1. |
- Tai, F, et al.
(författare)
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Abdominal Wall Miscellaneous
- 2015
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Ingår i: Hernia : the journal of hernias and abdominal wall surgery. - 1248-9204. ; 19 Suppl 1, s. S5-S12
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Tidskriftsartikel (refereegranskat)
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2. |
- Cumplido-Mayoral, I., et al.
(författare)
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Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex
- 2023
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Ingår i: Elife. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Brain--age can be inferred from structural neuroimaging and compared to chronological age (brain--age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging--derived measures from the UK Biobank dataset (N=22,661) were used to predict brain--age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-ss, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain--age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain--age delta as a non-invasive marker of biological brain aging in non--demented individuals with abnormal levels of biomarkers of AD and axonal injury.
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3. |
- Lorenzini, L., et al.
(författare)
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Eigenvector centrality dynamics are related to Alzheimer's disease pathological changes in non-demented individuals
- 2023
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Ingår i: Brain Communications. - : Oxford University Press (OUP). - 2632-1297. ; 5:3
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Tidskriftsartikel (refereegranskat)abstract
- Amyloid-beta accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer's disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer's disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer's Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer's disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer's disease pathology and cognitive decline. Lorenzini et al. demonstrate widespread dynamic functional connectivity impairments in relationship with Alzheimer's disease pathological changes in non-demented individuals. This work suggests that initial amyloid deposition affects eigenvector centrality temporal patterns by reducing the involvement of functional hubs in different network dynamics, therefore reducing functional integration, and promoting cognitive deterioration.
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4. |
- Béquignon, Olivier J. M., et al.
(författare)
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Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells
- 2023
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 63:17, s. 5433-5445
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Tidskriftsartikel (refereegranskat)abstract
- Oxidative stress is the consequence of an abnormal increase of reactive oxygen species (ROS). ROS are generated mainly during the metabolism in both normal and pathological conditions as well as from exposure to xenobiotics. Xenobiotics can, on the one hand, disrupt molecular machinery involved in redox processes and, on the other hand, reduce the effectiveness of the antioxidant activity. Such dysregulation may lead to oxidative damage when combined with oxidative stress overpassing the cell capacity to detoxify ROS. In this work, a green fluorescent protein (GFP)-tagged nuclear factor erythroid 2-related factor 2 (NRF2)-regulated sulfiredoxin reporter (Srxn1-GFP) was used to measure the antioxidant response of HepG2 cells to a large series of drug and drug-like compounds (2230 compounds). These compounds were then classified as positive or negative depending on cellular response and distributed among different modeling groups to establish structure-activity relationship (SAR) models. A selection of models was used to prospectively predict oxidative stress induced by a new set of compounds subsequently experimentally tested to validate the model predictions. Altogether, this exercise exemplifies the different challenges of developing SAR models of a phenotypic cellular readout, model combination, chemical space selection, and results interpretation.
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5. |
- Biver, N, et al.
(författare)
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Long-term evolution of the outgassing of comet Hale-Bopp from radio observations
- 1997
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Ingår i: EARTH MOON AND PLANETS. - : KLUWER ACADEMIC PUBL. - 0167-9295. ; 78:1-3, s. 5-11
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Tidskriftsartikel (refereegranskat)abstract
- C/1995 O1 (Hale-Bopp) has been observed on a regular basis since August 1995 at millimetre and submillimetre wavelengths using IRAM, JCMT, CSO and SEST radio telescopes. The production rates of eight molecular species (CO, HCN, CH3OH, H2CO, H2S, CS, CH3CN
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6. |
- Lorenzini, Luigi, et al.
(författare)
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The Open-Access European Prevention of Alzheimer?s Dementia (EPAD) MRI dataset and processing workflow
- 2022
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Ingår i: NeuroImage. - : Elsevier. - 2213-1582. ; 35
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Tidskriftsartikel (refereegranskat)abstract
- The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI pre-processing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses
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7. |
- Tranfa, Mario, et al.
(författare)
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Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure
- 2024
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Ingår i: ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY. - 2328-9503. ; 11:6, s. 1541-1556
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveAlzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-epsilon 4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.MethodsWithin the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 +/- 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid beta 1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 +/- 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract.ResultsAD pathology, APOE-epsilon 4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-epsilon 4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect.InterpretationOur results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.
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8. |
- Bollack, Ariane, et al.
(författare)
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Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies
- 2023
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Ingår i: NeuroImage. - 1053-8119. ; 280
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. Methods: Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation. Results: All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL. Conclusion: Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.
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