York University

About: York University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Politics. The organization has 18899 authors who have published 43357 publications receiving 1568560 citations.

Map-based cloning of a gene controlling omega-3 fatty acid desaturation in Arabidopsis

Abstract: A gene from the flowering plant Arabidopsis thaliana that encodes an omega-3 desaturase was cloned on the basis of the genetic map position of a mutation affecting membrane and storage lipid fatty acid composition. Yeast artificial chromosomes covering the genetic locus were identified and used to probe a seed complementary DNA library. A complementary DNA clone for the desaturase was identified and introduced into roots of both wild-type and mutant plants by Ti plasmid-mediated transformation. Transgenic tissues of both mutant and wild-type plants had significantly increased amounts of the fatty acid produced by this desaturase.

Relative reactivities in vinyl copolymerization

Abstract: From data in the literature on relative rates of copolymerization it has been possible to evaluate two constants, Q and e, characteristic of an individual monomer, which appear to account satisfactorily for its behavior in copolymerization. The constant Q describes the “general monomer reactivity” and is apparently related to possibilities for stabilization in a radical adduct. The constant e takes account of polar factors influencing copolymerization.

Species borders: ecological and evolutionary perspectives

Abstract: Recent ecological studies on species borders have used a number of approaches to establish causation for specific environmental factors and to identify the traits involved. These include interspecific comparisons, detailed investigations of marginal populations, and experimental manipulation. Species borders continue to be largely ignored in evolutionary biology, although some work suggests that marginal populations may often be relatively better-adapted to unfavourable conditions but perform poorly under most other conditions.

The Unengaged Mind: Defining Boredom in Terms of Attention

Abstract: Our central goal is to provide a definition of boredom in terms of the underlying mental processes that occur during an instance of boredom. Through the synthesis of psychodynamic, existential, arousal, and cognitive theories of boredom, we argue that boredom is universally conceptualized as "the aversive experience of wanting, but being unable, to engage in satisfying activity." We propose to map this conceptualization onto underlying mental processes. Specifically, we propose that boredom be defined in terms of attention. That is, boredom is the aversive state that occurs when we (a) are not able to successfully engage attention with internal (e.g., thoughts or feelings) or external (e.g., environmental stimuli) information required for participating in satisfying activity, (b) are focused on the fact that we are not able to engage attention and participate in satisfying activity, and (c) attribute the cause of our aversive state to the environment. We believe that our definition of boredom fully accounts for the phenomenal experience of boredom, brings existing theories of boredom into dialogue with one another, and suggests specific directions for future research on boredom and attention.

Practical recommendations for reporting Fine-Gray model analyses for competing risk data

Abstract: In survival analysis, a competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. Outcomes in medical research are frequently subject to competing risks. In survival analysis, there are 2 key questions that can be addressed using competing risk regression models: first, which covariates affect the rate at which events occur, and second, which covariates affect the probability of an event occurring over time. The cause-specific hazard model estimates the effect of covariates on the rate at which events occur in subjects who are currently event-free. Subdistribution hazard ratios obtained from the Fine-Gray model describe the relative effect of covariates on the subdistribution hazard function. Hence, the covariates in this model can also be interpreted as having an effect on the cumulative incidence function or on the probability of events occurring over time. We conducted a review of the use and interpretation of the Fine-Gray subdistribution hazard model in articles published in the medical literature in 2015. We found that many authors provided an unclear or incorrect interpretation of the regression coefficients associated with this model. An incorrect and inconsistent interpretation of regression coefficients may lead to confusion when comparing results across different studies. Furthermore, an incorrect interpretation of estimated regression coefficients can result in an incorrect understanding about the magnitude of the association between exposure and the incidence of the outcome. The objective of this article is to clarify how these regression coefficients should be reported and to propose suggestions for interpreting these coefficients.