Extraction of chemical structures and reactions from the literature

The ever increasing quantity of chemical literature necessitates the creation of automated techniques for extracting relevant information. This work focuses on two aspects: the conversion of chemical names to computer readable structure representations and the extraction of chemical reactions from text. Chemical names are a common way of communicating chemical structure information. OPSIN (Open Parser for Systematic IUPAC Nomenclature), an open source, freely available algorithm for converting chemical names to structures was developed. OPSIN employs a regular grammar to direct tokenisation and parsing leading to the generation of an XML parse tree. Nomenclature operations are applied successively to the tree with many requiring the manipulation of an in-memory connection table representation of the structure under construction. Areas of nomenclature supported are described with attention being drawn to difficulties that may be encountered in name to structure conversion. Results on sets of generated names and names extracted from patents are presented. On generated names, recall of between 96.2% and 99.0% was achieved with a lower bound of 97.9% on precision with all results either being comparable or superior to the tested commercial solutions. On the patent names OPSIN s recall was 2-10% higher than the tested solutions when the patent names were processed as found in the patents. The uses of OPSIN as a web service and as a tool for identifying chemical names in text are shown to demonstrate the direct utility of this algorithm. A software system for extracting chemical reactions from the text of chemical patents was developed. The system relies on the output of ChemicalTagger, a tool for tagging words and identifying phrases of importance in experimental chemistry text. Improvements to this tool required to facilitate this task are documented. The structure of chemical entities are where possible determined using OPSIN in conjunction with a dictionary of name to structure relationships. Extracted reactions are atom mapped to confirm that they are chemically consistent. 424,621 atom mapped reactions were extracted from 65,034 organic chemistry USPTO patents. On a sample of 100 of these extracted reactions chemical entities were identified with 96.4% recall and 88.9% precision. Quantities could be associated with reagents in 98.8% of cases and 64.9% of cases for products whilst the correct role was assigned to chemical entities in 91.8% of cases. Qualitatively the system captured the essence of the reaction in 95% of cases. This system is expected to be useful in the creation of searchable databases of reactions from chemical patents and in facilitating analysis of the properties of large populations of reactions

Supervised and unsupervised language modelling in Chest X-Ray radiological reports

Chest radiography (CXR) is the most commonly used imaging modality and deep neural network (DNN) algorithms have shown promise in effective triage of normal and abnormal radiograms. Typically, DNNs require large quantities of expertly labelled training exemplars, which in clinical contexts is a major bottleneck to effective modelling, as both considerable clinical skill and time is required to produce high-quality ground truths. In this work we evaluate thirteen supervised classifiers using two large free-text corpora and demonstrate that bi-directional long short-term memory (BiLSTM) networks with attention mechanism effectively identify Normal, Abnormal, and Unclear CXR reports in internal (n = 965 manually-labelled reports, f1-score = 0.94) and external (n = 465 manually-labelled reports, f1-score = 0.90) testing sets using a relatively small number of expert-labelled training observations (n = 3,856 annotated reports). Furthermore, we introduce a general unsupervised approach that accurately distinguishes Normal and Abnormal CXR reports in a large unlabelled corpus. We anticipate that the results presented in this work can be used to automatically extract standardized clinical information from free-text CXR radiological reports, facilitating the training of clinical decision support systems for CXR triage

Intra-Rater and Inter-Rater Reliability of Pressure Pain Algometry of the Sural and Tibial Nerves in Asymptomatic Elite Youth Footballers

Ankle injuries are highly prevalent in elite youth footballers and increase the mechanosensitivity of the local neural tissue, which may predispose athletes to re-injury and prolong rehabilitation periods. Increased neural mechanosensitivity presents clinically as altered pain pressure thresholds (PPTs) which are measured with pressure algometry. The purpose of this study was to determine the intra-rater and inter-rater reliability of PPTs of the ankle neural tissue in asymptomatic elite youth football players. Three raters utilised a digital algometer to evaluate the PPTs of the Sural and Tibial nervous tissue at the ankle of elite youth male footballers. Intraclass correlation coefficients (ICCs) with 95% confidence intervals (CI) were calculated to assess intra-rater and inter-rater reliability and Bland–Altman figures were plotted to enable visual evaluation of measurement error with a significance level of p < 0.05. Thirty-four players (16–18 years old) were assessed. Excellent intra-rater (Tibial ICC 0.88 (0.76–0.94); Sural ICC 0.89 (0.79–0.95)) and good inter-rater reliability (Tibial ICC 0.66 (0.40–0.82); Sural 0.71 (0.50–0.85)) was demonstrated. Bland–Altman plots demonstrated low levels of measurement error. Pressure algometry can be utilised clinically to accurately evaluate the PPTs of the Tibial and Sural nervous tissue at the ankle in asymptomatic elite male youth footballers

Impact of the earthworm Lumbricus terrestris (L.) on As, Cu, Pb and Zn mobility and speciation in contaminated soils

To assess the risks that contaminated soils pose to the environment properly a greater understanding of how soil biota influence the mobility of metal(loid)s in soils is required. Lumbricus terrestris L. were incubated in three soils contaminated with As, Cu, Pb and Zn. The concentration and speciation of metal(loid)s in pore waters and the mobility and partitioning in casts were compared with earthworm-free soil. Generally the concentrations of water extractable metal(loid)s in earthworm casts were greater than in earthworm-free soil. The impact of the earthworms on concentration and speciation in pore waters was soil and metal specific and could be explained either by earthworm induced changes in soil pH or soluble organic carbon. The mobilisation of metal(loid)s in the environment by earthworm activity may allow for leaching or uptake into biota

PANTHER: AZD8931, inhibitor of EGFR, ERBB2 and ERBB3 signalling, combined with FOLFIRI: a Phase I/II study to determine the importance of schedule and activity in colorectal cancer

BACKGROUND: Epidermal growth factor receptor (EGFR) is a therapeutic target to which HER2/HER3 activation may contribute resistance. This Phase I/II study examined the toxicity and efficacy of high-dose pulsed AZD8931, an EGFR/HER2/HER3 inhibitor, combined with chemotherapy, in metastatic colorectal cancer (CRC). METHODS: Treatment-naive patients received 4-day pulses of AZD8931 with irinotecan/5-FU (FOLFIRI) in a Phase I/II single-arm trial. Primary endpoint for Phase I was dose limiting toxicity (DLT); for Phase II best overall response. Samples were analysed for pharmacokinetics, EGFR dimers in circulating exosomes and Comet assay quantitating DNA damage. RESULTS: Eighteen patients received FOLFIRI and AZD8931. At 160 mg bd, 1 patient experienced G3 DLT; 160 mg bd was used for cohort expansion. No grade 5 adverse events (AE) reported. Seven (39%) and 1 (6%) patients experienced grade 3 and grade 4 AEs, respectively. Of 12 patients receiving 160 mg bd, best overall response rate was 25%, median PFS and OS were 8.7 and 21.2 months, respectively. A reduction in circulating HER2/3 dimer in the two responding patients after 12 weeks treatment was observed. CONCLUSIONS: The combination of pulsed high-dose AZD8931 with FOLFIRI has acceptable toxicity. Further studies of TKI sequencing may establish a role for pulsed use of such agents rather than continuous exposure. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov number: NCT01862003

Advanced Preparation Makes Research in Emergencies and Isolation Care Possible: The Case of Novel Coronavirus Disease (COVID-19)

The optimal time to initiate research on emergencies is before they occur. However, timely initiation of high-quality research may launch during an emergency under the right conditions. These include an appropriate context, clarity in scientific aims, preexisting resources, strong operational and research structures that are facile, and good governance. Here, Nebraskan rapid research efforts early during the 2020 coronavirus disease pandemic, while participating in the first use of U.S. federal quarantine in 50 years, are described from these aspects, as the global experience with this severe emerging infection grew apace. The experience has lessons in purpose, structure, function, and performance of research in any emergency, when facing any threat

A global database for metacommunity ecology, integrating species, traits, environment and space

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology