Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.

OBJECTIVES: We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research. DESIGN: Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries. SETTING: Electronic records from a large mental healthcare provider serving a geographic catchment of 1.2 million residents in four boroughs of south London, UK. PARTICIPANTS: The distribution of derived symptoms was described in 23 128 discharge summaries from 7962 patients who had received an SMI diagnosis, and 13 496 discharge summaries from 7575 patients who had received a non-SMI diagnosis. OUTCOME MEASURES: Fifty SMI symptoms were identified by a team of psychiatrists for extraction based on salience and linguistic consistency in records, broadly categorised under positive, negative, disorganisation, manic and catatonic subgroups. Text models for each symptom were generated using the TextHunter tool and the CRIS database. RESULTS: We extracted data for 46 symptoms with a median F1 score of 0.88. Four symptom models performed poorly and were excluded. From the corpus of discharge summaries, it was possible to extract symptomatology in 87% of patients with SMI and 60% of patients with non-SMI diagnosis. CONCLUSIONS: This work demonstrates the possibility of automatically extracting a broad range of SMI symptoms from English text discharge summaries for patients with an SMI diagnosis. Descriptive data also indicated that most symptoms cut across diagnoses, rather than being restricted to particular groups

Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process

Background Antipsychotic prescription information is commonly derived from structured fields in clinical health records. However, utilising diverse and comprehensive sources of information is especially important when investigating less frequent patterns of medication prescribing such as antipsychotic polypharmacy (APP). This study describes and evaluates a novel method of extracting APP data from both structured and free-text fields in electronic health records (EHRs), and its use for research purposes. Methods Using anonymised EHRs, we identified a cohort of patients with serious mental illness (SMI) who were treated in South London and Maudsley NHS Foundation Trust mental health care services between 1 January and 30 June 2012. Information about antipsychotic co-prescribing was extracted using a combination of natural language processing and a bespoke algorithm. The validity of the data derived through this process was assessed against a manually coded gold standard to establish precision and recall. Lastly, we estimated the prevalence and patterns of antipsychotic polypharmacy. Results Individual instances of antipsychotic prescribing were detected with high precision (0.94 to 0.97) and moderate recall (0.57-0.77). We detected baseline APP (two or more antipsychotics prescribed in any 6-week window) with 0.92 precision and 0.74 recall and long-term APP (antipsychotic co-prescribing for 6 months) with 0.94 precision and 0.60 recall. Of the 7,201 SMI patients receiving active care during the observation period, 338 (4.7 %; 95 % CI 4.2-5.2) were identified as receiving long-term APP. Two second generation antipsychotics (64.8 %); and first -second generation antipsychotics were most commonly co-prescribed (32.5 %). Conclusions These results suggest that this is a potentially practical tool for identifying polypharmacy from mental health EHRs on a large scale. Furthermore, extracted data can be used to allow researchers to characterize patterns of polypharmacy over time including different drug combinations, trends in polypharmacy prescribing, predictors of polypharmacy prescribing and the impact of polypharmacy on patient outcomes

Localized f electrons in CexLa1-xRhIn5: dHvA Measurements

Measurements of the de Haas-van Alphen effect in CexLa1-xRhIn5 reveal that the Ce 4f electrons remain localized for all x, with the mass enhancement and progressive loss of one spin from the de Haas-van Alphen signal resulting from spin fluctuation effects. This behavior may be typical of antiferromagnetic heavy fermion compounds, inspite of the fact that the 4f electron localization in CeRhIn5 is driven, in part, by a spin-density wave instability.Comment: 4 pages, 4 figures, submitted to PR

Zero temperature string breaking in lattice quantum chromodynamics

The separation of a heavy quark and antiquark pair leads to the formation of a tube of flux, or "string", which should break in the presence of light quark-antiquark pairs. This expected zero-temperature phenomenon has proven elusive in simulations of lattice QCD. We study mixing between the string state and the two-meson decay channel in QCD with two flavors of dynamical sea quarks. We confirm that mixing is weak and find that it decreases at level crossing. While our study does not show direct effects of internal quark loops, our results, combined with unitarity, give clear confirmation of string breaking.Comment: 20 pages, 7 figures. With small clarifications and two additions to references. Submitted to Phys. Rev.

What is a β cell? - Chapter I in the Human Islet Research Network (HIRN) review series

BACKGROUND: The pancreatic β cell, as the sole source of the vital hormone insulin, has been under intensive study for more than a century. Given the potential of newly created insulin-producing cells as a treatment or even cure of type 1 diabetes (T1D) and possibly in severe cases of type 2 diabetes (T2D), multiple academic and commercial laboratories are working to derive surrogate glucose-responsive, insulin-producing cells. SCOPE OF REVIEW: The recent development of advanced phenotyping technologies, including molecular, epigenomic, histological, or functional, have greatly improved our understanding of the critical properties of human β cells. Using this information, here we summarize the salient features of normal, fully functional adult human β cells, and propose minimal criteria for what should rightfully be termed 'β cells' as opposed to insulin-producing but not fully-functional surrogates that we propose should be referred to as 'β-like' cells or insulin-producing cells. MAJOR CONCLUSIONS: Clear criteria can be established to differentiate fully functional, mature β cells from 'β-like' surrogates. In addition, we outline important knowledge gaps that must be addressed to enable a greater understanding of the β cell

Asymptotic Expansions for Stationary Distributions of Perturbed Semi-Markov Processes

New algorithms for computing of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes are presented. The algorithms are based on special techniques of sequential phase space reduction, which can be applied to processes with asymptotically coupled and uncoupled finite phase spaces.Comment: 83 page

Neandertal and Denisovan DNA from Pleistocene sediments.

Although a rich record of Pleistocene human-associated archaeological assemblages exists, the scarcity of hominin fossils often impedes the understanding of which hominins occupied a site. Using targeted enrichment of mitochondrial DNA we show that cave sediments represent a rich source of ancient mammalian DNA that often includes traces of hominin DNA, even at sites and in layers where no hominin remains have been discovered. By automation-assisted screening of numerous sediment samples we detect Neandertal DNA in eight archaeological layers from four caves in Eurasia. In Denisova Cave we retrieved Denisovan DNA in a Middle Pleistocene layer near the bottom of the stratigraphy. Our work opens the possibility to detect the presence of hominin groups at sites and in areas where no skeletal remains are found

Observation of a Coherence Length Effect in Exclusive Rho^0 Electroproduction

Exclusive incoherent electroproduction of the rho^0(770) meson from 1H, 2H, 3He, and 14N targets has been studied by the HERMES experiment at squared four-momentum transfer Q**2>0.4 GeV**2 and positron energy loss nu from 9 to 20 GeV. The ratio of the 14N to 1H cross sections per nucleon, known as the nuclear transparency, was found to decrease with increasing coherence length of quark-antiquark fluctuations of the virtual photon. The data provide clear evidence of the interaction of the quark- antiquark fluctuations with the nuclear medium.Comment: RevTeX, 5 pages, 3 figure