New insight into the phylogeographic pattern of Liriodendron chinense (Magnoliaceae) revealed by chloroplast DNA: east–west lineage split and genetic mixture within western subtropical China

Background Subtropical China is a global center of biodiversity and one of the most important refugia worldwide. Mountains play an important role in conserving the genetic resources of species. Liriodendron chinense is a Tertiary relict tree largely endemic to subtropical China. In this study, we aimed to achieve a better understanding of the phylogeographical pattern of L. chinense and to explore the role of mountains in the conservation of L. chinense genetic resources. Methods Three chloroplast regions (psbJ-petA, rpl32-ndhF, and trnK5’-matK) were sequenced in 40 populations of L. chinense for phylogeographical analyses. Relationships among chloroplast DNA (cpDNA) haplotypes were determined using median-joining networks, and genetic structure was examined by spatial analysis of molecular variance (SAMOVA). The ancestral area of the species was reconstructed using the Bayesian binary Markov Chain Monte Carlo (BBM) method according to its geographic distribution and a maximum parsimony (MP) tree based on Bayesian methods. Results Obvious phylogeographic structure was found in L. chinense. SAMOVA revealed seven groups matching the major landscape features of the L. chinense distribution area. The haplotype network showed three clades distributed in the eastern, southwestern, and northwestern regions. Separate northern and southern refugia were found in the Wu Mountains and Yungui Plateau, with genetic admixture in the Dalou Mountains and Wuling Mountains. BBM revealed a more ancient origin of L. chinense in the eastern region, with a west–east split most likely having occurred during the Mindel glacial stage. Discussion The clear geographical distributions of haplotypes suggested multiple mountainous refugia of L. chinense. The east–west lineage split was most likely a process of gradual genetic isolation and allopatric lineage divergence when the Nanling corridor was frequently occupied by evergreen or coniferous forest during Late Quaternary oscillations. Hotspots of haplotype diversity in the Dalou Mountains and Wuling Mountains likely benefited from gene flow from the Wu Mountains and Yungui Plateau. Collectively, these results indicate that mountain regions should be the main units for conserving and collecting genetic resources of L. chinense and other similar species in subtropical China

HBV infection-induced liver cirrhosis development in dual-humanized mice with human bone mesenchymal stem cell transplantation

疾病动物模型是现代医学发展的基石，尤其是重大、突发传染病暴发时，适宜的疾病动物模型可为及时发现病原体、制定防控策略提供强大保障，原创的疾病动物模型已成为衡量一个国家生物医药科研水平的标志。我校夏宁邵教授团队和浙江大学附属第一医院李君教授团队历经5年的协同攻关，终于建立了国际上首个高度模拟人类乙肝病毒（HBV）自然感染诱发的慢乙肝肝硬化小鼠模型。厦门大学公共卫生学院袁伦志博士生、浙江大学医学院附属第一医院江静博士和厦门大学公共卫生学院刘旋博士生为该论文共同第一作者。厦门大学夏宁邵教授、浙江大学附属第一医院李君教授和厦门大学程通副教授为该论文共同通讯作者。【Abstract】Objective： Developing a small animal model that accurately delineates the natural history of hepatitis B virus (HBV) infection and immunopathophysiology is necessary to clarify the mechanisms of host-virus interactions and to identify intervention strategies for HBV-related liver diseases. This study aimed to develop an HBV-induced chronic hepatitis and cirrhosis mouse model through transplantation of human bone marrow mesenchymal stem cells (hBMSCs). Design： Transplantation of hBMSCs into Fah -/- Rag2 -/- IL-2Rγc -/- SCID (FRGS) mice with fulminant hepatic failure (FHF) induced by hamster-anti-mouse CD95 antibody JO2 generated a liver and immune cell dual-humanized (hBMSC-FRGS) mouse. The generated hBMSC-FRGS mice were subjected to assessments of sustained viremia, specific immune and inflammatory responses and liver pathophysiological injury to characterize the progression of chronic hepatitis and cirrhosis after HBV infection. Results： The implantation of hBMSCs rescued FHF mice, as demonstrated by robust proliferation and transdifferentiation of functional human hepatocytes and multiple immune cell lineages, including B cells, T cells, NK cells, dendritic cells (DCs) and immune cell lineages, including B cells, T cells, NK cells, dendritic cells (DCs) and viremia and specific immune and inflammatory responses and showed progression to chronic hepatitis and liver cirrhosis at a frequency of 55% after 54 weeks. Conclusion： This new humanized mouse model recapitulates the liver cirrhosis induced by human HBV infection, thus providing research opportunities for understanding viral immune pathophysiology and testing antiviral therapies in vivo.this work was supported by the national Science and technology Major Project (grant nos. 2017ZX10304402, 2017ZX10203201 and 2018ZX09711003-005-003), the national natural Science Foundation of china(grant nos. 81672023, 81571818 and 81771996), the Scientific research Foundation of the State Key laboratory of Molecular Vaccinology and Molecular Diagnostics (grant no 2016ZY005), Zhejiang Province and State's Key Project of the research and Development Plan of china (grant nos 2017c01026 and 2016YFc1101304/3).该研究获得了传染病防治国家科技重大专项、新药创制国家科技重大专项和国家自然科学基金的资助

Efficacy of Complex coils in embolization of intracranial lobulated aneurysms: a clinical analysis of 34 cases

Objective To evaluate the efficacy of Complex coils as the framing coils on the embolization of intracranial lobulated aneurysms. Methods From April 2017 to April 2018, 34 patients with lobulated aneurysms admitted in our neurosurgery department were enrolled in this study. They all underwent implantation of Complex coils as the framing coils, and their clinical data were collected and retrospectively analyzed. The results of intraoperative cerebral angiography and follow-up outcomes were discussed. Results According to the Raymond standard of aneurysm occlusion, grade Ⅰ occurred in 27 of 34 patients (79.4%), and grade Ⅱ in 5 patients (14.7%), in intraoperative assessment. In the 31 patients who were followed-up through digital subtraction angiography at 6 months after operation, no recurrence was found. In the assessment of aneurysm occlusion, Raymond grade Ⅰ was achieved in 28 patients (90.3%), and Raymond grade Ⅱ in 3 patients (9.7%). No complications associated with Complex coils were observed during perioperative period. Conclusion Complex coils achieves a high success rate as forming frame in the embolization of lobulated aneurysms, with no obvious increase in complications

Characterization and phylogenetic analysis of the complete chloroplast genome of Actinidia latifolia (Actinidiaceae)

The complete chloroplast (cp) genome of Actinidia latifolia was sequenced and assembled using Illumina pair-end sequencing data. The cp genome is 157,021 bp in length and comprises a large single copy (LSC) region of 88,557 bp and a small single copy (SSC) region of 21,562 bp separated by two inverted repeat (IR) regions of 23,451 bp. A total of 113 unique genes were identified, including 79 protein-coding genes, 30 tRNA genes, and four rRNA genes. Phylogenetic analysis based on cp genomes of 20 Actinidiaceae species revealed that A. latifolia was evolutionarily close to A. eriantha, A. styracifolia, and A. fulvicoma

The complete chloroplast genome sequence of Actinidia styracifolia C. F. Liang

The complete chloroplast (cp) genome sequence of Actinidia styracifolia C. F. Liang was assembled using Illumina pair-end sequencing data in this study. The assembled plastome was 156,845 bp in length, including a large single copy (LSC) region of 88,624 bp and a small single copy (SSC) region of 20,535bp, which were separated by two inverted repeat (IR) regions of 23,843 bp. The plastome contains 113 different genes, consisting of 79 unique protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Phylogenetic analysis based on chloroplast genomes revealed that A. styracifolia has a close genetic relationship with A. eriantha

A multimodal approach for improving market price estimation in online advertising

Learning the distribution of market prices is an important and challenging issue for demand-side platforms (DSPs) that serve as advertisers’ agents to compete for online advertising placements in real-time bidding (RTB) systems. Many existing approaches make an assumption that the market prices follow an unimodal distribution. However, based on analytical insights from real-world datasets, we found the distinct multimodal characteristics underlying the distribution of market prices. Moreover, the impression-level features for each ad are also ignored by these approaches in prediction, reducing the accuracy further. To address these problems, a Gaussian Mixture Model (GMM) is proposed in this paper to describe and discriminate the multimodal distribution of market price by utilizing the impression-level features. To further improve its robustness, GMM is extended into a censored version (CGMM) to handle the right-censored challenge in RTB systems (i.e., the market price is only visible to the winner of the ad auction. Thus, the dataset is always biased). Extensive experiments on two real-world public datasets demonstrate that GMM and CGMM significantly outperform 10 state-of-the-art baselines in terms of Wasserstein distance, KL-divergence, ANLP and MSE. To the best of our knowledge, this paper is the first work to simultaneously deal with the multimodal nature of market price distribution and the right-censored challenge in existing RTB systems. It will enable future RTB systems to develop more realistic bidding strategies to enhance the efficiency of online advertising placement auctioning.Nanyang Technological UniversityNational Research Foundation (NRF)This work was supported, in part, by the National Natural Science Foundation of China [grant numbers 71671069]; the National Key Research and Development Program of China [grant numbers 2018YFC0830900]; the Pre-Research Foundation of China [grant numbers 61400010205]; the National Research Foundation, Singapore under its the AI Singapore Programme [grant numbers AISG2-RP-2020-019]; the Joint NTU-WeBank Research Centre on Fintech, Singapore [grant numbers NWJ-2020-008]; the RIE 2020 Advanced Manufacturing and Engineering Programmatic Fund, Singapore [grant numbers A20G8b0102]; the Nanyang Assistant/Associate Professorships (NAP) and the Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Singapore; the Future Communications Research & Development Programme, Singapore [grant numbers FCP-NTU-RG-2021-014]

Deep learning detection of early retinal peripheral degeneration from ultra-widefield fundus photographs of asymptomatic young adult (17–19 Years) candidates to airforce cadets

Purpose: Artificial intelligence (AI)–assisted ultra-widefield (UWF) fundus photographic nterpretation is beneficial to improve the screening of fundus abnormalities. Therefore we constructed an AI machine-learning approach and performed preliminary training and validation. Methods: We proposed a two-stage deep learning-based framework to detect early retinal peripheral degeneration using UWF images from the Chinese Air Force cadets’ medical selection between February 2016 and June 2022. We developed a detection model for the localization of optic disc and macula, which are used to find the peripheral areas. Then we developed six classification models for the screening of various retinal cases. We also compared our proposed framework with two baseline models reported in the literature. The performance of the screening models was evaluated by area under the receiver operating curve (AUC) with 95% confidence interval. Results: A total of 3911 UWF fundus images were used to develop the deep learning model. The external validation included 760 UWF fundus images. The results of compar-ison study revealed that our proposed framework achieved competitive performance compared to existing baselines while also demonstrating significantly faster inference time. The developed classification models achieved an average AUC of 0.879 on six different retinal cases in the external validation dataset. Conclusions: Our two-stage deep learning–based framework improved the machine learning efficiency of the AI model for fundus images with high resolution and many interference factors by maximizing the retention of valid information and compressing the image file size. Translational Relevance: This machine learning model may become a new paradigm for developing UWF fundus photography AI-assisted diagnosis.</p

A revenue-maximizing bidding strategy for demand-side platforms

In real-time bidding (RTB) systems for display advertising, a demand-side platform (DSP) serves as an agent for advertisers and plays an important role in competing for online advertising spaces by placing proper bidding prices. A critical function of the DSP is formulating proper bidding strategies to maximize key performance indicators, such as the number of clicks and conversions. However, many small and medium-sized advertisers' main goal is to maximize revenue with an acceptable return on investment (ROI), rather than simply increase clicks or conversions. Most existing approaches are inapplicable of satisfying the revenue-maximizing goals directly. To solve this problem, we first theoretically analyze the relationships among the conversion rate, ROI, and ad cost, and how they affect revenue. By doing so, we reveal that it is a challenge to increase revenue by relying solely on improving ROI without considering the impact of the ad cost. Based on this insight, the maximal revenue (MR) bidding strategy is proposed to maximize revenue by maximizing the ad cost with a desirable ROI constraint. Unlike previous studies, the proposed MR first distinguishes bid prices from ad costs explicitly, which makes it more applicable to the real second-price auction (GSP) auction mechanism in RTB systems. Then, the winning function is empirically defined in the form of tanh that provides a promising solution for estimating ad costs by jointly considering ad costs with the winning function. The experimental results based on two real-world public datasets demonstrate that the MR significantly outperforms five state-of-the-art models in terms of both revenue and ROI.Published versio

Transcriptome and Metabolome Analyses of Leaves from Cutting Rejuvenation of Ancient <i>Cinnamomum camphora</i>

Rejuvenation refers to the transition from the state of mature to juvenile. Many ancient Cinnamomum camphora have aged and died due to climatic and anthropic factors. Vegetative propagation can protect valuable germplasm resources. In this study, a 2000-year-old ancient C. camphora and its 2-year-old cutting plantlets were selected as experimental materials. The results indicated that the number of leaves with palisade tissue (Pal) cell layers was different between samples, with two layers in the rejuvenated leaves (RLs) and one layer in the mature leaves (MLs) and young leaves (YLs). Indole-3-acetic acid (IAA), isopentenyladenine (iP) and isopentenyladenosine (iPR) concentrations were significantly higher in RLs than in MLs and YLs, but the abscisic acid (ABA) concentration was lower. Targeted metabolome analysis identified 293 differentially accumulated metabolites (DAMs). Meanwhile, a total of 5241 differentially expressed genes (DEGs) were identified by transcriptome sequencing. According to the KEGG analysis, there were seven important enriched pathways in the MLs, RLs and YLs, including plant hormone signal transduction (57 DEGs), plant–pathogen interaction (56 DEGs) and MAPK signaling pathway–plant (36 DEGs). KEGG enrichment conjoint analyses of DEGs and DAMs identified 16 common pathways. Integrated analyses of cytological, hormone, metabolome and transcriptome elements can provide a research basis in regard to the rejuvenation regulatory mechanism of ancient C. camphora