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Challenges and Perspectives of Neurological Disorders

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A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Systems Neuroscience".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 30207

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Dr. Woon-Man Kung

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1. Department of Exercise and Health Promotion, College of Kinesiology and Health, Chinese Culture University, Taipei, Taiwan
2. Division of Neurosurgery, Department of Surgery, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City, Taiwan
Interests: neurosurgery; neurological disorders; brain; dementia; clinical neuroscience; neuroimaging; neuroinformatics; neuroepidemiology; neuropharmacology; evidence-based medicine
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Dr. Dina Nur Anggraini Ningrum

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Public Health Department, Faculty of Medicine, Universitas Negeri Semarang (UNNES), Semarang, Indonesia
Interests: biomedical informatics; health informatics; health information system; public health; epidemiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurological disorders are increasingly recognized as one of the most prevalent disorders worldwide, with a high burden on patients, families, and society as a whole. Neurological disorders can affect the brain, spinal cord, and other nerves throughout the body. The results can be bothersome or even detrimentally devastating. There are many different etiologies per se. Neurological disorders refer not only to common neurodegenerative diseases, such as neurovascular disorders, neuro-oncological diseases, neuroinflammation, and infection, as well as traumatic brain/spinal cord injuries, but also to a category of other less common pathogeneses.

The burden of neurological disorders has increased in the past and is likely to increase in the future, due to the aging population worldwide, thus placing an increasing demand on already overstretched resources and services for patients with neurological disorders. There is an urgent need to improve the prevention and management of neurological disorders across the globe.

The detection and targeting of neuronal damage involves a spectrum of multifaceted technologies. We encourage all basic and clinical contributions pertaining to neurological disorders, without restrictions on the type of article. The findings of this topic will be useful to advance healthcare planning and resource allocation, to prevent and reduce the burden of neurological disorders.

Dr. Woon-Man Kung
Dr. Dina Nur Anggraini Ningrum
Guest Editors

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Keywords

nervous system disease
prevention and control
diagnosis and therapy
neurobiology
neuroinflammation
biomarker
neuroimaging
neuropharmacology
neurosurgery
neuroinformatics

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Published Papers (12 papers)

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Editorial

Jump to: Research, Other

3 pages, 178 KiB

Open AccessEditorial

Challenges and Perspectives of Neurological Disorders

by Dina Nur Anggraini Ningrum and Woon-Man Kung

Brain Sci. 2023, 13(4), 676; https://doi.org/10.3390/brainsci13040676 - 18 Apr 2023

Cited by 7 | Viewed by 2363

Abstract

Neurological disorders pose significant challenges to healthcare systems worldwide [...] Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

Research

Jump to: Editorial, Other

13 pages, 1931 KiB

Open AccessArticle

Based on Tau PET Radiomics Analysis for the Classification of Alzheimer’s Disease and Mild Cognitive Impairment

by Fangyang Jiao, Min Wang, Xiaoming Sun, Zizhao Ju, Jiaying Lu, Luyao Wang, Jiehui Jiang and Chuantao Zuo

Brain Sci. 2023, 13(2), 367; https://doi.org/10.3390/brainsci13020367 - 20 Feb 2023

Cited by 6 | Viewed by 2371

Abstract

Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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10 pages, 998 KiB

Open AccessArticle

Intermediate-Length GGC Repeat Expansion in NOTCH2NLC Was Identified in Chinese Patients with Amyotrophic Lateral Sclerosis

by Mengxia Wan, Ji He, Junyan Huo, Can Sun, Yu Fu and Dongsheng Fan

Brain Sci. 2023, 13(1), 85; https://doi.org/10.3390/brainsci13010085 - 1 Jan 2023

Cited by 1 | Viewed by 2163

Abstract

GGC repeat expansions in the 5’ untranslated region (5’UTR) of the Notch Homolog 2 N-terminal-like C gene (NOTCH2NLC) have been reported to be the genetic cause of neuronal intranuclear inclusion disease (NIID). However, whether they exist in other neurodegenerative disorders remains unclear. To determine whether there is a medium-length amplification of NOTCH2NLC in patients with amyotrophic lateral sclerosis (ALS), we screened 476 ALS patients and 210 healthy controls for the presence of a GGC repeat expansion in NOTCH2NLC by using repeat-primed polymerase chain reaction (RP-PCR) and fragment analysis. The repeat number in ALS patients was 16.11 ± 5.7 (range 7–46), whereas the repeat number in control subjects was 16.19 ± 3.79 (range 10–29). An intermediate-length GGC repeat expansion was observed in two ALS patients (numbers of repeats: 45, 46; normal repeat number ≤ 40) but not in the control group. The results suggested that the intermediate NOTCH2NLC GGC repeat expansion was associated with Chinese ALS patients, and further functional studies for intermediate-length variation are required to identify the mechanism. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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13 pages, 2132 KiB

Open AccessArticle

In Silico Structural Analysis Predicting the Pathogenicity of PLP1 Mutations in Multiple Sclerosis

by Antigoni Avramouli, Marios G. Krokidis, Themis P. Exarchos and Panagiotis Vlamos

Brain Sci. 2023, 13(1), 42; https://doi.org/10.3390/brainsci13010042 - 24 Dec 2022

Cited by 1 | Viewed by 2202

Abstract

The X chromosome gene PLP1 encodes myelin proteolipid protein (PLP), the most prevalent protein in the myelin sheath surrounding the central nervous system. X-linked dysmyelinating disorders such as Pelizaeus–Merzbacher disease (PMD) or spastic paraplegia type 2 (SPG2) are typically caused by point mutations in PLP1. Nevertheless, numerous case reports have shown individuals with PLP1 missense point mutations which also presented clinical symptoms and indications that were consistent with the diagnostic criteria of multiple sclerosis (MS), a disabling disease of the brain and spinal cord with no current cure. Computational structural biology methods were used to assess the impact of these mutations on the stability and flexibility of PLP structure in order to determine the role of PLP1 mutations in MS pathogenicity. The analysis showed that most of the variants can alter the functionality of the protein structure such as R137W variants which results in loss of helix and H140Y which alters the ordered protein interface. In silico genomic methods were also performed to predict the significance of these mutations associated with impairments in protein functionality and could suggest a better definition for therapeutic strategies and clinical application in MS patients. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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12 pages, 989 KiB

Open AccessArticle

Neurological Erdheim–Chester Disease Manifesting with Subacute or Progressive Cerebellar Ataxia: Novel Case Series and Review of the Literature

by Vittorio Riso, Tommaso Filippo Nicoletti, Salvatore Rossi, Maria Gabriella Vita, Perna Alessia, Daniele Di Natale and Gabriella Silvestri

Brain Sci. 2023, 13(1), 26; https://doi.org/10.3390/brainsci13010026 - 22 Dec 2022

Cited by 3 | Viewed by 2158

Abstract

Neurological involvement is relatively common in Erdheim–Chester disease (ECD), a rare clonal disorder of histiocytic myeloid precursors characterized by multisystem involvement. In ECD patients, neurological symptoms can occur either at onset or during the disease course and may lead to various degrees of neurological disability or affect patients’ life expectancy. The clinical neurological presentation of ECD often consists of cerebellar symptoms, showing either a subacute or progressive course. In this latter case, patients manifest with a slowly progressive cerebellar ataxia, variably associated with other non-specific neurological signs, infratentorial leukoencephalopathy, and cerebellar atrophy, possibly mimicking either adult-onset degenerative or immune-mediated ataxia. In such cases, diagnosis of ECD may be particularly challenging, yet some peculiar features are helpful to address it. Here, we retrospectively describe four novel ECD patients, all manifesting cerebellar symptoms at onset. In two cases, slow disease progression and associated brain MRI features simulated a degenerative cerebellar ataxia. Three patients received a definite diagnosis of histiocytosis, whereas one case lacked histology confirmation, although clinical diagnostic features were strongly suggestive. Our findings regarding existing literature data focused on neurological ECD will be also discussed to highlight those diagnostic clues helpful to address diagnosis. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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6 pages, 724 KiB

Open AccessCommunication

Perspective: Present and Future of Virtual Reality for Neurological Disorders

by Hyuk-June Moon and Sungmin Han

Brain Sci. 2022, 12(12), 1692; https://doi.org/10.3390/brainsci12121692 - 9 Dec 2022

Cited by 11 | Viewed by 2400

Abstract

Since the emergence of Virtual Reality technology, it has been adopted in the field of neurology. While Virtual Reality has contributed to various rehabilitation approaches, its potential advantages, especially in diagnosis, have not yet been fully utilized. Moreover, new tides of the Metaverse are approaching rapidly, which will again boost public and research interest and the importance of immersive Virtual Reality technology. Nevertheless, accessibility to such technology for people with neurological disorders has been critically underexplored. Through this perspective paper, we will briefly look over the current state of the technology in neurological studies and then propose future research directions, which hopefully facilitate beneficial Virtual Reality studies on a wider range of topics in neurology. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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12 pages, 1461 KiB

Open AccessArticle

In Vivo Tau Burden Is Associated with Abnormal Brain Functional Connectivity in Alzheimer’s Disease: A ¹⁸F-Florzolotau Study

by Zizhao Ju, Zhuoyuan Li, Jiaying Lu, Fangyang Jiao, Huamei Lin, Weiqi Bao, Ming Li, Ping Wu, Yihui Guan, Qianhua Zhao, Huiwei Zhang, Jiehui Jiang and Chuantao Zuo

Brain Sci. 2022, 12(10), 1355; https://doi.org/10.3390/brainsci12101355 - 6 Oct 2022

Cited by 4 | Viewed by 1964

Abstract

Purpose: ¹⁸F-Florzolotau is a novel second-generation tau radiotracer that shows higher binding affinity and selectivity and no off-target binding. The proportion loss of functional connectivity strength (PLFCS) is a new indicator for representing brain functional connectivity (FC) alteration. This study aims to estimate the relationship between the regional tau accumulation and brain FC abnormality in Alzheimer’s disease (AD) and mild cognitive impairment (MCI) patients based on Florzolotau PET and fMRI. Methods: 22 NC (normal control), 31 MCI and 42 AD patients who have already been scanned with ¹⁸F-Florzolotau PET were recruited in this study. (We calculated the PLFCS and standardized uptake value ratio (SUVR) of each node based on the Brainnetome atlas (BNA) template. The SUVR of 246 brain regions was calculated with the cerebellum as the reference region. Further functional connection strength (FCs), PLFCS and SUVR of each brain region were obtained in three groups for comparison.) For each patient, PLFCS and standardized uptake value ratio (SUVR) were calculated based on the Brainnetome atlas (BNA) template. These results, as well as functional connection strength (FCs), were then compared between different groups. Multiple permutation tests were used to determine the target nodes between NC and cognitive impairment (CI) groups (MCI and AD). The relationship between PLFCS and neuropsychological scores or cortical tau deposit was investigated via Pearson correlation analysis. Results: Higher PLFCS and FCs in AD and MCI groups were found compared to the NC group. The PLFCS of 129 brain regions were found to be different between NC and CI groups, and 8 of them were correlated with tau SUVR, including superior parietal lobule (MCI: r = 0.4360, p = 0.0260, AD: r = −0.3663, p = 0.0280), middle frontal gyrus (AD: MFG_R_7_2: r = 0.4106, p = 0.0129; MFG_R_7_5: r = 0.4239, p = 0.0100), inferior frontal gyrus (AD: IFG_R_6_2: r = 0.3589, p = 0.0316), precentral gyrus (AD: PrG_R_6_6: r = 0.3493, p = 0.0368), insular gyrus (AD: INS_R_6_3: r = 0.3496, p = 0.0366) and lateral occipital cortex (AD: LOcC _L_4_3: r = −0.3433, p = 0.0404). Noteworthily, the opposing relationship was found in the superior parietal lobule in the MCI and AD groups. Conclusions: Brain functional connectivity abnormality is correlated with tau pathology in AD and MCI. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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12 pages, 1717 KiB

Open AccessArticle

Development of a Machine Learning Model to Discriminate Mild Cognitive Impairment Subjects from Normal Controls in Community Screening

by Juanjuan Jiang, Jieming Zhang, Chenyang Li, Zhihua Yu, Zhuangzhi Yan and Jiehui Jiang

Brain Sci. 2022, 12(9), 1149; https://doi.org/10.3390/brainsci12091149 - 28 Aug 2022

Cited by 6 | Viewed by 2204

Abstract

Background: Mild cognitive impairment (MCI) is a transitional stage between normal aging and probable Alzheimer’s disease. It is of great value to screen for MCI in the community. A novel machine learning (ML) model is composed of electroencephalography (EEG), eye tracking (ET), and neuropsychological assessments. This study has been proposed to identify MCI subjects from normal controls (NC). Methods: Two cohorts were used in this study. Cohort 1 as the training and validation group, includes184 MCI patients and 152 NC subjects. Cohort 2 as an independent test group, includes 44 MCI and 48 NC individuals. EEG, ET, Neuropsychological Tests Battery (NTB), and clinical variables with age, gender, educational level, MoCA-B, and ACE-R were selected for all subjects. Receiver operating characteristic (ROC) curves were adopted to evaluate the capabilities of this tool to classify MCI from NC. The clinical model, the EEG and ET model, and the neuropsychological model were compared. Results: We found that the classification accuracy of the proposed model achieved 84.5 ± 4.43% and 88.8 ± 3.59% in Cohort 1 and Cohort 2, respectively. The area under curve (AUC) of the proposed tool achieved 0.941 (0.893–0.982) in Cohort 1 and 0.966 (0.921–0.988) in Cohort 2, respectively. Conclusions: The proposed model incorporation of EEG, ET, and neuropsychological assessments yielded excellent classification performances, suggesting its potential for future application in cognitive decline prediction. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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14 pages, 1094 KiB

Open AccessArticle

Gross Total Resection Promotes Subsequent Recovery and Further Enhancement of Impaired Natural Killer Cell Activity in Glioblastoma Patients

by Cheng-Chi Lee, Jeng-Fu You, Yu-Chi Wang, Shao-Wei Lan, Kuo-Chen Wei, Ko-Ting Chen, Yin-Cheng Huang, Tai-Wei Erich Wu and Abel Po-Hao Huang

Brain Sci. 2022, 12(9), 1144; https://doi.org/10.3390/brainsci12091144 - 27 Aug 2022

Cited by 2 | Viewed by 2412

Abstract

Glioblastoma is the most common primary malignant brain tumor, and median survival is relatively short despite aggressive standard treatment. Natural killer (NK) cell dysfunction is strongly associated with tumor recurrence and metastasis but is unclear in glioblastoma. NK activity (NKA) represents NK cell-secreted interferon-γ (IFN-γ), which modulates immunity and inhibits cancer progression. This study aimed to analyze NKA in glioblastoma patients to obtain a clearer overview of immunity surveillance. From 2020 to 2021, a total of 20 patients and six healthy controls were recruited. Peripheral blood samples were collected preoperatively and on postoperative days (POD) 3 and 30. Then, NKA was measured using the NK VUE kit. Although NKA decreased on POD3, it recovered and further significantly enhanced on POD30, with a nearly five-fold increase compared to baseline (p = 0.004). Furthermore, the percentage of CD56^brightCD16⁻ NK cells decreased significantly on POD3 (p = 0.022) and further recovered on PO30. Subgroup analysis of extent surgical resection further revealed that the recovery of impaired NKA was attributable to gross total resection (GTR) rather than subtotal resection (STR). In conclusion, NKA is significantly impaired in glioblastoma, and GTR has demonstrated superior benefit in improving the suppressed NKA and increased CD56^brightCD16⁻ NK subset in glioblastoma patients, which may be associated with subsequent patients’ prognosis. Therefore, the goal of performing GTR for glioblastoma should be achieved when possible since it appears to increase NKA cell immunity. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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14 pages, 2667 KiB

Open AccessArticle

A Novel Deep Learning Radiomics Model to Discriminate AD, MCI and NC: An Exploratory Study Based on Tau PET Scans from ADNI

by Yan Zhao, Jieming Zhang, Yue Chen and Jiehui Jiang

Brain Sci. 2022, 12(8), 1067; https://doi.org/10.3390/brainsci12081067 - 12 Aug 2022

Cited by 6 | Viewed by 2693

Abstract

Objective: We explored a novel model based on deep learning radiomics (DLR) to differentiate Alzheimer’s disease (AD) patients, mild cognitive impairment (MCI) patients and normal control (NC) subjects. This model was validated in an exploratory study using tau positron emission tomography (tau-PET) scans. Methods: In this study, we selected tau-PET scans from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI), which included a total of 211 NC, 197 MCI, and 117 AD subjects. The dataset was divided into one training/validation group and one separate external group for testing. The proposed DLR model contained the following three steps: (1) pre-training of candidate deep learning models; (2) extraction and selection of DLR features; (3) classification based on support vector machine (SVM). In the comparative experiments, we compared the DLR model with three traditional models, including the SUVR model, traditional radiomics model, and a clinical model. Ten-fold cross-validation was carried out 200 times in the experiments. Results: Compared with other models, the DLR model achieved the best classification performance, with an accuracy of 90.76% ± 2.15% in NC vs. MCI, 88.43% ± 2.32% in MCI vs. AD, and 99.92% ± 0.51% in NC vs. AD. Conclusions: Our proposed DLR model had the potential clinical value to discriminate AD, MCI and NC. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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9 pages, 1269 KiB

Open AccessArticle

Endovascular Treatment of ICAS Patients: Targeting Reperfusion Rather than Residual Stenosis

by Tingyu Yi, Alai Zhan, Yanmin Wu, Yimin Li, Xiufen Zheng, Dinglai Lin, Xiaohui Lin, Zhinan Pan, Rongcheng Chen, Mark Parsons, Wenhuo Chen and Longting Lin

Brain Sci. 2022, 12(8), 966; https://doi.org/10.3390/brainsci12080966 - 22 Jul 2022

Cited by 1 | Viewed by 2482

Abstract

Background and Purpose: Previous studies showed that acute reocclusion after endovascular therapy is related to residual stenosis. However, we observed that reperfusion status but not residual stenosis severity is related to acute reocclusion. This study aimed to assess which factor mention above is more likely to be associated with artery reocclusion after endovascular treatment. Methods: This study included 86 acute ischemic stroke patients who had middle cerebral artery (MCA) atherosclerotic occlusions and received endovascular treatment within 24 h of a stroke. The primary outcomes included intraprocedural reocclusion assessed during endovascular treatment and delayed reocclusion assessed through follow-up angiography. Results: Of the 86 patients, the intraprocedural reocclusion rate was 7.0% (6/86) and the delayed reocclusion rate was 2.3% (2/86). Regarding intraprocedural occlusion, for patients with severe residual stenosis, patients with successful thrombectomy reperfusion showed a significantly lower rate than unsuccessful thrombectomy reperfusion (0/30 vs. 6/31, p = 0.003); on the other hand, for patients with successful thrombectomy reperfusion, patients with severe residual stenosis showed no difference from those with mild to moderate residual stenosis in terms of intraprocedural occlusion (0/30 vs. 0/25, p = 1.00). In addition, after endovascular treatment, all patients achieved successful reperfusion. There was no significant difference in the delayed reocclusion rate between patients with severe residual stenosis and those with mild to moderate residual stenosis (2/25 vs. 0/61, p = 0.085). Conclusion: Reperfusion status rather than residual stenosis severity is associated with artery reocclusion after endovascular treatment. Once successful reperfusion was achieved, the reocclusion occurrence was fairly low in MCA atherosclerosis stroke patients, even with severe residual stenosis. Full article

(This article belongs to the Special Issue Challenges and Perspectives of Neurological Disorders)

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11 pages, 1090 KiB

Open AccessCase Report

Adult-Onset Neuronal Intranuclear Inclusion Disease with Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-Like (MELAS-like) Episode: A Case Report and Review of Literature

by Qian Zhou, Meiqun Tian, Huan Yang and Yue-Bei Luo

Brain Sci. 2022, 12(10), 1377; https://doi.org/10.3390/brainsci12101377 - 11 Oct 2022

Cited by 6 | Viewed by 2598

Abstract

Neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disease with highly heterogeneous manifestations. Curvilinear hyperintensity along the corticomedullary junction on diffusion-weighted images (DWI) is a vital clue for diagnosing NIID. DWI hyperintensity tends to show an anterior-to-posterior propagation pattern as the disease progresses. The rare cases of its disappearance may lead to misdiagnosis. Here, we reported a NIID patient with mitochondrial encephalomyopathy, lactic acidosis and stroke-like (MELAS-like) episode, and reversible DWI hyperintensities. A review of the literature on NIID with MELAS-like episodes was conducted. A 69-year-old woman stated to our clinics for recurrent nausea/vomiting, mixed aphasia, altered mental status, and muscle weakness for 2 weeks. Neurological examination showed impaired mental attention and reaction capacity, miosis, mixed aphasia, decreased muscle strength in limbs, and reduced tendon reflex. Blood tests were unremarkable. The serological examination was positive for antibody against dipeptidyl-peptidase-like protein 6 (DPPX) (1:32). Brain magnetic resonance imaging (MRI) revealed hyperintensities in the left temporal occipitoparietal lobe on DWI and correspondingly elevated lactate peak in the identified restricted diffusion area on magnetic resonance spectroscopy, mimicking the image of MELAS. Skin biopsy and genetic testing confirmed the diagnosis of NIID. Pulse intravenous methylprednisolone and oral prednisolone were administered, ameliorating her condition with improved neuroimages. This case highlights the importance of distinguishing NIID and MELAS, and reversible DWI hyperintensities can be seen in NIID. Full article

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