Effects of atmospheric ozone on microarray data quality

A data anomaly was observed that affected the uniformity and reproducibility of fluorescent signal across DNA microarrays. Results from experimental sets designed to identify potential causes (from microarray production to array scanning) indicated that the anomaly was linked to a batch process; further work allowed us to localize the effect to the posthybridization array stringency washes. Ozone levels were monitored and highly correlated with the batch effect. Controlled exposures of microarrays to ozone confirmed this factor as the root cause, and we present data that show susceptibility of a class of cyanine dyes (e.g., Cy5, Alexa 647) to ozone levels as low as 5-10 ppb for periods as short as 10-30 s. Other cyanine dyes (e.g., Cy3, Alexa 555) were not significantly affected until higher ozone levels (> 100 ppb). To address this environmental effect, laboratory ozone levels should be kept below 2 ppb (e.g., with filters in HVAC) to achieve high quality microarray data.     

Synthesis of carbon-nitride films using a fast-switched dual-source low energy ion beam deposition system

Thin C_xN_y films were deposited in UHV using alternating low energy ion beams of C⁺ and N⁺ or N₂⁺ in the energy range of 5 to 100 eV. The ion beam deposition system is equipped with two Freeman ion sources, mass analysis and fast automated beam switching, allowing perpendicular bombardment of the target with a single ion beam at a time. The composition and density of the films were studied by ARS (in situ), XPS and RBS. The dependence of the film properties and growth mechanisms on ion energy, beam switching rate, and C-to-N arrival ratio have been investigated. The influence of the deposition parameters on the film stoichiometry is discussed. Exposure of the film to atmosphere leads to oxygen incorporation, resulting in a lowered surface concentration of nitrogen. The XPS N 1s and C Is binding energies vary in a relatively broad range indicating that several bond states may be present. The influence of the substrate material on film growth has also been studied. On Si{100}, film growth commences with the formation of an interfacial silicon nitride. No film growth was observed on gold, however deposition was possible on tantalum and molybdenum.     

Amygdaloid lesion increases the toxicity of intrahippocampal kainic acid injection and reduces the late occurrence of spontaneous recurrent seizures in rats

Spontaneous recurrent seizures (SRS) following intrahippocampal kainic acid (KA) injection have been described in a previous paper from our laboratory. The SRSs are clinically similar to the seizures induced by kindling the amygdala and we suggested that the amygdala plays a role in initiating the SRSs. Accordingly, the present paper examines the effect of amygdaloid lesions on intrahippocampal KA-treated rats. There were short- and long-term effects. (1) Short-term: the toxicity of KA was increased in lesioned animals. Status epilepticus followed by death of the animals was evoked with half of the dose required to cause the same effect in intact rats. Moreover, a gross haematuria was encountered 6-12 h after KA injection. This was not observed in non-lesioned rats even following the highest KA doses. (2) Long-term: amygdaloid lesions delayed the occurrence of the SRSs, reduced their incidence and modified their expression. In lesioned animals seizures began with a period of tonic immobility with no sign of the masticatory movements seen in intact animals. Histological examination of the KA-induced lesions did not show any major differences between lesioned and intact animals. It is suggested that the short-term effects are due to an unspecific effect on homeostatic mechanisms, whereas the long-term ones reflect a specific involvement of the amygdala in the late appearing seizures.     

Soft syntactic constraints for Arabic–English hierarchical phrase-based translation

In adding syntax to statistical machine translation, there is a tradeoff between taking advantage of linguistic analysis and allowing the model to exploit parallel training data with no linguistic analysis: translation quality versus coverage. A number of previous efforts have tackled this tradeoff by starting with a commitment to linguistically motivated analyses and then finding appropriate ways to soften that commitment. We present an approach that explores the tradeoff from the other direction, starting with a translation model learned directly from aligned parallel text, and then adding soft constituent-level constraints based on parses of the source language. We argue that in order for these constraints to improve translation, they must be fine-grained: the constraints should vary by constituent type, and by the type of match or mismatch with the parse. We also use a different feature weight optimization technique, capable of handling large amount of features, thus eliminating the bottleneck of feature selection. We obtain substantial improvements in performance for translation from Arabic to English.