We found that it is possible to use whole blood to evaluate molecular subtypes and monitor antibiotic resistance in circulating T. pallidum strains, especially when chancres are absent. High frequency of macrolide-resistant T. pallidum indicates that macrolide antibiotics, such as azithromycin, should be avoided as a treatment option for syphilis in Hunan, China.
The outbreak of COVID-19 pandemic has increased the production costs of renewable energy facilities and undermines the profitability of renewable energy investment. Green finance polices, e.g. carbon pricing, tradable green certificate (TGC) and green credit, can provide low-cost finances and counteract the adverse effects of COVID-19 pandemic. In this work, the generation costs of offshore wind power before and after the COVID-19 pandemic in China are analyzed using the data of 97 offshore wind power projects implemented in the period of 2014–2020, and the effect of green finance policy on the generation cost and the project profitability are evaluated. The results show that the average levelized cost of electricity (LCOE) of offshore wind power decreased from 0.86 CNY/kWh in 2014 to 0.72 CNY/kWh in 2019, while it increased to 0.79 CNY/kWh in 2020, i.e. 10.85% increase relative to that in 2019. With the average carbon price of 50 CNY/t CO 2 , the average TGC price of 170 CNY and the green-credit policy being introduced, the average LCOE decreases to 0.76 CNY/kWh, 0.67 CNY/kWh and 0.74 CNY/kWh respectively. The green finance policy mix is still necessary to support the offshore wind power investment during the Covid-19 pandemic.
Thyroid transcription factor‐1 (TTF‐1), also known as NKX2‐1, plays a role as a lineage‐survival oncogene in lung adenocarcinoma that possesses double‐edged sword characteristics. Although evidence from previous studies has steadily accumulated regarding the roles of TTF‐1 in transcriptional regulation of protein‐coding genes, little is known about its regulatory relationship with microRNAs. Here, we utilized an integrative approach designed to extract maximal information from expression profiles of both patient tumors in vivo and TTF‐1‐inducible cell lines in vitro, which identified microRNA (miR)‐532‐5p as a novel transcriptional target of TTF‐1. We found that miR‐532‐5p is directly regulated by TTF‐1 through its binding to a genomic region located 8 kb upstream of miR‐532‐5p, which appears to impose transcriptional regulation independent of that of CLCN5, a protein‐coding gene harboring miR‐532‐5p in its intron 3. Furthermore, our results identified KRAS and MKL2 as novel direct targets of miR‐532‐5p. Introduction of miR‐532‐5p mimics markedly induced apoptosis in KRAS‐mutant as well as KRAS wild‐type lung adenocarcinoma cell lines. Interestingly, miR‐532‐5p showed effects on MEK‐ERK pathway signaling, specifically in cell lines sensitive to siKRAS treatment, whereas those miR‐532‐5p‐mediated effects were clearly rendered as phenocopies by repressing expression or inhibiting the function of MKL2 regardless of KRAS mutation status. In summary, our findings show that miR‐532‐5p is a novel transcriptional target of TTF‐1 that plays a tumor suppressive role by targeting KRAS and MKL2 in lung adenocarcinoma.
This companion paper supports the replication of scene image recognition experiments using Adaptive Discriminative Region Discovery (Adi-Red), an approach presented at ACM Multimedia 2018. We provide a set of artifacts that allow the replication of the experiments using a Python implementation. All the experiments are covered in a single shell script, which requires the installation of an environment, following our instructions, or using ReproZip. The data sets (images and labels) are automatically downloaded, and the train-test splits used in the experiments are created. The first experiment is from the original paper, and the second supports exploration of the resolution of the scale-specific input image, an interesting additional parameter. For both experiments, five other parameters can be adjusted: the threshold used to select the number of discriminative patches, the number of scales used, the type of patch selection (Adi-Red, dense or random), the architecture and pre-training data set of the pre-trained CNN feature extractor. The final output includes four tables (original Table 1, Table 2 and Table 4, and a table for the resolution experiment) and two plots (original Figure 3 and Figure 4).
Abstract. In spite of an initially promising anti-tumor activity, oxaliplatin-based combinatorial treatments can eventually result in a tumor resistance response. In this study we aimed to understand the role of autophagy in HCC cell resistance to oxaliplatin and to discuss its potential therapeutic implication. We found that exposure to oxaliplatin induced a significant increase in LC3 lipidation and subsequent LC3 puncta formation. While the proliferation of HCC cells was inhibited upon oxaliplatin exposure, inhibition of autophagy by ATG7 interference and chloroquine pre-treatment further increased the sensitivity to chemotherapy. Meanwhile, the oxaliplatininduced apoptotic cell death was significantly enhanced. These results suggest that autophagy may function importantly in HepG2 cell resistance to oxaliplatin. Intriguingly, the resistance could be recovered apparently by inhibition of autophagy. This also points to the potential therapy for hepatoma by perturbing autophagy.
We report an outbreak of carbapenemase-producing hypervirulent Klebsiella pneumoniae in two hospitals that undergo frequent patient transfers. Analysis of 11 completely assembled genomes showed that the bacteria were ST11-K64 strains. Moreover, 12 single nucleotide polymorphisms (SNPs) identified the strains as having originated from the same cluster, and were also indicative of the interhospital transmission of infection. Five plasmids were assembled in each of the strains. One plasmid carried several virulence genes, including the capsular polysaccharide regulators rmpA and rmpA2 . Two others carried antimicrobial-resistance genes, including one for carbapenem resistance, bla KPC–2 . Comparative genomic analysis indicated the occurrence of frequent and rapid gain and loss of genomic content along transmissions and the co-existence of progeny strains in the same ward. A 10-kbp fragment harboring antimicrobial resistance-conferring genes flanked by insert sequences was missing in a plasmid from strain KP20194c in patient 3, and this strain also likely subsequently infected patient 4. However, strains containing the 10-kbp fragment were also isolated from the ward environment at approximately the same time, and harbored different chromosome indels. Tn 1721 and multiple additional insert sequence-mediated transpositions were also seen. These results indicated that there is a rapid reshaping and diversification of the genomic pool of K. pneumoniae facilitated by mobile genetic elements, even a short time after outbreak onset. ST11-K64 CR-hvKP strains have the potential to become new significant superbugs and a threat to public health.
Identifying and correcting grammatical errors in the text written by non-native writers has received increasing attention in recent years. Although a number of annotated corpora have been established to facilitate data-driven grammatical error detection and correction approaches, they are still limited in terms of quantity and coverage because human annotation is labor-intensive, time-consuming, and expensive. In this work, we propose to utilize unlabeled data to train neural network based grammatical error detection models. The basic idea is to cast error detection as a binary classification problem and derive positive and negative training examples from unlabeled data. We introduce an attention-based neural network to capture long-distance dependencies that influence the word being detected. Experiments show that the proposed approach significantly outperforms SVMs and convolutional networks with fixed-size context window.
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