CAPS facilitates filling of the rapidly releasable pool of large dense-core vesicles

Calcium-activator protein for secretion (CAPS) is a cytosolic protein that associates with large dense-core vesicles and is involved in their secretion. Mammals express two CAPS isoforms, which share a similar domain structure including a Munc13 homology domain that is believed to be involved in the priming of secretory vesicles. A variety of studies designed to perturb CAPS function indicate that CAPS is involved in the secretion of large dense-core vesicles, but where in the secretory pathway CAPS acts is still under debate. Mice in which one allele of the CAPS-1 gene is deleted exhibit a deficit in catecholamine secretion from chromaffin cells. We have examined catecholamine secretion from chromaffin cells in which both CAPS genes were deleted and show that the deletion of both CAPS isoforms causes a strong reduction in the pool of rapidly releasable chromaffin granules and of sustained release during ongoing stimulation. We conclude that CAPS is required for the adequate refilling and/or maintenance of a rapidly releasable granule pool

CAPS1 Regulates Catecholamine Loading of Large Dense-Core Vesicles

SummaryCAPS1 is thought to play an essential role in mediating exocytosis from large dense-core vesicles (LDCVs). We generated CAPS1-deficient (KO) mice and studied exocytosis in a model system for Ca2+-dependent LDCV secretion, the adrenal chromaffin cell. Adult heterozygous CAPS1 KO cells display a gene dosage-dependent decrease of CAPS1 expression and a concomitant reduction in the number of docked vesicles and secretion. Embryonic homozygous CAPS1 KO cells show a strong reduction in the frequency of amperometrically detectable release events of transmitter-filled vesicles, while the total number of fusing vesicles, as judged by capacitance recordings or total internal reflection microscopy, remains unchanged. We conclude that CAPS1 is required for an essential step in the uptake or storage of catecholamines in LDCVs

Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations

Since the onset of computer-aided diagnosis in medical imaging, voxel-based segmentation has emerged as the primary methodology for automatic analysis of left ventricle (LV) function and morphology in cardiac magnetic resonance images (CMRI). In standard clinical practice, simultaneous multi-slice 2D cine short-axis MR imaging is performed under multiple breath-holds resulting in highly anisotropic 3D images. Furthermore, sparse-view CMRI often lacks whole heart coverage caused by large slice thickness and often suffers from inter-slice misalignment induced by respiratory motion. Therefore, these volumes only provide limited information about the true 3D cardiac anatomy which may hamper highly accurate assessment of functional and anatomical abnormalities. To address this, we propose a method that learns a continuous implicit function representing 3D LV shapes by training an auto-decoder. For training, high-resolution segmentations from cardiac CT angiography are used. The ability of our approach to reconstruct and complete high-resolution shapes from manually or automatically obtained sparse-view cardiac shape information is evaluated by using paired high- and low-resolution CMRI LV segmentations. The results show that the reconstructed LV shapes have an unconstrained subvoxel resolution and appear smooth and plausible in through-plane direction. Furthermore, Bland-Altman analysis reveals that reconstructed high-resolution ventricle volumes are closer to the corresponding reference volumes than reference low-resolution volumes with bias of [limits of agreement] −3.51 [−18.87, 11.85] mL, and 12.96 [−10.01, 35.92] mL respectively. Finally, the results demonstrate that the proposed approach allows recovering missing shape information and can indirectly correct for limited motion-induced artifacts

Two distinct secretory vesicle–priming steps in adrenal chromaffin cells

The calcium-dependent activator proteins for secretion, CAPS1 and CAPS2, facilitate syntaxin opening during synaptic vesicle priming

Algorithmic deformation of matrix factorisations

Branes and defects in topological Landau-Ginzburg models are described by matrix factorisations. We revisit the problem of deforming them and discuss various deformation methods as well as their relations. We have implemented these algorithms and apply them to several examples. Apart from explicit results in concrete cases, this leads to a novel way to generate new matrix factorisations via nilpotent substitutions, and to criteria whether boundary obstructions can be lifted by bulk deformations.Comment: 30 page

A software pipeline for processing and identification of fungal ITS sequences

<p>Abstract</p> <p>Background</p> <p>Fungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (<it>ITS</it>) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software – in the form of an identification pipeline for large sets of fungal <it>ITS </it>sequences – developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 <it>ITS </it>sequences from fungi growing as epiphytes on building material.</p> <p>Results</p> <p>The pipeline was written in Perl and uses a local installation of NCBI-BLAST for the similarity searches of the query sequences. The variable subregion <it>ITS2 </it>of the <it>ITS </it>region is extracted from the sequences and used for additional searches of higher sensitivity. Multiple alignments of each query sequence and its closest matches are computed, and query sequences sharing at least 50% of their best matches are clustered to facilitate the evaluation of hypothetically conspecific groups. The pipeline proved to speed up the processing, as well as enhance the resolution, of the evaluation dataset considerably, and the fungi were found to belong chiefly to the <it>Ascomycota</it>, with <it>Penicillium </it>and <it>Aspergillus </it>as the two most common genera. The <it>ITS2 </it>was found to indicate a different taxonomic affiliation than did the complete <it>ITS </it>region for 10% of the query sequences, though this figure is likely to vary with the taxonomic scope of the query sequences.</p> <p>Conclusion</p> <p>The present software readily assigns large sets of fungal query sequences to their respective best matches in the international sequence databases and places them in a larger biological context. The output is highly structured to be easy to process, although it still needs to be inspected and possibly corrected for the impact of the incomplete and sometimes erroneously annotated fungal entries in these databases. The open source pipeline is available for UNIX-type platforms, and updated releases of the target database are made available biweekly. The pipeline is easily modified to operate on other molecular regions and organism groups.</p

Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes

Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered a key pathogenic driver of these diseases, but the underlying immune states and their clinical implications remain poorly understood. Multiomic factor analysis (MOFA) allows unsupervised data exploration across multiple data types, identifying major axes of variation and associating these with underlying molecular processes. We hypothesized that applying MOFA to multiomic data obtained from blood might uncover hidden sources of variance and provide pathophysiological insights linked to clinical needs. Here we compile a longitudinal multiomic dataset of the systemic immune landscape in both ACS and CCS (n = 62 patients in total, n = 15 women and n = 47 men) and validate this in an external cohort (n = 55 patients in total, n = 11 women and n = 44 men). MOFA reveals multicellular immune signatures characterized by distinct monocyte, natural killer and T cell substates and immune-communication pathways that explain a large proportion of inter-patient variance. We also identify specific factors that reflect disease state or associate with treatment outcome in ACS as measured using left ventricular ejection fraction. Hence, this study provides proof-of-concept evidence for the ability of MOFA to uncover multicellular immune programs in cardiovascular disease, opening new directions for mechanistic, biomarker and therapeutic studies

Value of spectral detector CT for pretherapeutic, locoregional assessment of esophageal cancer

Purpose: To investigate the diagnostic value of spectral detector dual-energy CT-derived low-keV virtual monoenergetic images (VMI) and iodine overlays (IO) for locoregional, pretherapeutic assessment of esophageal cancer. Method: 74 patients with biopsy-proven esophageal cancer who underwent pre-therapeutic, portal-venous-phase staging examinations of the chest and abdomen were retrospectively included. Quantitative image analysis was performed ROI-based within the tumor, healthy esophageal wall, peri-esophageal lymph nodes, azygos vein, aorta, liver, diaphragm, and mediastinal fat. Two radiologists evaluated delineation of the primary tumor and locoregional lymph nodes, assessment of the celiac trunk and diagnostic certainty regarding tumor infiltration in conventional images (CI), VMI from 40 to 70 keV and IO. Moreover, presence/absence of advanced tumor infiltration (T3/T4) was determined binary using all available images. Results: VMI40-60keV showed significantly higher attenuation and signal-to-noise ratio compared to CI for all assessed ROIs, peaking at VMI40keV (p < 0.05). Contrast-to-noise ratio of tumor/esophagus (VMI40keV/CI: 7.7 + 4.7 vs. 2.3 +/- 1.5), tumor/diaphragm (VMI40keV/CI: 9.0 +/- 5.5 vs. 2.2 +/- 1.7) and tumor/liver (4.3 +/- 5.5 vs. 1.9 +/- 2.1) were all significantly higher compared to CI (p < 0.05). Qualitatively, lymph node delineation and diagnostic certainty regarding tumor infiltration received highest ratings both in IO and VMI40keV, whereas vascular assessment was rated highest in VMI40keV and primary tumor delineation in 10. Sensitivity/Specificity/ Accuracy for detecting advanced tumor infiltration using the combination of CI, VMI40-70keV and IO was 42.4 %/82.0 %/56.3 %. Conclusions: I0 and VMI40-60keV improve qualitative assessment of the primary tumor and depiction of lymph nodes and vessels at pretherapeutic SDCT of esophageal cancer patients yet do not mitigate the limitations of CT in determining tumor infiltration