The influence of semantic and phonological factors on syntactic decisions: An event-related brain potential study

During language production and comprehension, information about a word's syntactic properties is sometimes needed. While the decision about the grammatical gender of a word requires access to syntactic knowledge, it has also been hypothesized that semantic (i.e., biological gender) or phonological information (i.e., sound regularities) may influence this decision. Event-related potentials (ERPs) were measured while native speakers of German processed written words that were or were not semantically and/or phonologically marked for gender. Behavioral and ERP results showed that participants were faster in making a gender decision when words were semantically and/or phonologically gender marked than when this was not the case, although the phonological effects were less clear. In conclusion, our data provide evidence that even though participants performed a grammatical gender decision, this task can be influenced by semantic and phonological factors

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Regional distribution of white matter hyperintensities in vascular dementia, Alzheimer's disease and healthy aging

Background: White matter hyperintensities (WMH) on MRI scans indicate lesions of the subcortical fiber system. The regional distribution of WMH may be related to their pathophysiology and clinical effect in vascular dementia (VaD), Alzheimer's disease (AD) and healthy aging. Methods: Regional WMH volumes were measured in MRI scans of 20 VaD patients, 25 AD patients and 22 healthy elderly subjects using FLAIR sequences and surface reconstructions from a three-dimensional MRI sequence. Results: The intraclass correlation coefficient for interrater reliability of WMH volume measurements ranged between 0.99 in the frontal and 0.72 in the occipital lobe. For each cerebral lobe, the WMH index, i.e. WMH volume divided by lobar volume, was highest in VaD and lowest in healthy controls. Within each group, the WMH index was higher in frontal and parietal lobes than in occipital and temporal lobes. Total WMH index and WMH indices in the frontal lobe correlated significantly with the MMSE score in VaD. Category fluency correlated with the frontal lobe WMH index in AD, while drawing performance correlated with parietal and temporal lobe WMH indices in VaD. Conclusions: A similar regional distribution of WMH between the three groups suggests a common (vascular) pathogenic factor leading to WMH in patients and controls. Our findings underscore the potential of regional WMH volumetry to determine correlations between subcortical pathology and cognitive impairment. Copyright (C) 2004 S. Karger AG, Basel

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h2 = 0.53–0.90, p < 10− 5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application

Mouse models of neurodegenerative disease: preclinical imaging and neurovascular component.

Neurodegenerative diseases represent great challenges for basic science and clinical medicine because of their prevalence, pathologies, lack of mechanism-based treatments, and impacts on individuals. Translational research might contribute to the study of neurodegenerative diseases. The mouse has become a key model for studying disease mechanisms that might recapitulate in part some aspects of the corresponding human diseases. Neurode- generative disorders are very complicated and multifacto- rial. This has to be taken in account when testing drugs. Most of the drugs screening in mice are very di cult to be interpretated and often useless. Mouse models could be condiderated a ‘pathway models’, rather than as models for the whole complicated construct that makes a human disease. Non-invasive in vivo imaging in mice has gained increasing interest in preclinical research in the last years thanks to the availability of high-resolution single-photon emission computed tomography (SPECT), positron emission tomography (PET), high eld Magnetic resonance, Optical Imaging scanners and of highly speci c contrast agents. Behavioral test are useful tool to characterize di erent ani- mal models of neurodegenerative pathology. Furthermore, many authors have observed vascular pathological features associated to the di erent neurodegenerative disorders. Aim of this review is to focus on the di erent existing animal models of neurodegenerative disorders, describe behavioral tests and preclinical imaging techniques used for diagnose and describe the vascular pathological features associated to these diseases

MRD dynamics during maintenance for improved prognostication of 1280 patients with myeloma in the TOURMALINE-MM3 and -MM4 trials

Measurable residual disease (MRD) evaluation may help to guide treatment duration in multiple myeloma (MM). Paradoxically, limited longitudinal data exist on MRD during maintenance. We investigated the prognostic value of MRD dynamics in 1280 transplant-eligible and -ineligible patients from the TOURMALINE-MM3 and -MM4 randomized placebo-controlled phase 3 studies of 2-year ixazomib maintenance. MRD status at randomization showed independent prognostic value (median progression-free survival [PFS], 38.6 vs 15.6 months in MRD− vs MRD+ patients; HR, 0.47). However, MRD dynamics during maintenance provided more detailed risk stratification. A 14-month landmark analysis showed prolonged PFS in patients converting from MRD+ to MRD− status vs those with persistent MRD+ status (76.8% vs 27.6% 2-year PFS rates). Prolonged PFS was observed in patients with sustained MRD− status vs those converting from MRD− to MRD+ status (75.0% vs 34.2% 2-year PFS rates). Similar results were observed at a 28-month landmark analysis. Ixazomib maintenance vs placebo improved PFS in patients who were MRD+ at randomization (median, 18.8 vs 11.6 months; HR, 0.65) or at the 14-month landmark (median, 16.8 vs 10.6 months; HR, 0.65); no difference was observed in patients who were MRD−. This is the largest MM population undergoing yearly MRD evaluation during maintenance reported to date. We demonstrate the limited prognostic value of a single–time point MRD evaluation, because MRD dynamics over time substantially impact PFS risk. These findings support MRD− status as a relevant end point during maintenance and confirm the increased progression risk in patients converting to MRD+ from MRD− status. These trials were registered at www.clinicaltrials.gov as #NCT02181413 and #NCT02312258

Enhanced antitumoral activity of TLR7 agonists via activation of human endogenous retroviruses by HDAC inhibitors

In this work, we are reporting that “Shock and Kill”, a therapeutic approach designed to eliminate latent HIV from cell reservoirs, is extrapolatable to cancer therapy. This is based on the observation that malignant cells express a spectrum of human endogenous retroviral elements (HERVs) which can be transcriptionally boosted by HDAC inhibitors. The endoretroviral gene HERV-V2 codes for an envelope protein, which resembles syncytins. It is significantly overexpressed upon exposure to HDAC inhibitors and can be effectively targeted by simultaneous application of TLR7/8 agonists, triggering intrinsic apoptosis. We demonstrated that this synergistic cytotoxic effect was accompanied by the functional disruption of the TLR7/8-NFκB, Akt/PKB, and Ras-MEK-ERK signalling pathways. CRISPR/Cas9 ablation of TLR7 and HERV-V1/V2 curtailed apoptosis significantly, proving the pivotal role of these elements in driving cell death. The effectiveness of this new approach was confirmed in ovarian tumour xenograft studies, revealing a promising avenue for future cancer therapies

Watching TV news as a memory task -- brain activation and age effects

<p>Abstract</p> <p>Background</p> <p>Neuroimaging studies which investigate brain activity underlying declarative memory processes typically use artificial, unimodal laboratory stimuli. In contrast, we developed a paradigm which much more closely approximates real-life situations of information encoding.</p> <p>Methods</p> <p>In this study, we tested whether ecologically valid stimuli - clips of a TV news show - are apt to assess memory-related fMRI activation in healthy participants across a wide age range (22-70 years). We contrasted brain responses during natural stimulation (TV news video clips) with a control condition (scrambled versions of the same clips with reversed audio tracks). After scanning, free recall performance was assessed.</p> <p>Results</p> <p>The memory task evoked robust activation of a left-lateralized network, including primarily lateral temporal cortex, frontal cortex, as well as the left hippocampus. Further analyses revealed that - when controlling for performance effects - older age was associated with greater activation of left temporal and right frontal cortex.</p> <p>Conclusion</p> <p>We demonstrate the feasibility of assessing brain activity underlying declarative memory using a natural stimulation paradigm with high ecological validity. The preliminary result of greater brain activation with increasing age might reflect an attempt to compensate for decreasing episodic memory capacity associated with aging.</p

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

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