Vitamin D is not a true vitamin but a fat-soluble steroid prohormone that has long been known for its important and diverse role in the biological system. Many studies have revealed that vitamin D deficiency is linked with an increased risk of autoimmune diseases, cardiovascular diseases, cancers, type II diabetes and infectious diseases. Vitamin D3 is transformed to its active form, 1, 25-dihydroxyvitamin D3, through metabolisms in the liver and kidney. 1, 25-dihydroxyvitamin D3 interacts with its vitamin D receptor, and the brain is now known to have vitamin D receptors and 1alpha-hydroxylase. Several lines of evidences suggest vitamin D deficiency is associated with cognitive impairment and dementia, however, its position in cognitive function is still in its infancy. Vitamin D deficiency is a reversible condition and can be easily treated with supplements. Randomized controlled trials of vitamin D supplementation in patients with neurodegenerative conditions are needed.
Autoimmune Diseases ; Brain ; Cardiovascular Diseases ; Cholecalciferol ; Cognition ; Communicable Diseases ; Dementia ; Humans ; Kidney ; Liver ; Receptors, Calcitriol ; Vitamin D ; Vitamin D Deficiency ; Vitamins

Sarcopenia (Greek ‘sarx’ or flesh+‘penia’ or loss) originally is proposed as the term to describe age-related decrease of muscle mass. These days, sarcopenia is defined as a syndrome characterized by progressive loss of skeletal muscle mass and strength with a risk of adverse outcomes such as poor quality of life, physical disability, and death. In the recent decade, there are a few of consensus; European, international, and Asian consensus panels have published definitions. Additionally, measurement techniques that can be used for research and clinical practice settings according to their suitability are suggested. Many studies are reported about the association with sarcopenia and neurologic diseases, however, the results are heterogenous due to lack of sufficient studies. Some pharmacologic and non-pharmacologic methods are suggested as the intervention of sarcopenia, although there are not enough studies, yet. In this review, we summarize current understanding of the diagnostic sarcopenia and neurological point of view of sarcopenia.
Asian Continental Ancestry Group ; Consensus ; Diagnosis* ; Humans ; Muscle, Skeletal ; Quality of Life ; Sarcopenia*

Vertebral artery dissection is one of the most common causes of stroke in young adults. The course of the vertebral artery dissection is usually benign, and pure transient amnesia as an initial symptom has been rarely reported. We describe a patient with vertebral artery dissection who presented with acute transient amnesia, and review the medical literatures about the pathophysiological mechanism of transient global amenesia (TGA). This case could be a one of evidence which supports the cerebrovascular mechanism of TGA.
Amnesia ; Amnesia, Transient Global* ; Humans ; Stroke ; Vertebral Artery Dissection* ; Young Adult

Subacute combined degeneration (SCD) of the spinal cord, which is a result of vitamin B12 deficiency, may cause irreversible neurological deficits. The lesion in the spinal cord is typically localized to the posterior and lateral columns, as the name implies. In this paper, we report on two patients with SCD, whose lesions involved the bilateral anterior column as well as the posterior and lateral columns. This report illustrates the importance of awareness of clinical and radiologic variable characteristics of SCD.

Background: and Purpose: Recognizing cognitive decline patterns in mild cognitive impairment (MCI) is crucial for early screening and preventive interventions. However, studies on the trajectory of individual cognitive functions in MCI are limited. Thus, the purpose of this study was to identify subtypes and stages of cognitive decline in MCI using a machine learning method. Methods: A total of 944 subjects consisting of those who were cognitively normal and those with MCI were enrolled. Fifteen neuropsychological tasks were used in the analysis.The optimal number of subtypes was determined based on the cross-validation information criterion. Fifteen stages of cognitive trajectory were estimated for each subtype. Results: The following three subtypes were identified: amnestic-verbal subtype, dysexecutive subtype, and amnestic-visual subtype. Of 723 (76.6%) subjects who had reached stage 1 at least, amnestic-verbal subtype accounted for the most (n=340, 47.0%), followed by dysexecutive subtype (n=253, 35.0%) and amnestic-visual subtype (n=130, 18%). The amnestic-verbal subtype had significantly more males (amnestic-verbal: 41.8%, dysexecutive: 31.2%, and amnestic-visual: 28.5%), younger subjects (amnestic-verbal: 72.01 years, dysexecutive: 74.43 years, and amnestic-visual: 75.06 years), higher educational years (amnestic-verbal: 11.06 years, dysexecutive: 9.53 years, and amnestic-visual: 9.79 years), lower Clinical Dementia Rating sum of boxes (amnestic-verbal: 1.40, dysexecutive: 1.61, and amnestic-visual: 1.71), and lower Korean-Instrumental Activities of Daily Living score (amnestic-verbal: 0.20, dysexecutive: 0.27, and amnestic-visual: 0.26). Conclusions Three types of MCIs were extracted using SuStaIn. Pathways of MCI deterioration could be different. The amnestic type could be bisected based on whether episodic verbal or visual memory is degraded first.

Background: and Purpose: Recognizing cognitive decline patterns in mild cognitive impairment (MCI) is crucial for early screening and preventive interventions. However, studies on the trajectory of individual cognitive functions in MCI are limited. Thus, the purpose of this study was to identify subtypes and stages of cognitive decline in MCI using a machine learning method. Methods: A total of 944 subjects consisting of those who were cognitively normal and those with MCI were enrolled. Fifteen neuropsychological tasks were used in the analysis.The optimal number of subtypes was determined based on the cross-validation information criterion. Fifteen stages of cognitive trajectory were estimated for each subtype. Results: The following three subtypes were identified: amnestic-verbal subtype, dysexecutive subtype, and amnestic-visual subtype. Of 723 (76.6%) subjects who had reached stage 1 at least, amnestic-verbal subtype accounted for the most (n=340, 47.0%), followed by dysexecutive subtype (n=253, 35.0%) and amnestic-visual subtype (n=130, 18%). The amnestic-verbal subtype had significantly more males (amnestic-verbal: 41.8%, dysexecutive: 31.2%, and amnestic-visual: 28.5%), younger subjects (amnestic-verbal: 72.01 years, dysexecutive: 74.43 years, and amnestic-visual: 75.06 years), higher educational years (amnestic-verbal: 11.06 years, dysexecutive: 9.53 years, and amnestic-visual: 9.79 years), lower Clinical Dementia Rating sum of boxes (amnestic-verbal: 1.40, dysexecutive: 1.61, and amnestic-visual: 1.71), and lower Korean-Instrumental Activities of Daily Living score (amnestic-verbal: 0.20, dysexecutive: 0.27, and amnestic-visual: 0.26). Conclusions Three types of MCIs were extracted using SuStaIn. Pathways of MCI deterioration could be different. The amnestic type could be bisected based on whether episodic verbal or visual memory is degraded first.

Background: and Purpose: Recognizing cognitive decline patterns in mild cognitive impairment (MCI) is crucial for early screening and preventive interventions. However, studies on the trajectory of individual cognitive functions in MCI are limited. Thus, the purpose of this study was to identify subtypes and stages of cognitive decline in MCI using a machine learning method. Methods: A total of 944 subjects consisting of those who were cognitively normal and those with MCI were enrolled. Fifteen neuropsychological tasks were used in the analysis.The optimal number of subtypes was determined based on the cross-validation information criterion. Fifteen stages of cognitive trajectory were estimated for each subtype. Results: The following three subtypes were identified: amnestic-verbal subtype, dysexecutive subtype, and amnestic-visual subtype. Of 723 (76.6%) subjects who had reached stage 1 at least, amnestic-verbal subtype accounted for the most (n=340, 47.0%), followed by dysexecutive subtype (n=253, 35.0%) and amnestic-visual subtype (n=130, 18%). The amnestic-verbal subtype had significantly more males (amnestic-verbal: 41.8%, dysexecutive: 31.2%, and amnestic-visual: 28.5%), younger subjects (amnestic-verbal: 72.01 years, dysexecutive: 74.43 years, and amnestic-visual: 75.06 years), higher educational years (amnestic-verbal: 11.06 years, dysexecutive: 9.53 years, and amnestic-visual: 9.79 years), lower Clinical Dementia Rating sum of boxes (amnestic-verbal: 1.40, dysexecutive: 1.61, and amnestic-visual: 1.71), and lower Korean-Instrumental Activities of Daily Living score (amnestic-verbal: 0.20, dysexecutive: 0.27, and amnestic-visual: 0.26). Conclusions Three types of MCIs were extracted using SuStaIn. Pathways of MCI deterioration could be different. The amnestic type could be bisected based on whether episodic verbal or visual memory is degraded first.

Background: and Purpose: Recognizing cognitive decline patterns in mild cognitive impairment (MCI) is crucial for early screening and preventive interventions. However, studies on the trajectory of individual cognitive functions in MCI are limited. Thus, the purpose of this study was to identify subtypes and stages of cognitive decline in MCI using a machine learning method. Methods: A total of 944 subjects consisting of those who were cognitively normal and those with MCI were enrolled. Fifteen neuropsychological tasks were used in the analysis.The optimal number of subtypes was determined based on the cross-validation information criterion. Fifteen stages of cognitive trajectory were estimated for each subtype. Results: The following three subtypes were identified: amnestic-verbal subtype, dysexecutive subtype, and amnestic-visual subtype. Of 723 (76.6%) subjects who had reached stage 1 at least, amnestic-verbal subtype accounted for the most (n=340, 47.0%), followed by dysexecutive subtype (n=253, 35.0%) and amnestic-visual subtype (n=130, 18%). The amnestic-verbal subtype had significantly more males (amnestic-verbal: 41.8%, dysexecutive: 31.2%, and amnestic-visual: 28.5%), younger subjects (amnestic-verbal: 72.01 years, dysexecutive: 74.43 years, and amnestic-visual: 75.06 years), higher educational years (amnestic-verbal: 11.06 years, dysexecutive: 9.53 years, and amnestic-visual: 9.79 years), lower Clinical Dementia Rating sum of boxes (amnestic-verbal: 1.40, dysexecutive: 1.61, and amnestic-visual: 1.71), and lower Korean-Instrumental Activities of Daily Living score (amnestic-verbal: 0.20, dysexecutive: 0.27, and amnestic-visual: 0.26). Conclusions Three types of MCIs were extracted using SuStaIn. Pathways of MCI deterioration could be different. The amnestic type could be bisected based on whether episodic verbal or visual memory is degraded first.

Background: and Purpose: Each item in the instrumental activities of daily living (IADL) questionnaire has differential importance to an individual’s life functioning based on gender.However, IADL has mostly been utilized for its total score alone, without gender specificity.We identify the impact of each item on the transition from amnestic mild cognitive impairment (aMCI) to Alzheimer’s disease dementia (ADD), and determine if the impact of each item differs by gender. Methods: Subjects were aMCI or ADD with a global clinical dementia rating of 0.5 or 1. The sample size was 146 men and 154 women. We used logistic regression analysis to determine the effect of each item of IADL on the transition from aMCI to ADD. Results: The odds ratio (OR) for “remembering recent events” had similar values: 27.2 for men, and 27.7 for women. Gender difference was identified in the item with the highest OR value. For women, the “using transportation” item was 63.3, and for men, “conducting financial affairs” was overwhelmingly high at 89.1. Conclusions Functional decline on items with relatively higher ORs may indicate higher probability of a transition from aMCI to ADD. The OR of “conducting financial affairs” was relatively higher for both genders. In terms of gender differences, “conducting home repair” for men, and “using transportation” for women, have relatively higher impact. This study demonstrates that during the transition from aMCI to ADD, each item of IADL shows a staggered decline in functioning, and that this decline is gender-specific.

Background: Determination of inter-method differences between clinically available volumetry methods are essential for the clinical application of brain volumetry in a wider context.Purpose: The purpose of this study was to examine the inter-method reliability and differences between the Siemens morphometry (SM) software and the NeuroQuant (NQ) software. Materials and Methods: MR images of 86 subjects with subjective or objective cognitive impairment were included in this retrospective study. For this study, 3D T1 volume images were obtained in all subjects using a 3T MR scanner (Skyra 3T, Siemens). Volumetric analysis of the 3D T1 volume images was performed using SM and NQ. To analyze the inter-method difference, correlation, and reliability, we used the paired t-test, Bland-Altman plot, Pearson’s correlation coefficient, intraclass correlation coefficient (ICC), and effect size (ES) using the MedCalc and SPSS software. Results: SM and NQ showed excellent reliability for cortical gray matter, cerebral white matter, and cerebrospinal fluid; and good reliability for intracranial volume, whole brain volume, both thalami, and both hippocampi. In contrast, poor reliability was observed for both basal ganglia including the caudate nucleus, putamen, and pallidum. Paired comparison revealed that while the mean volume of the right hippocampus was not different between the two software, the mean difference in the left hippocampus volume between the two methods was 0.17 ml (P < 0.001). The other brain regions showed significant differences in terms of measured volumes between the two software. Conclusion SM and NQ provided good-to-excellent reliability in evaluating most brain structures, except for the basal ganglia in patients with cognitive impairment.Researchers and clinicians should be aware of the potential differences in the measured volumes when using these two different software interchangeably.