Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model

Denoising is the essential step for distant supervision based named entity recognition. Previous denoising methods are mostly based on instance-level confidence statistics, which ignore the variety of the underlying noise distribution on different datasets and entity types. This makes them difficult to be adapted to high noise rate settings. In this paper, we propose Hypergeometric Learning (HGL), a denoising algorithm for distantly supervised NER that takes both noise distribution and instance-level confidence into consideration. Specifically, during neural network training, we naturally model the noise samples in each batch following a hypergeometric distribution parameterized by the noise-rate. Then each instance in the batch is regarded as either correct or noisy one according to its label confidence derived from previous training step, as well as the noise distribution in this sampled batch. Experiments show that HGL can effectively denoise the weakly-labeled data retrieved from distant supervision, and therefore results in significant improvements on the trained models.Comment: Accepted to AAAI202

Volumetric Lattice Boltzmann Method for Wall Stresses of Image-Based Pulsatile Flows

Image-based computational fluid dynamics (CFD) has become a new capability for determining wall stresses of pulsatile flows. However, a computational platform that directly connects image information to pulsatile wall stresses is lacking. Prevailing methods rely on manual crafting of a hodgepodge of multidisciplinary software packages, which is usually laborious and error-prone. We present a new computational platform, to compute wall stresses in image-based pulsatile flows using the volumetric lattice Boltzmann method (VLBM). The novelty includes: (1) a unique image processing to extract flow domain and local wall normality, (2) a seamless connection between image extraction and VLBM, (3) an en-route calculation of strain-rate tensor, and (4) GPU acceleration (not included here). We first generalize the streaming operation in the VLBM and then conduct application studies to demonstrate its reliability and applicability. A benchmark study is for laminar and turbulent pulsatile flows in an image-based pipe (Reynolds number: 10 to 5000). The computed pulsatile velocity and shear stress are in good agreements with Womersley\u27s analytical solutions for laminar pulsatile flows and concurrent laboratory measurements for turbulent pulsatile flows. An application study is to quantify the pulsatile hemodynamics in image-based human vertebral and carotid arteries including velocity vector, pressure, and wall-shear stress. The computed velocity vector fields are in reasonably well agreement with MRA (magnetic resonance angiography) measured ones. This computational platform is good for image-based CFD with medical applications and pore-scale porous media flows in various natural and engineering systems

Correlative light and electron microscopy using cathodoluminescence from nanoparticles with distinguishable colours

Correlative light and electron microscopy promises to combine molecular specificity with nanoscale imaging resolution. However, there are substantial technical challenges including reliable co-registration of optical and electron images, and rapid optical signal degradation under electron beam irradiation. Here, we introduce a new approach to solve these problems: imaging of stable optical cathodoluminescence emitted in a scanning electron microscope by nanoparticles with controllable surface chemistry. We demonstrate well-correlated cathodoluminescence and secondary electron images using three species of semiconductor nanoparticles that contain defects providing stable, spectrally-distinguishable cathodoluminescence. We also demonstrate reliable surface functionalization of the particles. The results pave the way for the use of such nanoparticles for targeted labeling of surfaces to provide nanoscale mapping of molecular composition, indicated by cathodoluminescence colour, simultaneously acquired with structural electron images in a single instrument.Physic

N-myristoylation of Antimicrobial Peptide CM4 Enhances Its Anticancer Activity by Interacting With Cell Membrane and Targeting Mitochondria in Breast Cancer Cells

Development of antimicrobial peptides (AMPs) as highly effective and selective anticancer agents would represent great progress in cancer treatment. Here we show that myristoyl-CM4, a new synthetic analog generated by N-myristoylation of AMPs CM4, had anticancer activity against MCF-7, MDA-MB-231, MX-1 breast cancer cells (IC50 of 3–6 μM) and MDA-MB-231 xenograft tumors. The improved activity was attributed to the effect of myristoyl on the cell membrane. Flow cytometry and confocal laser scanning microscopy results showed that N-myristoylation significantly increased the membrane affinity toward breast cancer cells and also effectively mediated cellular entry. Despite increasing cytotoxicity against HEK293 and NIH3T3 cells and erythrocytes associated with its anticancer activity, myristoyl-CM4 maintained a certain selectivity toward breast cancer cells. Accordingly, the membrane affinity toward breast cancer cells was two to threefold higher than that of normal cells. Glycosylation analysis showed that sialic acid-containing oligosaccharides (including O-mucin and gangliosides) were important targets for myristoyl-CM4 binding to breast cancer cells. After internalization, co-localization analysis revealed that myristoyl-CM4 targeted mitochondria and induced mitochondrial dysfunction, including alterations in mitochondrial transmembrane potential, reactive oxygen species (ROS) generation and cytochrome c release. Activation of caspase 9, caspase 3 and cleavage of PARP were observed in MX-1, MCF-7, and MDA-MB-231 cells after myristoyl-CM4 treatment. The current work indicates that increasing hydrophobicity by myristoylation to modulate peptide-membrane interactions and then target mitochondria is a good strategy to develop AMPs as anticancer agents in the future

Microbe-seq : high-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

We present Microbe-seq , a high-throughput single-microbe method that yields strain-resolved genomes from complex microbial communities. We encapsulate individual microbes into droplets with microfluidics and liberate their DNA, which we amplify, tag with droplet-specific barcodes, and sequence. We use Microbe-seq to explore the human gut microbiome; we collect stool samples from a single individual, sequence over 20,000 microbes, and reconstruct nearly-complete genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe genomic signatures of microbial interactions: we reconstruct the horizontal gene transfer (HGT) network within the individual and observe far greater exchange within the same bacterial phylum than between different phyla. We probe bacteria-virus interactions; unexpectedly, we identify a significant in vivo association between crAssphage, an abundant bacteriophage, and a single strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution

Nickel pyrithione induces apoptosis in chronic myeloid leukemia cells resistant to imatinib via both Bcr/Abl-dependent and Bcr/Abl-independent mechanisms

Abstract Background Acquired imatinib (IM) resistance is frequently characterized by Bcr-Abl mutations that affect IM binding and kinase inhibition in patients with chronic myelogenous leukemia (CML). Bcr-Abl-T315I mutation is the predominant mechanism of the acquired resistance to IM. Therefore, it is urgent to search for additional approaches and targeting strategies to overcome IM resistance. We recently reported that nickel pyrithione (NiPT) potently inhibits the ubiquitin proteasome system via targeting the 19S proteasome-associated deubiquitinases (UCHL5 and USP14), without effecting on the 20S proteasome. In this present study, we investigated the effect of NiPT, a novel proteasomal deubiquitinase inhibitor, on cell survival or apoptosis in CML cells bearing Bcr-Abl-T315I or wild-type Bcr-Abl. Methods Cell viability was examined by MTS assay and trypan blue exclusion staining assay in KBM5, KBM5R, K562, BaF3-p210-WT, BaF3-p210-T315I cells, and CML patients’ bone marrow samples treated with NiPT. Cell apoptosis in CML cells was detected with Annexin V-FITC/PI and rhodamine-123 staining followed by fluorescence microscopy and flow cytometry and with western blot analyses for apoptosis-associated proteins. Expression levels of Bcr-Abl in CML cells were analyzed by using western blotting and real-time PCR. The 20S proteasome peptidase activity was measured using specific fluorogenic substrate. Active-site-directed labeling of proteasomal DUBs, as well as the phosphorylation of USP14 was used for evaluating the inhibition of the DUBs activity by NiPT. Mouse xenograft models of KBM5 and KBM5R cells were analyzed, and Bcr-Abl-related proteins and protein biomarkers related to proliferation, differentiation, and adhesion in tumor tissues were detected by western blots and/or immunohistological analyses. Results NiPT induced apoptosis in CML cells and inhibited the growth of IM-resistant Bcr-Abl-T315I xenografts in nude mice. Mechanistically, NiPT induced decreases in Bcr-Abl proteins, which were associated with downregulation of Bcr-Abl transcription and with the cleavage of Bcr-Abl protein by activated caspases. NiPT-induced ubiquitin proteasome system inhibition induced caspase activation in both IM-resistant and IM-sensitive CML cells, and the caspase activation was required for NiPT-induced Bcr-Abl downregulation and apoptotic cell death. Conclusions These findings support that NiPT can overcome IM resistance through both Bcr-Abl-dependent and Bcr-Abl-independent mechanisms, providing potentially a new option for CML treatment

Inlet and Outlet Boundary Conditions and Uncertainty Quantification in Volumetric Lattice Boltzmann Method for Image-Based Computational Hemodynamics

Inlet and outlet boundary conditions (BCs) play an important role in newly emerged image-based computational hemodynamics for blood flows in human arteries anatomically extracted from medical images. We developed physiological inlet and outlet BCs based on patients’ medical data and integrated them into the volumetric lattice Boltzmann method. The inlet BC is a pulsatile paraboloidal velocity profile, which fits the real arterial shape, constructed from the Doppler velocity waveform. The BC of each outlet is a pulsatile pressure calculated from the three-element Windkessel model, in which three physiological parameters are tuned by the corresponding Doppler velocity waveform. Both velocity and pressure BCs are introduced into the lattice Boltzmann equations through Guo’s non-equilibrium extrapolation scheme. Meanwhile, we performed uncertainty quantification for the impact of uncertainties on the computation results. An application study was conducted for six human aortorenal arterial systems. The computed pressure waveforms have good agreement with the medical measurement data. A systematic uncertainty quantification analysis demonstrates the reliability of the computed pressure with associated uncertainties in the Windkessel model. With the developed physiological BCs, the image-based computation hemodynamics is expected to provide a computation potential for the noninvasive evaluation of hemodynamic abnormalities in diseased human vessels

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics

The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells

In vitro and in vivo antiviral activity of monolaurin against Seneca Valley virus

IntroductionSurveillance of the Seneca Valley virus (SVV) shows a disproportionately higher incidence on Chinese pig farms. Currently, there are no vaccines or drugs to treat SVV infection effectively and effective treatment options are urgently needed.MethodsIn this study, we evaluated the antiviral activity of the following medium-chain fatty acids (MCFAs) or triglycerides (MCTs) against SVV: caprylic acid, caprylic monoglyceride, capric monoglyceride, and monolaurin.ResultsIn vitro experiments showed that monolaurin inhibited viral replication by up to 80%, while in vivo studies showed that monolaurin reduced clinical manifestations, viral load, and organ damage in SVV-infected piglets. Monolaurin significantly reduced the release of inflammatory cytokines and promoted the release of interferon-γ, which enhanced the viral clearance activity of this type of MCFA.DiscussionTherefore, monolaurin is a potentially effective candidate for the treatment of SVV infection in pigs

CCN1, a Pro-Inflammatory Factor, Aggravates Psoriasis Skin Lesions by Promoting Keratinocyte Activation

Psoriasis is a common chronic skin disease characterized by epidermal hyperplasia and inflammation. The pathogenesis of psoriasis is multifactorial and is not fully understood. Here we demonstrate that CCN1 (also called Cyr61, which is short for cysteine-rich 61), an extracellular matrix protein that is also considered a pro-inflammatory factor, is highly expressed in the lesional skin of psoriasis patients, as well as in that of imiquimod (IMQ)- and IL-23-treated psoriasis-like mice. Then we show that blocking CCN1 function in vivo attenuates epidermal hyperplasia and inflammation in psoriasis-like mice. Further, in primary cultured normal human keratinocytes and HaCaT (human keratinocyte cell line) cells, CCN1 promotes keratinocyte activation, including the proliferation and expression of immune-related molecules. Finally, we observe that integrin α6β1 is the receptor of CCN1 in keratinocytes, and CCN1 stimulation activates the downstream phosphoinositide-3 kinase/Akt/NF-κB signaling pathway. Taken together, our findings reveal that CCN1 has a critical role in psoriasis pathogenesis. Moreover, as CCN1 is a secreted extracellular matrix (ECM) protein, our study also provides evidence that ECM, which is involved in psoriatic pathogenesis, could be a potent target for psoriasis treatment