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Background Introns have been shown to be spliced in a defined order, and this order influences both alternative splicing regulation and splicing fidelity, but previous studies have only considered neighbouring introns. The detailed intron splicing order remains unknown. Results In this work, a method was developed that can calculate the intron splicing orders of all introns in each transcript. A simulation study showed that this method can accurately calculate intron splicing orders. I further applied this method to real S. pombe , fruit fly, Arabidopsis thaliana , and human sequencing datasets and found that intron splicing orders change from gene to gene and that humans contain more not in-order spliced transcripts than S. pombe , fruit fly and Arabidopsis thaliana . In addition, I reconfirmed that the first introns in humans are spliced slower than those in S. pombe , fruit fly, and Arabidopsis thaliana genome-widely. Both the calculated most likely orders and the method developed here are available on the web. Conclusions A novel computational method was developed to calculate the intron splicing orders and applied the method to real sequencing datasets. I obtained intron splicing orders for hundreds or thousands of genes in four organisms. I found humans contain more number of not in-order spliced transcripts.

When multiple adjectives precede a noun in English, they are often ordered in a way that is implicitly understood by all fluent speakers of the language. Adjective order might be described as a big fat deal , but to describe it as a fat big deal betrays a lack of knowledge of English. Sweet ( A New English Grammar: Part II, 1898/ 1955 ) proposed two related semantic principles to explain the phenomenon: definiteness of denotation (adjectives that denote a property that is most independent of the modified noun must be placed furthest from that noun) and closeness of adjective/noun in meaning (adjectives that denote properties essential to or inherent in the modified noun are placed closer to the noun). These observational descriptions of the phenomenon have received experimental support (Martin, Journal of Verbal Learning and Verbal Behavior, 8 (6), 697–704, 1969 ). However, the issue of why Sweet’s rules are true has not yet been solved. I propose, operationalize, test, and find strong support for a simple theory: that prenominal adjective order reflects likely need , the a priori probability that a particular adjective will be needed.

A combination of pharmacological and genetic approaches was used to determine the role of type 4 cAMP-specific cyclic nucleotide phosphodiesterase 4 (PDE4) in reversing alpha(2)-adrenoceptor-mediated anesthesia, a behavioral correlate of emesis in non-vomiting species. Among the family-specific PDE inhibitors, PDE4 inhibitors reduced the duration of xylazine/ketamine-induced anesthesia in mice, with no effect on pentobarbital-induced anesthesia. The rank order of the PDE4 inhibitors tested was 6-(4-pyridylmethyl)-8-(3-nitrophenyl)quinoline (PMNPQ) > (R)-rolipram > (S)-rolipram >> (R)-N-[4-[1-(3-cyclopentyloxy-4-methoxyphenyl)-2-(4-pyridyl)ethyl]phenyl]N'-ethylurea (CT-2450). The specific roles of PDE4B and PDE4D in this model were studied using mice deficient in either subtype. PDE4D-deficient mice, but not PDE4B-deficient mice, had a shorter sleeping time than their wild-type littermates under xylazine/ketamine-induced anesthesia, but not under that induced with pentobarbital. Concomitantly, rolipram-sensitive PDE activity in the brain stem was decreased only in PDE4D-deficient mice compared with their wild-type littermates. While PMNPQ significantly reduced the xylazine/ketamine-induced anesthesia period in wild-type mice and in PDE4B-null mice, it had no effect in PDE4D-deficient mice. These findings strongly support the hypothesis that inhibition of PDE4D is pivotal to the anesthesia-reversing effect of PMNPQ and is likely responsible for emesis induced by PDE4 inhibitors.

This chapter contains sections titled: The Language of the Septuagint A Semitic Interlude The Language of the New Testament Further Reading

This chapter contains sections titled: Introduction About Probability Problems Equally Likely Possible Outcomes Conditional Probability Conditional Probability Distributions Independent Events Classes of Independent Events Possible Outcomes Represented as Ordered k‐Tuples Product Experiments and Product Spaces Product Probability Spaces Dependence Between the Components in an Ordered k‐Tuple Multiple Observations Without Regard to Order Unordered Sampling with Replacement More Complicated Discrete Probability Problems Uncertainty and Randomness Fuzziness Summary