Galaxy formation with cold gas accretion and evolving stellar initial mass function

The evolution of the galaxy stellar mass function is especially useful to test the current model of galaxy formation. Observational data have revealed a few inconsistencies with predictions from the $\Lambda {\rm CDM}$ model. For example, most massive galaxies have already been observed at very high redshifts, and they have experienced only mild evolution since then. In conflict with this, semi-analytical models of galaxy formation predict an insufficient number of massive galaxies at high redshift and a rapid evolution between redshift 1 and 0 . In addition, there is a strong correlation between star formation rate and stellar mass for star-forming galaxies, which can be roughly reproduced with the model, but with a normalization that is too low at high redshift. Furthermore, the stellar mass density obtained from the integral of the cosmic star formation history is higher than the measured one by a factor of 2. In this paper, we study these issues using a semi-analytical model that includes: 1) cold gas accretion in massive halos at high redshift; 2) tidal stripping of stellar mass from satellite galaxies; and 3) an evolving stellar initial mass function (bottom-light) with a higher gas recycle fraction. Our results show that the combined effects from 1) and 2) can predict sufficiently massive galaxies at high redshifts and reproduce their mild evolution at low redshift, While the combined effects of 1) and 3) can reproduce the correlation between star formation rate and stellar mass for star-forming galaxies across wide range of redshifts. A bottom-light/top-heavy stellar IMF could partly resolve the conflict between the stellar mass density and cosmic star formation history.Comment: 9 pages, 7 figures. Accepted for publication in Ap

Self-Purification and Entanglement Revival in Lambda Matter

We explore the dynamics of entanglement in an ensemble of qutrits with a lambda-type level structure interacting with single-mode bosons. Our investigation focuses on zero-energy states within the subspace of totally symmetric wave functions. Remarkably, we observe a universal two-stage dynamics of entanglement with intriguing revival behavior. The revival of entanglement is a consequence of the self-purification process, where the quantum state relaxes and converges universally to a special dark state within the system.Comment: 5 pages, 6 figure

Discrete time crystal in an open optomechanical system

The spontaneous breaking of time translation symmetry in periodically driven Floquet systems can lead to a discrete time crystal. Here we study the occurrence of such dynamical phase in a driven-dissipative optomechanical system with two membranes in the middle. We find that, under certian conditions, the system can be mapped to an open Dicke model and realizes a superradianttype phase transition. Furthermore, applying a suitable periodically modulated drive, the system dynamics exhibits a robust subharmonic oscillation persistent in the thermodynamic limit

Newcastle disease virus-vectored Nipah encephalitis vaccines induce B and T cell responses in mice and long-lasting neutralizing antibodies in pigs

AbstractNipah virus (NiV), a member of the Paramyxoviridae family, causes deadly encephalitis in humans and huge economic losses to the pig industry. Here, we generated recombinant avirulent Newcastle disease virus (NDV) LaSota strains expressing the NiV G and F proteins respectively (designated as rLa-NiVG and rLa-NiVF), and evaluated their immunogenicity in mice and pigs. Both rLa-NiVG and rLa-NiVF displayed growth properties similar to those of LaSota virus in chicken eggs. Co-infection of rLa-NiVG and rLa-NiVF caused marked syncytia formation, while intracerebral co-inoculation of these viruses in mice showed they were safe in at least one mammalian species. Animal immunization studies showed rLa-NiVG and rLa-NiVF induced NiV neutralizing antibody responses in mice and pigs, and F protein-specific CD8+ T cell responses in mice. Most importantly, rLa-NiVG and rLa-NiVF administered alone or together, induced a long-lasting neutralizing antibody response in pigs. Recombinant rLa-NiVG/F thus appear to be promising NiV vaccine candidates for pigs and potentially humans

Macrophages Phenotype Regulated by IL-6 Are Associated with the Prognosis of Platinum-Resistant Serous Ovarian Cancer: Integrated Analysis of Clinical Trial and Omics

Background. The treatment of platinum-resistant recurrent ovarian cancer (PROC) is a clinical challenge and a hot topic. Tumor microenvironment (TME) as a key factor promoting ovarian cancer progression. Macrophage is a component of TME, and it has been reported that macrophage phenotype is related to the development of PROC. However, the mechanism underlying macrophage polarization and whether macrophage phenotype can be used as a prognostic indicator of PROC remains unclear. Methods. We used ESTIMATE to calculate the number of immune and stromal components in high-grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas database. The differential expression genes (DEGs) were analyzed via protein–protein interaction network, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis to reveal major pathways of DEGs. CD80 was selected for survival analysis. IL-6 was selected for gene set enrichment analysis (GSEA). A subsequent cohort study was performed to confirm the correlation of IL-6 expression with macrophage phenotype in peripheral blood and to explore the clinical utility of macrophage phenotype for the prognosis of PROC patients. Results. A total of 993 intersecting genes were identified as candidates for further survival analysis. Further analysis revealed that CD80 expression was positively correlated with the survival of HGSOC patients. The results of GO and KEGG analysis suggested that macrophage polarization could be regulated via chemokine pathway and cytokine–cytokine receptor interaction. GSEA showed that the genes were mainly enriched in IL-6-STAT-3. Correlation analysis for the proportion of tumor infiltration macrophages revealed that M2 was correlated with IL-6. The results of a cohort study demonstrated that the regulation of macrophage phenotype by IL-6 is bidirectional. The high M1% was a protective factor for progression-free survival. Conclusion. Thus, the macrophage phenotype is a prognostic indicator in PROC patients, possibly via a hyperactive IL-6-related pathway, providing an additional clue for the therapeutic intervention of PROC

Intravenous xenogeneic transplantation of human adipose-derived stem cells improves left ventricular function and microvascular integrity in swine myocardial infarction model

OBJECTIVES: The potential for beneficial effects of adipose-derived stem cells (ASCs) on myocardial perfusion and left ventricular dysfunction in myocardial ischemia (MI) has not been tested following intravenous delivery. METHODS: Surviving pigs following induction of MI were randomly assigned to 1 of 3 different groups: the placebo group (n = 7), the single bolus group (SB) (n = 7, 15 × 10(7) ASCs), or the divided dose group (DD) (n = 7, 5 × 10(7) ASCs/day for three consecutive days). Myocardial perfusion defect area and coronary flow reserve (CFR) were compared during the 28-day follow-up. Also, serial changes in the absolute number of circulating CD4(+) T and CD8(+) T cells were measured. RESULTS: The increases in ejection fraction were significantly greater in both the SB and the DD groups compared to the placebo group (5.4 ± 0.9%, 3.7 ± 0.7%, and -0.4 ± 0.6%, respectively), and the decrease in the perfusion defect area was significantly greater in the SB group than the placebo group (-36.3 ± 1.8 and -11.5 ± 2.8). CFR increased to a greater degree in the SB and the DD groups than in the placebo group (0.9 ± 0.2, 0.8 ± 0.1, and 0.2 ± 0.2, respectively). The circulating number of CD8(+) T cells was significantly greater in the SB and DD groups than the placebo group at day 7 (3,687 ± 317/µL, 3,454 ± 787/µL, and 1,928 ± 457/µL, respectively). The numbers of small vessels were significantly greater in the SB and the DD groups than the placebo group in the peri-infarct area. CONCLUSIONS: Both intravenous SB and DD delivery of ASCs are effective modalities for the treatment of MI in swine. Intravenous delivery of ASCs, with its immunomodulatory and angiogenic effects, is an attractive noninvasive approach for myocardial rescue

Characteristics of vegetation carbon sink carrying capacity and restoration potential of China in recent 40 years

Improving vegetation carbon sink is a key measure for China to achieve the goal of carbon neutrality. However, the gradual saturation of vegetation carbon fixation under the constraints of climate change and human activities has limited the long-term and sustainable growth of vegetation carbon sinks, resulting in significant uncertainty in understanding future carbon sink capacity and recovery potential. In this study, NPP has been selected as a carbon sink indicator to quantitatively evaluated the carbon sink carrying capacity (CSCC) and the carbon sink resilience (CSR) of China. Results demonstrated that (1) the NPP of vegetation cover areas in China exhibited an increasing trend from 1981 to 2018, with an average growth rate of 1.66 g C m−2 yr.−1 and a total net NPP increase of 0.32 P g C. (2) The average CSCC in China was 658.59 g C m−2 yr.−1, with a total amount of 4.13 Pg C yr.−1. The NPP exceeded 60% of CSCC in various years, and the total NPP in 2018 was 3.26 Pg C yr.−1, which reached 78.74% of CSCC. In the future, carbon sink that can be increased is 0.88 Pg C yr.−1, with an increase proportion of 21.26%. (3) From 2000 to 2018, the NPP of vegetation-covered area (VCA) in China had generally maintained a positive succession trend with the stronger CSR. Only four provinces (HUN, CQ, AH, and JS) in China showed the extremely strong levels of CSR. The study has revealed the huge and sustainable CSCC and restoration potential in China over the past 40 years, and has provided spatial positioning and theoretical guidance for future ecological carbon sink restoration and benefit assessment

Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study

Background Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children. Methods and findings Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ −6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered. Conclusions To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.This study was funded by the National Key R&D Program of China (2018YFC0116500), the National Natural Science Foundation of China (91546101, 81822010), the Guangdong Science and Technology Innovation Leading Talents (2017TX04R031), and Youth Pearl River Scholar in Guangdong (2016)