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Antioxidants (Basel, Switzerland) Jun 2024With neurodegenerative disorders being on the rise, a great deal of research from multiple fields is being conducted in order to further knowledge and propose novel... (Review)
Review
With neurodegenerative disorders being on the rise, a great deal of research from multiple fields is being conducted in order to further knowledge and propose novel therapeutic interventions. Among these investigations, research on the role of antioxidants in contrasting cognitive decline is putting forward interesting and promising results. In this review, we aim to collect evidence that focused on the role of a variety of antioxidants and antioxidant-rich foods in improving or stabilizing cognitive functions, memory, and Alzheimer's disease, the most common neurodegenerative disorder. Specifically, we considered evidence collected on humans, either through longitudinal studies or randomized, placebo-controlled ones, which evaluated cognitive performance, memory abilities, or the progression level of neurodegeneration. Overall, despite a great deal of variety between study protocols, cohorts of participants involved, neuropsychological tests used, and investigated antioxidants, there is a solid trend that suggests that the properties of antioxidants may be helpful in hampering cognitive decline in older people. Thus, the help of future research that will further elucidate the role of antioxidants in neuroprotection will lead to the development of novel interventions that will take into account such findings to provide a more global approach to treating neurodegenerative disorders.
PubMed: 38929140
DOI: 10.3390/antiox13060701 -
Diagnostics (Basel, Switzerland) Jun 2024Alzheimer's disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through... (Review)
Review
Alzheimer's disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through three stages: early stage, mild cognitive impairment (MCI) (middle stage), and dementia. Early diagnosis of Alzheimer's disease is crucial and can improve survival rates among patients. Traditional methods for diagnosing AD through regular checkups and manual examinations are challenging. Advances in computer-aided diagnosis systems (CADs) have led to the development of various artificial intelligence and deep learning-based methods for rapid AD detection. This survey aims to explore the different modalities, feature extraction methods, datasets, machine learning techniques, and validation methods used in AD detection. We reviewed 116 relevant papers from repositories including Elsevier (45), IEEE (25), Springer (19), Wiley (6), PLOS One (5), MDPI (3), World Scientific (3), Frontiers (3), PeerJ (2), Hindawi (2), IO Press (1), and other multiple sources (2). The review is presented in tables for ease of reference, allowing readers to quickly grasp the key findings of each study. Additionally, this review addresses the challenges in the current literature and emphasizes the importance of interpretability and explainability in understanding deep learning model predictions. The primary goal is to assess existing techniques for AD identification and highlight obstacles to guide future research.
PubMed: 38928696
DOI: 10.3390/diagnostics14121281 -
Brain Sciences Jun 2024The present study explores comparatively the effectiveness of a cognitive (verbal short-term memory (vSTM), verbal working memory (vWM)) and of a linguistic training...
The present study explores comparatively the effectiveness of a cognitive (verbal short-term memory (vSTM), verbal working memory (vWM)) and of a linguistic training (10-week duration each) in the diffusion of gains in cognitive abilities (vSTM and vWM) of in school-aged Greek-speaking children with developmental language disorder (DLD). To this purpose, two computerized training programs i.e., a linguistic and a cognitive one, were developed and applied to three groups (A, B, and C) of children with DLD (N = 49, in total). There were three assessments with two vSTM tasks (non-word repetition and forward digit span) and a vWM task (backward digit span): pre-therapeutically (time 1), where no significant between-group differences were found, post-therapeutically I (time 2), and post-therapeutically II (time 3) and two training phases. In phase Ι, group A received meta-syntactic training, whereas group B vSTM/vWM training and group C received no training. In phase ΙΙ, a reversal of treatment was performed for groups A and B: group A received vSTM/vWM while group B meta-syntactic training. Again, group C received no training. Overall, the results indicated a significant performance improvement for the treatment groups and revealed beneficial far-transfer effects as language therapy can affect vSTM and vWM in addition to direct and near transfer effects. In addition, the intervention type order affected performance as follows: first, better performance on the vSTM task (non-word repetition) was shown when the linguistic treatment was delivered first; second, better performance on the vWM in Time 2 and Time 3 was shown by group B, for which the cognitive treatment was delivered first. Concluding, not only intervention type but also intervention type order can affect performance in DLD.
PubMed: 38928580
DOI: 10.3390/brainsci14060580 -
Brain Sciences May 2024Protein kinase C (PKC) is a diverse enzyme family crucial for cell signalling in various organs. Its dysregulation is linked to numerous diseases, including cancer,... (Review)
Review
Protein kinase C (PKC) is a diverse enzyme family crucial for cell signalling in various organs. Its dysregulation is linked to numerous diseases, including cancer, cardiovascular disorders, and neurological problems. In the brain, PKC plays pivotal roles in synaptic plasticity, learning, memory, and neuronal survival. Specifically, PKC's involvement in Alzheimer's Disease (AD) pathogenesis is of significant interest. The dysregulation of PKC signalling has been linked to neurological disorders, including AD. This review elucidates PKC's pivotal role in neurological health, particularly its implications in AD pathogenesis and chronic alcohol addiction. AD, characterised by neurodegeneration, implicates PKC dysregulation in synaptic dysfunction and cognitive decline. Conversely, chronic alcohol consumption elicits neural adaptations intertwined with PKC signalling, exacerbating addictive behaviours. By unravelling PKC's involvement in these afflictions, potential therapeutic avenues emerge, offering promise for ameliorating their debilitating effects. This review navigates the complex interplay between PKC, AD pathology, and alcohol addiction, illuminating pathways for future neurotherapeutic interventions.
PubMed: 38928554
DOI: 10.3390/brainsci14060554 -
Brain Sciences May 2024R4Alz is utilized for the early detection of minor neurocognitive disorders. It was designed to assess three main dimensions of cognitive-control abilities:...
UNLABELLED
R4Alz is utilized for the early detection of minor neurocognitive disorders. It was designed to assess three main dimensions of cognitive-control abilities: working-memory capacity, attentional control, and executive functioning.
OBJECTIVES
To reveal the cognitive-control dimensions that can differentiate between adults and older adults with healthy cognition, people with subjective cognitive impairment, and people diagnosed with mild cognitive impairment by examining the factorial structure of the R4Alz tool.
METHODS
The study comprised 404 participants: (a) healthy adults (n = 192), (b) healthy older adults (n = 29), (c) people with SCI (n = 74), and (d) people diagnosed with MCI (n = 109). The R4Alz battery was administered to all participants, including tests that assess short-term memory storage, information processing, information updating in working memory, and selective, sustained and divided attention), task/rule-switching, inhibitory control, and cognitive flexibility.
RESULTS
A two-factorial structural model was confirmed for R4Alz, with the first factor representing "fluid intelligence (FI)" and the second factor reflecting "executive functions (EF)". Both FI and EFs discriminate among all groups.
CONCLUSIONS
The R4Alz battery presents sound construct validity, evaluating abilities in FI and EF. Both abilities can differentiate very early cognitive impairment (SCI) from healthy cognitive aging and MCI.
PubMed: 38928548
DOI: 10.3390/brainsci14060548 -
Brain Sciences May 2024Over the past twenty years, scientific research on body representations has grown significantly, with Body Memory (BM) emerging as a prominent area of interest in... (Review)
Review
Over the past twenty years, scientific research on body representations has grown significantly, with Body Memory (BM) emerging as a prominent area of interest in neurorehabilitation. Compared to other body representations, BM stands out as one of the most obscure due to the multifaceted nature of the concept of "memory" itself, which includes various aspects (such as implicit vs. explicit, conscious vs. unconscious). The concept of body memory originates from the field of phenomenology and has been developed by research groups studying embodied cognition. In this narrative review, we aim to present compelling evidence from recent studies that explore various definitions and explanatory models of BM. Additionally, we will provide a comprehensive overview of the empirical settings used to examine BM. The results can be categorized into two main areas: (i) how the body influences our memories, and (ii) how memories, in their broadest sense, could generate and/or influence metarepresentations-the ability to reflect on or make inferences about one's own cognitive representations or those of others. We present studies that emphasize the significance of BM in experimental settings involving patients with neurological and psychiatric disorders, ultimately analyzing these findings from an ontogenic perspective.
PubMed: 38928542
DOI: 10.3390/brainsci14060542 -
International Journal of Molecular... Jun 2024Posttraumatic stress disorder (PTSD) is a debilitating psychosomatic condition characterized by impairment of brain fear circuits and persistence of exceptionally strong...
Posttraumatic stress disorder (PTSD) is a debilitating psychosomatic condition characterized by impairment of brain fear circuits and persistence of exceptionally strong associative memories resistant to extinction. In this study, we investigated the neural and behavioral consequences of inhibiting protein synthesis, a process known to suppress the formation of conventional aversive memories, in an established PTSD animal model based on contextual fear conditioning in mice. Control animals were subjected to the conventional fear conditioning task. Utilizing c-Fos neural activity mapping, we found that the retrieval of PTSD and normal aversive memories produced activation of an overlapping set of brain structures. However, several specific areas, such as the infralimbic cortex and the paraventricular thalamic nucleus, showed an increase in the PTSD group compared to the normal aversive memory group. Administration of protein synthesis inhibitor before PTSD induction disrupted the formation of traumatic memories, resulting in behavior that matched the behavior of mice with usual aversive memory. Concomitant with this behavioral shift was a normalization of brain c-Fos activation pattern matching the one observed in usual fear memory. Our findings demonstrate that inhibiting protein synthesis during traumatic experiences significantly impairs the development of PTSD in a mouse model. These data provide insights into the neural underpinnings of protein synthesis-dependent traumatic memory formation and open prospects for the development of new therapeutic strategies for PTSD prevention.
Topics: Animals; Stress Disorders, Post-Traumatic; Fear; Proto-Oncogene Proteins c-fos; Mice; Disease Models, Animal; Male; Memory; Protein Synthesis Inhibitors; Mice, Inbred C57BL; Brain; Protein Biosynthesis
PubMed: 38928250
DOI: 10.3390/ijms25126544 -
International Journal of Molecular... Jun 2024Glutamate is the main excitatory neurotransmitter in the brain wherein it controls cognitive functional domains and mood. Indeed, brain areas involved in memory... (Review)
Review
Glutamate is the main excitatory neurotransmitter in the brain wherein it controls cognitive functional domains and mood. Indeed, brain areas involved in memory formation and consolidation as well as in fear and emotional processing, such as the hippocampus, prefrontal cortex, and amygdala, are predominantly glutamatergic. To ensure the physiological activity of the brain, glutamatergic transmission is finely tuned at synaptic sites. Disruption of the mechanisms responsible for glutamate homeostasis may result in the accumulation of excessive glutamate levels, which in turn leads to increased calcium levels, mitochondrial abnormalities, oxidative stress, and eventually cell atrophy and death. This condition is known as glutamate-induced excitotoxicity and is considered as a pathogenic mechanism in several diseases of the central nervous system, including neurodevelopmental, substance abuse, and psychiatric disorders. On the other hand, these disorders share neuroplasticity impairments in glutamatergic brain areas, which are accompanied by structural remodeling of glutamatergic neurons. In the current narrative review, we will summarize the role of glutamate-induced excitotoxicity in both the pathophysiology and therapeutic interventions of neurodevelopmental and adult mental diseases with a focus on autism spectrum disorders, substance abuse, and psychiatric disorders. Indeed, glutamatergic drugs are under preclinical and clinical development for the treatment of different mental diseases that share glutamatergic neuroplasticity dysfunctions. Although clinical evidence is still limited and more studies are required, the regulation of glutamate homeostasis is attracting attention as a potential crucial target for the control of brain diseases.
Topics: Humans; Glutamic Acid; Mental Disorders; Animals; Neurodevelopmental Disorders; Neuronal Plasticity; Brain; Adult; Substance-Related Disorders; Autism Spectrum Disorder
PubMed: 38928227
DOI: 10.3390/ijms25126521 -
Bioengineering (Basel, Switzerland) Jun 2024Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early...
Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early diagnosis and patient monitoring (traditionally involving lung auscultation) are essential for the effective management of respiratory diseases. However, the interpretation of lung sounds is a subjective and labor-intensive process that demands considerable medical expertise, and there is a good chance of misclassification. To address this problem, we propose a hybrid deep learning technique that incorporates signal processing techniques. Parallel transformation is applied to adventitious respiratory sounds, transforming lung sound signals into two distinct time-frequency scalograms: the continuous wavelet transform and the mel spectrogram. Furthermore, parallel convolutional autoencoders are employed to extract features from scalograms, and the resulting latent space features are fused into a hybrid feature pool. Finally, leveraging a long short-term memory model, a feature from the latent space is used as input for classifying various types of respiratory diseases. Our work is evaluated using the ICBHI-2017 lung sound dataset. The experimental findings indicate that our proposed method achieves promising predictive performance, with average values for accuracy, sensitivity, specificity, and F1-score of 94.16%, 89.56%, 99.10%, and 89.56%, respectively, for eight-class respiratory diseases; 79.61%, 78.55%, 92.49%, and 78.67%, respectively, for four-class diseases; and 85.61%, 83.44%, 83.44%, and 84.21%, respectively, for binary-class (normal vs. abnormal) lung sounds.
PubMed: 38927822
DOI: 10.3390/bioengineering11060586 -
Biomedicines May 2024Alzheimer's disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and...
Alzheimer's disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and mortality rates among older adults. However, the exact pathophysiological mechanism of AD remains unknown, and effective treatment options for AD are still lacking. Human induced pluripotent stem cells (iPSC) are emerging as promising platforms for disease research, offering the ability to model the genetic mutations associated with various conditions. Patient-derived iPSCs are useful for modeling neurodegenerative and neurodevelopmental disorders. In this study, we generated AD iPSCs from peripheral blood mononuclear cells obtained from a 65-year-old patient with AD carrying the E682K mutation in the gene encoding the amyloid precursor protein. Cerebral organoids derived from AD iPSCs recapitulated the AD phenotype, exhibiting significantly increased levels of tau protein. Our analysis revealed that an iPSC disease model of AD is a valuable assessment tool for pathophysiological research and drug screening.
PubMed: 38927400
DOI: 10.3390/biomedicines12061193