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Abstract Background It is well-established that understanding the mechanism of prostate cancer (PCa)-associated metastasis is paramount for improving its prognosis. Metastasis is known to involve the communication between tumor-associated macrophages (TAMs) and tumor cells. Exosomes are crucial in mediating this intercellular communication within the tumor microenvironment. Nonetheless, the role of exosomal proteins in PCa metastasis is not yet fully understood. Here, we investigated the mechanisms of prostate cancer-derived exosomal PSM-E on regulating macrophage M2 polarization to suppress tumor invasion and metastasis. Methods PSM-E levels in exosomes were detected by transmission electron microscopy and Western blotting analysis. The diagnostic value of urine-derived exosomal PSM-E in PCa were evaluated by LC-MS/MS, correlation analysis, and ROC curves analysis. The mechanisms underlying the inhibitory effect of exosomal PSM-E on the M2 polarization of macrophages was investigated by co-IP, IHC staining, and PCa tumorigenesis model, etc. Results We revealed that exosomal PSM-E is upregulated in exosomes derived from the serum and urine of PCa patients. Clinically, an elevated exosomal PSM-E expression in urine is significantly correlated with an advanced pathological tumor stage and a high Gleason score. Our research also revealed that exosomal PSM-E inhibits prostate cancer cell proliferation, invasion, and metastasis by suppressing macrophage polarization in vitro and in vivo. Furthermore, we provided compelling evidence that exosomal PSM-E inhibits M2 polarization of macrophages by recruiting RACK1 and suppressing the FAK and ERK signaling pathways, consequently suppressing PCa invasion and metastasis. Furthermore, we found that the protease-associated domain of PSM-E and the fourth tryptophan-aspartate repeat of RACK1 are crucial for the interaction between PSM-E and RACK1. Conclusions Notably, exosomes carrying PSM-E from PCa urine could potentially serve as a biomarker for PCa, and targeting exosomal PSM-E may represent a strategy for preventing tumor progression in this patient population.

Abstract Despite the well-established significance of transcription factors (TFs) in pathogenesis, their utilization as pharmacological targets has been limited by the inherent challenges in modulating their protein interactions. The lack of defined small-molecule binding pockets and the nuclear localization of TFs do not favor the use of traditional tools. Aptamers possess large molecular weights, expansive blocking surfaces and efficient cellular internalization, making them compelling tools for modulating TF interactions. Here, we report a structure-guided design strategy called Blocker-SELEX to develop inhibitory aptamers (iAptamers) that selectively block TF interactions. Our approach leads to the discovery of iAptamers that cooperatively disrupt SCAF4/SCAF8-RNAP2 interactions, dysregulating RNAP2-dependent gene expression, which impairs cell proliferation. This approach is further applied to develop iAptamers blocking WDR5-MYC interactions. Overall, our study highlights the potential of iAptamers in disrupting pathogenic TF interactions, implicating their potential utility in studying the biological functions of TF interactions and in nucleic acids drug discovery.

Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.

The Proton Exchange Membrane (PEM) water electrolyzer is considered one of the promising energy storing means for harnessing variable renewable energy sources to produce hydrogen. Understanding the internal fluid dynamics, which are often challenging to directly observe experimentally, has prompted the use of numerical models to investigate two-phase flow within PEM water electrolyzers. In this study, we provide a comprehensive review of prior research focusing on two-phase modeling of PEM electrolyzers, encompassing both components at mesoscopic scales and the full electrolyzer at the macroscopic level. We delve into the specifics of various modeling approaches for two-phase flow at different scales and summarize and discuss the current state of the art in the field. Presently, two-phase models for the full electrolyzer predominantly employ a macroscopic homogeneous assumption. However, mesoscopic and microscopic models capable of tracking phase interfaces are limited to components. Challenges persist in integrating various modeling scales into a comprehensive electrolyzer model, particularly in coupling two-phase flow between the channels and porous media. Future efforts should focus on developing multi-scale models and simulating two-phase flow under fluctuating input conditions. Additionally, given the structural similarities between PEM water electrolyzers and PEM fuel cells, we compare and discuss differences in two-phase modeling between the two technologies. This work offers the insights for researchers in the field of modeling of PEM water electrolyzers and even fuel cells.

Recently, Nominal Compound Chain Extraction (NCCE) has been proposed to detect related mentions in a document to improve understanding of the document’s topic. NCCE involves longer span detection and more complicated rules for relation decisions, making it more difficult than previous chain extraction tasks, such as coreference resolution. Current methods achieve certain progress on the NCCE task, but they suffer from insufficient syntax information utilization and incomplete mention relation mining, which are helpful for NCCE. To fill these gaps, we propose a syntax-guided model using a triaffine interaction to improve the performance of the NCCE task. Instead of solely relying on the text information to detect compound mentions, we also utilize the noun-phrase (NP) boundary information in constituency trees to incorporate prior boundary knowledge. In addition, we use biaffine and triaffine operations to mine the mention interactions in the local and global context of a document. To show the effectiveness of our methods, we conduct a series of experiments on a human-annotated NCCE dataset. Experimental results show that our model significantly outperforms the baseline systems. Moreover, in-depth analyses reveal the effect of utilizing syntactic information and mention interactions in the local and global contexts.

The performance degradation is a crucial factor affecting the commercialization of proton exchange membrane electrolyzer. However, it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales. In this paper, the data-driven method is employed to predict the electrolyzer voltage variation over time based on a convolutional neural network-long short term memory (CNN-LSTM) model. First, two datasets including constant operation for 1140 h and start-stop load for 660 h are collected from the durability tests. Second, the data-driven models are trained through the experimental data and the model hyper-parameters are optimized. Finally, the electrolyzer degradation in the next few hundred hours is predicted, and the prediction accuracy is compared with other time-series algorithms. The results show that the model can predict the degradation precisely on both datasets, with the R2 higher than 0.98. Compared to conventional models, the algorithm shows better fitting characteristic to the experimental data, especially as the prediction time increases. For constant and start-stop operations, the electrolyzers degradate by 4.5 % and 2.5 % respectively after 1000 h. The proposed method shows great potential for real-time monitoring in the electrolyzer system.

Karst landforms are widely distributed in southern China. The terrain and soil properties in karst basins are complex, which results in high spatial heterogeneity of the ecological environment and soil organic matter (SOM) in karst watersheds. To investigate the spatial distribution characteristics of SOM in different land uses in the karst plateau basin, a total of 3,816 soil samples were taken from 568 soil profiles. The soil animals and different soil properties were recorded, and the concentration of SOM was tested using the potassium dichromate method in the laboratory. Then, the changes in the SOM content associated with soil animals and the soil properties associated with the different land use types were analyzed. The results showed a large discrepancy in SOM in the karst plateau basin. The average values of SOM in different soil layers were between 9.23 g kg−1 and 59.39 g kg−1. The SOM decreased in the following order: forestland > grassland > barren land > cultivated land > garden land. The SOM in soil in which soil animals are present is generally greater than that in the absence of soil animals, and the SOM partially increases with soil species diversity. Agrotis segetum is the main soil animal species that positively affects the distribution of organic matter in the surface soil layer. The SOM in soil with the phylum Annelida is much greater than that in soils with other animals, and earthworms are the main contributor. The structure of soil animal species is complex, and the change trend of SOM is stable. The major positive factors affecting soil animal diversity are soil thickness, soil humidity and soil structure, and rock outcrops are the main negative factor. In summary, good land use can increase animal diversity and abundance in soil, which promotes soil organic matter accumulation. Moreover, microtopography is an important factor that influences soil organic matter accumulation in karst basins and further affects the restructuring of the spatial distribution of soil organic matter.

China’s coal-fired power plants emit over 5.7 billion tons of CO2 annually. To realize the dual carbon goals in time, it is necessary to reduce the carbon emissions of coal-fired power plants. Microalgae carbon fixation can efficiently absorb CO2 through photosynthesis and convert it into biomass, which is a highly promising technology for carbon reduction in coal-fired power plants. Light guide tubes can flexibly change the light distribution in a photobioreactor, while optical fibers can transmit light centrally with low light loss. Therefore, a microalgae photobioreactor with an optical fiber/light guide tube is proposed to expand the light-receiving area of the microalgae suspension, increase the light-harvesting of microalgal cells, and promote carbon fixation via microalgae photosynthesis. The optical simulation software was used to trace the propagation of light in the optical fiber/light guide tube, and the light intensity distribution of the tube wall was obtained. Microalgae cultivation experiments were conducted in various photobioreactors and under different input light energy conditions. The change trends of biomass yield, carbon sequestration rate, and chlorophyll content were obtained, and the impact of built-in optical fiber /light guide tubes on carbon fixation via microalgae was investigated. Results indicated that the light intensity emitted from the optical fiber terminal decreased precipitously from 30 mm to 140 mm along the side of the light guide tube. Additionally, the tube exhibited a concentrated light-emitting range. Adding a conical reflector to reflect the transmitted light at the tube bottom and designing a stepped optical fiber to emit input light from different steps can optimize the light-emitting effect of the light guide tube and make the light distribution in the microalgae photobioreactor more uniform, so that the microalgal cells far away from the light source area can receive the light energy to photosynthesize and fix carbon. At a light input of 3.3 W/L, the minimum light intensity on the side surface of the light guide comprising a two-stage stepped optical fiber and conical reflector was 47 μmol/(m2·s). The average light intensity was 64 μmol/(m2·s), representing a 2.6-fold increase compared to the light guide tube lacking both the optical fiber and any enhancements beyond its top section. After seven days of cultivation, the microalgae concentration in the stepped fiber photobioreactor (SF-PBR) could reach 1.9 g/L, which was 46.2% higher than that of the photobioreactor inserted with flat-end fiber optic light guide (FF-PBR) and 111.1% higher than that of the photobioreactor with only top-fed light (LG-PBR). When the light input was escalated to 5.0 W/L, a high microalgae concentration of 2.8 g/L was achieved at 7 d. Meanwhile, the average carbon sequestration rate of 608.3 mg/(L·d) was obtained, exhibiting 1.9-fold augmentation compared to the control LG-PBR.

A Scene-Based Nonuniformity Correction (SBNUC) approach is proposed for the correction of fixed-pattern-noise (FPN) in infrared image arrays. This method diverges from conventional neural-network based techniques by eschewing spatial filters for the computation of the desired image. Instead, it harnesses the sparse representation of the estimated irradiance within a hypersphere of adaptive radius, adhering to a distance constraint. The proposed method conceptualizes images as points in a high-dimensional space, with the distance between two images defined by their root mean square difference. The adaptive radius is derived from a sophisticated selection criterion, inversely related to the distance between the noisy input image and the estimated irradiance. This approach ensures edge preservation without excessive blurring while discarding FPN as redundant in the representation coefficients. We propose an adaptive learning rate tailored to the desired image from sparse representation, which contrasts with traditional learning rates that rely on local spatial standard deviation. This new learning rate is determined by the pixel-wise distance between the input image and the desired image, integrating a new motion detection criterion to synchronize the update of correction coefficients across pixels. Our experimental results demonstrate that the method proposed in this paper achieves better removal of fixed-pattern-noise in both simulated and real infrared image sequences compared to the methods used for comparison.

Sea fog detection is a significant and challenging issue in meteorological satellite imagery. Distinguishing between sea fog and low clouds is challenging due to the similar morphology and brightness characteristics of these two phenomena on the imageries. Most of the existing deep learning methods are based on a single imagery feature extraction without the time-related features in imagery sequence. Although the designed temporal models, such as temporal U-Net, expand the available features from a single imagery to the consecutive frames and introduce general temporal information, the learned motion features are not explicit and can only be implicitly learned through a large amount of data. Thus, we introduce motion features obtained from continuous temporal imagery sequences into the sea fog detection task due to the discrepancy between sea fog and other types of clouds. In this article, under the motion features acquired by Horn–Schunck (HS) optical flow method and attention mechanisms, a Motion Attention Network (MoANet) for sea fog detection is proposed, named MoANet. We performed detailed experiments on the Himawaria-8 satellite imagery data set (H-8 Dataset). The Mean Intersection over Union (MIoU) of our method reaches 81.38%, which is 6.49% higher than the single imagery method. The visualization of the results shows that MoANet has more smooth edges, as well as detects more complete area than others. Furthermore, we validate on International Comprehensive Ocean-Atmosphere Data Set (ICOADS) through contrasting visibility value to prove the practicality of the proposed method and the accuracy achieves 90.65%.

Centrifugal granulation is one key step to enable waste heat recovery from the molten slag in the iron and steel industry. Yet, it remains unknown about the granulation characteristics of molten slag with different chemical compositions, especially at high throughput. In this work, we provided an experimental study on centrifugal granulation with four types of molten slags. The stage-specific centrifugal granulation was recorded and analyzed at first. Both effects of atomizer configuration and chemical compositions on granulation were investigated in detail. The cup-type atomizer favors film-mode disintegration and possesses better anti-adhesion capacity although the final granule size was not strongly affected by the atomizer configuration. Most importantly, centrifugal granulation has been demonstrated with appreciable adaptability to composition-specific blast furnace (BF) slag with binary basicity of 0.9–1.3. The present study not only sheds light on the modest effect of the chemical composition of molten slag on centrifugal granulation characteristics, but also gains credit for the adaptivity of CGATER.

Abstract Biomedical named entity recognition (BioNER) is an essential task in biomedical information analysis. Recently, deep neural approaches have become widely utilized for BioNER. Biomedical dictionaries, implemented through a masked manner, are frequently employed in these methods to enhance entity recognition. However, their performance remains limited. In this work, we propose a dictionary-based matching graph network for BioNER. This approach utilizes the matching graph method to project all possible dictionary-based entity combinations in the text onto a directional graph. The network is implemented coherently with a bi-directional graph convolutional network (BiGCN) that incorporates the matching graph information. Our proposed approach fully leverages the dictionary-based matching graph instead of a simple masked manner. We have conducted numerous experiments on five typical Bio-NER datasets. The proposed model shows significant improvements in F1 score compared to the state-of-the-art (SOTA) models: 2.8% on BC2GM, 1.3% on BC4CHEMD, 1.1% on BC5CDR, 1.6% on NCBI-disease, and 0.5% on JNLPBA. The results show that our model, which is superior to other models, can effectively recognize natural biomedical named entities.

Objectives: This study aimed to determine the epidemiological and genetic features of human metapneumovirus (HMPV) infection in children in southern China, and the effect of meteorological factors on infection. Methods: 14,817 children (≤14 years) with acute respiratory tract infections from 2010 to 2019 were examined for HMPV and other respiratory viruses by real-time quantitative polymerase chain reaction. Full-length F gene of 54 positive samples were sequenced and subjected to phylogenetic analysis. The correlation between the HMPV-positive rate and meteorological factors was analyzed by linear regression analysis. Results: HMPV was detected in 524 (3.5%) children, who were mostly younger than 1 year. The seasonal peak of HMPV prevalence mainly occurred in spring. Respiratory syncytial virus was the most common virus coinfected with HMPV (5.3%). Phylogenetic analysis revealed that the sequenced HMPV strains belonged to four sublineages, including A2b (1.9%), A2c (31.5%), B1 (50.0%), and B2 (16.7%). After adjusting for all meteorological factors, sunshine duration was inversely correlated with the HMPV-positive rate. Conclusion: HMPV is an important respiratory pathogen that causes acute respiratory tract infections in children in southern China, particularly in children ≤5 years old. The prevalence peak of HMPV in this area appeared in spring, and the predominant subtype was B1. Meteorological factors, especially long sunshine duration, might decrease the HMPV prevalence.

Efferocytosis, the process of engulfing and removing apoptotic cells, plays an essential role in preserving tissue health and averting undue inflammation. While macrophages are primarily known for this task, dendritic cells (DCs) also play a significant role. This review delves into the unique contributions of various DC subsets to efferocytosis, highlighting the distinctions in how DCs and macrophages recognize and handle apoptotic cells. It further explores how efferocytosis influences DC maturation, thereby affecting immune tolerance. This underscores the pivotal role of DCs in orchestrating immune responses and sustaining immune equilibrium, providing new insights into their function in immune regulation.

Abstract Background Leaf-associated microbes play an important role in plant development and response to exogenous stress. Insect herbivores are known to alter the phyllosphere microbiome. However, whether the host plant’s defense against insects is related to the phyllosphere microbiome remains mostly elusive. Here, we investigated bacterial communities in the phyllosphere and endosphere of eight wheat cultivars with differing aphid resistance, grown in the same farmland. Results The bacterial community in both the phyllosphere and endosphere showed significant differences among most wheat cultivars. The phyllosphere was connected to more complex and stable microbial networks than the endosphere in most wheat cultivars. Moreover, the genera Pantoea, Massilia, and Pseudomonas were found to play a major role in shaping the microbial community in the wheat phyllosphere. Additionally, wheat plants showed phenotype-specific associations with the genera Massilia and Pseudomonas. The abundance of the genus Exiguobacterium in the phyllosphere exhibited a significant negative correlation with the aphid hazard grade in the wheat plants. Conclusion Communities of leaf-associated microbes in wheat plants were mainly driven by the host genotype. Members of the genus Exiguobacterium may have adverse effects on wheat aphids. Our findings provide new clues supporting the development of aphid control strategies based on phyllosphere microbiome engineering.

The investigation of genetics-based biopesticides has become a central focus in pesticide studies due to their inherent advantages, including species specificity, environmental safety, and a wide range of target genes. In this study, a mixture of miR-184 agomir and nanomaterial star polycation (SPc) was used to treat the nymphs of the English grain aphid, Sitobion avenae (F.). The life parameters of the aphids at various developmental stages were analyzed using an age–stage two-sex life table to assess the effect of miR-184 agomir on the experimental population. The results indicated that miR-184 agomir had a significant negative effect on four key life parameters, including the intrinsic rate of increase, the finite rate of increase, the net rate of increase, and the mean generation time. The population prediction revealed a substantial reduction (91.81% and 95.88%) in the population size of S. avenae at 60 d after treatment with miR-184 agomir, compared to the control groups. Our findings suggest that the miR-184 agomir has the potential to reduce the survival rate and mean longevity of S. avenae, highlighting its potential as a promising candidate for the development of an effective genetics-based biopesticide.

Introduction: Spontaneous subarachnoid hemorrhage (SAH), is a disorder that may be fatal and is primarily caused by a ruptured brain aneurysm. Despite significant leaps forward in the methods to produce aneurysms, the long-term outcomes did not much improve. Pioglitazone is a medication that has been authorized by the FDA as an agonist for the peroxisome proliferator-activated receptor-gamma (PPARγ). Pioglitazone or PPARγ has neuroprotective benefits in animal experiments both during and after traumatic brain injury (TBI) and SAH. Nevertheless, the treatment impact of Pioglitazone on humans is still unknown at this time. As a result, we will conduct a randomized, double-blind, placebo-controlled trial to explore the impact of pioglitazone on SAH.Methods/Design: This trial will recruit 400 patients with SAH from four Chinese hospitals. These patients will be equally and randomly assigned to Pioglitazone and placebo control groups for up to 30 days. Scores on the modified Rankin scale (mRS) are the primary outcomes. The secondary outcomes are a 30-day all-cause mortality rate, 6 months of Montreal cognitive assessment (Mo-CA), delayed cerebral ischemia, the requirement for intensive care, the incidence of sepsis, etc. All serious adverse events (SAEs) were recorded during the hospital. Every primary and safety analysis was conducted based on the intention-to-treat technique. The participants were given either a matching placebo or 15 mg of pioglitazone, with dose titrated to a target of 45 mg daily. Data on the therapeutic use of pioglitazone after SAH will be provided as a consequence of the findings of this experiment. In addition, this pilot trial is the first to prospectively investigate the effectiveness and safety of pioglitazone in patients with SAH.Ethics and dissemination: Ethics approval was obtained from the Medical Ethics Committee of 904th Hospital of Joint Logistic Support Force of PLA (Wuxi Taihu Hospital, approval No. 20220701). The findings of the trial will be presented at conferences, discussed in relevant patient groups, and published in peer-reviewed journals.Clinical Trial Registration:clinicaltrials.gov, identifier ChiCTR2200062954.

Abstract Aberrant activation of TGF-β signaling plays a pivotal role in cancer metastasis and progression. However, molecular mechanisms underlying the dysregulation of TGF-β pathway remain to be understood. Here, we found that SMAD7, a direct downstream transcriptional target and also a key antagonist of TGF-β signaling, is transcriptionally suppressed in lung adenocarcinoma (LAD) due to DNA hypermethylation. We further identified that PHF14 binds DNMT3B and serves as a DNA CpG motif reader, recruiting DNMT3B to the SMAD7 gene locus, resulting in DNA methylation and transcriptional suppression of SMAD7. Our in vitro and in vivo experiments showed that PHF14 promotes metastasis through binding DNMT3B to suppress SMAD7 expression. Moreover, our data revealed that PHF14 expression correlates with lowered SMAD7 level and shorter survival of LAD patients, and importantly that SMAD7 methylation level of circulating tumor DNA (ctDNA) can potentially be used for prognosis prediction. Together, our present study illustrates a new epigenetic mechanism, mediated by PHF14 and DNMT3B, in the regulation of SMAD7 transcription and TGF-β-driven LAD metastasis, and suggests potential opportunities for LAD prognosis.

Objective: This study aimed to investigate the infection status of Omicron in the population and the association between COVID-19 vaccination and infection with Omicron. Methods: We conducted a cross-sectional study to openly recruit participants for a survey of SARS-CoV-2 infection by convenience sampling from 1 January to 15 January 2023 after a COVID-19 pandemic swept across China. Additionally, the binary logistic regression model was adopted to evaluate the association between COVID-19 vaccination and the infection outcomes or symptom severity, respectively. Meanwhile, the relations between the vaccination and duration of the symptoms were estimated via ordinal logistic analysis. Results: Of the 2007 participants, the prevalence of infection with Omicron was 82.9%. Compared with unvaccinated individuals, inactivated COVID-19 vaccination could increase the risk of Omicron infection (OR = 1.942, 95% CI: 1.093–3.448), and the receipt of at least one dose of non-inactivated COVID-19 vaccines was a protective factor against infection (OR = 0.428, 95% CI: 0.226–0.812). By contrast, no relations were observed in COVID-19 vaccination with the symptoms of infection and duration of symptoms (p > 0.05). Conclusions: This cross-sectional study concluded that inactivated COVID-19 vaccination might increase the risk of Omicron infection, which should be a concern during COVID-19 vaccination and the treatment of variant infections in the future, and the receipt of at least one dose of non-inactivated COVID-19 vaccine was a protective factor against infection.

MicroRNAs (miRNA) play a vital role in insects’ growth and development and have significant potential value in pest control. Previously, we identified miR-306 from small RNA libraries within the English grain aphid, Sitobion avenae, a devasting insect pest for wheat. miR-306 not only involves in wing morphogenesis, but also is critically important for aphid survival. Its specific impacts on the life history traits, however, remain unclear. Here, we evaluate the impact of miR-306 perturbation on S. avenae populations using a two-sex life table approach. This comprehensive analysis revealed that miR-306 perturbation significantly prolongs the developmental stages (9.64% and 8.20%) and adult longevity of S. avenae, while decreasing pre-adult survival rate (41.45% and 38.74%) and slightly reducing average fecundity (5.80% and 13.05%). Overall, miR-306 perturbation negatively affects the life table parameters of the aphid population. The population prediction models show a significant decline in the aphid population 60 days post interference, compared to the control groups (98.14% and 97.76%). Our findings highlight the detrimental effects of miR-306 perturbation on S. avenae population growth and suggest potential candidate genes for the development of RNAi-based biopesticides targeted specifically at this pest species.

Abstract During the solidification of a sessile drop, the effect of heat exchange from the gaseous environmental medium is generally ignored. However, by combining experimental observations, direct numerical simulations, and a theoretical model, we have demonstrated that the environmental medium, particularly one with high thermal conductivity such as a liquid, has nonnegligible heat exchange with both the drop and the substrate, leading to accelerated cooling of the outer surface of the sessile drop. Consequently, it causes alterations in the geometry of the freezing front and ultimately results in the formation of a solidified shell that encloses the drop. Furthermore, the encapsulated liquid continues to solidify, which induces volume change and consequently changes the final outcome of the freezing process. This study highlights the importance of considering the properties of the environmental medium and provides novel strategies to manipulate the freezing rate and reshape the morphology of the solidified drop.

Cultural ecosystem services (CES) are intangible benefits humans derive from the ecosystem, closely related to residents' spiritual enrichment, perceptual development, entertainment, and aesthetics. Despite the growing recognition of CES, there remains a need for a public understanding of CES performance in terms of indicators content, change and occurrence. This study developed a three-level indicator framework for evaluating urban green spaces CES at the design level. We integrated seven categories of CES indicators as primary indicators of the framework. Based on text comments in social media data, a bottom-up approach was adopted to collect CES-related words as the secondary indicators and elements. We evaluated the CES performance in union square park using the established framework. The results indicate that interactive activities are the most popular CES in the park, while the sense of place, social relationship and educational functions fail to receive a wide response, which should be given strong attention. The leading indicators within the park exhibit consistent trends in seasonal and demographic changes. In addition, there are co-occurrences between CES indicators, mainly manifested in interactive activities, aesthetic values, and health benefits, and the degree of co-occurrence varies. The CES framework proposed in this study measures the CES perception within urban green spaces, provides a detailed explanation of CES indicators, and forms an effective theoretical basis for future park management and development.

Intensification of biofuel production processes could play a critical role in boosting the economic and environmental features of the whole process. A novel bionic flow-induced peristaltic reactor with a high conversion rate is constructed to realize efficient biofuel production from high-concentration high-viscosity fluids. It is experimentally verified through biodiesel production from soybean oil. Experimental results show that the conversion efficiency is up to 89.9% at 10 s in the peristaltic reactor, which is 38.4% higher than that in the rigid tube reactor. Furthermore, a three-dimensional peristaltic model is conducted to understand the mechanism of heat and mass transfer enhancement. The simulation results show that an increase in peristaltic amplitude strengthens the mixing of the bionic peristaltic reactor by 92.5-100.8%. The temperature distribution in the bionic peristaltic reactor is more uniform than in the traditional rigid tube reactor. The results demonstrate that the conversion rate of soybean oil in the bionic flow-induced peristaltic reactor is 528.82% min-1, which is 17-60 times higher than other intensified reactors operating in either continuous or batch modes.

In this study, polylactic acid/graphene oxide/Dopamine (PLA/GO/DA) porous nanofiber membrane was prepared by electrospinning. L _16 (4 ^3 ) orthogonal experiment was designed to investigate the effects of reaction temperature, reaction time, and DA concentration on the adsorption performance of DA oxidized and self-polymerized on the fiber. Based on the characterization of scanning electron microscopy and the determination of the adsorption performance of the fiber membrane to methylene blue (MB) dye, data visualization analysis, variance analysis, and F-test were conducted to determine the optimal process parameters: reaction temperature of 45 °C, reaction time of 30 h, and DA concentration of 2 mg ml ^−1 . PLA/GO/PDA(Polydopamine) nanofiber was prepared and characterized under the optimal process parameters. The results showed that the average diameter of the PDA-loaded nanofiber increased from 737 nm to 996 nm, and a layer of PDA with a thickness of about 129 nm was loaded on the outer surface of the fiber, making the contact angle of the fiber membrane with 0° and becoming a hydrophilic material. In adsorption performance testing of MB, the PLA/GO/PDA nanofiber membrane prepared based on the PLA/GO/DA fiber membrane with an adsorption rate of 98.81 % in 24 h was superior to the PLA/GO/PDA nanofiber membrane prepared based on the PLA/GO fiber membrane.

Based on porosity and permeability tests, high-pressure mercury injection (HPMI), nuclear magnetic resonance (NMR) and centrifugal experiments, this study comprehensively analyzed the quality, pore structure and fractal characteristics of tight sandstone reservoir in meandering stream facies. The purpose is to reveal the relationship between physical properties, geometry and topological parameters of pores, fluid mobility and heterogeneity of pore system of tight sandstone reservoirs in meandering stream facies. The results show that the second member of the Middle Jurassic Shaximiao Formation (J2S2) in the central Sichuan Basin has developed tight sandstone reservoir of meandering fluvial facies, the pore radius of type I reservoir (K>0.3 mD) is mainly distributed at 0.01 μm∼2 μm, the tortuosity ranges between 2.571 and 2.869, and the average movable fluid saturation is 70.12%. The pore radius of type II reservoir (0.08mD

Silicon-based polarization-encoding quantum key distribution (QKD) has been extensively studied due to its advantageous characteristics of its low cost and robustness. However, given the difficulty of fabricating polarized independent components on the chip, previous studies have only adopted off-chip devices to demodulate the quantum states or perform polarization compensation. In the current work, a fully chip-based decoder for polarization-encoding QKD was proposed. The chip realized a polarization state analyzer and compensated for the BB84 protocol without the requirement of additional hardware, which was based on a polarization-to-path conversion method utilizing a polarization splitter-rotator. The chip was fabricated adopting a standard silicon photonics foundry, which was of a compact design and suitable for mass production. In the experimental stability test, an average quantum bit error rate of 0.59% was achieved through continuous operation for 10 h without any polarization feedback. Furthermore, the chip enabled the automatic compensation of the fiber polarization drift when utilizing the developed feedback algorithm, which was emulated by a random fiber polarization scrambler. Moreover, a finite-key secret rate of 240 bps over a fiber spool of 100 km was achieved in the case of the QKD demonstration. This study marks an important step toward the integrated, practical, and large-scale deployment of QKD systems.

The well-documented decrease in the annual minimum Arctic sea ice extent over the past few decades is an alarming indicator of current climate change. However, much less is known about the thickness of the Arctic sea ice. Developing accurate forecasting models is critical to better predict its changes and monitor the impacts of global warming on the total Arctic sea ice volume (SIV). Significant improvements in forecasting performance are possible with the advances in signal processing and deep learning. Accordingly, here, we set out to utilize the recent advances in machine learning to develop non-physics-based techniques for forecasting the sea ice volume with low computational costs. In particular, this paper aims to provide a step-wise decision process required to develop a more accurate forecasting model over short- and mid-term horizons. This work integrates variational mode decomposition (VMD) and bidirectional long short-term memory (BiLSTM) for multi-input multi-output pan-Arctic SIV forecasting. Different experiments are conducted to identify the impact of several aspects, including multivariate inputs, signal decomposition, and deep learning, on forecasting performance. The empirical results indicate that (i) the proposed hybrid model is consistently effective in time-series processing and forecasting, with average improvements of up to 60% compared with the case of no decomposition and over 40% compared with other deep learning models in both forecasting horizons and seasons; (ii) the optimization of the VMD level is essential for optimal performance; and (iii) the use of the proposed technique with a divide-and-conquer strategy demonstrates superior forecasting performance.

A PCB spring terminal is a common type of connector found on the printed circuit board of electronic devices. Contact force is a crucial performance metric of this component that directly affects the product’s dependability. In actual production, the contact force is unstable, and the influencing factors are unknown, whereas conventional experimental research is restricted to costly and error-prone trial-and-error procedures. In this study, finite element simulation technology and Spearman rank correlation analysis are combined to determine the crucial factors controlling the contact force of the PCB spring terminals in the structural design parameters and the plating related parameters. The validity of the results is confirmed by the measured data. The results indicate that the thickness of the spring terminal is the most significant factor in controlling the contact force. According to the conclusion, the company has re-established the inspection standard and resolved production problems. This case shows that the combination of finite element simulation and correlation analysis can be used to find the most important design parameters of such components quickly, accurately, and cheaply.

Field populations of insect pests are affected by sub-lethal doses of insecticides, leading to hormesis. Imidacloprid is a neonicotinoid insecticide widely used to control various sucking insect pests, including aphids. In this study, the effects of sub-lethal concentrations of imidacloprid on the life table traits of the rose-grain aphid Metopolophium dirhodum (Walker) were evaluated on parental and first filial generations. The results showed that sub-lethal concentrations of imidacloprid significantly reduced the fecundity, adult longevity, and reproductive period of M. dirhodum in parental generation (F0). However, the imidacloprid-induced hormetic effects on development and reproduction were detected in the F1 generation. These hormetic effects were indicated by significantly higher adult longevity, fecundity, survival rate, intrinsic and finite rates of increase, and net reproductive rate of first filial generation (F1) of M. dirhodum. Our finding indicated that the application of sub-lethal concentrations of imidacloprid inhibited parental generation (F0), but it significantly stimulated the population growth of filial generation (F1) in the M. dirhodum. The results support the inclusion of insecticides in integrated pest management programs for managing wheat aphids.

A complex urban living environment and residents' sleep quality are intrinsically linked. Nonetheless, there is little evidence that the residential environment affects sleep quality. Based on the results of subjective questionnaires, this study uses the multiple regression combined with mediation analysis to construct a mechanical model of the impact of urban residential environmental perception characteristics on residents' sleep quality. Moreover, the differences among the influence intensities of the significant factors are compared and the results show that (1) in low-density environments (FAR < 2) and lower floors (4–6), residents sleep longer and have better sleep quality; (2) the environmental quality and service facilities of the physical environment and the sense of safety in the social environment have a significant impact on residents' sleep quality; and (3) the mental health of residents play a significant intermediary role in the relationship between social environment and sleep quality, with the highest effect accounting for 33.88%. The influence mechanisms of various environmental factors in a residential area on sleep quality were revealed and a more refined design basis for a healthy urban living environment, community renewal, and renovation was provided.

ObjectiveTo explore the value of color Doppler ultrasonography (CDU) to predict preoperatively and evaluate postoperatively the collateral development of two common revascularizations in patients with moyamoya disease (MMD).MethodsWe prospectively enrolled 49 patients with MMD who underwent unilateral superficial temporal artery (STA) -middle cerebral artery (MCA) anastomosis or encephalo-duro-arterio-synangiosis (EDAS). The parameters of the extracranial arteries, including STA, internal carotid artery (ICA), external carotid artery (ECA), and vertebral artery (VA), were performed before and at 3–6 months after surgery. DSA results were used to assess surgical collateral development.ResultsTo predict good collateral development before STA-MCA anastomosis, the preoperative D > 1.75 mm in the STA had the highest area under the Receiver Operating Characteristic curve (AUC). To predict good collateral development before EDAS, the preoperative EDV > 12.00 cm/s in the STA had the highest AUC. To evaluate the good collateral development after STA-MCA anastomosis, the postoperative EDV > 16.50 cm/s in the STA had the highest AUC. To evaluate the good collateral development after EDAS, an increase of D of 0.15 mm in the STA had the highest AUC. Logistic regression analysis showed that the preoperative RI and EDV in the STA were highly correlated with collateral development. Besides, the preoperative RI was an independent risk factor for collateral development.ConclusionCDU could predict preoperatively and evaluate postoperatively the collateral development of STA-MCA anastomosis and EDAS surgery postoperatively by detecting ultrasound parameters of the STA.

Pancreatic cancer is the fourth leading cause of cancer death in the United States. The main methods of treating pancreatic cancer are surgery and chemotherapy, but the treatment efficacy is low with a poor prognosis. Immunotherapy represented by PD-1/PD-L1 has brought a milestone progress in the treatment of pancreatic cancer. However, the unique tumor microenvironment of pancreatic cancer presents challenges for immunotherapy. In addition, m6A is a common RNA modification and a potential molecular target in tumor therapy. The expression pattern of m6A in pancreatic cancer is still unclear. LncRNAs also play an essential role in pancreatic cancer development and treatment. In this study, we found that some m6A regulators were significantly elevated in pancreatic cancer and associated with the expression of PD-1/PD-L1. Moreover, we observed that METTL3 can increase the expression of PD-L1. Notably, METTL3 positively regulates the expression of lncRNA MALAT1 in pancreatic cancer cells. Strikingly, lncRNA MALAT1 increased the expression of PD-L1 in pancreatic cancer cells. This finding indicated that METTL3 regulated the expression of PD-L1 possibly via targeting lncRNA MALAT1 in pancreatic cancer cells. Lastly, MALAT1 governed the viability of pancreatic cancer cells. Taken together, lncRNA MALAT1 is involved in METTL3-mediated promotion of PD-L1 expression in pancreatic cancer.

Doping of heteroatoms into carbon materials is a popular method to modify their physicochemical structures and has been widely used in the fields of energy conversion and storage. This study aims to investigate the effect of doping atmosphere on the catalytic performance of nitrogen and sulfur co-doped biochar supported Ru in the production of phenolic monomers from lignin hydrogenolysis. The results showed that the catalyst prepared under CO2 atmosphere (Ru@CNS-CO2) was able to produce phenolic monomers from corncob lignin with a yield up to 36.41 wt%, which was significantly higher than that from the run over N2-prepared catalyst (Ru@CNS-N2). The characterization of the catalysts demonstrated that the CNS-CO2 support had a larger specific surface area, richer C=S and C-S groups, and higher oxygen content than CNS-N2, resulting in finer Ru particles and more Ru0 content on the CNS-CO2 support. The Ru@CNS-CO2 catalyst exhibited high activity in hydrogenation and fragmentation of β-O-4 linkages.

The porous liquid (PLs) is a new material containing both permanent porosity of porous materials and liquid fluidity of solvent at room temperature, which has shown a great potential in gas separation. In this study, a novel type ? porous liquids were prepared using 2-methylimidazole zinc salt (ZIF-8) modified by tetraethylenepentamine (TEPA) as the main units and 1-Ethyl-3-methylimidazolium Bis(trifluoro-methanesulfonyl)-imide ([EMlm][NTf2]) as the sterically hindered solvent. The effect of amine loading on the CO2 absorption performance of PLs was investigated. When amine load was 30 wt%, 30TEPA@ZIF-8 not only had the pore structure inside but also effectively increased the CO2 absorption capacity of PLs. When the effect of different parameters on CO2 absorption capacity was investigated, it was found that the optimal adsorption temperature was 60 °C, and the optimal concentration of the main units was7.5 wt%. After five cycles, the absorbent's cycle efficiency and desorption efficiency were more than 98 %. All the results indicate that the prepared PLs in this paper had an application potential in CO2 capture.

Pesticides serve as indispensable inputs to ensure the optimal provision of agricultural commodities, thus exerting a significant influence on the quality and yield of food [...]

Zinc-based hybrid-flow batteries are considered as a promising alternative to conventional electrochemical energy-storage systems for medium- to large-scale applications due to their high energy densities, safety, and abundance. However, the performance of these batteries has been limited by issues such as dendritic growth and passivation of zinc anodes during charge–discharge cycling. To address this challenge, a variety of two- and three-dimensional zinc anodes have been investigated. While two-dimensional zinc anodes have been extensively studied, there has been limited investigation into three-dimensional zinc anodes for hybrid-flow batteries. This study highlights the potential of three-dimensional zinc anodes to mitigate overpotentials and improve the mass transport of active species to promote negative electrode reactions. The performance of a membraneless flow battery based on low-cost zinc and organic quinone was herein evaluated using experimental and numerical approaches. Specifically, the use of zinc fiber was shown to yield an average coulombic efficiency of approximately 90% and an average voltage efficiency of approximately 82% over the course of 100 cycles at a current density of 30 mA cm−2. These results indicate the viability of using zinc fiber anodes to improve the performance of existing hybrid-flow batteries.

Abstract Flexibly and precisely manipulating 3D droplet transportation is a fundamental challenge for broad implications in diagnostics, drug delivery, bioengineering, etc. Herein, a light method is developed for manipulating a droplet to make it behave like a submarine. This light method enables flexible 3D transportation, stable suspension, and floating of a droplet, which can be freely altered. It is demonstrated that the localized photothermal effect induced thermocapillary flow in the water droplet/oil phase is responsible for energizing and manipulating the droplet. With such remarkable motility, the light‐fueled submarine‐like droplet successfully realizes various functions such as the acid‐base detection, particle capture and transportation, and target crystal collection, dissolution and transportation. It is demonstrated that the light‐fueled submarine‐like droplet shows promising perspective for long‐sought precise droplet manipulation in various applications.

Activated Notch signalling promotes cancer metastasis and stemness. Here the authors show that Notch1 activates transcription of DNA replication factor RCF4 and that RCF4 binds and stabilises Notch1 intracellular domain (NICD1) to promote cancer metastasis.

Abstract Background Although several measures have been taken to control hand foot and mouth disease (HFMD) and herpangina (HA), these two diseases have been prevalent in China for 10 years with high incidence. We suspected that adults’ inapparent infection might be the cause of the continued prevalence of HFMD/HA infection in mainland China. Methods To explore the role of adults (especially caregivers) in the transmission process of HFMD/HA among children, 330 HFMD/HA cases and 330 healthy children (controls) were selected for a case–control study. Then, data were analyzed by logistic regression. Results Single-variable analyses revealed that caregivers who tested positive for enterovirus was a significant risk factor of HFMD/HA transmission to children (adjusted odds ratio (OR) = 9.22; 95% CI, 1.16 to 73.23). In the final multivariable model, caregiver behavior, such as cooling children’s food with mouth (OR = 1.85; 95% CI, 1.11 to 3.08) and feeding children with their own tableware (OR = 2.19; 95% CI, 1.07 to 4.45), significantly increased the risk of transmitting HFMD/HA to children. On the contrary, washing hands before feeding children reduced such risk. Conclusions These results implied that the caregivers might be the infectious source or carriers of enterovirus. Therefore, preventing or treating the caregivers’ enterovirus infection and improving their hygiene habits, especially when they are in contact with children, could provide a breakthrough for the effective control of HFMD/HA.

Ecdysteroid hormones are key regulators of insect development and metamorphosis. Ecdysone-inducible E75, a major component of insect ecdysone signaling pathway, has been well characterized in holometabolous insects, however, barely in hemimetabolous species. In this study, a total of four full-length E75 cDNAs from the English grain aphid, Sitobion avenae, were identified, cloned, and characterized. The four SaE75 cDNAs contained 3048, 2625, 2505, and 2179 bp open reading frames (ORF), encoding 1015, 874, 856, and 835 amino acids, respectively. Temporal expression profiles showed that SaE75 expression was low in adult stages, while high in pseudo embryo and nymphal stages. SaE75 was differentially expressed between winged and wingless morphs. RNAi-mediated suppression of SaE75 led to substantial biological impacts, including mortality and molting defects. As for the pleiotropic effects on downstream ecdysone pathway genes, SaHr3 (hormone receptor like in 46) was significantly up-regulated, while Sabr-c (broad-complex core protein gene) and Saftz-f1 (transcription factor 1) were significantly down-regulated. These combined results not only shed light on the regulatory role of E75 in the ecdysone signaling pathway, but also provide a potential novel target for the long-term sustainable management of S. avenae, a devastating global grain pest.

Abstract Metopolophium dirhodum (Walker) (Hemiptera: Aphididae) is one of the most common aphid pests of winter cereals. To facilitate accurate gene expression analyses with qRT-PCR assays, the expression stability of candidate reference genes under specific experimental conditions must be verified before they can be used to normalize target gene expression levels. In this study, 10 candidate reference genes in M. dirhodum were analyzed by qRT-PCR under various experimental conditions. Their expression stability was evaluated with delta Ct, BestKeeper, geNorm, and NormFinder methods, and the final stability ranking was determined with RefFinder. The results indicate that the most appropriate sets of internal controls were SDHB and RPL8 across geographic population; RPL8, Actin, and GAPDH across developmental stage; SDHB and NADH across body part; RPL8 and Actin across wing dimorphism and temperature; RPL4 and EF1A across starvation stress; AK and RPL4 across insecticide treatments; RPL8 and NADH across antibiotic treatments; RPL8, RPL4, Actin, and NADH across all samples. The results of this study provide useful insights for establishing a standardized qRT-PCR procedure for M. dirhodum and may be relevant for identifying appropriate reference genes for molecular analyses of related insects.

Motivated by MMS mission observations near magnetic reconnection sites, we have developed a new empirical reconstruction (ER) model of the three-dimensional (3D) magnetic field and the associated plasma currents. Our approach combines both the measurements from a constellation of satellites and a set of physics-based equations as physical constraints to build spatially smooth distributions. This ER model directly minimizes the loss function that characterizes the model-measurement differences and the model departures from linear or nonlinear physical constraints using an efficient stochastic optimization method by which the effects of random measurement errors can be effectively included. Depending on the availability of the measured parameters and the adopted physical constraints on the reconstructed fields, the ER model could be either slightly over-determined or under-determined, yielding nearly identical reconstructed fields when solved by the stochastic optimization method. As a result, the ER model remains valid and operational even if the input measurements are incomplete. Two sets of new indices associated respectively with the model-measurement differences and the model departures are introduced to objectively measure the accuracy and quality of the reconstructed fields. While applying the reconstruction model to observations of an electron diffusion region (EDR) observed by NASA’s Magnetospheric Multiscale (MMS) mission, we examine the relative contributions of the errors in the plasma current density arising from random measurement errors and linear approximations made in application of the curlometer technique. It was found that the errors in the plasma current density calculated directly from the measured magnetic fields using a linear approximation were mostly contributed from the nonlinear configuration of the 3D magnetic fields.

Background: Acute respiratory infections (ARIs) remain a significant public threat with high morbidity and mortality worldwide; viruses are significant pathogens that cause ARIs. This study was conducted to better understand the epidemiological characteristics of respiratory viruses circulating in southern China. Methods: We collected 22,680 respiratory samples from ARI patients in 18 hospitals in southern China during 2009–2018; seven common respiratory viruses including Flu, RSV, PIV, hMPV, ADV, HCoV, and HBoV were screened using in-house real-time PCR. Results: Of all samples, 9760 ARI cases (9760/22680, 43.03%) tested positive for the seven common respiratory viruses. The most detected virus was Flu (14.15%), followed by RSV (10.33%) and PIV (5.43%); Flu-A, PIV3, and HCoV-OC43 were the predominant subtypes. Although most of the viruses were detected in male inpatients, Flu was more likely detected in female outpatients. Flu infection was more likely to cause URTI (upper respiratory tract infection), whereas RSV infection was more likely to cause pneumonia and bronchitis. The prevalence of Flu was particularly high in 2009. The epidemic level was found notably high in 2014–2018 for RSV, in 2016–2018 for PIV, in the summer of 2018 for ADV, in the summer of 2016 and winter of 2018 for HCoV, and in the summer of 2011 and autumn of 2018 for HBoV. The co-detection rate of the seven viruses was 4.70%; RSV, PIV, and Flu were the most commonly co-detected viruses. Conclusions: This work demonstrates the epidemiological characteristics of seven common respiratory viruses in ARI patients in southern China.

The two-step photosynthetic biogas upgrading process, which combines CO2 capture by carbonate solution and carbonate regeneration by using aquatic microbial oxygenic photoautotrophs (i.e., cyanobacteria, algae, and diatoms), may provide a potential alternative to the commercial routes used for gaseous biofuel upgrading. Such a process not only provides a green and low energy intensive biogas upgrading pathway but also converts CO2 in biogas into high value biomass. To improve the upgrading performance, the effects of light intensity and NaHCO3 concentration on the growth and the HCO3- transformation characteristics of halophilic and alkaliphilic Spirulina platensis were investigated in this study. Experimental results showed that the light attenuation of S. platensis culture was significant. Increasing light intensity up to 210 μmol m-2 s-1 effectively improved the S. platensis growth and photosynthetic pigment accumulation. S. platensis could grow in the range of 0.05 to 0.6 M NaHCO3, and a maximum biomass concentration of 1.46 g L-1 was achieved under an optimal growth condition of 0.1 M NaHCO3, which was 65.9% higher than at 0.05 M NaHCO3. Moreover, the bicarbonate utilization efficiency reached 42.0%. Finally, in a case study, a biogas stream at a flow rate of 800 m3 h-1 could generate biomass up to 344 kg h-1, corresponding an energy value of 5591 MJ h-1.

Abstract Background Zika virus (ZIKV) infection is a global health problem, and its complications, including congenital Zika syndrome and Guillain-Barré syndrome, constitute a continued threat to humans. Unfortunately, effective therapeutics against ZIKV infection are not available thus far. Methods We screened the compounds collection consisting of 1789 FDA-approved drugs by a computational docking method to obtain anti-ZIKV candidate compounds targeting ZIKV RNA-dependent RNA polymerase (RdRp). SPR (BIAcore) assay was employed to demonstrate the candidate compounds’ direct binding to ZIKV RdRp, and polymerase activity assay was used to determine the inhibitory effect on ZIKV RdRp-catalyzed RNA synthesis. The antiviral effects on ZIKV in vitro and in vivo were detected in infected cultured cells and in Ifnar1 −/− mice infected by ZIKV virus using plaque assay, western blotting, tissue immunofluorescence, and immunohistochemistry. Results Here, we report that a first-in-class macrocyclic antibiotic, which has been clinically used to treat Clostridium difficile infection, fidaxomicin, potently inhibits ZIKV replication in vitro and in vivo. Our data showed that fidaxomicin was effective against African and Asian lineage ZIKV in a wide variety of cell lines of various tissue origins, and prominently suppressed ZIKV infection and significantly improved survival of infected mice. In addition, fidaxomicin treatment reduced the virus load in the brains and testes, and alleviated ZIKV-associated pathological damages, such as paralysis, hunching, and neuronal necrosis in the cerebra. Furthermore, our mechanistic study showed that fidaxomicin directly bound ZIKV NS5 protein and inhibited the RNA synthesis-catalyzing activity of ZIKV RdRp. Conclusions Our data suggest that fidaxomicin may represent an effective anti-ZIKV agent. In the light that fidaxomicin is already a clinically used drug, there might be a promising prospect in the development of fidaxomicin to be an antiviral therapeutic.

Keyphrases provide core information for users to understand the document. Most previous works utilize machine learning based methods for keyphrases extraction and achieve promising performance. However, these methods focus on identify keyphrases from the input text, and can not extract keyphrases that do not appear in the text. In this paper, we present an encoder-decoder framework, which incorporating copying mechanism, to generate keyphrases for the given text. This framework (CopyNet) integrates the generation part and copying part. The generation part generates the keyphrase from the predefined vocabulary, and the copy part gets the keyphrases from the source text. Furthermore, we improve the CopyNet by using different probability of the two parts. To incorporate more related information for keyphrase generation, the automatically built keyphrase semantic web is merged into the dataset to participate in the training process of the neural network. Semantic similarity based and word co-occurrence based methods are used for keyphrase semantic web construction. We build a large-scale biomedical keyphrase dataset to evaluate the system performance. Experiments show that our improved CopyNet can achieve better performance with different portions of the generation and copying part, and the incorporation of the semantic web also effectively improves the keyphrase generation.

Background: Human respiratory syncytial virus (RSV) is one of the most important pathogens that cause acute respiratory infections in children and immunocompromised adults. This work was conducted to understand the epidemiological and phylogenetic features of RSV in southern China during 2011–2016. Methods: A total of 16 024 nasopharyngeal swabs were collected from patients with respiratory infections in 14 hospitals, and screened for RSV and seven other respiratory viruses using real-time PCR. Six hundred and twenty-three RSV-positive samples from 13 hospitals were further analyzed for subtypes. G gene sequencing and phylogenetic analysis were performed based on 46 RSV-A and 15 RSV-B strains. Results: RSV was detected in 9.5% of the 16 024 specimens, the highest among the eight respiratory viruses screened. Most of these specimens came from inpatients and children under 3 years of age. The incidence of RSV-A (9.4%) was higher than that of RSV-B (4.4%) in children (

With the maturity and popularity of network technology and multimedia technology, more and more communication tools and means have entered people’s lives. The usual communication tools are often limited to the ability to transmit sound signals. This method does not well express the information between the two parties in some special occasions, such as a noisy environment, where both parties have language or hearing impairments. The multimedia communication system is a technology that combines network communication and multimedia. It utilizes the efficiency of data transmission over the network and the diversity of information in multimedia, making communication between people faster, clearer, and more intuitive. The multimedia communication system is an important part of the application to the intelligent transportation system. Intelligent transportation system is a systematic, real-time, accurate, interactive, and extensive traffic management system established by the comprehensive use of modern high and new technology in the transportation system. With these characteristics, intelligent transportation system has increasingly become an important means to solve modern traffic problems. Based on multimedia communication and intelligent transportation system, this article optimizes the vehicle path and realizes the application of intelligent transportation. The proposed intelligent transportation system realizes functions, such as vehicle speed detection, vehicle behavior semantic analysis, license plate recognition by processing video data, and image data acquired based on multimedia communication, and can capture illegal vehicles and then identify illegal vehicles. The license plate is conducive to promoting the management and control of intelligent transportation and reducing the occurrence of traffic accidents.