American journal of neurodegenerative disease最新文献

{"title":"Determining the normal range of the dimensions and volume of the pituitary gland of children using a 3D magnetic resonance imaging (MRI) protocol in Imam Hossein Hospital of Isfahan in 2021 to 2024.","authors":"Nilufar Ghorbani, Sam Mirfendereski, Neda Hosseini Moshkenani","doi":"10.62347/CXAQ5541","DOIUrl":"10.62347/CXAQ5541","url":null,"abstract":"<p><strong>Background: </strong>Understanding the morphological changes and dimensions of the pituitary gland is crucial for accurate diagnosis and personalized treatment in pediatric patients. Advanced imaging techniques, such as 3D magnetic resonance imaging (MRI), enhance our ability to address knowledge gaps and improve clinical practices in pediatric endocrinology. This study aims to determine normative pituitary gland dimensions and volumes in pediatric patients at Imam Hossein Hospital in Isfahan using advanced 3D MRI protocols.</p><p><strong>Methods: </strong>Conducted as a prospective cross-sectional study, this research focused on children under 15 years without specific conditions. A total of 412 participants were selected through simple random sampling, and data were analyzed using SPSS version 20 to rigorously assess measurements and extract insights beneficial for pediatric endocrinology.</p><p><strong>Results: </strong>The study included participants aged 0 to 15 years, with a higher representation of boys (63.83%) compared to girls (36.17%). Significant differences were observed in height and volume based on gender and age group. Scatterplots illustrated variations in the pituitary gland's volume, width, height, and anterior-posterior diameter according to age and gender.</p><p><strong>Conclusion: </strong>This research provides valuable insights into pediatric endocrinology, facilitating accurate diagnosis and treatment of pituitary disorders in children.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"14 1","pages":"42-50"},"PeriodicalIF":0.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929036/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of nuclear medicine in neurodegenerative diseases: a narrative review.","authors":"Farshad Riahi, Shahin Fesharaki","doi":"10.62347/SOGE3962","DOIUrl":"10.62347/SOGE3962","url":null,"abstract":"<p><p>Neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Lewy body dementia, are associated with the accumulation of brain proteins, leading to neuroinflammation, disruption of cellular clearance mechanisms, and neuronal death. Nuclear medicine, utilizing technologies like PET and SPECT, plays a crucial role in diagnosing and managing these disorders. Recent advancements in nuclear medicine have enhanced the understanding of disease pathophysiology and facilitated the development of tailored therapeutics. This study aims to address gaps in understanding nuclear medicine's potential to improve early diagnosis, monitor disease progression, and evaluate therapeutic effectiveness. In this review, we analyzed 28 papers and summarized their findings. PET radioligands have revolutionized the in vivo measurement of pathological targets in neurological diseases, offering new insights into the pathophysiology of neurodegenerative conditions. Amyloid PET has emerged as a reliable diagnostic imaging tool, accurately identifying cerebral amyloid-beta accumulation and enabling early differential diagnosis in clinical settings. Furthermore, radiopharmaceuticals such as [18F]Flortaucipir, [18F]FDOPA, and TSPO ligands provide significant advancements in the diagnosis and treatment of neurodegenerative disorders.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"14 1","pages":"34-41"},"PeriodicalIF":0.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Curvature estimation techniques for advancing neurodegenerative disease analysis: a systematic review of machine learning and deep learning approaches.","authors":"Seyed-Ali Sadegh-Zadeh, Nasrin Sadeghzadeh, Bahareh Sedighi, Elaheh Rahpeyma, Mahdiyeh Nilgounbakht, Mohammad Amin Barati","doi":"10.62347/DZNQ2482","DOIUrl":"10.62347/DZNQ2482","url":null,"abstract":"<p><p>Neurodegenerative diseases present complex challenges that demand advanced analytical techniques to decode intricate brain structures and their changes over time. Curvature estimation within datasets has emerged as a critical tool in areas like neuroimaging and pattern recognition, with significant applications in diagnosing and understanding neurodegenerative diseases. This systematic review assesses state-of-the-art curvature estimation methodologies, covering classical mathematical techniques, machine learning, deep learning, and hybrid methods. Analysing 105 research papers from 2010 to 2023, we explore how each approach enhances our understanding of structural variations in neurodegenerative pathology. Our findings highlight a shift from classical methods to machine learning and deep learning, with neural network regression and convolutional neural networks gaining traction due to their precision in handling complex geometries and data-driven modelling. Hybrid methods further demonstrate the potential to merge classical and modern techniques for robust curvature estimation. This comprehensive review aims to equip researchers and clinicians with insights into effective curvature estimation methods, supporting the development of enhanced diagnostic tools and interventions for neurodegenerative diseases.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"14 1","pages":"1-33"},"PeriodicalIF":0.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing neural computation: experimental validation and optimization of dendritic learning in feedforward tree networks.","authors":"Seyed-Ali Sadegh-Zadeh, Pooya Hazegh","doi":"10.62347/FIQW7087","DOIUrl":"10.62347/FIQW7087","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to explore the capabilities of dendritic learning within feedforward tree networks (FFTN) in comparison to traditional synaptic plasticity models, particularly in the context of digit recognition tasks using the MNIST dataset.</p><p><strong>Methods: </strong>We employed FFTNs with nonlinear dendritic segment amplification and Hebbian learning rules to enhance computational efficiency. The MNIST dataset, consisting of 70,000 images of handwritten digits, was used for training and testing. Key performance metrics, including accuracy, precision, recall, and F1-score, were analysed.</p><p><strong>Results: </strong>The dendritic models significantly outperformed synaptic plasticity-based models across all metrics. Specifically, the dendritic learning framework achieved a test accuracy of 91%, compared to 88% for synaptic models, demonstrating superior performance in digit classification.</p><p><strong>Conclusions: </strong>Dendritic learning offers a more powerful computational framework by closely mimicking biological neural processes, providing enhanced learning efficiency and scalability. These findings have important implications for advancing both artificial intelligence systems and computational neuroscience.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 5","pages":"49-69"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11751443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural reshaping: the plasticity of human brain and artificial intelligence in the learning process.","authors":"Seyed-Ali Sadegh-Zadeh, Mahboobe Bahrami, Ommolbanin Soleimani, Sahar Ahmadi","doi":"10.62347/NHKD7661","DOIUrl":"10.62347/NHKD7661","url":null,"abstract":"<p><p>This study explores the concept of neural reshaping and the mechanisms through which both human and artificial intelligence adapt and learn.</p><p><strong>Objectives: </strong>To investigate the parallels and distinctions between human brain plasticity and artificial neural network plasticity, with a focus on their learning processes.</p><p><strong>Methods: </strong>A comparative analysis was conducted using literature reviews and machine learning experiments, specifically employing a multi-layer perceptron neural network to examine regression and classification problems.</p><p><strong>Results: </strong>Experimental findings demonstrate that machine learning models, similar to human neuroplasticity, enhance performance through iterative learning and optimization, drawing parallels in strengthening and adjusting connections.</p><p><strong>Conclusions: </strong>Understanding the shared principles and limitations of neural and artificial plasticity can drive advancements in AI design and cognitive neuroscience, paving the way for future interdisciplinary innovations.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 5","pages":"34-48"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11751442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of dimensionality reduction techniques for EEG-based emotional state classification.","authors":"Seyed-Ali Sadegh-Zadeh, Nasrin Sadeghzadeh, Ommolbanin Soleimani, Saeed Shiry Ghidary, Sobhan Movahedi, Seyed-Yaser Mousavi","doi":"10.62347/ZWRY8401","DOIUrl":"10.62347/ZWRY8401","url":null,"abstract":"<p><strong>Objectives: </strong>The aim of this study is to evaluate the impact of various dimensionality reduction methods, including principal component analysis (PCA), Laplacian score, and Chi-square feature selection, on the classification performance of an electroencephalogram (EEG) dataset.</p><p><strong>Methods: </strong>We applied dimensionality reduction techniques, including PCA, Laplacian score, and Chi-square feature selection, and assessed their impact on the classification performance of EEG data using linear regression, K-nearest neighbour (KNN), and Naive Bayes classifiers. The models were evaluated in terms of their classification accuracy and computational efficiency.</p><p><strong>Results: </strong>Our findings suggest that all dimensionality reduction strategies generally improved or maintained classification accuracy while reducing the computational load. Notably, PCA and Autofeat techniques led to increased accuracy for the models.</p><p><strong>Conclusions: </strong>The use of dimensionality reduction techniques can enhance EEG data classification by reducing computational demands without compromising accuracy. These results demonstrate the potential for these techniques to be applied in scenarios where both computational efficiency and high accuracy are desired. The code used in this study is available at https://github.com/movahedso/Emotion-analysis.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 4","pages":"23-33"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11578865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142712066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exceptionally giant neglected sacral chordoma in a post-poliotic residual paralysis patient - a rare case scenario.","authors":"Prabodh Kantiwal, Aakarsh Aggarwal, Sandeep K Yadav, Nitesh Gahlot, Abhay Elhence","doi":"10.62347/EKNJ6411","DOIUrl":"10.62347/EKNJ6411","url":null,"abstract":"<p><p>Chordoma is a rare malignant tumour with an incidence of 0.1 case per 1 lakh population per year. The sacrococcygeal region is the most common site to be involved. Herein, we are reporting a case of sacral chordoma, who is a 32-year-old male patient, a known case of post-polio residual paralysis on the left lower limb, who presented with complaint of pain in the lower back and gluteal region for 2 years with swelling in the gluteal region for 1 year, which was gradually increasing in size for 1 year with associated weight loss. MRI revealed an ill-defined lytic expansile altered signal intensity lesion involving S3 to S5 and coccygeal vertebral bodies measuring 13.2 × 16.2 × 14 cm (ap × tr × cc) with adjacent large lobulated heterogeneous soft tissue component and showed multiple coarse calcifications. The lesion anteriorly displaced and abutted the rectum and was deriving its blood supply from branches of bilateral internal iliac arteries. The patient was planned and underwent wide-margin resection (middle sacrectomy with R0 margins with preservation of both S2 and right S3 nerve roots). Histologic Grade was reported to be G2, moderately differentiated, high grade. Pathologic stage classification was reported as pT3a. Postoperatively patient had the same neurological status and was discharged on advice to do full weight bearing walking and self-intermittent catheterisation and laxatives. He was on routine follow up and improved well symptomatically.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 3","pages":"13-22"},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11411203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of willingness to obtain of Covid 19 vaccine in patients with multiple sclerosis.","authors":"Masoud Ghiasian, Maryam Farhadian, Alireza Salehzadeh","doi":"10.62347/OCCZ6431","DOIUrl":"10.62347/OCCZ6431","url":null,"abstract":"<p><strong>Introduction: </strong>Assessing vaccine willingness and understanding sources of vaccine hesitancy in individuals with multiple sclerosis (MS) helps healthcare providers approach patients more effectively while respecting their autonomy to encourage coronavirus disease 2019 (COVID-19) vaccination.</p><p><strong>Materials and methods: </strong>A descriptive-analytical cross-sectional study using a researcher-made checklist was conducted on MS patients referred to Neshat Clinic of Hamadan during the years 2020-2021. The checklist contained questions about demographic information, MS phenotype, duration of illness, expanded disability status scale (EDSS) score, and COVID-19 vaccination status. The expanded disability status scale (EDSS) is the most commonly used instrument for measuring disability in patients with multiple sclerosis (MS). The EDSS scale ranges from 0 to 10 in increments of 0.5 units, denoting advanced points of disability.</p><p><strong>Results: </strong>Based on the results, 20 individuals (10%) were in the vaccine non-acceptance group, while 181 individuals (90%) were in the vaccine acceptance group. A significant number of relapsing and remitting (RR) type MS patients (90.7%) and all primary progressive (PP) type MS patients (100%) accepted the vaccine. In comparison, vaccine non-acceptance in the secondary progressive (SP) group was relatively higher (20.7%) compared to other types of MS, and this difference was significant (P < 0.05). Additionally, there was a statistically significant relationship between the history of COVID-19 and vaccine acceptance (P < 0.05).</p><p><strong>Conclusion: </strong>The study results demonstrated a high rate of COVID-19 vaccine acceptance among MS patients. MS phenotype, previous infection experiences, and other influences allow for COVID-19 vaccine acceptance among MS patients. This information can improve health programs and communication strategies for COVID-19 and future possible infectious disease vaccination in individuals with MS.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 2","pages":"7-12"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11250120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141636032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short segment posterior fixation of unstable thoracolumbar vertebral fractures with fractured vertebra augmentation with intermediate pedicle screw - a clinicoradiological analysis.","authors":"Sandeep Kumar Yadav, Rajesh Kumar Rajnish, Prabodh Kantiwal, Nitesh Gehlot, Abhay Elhence, Sumit Banerjee, Saurabh Gupta, Laxman Choudary, Anil Meena, Srikanth Eppakayala","doi":"10.62347/BKEX3282","DOIUrl":"10.62347/BKEX3282","url":null,"abstract":"<p><strong>Introduction: </strong>Unstable thoracolumbar burst fractures are routinely encountered in orthopedic practice. Recently, short-segment fixation with pedicle screw augmentation of the fractured vertebra for unstable thoracolumbar burst fractures has gained popularity. Nonetheless, the maintenance of the kyphotic correction during the follow-up period remains controversial. This study aimed to examine the clinical-radiological outcomes, complications, and functional outcomes of fractured vertebrae augmentation with intermediate pedicle screws in short-segment instrumentation in acute thoracolumbar spine fractures.</p><p><strong>Methods: </strong>This retrospective study was conducted in the Department of Orthopedics, All India Institute of Medical Sciences, Jodhpur, using medical records from January 2021 to October 2022. Parameters such as local kyphosis correction, loss of kyphotic correction at final follow-up, anterior body height correction (%), and loss of correction (%) at final follow-up were measured as primary outcomes. Various other parameters such as operative time, blood loss, length of hospital stay, and visual analog scale were measured as secondary outcomes.</p><p><strong>Results: </strong>The mean correction obtained via surgery in the immediate postoperative period was 13.7±2.3 degrees. The mean loss of correction at the final follow-up was 4.1±2.0 degrees, and the mean final local kyphotic angle was 7.2±2.4 degrees (P<0.05). The mean correction obtained via surgery in the immediate postoperative period was 37.2%±9.0%. The mean loss of correction at the final follow-up was 10.5%±5.3%, and the mean final anterior vertebral body height maintained was 72%±11.0% (P<0.05).</p><p><strong>Conclusion: </strong>Short-segment posterior fixation with pedicle screw augmentation achieves good correction of local kyphotic angle and anterior vertebral height in the immediate postoperative period, but some loss of correction at final follow-up is common. In our study, the loss of correction corresponded directly to the load-sharing score.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"13 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11087276/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell RNA sequencing analysis and Alzheimer's disease: a bibliometric analysis.","authors":"Lilach Soreq, Wael Mohamed","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a devastative disease, the 1^st most frequent neurodegenerative disease worldwide. Its prevalence is increasing and early detection methods as well as potential genomic based therapeutics are urgently needed.</p><p><strong>Objectives: </strong>To better characterize recent seq studies of AD and site recent relevant literature. Using single-cell RNA sequencing, the characteristics of neuronal cell populations in Alzheimer's disease (AD) have not been completely elucidated.</p><p><strong>Methods: </strong>We conducted a dynamic and longitudinal bibliometric analysis to investigate existing studies on Single-cell RNA sequencing analysis and Alzheimer's Disease and identify data gaps and possible new research avenues.</p><p><strong>Results: </strong>All AD papers concentrating on Single-cell RNA sequencing analysis were found using the search terms \"Alzheimer's Disease\", and \"Single-cell RNA sequencing analysis\" in the PubMed/MEDLINE database. Only English publications published between 2015 and 2023 were chosen using filters.</p><p><strong>Conclusions: </strong>Original English-language research publications disclosing Single-cell RNA sequencing analysis and Alzheimer's Disease were examined for inclusion. Two sets of independent reviewers discovered and extracted pertinent data. The bibliometric study was carried out using the R software packages Bibliometrix and Biblioshiny. The narrowed search yielded 158 publications, all published between 2015 and 2023. Yet, after applying filters and considering the inclusion requirements, the search results comprise just 51 original articles out of 158 articles. There were 107 articles eliminated. The importance of the discovery of Single-cell RNA sequencing analysis and Alzheimer's Disease a decade ago only grows with time. Our results have important implications for future studies of AD and may help researchers across the world better understand the global context of the Single-cell RNA sequencing analysis and Alzheimer's Disease link. This study puts emphasis on the critical need for more diverse participant demographics in Alzheimer's disease investigations.</p>","PeriodicalId":72170,"journal":{"name":"American journal of neurodegenerative disease","volume":"12 5","pages":"133-146"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10658177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138464710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}