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The prevalence of Parkinson's disease (PD) has increased steadily with the increase of the elderly population. PD may influence dietary intake and quality, and the gut microbiome composition. The present study examined differences in dietary intake and quality between PD patients and controls according to sex. In addition, we assessed the gut microbiome composition. This cross-sectional study was conducted at A Medical Center, Seoul, South Korea. PD severity, swallowing function, olfactory function, and constipation status were examined by a skilled nurse. Dietary data were collected through a semi-quantitative food frequency questionnaire. Stool samples were subjected to microbiome analysis. To examine dietary quality, the Dietary Quality Index-International (DQI-I), Healthy Eating Index (HEI), Index of Nutritional Quality (INQ), Dietary Diversity Score (DDS), and Mediterranean Diet Score (MDS) were used. An independent t-test was used to determine differences between patients and controls. A chi-square test was used to examine frequency differences. Dietary intake did not differ between the PD patient and control groups. Regarding dietary quality, the patients consumed more saturated fat compared to controls. Overall, the dietary differences between the groups were minor. The composition of the gut microbiome differed between PD patients and controls. Lactobacillus and Bifidobacterium genus were most abundant in PD patients. Prevotella VZCB and other Faecalibacterium were most abundant in controls. Our results indicated that PD patients may experience gut microbiome change even in the early stage, while nutritional needs can be met when a balanced diet including various food groups are consumed. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to identify predictors for the recurrence of spontaneous intracranial hypotension (SIH) after epidural blood patch (EBP). Background: Epidural blood patch is the main treatment option for SIH; however, the characteristics of patients who experience relapse after successful EBP treatment for SIH remain understudied. Methods: In this exploratory, retrospective, case–control study, we included 19 patients with SIH recurrence after EBP and 36 age‐ and sex‐matched patients without recurrence from a single tertiary medical institution. We analyzed clinical characteristics, neuroimaging findings, and volume changes in intracranial structures after EBP treatment. Machine learning methods were utilized to predict the recurrence of SIH after EBP treatment. Results: There were no significant differences in clinical features between the recurrence and no‐recurrence groups. Among brain magnetic resonance imaging signs, diffuse pachymeningeal enhancement and cerebral venous dilatation were more prominent in the recurrence group than no‐recurrence group after EBP (14/19 [73%] vs. eight of 36 [22%] patients, p = 0.001; 11/19 [57%] vs. seven of 36 [19%] patients, p = 0.010, respectively). The midbrain–pons angle decreased in the recurrence group compared to the no‐recurrence group after EBP, at a mean (standard deviation [SD]) of –12.0 [16.7] vs. +1.8[18.3]° (p = 0.048). In volumetric analysis, volume changes after EBP were smaller in the recurrence group than in the no‐recurrence group in intracranial cerebrospinal fluid (mean [SD] −11.6 [15.3] vs. +4.8 [17.1] mL, p = 0.001) and ventricles (mean [SD] +1.0 [2.0] vs. +2.0 [2.5] mL, p = 0.003). Notably, the random forest classifier indicated that the model constructed with brain volumetry was more accurate in discriminating SIH recurrence (area under the curve = 0.80 vs. 0.52). Conclusion: Our study suggests that volumetric analysis of intracranial structures may aid in predicting recurrence after EBP treatment in patients with SIH. Plain Language Summary: There is not much research about patients who experience symptom relapse after successful epidural blood patch (EBP) treatment for spontaneous intracranial hypotension (SIH). We used machine learning (an analysis that helps us understand patterns in data) to learn about medical records from 19 patients with SIH whose symptoms came back and 36 patients whose symptoms did not recur after EBP treatment. Our results suggest that changes in the amount of cerebrospinal fluid in the brain and the size of the ventricles can help predict the recurrence of SIH after EBP treatment. [ABSTRACT FROM AUTHOR]

Accumulation of aggregated amyloid-β (Aβ) in the brain is considered the first pathological event within the pathogenesis of Alzheimer's disease (AD). It is difficult to accurately identify the initial brain regions of Aβ accumulation due to the time-lag between the start of the pathophysiology and symptom onset. However, focal regional amyloid uptake on amyloid PET scans may provide insights into this. Hence, we aimed to evaluate the topographic distribution of amyloid deposition in patients with cognitive impairment and to identify the starting order of amyloid accumulation in the brain using conditional probability. We enrolled 58 patients composed of 9 normal cognition (NC), 32 mild cognitive impairment (MCI), and 17 dementia showing focal regional amyloid deposition corresponding to a brain amyloid plaque load (BAPL) score of 2 among those who visited the Memory Clinic of Asan Medical Center and underwent an 18F-florbetaben PET scan (March 2013 to April 2019). Regions of interest (ROI) included the frontal, parietal, lateral temporal, and occipital cortices, the posterior cingulate/precuneus, and the striatum. The most frequent occurrence of Aβ deposition was in the posterior cingulate/precuneus (n = 41, 68.3%). The second most frequent site was the lateral temporal cortex (n = 24, 40.0%), followed by the lateral parietal cortex (n = 21, 35.6%) and other lesions, such as the frontal and occipital cortices. The striatum was the least frequently affected. Our study found that the posterior cingulate/precuneus and the lateral temporal and parietal cortices may be the earliest areas to be affected by Aβ accumulation. Longitudinal follow-up of focal brain amyloid deposition may help elucidate the evolutionary pattern of Aβ accumulation in the brain of people with AD continuum. [ABSTRACT FROM AUTHOR]