Research directions for harvesting cross-sectorial correlations towards improved policy making

The current paper focuses on the emerging problem of the management of and the processing required for the massive amounts of interdisciplinary data produced nowadays. As it becomes apparent that “the truth and the useful information is drowned in a sea of irrelevance due to the vast amount of information available”1, there are strong indications that seemingly irrelevant co-occurrences of events and subtle links between them may form pieces of the same puzzle that complement each other towards the revealment of predictive or explanatory indicators for many sectors of the modern economy. To this direction, modern technologies like data mining, data and visual analytics, artificial intelligence, etc. can be of significant value, if offering a comprehensive communication of potentially useful information to the appropriate stake holders and/or policy-makers. In this context,a multi-purpose platform for data analytics is briefly exhibited in order to demonstrate the potential of such approaches to policy making

An Evaluation of Diversification Techniques

Diversification is a method of improving user satisfaction by increasing the variety of information shown to user. Due to the lack of a precise definition of information variety, many diversification techniques have been proposed. These techniques, however, have been rarely compared and analyzed under the same setting, rendering a ‘right’ choice for a particular application very difficult. Addressing this problem, this paper presents a benchmark that offers a comprehensive empirical study on the performance comparison of diversification. Specifically, we integrate several state-of-the-art diversification algorithms in a comparable manner, and measure distinct characteristics of these algorithms with various settings. We then provide in-depth analysis of the benchmark results, obtained by using both real data and synthetic data. We believe that the findings from the benchmark will serve as a practical guideline for potential applications

Overcoming fears: a pathway to publishing for early career researchers

Purpose – The purpose of this paper is to present reflections of five early career researchers on the challenges of journal publishing and how to tackle them. Design/methodology/approach – The authors attended a participatory workshop on demystifying academic publications. Working individually and in groups the authors shared, discussed, analysed, visualised and ranked perceived challenges and opportunities concerning academic publishing. The authors then delved into the existing literature on the subject. Following their enhanced understanding of the area, the authors reflected on the experience and learnings. Findings – Personal confidence relating to the development of a scholarly identity was found to be a critical factor in the attitude towards journal publishing. Supervisory and peer support, accessibility to journal editors, as well as opportunities to reflect on the writing, publishing and peer review processes through participatory workshops and writing groups, were deemed more effective than formal and conventional guidance schemes. Research limitations/implications – This work adds to the available literature regarding the issue of academic publishing for PhD students and early career researchers. Originality/value – The paper contributes to a deeper understanding of issues surrounding publishing apprehension, by laying out thoughts that are seldom expressed

On the Complexity of Query Result Diversification

Query result diversification is a bi-criteria optimization problem for ranking query results. Given a database D, a query Q and a positive integer k, it is to find a set of k tuples from Q(D) such that the tuples are as relevant as possible to the query, and at the same time, as diverse as possible to each other. Subsets of Q(D) are ranked by an objective function defined in terms of relevance and diversity. Query result diversification has found a variety of applications in databases, information retrieval and operations research. This paper studies the complexity of result diversification for relational queries. We identify three problems in connection with query result diversification, to determine whether there exists a set of k tuples that is ranked above a bound with respect to relevance and diversity, to assess the rank of a given k-element set, and to count how many k-element sets are ranked above a given bound. We study these problems for a variety of query languages and for three objective functions. We establish the upper and lower bounds of these problems, all matching, for both combined complexity and data complexity. We also investigate several special settings of these problems, identifying tractable cases. 1

Clinicopathologic predictors of renal outcomes in light chain cast nephropathy: a multicenter retrospective study

Light chain cast nephropathy (LCCN) in multiple myeloma often leads to severe and poorly reversible acute kidney injury. Severe renal impairment influences the allocation of chemotherapy and its tolerability; it also affects patient survival. Whether renal biopsy findings add to the clinical assessment in predicting renal and patient outcomes in LCCN is uncertain. We retrospectively reviewed clinical presentation, chemotherapy regimens, hematologic response, and renal and patient outcomes in 178 patients with biopsy-proven LCCN from 10 centers in Europe and North America. A detailed pathology review, including assessment of the extent of cast formation, was performed to study correlations with initial presentation and outcomes. Patients presented with a mean estimated glomerular filtration rate (eGFR) of 13 ± 11 mL/min/1.73 m2, and 82% had stage 3 acute kidney injury. The mean number of casts was 3.2/mm2 in the cortex. Tubulointerstitial lesions were frequent: acute tubular injury (94%), tubulitis (82%), tubular rupture (62%), giant cell reaction (60%), and cortical and medullary inflammation (95% and 75%, respectively). Medullary inflammation, giant cell reaction, and the extent of cast formation correlated with eGFR value at LCCN diagnosis. During a median follow-up of 22 months, mean eGFR increased to 43 ± 30 mL/min/1.73 m2. Age, β2-microglobulin, best hematologic response, number of cortical casts per square millimeter, and degree of interstitial fibrosis/tubular atrophy (IFTA) were independently associated with a higher eGFR during follow-up. This eGFR value correlated with overall survival, independently of the hematologic response. This study shows that extent of cast formation and IFTA in LCCN predicts the quality of renal response, which, in turn, is associated with overall survival.info:eu-repo/semantics/publishedVersio

Clinical, genetic, epidemiologic, evolutionary, and functional delineation of TSPEAR-related autosomal recessive ectodermal dysplasia 14

TSPEAR variants cause autosomal recessive ectodermal dysplasia (ARED) 14. The function of TSPEAR is unknown. The clinical features, the mutation spectrum, and the underlying mechanisms of ARED14 are poorly understood. Combining data from new and previously published individuals established that ARED14 is primarily characterized by dental anomalies such as conical tooth cusps and hypodontia, like those seen in individuals with WNT10A-related odontoonychodermal dysplasia. AlphaFold-predicted structure-based analysis showed that most of the pathogenic TSPEAR missense variants likely destabilize the β-propeller of the protein. Analysis of 100000 Genomes Project (100KGP) data revealed multiple founder TSPEAR variants across different populations. Mutational and recombination clock analyses demonstrated that non-Finnish European founder variants likely originated around the end of the last ice age, a period of major climatic transition. Analysis of gnomAD data showed that the non-Finnish European population TSPEAR gene-carrier rate is ∼1/140, making it one of the commonest AREDs. Phylogenetic and AlphaFold structural analyses showed that TSPEAR is an ortholog of drosophila Closca, an extracellular matrix-dependent signaling regulator. We, therefore, hypothesized that TSPEAR could have a role in enamel knot, a structure that coordinates patterning of developing tooth cusps. Analysis of mouse single-cell RNA sequencing (scRNA-seq) data revealed highly restricted expression of Tspear in clusters representing enamel knots. A tspeara−/−;tspearb−/− double-knockout zebrafish model recapitulated the clinical features of ARED14 and fin regeneration abnormalities of wnt10a knockout fish, thus suggesting interaction between tspear and wnt10a. In summary, we provide insights into the role of TSPEAR in ectodermal development and the evolutionary history, epidemiology, mechanisms, and consequences of its loss of function variants

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe