Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications

This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are further used to adjust the similarity matrix for constrained spectral clustering. Other than the traditional constraint propagation on single-source data, our approach is also extended to more challenging constraint propagation on multi-source data where each pairwise constraint is defined over a pair of data points from different sources. This multi-source constraint propagation has an important application to cross-modal multimedia retrieval. Extensive results have shown the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201

The inhibition of FGF receptor 1 activity mediates sorafenib-induced antiproliferative effects in human mesothelioma tumor-initiating cells

Tumor-initiating cells (TICs), the subset of cells within tumors endowed with stem-like features, being highly resistant to conventional cytotoxic drugs, are the major cause of tumor relapse. The identification of molecules able to target TICs remains a significant challenge in cancer therapy. Using TIC-enriched cultures (MM1, MM3 and MM4), from 3 human malignant pleural mesotheliomas (MPM), we tested the effects of sorafenib on cell survival and the intracellular mechanisms involved. Sorafenib inhibited cell-cycle progression in all the TIC cultures, but only in MM3 and MM4 cells this effect was associated with induction of apoptosis via the down-regulation of Mcl-1. Although sorafenib inhibits the activity of several tyrosine kinases, its effects are mainly ascribed to Raf inhibition. To investigate the mechanisms of sorafenib-mediated antiproliferative activity, TICs were treated with EGF or bFGF causing, in MM3 and MM4 cells, MEK, ERK1/2, Akt and STAT3 phosphorylation. These effects were significantly reduced by sorafenib in bFGF-treated cells, while a slight inhibition occurred after EGF stimulation, suggesting that sorafenib effects are mainly due to FGFR inhibition. Indeed, FGFR1 phosphorylation was inhibited by sorafenib. A different picture was observed in MM1 cells, which, releasing high levels of bFGF, showed an autocrine activation of FGFR1 and a constitutive phosphorylation/activation of MEK-ERK1/2. A powerful inhibitory response to sorafenib was observed in these cells, indirectly confirming the central role of sorafenib as FGFR inhibitor. These results suggest that bFGF signaling may impact antiproliferative response to sorafenib of MPM TICs, which is mainly mediated by a direct FGFR targeting

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Detect, Retrieve, Comprehend: A Flexible Framework for Zero-Shot Document-Level Question Answering

Researchers produce thousands of scholarly documents containing valuable technical knowledge. The community faces the laborious task of reading these documents to identify, extract, and synthesize information. To automate information gathering, document-level question answering (QA) offers a flexible framework where human-posed questions can be adapted to extract diverse knowledge. Finetuning QA systems requires access to labeled data (tuples of context, question and answer). However, data curation for document QA is uniquely challenging because the context (i.e. answer evidence passage) needs to be retrieved from potentially long, ill-formatted documents. Existing QA datasets sidestep this challenge by providing short, well-defined contexts that are unrealistic in real-world applications. We present a three-stage document QA approach: (1) text extraction from PDF; (2) evidence retrieval from extracted texts to form well-posed contexts; (3) QA to extract knowledge from contexts to return high-quality answers -- extractive, abstractive, or Boolean. Using QASPER for evaluation, our detect-retrieve-comprehend (DRC) system achieves a +7.19 improvement in Answer-F1 over existing baselines while delivering superior context selection. Our results demonstrate that DRC holds tremendous promise as a flexible framework for practical scientific document QA

Murine mesothelin: characterization, expression, and inhibition of tumor growth in a murine model of pancreatic cancer

Background Mesothelin has attracted much interest as a tumor specific antigen; it has been reported to promote tumor development and to be a good target for cancer treatment. Most studies to date have used human mesothelin in immunocompromised mice. Since these models do not allow for study of the natural immune response to mesothelin expressing tumors, we have undertaken the characterization of mouse mesothelin so the effects of this protein can be assessed in immunocompetent mouse strains. Methods We analyzed mouse mesothelin expression, tissue distribution, shedding and biochemistry. In addition we constructed stable mesothelin overexpressing lines of the pancreatic cancer line Panc02 by two methods and tested them for growth and tumorigencity in vitro and in vivo. Results We show here that mouse mesothelin is similar to human mesothelin in biochemical characteristics, tumor expression and tissue distribution, suggesting the mouse may be a suitable model for study of mesothelin. Stable overexpression of mesothelin in a pancreatic cancer cell line did not increase cell proliferation or anchorage-independent growth in vitro, suggesting that mesothelin is not necessarily a tumor progression factor. Surprisingly overexpression of mesothelin inhibited tumor formation in vivo in immunocompetent mice. Conclusion The mouse may be a good model for studying mesothelin in the context of an intact immune response. Mesothelin is not necessarily a tumor progression factor, and indeed mesothelin overexpression inhibited tumor growth in immunocompetent mice

Characterization of human mesothelin transcripts in ovarian and pancreatic cancer

BACKGROUND: Mesothelin is an attractive target for cancer immunotherapy due to its restricted expression in normal tissues and high level expression in several tumor types including ovarian and pancreatic adenocarcinomas. Three mesothelin transcript variants have been reported, but their relative expression in normal tissues and tumors has been poorly characterized. The goal of the present study was to clarify which mesothelin transcript variants are commonly expressed in human tumors. METHODS: Human genomic and EST nucleotide sequences in the public databases were used to evaluate sequences reported for the three mesothelin transcript variants in silico. Subsequently, RNA samples from normal ovary, ovarian and pancreatic carcinoma cell lines, and primary ovarian tumors were analyzed by reverse transcription-polymerase chain reaction (RT-PCR) and nucleotide sequencing to directly identify expressed transcripts. RESULTS: In silico comparisons of genomic DNA sequences with available EST sequences supported expression of mesothelin transcript variants 1 and 3, but there were no sequence matches for transcript variant 2. Newly-derived nucleotide sequences of RT-PCR products from tissues and cell lines corresponded to mesothelin transcript variant 1. Mesothelin transcript variant 2 was not detected. Transcript variant 3 was observed as a small percentage of total mesothelin amplification products from all studied cell lines and tissues. Fractionation of nuclear and cytoplasmic RNA indicated that variant 3 was present primarily in the nuclear fraction. Thus, mesothelin transcript variant 3 may represent incompletely processed hnRNA. CONCLUSION: Mesothelin transcript variant 1 represents the predominant mature mRNA species expressed by both normal and tumor cells. This conclusion should be important for future development of cancer immunotherapies, diagnostic tests, and gene microarray studies targeting mesothelin

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

The potential role of podoplanin in tumour invasion

Podoplanin is a small mucin-like transmembrane protein, widely expressed in various specialised cell types throughout the body. Here, we revisit the mechanism of podoplanin-mediated tumour invasion. We compare molecular pathways leading to single and collective cell invasion and discuss novel distinct concepts of tumour cell invasion

Pleomorphic adenoma of the vulva, clinical reminder of a rare occurrence

Pleomorphic adenoma, also known as mixed tumor, is a benign tumor which typically presents as a painless and persistent mass. The majority of pleomorphic adenomas involve the salivary glands, most commonly the parotid gland. Other sites include breast and skin. It is a rare tumor in the vulva. In this article we are reporting a case of pleomorphic adenoma of labia with characteristic pathologic and clinical findings, as reminder of a common benign neoplasm occurring with rare locality