Digital Twin Brain: a simulation and assimilation platform for whole human brain

In this work, we present a computing platform named digital twin brain (DTB) that can simulate spiking neuronal networks of the whole human brain scale and more importantly, a personalized biological brain structure. In comparison to most brain simulations with a homogeneous global structure, we highlight that the sparseness, couplingness and heterogeneity in the sMRI, DTI and PET data of the brain has an essential impact on the efficiency of brain simulation, which is proved from the scaling experiments that the DTB of human brain simulation is communication-intensive and memory-access intensive computing systems rather than computation-intensive. We utilize a number of optimization techniques to balance and integrate the computation loads and communication traffics from the heterogeneous biological structure to the general GPU-based HPC and achieve leading simulation performance for the whole human brain-scaled spiking neuronal networks. On the other hand, the biological structure, equipped with a mesoscopic data assimilation, enables the DTB to investigate brain cognitive function by a reverse-engineering method, which is demonstrated by a digital experiment of visual evaluation on the DTB. Furthermore, we believe that the developing DTB will be a promising powerful platform for a large of research orients including brain-inspiredintelligence, rain disease medicine and brain-machine interface.Comment: 12 pages, 11 figure

Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography

Significance: In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound healing process as their thickness is a vital indicator to judge whether the re-epithelialization process is normal or not. Since optical coherence tomography (OCT) is a real-time and non-invasive imaging technique that can perform a cross-sectional evaluation of tissue microstructure, it is an ideal imaging modality to monitor the thickness change of epidermal and scab tissues during wound healing processes in micron-level resolution. Traditional segmentation on epidermal and scab regions was performed manually, which is time-consuming and impractical in real-time.Aim: Develop a deep-learning-based skin layer segmentation method for automated quantitative assessment of the thickness of in-vivo epidermis and scab tissues during a time course of healing within a murine model.Approach: Five convolution neural networks (CNN) were trained using manually labelled epidermis and scab regions segmentation from 1000 OCT B-scan images (assisted by its corresponding angiographic information). The segmentation performance of five segmentation architectures were compared qualitatively and quantitatively for validation set.Results: Our results show higher accuracy and higher speed of the calculated thickness compared with human experts. The U-Net architecture represents a better performance than other deep neural network architectures with a 0.894 at F1-score, 0.875 at mean IOU, 0.933 at dice similarity coefficient, and 18.28 μm at an average symmetric surface distance. Furthermore, our algorithm is able to provide abundant quantitative parameters of the wound based on its corresponding thickness mapping in different healing phases. Among them, normalized epidermis thickness is recommended as an essential hallmark to describe the re-epithelialization process of the mouse model.Conclusions: The automatic segmentation and thickness measurements within different phases of wound healing data demonstrates that our pipeline provides a robust, quantitative, and accurate method for serving as a standard model for further research into effect of external pharmacological and physical factors

Boosting oxygen evolution reaction by activation of lattice‐oxygen sites in layered Ruddlesden‐Popper oxide

Emerging anionic redox chemistry presents new opportunities for enhancing oxygen evolution reaction (OER) activity considering that lattice-oxygen oxidation mechanism (LOM) could bypass thermodynamic limitation of conventional metal-ion participation mechanism. Thus, finding an effective method to activate lattice-oxygen in metal oxides is highly attractive for designing efficient OER electrocatalysts. Here, we discover that the lattice-oxygen sites in Ruddlesden-Popper (RP) crystal structure can be activated, leading to a new class of extremely active OER catalyst. As a proof-of-concept, the RP Sr3(Co0.8Fe0.1Nb0.1)2O7-δ (RP-SCFN) oxide exhibits outstanding OER activity (eg, 334 mV at 10 mA cm−2 in 0.1 M KOH), which is significantly higher than that of the simple SrCo0.8Fe0.1Nb0.1O3-δ perovskite and benchmark RuO2. Combined density functional theory and X-ray absorption spectroscopy studies demonstrate that RP-SCFN follows the LOM under OER condition, and the activated lattice oxygen sites triggered by high covalency of metal-oxygen bonds are the origin of the high catalytic activity.This work was financially supported by the Australian Research Council (Discovery Early Career Researcher Award No. DE190100005)

Genomic Insights Into the Admixture History of Mongolic- and Tungusic-Speaking Populations From Southwestern East Asia

As a major part of the modern Trans-Eurasian or Altaic language family, most of the Mongolic and Tungusic languages were mainly spoken in northern China, Mongolia, and southern Siberia, but some were also found in southern China. Previous genetic surveys only focused on the dissection of genetic structure of northern Altaic-speaking populations; however, the ancestral origin and genomic diversification of Mongolic and Tungusic–speaking populations from southwestern East Asia remain poorly understood because of the paucity of high-density sampling and genome-wide data. Here, we generated genome-wide data at nearly 700,000 single-nucleotide polymorphisms (SNPs) in 26 Mongolians and 55 Manchus collected from Guizhou province in southwestern China. We applied principal component analysis (PCA), ADMIXTURE, f statistics, qpWave/qpAdm analysis, qpGraph, TreeMix, Fst, and ALDER to infer the fine-scale population genetic structure and admixture history. We found significant genetic differentiation between northern and southern Mongolic and Tungusic speakers, as one specific genetic cline of Manchu and Mongolian was identified in Guizhou province. Further results from ADMIXTURE and f statistics showed that the studied Guizhou Mongolians and Manchus had a strong genetic affinity with southern East Asians, especially for inland southern East Asians. The qpAdm-based estimates of ancestry admixture proportion demonstrated that Guizhou Mongolians and Manchus people could be modeled as the admixtures of one northern ancestry related to northern Tungusic/Mongolic speakers or Yellow River farmers and one southern ancestry associated with Austronesian, Tai-Kadai, and Austroasiatic speakers. The qpGraph-based phylogeny and neighbor-joining tree further confirmed that Guizhou Manchus and Mongolians derived approximately half of the ancestry from their northern ancestors and the other half from southern Indigenous East Asians. The estimated admixture time ranged from 600 to 1,000 years ago, which further confirmed the admixture events were mediated via the Mongolians Empire expansion during the formation of the Yuan dynasty

The Ets Transcription Factor GABP Is a Component of the Hippo Pathway Essential for Growth and Antioxidant Defense

这是周大旺教授继2009年首次发现了Hippo信号通路在哺乳动物中控制器官大小及肿瘤发生具有重要作用后的又一重大研究成果，该研究系统阐述了 YAP基因在转录调控水平上的的调控机理，进一步完善了人们对Hippo信号通路的认识，也为由YAP调控异常所引发的癌症提供了一个潜在的治疗靶点。 该论文的第一作者为博士生吴黉坦和硕士生肖玉波和张世浩, 通讯作者是周大旺教授和陈兰芬副教授，该工作是与厦门市中医院、中山医院和医学高等专科学校等单位合作完成的。周大旺教授是中央首批“青年千人计划”入选者并获得国家首批“优秀青年科学基金”资助。The transcriptional coactivator Yes-associated protein (YAP) plays an important role in organ-size control and tumorigenesis. However, how Yap gene expression is regulated remains unknown. This study shows that the Ets family member GABP binds to the Yap promoter and activates YAP transcription. The depletion of GABP downregulates YAP, resulting in a G1/S cell-cycle block and increased cell death, both of which are substantially rescued by reconstituting YAP. GABP can be inactivated by oxidative mechanisms, and acetaminophen-induced glutathione depletion inhibits GABP transcriptional activity and depletes YAP. In contrast, activating YAP by deleting Mst1/Mst2 strongly protects against acetaminophen-induced liver injury. Similar to its effects on YAP, Hippo signaling inhibits GABP transcriptional activity through several mechanisms. In human liver cancers, enhanced YAP expression is correlated with increased nuclear expression of GABP. Therefore, we conclude that GABP is an activator of Yap gene expression and a potential therapeutic target for cancers driven by YAP

Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$

A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$