Constraints on Intervening Stellar Populations Toward the Large Magellanic Cloud

The suggestion by Zaritsky & Lin that a vertical extension of the red clump feature in color-magnitude diagrams of the Large Magellanic Cloud (LMC) is consistent with a significant population of foreground stars to the LMC that could account for the observed microlensing optical depth has been challenged by various investigators. We respond by (1) examining each of the challenges presented and (2) presenting new photometric and spectroscopic data. We conclude that although the CMD data do not mandate the existence of a foreground population, they are entirely consistent with a foreground population associated with the LMC that contributes significantly (~ 50%) to the observed microlensing optical depth. From our new data, we conclude that <~ 40% of the VRC stars are young, massive red clump stars because (1) synthetic color-magnitude diagrams created using the star formation history derived indepdently from HST data suggest that < 50% of the VRC stars are young, massive red clump stars, (2) the angular distribution of the VRC stars is more uniform than that of the young (age < 1 Gyr) main sequence stars, and (3) the velocity dispersion of the VRC stars in the region of the LMC examined by ZL is inconsistent with the expectation for a young disk population. Each of these arguments is predicated on assumptions and the conclusions are uncertain. Therefore, an exact determination of the contribution to the microlensing optical depth by the various hypothesized foreground populations, and the subsequent conclusions regarding the existence of halo MACHOs, requires a detailed knowledge of many complex astrophysical issues, such as the IMF, star formation history, and post-main sequence stellar evolution. (abridged)Comment: Scheduled for publication in AJ in May 199

Современная лекарственная терапия и прогностические факторы при хроническом лимфолейкозе. Обзор литературы и собственные данные

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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

Tumor Invasion Optimization by Mesenchymal-Amoeboid Heterogeneity

Metastasizing tumor cells migrate through the surrounding tissue and extracellular matrix toward the blood vessels, in order to colonize distant organs. They typically move in a dense environment, filled with other cells. In this work we study cooperative effects between neighboring cells of different types, migrating in a maze-like environment with directional cue. Using a computerized model, we measure the percentage of cells that arrive to the defined target, for different mesenchymal/amoeboid ratios. Wall degradation of mesenchymal cells, as well as motility of both types of cells, are coupled to metabolic energy-like resource level. We find that indirect cooperation emerges in mid-level energy, as mesenchymal cells create paths that are used by amoeboids. Therefore, we expect to see a small population of mesenchymals kept in a mostly-amoeboid population. We also study different forms of direct interaction between the cells, and show that energy-dependent interaction strength is optimal for the migration of both mesenchymals and amoeboids. The obtained characteristics of cellular cluster size are in agreement with experimental results. We therefore predict that hybrid states, e.g. epithelial-mesenchymal, should be utilized as a stress-response mechanism