Miracle-dz/UniFAR-FTUs huggingface dataset:
A Thapsigargin-Sensitive Ca 2 (cid:1) Pump Is Present in the Pea Golgi Apparatus Membrane 1

The Golgi apparatus behaves as a bona fide Ca 2 (cid:1) store in animal cells and yeast ( Saccharomyces cerevisiae ); however, it is not known whether this organelle plays a similar role in plant cells. In this work, we investigated the presence of an active Ca 2 (cid:1) accumulation mechanism in the plant cell Golgi apparatus. Toward this end, we measured Ca 2 (cid:1) uptake in subcellular fractions isolated from the elongating zone of etiolated pea ( Pisum sativum ) epicotyls. Separation of organelles using sucrose gradients showed a strong correlation between the distribution of an ATP-dependent Ca 2 (cid:1) uptake activity and the Golgi apparatus marker enzyme, xyloglucan-fucosyltransferase. The kinetic parameters obtained for this activity were: the rate of maximum Ca 2 (cid:1) uptake of 2.5 nmol mg min (cid:2) 1 and an apparent K m for Ca 2 (cid:1) of 209 n m . The ATP-dependent Ca 2 (cid:1) uptake was strongly inhibited by vanadate (inhibitor concentration causing 50% inhibition [I 50 ] (cid:3) 126 (cid:1) m ) and cyclopiazonic acid (I 50 (cid:3) 0.36 nmol mg protein (cid:2) 1 ) and was not stimulated by calmodulin (1 (cid:1) m ). Addition of Cd 2 (cid:1) and Cu 2 (cid:1) at nanomolar concentration inhibited the Ca 2 (cid:1) uptake, whereas Mn 2 (cid:1) , Fe 2 (cid:1) , and Co 2 (cid:1) had no significant effect. Interestingly, the active calcium uptake was inhibited by thapsigargin (apparent I 50 (cid:3) 88 n m ), a well-known inhibitor of the endoplasmic reticulum and Golgi sarco-endoplasmic reticulum Ca 2 (cid:1) ATPase from mammalian cells. A thapsigargin-sensitive Ca 2 (cid:1) uptake activity was also detected in a cauliflower ( Brassica oleracea ) Golgi-enriched fraction, suggesting that other plants may also possess thapsigargin-sensitive Golgi Ca 2 (cid:1) pumps. To our knowledge, this is the first report of a plant Ca 2 (cid:1) pump activity that shows sensitivity to low concentrations of thapsigargin.
Transferable Domain in the G 1 Cyclin Cln2 Sufﬁcient To Switch Degradation of Sic1 from the E3 Ubiquitin Ligase SCF Cdc4 to SCF Grr1

Degradation of Saccharomyces cerevisiae G 1 cyclins Cln1 and Cln2 is mediated by the ubiquitin-proteasome pathway and involves the SCF E3 ubiquitin-ligase complex containing the F-box protein Grr1 (SCF Grr1 ). Here we identify the domain of Cln2 that confers instability and describe the signals in Cln2 that result in binding to Grr1 and rapid degradation. We demonstrate that mutants of Cln2 that lack a cluster of four Cdc28 consensus phosphorylation sites are highly stabilized and fail to interact with Grr1 in vivo. Since one of the phosphorylation sites lies within the Cln2 PEST motif, a sequence rich in proline, aspartate or glutamate, serine, and threonine residues found in many unstable proteins, we fused various Cln2 C-terminal domains containing combinations of the PEST and the phosphoacceptor motifs to stable reporter proteins. We show that fusion of the Cln2 domain to a stabilized form of the cyclin-dependent kinase inhibitor Sic1 ( (cid:1) N-Sic1), a substrate of SCF Cdc4 , results in in a phosphorylation-dependent manner. Fusion of Cln2 degradation domains to (cid:1) N-Sic1 switches degradation of Sic1 from SCF Cdc4 to SCF Grr1 (cid:1) N-Sic1 fused with a Cln2 domain containing the PEST motif and four phosphorylation sites binds to Grr1 and unstable and ubiquitinated in the phosphoacceptor domain of Cln2 to Grr1 but is not ubiquitinated small transferable domain in Cln2 that can redirect a stabilized SCF Cdc4 target for SCF Grr1 -mediated degradation by the ubiquitin-proteasome pathway.
The Protective Eﬀect of Cichorium intybus L. Hydroalcoholic Extract Against Methotrexate-Induced Oxidative Stress in Rats

Background: Methotrexate as a chemotherapy agent causes oxidative stress in the liver. Chicory ( Cichorium intybus ), a member of the Asteraceae family, is a well-known herb possessing various biological activities. Objectives: The present study was conducted to assess the protective eﬀect of Cichorium intybus extract against methotrexate-induced oxidative stress in rats. Methods: Thirty male Wistar rats were divided into ﬁve groups. The negative control group was administered 5 mL/kg of normal saline. Inthepositivecontrolgroup, normalsalinewasadministeredfor11days, andasingledoseof methotrexate(MTX;20mg/kg, i.p) was injected on the 7th day. Groups 3 - 5 received Cichorium intybus extract (CIE) at the doses of 100, 200, and 400 mg/kg p.o. , re-spectively,for11days,andasingledoseof MTXwasadministeredonthe7thday. Theanimalsweresacriﬁced24hafterthelastinjec-tion. Blood samples were withdrawn to measure serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bilirubin (TB) levels. Glutathione (GSH), malondialdehyde (MDA) levels and catalase (CAT), superoxide dismutase(SOD),andglutathioneperoxidase(GPx)activitieswereassayedinlivertissues. Aportionof thelivertissueswasusedfor histological examination. Results: The results showed a dramatic reduction in the levels of AST, ALT, ALP, GSH, CAT, SOD, and GPx and a signiﬁcant increase in the levels of TB and MDA by MTX administration. The groups pretreated with CIE showed a signiﬁcant increase in the levels of AST, ALT, ALP, GSH, CAT, SOD, and GPx and a signiﬁcant decrease in the levels of TB and MDA at all the doses, but the most signiﬁcant change was observed at the dose of 400 mg/kg (P < 0.05). Our histological ﬁndings conﬁrmed the above-mentioned results. Conclusions: The results revealed that Cichorium intybus has protective eﬀects against the liver tissue damage induced by MTX.
GTPasesMyD88-Dependent Pathways and Rac TLR4 Signaling Shapes B Cell Dynamics via

B cells use a plethora of TLR to recognize pathogen-derived ligands. These innate signals have an important function in the B cell adaptive immune response and modify their trafﬁcking and tissue location. The direct role of TLR signaling on B cell dynamics nonetheless remains almost entirely unknown. In this study, we used a state-of-the-art two-dimensional model combined with real-time microscopy to study the effect of TLR4 stimulation on mouse B cell motility in response to chemokines. We show that a minimum stimulation period is necessary for TLR4 modiﬁcation of B cell behavior. TLR4 stimulation increased B cell polarization, migration, and directionality; these increases were dependent on the MyD88 signaling pathway and did not require ERK or p38 MAPK activity downstream of TLR4. In addition, TLR4 stimulation enhanced Rac GTPase activity and promoted sustained Rac activation in response to chemokines. These results increase our understanding of the regulation of B cell dynamics by innate signals and the underlying molecular mechanisms. The Journal of Immunology , 2013, 191: 000–000.
Bone marrow-derived mononuclear cells therapy for ischemic stroke

Background: Nowadays, the cerebrovascular event is the second cause of death and the third cause of disability worldwide. In the last few decades, stem cell-based approaches are widely analyzed as a potential treatment for this disease. One of these types of cells are bone marrow-derived mononuclear cells (BMMNCs). In this review, we analyzed 9 completed clinical trials with the use of BMMNCs in patients with ischemic stroke, which we found in the clinicaltrials. gov and PubMed databases, using the keywords “stroke“ and “bone marrow mononuclear cells”. Our goal was to analyze the safety and efficiency of this therapeutic approach, as well as the optimal therapeutic time window, transplantation route and cell dose used. The best stroke phase to apply this therapy is the subacute stage. Higher numbers of CD34+ cells, derived from BMMNCs were correlated with a trend toward a better outcome. All the clinical trials support the idea that BMMNCs transplantation is a safe therapy. Conclusions: In conclusion the author points out that the autologous transplantation of BMMNCs is harmless and not associated with severe complications. Although some clinical studies stated a better outcome in patients treated with BMMNCs, further clinical trials are needed to establish their therapeutic efficiency.
1785 Cutaneous Immunization Rapidly Activates Liver Invariant V (cid:2) 14 NKT Cells Stimulating B-1 B Cells to Initiate T Cell Recruitment for Elicitation of Contact

92121 Abstract T cell recruitment to elicit contact sensitivity (CS) requires a CS-initiating process mediated by B-1 cells that produce IgM, which activates complement to promote T cell passage into the tissues. We now show that V (cid:2) 14i NKT cells induce B-1 cell activation likely by releasing IL-4 early postimmunization. The CS initiation process is absent in J (cid:2) 18 (cid:3) / (cid:3) and CD1d (cid:3) / (cid:3) NKT cell– deficient mice and is reconstituted by populations enriched for V (cid:2) 14i NKT cells. Transfers are not effective if cells are derived from IL-4 (cid:3) / (cid:3) mice. Staining with specific tetramers directly showed that hepatic V (cid:2) 14i NKT cells increase by 30 min and nearly double by 2 h postimmunization. Transfer of immune B-1 cells also reconstitutes CS responses in NKT cell–deficient mice. The B-1 cells act downstream of the V (cid:2) 14i NKT cells to restore CS initiation. In addition, IL-4 given systemically to J (cid:2) 18 (cid:3) / (cid:3) or CD1d (cid:3) / (cid:3) NKT cell–deficient mice reconstitutes elicitation of CS. Further, splenocytes from immune J (cid:2) 18 (cid:3) / (cid:3) mice produce less antigen (Ag)-specific IgM antibodies compared with sensitized WT mice. Together these findings indicate that very early after skin immunization V (cid:2) 14i NKT cells are stimulated to produce IL-4, which activates B-1 cells to produce Ag-specific IgM, subsequently needed to recruit effector T cells for elicitation of CS
Aplicação de teste de usabilidade e avaliação heurística em aparelho medidor de pressão digital de pulso

Nowadays, medical equipment available are intended to be safe, practical and efficient, and industries innovation sectors invest in new technologies in order to attract more customers through the delivery of quality and reliability. However, some details are only visible to the user's eyes. Human Factors Engineering pursuits the systems adaptation to humans needs and limitations, considering their cognition to products and systems design. In this context, this study applies Usability Tests combined with Heuristic Analysis to a Wrist Digital Blood Pressure Meter in order to validate its safety and feasibility, and also to propose improvements to the product and its instructions manual, emphasizing the importance of users understanding regarding the product’s use. As a result, the product violates some usability heuristics, such as feedback, error message, error prevention and help and documentation, as well as it presents some obstacles in the execution of certain user tasks, in which this research suggests improvements.
Sketch Prediction using Neural Networks

—Recurrent Neural Networks are the state-of-the-art algorithm for sequential data and among others used by Apples Siri and Googles Voice Search. This is because it is the first algorithm that remembers its input, due to an internal memory, which makes it perfectly suited for Machine Learning problems that involve sequential data. It is one of the algorithms behind the scenes of the amazing achievements of Deep Learning in the past few years. We present Sketch Prediction Using Neural Network, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on a dataset of human-drawn images representing many different classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust training methods for generating coherent sketch drawings in a vector format. Our goal is to train machines to draw and generalize abstract concepts in a manner similar to humans. In this work, as a ﬁrst step towards this goal, we train our model on a dataset of hand-drawn sketches, each represented as a sequence of motor actions controlling a pen: which direction to move, when to lift the pen up, and when to stop drawing. In doing so, we created a model that potentially has many applications, from assisting the creative process of an artist, to helping teach students how to draw.
Doing more with less? Balancing sampling resolution and effort in measurements of protistan growth and grazing-rates LIMNOLOGY and OCEANOGRAPHY: METHODS

The dilution-method has been key in establishing the role of protistan-grazing in marine foodwebs. Yet its laborious application limits the sampling-resolution achieved. We assessed the reliability of an abbreviated method known as the 2-point by analyzing 77 dilution-experiments performed using 4–5 dilutions in diverse biotic and abiotic conditions. Our aim was to inform practitioners on how experimental design and nonlinear feeding behaviors affect the accuracy of 2-point rate-estimates. We found good agreement between rate-estimates of both phytoplankton growth ( l ) and grazer-induced mortality ( g ) from either method, even though the comparison included experiments with nonlinear feeding-responses. The accuracy of 2-point estimates was similar to the inherent standard deviation of dilution-series estimates ( 6 (cid:2) 0.1 d 2 1 ). Nonlinear feeding-responses did not alter overall rate-estimates, negating the need for more than two dilution-levels. Decreasing dilution resulting in an increase in biomass from 10% to 40% resulting in increased biomass increased the median difference between 2-point and dilution-series estimates (cid:2) 3-fold and increased 2-point estimates’ variance (cid:2) 2-fold, both for l and g . Recognition of these biomass vs. accuracy tradeoffs enables practitioners to choose whether to procure more biomass at the expense of constraining estimate variance. Using duplicate bottles at each dilution level doubled average accuracy of 2-point estimates. The reduction in effort and water-needs afforded by the 2-point design facilitates acquisition of higher-resolution data of predation-rates across seasons, latitudes, and in response to diverse environmental conditions in the ocean, which is critically needed to decipher abiotic and biotic drivers of protistan-grazing and to parameterize protistan herbivory in global biogeochemical models.
FENEC : un corpus équilibré pour l’évaluation des entités nommées en français (FENEC : a balanced sample corpus for French named entity recognition )

Nous présentons ici FENEC (FrEnch Named-entity Evaluation Corpus), un corpus à échantillons équilibrés contenant six genres, annoté en entités nommées selon le schéma fin Quæro. Les caractéristiques de ce corpus nous permettent d’évaluer et de comparer trois outils d’annotation automatique — un à base de règles et deux à base de réseaux de neurones — en jouant sur trois dimensions : la finesse du jeu d’étiquettes, le genre des corpus, et les métriques d’évaluation.
Abstraction ou hallucination ? État des lieux et évaluation du risque pour les modèles de génération de résumés automatiques de type séquence-à-séquence (Abstraction or Hallucination ? Status and Risk assessment for sequence-to-sequence Automatic)

La génération de texte a récemment connu un très fort intérêt au vu des avancées notables dans le domaine des modèles de langage neuronaux. Malgré ces avancées, cette tâche reste difficile quand il s’agit d’un résumé automatique de texte par abstraction. Certains systèmes de résumés génèrent des textes qui ne sont pas forcément fidèles au document source. C’est sur cette thématique que porte notre étude. Nous présentons une typologie d’erreurs pour les résumés automatique et ainsi qu’une caractérisation du phénomène de l’abstraction pour les résumés de référence afin de mieux comprendre l’ampleur de ces différents phénomènes sur les entités nommées. Nous proposons également une mesure d’évaluation du risque d’erreur lorsqu’un système tente de faire des abstractions sur les entités nommées d’un document.
Correction automatique d’examens écrits par approche neuronale profonde et attention croisée bidirectionnelle (Deep Neural Networks and Bidirectional Cross-Attention for Automatic Answer Grading)

Cet article présente les systèmes développés par l’équipe LIA-LS2N dans le cadre de la campagne d’évaluation DEFT 2022 (Grouin & Illouz, 2022). Nous avons participé à la première tâche impliquant la correction automatique de copies d’étudiants à partir de références existantes. Nous proposons trois systèmes de classification reposant sur des caractéristiques extraites de plongements de mots contextuels issus d’un modèle BERT (CamemBERT). Nos approches reposent sur les concepts suivants : extraction de mesures de similarité entre les plongements de mots, attention croisée bidirectionnelle entre les plongements et fine-tuning (affinage) des plongements de mots. Les soumissions finales comprenaient deux systèmes fusionnés combinant l’attention croisée bidirectionnelle avec nos classificateurs basés sur BERT et celui sur les mesures de similarité. Notre meilleure soumission obtient une précision de 72,6 % en combinant le classifieur basé sur un modèle CamemBERT affiné et le mécanisme d’attention croisée bidirectionnelle. Ces résultats sont proches de ceux obtenus par le meilleur système de cette édition (75,6 %).
Décontextualiser des plongements contextuels pour construire des thésaurus distributionnels (Decontextualizing contextual embeddings for building distributional thesauri )

Même si les modèles de langue contextuels sont aujourd’hui dominants en traitement automatique des langues, les représentations qu’ils construisent ne sont pas toujours adaptées à toutes les utilisations. Dans cet article, nous proposons une nouvelle méthode pour construire des plongements statiques à partir de modèles contextuels. Cette méthode combine la généralisation et l’agrégation des représentations contextuelles. Nous l’évaluons pour un large ensemble de noms en anglais dans la perspective de la construction de thésaurus distributionnels pour l’extraction de relations de similarité sémantique. Finalement, nous montrons que les représentations ainsi construites et les plongements statiques natifs peuvent être complémentaires.
Auto-correction dans un analyseur neuronal par transitions : un comportement factice ? (Self-correction in a transition-based neural parser : a spurious behaviour ?)

Cette étude explore la capacité d’auto-correction dans le cas d’un analyseur neuronal par transitions. Nous définissons un oracle dynamique pour le système étudié lui apprenant à s’auto-corriger. Les performances du modèle restent identiques à celles du modèle de base, qui ne s’auto-corrige pas. En effet, il y a à peu près autant de « corrections » justes que de fautives. Les erreurs finales commises par les deux modèles sont aussi similaires. Nous montrons néanmoins que beaucoup des corrections effectuées par le modèle avec oracle dynamique coïncident avec des cas difficiles à gérer par les analyseurs automatiques. Le problème d’apprentissage d’un comportement efficace d’auto-correction retombe dans un traitement efficace de ces cas difficiles.
Remplacement de mentions pour l’adaptation d’un corpus de reconnaissance d’entités nommées à un domaine cible (Mention replacement for adapting a named entity recognition dataset to a target domain)

La reconnaissance d’entités nommées est une tâche de traitement automatique du langage naturel bien étudiée et utile dans de nombreuses applications. Dernièrement, les modèles neuronaux permettent de la résoudre avec de très bonnes performances. Cependant, les jeux de données permettant l’entraînement et l’évaluation de ces modèles se concentrent sur un nombre restreint de domaines et types de documents (articles journalistiques, internet). Or, les performances d’un modèle entraîné sur un domaine ciblé sont en général moindres dans un autre : ceux moins couverts sont donc pénalisés. Pour tenter de remédier à ce problème, cet article propose d’utiliser une technique d’augmentation de données permettant d’adapter un corpus annoté en entités nommées d’un domaine source à un domaine cible où les types de noms rencontrés peuvent être différents. Nous l’appliquons dans le cadre de la littérature de fantasy, où nous montrons qu’elle peut apporter des gains de performance.
Predicting Instructor Performance in Higher Education Using Data Mining CART Technique

— Data mining techniques and methods are analyzes the students data to build a analytical model for students performance in higher education. The data mining is a process of result patterns in the fields of relative databases. Data mining is used for arrangement of educational problems by using techiniques for measuring the student and instructor performance. In this paper we are used different classification techniques, decision tree algorithms, artificial neural networks and CART technique. These performances are very high over a datasets of composed the responses of the students to course evaluation questionnaire using precision, exactness, and specificity performance. In this system get high results compare to other techniques over CART technique. Furthermore, the analysis shows that the instructors’ success based on the students’ perception mainly depends on the interest of the students in the course. The conclusion of the study indicate the effectiveness and expressiveness of data mining models in course evaluation and higher education mining. Moreover, these findings may be used to improve measurement instruments.
Ré-ordonnancement via programmation dynamique pour l’adaptation cross-lingue d’un analyseur en dépendances (Sentence reordering via dynamic programming for cross-lingual dependency parsing )

Cet article s’intéresse au transfert cross-lingue d’analyseurs en dépendances et étudie des méthodes pour limiter l’effet potentiellement néfaste pour le transfert de divergences entre l’ordre des mots dans les langues source et cible. Nous montrons comment apprendre et implémenter des stratégies de réordonnancement, qui, utilisées en prétraitement, permettent souvent d’améliorer les performances des analyseurs dans un scénario de transfert « zero-shot ».
Classification automatique de questions spontanées vs. préparées dans des transcriptions de l’oral (Automatic Classification of Spontaneous vs)

Ce travail a pour objectif de développer un modèle linguistique pour classifier automatiquement des questions issues de transcriptions d’enregistrements provenant des corpus ESLO2 et ACSYNT en deux catégories “spontané” et “préparé”. Avant de procéder au traitement automatique, nous proposons une liste de critères définitoires et discriminants permettant de distinguer les questions parmi d’autres énoncés. Les expériences basées sur des méthodes d’apprentissage supervisé sont réalisées selon une classification multiclasse comprenant les catégories “spontané”, “préparé” et “non-question” et selon une classification binaire incluant les catégories “spontané” et “préparé” uniquement. Les meilleurs résultats pour les méthodes traditionnelles d’apprentissage automatique sont obtenus avec une régression logistique combinée aux critères linguistiques significatifs uniquement (F-score de 0.75). Pour finir, nous mettons en parallèle ces résultats avec ceux obtenus en utilisant des techniques d’apprentissage profond.
État de l’art : Liage de ressources lexicales du français (State of the art : Linking French Lexical Resources)

Les ressources lexicales informatisées constituent des données indispensables à l’élaboration d’outils et de méthodes répondant aux différentes tâches de Traitement Automatique des Langues (TAL). Celles-ci sont hétérogènes dans leur taille, leur construction et leur niveau de description linguistique. Cette variété ouvre la porte à un regroupement des ressources ou à des tentatives de liage. Dans cet article, nous présentons un état de l’art sur les ressources lexicales du français. Plus précisément, nous abordons les différentes caractéristiques d’une ressource lexicale, les ressources construites à partir de liage ainsi que les approches employées à cette fin.