Deciding Equivalence of Linear Tree-to-Word Transducers in Polynomial Time

We show that the equivalence of deterministic linear top-down tree-to-word transducers is decidable in polynomial time. Linear tree-to-word transducers are non-copying but not necessarily order-preserving and can be used to express XML and other document transformations. The result is based on a partial normal form that provides a basic characterization of the languages produced by linear tree-to-word transducers.Comment: short version of this paper will be published in the proceedings of the 20th Conference on Developments in Language Theory (DLT 2016), Montreal, Canad

Synaptic stimulation protects against pathological tau by enhancing lysosomal degradation

AbstractBackgroundChanges in synaptic excitability and reduced brain metabolism are among the earliest alterations associated with the development of Alzheimer's disease (AD) (Reiman et al., 2004; Sperling et al., 2009). Among different approaches for therapeutics, the stimulation of synaptic activity has been shown to be protective in models of AD, and deep brain stimulation (DBS) provides amelioration in AD patients (Sankar et al., 2015; Swaab and Bao, 2010; Tampellini, 2015). Such positive effects might reflect changes occurring at cellular levels when activity is induced, indicating that brain stimulation might promote cellular mechanisms correcting neuronal and synaptic dysfunctions. We have demonstrated that synaptic stimulation, via DBS or other methods, exerts protection in mouse models of AD and frontotemporal dementia (FTD) by enhancing autophagy, lysosomal degradation of pathologic tau, and protecting synapses (Akwa et al., 2018; Mann et al., 2018). Ongoing investigations are revealing the involvement of TFEB and its downstream genes in the enhancement of lysosomal activity upon stimulation.MethodSynaptic activity was induced by electrode implantation in the entorhinal cortex of 3xTg mice (Mann et al., 2018). Cultured neurons were prepared from E15 PS19 mouse embryos (Akwa et al., 2018) and stimulated at 14 days in vitro (Ehlers, 2003). RT‐qPCR was performed as described (Napolitano et al., 2018). Confocal immunofluorescence, Western blot and statistical analyses were performed as described (Akwa et al., 2018).ResultDBS was able to reduce levels of hyperphosphorylated and oligomeric (but not total) tau restoring levels of synaptic proteins back to wild‐type in 3xTg mice. Pathological tau clearance required lysosmal activity, which was enhanced by synaptic stimulation. Trascription factor EB (TFEB) (Sardiello et al., 2009) plays a pivotal role in regulating lysosomal biogenesis and autophagy, and is involved in activity‐driven tau degradation. Indeed, our recent RT‐qPCR data analyses revealed increase expressions of TFEB downstream genes, including ATP6‐V1H and ATP6‐V0D1, in neurons during synaptic stimulation.ConclusionThe enhancement of lysosomal degradation by the involvement TFEB and related genes demonstrated positive effects of DBS/synaptic stimulation at cellular and molecular level against pathological tau

Stimulation of synaptic activity promotes TFEB-mediated clearance of pathological MAPT/Tau in cellular and mouse models of tauopathies

Synapses represent an important target of Alzheimer disease (AD), and alterations of their excitability are among the earliest changes associated with AD development. Synaptic activation has been shown to be protective in models of AD, and deep brain stimulation (DBS), a surgical strategy that modulates neuronal activity to treat neurological and psychiatric disorders, produced positive effects in AD patients. However, the molecular mechanisms underlying the protective role(s) of brain stimulation are still elusive. We have previously demonstrated that induction of synaptic activity exerts protection in mouse models of AD and frontotemporal dementia (FTD) by enhancing the macroautophagy/autophagy flux and lysosomal degradation of pathological MAPT/Tau. We now provide evidence that TFEB (transcription factor EB), a master regulator of lysosomal biogenesis and autophagy, is a key mediator of this cellular response. In cultured primary neurons from FTD-transgenic mice, synaptic stimulation inhibits MTORC1 signaling, thus promoting nuclear translocation of TFEB, which, in turn, induces clearance of MAPT/Tau oligomers. Conversely, synaptic activation fails to promote clearance of toxic MAPT/Tau in neurons expressing constitutively active RRAG GTPases, which sequester TFEB in the cytosol, or upon TFEB depletion. Activation of TFEB is also confirmed in vivo in DBS-stimulated AD mice. We also demonstrate that DBS reduces pathological MAPT/Tau and promotes neuroprotection in Parkinson disease patients with tauopathy. Altogether our findings indicate that stimulation of synaptic activity promotes TFEB-mediated clearance of pathological MAPT/Tau. This mechanism, underlying the protective effect of DBS, provides encouraging support for the use of synaptic stimulation as a therapeutic treatment against tauopathies.This work was supported by the ELKARTEK [KK-2020/00034]; Spanish Ministry of Science and Innovation [PID2019-109724RB-I00]; CIBERNED [CB06/0005/0076]; T.V. is supported by AIRC, IG 2017 #20661, and Italian Ministery of University and Research grant [PRIN2020CLZ5XWTV]

Adventage of mesenchymal stem cells (MSC) expansion directly from purified bone marrow CD105^+ and CD271^+ cells

Mesenchymal Stem Cells (MSC) are employed in gene and cellular therapies. Routinely MSC are isolated from bone marrow mononuclear cells (MNC) by plastic adherence. Here we compared new isolation strategies of bone marrow MSC including immunodepletion of hematopoietic cells and immunomagnetic isolation of CD105+ and CD271+ populations. Four fractions were obtained: MNC MSC, RosetteSep-isolated MSC, CD105+ and CD271+ sorted MSC. We evaluated i) number of CFU-F colonies, ii) cell phenotype, iii) in vitro differentiation of expanded cells and iv) expression of osteo/adipogenesis related genes. Results: Average number of day 9 CFU-F colonies was the highest for CD271 positive fraction. Real-Time PCR analysis revealed expression of RUNX2, PPARgamma and N-cadherin in isolated cells, particularly high in CD271+ cells. Expression of CD105, CD166, CD44, CD73 antigens was comparable for all expanded populations (over 90%). We observed various levels of hematopoietic contamination with the highest numbers of CD45+ cells in MNC-MSC fraction and the lowest in CD105+ and CD271+ fractions. Cells of all the fractions were CD34 antigen negative. Expanded CD105 and CD271 populations showed higher level of RUNX2, osteocalcin, PTHR, leptin, PPARgamma2 and aggrecan1 genes except for alpha1 collagen. After osteogenic differentiation CD105+ and CD271+ populations showed lower expression of RUNX, PPARgamma2 and also lower expression of osteocalcin and PTHR than MNC, with comparable alpha1-collagen expression. Chondrogenic and adipogenic gene expression was higher in MNC. More clonogenic CD105+ and particularly CD271+ cells, which seem to be the most homogenous fractions based on Real-Time PCR and immunostaining data, are better suited for MSC expansion

Gene expression down-regulation in CD90+ prostate tumor-associated stromal cells involves potential organ-specific genes

<p>Abstract</p> <p>Background</p> <p>The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. The tumor-associated stroma is marked by increased expression of CD90/THY1. Isolation and characterization of these stromal cells could provide valuable insight into the biology of the tumor microenvironment.</p> <p>Methods</p> <p>Prostate CD90⁺stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between histologically normal and tumor-associated stromal cells. For comparison, stromal cells were also isolated and analyzed from the urinary bladder.</p> <p>Results</p> <p>The tumor-associated stromal cells were found to have decreased expression of genes involved in smooth muscle differentiation, and those detected in prostate but not bladder. Other differential expression between the stromal cell types included that of the CXC-chemokine genes.</p> <p>Conclusion</p> <p>CD90⁺prostate tumor-associated stromal cells differed from their normal counterpart in expression of multiple genes, some of which are potentially involved in organ development.</p

(trad auto)Vers des méthotologies chimiométriques sur l'imagerie hyperspectrale pour la détection de composés à faible dose : application à la microscopie Raman.

Hyperspectral imaging is now considered as a powerful analytical tool in the pharmaceutical environment, both during development to ensure the drug product quality and to solve production issues on commercialized products. In this thesis, Raman microscopy is used to study the distribution of actives and excipients in a pharmaceutical drug product, by especially focusing on the identification of a low dose compound. This latter product is defined as a compound which has low spatial and spectral contributions, meaning that it is scattered in a few pixels of the image and that its spectral response is mixed with the other compounds of the formulation. While most chemometric tools are based on the decomposition of statistical moments (requiring sufficient variations between samples or image pixels), some limitations have been rapidly reached. The first part of this thesis highlights the difficulty to detect a low dose compound in a product by using independent component analysis or multivariate curve resolution. Different methodologies are proposed to circumvent these limitations. For both techniques, reduction of dimensions and filtering steps appears as critical parameters of the method. The second part of the thesis focusses on the signal space to determine absence/presence compound maps or to detect pure compounds in an unknown formulation. The proposed methods are only based on the spectral space of each formulation compound. There are perfectly suitable to a low dose compound and should be well‐adapted to other analytical techniques or to other environments.L'imagerie hyperspectrale est désormais considérée comme un outil analytique à part entière dans l'industrie pharmaceutique, aussi bien au cours du développement pour assurer la qualité d'un produit que pour résoudre des problématiques de production après la mise sur le marché du médicament. Dans ces travaux, la microscopie Raman est utilisée pour étudier la distribution en principes actifs et excipients au sein d'une forme pharmaceutique solide, en se focalisant tout particulièrement sur l'identification d'un composé faiblement dosé. Ce dernier est défini comme étant un produit ayant de faibles contributions spatiales et spectrales, signifiant qu'il est distribué dans quelques pixels de l'image avec une information spectrale peu présente dans un spectre de mélange. Alors que la plupart des algorithmes chimiométriques se basent sur la décomposition de moments statistiques, nécessitant une variation suffisante entre les échantillons (les pixels d'une image), les limites de ces outils pour résoudre ce cas spécifique sont rapidement atteintes. La première partie de la thèse met en évidence les difficultés de détection d'un composé faiblement dosé en utilisant l'analyse en composantes indépendantes et la résolution multivariée de courbes. Des méthodologies de travail sont proposées pour contourner ces limitations. Pour les deux techniques, les étapes de réduction de dimensions apparaissent comme des paramètres critiques de la méthode. La seconde partie de la thèse se focalise sur l'espace des signaux pour déterminer des cartes d'absence/présence de constituants ou pour détecter des constituants dans une formulation inconnue, en se basant sur des espaces spectraux portant une information relative aux constituants de la formulation. Les techniques proposées sont parfaitement adaptées à la détection d'un composé faiblement dosé et ces méthodes pourraient être adaptées à d'autres techniques de mesure ou d'autres domaines d'application

Approche itérative pour la détection de composé dans un produit pharmaceutique inconnu : application à l'imagerie Raman

International audienceRaman chemical imaging provides both spectral and spatial information on a pharmaceutical drug product. Even if the main objective of chemical imaging is to obtain distribution maps of each formulation compound, identification of pure signals in a mixture dataset remains of huge interest. In this work, an iterative approach is proposed to identify the compounds in a pharmaceutical drug product, assuming that the chemical composition of the product is not known by the analyst and that a low dose compound can be present in the studied medicine. The proposed approach uses a spectral library, spectral distances and orthogonal projections to iteratively detect pure compounds of a tablet. Since the proposed method is not based on variance decomposition, it should be well adapted for a drug product which contains a low dose product, interpreted as a compound located in few pixels and with low spectral contributions. The method is tested on a tablet specifically manufactured for this study with one active pharmaceutical ingredient and five excipients. A spectral library, constituted of 24 pure pharmaceutical compounds, is used as a reference spectral database. Pure spectra of active and excipients, including a modification of the crystalline form and a low dose compound, are iteratively detected. Once the pure spectra are identified, multivariate curve resolution-alternating least squares process is performed on the data to provide distribution maps of each compound in the studied sample. Distributions of the two crystalline forms of active and the five excipients were in accordance with the theoretical formulation

Utilisation de la microscopie Raman et des méthodes chimiométriques pour la détection de comprimés contrefaits

National audienceDans cet article, l'imagerie hyperspectrale Raman est utilisée pour la détection de comprimés contrefaits. Une première analyse qualitative (analyse en composante principale) basée sur la comparaison d'un composé authentique face à un comprimé suspect est réalisée. Le comprimé suspect est facilement identifié comme étant différent du comprimé de référence. Afin de déterminer les constituants du composé suspect, sans connaissance à priori des produits purs qui le composent, un algorithme de séparation de sources aveugles (analyse en composantes indépendantes) est utilisé

Application of independent component analysis on raman images of a pharmaceutical drug product: pure spectra determination and spatial distribution of constituents

Independent component analysis (ICA) was used as a blind source separation method on a Raman image of a pharmaceutical tablet. Calculations were performed without a priori knowledge concerning the formulation. The aim was to extract the pure signals from the initial data set in order to examine the distribution of actives and major excipients within the tablet. As a method based on the decomposition of a matrix of mixtures of several components, the number of independent component to choose is a critical step of the analysis. The ICA_by_blocks method, based on the calculation of several models using an increasing number of independent components on initial matrix blocks, was used. The calculated ICA signals were compared with the pure spectra of the formulation compounds. High correlations between the two active principal ingredient spectra and their corresponding calculated signals were observed giving a good overview of the distributions of these compounds within the tablet. Information from the major excipients (lactose and avicel) was found in several independent components but the ICA approach provides high level of information concerning their distribution within the tablet. However, the results could vary considerably by changing the number of independent components or the preprocessing method. Indeed, it was shown that under-decomposition of the matrix could lead to better signal quality (compared to the pure spectra) but in that case the contributions due to minor components or effects were not correctly identified and extracted. On the contrary, over-decomposition of the original dataset could provide information about low concentration compounds at the expense of some loss of signal interpretability for the other compounds

Mise en place de contrainte de rang local par projection orthogonale pour l'analyse de résolution des images : application à la détection de composés minoritaires dans des produits pharmaceutiques

International audienceRaman chemical imaging provides chemical and spatial information about pharmaceutical drug product. By using resolution methods on acquired spectra, the objective is to calculate pure spectra and distribution maps of image compounds. With multivariate curve resolution-alternating least squares, constraints are used to improve the performance of the resolution and to decrease the ambiguity linked to the final solution. Non negativity and spatial local rank constraints have been identified as the most powerful constraints to be used. In this work, an alternative method to set local rank constraints is proposed. The method is based on orthogonal projections pretreatment. For each drug product compound, raw Raman spectra are orthogonally projected to a basis including all the variability from the formulation compounds other than the product of interest. Presence or absence of the compound of interest is obtained by observing the correlations between the orthogonal projected spectra and a pure spectrum orthogonally projected to the same basis. By selecting an appropriate threshold, maps of presence/absence of compounds can be set up for all the product compounds. This method appears as a powerful approach to identify a low dose compound within a pharmaceutical drug product. The maps of presence/absence of compounds can be used as local rank constraints in resolution methods, such as multivariate curve resolution-alternating least squares process in order to improve the resolution of the system. The method proposed is particularly suited for pharmaceutical systems, where the identity of all compounds in the formulations is known and, therefore, the space of interferences can be well defined