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| 2. |
- 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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| 3. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 4. |
- Klionsky, Daniel J., et al.
(författare)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Forskningsöversikt (refereegranskat)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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| 6. |
- Sampson, Joshua N., et al.
(författare)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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| 7. |
- Ablikim, M., et al.
(författare)
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Amplitude analysis of D0 → K -π+π+π-
- 2017
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Ingår i: Physical Review D. - 2470-0010 .- 2470-0029. ; 95:7
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Tidskriftsartikel (refereegranskat)abstract
- We present an amplitude analysis of the decay D0 → K -π+π+π- based on a data sample of 2.93 fb−1 acquired by the BESIII detector at the ψ(3770) resonance. With a nearly background free sample of about 16000 events, we investigate the substructure of the decay and determine the relative fractions and the phases among the different intermediate processes. Our amplitude model includes the two-body decays D0 → ¯K*0ρ0, D0 → K−a+1(1260) and D0 → K−1(1270)π+, the three-body decays D0 →¯K*0π+π− and D0 → K−π+ρ0, as well as the four-body nonresonant decay D0 → K−π+π+π−. The dominant intermediate process is D0 → K−a+1(1260), accounting for a fit fraction of 54.6%.
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| 8. |
- Ablikim, M., et al.
(författare)
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Branching fraction measurement of J/ψ→KSKL and search for J/ψ→KSKS
- 2017
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Ingår i: Physical Review D. - 2470-0010 .- 2470-0029. ; 96:11
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Tidskriftsartikel (refereegranskat)abstract
- Using a sample of 1.31 x 10(9) J/Psi events collected with the BESIII detector at the BEPCII collider, we study the decays of J/Psi -> KSKL and KSKS. The branching fraction of J/Psi -> KSKL is determined to be B(J/Psi -> KSKL) = (1.93 +/- 0.01 (stat) +/- 0.05 (syst)) x 10(-4), which significantly improves on previous measurements. No clear signal is observed for the J/Psi -> KSKS process, and the upper limit at the 95% confidence level for its branching fraction is determined to be B(J/Psi -> KSKS) < 1.4 x 10(-8), which improves on the previous searches by 2 orders in magnitude and reaches the order of the Einstein-Podolsky-Rosen expectation.
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| 9. |
- Ablikim, M., et al.
(författare)
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Determination of the Spin and Parity of the Z(c)(3900)
- 2017
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Ingår i: Physical Review Letters. - : AMER PHYSICAL SOC. - 0031-9007 .- 1079-7114. ; 119:7
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Tidskriftsartikel (refereegranskat)abstract
- The spin and parity of the Z(c)(3900)(+/-) state are determined to be J(P) = 1(+) with a statistical significance larger than 7 sigma over other quantum numbers in a partial wave analysis of the process e(+)e(-) -> pi(+)pi(-) J/psi We use a data sample of 1.92 fb(-1) accumulated at root s = 4.23 and 4.26 GeV with the BESIII experiment. When parametrizing the Z(c)(3900)(+/-) with a Flatte-like formula, we determine its pole mass M-pole = (3881.2 +/- 4.2(stat) +/- 52.7(syst)) MeV/c(2) and pole width Gamma(pole) = (51.8 +/- 4.6(stat) +/- 36.0(syst)) MeV. We also measure cross sections for the process e(+)e(-) -> Z(c)(3900)(+)pi(-) + c.c. -> J/psi pi(+)pi(-) and determine an upper limit at the 90% confidence level for the process e(+)e(-) -> Z(c)(4020)(+)pi(-) + c.c. -> J/psi pi(+)pi(-).
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| 10. |
- Ablikim, M., et al.
(författare)
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Evidence for e+e−→γηc(1S) at center-of-mass energies between 4.01 and 4.60 GeV
- 2017
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Ingår i: Physical Review D. - 2470-0010 .- 2470-0029. ; 96:5
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Tidskriftsartikel (refereegranskat)abstract
- We present first evidence for the process e(+)e(-) -> gamma eta(c)(1S) at six center-of-mass energies between 4.01 and 4.60 GeV using data collected by the BESIII experiment operating at BEPCII. We measure the Born cross section at each energy using a combination of twelve eta(c)(1S) decay channels. We also combine all six energies under various assumptions for the energy-dependence of the cross section. If the process is assumed to proceed via the Y(4260), we measure a peak Born cross section sigma(peak)(e(+)e(-) -> gamma eta(c)(1S)) = 2.11 +/- 0.49 (stat.) +/- 0.36 (syst.) pb with a statistical significance of 4.2 sigma.
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