An Ontology-Based Recommender System with an Application to the Star Trek Television Franchise

Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organizations of users and items to enhance browsing, recommendation, and profile construction. While ontology-based approaches address the shortcomings of their collaborative filtering counterparts, ontological organizations of items can be difficult to obtain for items that mostly belong to the same category (e.g., television series episodes). In this paper, we present an ontology-based recommender system that integrates the knowledge represented in a large ontology of literary themes to produce fiction content recommendations. The main novelty of this work is an ontology-based method for computing similarities between items and its integration with the classical Item-KNN (K-nearest neighbors) algorithm. As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario. This transverse evaluation provides insights into the utility of different information resources and methods for the initial stages of recommender system development. We found our proposed method to be a convenient alternative to collaborative filtering approaches for collections of mostly similar items, particularly when other content-based approaches are not applicable or otherwise unavailable. Aside from the new methods, this paper contributes a testbed for future research and an online framework to collaboratively extend the ontology of literary themes to cover other narrative content.Comment: 25 pages, 6 figures, 5 tables, minor revision

A bilingual dictionary with Semantic Mediawiki: The language Saliba's case

The language Saliba is spoken approximately by 200 indigenous in the Departments of Casanare, Arauca and Vichada, in Colombia, although the total population of this culture is around 2200 people. The Saliba language is considered a severely endangered language because most of speaker people is over 60 years old. This paper presents the ongoing work of the indigenous languages team at Caro and Cuervo Institute in developing Saliba electronic dictionary in order to revitalize this language. This work consists in creating not only an electronic dictionary, but also a space where linguistic and cultural information is stored about the language; for example, location on a map in the web of the indigenous reserves in Colombia, a grammatical sketch, personal names and toponyms, among others. We have been working with the information collected by Hortensia Estrada during 90s; written texts, recordings, drawings. Our work consists in showing all of this information of a friendly manner in the web. In order to do this, we have had to create templates for placing the information, format the written texts files into the appropriate way, improve the quality of the drawings, and segment the recordings. Furthermore, we have created learning material for Saliba indigenous children. The main software that we have used to create the dictionary is MediaWiki (free software open source) and various kinds of extensions such as: Semantic Mediawiki, Mp3Handler, GoogleMaps, among others. The Mediawiki software, adapted to lexicography needs, has become in an important tool in this project. All of these tools have enabled us to show and recover information from each lexicographic entry. Additionally, we have exported the databases of this dictionary to create smart device applications. This work was socialized and made available for Saliba communities. Indigenous Salibas were taught in the management of these tools in order that this work continues by themselves

Anotación y descripción de textos digitales sin formato de la base de casos médicos de la Facultad de Medicina de la Universidad Nacional de Colombia

La Lingüística de Corpus es una metodología empírica ya que, a partir de grandes colecciones de textos -corpus o corpora- intenta describir las regularidades de las lenguas por medio de la implementación de programas computacionales, y así, simular los usos reales de ellas. Este trabajo aplica la Lingüística de Corpus a un conjunto de historias médicas electrónicas escritas en español nunca analizado lingüísticamente. De estas historias se desconoce la forma en que están escritas por parte de los médicos y las clases de palabras que utilizan cuando describen un suceso en una subdisciplina médica. El conjunto de datos está formado por 19 subdisciplinas médicas, las cuales contienen sus propias historias. Cada historia fue anotada en tres formas diferentes, lematización, tokenización y categoría gramatical (part-of-speech) por medio de TreeTagger. Posteriormente, las frecuencias de las anotaciones se describieron mediante AntConc. Los resultados encontrados para cada subdisciplina muestran las palabras con mayor frecuencia. Las palabras de clase cerrada son las más comunes y utilizadas. Algunas partes de las historias médicas fueron anotadas erróneamente. Por otra parte, se muestran ejemplos que dan a conocer la variabilidad de uso entre expresiones y abreviaturas por parte del personal médico. Además, la escritura médica de la Universidad Nacional de Colombia corrobora la Ley de Zipf

Mouse p53-deficient cancer models as platforms for obtaining genomic predictors of human cancer clinical outcomes

Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours

Multinational prospective cohort study of rates and risk factors for ventilator-associated pneumonia over 24 years in 42 countries of Asia, Africa, Eastern Europe, Latin America, and the Middle East: Findings of the International Nosocomial Infection Control Consortium (INICC)

Objective: Rates of ventilator-associated pneumonia (VAP) in low- and middle-income countries (LMIC) are several times above those of high-income countries. The objective of this study was to identify risk factors (RFs) for VAP cases in ICUs of LMICs. Design: Prospective cohort study. Setting: This study was conducted across 743 ICUs of 282 hospitals in 144 cities in 42 Asian, African, European, Latin American, and Middle Eastern countries. Participants: The study included patients admitted to ICUs across 24 years. Results: In total, 289,643 patients were followed during 1,951,405 patient days and acquired 8,236 VAPs. We analyzed 10 independent variables. Multiple logistic regression identified the following independent VAP RFs: male sex (adjusted odds ratio [aOR], 1.22; 95% confidence interval [CI], 1.16-1.28; P <.0001); longer length of stay (LOS), which increased the risk 7% per day (aOR, 1.07; 95% CI, 1.07-1.08; P <.0001); mechanical ventilation (MV) utilization ratio (aOR, 1.27; 95% CI, 1.23-1.31; P <.0001); continuous positive airway pressure (CPAP), which was associated with the highest risk (aOR, 13.38; 95% CI, 11.57-15.48; P <.0001)Revisión por pare

Inhibition of G-protein signalling in cardiac dysfunction of intellectual developmental disorder with cardiac arrhythmia (IDDCA) syndrome

Background: Pathogenic variants of GNB5 encoding the β5 subunit of the guanine nucleotide-binding protein cause IDDCA syndrome, an autosomal recessive neurodevelopmental disorder associated with cognitive disability and cardiac arrhythmia, particularly severe bradycardia. Methods: We used echocardiography and telemetric ECG recordings to investigate consequences of Gnb5 loss in mouse. Results: We delineated a key role of Gnb5 in heart sinus conduction and showed that Gnb5-inhibitory signalling is essential for parasympathetic control of heart rate (HR) and maintenance of the sympathovagal balance. Gnb5-/- mice were smaller and had a smaller heart than Gnb5+/+ and Gnb5+/-, but exhibited better cardiac function. Lower autonomic nervous system modulation through diminished parasympathetic control and greater sympathetic regulation resulted in a higher baseline HR in Gnb5-/- mice. In contrast, Gnb5-/- mice exhibited profound bradycardia on treatment with carbachol, while sympathetic modulation of the cardiac stimulation was not altered. Concordantly, transcriptome study pinpointed altered expression of genes involved in cardiac muscle contractility in atria and ventricles of knocked-out mice. Homozygous Gnb5 loss resulted in significantly higher frequencies of sinus arrhythmias. Moreover, we described 13 affected individuals, increasing the IDDCA cohort to 44 patients. Conclusions: Our data demonstrate that loss of negative regulation of the inhibitory G-protein signalling causes HR perturbations in Gnb5-/- mice, an effect mainly driven by impaired parasympathetic activity. We anticipate that unravelling the mechanism of Gnb5 signalling in the autonomic control of the heart will pave the way for future drug screening

Early-infantile onset epilepsy and developmental delay caused by bi-allelic GAD1 variants.

Gamma-aminobutyric acid (GABA) and glutamate are the most abundant amino acid neurotransmitters in the brain. GABA, an inhibitory neurotransmitter, is synthesized by glutamic acid decarboxylase (GAD). Its predominant isoform GAD67, contributes up to ∼90% of base-level GABA in the CNS, and is encoded by the GAD1 gene. Disruption of GAD1 results in an imbalance of inhibitory and excitatory neurotransmitters, and as Gad1-/- mice die neonatally of severe cleft palate, it has not been possible to determine any potential neurological dysfunction. Furthermore, little is known about the consequence of GAD1 disruption in humans. Here we present six affected individuals from six unrelated families, carrying bi-allelic GAD1 variants, presenting with developmental and epileptic encephalopathy, characterized by early-infantile onset epilepsy and hypotonia with additional variable non-CNS manifestations such as skeletal abnormalities, dysmorphic features and cleft palate. Our findings highlight an important role for GAD1 in seizure induction, neuronal and extraneuronal development, and introduce GAD1 as a new gene associated with developmental and epileptic encephalopathy