Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding

We propose a model for tagging unstructured texts with an arbitrary number of terms drawn from a tree-structured vocabulary (i.e., an ontology). We treat this as a special case of sequence-to-sequence learning in which the decoder begins at the root node of an ontological tree and recursively elects to expand child nodes as a function of the input text, the current node, and the latent decoder state. We demonstrate that this method yields state-of-the-art results on the important task of assigning MeSH terms to biomedical abstracts

Cell cycle times of short-term cultures of brain cancers as predictors of survival

Tumour cytokinetics estimated in vivo as potential doubling times (Tpot values) have been found to range in a variety of human cancers from 2 days to several weeks and are often related to clinical outcome. We have previously developed a method to estimate culture cycle times of short-term cultures of surgical material for several tumour types and found, surprisingly, that their range was similar to that reported for Tpot values. As Tpot is recognised as important prognostic variable in cancer, we wished to determine whether culture cycle times had clinical significance. Brain tumour material obtained at surgery from 70 patients with glioblastoma, medulloblastoma, astrocytoma, oligodendroglioma and metastatic melanoma was cultured for 7 days on 96-well plates, coated with agarose to prevent proliferation of fibroblasts. Culture cycle times were estimated from relative 3H-thymidine incorporation in the presence and absence of cell division. Patients were divided into two groups on the basis of culture cycle times of ⩽10 days and >10 days and patient survival was compared. For patients with brain cancers of all types, median survival for the ⩽10-day and >10-day groups were 5.1 and 12.5 months, respectively (P=0.0009). For 42 patients with glioblastoma, the corresponding values were 6.5 and 9.0 months, respectively (P=0.03). Lower grade gliomas had longer median culture cycle times (16 days) than those of medulloblastomas (9.9 days), glioblastomas (9.8 days) or melanomas (6.7 days). We conclude that culture cycle times determined using short-term cultures of surgical material from brain tumours correlate with patient survival. Tumour cells thus appear to preserve important cytokinetic characteristics when transferred to culture

Kuiper belt analogues in nearby M-type planet-host systems

We present the results of a Herschel survey of 21 late-type stars that host planets discovered by the radial velocity technique. The aims were to discover new discs in these systems and to search for any correlation between planet presence and disc properties. In addition to the known disc around GJ 581, we report the discovery of two new discs, in the GJ 433 and GJ 649 systems. Our sample therefore yields a disc detection rate of 14 per cent, higher than the detection rate of 1.2 per cent among our control sample of DEBRIS M-type stars with 98 per cent confidence. Further analysis however shows that the disc sensitivity in the control sample is about a factor of two lower in fractional luminosity than for our survey, lowering the significance of any correlation between planet presence and disc brightness below 98 per cent. In terms of their specific architectures, the disc around GJ 433 lies at a radius somewhere between 1 and 30 au. The disc around GJ 649 lies somewhere between 6 and 30 au, but is marginally resolved and appears more consistent with an edge-on inclination. In both cases the discs probably lie well beyond where the known planets reside (0.06–1.1 au), but the lack of radial velocity sensitivity at larger separations allows for unseen Saturn–mass planets to orbit out to ~5 au, and more massive planets beyond 5 au. The layout of these M-type systems appears similar to Sun-like star + disc systems with low-mass planets.This work was supported by the European Union through ERC grant number 279973 (GMK & MCW)

A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation

We consider the task of automatically annotating free texts describing clinical trials with concepts from a controlled, structured medical vocabulary. Specifically, we aim to build a model to infer distinct sets of (ontological) concepts describing complementary clinically salient aspects of the underlying trials: the populations enrolled, the interventions administered and the outcomes measured, i.e., the PICO elements. This important practical problem poses a few key challenges. One issue is that the output space is vast, because the vocabulary comprises many unique concepts. Compounding this problem, annotated data in this domain is expensive to collect and hence sparse. Furthermore, the outputs (sets of concepts for each PICO element) are correlated: specific populations (e.g., diabetics) will render certain intervention concepts likely (insulin therapy) while effectively precluding others (radiation therapy). Such correlations should be exploited. We propose a novel neural model that addresses these challenges. We introduce a Candidate-Selector architecture in which the model considers setes of candidate concepts for PICO elements, and assesses their plausibility conditioned on the input text to be annotated. This relies on a 'candidate set' generator, which may be learned or relies on heuristics. A conditional discriminative neural model then jointly selects candidate concepts, given the input text. We compare the predictive performance of our approach to strong baselines, and show that it outperforms them. Finally, we perform a qualitative evaluation of the generated annotations by asking domain experts to assess their quality

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

Diagnosis of Cystic Fibrosis: Consensus Guidelines from the Cystic Fibrosis Foundation.

OBJECTIVE: Cystic fibrosis (CF), caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, continues to present diagnostic challenges. Newborn screening and an evolving understanding of CF genetics have prompted a reconsideration of the diagnosis criteria. STUDY DESIGN: To improve diagnosis and achieve standardized definitions worldwide, the CF Foundation convened a committee of 32 experts in CF diagnosis from 9 countries to develop clear and actionable consensus guidelines on the diagnosis of CF and to clarify diagnostic criteria and terminology for other disorders associated with CFTR mutations. An a priori threshold of ≥80% affirmative votes was required for acceptance of each recommendation statement. RESULTS: After reviewing relevant literature, the committee convened to review evidence and cases. Following the conference, consensus statements were developed by an executive subcommittee. The entire consensus committee voted and approved 27 of 28 statements, 7 of which needed revisions and a second round of voting. CONCLUSIONS: It is recommended that diagnoses associated with CFTR mutations in all individuals, from newborn to adult, be established by evaluation of CFTR function with a sweat chloride test. The latest mutation classifications annotated in the Clinical and Functional Translation of CFTR project (http://www.cftr2.org/index.php) should be used to aid in diagnosis. Newborns with a high immunoreactive trypsinogen level and inconclusive CFTR functional and genetic testing may be designated CFTR-related metabolic syndrome or CF screen positive, inconclusive diagnosis; these terms are now merged and equivalent, and CFTR-related metabolic syndrome/CF screen positive, inconclusive diagnosis may be used. International Statistical Classification of Diseases and Related Health Problems, 10th Revision codes for use in diagnoses associated with CFTR mutations are included

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally

Foot pain and foot health in an educated population of adults: results from the Glasgow Caledonian University Alumni Foot Health Survey

Abstract Background Foot pain is common amongst the general population and impacts negatively on physical function and quality of life. Associations between personal health characteristics, lifestyle/behaviour factors and foot pain have been studied; however, the role of wider determinants of health on foot pain have received relatively little attention. Objectives of this study are i) to describe foot pain and foot health characteristics in an educated population of adults; ii) to explore associations between moderate-to-severe foot pain and a variety of factors including gender, age, medical conditions/co-morbidity/multi-morbidity, key indicators of general health, foot pathologies, and social determinants of health; and iii) to evaluate associations between moderate-to-severe foot pain and foot function, foot health and health-related quality-of-life. Methods Between February and March 2018, Glasgow Caledonian University Alumni with a working email address were invited to participate in the cross-sectional electronic survey (anonymously) by email via the Glasgow Caledonian University Alumni Office. The survey was constructed using the REDCap secure web online survey application and sought information on presence/absence of moderate-to-severe foot pain, patient characteristics (age, body mass index, socioeconomic status, occupation class, comorbidities, and foot pathologies). Prevalence data were expressed as absolute frequencies and percentages. Multivariate logistic and linear regressions were undertaken to identify associations 1) between independent variables and moderate-to-severe foot pain, and 2) between moderate-to-severe foot pain and foot function, foot health and health-related quality of life. Results Of 50,228 invitations distributed, there were 7707 unique views and 593 valid completions (median age [inter-quartile range] 42 [31–52], 67.3% female) of the survey (7.7% response rate). The sample was comprised predominantly of white Scottish/British (89.4%) working age adults (95%), the majority of whom were overweight or obese (57.9%), and in either full-time or part-time employment (82.5%) as professionals (72.5%). Over two-thirds (68.5%) of the sample were classified in the highest 6 deciles (most affluent) of social deprivation. Moderate-to-severe foot pain affected 236/593 respondents (39.8%). High body mass index, presence of bunions, back pain, rheumatoid arthritis, hip pain and lower occupation class were included in the final multivariate model and all were significantly and independently associated with moderate-to-severe foot pain (p < 0.05), except for rheumatoid arthritis (p = 0.057). Moderate-to-severe foot pain was significantly and independently associated lower foot function, foot health and health-related quality of life scores following adjustment for age, gender and body mass index (p < 0.05). Conclusions Moderate-to-severe foot pain was highly prevalent in a university-educated population and was independently associated with female gender, high body mass index, bunions, back pain, hip pain and lower occupational class. Presence of moderate-to-severe foot pain was associated with worse scores for foot function, foot health and health-related quality-of-life. Education attainment does not appear to be protective against moderate-to-severe foot pain

Gas and dust around A-type stars at tens of Myr: signatures of cometary breakup

Discs of dusty debris around main-sequence stars indicate fragmentation of orbiting planetesimals, and for a few A-type stars, a gas component is also seen that may come from collisionally released volatiles. Here we find the sixth example of a CO-hosting disc, around the ∼30 Myr-old A0-star HD 32997. Two more of these CO-hosting stars, HD 21997 and 49 Cet, have also been imaged in dust with SCUBA-2 within the SCUBA-2 Survey of Nearby Stars project. A census of 27 A-type debris hosts within 125 pc now shows 7/16 detections of carbon-bearing gas within the 5–50 Myr epoch, with no detections in 11 older systems. Such a prolonged period of high fragmentation rates corresponds quite well to the epoch when most of the Earth was assembled from planetesimal collisions. Recent models propose that collisional products can be spatially asymmetric if they originate at one location in the disc, with CO particularly exhibiting this behaviour as it can photodissociate in less than an orbital period. Of the six CO-hosting systems, only β Pic is in clear support of this hypothesis. However, radiative transfer modelling with the ProDiMo code shows that the CO is also hard to explain in a proto-planetary disc context.JSG and PW thank the ERC for funding for project DiscAnalysis, under the grant FP7-SPACE-2011 collaborative project 284405. JPM is supported by a UNSW Vice-Chancellor's postdoctoral fellowship. MCW and LM acknowledge the support of the European Union through ERC grant 279973. The JCMT is operated by the East Asian Observatory on behalf of The National Astronomical Observatory of Japan, Academia Sinica Institute of Astronomy and Astrophysics, the Korea Astronomy and Space Science Institute, the National Astronomical Observatories of China and the Chinese Academy of Sciences (Grant No. XDB09000000), with additional funding support from the Science and Technology Facilities Council of the United Kingdom and participating universities in the United Kingdom and Canada. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ