Effect of azole fungicide mixtures, alternations and dose on azole sensitivity in the wheat pathogen Zymoseptoria tritici

The evolution of fungicide resistance in the cereal pathogen Zymoseptoria tritici, is a serious threat to the sustainability and profitability of wheat production in Europe. Application of azole fungicides has been shown to affect fitness of Z. tritici variants differentially, so it has been hypothesised that combinations of azoles could slow the evolution of resistance. This work was initiated to assess the effects of dose, mixtures and alternations of two azoles on selection for isolates with reduced sensitivity and on disease control. Naturally infected field trials were carried out at six sites across Ireland and the sensitivity of Z. tritici isolates monitored pre- and post-treatment. The azoles epoxiconazole and metconazole were applied as solo products, in alternation with each other and as a pre-formulated mixture. Full and half label doses were tested. The two azoles were partially cross-resistant, with a common azole resistance principal component accounting for 75% of the variation between isolates. Selection for isolates with reduced azole sensitivity was correlated with disease control. Decreased doses were related to decreases in sensitivity but the effect was barely significant (P = 0.1) and control was reduced. Single applications of an active ingredient (a.i.) caused smaller decreases in sensitivity than double applications. Shifts in sensitivity to the a.i. applied to a plot were greater than to the a.i. not applied, and the decrease in sensitivity was greater to the a.i. applied at the second timing. These results confirm the need to mix a.i.s with different modes of action.

Exploding explicatures

‘Pragmaticist’ positions posit a three-way division within utterance content between: (i) the standing meaning of the sentence, (ii) a somewhat pragmatically enhanced meaning which captures what the speaker explicitly conveys (following Sperber and Wilson 1986, I label this the ‘explicature’), and (iii) further indirectly conveyed propositions which the speaker merely implies. Here I re-examine the notion of an explicature, asking how it is defined and what work explicatures are supposed to do. I argue that explicatures get defined in three different ways and that these distinct definitions can and do pull apart. Thus the notion of an explicature turns out to be ill-defined.

A self-assembling fluorescent dipeptide conjugate for cell labelling

Derivatives of fluorophore FITC (fluorescein isothiocyanate) are widely used in bioassays to label proteins and cells. An N-terminal leucine dipeptide is attached to FITC, and we show that this simple conjugate molecule is cytocompatible and is uptaken by cells (human dermal and corneal fibroblasts) in contrast to FITC itself. Co-localisation shows that FITC-LL segregates in peri-nuclear and intracellular vesicle regions. Above a critical aggregation concentration, the conjugate is shown to self-assemble into beta-sheet nanostructures comprising molecular bilayers.

Cannabinoids and epilepsy

Cannabis has been used for centuries to treat seizures. Recent anecdotal reports, accumulating animal model data, and mechanistic insights have raised interest in cannabis-based antiepileptic therapies. In this study, we review current understanding of the endocannabinoid system, characterize the pro- and anticonvulsive effects of cannabinoids [e.g., Δ9-tetrahydrocannabinol and cannabidiol (CBD)], and high-light scientific evidence from pre-clinical and clinical trials of cannabinoids in epilepsy. These studies suggest that CBD avoids the psychoactive effects of the endocannabinoid system to provide a well-tolerated, promising therapeutic for the treatment of seizures, while whole-plant cannabis can both contribute to and reduce seizures. Finally, we discuss results from a new multicenter, open-label study using CBD in a population with treatment-resistant epilepsy. In all, we seek to evaluate our current understanding of cannabinoids in epilepsy and guide future basic science and clinical studies.

A role for adhesion and degranulation-promoting adapter protein in collagen-induced platelet activation mediated via integrin α(2) β(1)

Platelet aggregation and phosphorylation of phospholipase Cγ2 induced by collagen were attenuated in ADAP(-/-) platelets. However, aggregation and signaling induced by collagen-related peptide (CRP), a GPVI-selective agonist, were largely unaffected. Platelet adhesion to CRP was also unaffected by ADAP deficiency. Adhesion to the α(2) β(1) -selective ligand GFOGER and to a peptide (III-04), which supports adhesion that is dependent on both GPVI and α(2) β(1), was reduced in ADAP(-/-) platelets. An impedance-based label-free detection technique, which measures adhesion and spreading of platelets, indicated that, in the absence of ADAP, spreading on GFOGER was also reduced. This was confirmed with non-fluorescent differential-interference contrast microscopy, which revealed reduced filpodia formation in ADAP(-/-) platelets adherent to GFOGER. This indicates that ADAP plays a role in mediating platelet activation via the collagen-binding integrin α(2) β(1). In addition, we found that ADAP(-/-) mice, which are mildly thrombocytopenic, have enlarged spleens as compared with wild-type animals. This may reflect increased removal of platelets from the circulation.

Big data: a normal accident waiting to happen?

Widespread commercial use of the internet has significantly increased the volume and scope of data being collected by organisations. ‘Big data’ has emerged as a term to encapsulate both the technical and commercial aspects of this growing data collection activity. To date, much of the discussion of big data has centred upon its transformational potential for innovation and efficiency, yet there has been less reflection on its wider implications beyond commercial value creation. This paper builds upon normal accident theory (NAT) to analyse the broader ethical implications of big data. It argues that the strategies behind big data require organisational systems that leave them vulnerable to normal accidents, that is to say some form of accident or disaster that is both unanticipated and inevitable. Whilst NAT has previously focused on the consequences of physical accidents, this paper suggests a new form of system accident that we label data accidents. These have distinct, less tangible and more complex characteristics and raise significant questions over the role of individual privacy in a ‘data society’. The paper concludes by considering the ways in which the risks of such data accidents might be managed or mitigated.

Cocoa flavanol intake improves endothelial function and Framingham Risk Score in healthy men and women: a randomised, controlled, double-masked trial: the Flaviola Health Study

Cocoa flavanol (CF) intake improves endothelial function in patients with cardiovascular risk factors and disease. We investigated the effects of CF on surrogate markers of cardiovascular health in low risk, healthy, middle-aged individuals without history, signs or symptoms of CVD. In a 1-month, open-label, one-armed pilot study, bi-daily ingestion of 450 mg of CF led to a time-dependent increase in endothelial function (measured as flow-mediated vasodilation (FMD)) that plateaued after 2 weeks. Subsequently, in a randomised, controlled, double-masked, parallel-group dietary intervention trial (Clinicaltrials.gov: NCT01799005), 100 healthy, middle-aged (35–60 years) men and women consumed either the CF-containing drink (450 mg) or a nutrient-matched CF-free control bi-daily for 1 month. The primary end point was FMD. Secondary end points included plasma lipids and blood pressure, thus enabling the calculation of Framingham Risk Scores and pulse wave velocity. At 1 month, CF increased FMD over control by 1·2 % (95 % CI 1·0, 1·4 %). CF decreased systolic and diastolic blood pressure by 4·4 mmHg (95 % CI 7·9, 0·9 mmHg) and 3·9 mmHg (95 % CI 6·7, 0·9 mmHg), pulse wave velocity by 0·4 m/s (95 % CI 0·8, 0·04 m/s), total cholesterol by 0·20 mmol/l (95 % CI 0·39, 0·01 mmol/l) and LDL-cholesterol by 0·17 mmol/l (95 % CI 0·32, 0·02 mmol/l), whereas HDL-cholesterol increased by 0·10 mmol/l (95 % CI 0·04, 0·17 mmol/l). By applying the Framingham Risk Score, CF predicted a significant lowering of 10-year risk for CHD, myocardial infarction, CVD, death from CHD and CVD. In healthy individuals, regular CF intake improved accredited cardiovascular surrogates of cardiovascular risk, demonstrating that dietary flavanols have the potential to maintain cardiovascular health even in low-risk subjects.

Multiprobabilistic prediction in early medical diagnoses

This paper describes the methodology of providing multiprobability predictions for proteomic mass spectrometry data. The methodology is based on a newly developed machine learning framework called Venn machines. Is allows to output a valid probability interval. The methodology is designed for mass spectrometry data. For demonstrative purposes, we applied this methodology to MALDI-TOF data sets in order to predict the diagnosis of heart disease and early diagnoses of ovarian cancer and breast cancer. The experiments showed that probability intervals are narrow, that is, the output of the multiprobability predictor is similar to a single probability distribution. In addition, probability intervals produced for heart disease and ovarian cancer data were more accurate than the output of corresponding probability predictor. When Venn machines were forced to make point predictions, the accuracy of such predictions is for the most data better than the accuracy of the underlying algorithm that outputs single probability distribution of a label. Application of this methodology to MALDI-TOF data sets empirically demonstrates the validity. The accuracy of the proposed method on ovarian cancer data rises from 66.7 % 11 months in advance of the moment of diagnosis to up to 90.2 % at the moment of diagnosis. The same approach has been applied to heart disease data without time dependency, although the achieved accuracy was not as high (up to 69.9 %). The methodology allowed us to confirm mass spectrometry peaks previously identified as carrying statistically significant information for discrimination between controls and cases.