Firefly Occurrences in Croatia – One Step Closer from Citizen Science to Open Data*

Fireflies (Coleoptera: Lampyridae), with more than 2 000 species in 100 genera worldwide, are a charismatic nocturnal species. Although popular in different cultures because of their association with warm summer evenings in childhood, fireflies are an under-researched insect. Like numerous other insects worldwide, fireflies have experienced declines in their distribution and abundance. Anthropogenic impacts and climate change are likely to influence their development, reproduction, and survival. A project called “Krešo Krijesnica” (eng. “Krešo the Firefly”), used a Citizen Science model of data collection, to determine where are the fireflies located and how abundant are they throughout Croatia. Citizen Science involves the participation of the general or non-scientific public in data collection so determining the basic demographic profile of the citizen scientists involved was also one of the project goals. During the first phase of the project (2019-2021), data on fireflies were provided by citizen scientists through a formal survey on social media (Facebook, Instagram). Phase two aims to open the fireflies’ datasets to the public through various open data portals. In the three years of the project, more than 16 000 records of fireflies were collected and analysed from over 1800 sightings. Descriptive statistics showed that the highest firefly population density was found in central Croatia, which is consistent with the greater number of people living in this area and thus a greater chance of firefly detection. Higher number pf female reporters were noted during the project. The dataset collected in this Citizen Science project presents a valuable source of information to the scientific community, especially in the field of entomology, conservation biology and ecology

Uncovering the hidden socioeconomic impact of juvenile idiopathic arthritis and paving the way for other rare childhood diseases: an international, cross-disciplinary, patient-centered approach (PAVE Consortium)

BACKGROUND: Juvenile idiopathic arthritis (JIA) refers to a heterogeneous group of rheumatic conditions in children. Novel drugs have greatly improved disease outcomes; however, outcomes are impacted by limited awareness of the importance of early diagnosis and adequate treatment, and by differences in access across health systems. As a result, patients with JIA continue to be at risk for short- and long-term morbidity, as well as impacts on virtually all aspects of life of the child and family. MAIN BODY: Literature on the socioeconomic burden of JIA is largely focused on healthcare costs, and the impact of JIA on patients, families, and communities is not well understood. High quality evidence on the impact of JIA is needed to ensure that patients are receiving necessary support, timely diagnostics, and adequate treatment, and to inform decision making and resource allocation. This commentary introduces the European Joint Programme on Rare Diseases: Producing an Arthritis Value Framework with Economic Evidence: Paving the Way for Rare Childhood Diseases (PAVE) project, which will co-develop a patient-informed value framework to measure the impact of JIA on individuals and on society. With a patient-centered approach, fundamental to PAVE is the involvement of three patient advocacy organizations from Canada, Israel, and Europe, as active research partners co-designing all project phases and ensuring robust patient and family engagement. The framework will build on the findings of projects from six countries: Canada, Germany, Switzerland, Spain, Israel, and Belgium, exploring costs, outcomes (health, well-being), and unmet needs (uveitis, mental health, equity). CONCLUSION: This unique international collaboration will combine evidence on costs (from family to societal), outcomes (clinical, patient and family outcomes), and unmet needs, to co-design and build a framework with patients and families to capture the full impact of JIA. The framework will support the development of high-quality evidence, encompassing economic and clinical considerations, unmet needs, and patient perspectives, to inform equitable resource allocation, health system planning, and quality of care better aligned with the needs of children with JIA, their families, and communities. Knowledge gained from this novel approach may pave the way forward to be applied more broadly to other rare childhood diseases

Transcriptional Regulation of N-Acetylglutamate Synthase

The urea cycle converts toxic ammonia to urea within the liver of mammals. At least 6 enzymes are required for ureagenesis, which correlates with dietary protein intake. The transcription of urea cycle genes is, at least in part, regulated by glucocorticoid and glucagon hormone signaling pathways. N-acetylglutamate synthase (NAGS) produces a unique cofactor, N-acetylglutamate (NAG), that is essential for the catalytic function of the first and rate-limiting enzyme of ureagenesis, carbamyl phosphate synthetase 1 (CPS1). However, despite the important role of NAGS in ammonia removal, little is known about the mechanisms of its regulation. We identified two regions of high conservation upstream of the translation start of the NAGS gene. Reporter assays confirmed that these regions represent promoter and enhancer and that the enhancer is tissue specific. Within the promoter, we identified multiple transcription start sites that differed between liver and small intestine. Several transcription factor binding motifs were conserved within the promoter and enhancer regions while a TATA-box motif was absent. DNA-protein pull-down assays and chromatin immunoprecipitation confirmed binding of Sp1 and CREB, but not C/EBP in the promoter and HNF-1 and NF-Y, but not SMAD3 or AP-2 in the enhancer. The functional importance of these motifs was demonstrated by decreased transcription of reporter constructs following mutagenesis of each motif. The presented data strongly suggest that Sp1, CREB, HNF-1, and NF-Y, that are known to be responsive to hormones and diet, regulate NAGS transcription. This provides molecular mechanism of regulation of ureagenesis in response to hormonal and dietary changes

Les modèles au Cemagref : formulation, validation, pertinence - tome 1

These minutes are a collection of 36 papers presented at an internal Cemagref symposium on October 12 and 13, 1995. Four main topics were covered: scale changes, observations and models (sampling, variability, representativeness and adjustment), process based modelling, and modelling of systems of multiple compounds or multiple agents. / Ces actes rassemblent 36 communications présentées lors de ce séminaire interne Cemagref tenu les 12 et 13 octobre 1995. Quatre thèmes ont été successivement traités : prise en compte des changements d'échelle, observation et modèles (échantillonnage, variabilité, représentativité et calage), modélisation à base de processus et modélisation des systèmes à composante multiples ou multi-agents

Les modèles au Cemagref : formulation, validation, pertinence - tome 2

General synthesis of this seminar. Presentation of four conferences (invited speakers) concerning how to take into account scale changes, observation and models (sampling, variability, representativity and adjustment), modelling based on processus and modelling of multiple components or multi-agent systems. Texts of five additional communications. / Synthèse générale de ce séminaire. Présentation de quatre conférences (conférenciers invités) concernant la prise en compte des changements d'échelle, l'observation et les modèles (échantillonnage, variabilité, représentativité et calage), la modélisation à base de processus et la modélisation des systèmes à composantes multiples ou multi-agents. Textes de cinq communications complémentaires

Abstract Las Vegas Algorithms for Gene Recognition: Suboptimal and Error-Tolerant Spliced Alignment

ment approach to gene recognition that provides 99 % ac-curate recognition of human gene if a related mammalian protein is available. However, even 99 % accurate gene pre-dictions are insufficient for automated sequence annotation in large-scale sequencing projects and therefore have to be complemented by experimental gene verification. 100 % ac-curate gene predictions would lead to a substantial reduction of experimental work on gene identification. Our goal is to develop an algorithm that either predicts an exon assembly with accuracy sufficient for sequence annotation or warns a biologist that the accuracy of a prediction is insufficient and further experimental work is required. We study subop-timal and error-t,olerant spliced alignment problems as the first steps towards such an algorithm, and report an algo-rithm which provides 100 % accurate recognition of human genes in 37 % of cases (if a related mammalian protein is available). For 52 % of genes, the algorithm predicts at least one exon with 100 % accuracy.