Towards a unified model for symbolic knowledge extraction with hypercube-based methods

The XAI community is currently studying and developing symbolic knowledge-extraction (SKE) algorithms as a means to produce human-intelligible explanations for black-box machine learning predictors, so as to achieve believability in human-machine interaction. However, many extraction procedures exist in the literature, and choosing the most adequate one is increasingly cumbersome, as novel methods keep on emerging. Challenges arise from the fact that SKE algorithms are commonly defined based on theoretical assumptions that typically hinder practical applicability. This paper focuses on hypercube-based SKE methods, a quite general class of extraction techniques mostly devoted to regression-specific tasks. We first show that hypercube-based methods are flexible enough to support classification problems as well, then we propose a general model for them, and discuss how they support SKE on datasets, predictors, or learning tasks of any sort. Empirical examples are reported as well – based upon the PSyKE framework –, showing the applicability of hypercube-based methods to actual classification tasks

Hypercube-Based Methods for Symbolic Knowledge Extraction: Towards a Unified Model

Symbolic knowledge-extraction (SKE) algorithms proposed by the XAI community to obtain human-intelligible explanations for opaque machine learning predictors are currently being studied and developed with growing interest, also in order to achieve believability in interactions. However, choosing the most adequate extraction procedure amongst the many existing in the literature is becoming more and more challenging, as the amount of available methods increases. In fact, most of the proposed algorithms come with constraints over their applicability. In this paper we focus upon a quite general class of SKE techniques, namely hypercube-based methods. Despite being commonly considered regression-specific, we discuss why hypercube-based SKE methods are flexible enough to deal with classification problems as well. More generally, we propose a common generalised model for hypercube-based methods, and we show how they can be exploited to perform SKE on datasets, predictors, or learning tasks of any sort. We also report as a concrete example the implementation of the proposed generalisation in the PSyKE framework

Bioelectric State and Cell Cycle Control of Mammalian Neural Stem Cells

The concerted action of ion channels and pumps establishing a resting membrane potential has been most thoroughly studied in the context of excitable cells, most notably neurons, but emerging evidences indicate that they are also involved in controlling proliferation and differentiation of nonexcitable somatic stem cells. The importance of understanding stem cell contribution to tissue formation during embryonic development, adult homeostasis, and regeneration in disease has prompted many groups to study and manipulate the membrane potential of stem cells in a variety of systems. In this paper we aimed at summarizing the current knowledge on the role of ion channels and pumps in the context of mammalian corticogenesis with particular emphasis on their contribution to the switch of neural stem cells from proliferation to differentiation and generation of more committed progenitors and neurons, whose lineage during brain development has been recently elucidated

DOT1L promotes progenitor proliferation and primes neuronal layer identity in the developing cerebral cortex

Cortical development is controlled by transcriptional programs, which are orchestrated by transcription factors. Yet, stable inheritance of spatiooral activity of factors influencing cell fate and localization in different layers is only partly understood. Here we find that deletion of Dot1l in the murine telencephalon leads to cortical layering defects, indicating DOT1L activity and chromatin methylation at H3K79 impact on the cell cycle, and influence transcriptional programs conferring upper layer identity in early progenitors. Specifically, DOT1L prevents premature differentiation by increasing expression of genes that regulate asymmetric cell division (Vangl2, Cenpj). Loss of DOT1L results in reduced numbers of progenitors expressing genes including SoxB1 gene family members. Loss of DOT1L also leads to altered cortical distribution of deep layer neurons that express either TBR1, CTIP2 or SOX5, and less activation of transcriptional programs that are characteristic for upper layer neurons (Satb2, Pou3f3, Cux2, SoxC family members). Data from three different mouse models suggest that DOT1L balances transcriptional programs necessary for proper neuronal composition and distribution in the six cortical layers. Furthermore, because loss of DOT1L in the pre-neurogenic phase of development impairs specifically generation of SATB2-expressing upper layer neurons, our data suggest that DOT1L primes upper layer identity in cortical progenitors.Fil: Franz, Henriette. Universität Freiburg Im Breisgau; AlemaniaFil: Villarreal, Alejandro. Universität Freiburg Im Breisgau; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Heidrich, Stefanie. Universität Freiburg Im Breisgau; AlemaniaFil: Videm, Pavankumar. Universität Freiburg Im Breisgau; AlemaniaFil: Kilpert, Fabian. Max Planck Institute Of Immunobiology And Epigenetics; AlemaniaFil: Mestres, Ivan. Technical University Dresden; AlemaniaFil: Calegari, Federico. Technical University Dresden; AlemaniaFil: Backofen, Rolf. Universidad de Copenhagen; Dinamarca. Universität Freiburg Im Breisgau; AlemaniaFil: Manke, Thomas. Max Planck Institute Of Immunobiology And Epigenetics; AlemaniaFil: Vogel, Tanja. Universität Freiburg Im Breisgau; Alemani

Defective Secretion of Islet Hormones in Chromogranin-B Deficient Mice

Granins are major constituents of dense-core secretory granules in neuroendocrine cells, but their function is still a matter of debate. Work in cell lines has suggested that the most abundant and ubiquitously expressed granins, chromogranin A and B (CgA and CgB), are involved in granulogenesis and protein sorting. Here we report the generation and characterization of mice lacking chromogranin B (CgB-ko), which were viable and fertile. Unlike neuroendocrine tissues, pancreatic islets of these animals lacked compensatory changes in other granins and were therefore analyzed in detail. Stimulated secretion of insulin, glucagon and somatostatin was reduced in CgB-ko islets, in parallel with somewhat impaired glucose clearance and reduced insulin release, but normal insulin sensitivity in vivo. CgB-ko islets lacked specifically the rapid initial phase of stimulated secretion, had elevated basal insulin release, and stored and released twice as much proinsulin as wildtype (wt) islets. Stimulated release of glucagon and somatostatin was reduced as well. Surprisingly, biogenesis, morphology and function of insulin granules were normal, and no differences were found with regard to β-cell stimulus-secretion coupling. We conclude that CgB is not required for normal insulin granule biogenesis or maintenance in vivo, but is essential for adequate secretion of islet hormones. Consequentially CgB-ko animals display some, but not all, hallmarks of human type-2 diabetes. However, the molecular mechanisms underlying this defect remain to be determined

Ingeniería Dirigida por Modelos Aplicada al Control Automático del Almacenamiento en Silos Bolsa

La preservación de granos en bolsas plásticas herméticas, conocidas como silos bolsa, es una estrategia de almacenamiento de gran expansión en Argentina, Uruguay y Chile. Este tipo de almacenamiento brinda una solución de bajo costo que permite aumentar la vida útil de los granos almacenados, disminuyendo los efectos dañinos del clima, insectos y microorganismos. Las condiciones de almacenamiento pueden mejorarse monitoreando y manteniendo niveles adecuados de temperatura y humedad, entre otros factores internos de los silos bolsa. En este artículo presentamos una infraestructura para la construcción automática de sistemas de monitoreo de las condiciones internas de los granos almacenados en silos bolsa. Los sistemas permiten registrar mediciones de las condiciones internas de los silos bolsa utilizando sensores y monitorear la evolución de estas condiciones. La infraestructura fue concebida siguiendo los lineamientos del paradigma de Ingeniería Dirigida por Modelos. Para ello, se definió un lenguaje de dominio específico que permite configurar distintos sistemas de monitoreo, los cuales se construyen automáticamente a partir de dichas configuraciones.The preservation of grains in hermetic plastic bags, also known as silobags, is a widespread strategy in Argentina, Uruguay and Chile. This type of storage provides a cost effective solution that can increase the useful life of the stored grains, reducing the harmful effects of weather, insects and microorganisms. The storage conditions can be improved monitoring and maintaining adequate levels of temperature and humidity, among other factors within the silobags. This paper presents a framework for the automatic construction of systems for monitoring the internal conditions of grain stored in silobags. The systems can record measurements of the internal conditions of the silobag using sensors and monitor the evolution of these conditions. The infrastructure was designed using the Model Driven Engineering paradigm. For this purpose, a domain-specific language was defined that allows the configuration of different monitoring systems, which are automatically constructed from these settings.Sociedad Argentina de Informática e Investigación Operativ

Overexpression of cdk4 and cyclinD1 triggers greater expansion of neural stem cells in the adult mouse brain

Inducible alterations in expression of cyclinD1 and cdk4 in the adult mouse hippocampus allow temporal control and manipulation of neurogenesis