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Establishing Typologies for Diverging Career Paths through the Life Course: A Comparison of two Methods

Discussions on policy and management initiatives to facilitate individuals throughout working careers take place without sufficient insight into how career paths are changing, how these changes are related to a modernization of life course biographies, and whether this leads to increased labour market transitions. This paper asks how new, flexible labour market patterns can best be analyzed using an empirical, quantitative approach. The data used are from the career module of the Panel Study of Belgian Households (PSBH). This module, completed by almost 4500 respondents consists of retrospective questions tracing lengthy and even entire working life histories. To establish any changes in career patterns over such extended periods of time, we compare two evolving methodologies: Optimal Matching Analysis (OMA) and Latent Class Regression Analysis (LCA). The analyses demonstrate that both methods show promising potential in discerning working life typologies and analyzing sequence trajectories. However, particularities of the methods demonstrate that not all research questions are suitable for each method. The OMA methodology is appropriate when the analysis concentrates on the labour market statuses and is well equipped to make clear and interpretable differentiations if there is relative stability in career paths during the period of observation but not if careers become less stable. Latent Class has the strength of adopting covariates in the clustering allowing for more historically connected types than the other methodology. The clustering is denser and the technique allows for more detailed model fitting controls than OMA. However, when incorporating covariates in a typology, the possibilities of using the typology in later, causal, analyses is somewhat reduced.

Natural language processing in toxicology: Delineating adverse outcome pathways and guiding the application of new approach methodologies

Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.

A scuticociliate causes mass mortality of Diadema antillarum in the Caribbean Sea

Echinoderm mass mortality events shape marine ecosystems by altering the dynamics among major benthic groups. The sea urchin Diadema antillarum, virtually extirpated in the Caribbean in the early 1980s by an unknown cause, recently experienced another mass mortality beginning in January 2022. We investigated the cause of this mass mortality event through combined molecular biological and veterinary pathologic approaches comparing grossly normal and abnormal animals collected from 23 sites, representing locations that were either affected or unaffected at the time of sampling. Here, we report that a scuticociliate most similar to Philaster apodigitiformis was consistently associated with abnormal urchins at affected sites but was absent from unaffected sites. Experimentally challenging naïve urchins with a Philaster culture isolated from an abnormal, field-collected specimen resulted in gross signs consistent with those of the mortality event. The same ciliate was recovered from treated specimens postmortem, thus fulfilling Koch’s postulates for this microorganism. We term this condition D. antillarum scuticociliatosis.

Physical activity after surgery for severe obesity: the role of exercise cognitions

Background Physical activity after bariatric surgery is associated with sustained weight loss and improved quality of life. Some bariatric patients engage insufficiently in physical activity. The aim of this study was to examine whether and to what extent both physical activity and exercise cognitions have changed at one and two years post-surgery, and whether exercise cognitions predict physical activity. Methods Forty-two bariatric patients (38 women, 4 men; mean age 38 ± 8 years, mean body mass index prior to surgery 47 ± 6 kg/m²), filled out self-report instruments to examine physical activity and exercise cognitions pre- and post surgery. Results Moderate to large healthy changes in physical activity and exercise cognitions were observed after surgery. Perceiving less exercise benefits and having less confidence in exercising before surgery predicted less physical activity two years after surgery. High fear of injury one year after surgery predicted less physical activity two years after surgery. Conclusion After bariatric surgery, favorable changes in physical activity and exercise cognitions are observed. Our results suggest that targeting exercise cognitions before and after surgery might be relevant to improve physical activity.

Compact tomato seedlings and plants upon overexpression of a tomato chromatin remodelling ATPase gene

Control of plant growth is an important aspect of crop productivity and yield in agriculture. Overexpression of the At CHR12/ 23 genes in Arabidopsis thaliana reduced growth habit without other morphological changes. These two genes encode Snf2 chromatin remodelling ATPases. Here, we translate this approach to the horticultural crop tomato ( Solanum lycopersicum). We identified and cloned the single tomato ortholog of the two Arabidopsis Snf2 genes, designated Sl CHR1. Transgenic tomato plants (cv. Micro-Tom) that constitutively overexpress the coding sequence of Sl CHR1 show reduced growth in all developmental stages of tomato. This confirms that Sl CHR1 combines the functions of both Arabidopsis genes in tomato. Compared to the wild type, the transgenic seedlings of tomato have significantly shorter roots, hypocotyls and reduced cotyledon size. Transgenic plants have a much more compact growth habit with markedly reduced plant height, severely compacted reproductive structures with smaller flowers and smaller fruits. The results indicate that either GMO-based or non- GMO-based approaches to modulate the expression of chromatin remodelling ATPase genes could develop into methods to control plant growth, for example to replace the use of chemical growth retardants. This approach is likely to be applicable and attractive for any crop for which growth habit reduction has added value.

Deconstructing the cloud