Joint classification of ALS and DIM point clouds

National mapping agencies (NMAs) have to acquire nation-wide Digital Terrain Models on a regular basis as part of their obligations to provide up-to-date data. Point clouds from Airborne Laser Scanning (ALS) are an important data source for this task; recently, NMAs also started deriving Dense Image Matching (DIM) point clouds from aerial images. As a result, NMAs have both point cloud data sources available, which they can exploit for their purposes. In this study, we investigate the potential of transfer learning from ALS to DIM data, so the time consuming step of data labelling can be reduced. Due to their specific individual measurement techniques, both point clouds have various distinct properties such as RGB or intensity values, which are often exploited for classification of either ALS or DIM point clouds. However, those features also hinder transfer learning between these two point cloud types, since they do not exist in the other point cloud type. As the mere 3D point is available in both point cloud types, we focus on transfer learning from an ALS to a DIM point cloud using exclusively the point coordinates. We are tackling the issue of different point densities by rasterizing the point cloud into a 2D grid and take important height features as input for classification. We train an encoder-decoder convolutional neural network with labelled ALS data as a baseline and then fine-tune this baseline with an increasing amount of labelled DIM data. We also train the same network exclusively on all available DIM data as reference to compare our results. We show that only 10% of labelled DIM data increase the classification results notably, which is especially relevant for practical applications

EXPLORING ALS AND DIM DATA FOR SEMANTIC SEGMENTATION USING CNNS

Over the past years, the algorithms for dense image matching (DIM) to obtain point clouds from aerial images improved significantly. Consequently, DIM point clouds are now a good alternative to the established Airborne Laser Scanning (ALS) point clouds for remote sensing applications. In order to derive high-level applications such as digital terrain models or city models, each point within a point cloud must be assigned a class label. Usually, ALS and DIM are labelled with different classifiers due to their varying characteristics. In this work, we explore both point cloud types in a fully convolutional encoder-decoder network, which learns to classify ALS as well as DIM point clouds. As input, we project the point clouds onto a 2D image raster plane and calculate the minimal, average and maximal height values for each raster cell. The network then differentiates between the classes ground, non-ground, building and no data. We test our network in six training setups using only one point cloud type, both point clouds as well as several transfer-learning approaches. We quantitatively and qualitatively compare all results and discuss the advantages and disadvantages of all setups. The best network achieves an overall accuracy of 96 % in an ALS and 83 % in a DIM test set

Building Change Detection in Airborne Laser Scanning and Dense Image Matching Point Clouds Using a Residual Neural Network

National Mapping Agencies (NMAs) acquire nation-wide point cloud data from Airborne Laser Scanning (ALS) sensors as well as using Dense Image Matching (DIM) on aerial images. As these datasets are often captured years apart, they contain implicit information about changes in the real world. While detecting changes within point clouds is not a new topic per se, detecting changes in point clouds from different sensors, which consequently have different point densities, point distributions and characteristics, is still an on-going problem. As such, we approach this task using a residual neural network, which detects building changes using height and class information on a raster level. In the experiments, we show that this approach is capable of detecting building changes automatically and reliably independent of the given point clouds and for various building sizes achieving mean F1-Scores of 80.5% and 79.8% for ALS-ALS and ALS-DIM point clouds on an object-level and F1-Scores of 91.1% and 86.3% on a raster-level, respectively

Rapid, diffusional shuttling of poly(A) RNA between nuclear speckles and the nucleoplasm

Speckles are nuclear bodies that contain pre-mRNA splicing factors and polyadenylated RNA. Because nuclear poly(A) RNA consists of both mRNA transcripts and nucleus-restricted RNAs, we tested whether poly(A) RNA in speckles is dynamic or rather an immobile, perhaps structural, component. Fluorescein-labeled oligo(dT) was introduced into HeLa cells stably expressing a red fluorescent protein chimera of the splicing factor SC35 and allowed to hybridize. Fluorescence correlation spectroscopy (FCS) showed that the mobility of the tagged poly(A) RNA was virtually identical in both speckles and at random nucleoplasmic sites. This same result was observed in photoactivation-tracking studies in which caged fluorescein-labeled oligo(dT) was used as hybridization probe, and the rate of movement away from either a speckle or nucleoplasmic site was monitored using digital imaging microscopy after photoactivation. Furthermore, the tagged poly(A) RNA was observed to rapidly distribute throughout the entire nucleoplasm and other speckles, regardless of whether the tracking observations were initiated in a speckle or the nucleoplasm. Finally, in both FCS and photoactivation-tracking studies, a temperature reduction from 37 to 22°C had no discernible effect on the behavior of poly(A) RNA in either speckles or the nucleoplasm, strongly suggesting that its movement in and out of speckles does not require metabolic energy. © 2006 by The American Society for Cell Biology

Probing Intranuclear Environments at the Single-Molecule Level

Genome activity and nuclear metabolism clearly depend on accessibility, but it is not known whether and to what extent nuclear structures limit the mobility and access of individual molecules. We used fluorescently labeled streptavidin with a nuclear localization signal as an average-sized, inert protein to probe the nuclear environment. The protein was injected into the cytoplasm of mouse cells, and single molecules were tracked in the nucleus with high-speed fluorescence microscopy. We analyzed and compared the mobility of single streptavidin molecules in structurally and functionally distinct nuclear compartments of living cells. Our results indicated that all nuclear subcompartments were easily and similarly accessible for such an average-sized protein, and even condensed heterochromatin neither excluded single molecules nor impeded their passage. The only significant difference was a higher frequency of transient trappings in heterochromatin, which lasted only tens of milliseconds. The streptavidin molecules, however, did not accumulate in heterochromatin, suggesting comparatively less free volume. Interestingly, the nucleolus seemed to exclude streptavidin, as it did many other nuclear proteins, when visualized by conventional fluorescence microscopy. The tracking of single molecules, nonetheless, showed no evidence for repulsion at the border but relatively unimpeded passage through the nucleolus. These results clearly show that single-molecule tracking can provide novel insights into mobility of proteins in the nucleus that cannot be obtained by conventional fluorescence microscopy. Our results suggest that nuclear processes may not be regulated at the level of physical accessibility but rather by local concentration of reactants and availability of binding sites

Targeted knock-down of miR21 primary transcripts using snoMEN vectors induces apoptosis in human cancer cell lines

We have previously reported an antisense technology, 'snoMEN vectors', for targeted knock-down of protein coding mRNAs using human snoRNAs manipulated to contain short regions of sequence complementarity with the mRNA target. Here we characterise the use of snoMEN vectors to target the knock-down of micro RNA primary transcripts. We document the specific knock-down of miR21 in HeLa cells using plasmid vectors expressing miR21-targeted snoMEN RNAs and show this induces apoptosis. Knock-down is dependent on the presence of complementary sequences in the snoMEN vector and the induction of apoptosis can be suppressed by over-expression of miR21. Furthermore, we have also developed lentiviral vectors for delivery of snoMEN RNAs and show this increases the efficiency of vector transduction in many human cell lines that are difficult to transfect with plasmid vectors. Transduction of lentiviral vectors expressing snoMEN targeted to pri-miR21 induces apoptosis in human lung adenocarcinoma cells, which express high levels of miR21, but not in human primary cells. We show that snoMEN-mediated suppression of miRNA expression is prevented by siRNA knock-down of Ago2, but not by knock-down of Ago1 or Upf1. snoMEN RNAs colocalise with Ago2 in cell nuclei and nucleoli and can be co-immunoprecipitated from nuclear extracts by antibodies specific for Ago2

Copanlisib synergizes with conventional and targeted agents including venetoclax in B- And T-cell lymphoma models

Copanlisib is a pan-class I phosphoinositide 3-kinase (PI3K) inhibitor with preferred activity toward PI3Ka and PI3Kd. Despite the clear overall clinical benefit, the number of patients achieving complete remissions with the single agent is relatively low, a problem shared by the vast majority of targeted agents. Here, we searched for novel copanlisib-based combinations. Copanlisib was tested as a single agent, in combination with an additional 17 drugs in 26 cell lines derived from mantle cell lymphoma (MCL), marginal zone lymphoma (MZL), and T-cell lymphomas. In vivo experiments, transcriptome analyses, and immunoblotting experiments were also performed. Copanlisib as a single agent showed in vitro dose-dependent antitumor activity in the vast majority of the models. Combination screening identified several compounds that synergized with copanlisib. The strongest combination was with the B-cell lymphoma 2 (BCL2) inhibitor venetoclax. The benefit of the combination over single agents was also validated in an MZL xenograft model and in MCL primary cells, and was due to increased induction of apoptosis, an effect likely sustained by the reduction of the antiapoptotic proteins myeloid cell leukemia 1 (MCL1) and BCL-XL, observed in MCL and MZL cell lines, respectively. These data supported the rationale for the design of the Swiss Group for Clinical Cancer Research (SAKK) 66/18phase 1 study currently exploring the combination of copanlisib and venetoclax in relapsed/refractory lymphomas

Widespread Regulation of miRNA Biogenesis at the Dicer Step by the Cold-Inducible RNA-Binding Protein, RBM3

MicroRNAs (miRNAs) play critical roles in diverse cellular events through their effects on translation. Emerging data suggest that modulation of miRNA biogenesis at post-transcriptional steps by RNA-binding proteins is a key point of regulatory control over the expression of some miRNAs and the cellular processes they influence. However, the extent and conditions under which the miRNA pathway is amenable to regulation at posttranscriptional steps are poorly understood. Here we show that RBM3, a cold-inducible, developmentally regulated RNA-binding protein and putative protooncogene, is an essential regulator of miRNA biogenesis. Utilizing miRNA array, Northern blot, and PCR methods, we observed that over 60% of miRNAs detectable in a neuronal cell line were significantly downregulated by knockdown of RBM3. Conversely, for select miRNAs assayed by Northern blot, induction of RBM3 by overexpression or mild hypothermia increased their levels. Changes in miRNA expression were accompanied by changes in the levels of their ∼70 nt precursors, whereas primary transcript levels were unaffected. Mechanistic studies revealed that knockdown of RBM3 does not reduce Dicer activity or impede transport of pre-miRNAs into the cytoplasm. Rather, we find that RBM3 binds directly to ∼70 nt pre-miRNA intermediates and promotes / de-represses their ability as larger ribonucleoproteins (pre-miRNPs) to associate with active Dicer complexes. Our findings suggest that the processing of a majority of pre-miRNPs by Dicer is subject to an intrinsic inhibitory influence that is overcome by RBM3 expression. RBM3 may thus orchestrate changes in miRNA expression during hypothermia and other cellular stresses, and in the euthermic contexts of early development, differentiation, and oncogenesis where RBM3 expression is highly elevated. Additionally, our data suggest that temperature-dependent changes in miRNA expression mediated by RBM3 may contribute to the therapeutic effects of hypothermia, and are an important variable to consider in in vitro studies of translation-dependent cellular events

The 4D Nucleome Project [preprint]

The spatial organization of the genome and its dynamics contribute to gene expression and cellular function in normal development as well as in disease. Although we are increasingly well equipped to determine a genome\u27s sequence and linear chromatin composition, studying the three-dimensional organization of the genome with high spatial and temporal resolution remains challenging. The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the long term goal of gaining deeper mechanistic understanding of how the nucleus is organized. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Further efforts will be directed at applying validated experimental approaches combined with biophysical modeling to generate integrated maps and quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells