Spore age and coverslip placement affects germination and post-germination development of Colletotrichum dematium var circinans

Spore suspensions from young (10–14 da; young spores) and old (4 mo; old spores) colonies of PColletotrichum dematium var circinans were placed on slides. Coverslips were left off, placed on in the normal manner, or supported on shims. Slides were placed in moist chambers and incubated in light or dark for up to 48 hrs. Germination and post-germination development were studied. Shimming had some beneficial effect on germination, especially for old spores in dark. In general, more germ-tubes and appressoria were produced on spores under shims than spores with other coverslip treatments. By 48 hrs more old spores under shims germinated, and greater numbers of germ-tubes and appressoria were produced than on other old spores under different coverslip treatments. However, numbers produced were lower than those predicted for comparably treated young spores. Spore age, incubation regime, and placement of coverslips did not affect germ-tube initiation. For all treatments more germ-tubes were initiated from spore tops than bottoms or tips. Fewer germ-tubes were initiated from spore centers than other locations on tops and bottoms, and from both tips than one tip. Approximately 26 % of all appressoria were produced sessile. A higher percentage of sessile appressoria were produced on old spores (80 %) than on young spores (20%).     

Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.     

The "Alzheimer's disease signature": potential perspectives for novel biomarkers

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.     

Identification, sequencing and mutagenesis of the gene for a d-carbamoylase from Agrobacterium radiobacter

Abstract A clone positive for d-carbamoylase activity (2.7 kb Hin dIII- Bam H1 DNA fragment) was obtained by screening a genomic library of Agrobacterium radiobacter in Escherichia coli . This DNA fragment contains an open reading frame of 912 bp which is predicted to encode a peptide of 304 amino acids with a calculated molecular mass of 34247 Da. The d-carbamoylase gene. named cauA , was placed under the control of T7 RNA-dependent promoter and expressed in E. coli BL21 (DE3). After induction with isopropyl-thio-β-d-galactopyranoside, the synthesis of d-carbamoylase in E. coli reached about 40% of the total protein. The expressed protein was shown to possess a molecular mass, on SDS-PAGE, of 36 kDa and showed an enhanced allowed us to establish that a Pro¹⁴→Leu¹⁴ exchange leads to an inactive enzyme species, while a Cys²⁷⁹→Ser²⁷⁹ exchange did not impair the functional properties of the enxyme.