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Composite rocks comprise the rock structures that are commonly used in geotechnical engineering. The fracture configuration has a substantial influence on the mechanical behavior, failure mode, and crack propagation of composite rocks. In this study, we considered a composite rock with two prefabricated coplanar fractures. Through laboratory uniaxial compression tests and using a digital image acquisition system, we systematically studied the effects of different fracture lengths and inclination angles on the mechanical properties and failure characteristics of the rocks. We obtained the following results: 1) during the loading deformation of the rock sample, the peak stress and elastic modulus increased with an increase in the fracture inclination angle and decreased with an increase in the fracture length. The deterioration coefficient k (the ratio of the difference between the peak strength of intact and fractured rock sample to that of intact rock sample) decreased with an increase in the fracture inclination angle and increased with an increase in the fracture length. 2) The failure type of the rock samples was primarily controlled by the fracture inclination angle and material of the two rock types, and the fragmentation degree was primarily controlled by the fracture length. With an increase in the fracture inclination angle, the failure mode of rock sample exhibited the following order of changes leading to failure: a double-Y type (trwo wing and one antiwing cracks appeared on each prefabricated fracture) → double-Z type (two wing cracks appeared on each prefabricated fracture) → Z type (one wing crack appeared on each prefabricated fracture). 3) The type of coalescence of the rock bridge was controlled by the fracture inclination angle and structural plane. The crack positions were primarily affected by the fracture length. 4) At a low fracture inclination angle (α ≤ 30°), the propagation of the microcracks showed aggregated band formation. Above moderate fracture inclination angles (α > 30°), the microcrack aggregation band gradually weakened and expanded in the direction of dispersion.

Abstract Spinal cord injury (SCI) is a central nervous system disorder that can lead to sensory and motor dysfunction, which can seriously increase pressure and economic burden on families and societies. The current SCI treatment is mainly to stabilize the spine, prevent secondary damage, and control inflammation. Drug treatment is limited to early, large‐scale use of steroids to reduce the effects of edema after SCI. In short, there is no direct treatment for SCI. Recent 3D bioprinting development provides a new solution for SCI treatment: a series of spinal cord bionic scaffolds are being developed to improve spinal cord function after injury. This paper reviews the pathophysiological characteristics of SCI, current treatment methods, and the progress of 3D bioprinting in SCI. Finally, its challenges and prospects in SCI treatment are summarized.

Summary: Our understanding of broad-scale biodiversity and functional trait patterns is largely based on plants, and relatively little information is available on soil arthropods. Here, we investigated the distribution of termite diversity globally and morphological traits and diversity across China. Our analyses showed increasing termite species richness with decreasing latitude at both the globally, and within-China. In addition, we detected obvious latitudinal trends in the mean community value of termite morphological traits on average, with body size and leg length decreasing with increasing latitude. Furthermore, temperature, NDVI and water variables were the most important drivers controlling the variation in termite richness, and temperature and soil properties were key drivers of the geographic distribution of termite morphological traits. Our global termite richness map is one of the first high resolution maps for any arthropod group and especially given the functional importance of termites, our work provides a useful baseline for further ecological analysis.

Bioactive organic compounds (BOCs) contained in bio-stabilized products of waste activated sludge (WAS) have attracted considerable attention, as they can enhance the fertilizing effect of WAS in land applications. This study investigated the molecular composition and plant-growth-promoting mechanisms of various BOCs in the bio-stabilized products of WAS. After stepwise fractionation, aerobic composting sludge (ACS) and anaerobic digestion sludge (ADS) were chemically fractioned into five subcomponents, namely dissolved organic matter (DOM) (C1), weakly interacted organic matter (OM) (C2), metal-bonded OM (C3), NaOH-extracted OM (C4), and strongly interacted OM (C5), in sequence. The results showed that fatty acids and carboxylic acid (CAs) present in ACS C2 promoted plant growth and enhanced the ability of plants against stresses by upregulating pathways related to “carbohydrate metabolism,” “lipid metabolism,” “amino acid metabolism,” and “phenylpropanoid biosynthesis.” However, in ACS C4, plenty of amino acids could promote plant growth via upregulating “carbohydrate metabolism” and “amino acid metabolism” pathways. As an important precursor, aromatic amino acids inside ACS C4 also stimulated the production of indoleacetic acids. In ADS C1, amino sugar and phytohormone were the major BOCs causing the up-regulation of “carbohydrate metabolism” and AAA catabolism in “amino acid metabolism” pathways. CAs enriched in ADS C2 stimulated plant growth through “amino acid metabolism” pathway. In summary, alkali extraction can recycle a large proportion of BOCs with low environmental risk from the bio-stabilization products of WAS. The results from this study provide scientific guidance for safe and value-added resource utilization of bio-stabilization products of WAS in land applications.

Relativistic quantum mechanics is typically used to describe phenomena of high-energy physics but can also be applied to describe some features of quantum materials. Here, the authors use electrical circuits to simulate Dirac-like phenomena and measure Zitterbewegung and Klein tunneling for a one dimensional Bose-Hubbard model.

The mitochondrial genome (mitogenome) of Gallinago gallinago gallinago Linnaeus, 1758 was determined by the high-throughput data. The assembled mitogenome was 16,919 bp in length, with a 58.7% A + T content and GC skew of −0.3850. Among 13 PCGs, an unusual start codon (GTG) was identified for the COX1 gene, and incomplete stop codons (T-) were found in the COX3, ND2 and ND4 genes. The function of a cytosine insertion at site 174 in the ND3 gene and its phylogenetic significance are worthy of further scrutiny. In the control region (CR), thirteen 15-bp simple sequence repeats were found in G. g. gallinago. Phylogenetic analysis indicated that Gallinago was clustered at the basal position of the Scolopax clade and that the monophyly of Gallinago was also recovered. The mitogenome data of G. g. gallinago provides useful resources for further studying the evolution of Scolopacidae.

Abstract Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) are the two main causes of heart failure (HF). Despite similar clinical characteristics and common “HF pathways”, ICM and DCM are expected to have different personalized treatment strategies. The underlying mechanisms of ICM and DCM have yet to be fully elucidated. The present study developed a novel computational method for identifying dysregulated long noncoding RNA (lncRNA)–microRNA (miRNA)–mRNA competing endogenous RNA (ceRNA) triplets. Time-ordered dysregulated ceRNA networks were subsequently constructed to reveal the possible disease progression of ICM and DCM based on the method. Biological functional analysis indicated that ICM and DCM had similar features during myocardial remodeling, whereas their characteristics differed during progression. Specifically, disturbance of myocardial energy metabolism may be the main characteristic during DCM progression, whereas early inflammation and response to oxygen are the characteristics that may be specific to ICM. In addition, several panels of diagnostic biomarkers for differentiating non-heart failure (NF) and ICM (NF-ICM), NF-DCM, and ICM-DCM were identified. Our study reveals biological differences during ICM and DCM progression and provides potential diagnostic biomarkers for ICM and DCM.

Abstract The amino acid response (AAR) and unfolded protein response (UPR) pathways converge on eIF2α phosphorylation, which is catalyzed by Gcn2 and Perk, respectively, under different stresses. This close interconnection makes it difficult to specify different functions of AAR and UPR. Here, we generated a zebrafish model in which loss of threonyl-tRNA synthetase (Tars) induces angiogenesis dependent on Tars aminoacylation activity. Comparative transcriptome analysis of the tars-mutant and wild-type embryos with/without Gcn2- or Perk-inhibition reveals that only Gcn2-mediated AAR is activated in the tars-mutants, whereas Perk functions predominantly in normal development. Mechanistic analysis shows that, while a considerable amount of eIF2α is normally phosphorylated by Perk, the loss of Tars causes an accumulation of uncharged tRNAThr, which in turn activates Gcn2, leading to phosphorylation of an extra amount of eIF2α. The partial switchover of kinases for eIF2α largely overwhelms the functions of Perk in normal development. Interestingly, although inhibition of Gcn2 and Perk in this stress condition both can reduce the eIF2α phosphorylation levels, their functional consequences in the regulation of target genes and in the rescue of the angiogenic phenotypes are dramatically different. Indeed, genetic and pharmacological manipulations of these pathways validate that the Gcn2-mediated AAR, but not the Perk-mediated UPR, is required for tars-deficiency induced angiogenesis. Thus, the interconnected AAR and UPR pathways differentially regulate angiogenesis through selective functions and mutual competitions, reflecting the specificity and efficiency of multiple stress response pathways that evolve integrally to enable an organism to sense/respond precisely to various types of stresses.

N6-methyladenosine (m6A), the most prevalent form of internal mRNA modification, is extensively involved in Treg cells differentiation and function. However, the involvement of m6A in functional Treg cells for transplantation tolerance remains to be elucidated. By using an experimental transplantation mouse model, we found that m6A levels in Treg cells were altered during the induction of transplant tolerance by performing a dot blotting assay. Subsequently, we used the heterogenic Treg-specific Mettl14 knockout mice (Foxp3-Mettl14f/+ cKO) to reduce METTL14 expression and performed islets allograft transplantation. Our result revealed that reduced expression of METTL14 prevented Treg cells expansion and promoted the infiltration of CD4+ and CD8+ T cells around the allograft, which led to rapid allograft rejection in Foxp3-Mettl14f/+ cKO mice. The expression of regulatory cytokines including IL-10 and TGF-β was significantly decreased in Foxp3-Mettl14f/+ cKO mice, and the suppressive function of Treg cells was also abrogated. In addition, an analysis of RNA-seq data revealed that the SOCS family (SOCS1, SOCS2 and SOCS3) is the subsequent signaling pathway affected by the METTL14 mediated m6A modification in Treg cells to modulate the suppressive function after transplantation. Taken together, our study showed for the first time that the METTL14-mediated m6A modification is essential for the suppressive function of Treg cells in transplantation and may serve as a regulatory element of Treg cell-based therapy in transplant medicine.

Macrophages and their precursor cells, monocytes, are the first line of defense of the body against foreign pathogens and tissue damage. Although the origins of macrophages are diverse, some common transcription factors (such as PU.1) are required to ensure proper development of monocytes/macrophages. Here, we report that the deficiency of zbtb14, a transcription repressor gene belonging to ZBTB family, leads to an aberrant expansion of monocyte/macrophage population in zebrafish. Mechanistically, Zbtb14 functions as a negative regulator of pu.1, and SUMOylation on a conserved lysine is essential for the repression activity of Zbtb14. Moreover, a serine to phenylalanine mutation found in an acute myeloid leukemia (AML) patient could target ZBTB14 protein to autophagic degradation. Hence, ZBTB14 is a newly identified gene implicated in both normal and malignant myelopoiesis.

Idiopathic sudden sensorineural hearing loss (ISSNHL) is an emergency ear disease that is referred to as a sensorineural hearing loss of at least 30 dB in three sequential frequencies and occurs over a period of < 72 h. Because of its etiology, pathogenesis, and prognostic factors, the current treatment methods are not ideal. Previous studies have developed prognostic models to predict hearing recovery from ISSNHL, but few studies have incorporated serum biochemical indicators into previous models. The aim of this study was to explore the factors influencing the ISSNHL prognosis of combination therapy (combined intratympanic and systemic use of steroids, CT), among the patient population data, the serum biochemical indicators before the treatment, and the clinical features of ISSNHL. The new prediction model was developed through these factors. From November 2015 to April 2022, 430 patients who underwent CT at the Department of Otorhinolaryngology Head and Neck Surgery, Tangdu Hospital, Air Force Medical University for ISSNHL, were reviewed retrospectively. We found significant differences in age (P = 0.018), glucose (P = 0.035), white blood cell (WBC) (P = 0.021), vertigo (P = 0.000) and type (P = 0.000) with different therapeutic efficacies. Multivariate logistic regression analysis showed that age (OR = 0.715, P = 0.023), WBC (OR = 0.527, P = 0.01), platelet to lymphocyte ratio (PLR) (OR = 0.995, P = 0.038), vertigo (OR = 0.48, P = 0.004), course (time from onset to treatment) (OR = 0.681, P = 0.016) and type (OR = 0.409, P = 0.000) were independent risk factors for ISSNHL prognosis. Based on independent risk factors, a predictive model and nomogram were developed to predict hearing outcomes in ISSNHL patients. The area under the curve (AUC) value of the model developed in this study was 0.773 (95% CI = 0.730–0.812), which has a certain predictive ability. The calibration curve indicated good consistency between the actual diagnosed therapeutic effectiveness and the predicted probability. The model and nomogram can predict the hearing prognosis of ISSNHL patients treated with CT and can provide help for medical staff to make the best clinical decision. This study has been registered with the registration number ChiCTR2200061379.

With limited medical resources, it is of great significance for countries all over the world to explore architectural design methods to enhance the value of medical facilities. Therefore, it is very necessary to carry out an extensive international comparison. In order to grasp the research trend of healthcare facilities in the world, this paper conducts co-occurrence analysis, cluster analysis, and trend analysis of the keywords of 334 English articles and 153 Japanese articles related to healthcare facilities published in important academic journals in the USA and Japan in the past 15 years. We not only compare the similarities and differences in healthcare facility research between the USA and Japan, but also explore the reasons for these differences. It is found that by introducing three kinds of value variables, such as time, space, and behavior, we can not only well explain the difference in the solution of healthcare facilities in the USA and Japan to reduce medical costs but also provide new ideas for architectural design to enhance the value of hospitals. Based on the above analysis, a conceptual framework of value-based design of healthcare facilities that combines the advantages of the USA and Japan is proposed in this paper.

Considering the nonlinear, time-varying, and multivariate coupling nature of the welding process, achieving excellent control of the welding process can be challenging. In addition, welding experience varies from person to person, making it difficult to establish a uniform standard. In this work, rough set theory is introduced and applied to arc welding process modeling and quality control to achieve effective online control of weld penetration during welding. A variable precision neighborhood rough-fuzzy method is proposed to enhance the efficiency and adaptability of rough set theory for information processing in the welding process. By designing welding experiments with different gaps and currents, descriptors such as the tail area coefficient and the length-width ratio of the melt pool have been proposed to characterize the melt pool. Rough set theory has been used to extract decision classification rules for welding percolation state information, and clustering analysis, fuzzy logic, and min-max fuzzy methods have been introduced for knowledge modeling. The proposed variable precision neighborhood rough-fuzzy control model is verified via three sets of experiments, and the results show that the model has excellent stability and effectiveness.

Vertically discharged multiple jets in crossflow is a common form of wastewater discharge. The presence of vegetation in the flow channel complicates the hydraulic characteristics of jets. The realizable k-ε turbulent model is used to simulate the flow, turbulence, and vortex characteristics of multiple jets with different spacing and jet-to-crossflow velocity ratios, to study the flow characteristics and vortex structure of multiple jets in a vegetated channel. The results reveal that vegetation inhibits the development of a counterrotating vortex pair. The jets with a low jet-to-crossflow velocity ratio are concentrated near the flow symmetry profile by the dual constraints of ambient flow and vegetation. The jets gradually spread outward and the counterrotating vortex pair become more obvious when the jet-to-crossflow velocity ratio increases. Vegetation reduces the shading effect of the front jet on the rear jet by accelerating the dissipation of shear layer vortices. The influence of the front jet on the rear jet decreases as the spacing increases.

Electrochemical impedance is a powerful technique for elucidating the multi-scale polarization process of the proton exchange membrane (PEM) fuel cell from a frequency domain perspective. It is advantageous to acquire frequency impedance depicting dynamic losses from signals measured by the vehicular sensor without resorting to costly impedance measurement devices. Based on this, the impedance data can be leveraged to assess the fuel cell’s internal state and optimize system control. In this paper, a residual network (ResNet) with strong feature extraction capabilities is applied, for the first time, to estimate characteristic frequency impedance based on eight measurable signals of the vehicle fuel cell system. Specifically, the 2500 Hz high-frequency impedance (HFR) representing proton transfer loss and 10 Hz low-frequency impedance (LFR) representing charge transfer loss are selected. Based on the established dataset, the mean absolute percentage errors (MAPEs) of HFR and LFR of ResNet are 0.802% and 1.386%, respectively, representing a superior performance to other commonly used regression and deep learning models. Furthermore, the proposed framework is validated under different noise levels, and the findings demonstrate that ResNet can attain HFR and LFR estimation with MAPEs of 0.911% and 1.610%, respectively, even in 40 dB of noise interference. Finally, the impact of varying operating conditions on impedance estimation is examined.

In the scenario of device-free localization under multiple effects, the accuracy of localization based on compressed sensing theory is severely affected. Most existing localization techniques directly ignore multiple path effects. However, it is not practical to ignore the multiple path effect due to its high signal strength, which can provide localization information. In this paper, we formulate the sensing matrix optimization problem in compressed sensing for device-free localization scenarios based on multiple reflections. To solve this problem, we model it as a constrained combinatorial optimization problem and propose a hybrid meta-heuristic algorithm. First, smart reflection surfaces and virtual node models are used to construct the desired communication links. Second, we iteratively improve the properties of the measurement matrix by using K-means clustering to obtain reasonable thresholds, and use a meta-heuristic algorithm to optimize the sensing matrix. Finally, the simulation results show that the proposed method efficiently optimizes the sensing matrix and achieves fast and high-precision localization while conserving communication resources.

Welding is an important production and processing method in industrial production. Due to the uncertainty of its process and the complexity of its mechanism, it is challenging to construct an accurate welding process parameter model to describe it. Fuzzy interpolation reasoning is a valuable tool in the realm of intelligent systems. It helps to reduce the complexity of fuzzy models and can be used for reasoning in fuzzy systems with sparse rule bases. This paper provides an interpolation reasoning method that combines fuzzy set distance and similarity. The proposed method is applied to welding forming predictions, and welding penetration is predicted by the given welding current and speed. The results show that the algorithm has high calculation accuracy.

In this paper, we investigate the deep learning applications of radio automatic modulation recognition (AMR) applications in unmanned aerial vehicle (UAV)-to-ground AMR systems. The integration of deep learning in a UAV-aided signal processing terminal can recognize the modulation mode without the provision of parameters. However, the layers used in current models have a small data processing range, and their low noise resistance is another disadvantage. Most importantly, large numbers of parameters and high amounts of computation will burden terminals in the system. We propose a multi-subsampling self-attention (MSSA) network for UAV-to-ground AMR systems, for which we devise a residual dilated module containing ordinary and dilated convolution to expand the data processing range, followed by a self-attention module to improve the classification, even in the presence of noise interference. We subsample the signals to reduce the number of parameters and amount of calculation. We also propose three model sizes, namely large, medium, and small, and the smaller the model, the more suitable it will be for UAV-to-ground AMR systems. We conduct ablation experiments with state-of-the-art and baseline models on the common AMR and radio machine learning (RML) 2018.01a datasets. The proposed method achieves the highest accuracy of 97.00% at a 30 dB signal-to-noise ratio (SNR). The weight file of the small MSSA is only 642 KB.

Polypropylene (PP) exhibits excellent insulation properties, high thermo-stability, and recyclable nature, thus expected to be the next-generation insulation material for HV cable application. Chemical grafting modification is an effective technology to improve the electrical properties of polypropylene. In this paper, we develop and report a new-type grafted PP insulation material by water-phase grafting technology. The comprehensive properties including electrical, thermal, and mechanical of it are tested and compared with traditional cable insulation material—crosslinked polyethylene (XLPE). The results show that the grafted PP holds superior thermal properties and enough mechanical flexibility. The electrical properties are of significant advantages, including resistivity enhanced by nearly two degrees of magnitudes, AC/DC breakdown strength raised by over 20%, and obviously suppressed space charge accumulation. These results indicate that grafted PP is very suitable for application in HV cable systems, either AC or DC. This research lays a foundation for the research and development of the next-generation recyclable polypropylene cables at higher voltage levels.

Abstract Background Circular RNAs (circRNAs) are becoming a unique member of non-coding RNAs (ncRNAs) with emerging evidence of their regulatory roles in various cancers. However, with regards to pancreatic ductal adenocarcinoma (PDAC), circRNAs biological functions remain largely unknown and worth investigation for potential therapeutic innovation. Methods In our previous study, next-generation sequencing was used to identify differentially expressed circRNAs in 3 pairs of PDAC and adjacent normal tissues. Further validation of circRHOBTB3 expression in PDAC tissues and cell lines and gain-and-loss function experiments verified the oncogenic role of circRHOBTB3. The mechanism of circRHOBTB3 regulatory role was validated by pull-down assays, RIP, luciferase reporter assays. The autophagy response of PANC-1 and MiaPaca-2 cells were detected by mCherry-GFP-LC3B labeling and confocal microscopy, transmission electron microscopy and protein levels of LC3B or p62 via Western blot. Results circRHOBTB3 is highly expressed in PDAC cell lines and tissues, which also promotes PDAC autophagy and then progression in vitro and in vivo. Mechanistically, circRHOBTB3 directly binds to miR-600 and subsequently acts as a miRNA-sponge to maintain the expression level of miR-600-targeted gene NACC1, which facilitates the autophagy response of PDAC cells for adaptation of proliferation via Akt/mTOR pathway. Moreover, the RNA-binding protein FUS (FUS) directly binds to pre-RHOBTB3 mRNA to mediate the biogenesis of circRHOBTB3. Clinically, circRHOBTB3, miR-600 and NACC1 expression levels are correlated with the prognosis of PDAC patients and serve as independent risk factors for PDAC patients. Conclusions FUS-mediated circRHOBTB3 functions as a tumor activator to promote PDAC cell proliferation by modulating miR-600/NACC1/Akt/mTOR axis regulated autophagy.

Abstract Background Aedes albopictus is the primary vector of dengue fever in China. This mosquito species has a wide distribution range in China and can be found in the tropical climate zones of southern provinces through to temperate climate zones of northern provinces. Insecticides are an important control method, especially during outbreaks of dengue fever, but increasing insecticide resistance raises the risk of failure to control vector-borne diseases. Knockdown resistance (kdr) caused by point mutations in the voltage-gated sodium channel (VGSC) gene is a key mechanism that confers resistance to pyrethroids. In this study we explored the characteristics and possible evolutionary trend of kdr mutation in Ae. albopictus based on analysis of the kdr mutations in field populations of mosquitoes in China. Methods A total of 1549 adult Ae. albopictus were collected from 18 sites in China from 2017 to 2019 and 50 individuals from three sites in the 1990s. A fragment of approximately 350 bp from part of the S6 segment in the VGSC gene domain III was amplified and sequenced. Using TCS software version 1.21A, we constructed haplotypes of the VGSC gene network and calculated outgroup probability of the haplotypes. Data of annual average temperatures (AAT) of the collection sites were acquired from the national database. The correlation between AAT of the collection site and the kdr mutation rate was analyzed by Pearson correlation using SPSS software version 21.0. Results The overall frequency of mutant allele F1534 was 45.6%. Nine mutant alleles were detected at codon 1534 in 15 field populations, namely TCC/TCG (S) (38.9%), TTG/CTG/CTC/TTA (L) (3.7%), TGC (C) (2.9%), CGC (R) (0.3%) and TGG (W) (0.1%). Only one mutant allele, ACC (T), was found at codon 1532, with a frequency of 6.4% in ten field populations. Moreover, multiple mutations at alleles I1532 and F1534 in a sample appeared in five populations. The 1534 mutation rate was significantly positively related to AAT (Pearson correlation: r (18) = 0.624, P = 0.0056), while the 1532 mutation rate was significantly negatively related to AAT (Pearson correlation: r (18) = − 0.645, P = 0.0038). Thirteen haplotypes were inferred, in which six mutant haplotypes were formed by one step, and one additional mutation formed the other six haplotypes. In the samples from the 1990s, no mutant allele was detected at codon 1532 of the VGSC gene. However, F1534S/TCC was found in HNHK94 with an unexpected frequency of 100%. Conclusions Kdr mutations are widespread in the field populations of Ae. albopictus in China. Two novel mutant alleles, F1534W/TGG and F1534R/CGC, were detected in this study. The 1534 kdr mutation appeared in the population of Ae. albopictus no later than the 1990s. The F1534 mutation rate was positively correlated with AAT, while the I1532 mutation rate was negatively correlated with AAT. These results indicate that iInsecticide usage should be carefully managed to slow down the spread of highly resistant Ae. albopictus populations, especially in the areas with higher AAT. Graphical abstract

Bioremediation is one of the treatment technologies for the black-odorous water, and obtaining functional bacteria is the key step to its success. In this study, a number of highly efficient pollutant degrading strains were isolated from the sediment of black-odorous river, and were identified by phenotypic and phylogenetic analysis. The composite bacterial agent J1 was mixed by strains A1, A2, A5 and A7, with a volume ratio of 4:4:2:1. And the final compound bacteria injected into black-odorous water were composed of J1 and NS3, with the volume ratio of 1:1. Optimized degradation conditions of compound bacterium agent were as follows: pH 7.5, DO 2.5 mg/L, temperature 30 °C. Under optimized conditions, add 1% by volume to the black-odorous water for a 50-day experimental operation. Finally, the overlying water ammonia nitrogen, chemical oxygen demand (COD), and total phosphorus has been significantly degraded. The research is expected to contribute to the use of bioremediation methods to repair black-odorous water, and the application of isolates can be carried out in situ for water types similar to pollute waterways. HIGHLIGHTS Controllable functional microbes for characteristic pollutants were obtained.; Physiological, biochemical and degradation characteristics of microbial isolates were explored.; A basic framework of in-situ bioremediation of black-odorous water was demonstrated.;

COVID-19 is a critical public health threat, but molecular characterizations of patients’ immunity is still lacking. Here the authors collected blood from patients with various disease severity, and prefiltered to exclude selected comorbidity, to obtain genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles to report a trans-omics landscape.

Edge computing can provide users with low-latency and high-bandwidth services by deploying many edge servers at the network edge.However, a large number of deployments also bring problems of high energy consumption.When dispatching tasks from end devices to different edge servers, different energy consumption and delays will occur due to the edge servers’ heterogeneity.Therefore, it is a challenge to select an optimal server among many edge servers for task dispatching so that energy consumption and delay are relatively low.An energy-aware task dispatching method with quality of service (QoS) guarantee based on online learning was proposed.It can obtain real-time information by interacting with the environment to ensure energy consumption was minimal while the QoS was acceptable when dispatching tasks.Experiments show that the proposed method can dispatch tasks efficiently to the optimal server compared with other methods, thereby reducing the edge computing network’s overall energy consumption significantly.

Micro/nanomotors (MNMs) are miniaturized machines that can convert many kinds of energy into mechanical motion. Over the past decades, a variety of driving mechanisms have been developed, which have greatly extended the application scenarios of MNMs. Enzymes exist in natural organisms which can convert chemical energy into mechanical force. It is an innovative attempt to utilize enzymes as biocatalyst providing driving force for MNMs. The fuels for enzymatic reactions are biofriendly as compared to traditional counterparts, which makes enzyme-powered micro/nanomotors (EMNMs) of great value in biomedical field for their nature of biocompatibility. Until now, EMNMs with various shapes can be propelled by catalase, urease and many others. Also, they can be endowed with multiple functionalities to accomplish on-demand tasks. Herein, combined with the development process of EMNMs, we are committed to present a comprehensive understanding of EMNMs, including their types, propelling principles, and potential applications. In this review, we will introduce single enzyme that can be used as motor, enzyme powered molecule motors and other micro/nano-architectures. The fundamental mechanism of energy conversion process of EMNMs and crucial factors that affect their movement behavior will be discussed. The current progress of proof-of-concept applications of EMNMs will also be elaborated in detail. At last, we will summarize and prospect the opportunities and challenges that EMNMs will face in their future development.

Abstract The human ζ-globin gene (HBZ) is transcribed in primitive erythroid cells only during the embryonic stages of development. Reactivation of this embryonic globin synthesis would likely alleviate symptoms both in α-thalassemia and sickle-cell disease. However, the molecular mechanisms controlling ζ-globin expression have remained largely undefined. Moreover, the pharmacologic agent capable of inducing ζ-globin production is currently unavailable. Here, we show that TRIAC, a bioactive thyroid hormone metabolite, significantly induced ζ-globin gene expression during zebrafish embryogenesis. The induction of ζ-globin expression by TRIAC was also observed in human K562 erythroleukemia cell line and primary erythroid cells. Thyroid hormone receptor α (THRA) deficiency abolished the ζ-globin-inducing effect of TRIAC. Furthermore, THRA could directly bind to the distal enhancer regulatory element to regulate ζ-globin expression. Our study provides the first evidence that TRIAC acts as a potent inducer of ζ-globin expression, which might serve as a new potential therapeutic option for patients with severe α-thalassemia or sickle-cell disease.

Glycosylation alterations, a key driver throughout tumorigenesis and tumor progression, could regulate the microenvironment and immune response as well as lead to harmful metabolism and cell signaling. In this study, we first comprehensively evaluated the glycosylation modification patterns of LGGs based on glycosyltransferase family genes and systematically integrated these modification patterns with tumor metabolism and immune microenvironment characteristics. Glycosylation score was also developed to quantify glycosylation modification patterns of individuals. As a result, two glycosylation modification patterns were identified, with distinct prognosis, metabolism, and immune microenvironment features. The glycosylation subtype A and cluster A were characterized by higher carbohydrates and amino acid metabolism activity, higher levels of infiltrating cells, and poor prognosis, whereas an opposite modification pattern was observed in glycosylation subtype B and cluster B. In addition, a high glycosylation score is closer to a microenvironment characterized by chronic inflammation, immunosuppression, and tumor promotion. Following analysis and validation, the glycosylation score was a reliable and independent prognostic index. More importantly, the glycosylation score influenced the response to immunotherapy, chemotherapy, or targeted therapy, which provided a novel insight into promoting personalized therapy in the future and may contribute to developing novel therapeutic drugs or exploring promising drug combination therapy strategies.

Reading comprehension and arithmetic skills are essential abilities for children, particularly at the early career. Examine the link between language proficiency and numeral information process amongst primary school children. This study examines numeral comprehension in 600 Chinese primary second graders with different levels of decoding and linguistic comprehension skills. Four groups of children were compared, including typical readers (TR), poor decoders (PD), poor comprehenders (PC) and general poor readers (GPR). Results showed that the four groups had similar performances in numeral comprehension when the answer options to a question on the quantity of numerals were presented in Arabic numbers. However, when the answer options to a question on the quantity of numeral information were presented in analogue nonsymbolic magnitude representations, the PC group outperformed the PD and GPR group. The findings of this study has demonstrated the link between language proficiency and numerical information process in reading comprehension.

Abstract Pancreatic tumors are classified into endocrine and exocrine types, and the clinical manifestations in patients are nonspecific. Most patients, especially those with pancreatic ductal adenocarcinoma (PDAC), have lost the opportunity to receive for the best treatment at the time of diagnosis. Although chemotherapy and radiotherapy have shown good therapeutic results in other tumors, their therapeutic effects on pancreatic tumors are minimal. A multifunctional transcription factor, Yin-Yang 1 (YY1) regulates the transcription of a variety of important genes and plays a significant role in diverse tumors. Studies have shown that targeting YY1 can improve the survival time of patients with tumors. In this review, we focused on the mechanism by which YY1 affects the occurrence and development of pancreatic tumors. We found that a YY1 mutation is specific for insulinomas and has a role in driving the degree of malignancy. In addition, changes in the circadian network are a key causative factor of PDAC. YY1 promotes pancreatic clock progression and induces malignant changes, but YY1 seems to act as a tumor suppressor in PDAC and affects many biological behaviors, such as proliferation, migration, apoptosis and metastasis. Our review summarizes the progress in understanding the role of YY1 in pancreatic endocrine and exocrine tumors and provides a reasonable assessment of the potential for therapeutic targeting of YY1 in pancreatic tumors.

Abstrac: In order to reduce the manufacturing cycle and improve the forming performance of the incremental sheet forming (ISF) process, a hybrid manufacturing process that combines thermal spraying and incremental forming process was firstly proposed. The effects of different thermal spraying parameters on the forming properties and mechanical properties of sheet metal were investigated. Firstly, Fe316L coating was prepared on AA2024-T3 plate by using atmospheric plasma thermal spraying, and then the plate is formed into the target shape with variable angles. In addition, tensile tests were carried out on the plates pretreated by thermal spraying with different parameters. The results showed that the yield strength of the plate decreased up to 70% and the elongation increased by 65% under the appropriate thermal spraying power. In the process of ISF, the axial forming force of sheet metal after thermal spraying decreased obviously and the forming limit increased obviously. In addition, influences of different processing steps (sand blasting and heating) on the forming performance of sheet metal were investigated. It is found that the heating effect in the thermal spraying process has the most obvious effect on the improvement of forming performance, while the sand blasting process has adverse effect. Finally, in order to optimize the thermal spraying area, the influence of thermal spraying at different areas on the forming performance of sheet metal was investigated.

Most fluorescence probes to measure hypoxia are irreversible. Here, the authors develop a near infrared luminescent probe to measure hypoxia which is reversible and use the probe to monitor hypoxia-reoxygenation in several animal models.

Abstract Background The relict gull (Larus relictus), was classified as vulnerable on the IUCN Red List and is a first-class national protected bird in China. Genomic resources for L. relictus are lacking, which limits the study of its evolution and its conservation. Results In this study, based on the Illumina and PacBio sequencing platforms, we successfully assembled the genome of L. relictus, one of the few known reference genomes in genus Larus. The size of the final assembled genome was 1.21 Gb, with a contig N50 of 8.11 Mb. A total of 18,454 genes were predicted from the assembly results, with 16,967 (91.94%) of these genes annotated. The genome contained 92.52 Mb of repeat sequence, accounting for 7.63% of the assembly. A phylogenetic tree was constructed using 4902 single-copy orthologous genes, which showed L. relictus had closest relative of L. smithsonianus, with divergence time of 14.7 Mya estimated between of them. PSMC analyses indicated that L. relictus had been undergoing a long-term population decline during 0.01-0.1 Mya with a small effective population size fom 8800 to 2200 individuals. Conclusions This genome will be a valuable genomic resource for a range of genomic and conservation studies of L. relictus and will help to establish a foundation for further studies investigating whether the breeding population is a complex population. As the species is threatened by habitat loss and fragmentation, actions to protect L. relictus are suggested to alleviate the fragmentation of breeding populations.

Abstract The unmanned ground vehicle (UGV) has been widely used to accomplish various missions in civilian or military environments. Formation of the UGVs group is an important technique to support the broad applications of multi‐functional UGVs. This study proposes a scalable regular UGV formation maintenance (SRUFM) algorithm based on deep reinforcement learning (DRL), which aims to use a unified DRL framework to improve the lateral control and longitudinal control performance of UGV in different situations of the formation. Based on the tailored design of state, action space, related inter‐vehicle information, and the dueling double deep Q‐network (D3QN), SRUFM outperforms nature deep Q‐network and double deep Q‐network in the exploration efficiency and the convergence speed in same CARLA training environments with fixed size formation. Furthermore, when the formation's scale is extended with similar initialisation conditions, the SRUFM can still get a nearly 90% success rate to execute all experiment formation maintenance missions after 4000 episodes of training. Each UGV in the formation can keep distance within the upper and lower error threshold of 0.15 m. The simulation experiments show that the proposed centralised training frame with D3QN is suitable to solve scalable regular UGV formation maintenance missions.

Abstract Objective To analyze and compare the effects of peri-treatment analgesics on acute and chronic pain and postoperative functional recovery of patients with thoracolumbar fractures, so as to guide the clinical drug use. Methods Seven hundred nineteen patients with thoracolumbar fractures were collected and divided into acetaminophen dihydrocodeine, celecoxib, and etoricoxib groups. The main indicators were the degree of postoperative pain (visual analog scale (VAS)), the incidence of chronic pain and postoperative functional recovery (Oswestry dysfunction index (ODI) and Japanese Orthopedics Association score (JOA)), which were continuously tracked through long-term telephone follow-up. The correlation analysis of ODI-pain score, peri-treatment VAS score, and ODI index was performed, and bivariate regression analysis was conducted to understand the risk factors for chronic pain. Results Regression analysis showed that severe spinal cord injury and peri-treatment use of acetaminophen dihydrocodeine were both one of the risk factors for postoperative chronic pain. But there were no statistically conspicuous differences in basic characteristics, preoperative injury, and intraoperative conditions. Compared with the other two groups, patients in the acetaminophen dihydrocodeine group had longer peri-therapeutic analgesic use, higher pain-related scores (VAS 1 day preoperatively, VAS 1 month postoperatively, and ODI-pain 1 year postoperatively), higher VAS variation, higher incidence of chronic pain 1 year after surgery, and higher ODI index. And other ODI items and JOA assessments showed no statistically significant differences. In addition, the correlation analysis showed that the peri-treatment pain score was correlated with the severity of postoperative chronic pain. Conclusion Although the peri-treatment analgesic effect of acetaminophen dihydrocodeine is good, it is still necessary to combine analgesics with different mechanisms of action for patients with severe preoperative pain of thoracolumbar fracture, so as to inhibit the incidence of postoperative chronic pain and improve the quality of postoperative rehabilitation.

Abstract Background A growing number of studies have focused on investigating circRNAs as crucial regulators in the progression of multiple cancer types. Nevertheless, the biological effects and underlying mechanisms of circRNAs in pancreatic ductal adenocarcinoma (PDAC) remain unclear. Methods Differentially expressed circRNAs between cancerous tissue and adjacent normal tissues were identified by RNA sequencing in PDAC. Subsequently, in vitro and in vivo functional experiments were performed to investigate the functional roles of circNEIL3 in PDAC tumour growth and metastasis. Furthermore, RNA pull-down, dual-luciferase reporter assays, RNA immunoprecipitation (RIP) assays, fluorescent in situ hybridization (FISH) and Sanger sequencing assays were performed to examine the circular interaction among circNEIL3, miR-432-5p and adenosine deaminases acting on RNA 1 (ADAR1). Results CircNEIL3 was upregulated in PDAC and promoted the progression of PDAC cells both in vitro and in vivo. Mechanistically, circNEIL3 was shown to regulate the expression of ADAR1 by sponging miR-432-5p to induce RNA editing of glioma-associated oncogene 1 (GLI1), ultimately influencing cell cycle progression and promoting epithelial-to-mesenchymal transition (EMT) in PDAC cells. Moreover, we discovered that the circNEIL3/miR-432-5p/ADAR1 axis was correlated with the PDAC clinical stage and overall survival of PDAC patients, while ADAR1 may reduce the biogenesis of circNEIL3. Conclusions Our findings reveal that circNEIL3 facilitates the proliferation and metastasis of PDAC through the circNEIL3/miR-432-5p/ADAR1/GLI1/cell cycle and EMT axis and that its expression is regulated by ADAR1 through a negative feedback loop. Therefore, circNEIL3 may serve as a prognostic marker and a therapeutic target for PDAC.

In this paper, the hybrid gas–liquid discharge plasma can efficiently degrade pesticide residues in water driven by nanosecond pulse power, which can achieve the simultaneous discharge process in the liquid and gas phases. The relevant factors are systematically investigated, including the waveforms of discharge current and pulse voltage, discharge images, and optical emission spectra during the discharge process. The Stark broadening of Hα calculates the electron density. The effects of the pulse peak voltage and discharge time on the emission intensities of OH (A2∑ → X2∏), N2 (C3∏u → B3∏g), Hα, and O (3p5P → 3s5S0) are discussed in-depth by the optical emission spectra. The gas–liquid discharge plasma with an electron density of 7.14 × 1017 cm−3 was found. The emission intensities of OH (A2∑ → X2∏), N2 (C3∏u → B3∏g), Hα, and O (3p5P → 3s5S0) present the rising trend by increasing the pulse peak voltage and discharge time. In addition, pyraclostrobin is adopted as the research object to study the removal efficiency of pollutants. The results confirm that pyraclostrobin can be completely degraded after 10 min of plasma treatment with the pulse peak voltage of 28 kV, and the degradation rate and energy yield was 0.323 min−1, and 1.91 g/kWh, respectively. The intermediate products and the possible degradation mechanism of pyraclostrobin are further explored by combining the results of high-performance liquid chromatography–mass spectrometry (HPLC-MS/MS) and density functional theory (DFT), the developmental toxicity of the intermediate products was analyzed, which provided a scheme for the treatment of pesticide wastewater by gas–liquid discharge plasma technology.

Attosecond streaking provides an extremely high temporal resolution for characterizing light pulses and photoionization processes with attosecond (10−18 s) accuracy, which employs a laser as a streaking field to deflect electrons generated by photoionization. The current attosecond streaking requires a time delay scan between the attosecond pulses and streaking field with attosecond accuracy and a femtosecond range, which is difficult to realize real-time measurement. In this study, we theoretically propose a non-collinear attosecond streaking scheme without the time delay scan, enabling real-time and even the potential to perform single-shot attosecond pulse measurement. In the proposal, time-delay information is projected into longitudinal space, both horizontally and vertically, enabling attosecond pulse characterization with temporal-spatial coupling. From our calculation, down to 70 as pulses with pulse front and wavefront tilt are characterized with high accuracy. Our study not only provides a method toward real-time attosecond pulse measurement, but also an approach for attosecond pump-probe experiments without time delay scan.

Low-dimensional materials with a negative Poisson’s ratio (NPR) have attracted lots of attention for their potential applications in aerospace, defense, etc. Although graphene and monolayer h-BN have been reported to have NPR behavior under external strains, the mechanism is not clear, and the critical strains of the occurrence of a NPR are relatively larger. Here, we propose that the origination of the NPR phenomena in the 2D honeycomb structures can be explained by the variation of the zigzag chains under strains. Our calculations clarify that a NPR occurs along the armchair-chain direction rather than the zigzag-chain direction in these materials. Furthermore, a series of two-dimensional carbon networks including zigzag chains have demonstrated that there is NPR phenomena in them. In some of the networks, a NPR can be found under a small external strain. Our study not only deepens the understanding of the origin of NPR in honeycomb systems but also offers guidance to design auxetic nanostructures.

This paper studies the interaction of two droplets splashing on a stationary film. A source term is included in the large-density-ratio pseudopotential lattice Boltzmann method to achieve tuneable surface tension. This model offers excellent numerical accuracy and stability for droplet impacts on liquid films. The influence of the Reynolds number, Weber number, film thickness, and horizontal/vertical distance between the droplets on the crown geometry evolution is investigated. The energy loss during the impact process and the velocity discontinuity in the liquid film are the two key factors affecting the stability and evolution process of the crown. A smaller Reynolds number or thicker liquid film enhances the energy loss and decreases the velocity discontinuity, leading to more stable side and central jets. An increase in the horizontal distance between the droplets reduces the velocity discontinuity, causing the central jet height to decrease. An increase in the Weber number does not affect the energy loss or velocity discontinuity, but the lower surface tension leads to a dramatic deformation in both the central and side jets. A vertical distance between the two droplets causes an asymmetrical evolution of the crown geometry, and postpones the breakup time of the central jet .

We propose an efficient scheme for qutrit state tomography based on optimal unambiguous discrimination of three nonorthogonal pure qutrit states. In our scheme, we first introduce an ancillary qubit initially prepared in a known state and apply a joint unitary transformation on the whole system composed of a qutrit state and an ancillary qubit state. Afterwards, we make a local von Neumann measurement (VNM) on the ancillary qubit. If it is projected onto the state |0〉, we finally perform mutually unbiased measurements (MUMs) on the collapsed qutrit state arbitrarily chosen from a complete set of four mutually unbiased bases (MUBs). With only six properly-chosen projectors, the real and imaginary parts of non-diagonal elements can be entirely obtained. Together with the diagonal elements obtained directly from one VNM in the computational bases, the density matrix of an arbitrary unknown qutrit state can be fully determined. Compared with the previous work (R. Salazar and A. Delgado 2012), our scheme consumes much less resources. In comparison with MUBs-based tomography scheme (H. Yuan, et al., 2016), our scheme requires more measurements and less projectors, but pays the price of a loss of certain fraction identically prepared states. Our proposal can be extended to the case of other d-dimensional quantum states if their d MUBs are exactly known.

Abstract Digital nucleic acid amplification tests enable absolute quantification of nucleic acids, but the generation of uniform compartments and reading of the fluorescence requires specialized instruments that are costly, limiting their widespread applications. Here, the authors report deep learning‐enabled polydisperse emulsion‐based digital loop‐mediated isothermal amplification (deep‐dLAMP) for label‐free, low‐cost nucleic acid quantification. deep‐dLAMP performs LAMP reaction in polydisperse emulsions and uses a deep learning algorithm to segment and determine the occupancy status of each emulsion in images based on precipitated byproducts. The volume and occupancy data of the emulsions are then used to infer the nucleic acid concentration based on the Poisson distribution. deep‐dLAMP can accurately predict the sizes and occupancy status of each emulsion and provide accurate measurements of nucleic acid concentrations with a limit of detection of 5.6 copies µl‐1 and a dynamic range of 37.2 to 11000 copies µl‐1. In addition, deep‐dLAMP shows robust performance under various parameters, such as the vortexing time and image qualities. Leveraging the state‐of‐the‐art deep learning models, deep‐dLAMP represents a significant advancement in digital nucleic acid tests by significantly reducing the instrument cost. We envision deep‐dLAMP would be readily adopted by biomedical laboratories and be developed into a point‐of‐care digital nucleic acid test system.