Zebrafish (Danio rerio) are widely used as a vertebrate model in cardiovascular research due to their genetic similarity to humans, optical transparency during early development, and amenability to in vivo imaging. This manuscript presents a standardized, accessible protocol for assessing cardiac morphology and function in zebrafish embryos at 96 h post-fertilization (hpf) using brightfield light microscopy. The method includes embryo collection, morphological screening, immobilization in agarose, video recording of the beating heart, and image-based analysis of cardiac parameters such as ventricular dimensions, stroke volume, heart rate, ejection fraction, and cardiac output. Calculations are based on geometric approximations of the ventricle using open-source software (e.g., ImageJ, Zembryo Analyzer). The protocol enables quantitative assessment of cardiac performance using widely available equipment, making it suitable for laboratories with limited resources and high-throughput screenings. In this study, 96 hpf zebrafish larvae were analyzed by recording the beating heart under a light microscope. Key cardiac parameters measured included ventricular dimensions, which were used to calculate stroke volume and heart rate, determined by beats per minute. From these, ejection fraction and cardiac output were derived to assess overall cardiac performance. Representative results from healthy embryos demonstrated consistent ventricular contraction and robust functional indices, while embryos exposed to cadmium showed impaired cardiac morphology and significantly reduced cardiac output. Overall, the method is important for detecting developmental cardiotoxicity and provides a reproducible, non-invasive approach for evaluating cardiac function in vivo during early zebrafish development.

Numerous datasets have been made available on open data portals as a result of the open data initiatives. These portals offer a variety of search possibilities based on the metadata of datasets to facilitate data findability and usability. However, insufficient information frequently has a direct effect on search result quality and, in turn, data discoverability. As a result, methods for completing the missing metadata information—such as missing dataset category values—have become necessary. One of these methods focuses on classifying datasets according to the tags that are applied to them. The foundation of this method is a knowledge base made up of concept lattices produced for every category using the Formal Concept Analysis method. We analyze two sets of reduced concept lattices created for Ireland’s open data portal datasets in 2020 and 2021 and their usability for categorizing new datasets that were available on the portal in 2021 and 2023. Among other results, we will show that concept lattices, although reduced, can be used for a long period and still preserve the accuracy of the categorization algorithm above 90%.

The findability and usability of open data have never been more important due to the volume of available data. Therefore, methods have been developed to improve the dataset metadata quality, enhancing its findability and usability. One effective approach for filling in missing category information is based on the Formal Concept Analysis method. Since this method relies on a knowledge base consisting of concept lattices produced for each category on an open data portal, the focus of this research is to analyze the usability of the semantically reduced concept lattice over time. In particular, we are focused on (1) the impact of the semantic reduction threshold on the long-term usability and expressiveness of the generated concept lattices and (2) the identification of metadata change indicators that would require recreation of the knowledge bases. We perform this analysis using Ireland’s and Canada’s open data portals—two portals with different approaches to dataset categorization. For both portals, datasets from 2020, 2021, and 2023 are used for knowledge bases creation, while semantically reduced concept lattices are evaluated using six test datasets per portal, containing new datasets from 2020 to 2025. We will show that semantically reduced concept lattices maintain good long-term usability under regular dataset growth. Among other findings, we will demonstrate that dataset categorization based on two-year-old concept lattices achieves over 83% accuracy and that at the category level, even four-year-old reduced concept lattices attain accuracy exceeding 90%.

Starvation is a fundamental physiological stressor that triggers conserved adaptive responses across species, however, its effects are shaped by both developmental stage and prior nutritional history. This study aimed to investigate the effects of acute nutrient deprivation in Artemia franciscana, comparing newly hatched nauplii and adult individuals previously exposed to reduced caloric intake during development. Organisms were subjected to starvation for 24, 48, and 72 h, and mortality, morphometric parameters, and locomotor activity were assessed, complemented by in silico analysis of starvation-related pathways. Starvation induced distinct responses between groups, with markedly higher mortality in adults compared to nauplii. While these differences reflect developmental stage-associated responses, they are also influenced by prior nutritional history. Body length was significantly reduced under starvation in both developmental stages, while antennal length remained largely unchanged. Locomotor activity, including distance travelled and swimming velocity, was consistently decreased, indicating energy-conserving behavioral adaptation. Partial recovery of locomotor performance and antennal length was observed following restoration of feeding. Bioinformatic analysis suggested the presence of conserved autophagy-related genes and enrichment of pathways associated with autophagy and TOR signaling. However, these findings should be interpreted as hypothesis-generating, given the reliance on a proxy species for pathway inference. These findings indicate that starvation responses in A. franciscana are shaped by an interaction between developmental stage and prior nutritional history, supported by conserved stress–response pathways, highlighting the potential of this model for studying metabolic stress responses.