The ilvIH operon of Escherichia coli K-12. Identification of the gene products and recognition of the translational start by polypeptide microsequencing

The ilvI and ilvH gene products were identified physically by electrophoretic analysis of in vivo-labelled polypeptides produced in minicells from plasmids carrying the wild-type ilvIH operon of Escherichia coli K-12 and derivatives of it. An analysis of the distribution of methionine residues in the amino-terminal portion of micro-quantities of the ilvI product eluted from gel showed that the translational start of the ilvI gene is the promoter-proximal one of three putative methionine codons predicted from the DNA sequence.     

The metalloproteinase ADAM‐12 regulates bronchial epithelial cell proliferation and apoptosis

Abstract. Objectives: The ADAMs (a disintegrin and metalloproteinase) enzymes compose a family of membrane‐bound proteins characterized by their multi‐domain structure and ADAM‐12 expression is elevated in human non‐small cell lung cancers. The aim of this study was to investigate the roles played by ADAM‐12 in critical steps of bronchial cell transformation during carcinogenesis. Materials and methods: To assess the role of ADAM‐12 in tumorigenicity, BEAS‐2B cells were transfected with a plasmid encoding human full‐length ADAM‐12 cDNA, and then the effects of ADAM‐12 overexpression on cell behaviour were explored. Treatment of clones with heparin‐binding epidermal growth factor (EGF)‐like growth factor (HB‐EGF) neutralizing antibodies as well as an EGFR inhibitor allowed the dissection of mechanisms regulating cell proliferation and apoptosis. Results: Overexpression of ADAM‐12 in BEAS‐2B cells promoted cell proliferation. ADAM‐12 overexpressing clones produced higher quantities of HB‐EGF in their culture medium which may rely on membrane‐bound HB‐EGF shedding by ADAM‐12. Targeting HB‐EGF activity with a neutralizing antibody abrogated enhanced cell proliferation in the ADAM‐12 overexpressing clones. In sharp contrast, targeting of amphiregulin, EGF or transforming growth factor‐α failed to influence cell proliferation; moreover, ADAM‐12 transfectants were resistant to etoposide‐induced apoptosis and the use of a neutralizing antibody against HB‐EGF activity restored rates of apoptosis to be similar to controls.Conclusions: ADAM‐12 contributes to enhancing HB‐EGF shedding from plasma membranes leading to increased cell proliferation and reduced apoptosis in this bronchial epithelial cell line.     

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.