bonndata (Rheinische Friedrich-Wilhelms-Universität Bonn)
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Digitalis purpurea genome sequence and annotation V2
No full textHere we present a high-quality genome sequence and annotation of Digitalis purpurea (commonly known as foxglove), a plant valued both for its ornamental flowers and for producing the cardiac drug digoxin. The study aims to uncover the genetic basis of flower color variation in this species. Using ONT long-read sequencing data, we assembled the genome sequence of a magenta-flowering D. purpurea individual. We performed extensive gene prediction and functional annotation of protein-coding genes. Genes of the flavonoid biosynthesis were compared between magenta and white flowering individuals. Expression patterns were compared between different plant organs and between plants with different flower colors. Through these analyses, we identified a large insertion in the anthocyanidin synthase (ANS) that explains the differences between magenta and white flowers.
This data publication contains the genome sequence with the corresponding annotation V2
Data from dissertation "Transcriptomic regulation of hybrid vigor in immortalized backcross populations of maize (Zea mays L.)"
No full textThe data originates from a transcriptomic dataset from maize and contains results (eg. lists of candidate genes or genes with specific expression pattern), intermediate (genomic information on the lines of the study) and descriptive tables (sample information and locus information)
Supplementary data for "Three-loop banana integrals with four unequal masses"
No full textAncillary files that accompany the paper "Three-loop banana integrals with four unequal masses".
This dataset accompanies the paper "Three-loop banana integrals with four unequal masses".
It contains the canonical differential equations satisfied by the three-loop banana integrals with four distinct non-zero masses in D = 2-2\eps dimensions. Together with the initial condition in the small-mass limit, this provides all the ingredients to find analytic results for three-loop banana integrals in terms of iterated integrals to any desired order in the dimensional regulator.
It also contains: the cohomology intersection matrix, the starting differential equation matrix, the canonical differential equation matrix, the inverse of Z (the \epsilon^0 part of the cohomology intersection matrix without the entries related to the ISPs integrals), the rational functions that appear in the differential equation for G_0, the full set of relations among the \epsilon-functions and some compact substitutions for some entries in the canonical differential equation matrix
MuST-C Dataset: The Multi-Sensor and Multi-Temporal Data Set of Multiple Crops for In-Field Phenotyping and Monitoring
No full textPhenotyping is crucial for understanding crop trait variation and advancing research, but is currently limited by expensive, labor-intensive monitoring. New phenotypic trait monitoring methods are being proposed to reduce this so-called phenotyping bottleneck via automation. These methods are often data-driven, requiring a dataset recorded with a specific sensor and corresponding reference values for developing novel methods.
To this end, we present the MuST-C (Multi-Sensor, multi-Temporal, multiple Crops) dataset, which contains field data from various sensors collected over a growing season, covering six crop species. All data was georeferenced for alignment across sensors and dates. To collect our dataset, we deployed aerial and ground robotic platforms equipped with RGB cameras, LiDARs, and multispectral cameras, aiming to capture a wide variety of modalities and observations from different viewpoints. In addition to sensor data, we also provide manually collected leaf area index and biomass reference measurements. Our dataset enables the development of novel automatic phenotypic trait estimation methods, allows comparisons across different sensors, and generalizability across crop species
BUP-ST20: Weakly Labelled Spatial Temporal Sweet Pepper Data
No full textAccurate monitoring of crop phenotypic traits is essential for efficient farm management and automation in agriculture. Multi-object tracking (MOT) and video instance segmentation (VIS) offer promising approaches to enhance agricultural robotic vision systems, yet a major limitation is the scarcity of high-quality spatial-temporal datasets. We introduce BUP-ST20, a novel weakly labelled spatial-temporal dataset for sweet pepper tracking and segmentation captured on a robotic platform. BUP-ST20 contains 16,240 images from 275 sequences, each with bounding boxes, instance segmentation masks, and temporal identities.The dataset has weakly labelled training and validation sets, while the evaluation set includes 3810 frames with hand-labelled ground truth annotations
Image data related to the publication "Kupffer cell programming by maternal obesity triggers fatty liver disease"
No full textKupffer cells (KCs) are tissue-resident macrophages which colonize the liver early during embryogenesis. Upon liver colonization, KCs rapidly acquire a tissue-specific transcriptional signature, mature alongside the developing liver, and adapt to its functions. Throughout development and adulthood, KCs perform distinct core functions essential for liver and organismal homeostasis, including supporting fetal erythropoiesis, postnatal erythrocyte recycling, and liver metabolism. However, whether perturbations of macrophage core functions during development contribute to or cause disease at postnatal stages is poorly understood. Here, we utilize a mouse model of maternal obesity to perturb KC functions during gestation. We show that offspring exposed to maternal obesity develop fatty liver disease, driven by aberrant developmental programming of KCs that persists into adulthood. Programmed KCs promote lipid uptake by hepatocytes through apolipoprotein secretion. KC depletion in neonates born to obese mothers, followed by replenishment with naïve monocytes, rescues fatty liver disease. Further, genetic ablation of hypoxia-inducible factor alpha (Hif1a) in macrophages during gestation prevents the metabolic programming of KCs from oxidative phosphorylation to glycolysis, thereby averting the development of fatty liver disease. These results establish developmental perturbation of KC functions as a causal factor in fatty liver disease in adulthood and position fetal-derived macrophages as critical intergenerational messengers within the concept of developmental origins of health and diseases
Microscopy images of renal macrophages in the tissue environment and in 3D cultures
No full textMicroscopy images (confocal, brightfield) shown in the publication. We present here the unedited raw images in a .tif or .jpg format. The images are supplementary information for the various figures shown in the paper "Renal tissue-resident macrophages promote cystogenesis in early polycystic kidney disease"
Critical fluctuations of the exponential last passage percolation with thick boundaries
No full textThose files contain a numerical implementation of the generalized Baik-Rains distribution and some other related materials
Code and scripts for ``Matching Lagrangian and Hamiltonian Simulations in (2+1)-dimensional U(1) Gauge Theory''
No full textAt finite lattice spacing, Lagrangian and Hamiltonian predictions differ due to discretization effects.
In the Hamiltonian limit, i.e. at vanishing temporal lattice spacing a_t, the path integral approach in the Lagrangian formalism reproduces the results of the Hamiltonian theory.
In this work, we numerically calculate the Hamiltonian limit of a U(1) gauge theory in (2+1) dimensions.
This is achieved by Monte Carlo simulations in the Lagrangian formalism with lattices that are anisotropic in the time direction.
For each ensemble, we determine the ratio between the temporal and spatial scale with the static quark potential and extrapolate to a_t to 0.
Our results are compared with the data from Hamiltonian simulations at small volumes, showing agreement within <2 sigma.
These results can be used to match the two formalisms.
Here we provide the code and scripts needed to reproduce our results
Confocal live cell images of microglia in 3D cell culture from the dissertation ' 3D culture conditions instruct an in vivo-like phenotype in primary microgia'
No full textMicroglia are innate immune cells of the central nervous system. They possess a diverse range of morphological features that enable them to perform different functions, such as surveillance, phagocytosis and immune response. In response to changes in physiological conditions within the CNS, microglia actively alter their shape in order to maintain brain homeostasis.
Previous studies on the morphology and function of microglia have been conducted in 2D cell culture systems, which have been associated with an artificial morphology in microglia and altered microglial functions. Consequently, there is an increasing imperative to develop 3D cell culture systems that can more accurately replicate the complex microenvironment of the brain. The present study aims to investigate the impact of defined 3D cell culture conditions on gene expression, morphology, cell motility, innate immune response, and electrophysiological properties of cultured primary murine microglia.
To this end, live cell confocal microscopy imaging was employed to visualise microglia within a 3D cell culture environment, thereby enabling the study of their motility, morphology and phagocytosis.The findings of this study demonstrate that microglia develop a more in vivo-like morphology and surveillance motility when cultured under 3D compared to 2D conditions