Automatic annotation of the Penn-treebank with LFG f-structure information

Lexical-Functional Grammar f-structures are abstract syntactic representations approximating basic predicate-argument structure. Treebanks annotated with f-structure information are required as training resources for stochastic versions of unification and constraint-based grammars and for the automatic extraction of such resources. In a number of papers (Frank, 2000; Sadler, van Genabith and Way, 2000) have developed methods for automatically annotating treebank resources with f-structure information. However, to date, these methods have only been applied to treebank fragments of the order of a few hundred trees. In the present paper we present a new method that scales and has been applied to a complete treebank, in our case the WSJ section of Penn-II (Marcus et al, 1994), with more than 1,000,000 words in about 50,000 sentences

Novel ingredients from brewers' spent grain - bioactivity in cell culture model systems and bioactivity retention in fortified food products

Functional food ingredients, with scientifically proven and validated bioactive effects, present an effective means of inferring physiological health benefits to consumers to reduce the risk of certain diseases. The search for novel bioactive compounds for incorporation into functional foods is particularly active, with brewers’ spent grain (BSG, a brewing industry co-product) representing a unique source of potentially bioactive compounds. The DNA protective, antioxidant and immunomodulatory effects of phenolic extracts from both pale (P1 - P4) and black (B1 – B4) BSG were examined. Black BSG extracts significantly (P p-coumaric acid (p-CA) derivatives > FA derivatives > p-CA > caffeic acid (CA) > CA derivatives. Results suggested that brewing and roasting decreased the HA content. Protein hydrolysates from BSG were also screened for their antioxidant and anti-inflammatory potential. A total of 34 BSG protein samples were tested. Initial analyses of samples A – J found the protein samples did not exert DNA protective effects (except hydrolysate H) or antioxidant effects by the comet and SOD assays, respectively. Samples D, E, F and J selectively reduced IFN-γ production (P 5 kDa, found that higher molecular weight (> 5 kDa) and unfractionated hydrolysates demonstrate greatest anti-inflammatory effects, while fractionated hydrolysates were also shown to have antioxidant activity, by the SOD activity assay. A commercially available yogurt drink (Actimel) and snack-bar and chocolate-drink formulations were fortified with the most bioactive phenolic and protein samples – P2, B2, W, W 5 kDa. All fortified foods were subjected to a simulated gastrointestinal in vitro digestion procedure and bioactivity retention in the digestates was determined using the comet and ELISA assays. Yogurt fortified with B2 digestate significantly (P < 0.05) protected against H2O2-induced DNA damage in Caco-2 cells. Greatest immunomodulatory activity was demonstrated by the snack-bar formulation, significantly (P < 0.05) reducing IFN-γ production in con-A stimulated Jurkat T cells. Hydrolysate W significantly (P < 0.05) increased the IFN-γ reducing capacity of the snack-bar. Addition of fractionated hydrolysate W < 3 kDa and W < 5 kDa to yogurt also reduced IL-2 production to a greater extent than the unfortified yogurt (P < 0.05)

Treebank-based multilingual unification-grammar development

Broad-coverage, deep unification grammar development is time-consuming and costly. This problem can be exacerbated in multilingual grammar development scenarios. Recently (Cahill et al., 2002) presented a treebank-based methodology to semi-automatically create broadcoverage, deep, unification grammar resources for English. In this paper we present a project which adapts this model to a multilingual grammar development scenario to obtain robust, wide-coverage, probabilistic Lexical-Functional Grammars (LFGs) for English and German via automatic f-structure annotation algorithms based on the Penn-II and TIGER treebanks. We outline our method used to extract a probabilistic LFG from the TIGER treebank and report on the quality of the f-structures produced. We achieve an f-score of 66.23 on the evaluation of 100 random sentences against a manually constructed gold standard

Quasi-logical forms from f-structures for the Penn treebank

In this paper we show how the trees in the Penn treebank can be associated automatically with simple quasi-logical forms. Our approach is based on combining two independent strands of work: the first is the observation that there is a close correspondence between quasi-logical forms and LFG f-structures [van Genabith and Crouch, 1996]; the second is the development of an automatic f-structure annotation algorithm for the Penn treebank [Cahill et al, 2002a; Cahill et al, 2002b]. We compare our approach with that of [Liakata and Pulman, 2002]

Parsing with PCFGs and automatic f-structure annotation

The development of large coverage, rich unification- (constraint-) based grammar resources is very time consuming, expensive and requires lots of linguistic expertise. In this paper we report initial results on a new methodology that attempts to partially automate the development of substantial parts of large coverage, rich unification- (constraint-) based grammar resources. The method is based on a treebank resource (in our case Penn-II) and an automatic f-structure annotation algorithm that annotates treebank trees with proto-f-structure information. Based on these, we present two parsing architectures: in our pipeline architecture we first extract a PCFG from the treebank following the method of (Charniak,1996), use the PCFG to parse new text, automatically annotate the resulting trees with our f-structure annotation algorithm and generate proto-f-structures. By contrast, in the integrated architecture we first automatically annotate the treebank trees with f-structure information and then extract an annotated PCFG (A-PCFG) from the treebank. We then use the A-PCFG to parse new text to generate proto-f-structures. Currently our best parsers achieve more than 81% f-score on the 2400 trees in section 23 of the Penn-II treebank and more than 60% f-score on gold-standard proto-f-structures for 105 randomly selected trees from section 23

Evaluating automatic F-structure annotation for the Penn-II treebank

Methodologies have been developed (van Genabith et al., 1999a,b; Sadler et al., 2000; Frank, 2000; van Genabith et al., 2001; Frank et al., 2002) for automatically annotating treebank resources with Lexical-Functional Grammar (LFG: Kaplan and Bresnan, 1982) fstructure information. Until recently, however, most of this work on automatic annotation has been applied only to limited datasets, so while it may have shown 'proof of concept', it has not been demonstrated that the techniques developed scale up to much larger data sets (Liakata and Pulman, 2002). More recent work (Cahill et al., 2002a,b) has presented efforts in evolving and scaling techniques established in these previous papers to the full Penn-ll Treebank (Marcus et al., 1994). In this paper, we present and assess a number of quantitative and qualitative evaluation methodologies which provide insights into the effectiveness of the techniques developed to derive automatically a set of f-structures for the more than 1,000,000 words and 49,000 sentences of Penn-II

Human factors and patient safety in undergraduate healthcare education : A systematic review

Peer reviewedPublisher PD

Stabilising effect of α-lactalbumin on concentrated infant milk formula emulsions heat treated pre- or post-homogenisation

peer-reviewedProtein type and/or heat treatment pre- or post-homogenisation can affect the physical stability of infant formulations during manufacture. Previous research has described the use of α-lactalbumin addition in infant formulae, but has not demonstrated the effect of heating pre- or post-emulsion formulation during processing. The objective of this study was to evaluate the effect of both of these parameters. Three batches of model 1st-stage infant formula containing differing whey protein ratios (60:40 whey: casein with α-lactalbumin content 12, 30 or 48% of total protein) were prepared. Each batch was split; one half receiving heat treatment pre-homogenisation and the second half homogenised and then heat treated. Emulsion stability was determined by size exclusion chromatography, SDS-PAGE, particle size and viscosity measurements. There was a significant (P < 0.05) reduction in the formation of large soluble aggregates upon increasing α-lac concentration in emulsions heat treated either before or after homogenisation. Heat treatment of formulations post-homogenisation resulted in a higher (P < 0.05) D.v09 within the particle size distribution; increasing α-lactalbumin concentration to 30 or 48% significantly (P < 0.05) reduced the D.v09 within the particle size distribution in these emulsions. The viscosity of concentrates (55 % total solids) containing the 12% α-lactalbumin, heat treated post-homogenisation, was significantly greater (P < 0.05) than the equivalent emulsion heat treated pre-homogenisation; increasing the α-lactalbumin concentration to 30 or 48% significantly (P < 0.05) reduced viscosity. When the α-lactalbumin content was increased to 48% as a percentage of the total protein, heating before or after emulsion formation had no effect on concentrate viscosity. The findings demonstrate the importance of thermal denaturation/aggregation of whey proteins (and in particular, the ratio of α-lactalbumin to β-lactoglobulin) prior to homogenisation of infant formula emulsions

Poly(ethylene glycol)-Based Peptidomimetic “PEGtide” of Oligo-Arginine allows for efficient siRNA Transfection and gene inhibition

While a wide range of experimental and commercial transfection reagents are currently available, persistent problems remain regarding their suitability for continued development. These include the transfection efficiency for difficult-to-transfect cell types and the risks of decreased cell viability that may arise from any transfection that does occur. Therefore, research is now turning toward alternative molecules that improve the toxicity profile of the gene delivery vector (GDV), while maintaining the transfection efficiency. Among them, cell-penetrating peptides, such as octa-arginine, have shown significant potential as GDVs. Their pharmacokinetic and pharmacodynamic properties can be enhanced through peptidomimetic conversion, whereby a peptide is modified into a synthetic analogue that mimics its structure and/or function, but whose backbone is not solely based on α-amino acids. Using this technology, novel peptidomimetics were developed by co- and postpolymerization functionalization of substituted ethylene oxides, producing poly(ethylene glycol) (PEG)-based peptidomimetics termed “PEGtides”. Specifically, a PEGtide of the poly(α-amino acid) oligo-arginine [poly(glycidylguanidine)] was assessed for its ability to complex and deliver a small interfering ribonucleic acid (siRNA) using a range of cell assays and high-content analysis. PEGtide–siRNA demonstrated significantly increased internalization and gene inhibition over 24 h in Calu-3 pulmonary epithelial cells compared to commercial controls and octa-arginine-treated samples, with no evidence of toxicity. Furthermore, PEGtide–siRNA nanocomplexes can provide significant levels of gene inhibition in “difficult-to-transfect” mouse embryonic hypothalamic (mHypo N41) cells. Overall, the usefulness of this novel PEGtide for gene delivery was clearly demonstrated, establishing it as a promising candidate for continued translational research

Randomised controlled trial of an intervention to improve parental knowledge and management practices of fever

Background: We know that parents require resources which can assist them to improve fever knowledge and management practices. The purpose of this study, using an RCT, was to examine the effectiveness of an information leaflet at increasing parental knowledge of fever, specifically temperature definition. Methods: A prospective, multi-centre, randomised, two-parallel arm, controlled trial with blinded outcome ascertainment was conducted. Parents presenting at purposively selected healthcare facilities who had a child aged ≤5 years of age were invited to participate. An information leaflet for use in the trial was designed based on previous studies with parents. Parents in the intervention arm read an information leaflet on fever and management of fever in children, completed a short questionnaire at Time 1 (T1) and again 2 weeks after randomisation at Time 2 (T2). Parents in the control arm did not receive the fever information leaflet but completed the same questionnaire as the intervention arm at T1 and againat T2. The primary outcome was the correct definition of fever (higher than ≥38 °C). Results: A total of 100 parents participated in the study at T1. A greater proportion of the intervention group (76%) than the control group (28%) selected the correct temperature (≥38 °C) at T1. 76% of the intervention arm correctly identified “higher than ≥38°C” as the temperature at which a fever is said to be present compared to 28% of the control arm. After 2 weeks, there was an increase of 6% of parents in the intervention arm (increase to 82.4%) who gave the correct temperature compared to just a 2.8% increase in the control arm (increase to 30.8%). Univariate logistic regression showed that parents in the intervention arm were significantly more likely to give the correct answer at both time-points (T1: OR 8.1; CI 95% 3.3–19.9: p < 0.01; T2: OR 10.5; CI 95% 3.4–32.0: p < 0.01). Conclusions: Our RCT of this simple educational intervention has been shown to improve parental understanding of fever knowledge and correct management strategies. Education interventions providing simple, clear information is a key step to decreasing parental mismanagement of fever and febrile illness in children