Stable isotope dilution assay for the accurate determination of mycotoxins in maize by UHPLC-MS/MS

A fast, easy-to-handle and cost-effective analytical method for 11 mycotoxins currently regulated in maize and other cereal-based food products in Europe was developed and validated for maize. The method is based on two extraction steps using different acidified acetonitrile–water mixtures. Separation is achieved using ultrahigh-performance liquid chromatography (UHPLC) by a linear water–methanol gradient. After electrospray ionisation, tandem mass spectrometric detection is performed in dynamic multiple reaction monitoring mode. Since accurate mass spectrometric quantification is hampered by matrix effects, uniformly [13C]-labelled mycotoxins for each of the 11 compounds were added to the sample extracts prior to UHPLC-MS/MS analysis. Method performance parameters were obtained by spiking blank maize samples with mycotoxins before as well as after extraction on six levels in triplicates. The twofold extraction led to total recoveries of the extraction steps between 97% and 111% for all target analytes, including fumonisins. The [13C]-labelled internal standards efficiently compensated all matrix effects in electrospray ionisation, leading to apparent recoveries between 88% and 105% with reasonable additional costs. The relative standard deviations of the whole method were between 4% and 11% for all analytes. The trueness of the method was verified by the measurement of several maize test materials with well-characterized concentrations. In conclusion, the developed method is capable of determining all regulated mycotoxins in maize and presuming similar matrix effects and extraction recovery also in other cereal-based foods

Cost effectiveness of support for people starting a new medication for a long term condition through community pharmacies: an economic evaluation of the New Medicine Service (NMS) compared with normal practice

Background: The English community pharmacy New Medicine Service (NMS) significantly increases patient adherence to medicines, compared with normal practice. We examined the cost-effectiveness of NMS compared with normal practice by combining adherence improvement and intervention costs with the effect of increased adherence on patient outcomes and healthcare costs. Methods: We developed Markov models for diseases targeted by the NMS (hypertension, type 2 diabetes, chronic obstructive pulmonary disease, asthma and antiplatelet regimens) to assess the impact of patients’ non-adherence. Clinical event probability, treatment pathway, resource-use and costs were extracted from literature and costing tariffs. Incremental costs and outcomes associated with each disease were incorporated additively into a composite probabilistic model and combined with adherence rates and intervention costs from the trial. Costs per extra quality-adjusted-life-year(QALY) were calculated from the perspective of NHS England, using a lifetime horizon. Results: NMS generated a mean of 0.05 (95%CI: 0.00, 0.13) more QALYs per patient, at a mean reduced cost of -£144 (95%CI: -769, 73). The NMS dominates normal practice with probability of 0.78 (ICER: - £3166 per QALY). NMS has a 96.7% probability of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Sensitivity analysis demonstrated that targeting each disease with NMS has a probability over 0.90 of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Conclusions: Our study suggests that the New Medicine Service increased patient medicine adherence compared with normal practice, which translated into increased health gain at reduced overall cost

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Unbiased quantitative proteomics reveals a crucial role of the allergen context for the activation of human dendritic cells

Worldwide, more than 1 billion people suffer from allergic diseases. However, until now it is not fully understood how certain proteins can induce allergic immune responses, while others cannot. Studies suggest that allergenicity is a process not only determined by properties of the allergen itself but also by costimulatory factors, that are not classically associated with allergic reactions. To investigate the allergenicity of the major birch pollen allergen Bet v 1 and the impact of adjuvants associated with pollen, e.g. lipopolysaccharide (LPS), we performed quantitative proteome analysis to study the activation of monocyte-derived dendritic cells (moDCs). Thus, we treated cells with birch pollen extract (BPE), recombinant Bet v 1, and LPS followed by proteomic profiling via high-performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) using isobaric labelling. Enrichment and pathway analysis revealed the influence of regulated proteins especially in cytokine signalling and dendritic cell activation. We found highly regulated, but differentially expressed proteins after treatment with BPE and LPS, whereas the cellular response to Bet v 1 was limited. Our findings lead to the conclusion that Bet v 1 needs a specific "allergen context" involving cofactors apart from LPS to induce an immune response in human moDCs.P25696(VLID)238295