Abstract
Background
The high cost and insufficient supply of human papillomavirus (HPV) vaccines have slowed the pace of controlling cervical cancer. A phase III clinical trial was conducted to ...evaluate the efficacy, safety, and immunogenicity of a novel Escherichia coli-produced bivalent HPV-16/18 vaccine.
Methods
A multicenter, randomized, double-blind trial started on November 22, 2012 in China. In total, 7372 eligible women aged 18–45 years were age-stratified and randomly assigned to receive three doses of the test or control (hepatitis E) vaccine at months 0, 1, and 6. Co-primary endpoints included high-grade genital lesions and persistent infection (over 6 months) associated with HPV-16/18. The primary analysis was performed on a per-protocol susceptible population of individuals who were negative for relevant HPV type-specific neutralizing antibodies (at day 0) and DNA (at day 0 through month 7) and who received three doses of the vaccine. This report presents data from a prespecified interim analysis used for regulatory submission.
Results
In the per-protocol cohort, the efficacies against high-grade genital lesions and persistent infection were 100.0% (95% confidence interval = 55.6% to 100.0%, 0 of 3306 in the vaccine group vs 10 of 3296 in the control group) and 97.8% (95% confidence interval = 87.1% to 99.9%, 1 of 3240 vs 45 of 3246), respectively. The side effects were mild. No vaccine-related serious adverse events were noted. Robust antibody responses for both types were induced and persisted for at least 42 months.
Conclusions
The E coli-produced HPV-16/18 vaccine is well tolerated and highly efficacious against HPV-16/18–associated high-grade genital lesions and persistent infection in women.
During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in ...other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences.
Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined.
At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7
44.9 years), had more cases with comorbidity (32.9%
19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7
4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0%
11.1%, death rate 7.3%
0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4
4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)).
There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.
Bioprinting is the most convenient microfabrication method to create biomimetic three‐dimensional (3D) cardiac tissue constructs, that can be used to regenerate damaged tissue and provide platforms ...for drug screening. However, existing bioinks, which are usually composed of polymeric biomaterials, are poorly conductive and delay efficient electrical coupling between adjacent cardiac cells. To solve this problem, a gold nanorod (GNR)‐incorporated gelatin methacryloyl (GelMA)‐based bioink is developed for printing 3D functional cardiac tissue constructs. The GNR concentration is adjusted to create a proper microenvironment for the spreading and organization of cardiac cells. At optimized concentrations of GNR, the nanocomposite bioink has a low viscosity, similar to pristine inks, which allows for the easy integration of cells at high densities. As a result, rapid deposition of cell‐laden fibers at a high resolution is possible, while reducing shear stress on the encapsulated cells. In the printed GNR constructs, cardiac cells show improved cell adhesion and organization when compared to the constructs without GNRs. Furthermore, the incorporated GNRs bridge the electrically resistant pore walls of polymers, improve the cell‐to‐cell coupling, and promote synchronized contraction of the bioprinted constructs. Given its advantageous properties, this gold nanocomposite bioink may find wide application in cardiac tissue engineering.
A gold nanorod‐incorporated gelatin methacryloyl‐based bioink for printing of 3D cardiac tissue constructs is developed. The rapid deposition of the cell‐laden fibers at a high resolution is achieved, while reducing the shear stress on the encapsulated cells. The incorporated gold nanorods improve the electrical propagation between cardiac cells and promote their functional improvement in the printed cardiac construct.
As core units of organ tissues, cells of various types play their harmonious rhythms to maintain the homeostasis of the human body. It is essential to identify the characteristics of cells in human ...organs and their regulatory networks for understanding the biological mechanisms related to health and disease. However, a systematic and comprehensive single-cell transcriptional profile across multiple organs of a normal human adult is missing.
We perform single-cell transcriptomes of 84,363 cells derived from 15 tissue organs of one adult donor and generate an adult human cell atlas. The adult human cell atlas depicts 252 subtypes of cells, including major cell types such as T, B, myeloid, epithelial, and stromal cells, as well as novel COCH
fibroblasts and FibSmo cells, each of which is distinguished by multiple marker genes and transcriptional profiles. These collectively contribute to the heterogeneity of major human organs. Moreover, T cell and B cell receptor repertoire comparisons and trajectory analyses reveal direct clonal sharing of T and B cells with various developmental states among different tissues. Furthermore, novel cell markers, transcription factors, and ligand-receptor pairs are identified with potential functional regulations in maintaining the homeostasis of human cells among tissues.
The adult human cell atlas reveals the inter- and intra-organ heterogeneity of cell characteristics and provides a useful resource in uncovering key events during the development of human diseases in the context of the heterogeneity of cells and organs.
pH determines selectivity: The ligation of peptide hydrazides is a new method for protein chemical synthesis that is complementary to native chemical ligation. Peptide hydrazides may be the ...long‐sought reagent equivalent to a “thioester synthon”, one that is stable to the conditions of native chemical ligation.
The lithium metal anode has attracted soaring attention as an ideal battery anode. Unfortunately, nonuniform Li nucleation results in uncontrollable growth of dendritic Li, which incurs serious ...safety issues and poor electrochemical performance, hindering its practical applications. Herein, this study shows that uniform Li nucleation/growth can be induced by an ultralight 3D current collector consisting of in situ nitrogen‐doped graphitic carbon foams (NGCFs) to realize suppressing dendritic Li growth at the nucleating stage. The N‐containing functional groups guide homogenous growth of Li nucleus nanoparticles and the initial Li nucleus seed layer regulates the following well‐distributed Li growth. Benefiting from such favorable Li growth behavior, superior electrochemical performance can be achieved as evidenced by the high Coulombic efficiency (≈99.6% for 300 cycles), large capacity (10 mA h cm−2, 3140 mA h g−1NGCF‐Li), and ultralong lifespan (>1200 h) together with low overpotential (<25 mV at 3 mA cm−2); even under a high current density up to 10 mA cm−2, it still displays low overpotential of 62 mV.
Uniform Li nucleation/growth can be induced by an ultralight 3D current collector consisting of in situ nitrogen‐doped graphitic carbon foams for high‐performance lithium‐metal anodes. The N‐containing functional groups guide initial homogeneous formation of Li nanoparticles and the initial nucleus seed layer regulates the even Li growth that follows. Significantly improved electrochemical performance can be achieved.
The heterogeneous nature of tumour microenvironment (TME) underlying diverse treatment responses remains unclear in nasopharyngeal carcinoma (NPC). Here, we profile 176,447 cells from 10 NPC ...tumour-blood pairs, using single-cell transcriptome coupled with T cell receptor sequencing. Our analyses reveal 53 cell subtypes, including tumour-infiltrating CD8
T, regulatory T (Treg), and dendritic cells (DCs), as well as malignant cells with different Epstein-Barr virus infection status. Trajectory analyses reveal exhausted CD8
T and immune-suppressive TNFRSF4
Treg cells in tumours might derive from peripheral CX3CR1
CD8
T and naïve Treg cells, respectively. Moreover, we identify immune-regulatory and tolerogenic LAMP3
DCs. Noteworthily, we observe intensive inter-cell interactions among LAMP3
DCs, Treg, exhausted CD8
T, and malignant cells, suggesting potential cross-talks to foster an immune-suppressive niche for the TME. Collectively, our study uncovers the heterogeneity and interacting molecules of the TME in NPC at single-cell resolution, which provide insights into the mechanisms underlying NPC progression and the development of precise therapies for NPC.
•A Domain-adversarial Neural Network based damage detection method for bridge structures.•The domain invariant feature space between the source and target domain is extracted by adversarial ...training.•The damage label information is transferred from the source domain to the target domain for damage detection.•The proposed method can reduce the distribution gap and achieve higher damage detection accuracy.
Bridge damage detection methods based on moving load induced response and deep learning are popular, and they are effective when the training data generated by a finite element model (FEM) and the testing data measured from the actual bridge have the same distribution. However, their distributions are normally different due to the measurement and model error. This paper proposes a Domain-adversarial Neural Network (DANN) based damage detection method for bridge structures. The moving load induced displacement responses of the FEM and the actual bridge are taken as network inputs, and the feature space with the minimum differentiation between the edge distributions of the FEM (source domain) and the actual bridge (target domain) is extracted by adversarial training between the domain discriminator and the feature extractor. This feature space is a domain invariant feature of the source domain and the target domain and contains damage information only. Thus the damage label information is transferred from the source domain to the target domain for damage detection. Numerical and experimental examples manifest that the proposed method can reduce the distribution gap between the source domain and the target domain, and achieve higher damage detection accuracy than that of the traditional deep learning method by using a small number of sensors without a large amount of damage label data.
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