Modified spinning black holes

In the context of f(R) modified gravity theories we determine that the black holes existence is determined by the sign of a parameter dependent of the mass, the charge, the spin and the scalar curvature. We obtain the different astrophysical objects derived from the presence of different horizons. Thermodynamics for this kind of black holes is studied for negative values of the curvature, revealing that we can distinguish between two kinds of BH: fast and slow.Comment: 4 pages, 6 figures, Contribution to the ERE2011 Spanish Relativity Meeting, Madrid 201

EXOSC10 is required for RPA assembly and controlled DNA end resection at DNA double-strand breaks

The exosome is a ribonucleolytic complex that plays important roles in RNA metabolism. Here we show that the exosome is necessary for the repair of DNA double-strand breaks (DSBs) in human cells and that RNA clearance is an essential step in homologous recombination. Transcription of DSB-flanking sequences results in the production of damage-induced long non-coding RNAs (dilncRNAs) that engage in DNA-RNA hybrid formation. Depletion of EXOSC10, an exosome catalytic subunit, leads to increased dilncRNA and DNA-RNA hybrid levels. Moreover, the targeting of the ssDNA-binding protein RPA to sites of DNA damage is impaired whereas DNA end resection is hyper-stimulated in EXOSC10-depleted cells. The DNA end resection deregulation is abolished by transcription inhibitors, and RNase H1 overexpression restores the RPA recruitment defect caused by EXOSC10 depletion, which suggests that RNA clearance of newly synthesized dilncRNAs is required for RPA recruitment, controlled DNA end resection and assembly of the homologous recombination machinery.España, Ministerio de Economía y Competitividad R + D + I project grant SAF2016-74855-P to P.

MeSH indexing based on automatically generated summaries

BACKGROUND: MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. RESULTS: We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. CONCLUSIONS: Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading