Disaster medical support plan as an element of the hospital disaster resilience.

Abstract.

Annexin A6 and NPC1 regulate LDL-inducible cell migration and distribution of focal adhesions.

Cholesterol is considered indispensable for cell motility, but how physiological cholesterol pools enable cells to move forward remains to be clarified. The majority of cells obtain cholesterol from the uptake of Low-Density lipoproteins (LDL) and here we demonstrate that LDL stimulates A431 squamous epithelial carcinoma and Chinese hamster ovary (CHO) cell migration and invasion. LDL also potentiated epidermal growth factor (EGF) -stimulated A431 cell migration as well as A431 invasion in 3-dimensional environments, using organotypic assays. Blocking cholesterol export from late endosomes (LE), using Niemann Pick Type C1 (NPC1) mutant cells, pharmacological NPC1 inhibition or overexpression of the annexin A6 (AnxA6) scaffold protein, compromised LDL-inducible migration and invasion. Nevertheless, NPC1 mutant cells established focal adhesions (FA) that contain activated focal adhesion kinase (pY397FAK, pY861FAK), vinculin and paxillin. Compared to controls, NPC1 mutants display increased FA numbers throughout the cell body, but lack LDL-inducible FA formation at cell edges. Strikingly, AnxA6 depletion in NPC1 mutant cells, which restores late endosomal cholesterol export in these cells, increases their cell motility and association of the cholesterol biosensor D4H with active FAK at cell edges, indicating that AnxA6-regulated transport routes contribute to cholesterol delivery to FA structures, thereby improving NPC1 mutant cell migratory behaviour.

Prostate cancer cell proliferation is influenced by LDL-cholesterol availability and cholesteryl ester turnover.

BACKGROUND: Prostate cancer growth is driven by androgen receptor signaling, and advanced disease is initially treatable by depleting circulating androgens. However, prostate cancer cells inevitably adapt, resulting in disease relapse with incurable castrate-resistant prostate cancer. Androgen deprivation therapy has many side effects, including hypercholesterolemia, and more aggressive and castrate-resistant prostate cancers typically feature cellular accumulation of cholesterol stored in the form of cholesteryl esters. As cholesterol is a key substrate for de novo steroidogenesis in prostate cells, this study hypothesized that castrate-resistant/advanced prostate cancer cell growth is influenced by the availability of extracellular, low-density lipoprotein (LDL)-derived, cholesterol, which is coupled to intracellular cholesteryl ester homeostasis. METHODS: C4-2B and PC3 prostate cancer cells were cultured in media supplemented with fetal calf serum (FCS), charcoal-stripped FCS (CS-FCS), lipoprotein-deficient FCS (LPDS), or charcoal-stripped LPDS (CS-LPDS) and analyzed by a variety of biochemical techniques. Cell viability and proliferation were measured by MTT assay and Incucyte, respectively. RESULTS: Reducing lipoprotein availability led to a reduction in cholesteryl ester levels and cell growth in C4-2B and PC3 cells, with concomitant reductions in PI3K/mTOR and p38MAPK signaling. This reduced growth in LPDS-containing media was fully recovered by supplementation of exogenous low-density lipoprotein (LDL), but LDL only partially rescued growth of cells cultured with CS-LPDS. This growth pattern was not associated with changes in androgen receptor signaling but rather increased p38MAPK and MEK1/ERK/MSK1 activation. The ability of LDL supplementation to rescue cell growth required cholesterol esterification as well as cholesteryl ester hydrolysis activity. Further, growth of cells cultured in low androgen levels (CS-FCS) was suppressed when cholesteryl ester hydrolysis was inhibited. CONCLUSIONS: Overall, these studies demonstrate that androgen-independent prostate cancer cell growth can be influenced by extracellular lipid levels and LDL-cholesterol availability and that uptake of extracellular cholesterol, through endocytosis of LDL-derived cholesterol and subsequent delivery and storage in the lipid droplet as cholesteryl esters, is required to support prostate cancer cell growth. This provides new insights into the relationship between extracellular cholesterol, intracellular cholesterol metabolism, and prostate cancer cell growth and the potential mechanisms linking hypercholesterolemia and more aggressive prostate cancer.

Ultrafast homomorphic encryption models enable secure outsourcing of genotype imputation.

Genotype imputation is a fundamental step in genomic data analysis, where missing variant genotypes are predicted using the existing genotypes of nearby "tag" variants. Although researchers can outsource genotype imputation, privacy concerns may prohibit genetic data sharing with an untrusted imputation service. Here, we developed secure genotype imputation using efficient homomorphic encryption (HE) techniques. In HE-based methods, the genotype data are secure while it is in transit, at rest, and in analysis. It can only be decrypted by the owner. We compared secure imputation with three state-of-the-art non-secure methods and found that HE-based methods provide genetic data security with comparable accuracy for common variants. HE-based methods have time and memory requirements that are comparable or lower than those for the non-secure methods. Our results provide evidence that HE-based methods can practically perform resource-intensive computations for high-throughput genetic data analysis. The source code is freely available for download at https://github.com/K-miran/secure-imputation.

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption.

BACKGROUND: Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithms to be securely deployed in the cloud because operations on encrypted genomic databases are conducted without revealing any individual genomes. Methods for secure computation have shown significant performance improvements over the last several years. However, it is still challenging to apply them on large biomedical datasets. METHODS: The HE Track of iDash 2018 competition focused on solving an important problem in practical machine learning scenarios, where a data analyst that has trained a regression model (both linear and logistic) with a certain set of features, attempts to find all features in an encrypted database that will improve the quality of the model. Our solution is based on the hybrid framework Chimera that allows for switching between different families of fully homomorphic schemes, namely TFHE and HEAAN. RESULTS: Our solution is one of the finalist of Track 2 of iDash 2018 competition. Among the submitted solutions, ours is the only bootstrapped approach that can be applied for different sets of parameters without re-encrypting the genomic database, making it practical for real-world applications. CONCLUSIONS: This is the first step towards the more general feature selection problem across large encrypted databases.

Single-cell absolute contact probability detection reveals chromosomes are organized by multiple low-frequency yet specific interactions.

At the kilo- to megabase pair scales, eukaryotic genomes are partitioned into self-interacting modules or topologically associated domains (TADs) that associate to form nuclear compartments. Here, we combine high-content super-resolution microscopies with state-of-the-art DNA-labeling methods to reveal the variability in the multiscale organization of the Drosophila genome. We find that association frequencies within TADs and between TAD borders are below ~10%, independently of TAD size, epigenetic state, or cell type. Critically, despite this large heterogeneity, we are able to visualize nanometer-sized epigenetic domains at the single-cell level. In addition, absolute contact frequencies within and between TADs are to a large extent defined by genomic distance, higher-order chromosome architecture, and epigenetic identity. We propose that TADs and compartments are organized by multiple, small-frequency, yet specific interactions that are regulated by epigenetics and transcriptional state.

Near-Infrared Spectroscopic Analysis of Total Phenolic Content and Antioxidant Activity of Berry Fruits.

This study evaluates the feasibility of using near-infrared (NIR) spectroscopy as a rapid and environmentally friendly technique for validation and prediction of the total phenolic content (TPC) and antioxidant activity (AOA) indices (as 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, inhibition time (IT) of the Briggs-Rauscher oscillating reaction, and relative antioxidant capacity (RAC)) of berry fruit extracts. The analysed berry samples originated from Croatia (blackberries, wild blueberries, raspberries, red currants and strawberries) and Bulgaria (wild blueberries, raspberries and strawberries). Principal component analysis and partial least squares (PLS) regression were used from the set of chemometric tools in distinguishing and validating the measured berry fruit extract. ANOVA and PCA showed no significant impact of the origin and freshness of the samples. PLS models were developed to validate the relationship of NIR spectra with TPC and AOA of berry fruits. Representativeness of the models was expressed with the R2 and the ratio of performance to deviation. Calculated R2 values were above 0.84 and the ratio of performance to deviation was between 1.8 and 3.1, indicating adequacy of the PLS models.

Foci of cyclin A2 interact with actin and RhoA in mitosis.

Cyclin A2 is a key player in the regulation of the cell cycle. Its degradation in mid-mitosis depends primarily on the ubiquitin-proteasome system (UPS), while autophagy also contributes. However, a fraction of cyclin A2 persists beyond metaphase. In this work, we focus on cyclin A2-rich foci detected in mitosis by high resolution imaging and analyse their movements. We demonstrate that cyclin A2 interacts with actin and RhoA during mitosis, and that cyclin A2 depletion induces a dramatic decrease in active RhoA in mitosis. Our data suggest cyclin A2 participation in RhoA activation in late mitosis.

Nanometer resolved single-molecule colocalization of nuclear factors by two-color super resolution microscopy imaging.

In order to study the detailed assembly and regulation mechanisms of complex structures and machineries in the cell, simultaneous in situ observation of all the individual interacting components should be achieved. Multi-color Single-Molecule Localization Microscopy (SMLM) is ideally suited for these quantifications. Here, we build on previous developments and thoroughly discuss a protocol for two-color SMLM combining PALM and STORM, including sample preparation details, image acquisition and data postprocessing analysis. We implement and evaluate a recently proposed colocalization analysis method (aCBC) that allows single-molecule colocalization quantification with the potential of revealing fine, nanometer-scaled, structural details of multicomponent complexes. Finally, using a doubly-labeled nuclear factor (Beaf-32) in Drosophila S2 cells we experimentally validate the colocalization quantification algorithm, highlight its advantages and discuss how using high molecular weight fluorescently labeled tags compromises colocalization precision in two-color SMLM experiments.