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| 2. |
- 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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| 3. |
- Ablikim, M., et al.
(författare)
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Search for eta(c)(2S)h(c) -> p(p)over-bar decays and measurements of the chi(cJ) -> p(p)over-bar branching fractions
- 2013
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Ingår i: Physical Review D. - 1550-7998 .- 1550-2368. ; 88:11, s. 112001-
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Tidskriftsartikel (refereegranskat)abstract
- Using a sample of 1.06 x 10(8)psi(3686) events collected with the BESIII detector at BEPCII, the decays eta(c)(2S) -> p (p) over bar and h(c) -> p (p) over bar are searched for, where eta(c)(2S) and h(c) are reconstructed in the decay chains psi(3686) -> gamma eta(c)(2S), eta(c)(2S) -> p (p) over bar and psi(3686) -> pi(0)h(c), h(c) -> p (p) over bar, respectively. No significant signals are observed. The upper limits of the product branching fractions are determined to be B(psi(3686) -> gamma eta(c)(2S)) x B(eta(c)(2S) -> p (p) over bar) < 1.4 x 10(-6) and B(psi(3686) -> pi(0)h(c)) x B(h(c) -> p<(p)over bar>) < 1.3 x 10(-7) at the 90% C.L.. The branching fractions for chi(cJ) -> p<(p)over bar> (J = 0, 1, 2) are also measured to be (24.5 +/- 0.8 +/- 1.3, 8.6 +/- 0.5 +/- 0.5, 8.4 +/- 0.5 +/- 0.5) x 10(-5), which are the world's most precise measurements.
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| 7. |
- 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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| 8. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 9. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 10. |
- Shi, Tian-Le, et al.
(författare)
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High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar
- 2024
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Ingår i: Plant Physiology. - : Oxford University Press. - 0032-0889 .- 1532-2548. ; 195:1, s. 652-670
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Tidskriftsartikel (refereegranskat)abstract
- Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid “84K” (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.
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