nils-herrmann/clean_scirepeval huggingface dataset:
miRpower: a web tool to validate survival associated miRNAs utilizing expression data from 2178 breast cancer patients
Venue: Breast Cancer Research and Treatment

PurposeThe proper validation of prognostic biomarkers is an important clinical issue in breast cancer research. MicroRNAs (miRNAs) have emerged as a new class of promising breast cancer biomarkers. In the present work, we developed an integrated online bioinformatic tool to validate the prognostic relevance of miRNAs in breast cancer.MethodsA database was set up by searching the GEO, EGA, TCGA, and PubMed repositories to identify datasets with published miRNA expression and clinical data. Kaplan Meier survival analysis was performed to validate the prognostic value of a set of 41 previously published survival associated miRNAs.ResultsAll together 2178 samples from four independent datasets were integrated into the system including the expression of 1052 distinct human miRNAs. In addition, the web tool allows for the selection of patients, which can be filtered by receptors status, lymph node involvement, histological grade, and treatments. The complete analysis tool can be accessed online at: www.kmplot.com/mirpower. We used this tool to analyze a large number of deregulated miRNAs associated with breast cancer features and outcome, and confirmed the prognostic value of 26 miRNAs. A significant correlation in three out of four datasets was validated only for miR 29c and miR 101.ConclusionsIn summary, we established an integrated platform capable to mine all available miRNA data to perform a survival analysis for the identification and validation of prognostic miRNA markers in breast cancer.
Triple negative breast cancer: treatment challenges and solutions
Venue: Breast cancer

Triple negative breast cancers (TNBCs) are defined by the absence of estrogen and progesterone receptors and the absence of HER2 overexpression. These cancers represent a heterogeneous breast cancer subtype with a poor prognosis. Few systemic treatment options exist besides the use of chemotherapy (CT) The heterogeneity of the disease has limited the successful development of targeted therapy in unselected patient populations. Currently, there are no approved targeted therapies for TNBC. However, intense research is ongoing to identify specific targets and develop additional and better systemic treatment options. Standard adjuvant and neoadjuvant regimens include anthracyclines, cyclophosphamide, and taxanes. Platinum based CT has been proposed as another CT option of interest in TNBC. We review the role of this therapy in general, and particularly in patients carrying BRCA germ line mutations. Available data concerning the role of platinum based CT in TNBC were acquired primarily in the neoadjuvant setting. The routine use of platinum based CT is not yet recommended by available guidelines. Many studies have reported the molecular characterization of TNBCs. Several actionable targets have been identified. Novel therapeutic strategies are currently being tested in clinical trials based on promising results observed in preclinical studies. These targets include androgen receptor, EGFR, PARP, FGFR, and the angiogenic pathway. We review the recent data on experimental drugs in this field. We also discuss the recent data concerning immunologic checkpoint inhibitors.
Second international consensus guidelines for breast cancer in young women (BCY2)
Venue: Breast

The 2nd International Consensus Conference for Breast Cancer in Young Women (BCY2) took place in November 2014, in Dublin, Ireland organized by the European School of Oncology (ESO) Consensus recommendations for the management of breast cancer in young women (BCYW) were updated from BCY1 with incorporation of new evidence to inform the guidelines, and areas of research priorities were identified. This manuscript summarizes these international consensus recommendations, which are also endorsed by the European Society of Breast Specialists (EUSOMA)
Tumor associated macrophages: unwitting accomplices in breast cancer malignancy
Venue: npj Breast Cancer

Deleterious inflammation is a primary feature of breast cancer. Accumulating evidence demonstrates that macrophages, the most abundant leukocyte population in mammary tumors, have a critical role at each stage of cancer progression. Such tumor associated macrophages facilitate neoplastic transformation, tumor immune evasion and the subsequent metastatic cascade. Herein, we discuss the dynamic process whereby molecular and cellular features of the tumor microenvironment act to license tissue repair mechanisms of macrophages, fostering angiogenesis, metastasis and the support of cancer stem cells. We illustrate how tumors induce, then exploit trophic macrophages to subvert innate and adaptive immune responses capable of destroying malignant cells. Finally, we discuss compelling evidence from murine models of cancer and early clinical trials in support of macrophage targeted intervention strategies with the potential to dramatically reduce breast cancer morbidity and mortality.
Plasma exosome microRNAs are indicative of breast cancer
Venue: Breast Cancer Research

BackgroundmicroRNAs are promising candidate breast cancer biomarkers due to their cancer specific expression profiles. However, efforts to develop circulating breast cancer biomarkers are challenged by the heterogeneity of microRNAs in the blood. To overcome this challenge, we aimed to develop a molecular profile of microRNAs specifically secreted from breast cancer cells. Our first step towards this direction relates to capturing and analyzing the contents of exosomes, which are small secretory vesicles that selectively encapsulate microRNAs indicative of their cell of origin. To our knowledge, circulating exosome microRNAs have not been well evaluated as biomarkers for breast cancer diagnosis or monitoring.MethodsExosomes were collected from the conditioned media of human breast cancer cell lines, mouse plasma of patient derived orthotopic xenograft models (PDX) and human plasma samples. Exosomes were verified by electron microscopy, nanoparticle tracking analysis, and western blot. Cellular and exosome microRNAs from breast cancer cell lines were profiled by next generation small RNA sequencing. Plasma exosome microRNA expression was analyzed by qRT PCR analysis.ResultsSmall RNA sequencing and qRT PCR analysis showed that several microRNAs are selectively encapsulated or highly enriched in breast cancer exosomes. Importantly, the selectively enriched exosome microRNA, human miR 1246, was detected at significantly higher levels in exosomes isolated from PDX mouse plasma, indicating that tumor exosome microRNAs are released into the circulation and can serve as plasma biomarkers for breast cancer. This observation was extended to human plasma samples where miR 1246 and miR 21 were detected at significantly higher levels in the plasma exosomes of 16 patients with breast cancer as compared to the plasma exosomes of healthy control subjects. Receiver operating characteristic curve analysis indicated that the combination of plasma exosome miR 1246 and miR 21 is a better indicator of breast cancer than their individual levels.ConclusionsOur results demonstrate that certain microRNA species, such as miR 21 and miR 1246, are selectively enriched in human breast cancer exosomes and significantly elevated in the plasma of patients with breast cancer. These findings indicate a potential new strategy to selectively analyze plasma breast cancer microRNAs indicative of the presence of breast cancer.
Predicting stock using microblog moods
Venue: China Communications

Some research work has showed that public mood and stock market price have some relations in some degree. Although it is difficult to clear the relation, the research about the relation between stock market price and public mood is interested by some scientists. This paper tries to find the relationship between Chinese stock market and Chinese local Microblog. First, C POMS (Chinese Profile of Mood States) was proposed to analyze sentiment of Microblog feeds. Then Granger causality test confirmed the relation between C POMS analysis and price series. SVM and Probabilistic Neural Network were used to make prediction, and experiments show that SVM is better to predict stock market movements than Probabilistic Neural Network. Experiments also indicate that adding certain dimension of C POMS as the input data will improve the prediction accuracy to 66.667% Two dimensions to input data leads to the highest accuracy of 71.429% which is about 20% higher than using only history stock data as the input data. This paper also compared the proposed method with the ROSTEA scores, and concluded that only the proposed method brings more accurate predicts.
Graph Clustering: Block models and model free results
Venue: NIPS

Clustering graphs under the Stochastic Block Model (SBM) and extensions are well studied. Guarantees of correctness exist under the assumption that the data is sampled from a model. In this paper, we propose a framework, in which we obtain "correctness" guarantees without assuming the data comes from a model. The guarantees we obtain depend instead on the statistics of the data that can be checked. We also show that this framework ties in with the existing model based framework, and that we can exploit results in model based recovery, as well as strengthen the results existing in that area of research.
Analysing potato late blight control as a social ecological system using fuzzy cognitive mapping
Venue: Agronomy for Sustainable Development

Potato late blight, caused by Phytophthora infestans, is one of the main diseases in potato production, causing major losses in yield. Applying environmentally harmful fungicides is the prevailing and classical method for controlling late blight, thus contaminating food and water. There is therefore a need for innovative research approaches to produce food sustainably. Here, we used a systems approach to identify sustainable management strategies for disease control in potato production in the Netherlands. We focussed not only on ecological processes, the classical approach, but also on decision making concerning disease management. For that, we performed a literature study, stakeholder interviews and modelling using fuzzy cognitive mapping. Interviews were carried out with farmers, representatives of breeding companies and experts. The fuzzy cognitive map allows to identify major concepts and their influence on late blight management. Three management scenarios were analysed using the fuzzy cognitive map. Results show that published research on the control of potato late blight focusses on agronomic practices, plant breeding for resistance to late blight and chemical based disease suppression. Farmers are strongly influenced by corporate (such as traders, breeders and retail) and public institutes and policies, each pushing their own objectives and interests. The fuzzy cognitive map showed that social and ecological processes are tightly related. The scenario analysis showed that increasing stakeholder cooperation and a change in market demands towards resistant cultivars could improve sustainability of late blight management. In contrast, policies restricting the use of fungicides would result in increased disease severity if no alternative strategies were implemented. Adoption of such strategies would require social institutional support and facilitation. We conclude that our systems approach improves the understanding of the system dynamics which is necessary for developing and deploying effective strategies for controlling P. infestans.
Controlled Clinical Trial on Bone anchored Hearing Implants and a Surgical Technique With Soft tissue Preservation
Venue: Otology neurotology official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology

To compare the clinical and audiological outcomes after linear incision with soft tissue preservation and standard linear incision with soft tissue reduction for placement of percutaneous bone anchored hearing implants.  Clinical trial with historical control group from a previous randomized controlled trial.  Tertiary referral center.  Twenty five patients were enrolled in a prospective cohort of bone anchored hearing implant placement with linear incision and tissue preservation with a follow up of 6 months. The control group consisted of 25 patients from a previous randomized controlled trial in the same tertiary referral center. All sound processors were fitted 3 weeks after surgery.  Numbness around the abutment, length of surgery, soft tissue reactions according to Holgers' classification, Patient and Observer Scar Assessment Scale, implant loss, Implant Stability Quotient, and audiological outcome.  Tissue preservation resulted in better results on sensibility (mean percentage correct responses 98% [SD 4.4] versus 89% [SD 15.0] p 0.003) on the Patient and Observer Scar Assessment Scale (mean observer score 15.3 [SD 4.3] versus 19.4 [SD 6.3] p 0.006) and shorter total surgery time (mean 24.6 min [SD 6.2] versus 31.9 min [SD 6.5] p 0.001) More adverse soft tissue reactions as measured by the Holgers classification were observed in the test group (n 7 [28% versus n 1 [4% p 0.049) For Implant Stability Quotient and audiology the study did not provide evidence that tissue preservation is better or worse compared with tissue reduction.  Tissue preservation compared with tissue reduction leads to a generally favorable clinical outcome, comparable audiology results, and significantly shorter surgery time. Longer follow up is warranted to conclude on the increased adverse soft tissue reactions after 6 months.
Parallel Recurrent Neural Network Architectures for Feature rich Session based Recommendations
Venue: RecSys

Real life recommender systems often face the daunting task of providing recommendations based only on the clicks of a user session. Methods that rely on user profiles such as matrix factorization perform very poorly in this setting, thus item to item recommendations are used most of the time. However the items typically have rich feature representations such as pictures and text descriptions that can be used to model the sessions. Here we investigate how these features can be exploited in Recurrent Neural Network based session models using deep learning. We show that obvious approaches do not leverage these data sources. We thus introduce a number of parallel RNN (p RNN) architectures to model sessions based on the clicks and the features (images and text) of the clicked items. We also propose alternative training strategies for p RNNs that suit them better than standard training. We show that p RNN architectures with proper training have significant performance improvements over feature less session models while all session based models outperform the item to item type baseline.
True Happiness in the Presence of YHWH The Literary and Theological Context for Understanding Psalm 16

This article attempts to interpret Ps 16 as part of the cluster of Psalms 15 24, but also as a Torah wisdom psalm. Hossfeld and Zenger have argued that Ps 16 was added to this cluster simultaneously with Pss 19 and 23, but that this happened quite some time before Ps 1 was composed to serve (together with Ps 2) as the preface to the whole Psalter. It is proposed here that Ps 16 is a Torahwisdom composition which exemplifies true blessedness as compliance with the Torah of YHWH in contentedness with one's lot in life. It thus represents the kind of piety also portrayed in other Torahwisdom psalms such as Pss 1, 19, 23 and 73. It is consequently suggested that Ps 16 is much closer to Ps 1 in time of origin and teaching as has been accepted until now. This does have implications for its interpretation.
Recent declines in cancer incidence: related to the Great Recession?
Venue: Cancer Causes Control

PurposeIn recent years, cancer case counts in the U.S. underwent a large, rapid decline an unexpected change given population growth for older persons at highest cancer risk. As these declines coincided with the Great Recession, we examined whether they were related to economic conditions.MethodsUsing California Cancer Registry data from California's 30 most populous counties, we analyzed trends in cancer incidence during pre recession (1996 2007) and recession/recovery (2008 2012) periods for all cancers combined and the ten most common sites. We evaluated the recession's association with rates using a multifactorial index that measured recession impact, and modeled associations between case counts and county level unemployment rates using Poisson regression.ResultsYearly cancer incidence rate declines were greater during the recession/recovery (3.3% among males, 1.4% among females) than before (0.7 and 0.5% respectively) particularly for prostate, lung, and colorectal cancers. Lower case counts, especially for prostate and liver cancer among males and breast cancer, melanoma, and ovarian cancer among females, were associated with higher unemployment rates, irrespective of time period, but independent of secular effects. The associations for melanoma translated up to a 3.6% decrease in cases with each 1% increase in unemployment. Incidence declines were not greater in counties with higher recession impact index.ConclusionsAlthough recent declines in incidence of certain cancers are not differentially impacted by economic conditions related to the Great Recession relative to pre recession conditions, the large recent absolute declines in the case counts of some cancer may be attributable to the large declines in unemployment in the recessionary period. This may occur through decreased engagement in preventive health behaviors, particularly for clinically less urgent cancers. Continued monitoring of trends is important to detect any rises in incidence rates as deferred diagnoses come to clinical attention.
Construction Quality Assessment Using 3D as built Models Generated with Project Tango

Assessing the quality of construction for compliance with the design intent has been a challenging task in the AEC (Architecture, Engineering, and Construction) industry. As modern design methods using Building Information Modeling (BIM) techniques have been increasingly adopted by the AEC industry, construction quality assessment using BIM has become a challenging new task for practitioners. In the past few years, 3D as built models for construction quality assessment have been developed using data acquisition techniques like 3D laser scanning and photogrammetry. However, certain limitations like non affordability, requiring expertise to operate, and dependence on time consuming processes are restricting their usage for construction quality control purposes. The main objective of this work is to study the applicability of using a new, affordable, easy to use, and faster modeling technology (Project Tango) to produce 3D as built models for facilitating the construction quality control process. For this purpose, a construction project was chosen as a case study and three different scenarios (including interior and exterior environments) were modelled using Project Tango. A post processing method was developed to prepare the scanned as built models for comparison with the design BIM. The accuracy level of these as built models were also evaluated using dimension accuracy analysis. The prepared as built models and the design BIM were then integrated and adjusted in the Autodesk Navisworks environment to perform the quality control assessment. This assessment process includes object completeness testing and spatial deviation analyses. This research thus highlights both the advantages and limitations of Project Tango and shows that such technologies have a great potential for construction quality assessments.
Doing well by doing good? The case of housing construction quality in China

Construction quality is a major problem in China's housing market. We investigate whether the housing market could provide incentives to encourage developers to promote construction quality beyond the compulsory, minimum standards by testing the financial viability of efforts made in this field by developers. This study takes place in the city of Beijing, where the "Great Wall Award" granted by the local construction bureau, is used as an indicator of excellent performance in construction quality. Our analysis shows that, from 2005 to 2010, the transaction price in the housing resale market of a unit that received the award can be up to 7.0% higher than a similar unit that did not receive the award. This difference is due to both the higher possible rent and a lower capitalization rate. However, we find no meaningful price premium at the presale stage, while developers with a record of winning the award cannot use such reputation to obtain price premiums in later projects either. These findings indicate a mismatch between the costs and benefits that residential developers face when deciding to enhance the quality of their construction. This mismatch partially explains the current housing construction quality problems in China, and may also discourage future improvements in this field. More efforts from the government are required to correct such market failures.
Drivers of employee propensity to endorse their corporate brand

Employees play an important role in building corporate brand equity both at their places of work and in their interactions with friends and family. The purpose of this study was to test the relative roles of brand knowledge and engagement of employees in predicting their propensity to endorse their organisation's brand to friends and family. An e mail survey was administered to employees of a large South African retail and merchant bank. Result of a moderated regression confirmed that, not only do both employee engagement and brand knowledge play an important in predicting their likelihood to endorse their brand, but that employee engagement moderates the relationship between employees' brand knowledge and their propensity to endorse. We discuss the relevance of our findings, not only to scholars interested in the role played by employees in building corporate brand equity, but also for brand and human resources managers.
Corporate brands and corporate marketing: Emerging trends in the big five eco system

Drawing on the final reflections made at the seventeenth International Corporate Identity Group Symposium (2014) at Cape Town Business School, five trends emerged from the diverse papers delivered at the symposium: assimilation, bifurcation, contextualisation, definitions and ethics. These trends reflect the richness as well as the complexity of the broad corporate marketing and corporate brand fields. This commentary also provides short overviews of the six articles comprising this special edition of the Journal of Brand Management.
Reducing Reputational Risk: Evaluating Stakeholder Salience and Prioritising Stakeholder Claims

The purpose of this paper is to establish how executive managers in a South African organisation prioritise and manage reputational risks arising from stakeholder claims. The authors establish how corporate reputation and reputational risk fits into their decision making when considering stakeholder claims.  The authors conducted in depth interviews with the top management of a South African paint manufacture. They identified eight stakeholder claims and discussed how they assessed and addressed each one.  Respondents identified highly, moderate, and low salient claims. They reported on how they dealt with these different claims in terms of the attributes of power, legitimacy, and urgency.  This is an empirical theory testing study of how managers deal with stakeholder claims. The authors establish how corporate reputation and reputational risk fits into their decision making when considering stakeholder claims. The authors suggest that managers must not only understand who their stakeholders are, but need to evaluate the impact of stakeholder claims in order to manage reputational risk.