appropriate trials.