Information Extraction in Illicit Domains

Extracting useful entities and attribute values from illicit domains such as human trafficking is a challenging problem with the potential for widespread social impact. Such domains employ atypical language models, have `long tails' and suffer from the problem of concept drift. In this paper, we propose a lightweight, feature-agnostic Information Extraction (IE) paradigm specifically designed for such domains. Our approach uses raw, unlabeled text from an initial corpus, and a few (12-120) seed annotations per domain-specific attribute, to learn robust IE models for unobserved pages and websites. Empirically, we demonstrate that our approach can outperform feature-centric Conditional Random Field baselines by over 18\% F-Measure on five annotated sets of real-world human trafficking datasets in both low-supervision and high-supervision settings. We also show that our approach is demonstrably robust to concept drift, and can be efficiently bootstrapped even in a serial computing environment.Comment: 10 pages, ACM WWW 201

Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Directing cellular responses in a nanocomposite 3D matrix for tissue regeneration with nanoparticle-mediated drug delivery

Hydrogels play an important role in tissue engineering due to their native extracellular matrix-like characteristics, but they are insufficient in providing the necessary stimuli to support tissue formation. Efforts to integrate bioactive cues directly into hydrogels are hindered by incompatibility with hydrophobic drugs, issues of burst/uncontrolled release, and rapid degradation of the bioactive molecules. Skeletal muscle tissue repair requires internal stimuli and communication between cells for regeneration, and nanocomposite systems offer to improve the therapeutic effects in tissue regeneration. Here, the versatility of mesoporous silica nanoparticles (MSN) was leveraged to formulate a nanoparticle-hydrogel composite and to combine the benefits of controlled delivery of bioactive cues and cellular support. The tunable surface characteristics of MSNs were exploited to optimize homogeneity and intracellular drug delivery in a 3D matrix. Nanocomposite hydrogels formulated with acetylated or succinylated MSNs achieved high homogeneity in 3D distribution, with succinylated MSNs being rapidly internalized and acetylated MSNs exhibiting slower cellular uptake. MSN-hydrogel nanocomposites simultaneously allowed efficient local intracellular delivery of a hydrophobic model drug. To further study the efficiency of directing cell response, a Notch signaling inhibitor (DAPT) was incorporated into succinylated MSNs and incorporated into the hydrogel. MSN-hydrogel nanocomposites effectively downregulated the Notch signaling target genes, and accelerated and maintained the expression of myogenic markers. The current findings demonstrate a proof-of-concept in effective surface engineering strategies for MSN-based nanocomposites, suited for hydrophobic drug delivery in tissue regeneration with guided cues.</p

Directing cellular responses in a nanocomposite 3D matrix for tissue regeneration with nanoparticle-mediated drug delivery

Hydrogels play an important role in tissue engineering due to their native extracellular matrix-like characteristics, but they are insufficient in providing the necessary stimuli to support tissue formation. Efforts to integrate bioactive cues directly into hydrogels are hindered by incompatibility with hydrophobic drugs, issues of burst/uncontrolled release, and rapid degradation of the bioactive molecules. Skeletal muscle tissue repair requires internal stimuli and communication between cells for regeneration, and nanocomposite systems offer to improve the therapeutic effects in tissue regeneration. Here, the versatility of mesoporous silica nanoparticles (MSN) was leveraged to formulate a nanoparticle-hydrogel composite and to combine the benefits of controlled delivery of bioactive cues and cellular support. The tunable surface characteristics of MSNs were exploited to optimize homogeneity and intracellular drug delivery in a 3D matrix. Nanocomposite hydrogels formulated with acetylated or succinylated MSNs achieved high homogeneity in 3D distribution, with succinylated MSNs being rapidly internalized and acetylated MSNs exhibiting slower cellular uptake. MSN-hydrogel nanocomposites simultaneously allowed efficient local intracellular delivery of a hydrophobic model drug. To further study the efficiency of directing cell response, a Notch signaling inhibitor (DAPT) was incorporated into succinylated MSNs and incorporated into the hydrogel. MSN-hydrogel nanocomposites effectively downregulated the Notch signaling target genes, and accelerated and maintained the expression of myogenic markers. The current findings demonstrate a proof-of-concept in effective surface engineering strategies for MSN-based nanocomposites, suited for hydrophobic drug delivery in tissue regeneration with guided cues.</p

An in vitro model of cancer invasion with heterogeneous ECM created with droplet microfluidics

Metastasis is a multi-step process that is critically affected by cues from the tumor micro-environment (TME), such as from the extracellular matrix (ECM). The role of the ECM in the onset of metastasis, invasion, is not yet fully understood. A further complicating factor is that the ECM in the TME is mostly heterogeneous, in particular presenting a basement membrane (BM) directly enveloping the tumor, which acts as a barrier to invasion into the surrounding stromal ECM. To systematically investigate the role of ECM in invasion, appropriate in vitro models with control over such ECM heterogeneity are essential. We present a novel high-throughput microfluidic approach to build such a model, which enables to capture the invasion of cancer cells from the tumor, through the BM and into the stromal tissue. We used a droplet-maker device to encapsulate cells in beads of a primary hydrogel mimicking BM, Matrigel, which were then embedded in a secondary hydrogel mimicking stromal ECM, collagen I. Our technology ultimately provides control over parameters such as tissue size, cell count and type, and ECM composition and stiffness. As a proof-of-principle, we carried out a comparative study with two breast cancer cell types, and we observed typical behavior consistent with previous studies. Highly invasive MDA-MB-231 cells showed single cell invasion behavior, whereas poorly invasive MCF-7 cells physically penetrated the surrounding matrix collectively. A comparative analysis conducted between our heterogeneous model and previous models employing a single type of hydrogel, either collagen I or Matrigel, has unveiled a substantial difference in terms of cancer cell invasion distance. Our in vitro model resembles an in vivo heterogeneous cancer microenvironment and can potentially be used for high throughput studies of cancer invasion.</p

Ex Vivo Models to Decipher the Molecular Mechanisms of Genetic Notch Cardiovascular Disorders

Impact statementIn this review, a comprehensive overview of the limitations of current in vivo models of genetic Notch cardiovascular diseases is provided, followed by a discussion over the potential of microphysiological systems and computational models in overcoming these limitations and in potentiating drug testing and modeling of these pathologies.Notch is an evolutionary, conserved, cell-cell signaling pathway that is central to several biological processes, from tissue morphogenesis to homeostasis. It is therefore not surprising that several genetic mutations of Notch components cause inherited human diseases, especially cardiovascular disorders. Despite numerous efforts, current in vivo models are still insufficient to unravel the underlying mechanisms of these pathologies, hindering the development of utmost needed medical therapies. In this perspective review, we discuss the limitations of current murine models and outline how the combination of microphysiological systems (MPSs) and targeted computational models can lead to breakthroughs in this field. In particular, while MPSs enable the experimentation on human cells in controlled and physiological environments, in silico models can provide a versatile tool to translate the in vitro findings to the more complex in vivo setting. As a showcase example, we focus on Notch-related cardiovascular diseases, such as Alagille syndrome, Adams-Oliver syndrome, and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL)

Notch in mechanotransduction - from molecular mechanosensitivity to tissue mechanostasis

Tissue development and homeostasis are controlled by mechanical cues. Perturbation of the mechanical equilibrium triggers restoration of mechanostasis through changes in cell behavior, while defects in these restorative mechanisms lead to mechanopathologies, for example, osteoporosis, myopathies, fibrosis or cardiovascular disease. Therefore, sensing mechanical cues and integrating them with the biomolecular cell fate machinery is essential for the maintenance of health. The Notch signaling pathway regulates cell and tissue fate in nearly all tissues. Notch activation is directly and indirectly mechanosensitive, and regulation of Notch signaling, and consequently cell fate, is integral to the cellular response to mechanical cues. Fully understanding the dynamic relationship between molecular signaling, tissue mechanics and tissue remodeling is challenging. To address this challenge, engineered microtissues and computational models play an increasingly large role. In this Review, we propose that Notch takes on the role of a 'mechanostat', maintaining the mechanical equilibrium of tissues. We discuss the reciprocal role of Notch in the regulation of tissue mechanics, with an emphasis on cardiovascular tissues, and the potential of computational and engineering approaches to unravel the complex dynamic relationship between mechanics and signaling in the maintenance of cell and tissue mechanostasis

Cell Volume (3D) Correlative Microscopy Facilitated by Intracellular Fluorescent Nanodiamonds as Multi-Modal Probes

Three-dimensional correlative light and electron microscopy (3D CLEM) is attaining popularity as a potential technique to explore the functional aspects of a cell together with high-resolution ultrastructural details across the cell volume. To perform such a 3D CLEM experiment, there is an imperative requirement for multi-modal probes that are both fluorescent and electron-dense. These multi-modal probes will serve as landmarks in matching up the large full cell volume datasets acquired by different imaging modalities. Fluorescent nanodiamonds (FNDs) are a unique nanosized, fluorescent, and electron-dense material from the nanocarbon family. We hereby propose a novel and straightforward method for executing 3D CLEM using FNDs as multi-modal landmarks. We demonstrate that FND is biocompatible and is easily identified both in living cell fluorescence imaging and in serial block-face scanning electron microscopy (SB-EM). We illustrate the method by registering multi-modal datasets.Peer reviewe

MDA-MB-231 Breast Cancer Cells and Their CSC Population Migrate Towards Low Oxygen in a Microfluidic Gradient Device

Most cancer deaths are caused by secondary tumors formed through metastasis, yet due to our limited understanding of this process, prevention remains a major challenge. Recently, cancer stem cells (CSCs) have been proposed as the source of metastases, but only little is known about their migratory behavior. Oxygen gradients in the tumor have been linked to directional migration of breast cancer cells. Here, we present a method to study the effect of oxygen gradients on the migratory behavior of breast CSCs using a microfluidic device. Our chip contains a chamber in which an oxygen gradient can be generated between hypoxic (<1%) and ambient (21%) conditions. We tracked the migration of CSCs obtained from MDA-MB-231 breast cancer cells, and found that their migration patterns do not differ from the average MDA-MB-231 population. Surprisingly, we found that the cells migrate towards low oxygen levels, in contrast with an earlier study. We hypothesize that in our device, migration is exclusively due to the pure oxygen gradient, whereas the effects of oxygen in earlier work were obscured by additional cues from the tumor microenvironment (e.g., nutrients and metabolites). These results open new research directions into the role of oxygen in directing cancer and CSC migration

A multiscale computational model of arterial growth and remodeling including Notch signaling

Blood vessels grow and remodel in response to mechanical stimuli. Many computational models capture this process phenomenologically, by assuming stress homeostasis, but this approach cannot unravel the underlying cellular mechanisms. Mechano-sensitive Notch signaling is well-known to be key in vascular development and homeostasis. Here, we present a multiscale framework coupling a constrained mixture model, capturing the mechanics and turnover of arterial constituents, to a cell-cell signaling model, describing Notch signaling dynamics among vascular smooth muscle cells (SMCs) as influenced by mechanical stimuli. Tissue turnover was regulated by both Notch activity, informed by in vitro data, and a phenomenological contribution, accounting for mechanisms other than Notch. This novel framework predicted changes in wall thickness and arterial composition in response to hypertension similar to previous in vivo data. The simulations suggested that Notch contributes to arterial growth in hypertension mainly by promoting SMC proliferation, while other mechanisms are needed to fully capture remodeling. The results also indicated that interventions to Notch, such as external Jagged ligands, can alter both the geometry and composition of hypertensive vessels, especially in the short term. Overall, our model enables a deeper analysis of the role of Notch and Notch interventions in arterial growth and remodeling and could be adopted to investigate therapeutic strategies and optimize vascular regeneration protocols.</p