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Background The RAR-related orphan receptor alpha (RORA), a circadian clock molecule, is highly associated with anti-oncogenes. In this paper, we defined the precise action and mechanistic basis of RORA in ESCC development under hypoxia. Methods Expression analysis was conducted by RT-qPCR, western blotting, immunofluorescence (IF), and immunohistochemistry (IHC) assays. The functions of RORA were assessed by detecting its regulatory effects on cell viability, motility, invasion, and tumor growth. DNA pull-down assay and proteomic analysis were employed to identify proteins bound to the RORA promoter. The promoter methylation level of RORA was detected by DNA pyrosequencing. RNA-seq analysis was performed to explore the downstream mechanisms of RORA, and the transcriptional regulation of RORA on SLC2A3 was verified by ChIP-qPCR and dual-luciferase reporter assay. Glycolysis was assessed by detecting the consumption of glucose and the production of lactic acid and ATP. Results In vitro, RORA was shown to suppress ESCC cell viability, motility, and invasion under hypoxic condition. In vivo, increased RORA expression in mouse xenografts impeded tumor growth. DNMT1 was identified to widely exist in the RORA promoter, increasing DNA methylation and reducing RORA expression in hypoxia-induced KYSE150 ESCC cells. Mechanistically, RORA was found to inactivate the transcription of glucose transporter protein SLC2A3 by interacting with its promoter F1 region. Furthermore, rescue experiments revealed that RORA-mediated suppressive effects on ESCC cell migration and invasion were largely based on its negative regulation of SLC2A3 and glycolysis. Conclusion DNMT1-driven methylation of RORA promotes ESCC progression largely through affecting SLC2A3 transcription and glycolysis. These findings turn RORA into potential target of anti-cancer therapeutic agents. Highlights RORA works as a tumor suppressor in ESCC under hypoxia. DNMT1 downregulates RORA by induction of methylation. RORA inactivates SLC2A3 transcription through its promoter F1 region. RORA inactivates SLC2A3 transcription to inhibit ESCC cell glycolysis and metastasis.

Even under the standard medical care, patients with left ventricular (LV) failure or heart failure (HF) often progress to pulmonary hypertension and right ventricular (RV) hypertrophy. We previously showed that inflammation and regulatory T cells (Tregs) modulate HF progression in mice with preexisting LV failure. The main objective of this study is to determine the role of CD8 T cells in modulating LV failure and the consequent pulmonary inflammation and RV hypertrophy in mice with preexisting LV failure. Mice with LV failure produced by transverse aortic constriction (TAC) were randomized to depletion of cytotoxic CD8 T cells, Tregs, or both using specific blocking antibodies. Cardiac function, lung inflammation, fibrosis, vascular remodeling, and right ventricular remodeling were determined. LV failure caused pulmonary inflammation, fibrosis, vascular remodeling, and RV hypertrophy. Depletion of CD8 T cells significantly attenuated above changes in mice with preexisting LV failure. LV failure was associated with increased CD4 and CD8 T cell activation, and increased ratios of activated T cells to Tregs. Treg depletion exacerbated lung inflammation and HF progression, as well as lung CD4 and CD8 T cell infiltration and activation in HF mice. However, CD8 T cells depletion rescue these mice from exacerbated lung inflammation and RV hypertrophy after Treg depletion. Our findings demonstrate an important role of CD8 T cells in promoting pulmonary inflammation and RV hypertrophy in mice with preexisting LV failure. Depletion of CD8 T cells also rescued HF mice from the exacerbated HF progression by Treg depletion.

Background: Cancer is a significant health concern and is China's leading cause of mortality. Targeted therapies, such as trastuzumab and rituximab, have enhanced clinical treatment efficacy. However, their high costs burden patients and healthcare systems considerably. Patient demographic factors further influence the utilization of these expensive drugs. On September 1, 2017, China implemented the National Health Insurance Coverage (NHIC) policy, necessitating additional real-world evidence to assess its impact on patients. Methods: Data on human epidermal growth factor receptor 2-positive breast cancer and CD20-positive non-Hodgkin B-cell lymphoma patients were gathered in Jiangsu Cancer Hospital and Fujian Cancer Hospital from September 2015 to August 2019, including demographic and clinical information. All eligible patients were divided into two groups. Univariate analysis and multi-variable logistic regression were used to investigate the differences between subgroups. An interrupted time-series regression was used to examine the change in trastuzumab and rituximab utilization percentages. Results: Before and after the NHIC policy, utilization of trastuzumab increased from 61.13% to 75.10%, and the increase was statistically significant. Rituximab therapy increased statistically significantly from 64.79% to 74.88%. The key factor influencing trastuzumab and rituximab use was the NHIC policy. With policy implementation, medical insurance status, occupations, and cancer disease stage affected trastuzumab and rituximab use. Conclusion: The NHIC policy is essential to the utilization of trastuzumab and rituximab, and the patient's income level and repayment abilities continue to impact the use of innovative anti-cancer drugs. Appropriate steps, such as reducing the urban-rural gap and broadening medical insurance coverage, would enable more people to access novel anti-cancer drugs. Keywords: National Health Insurance Coverage, trastuzumab, rituximab, breast cancer, non-Hodgkin lymphoma, utilization

The tight oil layer is poor in physical property, small pore throat radius, serious heterogeneity of reservoir, low flooding efficiency, poor water flooding efficiency and final recovery is lower than 10%. In order to further improve the oil displacement yield and simulate the conditions of oil layer, we have carried out the experiment of air foam liquid system to flooding oil, and studied the rule of improving the displacement efficiency of air tight foam reservoir. The experimental results show that the density of Gaotaizi water flooding ultimate oil displacement efficiency is 48.95% on average, after water flooding to air - foam flooding alternating final displacement efficiency is high up 79.63%, the oil displacement efficiency can be increased by 26.92%; a short alternately displacement than the big slug is better, the gas-liquid ratio is too high, the breakthrough time of change in short, flooding effect, direct air - foam liquid slug can achieve good flooding effect. That air foam flooding can improve the oil displacement efficiency of dense oil after water flooding by air - foam liquid slug, gas-liquid ratio, cycle injection parameter optimization, to further improve the dense oil displacement effect, the results of air foam flooding field test has the reference and guiding significance for the tight reservoir.

MicroRNAs (miRNAs/miRs) are a class of small, non-coding RNA molecules that serve a key function in carcinogenesis and tumor progression. Recent evidence indicates that miRNAs may act as powerful regulators of migration and invasion. The present study aimed to investigate the effect of miR-25 on the invasion and metastasis of KYSE-150 and EC109 esophageal squamous cell carcinoma (ESCC) cells, and predict the mechanism of this effect by bioinformatically analyzing the miR-106b-25 cluster. In order to alter the expression of miR-25 in the two cell lines, a miR-25 inhibitor or mimic were transfected into the cells, which were then studied via Transwell migration and invasion assays. Subsequently, the target genes of the miR-106b-25 cluster were predicted using miRanda, PicTar, TargetScan and miRTarbase, and the functions of the target genes were predicted via Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Then, a protein-protein interaction (PPI) network was produced using the Search Tool for the Retrieval of Interacting Genes. The results revealed that overexpressing miR-25 led to significantly increased cell migration and invasion in KYSE150 and EC109 cells. Suppressing miR-25 resulted in significantly decreased cell migration and invasion in KYSE150 cells, while the result was not significant in EC109 cells. Target genes of the miR-106b-25 cluster were significantly enriched in the biological process regulation of cellular metabolic process and several cancer-associated pathways, such as those for glioma and melanoma. The PPI network revealed that PTEN, TP53, MDM2, E2F1, PRMT5, MCM2, RB1, CDKN1A, SHAD7 and EZH2 may serve core roles within the network and associate with one another during the pathogenesis of ESCC. These results indicate that a high expression of miR-25 promotes the invasion and metastasis of ESCC cells, while the influence of low expression of miR-25 differs with cells with different degrees of differentiation. Invasion and metastasis are not effected in cells with poor differentiation, while they were decreased in well differentiated cells. Furthermore, PTEN, TP53, MDM2, E2F1, PRMT5, MCM2, RB1, CDKN1A, SHAD7 and EZH2 may be targeted by the miR-106b-25 cluster, and act together to regulate the development of ESCC.

A new three-band model was developed to estimate chlorophyll-a concentrations in turbid inland waters. This model makes a number of important improvements with respect to the three-band model commonly used, including lower restrictions on wavelength optimization and the use of coefficients which represent specific inherent optical properties. Results showed that the new model provides a significantly higher determination coefficient and lower root mean squared error (RMSE) with respect to the original model for upwelling data from Taihu Lake, China. The new model was tested using simulated data for the MERIS and GOCI satellite systems, showing high correlations with the former and poorer correlations with the latter, principally due to the lack of a 709nm centered waveband. The new model provides numerous advantages, making it a suitable alternative for chlorophyll-a estimations in turbid and eutrophic waters.

Visual memory search involves comparing a probe item against multiple memorized items. Previous work has shown that distractor probes from a different object category than the objects in the memory set are rejected more quickly than distractor probes from the same category. Because objects belonging to the same superordinate category usually share both visual and semantic features compared with objects of different categories, it is unclear whether the category effects reported in previous studies reflected visual and/or semantic target-distractor similarity. Here, we employed old/new recognition tasks to examine the role of categorical, semantic, and visual similarity in short- and long-term memory search. Participants (N=64) performed visual long-term memory (LTM) or short-term memory (STM) search tasks involving animate and inanimate objects. Trial-wise RT variability to distractor probes in LTM and STM search was modelled using regression analyses that included predictors capturing categorical target-distractor similarity (same or different category), semantic target-distractor similarity (from a distributional semantic model), and visual target-distractor similarity (from a deep neural network). We found that categorical, semantic, and visual similarity all explained unique variance in trial-wise memory search performance. However, their respective contributions varied with memory set size and task, with STM performance being relatively more strongly influenced by visual and categorical similarity and LTM performance being relatively more strongly influenced by semantic similarity. These results clarify the nature of the representations used in memory search and reveal both similarities and differences between search in STM and LTM.

We often need to decide whether the object we look at is also the object we look for. When we look for one specific object, this process can be facilitated by preparatory feature-based attention. However, when we look for multiple objects at the same time (e.g., the products on our shopping list) such a strategy may no longer be possible, as research has shown that we can actively prepare to detect only one object at a time. Therefore, looking for multiple objects may additionally involve search in long-term memory, slowing down decision making. Interestingly, however, previous research has shown that memory search can be very efficient when distractor objects are from a different category than the items in the memory set. Here, using EEG, we show that this efficiency is supported by top-down attention at the category level. In Experiment 1, human participants (both sexes) performed a memory search task on individually presented objects of the same or different category as the objects in the memory set. We observed category-level attentional modulation of distractor processing from ~150 ms after stimulus onset, expressed both as an evoked response modulation and as an increase in decoding accuracy of same-category distractors. In Experiment 2, memory search was performed on two concurrently presented objects. When both objects were distractors, spatial attention (indexed by the N2pc component) was directed to the object that was of the same category as the objects in the memory set. Together, these results demonstrate how attention can facilitate memory search.Competing Interest StatementThe authors have declared no competing interest.

Metasurfaces have provided a promising approach to enhance the nonlinearity at subwavelength scale, but usually suffer from a narrow bandwidth as imposed by sharp resonant features. Here, we counterintuitively report a broadband, enhanced second-harmonic generation, in nanopatterned hyperbolic metamaterials. The nanopatterning allows the direct access of the mode with large momentum, rendering the rainbow light trapping, i.e. slow light in a broad frequency, and thus enhancing the local field intensity for boosted nonlinear light-matter interactions. For a proof-of-concept demonstration, we fabricated a nanostructured Au/ZnO multilayer, and enhanced second harmonic generation can be observed within the visible wavelength range (400-650 nm). The enhancement factor is over 50 within the wavelength range of 470-650 nm, and a maximum conversion efficiency of 1.13×10 −6 is obtained with a pump power of only 8.80 mW. Our results herein offer an effective and robust approach towards the broadband metasurface-based nonlinear devices for various important technologies. Though metamaterials enhance nonlinear light-matter interactions due to their resonant features, these materials typically show a narrow spectral bandwidth. Here, the authors report broadband enhanced second-harmonic generation in patterned multilayer hyperbolic metamaterial arrays.

Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution ones. Recently, the VSR methods based on deep neural networks have made great progress. However, there is rarely systematical review on these methods. In this survey, we comprehensively investigate 37 state-of-the-art VSR methods based on deep learning. It is well known that the leverage of information contained in video frames is important for video super-resolution. Thus we propose a taxonomy and classify the methods into seven sub-categories according to the ways of utilizing inter-frame information. Moreover, descriptions on the architecture design and implementation details are also included. Finally, we summarize and compare the performance of the representative VSR methods on some benchmark datasets. We also discuss the applications, and some challenges, which need to be further addressed by researchers in the community of VSR. To the best of our knowledge, this work is the first systematic review on VSR tasks, and it is expected to make a contribution to the development of recent studies in this area and potentially deepen our understanding of the VSR techniques based on deep learning.