Resistance to diet-induced adiposity in cannabinoid receptor-1 deficient mice is not due to impaired adipocyte function

Background: Overactivity and/or dysregulation of the endocannabinoid system (ECS) contribute to development of obesity. In vitro studies indicate a regulatory role for the cannabinoid receptor 1 (CB1) in adipocyte function and CB1-receptor deficient (CB1-/-) mice are resistant to high fat diet-induced obesity. Whether this phenotype of CB1-/- mice is related to altered fat metabolism in adipose tissue is unknown. Methods: We evaluated adipose tissue differentiation/proliferation markers and quantified lipogenic and lipolytic activities in fat tissues of CB1-/- and CB1+/+ mice fed a high-fat (HF) or a high-fat/fish oil (HF/FO) diet as compared to animals receiving a low-fat chow diet. Comparison between HF diet and HF/FO diet allowed to investigate the influence of dietary fat quality on adipose tissue biology in relation to CB1 functioning. Results: The adiposity-resistant phenotype of the CB1-/- mice was characterized by reduced fat mass and adipocyte size in HF and HF/FO-fed CB1-/- mice in parallel to a significant increase in energy expenditure as compared to CB1+/+ mice. The expression levels of adipocyte differentiation and proliferation markers were however maintained in these animals. Consistent with unaltered lipogenic gene expression, the fatty acid synthesis rates in adipose tissues from CB1-/- and CB1+/+ mice were unchanged. Whole-body and adipose-specific lipoprotein lipase (LPL) activities were also not altered in CB1-/- mice. Conclusions: These findings indicate that protection against diet-induced adiposity in CB1-deficient mice is not related to changes in adipocyte function per se, but rather results from increased energy dissipation by oxidative and non-oxidative pathways.

The BMP Antagonist Follistatin-Like 1 Is Required for Skeletal and Lung Organogenesis

Follistatin-like 1 (Fstl1) is a secreted protein of the BMP inhibitor class. During development, expression of Fstl1 is already found in cleavage stage embryos and becomes gradually restricted to mesenchymal elements of most organs during subsequent development. Knock down experiments in chicken and zebrafish demonstrated a role as a BMP antagonist in early development. To investigate the role of Fstl1 during mouse development, a conditional Fstl1 KO allele as well as a Fstl1-GFP reporter mouse were created. KO mice die at birth from respiratory distress and show multiple defects in lung development. Also, skeletal development is affected. Endochondral bone development, limb patterning as well as patterning of the axial skeleton are perturbed in the absence of Fstl1. Taken together, these observations show that Fstl1 is a crucial regulator in BMP signalling during mouse development

International Paediatric Mitochondrial Disease Scale

OBJECTIVE : There is an urgent need for reliable and universally applicable outcome measures for children with mitochondrial diseases. In this study, we aimed to adapt the currently available Newcastle Paediatric Mitochondrial Disease Scale (NPMDS) to the International Paediatric Mitochondrial Disease Scale (IPMDS) during a Delphi-based process with input from international collaborators, patients and caretakers, as well as a pilot reliability study in eight patients. Subsequently, we aimed to test the feasibility, construct validity and reliability of the IPMDS in a multicentre study. METHODS : A clinically, biochemically and genetically heterogeneous group of 17 patients (age 1.6–16 years) from five different expert centres from four different continents were evaluated in this study. RESULTS : The feasibility of the IPMDS was good, as indicated by a low number of missing items (4 %) and the positive evaluation of patients, parents and users. Principal component analysis of our small sample identified three factors, which explained 57.9 % of the variance. Good construct validity was found using hypothesis testing. The overall interrater reliability was good [median intraclass correlation coefficient for agreement between raters (ICCagreement) 0.85; range 0.23–0.99). CONCLUSION : In conclusion, we suggest using the IPMDS for assessing natural history in children with mitochondrial diseases. These data should be used to further explore construct validity of the IPMDS and to set age limits. In parallel, responsiveness and the minimal clinically important difference should be studied to facilitate sample size calculations in future clinical trials.The work of SK and JS was sponsored by ZonMW (The Netherlands Organization for Health Research and Development).http://link.springer.com/journal/10545am2017Paediatrics and Child Healt

Advancing Ontology Alignment in the Labor Market: Combining Large Language Models with Domain Knowledge

One of the approaches to help the demand and supply problem in the labor market domain is to change from degree-based hiring to skill-based hiring. The link between occupations, degrees and skills is captured in domain ontologies such as ESCO in Europe and O*NET in the US. Several countries are also building or extending these ontologies. The alignment of the ontologies is important, as it should be clear how they all relate. Aligning two ontologies by creating a mapping between them is a tedious task to do manually, and with the rise of generative large language models like GPT-4, we explore how language models and domain knowledge can be combined in the matching of the instances in the ontologies and in finding the specific relation between the instances (mapping refinement). We specifically focus on the process of updating a mapping, but the methods could also be used to create a first-time mapping. We compare the performance of several state-of-the-art methods such as GPT-4 and fine-tuned BERT models on the mapping between ESCO and O*NET and ESCO and CompetentNL (the Dutch variant) for both ontology matching and mapping refinement. Our findings indicate that: 1) Match-BERT-GPT, an integration of BERT and GPT, performs best in ontology matching, while 2) TaSeR outperforms GPT-4, albeit marginally, in the task of mapping refinement. These results show that domain knowledge is still important in ontology alignment, especially in the updating of a mapping in our use cases in the labor domain

Flexible image analysis for law enforcement agencies with deep neural networks to determine: where, who and what

International audienceDue to the increasing need for effective security measures and the integration of cameras in commercial products, a hugeamount of visual data is created today. Law enforcement agencies (LEAs) are inspecting images and videos to findradicalization, propaganda for terrorist organizations and illegal products on darknet markets. This is time consuming.Instead of an undirected search, LEAs would like to adapt to new crimes and threats, and focus only on data from specificlocations, persons or objects, which requires flexible interpretation of image content. Visual concept detection with deepconvolutional neural networks (CNNs) is a crucial component to understand the image content. This paper has fivecontributions. The first contribution allows image-based geo-localization to estimate the origin of an image. CNNs andgeotagged images are used to create a model that determines the location of an image by its pixel values. The secondcontribution enables analysis of fine-grained concepts to distinguish sub-categories in a generic concept. The proposedmethod encompasses data acquisition and cleaning and concept hierarchies. The third contribution is the recognition ofperson attributes (e.g., glasses or moustache) to enable query by textual description for a person. The person-attributeproblem is treated as a specific sub-task of concept classification. The fourth contribution is an intuitive image annotationtool based on active learning. Active learning allows users to define novel concepts flexibly and train CNNs with minimalannotation effort. The fifth contribution increases the flexibility for LEAs in the query definition by using query expansion.Query expansion maps user queries to known and detectable concepts. Therefore, no prior knowledge of the detectableconcepts is required for the users. The methods are validated on data with varying locations (popular and non-touristiclocations), varying person attributes (CelebA dataset), and varying number of annotations

Blind late fusion in multimedia event retrieval

Contains fulltext : 163082.pdf (publisher's version ) (Closed access

Query interpretation : an application of semiotics in image retrieval

One of the challenges in the field of content-based image retrieval is to bridge the semantic gap that exists between the information extracted from visual data using classifiers, and the interpretation of this data made by the end users. The semantic gap is a cascade of 1) the transformation of image pixels into labelled objects and 2) the semantic distance between the label used to name the classifier and that what it refers to for the end-user. In this paper, we focus on the second part and specifically on (semantically) scalable solutions that are independent from domain-specific vocabularies. To this end, we propose a generic semantic reasoning approach that applies semiotics in its query interpretation. Semiotics is about how humans interpret signs, and we use its text analysis structures to guide the query expansion that we apply. We evaluated our approach using a general-purpose image search engine. In our experiments, we compared several semiotic structures to determine to what extent semiotic structures contribute to the semantic interpretation of user queries. From the results of the experiments we conclude that semiotic structures can contribute to a significantly higher semantic interpretation of user queries and significantly higher image retrieval performance, measured in quality and effectiveness and compared to a baseline with only synonym expansions