Reconstruction and annotation of volume electron microscopy data sets of brain tissue is challenging but can reveal invaluable information about neuronal circuits. Significant progress has recently ...been made in automated neuron reconstruction as well as automated detection of synapses. However, methods for automating the morphological analysis of nanometer-resolution reconstructions are less established, despite the diversity of possible applications. Here, we introduce cellular morphology neural networks (CMNs), based on multi-view projections sampled from automatically reconstructed cellular fragments of arbitrary size and shape. Using unsupervised training, we infer morphology embeddings (Neuron2vec) of neuron reconstructions and train CMNs to identify glia cells in a supervised classification paradigm, which are then used to resolve neuron reconstruction errors. Finally, we demonstrate that CMNs can be used to identify subcellular compartments and the cell types of neuron reconstructions.
Teravoxel volume electron microscopy data sets from neural tissue can now be acquired in weeks, but data analysis requires years of manual labor. We developed the SyConn framework, which uses deep ...convolutional neural networks and random forest classifiers to infer a richly annotated synaptic connectivity matrix from manual neurite skeleton reconstructions by automatically identifying mitochondria, synapses and their types, axons, dendrites, spines, myelin, somata and cell types. We tested our approach on serial block-face electron microscopy data sets from zebrafish, mouse and zebra finch, and computed the synaptic wiring of songbird basal ganglia. We found that, for example, basal-ganglia cell types with high firing rates in vivo had higher densities of mitochondria and vesicles and that synapse sizes and quantities scaled systematically, depending on the innervated postsynaptic cell types.
Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a ...resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14 × 14 × 25 nm
. We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system.
Seagrass beds are the foundation species of functionally important coastal ecosystems worldwide. The world's largest losses of the widespread seagrass Zostera marina (eelgrass) have been reported as ...a consequence of wasting disease, an infection with the endophytic protist Labyrinthula zosterae. During one of the most extended epidemics in the marine realm, ∼90% of East and Western Atlantic eelgrass beds died-off between 1932 and 1934. Today, small outbreaks continue to be reported, but the current extent of L. zosterae in European meadows is completely unknown. In this study we quantify the abundance and prevalence of the wasting disease pathogen among 19 Z. marina populations in northern European coastal waters, using quantitative PCR (QPCR) with primers targeting a species specific portion of the internally transcribed spacer (ITS1) of L. zosterae. Spatially, we found marked variation among sites with abundances varying between 0 and 126 cells mg(-1) Z. marina dry weight (mean: 5.7 L. zosterae cells mg(-1) Z. marina dry weight ±1.9 SE) and prevalences ranged from 0-88.9%. Temporarily, abundances varied between 0 and 271 cells mg(-1) Z. marina dry weight (mean: 8.5±2.6 SE), while prevalences ranged from zero in winter and early spring to 96% in summer. Field concentrations accessed via bulk DNA extraction and subsequent QPCR correlated well with prevalence data estimated via isolation and cultivation from live plant tissue. L. zosterae was not only detectable in black lesions, a sign of Labyrinthula-induced necrosis, but also occurred in green, apparently healthy tissue. We conclude that L. zosterae infection is common (84% infected populations) in (northern) European eelgrass populations with highest abundances during the summer months. In the light of global climate change and increasing rate of marine diseases our data provide a baseline for further studies on the causes of pathogenic outbreaks of L. zosterae.
The ability to acquire ever larger datasets of brain tissue using volume electron microscopy leads to an increasing demand for the automated extraction of connectomic information. We introduce ...SyConn2, an open-source connectome analysis toolkit, which works with both on-site high-performance compute environments and rentable cloud computing clusters. SyConn2 was tested on connectomic datasets with more than 10 million synapses, provides a web-based visualization interface and makes these data amenable to complex anatomical and neuronal connectivity queries.
Seagrasses, a polyphyletic group of about 60 marine angiosperm species, are the foundation of diverse and functionally important marine habitats along sheltered sedimentary coasts. As a novel ...ecological function with high societal relevance, a role of the seagrass leaf canopy for reducing potentially harmful bacteria has recently been hypothesized in tropical regions, but data for temperate regions are lacking. Here, we tested whether or not the abundance of general bacteria and more specifically, those belonging to the genus
Vibrio
were reduced within temperate
Zostera marina
(eelgrass) meadows compared to adjacent sand flats and sampled 5 sites in the south-western Baltic Sea using SCUBA. Compared to non-vegetated area, we found an average reduction of 39% for all
Vibrio
and 63% for the potentially harmful
V. vulnificus/cholerae
subtype based on robust plate counting data on
Vibrio
selective agar. The underlying mechanism of the reduction in bacterial load is currently elusive and clearly merits further study. Our results underline the critical importance of seagrasses in maintaining shallow water ecosystem functioning including water quality and provide further motivation for their protection and restoration.
Unified risk analysis in radiation therapy Lohmann, Daniel; Shariff, Maya; Schubert, Philipp ...
Zeitschrift für medizinische Physik,
11/2023, Letnik:
33, Številka:
4
Journal Article
Recenzirano
Odprti dostop
The increasing complexity of new treatment methods as well as the Information Technology (IT) infrastructure within radiotherapy require new methods for risk analysis. This work presents a ...methodology on how to model the treatment process of radiotherapy in different levels. This subdivision makes it possible to perform workflow-specific risk analysis and to assess the impact of IT risks on the overall treatment workflow.
A Unified Modeling Language (UML) activity diagram is used to model the workflows. The subdivision of the workflows into different levels is done with the help of swim lanes. The model created in this way is exported in an xml-compatible format and stored in a database with the help of a Python program.
Based on an existing risk analysis, the workflows CT Appointment, Glioblastoma Multiforme, and Deep Inspiration Breath Hold (DIBH) were modeled in detail. Part of the analysis are automatically generated workflow-specific risk matrices including risks of medical devices incorporated into a specific workflow. In addition, SQL queries allow to quickly retrieve e.g., the details of the medical device network installed in a department.
Activity diagrams of UML can be used to model workflows in radiotherapy. Through this, a connection between the different levels of the entire workflow can be established and workflow-specific risk analysis is possible.
Seagrass meadows are one of the most important benthic habitats in the Baltic Sea. Nevertheless, spatially continuous mapping data of Zostera marina, the predominant seagrass species in the Baltic ...Sea, are lacking in the shallow coastal waters. Sentinel‐2 turned out to be valuable for mapping coastal benthic habitats in clear waters, whereas knowledge in turbid waters is rare. Here, we transfer a clear water mapping approach to turbid waters to assess how Sentinel‐2 can contribute to seagrass mapping in the Western Baltic Sea. Sentinel‐2 data were atmospherically corrected using ACOLITE and subsequently corrected for water column effects. To generate a data basis for training and validating random forest classification models, we developed an upscaling approach using video transect data and aerial imagery. We were able to map five coastal benthic habitats: bare sand (25 km²), sand dominated (16 km²), seagrass dominated (7 km²), dense seagrass (25 km²) and mixed substrates with red/ brown algae (3.5 km²) in a study area along the northern German coastline. Validation with independent data pointed out that water column correction does not significantly improve classification results compared to solely atmospherically corrected data (balanced overall accuracies ~0.92). Within optically shallow waters (0–4 m), per class and overall balanced accuracies (>0.82) differed marginally depending on the water depth. Overall balanced accuracy became worse (<0.8) approaching the border to optically deep water (~ 5 m). The spatial resolution of Sentinel‐2 (10–20 m) allowed delineating detailed spatial patterns of seagrass habitats, which may serve as a basis to retrieve spatially continuous data for ecologically relevant metrics such as patchiness. Thus, Sentinel‐2 can contribute unprecedented information for seagrass mapping between 0 and around 5 m water depths in the Western Baltic Sea.
Sentinel‐2 provides unprecedented information on seagrass distribution in the Western Baltic Sea between 0 and 5‐m water depths. Classification results and accuracies are similar using only atmospherically or additionally water‐column corrected reflectance data. The turbid waters limit analyses to water depths less than 5 m. In these shallow waters, the new maps provide spatially continuous data on seagrass distribution patches, for example patches or large, connected meadows, which is highly interesting for seagrass ecology (e.g. restoration projects and management).
In the northern hemisphere, eelgrass Zostera marina L. is the most important and widespread seagrass species. Despite its ecological importance, baseline data on eelgrass distribution and abundance ...are mostly absent, particularly in subtidal areas with relatively turbid waters. Here, we report a combined approach of vegetation mapping in the Baltic Sea coupled to a species distribution model (SDM). Eelgrass cover was mapped continuously in the summers of 2010 and 2011 with an underwater towed camera along ~400 km of seafloor. Eelgrass populated 80% of the study region and occurred at water depths between 0.6 and 7.6 m at sheltered to moderately exposed coasts. Mean patch length was 128.6 m but was higher at sheltered locations, with a maximum of >2000 m. The video observations (n = 7824) were used as empiric input to the SDMs. Using generalized additive models, 3 predictor variables (depth, wave exposure, and slope), which were selected based on Akaike’s information criterion, were sufficient to predict eelgrass presence/absence. Along with a very good overall discriminative ability (area under the receiver-operating characteristic curve ROC/AUC = 0.82), depth (as a proxy for light), wave exposure, and slope contributed 66, 29, and 5%, respectively, to the final model. The estimated total areal extent of eelgrass in the study region amounts to 140.5 km² and comprises about 11.5% of all known Baltic seagrass beds. The present work is, to the best of our knowledge, the largest study undertaken to date on vegetation mapping and the first to assess distribution of eelgrass quantitatively in the western Baltic Sea.
BackgroundThe predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should ...identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis.MethodsA total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients’ peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status.ResultsWhole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14high monocytes, CD8+/PD-1+ T cells, plasmacytoid dendritic cells, neutrophils, and CD3+/CD56+/CD16+ natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI.ConclusionOur study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood.Trial registration numberNCT03453892.
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