Distributed Representations of Signed Networks

Recent successes in word embedding and document embedding have motivated researchers to explore similar representations for networks and to use such representations for tasks such as edge prediction, node label prediction, and community detection. Such network embedding methods are largely focused on finding distributed representations for unsigned networks and are unable to discover embeddings that respect polarities inherent in edges. We propose SIGNet, a fast scalable embedding method suitable for signed networks. Our proposed objective function aims to carefully model the social structure implicit in signed networks by reinforcing the principles of social balance theory. Our method builds upon the traditional word2vec family of embedding approaches and adds a new targeted node sampling strategy to maintain structural balance in higher-order neighborhoods. We demonstrate the superiority of SIGNet over state-of-the-art methods proposed for both signed and unsigned networks on several real world datasets from different domains. In particular, SIGNet offers an approach to generate a richer vocabulary of features of signed networks to support representation and reasoning.Comment: Published in PAKDD 201

Service triads:a research agenda for buyer–supplier–customer triads in business services

Service triads, in which a buyer contracts with a supplier to deliver services directly to the buyer's customer, represent an emerging business model. This special issue is dedicated to this theme. To set the context, in this lead article, we first define service triads, both as a phenomenon and a research topic. We then provide a review of different strands of existing research and various theoretical frameworks that can inform our study of service triads. This culminates in an outline of a research agenda that can guide future study. As such, this paper not only introduces the articles in the special issue, but is also intended as a point of reference and motivation for further work on service triads, and on triads in general

Fragmentation patterns and personalized sequencing of cell-free DNA in urine and plasma of glioma patients.

Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy because quantities in body fluids are low. We determined the glioma-derived DNA fraction in cerebrospinal fluid (CSF), plasma, and urine samples from patients using sequencing of personalized capture panels guided by analysis of matched tumor biopsies. By sequencing cfDNA across thousands of mutations, identified individually in each patient's tumor, we detected tumor-derived DNA in the majority of CSF (7/8), plasma (10/12), and urine samples (10/16), with a median tumor fraction of 6.4 × 10-3 , 3.1 × 10-5 , and 4.7 × 10-5 , respectively. We identified a shift in the size distribution of tumor-derived cfDNA fragments in these body fluids. We further analyzed cfDNA fragment sizes using whole-genome sequencing, in urine samples from 35 glioma patients, 27 individuals with non-malignant brain disorders, and 26 healthy individuals. cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (P = 1.7 × 10-2 ) and healthy individuals (P = 5.2 × 10-9 ). Machine learning models integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80-0.91) suggesting possibilities for truly non-invasive cancer detection

Identification of genes specifically required for the anaerobic metabolism of benzene in Geobacter metallireducens

Although the biochemical pathways for the anaerobic degradation of many of the hydrocarbon constituents in petroleum reservoirs have been elucidated, the mechanisms for anaerobic activation of benzene, a very stable molecule, are not known. Previous studies have demonstrated that Geobacter metallireducens can anaerobically oxidize benzene to carbon dioxide with Fe(III) as the sole electron acceptor and that phenol is an intermediate in benzene oxidation. In an attempt to identify enzymes that might be involved in the conversion of benzene to phenol, whole-genome gene transcript abundance was compared in cells metabolizing benzene and cells metabolizing phenol. Eleven genes had significantly higher transcript abundance in benzene-metabolizing cells. Five of these genes had annotations suggesting that they did not encode proteins that could be involved in benzene metabolism and were not further studied. Strains were constructed in which one of the remaining six genes was deleted. The strain in which the monocistronic gene Gmet 0232 was deleted metabolized phenol, but not benzene. Transcript abundance of the adjacent monocistronic gene, Gmet 0231, predicted to encode a zinc-containing oxidoreductase, was elevated in cells metabolizing benzene, although not at a statistically significant level. However, deleting Gmet 0231 also yielded a strain that could metabolize phenol, but not benzene. Although homologs of Gmet 0231 and Gmet 0232 are found in microorganisms not known to anaerobically metabolize benzene, the adjacent localization of these genes is unique to G. metallireducens. The discovery of genes that are specifically required for the metabolism of benzene, but not phenol in G. metallireducens is an important step in potentially identifying the mechanisms for anaerobic benzene activation

Loss of Ep-CAM (CO17-1A) expression predicts survival in patients with gastric cancer

Preoperative staging of gastric cancer is difficult and not optimal. The TNM stage is an important prognostic factor, but it can only be assessed reliably after surgery. Therefore, there is need for additional, reliable prognostic factors that can be determined preoperatively in order to select patients who might benefit from (neo) adjuvant treatment. Expression of immunohistochemical markers was demonstrated to be associated with tumour progression and metastasis. The expression of p53, CD44 (splice variants v5, v6 and v9), E-cadherin, Ep-CAM (CO17-1A antigen) and c-erB2/neu were investigated in tumour tissues of 300 patients from the Dutch Gastric Cancer Trial, investigating the value of extended lymphadenectomy compared to that of limited lymphadenectomy). The expression of tumour markers was analysed with respect to patient survival. Patients without loss of Ep-CAM-expression of tumour cells (19%) had a significantly better 10-year survival (P<0.0001) compared to patients with any loss: 42% (s.e.=7%) vs 22% (s.e.=3%). Patients with CD44v6 (VFF18) expression in more than 25% of the tumour cells (69% of the patients) also had a significantly better survival (P=0.01) compared to patients with expression in less than 25% of the tumour cells: 10 year survival rate of 29% (s.e.=3%) vs 19% (s.e.=4%). The prognostic value of both markers was stronger in stages I and II, and independent of the TNM stage. Ep-CAM and CD44v6-expression provides prognostic information additional to the TNM stage. Loss of Ep-CAM-expression identifies aggressive tumours especially in patients with stage I and II disease. This information may be helpful in selecting patients suitable for surgery or for additional treatment pre- or postoperatively

Effects of gain—loss frames on satisfaction with self–other outcome-differences

This research concerned satisfaction with outcome-differences (advantageous inequity, equity, or disadvantageous inequity) as a function of the individual's gain or loss frame, other's gain or loss frame, the cooperative or noncooperative nature of the relationship, and their interactions. After reading a scenario, subjects rated on a satisfaction-dissatisfaction soak a series of outcome-pairs providing themselves and another party with outcomes. Consistent with Equity Theory, results showed that gain framed individuals found equity more pleasing than advantageous inequity, which in turn was preferred over disadvantageous inequity, but only when the decision making context was cooperative rather than noncooperative. In a noncooperative context, gain framed individuals were as pleased with equity as with advantageous inequity. Contrary to Equity Theory, but consistent with Prospect Theory, loss framed individuals were relatively insensitive to outcome-differences and the nature of the relationship. Results finally suggested that advantageous inequity was preferred less when the other party had a loss rather than gain frame, albeit only under cooperative circumstances

Enhanced detection of circulating tumor DNA by fragment size analysis.

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and the EPSRC (CRUK grant numbers A11906 (NR), A20240 (NR), A22905 (JDB), A15601 (JDB), A25177 (CRUK Cancer Centre Cambridge), A17242 (KMB), A16465 (CRUK-EPSRC Imaging Centre in Cambridge and Manchester)). The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 337905. The research was supported by the National Institute for Health Research Cambridge, National Cancer Research Network, Cambridge Experimental Cancer Medicine Centre and Hutchison Whampoa Limited. This research is also supported by Target Ovarian Cancer and the Medical Research Council through their Joint Clinical Research Training Fellowship for Dr Moore. The CALIBRATE study was supported by funding from AstraZeneca