177 research outputs found
Donner corps aux interactions (l'interaction enfin concrétisée)
Depuis plusieurs années, nous utilisons IODA comme méthode de description et de réalisation de simulations multi-agents. Cette méthode a pour originalité de concrétiser les interactions de manière à ce qu'elles soient génériques et réutilisables dans différents contextes. Cet article a pour objectif d'identifier les problèmes durs dans ce type de simulation et de montrer comment IODA apporte une aide à leur résolution. Since several years, we use in our team the IODA methodology to describe and realize multi-agent simulations. This method is original and not similar to the others because it makes Interactions becoming concrete and then able to become sufficiently general to be reused in many contexts. The aim of this paper is to identify some hard problems in this kind of simulation and to show how IODA can be helful to solve them
Membrane topological model of glycosyltransferases of the GT-C superfamily
Glycosyltransferases that use polyisoprenol-linked donor substrates are categorized in the GT-C superfamily. In eukaryotes, they act in the endoplasmic reticulum (ER) lumen and are involved in N-glycosylation, glypiation, O-mannosylation, and C-mannosylation of proteins. We generated a membrane topology model of C-mannosyltransferases (DPY19 family) that concurred perfectly with the 13 transmembrane domains (TMDs) observed in oligosaccharyltransferases (STT3 family) structures. A multiple alignment of family members from diverse organisms highlighted the presence of only a few conserved amino acids between DPY19s and STT3s. Most of these residues were shown to be essential for DPY19 function and are positioned in luminal loops that showed high conservation within the DPY19 family. Multiple alignments of other eukaryotic GT-C families underlined the presence of similar conserved motifs in luminal loops, in all enzymes of the superfamily. Most GT-C enzymes are proposed to have an uneven number of TDMs with 11 (POMT, TMTC, ALG9, ALG12, PIGB, PIGV, and PIGZ) or 13 (DPY19, STT3, and ALG10) membrane-spanning helices. In contrast, PIGM, ALG3, ALG6, and ALG8 have 12 or 14 TMDs and display a C-terminal dilysine ER-retrieval motif oriented towards the cytoplasm. We propose that all members of the GT-C superfamily are evolutionary related enzymes with preserved membrane topology
Iron(III)-Salophene: An Organometallic Compound with Selective Cytotoxic and Anti-Proliferative Properties in Platinum-Resistant Ovarian Cancer Cells
Background: In this pioneer study to the biological activity of organometallic compound Iron(III)-salophene (Fe-SP) the specific effects of Fe-SP on viability, morphology, proliferation, and cell-cycle progression on platinum-resistant ovariancancer cell lines were investigated.
Methodology/Principal Findings: Fe-SP displayed selective cytotoxicity against SKOV-3 and OVCAR-3 (ovarian epithelial adenocarcinoma) cell lines at concentrations between 100 nM and 1 μM, while the viability of HeLa cells (epithelial cervix adenocarcinoma) or primary lung or skin fibroblasts was not affected. SKOV-3 cells in contrast to fibroblasts after treatment with Fe-SP revealed apparent hallmarks of apoptosis including densely stained nuclear granular bodies within fragmented nuclei, highly condensed chromatin and chromatin fragmentation. Fe-SP treatment led to the activation of markers of the extrinsic (Caspase-8) and intrinsic (Caspase-9) pathway of apoptosis as well as of executioner Caspase-3 while PARP-1 was deactivated. Fe-SP exerted effects as an anti-proliferative agent with an IC50 value of 300 nM and caused delayed progression of cells through S-phase phase of the cell cycle resulting in a complete S-phase arrest. When intra-peritoneally applied to rats Fe-SP did not show any systemic toxicity at concentrations that in preliminary trials were determined to be chemotherapeutic relevant doses in a rat ovarian cancer cell model.
Conclusion/Significance: The present report suggests that Fe-SP is a potent growth-suppressing agent in vitro for cell lines derived from ovarian cancer and a potential therapeutic drug to treat such tumors in viv
Prodromal neuroinflammatory, cholinergic and metabolite dysfunction detected by PET and MRS in the TgF344-AD transgenic rat model of AD: A collaborative multi-modal study
Mouse models of Alzheimer s disease (AD) are valuable but do not fully recapitulate human AD pathology, such as spontaneous Tau fibril accumulation and neuronal loss, necessitating the development of new AD models. The transgenic (TG) TgF344-AD rat has been reported to develop age-dependent AD features including neuronal loss and neurofibrillary tangles, despite only expressing APP and PSEN1 mutations, suggesting an improved modelling of AD hallmarks. Alterations in neuronal networks as well as learning performance and cognition tasks have been reported in this model, but none have combined a longitudinal, multimodal approach across multiple centres, which mimics the approaches commonly taken in clinical studies. We therefore aimed to further characterise the progression of AD-like pathology and cognition in the TgF344-AD rat from young-Adults (6 months (m)) to mid-(12 m) and advanced-stage (18 m, 25 m) of the disease. Methods: TgF344-AD rats and wild-Type (WT) littermates were imaged at 6 m, 12 m and 18 m with [18F]DPA-714 (TSPO, neuroinflammation), [18F]Florbetaben (A) and [18F]ASEM (7-nicotinic acetylcholine receptor) and with magnetic resonance spectroscopy (MRS) and with (S)-[18F]THK5117 (Tau) at 15 and 25 m. Behaviour tests were also performed at 6 m, 12 m and 18 m. Immunohistochemistry (CD11b, GFAP, A, NeuN, NeuroChrom) and Tau (S)-[18F]THK5117 autoradiography, immunohistochemistry and Western blot were also performed. Results: [18F]DPA-714 positron emission tomography (PET) showed an increase in neuroinflammation in TG vs wildtype animals from 12 m in the hippocampus (+11%), and at the advanced-stage AD in the hippocampus (+12%), the thalamus (+11%) and frontal cortex (+14%). This finding coincided with strong increases in brain microgliosis (CD11b) and astrogliosis (GFAP) at these time-points as assessed by immunohistochemistry. In vivo [18F]ASEM PET revealed an age-dependent increase uptake in the striatum and pallidum/nucleus basalis of Meynert in WT only, similar to that observed with this tracer in humans, resulting in TG being significantly lower than WT by 18 m. In vivo [18F]Florbetaben PET scanning detected A accumulation at 18 m, and (S)-[18F]THK5117 PET revealed subsequent Tau accumulation at 25m in hippocampal and cortical regions. A plaques were low but detectable by immunohistochemistry from 6 m, increasing further at 12 and 18 m with Tau-positive neurons adjacent to A plaques at 18 m. NeuroChrom (a pan neuronal marker) immunohistochemistry revealed a loss of neuronal staining at the A plaques locations, while NeuN labelling revealed an age-dependent decrease in hippocampal neuron number in both genotypes. Behavioural assessment using the novel object recognition task revealed that both WT & TgF344-AD animals discriminated the novel from familiar object at 3 m and 6 m of age. However, low levels of exploration observed in both genotypes at later time-points resulted in neither genotype successfully completing the task. Deficits in social interaction were only observed at 3 m in the TgF344-AD animals. By in vivo MRS, we showed a decrease in neuronal marker N-Acetyl-Aspartate in the hippocampus at 18 m (-18% vs age-matched WT, and-31% vs 6 m TG) and increased Taurine in the cortex of TG (+35% vs age-matched WT, and +55% vs 6 m TG). Conclusions: This multi-centre multi-modal study demonstrates, for the first time, alterations in brain metabolites, cholinergic receptors and neuroinflammation in vivo in this model, validated by robust ex vivo approaches. Our data confirm that, unlike mouse models, the TgF344-AD express Tau pathology that can be detected via PET, albeit later than by ex vivo techniques, and is a useful model to assess and longitudinally monitor early neurotransmission dysfunction and neuroinflammation in AD
PET-BIDS, an extension to the brain imaging data structure for positron emission tomography
The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets
Neurite density is reduced in the presymptomatic phase of C9orf72 disease
OBJECTIVE: To assess the added value of neurite orientation dispersion and density imaging (NODDI) compared with conventional diffusion tensor imaging (DTI) and anatomical MRI to detect changes in presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation. METHODS: The PREV-DEMALS (Predict to Prevent Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis) study is a prospective, multicentre, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Sixty-seven participants (38 presymptomatic C9orf72 mutation carriers (C9+) and 29 non-carriers (C9-)) were included in the present cross-sectional study. Each participant underwent one single-shell, multishell diffusion MRI and three-dimensional T1-weighted MRI. Volumetric measures, DTI and NODDI metrics were calculated within regions of interest. Differences in white matter integrity, grey matter volume and free water fraction between C9+ and C9- individuals were assessed using linear mixed-effects models. RESULTS: Compared with C9-, C9+ demonstrated white matter abnormalities in 10 tracts with neurite density index and only 5 tracts with DTI metrics. Effect size was significantly higher for the neurite density index than for DTI metrics in two tracts. No tract had a significantly higher effect size for DTI than for NODDI. For grey matter cortical analysis, free water fraction was increased in 13 regions in C9+, whereas 11 regions displayed volumetric atrophy. CONCLUSIONS: NODDI provides higher sensitivity and greater tissue specificity compared with conventional DTI for identifying white matter abnormalities in the presymptomatic C9orf72 carriers. Our results encourage the use of neurite density as a biomarker of the preclinical phase. TRIAL REGISTRATION NUMBER: NCT02590276
Morphomechanical Innovation Drives Explosive Seed Dispersal
How mechanical and biological processes are coordinated across cells, tissues, and organs to produce complex traits is a key question in biology. Cardamine hirsuta, a relative of Arabidopsis thaliana, uses an explosive mechanism to disperse its seeds. We show that this trait evolved through morphomechanical innovations at different spatial scales. At the organ scale, tension within the fruit wall generates the elastic energy required for explosion. This tension is produced by differential contraction of fruit wall tissues through an active mechanism involving turgor pressure, cell geometry, and wall properties of the epidermis. Explosive release of this tension is controlled at the cellular scale by asymmetric lignin deposition within endocarp b cells-a striking pattern that is strictly associated with explosive pod shatter across the Brassicaceae plant family. By bridging these different scales, we present an integrated mechanism for explosive seed dispersal that links evolutionary novelty with complex trait innovation
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge
Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org
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