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Introduction: Alzheimer's disease (AD) prevalence has increased in the last century which can be attributed to increased lifespan, but environment is also important. Exposure to artificial light at night is one environmental factor that may influence AD. Methods: This study evaluated the relationship between outdoor nighttime light exposure and AD prevalence in the United States using satellite acquired outdoor nighttime light intensity and Medicare data. Results: Higher outdoor nighttime light was associated with higher prevalence of AD. While atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke were associated more strongly with AD prevalence than nighttime light intensity, nighttime light was more strongly associated with AD prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity. Startlingly, nighttime light exposure more strongly associated with AD prevalence in those under the age of 65 than any other disease factor examined. Discussion: These data suggest light exposure at night may influence AD, but additional studies are needed. [ABSTRACT FROM AUTHOR]

Identifying disease-specific imaging features of idiopathic Normal Pressure Hydrocephalus (iNPH) is crucial to develop accurate diagnoses, although the abnormal brain anatomy of patients with iNPH creates challenges in neuroimaging analysis. We quantified cortical thickness and volume using FreeSurfer 7.3.2 in 19 patients with iNPH, 28 patients with Alzheimer's disease (AD), and 30 healthy controls (HC). We noted the frequent need for manual correction of the automated segmentation in iNPH and examined the effect of correction on the results. We identified statistically significant higher proportion of volume changes associated with manual edits in individuals with iNPH compared to both HC and patients with AD. Changes in cortical thickness and volume related to manual correction were also partly correlated with the severity of radiological features of iNPH. We highlight the challenges posed by the abnormal anatomy in iNPH when conducting neuroimaging analysis and emphasise the importance of quality checking and correction in this clinical population. [ABSTRACT FROM AUTHOR]

The editorial discusses the role of noncoding RNAs (ncRNAs) in neurodegenerative disorders (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). Various types of ncRNAs, including piRNAs, miRNAs, lncRNAs, circRNAs, and ceRNAs, are explored in relation to NDs, offering insights into molecular mechanisms and potential therapeutic targets. The research highlights the importance of ncRNAs as biomarkers and therapeutic tools in understanding and treating NDs, emphasizing the need for further research and development in this area. [Extracted from the article]

Background: Dementia with Lewy bodies (DLB) can be difficult to distinguish from Alzheimer's disease (AD) and Parkinson's disease dementia (PDD) at different stages of its progression due to some overlaps in the clinical and neuropathological presentation of these conditions compared with DLB. Metallomic changes have already been observed in the AD and PDD brain--including widespread decreases in Cu levels and more localised alterations in Na, K, Mn, Fe, Zn, and Se. This study aimed to determine whether these metallomic changes appear in the DLB brain, and how the metallomic profile of the DLB brain appears in comparison to the AD and PDD brain. Methods: Brain tissues from ten regions of 20 DLB cases and 19 controls were obtained. The concentrations of Na, Mg, K, Ca, Zn, Fe, Mn, Cu, and Se were determined using inductively coupled plasma-mass spectrometry (ICPMS). Case-control differences were evaluated using Mann-Whitney U tests. Results were compared with those previously obtained from AD and PDD brain tissue, and principal component analysis (PCA) plots were created to determine whether cerebral metallomic profiles could distinguish DLB from AD or PDD metallomic profiles. Results: Na was increased and Cu decreased in four and five DLB brain regions, respectively. More localised alterations in Mn, Ca, Fe, and Se were also identified. Despite similarities in Cu changes between all three diseases, PCA plots showed that DLB cases could be readily distinguished from AD cases using data from the middle temporal gyrus, primary visual cortex, and cingulate gyrus, whereas DLB and PDD cases could be clearly separated using data from the primary visual cortex alone. Conclusion: Despite shared alterations in Cu levels, the post-mortem DLB brain shows very few other similarities with the metallomic profile of the AD or PDD brain. These findings suggest that while Cu deficiencies appear common to all three conditions, metal alterations otherwise differ between DLB and PDD/AD. These findings can contribute to our understanding of the underlying pathogenesis of these three diseases; if these changes can be observed in the living human brain, they may also contribute to the differential diagnosis of DLB from AD and/or PDD. [ABSTRACT FROM AUTHOR]

IntroductionAlzheimer’s disease (AD) prevalence has increased in the last century which can be attributed to increased lifespan, but environment is also important. Exposure to artificial light at night is one environmental factor that may influence AD.MethodsThis study evaluated the relationship between outdoor nighttime light exposure and AD prevalence in the United States using satellite acquired outdoor nighttime light intensity and Medicare data.ResultsHigher outdoor nighttime light was associated with higher prevalence of AD. While atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke were associated more strongly with AD prevalence than nighttime light intensity, nighttime light was more strongly associated with AD prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity. Startlingly, nighttime light exposure more strongly associated with AD prevalence in those under the age of 65 than any other disease factor examined.DiscussionThese data suggest light exposure at night may influence AD, but additional studies are needed.

BackgroundDementia with Lewy bodies (DLB) can be difficult to distinguish from Alzheimer’s disease (AD) and Parkinson’s disease dementia (PDD) at different stages of its progression due to some overlaps in the clinical and neuropathological presentation of these conditions compared with DLB. Metallomic changes have already been observed in the AD and PDD brain—including widespread decreases in Cu levels and more localised alterations in Na, K, Mn, Fe, Zn, and Se. This study aimed to determine whether these metallomic changes appear in the DLB brain, and how the metallomic profile of the DLB brain appears in comparison to the AD and PDD brain.MethodsBrain tissues from ten regions of 20 DLB cases and 19 controls were obtained. The concentrations of Na, Mg, K, Ca, Zn, Fe, Mn, Cu, and Se were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Case–control differences were evaluated using Mann–Whitney U tests. Results were compared with those previously obtained from AD and PDD brain tissue, and principal component analysis (PCA) plots were created to determine whether cerebral metallomic profiles could distinguish DLB from AD or PDD metallomic profiles.ResultsNa was increased and Cu decreased in four and five DLB brain regions, respectively. More localised alterations in Mn, Ca, Fe, and Se were also identified. Despite similarities in Cu changes between all three diseases, PCA plots showed that DLB cases could be readily distinguished from AD cases using data from the middle temporal gyrus, primary visual cortex, and cingulate gyrus, whereas DLB and PDD cases could be clearly separated using data from the primary visual cortex alone.ConclusionDespite shared alterations in Cu levels, the post-mortem DLB brain shows very few other similarities with the metallomic profile of the AD or PDD brain. These findings suggest that while Cu deficiencies appear common to all three conditions, metal alterations otherwise differ between DLB and PDD/AD. These findings can contribute to our understanding of the underlying pathogenesis of these three diseases; if these changes can be observed in the living human brain, they may also contribute to the differential diagnosis of DLB from AD and/or PDD.

Introduction: Alzheimer's disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD. Methods: Participants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS (n = 8) and Sham-tDCS (n = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid. Results: The Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in postintervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers. Discussion: Our results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies. [ABSTRACT FROM AUTHOR]

IntroductionAlzheimer’s disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD.MethodsParticipants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS (n = 8) and Sham-tDCS (n = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid.ResultsThe Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in post-intervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers.DiscussionOur results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies.

Introduction: Diagnosing Alzheimer's disease (AD) lesions via visual examination of Electroencephalography (EEG) signals poses a considerable challenge. This has prompted the exploration of deep learning techniques, such as Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs), for AD prediction. However, the classification performance of CNN-based methods has often been deemed inadequate. This is primarily attributed to CNNs struggling with extracting meaningful lesion signals from the complex and noisy EEG data. Methods: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency. Results: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects. Discussion: This outcome outperforms prevailing state-of-the-artmethodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is a highly damaging disease that affects one’s cognition and memory and presents an increasing societal and economic burden globally. Considerable research has gone into understanding AD; however, there is still a lack of effective biomarkers that aid in early diagnosis and intervention. The recent discovery of the glymphatic system and associated Perivascular Spaces (PVS) has led to the theory that enlarged PVS (ePVS) may be an indicator of AD progression and act as an early diagnostic marker. Visible on Magnetic Resonance Imaging (MRI), PVS appear to enlarge when known biomarkers of AD, amyloid-β and tau, accumulate. The central goal of ePVS and AD research is to determine when ePVS occurs in AD progression and if ePVS are causal or epiphenomena. Furthermore, if ePVS are indeed causative, interventions promoting glymphatic clearance are an attractive target for research. However, it is necessary first to ascertain where on the pathological progression of AD ePVS occurs. This review aims to examine the knowledge gap that exists in understanding the contribution of ePVS to AD. It is essential to understand whether ePVS in the brain correlate with increased regional tau distribution and global or regional Amyloid-β distribution and to determine if these spaces increase proportionally over time as individuals experience neurodegeneration. This review demonstrates that ePVS are associated with reduced glymphatic clearance and that this reduced clearance is associated with an increase in amyloid-β. However, it is not yet understood if ePVS are the outcome or driver of protein accumulation. Further, it is not yet clear if ePVS volume and number change longitudinally. Ultimately, it is vital to determine early diagnostic criteria and early interventions for AD to ease the burden it presents to the world; ePVS may be able to fulfill this role and therefore merit further research. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common types of neurodegenerative dementia among the elderly with similar symptoms of cognitive decline and overlapping neuropsychological profiles. Biological markers to distinguish patients with VaD from AD would be very useful. We aimed to investigate the expression of blood-brain barrier (BBB)-related blood-borne factors of soluble lowdensity lipoprotein receptor-related protein 1 (sLRP1), cyclophilin A (CyPA), and matrix metalloproteinase 9 (MMP9) and its correlation with cognitive function between patients with AD and VaD. Materials and methods: Plasma levels of sLRP1, CyPA, and MMP9 were analyzed in 26 patients with AD, 27 patients with VaD, and 27 normal controls (NCs). Spearman's rank correlation analysis was used to explore the relationships among biomarker levels, cognitive function, and imaging references. Receiver operating characteristic (ROC) curve analysis was used to discriminate the diagnosis of AD and VaD. Results: Among these BBB-related factors, plasma CyPA levels in the VaD group were significantly higher than that in the AD group (p < 0.05). Plasma sLRP1 levels presented an increasing trend in VaD while maintaining slightly low levels in patients with AD (p > 0.05). Plasma MMP9 in different diagnostic groups displayed the following trend: VaD group > AD group > NC group, but the difference was not statistically significant (p > 0.05). Furthermore, plasma sLRP1 levels were positively related to MoCA scores, and plasma CyPA levels were significantly correlated with MTA scores (p < 0.05) in the AD group. Plasma MMP9 levels were negatively correlated with MoCA scores (p < 0.05) in the VaD groups. No significant correlation was detected between the other factors and different cognitive scores (p > 0.05). ROC analysis showed a good preference of plasma CyPA [AUC = 0.725, 95% CI (0.586-0.865); p = 0.0064] in diagnosis. Conclusion: The plasma CyPA level is a reference index when distinguishing between an AD and subcortical ischemic vascular dementia (SIVD) diagnosis. Blood-derived factors associated with the BBB may provide new insights into the differential diagnosis of neurodegenerative dementia and warrant further investigation. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is a highly damaging disease that affects one’s cognition and memory and presents an increasing societal and economic burden globally. Considerable research has gone into understanding AD; however, there is still a lack of effective biomarkers that aid in early diagnosis and intervention. The recent discovery of the glymphatic system and associated Perivascular Spaces (PVS) has led to the theory that enlarged PVS (ePVS) may be an indicator of AD progression and act as an early diagnostic marker. Visible on Magnetic Resonance Imaging (MRI), PVS appear to enlarge when known biomarkers of AD, amyloid-β and tau, accumulate. The central goal of ePVS and AD research is to determine when ePVS occurs in AD progression and if ePVS are causal or epiphenomena. Furthermore, if ePVS are indeed causative, interventions promoting glymphatic clearance are an attractive target for research. However, it is necessary first to ascertain where on the pathological progression of AD ePVS occurs. This review aims to examine the knowledge gap that exists in understanding the contribution of ePVS to AD. It is essential to understand whether ePVS in the brain correlate with increased regional tau distribution and global or regional Amyloid-β distribution and to determine if these spaces increase proportionally over time as individuals experience neurodegeneration. This review demonstrates that ePVS are associated with reduced glymphatic clearance and that this reduced clearance is associated with an increase in amyloid-β. However, it is not yet understood if ePVS are the outcome or driver of protein accumulation. Further, it is not yet clear if ePVS volume and number change longitudinally. Ultimately, it is vital to determine early diagnostic criteria and early interventions for AD to ease the burden it presents to the world; ePVS may be able to fulfill this role and therefore merit further research.

Certain hippocampal-enriched miRNAs such as members of the miRNA-29 microRNA family (miRNA-29a, miRNA-29b and miRNA-29c) exhibit different expression patterns in the hippocampus, being up-regulated in the early stages of AD in transgenic murine models while being significantly downregulated in the other regions of the brain cortex as AD-type neurodegeneration progresses (Zong et al., [65]; Wei et al., [61]). Brain and central nervous system (CNS) miRNAs have typically short half-lives and information-carrying miRNA signals conveyed between the genome and the transcriptome are relatively rapid biological events. miRNAs are often mis-regulated in age-related neurological disorders such as Alzheimer's disease (AD). Alzheimer's disease (AD), heterogeneity, microRNA, miRNA stabilization, miRNA-146a, miRNA therapy Keywords: Alzheimer's disease (AD); heterogeneity; miRNA-146a; microRNA; miRNA therapy; miRNA stabilization EN Alzheimer's disease (AD) heterogeneity miRNA-146a microRNA miRNA therapy miRNA stabilization 1 7 7 05/05/22 20220503 NES 220503 Overview Small single-stranded non-coding ribonucleic acids (sncRNA) such as brain microRNA (miRNA) have biologically evolved for rapid post-transcriptional signaling to target messenger RNA (mRNA) and by doing so shape the transcriptome of the cell. [Extracted from the article]

Background: Both animal studies and prospective observational studies on patients with neurodegenerative disease have reported a positive link between oral diseases and cognitive function. However, the effect of early tooth loss on hippocampal morphology remains unknown. Methods: In this study, 6-week-old, male, juvenile Sprague–Dawley (SD) rats were randomized into the control (C) and tooth loss (TL) groups. In the TL group, all right maxillary molars of SD rats were extracted, while in the C group, no teeth were extracted. After 3 months, the learning and memory behavior were examined by Morris Water Maze (MWM), and the protein expression and mechanic signaling pathways were analyzed by real-time polymerase chain reaction, and cresyl violet staining. Results: Two days after the operation, the body weight of both groups recovered and gradually returned to the level before operation. Three months after tooth extraction, the completion time of the C group in the MWM was significantly shorter than the TL group. The mRNA expression of BDNF, TrkB, AKT1 , and NR2B in the C group were significantly higher than in the TL group. The pyramidal neurons in the TL group was fewer than in the C group. Conclusion: Tooth loss in the juvenile SD rats will reduce the number of pyramidal neurons in the hippocampus, inhibit the expression of BDNF, TrkB, AKT1 , and NR2B , and eventually lead to cognitive dysfunction. [ABSTRACT FROM AUTHOR]

Introduction: Alzheimer's disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD. Materials and Methods: Three microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls. Results: 53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P < 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P < 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD. Conclusion: We identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring. [ABSTRACT FROM AUTHOR]

BackgroundBoth animal studies and prospective observational studies on patients with neurodegenerative disease have reported a positive link between oral diseases and cognitive function. However, the effect of early tooth loss on hippocampal morphology remains unknown.MethodsIn this study, 6-week-old, male, juvenile Sprague–Dawley (SD) rats were randomized into the control (C) and tooth loss (TL) groups. In the TL group, all right maxillary molars of SD rats were extracted, while in the C group, no teeth were extracted. After 3 months, the learning and memory behavior were examined by Morris Water Maze (MWM), and the protein expression and mechanic signaling pathways were analyzed by real-time polymerase chain reaction, and cresyl violet staining.ResultsTwo days after the operation, the body weight of both groups recovered and gradually returned to the level before operation. Three months after tooth extraction, the completion time of the C group in the MWM was significantly shorter than the TL group. The mRNA expression of BDNF, TrkB, AKT1, and NR2B in the C group were significantly higher than in the TL group. The pyramidal neurons in the TL group was fewer than in the C group.ConclusionTooth loss in the juvenile SD rats will reduce the number of pyramidal neurons in the hippocampus, inhibit the expression of BDNF, TrkB, AKT1, and NR2B, and eventually lead to cognitive dysfunction.

IntroductionAlzheimer’s disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD.Materials and MethodsThree microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls.Results53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P < 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P < 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD.ConclusionWe identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring.

Background: In recent years, classification frameworks using imaging data have shown that multimodal classification methods perform favorably over the use of a single imaging modality for the diagnosis of Alzheimer’s Disease. The currently used clinical approach often emphasizes the use of qualitative MRI and/or PET data for clinical diagnosis. Based on the hypothesis that classification of isolated imaging modalities is not predictive of their respective value in combined approaches, we investigate whether the combination of T1 Weighted MRI and diffusion tensor imaging (DTI) can yield an equivalent performance as the combination of quantitative structural MRI (sMRI) with amyloid-PET.Methods: We parcellated the brain into regions of interest (ROI) following different anatomical labeling atlases. For each region of interest different metrics were extracted from the different imaging modalities (sMRI, PiB-PET, and DTI) to be used as features. Thereafter, the feature sets were reduced using an embedded-based feature selection method. The final reduced sets were then used as input in support vector machine (SVM) classifiers. Three different base classifiers were created, one for each imaging modality, and validated using internal (n = 41) and external data from the ADNI initiative (n = 330 for sMRI, n = 148 for DTI and n = 55 for PiB-PET) sources. Finally, the classifiers were ensembled using a weighted method in order to evaluate the performance of different combinations.Results: For the base classifiers the following performance levels were found: sMRI-based classifier (accuracy, 92%; specificity, 97% and sensitivity, 87%), PiB-PET (accuracy, 91%; specificity, 89%; and sensitivity, 92%) and the lowest performance was attained with DTI (accuracy, 80%; specificity, 76%; and sensitivity, 82%). From the multimodal approaches, when integrating two modalities, the following results were observed: sMRI+PiB-PET (accuracy, 98%; specificity, 98%; and sensitivity, 99%), sMRI+DTI (accuracy, 97%; specificity, 99%; and sensitivity, 94%) and PiB-PET+DTI (accuracy, 91%; specificity, 90%; and sensitivity, 93%). Finally, the combination of all imaging modalities yielded an accuracy of 98%, specificity of 97% and sensitivity of 99%.Conclusion: Although DTI in isolation shows relatively poor performance, when combined with structural MR, it showed a surprising classification performance which was comparable to MR combined with amyloid PET. These results are consistent with the notion that white matter changes are also important in Alzheimer’s Disease.

Background: In recent years, classification frameworks using imaging data have shown that multimodal classification methods perform favorably over the use of a single imaging modality for the diagnosis of Alzheimer's Disease. The currently used clinical approach often emphasizes the use of qualitative MRI and/or PET data for clinical diagnosis. Based on the hypothesis that classification of isolated imaging modalities is not predictive of their respective value in combined approaches, we investigate whether the combination of T1 Weighted MRI and diffusion tensor imaging (DTI) can yield an equivalent performance as the combination of quantitative structural MRI (sMRI) with amyloid-PET. Methods: We parcellated the brain into regions of interest (ROI) following different anatomical labeling atlases. For each region of interest different metrics were extracted from the different imaging modalities (sMRI, PiB-PET, and DTI) to be used as features. Thereafter, the feature sets were reduced using an embedded-based feature selection method. The final reduced sets were then used as input in support vector machine (SVM) classifiers. Three different base classifiers were created, one for each imaging modality, and validated using internal (n = 41) and external data from the ADNI initiative (n = 330 for sMRI, n = 148 for DTI and n = 55 for PiB-PET) sources. Finally, the classifiers were ensembled using a weighted method in order to evaluate the performance of different combinations. Results: For the base classifiers the following performance levels were found: sMRI-based classifier (accuracy, 92%; specificity, 97% and sensitivity, 87%), PiB-PET (accuracy, 91%; specificity, 89%; and sensitivity, 92%) and the lowest performance was attained with DTI (accuracy, 80%; specificity, 76%; and sensitivity, 82%). From the multimodal approaches, when integrating two modalities, the following results were observed: sMRI+PiB-PET (accuracy, 98%; specificity, 98%; and sensitivity, 99%), sMRI+DTI (accuracy, 97%; specificity, 99%; and sensitivity, 94%) and PiB-PET+DTI (accuracy, 91%; specificity, 90%; and sensitivity, 93%). Finally, the combination of all imaging modalities yielded an accuracy of 98%, specificity of 97% and sensitivity of 99%. Conclusion: Although DTI in isolation shows relatively poor performance, when combined with structural MR, it showed a surprising classification performance which was comparable to MR combined with amyloid PET. These results are consistent with the notion that white matter changes are also important in Alzheimer's Disease. [ABSTRACT FROM AUTHOR]

Sevoflurane (SEVO) is a highly fluorinated methyl isopropyl ether used as an inhalational anesthetic for general anesthesia. Previous studies have shown that SEVO may induce impaired memory and recognition ability and may be associated with neurodegenerative disease, e.g., Alzheimer's disease (AD). However, the underlying mechanism remains unknown. Here, we used a mouse AD model, APP/PS1, to study the effects of SEVO on neurodegeneration occurring in AD. We found that SEVO exposure significantly impaired the spatial reference memory, sensorimotor, and cognitive function of the mice. Mechanistically, we found that SEVO induced formation of NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome and its downstream caspase 1-mediated production of IL-1β and IL-18, which subsequently deactivated brain-derived neurotrophic factor (BDNF) to promote neurodegeneration. Together, these data suggest that NLRP3 inflammasome is essential for SEVO-induced AD. [ABSTRACT FROM AUTHOR]

Sevoflurane (SEVO) is a highly fluorinated methyl isopropyl ether used as an inhalational anesthetic for general anesthesia. Previous studies have shown that SEVO may induce impaired memory and recognition ability and may be associated with neurodegenerative disease, e.g., Alzheimer’s disease (AD). However, the underlying mechanism remains unknown. Here, we used a mouse AD model, APP/PS1, to study the effects of SEVO on neurodegeneration occurring in AD. We found that SEVO exposure significantly impaired the spatial reference memory, sensorimotor, and cognitive function of the mice. Mechanistically, we found that SEVO induced formation of NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome and its downstream caspase 1-mediated production of IL-1β and IL-18, which subsequently deactivated brain-derived neurotrophic factor (BDNF) to promote neurodegeneration. Together, these data suggest that NLRP3 inflammasome is essential for SEVO-induced AD.

Beta amyloid, Aβ 1–42, originally named as Amyloid A4 protein, is one of the most investigated peptides in neuroscience and has attracted substantial interest since its discovery as the main insoluble fibril-type protein in cerebrovascular amyloid angiopathy (Glenner and Wong, 1984; Masters et al., 1985) of Alzheimer’s disease (AD). From the very beginning, Aβ was regarded per se as a “bad molecule,” triggering the so-called “beta amyloid cascade hypothesis” (Hardy and Higgins, 1992). This hypothesis ignored any physiological function for in situ generated Aβ monomer with normal production and turnover rate (Bateman et al., 2006). Accordingly, pan-Aβ-related therapeutic approaches were designed to eliminate or lower the three structural isoforms in parallel: (1) the pre-amyloid monomer, (2) the misfolded oligomer, and (3) the final fibril. While we already knew about poor correlations between plaques and cognitive decline quite early (Terry et al., 1991), data for an essential benign physiological role for Aβ monomer at low concentrations were also not considered to be relevant. Here, a different Beta Amyloid hypothesis is described, the so-called “Beta Amyloid Dysfunction hypothesis,” which, in contrast to the “Beta Amyloid Cascade hypothesis,” builds on the homeostasis of essential Aβ monomer in the synaptic vesicle cycle (SVC). Disease-relevant early pathology emerges through disturbance of the Aβ homeostasis by so far unknown factors leading to the formation of misfolded Aβ oligomers. These early species interfere with the synaptic physiological Aβ monomer regulation and exert their neurotoxicity via various receptors for sticky oligomer-type Aβ aggregates. The Beta Amyloid Dysfunction (BAD) hypothesis is introduced and shown to explain negative clinical results of Gamma-secretase and Beta-secretase (BACE) inhibitors as well as pan-Aβ isotype unselective immunotherapies. This hypothesis gives guidance to what needs to be done therapeutically to revive successful clinical testing in AD for this highly validated target. The BAD hypothesis will need further refinement in particular through more detailed exploration for the role of physiological Aβ monomer.

The hyperphosphorylation of tau protein and the overexpression of mTOR are considered to be the driving force behind Aβ plaques and Neurofibrillay Tangles (NFT's), hallmarks of Alzheimer's disease (AD). It is now evident that miscellaneous diseases such as Diabetes, Autoimmune diseases, Cancer, etc. are correlated with AD. Therefore, we reviewed the literature on the causes of AD and investigated the association of tau and mTOR with other diseases. We have discussed the role of insulin deficiency in diabetes, activated microglial cells, and dysfunction of blood-brain barrier (BBB) in Autoimmune diseases, Presenilin 1 in skin cancer, increased reactive species in mitochondrial dysfunction and deregulated Cyclins/CDKs in promoting AD pathogenesis. We have also discussed the possible therapeutics for AD such as GSK3 inactivation therapy, Rechaperoning therapy, Immunotherapy, Hormonal therapy, Metal chelators, Cell cycle therapy, γ-secretase modulators, and Cholinesterase and BACE 1-inhibitors which are thought to serve a major role in combating pathological changes coupled with AD. Recent research about the relationship between mTOR and aging and hepatic Aβ degradation offers possible targets to effectively target AD. Future prospects of AD aims at developing novel drugs and modulators that can potentially improve cell to cell signaling, prevent Aβ plaques formation, promote better release of neurotransmitters and prevent hyperphosphorylation of tau.

The remarkable co-localization of highly pro-inflammatory lipopolysaccharide (LPS) with sporadic Alzheimer’s disease (AD)-affected neuronal nuclei suggests that there may be some novel pathogenic contribution of this heat stable neurotoxin to neuronal activity and neuron-specific gene expression. In this communication we show for the first time: (i) the association and envelopment of sporadic AD neuronal nuclei with LPS in multiple AD neocortical tissue samples; and (ii) a selective repression in the output of neuron-specific neurofilament light (NF-L) chain messenger RNA (mRNA), perhaps as a consequence of this association. The down-regulation of NF-L mRNA and protein is a characteristic attribute of AD brain and accompanies neuronal atrophy and an associated loss of neuronal architecture with synaptic deficits. To study this phenomenon further, human neuronal-glial (HNG) cells in primary culture were incubated with LPS, and DNA arrays, Northern, Western, and ELISA analyses were used to quantify transcription patterns for the three member neuron-specific intermediate filament-gene family NF-H, NF-M, and NF-L. As in sporadic AD limbic-regions, down-regulated transcription products for the NF-L intermediate filament protein was significant. These results support our novel hypothesis: (i) that internally sourced, microbiome-derived neurotoxins such as LPS contribute to a progressive disruption in the read-out of neuron-specific genetic-information; (ii) that the presence of LPS-enveloped neuronal nuclei is associated with a down-regulation in NF-L expression, a key neuron-specific cytoskeletal component; and (iii) this may have a bearing on progressive neuronal atrophy, loss of synaptic-contact and disruption of neuronal architecture, all of which are characteristic pathological features of sporadic-AD brain. This is the first report that provides evidence for a neuron-specific effect of a human GI-tract microbiome-derived neurotoxin on decreased NF-L abundance in both sporadic AD temporal lobe neocortex in vivo and in LPS-stressed HNG cells in vitro.

The Plexin-A 4 (PLXNA4) gene, has recently been identified in genome wide association studies (GWAS), as a novel genetic player associated with Alzheimer's disease (AD). Additionally, PLXNA4 genetic variations were also found to increase AD risk by tau pathology in vitro. However, the potential roles of PLXNA4 variants in the amyloid-β (Aβ) pathology, were not evaluated. Five targeted loci capturing the top common variations in PLXNA4, were extracted using tagger methods. Multiple linear regression models were used to explore whether these variations can affect the cerebrospinal fluid (CSF) (Aβ1−42, T-tau, and P-tau) phenotypes in the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset. We detected that two loci (rs6467431, rs67468325) were significantly associated with CSF Aβ1−42 levels in the hybrid population (rs6467431: P = 0.01376, rs67468325: P = 0.006536) and the significance remained after false discovery rate (FDR) correction (rs6467431: Pc = 0.03441, rs67468325: Pc = 0.03268). In the subgroup analysis, we further confirmed the association of rs6467431 in the cognitively normal (CN) subgroup (P = 0.01904, Pc = 0.04761). Furthermore, rs6467431-A carriers and rs67468325-G carriers showed higher CSF Aβ1−42 levels than non-carriers. Nevertheless, we did not detect any significant relationships between the levels of T-tau, P-tau and these PLXNA4 loci. Our findings provided preliminary evidence that PLXNA4 variants can confer AD risk through modulating the Aβ deposition.

Introduction: Alzheimer's disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD., Methods: Participants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS ( n  = 8) and Sham-tDCS ( n  = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid., Results: The Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in post-intervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers., Discussion: Our results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kim and Yang.)

The remarkable co-localization of highly pro-inflammatory lipopolysaccharide (LPS) with sporadic Alzheimer's disease (AD)-affected neuronal nuclei suggests that there may be some novel pathogenic contribution of this heat stable neurotoxin to neuronal activity and neuron-specific gene expression. In this communication we show for the first time: (i) the association and envelopment of sporadic AD neuronal nuclei with LPS in multiple AD neocortical tissue samples; and (ii) a selective repression in the output of neuron-specific neurofilament light (NF-L) chain messenger RNA (mRNA), perhaps as a consequence of this association. The down-regulation of NF-L mRNA and protein is a characteristic attribute of AD brain and accompanies neuronal atrophy and an associated loss of neuronal architecture with synaptic deficits. To study this phenomenon further, human neuronal-glial (HNG) cells in primary culture were incubated with LPS, and DNA arrays, Northern, Western, and ELISA analyses were used to quantify transcription patterns for the three member neuron-specific intermediate filament-gene family NF-H, NF-M, and NF-L. As in sporadic AD limbic-regions, down-regulated transcription products for the NF-L intermediate filament protein was significant. These results support our novel hypothesis: (i) that internally sourced, microbiome-derived neurotoxins such as LPS contribute to a progressive disruption in the read-out of neuron-specific genetic-information; (ii) that the presence of LPS-enveloped neuronal nuclei is associated with a down-regulation in NF-L expression, a key neuron-specific cytoskeletal component; and (iii) this may have a bearing on progressive neuronal atrophy, loss of synaptic-contact and disruption of neuronal architecture, all of which are characteristic pathological features of sporadic-AD brain. This is the first report that provides evidence for a neuron-specific effect of a human GI-tract microbiome-derived neurotoxin on decreased NF-L abundance in both sporadic AD temporal lobe neocortex in vivo and in LPS-stressed HNG cells in vitro. [ABSTRACT FROM AUTHOR]

Tauopathies are a diverse group of diseases featuring progressive dying-back neurodegeneration of specific neuronal populations in association with accumulation of abnormal forms of the microtubule-associated protein tau. It is well-established that the clinical symptoms characteristic of tauopathies correlate with deficits in synaptic function and neuritic connectivity early in the course of disease, but mechanisms underlying these critical pathogenic events are not fully understood. Biochemical in vitro evidence fueled the widespread notion that microtubule stabilization represents tau's primary biological role and that the marked atrophy of neurites observed in tauopathies results from loss of microtubule stability. However, this notion contrasts with the mild phenotype associated with tau deletion. Instead, an analysis of cellular hallmarks common to different tauopathies, including aberrant patterns of protein phosphorylation and early degeneration of axons, suggests that alterations in kinase-based signaling pathways and deficits in axonal transport (AT) associated with such alterations contribute to the loss of neuronal connectivity triggered by pathogenic forms of tau. Here, we review a body of literature providing evidence that axonal pathology represents an early and common pathogenic event among human tauopathies. Observations of axonal degeneration in animal models of specific tauopathies are discussed and similarities to human disease highlighted. Finally, we discuss potential mechanistic pathways other than microtubule destabilization by which disease-related forms of tau may promote axonopathy.

Tauopathies are a diverse group of diseases featuring progressive dying-back neurodegeneration of specific neuronal populations in association with accumulation of abnormal forms of the microtubule-associated protein tau. It is well-established that the clinical symptoms characteristic of tauopathies correlate with deficits in synaptic function and neuritic connectivity early in the course of disease, but mechanisms underlying these critical pathogenic events are not fully understood. Biochemical in vitro evidence fueled the widespread notion that microtubule stabilization represents tau's primary biological role and that the marked atrophy of neurites observed in tauopathies results from loss of microtubule stability. However, this notion contrasts with the mild phenotype associated with tau deletion. Instead, an analysis of cellular hallmarks common to different tauopathies, including aberrant patterns of protein phosphorylation and early degeneration of axons, suggests that alterations in kinase-based signaling pathways and deficits in axonal transport (AT) associated with such alterations contribute to the loss of neuronal connectivity triggered by pathogenic forms of tau. Here, we review a body of literature providing evidence that axonal pathology represents an early and common pathogenic event among human tauopathies. Observations of axonal degeneration in animal models of specific tauopathies are discussed and similarities to human disease highlighted. Finally, we discuss potential mechanistic pathways other than microtubule destabilization by which disease-related forms of tau may promote axonopathy. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene (HTT), but the pathophysiological mechanismofmutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinalmuscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Introduction: Diagnosing Alzheimer's disease (AD) lesions via visual examination of Electroencephalography (EEG) signals poses a considerable challenge. This has prompted the exploration of deep learning techniques, such as Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs), for AD prediction. However, the classification performance of CNN-based methods has often been deemed inadequate. This is primarily attributed to CNNs struggling with extracting meaningful lesion signals from the complex and noisy EEG data., Methods: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency., Results: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects., Discussion: This outcome outperforms prevailing state-of-the-art methodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Chen, Wang, Zhang, Zhang and Tao.)

There is evidence of altered vascular function, including cerebrovascular, in Alzheimer’s disease (AD) and transgenic models of the disease. Indeed vasoconstrictor responses are increased, while vasodilation is reduced in both conditions. β-Amyloid (Aβ) appears to be responsible, at least in part, of alterations in vascular function. Cannabinoids, neuroprotective and anti-inflammatory agents, induce vasodilation both in vivo and in vitro. We have demonstrated a beneficial effect of cannabinoids in models of AD by preventing glial activation. In this work we have studied the effects of these compounds on vessel density in amyloid precursor protein (APP) transgenic mice, line 2576, and on altered vascular responses in aortae isolated ring. First we showed increased collagen IV positive vessels in AD brain compared to control subjects, with a similar increase in TgAPP mice, which was normalized by prolonged oral treatment with the CB1/CB2 mixed agonist WIN 55,212-2 (WIN) and the CB2 selective agonist JWH-133 (JWH). In Tg APP mice the vasoconstriction induced by phenylephrine and the thromboxane agonist U46619 was significantly increased, and no change in the vasodilation to acetylcholine (ACh) was observed. Tg APP displayed decreased vasodilation to both cannabinoid agonists, which were able to prevent decreased ACh relaxation in the presence of Aβ. In summary, we have confirmed and extended the existence of altered vascular responses in Tg APP mice. Moreover, our results suggest that treatment with cannabinoids may ameliorate the vascular responses in AD-type pathology.

Non-invasive brain stimulation techniques, including transcranial direct current stimulation (t-DCS) have been used in the rehabilitation of cognitive function in a spectrum of neurological disorders. The present review outlines methodological communalities and differences of t-DCS procedures in neurocognitive rehabilitation. We consider the efficacy of tDCS for the management of specific cognitive deficits in four main neurological disorders by providing a critical analysis of recent studies that have used t-DCS to improve cognition in patients with Parkinson’s Disease, Alzheimer’s Disease, Hemi-spatial Neglect and Aphasia. The evidence from this innovative approach to cognitive rehabilitation suggests that tDCS can influence cognition. However, the results show a high variability between studies both in terms of the methodological approach adopted and the cognitive functions targeted. The review also focuses both on methodological issues such as technical aspects of the stimulation (electrode position and dimension; current intensity; duration of protocol) and on the inclusion of appropriate assessment tools for cognition. A further aspect considered is the optimal timing for administration of tDCS: before, during or after cognitive rehabilitation. We conclude that more studies using common methodology are needed to gain a better understanding of the efficacy of tDCS as a new tool for rehabilitation of cognitive disorders in a range of neurological disorders.

Tau is a microtubule-associated protein whose misfolding, hyper-phosphorylation, loss of normal function and toxic gain of function are linked to several neurodegenerative disorders, including Alzheimer’s disease (AD). This review discusses the role of tau in amyloid-β (Aβ) induced toxicity in AD. The consequences of tau dysfunction, starting from the axon and concluding at somadendritic compartments, will be highlighted.

Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer’s disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e. 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.

Previous evidence showed a 75.5% best accuracy in the classification of 120 Alzheimer's disease (AD) patients with dementia and 100 matched normal elderly (Nold) subjects based on cortical source current density and linear lagged connectivity estimated by eLORETA freeware from resting state eyes-closed electroencephalographic (rsEEG) rhythms (Babiloni et al., 2016a). Specifically, that accuracy was reached using the ratio between occipital delta and alpha1 current density for a linear univariate classifier (receiver operating characteristic curves). Here we tested an innovative approach based on an artificial neural network (ANN) classifier from the same database of rsEEG markers. Frequency bands of interest were delta (2-4 Hz), theta (4-8 Hz Hz), alpha1 (8-10.5 Hz), and alpha2 (10.5-13 Hz). ANN classification showed an accuracy of 77% using the most 4 discriminative rsEEG markers of source current density (parietal theta/alpha 1, temporal theta/alpha 1, occipital theta/alpha 1, and occipital delta/alpha 1). It also showed an accuracy of 72% using the most 4 discriminative rsEEG markers of source lagged linear connectivity (inter-hemispherical occipital delta/alpha 2, intra-hemispherical right parietal-limbic alpha 1, intra-hemispherical left occipital-temporal theta/alpha 1, intra-hemispherical right occipital-temporal theta/alpha 1). With these 8 markers combined, an accuracy of at least 76% was reached. Interestingly, this accuracy based on 8 (linear) rsEEG markers as inputs to ANN was similar to that obtained with a single rsEEG marker (Babiloni et al., 2016a), thus unveiling their information redundancy for classification purposes. In future AD studies, inputs to ANNs should include other classes of independent linear (i.e., directed transfer function) and non-linear (i.e., entropy) rsEEG markers to improve the classification. [ABSTRACT FROM AUTHOR]