Role of left inferior prefrontal cortex in retrieval of semantic knowledge: A reevaluation

A number of neuroimaging findings have been interpreted as evidence that the left inferior frontal gyrus (IFG) subserves retrieval of semantic knowledge. We provide a fundamentally different interpretation, that it is not retrieval of semantic knowledge per se that is associated with left IFG activity but rather selection of information among competing alternatives from semantic memory. Selection demands were varied across three semantic tasks in a single group of subjects. Functional magnetic resonance imaging signal in overlapping regions of left IFG was dependent on selection demands in all three tasks. In addition, the degree of semantic processing was varied independently of selection demands in one of the tasks. The absence of left IFG activity for this comparison counters the argument that the effects of selection can be attributed solely to variations in degree of semantic retrieval. Our findings suggest that it is selection, not retrieval, of semantic knowledge that drives activity in the left IFG.

Statistical methods for characterizing similarities and differences between semantic structures

This paper describes a variety of statistical methods for obtaining precise quantitative estimates of the similarities and differences in the structures of semantic domains in different languages. The methods include comparing mean correlations within and between groups, principal components analysis of interspeaker correlations, and analysis of variance of speaker by question data. Methods for graphical displays of the results are also presented. The methods give convergent results that are mutually supportive and equivalent under suitable interpretation. The methods are illustrated on the semantic domain of emotion terms in a comparison of the semantic structures of native English and native Japanese speaking subjects. We suggest that, in comparative studies concerning the extent to which semantic structures are universally shared or culture-specific, both similarities and differences should be measured and compared rather than placing total emphasis on one or the other polar position.

Spermatogonial stem cell enrichment by multiparameter selection of mouse testis cells

The spermatogonial stem cell initiates and maintains spermatogenesis in the testis. To perform this role, the stem cell must self replicate as well as produce daughter cells that can expand and differentiate to form spermatozoa. Despite the central importance of the spermatogonial stem cell to male reproduction, little is known about its morphological or biochemical characteristics. This results, in part, from the fact that spermatogonial stem cells are an extremely rare cell population in the testis, and techniques for their enrichment are just beginning to be established. In this investigation, we used a multiparameter selection strategy, combining the in vivo cryptorchid testis model with in vitro fluorescence-activated cell sorting analysis. Cryptorchid testis cells were fractionated by fluorescence-activated cell sorting analysis based on light-scattering properties and expression of the cell surface molecules α6-integrin, αv-integrin, and the c-kit receptor. Two important observations emerged from these analyses. First, spermatogonial stem cells from the adult cryptorchid testis express little or no c-kit. Second, the most effective enrichment strategy, in this study, selected cells with low side scatter light-scattering properties, positive staining for α6-integrin, and negative or low αv-integrin expression, and resulted in a 166-fold enrichment of spermatogonial stem cells. Identification of these characteristics will allow further purification of these valuable cells and facilitate the investigation of molecular mechanisms governing spermatogonial stem cell self renewal and hierarchical differentiation.

Enrichment for murine keratinocyte stem cells based on cell surface phenotype

The identification and physical isolation of epithelial stem cells is critical to our understanding of their growth regulation during homeostasis, wound healing, and carcinogenesis. These stem cells remain poorly characterized because of the absence of specific molecular markers that permit us to distinguish them from their progeny, the transit amplifying (TA) cells, which have a more restricted proliferative potential. Cell kinetic analyses have permitted the identification of murine keratinocyte stem cells (KSCs) as slowly cycling cells that retain [3H]thymidine ([3H]Tdr) label, termed label-retaining cells (LRCs), whereas TA cells are visualized as rapidly cycling cells after a single pulse of [3H]Tdr, termed pulse-labeled cells (PLCs). Here, we report on the successful separation of KSCs from TA cells through the combined use of in vivo cell kinetic analysis and fluorescence-activated cell sorting. Specifically, we demonstrate that murine dorsal keratinocytes characterized by their high levels of α6 integrin and low to undetectable expression of the transferrin receptor (CD71) termed α6briCD71dim cells, are enriched for epithelial stem cells because they represent a minor (≈8%) and quiescent subpopulation of small blast-like cells, with a high nuclear:cytoplasmic ratio, containing ≈70% of label-retaining cells, the latter being a well documented characteristic of stem cells. Conversely, TA cells could be enriched in a phenotypically distinct subpopulation termed α6briCD71bri, representing the majority (≈60%) of basal keratinocytes that are actively cycling, and importantly contain ≈70% of [3H]Tdr pulse-labeled cells. Importantly, immunostaining of dorsal skin revealed the presence of CD71dim cells in the hair follicle bulge region, a well documented location for KSCs.

Does Leaf Position within a Canopy Affect Acclimation of Photosynthesis to Elevated CO2?1 : Analysis of a Wheat Crop under Free-Air CO2 Enrichment

Previous studies of photosynthetic acclimation to elevated CO2 have focused on the most recently expanded, sunlit leaves in the canopy. We examined acclimation in a vertical profile of leaves through a canopy of wheat (Triticum aestivum L.). The crop was grown at an elevated CO2 partial pressure of 55 Pa within a replicated field experiment using free-air CO2 enrichment. Gas exchange was used to estimate in vivo carboxylation capacity and the maximum rate of ribulose-1,5-bisphosphate-limited photosynthesis. Net photosynthetic CO2 uptake was measured for leaves in situ within the canopy. Leaf contents of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), light-harvesting-complex (LHC) proteins, and total N were determined. Elevated CO2 did not affect carboxylation capacity in the most recently expanded leaves but led to a decrease in lower, shaded leaves during grain development. Despite this acclimation, in situ photosynthetic CO2 uptake remained higher under elevated CO2. Acclimation at elevated CO2 was accompanied by decreases in both Rubisco and total leaf N contents and an increase in LHC content. Elevated CO2 led to a larger increase in LHC/Rubisco in lower canopy leaves than in the uppermost leaf. Acclimation of leaf photosynthesis to elevated CO2 therefore depended on both vertical position within the canopy and the developmental stage.

Neural basis of lexical-semantic processing and integration of symbolic gestures with words

Three studies investigated the relation between symbolic gestures and words, aiming at discover the neural basis and behavioural features of the lexical semantic processing and integration of the two communicative signals. The first study aimed at determining whether elaboration of communicative signals (symbolic gestures and words) is always accompanied by integration with each other and, if present, this integration can be considered in support of the existence of a same control mechanism. Experiment 1 aimed at determining whether and how gesture is integrated with word. Participants were administered with a semantic priming paradigm with a lexical decision task and pronounced a target word, which was preceded by a meaningful or meaningless prime gesture. When meaningful, the gesture could be either congruent or incongruent with word meaning. Duration of prime presentation (100, 250, 400 ms) randomly varied. Voice spectra, lip kinematics, and time to response were recorded and analyzed. Formant 1 of voice spectra, and mean velocity in lip kinematics increased when the prime was meaningful and congruent with the word, as compared to meaningless gesture. In other words, parameters of voice and movement were magnified by congruence, but this occurred only when prime duration was 250 ms. Time to response to meaningful gesture was shorter in the condition of congruence compared to incongruence. Experiment 2 aimed at determining whether the mechanism of integration of a prime word with a target word is similar to that of a prime gesture with a target word. Formant 1 of the target word increased when word prime was meaningful and congruent, as compared to meaningless congruent prime. Increase was, however, present for whatever prime word duration. In the second study, experiment 3 aimed at determining whether symbolic prime gesture comprehension makes use of motor simulation. Transcranial Magnetic Stimulation was delivered to left primary motor cortex 100, 250, 500 ms after prime gesture presentation. Motor Evoked Potential of First Dorsal Interosseus increased when stimulation occurred 100 ms post-stimulus. Thus, gesture was understood within 100ms and integrated with the target word within 250 ms. Experiment 4 excluded any hand motor simulation in order to comprehend prime word. The effect of the prior presentation of a symbolic gesture on congruent target word processing was investigated in study 3. In experiment 5, symbolic gestures were presented as primes, followed by semantically congruent target word or pseudowords. In this case, lexical-semantic decision was accompanied by a motor simulation at 100ms after the onset of the verbal stimuli. Summing up, the same type of integration with a word was present for both prime gesture and word. It was probably subsequent to understanding of the signal, which used motor simulation for gesture and direct access to semantics for words. However, gesture and words could be understood at the same motor level through simulation if words were preceded by an adequate gestural context. Results are discussed in the prospective of a continuum between transitive actions and emblems, in parallelism with language; the grounded/symbolic content of the different signals evidences relation between sensorimotor and linguistic systems, which could interact at different levels.

Automatic extraction of syntactic semantic patterns for multilingual resources

In this paper we present an automatic system for the extraction of syntactic semantic patterns applied to the development of multilingual processing tools. In order to achieve optimum methods for the automatic treatment of more than one language, we propose the use of syntactic semantic patterns. These patterns are formed by a verbal head and the main arguments, and they are aligned among languages. In this paper we present an automatic system for the extraction and alignment of syntactic semantic patterns from two manually annotated corpora, and evaluate the main linguistic problems that we must deal with in the alignment process.

A general proposal to multilingual information access based on syntactic-semantic patterns

In the last few years, there has been a wide development in the research on textual information systems. The goal is to improve these systems in order to allow an easy localization, treatment and access to the information stored in digital format (Digital Databases, Documental Databases, and so on). There are lots of applications focused on information access (for example, Web-search systems like Google or Altavista). However, these applications have problems when they must access to cross-language information, or when they need to show information in a language different from the one of the query. This paper explores the use of syntactic-sematic patterns as a method to access to multilingual information, and revise, in the case of Information Retrieval, where it is possible and useful to employ patterns when it comes to the multilingual and interactive aspects. On the one hand, the multilingual aspects that are going to be studied are the ones related to the access to documents in different languages from the one of the query, as well as the automatic translation of the document, i.e. a machine translation system based on patterns. On the other hand, this paper is going to go deep into the interactive aspects related to the reformulation of a query based on the syntactic-semantic pattern of the request.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

Developing Semantic Rich Internet Applications with the Sm4RIA Extension for OIDE

This paper introduces the Sm4RIA Extension for OIDE, which implements the Sm4RIA approach in OIDE (OOH4RIA Integrated Development Environment). The application, based on the Eclipse framework, supports the design of the Sm4RIA models as well as the model-to-model and model-to-text transformation processes that facilitate the generation of Semantic Rich Internet Applications, i.e., RIA applications capable of sharing data as Linked data and consuming external data from other sources in the same manner. Moreover, the application implements mechanisms for the creation of RIA interfaces from ontologies and the automatic generation of administration interfaces for a previously design application.

The role of statistical and semantic features in single-document extractive summarization

This paper reports on the further results of the ongoing research analyzing the impact of a range of commonly used statistical and semantic features in the context of extractive text summarization. The features experimented with include word frequency, inverse sentence and term frequencies, stopwords filtering, word senses, resolved anaphora and textual entailment. The obtained results demonstrate the relative importance of each feature and the limitations of the tools available. It has been shown that the inverse sentence frequency combined with the term frequency yields almost the same results as the latter combined with stopwords filtering that in its turn proved to be a highly competitive baseline. To improve the suboptimal results of anaphora resolution, the system was extended with the second anaphora resolution module. The present paper also describes the first attempts of the internal document data representation.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

Syntactic and Semantic Relationships in Models of Complex Systems: An Ecological Case

In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.