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- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 4. |
- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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| 8. |
- Zhang, S. -N, et al.
(författare)
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Introduction to the high energy cosmic-radiation detection (HERD) facility onboard China's future space station
- 2017
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Ingår i: Proceedings of Science. - : Sissa Medialab Srl.
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Konferensbidrag (refereegranskat)abstract
- The High Energy cosmic-Radiation Detection (HERD) facility is one of several space astronomy payloads onboard China's Space Station, which is planned for operation starting around 2025 for about 10 years. The main scientific objectives of HERD are searching for signals of dark matter annihilation products, precise cosmic electron (plus positron) spectrum and anisotropy measurements up to 10 TeV, precise cosmic ray spectrum and composition measurements up to the knee energy, and high energy gamma-ray monitoring and survey. HERD is composed of a 3-D cubic calorimeter (CALO) surrounded by microstrip silicon trackers (STKs) from five sides except the bottom. CALO is made of about 7,500 cubes of LYSO crystals, corresponding to about 55 radiation lengths and 3 nuclear interaction lengths, respectively. The top STK microstrips of six X-Y layers are sandwiched with tungsten converters to make precise directional measurements of incoming electrons and gamma-rays. In the baseline design, each of the four side STKs is made of only three layers microstrips. All STKs will also be used for measuring the charge and incoming directions of cosmic rays, as well as identifying back scattered tracks. With this design, HERD can achieve the following performance: energy resolution of 1% for electrons and gamma-rays beyond 100 GeV and 20% for protons from 100 GeV to 1 PeV; electron/proton separation power better than 10-5; effective geometrical factors of >3 m2sr for electron and diffuse gamma-rays, >2 m2sr for cosmic ray nuclei. R&D is under way for reading out the LYSO signals with optical fiber coupled to image intensified IsCMOS and CALO prototype of 250 LYSO crystals.
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| 10. |
- Ablikim, M., et al.
(författare)
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Observation of the decay psi(3686) -> Lambda(Sigma)over-bar(+/-) pi(-/+) + c.c
- 2013
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Ingår i: Physical Review D. - 1550-7998 .- 1550-2368. ; 88:11, s. 112007-
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Tidskriftsartikel (refereegranskat)abstract
- Using a sample of 1:06 X 10(8) psi(3686) events collected with the BESIII detector, we present the first observation of the decays of psi(3686) -> Lambda(Sigma) over bar (+) pi(-) + c.c. and psi(3686) -> Lambda(Sigma) over bar (-) pi(+) + c.c. The branching fractions are measured to be B(psi(3686) -> Lambda(Sigma) over bar (+) pi(-) + c.c.) = (1.40 +/- 0.03 +/- 0.13) X 10(-4) and B(psi(3686) -> Lambda (Sigma) over bar (-) pi(+) + c.c.) = (1.54 +/- 0.04 +/- 0.13) X 10(-4) where the first errors are statistical and the second ones systematic.
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