Showing papers by "Xin Zhou published in 2022"
TL;DR: In this article , a genomic and transcriptomic analysis of 2,754 childhood acute lymphoblastic leukemias identifies 376 putative driver genes, and associations between disease subtypes and prognosis.
Abstract: Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Here, using whole-genome, exome and transcriptome sequencing of 2,754 childhood patients with ALL, we find that, despite a generally low mutation burden, ALL cases harbor a median of four putative somatic driver alterations per sample, with 376 putative driver genes identified varying in prevalence across ALL subtypes. Most samples harbor at least one rare gene alteration, including 70 putative cancer driver genes associated with ubiquitination, SUMOylation, noncoding transcripts and other functions. In hyperdiploid B-ALL, chromosomal gains are acquired early and synchronously before ultraviolet-induced mutation. By contrast, ultraviolet-induced mutations precede chromosomal gains in B-ALL cases with intrachromosomal amplification of chromosome 21. We also demonstrate the prognostic significance of genetic alterations within subtypes. Intriguingly, DUX4- and KMT2A-rearranged subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of the ALL genomic landscape and associated outcomes. A genomic and transcriptomic analysis of 2,754 childhood acute lymphoblastic leukemias identifies 376 putative driver genes, and associations between disease subtypes and prognosis.
46 citations
TL;DR: In this article , appropriate data acquisition approaches for UBEM are reviewed for four data inputs, learning from both building science and other disciplines such as geography, transportation and computer science.
28 citations
TL;DR: Wang et al. as discussed by the authors proposed a method to detect egg freshness, scattered yolk and eggshell cracks by applying hyperspectral imaging (HSI), multivariate analysis and image process.
22 citations
TL;DR: A feature pyramid structure with a refined hierarchical-split block, referred to as Scale-FPN, which can better handle the challenging problem of scale variation across object instances and improves the state-of-the-art result of CrowdDet from 41.4% to 39.9% MR-2.
20 citations
TL;DR: In this article , a combined cyber-attack model is proposed, which utilises two sets of independent stochastic sequences to reflect randomly occurring cyber-attacks, and a dynamic event-triggered protocol is constructed to relieve the restricted bandwidth pressure by reducing the data transmission of the communication channel from the plant to the controller.
17 citations
TL;DR: In this article , single-cell and single-nucleus RNA sequencing was used to show that RMS tumors recapitulate the spectrum of embryonal myogenesis and that targeting each developmental state in embryonal RMS is an effective strategy for improving outcomes by preventing disease recurrence.
17 citations
17 citations
TL;DR: Wang et al. as mentioned in this paper established patient-derived organoids from colorectal cancer patients and performed single-cell RNA-Seq for pairwise samples from seven patients for both organoids and their corresponding tumor and normal tissues in vivo.
Abstract: Patient-derived organoid culture is a powerful system for studying the molecular mechanisms of cancers, especially colorectal cancer (CRC), one of the most prevalent cancers worldwide. There are two main types of 3D culture methods for colonic cells, but the similarities and differences between gene expression patterns in different culture media remain largely unexplored.Here, we establish patient-derived organoids from colorectal cancer patients and perform single-cell RNA-Seq for pairwise samples from seven patients for both organoids and their corresponding tumor and normal tissues in vivo. We find that organoids derived from tumor tissues faithfully recapitulate the main gene expression signatures of cancer cells in vivo. On the other hand, organoids derived from normal tissues exhibited some tumor-like features at the whole transcriptome level but retained normal genomic features, such as CNVs, point mutations, and normal global DNA methylation levels, for both cultural media. More importantly, we show that conditioned medium outperforms chemical-defined medium in long-term culture of tumor epithelial cells. Finally, we mutually exchange the culture medium for the organoids and find that after interchanging the medium, the organoid cells basically maintain the transcriptome characteristics of the original medium.Our work gives a thorough evaluation of both the cultural conditions and the biological features of organoids of CRC patients.
16 citations
TL;DR: In this article , the authors highlight recent advances in ML-driven energy research, outline current and future challenges, and describe what is required to make the best use of ML techniques.
Abstract: Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances - at the materials, devices and systems levels - for the efficient harvesting, storage, conversion and management of renewable energy. Energy researchers have begun to incorporate machine learning (ML) techniques to accelerate these advances. In this Perspective, we highlight recent advances in ML-driven energy research, outline current and future challenges, and describe what is required to make the best use of ML techniques. We introduce a set of key performance indicators with which to compare the benefits of different ML-accelerated workflows for energy research. We discuss and evaluate the latest advances in applying ML to the development of energy harvesting (photovoltaics), storage (batteries), conversion (electrocatalysis) and management (smart grids). Finally, we offer an overview of potential research areas in the energy field that stand to benefit further from the application of ML.
13 citations
TL;DR: In this article , the authors formulated a morphological design framework for urban green infrastructures (UGI) as part of the urban design process to reduce urban building energy consumption.
12 citations
TL;DR: In this article , the effects and mechanism of action of Qingfeiyin (QFY) using network pharmacology and molecular docking were systematically explored using a protein-protein interaction (PPI) network to screen the core targets.
TL;DR: The present study shows that brain-derived neurotrophic factor precursor (proBDNF) and its high-affinity pan-75 neurotrophin receptor (p75NTR) are highly expressed in CD19+CD27hiCD38hi ASCs in patients with SLE and in lupus-like mice, and suggests that proBDNF-p 75NTR signaling plays a critical pathogenic role in SLE through promoting ASC dysfunction.
Abstract: Inappropriate expansion of antibody-secreting cells (ASCs) is typical of systemic lupus erythematosus (SLE), but the regulatory signaling of pathogenic ASCs is unclear. The present study shows that brain-derived neurotrophic factor precursor (proBDNF) and its high-affinity pan-75 neurotrophin receptor (p75NTR) are highly expressed in CD19+CD27hiCD38hi ASCs in patients with SLE and in CD19+CD44hiCD138+ ASCs in lupus-like mice. The increased proBDNF+ ASCs were positively correlated with clinical symptoms and higher titers of autoantibodies in SLE. Administration of monoclonal antibodies against proBDNF or specific knockout of p75NTR in CD19+ B cells exerted a therapeutic effect on lupus mice by limiting the proportion of ASCs, reducing the production of autoantibodies and attenuating kidney injury. Blocking the biological function of proBDNF or p75NTR also inhibits ASC differentiation and antibody production in vitro. Together, these findings suggest that proBDNF-p75NTR signaling plays a critical pathogenic role in SLE through promoting ASC dysfunction.
TL;DR: Adding most self-reported favorable diet and lifestyle exposures to multivariate modeling improved 5-year DFS of all patients and by 6.3% for good-risk, 21.4% for average- risk, and 42.6% for poor-risk clinical and pathologic features.
Abstract: PURPOSE Current tools in predicting survival outcomes for patients with colon cancer predominantly rely on clinical and pathologic characteristics, but increasing evidence suggests that diet and lifestyle habits are associated with patient outcomes and should be considered to enhance model accuracy. METHODS Using an adjuvant chemotherapy trial for stage III colon cancer (CALGB 89803), we developed prediction models of disease-free survival (DFS) and overall survival by additionally incorporating self-reported nine diet and lifestyle factors. Both models were assessed by multivariable Cox proportional hazards regression and externally validated using another trial for stage III colon cancer (CALGB/SWOG 80702), and visual nomograms of prediction models were constructed accordingly. We also proposed three hypothetical scenarios for patients with (1) good-risk, (2) average-risk, and (3) poor-risk clinical and pathologic features, and estimated their predictive survival by considering clinical and pathologic features with or without adding self-reported diet and lifestyle factors. RESULTS Among 1,024 patients (median age 60.0 years, 43.8% female), we observed 394 DFS events and 311 deaths after median follow-up of 7.3 years. Adding self-reported diet and lifestyle factors to clinical and pathologic characteristics meaningfully improved performance of prediction models (c-index from 0.64 [95% CI, 0.62 to 0.67] to 0.69 [95% CI, 0.67 to 0.72] for DFS, and from 0.67 [95% CI, 0.64 to 0.70] to 0.71 [95% CI, 0.69 to 0.75] for overall survival). External validation also indicated good performance of discrimination and calibration. Adding most self-reported favorable diet and lifestyle exposures to multivariate modeling improved 5-year DFS of all patients and by 6.3% for good-risk, 21.4% for average-risk, and 42.6% for poor-risk clinical and pathologic features. CONCLUSION Diet and lifestyle factors further inform current recurrence and survival prediction models for patients with stage III colon cancer. Summary: We developed and validated novel prediction models for patients with colon cancer to better estimate survival
TL;DR: J1C2 Presentation Abstract at IEEE SERVICES 2022 for IEEE Transactions on Services Computing DOI 10.1109/TSC.2022.3157145 is presented.
Abstract: [J1C2 Presentation Abstract at IEEE SERVICES 2022 for IEEE Transactions on Services Computing DOI 10.1109/TSC.2022.3157145]
TL;DR: In vivo experiments demonstrated that naringenin remarkably reversed LPS-induced bone loss and assisted the healing of calvarial defect, serving as a potential anabolic treatment for pathological bone loss.
Abstract: Bone undergoes constant remodeling of formation by osteoblasts and resorption by osteoclasts. In particular, macrophages have been reported to play an essential role in the regulation of bone homeostasis and regeneration. Naringenin, the predominant flavanone in citrus fruits, is reported to exert anti-inflammatory, anti-osteoclastic, and osteogenic effects. However, whether naringenin could modulate the crosstalk between macrophages and osteoblasts/osteoclasts remains to be investigated. In this study, we confirmed that naringenin enhanced osteogenesis and inhibited osteoclastogenesis directly. Naringenin promoted M2 transition and the secretion of osteogenic cytokines including IL-4, IL-10, BMP2, and TGF-β, while suppressing LPS-induced M1 polarization and the production of proinflammatory factors such as TNF-α and IL-1β. In addition, the coculture of primary bone mesenchymal stem cells (BMSCs)/bone marrow monocytes (BMMs) with macrophages showed that the naringenin-treated medium significantly enhanced osteogenic differentiation and impeded osteoclastic differentiation in both inflammatory and non-inflammatory environment. Moreover, in vivo experiments demonstrated that naringenin remarkably reversed LPS-induced bone loss and assisted the healing of calvarial defect. Taken together, naringenin serves as a potential anabolic treatment for pathological bone loss.
TL;DR: In this paper , a co-simulation technique combining urban microclimate and urban energy is proposed, and a quantitative analysis of the correlation between urban energy use and urban vegetation morphology is presented.
TL;DR: In this article , the authors present a review of the latest advances in multiscale structure imaging from organelles to the whole brain, including Magnetic Resonance Imaging (MRI), CT, PET, serial-section electron microscopy (ssEM), light microscopy, and synchrotron-based X-ray microscopy.
Abstract: Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.
TL;DR: In this paper , the problem of finite-time dissipative control for discrete-time stochastic delayed systems (DTSDSs) with Markovian switching and interval parameters is studied.
TL;DR: In this paper , the authors used a meteorological tower in Beijing as a model to provide a reduced-order method for data of typical meteorological years (TMY) and outdoor air design condition for high-rise buildings.
01 May 2022
TL;DR: This paper proposes a safety-aware DRL framework for single-hall data center cooling control that applies offline imitation learning and online post-hoc rectification to holis-tically prevent thermal unsafety during online DRL.
Abstract: Deep reinforcement learning (DRL) has shown good performance in tackling Markov decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising approach to improving the energy efficiency of data center cooling. However, enforcement of thermal safety constraint during DRL's state exploration is a main challenge. The widely adopted reward shaping approach adds negative reward when the exploratory action results in unsafety. Thus, it needs to experience sufficient unsafe states before it learns how to prevent unsafety. In this paper, we propose a safety-aware DRL framework for single-hall data center cooling control. It applies offline imitation learning and online post-hoc rectification to holis-tically prevent thermal unsafety during online DRL. In particular, the post-hoc rectification searches for the minimum modification to the DRL-recommended action such that the rectified action will not result in unsafety. The rectification is designed based on a thermal state transition model that is fitted using historical safe operation traces and able to extrapolate the transitions to unsafe states ex-plored by DRL. Extensive evaluation for chilled water and direct expansion cooled data centers in two climate conditions shows that our approach saves 22.7% to 26.6% total data center power compared with conventional control, reduces safety violations by 94.5% to 99% compared with reward shaping.
TL;DR: In this paper , the authors proposed a physics-based model of building envelope thermal transmittance to generate the U-value distributions of building stocks, and compared the impact of uncertainty in building envelope U-values on heating/cooling demand at the urban scale, taking 33,222 residential buildings in Beijing as a case study.
TL;DR: In this paper , the role of the RNA helicase DEAD-box (DDX) family in colorectal cancer has not been elucidated, but the expression data of CRC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed.
Abstract: Colorectal cancer (CRC) has become the second deadliest cancer in the world and severely threatens human health. An increasing number of studies have focused on the role of the RNA helicase DEAD-box (DDX) family in CRC. However, the mechanism of DDX10 in CRC has not been elucidated.In our study, we analysed the expression data of CRC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Subsequently, we performed cytological experiments and animal experiments to explore the role of DDX10 in CRC cells. Furthermore, we performed Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analyses. Finally, we predicted the interacting protein of DDX10 by LC-MS/MS and verified it by coimmunoprecipitation (Co-IP) and qPCR.In the present study, we identified that DDX10 mRNA was extremely highly expressed in CRC tissues compared with normal colon tissues in the TCGA and GEO databases. The protein expression of DDX10 was measured by immunochemistry (IHC) in 17 CRC patients. The biological roles of DDX10 were explored via cell and molecular biology experiments in vitro and in vivo and cell cycle assays. We found that DDX10 knockdown markedly reduced CRC cell proliferation, migration and invasion. Then, we constructed a PPI network with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA) showed that DDX10 was closely related to RNA splicing and E2F targets. Using LC-MS/MS and Co-IP assays, we discovered that RPL35 is the interacting protein of DDX10. In addition, we hypothesize that RPL35 is related to the E2F pathway and the immune response in CRC.In conclusion, provides a better understanding of the molecular mechanisms of DDX10 in CRC and provides a potential biomarker for the diagnosis and treatment of CRC.
TL;DR: CIViC as mentioned in this paper is a public-domain, crowd-sourced and adaptable knowledgebase of evidence for the clinical interpretation of variants in cancer, designed to reduce barriers to knowledge sharing and alleviate the variant-interpretation bottleneck.
Abstract: As guidelines, therapies and literature on cancer variants expand, the lack of consensus variant interpretations impedes clinical applications. CIViC is a public-domain, crowd-sourced and adaptable knowledgebase of evidence for the clinical interpretation of variants in cancer, designed to reduce barriers to knowledge sharing and alleviate the variant-interpretation bottleneck.
TL;DR: In this paper , the authors used nuclear magnetic resonance spectroscopy to show that the truncation alters α-syn conformation, resulting in an attractive interaction of the N-terminus with membranes and molecular chaperone, protein disulfide isomerase (PDI).
Abstract: Abstract α-Synuclein (α-syn) is the main protein component of Lewy bodies, the major pathological hallmarks of Parkinson’s disease (PD). C-terminally truncated α-syn is found in the brain of PD patients, reduces cell viability and tends to form fibrils. Nevertheless, little is known about the mechanisms underlying the role of C-terminal truncation on the cytotoxicity and aggregation of α-syn. Here, we use nuclear magnetic resonance spectroscopy to show that the truncation alters α-syn conformation, resulting in an attractive interaction of the N-terminus with membranes and molecular chaperone, protein disulfide isomerase (PDI). The truncated protein is more toxic to mitochondria than full-length protein and diminishes the effect of PDI on α-syn fibrillation. Our findings reveal a modulatory role for the C-terminus in the cytotoxicity and aggregation of α-syn by interfering with the N-terminus binding to membranes and chaperone, and provide a molecular basis for the pathological role of C-terminal truncation in PD pathogenesis.
TL;DR: In this article , the authors present a review of the research conducted on UGI modeling in numerical simulations of building energy consumption over the past 35 years and outlined the general workflow of these simulations.
TL;DR: Outcomes and molecular features of children with CNS-PNETs from two multi-center risk-adapted studies complemented by a non-protocol institutional cohort are reported to shed light on response to therapy and guide clinical decision-making.
TL;DR: In this article , an intelligent prediction algorithm combining feed-forward and recurrent networks and a fault-tolerant control strategy combining analytical redundancy and controller switching was proposed for the direct thrust control system of aeroengines.
TL;DR: In this paper , C1q/tumour necrosis factor-related protein-9 (CTRP9) has been shown to be involved in diverse inflammatory diseases, and the underlying impact of CTRP9 on NLRP3 inflammasome activation was assessed.
TL;DR: In this paper , a method for comprehensive evaluation that combines subjective and objective weighing approaches is proposed to address the issue of smart grid planning and construction. But, the evaluation model is based on a set of evaluation index system, and the actual data from the distribution network is evaluated and scored.
Abstract: In the context of smart grid planning and construction, how to tackle the future distribution network, a comprehensive evaluation of smart distribution network planning has become an urgent problem to be solved. To address this issue, this research provides a method for comprehensive evaluation that combines subjective and objective weighing approaches. Firstly, a set of evaluation index system is constructed and quantified based on the characteristics of the future distribution network; after that a comprehensive evaluation model is established and a subjective and objective weighting method combining AHP-entropy weighting method is used to weight the indicators; Finally, the actual data from the distribution network is evaluated and scored. Based on the scoring verification results, the correctness and effectiveness of the method proposed in this paper are verified.