Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach.

BACKGROUND/OBJECTIVES: Although the involvement of progressive brain alterations in epilepsy was recently suggested, individual patients' trajectories of white matter (WM) disruption are not known. METHODS: We investigated the disease progression patterns of WM damage and its associations with clinical metrics. We examined the cross-sectional diffusion tensor imaging (DTI) data of 155 patients with unilateral temporal lobe epilepsy (TLE) and 270 age/gender-matched healthy controls, and we then calculated the average fractional anisotropy (FA) values within 20 WM tracts of the whole brain. We used the Subtype and Stage Inference (SuStaIn) program to detect the progression trajectory of FA changes and investigated its association with clinical parameters including onset age, disease duration, drug-responsiveness, and the number of anti-seizure medications (ASMs). RESULTS: The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). This pattern was replicated when analyzing TLE with hippocampal sclerosis (n = 50) and TLE with no lesions (n = 105) separately. Further-progressed stages were associated with longer disease duration (p < 0.001) and a greater number of ASMs (p = 0.001). CONCLUSIONS: the disease progression model based on WM tracts may be useful as a novel individual-level biomarker.

Path Integration Detects Prodromal Alzheimer's Disease and Predicts Cognitive Decline.

Background: The entorhinal cortex is the very earliest involvement of Alzheimer's disease (AD). Grid cells in the medial entorhinal cortex form part of the spatial navigation system. Objective: We aimed to determine whether path integration performance can be used to detect patients with mild cognitive impairment (MCI) at high risk of developing AD, and whether it can predict cognitive decline. Methods: Path integration performance was assessed in 71 patients with early MCI (EMCI) and late MCI (LMCI) using a recently developed 3D virtual reality navigation task. Patients with LMCI were further divided into those displaying characteristic brain imaging features of AD, including medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single-photon emission tomography (LMCI+), and those not displaying such features (LMCI-). Results: Path integration performance was significantly lower in patients with LMCI+than in those with EMCI and LMCI-. A significantly lower performance was observed in patients who showed progression of MCI during 12 months, than in those with stable MCI. Path integration performance distinguished patients with progressive MCI from those with stable MCI, with a high classification accuracy (a sensitivity of 0.88 and a specificity of 0.70). Conclusions: Our results suggest that the 3D virtual reality navigation task detects prodromal AD patients and predicts cognitive decline after 12 months. Our navigation task, which is simple, short (12-15 minutes), noninvasive, and inexpensive, may be a screening tool for therapeutic choice of disease-modifiers in individuals with prodromal AD.

Relationships between neuroimaging biomarkers and glymphatic-system activity in dementia with Lewy bodies.

Alpha-synuclein deposits in the brain have been suspected to cause Parkinson's disease and dementia with Lewy bodies (DLB). It was recently revealed that the glymphatic system is largely responsible for the removal of alpha-synuclein. We investigated changes in the glymphatic system's activity by determining the DTI­ALPS (diffusion tensor image analysis along the perivascular space) index in DLB patients. Twenty-six patients with DLB and 43 healthy subjects underwent diffusion tensor imaging (DTI) scanning at our hospital during the period April 2013 to March 2023. We retrospectively computed each subject's DTI­ALPS index to evaluate his/her glymphatic-system activity and then analyzed the relationships between the subjects' DTI­ALPS index data and their DLB neuroimaging biomarker values. A significant reduction of the DTI­ALPS index was observed in the patients with DLB compared to the healthy subjects. Significant positive correlations were also detected in the DLB group between the DTI­ALPS index and the regional gray matter volume in the left insula and between the index and the specific binding ratio of 123I-N-ω-fluoropropyl-2ß-carboxymethoxy-3ß-(4-iodophenyl)nortropane ([123I]-FP-CIT). These results indicate that (i) the DTI­ALPS index is a good biomarker of the progression of DLB, and (ii) this index might be effective to distinguish DLB from other neurocognitive disorders.

White matter brain-age in diverse forms of epilepsy and interictal psychosis.

Abnormal brain aging is suggested in epilepsy. Given the brain network dysfunction in epilepsy, the white matter tracts, which primarily interconnect brain regions, could be of special importance. We focused on white matter brain aging in diverse forms of epilepsy and comorbid psychosis. We obtained brain diffusion tensor imaging (DTI) data at 3 T-MRI in 257 patients with epilepsy and 429 healthy subjects. The tract-based fractional anisotropy values of the healthy subjects were used to build a brain-age prediction model, and we calculated the brain-predicted age difference (brain-PAD: predicted age-chronological age) of all subjects. As a result, almost all epilepsy categories showed significantly increased brain-PAD (p < 0.001), including temporal lobe epilepsy (TLE) with no MRI-lesion (+ 4.2 yr), TLE with hippocampal sclerosis (+ 9.1 yr), extratemporal focal epilepsy (+ 5.1 yr), epileptic encephalopathy or progressive myoclonus epilepsy (+ 18.4 yr), except for idiopathic generalized epilepsy (IGE). Patients with psychogenic non-epileptic seizures also presented increased brain-PAD. In TLE, interictal psychosis significantly raised brain-PAD by 8.7 years. In conclusion, we observed increased brain aging in most types of epilepsy, which was generally consistent with brain morphological aging results in previous studies. Psychosis may accelerate brain aging in TLE. These findings may suggest abnormal aging mechanisms in epilepsy and comorbid psychotic symptoms.

Using eZIS to Predict Progression from MCI to Dementia in Three Years.

(1) Background: Mild cognitive impairment (MCI) due to Alzheimer's disease (AD) progresses to dementia at a higher annual rate, while other MCIs may remain stable or even improve over time. Discriminating progressive from non-progressive cases of MCI is crucial and challenging. (2) Methods: A retrospective study of individuals with MCI was conducted at a university hospital located in southern Taiwan. The researchers collected demographic data, comorbidities, the scores of cognitive tests, three easy Z-score imaging system (eZIS) indicators (severity, extent, and ratio), Fazekas scale scores, mesial temporal atrophy (MTA) scores, clinical outcomes including deterioration of Cognitive Abilities Screening Instrument, Mini-mental State Examination, Clinical Dementia Rating Sum of Box scores, and the conversion from MCI to dementia. Those who converted to dementia in three years and non-converters were compared by the three eZIS indicators to test the predictive utility, and the clinical outcomes were evaluated by regression and ROC curve analysis. (3) Results: The three eZIS indicators were significantly higher in the group of progressive MCI than in stable MCI. eZIS severity is positively correlated with a deterioration in the scores of the Cognitive Abilities Screening Instrument and Clinical Dementia Rating Sum of Box. eZIS severity is also positively correlated with conversion from MCI to dementia. The AUC for severity is 0.719, and the optimal cutoff value of severity for predicting conversion is 1.22. (4) Conclusions: During three years of follow-up, MCI individuals with greater eZIS severity were significantly associated with worse cognitive assessment scores and a higher conversion rate to dementia.

Comparison of DNA extraction methods for genotyping equine histidine-rich glycoprotein insertion/deletion polymorphisms using oral mucosa swabs and feces.

Previously, we demonstrated unique insertion/deletion polymorphisms of equine histidine-rich glycoprotein (eHRG) with five genotypes composed of 45-bp or 90-bp deletions in the histidine-rich region of eHRG in Thoroughbred horses. Although leukocytes are typically used to collect DNA for genotyping, blood sampling from animals is sometimes difficult and invasive. Moreover, the method for extracting DNA from blood leukocytes involves complicated steps and must be performed soon after blood sampling for sensitive gene analysis. In the present study, we performed eHRG genotyping using DNA, isolated from oral mucosa swabs collected by rubbing the mucosa on the underside of the upper lip of horses and 100 mg of freshly excreted feces obtained by scraping their surface. In the present study, we performed eHRG genotyping using DNA isolated from oral mucosa swabs and feces of horses (18 Thoroughbreds, 17 mixed breeds, 2 warm bloods), and compared the accuracy of this method with that of the method using DNA from leukocytes. The DNA derived from oral mucosa swabs was sufficient in quantity and quality for eHRG genotyping. However, DNA derived from fecal samples requires a more sensitive detection system because of contamination with non-horse DNA, and the test quality is low. Collection of oral mucosa swabs is less invasive than blood sampling; further, oral swabs can be stored for a longer period in a specified high-quality solution. Therefore, collecting DNA samples from oral mucosa swabs is recommended for the genetic analysis of not only horses but also other animals that are not accustomed to humans.

Multimodal imaging analyses in neuromyelitis optica spectrum disorder with or without visual disturbance.

BACKGROUND AND PURPOSE: Neuromyelitis optica spectrum disorder is a demyelinating and inflammatory affliction that often leads to visual disturbance. Various imaging techniques, including free-water imaging, have been used to determine neuroinflammation and degeneration. Therefore, this study aimed at determining multimodal imaging differences between patients with neuromyelitis optica spectrum disorder, especially those with visual disturbance, and healthy controls. MATERIALS AND METHODS: Eighty-five neuromyelitis optica spectrum disorder patients and 89 age- and sex-matched healthy controls underwent 3-T magnetic resonance imaging (MRI). We analyzed adjusted brain-predicted age difference, voxel-based morphometry, and free-water-corrected diffusion tensor imaging (DTI) by tract-based spatial statistics in each patient group (MRI-positive/negative neuromyelitis optica spectrum disorder patients with or without a history of visual disturbance) compared with the healthy control group. RESULTS: MRI-positive neuromyelitis optica spectrum disorder patients exhibited reduced volumes of the bilateral thalamus. Tract-based spatial statistics showed diffuse white matter abnormalities in all DTI metrics in MRI-positive neuromyelitis optica spectrum disorder patients with a history of visual disturbance. In MRI-negative neuromyelitis optica spectrum disorder patients with a history of visual disturbance, voxel-based morphometry showed volume reduction of bilateral thalami and optic radiations, and tract-based spatial statistics revealed significantly lower free-water-corrected fractional anisotropy and higher mean diffusivity in the posterior dominant distributions, including the optic nerve radiation. CONCLUSION: Free-water-corrected DTI and voxel-based morphometry analyses may reflect symptoms of visual disturbance in neuromyelitis optica spectrum disorder.

Histopathological evaluation of the lungs in experimental autoimmune encephalomyelitis.

IMPORTANCE: Experimental autoimmune encephalomyelitis (EAE) is an animal model of multiple sclerosis characterized by inflammation within the central nervous system. However, inflammation in non-neuronal tissues, including the lungs, has not been fully evaluated. OBJECTIVE: This study evaluated the inflammatory response in lungs of EAE mice by immunohistochemistry and histochemistry. METHODS: Eight adult C57BL/6 mice were injected with myelin oligodendrocyte glycoprotein35-55 to induce the EAE. Lungs and spinal cords were sampled from the experimental mice at the time of sacrifice and used for the western blotting, histochemistry, and immunohistochemistry. RESULTS: Histopathological examination revealed inflammatory lesions in the lungs of EAE mice, characterized by infiltration of myeloperoxidase (MPO)- and galectin-3-positive cells, as determined by immunohistochemistry. Increased numbers of collagen fibers in the lungs of EAE mice were confirmed by histopathological analysis. Western blotting revealed significantly elevated level of osteopontin (OPN), cluster of differentiation 44 (CD44), MPO and galectin-3 in the lungs of EAE mice compared with normal controls (p < 0.05). Immunohistochemical analysis revealed both OPN and CD44 in ionized calcium-binding adapter molecule 1-positive macrophages within the lungs of EAE mice. CONCLUSIONS AND RELEVANCE: Taken together, these findings suggest that the increased OPN level in lungs of EAE mice led to inflammation; concurrent increases in proinflammatory factors (OPN and galectin-3) caused pulmonary impairment.

Differential centiloid scale normalization techniques: comparison between hybrid PET/MRI and independently acquired MRI.

OBJECTIVE: Centiloid (CL) scales play an important role in semiquantitative analyses of amyloid-ß (Aß) PET. CLs are derived from the standardized uptake value ratio (SUVR), which needs Aß positron emission tomography (PET) normalization processing. There are two methods to collect the T1-weighted imaging (T1WI) for normalization: (i) anatomical standardization using simultaneously acquired T1WI (PET/MRI), usually adapted to PET images from PET/MRI scanners, and (ii) T1WI from a separate examination (PET + MRI), usually adapted to PET images from PET/CT scanners. This study aimed to elucidate the correlations and differences in CLs between when using the above two T1WI collection methods. METHODS: Among patients who underwent Aß PET/MRI (using 11C-Pittuberg compound B (11C-PiB) or 18F-flutemetamol (18F-FMM)) at our institution from 2015 to 2023, we selected 49 patients who also underwent other additional MRI examinations, including T1WI for anatomic standardization within 3 years. Thirty-one of them underwent 11C-PiB PET/MRI, and 18 participants underwent 18F-FMM PET/MRI. Twenty-five of them, additional MRI acquisition parameters were identical to simultaneous MRI during PET, and 24 participants were different. After normalization using PET/MRI or PET + MRI method each, SUVR was measured using the Global Alzheimer's Association Initiative Network cerebral cortical and striatum Volume of Interest templates (VOI) and whole cerebellum VOI. Subsequently, CLs were calculated using the previously established equations for each Aß PET tracer. RESULTS: Between PET/MRI and PET + MRI methods, CLs correlated linearly in 11C-PiB PET (y = 1.00x - 0.11, R2 = 0.999), 18F-FMM PET (y = 0.97x - 0.12, 0.997), identical additional MRI acquisition (y = 1.00x + 0.33, 0.999), different acquisition (y = 0.98x - 0.43, 0.997), and entire study group (y = 1.00x - 0.24, 0.999). Wilcoxon signed-rank test revealed no significant differences: 11C-PiB (p = 0.49), 18F-FMM (0.08), and whole PET (0.46). However, significant differences were identified in identical acquisition (p = 0.04) and different acquisition (p = 0.02). Bland-Altman analysis documented only a small bias between PET/MRI and PET + MRI in 11C-PiB PET, 18F-FMM PET, identical additional MRI acquisition, different acquisition, and whole PET (- 0.05, 0.67, - 0.30, 0.78, and 0.21, respectively). CONCLUSIONS: Anatomical standardizations using PET/MRI and using PET + MRI can lead to almost equivalent CL. The CL values obtained using PET/MRI or PET + MRI normalization methods are consistent and comparable in clinical studies.

Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging.

Background: Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics. Objective: The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics. Methods: Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics. Results: Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology. Conclusions: This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.

Prediction of Co-Occurrence of Lewy Body Disease with Alzheimer's Disease.

Identifying the coexistence of Lewy body (LB) pathology with Alzheimer's disease (AD) in clinical practice is important in the era of anti-amyloid-ß antibody therapy. However, few studies have predicted the presence of comorbid LB pathology with AD using indicative biomarkers of dementia with Lewy bodies or by collecting detailed clinical symptoms. We report the clinical progression of a 67-year-old patient diagnosed with AD who developed rapid eye movement sleep disorder-like symptoms and transient visual hallucinations 10 years after AD onset and was considered to have comorbid LB pathology based on imaging indicative biomarkers of dementia with Lewy bodies.

Impact of amyloid and tau positivity on longitudinal brain atrophy in cognitively normal individuals.

BACKGROUND: Individuals on the preclinical Alzheimer's continuum, particularly those with both amyloid and tau positivity (A + T +), display a rapid cognitive decline and elevated disease progression risk. However, limited studies exist on brain atrophy trajectories within this continuum over extended periods. METHODS: This study involved 367 ADNI participants grouped based on combinations of amyloid and tau statuses determined through cerebrospinal fluid tests. Using longitudinal MRI scans, brain atrophy was determined according to the whole brain, lateral ventricle, and hippocampal volumes and cortical thickness in AD-signature regions. Cognitive performance was evaluated with the Preclinical Alzheimer's Cognitive Composite (PACC). A generalized linear mixed-effects model was used to examine group × time interactions for these measures. In addition, progression risks to mild cognitive impairment (MCI) or dementia were compared among the groups using Cox proportional hazards models. RESULTS: A total of 367 participants (48 A + T + , 86 A + T - , 63 A - T + , and 170 A - T - ; mean age 73.8 years, mean follow-up 5.1 years, and 47.4% men) were included. For the lateral ventricle and PACC score, the A + T - and A + T + groups demonstrated statistically significantly greater volume expansion and cognitive decline over time than the A - T - group (lateral ventricle: ß = 0.757 cm3/year [95% confidence interval 0.463 to 1.050], P < .001 for A + T - , and ß = 0.889 cm3/year [0.523 to 1.255], P < .001 for A + T + ; PACC: ß = - 0.19 /year [- 0.36 to - 0.02], P = .029 for A + T - , and ß = - 0.59 /year [- 0.80 to - 0.37], P < .001 for A + T +). Notably, the A + T + group exhibited additional brain atrophy including the whole brain (ß = - 2.782 cm3/year [- 4.060 to - 1.504], P < .001), hippocampus (ß = - 0.057 cm3/year [- 0.085 to - 0.029], P < .001), and AD-signature regions (ß = - 0.02 mm/year [- 0.03 to - 0.01], P < .001). Cox proportional hazards models suggested an increased risk of progressing to MCI or dementia in the A + T + group versus the A - T - group (adjusted hazard ratio = 3.35 [1.76 to 6.39]). CONCLUSIONS: In cognitively normal individuals, A + T + compounds brain atrophy and cognitive deterioration, amplifying the likelihood of disease progression. Therapeutic interventions targeting A + T + individuals could be pivotal in curbing brain atrophy, cognitive decline, and disease progression.

Enhancing Cerebral Amyloid Angiopathy-Related Inflammation Diagnosis With PET Using Pittsburgh Compound B.

ABSTRACT: Cerebral amyloid angiopathy-related inflammation is a rare encephalopathy characterized by inflammation against amyloid protein accumulated in cerebral small vessels. A 50-year-old man was presented with a subacute consciousness disorder. Brain MRI revealed high intensity lesions in the white matter of the right parietal and occipital lobes on fluid-attenuated inversion recovery sequences and cerebral microbleeds in the right parietal and occipital lobes on T2*-weighted images. Pittsburgh compound B-PET demonstrated accumulation in the right temporoparietal lobe, confirming a potential diagnosis of probable cerebral amyloid angiopathy-related inflammation without brain biopsy. Steroid pulse therapy was initiated, with good results.

Regioselective Propargylic Suzuki-Miyaura Coupling by SciPROP-Iron Catalyst.

The iron-catalyzed Suzuki-Miyaura cross-coupling of secondary propargyl electrophiles with lithium organoborates has been established. A propyl-bridged bulky bisphosphine ligand, SciPROP-TB, cooperated with the bulky TIPS substituent at the alkyne terminal position to achieve the cross-coupling reaction with exclusive propargylic selectivity. The reaction features high functional group compatibility, regioselectivity, and yield with a broad substrate scope. The reaction of an optically active chiral propargyl bromide proceeds with complete racemization, supporting a mechanism involving propargyl radical formation.

Deep Learning-Driven Estimation of Centiloid Scales from Amyloid PET Images with 11C-PiB and 18F-Labeled Tracers in Alzheimer's Disease.

BACKGROUND: Standard methods for deriving Centiloid scales from amyloid PET images are time-consuming and require considerable expert knowledge. We aimed to develop a deep learning method of automating Centiloid scale calculations from amyloid PET images with 11C-Pittsburgh Compound-B (PiB) tracer and assess its applicability to 18F-labeled tracers without retraining. METHODS: We trained models on 231 11C-PiB amyloid PET images using a 50-layer 3D ResNet architecture. The models predicted the Centiloid scale, and accuracy was assessed using mean absolute error (MAE), linear regression analysis, and Bland-Altman plots. RESULTS: The MAEs for Alzheimer's disease (AD) and young controls (YC) were 8.54 and 2.61, respectively, using 11C-PiB, and 8.66 and 3.56, respectively, using 18F-NAV4694. The MAEs for AD and YC were higher with 18F-florbetaben (39.8 and 7.13, respectively) and 18F-florbetapir (40.5 and 12.4, respectively), and the error rate was moderate for 18F-flutemetamol (21.3 and 4.03, respectively). Linear regression yielded a slope of 1.00, intercept of 1.26, and R2 of 0.956, with a mean bias of -1.31 in the Centiloid scale prediction. CONCLUSIONS: We propose a deep learning means of directly predicting the Centiloid scale from amyloid PET images in a native space. Transferring the model trained on 11C-PiB directly to 18F-NAV4694 without retraining was feasible.

Comparison of consistency in centiloid scale among different analytical methods in amyloid PET: the CapAIBL, VIZCalc, and Amyquant methods.

OBJECTIVE: The Centiloid (CL) scale is a standardized measure for quantifying amyloid deposition in amyloid positron emission tomography (PET) imaging. We aimed to assess the agreement among 3 CL calculation methods: CapAIBL, VIZCalc, and Amyquant. METHODS: This study included 192 participants (mean age: 71.5 years, range: 50-87 years), comprising 55 with Alzheimer's disease, 65 with mild cognitive impairment, 13 with non-Alzheimer's dementia, and 59 cognitively normal participants. All the participants were assessed using the three CL calculation methods. Spearman's rank correlation, linear regression, Friedman tests, Wilcoxon signed-rank tests, and Bland-Altman analysis were employed to assess data correlations, linear associations, method differences, and systematic bias, respectively. RESULTS: Strong correlations (rho = 0.99, p < .001) were observed among the CL values calculated using the three methods. Scatter plots and regression lines visually confirmed these strong correlations and met the validation criteria. Despite the robust correlations, a significant difference in CL value between CapAIBL and Amyquant was observed (36.1 ± 39.7 vs. 34.9 ± 39.4; p < .001). In contrast, no significant differences were found between CapAIBL and VIZCalc or between VIZCalc and Amyquant. The Bland-Altman analysis showed no observable systematic bias between the methods. CONCLUSIONS: The study demonstrated strong agreement among the three methods for calculating CL values. Despite minor variations in the absolute values of the Centiloid scores obtained using these methods, the overall agreement suggests that they are interchangeable.

Harmonizing multisite data with the ComBat method for enhanced Parkinson's disease diagnosis via DAT-SPECT.

Background: Dopamine transporter single-photon emission computed tomography (DAT-SPECT) is a crucial tool for evaluating patients with Parkinson's disease (PD). However, its implication is limited by inter-site variability in large multisite clinical trials. To overcome the limitation, a conventional prospective correction method employs linear regression with phantom scanning, which is effective yet available only in a prospective manner. An alternative, although relatively underexplored, involves retrospective modeling using a statistical method known as "combatting batch effects when combining batches of gene expression microarray data" (ComBat). Methods: We analyzed DAT-SPECT-specific binding ratios (SBRs) derived from 72 healthy older adults and 81 patients with PD registered in four clinical sites. We applied both the prospective correction and the retrospective ComBat correction to the original SBRs. Next, we compared the performance of the original and two corrected SBRs to differentiate the PD patients from the healthy controls. Diagnostic accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results: The original SBRs were 6.13 ± 1.54 (mean ± standard deviation) and 2.03 ± 1.41 in the control and PD groups, respectively. After the prospective correction, the mean SBRs were 6.52 ± 1.06 and 2.40 ± 0.99 in the control and PD groups, respectively. After the retrospective ComBat correction, the SBRs were 5.25 ± 0.89 and 2.01 ± 0.73 in the control and PD groups, respectively, resulting in substantial changes in mean values with fewer variances. The original SBRs demonstrated fair performance in differentiating PD from controls (Hedges's g = 2.76; AUC-ROC = 0.936). Both correction methods improved discrimination performance. The ComBat-corrected SBR demonstrated comparable performance (g = 3.99 and AUC-ROC = 0.987) to the prospectively corrected SBR (g = 4.32 and AUC-ROC = 0.992) for discrimination. Conclusion: Although we confirmed that SBRs fairly discriminated PD from healthy older adults without any correction, the correction methods improved their discrimination performance in a multisite setting. Our results support the utility of harmonization methods with ComBat for consolidating SBR-based diagnosis or stratification of PD in multisite studies. Nonetheless, given the substantial changes in the mean values of ComBat-corrected SBRs, caution is advised when interpreting them.

Glymphatic System Activity and Brain Morphology in Patients With Psychogenic Non-epileptic Seizures.

BACKGROUND: To clarify the neural correlates underlying psychogenic non-epileptic seizures (PNES), we compared glymphatic system activity between patients with PNES and healthy participants using diffusion tensor imaging (DTI)-analysis along the perivascular space (ALPS) method. METHODS: The DTI scans were acquired from 16 patients with PNES and 25 healthy participants. We computed the DTI-ALPS index as an index of glymphatic system function and estimated the disease-related changes in the DTI-ALPS index and brain structures in PNES patients. RESULTS: There were no significant differences in the DTI-ALPS index between patients with PNES and healthy participants. On the other hand, patients with PNES had decreased fractional anisotropy values in the bilateral posterior cingula, a higher mean diffusivity value around the left insula, and a lower gray matter volume in the bilateral amygdalae compared with healthy participants. CONCLUSIONS: Patients with PNES exhibited an impairment of white matter integrity and a reduction of gray matter volume, but no glymphatic-system changes. These findings will play a significant role in our comprehension of this complex illness.

Eugenol alleviates the symptoms of experimental autoimmune encephalomyelitis in mice by suppressing inflammatory responses.

Eugenol is a principal compound in essential clove oil, known for its anti-inflammatory and antioxidant properties. While recent studies have demonstrated its neuroprotective effects on central nervous system (CNS) injuries, such as brain ischemia/reperfusion injuries, but its potential impact on multiple sclerosis (MS), an autoimmune disease of the CNS, has not yet been explored. We evaluated the therapeutic effects of eugenol on experimental autoimmune encephalomyelitis (EAE), an established animal model of MS. EAE was induced in C57BL/6 mice using the myelin oligodendrocyte glycoprotein (MOG)35-55 peptide. Clinical symptoms, including paralysis, were monitored daily, and levels of pro-inflammatory mediators were evaluated using real-time quantitative polymerase chain reaction, Western blot analyses, and immunohistochemistry. Daily oral administration of eugenol to MOG-induced EAE mice led to a notable decline in the severity of clinical symptoms. Eugenol inhibited EAE-related immune cell infiltration and the production of pro-inflammatory mediators. Histological examinations confirmed its ability to mitigate inflammation and demyelination in the spinal cord post-EAE induction. Eugenol alleviates neuroinflammation in the spinal cords of EAE-induced mice, primarily through anti-inflammatory action.

Brain Abnormalities in Becker Muscular Dystrophy: Evaluation by Voxel-Based DTI and Morphometric Analysis.

BACKGROUND AND PURPOSE: Although various neuropsychological problems in Becker muscular dystrophy have attracted attention, there have been few related neuroimaging studies. We investigated brain abnormalities in patients with Becker muscular dystrophy using 3D T1WI and DTI. MATERIALS AND METHODS: MR images were obtained for 30 male patients and 30 age-matched healthy male controls. We classified patients into Dp140+ and Dp140- subgroups based on their predicted dystrophin Dp140 isoform expression and performed voxel-based comparisons of gray and white matter volumes and DTI metrics among the patients, patient subgroups, and controls. ROI-based DTI analyses were also performed. RESULTS: Significantly decreased fractional anisotropy was observed in the left planum temporale and right superior parietal lobule compared between the Becker muscular dystrophy and control groups. In the Dp140- subgroup, decreased fractional anisotropy was observed in the left planum temporale, but no significant changes were seen in the Dp140+ subgroup. The ROI-based analysis obtained the same results. No significant differences were evident in the gray or white matter volumes or the DTI metrics other than fractional anisotropy between the groups. CONCLUSIONS: A DTI metric analysis is useful to detect white-matter microstructural abnormalities in Becker muscular dystrophy that may be affected by the Dp140 isoform expression.