Searching for Ξcc+\Xi_{cc}^+ in Relativistic Heavy Ion Collisions

We study the doubly charmed baryon $\Xi_{cc}^+$ in high energy nuclear collisions. We solve the three-body Schroedinger equation with relativistic correction and calculate the $\Xi_{cc}^+$ yield and transverse momentum distribution via coalescence mechanism. For $\Xi_{cc}^+$ production in central Pb+Pb collisions at LHC energy, the yield is extremely enhanced, and the production cross section per binary collision is one order of magnitude larger than that in p+p collisions. This indicates that, it is most probable to discover $\Xi_{cc}^+$ in heavy ion collisions and its discovery can be considered as a probe of the quark-luon plasma formation.Comment: 5 pages and 4 figure

Ωccc\Omega_{ccc} Production in High Energy Nuclear Collisions

We investigate the production of $\Omega_{ccc}$ baryon in high energy nuclear collisions via quark coalescence mechanism. The wave function of $\Omega_{ccc}$ is solved from the Schr\"odinger equation for the bound state of three charm quarks by using the hyperspherical method. The production cross section of $\Omega_{ccc}$ per binary collision in a central Pb+Pb collision at $\sqrt{s_{NN}}=2.76$ TeV reaches 9 nb, which is at least two orders of magnitude larger than that in a p+p collision at the same energy. Therefore, it is most probable to discover $\Omega_{ccc}$ in heavy ion collisions at LHC, and the observation will be a clear signature of the quark-gluon plasma formation.Comment: 6 pages, 5 figure

SEMI: Self-supervised Exploration via Multisensory Incongruity

Efficient exploration is a long-standing problem in reinforcement learning. In this work, we introduce a self-supervised exploration policy by incentivizing the agent to maximize multisensory incongruity, which can be measured in two aspects: perception incongruity and action incongruity. The former represents the uncertainty in multisensory fusion model, while the latter represents the uncertainty in an agent's policy. Specifically, an alignment predictor is trained to detect whether multiple sensory inputs are aligned, the error of which is used to measure perception incongruity. The policy takes the multisensory observations with sensory-wise dropout as input and outputs actions for exploration. The variance of actions is further used to measure action incongruity. Our formulation allows the agent to learn skills by exploring in a self-supervised manner without any external rewards. Besides, our method enables the agent to learn a compact multimodal representation from hard examples, which further improves the sample efficiency of our policy learning. We demonstrate the efficacy of this formulation across a variety of benchmark environments including object manipulation and audio-visual games

Mediating Dynamic Supply Chain Formation by Collaborative Single Machine Earliness/Tardiness Agents in Supply Mesh

Nowadays, a trend of forming dynamic supply chains with different trading partners over different e-marketplaces has emerged. These supply chains, which are called “supply mesh,” generally refer to heterogeneous electronic marketplaces in which dynamic supply chains, as per project (often make-to-order), are formed across different parties. Conceptually, in a supply mesh a dynamic supply chain is formed vertically, mediating several companies for a project. Companies that are on the same level horizontally are either competitors or cohorts. A complex scenario such as this makes it challenging to find the right group of members for a dynamic supply chain. Earlier on, a multiagent model called the collaborative single machine earliness/tardiness (CSET) model was proposed for the optimal formation of make-to-order supply chains. This paper contributes the particular agent designs, for enabling the mediation of CSET in a supply mesh, and the possibilities are discussed. It is demonstrated via a computer simulation, based on samples from the U.S. textile industry, that by using intelligent agents under the CSET model it is possible to automatically find an ideal group of trading partners from a supply mesh

Distributed gene clinical decision support system based on cloud computing

Background: The clinical decision support system can effectively break the limitations of doctors’ knowledge and reduce the possibility of misdiagnosis to enhance health care. The traditional genetic data storage and analysis methods based on stand-alone environment are hard to meet the computational requirements with the rapid genetic data growth for the limited scalability. Methods: In this paper, we propose a distributed gene clinical decision support system, which is named GCDSS. And a prototype is implemented based on cloud computing technology. At the same time, we present CloudBWA which is a novel distributed read mapping algorithm leveraging batch processing strategy to map reads on Apache Spark. Results: Experiments show that the distributed gene clinical decision support system GCDSS and the distributed read mapping algorithm CloudBWA have outstanding performance and excellent scalability. Compared with state-of-the-art distributed algorithms, CloudBWA achieves up to 2.63 times speedup over SparkBWA. Compared with stand-alone algorithms, CloudBWA with 16 cores achieves up to 11.59 times speedup over BWA-MEM with 1 core. Conclusions: GCDSS is a distributed gene clinical decision support system based on cloud computing techniques. In particular, we incorporated a distributed genetic data analysis pipeline framework in the proposed GCDSS system. To boost the data processing of GCDSS, we propose CloudBWA, which is a novel distributed read mapping algorithm to leverage batch processing technique in mapping stage using Apache Spark platform. Keywords: Clinical decision support system, Cloud computing, Spark, Alluxio, Genetic data analysis, Read mappin

Natural Phenolic Acids and Their Derivatives against Human Viral Infections

Natural compounds with structural diversity and complexity offer a great chance to find new antiviral agents. Phenolic acids have attracted considerable attention due to their potent antiviral abilities and unique mechanisms. The aim of this review is to report new discoveries and update pertaining to antiviral phenolic acids. The antiviral phenolic acids were classified according to their structural properties and antiviral types. Meanwhile, the antiviral characteristics and structure-activity relationships of phenolic acids and their derivatives were summarized. Natural phenolic acids and their derivatives possess potent inhibitory effects on multiple viruses in humans such as human immunodeficiency virus, hepatitis C virus, hepatitis B virus, herpes simplex virus, influenza virus and respiratory syncytial virus etc. In particular, caffeic acid/gallic acid and their derivatives exhibit outstanding antiviral properties through a variety of modes of action. In conclusion, naturally derived phenolic acids especially caffeic acid/gallic acid and their derivatives may be regarded as novel promising antiviral leads or candidates. Additionally, scarcely any of these compounds have been used as antiviral treatments in clinical practice. Therefore, these phenolic acids with diverse skeletons and mechanisms provide us an excellent resource for finding novel antiviral drugs

Lead induced structural and functional damage and microbiota dysbiosis in the intestine of crucian carp (Carassius auratus)

Lead (Pb) is a hazardous pollutant in water environments that can cause significant damage to aquatic animals and humans. In this study, crucian carp (Carassius auratus) were exposed to waterborne Pb for 96 h; then, histopathological analysis, quantitative qPCR analysis, and 16S high-throughput sequencing were performed to explore the effects of Pb on intestinal bioaccumulation, structural damage, oxidative stress, immune response, and microbiota imbalance of C. auratus. After Pb exposure, the intestinal morphology was obviously damaged, including significantly increasing the thickness of the intestinal wall and the number of goblet cells and reducing the depth of intestinal crypts. Pb exposure reduced the mRNA expressions of Claudin-7 and villin-1 while significantly elevated the level of GST, GSH, CAT, IL-8, IL-10, IL-1, and TNF-α. Furthermore, 16S rRNA analysis showed that the Shannon and Simpson indices decreased at 48 h after Pb exposure, and the abundance of pathogenic bacteria (Erysipelotrichaceae, Weeksellaceae, and Vibrionaceae) increased after Pb exposure. In addition, the correlation network analysis found that Proteobacteria were negatively correlated with Firmicutes and positively correlated with Bacteroidetes. Functional prediction analysis of bacteria speculated that the change in intestinal microbiota led to the PPAR signaling pathway and peroxisome function of the intestine of crucian carp was increased, while the immune system and membrane transport function were decreased. Finally, canonical correlation analysis (CCA) found that there were correlations between the intestinal microbiota, morphology, antioxidant factors, and immune factors of crucian carp after Pb exposure. Taken together, our results demonstrated that intestinal flora dysbiosis, morphological disruption, oxidative stress, and immune injury are involved in the toxic damage of Pb exposure to the intestinal structure and function of crucian carp. Meanwhile, Pb exposure rapidly increased the abundance of pathogenic bacteria, leading to intestinal disorders, further aggravating the damage of Pb to intestinal structure and function. These findings provide us a basis for the link between gut microbiome changes and heavy metal toxicity, and gut microbiota can be used as biomarkers for the evaluation of heavy metal pollution in future

The detailed distribution of T cell subpopulations in immune-stable renal allograft recipients: a single center study

Background Most renal allograft recipients reach a stable immune state (neither rejection nor infection) after transplantation. However, the detailed distribution of overall T lymphocyte subsets in the peripheral blood of these immune-stable renal transplant recipients remains unclear. We aim to identify differences between this stable immune state and a healthy immune state. Methods In total, 103 recipients underwent renal transplantation from 2012 to 2016 and received regular follow-up in our clinic. A total of 88 of these 103 recipients were enrolled in our study according to the inclusion and exclusion criteria. A total of 47 patients were 1 year post-transplantation, and 41 were 5 years post-transplantation. In addition, 41 healthy volunteers were recruited from our physical examination clinic. Detailed T cell subpopulations from the peripheral blood were assessed via flow cytometry. The parental frequency of each subset was calculated and compared among the diverse groups. Results The demographics and baseline characteristics of every group were analyzed. The frequency of total T cells (CD3+) was decreased in the renal allograft recipients. No difference in the variation of the CD4+, CD8+, and activated (HLA-DR+) T cell subsets was noted among the diverse groups. Regarding T cell receptor (TCR) markers, significant reductions were found in the proportion of γδ T cells and their Vδ2 subset in the renal allograft recipients. The proportions of both CD4+ and CD8+ programmed cell death protein (PD) 1+ T cell subsets were increased in the renal allograft recipients. The CD27+CD28+ T cell proportions in both the CD4+ and CD8+ populations were significantly decreased in the allograft recipients, but the opposite results were found for both CD4+ and CD8+ CD27-CD28- T cells. An increased percentage of CD4+ effector memory T cells and a declined fraction of CD8+ central memory T cells were found in the renal allograft recipients. Conclusion Limited differences in general T cell subsets (CD4+, CD8+, and HLA-DR+) were noted. However, obvious differences between renal allograft recipients and healthy volunteers were identified with TCR, PD1, costimulatory molecules, and memory T cell markers

Sequencing of a Chinese tetralogy of Fallot cohort reveals clustering mutations in myogenic heart progenitors

Tetralogy of Fallot (TOF) is the most common cyanotic heart defect, yet the underlying genetic mechanisms remain poorly understood. Here, we performed whole-genome sequencing analysis on 146 nonsyndromic TOF parent-offspring trios of Chinese ethnicity. Comparison of de novo variants and recessive genotypes of this data set with data from a European cohort identified both overlapping and potentially novel gene loci and revealed differential functional enrichment between cohorts. To assess the impact of these mutations on early cardiac development, we integrated single-cell and spatial transcriptomics of early human heart development with our genetic findings. We discovered that the candidate gene expression was enriched in the myogenic progenitors of the cardiac outflow tract. Moreover, subsets of the candidate genes were found in specific gene coexpression modules along the cardiomyocyte differentiation trajectory. These integrative functional analyses help dissect the pathogenesis of TOF, revealing cellular hotspots in early heart development resulting in cardiac malformations