Publications by authors named "David Vanavermaete"

Article Synopsis
  • The study highlights the challenges in accurately analyzing microplastics in marine environments, particularly regarding smaller sizes and the effects of environmental weathering on plastic reliability.
  • It tests two automated analysis techniques—decision tree (DT) and random forest (RF)—that use machine learning and fluorescent staining to improve detection and identification of various weathered microplastic types.
  • While both models showed high accuracy for pristine plastics, RF models outperformed in distinguishing weathered microplastics, though results varied by lab, indicating the method's adaptability for future research.
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Determining the extent of pollution in the marine environment remains challenging. Polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and metals can, during dredging operations, be transported from a port or harbour into the open sea, where they may exert a harmful effect on the marine ecosystem. To fully understand the impact of these chemicals, monitoring programs should not only focus on sediment concentrations, but should also take into account the bioaccumulated concentration in the tissue of multiple target organisms.

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An intercomparison exercise on "microplastics in sediment" was carried out by five laboratories using samples collected in the Bay of Marseille in September 2021. The results from different extraction and identification methods varied depending on the type and size classes of MPs, and was better than 80 % for the size class >300 μm and for the fragments. The variability in recovery rates can be attributed to the choice of reagents and extraction protocols.

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The biofouling of submerged surfaces such as ship hulls is often prevented by using anti-fouling components in combination with booster biocides. These booster biocides enter the water column and may affect non-target organisms. Although different negative effects have been associated with the use of booster biocides, their effects on non-target organisms are often unknown.

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In a growing multidrug-resistant environment, the identification of potential new drug candidates with an acceptable safety profile is a substantial crux in pharmaceutical discovery. This review discusses several aspects and properties of approved marine natural products derived from ascidian sources (phylum Chordata, subphylum Tunicata) and/or their deduced analogues including their biosynthetic origin, (bio)chemical preclinical assessments and known efficacy-safety profiles, clinical status in trials, but also translational developments, opportunities and final conclusions. The review also describes the preclinical assessments of a large number of other ascidian compounds that have not been involved in clinical trials yet.

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Since the introduction of genomic selection in plant breeding, high genetic gains have been realized in different plant breeding programs. Various methods based on genomic estimated breeding values (GEBVs) for selecting parental lines that maximize the genetic gain as well as methods for improving the predictive performance of genomic selection have been proposed. Unfortunately, it remains difficult to measure to what extent these methods really maximize long-term genetic values.

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Dredging activities can result in the relocation of contaminants such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and metals from shipping channels, harbours, and ports into the marine environment where these components may exert a negative effect on the marine ecosystem. In this work, contamination associated with dredging is evaluated at and around dredged spoil disposal sites in the Belgian part of the North Sea, taking into account spatial as well as temporal variation. A homogeneous dispersion of the different contaminants was observed at the different sites.

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The deep scoping method incorporates the use of a gene bank together with different population layers to reintroduce genetic variation into the breeding population, thus maximizing the long-term genetic gain without reducing the short-term genetic gain or increasing the total financial cost. Genomic prediction is often combined with truncation selection to identify superior parental individuals that can pass on favorable quantitative trait locus (QTL) alleles to their offspring. However, truncation selection reduces genetic variation within the breeding population, causing a premature convergence to a sub-optimal genetic value.

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Genomic selection has been successfully implemented in plant and animal breeding. The transition of parental selection based on phenotypic characteristics to genomic selection (GS) has reduced breeding time and cost while accelerating the rate of genetic progression. Although breeding methods have been adapted to include genomic selection, parental selection often involves selection, selecting the individuals with the highest genomic estimated breeding values (GEBVs) in the hope that favorable properties will be passed to their offspring.

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