Impact of sea ice transport on Beaufort Gyre liquid freshwater content.

The Arctic Ocean's Beaufort Gyre (BG) is a wind-driven reservoir of relatively fresh seawater, situated beneath time-mean anticyclonic atmospheric circulation, and is covered by mobile pack ice for most of the year. Liquid freshwater accumulation in and expulsion from this gyre is of critical interest due to its potential to affect the Atlantic meridional overturning circulation and due to the importance of freshwater in modulating vertical fluxes of heat, nutrients and carbon in the ocean, and exchanges of heat and moisture with the atmosphere. Here, we investigate the hypothesis that wind-driven sea ice transport into/from the BG region influences the freshwater content of the gyre and its variability. To test this hypothesis, we use the results of a coordinated climate response function experiment with four ice-ocean models, in combination with targeted experiments using a regional setup of the MITgcm, in which we rotate the surface wind forcing vectors (thereby changing the ageostrophic component of these winds). Our results show that, via an effect on the net thermodynamic growth rate, anomalies in sea ice transport into the BG affect liquid freshwater adjustment. Specifically, increased ice import increases freshwater retention in the gyre, whereas ice export decreases freshwater in the gyre. Our results demonstrate that uncertainty in the ageostrophic component of surface winds, and in the dynamic sea ice response to these winds, has important implications for ice thermodynamics and freshwater. This sensitivity may explain some of the observed inter-model spread in simulations of Beaufort Gyre freshwater and its adjustment in response to wind forcing.

Future strengthening of the Nordic Seas overturning circulation.

The overturning circulation in the Nordic Seas involves the transformation of warm Atlantic waters into cold, dense overflows. These overflow waters return to the North Atlantic and form the headwaters to the deep limb of the Atlantic meridional overturning circulation (AMOC). The Nordic Seas are thus a key component of the AMOC. However, little is known about the response of the overturning circulation in the Nordic Seas to future climate change. Here we show using global climate models that, in contrast to the North Atlantic, the simulated density-space overturning circulation in the Nordic Seas increases throughout most of the 21st century as a result of enhanced horizontal circulation and a strengthened zonal density gradient. The increased Nordic Seas overturning is furthermore manifested in the overturning circulation in the eastern subpolar North Atlantic. A strengthened Nordic Seas overturning circulation could therefore be a stabilizing factor in the future AMOC.

Sources of marine debris for Seychelles and other remote islands in the western Indian Ocean.

Vast quantities of debris are beaching at remote islands in the western Indian Ocean. We carry out marine dispersal simulations incorporating currents, waves, winds, beaching, and sinking, for both terrestrial and marine sources of debris, to predict where this debris comes from. Our results show that most terrestrial debris beaching at these remote western Indian Ocean islands drifts from Indonesia, India, and Sri Lanka. Debris associated with fisheries and shipping also poses a major risk. Debris accumulation at Seychelles is likely seasonal, peaking during February-April. This pattern is driven by monsoonal winds and may be amplified during positive Indian Ocean Dipole and El-Niño events. Our results underline the vulnerability of small island states to marine plastic pollution, and are a crucial step towards improved management of the issue. The trajectories used in this study are available for download, and our analyses can be rerun under different parameter choices.

Skillful prediction of northern climate provided by the ocean.

This corrects the article DOI: 10.1038/ncomms15875.

Skillful prediction of northern climate provided by the ocean.

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981-2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

Acquisition and evaluation of verb subcategorization resources for biomedicine.

BACKGROUND: Biomedical natural language processing (NLP) applications that have access to detailed resources about the linguistic characteristics of biomedical language demonstrate improved performance on tasks such as relation extraction and syntactic or semantic parsing. Such applications are important for transforming the growing unstructured information buried in the biomedical literature into structured, actionable information. In this paper, we address the creation of linguistic resources that capture how individual biomedical verbs behave. We specifically consider verb subcategorization, or the tendency of verbs to "select" co-occurrence with particular phrase types, which influences the interpretation of verbs and identification of verbal arguments in context. There are currently a limited number of biomedical resources containing information about subcategorization frames (SCFs), and these are the result of either labor-intensive manual collation, or automatic methods that use tools adapted to a single biomedical subdomain. Either method may result in resources that lack coverage. Moreover, the quality of existing verb SCF resources for biomedicine is unknown, due to a lack of available gold standards for evaluation. RESULTS: This paper presents three new resources related to verb subcategorization frames in biomedicine, and four experiments making use of the new resources. We present the first biomedical SCF gold standards, capturing two different but widely-used definitions of subcategorization, and a new SCF lexicon, BioCat, covering a large number of biomedical sub-domains. We evaluate the SCF acquisition methodologies for BioCat with respect to the gold standards, and compare the results with the accuracy of the only previously existing automatically-acquired SCF lexicon for biomedicine, the BioLexicon. Our results show that the BioLexicon has greater precision while BioCat has better coverage of SCFs. Finally, we explore the definition of subcategorization using these resources and its implications for biomedical NLP. All resources are made publicly available. CONCLUSION: The SCF resources we have evaluated still show considerably lower accuracy than that reported with general English lexicons, demonstrating the need for domain- and subdomain-specific SCF acquisition tools for biomedicine. Our new gold standards reveal major differences when annotators use the different definitions. Moreover, evaluation of BioCat yields major differences in accuracy depending on the gold standard, demonstrating that the definition of subcategorization adopted will have a direct impact on perceived system accuracy for specific tasks.

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools.

BACKGROUND: We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. RESULTS: Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. CONCLUSIONS: The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications.

HIGH-PRECISION BIOLOGICAL EVENT EXTRACTION: EFFECTS OF SYSTEM AND OF DATA.

We approached the problems of event detection, argument identification, and negation and speculation detection in the BioNLP'09 information extraction challenge through concept recognition and analysis. Our methodology involved using the OpenDMAP semantic parser with manually written rules. The original OpenDMAP system was updated for this challenge with a broad ontology defined for the events of interest, new linguistic patterns for those events, and specialized coordination handling. We achieved state-of-the-art precision for two of the three tasks, scoring the highest of 24 teams at precision of 71.81 on Task 1 and the highest of 6 teams at precision of 70.97 on Task 2. We provide a detailed analysis of the training data and show that a number of trigger words were ambiguous as to event type, even when their arguments are constrained by semantic class. The data is also shown to have a number of missing annotations. Analysis of a sampling of the comparatively small number of false positives returned by our system shows that major causes of this type of error were failing to recognize second themes in two-theme events, failing to recognize events when they were the arguments to other events, failure to recognize nontheme arguments, and sentence segmentation errors. We show that specifically handling coordination had a small but important impact on the overall performance of the system. The OpenDMAP system and the rule set are available at http://bionlp.sourceforge.net.

The structural and content aspects of abstracts versus bodies of full text journal articles are different.

BACKGROUND: An increase in work on the full text of journal articles and the growth of PubMedCentral have the opportunity to create a major paradigm shift in how biomedical text mining is done. However, until now there has been no comprehensive characterization of how the bodies of full text journal articles differ from the abstracts that until now have been the subject of most biomedical text mining research. RESULTS: We examined the structural and linguistic aspects of abstracts and bodies of full text articles, the performance of text mining tools on both, and the distribution of a variety of semantic classes of named entities between them. We found marked structural differences, with longer sentences in the article bodies and much heavier use of parenthesized material in the bodies than in the abstracts. We found content differences with respect to linguistic features. Three out of four of the linguistic features that we examined were statistically significantly differently distributed between the two genres. We also found content differences with respect to the distribution of semantic features. There were significantly different densities per thousand words for three out of four semantic classes, and clear differences in the extent to which they appeared in the two genres. With respect to the performance of text mining tools, we found that a mutation finder performed equally well in both genres, but that a wide variety of gene mention systems performed much worse on article bodies than they did on abstracts. POS tagging was also more accurate in abstracts than in article bodies. CONCLUSIONS: Aspects of structure and content differ markedly between article abstracts and article bodies. A number of these differences may pose problems as the text mining field moves more into the area of processing full-text articles. However, these differences also present a number of opportunities for the extraction of data types, particularly that found in parenthesized text, that is present in article bodies but not in article abstracts.

Exploring species-based strategies for gene normalization.

We introduce a system developed for the BioCreative II.5 community evaluation of information extraction of proteins and protein interactions. The paper focuses primarily on the gene normalization task of recognizing protein mentions in text and mapping them to the appropriate database identifiers based on contextual clues. We outline a ""fuzzy" dictionary lookup approach to protein mention detection that matches regularized text to similarly regularized dictionary entries. We describe several different strategies for gene normalization that focus on species or organism mentions in the text, both globally throughout the document and locally in the immediate vicinity of a protein mention, and present the results of experimentation with a series of system variations that explore the effectiveness of the various normalization strategies, as well as the role of external knowledge sources. While our system was neither the best nor the worst performing system in the evaluation, the gene normalization strategies show promise and the system affords the opportunity to explore some of the variables affecting performance on the BCII.5 tasks.

Cocaine-exposed infant behavior during Still-Face: risk factor analyses.

Prenatal cocaine exposure and the role of gender were evaluated using risk factor analyses to determine whether 6-month-old cocaine-exposed male infants demonstrated greater disruptions in infant-caregiver socioemotional interactions during a Still-Face test. Overall, non-cocaine-exposed infants spent more time looking at toys, compared with cocaine-exposed infants; nonexposed female infants spent more time scanning the environment, compared with nonexposed male infants. When caregiver behavior during the Still-Face was evaluated, differences emerged in amount of time the caregiver spent vocalizing to the infant. She vocalized more to a cocaine-exposed infant compared with a nonexposed one; she reduced vocalizing more during the test if the cocaine-exposed infant was female. An exposure by gender interaction emerged in the amount of change in caregiver vocalizations; however, the overarching hypothesis that male cocaine-exposed infants are at higher risk than nonexposed male, nonexposed female, and cocaine-exposed female infants was not supported. Because this interaction was evident in this cohort at 24 months, future research is needed to determine at what age an interaction begins to emerge in this cohort.

Concept recognition for extracting protein interaction relations from biomedical text.

BACKGROUND: Reliable information extraction applications have been a long sought goal of the biomedical text mining community, a goal that if reached would provide valuable tools to benchside biologists in their increasingly difficult task of assimilating the knowledge contained in the biomedical literature. We present an integrated approach to concept recognition in biomedical text. Concept recognition provides key information that has been largely missing from previous biomedical information extraction efforts, namely direct links to well defined knowledge resources that explicitly cement the concept's semantics. The BioCreative II tasks discussed in this special issue have provided a unique opportunity to demonstrate the effectiveness of concept recognition in the field of biomedical language processing. RESULTS: Through the modular construction of a protein interaction relation extraction system, we present several use cases of concept recognition in biomedical text, and relate these use cases to potential uses by the benchside biologist. CONCLUSION: Current information extraction technologies are approaching performance standards at which concept recognition can begin to deliver high quality data to the benchside biologist. Our system is available as part of the BioCreative Meta-Server project and on the internet http://bionlp.sourceforge.net.

OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.

BACKGROUND: Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. RESULTS: OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport), protein-protein interaction assertions (interaction) and assertions that a gene is expressed in a cell type (expression). Evaluations were performed on each system, resulting in F-scores ranging from .26-.72 (precision .39-.85, recall .16-.85). Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. CONCLUSION: OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for information extraction. The open source OpenDMAP code library is freely available at http://bionlp.sourceforge.net/

A fault model for ontology mapping, alignment, and linking systems.

There has been much work devoted to the mapping, alignment, and linking of ontologies (MALO), but little has been published about how to evaluate systems that do this. A fault model for conducting fine-grained evaluations of MALO systems is proposed, and its application to the system described in Johnson et al. [15] is illustrated. Two judges categorized errors according to the model, and inter-judge agreement was calculated by error category. Overall inter-judge agreement was 98% after dispute resolution, suggesting that the model is consistently applicable. The results of applying the model to the system described in [15] reveal the reason for a puzzling set of results in that paper, and also suggest a number of avenues and techniques for improving the state of the art in MALO, including the development of biomedical domain specific language processing tools, filtering of high frequency matching results, and word sense disambiguation.

Corpus refactoring: a feasibility study.

BACKGROUND: Most biomedical corpora have not been used outside of the lab that created them, despite the fact that the availability of the gold-standard evaluation data that they provide is one of the rate-limiting factors for the progress of biomedical text mining. Data suggest that one major factor affecting the use of a corpus outside of its home laboratory is the format in which it is distributed. This paper tests the hypothesis that corpus refactoring - changing the format of a corpus without altering its semantics - is a feasible goal, namely that it can be accomplished with a semi-automatable process and in a time-effcient way. We used simple text processing methods and limited human validation to convert the Protein Design Group corpus into two new formats: WordFreak and embedded XML. We tracked the total time expended and the success rates of the automated steps. RESULTS: The refactored corpus is available for download at the BioNLP SourceForge website http://bionlp.sourceforge.net. The total time expended was just over three person-weeks, consisting of about 102 hours of programming time (much of which is one-time development cost) and 20 hours of manual validation of automatic outputs. Additionally, the steps required to refactor any corpus are presented. CONCLUSION: We conclude that refactoring of publicly available corpora is a technically and economically feasible method for increasing the usage of data already available for evaluating biomedical language processing systems.

Evaluation of lexical methods for detecting relationships between concepts from multiple ontologies.

We used exact term matching, stemming, and inclusion of synonyms, implemented via the Lucene information retrieval library, to discover relationships between the Gene Ontology and three other OBO ontologies: ChEBI, Cell Type, and BRENDA Tissue. Proposed relationships were evaluated by domain experts. We discovered 91,385 relationships between the ontologies. Various methods had a wide range of correctness. Based on these results, we recommend careful evaluation of all matching strategies before use, including exact string matching. The full set of relationships is available at compbio.uchsc.edu/dependencies.

Neurological and developmental outcomes of prenatally cocaine-exposed offspring from 12 to 36 months.

Second generation studies of prenatal cocaine exposure failed to find gross deficits after controlling for confounders. Concern remained that exposure could cause subtle deficits. This prospective, cohort study evaluated effects of cocaine on development at 12, 18, 24, and 36 months. From 1991-1993, 361 mother-infant pairs were recruited from the Children's Hospital of New York, Presbyterian Medical Center's prenatal clinic or delivery room suite. Mothers were assigned to the cocaine group based on report of prenatal cocaine use or positive urine toxicology. Control mothers were enrolled from the same clinic and matched for age and socioeconomic status (SES). Women with serious medical problems were excluded from either group. Of the retained cohort, at 12 months, 147 infants were exposed and 89 were unexposed case controls. Both groups were raised in impoverished environments with few supports. Developmental evaluations were conducted blinded to group. Cross-sectional analysis revealed cocaine-related deficits in neurological exams and speech across all time periods, in spite of catch up in weight, length, and head circumference. Overall analysis of development was evaluated using Generalized Estimating Equations regression analysis. Bayley Mental [Badj = -6.5 (CI--9.4, -3.5, p < or = 0.001)] and Psychomotor [Badj = -3.9 (CI--7.4, -0.5, p = 0.02)] Developmental Indices showed deficits after controlling for confounders. Males were more vulnerable to cocaine exposure for height, motor development, and emotional regulation. Dose-response relationships existed for abnormal neurological exams (Ptrends < 0.08), Mental Development Index (MDI) (Ptrend < 0.001), and Psychomotor Development Index (PDI) (Ptrend < 0.001) deficits. Although nonexposed children performed poorly, cocaine-exposed children showed worse performance. Both groups showed declines at 18 months in mental and psychomotor development from which only nonexposed children rebounded. Overall, cocaine exposure adds an additional risk to disadvantaged children's development. Cocaine-exposed children are less resilient to effects of these multiple risks.