Genetic inter-relationships among Chinese wild grapes based on SRAP marker analyses

Sequence-Related Amplified Polymorphism (SRAP) markers were used to assess genetic inter-relationships among 39 grape genotypes. These included 22 indigenous Chinese grape species/varieties, the north American V. riparia and the European V. vinifera L. 'Thompson seedless' and 'Pinot noir'. Of the 72 SRAP primer combinations tested, 25 primers generated 135 reliable bands, with an average of 5.52 bands per primer pair. Further analysis shows that 106 of 135 bands were generated by 25 polymorphic primer pairs, with a polymorphism efficiency of 79 %. The similarity coefficients of SRAP polymorphism varied from 0.463 to 0.981 among the genotypes analysed. A dendrogram analysis divided the 39 Vitis accessions into 21 groups with similarity coefficients of 0.83. It reveals broadly similar genetic relationships among the genotypes examined to those previously determined using classical taxonomic methods. Our results define V. heyneana subsp. ficifolia and V. baihensis as subspecies of V. heyneana and V. bashanica, respectively. We question the placement of V. davidii var. cyanocarpa and V. davidii var. ningqiangensis as varieties in V. davidii

Online Clustering of Bandits with Misspecified User Models

The contextual linear bandit is an important online learning problem where given arm features, a learning agent selects an arm at each round to maximize the cumulative rewards in the long run. A line of works, called the clustering of bandits (CB), utilize the collaborative effect over user preferences and have shown significant improvements over classic linear bandit algorithms. However, existing CB algorithms require well-specified linear user models and can fail when this critical assumption does not hold. Whether robust CB algorithms can be designed for more practical scenarios with misspecified user models remains an open problem. In this paper, we are the first to present the important problem of clustering of bandits with misspecified user models (CBMUM), where the expected rewards in user models can be perturbed away from perfect linear models. We devise two robust CB algorithms, RCLUMB and RSCLUMB (representing the learned clustering structure with dynamic graph and sets, respectively), that can accommodate the inaccurate user preference estimations and erroneous clustering caused by model misspecifications. We prove regret upper bounds of $O(\epsilon_*T\sqrt{md\log T} + d\sqrt{mT}\log T)$ for our algorithms under milder assumptions than previous CB works (notably, we move past a restrictive technical assumption on the distribution of the arms), which match the lower bound asymptotically in $T$ up to logarithmic factors, and also match the state-of-the-art results in several degenerate cases. The techniques in proving the regret caused by misclustering users are quite general and may be of independent interest. Experiments on both synthetic and real-world data show our outperformance over previous algorithms

On-Demand Communication for Asynchronous Multi-Agent Bandits

This paper studies a cooperative multi-agent multi-armed stochastic bandit problem where agents operate asynchronously -- agent pull times and rates are unknown, irregular, and heterogeneous -- and face the same instance of a K-armed bandit problem. Agents can share reward information to speed up the learning process at additional communication costs. We propose ODC, an on-demand communication protocol that tailors the communication of each pair of agents based on their empirical pull times. ODC is efficient when the pull times of agents are highly heterogeneous, and its communication complexity depends on the empirical pull times of agents. ODC is a generic protocol that can be integrated into most cooperative bandit algorithms without degrading their performance. We then incorporate ODC into the natural extensions of UCB and AAE algorithms and propose two communication-efficient cooperative algorithms. Our analysis shows that both algorithms are near-optimal in regret.Comment: Accepted by AISTATS 202

Hyper-Activation of pp60(Src) Limits Nitric Oxide Signaling by Increasing Asymmetric Dimethylarginine Levels During Acute Lung Injury

The molecular mechanisms by which the endothelial barrier becomes compromised during lipopolysaccharide (LPS) mediated acute lung injury (ALI) are still unresolved. We have previously reported that the disruption of the endothelial barrier is due, at least in part, to the uncoupling of endothelial nitric oxide synthase (eNOS) and increased peroxynitrite-mediated nitration of RhoA. The purpose of this study was to elucidate the molecular mechanisms by which LPS induces eNOS uncoupling during ALI. Exposure of pulmonary endothelial cells (PAEC) to LPS increased pp60Src activity and this correlated with an increase in nitric oxide (NO) production, but also an increase in NOS derived superoxide, peroxynitrite formation and 3-nitrotyrosine (3-NT) levels. These effects could be simulated by the over-expression of a constitutively active pp60Src (Y527FSrc) mutant and attenuated by over-expression of dominant negative pp60Src mutant or reducing pp60Src expression. LPS induces both RhoA nitration and endothelial barrier disruption and these events were attenuated when pp60Src expression was reduced. Endothelial NOS uncoupling correlated with an increase in the levels of asymmetric dimethylarginine (ADMA) in both LPS exposed and Y527FSrc over-expressing PAEC. The effects in PAEC were also recapitulated when we transiently over-expressed Y527FSrc in the mouse lung. Finally, we found that the pp60Src-mediated decrease in DDAH activity was mediated by the phosphorylation of DDAH II at Y207 and that a Y207F mutant DDAH II was resistant to pp60Src-mediated inhibition. We conclude that pp60Src can directly inhibit DDAH II and this is involved in the increased ADMA levels that enhance eNOS uncoupling during the development of ALI

CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patient discomfort and introduces artifacts in the images. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have not been publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. Manual segmentations of the myocardium and chambers of all the subjects are also provided within the dataset. Scripts of state-of-the-art reconstruction algorithms were also provided as a point of reference. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community. Researchers can access the dataset at https://www.synapse.org/#!Synapse:syn51471091/wiki/.Comment: 14 pages, 8 figure

Genomic mosaicism due to homoeologous exchange generates extensive phenotypic diversity in nascent allopolyploids

Allopolyploidy is an important process in plant speciation, yet newly formed allopolyploid species typically suffer from extreme genetic bottlenecks. One escape from this impasse might be homoeologous meiotic pairing, during which homoeologous exchanges (HEs) generate phenotypically variable progeny. However, the immediate genome-wide patterns and resulting phenotypic diversity generated by HEs remain largely unknown. Here, we analyzed the genome composition of 202 phenotyped euploid segmental allopolyploid individuals from the 4th selfed generation following chromosomal doubling of reciprocal F1 hybrids of crosses between rice subspecies, using whole genome sequencing. We describe rampant occurrence of HEs that, by overcoming incompatibility or conferring superiority of hetero-cytonuclear interactions, generate extensive and individualized genomic mosaicism across the analyzed tetraploids. We show that the resulting homoeolog copy number alteration in tetraploids affects known-function genes and their complex genetic interactions, in the process creating extraordinary phenotypic diversity at the population level following a single initial hybridization. Our results illuminate the immediate genomic landscapes possible in a tetraploid genomic environment, and underscore HE as an important mechanism that fuels rapid phenotypic diversification accompanying the initial stages of allopolyploid evolution

Robust estimation of bacterial cell count from optical density

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

On the Differences between Chinese Languages Education in Xinjiang and Economically Developed Cities under the New Curriculum Standard

By examining the ancient and modern educational approaches in the Xinjiang Uyghur Autonomous Region, this study analyzes the changes and processes based on the analysis of Xinjiang’s location, ethnic situation, and educational resources and studies the differences between language education in Xinjiang and the general region, which proposes the importance of the popularization of the common national language for language education. It also analyzes the relationship between the common national language and Chinese language education.The paper is divided into four parts. The first part introduces the background. The second part introduces language education under the new curriculum standards and explores in depth through language learning requirements, teaching materials, and school-based resources. The third part analyzes the current situation of the use of national languages by ethnic minorities in Xinjiang and explores it through students, language teachers, and learning. The fourth part concludes. The shift from “bilingual education” to full Chinese language teaching has been a long-standing educational goal in Xinjiang, and it has been achieved. However, the version of language teaching materials in the region lags, the curriculum reform is slow, and teachers and language curriculum resources are relatively scarce. This will provide some reference for future research and exploration of language education in Xinjiang. This study finds that the versions of the language teaching materials lag, the curriculum reform is slow, and the teacher strength and the language curriculum resources are relatively scarce