Subthreshold amyloid deposition, cerebral small vessel disease, and functional brain network disruption in delayed cognitive decline after stroke.

Background: Although its incidence is relatively low, delayed-onset post-stroke cognitive decline (PSCD) may offer valuable insights into the "vascular contributions to cognitive impairment and dementia," particularly concerning the roles of vascular and neurodegenerative mechanisms. We postulated that the functional segregation observed during post-stroke compensation could be disrupted by underlying amyloid pathology or cerebral small vessel disease (cSVD), leading to delayed-onset PSCD. Methods: Using a prospective stroke registry, we identified patients who displayed normal cognitive function at baseline evaluation within a year post-stroke and received at least one subsequent assessment. Patients suspected of pre-stroke cognitive decline were excluded. Decliners [defined by a decrease of ≥3 Mini-Mental State Examination (MMSE) points annually or an absolute drop of ≥5 points between evaluations, confirmed with detailed neuropsychological tests] were compared with age- and stroke severity-matched non-decliners. Index-stroke MRI, resting-state functional MRI, and 18F-florbetaben PET were used to identify cSVD, functional network attributes, and amyloid deposits, respectively. PET data from age-, sex-, education-, and apolipoprotein E-matched stroke-free controls within a community-dwelling cohort were used to benchmark amyloid deposition. Results: Among 208 eligible patients, 11 decliners and 10 matched non-decliners were identified over an average follow-up of 5.7 years. No significant differences in cSVD markers were noted between the groups, except for white matter hyperintensities (WMHs), which were strongly linked with MMSE scores among decliners (rho = -0.85, p < 0.01). Only one decliner was amyloid-positive, yet subthreshold PET standardized uptake value ratios (SUVR) in amyloid-negative decliners inversely correlated with final MMSE scores (rho = -0.67, p = 0.04). Decliners exhibited disrupted modular structures and more intermingled canonical networks compared to non-decliners. Notably, the somato-motor network's system segregation corresponded with the decliners' final MMSE (rho = 0.67, p = 0.03) and was associated with WMH volume and amyloid SUVR. Conclusion: Disruptions in modular structures, system segregation, and inter-network communication in the brain may be the pathophysiological underpinnings of delayed-onset PSCD. WMHs and subthreshold amyloid deposition could contribute to these disruptions in functional brain networks. Given the limited number of patients and potential residual confounding, our results should be considered hypothesis-generating and need replication in larger cohorts in the future.

Sex Differences in Frequency, Severity, and Distribution of Cerebral Microbleeds.

Importance: Cerebral small vessel disease (SVD) is associated with various cerebrovascular outcomes, but data on sex differences in SVD are scarce. Objective: To investigate whether the frequency, severity, and distribution of cerebral microbleeds (CMB), other SVD markers on magnetic resonance imaging (MRI), and outcomes differ by sex. Design, Setting, and Participants: This cohort study used pooled individual patient data from the Microbleeds International Collaborative Network, including patients from 38 prospective cohort studies in 18 countries between 2000 and 2018, with clinical follow-up of at least 3 months (up to 5 years). Participants included patients with acute ischemic stroke or transient ischemic attack with available brain MRI. Data were analyzed from April to December 2023. Main Outcomes and Measures: Outcomes of interest were presence of CMB, lacunes, and severe white matter hyperintensities determined on MRI. Additionally, mortality, recurrent ischemic stroke, and intracranial hemorrhage during follow-up were assessed. Multivariable random-effects logistic regression models, Cox regression, and competing risk regression models were used to investigate sex differences in individual SVD markers, risk of recurrent cerebrovascular events, and death. Results: A total of 20 314 patients (mean [SD] age, 70.1 [12.7] years; 11 721 [57.7%] male) were included, of whom 5649 (27.8%) had CMB. CMB were more frequent in male patients, and this was consistent throughout different age groups, locations, and in multivariable models (female vs male adjusted odds ratio [aOR], 0.86; 95% CI, 0.80-0.92; P < .001). Female patients had fewer lacunes (aOR, 0.82; 95% CI, 0.74-0.90; P < .001) but a higher prevalence of severe white matter hyperintensities (aOR, 1.10; 95% CI, 1.01-1.20; P = .04) compared with male patients. A total of 2419 patients (11.9%) died during a median (IQR) follow-up of 1.4 (0.7-2.5) years. CMB presence was associated with a higher risk of mortality in female patients (hazard ratio, 1.15; 95% CI, 1.02-1.31), but not male patients (hazard ratio, 0.95; 95% CI, 0.84-1.07) (P for interaction = .01). A total of 1113 patients (5.5%) had recurrent ischemic stroke, and 189 patients (0.9%) had recurrent intracranial hemorrhage, with no sex differences. Conclusions and Relevance: This cohort study using pooled individual patient data found varying frequencies of individual SVD markers between female and male patients, indicating potential pathophysiological differences in manifestation and severity of SVD. Further research addressing differences in pathomechanisms and outcomes of SVD between female and male patients is required.

Automated Idiopathic Normal-Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis.

BACKGROUND AND PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) is reversible dementia, that is underdiagnosed. The purpose of this study was to develop an automated diagnostic method for iNPH using artificial intelligence techniques with a T1-weighted MRI scan. MATERIALS AND METHODS: We quantified iNPH, Parkinson's disease, Alzheimer's disease, and healthy control patients on T1-weighted 3D brain MRI scans using 452 scans for training and 110 scans for testing. Automatic component measurement algorithms were developed for Evans' index, Sylvian fissure enlargement, high-convexity tightness, callosal angle, and normalized lateral ventricle volume. XGBoost models were trained for both automated measurements and manual labels for iNPH prediction. RESULTS: A total of 452 patients (200 men; mean age ± standard deviation, 73.2 ± 6.5 years) were included in the training set. Of the 452 patients, 111 (24.6%) had iNPH. We obtained AUC values of 0.956 for automatically measured high-convexity tightness and 0.830 for Sylvian fissure enlargement. Intra-class correlation values of 0.824 for the callosal angle and 0.924 for Evans' index were measured. Using the decision tree of the XGBoost model, the model trained on manual labels obtained an average cross-validation AUC of 0.988 on the training set and 0.938 on the unseen test set, while the fully automated model obtained a cross-validation AUC of 0.983 and an unseen test AUC of 0.936. CONCLUSION: We demonstrated a machine-learning algorithm capable of diagnosing iNPH from a 3D T1-weighted MRI scan that is robust to the failure. We propose a method to scan large numbers of 3D T1-weighted MRI scans with minimal human intervention, making possible large-scale iNPH screening. ABBREVIATIONS: iNPH = idiopathic normal-pressure hydrocephalus; PD = Parkinson's disease; AD = Alzheimer's disease; HC = healthy control; CSF = cerebrospinal fluid; DESH = disproportionately enlarged subarachnoid space hydrocephalus; 3D = three-dimensional.

Amyloid-Related Imaging Abnormalities in the Era of Anti-Amyloid Beta Monoclonal Antibodies for Alzheimer's Disease: Recent Updates on Clinical and Imaging Features and MRI Monitoring.

Recent advancements in Alzheimer's disease treatment have focused on the elimination of amyloid-beta (Aß) plaque, a hallmark of the disease. Monoclonal antibodies such as lecanemab and donanemab can alter disease progression by binding to different forms of Aß aggregates. However, these treatments raise concerns about adverse effects, particularly amyloid-related imaging abnormalities (ARIA). Careful assessment of safety, especially regarding ARIA, is crucial. ARIA results from treatment-related disruption of vascular integrity and increased vascular permeability, leading to the leakage of proteinaceous fluid (ARIA-E) and heme products (ARIA-H). ARIA-E indicates treatment-induced edema or sulcal effusion, while ARIA-H indicates treatment-induced microhemorrhage or superficial siderosis. The minimum recommended magnetic resonance imaging sequences for ARIA assessment are T2-FLAIR, T2* gradient echo (GRE), and diffusion-weighted imaging (DWI). T2-FLAIR and T2* GRE are necessary to detect ARIA-E and ARIA-H, respectively. DWI plays a role in differentiating ARIA-E from acute to subacute infarcts. Physicians, including radiologists, must be familiar with the imaging features of ARIA, the appropriate imaging protocol for the ARIA workup, and the reporting of findings in clinical practice. This review aims to describe the clinical and imaging features of ARIA and suggest points for the timely detection and monitoring of ARIA in clinical practice.

Effects of strategic white matter hyperintensities of cholinergic pathways on basal forebrain volume in patients with amyloid-negative neurocognitive disorders.

BACKGROUND: The cholinergic neurotransmitter system is crucial to cognitive function, with the basal forebrain (BF) being particularly susceptible to Alzheimer's disease (AD) pathology. However, the interaction of white matter hyperintensities (WMH) in cholinergic pathways and BF atrophy without amyloid pathology remains poorly understood. METHODS: We enrolled patients who underwent neuropsychological tests, magnetic resonance imaging, and 18F-florbetaben positron emission tomography due to cognitive impairment at the teaching university hospital from 2015 to 2022. Among these, we selected patients with negative amyloid scans and additionally excluded those with Parkinson's dementia that may be accompanied by BF atrophy. The WMH burden of cholinergic pathways was quantified by the Cholinergic Pathways Hyperintensities Scale (CHIPS) score, and categorized into tertile groups because the CHIPS score did not meet normal distribution. Segmentation of the BF on volumetric T1-weighted MRI was performed using FreeSurfer, then was normalized for total intracranial volume. Multivariable regression analysis was performed to investigate the association between BF volumes and CHIPS scores. RESULTS: A total of 187 patients were enrolled. The median CHIPS score was 12 [IQR 5.0; 24.0]. The BF volume of the highest CHIPS tertile group (mean ± SD, 3.51 ± 0.49, CHIPSt3) was significantly decreased than those of the lower CHIPS tertile groups (3.75 ± 0.53, CHIPSt2; 3.83 ± 0.53, CHIPSt1; P = 0.02). In the univariable regression analysis, factors showing significant associations with the BF volume were the CHIPSt3 group, age, female, education, diabetes mellitus, smoking, previous stroke history, periventricular WMH, and cerebral microbleeds. In multivariable regression analysis, the CHIPSt3 group (standardized beta [ßstd] = -0.25, P = 0.01), female (ßstd = 0.20, P = 0.04), and diabetes mellitus (ßstd = -0.22, P < 0.01) showed a significant association with the BF volume. Sensitivity analyses showed a negative correlation between CHIPS score and normalized BF volume, regardless of WMH severity. CONCLUSIONS: We identified a significant correlation between strategic WMH burden in the cholinergic pathway and BF atrophy independently of amyloid positivity and WMH severity. These results suggest a mechanism of cholinergic neuronal loss through the dying-back phenomenon and provide a rationale that strategic WMH assessment may help identify target groups that may benefit from acetylcholinesterase inhibitor treatment.

Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke.

Introduction: Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke. Materials and methods: Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke. Results: Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only. Conclusion: This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.

Architecture and anatomy of executive processes: evidence from verbal fluency and Trail Making Test in 2009 stroke patients.

OBJECTIVES: The few voxel-wise lesion-symptom mapping (VLSM) studies aimed at identifying the anatomy of executive function are limited by the absence of a model and by small populations. Using Trail Making Test (TMT) and verbal fluency and a model of their architectures, our objective was to identify the key structures underlying two major executive processes, set-shifting and strategic word search. METHODS: We applied a validated VLSM analysis to harmonized cognitive and imaging data from 2009 ischemic stroke patients as a part of the Meta VCI Map consortium. All contrast analyses used an adjusted threshold with 2000 Freedman-Lane permutations (p ≤ 0.05). RESULTS: The TMT parts A and B were associated with structures involved in visual-spatial processing, the motor system, the frontal lobes, and their subcortical connections. Set-shifting depended on the left dorsomedial frontal region. Both semantic and phonemic fluency tests depended on verbal output abilities and processing speed with similar slopes in different languages. The strategic search process depended on Broca's area, F2 and related tracts, temporal and deep regions. Lastly, the lesion map of set-shifting did not overlap with those of strategic word search processes. INTERPRETATION: Our results identify the anatomical substrates of two main executive processes, revealing that they represent only a specific subpart of previously reported structures. Finally, our results indicate that executive functions depend on several specific, anatomically separable executive processes mainly operating in various parts of the frontal lobes.

Deep Learning-Based Automatic Classification of Ischemic Stroke Subtype Using Diffusion-Weighted Images.

BACKGROUND AND PURPOSE: Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. METHODS: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. RESULTS: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%-60.7% and 73.7%-74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen's kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. CONCLUSION: Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.

Bayesian modelling disentangles language versus executive control disruption in stroke.

Stroke is the leading cause of long-term disability worldwide. Incurred brain damage can disrupt cognition, often with persisting deficits in language and executive capacities. Yet, despite their clinical relevance, the commonalities and differences between language versus executive control impairments remain under-specified. To fill this gap, we tailored a Bayesian hierarchical modelling solution in a largest-of-its-kind cohort (1080 patients with stroke) to deconvolve language and executive control with respect to the stroke topology. Cognitive function was assessed with a rich neuropsychological test battery including global cognitive function (tested with the Mini-Mental State Exam), language (assessed with a picture naming task), executive speech function (tested with verbal fluency tasks), executive control functions (Trail Making Test and Digit Symbol Coding Task), visuospatial functioning (Rey Complex Figure), as well as verbal learning and memory function (Soul Verbal Learning). Bayesian modelling predicted interindividual differences in eight cognitive outcome scores three months after stroke based on specific tissue lesion topologies. A multivariate factor analysis extracted four distinct cognitive factors that distinguish left- and right-hemispheric contributions to ischaemic tissue lesions. These factors were labelled according to the neuropsychological tests that had the strongest factor loadings: One factor delineated language and general cognitive performance and was mainly associated with damage to left-hemispheric brain regions in the frontal and temporal cortex. A factor for executive control summarized mental flexibility, task switching and visual-constructional abilities. This factor was strongly related to right-hemispheric brain damage of posterior regions in the occipital cortex. The interplay of language and executive control was reflected in two distinct factors that were labelled as executive speech functions and verbal memory. Impairments on both factors were mainly linked to left-hemispheric lesions. These findings shed light onto the causal implications of hemispheric specialization for cognition; and make steps towards subgroup-specific treatment protocols after stroke.

Novel role of LLGL2 silencing in autophagy: reversing epithelial-mesenchymal transition in prostate cancer.

PURPOSE: Prostate cancer (PCa) is a major urological disease that is associated with significant morbidity and mortality in men. LLGL2 is the mammalian homolog of Lgl. It acts as a tumor suppressor in breast and hepatic cancer. However, the role of LLGL2 and the underlying mechanisms in PCa have not yet been elucidated. Here, we investigate the role of LLGL2 in the regulation of epithelial-mesenchymal transition (EMT) in PCa through autophagy in vitro and in vivo. METHODS: PC3 cells were transfected with siLLGL2 or plasmid LLGL2 and autophagy was examined. Invasion, migration, and wound healing were assessed in PC3 cells under autophagy regulation. Tumor growth was evaluated using a shLLGL2 xenograft mouse model. RESULTS: In patients with PCa, LLGL2 levels were higher with defective autophagy and increased EMT. Our results showed that the knockdown of LLGL2 induced autophagy flux by upregulating Vps34 and ATG14L. LLGL2 knockdown inhibits EMT by upregulating E-cadherin and downregulating fibronectin and α-SMA. The pharmacological activation of autophagy by rapamycin suppressed EMT, and these effects were reversed by 3-methyladenine treatment. Interestingly, in a shLLGL2 xenograft mouse model, tumor size and EMT were decreased, which were improved by autophagy induction and worsened by autophagy inhibition. CONCLUSION: Defective expression of LLGL2 leads to attenuation of EMT due to the upregulation of autophagy flux in PCa. Our results suggest that LLGL2 is a novel target for alleviating PCa via the regulation of autophagy.

Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients.

BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear. AIMS: We determined if WMH in strategic white matter tracts explain cognitive performance after stroke. METHODS: Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus. RESULTS: The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume. CONCLUSION: These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH. DATA ACCESS STATEMENT: The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.

EarlyTect BCD, a Streamlined PENK Methylation Test in Urine DNA, Effectively Detects Bladder Cancer in Patients with Hematuria.

The current noninvasive diagnostic approaches for detecting bladder cancer (BC) often exhibit limited clinical performance, especially for the initial diagnosis. This study aims to evaluate the validity of a streamlined urine-based PENK methylation test called EarlyTect BCD in detecting BC in patients with hematuria scheduled for cystoscopy in Korean and American populations. The test seamlessly integrates two steps, linear target enrichment and quantitative methylation-specific PCR within a single closed tube. The detection limitation of the test was approximately two genome copies of methylated PENK per milliliter of urine. In the retrospective training set (n = 105), an optimal cutoff value was determined to distinguish BC from non-BC, resulting in a sensitivity of 87.3% and a specificity of 95.2%. In the prospective validation set (n = 210, 122 Korean and 88 American patients), the overall sensitivity for detecting all stages of BC was 81.0%, with a specificity of 91.5% and an area under the curve value of 0.889. There was no significant difference between the two groups. The test achieved a sensitivity of 100% in detecting high-grade Ta and higher stages of BC. The negative predictive value of the test was 97.7%, and the positive predictive value was 51.5%. The findings of this study demonstrate that EarlyTect BCD is a highly effective noninvasive diagnostic tool for identifying BC among patients with hematuria.

Efficacy and Safety of Low-Dose Intravesical OnabotulinumtoxinA Injections in Female Patients With Detrusor Overactivity With Detrusor Underactivity.

PURPOSE: We assessed the effectiveness and safety of using intravesical onabotulinumtoxinA (onabotA; BOTOX) injection with a low dose (75 units) for treating urinary storage symptoms in patients with detrusor overactivity with detrusor underactivity (DODU) compared to using the standard 100 units of onabotA in patients with overactive bladder (OAB). METHODS: This ambidirectional study included 121 female patients who received intravesical onabotA injections at our hospitals. A total of 87 patients with OAB and 34 patients with DODU were reviewed using a 3-day voiding diary, uroflowmetry, and questionnaires including the International Prostate Symptom Score (IPSS), Overactive Bladder Symptom Score, and Patient Perception of Bladder Condition. Patients were evaluated at baseline, within 2 weeks of treatment, and beyond 3 months after treatment. RESULTS: Questionnaire scores of the DODU group demonstrated significant improvement in the short term, with a subsequent decline, but an overall improvement compared to baseline in the long term. Notably, the DODU group exhibited enhanced IPSS voiding scores after the treatment. In the OAB group, most questionnaire scores, excluding the IPSS voiding score, showed significant posttreatment improvement, which was sustained to some extent in the long term. Voiding diary parameters related to storage symptoms were enhanced in both groups. The maximum and mean flow rates decreased in the OAB group but increased in the DODU group, particularly in the short term (P=0.000). The postvoid residual volume increased in both groups after posttreatment, with a mitigated change in the long term. Safety assessments revealed manageable adverse events in both groups with comparable frequencies. CONCLUSION: Low-dose intravesical onabotA for DODU demonstrated a relatively shorter duration of efficacy than OAB. Nonetheless, the treatment improved both storage and voiding symptoms in patients with DODU without significant adverse effects.

Impact of the COVID-19 pandemic on mortality and loss to follow-up among patients with dementia receiving anti-dementia medications.

The coronavirus disease 2019 (COVID-19) pandemic has profoundly impacted vulnerable groups, such as patients with dementia. We examined changes in mortality and loss to follow-up in patients with dementia using data from the Korean National Health Insurance Service research database. Patients with dementia who visited a medical institution with a recorded dementia-related diagnostic code, including Alzheimer's disease, and who received anti-dementia medication between February 2018 and January 2020 were included in this study. We divided patients with dementia receiving anti-dementia medications into two cohorts: those newly diagnosed with dementia between February 2018 and January 2019 (n = 62,631) and those diagnosed between February 2019 and January 2020 (n = 54,494). Then, we conducted a one-year follow-up of their records, tracking the cohort diagnosed between February 2018 and January 2019 from February 2019 to January 2020, as well as the cohort diagnosed between February 2019 and January 2020 from February 2020 to January 2021. There was a significant increase in follow-up loss among patients newly diagnosed with dementia during the COVID-19 outbreak, from 42.04% in 2019 to 45.89% in 2020. Female sex, younger age, fewer comorbidities, diagnosis of dementia at the Department of Neurology or Psychiatry, and higher income were associated with decreased follow-up loss and mortality. This study highlights the importance of paying extra attention to patients with dementia receiving anti-dementia medications, particularly during pandemics, given their increased risk of loss to follow-up.

Development of statistical auto-segmentation method for diffusion restriction gray matter lesions in patients with newly diagnosed sporadic Creutzfeldt-Jakob disease.

Quantification of diffusion restriction lesions in sporadic Creutzfeldt-Jakob disease (sCJD) may provide information of the disease burden. We aim to develop an automatic segmentation model for sCJD and to evaluate the volume of disease extent as a prognostic marker for overall survival. Fifty-six patients (mean age ± SD, 61.2 ± 9.9 years) were included from February 2000 to July 2020. A threshold-based segmentation was used to obtain abnormal signal intensity masks. Segmented volumes were compared with the visual grade. The Dice similarity coefficient was calculated to measure the similarity between the automatic vs. manual segmentation. Cox proportional hazards regression analysis was performed to evaluate the volume of disease extent as a prognostic marker. The automatic segmentation showed good correlation with the visual grading. The cortical lesion volumes significantly increased as the visual grade aggravated (extensive: 112.9 ± 73.2; moderate: 45.4 ± 30.4; minimal involvement: 29.6 ± 18.1 mm3) (P < 0.001). The deep gray matter lesion volumes were significantly higher for positive than for negative involvement of the deep gray matter (5.6 ± 4.6 mm3 vs. 1.0 ± 1.3 mm3, P < 0.001). The mean Dice similarity coefficients were 0.90 and 0.94 for cortical and deep gray matter lesions, respectively. However, the volume of disease extent was not associated with worse overall survival (cortical extent: P = 0.07; deep gray matter extent: P = 0.12).

The Usefulness of 18F-FDG PET to Differentiate Subtypes of Dementia: The Systematic Review and Meta-Analysis.

Background and Purpose: Dementia subtypes, including Alzheimer's dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods: A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results: From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88-0.98) and specificity was 0.84 (95% CI, 0.70-0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70-0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80-0.91) and the specificity was 0.88 (95% CI, 0.80-0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions: 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.

Clinical Associations and Prognostic Value of MRI-Visible Perivascular Spaces in Patients With Ischemic Stroke or TIA: A Pooled Analysis

BACKGROUND AND OBJECTIVES: Visible perivascular spaces are an MRI marker of cerebral small vessel disease and might predict future stroke. However, results from existing studies vary. We aimed to clarify this through a large collaborative multicenter analysis. METHODS: We pooled individual patient data from a consortium of prospective cohort studies. Participants had recent ischemic stroke or transient ischemic attack (TIA), underwent baseline MRI, and were followed up for ischemic stroke and symptomatic intracranial hemorrhage (ICH). Perivascular spaces in the basal ganglia (BGPVS) and perivascular spaces in the centrum semiovale (CSOPVS) were rated locally using a validated visual scale. We investigated clinical and radiologic associations cross-sectionally using multinomial logistic regression and prospective associations with ischemic stroke and ICH using Cox regression. RESULTS: We included 7,778 participants (mean age 70.6 years; 42.7% female) from 16 studies, followed up for a median of 1.44 years. Eighty ICH and 424 ischemic strokes occurred. BGPVS were associated with increasing age, hypertension, previous ischemic stroke, previous ICH, lacunes, cerebral microbleeds, and white matter hyperintensities. CSOPVS showed consistently weaker associations. Prospectively, after adjusting for potential confounders including cerebral microbleeds, increasing BGPVS burden was independently associated with future ischemic stroke (versus 0-10 BGPVS, 11-20 BGPVS: HR 1.19, 95% CI 0.93-1.53; 21+ BGPVS: HR 1.50, 95% CI 1.10-2.06; p = 0.040). Higher BGPVS burden was associated with increased ICH risk in univariable analysis, but not in adjusted analyses. CSOPVS were not significantly associated with either outcome. DISCUSSION: In patients with ischemic stroke or TIA, increasing BGPVS burden is associated with more severe cerebral small vessel disease and higher ischemic stroke risk. Neither BGPVS nor CSOPVS were independently associated with future ICH.

Mucosal TLR5 activation controls healthspan and longevity.

Addressing age-related immunological defects through therapeutic interventions is essential for healthy aging, as the immune system plays a crucial role in controlling infections, malignancies, and in supporting tissue homeostasis and repair. In our study, we show that stimulating toll-like receptor 5 (TLR5) via mucosal delivery of a flagellin-containing fusion protein effectively extends the lifespan and enhances the healthspan of mice of both sexes. This enhancement in healthspan is evidenced by diminished hair loss and ocular lens opacity, increased bone mineral density, improved stem cell activity, delayed thymic involution, heightened cognitive capacity, and the prevention of pulmonary lung fibrosis. Additionally, this fusion protein boosts intestinal mucosal integrity by augmenting the surface expression of TLR5 in a certain subset of dendritic cells and increasing interleukin-22 (IL-22) secretion. In this work, we present observations that underscore the benefits of TLR5-dependent stimulation in the mucosal compartment, suggesting a viable strategy for enhancing longevity and healthspan.

Novel role of LLGL2 silencing in autophagy: reversing epithelial-mesenchymal transition in prostate cancer

Purpose Prostate cancer (PCa) is a major urological disease that is associated with significant morbidity and mortality in men. LLGL2 is the mammalian homolog of Lgl. It acts as a tumor suppressor in breast and hepatic cancer. However, the role of LLGL2 and the underlying mechanisms in PCa have not yet been elucidated. Here, we investigate the role of LLGL2 in the regulation of epithelial-mesenchymal transition (EMT) in PCa through autophagy in vitro and in vivo. Methods PC3 cells were transfected with siLLGL2 or plasmid LLGL2 and autophagy was examined. Invasion, migration, and wound healing were assessed in PC3 cells under autophagy regulation. Tumor growth was evaluated using a shLLGL2 xenograft mouse model. Results In patients with PCa, LLGL2 levels were higher with defective autophagy and increased EMT. Our results showed that the knockdown of LLGL2 induced autophagy flux by upregulating Vps34 and ATG14L. LLGL2 knockdown inhibits EMT by upregulating E-cadherin and downregulating fibronectin and α-SMA. The pharmacological activation of autophagy by rapamycin suppressed EMT, and these effects were reversed by 3-methyladenine treatment. Interestingly, in a shLLGL2 xenograft mouse model, tumor size and EMT were decreased, which were improved by autophagy induction and worsened by autophagy inhibition. Conclusion Defective expression of LLGL2 leads to attenuation of EMT due to the upregulation of autophagy flux in PCa. Our results suggest that LLGL2 is a novel target for alleviating PCa via the regulation of autophagy.

Corrigendum: Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg.

[This corrects the article DOI: 10.3389/fneur.2023.1221892.].