Peking University Shenzhen Hospital

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics. The 1000 Genomes Project has sought to comprehensively catalogue human genetic variation across populations, providing a valuable public genomic resource. The data obtained so far have found applications ranging from association studies and fine mapping studies to the filtering of likely neutral variants in rare-disease cohorts. The authors now report on the final phase of the project, phase 3, which covers previously uncharacterized areas of human genetic diversity in terms of the populations sampled and categories of characterized variation. The sample now includes more than 2,500 individuals from 26 global populations, with low coverage whole-genome and deep exome sequencing, as well as dense microarray genotyping. They find that while most common variants are shared across populations, rarer variants are often restricted to closely related populations. The authors also demonstrate the use of the phase 3 dataset as a reference panel for imputation to improve the resolution in genetic association studies.

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual. This report by the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations. Integrative analyses reveal profiles of rare and common variants in different populations. The frequencies of rare variants vary across biological pathways, and hundreds of rare, non-coding variants at conserved sites — such as changes disrupting transcription-factor motifs — can be established for each individual.

The Modification of Diet in Renal Disease (MDRD) equations provide a rapid method of assessing GFR in patients with chronic kidney disease (CKD). However, previous research indicated that modification of these equations is necessary for application in Chinese patients with CKD. The objective of this study was to modify MDRD equations on the basis of the data from the Chinese CKD population and compare the diagnostic performance of the modified MDRD equations with that of the original MDRD equations across CKD stages in a multicenter, cross-sectional study of GFR estimation from plasma creatinine, demographic data, and clinical characteristics. A total of 684 adult patients with CKD, from nine geographic regions of China were selected. A random sample of 454 of these patients were included in the training sample set, and the remaining 230 patients were included in the testing sample set. With the use of the dual plasma sampling (99m)Tc-DTPA plasma clearance method as a reference for GFR measurement, the original MDRD equations were modified by two methods: First, by adding a racial factor for Chinese in the original MDRD equations, and, second, by applying multiple linear regression to the training sample and modifying the coefficient that is associated with each variable in the original MDRD equations and then validating in the testing sample and comparing it with the original MDRD equations. All modified MDRD equations showed significant performance improvement in bias, precision, and accuracy compared with the original MDRD equations, and the percentage of estimated GFR that did not deviate >30% from the reference GFR was >75%. The modified MDRD equations that were based on the Chinese patients with CKD offered significant advantages in different CKD stages and could be applied in clinical practice, at least in Chinese patients with CKD.

Activation of the B-cell antigen receptor (BCR) signaling pathway contributes to the initiation and maintenance of B-cell malignancies and autoimmune diseases. The Bruton tyrosine kinase (Btk) is specifically required for BCR signaling as demonstrated by human and mouse mutations that disrupt Btk function and prevent B-cell maturation at steps that require a functional BCR pathway. Herein we describe a selective and irreversible Btk inhibitor, PCI-32765, that is currently under clinical development in patients with B-cell non-Hodgkin lymphoma. We have used this inhibitor to investigate the biologic effects of Btk inhibition on mature B-cell function and the progression of B cell-associated diseases in vivo. PCI-32765 blocked BCR signaling in human peripheral B cells at concentrations that did not affect T cell receptor signaling. In mice with collagen-induced arthritis, orally administered PCI-32765 reduced the level of circulating autoantibodies and completely suppressed disease. PCI-32765 also inhibited autoantibody production and the development of kidney disease in the MRL-Fas(lpr) lupus model. Occupancy of the Btk active site by PCI-32765 was monitored in vitro and in vivo using a fluorescent affinity probe for Btk. Active site occupancy of Btk was tightly correlated with the blockade of BCR signaling and in vivo efficacy. Finally, PCI-32765 induced objective clinical responses in dogs with spontaneous B-cell non-Hodgkin lymphoma. These findings support Btk inhibition as a therapeutic approach for the treatment of human diseases associated with activation of the BCR pathway.

Reports on bacteria detected in maternal fluids during pregnancy are typically associated with adverse consequences, and whether the female reproductive tract harbours distinct microbial communities beyond the vagina has been a matter of debate. Here we systematically sample the microbiota within the female reproductive tract in 110 women of reproductive age, and examine the nature of colonisation by 16S rRNA gene amplicon sequencing and cultivation. We find distinct microbial communities in cervical canal, uterus, fallopian tubes and peritoneal fluid, differing from that of the vagina. The results reflect a microbiota continuum along the female reproductive tract, indicative of a non-sterile environment. We also identify microbial taxa and potential functions that correlate with the menstrual cycle or are over-represented in subjects with adenomyosis or infertility due to endometriosis. The study provides insight into the nature of the vagino-uterine microbiome, and suggests that surveying the vaginal or cervical microbiota might be useful for detection of common diseases in the upper reproductive tract.Whether the female reproductive tract harbours distinct microbiomes beyond the vagina has been a matter of debate. Here, the authors show a subject-specific continuity in microbial communities at six sites along the female reproductive tract, indicative of a non-sterile environment.

Recent years have witnessed an upsurge in the development of non-precious catalysts (NPCs) for alkaline water electrolysis (AWE), especially with the strides made in experimental and computational techniques. In this contribution, the most recent advances in NPCs for AWE were systematically reviewed, emphasizing the application of in situ/operando experimental methods and density functional theory (DFT) calculations in their understanding and development. First, we briefly introduced the fundamentals of the anode and cathode reaction for AWE, i.e., the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER), respectively. Next, the most popular in situ/operando approaches for characterizing AWE catalysts, including hard and soft XAS, ambient-pressure XPS, liquid and identical location TEM, electrochemical mass spectrometry, and Raman spectroscopy were thoroughly summarized. Subsequently, we carefully discussed the principles, computational methods, applications, and combinations of DFT with machine learning for modeling NPCs and predicting the alkaline OER and HER. With the improved understanding of the structure-property-performance relationship of NPCs for AWE, we proceeded to overview their current development, summarising state-of-the-art design strategies to boost their activity. In addition, advances in various extensively investigated NPCs for AWE were evaluated. By conveying these methods, progress, insights, and perspectives, this review will contribute to a better understanding and rational development of non-precious AWE electrocatalysts for hydrogen production.

China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.

Since 1987, immortalized cells from the ovary of a Chinese hamster have been the workhorse for producing recombinant therapeutics, including monoclonal antibodies, blood factors, hormones, growth factors and enzymes. Xu et al. provide the genome sequence of the ancestral CHO-K1 cell line, which should aid in the optimization of current production cell lines. Chinese hamster ovary (CHO)–derived cell lines are the preferred host cells for the production of therapeutic proteins. Here we present a draft genomic sequence of the CHO-K1 ancestral cell line. The assembly comprises 2.45 Gb of genomic sequence, with 24,383 predicted genes. We associate most of the assembled scaffolds with 21 chromosomes isolated by microfluidics to identify chromosomal locations of genes. Furthermore, we investigate genes involved in glycosylation, which affect therapeutic protein quality, and viral susceptibility genes, which are relevant to cell engineering and regulatory concerns. Homologs of most human glycosylation-associated genes are present in the CHO-K1 genome, although 141 of these homologs are not expressed under exponential growth conditions. Many important viral entry genes are also present in the genome but not expressed, which may explain the unusual viral resistance property of CHO cell lines. We discuss how the availability of this genome sequence may facilitate genome-scale science for the optimization of biopharmaceutical protein production.

The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics. However, relying solely on text prompts cannot fully take advantage of the knowledge learned by the model, especially when flexible and accurate controlling (e.g., structure and color) is needed. In this paper, we aim to ``dig out" the capabilities that T2I models have implicitly learned, and then explicitly use them to control the generation more granularly. Specifically, we propose to learn low-cost T2I-Adapters to align internal knowledge in T2I models with external control signals, while freezing the original large T2I models. In this way, we can train various adapters according to different conditions, achieving rich control and editing effects in the color and structure of the generation results. Further, the proposed T2I-Adapters have attractive properties of practical value, such as composability and generalization ability. Extensive experiments demonstrate that our T2I-Adapter has promising generation quality and a wide range of applications. Our code is available at https://github.com/TencentARC/T2I-Adapter.

Optical techniques using developed laser and optical devices have made a profound impact on modern medicine, with "biomedical optics" becoming an emerging field. Sophisticated technologies have been developed in cancer nanomedicine, such as photothermal therapy and photodynamic therapy, among others. However, single-mode phototherapy cannot completely treat persistent tumors, with the challenges of relapse or metastasis remaining; therefore, combinatorial strategies are being developed. In this review, the role of light in cancer therapy and the challenges of phototherapy are discussed. The development of combinatorial strategies with other therapeutic methods, including chemotherapy, immunotherapy, gene therapy, and radiotherapy, is presented and future directions are further discussed. This review aims to highlight the significance of light in cancer therapy and discuss the combinatorial strategies that show promise in addressing the challenges of phototherapy.

* Different portions of tree root systems play distinct functional roles, yet precisely how to distinguish roots of different functions within the branching fine-root system is unclear. * Here, anatomy and mycorrhizal colonization was examined by branch order in 23 Chinese temperate tree species of both angiosperms and gymnosperms forming ectomycorrhizal and arbuscular-mycorrhizal associations. * Different branch orders showed marked differences in anatomy. First-order roots exhibited primary development with an intact cortex, a high mycorrhizal colonization rate and a low stele proportion, thus serving absorptive functions. Second and third orders had both primary and secondary development. Fourth and higher orders showed mostly secondary development with no cortex or mycorrhizal colonization, and thus have limited role in absorption. Based on anatomical traits, it was estimated that c. 75% of the fine-root length was absorptive, and 68% was mycorrhizal, averaged across species. * These results showed that: order predicted differences in root anatomy in a relatively consistent manner across species; anatomical traits associated with absorption and mycorrhizal colonization occurred mainly in the first three orders; the single diameter class approach may have overestimated absorptive root length by 25% in temperate forests.

BACKGROUND: With the advent of second-generation sequencing, the expression of gene transcripts can be digitally measured with high accuracy. The purpose of this study was to systematically profile the expression of both mRNA and miRNA genes in clear cell renal cell carcinoma (ccRCC) using massively parallel sequencing technology. METHODOLOGY: The expression of mRNAs and miRNAs were analyzed in tumor tissues and matched normal adjacent tissues obtained from 10 ccRCC patients without distant metastases. In a prevalence screen, some of the most interesting results were validated in a large cohort of ccRCC patients. PRINCIPAL FINDINGS: A total of 404 miRNAs and 9,799 mRNAs were detected to be differentially expressed in the 10 ccRCC patients. We also identified 56 novel miRNA candidates in at least two samples. In addition to confirming that canonical cancer genes and miRNAs (including VEGFA, DUSP9 and ERBB4; miR-210, miR-184 and miR-206) play pivotal roles in ccRCC development, promising novel candidates (such as PNCK and miR-122) without previous annotation in ccRCC carcinogenesis were also discovered in this study. Pathways controlling cell fates (e.g., cell cycle and apoptosis pathways) and cell communication (e.g., focal adhesion and ECM-receptor interaction) were found to be significantly more likely to be disrupted in ccRCC. Additionally, the results of the prevalence screen revealed that the expression of a miRNA gene cluster located on Xq27.3 was consistently downregulated in at least 76.7% of ∼50 ccRCC patients. CONCLUSIONS: Our study provided a two-dimensional map of the mRNA and miRNA expression profiles of ccRCC using deep sequencing technology. Our results indicate that the phenotypic status of ccRCC is characterized by a loss of normal renal function, downregulation of metabolic genes, and upregulation of many signal transduction genes in key pathways. Furthermore, it can be concluded that downregulation of miRNA genes clustered on Xq27.3 is associated with ccRCC.

Carbon dots (CDs) have tremendous potential applications in bioimaging, biomedicine, and optoelectronics. By far, it is still difficult to produce photoluminescence (PL) tunable CDs with high quantum yield (QY) across the entire visible spectrum and narrow the emission peak widths of CDs close to those of typical quantum dots. In this work, a series of CDs with tunable emission from 443 to 745 nm, quantum yield within 13-54%, and narrowed full width at half maximum (FWHM) from 108 to 55 nm, are obtained by only adjusting the reaction solvents in a one-pot solvothermal route. The distinct optical features of these CDs are based on their differences in the particle size, and the content of graphitic nitrogen and oxygen-containing functional groups, which can be modulated by controlling the dehydration and carbonization processes during solvothermal reactions. Blue, green, yellow, red, and even pure white light emitting films (Commission Internationale de L'Eclairage (CIE)= 0.33, 0.33, QY = 39%) are prepared by dispersing one or three kinds of CDs into polyvinyl alcohol with appropriate ratios. The near-infrared emissive CDs are excellent fluorescent probes for both in vitro and in vivo bioimaging because of their high QY in water, long-term stability, and low cytotoxicity.

Single image super-resolution (SISR) has witnessed great strides with the development of deep learning. However, most existing studies focus on building more complex networks with a massive number of layers. Recently, more and more researchers start to explore the application of Transformer in computer vision tasks. However, the heavy computational cost and high GPU memory occupation of the vision Transformer cannot be ignored. In this paper, we propose a novel Efficient Super-Resolution Transformer (ESRT) for SISR. ESRT is a hybrid model, which consists of a Lightweight CNN Backbone (LCB) and a Lightweight Transformer Backbone (LTB). Among them, LCB can dynamically adjust the size of the feature map to extract deep features with a low computational costs. LTB is composed of a series of Efficient Transformers (ET), which occupies a small GPU memory occupation, thanks to the specially designed Efficient Multi-Head Attention (EMHA). Extensive experiments show that ESRT achieves competitive results with low computational cost. Compared with the original Transformer which occupies 16,057M GPU memory, ESRT only occupies 4,191M GPU memory. All codes are available at https://github.com/luissen/ESRT.

// Wei-Cheng Liang 1, 2 , Wei-Ming Fu 3 , Cheuk-Wa Wong 1, 2 , Yan Wang 1 , Wei-Mao Wang 1 , Guo-Xin Hu 4 , Li Zhang 1 , Li-Jia Xiao 5 , David Chi-Cheong Wan 1 , Jin-Fang Zhang 1, 6 , Mary Miu-Yee Waye 1, 2 1 School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, P.R. China 2 Croucher Laboratory for Human Genomics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, P.R. China 3 Guangzhou Institute of Advanced Technology, Chinese Academy of Sciences, Guangzhou, P.R. China 4 Department of Infectious Diseases, Peking University Shenzhen Hospital, Shenzhen, P.R. China 5 Department of Clinical Laboratory, Nanshan Affiliated Hospital of Guangdong Medical College, Shenzhen, P.R. China 6 Department of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, P.R. China Correspondence to: Mary Miu-Yee Waye, e-mail: mary-waye@cuhk.edu.hk Jin-Fang Zhang, e-mail: zhangjf06@cuhk.edu.hk Keywords: miRNA sponges, lncRNA, ceRNA Received: February 05, 2015      Accepted: May 23, 2015      Published: June 05, 2015 ABSTRACT Recently, the long non-coding RNA (lncRNA) H19 has been identified as an oncogenic gene in multiple cancer types and elevated expression of H19 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in colorectal cancer (CRC) especially during epithelial to mesenchymal transition (EMT) progression. In our studies, H19 was characterized as a novel regulator of EMT in CRC. We found that H19 was highly expressed in mesenchymal-like cancer cells and primary CRC tissues. Stable expression of H19 significantly promotes EMT progression and accelerates in vivo and in vitro tumor growth. Furthermore, by using bioinformatics study and RNA immunoprecipitation combined with luciferase reporter assays, we demonstrated that H19 functioned as a competing endogenous RNA (ceRNA) for miR-138 and miR-200a, antagonized their functions and led to the de-repression of their endogenous targets Vimentin, ZEB1, and ZEB2, all of which were core marker genes for mesenchymal cells. Taken together, these observations imply that the lncRNA H19 modulated the expression of multiple genes involved in EMT by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and EMT progression.

Video anomaly detection under weak labels is formulated as a typical multiple-instance learning problem in previous works. In this paper, we provide a new perspective, i.e., a supervised learning task under noisy labels. In such a viewpoint, as long as cleaning away label noise, we can directly apply fully supervised action classifiers to weakly supervised anomaly detection, and take maximum advantage of these well-developed classifiers. For this purpose, we devise a graph convolutional network to correct noisy labels. Based upon feature similarity and temporal consistency, our network propagates supervisory signals from high-confidence snippets to low-confidence ones. In this manner, the network is capable of providing cleaned supervision for action classifiers. During the test phase, we only need to obtain snippet-wise predictions from the action classifier without any extra post-processing. Extensive experiments on 3 datasets at different scales with 2 types of action classifiers demonstrate the efficacy of our method. Remarkably, we obtain the frame-level AUC score of 82.12% on UCF-Crime.

Abstract In recent years, Prussian blue analogue (PBA) materials have been widely explored and investigated in energy storage/conversion fields. Herein, the structure/property correlations of PBA materials as host frameworks for various charge‐carrier ions (e.g., Na + , K + , Zn 2+ , Mg 2+ , Ca 2+ , and Al 3+ ) is reviewed, and the optimization strategies to achieve advanced performance of PBA electrodes are highlighted. Prospects for further applications of PBA materials in proton, ammonium‐ion, and multivalent‐ion batteries are summarized, with extra attention given to the selection of anode materials and electrolytes for practical implementation. This work provides a comprehensive understanding of PBA materials, and will serve as a guidance for future research and development of PBA electrodes.

Zhiming Cai and colleagues report whole-genome and whole-exome sequencing of 99 paired tumor-normal samples of transitional cell carcinoma of the bladder. They find that 32% of tumors harbor alterations in genes involved in sister chromatid cohesion, including STAG2, ESPL1, NIPBL, SMC1A and SMC3. Bladder cancer is one of the most common cancers worldwide, with transitional cell carcinoma (TCC) being the predominant form. Here we report a genomic analysis of TCC by both whole-genome and whole-exome sequencing of 99 individuals with TCC. Beyond confirming recurrent mutations in genes previously identified as being mutated in TCC, we identified additional altered genes and pathways that were implicated in TCC. Notably, we discovered frequent alterations in STAG2 and ESPL1, two genes involved in the sister chromatid cohesion and segregation (SCCS) process. Furthermore, we also detected a recurrent fusion involving FGFR3 and TACC3, another component of SCCS, by transcriptome sequencing of 42 DNA-sequenced tumors. Overall, 32 of the 99 tumors (32%) harbored genetic alterations in the SCCS process. Our analysis provides evidence that genetic alterations affecting the SCCS process may be involved in bladder tumorigenesis and identifies a new therapeutic possibility for bladder cancer.

Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.

ABSTRACT Carbapenem-resistant Enterobacteriaceae (CRE) infection is highly endemic in China, but estimates of the infection burden are lacking. We established the incidence of CRE infection from a multicenter study that covered 25 tertiary hospitals in 14 provinces. CRE cases defined as carbapenem-nonsusceptible Citrobacter freundii , Escherichia coli , Enterobacter cloacae , or Klebsiella pneumoniae infections during January to December 2015 were collected and reviewed from medical records. Antimicrobial susceptibility testing and carbapenemase gene identification were performed. Among 664 CRE cases, most were caused by K. pneumoniae (73.9%), followed by E. coli (16.6%) and E. cloacae (7.1%). The overall CRE infection incidence per 10,000 discharges was 4.0 and differed significantly by region, with the highest in Jiangsu (14.97) and the lowest in Qinghai (0.34). Underlying comorbidities were found in 83.8% of patients; the median patient age was 62 years (range, 45 to 74 years), and 450 (67.8%) patients were male. Lower respiratory tract infections (65.4%) were the most common, followed by urinary tract infection (16.6%), intra-abdominal infection (7.7%), and bacteremia (7.7%). The overall hospital mortality rate was 33.5%. All isolates showed nonsusceptibility to carbapenems and cephalosporins. The susceptibility rate of polymyxin B was >90%. Tigecycline demonstrated a higher susceptibility rate against E. coli than against K. pneumoniae (90.9% versus 40.2%). Of 155 clinical isolates analyzed, 89% produced carbapenemases, with a majority of isolates producing KPC (50%) or NDM (33.5%)-type beta-lactamases among K. pneumoniae and E. coli . The incidence of CRE infection in China was 4.0 per 10,000 discharges. The patient-based disease burden in tertiary hospitals in China is severe, suggesting an urgent need to enhance infection control.