Current achievements and future developments of a novel AI based visual monitoring of beehives in ecotoxicology and for the monitoring of landscape structures

Honey bees are valuable bioindicators. As such, they hold a vast potential to help shed light on the extent and interdependencies of factors influencing the decline in the number of insects. However, to date this potential has not yet been fully leveraged, as the production of reliable data requires large-scale study designs, which are very labour intensive and therefore costly. A novel Artificial Intelligence (AI) based visual monitoring system could enable the partial automatization of data collection on activity, forager loss and impairment of the central nervous system. The possibility to extract features from image data could prospectively also allow an assessment of pollen intake and a differentiation of dead bees, drones and worker bees as well as other insects such as wasps or hornets. The technology was validated in different studies with regards to its scalability and its ability to extract motion and feature related information. The prospective possibilities were analyzed regarding their potential to enable advances both within ecotoxicological research and the monitoring of pollinator habitats.Honey bees are valuable bioindicators. As such, they hold a vast potential to help shed light on the extent and interdependencies of factors influencing the decline in the number of insects. However, to date this potential has not yet been fully leveraged, as the production of reliable data requires large-scale study designs, which are very labour intensive and therefore costly. A novel Artificial Intelligence (AI) based visual monitoring system could enable the partial automatization of data collection on activity, forager loss and impairment of the central nervous system. The possibility to extract features from image data could prospectively also allow an assessment of pollen intake and a differentiation of dead bees, drones and worker bees as well as other insects such as wasps or hornets. The technology was validated in different studies with regards to its scalability and its ability to extract motion and feature related information. The prospective possibilities were analyzed regarding their potential to enable advances both within ecotoxicological research and the monitoring of pollinator habitats

Impact of an Oomen feeding with a neonicotinoid on daily activity and colony development of honeybees assessed with an AI based monitoring device

Feeding experiments are standard tools in the pollinator risk assessment. The design (Oomen et al. 1992) was developed to test insect growth regulators and herbicides. In recent years there was an update (Lückmann & Schmitzer 2015) on the outline in order to also focus on the advantage of different rates making a dose response design possible where exposure levels are known. Additionally, this design gives the possibility to test different rates for honey bee colonies foraging in the same landscape. The main objective of the experiment presented here was to determine the natural variability of foragers losses of hives fed with a sub-lethal neonicotinoid concentration compared to an untreated control. Other objectives were to see if the neurotoxic exposure results in any observable sub-lethal effects and to find out if losses can be correlated to hive development. This was assessed with traditional methods and a novel, visual monitoring device.Feeding experiments are standard tools in the pollinator risk assessment. The design (Oomen et al. 1992) was developed to test insect growth regulators and herbicides. In recent years there was an update (Lückmann & Schmitzer 2015) on the outline in order to also focus on the advantage of different rates making a dose response design possible where exposure levels are known. Additionally, this design gives the possibility to test different rates for honey bee colonies foraging in the same landscape. The main objective of the experiment presented here was to determine the natural variability of foragers losses of hives fed with a sub-lethal neonicotinoid concentration compared to an untreated control. Other objectives were to see if the neurotoxic exposure results in any observable sub-lethal effects and to find out if losses can be correlated to hive development. This was assessed with traditional methods and a novel, visual monitoring device

Comparative analysis of targeted next-generation sequencing panels for the detection of gene mutations in chronic lymphocytic leukemia: an ERIC multi-center study

Next-generation sequencing (NGS) has transitioned from research to clinical routine, yet the comparability of different technologies for mutation profiling remains an open question. We performed a European multicenter (n=6) evaluation of three amplicon-based NGS assays targeting 11 genes recurrently mutated in chronic lymphocytic leukemia. Each assay was assessed by two centers using 48 pre-characterized chronic lymphocytic leukemia samples; libraries were sequenced on the Illumina MiSeq instrument and bioinformatics analyses were centralized. Across all centers the median percentage of target reads ≥100x ranged from 94.2-99.8%. To rule out assay-specific technical variability, we first assessed variant calling at the individual assay level i.e. pairwise analysis of variants detected amongst partner centers. After filtering for variants present in the paired normal sample and removal of PCR/sequencing artefacts, the panels achieved 96.2% (Multiplicom), 97.7% (TruSeq) and 90% (HaloPlex) concordance at a VAF >0.5%. Reproducibility was assessed by looking at the inter-laboratory variation in detecting mutations and 107/115 (93% concordance) of mutations were detected by all 6 centers, while the remaining 8/115 (7%) variants were undetected by a single center and 6/8 of these variants concerned minor subclonal mutations (VAF 5%, after rigorous validation, the use of unique molecular identifiers may be necessary to reach a higher sensitivity and ensure consistent and accurate detection of low-frequency variants

Natural color dispersion of corbicular pollen limits color-based classification

Various methods have been developed to assign pollen to its botanical origin. They range from technically complex approaches to the less precise but sophisticated chromatic assessment, in which the pollen colors are used for identification. However, a common challenge lies in the similarity of colors of pollen from different plant species. The advent of camera-based bee monitoring systems has sparked renewed interest in classifying pollen based on color and offers potential advances for honey bee biomonitoring. Despite the promise of improved sensor accuracy, a critical examination of whether color diversity within a single species may be the primary limiting factor has been lacking. Our comprehensive analysis, which includes over 85,000 corbicular pollen from 30 major pollen species, shows that the average color variation within each species is distinguishable to a human observer, similar to the difference between two dissimilar colors. From today's perspective, the considerable color variation within a single pollen source makes the use of color alone to classify pollen impractical. When picking a single pollen color from the entire dataset, we report a correct pollen type classification rate of 67 %. The accuracy was highly dependent on the type and ranged from 0 % for rare types with common colors to 99 % for distinct colors. The large color dispersion within species highlights the need for complementary methods to improve the accuracy and reliability of color-based pollen identification in biomonitoring applications

Color dispersion of corbicular pollen loads - Supplementary Material

Dataset DescriptionThis dataset belongs to paper [1] where Gaussian Mixture Models were used to establish a mapping between 62,343 corbicular pollen colors and their respective pollen types. The data set contains 30 different pollen types, including 14 of the 31 most important European pollen types.We provide the following resources in this repository:Folder pollen samples contains data for 86 samples / 62,343 corbicular pollenCSV filesColumn 1: Dataset identifierColumn 2: Sample identifierColumn 3-5: L*A*B* pollen colorsColumn 6-End: pollen type probabilitiesJSON filesFor each dataset and sample: The estimated mean and covariance parameters of the Gaussian Mixture Models are reported along with the relative and absolute pollen type abundance.PDF/PNG filesFor each dataset and sample: Scatter plots show the pollen colors (left) morphological pollen type analysis (middle) and GMM reconstruction (right).Folder pollen typesPDF/PNG filesFor each pollen type: A scatter plot of all corbicular pollen colors that were attributed to the type.File Method_Pollen_Determination_Mayen_en.pdfA protocol describing the method of morphological pollen type determination carried out at the Expert Center for Bees and Beekeeping, Mayen, GermanyDetailed information on the sampling locations, periods and intervals can be found in the paper.AbstractVarious methods have been developed to assign pollen to its botanical origin. They range from technically complex approaches to the less precise but sophisticated chromatic assessment, in which the pollen colors are used for identification. However, a common challenge lies in the similarity of colors of pollen from different plant species. The advent of camera-based bee monitoring systems has sparked renewed interest in classifying pollen based on color and offers potential advances for honey bee biomonitoring. Despite the promise of improved sensor accuracy, a critical examination of whether color diversity within a single species may be the primary limiting factor has been lacking. Our comprehensive analysis, which includes over 85,000 corbicular pollen from 30 major pollen species, shows that the average color variation within each species is distinguishable to a human observer, similar to the difference between two dissimilar colors. From today's perspective, the considerable color variation within a single pollen source makes the use of color alone to classify pollen impractical. When picking a single pollen color from the entire dataset, we report a correct pollen type classification rate of 67 %. The accuracy was highly dependent on the type and ranged from 0 % for rare types with common colors to 99 % for distinct colors. The large color dispersion within species highlights the need for complementary methods to improve the accuracy and reliability of color-based pollen identification in biomonitoring applications.References[1] P. Borlinghaus, R. Odemer and F. Tausch, ‘Natural color dispersion of corbicular pollen limits color-based classification’, Open Journal of Photogrammetry and Remote Sensing, 2024 (accepted).</p

ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia—2024 update

In chronic lymphocytic leukemia (CLL), analysis of TP53 aberrations (deletion and/or mutation) is a crucial part of treatment decision-making algorithms. Technological and treatment advances have resulted in the need for an update of the last recommendations for TP53 analysis in CLL, published by ERIC, the European Research Initiative on CLL, in 2018. Based on the current knowledge of the relevance of low-burden TP53-mutated clones, a specific variant allele frequency (VAF) cut-off for reporting TP53 mutations is no longer recommended, but instead, the need for thorough method validation by the reporting laboratory is emphasized. The result of TP53 analyses should always be interpreted within the context of available laboratory and clinical information, treatment indication, and therapeutic options. Methodological aspects of introducing next-generation sequencing (NGS) in routine practice are discussed with a focus on reliable detection of low-burden clones. Furthermore, potential interpretation challenges are presented, and a simplified algorithm for the classification of TP53 variants in CLL is provided, representing a consensus based on previously published guidelines. Finally, the reporting requirements are highlighted, including a template for clinical reports of TP53 aberrations. These recommendations are intended to assist diagnosticians in the correct assessment of TP53 mutation status, but also physicians in the appropriate understanding of the lab reports, thus decreasing the risk of misinterpretation and incorrect management of patients in routine practice whilst also leading to improved stratification of patients with CLL in clinical trials

Comparative analysis of targeted next-generation sequencing panels for the detection of gene mutations in chronic lymphocytic leukemia : an ERIC multi-center study

Next-generation sequencing (NGS) has transitioned from research to clinical routine, yet the comparability of different technologies for mutation profiling remains an open question. We performed a European multicenter (n=6) evaluation of three amplicon-based NGS assays targeting 11 genes recurrently mutated in chronic lymphocytic leukemia. Each assay was assessed by two centers using 48 pre-characterized chronic lymphocytic leukemia samples; libraries were sequenced on the Illumina MiSeq instrument and bioinformatics analyses were centralized. Across all centers the median percentage of target reads &gt;= 100x ranged from 94.299.8%. In order to rule out assay-specific technical variability, we first assessed variant calling at the individual assay level i.e., pairwise analysis of variants detected amongst partner centers. After filtering for variants present in the paired normal sample and removal of PCR/sequencing artefacts, the panels achieved 96.2% (Multiplicom), 97.7% (TruSeq) and 90% (HaloPlex) concordance at a variant allele frequency (VAF) 5%). We sought to investigate low-frequency mutations further by using a high-sensitivity assay containing unique molecular identifiers, which confirmed the presence of several minor subclonal mutations. Thus, while amplicon-based approaches can be adopted for somatic mutation detection with VAF 5%, after rigorous validation, the use of unique molecular identifiers may be necessary to reach a higher sensitivity and ensure consistent and accurate detection of low-frequency variants