The Latest Articles on Innovative Treatments for Neurodegenerative Diseases
Our staff editors continue to share exciting, interesting, and thought-provoking reading material in the recommended articles series.
This week, we would like to share several latest articles on innovative treatments for neurodegenerative diseases.
Title: The t-N-methyl-d-aspartate receptor: Making the case for d-Serine to be considered its inverse co-agonist
Authors: Stephen Beesley, Sanjay S. Kumar
Type: Review
Abstract:
The N-methyl-d-aspartate receptor (NMDAR) is an enigmatic macromolecule that has garnered a good deal of attention on account of its involvement in the cellular processes that underlie learning and memory, following its discovery in the mid twentieth century (Baudry and Davis, 1991). Yet, despite advances in knowledge about its function, there remains much more to be uncovered regarding the receptor's biophysical properties, subunit composition, and role in CNS physiology and pathophysiology. The motivation for this review stems from the need for synthesizing new information gathered about these receptors that sheds light on their role in synaptic plasticity and their dichotomous relationship with the amino acid d-serine through which they influence the pathogenesis of neurodegenerative diseases like temporal lobe epilepsy (TLE), the most common type of adult epilepsies (Beesley et al., 2020a). This review will outline pertinent ideas relating structure and function of t-NMDARs (GluN3 subunit-containing triheteromeric NMDARs) for which d-serine might serve as an inverse co-agonist. We will explore how tracing d-serine's origins blends glutamate-receptor biology with glial biology to help provide fresh perspectives on how neurodegeneration might interlink with neuroinflammation to initiate and perpetuate the disease state. Taken together, we envisage the review to deepen our understanding of endogenous d-serine's new role in the brain while also recognizing its therapeutic potential in the treatment of TLE that is oftentimes refractory to medications.
Access this article: https://doi.org/10.1016/j.neuropharm.2023.109654
Title: AD-BERT: Using Pre-trained Language Model to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease
Authors: Chengsheng Mao, Jie Xu, Luke Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer Pacheco, Borna Bonakdarpour, Robert Vassar, Li Shen, Guoqian Jiang, Fei Wang, Jyotishman Pathak, Yuan Luo
Type: Research Article
Abstract:
Objective:
We develop a deep learning framework based on the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model using unstructured clinical notes from electronic health records (EHRs) to predict the risk of disease progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD).
Methods:
We identified 3657 patients diagnosed with MCI together with their progress notes from Northwestern Medicine Enterprise Data Warehouse (NMEDW) between 2000-2020. The progress notes no later than the first MCI diagnosis were used for the prediction. We first preprocessed the notes by deidentification, cleaning and splitting into sections, and then pre-trained a BERT model for AD (named AD-BERT) based on the publicly available Bio+Clinical BERT on the preprocessed notes. All sections of a patient were embedded into a vector representation by AD-BERT and then combined by global MaxPooling and a fully connected network to compute the probability of MCI-to-AD progression. For validation, we conducted a similar set of experiments on 2563 MCI patients identified at Weill Cornell Medicine (WCM) during the same timeframe.
Results:
Compared with the 7 baseline models, the AD-BERT model achieved the best performance on both datasets, with Area Under receiver operating characteristic Curve (AUC) of 0.849 and F1 score of 0.440 on NMEDW dataset and AUC of 0.883 and F1 score of 0.680 on WCM dataset.
Conclusion:
The use of EHRs for AD-related research is promising, and AD-BERT shows superior predictive performance to other state-of-the-art models for MCI-to-AD progression prediction. Our study demonstrates the utility of pre-trained language models and clinical notes in predicting MCI-to-AD progression, which could have important implications for improving early detection and intervention for AD.
Access this article: https://doi.org/10.1016/j.jbi.2023.104442
Title: Social robots in care homes in French-speaking Switzerland: A qualitative and reflective study
Authors: S. Perruchoud, N. Banwell, Ralf R. Jox, N. Eggert
Type: Research Article
Summary:
Background:
The number of elderly people with dementia in nursing homes is increasing in French-speaking Switzerland. This study investigates the use of social robots to improve and/or maintain the quality of life of these subjects, analyzed from the perspective of beneficence.
Methodology:
Semi-structured face-to-face interviews were conducted in a selected number of care homes using social robots with their residents in French-speaking Switzerland. The impact of this use was analyzed at anthropological and ethical levels by developing a reflexive analysis around two central themes: truth and beneficence.
Results:
The reflexive analysis illustrated the importance of several themes in the use of social robots in institutions, including the: (1) fears and hesitations surrounding the use of social robots in care homes; (2) role of interdisciplinarity and training of the nursing staff in this use; (3) necessity of a continuous evaluation guiding the use; and (4) importance of values and attitudes. In particular, this study highlighted the importance of showing at what levels this use is beneficial and identifying the “fuzzy” uncertainties that need to be studied in depth in order to make this practice increasingly ethical.
Conclusions:
This exploratory study shows that using social robots (in particular in animal form) in care homes, is perceived by the users (health care workers and animators of the visited care homes) as having a generally positive impact on the residents, particularly for those suffering from dementia. These positive impacts occur at the level of bodily experience, as well as the maintenance, or even improvement, of personal capacities. At the same time, this use, when well framed, seems beneficial both for the residents the care team involved, who progressively notice the beneficial effects through the daily care relationship.
Access this article: https://doi.org/10.1016/j.jemep.2023.100918
Title: An update on stem cell and stem cell-derived extracellular vesicle-based therapy in the management of Alzheimer’s disease
Authors: Madhan Jeyaraman, Ramya Lakshmi Rajendran, Sathish Muthu, Naveen Jeyaraman, Shilpa Sharma, Saurabh Kumar Jha, Purushothaman Muthukanagaraj, Chae Moon Hong, Lucas Furtado da Fonseca, José Fábio Santos Duarte Lana, Byeong-Cheol Ahn, Prakash Gangadaran
Type: Review
Abstract:
Globally, neurological diseases pose a major burden to healthcare professionals in terms of the management and prevention of the disorder. Among neurological diseases, Alzheimer’s disease (AD) accounts for 50%–70% of dementia and is the fifth leading cause of mortality worldwide. AD is a progressive, degenerative neurological disease, with the loss of neurons and synapses in the cerebral cortex and subcortical regions. The management of AD remains a debate among physicians as no standard and specific “disease-modifying” modality is available. The concept of ‘Regenerative Medicine’ is aimed at regenerating the degenerated neural tissues to reverse the pathology in AD. Genetically modified engineered stem cells modify the course of AD after transplantation into the brain. Extracellular vesicles (EVs) are an emerging new approach in cell communication that involves the transfer of cellular materials from parental cells to recipient cells, resulting in changes at the molecular and signaling levels in the recipient cells. EVs are a type of vesicle that can be transported between cells. Many have proposed that EVs produced from mesenchymal stem cells (MSCs) may have therapeutic promise in the treatment of AD. The biology of AD, as well as the potential applications of stem cells and their derived EVs-based therapy, were explored in this paper.
Access this article: https://doi.org/10.1016/j.heliyon.2023.e17808
Title: Experimental pharmacology: Targeting metabolic pathways
Authors: Vincenzo Leuzzi, Serena Galosi
Type: Book chapter
Abstract:
Since the discovery of the treatment for Wilson disease a growing number of treatable inherited dystonias have been identified and their search and treatment have progressively been implemented in the clinics of patients with dystonia. While waiting for gene therapy to be more widely and adequately translated into the clinical setting, the efforts to divert the natural course of dystonia reside in unveiling its pathogenesis. Specific metabolic treatments can rewrite the natural history of the disease by preventing neurotoxic metabolite accumulation or interfering with the cell accumulation of damaging metabolites, restoring energetic cell fuel, supplementing defective metabolites, and supplementing the defective enzyme. A metabolic derangement of cell homeostasis is part of the progression of many non-metabolic genetic lesions and could be the target for possible metabolic approaches. In this chapter, we provided an update on treatment strategies for treatable inherited dystonias and an overview of genetic dystonias with new experimental therapeutic approaches available or close to clinical translation.
Access this article: https://doi.org/10.1016/bs.irn.2023.05.005
