Inverse design of metasurfaces with customized transmission characteristics of frequency band based on generative adversarial networks.

In recent years, deep learning (DL) has demonstrated significant potential in the inverse design of metasurfaces, and the generation of metasurfaces with customized transmission characteristics of frequency band remains a challenging and underexplored area. In this study, we propose a DL-assisted method for the inverse design of transmissive metasurfaces. The method consists of a generative adversarial network (GAN)-based graph generator, an electromagnetic response predictor, and a genetic algorithm optimizer. By integrating these components, we can obtain customized metasurfaces with desired transmission characteristics of frequency band. We demonstrate the effectiveness of the proposed method through examples of inverse-designed three-layer cascaded transmissive metasurfaces with wideband, dual-band, and stopband responses in the 8∼12 GHz frequency range. Specifically, we realize three different types of dual-band metasurfaces, namely double-wide, front-wide and rear-narrow, and front-narrow and rear-wide configurations. Additionally, we analyze the accuracy and reliability of the inverse design method by employing data from the training dataset, self-defined objectives, and bandwidth-reduced target responses scaled from the wideband type as design inputs. Quantitative evaluation is performed using metrics such as mean absolute error and average precision. The proposed method successfully achieves the desired effect as intended.

NF-κB regulates the expression of STING via alternative promoter usage.

AIMS: Stimulator of interferon genes (STING) is a transmembrane protein in endoplasmic reticulum and plays crucial roles in autophagy, antiviral and anti-tumor responses. However, there are few studies on the transcriptional regulation mechanism of STING. MAIN METHODS: The 5' RACE experiment was used to determine the location of STING promoters. Luciferase reporting assay confirmed the activity and core region of STING internal promoter. Site-directed mutagenesis confirmed that NF-κB regulates the activity of STING promoters. The regulation of NF-κB on STING was investigated by real-time quantitative PCR, western blot, chromatin immunoprecipitation assay and lipopolysaccharide (LPS) inflammatory cell model. KEY FINDINGS: There was also a transcription start site at the 17 bp sequence upstream of STING second exon. STING-285 was the core region of the internal promoter. After NF-κB binding site mutation, the activity of STING internal promoter decreased significantly. In addition, we found that NF-κB can bind to the promoter region of wild-type STING. Overexpression of NF-κB significantly increased the activity of STING internal promoter and wild-type promoter, while knockdown of endogenous NF-κB significantly inhibited the activity of STING promoters. The binding of NF-κB to STING promoters in vivo were confirmed by chromatin immunoprecipitation assay. Meanwhile, we stimulated HeLa cells with LPS to activate the NF-κB pathway and found that STING expression was up-regulated. SIGNIFICANCE: These results suggest that transcription factor NF-κB positively regulates the expression of STING via alternative promoter usage. This provides a new basis and potential drug targets for the clinical treatment of STING related diseases.

Global prevalence of occult hepatitis B: A systematic review and meta-analysis.

The study aimed to investigate the prevalence and risk factors associated with occult hepatitis B virus (HBV) infection (OBI) in the global population. We searched PubMed, Embase, CINAHL, Cochrane and Web of Science from database inception through 27 Dec, 2018. Studies reporting HBV-DNA serological data in previously undiagnosed hepatitis B patients were included. The data were further categorized according to the presence of risk factors. After an initial screening of 2,325 records, we finally included 98 articles about the prevalence of OBI from 34 countries and regions. The OBI prevalence was 0.82% (95% CI:0.69-0.96) in the general population, 16.26% (95% CI:10.97-22.34) in HIV patients, 13.99% (95% CI:8.33-20.79) in patients with other liver diseases, 4.25% (95% CI:1.64-7.87) in haemodialysis patients and 5.14% (95% CI:2.26-9.01) patients with other risk factors. In conclusion, OBI prevalence varies significantly across different populations and nations, which deserve attention from the public health authorities. Our results generate further epidemiological data to identify the population with OBI, which has important clinical implications in finding these high-risk populations to design preventive and management strategies.

Hepatitis D: challenges in the estimation of true prevalence and laboratory diagnosis.

Hepatitis delta virus (HDV) is a defective single negative chain RNA virus, as its envelope protein synthesis is dependent on hepatitis B virus (HBV). Studies have consistently shown that coinfection of HBV and HDV is the most serious form of viral hepatitis, with accelerated progression to liver cirrhosis and hepatocellular carcinoma. About 74 million of HBV surface antigen (HBsAg) positive patients worldwide are also co-infected with HDV. Besides, patients with intravenous drug use and high-risk sexual behavior are at higher risk of HDV infection. Therapeutic schedules for HDV are limited, and relapse of HDV has been observed after treatment with pegylated interferon alpha. To reduce the transmission of HDV, all people infected with HBV should be screened for HDV. At present, several serological and molecular detection methods are widely used in the diagnosis of HDV. However, due to the lack of international standards diagnostic results from different laboratories are often not comparable. Therefore, the true prevalence of HDV is still unclear. In this manuscript, we have analyzed various factors influencing the estimation of HDV prevalence. We have also discussed about the advantages and disadvantages of currently available HDV laboratory diagnostic methods, in order to provide some ideas for improving the detection of HDV.

Transcriptional regulation of human cyclic GMP-AMP synthase gene.

Cyclic GMP-AMP synthase (cGAS, cGAMP synthase) plays crucial roles in autoimmune disease, anti-tumor response, anti-senescence and anti-inflammatory response. Many studies have focused on cGAS-mediated signaling pathway. However, transcriptional mechanisms of cGAS gene have remained largely unknown. Here, we cloned the cGAS promoter region and characterized the molecular mechanisms controlling the cGAS transcriptional activity. By a series of 5' deletion and promoter constructions, we showed that the region (-414 to +76 relatives to the transcription start site) was sufficient for promoter activity. Mutation of Sp1 and CREB binding sites in this promoter region led to an apparent reduction of the cGAS promoter activity. Overexpression of Sp1 and CREB could obviously enhance promoter activity, whereas knocking-down of endogenous Sp1 and CREB markedly restrained the cGAS promoter activity. Sp1 and CREB binding to the cGAS promoter region in vivo was verified by Chromatin immunoprecipitation assay. These results pointed out that transcription factors Sp1 and CREB regulate the transcription of the cGAS gene.

A quantitative spectral component analysis method based on maximum likelihood.

In spectroscopy, the compositional analysis of the spectrum is important, such as extracting information about the species of spectral objects contributing to spectral data from an emission spectrum of photon energy. A quantitative spectral component analysis method based on Maximum Likelihood Estimation using Expectation Maximization (MLEM) is developed, which could quantitatively decompose out the components of the measured spectrum of low counts and surpass conventional techniques which belong to classification or regression. Abundant experimental and simulated spectra data on gamma-ray spectrum of radionuclides are presented to demonstrate and evaluate this method, while the ingredient radionuclides in the mixed spectrum are identified accurately with high precision. It will be a powerful and alternative method recommended for the circumstances needing fast and quantitative spectral analysis, including radionuclide identification (gamma-ray spectra), biomass or mineral composition (near-infrared spectra), laser-induced breakdown spectra and other spectroscopy scenarios.

[Effects of simulated warming and functional group removal on survival and growth of Abies faxoniana seedlings]. / 模拟增温和功能群去除对岷江冷杉幼苗存活和生长的影响.

Warming and herbaceous functional group removal experiment was conducted in subalpine meadow to examine the effects of herbaceous species on Abies faxoniana seedlings by analyzing its physiological responses. The survival rate and non-structural carbohydrate content were significantly increased, but the growth and root/shoot of A. faxoniana were decreased. Seedling survival was significantly positively correlated with non-structural carbohydrate content, especially with soluble sugar. Under the treatment without warming, herbaceous species inhibited the survival of A. faxoniana, increased height growth and aboveground biomass. Grasses and forbs decreased the root length and belowground biomass of A. faxoniana. In the warming treatment, forbs increased the survival of A. faxoniana, sedges decreased root length and belowground biomass of A. faxoniana, and grasses and forbs decreased height growth and aboveground biomass of A. faxoniana. Simulated warming increased the survival of A. faxoniana seedlings, but also made it face stronger competition from herbaceous and thus inhibited its growth.

Clonal integration increases tolerance of a phalanx clonal plant to defoliation.

Defoliation by herbivores commonly imposes negative effects on plants, and physiological integration (resource sharing) can enhance the ability of guerilla clonal plants to tolerate stresses. Here we examined whether physiological integration can increase the ability of phalanx clonal plants to withstand defoliation. On a high mountain grassland in southwestern China, we subjected the phalanx clonal plant Iris delavayi within 10cm×10cm plots to three levels of defoliation intensity, i.e., control (no defoliation), moderate (50% shoot removal to simulate moderate herbivory) and heavy defoliation (100% shoot removal to simulate heavy herbivory), and kept rhizomes at the plot edges connected (allowing physiological integration) or disconnected (preventing integration) with intact ramets outside the plots. Defoliation significantly reduced leaf biomass, root biomass and ramet number of I. delavayi. Clonal integration did not affect the growth of I. delavayi under control, but significantly increased total biomass, rhizome and root biomass under heavy defoliation, and leaf biomass and ramet number under moderate defoliation. We conclude that clonal integration associated with resource reallocation plays an important role in maintaining the productivity of the alpine and subalpine grassland ecosystems in SW China where clonal plants are a dominant component of the grasslands and are commonly extensively managed with moderate grazing intensity. Our results also help to better understand the adaption and tolerance of phalanx clonal plants subjected to long-term grazing in the high mountain environment.

[Recognition of Three Types of Plantation Wood Species with Near Infrared Spectra Coupled with Back-Propagation Network].

In this study, the near infrared spectroscopy coupled with Back-Propagation (BP) network was used for the recognition of three kinds of plantation wood (Eucalyptus urophylla, Pinus massoniana, Populus X euramericana (Dode) Guineir cv. "San Martino" (1-72/58)). The study considered the effects of hidden layer neurons number, spectral pretreatment method and spectral regions on BP model, which are compared with SIMCA model simultaneously. The results showed that, (1) the recognition rate was 97.78% achieved by BP network model with hidden layer neurons number 13 and the spectral region of 780～2 500 nm. (2) BP model with spectral region of 780～2 500 nm was more robust than the other two BP models with spectral regions of 780～1 100 and 1 100～2 500 nm, of which recognition rates were 97.78%, 95.56% and 96.67%, respectively. After the full spectra was pretreated with the first derivative and the second derivative methods, the recognition rates of BP models fell down to 93.33% and 71.11%. However, the recognition rate of BP model rose to 98.89% with the full spectra being pretreated by the multiplicative scatter correction (MSC). (3) Compared with SIMCA models that recognition rates of three spectral regions (780～2 500, 780～1 100 nm, and 1 100～2 500 nm) were 76.67%, 81.11% and 82.22% respectively, BP network work models had higher recognition rates.