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The mechanisms by which hypoxic tumours evade immunological pressure and anti-tumour immunity remain elusive. Here, we report that two hypoxia-responsive microRNAs, miR-25 and miR-93, are important for establishing an immunosuppressive tumour microenvironment by downregulating expression of the DNA sensor cGAS. Mechanistically, miR-25/93 targets NCOA3, an epigenetic factor that maintains basal levels of cGAS expression, leading to repression of cGAS during hypoxia. This allows hypoxic tumour cells to escape immunological responses induced by damage-associated molecular pattern molecules, specifically the release of mitochondrial DNA. Moreover, restoring cGAS expression results in an anti-tumour immune response. Clinically, decreased levels of cGAS are associated with poor prognosis for patients with breast cancer harbouring high levels of miR-25/93. Together, these data suggest that inactivation of the cGAS pathway plays a critical role in tumour progression, and reveal a direct link between hypoxia-responsive miRNAs and adaptive immune responses to the hypoxic tumour microenvironment, thus unveiling potential new therapeutic strategies.

Single image dehazing has become an important vision task for prevailing image degradation caused by detrimental atmosphere transmission conditions. Attention mechanism has been widely utilized in learning based methods to assist the model to discard redundant information and hence boost the performance. However, existing methods are mainly dealing with either channel-wise or pixel-wise attention, which requires much more parameters when the size of feature maps increases. In this paper, we introduce the operation-wise attention in the proposed Feedback Operation-Attention Network (FOANet) to focus on attaining optimal combination of network operations for image dehazing. Specifically, our model consists of two main steps. First, the extracted features of hazy input image are fed to the novel operation-attention block which can adjust the weight of different operations dynamically to produce the optimal processed features. The operation space of an operation-attention block comprises vanilla and dilated convolutions with different kernel sizes along with max pooling and average pooling. Second, we adopt curriculum learning with feedback mechanism to continually refine the features in a recurrent fashion and generate the haze-free image. The experimental results on both synthetic and realistic subsets of RESIDE dataset have demonstrated our method can perform dehazing favorably against other dehazing algorithms. [ABSTRACT FROM AUTHOR]

Nanotechnology is an emerging technology and it brings a tremendous change to human life and economy. When the size of a material is reduced to the nanoscale, its properties may change significantly and becomes a new substance. A fullerene is a molecule of carbon in the shape of a hollow sphere, ellipsoid, tube, and many other geometrical structures. For example, buckyballs are spherical fullerenes and carbon nanotubes are cylindrical fullerenes. Fullerenes have been under intensive investigation for their expanding applications in electronics, energy, medicine, and many other research fields. Nanostructure analysis is very important for understanding the formation of different materials and their properties. In this study, a virtual laboratory is developed for learning fullerene production and its nanostructure analysis. The learners can use the arc discharge equipment to produce fullerenes and then use the transmission electron microscope (TEM) to observe the nanostructures of different fullerene samples. The high interactivity and 3D visual effects of the virtual laboratory enable the learners to become familiar with the geometrical structures and properties of fullerenes. A teaching experiment has been conducted and the results show that the virtual laboratory can improve their learning motivation and effectiveness. [ABSTRACT FROM AUTHOR]

The association between air pollution and infant mortality has been inconsistently reported. A few studies have estimated short-term effects of air pollution on infants' health. This population-based case–control study aimed to examine the potential effects of air pollution on sudden infant death syndrome (SIDS) in the post-neonatal period in Taiwan during 1997–2002. Each case of infant death was matched with 20 randomly selected sex-matched controls who were born on the same day and were still alive. We obtained 24-h measurements of air pollutants and meteorological factors in each case and control with 1- to 14-day lags from 55 air-quality monitoring stations. After controlling for potential confounders, conditional logistic regression analysis was performed to estimate effects of air pollutants on SIDS (n = 398) and respiratory death (n = 121) among neonates. In single- and multi-pollutant models, we found that 100-ppb increment in carbon monoxide (Odds Ratio = 1.04–1.07) and 10-ppb increment in nitrogen dioxide (Odds Ratio = 1.20–1.35) with 1- to 14-day lags were associated with significant increase in SIDS, although a significant relationship between air pollution and respiratory death was not determined in 1- to 14-day lags. Short-term carbon monoxide and nitrogen dioxide exposure were associated with significant increase in SIDS in the post-neonatal period, with latency estimated within days before death. • Use population-based case–control methodology to examine the acute effects of air pollution on the SIDS. • Positive association between CO, NO 2 exposure and SIDS. • Traffic air pollution may play a key factor to SIDS with a latency of days before death. • Negative finding between respiratory death and air pollutant. [ABSTRACT FROM AUTHOR]

The new title compound is hydrothermally synthesized from a mixture of Ca(OH)2, UO3, SiO2, KOH, and H2O in a molar ratio of K:Ca:U:Si = 75:1:1:4 (gold ampule, 1400 bar, 550 °C, 4 d; 45% yield). [ABSTRACT FROM AUTHOR]

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.