Serum Neudesin Levels in Obese Adolescents

Objective: Advances in knowledge of neurotrophic factors are now revealing the complex control of energy homeostasis and appetite, as well as the crucial role these factors play in nervous system function. The aim of this study was to assess serum levels of neudesin in adolescents with obesity and to examine the relationship between these levels and metabolic outcomes. Methods: Adolescents, aged 10-17 years were enrolled. Subjects were divided into normal weight, obese and morbidly obese subgroups. Serum neudesin concentrations were compared between the groups. Results: In total, 88 adolescents were recruited, of whom 30 (34.1%) were normal weight, 15 (17.0%) were obese and 43 (48.9%) were morbidly obese. Neudesin levels were significantly lower in obese adolescents than in the control group (p=0.013). A correlation analysis applied to the whole study group revealed a negative correlation between serum neudesin concentration and body mass index (BMI) z scores (r=-0.40, p<0.001). Serum neudesin levels tended to increase in adolescents with metabolic syndrome, insulin resistance, dyslipidaemia, and hypertension but the differences were not significant (p=0.259, p=0.246, p=0.259, and p=0.523, respectively). Conclusion: Serum neudesin levels were significantly correlated with BMI z score in obese adolescents. Generally, serum neudesin levels were low in obese and morbidly obese adolescents and tended to increase with the appearance of metabolic disorders. Both obesity and associated metabolic disorders have multifactorial causes. Therefore, we suggest that the role of the neudesin molecule in the regulatory mechanisms of obesity and metabolic disorders should be further investigated with well-designed studies enrolling larger groups

Relapse of minimal change disease after inactivated SARS-CoV-2 vaccination: case report

[No Abstract Available

Scale development for pre-service mathematics teachers’ perceptions related to their pedagogical content knowledge

The purpose of this study is to develop a scale to determine pre-service mathematics teachers’ perceptions related to their pedagogical content knowledge. Firstly, a preliminary perception scale of pedagogical content knowledge was constructed and then administered to 112 pre-service mathematics teachers who were enrolled in a mathematics teacher education programme. Exploratory and confirmatory factor analysis, item analysis, correlation analysis, internal consistency and descriptive statistic techniques were used to analyse the data. Then validity and reliability of the scale were investigated. The analyses resulted in the development of a five-factor scale of 17 items that was proved valid and reliable. We contend that the scale developed has the merit to contribute to pre-service teachers’ self-awareness by revealing their perceptions regarding their pedagogical content knowledge.Keywords: pedagogical content knowledge, pre-service mathematics teachers,scale developmen

Ontology-based data access with a horn fragment of metric temporal logic

We advocate datalogMTL, a datalog extension of a Horn fragment of the metric temporal logic MTL, as a language for ontology-based access to temporal log data. We show that datalogMTL is EXPSPACE-complete even with punctual intervals, in which case MTL is known to be undecidable. Nonrecursive datalogMTL turns out to be PSPACE-complete for combined complexity and in AC0 for data complexity. We demonstrate by two real-world use cases that nonrecursive datalogMTL programs can express complex temporal concepts from typical user queries and thereby facilitate access to log data. Our experiments with Siemens turbine data and MesoWest weather data show that datalogMTL ontology-mediated queries are efficient and scale on large datasets of up to 11GB

Children's Foreign Language Anxiety Scale: Preliminary Tests of Reliability and Validity

Foreign language anxiety (FLA), which constitutes a serious problem in the foreign language learning process, has been mainly seen as a research issue regarding adult language learners, while it has been overlooked in children. This is because there is a lack of appropriate tools to measure FLA among children, whereas there are many studies on the scales that aim to measure anxiety levels among adult learners. Thus, the current study aims to conduct the preliminary tests of reliability and validity of the Children's Foreign Language Anxiety Scale (CFLAS) and to report on the pilot examination of reliability, validity and factor structure of the CFLAS. The findings of the pilot study show that CFLAS is a reliable and valid tool to measure FLA levels among children who learn English as a foreign language (EFL) within the age range of 7-12 in a Turkish EFL context

A Goal Oriented Navigation System Using Vision

This paper addresses a goal oriented navigation framework in a behavior-based manner for autonomous systems. The framework is mainly designed based on a behavioral architecture and relies on a monocular vision camera to obtain the location of goal. The framework employs a virt ual physic based method to steer the robot towards the goal while avoiding unknown obstacles, located along its path. Simulation results validate the performance of the proposed framework

Querying log data with Metric Temporal Logic

We propose a novel framework for ontology-based access to temporal log data using a datalog extension datalogMTL of a Horn fragment of the metric temporal logic MTL. We show that datalogMTL is ExpSpace-complete even with punctual intervals, in which case full MTL is known to be undecidable. We also prove that nonrecursive datalogMTL is PSpace-complete for combined complexity and in AC0 for data complexity. We demonstrate by two real-world use cases that nonrecursive datalogMTL programs can express complex temporal concepts from typical user queries and thereby facilitate access to temporal log data. Our experiments with Siemens turbine data and MesoWest weather data show that datalogMTL ontology-mediated queries are efficient and scale on large datasets of up to 8.3GB

Primary tumor-induced immunity eradicates disseminated tumor cells in syngeneic mouse model

WOS: 000462721900029PubMed ID: 30926774Although clinically apparent metastasis is associated with late stages of cancer development, micro-metastatic dissemination may be an early event. However, the fate of these early disseminated tumor cells (DTC) remains elusive. We show that despite their capacity to disseminate into secondary organs, 4T1 tumor models develop overt metastasis while EMT6-tumor bearing mice clear DTCs shed from primary tumors as well as those introduced by intravenous (IV) injection. Following the surgical resection of primary EMT6 tumors, mice do not develop detectable metastasis and reject IV-injected tumor cells. In contrast, these cells readily grow and metastasize in immuno-deficient athymic or Rag2(-/- )mice, an effect mimicked by CD8(+) T-cell depletion in immunocompetent mice. Furthermore, recombinant G-CSF or adoptive transfer of granulocytic-MDSCs isolated from 4T1 tumor-bearing mice, induce metastasis by suppressing CD8(+) T-cells in EMT6-primed mice. Our studies support the concept of immune surveillance providing molecular insights into the immune mechanisms during tumor progression.Georgia Cancer Center; Forbes Institute research fund; Bridge Fund by Augusta University Research Inc.; American Cancer Society Institutional fundWe gratefully acknowledge the generous help from Flow Cytometry, Genomics Core facilities, and Labaratory of Animal Services. We thank Drs. Rafi Ahmed and Paulo C. Rodriguez for insightful discussions and comments, Dr. Iskander Asm for for helping with and training of our staff on the tail vein injections. This work was supported by start up funds to H.K. by Georgia Cancer Center. Additional research fundings to H.K. provided by American Cancer Society Institutional fund, Forbes Institute research fund, and Bridge Fund by Augusta University Research Inc

Two-dimensional rule language for querying sensor log data: a framework and use cases

Motivated by two industrial use cases that involve detecting events of interest in (asynchronous) time series from sensors in manufacturing rigs and gas turbines, we design an expressive rule language DslD equipped with interval aggregate functions (such as weighted average over a time interval), Allen’s interval relations and various metric constructs. We demonstrate how to model events in the uses cases in terms of DslD programs. We show that answering DslD queries in our use cases can be reduced to evaluating SQL queries. Our experiments with the use cases, carried out on the Apache Spark system, show that such SQL queries scale well on large real-world datasets

The virtual knowledge graph system Ontop

Ontop is a popular open-source virtual knowledge graph system that can expose heterogeneous data sources as a unified knowledge graph. Ontop has been widely used in a variety of research and industrial projects. In this paper, we describe the challenges, design choices, new features of the latest release of Ontop v4, summarizing the development efforts of the last 4 years