Hippocampal and Hippocampal-Subfield Volumes From Early-Onset Major Depression and Bipolar Disorder to Cognitive Decline

Background: The hippocampus and its subfields (HippSub) are reported to be diminished in patients with Alzheimer's disease (AD), bipolar disorder (BD), and major depressive disorder (MDD). We examined these groups vs healthy controls (HC) to reveal HippSub alterations between diseases. Methods: We segmented 3T-MRI T2-weighted hippocampal images of 67 HC, 58 BD, and MDD patients from the AFFDIS study and 137 patients from the DELCODE study assessing cognitive decline, including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and AD, via Free Surfer 6.0 to compare volumes across groups. Results: Groups differed significantly in several HippSub volumes, particularly between patients with AD and mood disorders. In comparison to HC, significant lower volumes appear in aMCI and AD groups in specific subfields. Smaller volumes in the left presubiculum are detected in aMCI and AD patients, differing from the BD group. A significant linear regression is seen between left hippocampus volume and duration since the first depressive episode. Conclusions: HippSub volume alterations were observed in AD, but not in early-onset MDD and BD, reinforcing the notion of different neural mechanisms in hippocampal degeneration. Moreover, duration since the first depressive episode was a relevant factor explaining the lower left hippocampal volumes present in groups

Low grade squamous intra-epithelial lesions and human papillomavirus infection in Colombian women

Low grade squamous intra-epithelial lesions could be considered as a manifestation of human papillomavirus exposition, however the discrepancy between rates of infection with human papillomavirus and development of low grade squamous intra-epithelial lesions is notable. Here we report a cross-sectional three-armed case–control study in the Colombian population, to compare the risk factors of women with low grade squamous intra-epithelial lesions with that of human papillomavirus DNA-negative and positive women with normal cytology

Association of Cholinergic Basal Forebrain Volume and Functional Connectivity with Markers of Inflammatory Response in the Alzheimer's Disease Spectrum

BACKGROUND: Inflammation has been described as a key pathogenic event in Alzheimer's disease (AD), downstream of amyloid and tau pathology. Preclinical and clinical data suggest that the cholinergic basal forebrain may moderate inflammatory response to different pathologies. OBJECTIVE: To study the association of cholinergic basal forebrain volume and functional connectivity with measures of neuroinflammation in people from the AD spectrum. METHODS: We studied 261 cases from the DELCODE cohort, including people with subjective cognitive decline, mild cognitive impairment, AD dementia, first degree relatives, and healthy controls. Using Bayesian ANCOVA, we tested associations of MRI indices of cholinergic basal forebrain volume and functional connectivity with cerebrospinal fluid (CSF) levels of sTREM2 as a marker of microglia activation, and serum levels of complement C3. Using Bayesian elastic net regression, we determined associations between basal forebrain measures and a large inflammation marker panel from CSF and serum. RESULTS: We found anecdotal to moderate evidence in favor of the absence of an effect of basal forebrain volume and functional connectivity on CSF sTREM2 and serum C3 levels both in Aβ42/ptau-positive and negative cases. Bayesian elastic net regression identified several CSF and serum markers of inflammation that were associated with basal forebrain volume and functional connectivity. The effect sizes were moderate to small. CONCLUSION: Our data-driven analyses generate the hypothesis that cholinergic basal forebrain may be involved in the neuroinflammation response to Aβ42 and phospho-tau pathology in people from the AD spectrum. This hypothesis needs to be tested in independent samples

Challenges and strategies of children and adolescents with inflammatory bowel disease: a qualitative examination

© 2007 Nicholas et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency" and decrease of the "clustering coefficient" in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes

Arterial hypertension and β-amyloid accumulation have spatially overlapping effects on posterior white matter hyperintensity volume: a cross-sectional study

Background: White matter hyperintensities (WMH) in subjects across the Alzheimer’s disease (AD) spectrum with minimal vascular pathology suggests that amyloid pathology—not just arterial hypertension—impacts WMH, which in turn adversely influences cognition. Here we seek to determine the effect of both hypertension and Aβ positivity on WMH, and their impact on cognition. Methods: We analysed data from subjects with a low vascular profile and normal cognition (NC), subjective cognitive decline (SCD), and amnestic mild cognitive impairment (MCI) enrolled in the ongoing observational multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (n = 375, median age 70.0 [IQR 66.0, 74.4] years; 178 female; NC/SCD/MCI 127/162/86). All subjects underwent a rich neuropsychological assessment. We focused on baseline memory and executive function—derived from multiple neuropsychological tests using confirmatory factor analysis—, baseline preclinical Alzheimer’s cognitive composite 5 (PACC5) scores, and changes in PACC5 scores over the course of three years (ΔPACC5). Results: Subjects with hypertension or Aβ positivity presented the largest WMH volumes (pFDR < 0.05), with spatial overlap in the frontal (hypertension: 0.42 ± 0.17; Aβ: 0.46 ± 0.18), occipital (hypertension: 0.50 ± 0.16; Aβ: 0.50 ± 0.16), parietal lobes (hypertension: 0.57 ± 0.18; Aβ: 0.56 ± 0.20), corona radiata (hypertension: 0.45 ± 0.17; Aβ: 0.40 ± 0.13), optic radiation (hypertension: 0.39 ± 0.18; Aβ: 0.74 ± 0.19), and splenium of the corpus callosum (hypertension: 0.36 ± 0.12; Aβ: 0.28 ± 0.12). Elevated global and regional WMH volumes coincided with worse cognitive performance at baseline and over 3 years (pFDR < 0.05). Aβ positivity was negatively associated with cognitive performance (direct effect—memory: − 0.33 ± 0.08, pFDR < 0.001; executive: − 0.21 ± 0.08, pFDR < 0.001; PACC5: − 0.29 ± 0.09, pFDR = 0.006; ΔPACC5: − 0.34 ± 0.04, pFDR < 0.05). Splenial WMH mediated the relationship between hypertension and cognitive performance (indirect-only effect—memory: − 0.05 ± 0.02, pFDR = 0.029; executive: − 0.04 ± 0.02, pFDR = 0.067; PACC5: − 0.05 ± 0.02, pFDR = 0.030; ΔPACC5: − 0.09 ± 0.03, pFDR = 0.043) and WMH in the optic radiation partially mediated that between Aβ positivity and memory (indirect effect—memory: − 0.05 ± 0.02, pFDR = 0.029). Conclusions: Posterior white matter is susceptible to hypertension and Aβ accumulation. Posterior WMH mediate the association between these pathologies and cognitive dysfunction, making them a promising target to tackle the downstream damage related to the potentially interacting and potentiating effects of the two pathologies. Trial registration: German Clinical Trials Register (DRKS00007966, 04/05/2015)

An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes

For the analysis of neuronal cooperativity, simultaneously recorded extracellular signals from neighboring neurons need to be sorted reliably by a spike sorting method. Many algorithms have been developed to this end, however, to date, none of them manages to fulfill a set of demanding requirements. In particular, it is desirable to have an algorithm that operates online, detects and classifies overlapping spikes in real time, and that adapts to non-stationary data. Here, we present a combined spike detection and classification algorithm, which explicitly addresses these issues. Our approach makes use of linear filters to find a new representation of the data and to optimally enhance the signal-to-noise ratio. We introduce a method called “Deconfusion” which de-correlates the filter outputs and provides source separation. Finally, a set of well-defined thresholds is applied and leads to simultaneous spike detection and spike classification. By incorporating a direct feedback, the algorithm adapts to non-stationary data and is, therefore, well suited for acute recordings. We evaluate our method on simulated and experimental data, including simultaneous intra/extra-cellular recordings made in slices of a rat cortex and recordings from the prefrontal cortex of awake behaving macaques. We compare the results to existing spike detection as well as spike sorting methods. We conclude that our algorithm meets all of the mentioned requirements and outperforms other methods under realistic signal-to-noise ratios and in the presence of overlapping spikes

Impact of Load-Related Neural Processes on Feature Binding in Visuospatial Working Memory

BACKGROUND: The capacity of visual working memory (WM) is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. OBJECTIVE: To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. METHODS AND FINDINGS: 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position) in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. CONCLUSIONS AND SIGNIFICANCE: The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this network. These findings provide new insights into how feature binding operates within the capacity-limited WM system