Comparative Transcriptomics of Strawberries (Fragaria spp.) Provides Insights into Evolutionary Patterns

Multiple closely related species with genomic sequences provide an ideal system for studies on comparative and evolutionary genomics, as well as the mechanism of speciation. The whole genome sequences of six strawberry species (Fragaria spp.) have been released, which provide one of the richest genomic resources of any plant genus. In this study, we first generated seven transcriptome sequences of Fragaria species de novo, with a total of 48,557–82,537 unigenes per species. Combined with 13 other species genomes in Rosales, we reconstructed a phylogenetic tree at the genomic level. The phylogenic tree shows that Fragaria closed grouped with Rubus and the Fragaria clade is divided into three subclades. East Asian species appeared in every subclade, suggesting that the genus originated in this area at ∼7.99 Mya. Four species found in mountains of Southwest China originated at ∼3.98 Mya, suggesting that rapid speciation occurred to adapt to changing environments following the uplift of the Qinghai–Tibet Plateau. Moreover, we identified 510 very significantly positively selected genes in the cultivated species F. × ananassa genome. This set of genes was enriched in functions related to specific agronomic traits, such as carbon metabolism and plant hormone signal transduction processes, which are directly related to fruit quality and flavor. These findings illustrate comprehensive evolutionary patterns in Fragaria and the genetic basis of fruit domestication of cultivated strawberry at the genomic/transcriptomic level

Void Lensing in Cubic Galileon Gravity

Weak lensing studies via cosmic voids are a promising probe of Modified Gravity (MG). Excess surface mass density (ESD) is widely used as a lensing statistic in weak lensing research. In this paper, we use the ray-tracing method to study the ESD around voids in simulations based on Cubic Galileon (CG) gravity. With the compilation of N-body simulation and ray-tracing method, changes in structure formation and deflection angle resulting from MG can both be considered, making the extraction of lensing signals more realistic. We find good agreements between the measurement and theoretical prediction of ESD for CG gravity. Meanwhile, the lensing signals are much less affected by the change of the deflection angle than the change of the structure formation, indicating a good approximation of regarding ESD (statistics) as the projection of 3D dark matter density field. Finally, we demonstrate that it is impossible to distinguish CG and General Relativity in our simulation, however, in the next-generation survey, thanks to the large survey area and the increased galaxy number density, detecting the differences between these two models is possible. The methodology employed in this paper that combines N-body simulation and ray-tracing method can be a robust way to measure the lensing signals from simulations based on the MGs, and especially on that which significantly modifies the deflection angle.Comment: 14 pages, 9 figure

The combined impact of social networks and connectedness on anxiety, stress, and depression during COVID-19 quarantine: a retrospective observational study

IntroductionThe COVID-19 pandemic and associated quarantine measures have precipitated a surge in mental health disorders, particularly depression and anxiety. Government policies and restrictions on physical activity have contributed to this phenomenon, as well as diminished subjective social connectedness and exacerbated objective social isolation. As two dimensions of social isolation, it is worth noting that subjectively perceived social connectedness serves as a protective factor for mental health, whereas the decline in the size of objectively evaluated social networks poses a significant risk. However, research investigating the combined influence of these two dimensions remains limited.MethodsThis study used an online survey to collect data to investigate the effects of objective social connectedness and objective social networks on anxiety, stress, and depression during COVID-19 quarantine. A total of 485 participants were analyzed using statistical methods, including paired t-test, Pearson correlation analysis, linear regression, cluster analysis, ANOVA, and moderated mediated.ResultsThe study found that anxiety and depression scores increased during the quarantine, with age, education, and social connectedness scores associated with the increase. Pre-quarantine anxiety and depression levels were strongly correlated with mental health status during quarantine. Cluster analysis, respectively, revealed three clusters for those without increasing anxiety and depression scores. The study also found that objective social network influences the impact of subjective social connectedness on pre-quarantine mental health, which in turn affects anxiety and depression levels during quarantine.ConclusionThe study identified that quarantine increased anxiety and depression, with age being protective, and education and subjective social connectedness as risk factors. The study also emphasizes the comprehensive impact of objective and subjective social isolation. Although individuals perceive the same degree of social connectedness, those with smaller social networks are more prone to developing symptoms of anxiety and depression, which are also more likely to worsen during quarantine

Predicting Social Unrest Events with Hidden Markov Models Using GDELT

Proactive handling of social unrest events which are common happenings in both democracies and authoritarian regimes requires that the risk of upcoming social unrest event is continuously assessed. Most existing approaches comparatively pay little attention to considering the event development stages. In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability. The framework utilizes the temporal burst patterns in GDELT event streams to uncover the underlying event development mechanics and formulates the social unrest event prediction as a sequence classification problem based on Bayes decision. Extensive experiments with data from five countries in Southeast Asia demonstrate the effectiveness of this framework, which outperforms the logistic regression method by 7% to 27% and the baseline method 34% to 62% for various countries

Clinical characteristics and related influencing factors of common rheumatic diseases concomitant with tuberculosis

ObjectiveTo explore the clinical characteristics and risk factors of common systemic rheumatism concomitant with tuberculosis (TB).MethodsA total of 3,906 patients of RA, SLE, and SS diagnosed in the People's Hospital of Sichuan Province from January 2007 to January 2017 were collected. One hundred and five patients with TB were included as TB group, including 42 RA, 41 SLE, and 22 SS patients. In the non-TB group, 84 RA, 82 SLE, and 44 SS patients were randomly selected during the same period.ResultsFever was the most common symptom among RA, SLE, and SS patients with TB, accounting for 83.3%, 92.7%, and 68.2%, respectively. Cough, weight loss or fatigue were the next common. RA patients with TB were mostly pulmonary TB (PTB), accounting for 64.3%. The proportion of PTB for SLE and SS were 46.3%, 59.01%, respectively. In TB group, 59% RA, 57% SLE, and 62% SS with PTB had two or more chest CT findings. There were 48 TB cases received both Interferon Gamma Release Assay (IGRA) and Tuberculin skin test (TST) with positive rates of 91.8%, 45.8%, respectively. The daily average dose of glucocorticoids within 1 year in TB group was higher than that in non-TB group of SLE patients, lower counts of CD4+ T cell count were found in TB group (P < 0.05), while no such differences were found in RA and SS patients.ConclusionRA patients with TB are mainly pulmonary TB. For SLE and SS patients, the chance of PTB and extrapulmonary tuberculosis is similar. Daily average dose of glucocorticoids within 1 year may be a common risk factor for RA, SLE and SS patients developing TB. Decreased CD4+ T cell count may also be a risk factor for SLE patients with TB. Symptoms of RA, SLE, SS with TB, are similar with the primary disease or other infection. It is recommended to conduct both TST and IGRA to help diagnose TB

Evolutionary history and pan-genome dynamics of strawberry (Fragaria spp.)

Strawberry (Fragaria spp.) has emerged as a model system for various fundamental and applied research in recent years. In total, the genomes of five different species have been sequenced over the past 10 y. Here, we report chromosome-scale reference genomes for five strawberry species, including three newly sequenced species’ genomes, and genome resequencing data for 128 additional accessions to estimate the genetic diversity, structure, and demographic history of key Fragaria species. Our analyses obtained fully resolved and strongly supported phylogenies and divergence times for most diploid strawberry species. These analyses also uncovered a new diploid species (Fragaria emeiensis Jia J. Lei). Finally, we constructed a pan-genome for Fragaria and examined the evolutionary dynamics of gene families. Notably, we identified multiple independent single base mutations of the MYB10 gene associated with white pigmented fruit shared by different strawberry species. These reference genomes and datasets, combined with our phylogenetic estimates, should serve as a powerful comparative genomic platform and resource for future studies in strawberry.DATA AVAILABILITY: The raw genomic reads generated in this study have been deposited in the NCBI Sequence Read Archive (BioProject nos. PRJNA743176 and PRJNA757203). The genome assembly and annotation files are available at the Genome Database for Rosaceae (F. daltoniana: https://www.rosaceae.org/Analysis/11885161; F. pentaphylla: https://www.rosaceae.org/Analysis/12137892; F. mandschurica: https://www.rosaceae.org/Analysis/12137893; F. nilgerrensis: https://www.rosaceae.org/Analysis/12137894; F. viridis: https://www.rosaceae.org/Analysis/12137895).National Natural Science Foundation of China; National Key Research and Development Project; Michigan State University AgBioResearch, US Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA); National Science Foundation; the European Research Council under the European Union’s Horizon 2020 research and innovation program and Ghent University.https://www.pnas.orghj2022BiochemistryGeneticsMicrobiology and Plant Patholog

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Endogenous Driving Forces in Ecology-Production-Living Space Changes at Micro-Scale: A Mountain Town Example in Inland China

Studying land use transition and restructuring has value for promoting sustainable regional development, especially in China’s vast rural areas, which are undergoing rapid changes. Current research tends to focus on the macro level, and analyses of driving forces are mostly based on the correlation analysis of influencing factors. However, in the case of villages and towns, which are at the micro level, it is important to know who promotes land use transition and how to promote it under the influence of the macro environment. This study, therefore, focused on the endogenous driving force behind land use transition and its characteristics at the micro level of villages and towns. On the basis of our theoretical framework, an empirical study was carried out on the transformation and restructuring of ecology–production–living (EPL) spaces in the town of Zhulin in Central China over the past 30 years. We found the following: (1) The overall distribution of EPL spaces in Zhulin shifted from mixed distribution to relatively concentrated distribution, and the spatial transfer of EPL spaces showed fluctuations in the expansion and contraction of different types of spaces. (2) Land use transition was more active in spatial interface areas than in noninterface areas, where the interconversion of ecological space and agricultural production space was concentrated at the terrain interface. In addition, transformation processes related to living space and non-agricultural production space were concentrated at the urban–rural interface. (3) Macro-level social and economic changes were the root cause of land use transformation, and the autonomous spatial governance capability of villagers’ self-organization institutions was key to regulating land use transformation. The spatial interface was a sensitive area for land use transformation in a natural state. An endogenous driving mode of active response to land use transformation based on rural autonomous spatial governance capability and spatial interface sensitivity is proposed. How to improve the rural governance capacity of key local actors in different regions and at different levels is an aspect worthy of further consideration