The claudin family of proteins in human malignancy: A clinical perspective

Tight junctions, or zonula occludens, are the most apical component of the junctional complex and provide one form of cell–cell adhesion in epithelial and endothelial cells. Nearly 90% of malignant tumors are derived from the epithelium. Loss of cell–cell adhesion is one of the steps in the progression of cancer to metastasis. At least three main tight junction family proteins have been discovered: occludin, claudin, and junctional adhesion molecule (JAM). Claudins are the most important structural and functional components of tight junction integral membrane proteins, with at least 24 members in mammals. They are crucial for the paracellular flux of ions and small molecules. Overexpression or downregulation of claudins is frequently observed in epithelial-derived cancers. However, molecular mechanisms by which claudins affect tumorigenesis remain largely unknown. As the pivotal proteins in epithelial cells, altered expression and distribution of different claudins have been reported in a wide variety of human malignancies, including pancreatic, colonic, lung, ovarian, thyroid, prostate, esophageal, and breast cancers. In this review, we will give the readers an overall picture of the changes in claudin expression observed in various cancers and their mechanisms of regulation. Downregulation of claudins contributes to epithelial transformation by increasing the paracellular permeability of nutrients and growth factors to cancerous cells. In the cases of upregulation of claudin expression, the barrier function of the cancerous epithelia changes, as they often display a disorganized arrangement of tight junction strands with increased permeability to paracellular markers. Finally, we will summarize the literature suggesting that claudins may become useful biomarkers for cancer detection and diagnosis as well as possible therapeutic targets for cancer treatment

Resolving power of diffraction imaging with an objective: a numerical study

Diffraction imaging in the far-field can detect 3D morphological features of an object for its coherent nature. We describe methods for accurate calculation and analysis of diffraction images of scatterers of single and double spheres by an imaging unit based on microscope objective at non-conjugate positions. A quantitative study of the calculated diffraction imaging in spectral domain has been performed to assess the resolving power of diffraction imaging. It has been shown numerically that with coherent illumination of 532 nm in wavelength the imaging unit can resolve single spheres of 2 μm or larger in diameters and double spheres separated by less than 300 nm between their centers.ECU Open Access Publishing Fun

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.ECU Open Access Publishing Support Fun

The prognostic impact of preoperative blood monocyte count in pathological T3N0M0 rectal cancer without neoadjuvant chemoradiotherapy

It remains controversial whether adjuvant therapy should be delivered to pathological T3N0M0 rectal cancer without neoadjuvant chemoradiotherapy. Thus identification of patients at high risk is of particular importance. Herein, we aimed to evaluate whether the absolute peripheral blood monocyte count can stratify the pathological T3N0M0M0 rectal cancer patients in survival. A total of 270 pathological T3N0M0 rectal cancer patients with total mesorectal excision-principle radical resection were included. The optimal cut-off value of preoperative monocyte count was determined by receiver operating characteristic curve analysis. Overall survival and disease-free survival between low- and high-monocyte were estimated by Kaplan–Meier method and Cox regression model. The optimal cut-off value for monocyte count was 595 mm(3). In univariate analysis, patients with monocyte counts higher than 595/mm(3) had significantly inferior 5-year overall survival (79.2 vs 94.2 %, P = 0.006) and disease-free survival (67.8 vs 86.0 %, P < 0.001). With adjustment for the known covariates, monocyte count remained to be associated with poor overall survival (HR = 2.55, 95 % CI 1.27–5.10; P = 0.008) and disease-free survival (HR = 2.63, 95 % CI 1.48–4.69; P = 0.001). Additionally, the significant association of monocyte count with disease-free survival was hardly influenced in the subgroup analysis, whereas this correlation was restricted to the males and patients with normal carcinoembryonic antigen (CEA) level (<5 μg/L), tumor grade II, and with adjuvant therapy. High preoperative monocyte count is independently predictive of worse survival of pathological T3N0M0 rectal cancer patients without neoadjuvant chemoradiotherapy. Postoperative adjuvant therapy might be considered for patients with high-monocyte count

A non-tight junction function of claudin-7—Interaction with integrin signaling in suppressing lung cancer cell proliferation and detachment

Background Claudins are a family of tight junction (TJ) membrane proteins involved in a broad spectrum of human diseases including cancer. Claudin-7 is a unique TJ membrane protein in that it has a strong basolateral membrane distribution in epithelial cells and in tissues. Therefore, this study aims to investigate the functional significance of this non-TJ localization of claudin-7 in human lung cancer cells. Methods Claudin-7 expression was suppressed or deleted by lentivirus shRNA or by targeted-gene deletion. Cell cycle analysis and antibody blocking methods were employed to assay cell proliferation and cell attachment, respectively. Electron microscopy and transepthelial electrical resistance measurement were performed to examine the TJ ultrastructure and barrier function. Co-immunolocalization and co-immunoprecipitation was used to study claudin-7 interaction with integrin β1. Tumor growth in vivo were analyzed using athymic nude mice. Results Claudin-7 co-localizes and forms a stable complex with integrin β1. Both suppressing claudin-7 expression by lentivirus shRNA in human lung cancer cells (KD cells) and deletion of claudin-7 in mouse lungs lead to the reduction in integrin β1 and phospho-FAK levels. Suppressing claudin-7 expression increases cell growth and cell cycle progression. More significantly, claudin-7 KD cells have severe defects in cell-matrix interactions and adhere poorly to culture plates with a remarkably reduced integrin β1 expression. When cultured on uncoated glass coverslips, claudin-7 KD cells grow on top of each other and form spheroids while the control cells adhere well and grow as a monolayer. Reintroducing claudin-7 reduces cell proliferation, upregulates integrin β1 expression and increases cell-matrix adhesion. Integrin β1 transfection partially rescues the cell attachment defect. When inoculated into nude mice, claudin-7 KD cells produced significantly larger tumors than control cells. Conclusion In this study, we identified a previously unrecognized function of claudin-7 in regulating cell proliferation and maintaining epithelial cell attachment through engaging integrin β1

ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads (Extended)

For efficient query processing, DBMS query optimizers have for decades relied on delicate cardinality estimation methods. In this work, we propose an Attention-based LEarned Cardinality Estimator (ALECE for short) for SPJ queries. The core idea is to discover the implicit relationships between queries and underlying dynamic data using attention mechanisms in ALECE's two modules that are built on top of carefully designed featurizations for data and queries. In particular, from all attributes in the database, the data-encoder module obtains organic and learnable aggregations which implicitly represent correlations among the attributes, whereas the query-analyzer module builds a bridge between the query featurizations and the data aggregations to predict the query's cardinality. We experimentally evaluate ALECE on multiple dynamic workloads. The results show that ALECE enables PostgreSQL's optimizer to achieve nearly optimal performance, clearly outperforming its built-in cardinality estimator and other alternatives.Comment: VLDB 202

A QoS-Based Services Selected Method in Service-Oriented Architectures Using Ant Colony System - A Case Study of Airflights

Semantic web is becoming more and more popular these days, and it’s an opportune moment to look at the field’s current state and future opportunities. However, most researchers focus on only one single service recommend from semantic web inference. In some situations, the Multi-Services which are combined many complex services from various service providers are better than single service. The designed Multi-Services Semantic Search System (MS4), which provides the cooperation web-based platform for all related mobile users and service providers, could strengthen the ability of Multi-Services suggestion. In this research, MS4 chooses the adaptable airflight as a case study. MS4 is a five-components system composed of the Mobile Users (MUs), UDDI Registries (UDDIRs), Service Providers (SPs), Semantic Web Services Server (SWSS), and Database Server (DS). Using SOA, OWL-S to build semantic web environment to inference user’s requirements and search various web services which are published in UDDI through the communication networks include internet and 3G/GPRS/GSM mobile networks. In this airline case, we propose the Adaptive Airflights Inference Module (AAIM) combined QoS-Based Services Selected Method (QBSSM) using Ant Colony System (ACS) to reference the adaptable airflights to MUs

DILI: A Distribution-Driven Learned Index

Targeting in-memory one-dimensional search keys, we propose a novel DIstribution-driven Learned Index tree (DILI), where a concise and computation-efficient linear regression model is used for each node. An internal node's key range is equally divided by its child nodes such that a key search enjoys perfect model prediction accuracy to find the relevant leaf node. A leaf node uses machine learning models to generate searchable data layout and thus accurately predicts the data record position for a key. To construct DILI, we first build a bottom-up tree with linear regression models according to global and local key distributions. Using the bottom-up tree, we build DILI in a top-down manner, individualizing the fanouts for internal nodes according to local distributions. DILI strikes a good balance between the number of leaf nodes and the height of the tree, two critical factors of key search time. Moreover, we design flexible algorithms for DILI to efficiently insert and delete keys and automatically adjust the tree structure when necessary. Extensive experimental results show that DILI outperforms the state-of-the-art alternatives on different kinds of workloads.Comment: PVLDB Volume 1