Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A retrospective analysis of biochemical and haematological parameters in patients with eating disorders

Background: The objective of the study was to determine whether levels of biochemical and haematological parameters in patients with eating disorders (EDs) varied from the general population. Whilst dietary restrictions can lead to nutritional deficiencies, specific abnormalities may be relevant to the diagnosis, pathogenesis and treatment of EDs

SDSS-III : massive spectroscopic surveys of the distant universe, the Milk Way, and extra-solar planetary systems

Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS Data Release 8 (DR8), which was made public in 2011 January and includes SDSS-I and SDSS-II images and spectra reprocessed with the latest pipelines and calibrations produced for the SDSS-III investigations. This paper presents an overview of the four surveys that comprise SDSS-III. The Baryon Oscillation Spectroscopic Survey will measure redshifts of 1.5 million massive galaxies and Lyα forest spectra of 150,000 quasars, using the baryon acoustic oscillation feature of large-scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z < 0.7 and at z ≈ 2.5. SEGUE- 2, an already completed SDSS-III survey that is the continuation of the SDSS-II Sloan Extension for Galactic Understanding and Exploration (SEGUE), measured medium-resolution (R = λ/Δλ ≈ 1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE, the Apache Point Observatory Galactic Evolution Experiment, will obtain high-resolution (R ≈ 30,000), high signal-to-noise ratio (S/N 100 per resolution element), H-band (1.51μm < λ < 1.70μm) spectra of 105 evolved, late-type stars, measuring separate abundances for ∼15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. The Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS) will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10–40ms−1, ∼24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. As of 2011 January, SDSS-III has obtained spectra of more than 240,000 galaxies, 29,000 z 2.2 quasars, and 140,000 stars, including 74,000 velocity measurements of 2580 stars for MARVELS

Author Correction: Global status and conservation potential of reef sharks

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.</p

SDSS-III : massive spectroscopic surveys of the distant universe, the Milk Way, and extra-solar planetary systems

Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS Data Release 8 (DR8), which was made public in 2011 January and includes SDSS-I and SDSS-II images and spectra reprocessed with the latest pipelines and calibrations produced for the SDSS-III investigations. This paper presents an overview of the four surveys that comprise SDSS-III. The Baryon Oscillation Spectroscopic Survey will measure redshifts of 1.5 million massive galaxies and Lyα forest spectra of 150,000 quasars, using the baryon acoustic oscillation feature of large-scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z < 0.7 and at z ≈ 2.5. SEGUE- 2, an already completed SDSS-III survey that is the continuation of the SDSS-II Sloan Extension for Galactic Understanding and Exploration (SEGUE), measured medium-resolution (R = λ/Δλ ≈ 1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE, the Apache Point Observatory Galactic Evolution Experiment, will obtain high-resolution (R ≈ 30,000), high signal-to-noise ratio (S/N 100 per resolution element), H-band (1.51μm < λ < 1.70μm) spectra of 105 evolved, late-type stars, measuring separate abundances for ∼15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. The Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS) will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10–40ms−1, ∼24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. As of 2011 January, SDSS-III has obtained spectra of more than 240,000 galaxies, 29,000 z 2.2 quasars, and 140,000 stars, including 74,000 velocity measurements of 2580 stars for MARVELS