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Abstract Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes.

AbstractContext The Xihuang pill (XHP) is a traditional Chinese medicine formulation that has been historically used in the prevention and treatment of proliferative breast diseases. However, there is a lack of guidelines that offer recommendations for its clinical use.Objective The task force from the Chinese Guangdong Pharmaceutical Association aims to develop evidence-based guidelines for XHP to prevent and treat proliferative breast diseases.Methods We searched six Chinese and English electronic databases, including the China National Knowledge Infrastructure, the Chinese Scientific Journal Database, the Wanfang Medical Database, PubMed, and Embase, up to November 1, 2022. Publications (case reports, clinical observation, clinical trials, reviews) on using XHP to treat proliferative breast diseases were manually searched. The search terms were Xihuang pill, hyperplasia of the mammary gland, breast lump, and mastalgia. The writing team developed recommendations based on the best available evidence.Results Treatment should be customized based on syndrome identification. We recommend using XHP for the prevention and treatment of breast hyperplasia disease when a patient presents the following syndromes: concurrent blood stasis syndrome, concurrent phlegm-stasis syndrome, and concurrent liver fire syndrome. Safety indicators, including blood analysis and liver and kidney function monitoring, should be performed regularly during treatment.Conclusions Current clinical evidence suggests that XHP can be used as a standalone treatment or in conjunction with other medications to prevent and manage breast hyperplasia diseases. More randomized controlled studies are warranted to establish high-quality evidence of its use.

Abstract Photo-thermal-coupling ammonia decomposition presents a promising strategy for utilizing the full-spectrum to address the H2 storage and transportation issues. Herein, we exhibit a photo-thermal-catalytic architecture by assembling gallium nitride nanowires-supported ruthenium nanoparticles on a silicon for extracting hydrogen from ammonia aqueous solution in a batch reactor with only sunlight input. The photoexcited charge carriers make a predomination contribution on H2 activity with the assistance of the photothermal effect. Upon concentrated light illumination, the architecture significantly reduces the activation energy barrier from 1.08 to 0.22 eV. As a result, a high turnover number of 3,400,750 is reported during 400 h of continuous light illumination, and the H2 activity per hour is nearly 1000 times higher than that under the pure thermo-catalytic conditions. The reaction mechanism is extensively studied by coordinating experiments, spectroscopic characterizations, and density functional theory calculation. Outdoor tests validate the viability of such a multifunctional architecture for ammonia decomposition toward H2 under natural sunlight.

Abstract Background Standard systematic review can be labor-intensive and time-consuming meaning that it can be difficult to provide timely evidence when there is an urgent public health emergency such as a pandemic. The ClinicalTrials.gov provides a promising way to accelerate evidence production. Methods We conducted a search on PubMed to gather systematic reviews containing a minimum of 5 studies focused on safety aspects derived from randomized controlled trials (RCTs) of pharmacological interventions, aiming to establish a real-world dataset. The registration information of each trial from eligible reviews was further collected and verified. The meta-analytic data were then re-analyzed by using 1) the full meta-analytic data with all trials and 2) emulated rapid data with trials that had been registered and posted results on ClinicalTrials.gov, under the same synthesis methods. The effect estimates of the full meta-analysis and rapid meta-analysis were then compared. Results The real-world dataset comprises 558 meta-analyses. Among them, 56 (10.0%) meta-analyses included RCTs that were not registered in ClinicalTrials.gov. For the remaining 502 meta-analyses, the median percentage of RCTs registered within each meta-analysis is 70.1% (interquartile range: 33.3% to 88.9%). Under a 20% bias threshold, rapid meta-analyses conducted through ClinicalTrials.gov achieved accurate point estimates ranging from 77.4% (using the MH model) to 83.1% (using the GLMM model); 91.0% to 95.3% of these analyses accurately predicted the direction of effects. Conclusions Utilizing the ClinicalTrials.gov platform for safety assessment with a minimum of 5 RCTs holds significant potential for accelerating evidence synthesis to support urgent decision-making.

Turnip mosaic virus (TuMV) is a devastating potyvirus pathogen that infects a wide variety of both cultivated and wild Brassicaceae plants. We urgently need more information and understanding of TuMV pathogenesis and the host responses involved in disease development in cruciferous crops. TuMV displays great versatility in viral pathogenesis, especially in its replication and intercellular movement. Moreover, in the coevolutionary arms races between TuMV and its hosts, the virus has evolved to co-opt host factors to facilitate its infection and counter host defense responses. This review mainly focuses on recent advances in understanding the viral factors that contribute to the TuMV infection cycle and the host resistance mechanism in Brassica. Finally, we propose some future research directions on TuMV pathogenesis and control strategies to design durable TuMV-resistant Brassica crops.

Exploitation of oxygen evolution reaction (OER) and urea oxidation reaction (UOR) catalysts with high activity and stability at large current density is a major challenge for energy-saving H2 production in water electrolysis. Herein, we use the pyridinic-N doping carbon layers coupled with tensile strain of FeNi alloy activated by NiFe2O4 (FeNi/NiFe2O4@NC) for efficiently increasing the performance of water and urea oxidation. Due to the tensile strain effect on FeNi/NiFe2O4@NC, it provides a favorable modulation on the electronic properties of the active center, thus enabling amazing OER (η100 = 196 mV) and UOR (E10 = 1.32 V) intrinsic activity. Besides, the carbon-coated layers can be used as armor to prevent FeNi alloy from being corroded by the electrolyte for enhancing the OER/UOR stability at large current density, showing high industrial practicability. This work thus provides a simple way to prepare high-efficiency catalyst for activating water and urea oxidation.

The forage-livestock balance is an important component of natural grassland management, and realizing a balance between the nutrient energy demand of domestic animals and the energy supply of grasslands is the core challenge in forage-livestock management. This study was performed at the Xieertala Ranch in Hulunbuir City, Inner Mongolia. Using the GRAZPLAN and GrazFeed models, we examined the forage-livestock energy balance during different grazing periods and physiological stages of livestock growth under natural grazing conditions. Data on pasture conditions, climatic factors, supplemental feeding, and livestock characteristics, were used to analyze the metabolizable energy (ME), metabolizable energy for maintenance (MEm), and total metabolizable energy intake (MEItotal) of grazing livestock. The results showed that the energy balance between forage and animals differed for adult cows at different physiological stages. In the early lactation period, although the MEItotal was greater than MEm, it did not meet the requirement for ME. MEItotal was greater than ME during mid-lactation, but there was still an energy imbalance in the early and late lactation periods. In the late lactation period, MEItotal could meet ME requirements from April–September. Adult gestational lactating cows with or without calves were unable to meet their ME requirement, especially in the dry period, even though MEItotal was greater than MEm. Adult cows at different physiological stages exhibited differences in daily forage intake and rumen microbial crude protein (MCP) metabolism, and the forage intake by nonpregnant cows decreased as follows: early lactation > mid-lactation > late lactation, pregnant cows’ lactation > dry period. For the degradation, digestion and synthesis of rumen MCP, early-lactation cows were similar to those in the mid-lactation group, but both were higher than those in the late-lactation group, while pregnant cows had greater degradation, digestion, and synthesis of MCP in the lactation period relative to the dry period. For lactating cows, especially those with calves, grazing energy requirements, methane emission metabolism and heat production were highest in August, with increased energy expenditure in winter. Overall, grazing energy, methane emissions and heat production by dry cows were low. In the context of global climate change and grassland degradation, managers must adopt different strategies according to the physiological stages of livestock to ensure a forage-livestock balance and the sustainable utilization and development of grasslands.

Deltacoronavirus, widely distributed among pigs and wild birds, pose a significant risk of cross-species transmission, including potential human epidemics. Metagenomic analysis of bird samples from Qinghai Lake, China in 2021 reported the presence of Deltacoronavirus. A specific gene fragment of Deltacoronavirus was detected in fecal samples from wild birds at a positive rate of 5.94% (6/101). Next-generation sequencing (NGS) identified a novel Deltacoronavirus strain, which was closely related to isolates from the United Arab Emirates (2018), China (2022), and Poland (2023). Subsequently the strain was named A/black-headed gull/Qinghai/2021(BHG-QH-2021) upon confirmation of the Cytochrome b gene of black-headed gull in the sample. All available genome sequences of avian Deltacoronavirus, including the newly identified BHG-QH-2021 and 5 representative strains of porcine Deltacoronavirus (PDCoV), were classified according to ICTV criteria. In contrast to Coronavirus HKU15, which infects both mammals and birds and shows the possibility of cross-species transmission from bird to mammal host, our analysis revealed that BHG-QH-2021 is classified as Putative species 4. Putative species 4 has been reported to infect 5 species of birds but not mammals, suggesting that cross-species transmission of Putative species 4 is more prevalent among birds. Recombination analysis traced BHG-QH-2021 origin to dut148cor1 and MW01_1o strains, with MW01_1o contributing the S gene. Surprisingly, SwissModle prediction showed that the optimal template for receptor-binding domain (RBD) of BHG-QH-2021 is derived from the human coronavirus 229E, a member of the Alphacoronavirus, rather than the anticipated RBD structure of PDCoV of Deltacoronavirus. Further molecular docking analysis revealed that substituting the loop 1–2 segments of HCoV-229E significantly enhanced the binding capability of BHG-QH-2021 with human Aminopeptidase N (hAPN), surpassing its native receptor-binding domain (RBD). Most importantly, this finding was further confirmed by co-immunoprecipitation experiment that loop 1–2 segments of HCoV-229E enable BHG-QH-2021 RBD binding to hAPN, indicating that the loop 1–2 segment of the RBD in Putative species 4 is a probable key determinant for the virus ability to spill over into humans. Our results summarize the phylogenetic relationships among known Deltacoronavirus, reveal an independent putative avian Deltacoronavirus species with inter-continental and inter-species transmission potential, and underscore the importance of continuous surveillance of wildlife Deltacoronavirus.

Daylighting plays a crucial role in building science, impacting both occupants’ well-being and energy consumption in buildings. Balancing the size of openings with energy efficiency has long been a challenge. To address this, various daylight metrics have been developed to assess interior spaces’ daylight quality. Additionally, architects have been using simulation algorithms to predict postconstruction light conditions. In recent years, machine learning (ML) has revolutionized daylight simulations, offering a way to predict daylight conditions without cumbersome 3D modeling or heavy computational resources. However, accommodating architects’ creativity remains a challenge for current machine learning-based models. Specifically, the diversity of window shapes and their locations on facades poses difficulties for prediction accuracy. To overcome this limitation, this paper proposes a novel method that transforms wall information into matrices and uses them as input to train an artificial neural network-based model; this model can well predict the annual daylight simulation result generated by the Climate-Based Daylight Modeling tools. This method allows the model to adapt to various real-world design scenarios in real time, and its robust reliability has been demonstrated through evaluations of prediction accuracy concerning different annual daylight metrics. This approach caters to specific cases and opens possibilities for application in other machine learning and deep learning-based methods.

Multiple unmanned aerial vehicle (multi-UAV) confrontation is becoming an increasingly important combat mode in intelligent air combat. The confrontation highly relies on the intelligent collaboration and real-time decision-making of the UAVs. Thus, a decomposed and prioritized experience replay (PER)-based multi-agent deep deterministic policy gradient (DP-MADDPG) algorithm has been proposed in this paper for the moving and attacking decisions of UAVs. Specifically, the confrontation is formulated as a partially observable Markov game. To solve the problem, the DP-MADDPG algorithm is proposed by integrating the decomposed and PER mechanisms into the traditional MADDPG. To overcome the technical challenges of the convergence to a local optimum and a single dominant policy, the decomposed mechanism is applied to modify the MADDPG framework with local and global dual critic networks. Furthermore, to improve the convergence rate of the MADDPG training process, the PER mechanism is utilized to optimize the sampling efficiency from the experience replay buffer. Simulations have been conducted based on the Multi-agent Combat Arena (MaCA) platform, wherein the traditional MADDPG and independent learning DDPG (ILDDPG) algorithms are benchmarks. Simulation results indicate that the proposed DP-MADDPG improves the convergence rate and the convergent reward value. During confrontations against the vanilla distance-prioritized rule-empowered and intelligent ILDDPG-empowered blue parties, the DP-MADDPG-empowered red party can improve the win rate to 96% and 80.5%, respectively.

Abstract Exploiting efficient urea oxidation reaction (UOR) and hydrogen evolution reaction (HER) catalysts are significant for energy‐saving H2 production through urea‐assisted water electrolysis, but it is still challenging. Herein, carbon‐encapsulated CoNi coupled with CoNiMoO (CoNi@CN‐CoNiMoO) is prepared by solvothermal method and calcination to enhance the activity/stability of urea‐assisted water electrolysis at large current density. It exhibits good activity for UOR (E10/1,000 = 1.29/1.40 V) and HER (E−10/−1000 = −45/−245 mV) in 1.0 M KOH + 0.5 M urea solution. For the UOR||HER system, CoNi@CN‐CoNiMoO only needs 1.58 V at 500 mA cm−2 and shows good stability. Density functional theory calculation suggests that the strong electronic interaction at the interface between NiCo alloy and N‐doping‐carbon layers can optimize the adsorption/desorption energy of UOR/HER intermediates and accelerate the water dissociation, which can expedite urea decomposition and Volmer step, thus increasing the UOR and HER activity, respectively. This work provides a new solution to design UOR/HER catalysts for H2 production through urea‐assisted water electrolysis.

Evidence synthesis serves an important role to promote informed decision-making in healthcare practice. A key issue of evidence synthesis is the approach to deal with rare adverse events and the methods to address bias of harm effects. Empirical data is essential to help methodologists and statisticians to solve the issues in evidence synthesis of adverse events. For this reason, we have established SMART Safety dataset, the largest empirical dataset of meta-analyses of adverse events. The dataset contains 151 systematic reviews with 629 meta-analyses on safety outcomes, which covers more than 2,300 randomized controlled trials and 362 harm outcomes, with 10,069 rows and 45 columns of trial level information. All information was double- or even quadra-checked and further verified by referring the original source (e.g., the full-text of the included randomized trials) to ensure high validity of the data.

Abstract Objectives In evidence synthesis practice, dealing with studies with no cases in both arms has been a tough problem, for which there is no consensus in the research community. In this study, we propose a method to measure the potential impact of studies with no cases for meta-analysis results which we define as harms index (Hi) and benefits index (Bi) as an alternative solution for deciding how to deal with such studies. Methods Hi and Bi are defined by the minimal number of cases added to the treatment arm (Hi) or control arm (Bi) of studies with no cases in a meta-analysis that lead to a change of the direction of the estimates or its statistical significance. Both exact and approximating methods are available to calculate Hi and Bi. We developed the “hibi” module in Stata so that researchers can easily implement the method. A real-world investigation of meta-analyses from Cochrane reviews was employed to evaluate the proposed method. Results Based on Hi and Bi, our results suggested that 21.53% (Hi) to 26.55% (Bi) of Cochrane meta-analyses may be potentially impacted by studies with no cases, for which studies with no cases could not be excluded from the synthesis. The approximating method shows excellent specificity (100%) for both Hi and Bi, moderate sensitivity (68.25%) for Bi, and high sensitivity (80.61%) for Hi compared to the exact method. Conclusions The proposed method is practical and useful for systematic reviewers to measure whether studies with no cases impact the results of meta-analyses and may act as an alternative solution for review authors to decide whether to include studies with no events for the synthesis or not.

Seed banks are crucial regenerative resources for aboveground vegetation. The pattern of their changes holds immense significance in understanding alterations in the belowground seed bank. This understanding is pivotal for uncovering both short-term and long-term shifts in plant communities. Additionally, it contributes to the restoration of grassland ecosystems. To better protect grassland biodiversity and provide a theoretical basis for the restoration of degraded grasslands, in this study, the germination characteristics of soil seed banks in free-grazed, enclosed and mown areas were compared, and the results were combined with those of previous studies for a comprehensive analysis. The density of soil seed bank and perennial forage soil seed bank were significantly affected by different grassland utilization and soil depths. Grazing and enclosure grassland utilization methods increased the content of the soil seed bank, and mowing reduced the content of the seed bank. The soil seed bank density of perennial grasses accounted for the highest proportion under grazing, followed by mowing, and its lowest proportion was observed in the enclosures. Grazing not only facilitated the germination of the perennial grass seed bank but also substantially augmented its content. Mowing inhibited the germination of the upper growth grasses seed bank, which was particularly significant in the 0-2 cm soil layer under grazing. The content of the upper growth grasses seed bank affected the total seed bank to a certain extent, mainly in the 5-10 cm layer. The general correlations among the perennial grasses, upper growth grasses and soil germination seed bank resulted in 84.58% information extraction, and this information has practical significance for grassland ecological restoration.

Video Super-Resolution (VSR) is the task of reconstructing high-resolution (HR) video sequences from low-resolution (LR) video sequences. Apart from spatial information of reference frames, temporal information of neighboring frames is also important for reconstruction. Current VSR methods usually take advantage of the temporal information through optical flow estimation and compensation. However, optical flow estimation is often inaccurate and difficult, which may result in artifacts or blurring in the reconstructed frames. In this paper, we propose a Novel Flow-guided Deformable Alignment Module (NFDAM) for frame alignment. In this module, a lightweight optical network FNet is designed to estimate optical flow as a coarse offset, which then guides the deformable convolution at the feature and image level. On this basis, we propose a Flow-guided Gated Bidirectional Recurrent Separated Network (FGBRSN) for VSR, in which a gated recurrent structure is designed to leverage long-term information and a multilevel residual fusion approach is used in upsampling module. Our experiments on public datasets have shown that the proposed method improves both quantitative evaluation and visual effects compared with the existing methods.

This paper develops an adaptive output feedback control for a class of functional constraint systems with unmeasurable states and unknown dead zone input. The constraint is a series of functions closely linked to state variables and time, which is not achieved in current research results and is more general in practical systems. Furthermore, a fuzzy approximator based adaptive backstepping algorithm is designed and an adaptive state observer with time-varying functional constraints (TFC) is constructed to estimate the unmeasurable states of the control system. Relying on the relevant knowledge of dead zone slopes, the issue of non-smooth dead-zone input is successfully solved. The time-varying integral barrier Lyapunov functions (iBLFs) are employed to guarantee that the states of the system remain within the constraint interval. By Lyapunov stability theory, the adopted control approach can ensure the stability of the system. Finally, the feasibility of the considered method is conformed via a simulation experiment.

ABSTRACT Long noncoding RNAs (lncRNAs) are a class of noncoding RNAs that are involved in multiple biological processes. Here, we report a mechanism through which the lnc-AROD–miR-324-5p–CUEDC2 axis regulates the host innate immune response, using influenza A virus (IAV) as a model. We identified that host lnc-AROD without protein-coding capability is composed of 975 nucleotides. Moreover, lnc-AROD inhibited interferon-β expression, as well as interferon-stimulated genes ISG15 and MxA. Furthermore, in vivo assays confirmed that lnc-AROD overexpression increased flu virus pathogenicity and mortality in mice. Mechanistically, lnc-AROD interacted with miR-324-5p, leading to decreased binding of miR-324-5p to CUEDC2. Collectively, our findings demonstrated that lnc-AROD is a critical regulator of the host antiviral response via the miR-324-5p–CUEDC2 axis, and lnc-AROD functions as competing endogenous RNA. Our results also provided evidence that lnc-AROD serves as an inhibitor of the antiviral immune response and may represent a potential drug target. IMPORTANCE lnc-AROD is a potential diagnostic and discriminative biomarker for different cancers. However, so far the mechanisms of lnc-AROD regulating virus replication are not well understood. In this study, we identified that lnc-AROD is downregulated during RNA virus infection. We demonstrated that lnc-AROD enhanced CUEDC2 expression, which in turn inhibited innate immunity and favored IAV replication. Our studies indicated that lnc-AROD functions as a competing endogenous RNA that binds miR-324-5p and reduces its inhibitory effect on CUEDC2. Taken together, our findings reveal that lnc-AROD plays an important role during the host antiviral immune response.

The degradation and desertification of grassland ecosystems have garnered significant attention both domestically and internationally. Grassland restoration techniques are widely considered a principal measure to promote the sustainable utilization of grasslands, with soil nutrient content being a core indicator for assessing the effectiveness of restoration in degraded grasslands. This study aims to explore the differential impacts of various grassland restoration methods on soil nutrient distribution in degraded Stipa grandis grasslands. Three major restoration methods, i.e., root cutting, enclosure, and fertilization, were applied in the study area. The soil nutrient content was measured and analyzed under the different restoration methods and at varying depths. The results revealed that under all three restoration methods and at different soil depths (0–10 cm, 10–20 cm, 20–30 cm), the organic matter, total nitrogen, total phosphorus, alkali-hydrolyzable nitrogen, alkali-hydrolyzable phosphorus, and available potassium contents were significantly higher than those in the control group (p < 0.05). Furthermore, as soil depth increased, the contents of organic matter and all nutrients gradually decreased. Specifically, regarding the contents of different nutrients, the order of organic matter, total nitrogen, total phosphorus, alkali-hydrolyzable nitrogen, and available phosphorus was as follows: fertilization > enclosure > root cutting > control, while the contents of total potassium and available potassium followed the sequence: fertilization > enclosure > control > root cutting. Additionally, based on the canonical correlation analysis (R2 = 0.88), the total phosphorus content in soil had the greatest impact on soil nutrients, while vegetation cover and plant height contributed the most to vegetation characteristics. In grassland restoration, the increase in soil total phosphorus led to higher vegetation cover and height, mildly influenced plant diversity and density, and simultaneously promoted biomass accumulation. These research findings provide a solid theoretical foundation for the application of grassland restoration techniques, contributing to the sustainable development of grassland ecosystems.

Abstract Constructing heterojunction is an effective strategy to develop high-performance non-precious-metal-based catalysts for electrochemical water splitting (WS). Herein, we design and prepare an N-doped-carbon-encapsulated Ni/MoO2 nano-needle with three-phase heterojunction (Ni/MoO2@CN) for accelerating the WS under industrial alkaline condition. Density functional theory calculations reveal that the electrons are redistributed at the three-phase heterojunction interface, which optimizes the adsorption energy of H- and O-containing intermediates to obtain the best ΔG H* for hydrogen evolution reaction (HER) and decrease the ΔG value of rate-determining step for oxygen evolution reaction (OER), thus enhancing the HER/OER catalytic activity. Electrochemical results confirm that Ni/MoO2@CN exhibits good activity for HER (ƞ -10 = 33 mV, ƞ -1000 = 267 mV) and OER (ƞ 10 = 250 mV, ƞ 1000 = 420 mV). It shows a low potential of 1.86 V at 1000 mA cm−2 for WS in 6.0 M KOH solution at 60 °C and can steadily operate for 330 h. This good HER/OER performance can be attributed to the three-phase heterojunction with high intrinsic activity and the self-supporting nano-needle with more active sites, faster mass diffusion, and bubbles release. This work provides a unique idea for designing high efficiency catalytic materials for WS.

Biohybrid robots, composed of cellular actuators and synthetic scaffolds, have garnered much attention in recent years owing to the advantages provided by their biological components. In recent years, various forms of biohybrid robots have been developed that are capable of life-like movements, such as walking, swimming, and gripping. Specifically, for walking or crawling biorobots, there is a need for complex functionality and versatile and robust fabrication processes. Here, we designed and fabricated multi-actuator biohybrid walkers with multi-directional walking capabilities in response to noninvasive optical stimulation through a scalable modular biofabrication process. Our new fabrication approach provides a constant mechanical strain throughout the cellular differentiation and maturation process. This maximizes the myotube formation and alignment, limits passive bending, and produces higher active forces. These demonstrations of the new fabrication process and bioactuator designs can pave the way for advanced multi-cellular biohybrid robots and enhance our understanding of the emergent behaviors of these multi-cellular engineered living systems.

The quality of residential buildings in old urban areas of Beijing is known to be inconsistent, prompting numerous urban renewal projects in the city. This research investigates how building space impacts energy usage and daylighting in courtyard areas of old urban regions in northern China. It also proposes a quick evaluation method for building performance in courtyard spaces, utilizing multi-objective optimization and machine learning classification prediction as a theoretical framework. A study was conducted to gather and organize building space parameters and their corresponding performances using a genetic algorithm. The dataset was then pre-processed and trained using the LightGBM algorithm. The model validation results revealed a recall of 0.9 and an F1-score of 0.8. These scores indicate that the design scheme’s performance level can be accurately identified in practical use. The goal of this study is to propose a set of rapid assessment methods for building performance levels in courtyard spaces. These methods can significantly improve the feedback efficiency between design decision and performance assessment, reduce the time wasted in building performance simulation during the architectural design process, and avoid unreasonable renovation and addition in urban renewal. Furthermore, the research method has universality and can be applied to courtyard-shaped buildings in other regions.

Long-term grazing leads to soil degradation in Inner Mongolia grassland. Based on the Hulunbeier meadow steppe, the variation characteristics of soil nitrogen content and storage in soil layers between 0–40 cm, under six different grazing intensities, and the response of vegetation and other physical and chemical properties of soil to grazing were studied. The main results were as follows: (1) Moderate grazing increased soil total nitrogen (TN), soluble total nitrogen (STN) and microbial biomass nitrogen (MBN) contents, while heavy grazing decreased MBN content. In the year with more rain, heavy grazing increased nitrate nitrogen (NO3−-N) content and storage, while less rain increased ammonium nitrogen (NH4+-N) content. (2) The proportion of 0–40 cm nitrogen components showed an upward trend in the year with more rain, and the opposite in the years with less rainfall with the increase of grazing intensity. Soil soluble organic nitrogen (SON) and NO3−-N storages decreased and MBN storage increased in rainy years. (3) Soil nitrogen component contents and storages were correlated with plant growth status, soil moisture (SM) and soil bulk density (SBD), and were significantly negatively correlated with soil temperature (ST) and pH (p < 0.05). The content and storage of soil nitrogen were affected by grazing, soil, vegetation, meteorological and other environmental factors. Moderate grazing was more conducive to the improvement of soil nitrogen storage capacity and the healthy development of grassland.

Abstract Developing highly effective and stable non-noble metal-based bifunctional catalyst working at high current density is an urgent issue for water electrolysis (WE). Herein, we prepare the N-doped graphene-decorated NiCo alloy coupled with mesoporous NiCoMoO nano-sheet grown on 3D nickel foam (NiCo@C-NiCoMoO/NF) for water splitting. NiCo@C-NiCoMoO/NF exhibits outstanding activity with low overpotentials for hydrogen and oxygen evolution reaction (HER: 39/266 mV; OER: 260/390 mV) at ± 10 and ± 1000 mA cm−2. More importantly, in 6.0 M KOH solution at 60 °C for WE, it only requires 1.90 V to reach 1000 mA cm−2 and shows excellent stability for 43 h, exhibiting the potential for actual application. The good performance can be assigned to N-doped graphene-decorated NiCo alloy and mesoporous NiCoMoO nano-sheet, which not only increase the intrinsic activity and expose abundant catalytic activity sites, but also enhance its chemical and mechanical stability. This work thus could provide a promising material for industrial hydrogen production.

Abstract Background Many treatments are currently available for amblyopic patients; although, the comparative efficacy of these therapies is unclear. We conducted a systematic review and network meta-analysis (NMA) to establish the relative efficacy of these treatments for amblyopia. Methods Electronic databases (MEDLINE, EMBASE, Cochrane Library) were systematically searched from inception to Sep. 2019. Only Randomized clinical trials comparing any two or three of the following treatments were included: refractive correction (spectacles alone), patching of 2 h per day (patch 2H), patch 6H, patch 12H, patch 2H + near activities (N), patch 2H + distant activities (D), atropine (Atr) daily, Atr weekly, Atr weekly + plano lens over the sound eye (Plano), optical penalization and binocular therapy. The reviewers independently extracted the data according to the PRISMA guidelines; assessed study quality by Cochrane risk-of-bias tool for randomized trials. The primary outcome measure was the change in best-corrected visual acuity (BCVA) expressed as log MAR lines. Direct comparisons and a Bayesian meta-analysis were performed to synthesize data. Results Twenty-three studies with 3279 patients were included. In the network meta-analysis, optical penalization was the least effective of all the treatments for the change of visual acuity, spectacles (mean difference [MD], 2.9 Log MAR lines; 95% credibility interval [CrI], 1.8–4.0), patch 2H (MD, 3.3; 95% CrI, 2.3–4.3), patch 6H (MD, 3.6; 95% CrI, 2.6–4.6), patch 12H (MD, 3.4; 95% CrI, 2.3–4.5), patch 2H + N (MD, 3.7; 95% CrI, 2.5–5.0), patch 2H + D (MD, 3.5; 95% CrI, 2.1–5.0), Atr daily (MD, 3.2; 95% CrI, 2.2–4.3), Atr weekly (MD, 3.2; 95% CrI, 2.2–4.3), Atr weekly + Plano (MD, 3.7; 95% CrI, 2.7–4.7), binocular therapy (MD, 3.1; 95% CrI, 2.0–4.2). The patch 6H and patch 2H + N were better than spectacles ([MD, 0.73; 95% Crl, 0.10–1.40]; [MD, 0.84; 95% CrI, 0.19–1.50]). Conclusions The NMA indicated that the efficacy of the most of the examined treatment modalities for amblyopia were comparable, with no significant difference. Further high quality randomized controlled trials are required to determine their efficacy and acceptability. Systematic review registration CRD42019119843.

Abstract Very few materials show large magnetoresistance (MR) under a low magnetic field at room temperature, which causes the barrier to the development of magnetic field sensors for detecting low-level electromagnetic radiation in real- time. Here, a hybrid reduced graphene oxide (rGO)-based magnetic field sensor is produced by in situ deposition of FeCo nanoparticles (NPs) on reduced graphene oxide (rGO). Special quantum magnetoresistance (MR) of the hybrid rGO is observed, which unveils that Abrikosov’s quantum model for layered materials can occur in hybrid rGO; meanwhile, the MR value can be tunable by adjusting the particle density of FeCo NPs on rGO nanosheets. Very high MR value up to 21.02 ± 5.74% at 10 kOe at room temperature is achieved, and the average increasing rate of resistance per kOe is up to 0.9282 Ω kOe−1. In this paper, we demonstrate that the hybrid rGO-based magnetic field sensor can be embedded in a wireless system for real-time detection of low-level electromagnetic radiation caused by a working mobile phone. We believe that the two-dimensional nanomaterials with controllable MR can be integrated with a wireless system for the future connected society.

Studies on the impacts of fertilization on plant production and species diversity are crucial for better maintaining the stability of grassland ecosystems and restoring degraded grasslands. Using a controlled fertilization experimental platform in a temperate Leymus chinensis meadow steppe ecosystem, the effects of different levels of nitrogen (N) and phosphorus (P) addition on plant community structure, biomass allocation, diversity, and the correlation relationship were explored. The major results were as follows: (1) The structural composition of the plant community changed after different levels of N and P addition; the dominance ratio and biomass of Poaceae plants increased gradually with increasing N and P addition levels. (2) The addition of N and P increased the height, density and coverage of the plant community, the biomass of the dominant L. chinensis and plant community and the total productivity of grassland, and reduced the root–shoot ratio of grassland biomass. For example, plant community biomass, gramineous plant biomass and grassland total productivity increased by 84.46–204.08%, 162.64–424.20%, and 38.12–46.44%, respectively, after N and P addition. (3) The community richness, diversity, and evenness indices decreased overall and showed binomial regression after N and P addition; the functional group of Poaceae plants was highly significantly negatively correlated with species diversity indices and was highly significantly positively correlated with the aboveground biomass of L. chinensis and community; Leguminosae plants and Ranunculaceae plants were highly significantly positively correlated with Margalef and Patrick richness indices; Ranunculaceae plants were highly significantly and negatively correlated with L. chinensis biomass, community biomass, and Poaceae plants. Moderate fertilization not only improved the plant community structure and productivity but was also beneficial for maintaining the grassland species diversity and stability.

ABSTRACTThe ANP32A is responsible for mammalian-restricted influenza virus polymerase activity. However, the mechanism of ANP32A modulation of polymerase activity remains poorly understood. Here, we report that chicken ANP32A (chANP32A) -X1 and -X2 stimulated mammalian-restricted PB2 627E polymerase activity in a dose-dependent manner. Distinct effects of ANP32A constructs suggested that the 180VK181 residues within chANP32A-X1 are necessary but not sufficient to stimulate PB2 627E polymerase activity. The PB2 N567D, T598V, A613V or F636L mutations promoted PB2 627E polymerase activity and chANP32A-X1 showed additive effects, providing further support that species-specific regulation of ANP32A might be only relevant with the PB2 E627K mutation. Rescue of cycloheximide-mediated inhibition showed that ANP32A is species-specific for modulation of vRNA but not mRNA and cRNA, demonstrating chANP32A-X1 compensated for defective cRNPs produced by PB2 627E virus in mammalian cells. The promoter mutations of cRNA enhanced the restriction of PB2 627E polymerase in mammalian cells, which could be restored by chANP32A-X1, indicating that ANP32A is likely to regulate the interaction of viral polymerase with RNA promoter. Coimmunoprecipitation showed that ANP32A did not affect the primary cRNPs assembly. We propose a model that chANP32A-X1 regulates PB2 627E polymerase for suitable interaction with cRNA promoter for vRNA replication.

Given the advantages of low cost and easy deployment,large-scale Internet of things (IoT) has been deployed for environment monitoring pervasively.Within such systems,cloud platform is typically utilized as a remote data and control center.However,tremendous amount of data uploading and processing induce huge challenges on bandwidth load and real-time data gathering.In order to overcome these challenges,edge computing enabled IoT system architecture was proposed for environmental monitoring.As the intermediate layer,local processing could be supported for end devices with low latency and assist with preliminary analysis to offload computational tasks from cloud and the amount of data uploading could be reduced.Based on this system architecture,an autoencoder neural network-based abnormal data detection scheme was developed newly.Performance evaluation has been conducted based on the practical oceanic atmospheric data.Simulation results indicate that the proposed scheme can accurately detect the abnormal data by fully exploiting the spatial data correlation.

Summary: Heterogeneous nuclear ribonucleoproteins (hnRNPs) play critical roles in the nuclear export, splicing, and sensing of RNA. However, the role of heterogeneous nuclear ribonucleoprotein A/B (hnRNPAB) is poorly understood. In this study, we report that hnRNPAB cooperates with nucleoprotein (NP) to restrict viral mRNA nuclear export via inhibiting viral mRNA binding to ALY and NXF1. HnRNPAB restricts mRNA transfer from ALY to NXF1, inhibiting the mRNA nuclear export. Moreover, when cells are invaded by influenza A virus, NP interacts with hnRNPAB and interrupts the ALY-UAP56 interaction, leading to repression of ALY-viral mRNA binding, and then inhibits the viral mRNA binding to NXF1, leading to nuclear stimulation of viral mRNA. Collectively, these observations provide a new role of hnRNPAB to act as an mRNA nuclear retention factor, which is also effective for viral mRNA of influenza A virus, and NP cooperates with hnRNPAB to further restrict the viral mRNA nuclear export.

Flying ad hoc networks (FANETs) have been gradually deployed in diverse application scenarios, ranging from civilian to military. However, the high-speed mobility of unmanned aerial vehicles (UAVs) and dynamically changing topology has led to critical challenges for the stability of communications in FANETs. To overcome the technical challenges, an Improved Weighted and Location-based Clustering (IWLC) scheme is proposed for FANET performance enhancement, under the constraints of network resources. Specifically, a location-based K-means++ clustering algorithm is first developed to set up the initial UAV clusters. Subsequently, a weighted summation-based cluster head selection algorithm is proposed. In the algorithm, the remaining energy ratio, adaptive node degree, relative mobility, and average distance are adopted as the selection criteria, considering the influence of different physical factors. Moreover, an efficient cluster maintenance algorithm is proposed to keep updating the UAV clusters. The simulation results indicate that the proposed IWLC scheme significantly enhances the performance of the packet delivery ratio, network lifetime, cluster head changing ratio, and energy consumption, compared to the benchmark clustering methods in the literature.

Virus-host interaction is a tug of war between pathogenesis and immunity, followed by either activating the host immune defense system to eliminate virus or manipulating host immune control mechanisms to survive and facilitate virus propagation. Comprehensive knowledge of interactions between host and viral proteins might provide hints for developing novel antiviral strategies. To gain a more detailed knowledge of the interactions with porcine circovirus type 2 capsid protein, we employed a coimmunoprecipitation combined with liquid chromatography mass spectrometry (LC-MS) approach and 222 putative PCV2 Cap-interacting host proteins were identified in the infected porcine kidney (PK-15) cells. Further, a protein-protein interactions (PPIs) network was plotted, and the PCV2 Cap-interacting host proteins were potentially involved in protein binding, DNA transcription, metabolism and innate immune response based on the gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes database enrichment. Verification in vitro assay demonstrated that eight cellular proteins, namely heterogeneous nuclear ribonucleoprotein C, nucleophosmin-1, DEAD-box RNA helicase 21, importin β3, eukaryotic translation initiation factor 4A2, snail family transcriptional repressor 2, MX dynamin like GTPase 2, and intermediate chain 1 interacted with PCV2 Cap. Thus, this work effectively provides useful protein-related information to facilitate further investigation of the underlying mechanism of PCV2 infection and pathogenesis.

Porcine delta coronavirus (PDCoV) is a novel emerging enterocytetropic virus causing diarrhea, vomiting, dehydration, and mortality in suckling piglets. Long non-coding RNAs (lncRNAs) are known to be important regulators during virus infection. Here, we describe a comprehensive transcriptome profile of lncRNA in PDCoV-infected swine testicular (ST) cells. In total, 1,308 annotated and 1,190 novel lncRNA candidate sequences were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these lncRNAs might be involved in numerous biological processes. Clustering analysis of differentially expressed lncRNAs showed that 454 annotated and 376 novel lncRNAs were regulated after PDCoV infection. Furthermore, we constructed a lncRNA-protein-coding gene co-expression interaction network. The KEGG analysis of the co-expressed genes showed that these differentially expressed lncRNAs were enriched in pathways related to metabolism and TNF signaling. Our study provided comprehensive information about lncRNAs that would be a useful resource for studying the pathogenesis of and designing antiviral therapy for PDCoV infection.