1,721,371 research outputs found
Oocyte maturation <i>in vitro</i> is comparable between <i>Wee2</i><sup><i>+/-21878</i></sup> HET and <i>Wee2</i><sup><i>-21878/-21878</i></sup> KO mice.
(A-C) (GV) stage oocytes were collected from Wee2+/-21878 HET (n = 6) and Wee2-21878/-21878 KO mice (n = 6) 46 hours following PMSG stimulation and cultured in medium containing dibutyryl-cAMP (dbcAMP) to maintain high intraoocyte cAMP levels and maintain GV arrest. The occurrence of germinal vesicle breakdown (GVBD) was measured 24 hours after incubation dbcAMP and 24 h after removal of dbcAMP. No differences were observed in the rate of GVBD between the two genotypes when incubated in the presence or absence of dbcAMP. Representative images of oocytes from Wee2+/-21878 HET and Wee2-21878/-21878 KO mice following incubation without dbcAMP.</p
Quantification of WEE-related kinases, <i>Wee2</i>, <i>Myt1 and Wee1</i>, in the ovaries of <i>Wee2</i><sup><i>+/-21878</i></sup> HET and <i>Wee2</i><sup><i>21878/-21878</i></sup> mice.
(A-C) Gene expression analysis of Wee2 (A), Myt1 (B), and Wee1 (C) transcripts in WT (n = 3), Wee2+/-21878 HETs (n = 3), and Wee2-21878/-21878 KO mouse ovaries (n = 3). Gapdh was used as an internal control. Data in histograms represent average fold change ± standard error of the mean. Analyzed by a one-way ANOVA with a Dunnet’s post-test. 0.033 (*), 0.002 (**), <0.001 (***).</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
<i>Wee2</i> KO causes female subfertility.
(A) Average litter size, (B) litters per female, and (C) pups per female of Wee2 HET and Wee2-21878/-21878 KO female mice mated to WT males over the course of a 6-month fertility trial. Fertility data are also displayed as (D) the average number of pups per month. (E) Body mass average of Wee2 HET and Wee2-21878/-21878 KO female mice. (F) Average weight of individual ovaries from Wee2 HET and Wee2-21878/-21878 KO female mice. (G) Average number of ovulated oocytes from Wee2 HET and Wee2-21878/-21878 KO female mice following superovulation with PMSG and hCG. Data in histograms represent average ± standard error of the mean. Analyzed by an unpaired t-test, * = 0.04.</p
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