Developing human biomonitoring as a 21st century toolbox within the European exposure science strategy 2020-2030.

Human biomonitoring (HBM) is a crucial approach for exposure assessment, as emphasised in the European Commission's Chemicals Strategy for Sustainability (CSS). HBM can help to improve chemical policies in five major key areas: (1) assessing internal and aggregate exposure in different target populations; 2) assessing exposure to chemicals across life stages; (3) assessing combined exposure to multiple chemicals (mixtures); (4) bridging regulatory silos on aggregate exposure; and (5) enhancing the effectiveness of risk management measures. In this strategy paper we propose a vision and a strategy for the use of HBM in chemical regulations and public health policy in Europe and beyond. We outline six strategic objectives and a roadmap to further strengthen HBM approaches and increase their implementation in the regulatory risk assessment of chemicals to enhance our understanding of exposure and health impacts, enabling timely and targeted policy interventions and risk management. These strategic objectives are: 1) further development of sampling strategies and sample preparation; 2) further development of chemical-analytical HBM methods; 3) improving harmonisation throughout the HBM research life cycle; 4) further development of quality control / quality assurance throughout the HBM research life cycle; 5) obtain sustained funding and reinforcement by legislation; and 6) extend target-specific communication with scientists, policymakers, citizens and other stakeholders. HBM approaches are essential in risk assessment to address scientific, regulatory and societal challenges. HBM requires full and strong support from the scientific and regulatory domain to reach its full potential in public and occupational health assessment and in regulatory decision-making.

Stochastic Fluctuations of Low-Energy Cosmic Rays and the Interpretation of Voyager Data.

Data from the Voyager probes have provided us with the first measurement of cosmic ray intensities at MeV energies, an energy range that had previously not been explored. Simple extrapolations of models that fit data at GeV energies, e.g., from AMS-02, however, fail to reproduce the Voyager data in that the predicted intensities are too high. Oftentimes, this discrepancy is addressed by adding a break to the source spectrum or the diffusion coefficient in an ad hoc fashion, with a convincing physical explanation yet to be provided. Here, we argue that the discrete nature of cosmic ray sources, which is usually ignored, is instead a more likely explanation. We model the distribution of intensities expected from a statistical model of discrete sources and show that its expectation value is not representative but has a spectral shape different from that for a typical configuration of sources. The Voyager proton and electron data are however compatible with the median of the intensity distribution.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain.

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species.

Automatic Segmentation of Drosophila Neural Compartments Using GAL4 Expression Data Reveals Novel Visual Pathways.

Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates.

Adaptive and Background-Aware GAL4 Expression Enhancement of Co-registered Confocal Microscopy Images.

GAL4 gene expression imaging using confocal microscopy is a common and powerful technique used to study the nervous system of a model organism such as Drosophila melanogaster. Recent research projects focused on high throughput screenings of thousands of different driver lines, resulting in large image databases. The amount of data generated makes manual assessment tedious or even impossible. The first and most important step in any automatic image processing and data extraction pipeline is to enhance areas with relevant signal. However, data acquired via high throughput imaging tends to be less then ideal for this task, often showing high amounts of background signal. Furthermore, neuronal structures and in particular thin and elongated projections with a weak staining signal are easily lost. In this paper we present a method for enhancing the relevant signal by utilizing a Hessian-based filter to augment thin and weak tube-like structures in the image. To get optimal results, we present a novel adaptive background-aware enhancement filter parametrized with the local background intensity, which is estimated based on a common background model. We also integrate recent research on adaptive image enhancement into our approach, allowing us to propose an effective solution for known problems present in confocal microscopy images. We provide an evaluation based on annotated image data and compare our results against current state-of-the-art algorithms. The results show that our algorithm clearly outperforms the existing solutions.

Structure-based neuron retrieval across Drosophila brains.

Comparing local neural structures across large sets of examples is crucial when studying gene functions, and their effect in the Drosophila brain. The current practice of aligning brain volume data to a joint reference frame is based on the neuropil. However, even after alignment neurons exhibit residual location and shape variability that, together with image noise, hamper direct quantitative comparison and retrieval of similar structures on an intensity basis. In this paper, we propose and evaluate an image-based retrieval method for neurons, relying on local appearance, which can cope with spatial variability across the population. For an object of interest marked in a query case, the method ranks cases drawn from a large data set based on local neuron appearance in confocal microscopy data. The approach is based on capturing the orientation of neurons based on structure tensors and expanding this field via Gradient Vector Flow. During retrieval, the algorithm compares fields across cases, and calculates a corresponding ranking of most similar cases with regard to the local structure of interest. Experimental results demonstrate that the similarity measure and ranking mechanisms yield high precision and recall in realistic search scenarios.

Automated landmarking and labeling of fully and partially scanned spinal columns in CT images.

The spinal column is one of the most distinguishable structures in CT scans of the superior part of the human body. It is not necessary to segment the spinal column in order to use it as a frame of reference. It is sufficient to place landmarks and the appropriate anatomical labels at intervertebral disks and vertebrae. In this paper, we present an automated system for landmarking and labeling spinal columns in 3D CT datasets. We designed this framework with two goals in mind. First, we relaxed input data requirements found in the literature, and we label both full and partial spine scans. Secondly, we intended to fulfill the performance requirement for daily clinical use and developed a high throughput system capable of processing thousands of slices in just a few minutes. To accomplish the aforementioned goals, we encoded structural knowledge from training data in probabilistic boosting trees and used it to detect efficiently the spinal canal, intervertebral disks, and three reference regions responsible for initializing the landmarking and labeling. Final landmarks and labels are selected by Markov Random Field-based matches of newly introduced 3-disk models. The framework has been tested on 36 CT images having at least one of the regions around the thoracic first ribs, the thoracic twelfth ribs, or the sacrum. In an average time of 2 min, we achieved a correct labeling in 35 cases with precision of 99.0% and recall of 97.2%. Additionally, we present results assuming none of the three reference regions could be detected.

Intra-operative virtual endoscopy for image guided endonasal transsphenoidal pituitary surgery.

PURPOSE: Virtual endoscopy has already proven its benefit for pre-operative planning of endoscopic pituitary surgery. The translation of such a system into the operating room is a logical consequence, but only a few general intra-operative image guided systems providing virtual endoscopic images have been proposed so far. A discussion of related visualization and interaction problems occurring during sinus and pituitary surgery is still missing. METHODS: This paper aims at filling this gap and proposes a system that integrates an existing virtual endoscopy system originally designed for pre-operative planning of pituitary surgery with a professional intra-operative navigation system. Visualization and interaction possibilities of the pre-operative planning system have been extended to fulfill the special requirements to the system if used for intra-operative navigation of endonasal transsphenoidal pituitary surgery. RESULTS: The feasibility of the system has been successfully tested on 1 cadaver and 12 patients. The virtual endoscopic images were found useful (1) during the endonasal transsphenoidal approach in cases of anatomic variations and for the individually tailored opening of the sellar floor, and (2) during tumor resection for respecting the internal carotid artery. The visualization of hidden anatomical structures behind the bony walls of the sphenoid sinus during the sellar phase of the surgery has been found most beneficial. DISCUSSION: According to our data, intra-operative virtual endoscopy provides additional anatomical information to the surgeon. By depicting individual anatomical variations in advance, it may add to the safety of this frequent neurosurgical procedure.

Degradation of Saccharomyces cerevisiae transcription factor Gcn4 requires a C-terminal nuclear localization signal in the cyclin Pcl5.

Pcl5 is a Saccharomyces cerevisiae cyclin that directs the phosphorylation of the general amino acid control transcriptional activator Gcn4 by the cyclin-dependent kinase (CDK) Pho85. Phosphorylation of Gcn4 by Pho85/Pcl5 initiates its degradation via the ubiquitin/proteasome system and is regulated by the availability of amino acids. In this study, we show that Pcl5 is a nuclear protein and that artificial dislocation of Pcl5 into the cytoplasm prevents the degradation of Gcn4. Nuclear localization of Pcl5 depends on the beta-importin Kap95 and does not require Pho85, Gcn4, or the CDK inhibitor Pho81. Pcl5 nuclear import is independent on the availability of amino acids and is mediated by sequences in its C-terminal domain. The nuclear localization signal is distinct from other functional domains of Pcl5. This is corroborated by a C-terminally truncated Pcl5 variant, which carries the N-terminal nuclear domain of Pho80. This hybrid is still able to fulfill Pcl5 function, whereas Pho80, which is another Pho85 interacting cyclin, does not mediate Gcn4 degradation.

Differential Flo8p-dependent regulation of FLO1 and FLO11 for cell-cell and cell-substrate adherence of S. cerevisiae S288c.

Cell-cell and cell-surface adherence represents initial steps in forming multicellular aggregates or in establishing cell-surface interactions. The commonly used Saccharomyces cerevisiae laboratory strain S288c carries a flo8 mutation, and is only able to express the flocculin-encoding genes FLO1 and FLO11, when FLO8 is restored. We show here that the two flocculin genes exhibit differences in regulation to execute distinct functions under various environmental conditions. In contrast to the laboratory strain Sigma1278b, haploids of the S288c genetic background require FLO1 for cell-cell and cell-substrate adhesion, whereas FLO11 is required for pseudohyphae formation of diploids. In contrast to FLO11, FLO1 repression requires the Sin4p mediator tail component, but is independent of the repressor Sfl1p. FLO1 regulation also differs from FLO11, because it requires neither the KSS1 MAP kinase cascade nor the pathways which lead to the transcription factors Gcn4p or Msn1p. The protein kinase A pathway and the transcription factors Flo8p and Mss11p are the major regulators for FLO1 expression. Therefore, S. cerevisiae is prepared to simultaneously express two genes of its otherwise silenced FLO reservoir resulting in an appropriate cellular surface for different environments.

The Saccharomyces homolog of mammalian RACK1, Cpc2/Asc1p, is required for FLO11-dependent adhesive growth and dimorphism.

Nutrient starvation results in the interaction of Saccharomyces cerevisiae cells with each other and with surfaces. Adhesive growth requires the expression of the FLO11 gene regulated by the Ras/cAMP/cAMP-dependent protein kinase, the Kss1p/MAPK, and the Gcn4p/general amino acid control pathway, respectively. Proteomics two-dimensional DIGE experiments revealed post-transcriptionally regulated proteins in response to amino acid starvation including the ribosomal protein Cpc2p/Asc1p. This putative translational regulator is highly conserved throughout the eukaryotic kingdom and orthologous to mammalian RACK1. Deletion of CPC2/ASC1 abolished amino acid starvation-induced adhesive growth and impaired basal expression of FLO11 and its activation upon starvation in haploid cells. In addition, the diploid Flo11p-dependent pseudohyphal growth during nitrogen limitation was CPC2/ASC1-dependent. A more detailed analysis revealed that a CPC2/ASC1 deletion caused increased sensitivity to cell wall drugs suggesting that the gene is required for general cell wall integrity. Phosphoproteome and Western hybridization data indicate that Cpc2p/Asc1p affected the phosphorylation of the translational initiation factors eIF2 alpha and eIF4A and the ribosome-associated complex RAC. A crucial role of Cpc2p/Asc1p at the ribosomal interface coordinating signal transduction, translation initiation, and transcription factor formation was corroborated.

Yeast Gcn4p stabilization is initiated by the dissociation of the nuclear Pho85p/Pcl5p complex.

Protein stability of the c-jun-like yeast bZIP transcriptional activator Gcn4p is exclusively controlled in the yeast nucleus. Phosphorylation by the nuclear Pho85p cyclin-dependent protein kinase, a functional homolog of mammalian Cdk5, initiates the Gcn4p degradation pathway in complex with the cyclin Pcl5p. We show that the initial step in Gcn4p stabilization is the dissociation of the Pho85p/Pcl5p complex. Pcl7p, another nuclear and constantly present cyclin, is required for Gcn4p stabilization and is able to associate to Pho85p independently of the activity of the Gcn4p degradation pathway. In addition, the nuclear cyclin-dependent Pho85p kinase inhibitor Pho81p is required for Gcn4p stabilization. Pho81p only interacts with Pcl5p when Gcn4p is rapidly degraded but constitutively interacts with Pcl7p. Our data suggest that Pcl7p and Pho81p are antagonists of the Pho85p/Pcl5p complex formation in a yet unknown way, which are specifically required for Gcn4p stabilization. We suggest that dissociation of the Pho85p/Pcl5p complex as initial step in Gcn4p stabilization is a prerequisite for a shift of equilibrium to an increased amount of the Pho85p/Pcl7p complexes and subsequently results in decreased Gcn4p phosphorylation and therefore increased stability of the transcription factor.