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Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution...
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Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Neurobiology and Clinical Neuroscience".

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 8252

Special Issue Editors

Dr. Masaru Tanaka

E-Mail Website
Guest Editor
Danube Neuroscience Research Laboratory, HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Tisza Lajos krt. 113, H-6725 Szeged, Hungary
Interests: depression; anxiety; dementia pain; and their comorbidities nature; and translational research in neurological diseases and psychiatric disorders
Special Issues, Collections and Topics in MDPI journals
Dr. Simone Battaglia

E-Mail Website1 Website2
Guest Editor
1. Department of Psychology, University of Turin, Turin, Italy
2. Center for Studies and Research in Cognitive Neuroscience, Department of Psychology, University of Bologna, Bologna, Italy
Interests: NIBS techniques; TMS; skin conductance; heart rate variability; fear conditioning; fear learning; learning; neuropsychology; prefrontal cortex; amygdala; hippocampus; anxiety; depression; working memory; PTSD; skin conductance responses; psychophysiology; error-related negativity; EEG; tDCS; Alzheimer’s disease; PIT; stress-related disorders; Parkinson’s disease; resilience; memory; neurologic patients; cognitive decisions; fMRI; translational and molecular psychiatry
Special Issues, Collections and Topics in MDPI journals
Dr. Donato Liloia

E-Mail Website
Guest Editor
Department of Psychology, University of Turin, Turin, Italy
Interests: magnetic resonance imaging; human brain mapping; meta-research; connectomics; brain connectivity; computational neuroscience; Bayesian statistics; fMRI; meta-analysis; clinical trials; DTI; default mode network; Alzheimer’s disease; biological psychiatry; autism; cerebellum; translational neuroimaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurodegenerative diseases are a group of disorders that affect the structure and function of the central nervous system, leading to the progressive loss of cognitive, motor, and sensory abilities. They include Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and many others. Neurodegenerative diseases pose a major challenge for public health as they affect millions of people worldwide and have no cure. Moreover, they are associated with a high burden of disability, morbidity, mortality, and socioeconomic costs.

In recent years, significant advances have been made in the understanding of the pathophysiology, epidemiology, and genetics of neurodegenerative diseases, as well as in the development of novel diagnostic tools, therapeutic interventions, and rehabilitation strategies. Non-invasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have shown potential to improve both motor and nonmotor symptoms in patients with neurodegenerative diseases like Alzheimer’s and Parkinson’s. These techniques are of particular interest for the treatment of cognitive impairment in Alzheimer’s disease and axial disturbances in Parkinson’s disease, where conventional pharmacological therapies have shown limited effects. Recent evidence suggests that NIBS may have a neuroprotective effect, potentially slowing disease progression and modulating the aggregation state of pathological proteins. However, many gaps and challenges remain in the field, such as the identification of reliable biomarkers, the elucidation of the environmental and lifestyle factors that modulate disease risk and progression, the optimization of clinical trials and drug delivery systems, and improvements in the quality of life and care of patients and caregivers. Moreover, the potential of NIBS to influence disease progression over time remains poorly understood, along with ongoing investigations into the development of standardized stimulation protocols for the precise targeting of deep brain regions.

This Topical Collection aims to showcase the latest research and innovations in the field of neurodegenerative diseases, covering a wide range of topics, such as the following:

  • Risk factors, such as genetic and environmental, that influence the onset and course of neurodegenerative diseases;
  • Prodromal symptoms and early diagnosis, using advanced imaging techniques, biomarkers, and digital technologies;
  • Comorbidities, such as psychiatric, metabolic, and cardiovascular disorders, that affect or are affected by neurodegenerative diseases;
  • Novel therapeutic targets and treatments, such as gene therapy, stem cell therapy, immunotherapy, medicinal plants, phytocompounds, and neuroprotective agents;
  • Role of oxidative stress and inflammation as triggers of neurodegenerative conditions;
  • Quality-of-life-oriented rehabilitation, such as cognitive, physical, and psychosocial interventions that enhance the functioning and well-being of patients and caregivers;
  • Innovative translational research, such as bench-to-bed and bed-to-bench, and modeling, such as in vitro and in vivo;
  • Non-invasive brain stimulation (NIBS) as a therapeutic intervention that may offer neuroprotective effects and improve symptoms in neurodegenerative diseases.

We invite researchers and clinicians from various disciplines and backgrounds to submit their original articles and reviews to this Topical Collection contribute to the advancement of knowledge and practice in the field of neurodegenerative diseases. We hope that this Topical Collection will provide a comprehensive and up-to-date overview of the current state and future directions of the field and will stimulate further research and collaboration among the scientific community.

Dr. Masaru Tanaka
Dr. Simone Battaglia
Dr. Donato Liloia
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Alzheimer’s disease
  • frontotemporal lobar degeneration
  • Parkinson’s disease
  • aging decline
  • mild cognitive impairment
  • multiple sclerosis
  • stroke
  • acquired brain damage
  • altered cognitive processes
  • brain functional impairment
  • neurocognitive disorders
  • cognitive, behavioral, and functional disorders
  • acquired trauma
  • brain plasticity and connectivity
  • non-invasive brain stimulation
  • diagnosis and treatment
  • functional evidence of altered cognition and connectivity
  • blood-based biomarkers
  • disease heterogeneity
  • prognosis
  • protein aggregation
  • inflammation
  • oxidative stress
  • medicinal plants
  • phytocompounds

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

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Research

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14 pages, 419 KB  
Article
Young-Onset Dementia: Clinical Findings and Factors That Delay Early Diagnosis—A Retrospective Observational Study
by Juan Rivas, Mauricio Hernández, Jose Miguel Erazo, Oscar Arango, Paulina Cortés, Jennifer Lasso, Simon Giraldo and Carlos Miranda
Biomedicines 2025, 13(11), 2793; https://doi.org/10.3390/biomedicines13112793 - 17 Nov 2025
Viewed by 752
Abstract
Background/Objectives: Young-onset dementia (YOD) is a form of dementia where symptoms appear before the age of 65 years with a worse course, a poorer prognosis, and a lower survival rate than late-onset dementia. Psychiatric disorders often entail confusion, which delays their diagnosis [...] Read more.
Background/Objectives: Young-onset dementia (YOD) is a form of dementia where symptoms appear before the age of 65 years with a worse course, a poorer prognosis, and a lower survival rate than late-onset dementia. Psychiatric disorders often entail confusion, which delays their diagnosis and management. This study emphasizes the risk factors and confounders that limit opportunities to provide adequate early diagnoses of YOD. Methods: A retrospective, analytical, and observational study was based on the clinical records of 191 patients with a diagnosis of probable YOD in a medium-complexity hospital between 2009 and 2024. Demographic variables and the characteristics of the population were analyzed. An explanatory linear regression analysis was conducted to highlight the time required for diagnosis beginning at the onset of symptoms. Results: A high proportion of initial misdiagnoses were identified, and most patients were initially diagnosed with psychiatric or neurological disorders other than dementia. The main preventable risk factors were high blood pressure (HBP), type 2 diabetes mellitus (T2DM), and traumatic brain injury (TBI). HBP and the presence of irritability were associated with earlier diagnosis, whereas T2DM and the initial diagnosis of an affective or anxiety disorder were associated with a longer delay prior to diagnosis. Conclusions: Due to delays in seeking care and initial misdiagnoses as affective or anxiety disorders, T2DM is associated with a delayed final dementia diagnosis. In contrast, HBP and irritability were linked to shorter diagnostic times. These findings underscore the need for improved diagnostic capacity, adapted clinical tools, and awareness strategies to promote the early recognition of YOD. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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19 pages, 1923 KB  
Article
Interpretable Machine Learning for Risk Stratification of Hippocampal Atrophy in Alzheimer’s Disease Using CSF Erythrocyte Load and Clinical Data
by Rafail C. Christodoulou, Georgios Vamvouras, Platon S. Papageorgiou, Maria Daniela Sarquis, Vasileia Petrou, Ludwing Rivera, Celimar Morales, Gipsany Rivera, Sokratis G. Papageorgiou and Evros Vassiliou
Biomedicines 2025, 13(11), 2689; https://doi.org/10.3390/biomedicines13112689 - 31 Oct 2025
Viewed by 692
Abstract
Background/Objectives: Hippocampal atrophy indicates Alzheimer’s disease (AD) progression and guides follow-up and trial enrichment. Identifying high-risk patients is crucial for optimizing care, but accessible, interpretable machine-learning models (ML) are limited. We developed an explainable ML model using clinical data and CSF erythrocyte load [...] Read more.
Background/Objectives: Hippocampal atrophy indicates Alzheimer’s disease (AD) progression and guides follow-up and trial enrichment. Identifying high-risk patients is crucial for optimizing care, but accessible, interpretable machine-learning models (ML) are limited. We developed an explainable ML model using clinical data and CSF erythrocyte load (CTRED) to classify adults with AD as high- or low-risk based on hippocampal volume decline. Methods: Included ADNI participants with ≥2 MRIs, baseline lumbar puncture, and vital signs within 6 months of MRI (n = 26). The outcome was the Annual Percentage Change (APC) in hippocampal volume, classified as low or high risk. Predictors were standardized; models included SVM, logistic regression, and Ridge Classifier, tuned and tested on a set (n = 6). Thresholds were based on out-of-fold predictions under a 10–90% positive rate. Explainability used PFI and SHAP for per-patient contributions. Results: All models gave identical classifications, but discrimination varied: Ridge AUC = 1.00, logistic = 0.889, and SVM = 0.667. PFI highlighted MAPres and sex as main signals; CTRED contributed, and age had a minor impact. Conclusions: The explainable ML model with clinical data and CTRED can stratify AD patients by hippocampal atrophy risk, aiding follow-up and vascular assessment planning rather than treatment decisions. Validation in larger cohorts is needed. This is the first ML study to use CSF erythrocyte load to predict hippocampal atrophy risk in AD. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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17 pages, 1204 KB  
Article
Preliminary Evidence of Biological and Cognitive Efficacy of Prismatic Adaptation Combined with Cognitive Training on Patients with Mild Cognitive Impairment
by Laura Danesin, Giorgia D’Este, Rita Barresi, Elena Piazzalunga, Agnese Di Garbo, Andreina Giustiniani, Carlo Semenza, Gabriella Bottini, Massimiliano Oliveri and Francesca Burgio
Biomedicines 2025, 13(10), 2447; https://doi.org/10.3390/biomedicines13102447 - 8 Oct 2025
Viewed by 868
Abstract
Background/Objectives: This study evaluated a novel rehabilitation tool that combines prismatic adaptation (PA) and cognitive training through serious games (SGs) in patients with mild cognitive impairment (MCI) due to prodromal Alzheimer’s dementia or consequent to Parkinson’s disease. While non-pharmacological interventions have been [...] Read more.
Background/Objectives: This study evaluated a novel rehabilitation tool that combines prismatic adaptation (PA) and cognitive training through serious games (SGs) in patients with mild cognitive impairment (MCI) due to prodromal Alzheimer’s dementia or consequent to Parkinson’s disease. While non-pharmacological interventions have been shown to improve cognition or delay dementia onset, their underlying neurobiological mechanisms, such as brain plasticity, remain unclear. Leveraging studies suggesting neuromodulatory effects of PA, we investigated whether the combined PA+SGs treatment could influence plasticity-related mechanisms, assessed through brain-derived neurotrophic factor (BDNF) serum levels, compared to cognitive training with only SGs and standard cognitive rehabilitation (SCR). Methods: Twenty three MCI patients were randomized into three intervention groups: PA+SGs (experimental group), SG-only (control group), and SCR (control group), completing ten treatment sessions. Patients underwent neuropsychological assessments and blood sampling pre- and post-treatment. Results: At baseline, demographic, clinical, and biological characteristics were comparable across groups. Post-treatment, though differences from control groups were not statistically significant, the PA+SGs group showed significant within-group improvements in memory, with trend-level changes also in executive function and visuospatial abilities, which, however, did not reach the significance threshold. Notably, only the PA+SGs group exhibited increased BDNF levels, which positively correlated with memory and language performance. Conclusions: Our findings suggest that combining PA with cognitive training may enhance cognitive functioning in MCI patients, yielding results comparable to SCR. Furthermore, PA appears to enhance neuroplasticity mechanisms that may support the behavioral improvements observed in cognitive training. Future research should validate these findings and further explore the relationship between cognitive impairment and its rehabilitation, while also considering the underlying neurobiological mechanisms. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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26 pages, 2897 KB  
Article
Acceleration-Dependent Effects of Vibrotactile Gamma Stimulation on Cognitive Recovery and Cholinergic Function in a Scopolamine-Induced Neurotoxicity Mouse Model
by Tae-Woo Kim, Hee-Jung Park, Myeong-Hyun Nam, In-Ho Lee, Zu-Yu Chen, Hee-Deok Yun and Young-Kwon Seo
Biomedicines 2025, 13(8), 2031; https://doi.org/10.3390/biomedicines13082031 - 20 Aug 2025
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Abstract
Background: Alzheimer’s disease is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. Gamma (γ) oscillations are closely linked to learning and memory, and recent interest has grown around Gamma ENtrainment Using Sensory stimulation (GENUS) as a non-invasive neuromodulation strategy. However, [...] Read more.
Background: Alzheimer’s disease is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. Gamma (γ) oscillations are closely linked to learning and memory, and recent interest has grown around Gamma ENtrainment Using Sensory stimulation (GENUS) as a non-invasive neuromodulation strategy. However, the therapeutic impact of vibrotactile gamma stimulation under varying physical parameters such as acceleration remains underexplored. Methods: Differentiated SH-SY5Y cells were treated with amyloid-β (Aβ) and exposed to vibrotactile stimulation at 2.2 or 4.0 m/s2. In vivo, male C57BL/6N mice (7 weeks old, 35 g) were administered scopolamine to induce neurotoxicity and randomly assigned to sham, scopolamine, donepezil, or vibrotactile stimulation groups (n = 10 each). Behavioral tests, biochemical assays, Western blotting, and immunohistochemistry were performed to evaluate cognitive function, oxidative stress, cholinergic activity, synaptic plasticity, and neuroinflammation. Results: In vitro, SH-SY5Y cells exposed to amyloid-beta (Aβ) were treated with vibrotactile stimulation, resulting in enhanced neuronal marker expression at 2.2 m/s2. In vivo, mice receiving stimulation at 2.2 m/s2 showed improved cognitive performance, reduced oxidative stress, restored cholinergic function, suppressed neuroinflammation, and enhanced synaptic plasticity. Mechanistically, these effects were associated with activation of the AKT/GSK3β/β-catenin pathway. Conclusions: Our findings demonstrate that vibrotactile gamma stimulation at 2.2 m/s2 exerts greater therapeutic efficacy than higher acceleration, highlighting the importance of optimizing stimulation parameters. This work supports the potential of acceleration-tuned, non-invasive GENUS-based therapies as effective strategies for cognitive recovery in neurodegenerative conditions. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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Review

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18 pages, 1384 KB  
Review
From Lesion to Decision: AI for ARIA Detection and Predictive Imaging in Alzheimer’s Disease
by Rafail C. Christodoulou, Platon S. Papageorgiou, Maria Daniela Sarquis, Ludwing Rivera, Celimar Morales Gonzalez, Daniel Eller, Gipsany Rivera, Vasileia Petrou, Georgios Vamvouras, Evros Vassiliou, Sokratis G. Papageorgiou and Michalis F. Georgiou
Biomedicines 2025, 13(11), 2739; https://doi.org/10.3390/biomedicines13112739 - 10 Nov 2025
Viewed by 1298
Abstract
Background: Alzheimer’s disease (AD) remains the leading cause of dementia worldwide, with anti-amyloid monoclonal antibodies (MABs) marking a significant advance as the first disease-modifying therapies. Their use, however, is limited by amyloid-related imaging abnormalities (ARIA), which appear as vasogenic edema or effusion (ARIA-E) [...] Read more.
Background: Alzheimer’s disease (AD) remains the leading cause of dementia worldwide, with anti-amyloid monoclonal antibodies (MABs) marking a significant advance as the first disease-modifying therapies. Their use, however, is limited by amyloid-related imaging abnormalities (ARIA), which appear as vasogenic edema or effusion (ARIA-E) and hemosiderin-related changes (ARIA-H) on MRI. Variability in imaging protocols, subtle early findings, and the lack of standardized risk models challenge detection and management. Methods: This narrative review summarizes current artificial intelligence (AI) applications for ARIA detection and risk prediction. A comprehensive literature search across PubMed, Embase, and Scopus identified studies focusing on MRI-based AI analysis, lesion quantification, and predictive modeling. Results: The evidence is organized into six thematic domains: ARIA definitions, imaging challenges, foundations of AI in neuroimaging, detection tools, predictive frameworks, and future perspectives. Conclusions: AI offers promising avenues to standardize ARIA evaluation, improve lesion quantification, and enable individualized risk prediction. Progress will depend on multicenter datasets, shared frameworks, and prospective validation. Ultimately, AI-driven neuroimaging may transform how treatment-related complications are monitored in the era of anti-amyloid therapy. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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19 pages, 770 KB  
Review
From Qualitative to Quantitative Functional Assessment in Stroke Rehabilitation with a Focus on Ultrasound Role
by Rosita Rabbito, Eleonora Ficiarà, Lorenzo Priano, Matteo Bigoni, Caterina Guiot and Silvestro Roatta
Biomedicines 2025, 13(11), 2594; https://doi.org/10.3390/biomedicines13112594 - 23 Oct 2025
Viewed by 790
Abstract
Stroke-surviving patients may present a wide range of neurological deficits affecting both sensory and motor functions as well as the cognitive and the emotional domains, with an impact on independence on daily activities and quality of life in general. Assessment scales are essential [...] Read more.
Stroke-surviving patients may present a wide range of neurological deficits affecting both sensory and motor functions as well as the cognitive and the emotional domains, with an impact on independence on daily activities and quality of life in general. Assessment scales are essential tools for evaluating all these aspects of a patient’s condition and for monitoring their evolution in time, attempting to provide a quantitative index to complex and sometimes indirectly observable parameters. In fact, the use of these scales entails methodological and interpretative challenges that can limit their applicability and effectiveness. This narrative review explores the current state and limitations of assessment scales used in the rehabilitative evaluation of post-stroke patients. Common neurorehabilitation techniques and traditionally used assessment scales for measuring patient progress are reviewed, highlighting their main limitations. As an alternative to the observational approach, direct assessment of the effect of the ongoing rehabilitative process on the functional recovery of the damaged neurological network, based on the recording of their electric signaling or on the modification in regional cerebral blood flow, have been recently proposed. Innovative rehabilitation assessment methods based on quantitative data are reviewed, with a special focus on ultrasound-based techniques, aiming to improve accuracy and sensitivity in clinical assessment. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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Other

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30 pages, 1099 KB  
Systematic Review
Immersive Technologies Targeting Spatial Memory Decline: A Systematic Review
by Lucía Solares, Sara García-Navarra, Tania Llana, Sara Garces-Arilla and Marta Mendez
Biomedicines 2025, 13(9), 2105; https://doi.org/10.3390/biomedicines13092105 - 29 Aug 2025
Viewed by 1451
Abstract
Background/Objectives: The ability to preserve cognitive health in aging populations increasingly relies on early detection and intervention in neurodegenerative processes. Spatial memory, a fundamental cognitive ability supporting navigation, environmental awareness, and daily independence, often deteriorates in the preclinical stages of neurodegenerative diseases. [...] Read more.
Background/Objectives: The ability to preserve cognitive health in aging populations increasingly relies on early detection and intervention in neurodegenerative processes. Spatial memory, a fundamental cognitive ability supporting navigation, environmental awareness, and daily independence, often deteriorates in the preclinical stages of neurodegenerative diseases. However, conventional assessment tools frequently lack ecological validity and fail to capture the multifaceted nature of spatial cognition in real-world contexts. This systematic review aims to examine the application of immersive technologies, specifically Immersive Virtual Reality (VR) and Mixed Reality (MR), in the evaluation and rehabilitation of spatial memory. Methods: Following PRISMA guidelines, a total of 42 peer-reviewed studies were selected from SCOPUS, Web of Science, and PubMed databases. We included original, peer-reviewed studies that assessed spatial memory or cognition using VR/MR in adults aged ≥50 or clinical populations at neurodegenerative risk and reported quantitative data or diagnostic validity. A narrative synthesis was performed to examine the most employed immersive tools, assessing their benefits, limitations, and practical challenges. Results: Findings indicate substantial variability in diagnostic sensitivity, ecological validity, and user engagement across platforms. Nevertheless, the evidence supports the potential of immersive environments as effective tools for the early detection of spatial disorientation and cognitive decline, particularly in at-risk populations such as individuals with Mild Cognitive Impairment and Alzheimer’s Disease. Conclusions: Immersive and semi-immersive VR technologies represent a promising advancement in spatial memory assessment and rehabilitation, offering scalable solutions for both clinical and home-based interventions in aging populations. Full article
(This article belongs to the Special Issue Neurodegeneration No More: Cutting-Edge Technologies and Therapies in the Evolution of Neurodegenerative Disease Management—2nd Edition)
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