Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Evidence implicating Gfi-1 and Pim-1 in pre-T-cell differentiation steps associated with beta-selection.

After rearrangement of the T-cell receptor (TCR) beta-locus, early CD4(-)/CD8(-) double negative (DN) thymic T-cells undergo a process termed 'beta-selection' that allows the preferential expansion of cells with a functional TCR beta-chain. This process leads to the formation of a rapidly cycling subset of DN cells that subsequently develop into CD4(+)/CD8(+) double positive (DP) cells. Using transgenic mice that constitutively express the zinc finger protein Gfi-1 and the serine/threonine kinase Pim-1, we found that the levels of both proteins are important for the correct development of DP cells from DN precursors at the stage where 'beta-selection' occurs. Analysis of the CD25(+)/CD44(-,lo) DN subpopulation from these animals revealed that Gfi-1 inhibits and Pim-1 promotes the development of larger beta-selected cycling cells ('L subset') from smaller resting cells ('E subset') within this subpopulation. We conclude from our data that both proteins, Pim-1 and Gfi-1, participate in the regulation of beta-selection-associated pre-T-cell differentiation in opposite directions and that the ratio of both proteins is important for pre-T-cells to pass the 'E' to 'L' transition correctly during beta-selection

Male and female mice derived from the same embryonic stem cell clone by tetraploid embryo complementation.

We have devised a general strategy for producing female mice from 39,X0 embryonic stem (ES) cells derived from male cell lines carrying a targeted mutation of interest. We show that the Y chromosome is lost in 2% of subclones from 40,XY ES cell lines, making the identification of targeted 39,X0 subclones a routine procedure. After gene targeting, male and female mice carrying the mutation can be generated by tetraploid embryo complementation from the 40,XY ES cell line and its 39,X0 derivatives. A single intercross then produces homozygous mutant offspring. Because this strategy avoids outcrossing and therefore segregation of mutant alleles introduced into the ES cells, the time and expense required for production of experimental mutant animals from a targeted ES cell clone are substantially reduced. Our data also indicate that ES cells have inherently unstable karyotypes, but this instability does not interfere with production of adult ES cell tetraploid mice