E6 Protein Expressed by High-Risk HPV Activates Super-Enhancers of the EGFR and c-MET Oncogenes by Destabilizing the Histone

The high-risk (HR) human papillomaviruses (HPV) are causative agents of anogenital tract dysplasia and cancers and a fraction of head and neck cancers. The HR HPV E6 oncoprotein possesses canonical oncogenic functions, such as p53 degradation and telomerase activation. It is also capable of stimulating expression of several oncogenes, but the molecular mechanism underlying these events is poorly understood. Here, we provide evidence that HPV16 E6 physically interacts with histone H3K4 demethylase KDM5C, resulting in its degradation in an E3 ligase E6AP- and proteasome-dependent manner. Moreover, we found that HPV16-positive cancer cell lines exhibited lower KDM5C protein levels than HPV-negative cancer cell lines. Restoration of KDM5C significantly suppressed the tumorigenicity of CaSki cells, an HPV16-positive cervical cancer cell line. Whole genome ChIP-seq and RNA-seq results revealed that CaSki cells contained super-enhancers in the proto-oncogenes EGFR and c-MET. Ectopic KDM5C dampened these super-enhancers and reduced the expression of proto-oncogenes. This effect was likely mediated by modulating H3K4me3/H3K4me1 dynamics and decreasing bidirectional enhancer RNA transcription. Depletion of KDM5C or HPV16 E6 expression activated these two super-enhancers. These results illuminate a pivotal relationship between the oncogenic E6 proteins expressed by HR HPV isotypes and epigenetic activation of super-enhancers in the genome that drive expression of key oncogenes like EGFR and c-MET. Significance: This study suggests a novel explanation for why infections with certain HPV isotypes are associated with elevated cancer risk by identifying an epigenetic mechanism through which E6 proteins expressed by those isotypes can drive expression of key oncogenes.</p

A Global View of Cancer-Specific Transcript Variants by Subtractive Transcriptome-Wide Analysis

BACKGROUND: Alternative pre-mRNA splicing (AS) plays a central role in generating complex proteomes and influences development and disease. However, the regulation and etiology of AS in human tumorigenesis is not well understood. METHODOLOGY/PRINCIPAL FINDINGS: A Basic Local Alignment Search Tool database was constructed for the expressed sequence tags (ESTs) from all available databases of human cancer and normal tissues. An insertion or deletion in the alignment of EST/EST was used to identify alternatively spliced transcripts. Alignment of the ESTs with the genomic sequence was further used to confirm AS. Alternatively spliced transcripts in each tissue were then subtractively cross-screened to obtain tissue-specific variants. We systematically identified and characterized cancer/tissue-specific and alternatively spliced variants in the human genome based on a global view. We identified 15,093 cancer-specific variants of 9,989 genes from 27 types of human cancers and 14,376 normal tissue-specific variants of 7,240 genes from 35 normal tissues, which cover the main types of human tumors and normal tissues. Approximately 70% of these transcripts are novel. These data were integrated into a database HCSAS (http://202.114.72.39/database/human.html, pass:68756253). Moreover, we observed that the cancer-specific AS of both oncogenes and tumor suppressor genes are associated with specific cancer types. Cancer shows a preference in the selection of alternative splice-sites and utilization of alternative splicing types. CONCLUSIONS/SIGNIFICANCE: These features of human cancer, together with the discovery of huge numbers of novel splice forms for cancer-associated genes, suggest an important and global role of cancer-specific AS during human tumorigenesis. We advise the use of cancer-specific alternative splicing as a potential source of new diagnostic, prognostic, predictive, and therapeutic tools for human cancer. The global view of cancer-specific AS is not only useful for exploring the complexity of the cancer transcriptome but also widens the eyeshot of clinical research

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Contact fatigue model and life prediction of compound motion curve-face gear pair

Different from the common face gear pair fixed rotation motion between intersecting axes, the compound transmission of the curve-face gear is a new motion form, which can convert rotational motion into rotation and movement motion. To solve the contact fatigue life problem of this new motion form gear pair, a new contact fatigue life calculation method of the compound transmission curve-face gear pair was proposed. Based on the space gear engagement principle and the fracture mechanics theory, the theoretical contact fatigue model of the curve-face gear composite transmission was established. Considering that the contact load for every tooth is time-varying in the half-period of the curve-face gear, the contact fatigue life stage of the curve-face gear was divided into crack initiation and crack growth, and the crack growth fatigue life for each tooth was calculated using the finite element method. The curve-face gear pair was processed in the five-axis NC machining center and the compound transmission experiment platform of the curve-face gear was set up to measure the tooth surface dynamic contact stress, and the overall life of the curve-face gear was predicted. The comparison analysis between theoretical and experimental results verified the correctness of the theoretical contact fatigue calculation model.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Computational model of pesticide deposition distribution on canopies for air-assisted spraying

The deposited pesticide distribution in fruit tree canopies is crucial for evaluating the efficacy of air-assisted spraying in orchards. Most studies have determined the impact of pesticide application on pesticide deposition on canopies without a quantitative computational model. In this study, an air-assisted orchard sprayer with airflow control was used to perform spraying experiments on artificial and peach trees. In the spraying experiment on an artificial tree, a canopy with leaf areas ranging from 2.54~5.08 m2 was found to require an effective air speed of 18.12~37.05 m/s. The canopy leaf area, air speed at the sprayer fan outlet and spray distance were used as test factors in a three-factor five-level quadratic general rotational orthogonal test to develop a computational model for pesticide deposition at the inner, outer and middle regions of a fruit tree canopy with R2 values of 0.9042, 0.8575 and 0.8199, respectively. A significance analysis was used to rank the influencing factors for the deposited pesticide distribution in decreasing order of significance as follows: the spray distance, leaf area and air speed for the inner region of the canopy, followed by the spray distance, air speed and leaf area for the middle and outer regions of the canopy. The results of the verification test conducted in a peach orchard showed that the computational errors of the pesticide deposition model for the inner, middle and outer regions of the canopy were 32.62%, 22.38% and 23.26%, respectively. The results provide support for evaluating the efficacy of an air-assisted orchard sprayer and optimizing the sprayer parameters

Exploring the Evolution of New Mobile Services

The emergence and widespread use of mobile Internet technology has led to many different kinds of new mobile communications services, such as WeChat. Users could have more choices when attempting to satisfy their communications needs. The ability to predict the way in which users will use new mobile communications services is extremely valuable to mobile communications service providers. In this work, we propose a method for predicting how a user will use a new mobile service. Our scheme is inspired by the evolutionary game theory. With large-scale real world datasets collected from mobile service providers, we first extract the benefit-related features for users who were starting to use a new mobile service. Then we design our training and prediction methods for predicting potential users. We evaluate our scheme using experiments with large-scale real data. The results show that our approach can predict users’ future behavior with satisfying accuracy

Efficacy and safety of daptomycin for the treatment of infectious disease: a meta-analysis based on randomized controlled trials

A systematic review and meta-analysis based on randomized controlled trials (RCTs) of the efficacy and safety of daptomycin versus comparators. Electronic databases (PubMed, Embase, Cochrane Central Register of Controlled Trials and clinical registered trials) were searched to identify RCTs that assessed the efficacy and safety of daptomycin versus therapy with comparators. Two reviewers independently applied selection criteria, performed a quality assessment and extracted the data. The I-2 statistic was calculated for heterogeneity, and a random-effects or fixed-effects model was used for estimates of risk ratio (RR). The primary outcome assessed was clinical treatment success among the intention-to-treat (ITT) population. Thirteen trials fulfilled the inclusion criteria. Daptomycin was as efficacious as comparator regimens among the ITT population (RRaEuroS=aEuroS0.98, 95% CI 0.93-1.03) but had a lower efficacy among the clinically evaluable (CE) population (RRaEuroS=aEuroS0.96, 95% CI 0.93-1.00). Subgroup analyses according to the quality of the trial, the type of antibiotic and the type of infection did not alter the outcomes. No significant difference was identified for all-cause mortality between the daptomycin and comparator groups (RRaEuroS=aEuroS1.17, 95% CI 0.76-1.79) but daptomycin therapy did reduce the duration of treatment. Daptomycin caused a significantly lower incidence of renal impairment, nausea and headache but caused a reversible increase in creatine phosphokinase (CPK). Subgroup analysis indicated that daptomycin was significantly associated with a higher incidence of CPK elevation and fewer renal impairments among the population with a mean age a parts per thousand currency sign60 years and a dose of daptomycin a parts per thousand yen6 mg/kg/24 h. Daptomycin showed efficacy similar to the comparator regimens among the ITT population but lower efficacy among the CE population. Fewer adverse effects in total, but more CPK elevation effects, were observed in patients treated with daptomycin.Infectious DiseasesMicrobiologyPharmacology &amp; PharmacySCI(E)[email protected]

Achieving urban net-zero targets through regionalized electric bus penetration and energy transition

The electrification of public transit is one of the key actions in the transportation sector. This study proposed an innovative framework for analyzing the effectiveness and emission reduction potential of electrifying transit policies. The future energy consumption, GHG emissions, and pollutant emissions of bus fleets in representative Canadian cities were analyzed. Under the high oil price scenarios, this study incorporated the upfront infrastructure costs, the social costs of pollution, and the dynamics of carbon prices and fuel prices, allowing for a comprehensive analysis of carbon reduction costs during transition. Compared to the BAU scenarios, the cumulative GHG emissions from 2019 to 2030 of bus fleet in ESD scenarios in Toronto, Montreal, Edmonton, and Halifax had a reduction of 18.7 %, 30.1 %, 21.3 % and 34.6 %, respectively. The findings have implications for the trade-off management of climate policies at the provincial level and can help understand polycentric governance from multiple resource perspectives