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The present study aimed to explore whether water flow velocity could affect the swimming ability and overall energy metabolism of wild Amur grayling (Thymallus grubii). Swimming performance was assessed by measuring critical swimming speed (Ucrit), burst speed (Uburst), and oxygen consumption rate (MO2) based on the stepped velocity test method. Our results showed that the absolute values of Ucrit and Uburst tended to increase with body length. In contrast, the relative values of Ucrit and Uburst tended to decrease and increase, respectively. MO2 in Amur grayling was elevated with increasing velocity, suggesting relatively high swimming efficiency. We also measured the biochemical indices related to energy metabolism. Lactate dehydrogenase, hexokinase, and pyruvate kinase activities significantly increased (p < 0.05). Hepatic glycogen, glucose, and muscle glycogen contents decreased with the increasing trend of velocity (p < 0.05), the lactic acid contents of the blood and muscles increased significantly with the increase in velocities (p < 0.05), and changes in creatine phosphate content showed no significant difference (p > 0.05). The results not only denote the relationship between body size and swimming speed but also show the effects of water flow velocity on energy metabolism in Amur grayling. The results provide basic data for the construction of fish passage.

Previous studies have demonstrated that CUX1 could contribute to the proliferation of DPCs in vitro, but the upstream transcriptional regulatory mechanisms of CUX1 remain largely unknown. This study aimed to investigate the upstream transcriptional regulators of CUX1 to enhance our comprehension of the mechanism of action of the CUX1 gene in ovine DPCs. Initially, the JASPAR (2024) software was used to predict the upstream target transcription factors for the CUX1 gene. Subsequently, through RT-qPCR and a double luciferase reporter assay, the interaction between SP1, KROX20, and CUX1 was established, respectively. The results indicated that SP1 and KROX20 were two highly reliable upstream transcription regulators for the CUX1 gene. Additionally, we found that SP1 promoted the proliferation of DPCs by overexpressing SP1 in DPCs, and KROX20 inhibited the proliferation of DPCs by overexpressing KROX20 in DPCs. These findings are also consistent with the transcriptional regulation of CUX1 by SP1 and KROX20, respectively. This study suggests that the effect of DPC proliferation in vitro by CUX1 may regulated by the transcription factors SP1 and KROX20.

Underground water-sealed oil storage caverns constructed in island environments is a promising approach for expanding oil storage caverns. However, few researchers have studied the risks of seawater intrusion and the distribution characteristics of intrusion interfaces in large underground water-sealed oil storage caverns in island environments. In this paper, we established a visualized physical simulation platform to investigate the characteristics and control measures of seawater intrusion in single fracture of rock masses within island underground water-sealed oil storage caverns. In addition, the effects of the excavation of caverns, the distance between the cavern and coast, fracture width, seawater level, oil storage stage, water curtain, and water injection pressure were evaluated. The results show that excavation of oil storage caverns carries the risk of seawater intrusion. Specifically, reducing the distance between the oil storage caverns and the coast, increasing the fracture width, and raising the seawater level all contribute to accelerated seawater intrusion into the caverns. However, the vertical water curtain can effectively inhibit seawater intrusion, and increasing the injection pressure of vertical water curtain can avoid the risk of seawater intrusion into the caverns. The research results provide an experimental basis for the study of seawater intrusion in underground oil storage caverns in island environments.

The attainment of a well-crystallized photo-absorbing layer with minimal defects is crucial for achieving high photovoltaic performance in polycrystalline solar cells. However, in the case of perovskite solar cells (PSCs), precise control over crystallization and elemental distribution through solution processing remains a challenge. In this study, we propose the use of a multifunctional molecule, α-amino-γ-butyrolactone (ABL), as a modulator to simultaneously enhance crystallization and passivate defects, thereby improving film quality and deactivating nonradiative recombination centers in the perovskite absorber. The Lewis base groups present in ABL facilitate nucleation, leading to enhanced crystallinity, while also retarding crystallization. Additionally, ABL effectively passivates Pb2+ dangling bonds, which are major deep-level defects in perovskite films. This passivation process reduces recombination losses, promotes carrier transfer and extraction, and further improves efficiency. Consequently, the PSCs incorporating the ABL additive exhibit an increase in conversion efficiency from 18.30% to 20.36%, along with improved long-term environmental stability. We believe that this research will contribute to the design of additive molecular structures and the engineering of components in perovskite precursor colloids.

At present, there are many excellent cultivars of raspberry worldwide with different fruit colors, such as yellow, red, purple and black. Anthocyanin accumulation is responsible for flower and fruit coloration in plants. Anthocyanins belong to flavonoids which are natural pigments widely distributed in plants. The MYB transcription factor (TF) plays a vital regulatory role in the metabolic pathway of anthocyanins. Here, RoMYB10, an R2R3-MYB in black raspberry (Rubus occidentalis L.), was isolated. The basic physical and chemical properties, conserved motif distribution, evolutionary relationship and subcellular localization were analyzed for the RoMYB10 encoded amino acid sequence. The contents of anthocyanin were determined in four different colored raspberry fruits by high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS). The expression levels of MYB10 genes in various tissues and fruits at different developmental stages of the four different colored raspberries were detected by real-time fluorescence quantitative PCR (qRT-PCR). The results showed that the contents of anthocyanin and the expression levels of the MYB10 gene were the highest in black raspberry. Moreover, the expression of MYB10 in the fruit was significantly higher than in other tissues, especially in ripe and mottled fruits. When ectopic overexpression of RoMYB10 occurred in tobacco, the expression levels of the RoMYB10 gene and total anthocyanin contents in transgenic tobacco plants were significantly higher than those in wild-type (WT) plants. In addition, overexpression of RoMYB10 up-regulated the key genes in the anthocyanin biosynthesis, such as NtCHS, NtCHI, NtF3H, NtANS and NtUFGT. Our study suggests that RoMYB10 is involved in the regulating of anthocyanin biosynthesis in raspberry and has potential as a molecular tool for manipulating biosynthesis of anthocyanins in fruits using metabolic engineering.

This paper presents an unconditionally stable integration method, which introduces a linearly implicit algorithm featuring an explicit displacement expression. The technique that is being considered integrates one Newton iteration into the mean acceleration method. The stability of the proposed algorithm in solving equations of motion containing nonlinear restoring force and nonlinear damping force is analyzed using the root locus method. The objective of this investigation was to assess the accuracy and consistency of the proposed approach in contrast to the Chang method and the CR method. This is achieved by analyzing the dynamic response of three distinct structures: a three-layer shear structure model outfitted with viscous dampers, a three-layer shear structure model featuring metal dampers, and an eight-story planar frame structure. Empirical evidence indicates that the algorithm in question exhibits a notable degree of precision and robustness when applied to nonlinear dynamic problem-solving.

In our previous study of Hu sheep hair follicles, we found that CRABP2 was highly expressed in DPCs, which suggested that CRABP2 may influence the number of DPCs. In the present study, we aimed to understand the effect of CRABP2 in Hu sheep dermal papilla cells (DPCs). First, we explored the influence of CRABP2 on the ability of Hu sheep DPCs’ proliferation. Based on the results obtained from some experiments, such as CCK-8, EDU, qPCR, and Western blot experiment, we found that the overexpression of CRABP2 facilitated the proliferation of DPCs compared to the negative control group. Then, we also detected the effect of CRABP2 on the Wnt/β-catenin pathway based on the important function of the Wnt/β-catenin pathway in hair follicles. The results showed that CRABP2 could activate the Wnt/β-catenin pathway in DPCs, and it rescues the proliferation of DPCs when the Wnt/β-catenin pathway was inhibited. In summary, our findings indicate that CRABP2 is a vital functional gene in the proliferation of Hu sheep DPCs. Our study will be of great use for revealing the roles of CRABP2 in the hair follicles of Hu sheep.

Escherichia coli (E. coli) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of E. coli F17-antagonism (AN) and -sensitive (SE) lambs; however, the biological mechanism underlying E. coli F17 infection has not been fully elucidated. Therefore, the present study first analyzed the metabolite data obtained with UHPLC-MS/MS. A total of 1957 metabolites were profiled in the present study, and 11 differential metabolites were identified between E. coli F17 AN and SE lambs (i.e., FAHFAs and propionylcarnitine). Functional enrichment analyses showed that most of the identified metabolites were related to the lipid metabolism. Then, we presented a machine-learning approach (Random Forest) to integrate the microbiome, metabolome and transcriptome data, which identified subsets of potential biomarkers for E. coli F17 infection (i.e., GlcADG 18:0-18:2, ethylmalonic acid and FBLIM1); furthermore, the PCCs were calculated and the interaction network was constructed to gain insight into the crosstalk between the genes, metabolites and bacteria in E. coli F17 AN/SE lambs. By combing classic statistical approaches and a machine-learning approach, our results revealed subsets of metabolites, genes and bacteria that could be potentially developed as candidate biomarkers for E. coli F17 infection in lambs.

Sox18 is a developmental gene that encodes transcription factors. It has been indicated as be a key gene affecting the growth and development of hair follicles, in which dermal papilla cells (DPCs) have been demonstrated to play an important role through their ability to induce the formation of hair follicles. Pre-laboratory studies have found that Sox18 is differentially expressed in the dermal papilla cells of different pattern types of Hu sheep. We speculated that Sox18 plays an important role in the dermal papilla cells of Hu sheep. In our study, we analyzed the effect of Sox18 on the induction ability of DPCs in order to elucidate the function and molecular mechanism of Sox18 in the DPCs of Hu sheep. We first identified the expression of Sox18 in the DPCs of Hu sheep by immunofluorescence staining. We then used alkaline phosphatase staining, cell morphology observations and RT-PCR to detect the effect of Sox18 on the induction of DPCs after overexpression of or interference with Sox18. We also used RT-PCR, WB and immunofluorescence staining to detect the effect of Sox18 on the Wnt/β-catenin signal pathway in DPCs. We found that Sox18 was specifically expressed in the DPCs of Hu sheep, and that Sox18 could enhance the alkaline phosphatase activity in the DPCs of Hu sheep and accelerate cell agglutination. The results of RT-PCR revealed that Sox18 promoted the mRNA expression of Versican, HHIP and FGFRI, and inhibited the mRNA expression of BMP4 and WIF1. Further studies showed that Sox18 promoted the expression of β-catenin and activated the Wnt/β-catenin signal pathway in DPCs. When the Wnt/β-catenin signal pathway of DPCs was activated, the induction ability of DPCs was enhanced. Overall, we believe that Sox18 could enhance the induction ability of DPCs in Hu sheep and regulate the induction ability of DPCs through the Wnt/β-catenin signal pathway.

Pavement texture characteristics can reflect early performance decay, skid resistance, and other information. However, most statistical texture indicators cannot express this difference. This study adopts 3D image camera equipment to collect texture data from laboratory asphalt mixture specimens and actual pavement. A pre-processing method was carried out, including data standardisation, slope correction, missing value and outlier processing, and envelope processing. Then the texture data were calculated based on texture separation, texture power spectrum, grey level co-occurrence matrix, and fractal theory to acquire six leading texture indicators and eight extended indicators. The Pearson correlation coefficient was used to analyse the correlation of different texture indicators. The distinction vector based on the information entropy is calculated to analyse the distinction of the indicators. High correlations between ENE (energy) and ENT (entropy), ENT and D (Minkowski dimension) were found. The CON (contrast) has low correlations with HT (macro-texture power spectrum area), ENT and D. However, the differentiation of ENE and HT is more prominent, and the differentiation of the CON is smaller. ENE, ENT, CON and D indicators based on macro-texture and the corresponding original texture have strong linear correlations. However, the microtexture indicators are not linearly correlated with the corresponding original texture indicators. D, WT (micro-texture power spectrum area) and ENT exhibit high degrees of numerical concentration for the same road sections and may be more statistically helpful in distinguishing the characteristics of the pavement performance decay of the road sections.

Hysteresis is one of the main factors affecting the measurement accuracy of TMR sensors, especially in dynamic measurements. The commonly used Preisach hysteresis compensation model has some problems, such as complex modeling and difficulty in accurately measuring the step time, resulting in low accuracy in dynamic measurements. In this paper, considering the distribution characteristics of the conversion time of the hysteresis operator in dynamic measurements, a dynamic hysteresis model based on the probability estimation of the hysteresis operator and its conversion time is proposed. Compared with the existing methods, this method only needs to calculate the distribution of the sensor hysteresis operator to realize the calculation of hysteresis characteristics without a physical model or fitting algorithm. It has good generalization performance and a corresponding fast speed. In the test of two typical TMR sensors, compared with the transmission Preisach model, the maximum error of this method is reduced by 46.7%, the variance can be reduced by 90.2%, and the average value can be reduced by 65.1%.

Tunneling magnetoresistive (TMR) sensors have broad application prospects because of their high sensitivity and small volume. However, the inherent hysteresis characteristics of TMR affect its applications in high accuracy scenarios. It is essential to build a model to describe the attributes of hysteresis of TMR accurately. Preisach model is one of the popular models to describe the behavior of inherent hysteresis for TMR, whereas it presents low accuracy in high-order hysteresis reversal curves. Furthermore, the traditional Preisach model has strict congruence constraints, and the amount of data seriously affects the accuracy. This paper proposes a hysteresis model from a probability perspective. This model has the same computational complexity as the classic Preisach model while presenting higher accuracy, especially in high-order hysteresis reversal curves. When measuring a small amount of data, the error of this method is significantly reduced compared with the classical Preisach model. Besides, the proposed model’s congruence in this paper only needs equal vertical chords.

Coal is a complex heterogeneous and anisotropic material conformed with fractal characteristics. The pore and fracture characteristics have important influence on the dynamic disasters including rock burst and gas outburst, however, the relationship between them is not accurately investigated due to inadequate research method. The pore and fracture distribution of coal with different bursting proneness were obtained by comprehensive application of MIP, LTNAD, SEM, and X-ray CT, and then fractal theory and DIC were used to research the pore and fracture characteristics. The result indicated that the modification of MIP result by LTNAD result could effectively eliminate the adverse effect of coal matrix compressibility, exactly reflect the distribution of pore and fracture in coal, and the pore distribution of coal with different bursting proneness were quite different. Gray scale image from SEM and 3D reconstruction technology based on X-ray CT could show the geological structure, fracture structure, and pore structure characteristics of coal. The study of LTNAD, SEM, and X-ray CT showed that these methods complemented each other, the coal had fractal properties, and the fractal dimension value had a positive correlation with the bursting proneness of coal sample.

The X-ray satellite “Einstein Probe” of the Chinese Academy of Sciences (CAS) was successfully launched on 9 January 2024 at 15:03 Beijing Time from the Xichang Satellite Launch Center in China with a “Long March-2C” rocket. The Einstein Probe is equipped with two scientific X-ray telescopes. One is the Wide-field X-ray Telescope (WXT), which uses lobster-eye optics. The other is the Follow-up X-ray Telescope (FXT), a Wolter-I type telescope. These telescopes are designed to study the universe for high-energy X-rays associated with transient high-energy phenomena. The FXT consists of two modules based on 54 thin X-ray Wolter-I grazing incidence Ni-replicated mirrors produced by the Italian Media Lario company, as contributions from the European Space Agency and the Max Planck Institute for Extraterrestrial Physics (MPE), which also provided the focal-plane detectors. Meanwhile, the Institute of High Energy Physics (IHEP), together with the Harbin Institute of Technology and Xi’an Institute of Optics and Precision Mechanics, has also completed the development and production of the structural and thermal model (STM), qualification model (QM) and flight model (FM) of FXT mirrors for the Einstein Probe (EP) satellites for demonstration purposes. This paper introduces the precision manufacturing adopted in China of Wolter-I X-ray mirror mandrels similar to those used for the EP-FXT payload. Moreover, the adopted electroformed nickel replication process, based on a chemical nickel–phosphorus alloy, is reported. The final results show that the surface of the produced mandrels after demolding and the internal surface of the mirrors have been super polished to the roughness level better than 0.3 nm RMS and the surface accuracy is better than 0.2 μm, and the mirror angular resolution for single mirror shells may be as good as 17.3 arcsec HPD (Half Power Diameter), 198 arcsec W90 (90% Energy Width) @1.49 keV (Al-K line). These results demonstrate the reliability and advancement of the process. As the first efficient X-ray-focusing optics manufacturing chain established in China, we successfully developed the first focusing mirror prototype that could be used for future X-ray satellite payloads.

Lithium-ion capacitors (LICs) are emerging as promising hybrid energy storage devices that combine the high energy densities of lithium-ion batteries (LIBs) with high power densities of supercapacitors (SCs). Nevertheless, the development of LICs is hindered by the kinetic imbalances between battery-type anodes and capacitor-type cathodes. To address this issue, honeycomb-like N-doped carbon matrices encapsulating Co1−xS/Co(PO3)2 heterostructures were prepared using a simple chemical blowing-vulcanization process followed by phosphorylation treatment (Co1−xS/Co(PO3)2@NC). The Co1−xS/Co(PO3)2@NC features a unique heterostructure engineered within carbon honeycomb structures, which efficiently promotes charge transfer at the interfaces, alleviates the volume expansion of Co-based materials, and accelerates reaction kinetics. The optimal Co1−xS/Co(PO3)2@NC composite demonstrates a stable reversible capacity of 371.8 mAh g−1 after 800 cycles at 1 A g−1, and exhibits an excellent rate performance of 242.9 mAh g−1 even at 8 A g−1, alongside enhanced pseudocapacitive behavior. The assembled Co1−xS/Co(PO3)2@NC//AC LIC delivers a high energy density of 90.47 Wh kg−1 (at 26.28 W kg−1), a high power density of 504.94 W kg−1 (at 38.31 Wh kg−1), and a remarkable cyclic stablitiy of 86.3% retention after 5000 cycles. This research is expected to provide valuable insights into the design of conversion-type electrode materials for future energy storage applications.

Joint attention (JA), a core deficit in children with autism spectrum disorder (ASD), is crucial for social interaction, emotional understanding, and cognitive development. This study aims to compare and analyze the eye-tracking data of ASD and typically developing children (TDC) during virtual games, exploring how different cue types affect JA performance in ASD children. A total of 31 TDC and 40 ASD children participated in the study. Using eye-tracking devices, we recorded the children’s eye movements as they played virtual games, selecting the correct target based on cues provided by virtual characters. Our findings revealed that different cue types significantly impacted the game scores of ASD children but had no significant effect on TDC, highlighting a notable disparity between the two groups. ASD children showed a lower fixation frequency, irregular fixation paths, and increased attention to non-target objects compared to TDC. Interestingly, among the three cue types, ASD children exhibited a preference for the third type, leading to longer fixation on the region of interest and higher game scores. These results underscore the importance of cue selection in enhancing JA in ASD children. This study provides novel insights into the JA deficits in ASD children and offers a scientific basis for the development of targeted and individualized intervention programs.

The differential distribution of original rock stress and stress concentration caused by the variation in coal seam depth in karst topography are critical factors influencing the selection of roof-cutting parameters. Based on this, this study explores a method to determine reasonable roof-cutting parameters by incorporating the characteristics of coal seam depth variation in karst mountainous areas. A mechanical model of the cantilever beam structure for roof cutting in gob-side entry retention (GSER) is constructed, and the critical values and reasonable ranges of roof-cutting height and angle under different burial depths are derived. Furthermore, the displacement and stress evolution characteristics of surrounding rocks in gob-side entry retention under different coal seam burial depths, roof-cutting heights, and roof-cutting angles within the reasonable range of roof-cutting parameters are analyzed. The results show that there is a positive correlation between roof-cutting height and tensile stress in the uncut portion of the main roof, while roof-cutting angle and coal seam depth are negatively correlated with tensile stress. From the perspective of impact, roof-cutting height has a greater impact than roof-cutting angle, followed by coal seam depth. As for the distribution characteristics of the reasonable roof-cutting parameter range, the fan-shaped area of reasonable roof-cutting parameters gradually decreases with increasing coal seam depth. Taking the geological conditions of Anshun Coal Mine as an example, when the burial depth increases from 350 m to 550 m, adjusting the roof-cutting height to 6 m, 7 m, and 8 m, respectively, and setting the roof-cutting angle at 10° can effectively achieve the stability of the surrounding rock in the GSER. The research findings can provide a scientific basis and engineering references for selecting roof-cutting parameters in mines with similar geological conditions.

Diabetic retinopathy (DR) is a leading cause of blindness, yet its molecular mechanisms are unclear. Extracellular vesicles (EVs) contribute to dysfunction in DR, but the characteristics and functions of vitreous EVs are unclear. This study investigated the inflammatory properties of type 2 diabetic (db) vitreous EVs. EVs isolated from the vitreous of db and non-db donors were used for nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), immunogold staining, Western blotting, and proteomic analysis by mass spectrometry. Intracellular uptake of vitreous EVs by differentiated macrophages was evaluated using ExoGlow membrane labeling, and the impact of EVs on macrophage (THP-1) activation was assessed by cytokine levels using RT-qPCR. NTA and TEM analysis of db and non-db vitreous EVs showed non-aggregated EVs with a heterogeneous size range below 200 nm. Western blot detected EV markers (Alix, Annexin V, HSP70, and Flotillin 1) and an upregulation of Cldn5 in db EVs. While the db EVs were incorporated into macrophages, treatment of THP-1 cells with db EVs significantly increased mRNA levels of TNFα and IL-1β compared to non-db EVs. Proteomic and gene enrichment analysis indicated pro-inflammatory characteristics of db EVs. Our results suggest a potential involvement of EC-derived Cldn5+ EVs in triggering inflammation, offering a novel mechanism involved and presenting a possible therapeutic avenue for DR.

The fast and accurate reconstruction of the turbulence phase is crucial for compensating atmospheric disturbances in free-space coherent optical communication. Traditional methods suffer from slow convergence and inadequate phase reconstruction accuracy. This paper introduces a deep learning-based approach for atmospheric turbulence phase reconstruction, utilizing light intensity images affected by turbulence as the basis for feature extraction. The method employs extensive light intensity-phase samples across varying turbulence intensities for training, enabling phase reconstruction from light intensity images. The trained U-Net model reconstructs phases for strong, medium, and weak turbulence with an average processing time of 0.14 s. Simulation outcomes indicate an average loss function value of 0.00027 post-convergence, with a mean squared error of 0.0003 for individual turbulence reconstructions. Experimental validation yields a mean square error of 0.0007 for single turbulence reconstruction. The proposed method demonstrates rapid convergence, robust performance, and strong generalization, offering a novel solution for atmospheric disturbance correction in free-space coherent optical communication.

The galvanic dissolved oxygen sensor finds widespread applications in multiple critical fields due to its high precision and excellent stability. As its core sensing components, the oxygen-permeable membrane, electrode, and electrolyte significantly impact the sensor’s performance. To systematically investigate the comprehensive effects of these core sensing components on the performance of galvanic dissolved oxygen sensors, this study selected six types of oxygen-permeable membranes made from two materials (Perfluoroalkoxy Polymer (PFA) and Fluorinated Ethylene Propylene Copolymer (FEP)) with three thicknesses (0.015 mm, 0.03 mm, and 0.05 mm). Additionally, five concentrations of KCl electrolyte were configured, and four different proportions of lead–tin alloy electrodes were chosen. Single-factor and crossover experiments were conducted using the OxyGuard dissolved oxygen sensor as the experimental platform. The experimental results indicate that under the same membrane thickness conditions, PFA membranes provide a higher output voltage compared to FEP membranes. Moreover, the oxygen permeability of FEP membranes is more significantly affected by temperature. Furthermore, the oxygen permeability of the membrane is inversely proportional to its thickness; the thinner the membrane, the better the oxygen permeability, resulting in a corresponding increase in sensor output voltage. When the membrane thickness is reduced from 0.05 mm to 0.015 mm, the sensor output voltage for PFA and FEP membranes increases by 86% and 74.91%, respectively. However, this study also observed that excessively thin membranes might compromise measurement accuracy. In a saturated, dissolved oxygen environment, the sensor output voltage corresponding to the six oxygen-permeable membranes used in the experiment exhibits a highly linear inverse relationship with temperature (correlation coefficient ≥ 98%). Meanwhile, the lead–tin ratio of the electrode and electrolyte concentration have a relatively minor impact on the sensor output voltage, demonstrating good stability at different temperatures (coefficient of variation ≤ 0.78%). In terms of response time, it is directly proportional to the thickness of the oxygen-permeable membrane, especially for PFA membranes. When the thickness increases from 0.015 mm to 0.05 mm, the response time extends by up to 2033.33%. In contrast, the electrode material and electrolyte concentration have a less significant effect on response time. To further validate the practical value of the experimental results, the best-performing combination of core sensing components from the experiments was selected to construct a new dissolved oxygen sensor. A performance comparison test was conducted between this new sensor and the OxyGuard dissolved oxygen sensor. The results showed that both sensors had the same response time (49 s). However, in an anaerobic environment, the OxyGuard sensor demonstrated slightly higher accuracy by 2.44%. This study not only provides a deep analysis of the combined effects of oxygen-permeable membranes, electrodes, and electrolytes on the performance of galvanic dissolved oxygen sensors but also offers scientific evidence and practical guidance for optimizing sensor design.

Following recovery from the acute infection stage of the SARS-CoV-2 virus (COVID-19), survivors can experience a wide range of persistent Post-Acute Sequelae of COVID-19 (PASC), also referred to as long COVID. According to the US National Research Action Plan on Long COVID 2022, up to 23.7 million Americans suffer from long COVID, and approximately one million workers may be out of the workforce each day due to these symptoms, leading to a USD 50 billion annual loss of salary. Neurological symptoms associated with long COVID result from persistent infection with SARS-CoV-2 in the nasal neuroepithelial cells, leading to inflammation in the central nervous system (CNS). As of today, there is no evidence that vaccines or medications can clear the persistent viral infection in olfactory mucosa. Recently published clinical data demonstrate that only 5% of long COVID anosmia patients have fully recovered during the past 2 years, and 10.4% of COVID patients are still symptomatic 18 months post-infection. Our group demonstrated that epigallocatechin-3-gallate-monopalmitate (EC16m) nanoformulations possess strong antiviral activity against human coronavirus, suggesting that this green-tea-derived compound in nanoparticle formulations could be developed as an intranasally delivered new drug targeting the persistent SARS-CoV-2 infection, as well as inflammation and oxidative stress in the CNS, leading to restoration of neurologic functions. The objective of the current study was to evaluate the mucociliary safety of the EC16m nasal nanoformulations and their efficacy against human coronavirus. Methods: Nanoparticle size and Zeta potential were measured using the ZetaView Nanoparticle Tracking Analysis system; mucociliary safety was determined using the MucilAir human nasal model; contact antiviral activity and post-infection inhibition against the OC43 viral strain were assessed by the TCID50 assay for cytopathic effect on MRC-5 cells. Results: The saline-based EC16 mucoadhesive nanoformulations containing 0.005 to 0.02% w/v EC16m have no significant difference compared to saline (0.9% NaCl) with respect to tissue integrity, cytotoxicity, and cilia beat frequency. A 5 min contact resulted in 99.9% inactivation of β-coronavirus OC43. OC43 viral replication was inhibited by >90% after infected MRC-5 cells were treated with the formulations. Conclusion: The saline-based novel EC16m mucoadhesive nasal nanoformulations rapidly inactivated human coronavirus with mucociliary safety properties comparable to saline, a solution widely used for nasal applications.

Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations’ data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city’s gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China.

Drought stress is the primary abiotic factor affecting wheat growth, development, and yield formation. The application of plant growth-promoting rhizobacteria (PGPR) represents an environmentally sustainable approach to mitigate the impacts of drought stress on wheat. This study conducted field experiments using two winter wheat varieties, the drought-sensitive variety Jimai 22 and the drought-resistant variety Chang 6878, aiming to investigate the effects of Streptomyces pactum Act12 inoculation on photosynthetic characteristics, physiological parameters, and yield traits during the jointing, heading, and middle-filling stages under drought stress. The results revealed that drought stresses significantly reduced chlorophyll content, leaf area, biomass, and yield in wheat, while Act12 inoculation significantly increased chlorophyll content, photosynthetic efficiency, antioxidant enzyme activity such as superoxide dismutase (SOD) and peroxidase (POD), osmolyte content (proline and soluble proteins), and decreased malondialdehyde (MDA) content. These combined effects alleviated drought stress, resulting in increased biomass and yield in wheat. Under drought stress, an increase in leaf proline content of 13.53% to 53.23% (Jimai 22) and 17.17% to 43.08% (Chang 6878) was observed upon Act12 inoculation. Moreover, a decrease in MDA content was recorded of 15.86% to 53.61% (Jimai 22) and 13.47% to 26.21% (Chang 6878). Notably, there was a corresponding increase in yield of 11.78% (Jimai 22) and 13.55% (Chang 6878). In addition, grain quality analysis revealed a significant improvement in grain hardness with Act12 inoculation. Therefore, Act12 demonstrates the potential for enhancing the sustainable development of wheat production in arid and semi-arid regions.

Vaccination-route-dependent adjuvanticity was identified as being associated with the specific features of antigen-carrying nanoparticles (NPs) in the present work. Here, we demonstrated that the mechanical properties and the decomposability of NP adjuvants play key roles in determining the antigen accessibility and thus the overall vaccine efficacy in the immune system when different vaccination routes were employed. We showed that soft nano-vaccines were associated with more efficient antigen uptake when administering subcutaneous (S.C.) vaccination, while the slow decomposition of hard nano-vaccines promoted antigen uptake when intravenous (I.V.) vaccination was employed. In comparison to the clinically used aluminum (Alum) adjuvant, the NP adjuvants were found to stimulate both humoral and cellular immune responses efficiently, irrespective of the vaccination route. For vaccination via S.C. and I.V. alike, the NP-based vaccines show excellent protection for mice from Staphylococcus aureus (S. aureus) infection, and their survival rates are 100% after lethal challenge, being much superior to the clinically used Alum adjuvant.

A recent estimate indicates that up to 23.7 million Americans suffer from long COVID, and approximately one million workers may be out of the workforce each day due to associated symptoms, leading to a USD 50 billion annual loss of salary. Post-COVID (Long COVID) neurologic symptoms are due to the initial robust replication of SARS-CoV-2 in the nasal neuroepithelial cells, leading to inflammation of the olfactory epithelium (OE) and the central nervous system (CNS), and the OE becoming a persistent infection site. Previously, our group showed that Epigallocatechin-3-gallate-palmitate (EC16) nanoformulations possess strong antiviral activity against human coronavirus, suggesting this green tea-derived compound in nanoparticle formulations could be developed as an intranasally delivered new drug to eliminate the persistent SARS-CoV-2 infection, leading to restored olfactory function and reduced inflammation in the CNS. The objective of the current study was to determine the compatibility of the nanoformulations with human nasal primary epithelial cells (HNpECs). Methods: Nanoparticle size was measured using the ZetaView Nanoparticle Tracking Analysis (NTA) system; contact antiviral activity was determined by TCID50 assay for cytopathic effect on MRC-5 cells; post-infection inhibition activity was determined in HNpECs; and cytotoxicity for these cells was determined using an MTT assay. The rapid inactivation of OC43 (a β-coronavirus) and 229E (α-coronavirus) viruses was further characterized by transmission electron microscopy. Results: A saline-based nanoformulation containing 0.1% w/v EC16 was able to inactivate 99.9999% β-coronavirus OC43 on direct contact within 1 min. After a 10-min incubation of infected HNpECs with a formulation containing drug-grade EC16 (EGCG-4′ mono-palmitate or EC16m), OC43 viral replication was inhibited by 99%. In addition, all nanoformulations tested for their effect on cell viability were comparable to normal saline, a regularly used nasal irrigation solution. A 1-min incubation of an EC16 nanoformulation with either OC43 or 229E showed an altered viral structure. Conclusion: Nanoformulations containing EC16 showed properties compatible with nasal application to rapidly inactivate SARS-CoV-2 residing in the olfactory mucosa and to reduce inflammation in the CNS, pending additional formulation and safety studies.

In recent years, virtual reality technology, which is able to simulate real-life environments, has been widely used in the field of intervention for individuals with autism and has demonstrated distinct advantages. This review aimed to evaluate the impact of virtual reality technology on safety skills intervention for individuals with autism. After searching and screening three databases, a total of 20 pertinent articles were included. There were six articles dedicated to the VR training of street-crossing skills for individuals with autism, nine articles focusing on the training of driving skills for individuals with ASD, and three studies examining the training of bus riding for individuals with ASD. Furthermore, there were two studies on the training of air travel skills for individuals with ASD. First, we found that training in some complex skills (e.g., driving skills) should be selected for older, high-functioning individuals with ASD, to determine their capacity to participate in the training using scales or questionnaires before the intervention; VR devices with higher levels of immersion are not suitable for younger individuals with ASD. Second, VR is effective in training safety skills for ASD, but there is not enough evidence to determine the relationship between the level of VR immersion and intervention effects. Although the degree of virtual reality involvement has an impact on the ability of ASD to be generalized to the real world, it is important to ensure that future virtual reality settings are realistic and lifelike. Again, adaptive models that provide personalized training to individuals with ASD in VR environments are very promising, and future research should continue in this direction. This paper also discusses the limitations of these studies, as well as potential future research directions.

Nanoparticles have been identified in numerous studies as effective antigen delivery systems that enhance immune responses. However, it remains unclear whether this enhancement is a result of increased antigen uptake when carried by nanoparticles or the adjuvanticity of the nanoparticle carriers. Consequently, it is important to quantify antigen uptake by dendritic cells in a manner that is free from artifacts in order to analyze the immune response when antigens are carried by nanoparticles. In this study, we demonstrated several scenarios (antigens on nanoparticles or inside cells) that are likely to contribute to the generation of artifacts in conventional fluorescence-based quantification. Furthermore, we developed the necessary assay for accurate uptake quantification. PLGA NPs were selected as the model carrier system to deliver EsxB protein (a Staphylococcus aureus antigen) in order to testify to the feasibility of the established method. The results showed that for the same antigen uptake amount, the antigen delivered by PLGA nanoparticles could elicit 3.6 times IL-2 secretion (representative of cellular immune response activation) and 1.5 times IL-12 secretion (representative of DC maturation level) compared with pure antigen feeding. The findings above give direct evidence of the extra adjuvanticity of PLGA nanoparticles, except for their delivery functions. The developed methodology allows for the evaluation of immune cell responses on an antigen uptake basis, thus providing a better understanding of the origin of the adjuvanticity of nanoparticle carriers. Ultimately, this research provides general guidelines for the formulation of nano-vaccines.

Keratoconus (KC) is characterized by localized, central thinning and cone-like protrusion of the cornea. Its precise etiology remains undetermined, although both genetic and environmental factors are known to contribute to disease susceptibility. Due to KC’s complex nature, there is currently no ideal animal model to represent both the corneal phenotype and underlying pathophysiology. Attempts to establish a KC model have involved mice, rats, and rabbits, with some additional novel animals suggested. Genetic animal models have only been attempted in mice. Similarly, spontaneously occurring animal models for KC have only been discovered in mice. Models generated using chemical or environmental treatments have been attempted in mice, rats, and rabbits. Among several methods used to induce KC in animals, ultraviolet radiation exposure and treatment with collagenase are some of the most prevalent. There is a clear need for an experimental model animal to elucidate the underlying mechanisms behind the development and progression of keratoconus. An appropriate animal model could also aid in the development of treatments to slow or arrest the disorder.

The utilization of Fiber-Reinforced Polymer (FRP) rods to strengthen concrete beam structures can enhance their ultimate load-carrying capacity and mitigate steel reinforcement corrosion damage. However, a prominent issue with BFRP (Basalt FRP) rod reinforcement in flexural members is its lack of yielding behavior, which can lead to catastrophic brittle failure without any preventive measures. Therefore, this study aims to enhance the ductility of concrete by introducing a specific quantity of basalt fiber, thereby reducing the hazards associated with the brittle failure of this composite structure. This experiment focuses on two main variables: the inclusion rate of basalt fiber and the type of longitudinal reinforcement and conducts four-point static bending tests on four BFRP bar BFRC (Basalt-Fiber-Reinforced Concrete) beams. Results showed that the inclusion of fibers resulted in a delayed initiation of vertical cracks and a reduction in the severity of beam failure, thereby enhancing structural safety and reliability. When the basalt fiber inclusion rate was 0.2%, the cracking load and ultimate load of the beam increased by 18.42% and 8.27%, respectively. Furthermore, compared to traditional RC beams, BFRP bar BFRC beams showed a 58.27% increase in ultimate load capacity. A cracking moment calculation model for BFRP beams is proposed and subsequently validated through the utilization of existing experimental data.

Highly sensitive staphylococcal enterotoxin B (SEB) assay is of great importance for the prevention of toxic diseases caused by SEB. In this study, we present a gold nanoparticle (AuNP)-linked immunosorbent assay (ALISA) for detecting SEB in a sandwich format using a pair of SEB specific monoclonal antibodies (mAbs) performed in microplates. First, the detection mAb was labeled with AuNPs of different particle sizes (15, 40 and 60 nm). Then the sandwich immunosorbent assay for SEB detection was performed routinely in a microplate except for using AuNPs-labeled detection mAb. Next, the AuNPs adsorbed on the microplate were dissolved with aqua regia and the content of gold atoms was determined by graphite furnace atomic absorption spectrometry (GFAAS). Finally, a standard curve was drawn of the gold atomic content against the corresponding SEB concentration. The detection time of ALISA was about 2.5 h. AuNPs at 60 nm showed the highest sensitivity with an actual measured limit of detection (LOD) of 0.125 pg/mL and a dynamic range of 0.125–32 pg/mL. AuNPs at 40 nm had an actual measured LOD of 0.5 pg/mL and a dynamic range of 0.5 to 128 pg/mL. AuNPs at 15 nm had an actual measured LOD of 5 pg/mL, with a dynamic range of 5–1280 pg/mL. With detection mAb labeled with AuNPs at 60 nm, ALISA’s intra- and interassay coefficient variations (CV) at three concentrations (2, 8, and 20 pg/mL) were all lower than 12% and the average recovery level was ranged from 92.7% to 95.0%, indicating a high precision and accuracy of the ALISA method. Moreover, the ALISA method could be successfully applied to the detection of various food, environmental, and biological samples. Therefore, the successful establishment of the ALISA method for SEB detection might provide a powerful tool for food hygiene supervision, environmental management, and anti-terrorism procedures and this method might achieve detection and high-throughput analysis automatically in the near future, even though GFAAS testing remains costly at present.

New CMOS imaging sensor (CIS) techniques in smartphones have helped user-generated content dominate our lives over traditional DSLRs. However, tiny sensor sizes and fixed focal lengths also lead to more grainy details, especially for zoom photos. Moreover, multi-frame stacking and post-sharpening algorithms would produce zigzag textures and over-sharpened appearances, for which traditional image-quality metrics may over-estimate. To solve this problem, a real-world zoom photo database is first constructed in this paper, which includes 900 tele-photos from 20 different mobile sensors and ISPs. Then we propose a novel no-reference zoom quality metric which incorporates the traditional estimation of sharpness and the concept of image naturalness. More specifically, for the measurement of image sharpness, we are the first to combine the total energy of the predicted gradient image with the entropy of the residual term under the framework of free-energy theory. To further compensate for the influence of over-sharpening effect and other artifacts, a set of model parameters of mean subtracted contrast normalized (MSCN) coefficients are utilized as the natural statistics representatives. Finally, these two measures are combined linearly. Experimental results on the zoom photo database demonstrate that our quality metric can achieve SROCC and PLCC over 0.91, while the performance of single sharpness or naturalness index is around 0.85. Moreover, compared with the best tested general-purpose and sharpness models, our zoom metric outperforms them by 0.072 and 0.064 in SROCC, respectively.

The recognition of submarine cable magnetic anomaly (SCMA) signals is a challenging task in magnetic signal data processing. In this study, a multi-task convolutional neural network (MTCNN) model is proposed to simultaneously recognize abnormal signals and locate abnormal regions. The residual block is added to the shared feature backbone to improve the ability of the network to extract high-level features and maintain the gradient stability of the model in the training process. The long short-term memory (LSTM) block is added to the classification branch task to learn the internal relationship of the magnetic anomaly time series, so as to improve the network’s ability to recognize magnetic anomalies. Our proposed model can accurately recognize the SCMA signals collected in the East China Sea and the South China Sea. The classification accuracy and the ability to locate the abnormal regions are close to the manual labeling of human analysts. The newly developed model can help analysts reduce the probability of missing and misjudging submarine cable magnetic anomalies, improve the efficiency and accuracy of interpretation, and could even be deployed to an unmanned platform to realize the automatic detection of SCMAs.

Rapidly completing the exploration and construction of unknown environments is an important task of a UAV cluster. However, the formulation of an online autonomous exploration strategy based on a real-time detection map is still a problem that needs to be discussed and optimized. In this paper, we propose a distributed unknown environment exploration framework for a UAV cluster that comprehensively considers the path and terminal state gain, which is called the Distributed Next-Best-Path and Terminal (DNBPT) method. This method calculates the gain by comprehensively calculating the new exploration grid brought by the exploration path and the guidance of the terminal state to the unexplored area to guide the UAV’s next decision. We propose a suitable multistep selective sampling method and an improved Discrete Binary Particle Swarm Optimization algorithm for path optimization. The simulation results show that the DNBPT can realize rapid exploration under high coverage conditions in multiple scenes.

Clinical trials have shown that electric stimulation (ELSM) using either cardiac resynchronization therapy (CRT) or cardiac contractility modulation (CCM) approaches is an effective treatment for patients with moderate to severe heart failure, but the mechanisms are incompletely understood. Extracellular vesicles (EV) produced by cardiac mesenchymal stem cells (C-MSC) have been reported to be cardioprotective through cell-to-cell communication. In this study, we investigated the effects of ELSM stimulation on EV secretion from C-MSCs (C-MSCELSM). We observed enhanced EV-dependent cardioprotection conferred by conditioned medium (CM) from C-MSCELSM compared to that from non-stimulated control C-MSC (C-MSCCtrl). To investigate the mechanisms of ELSM-stimulated EV secretion, we examined the protein levels of neutral sphingomyelinase 2 (nSMase2), a key enzyme of the endosomal sorting complex required for EV biosynthesis. We detected a time-dependent increase in nSMase2 protein levels in C-MSCELSM compared to C-MSCCtrl. Knockdown of nSMase2 in C-MSC by siRNA significantly reduced EV secretion in C-MSCELSM and attenuated the cardioprotective effect of CM from C-MSCELSM in HL-1 cells. Taken together, our results suggest that ELSM-mediated increases in EV secretion from C-MSC enhance the cardioprotective effects of C-MSC through an EV-dependent mechanism involving nSMase2.

Land use change affects soil aggregate composition and stability, which impacts soil structure and health. To reveal how land use change impacted soil aggregates of alpine grassland in a high-altitude watershed, soil samples from 161 sites including alpine grassland, cropland and abandoned land were selected to measure and analyze the distribution of aggregate fractions (macro-aggregates, micro-aggregates, silt+clay), soil aggregate stability (mean weight diameter, geometric mean diameter, fractal dimension, etc.) and related soil properties (soil organic carbon content, soil particle composition, etc.) in the Huangshui River watershed of the Qinghai–Tibet Plateau. The results showed: (1) As alpine grasslands were converted to croplands and croplands to abandoned lands, the proportion of macro-aggregates and the aggregate stability index showed a trend of first decreasing and then increasing (p < 0.05), indicating that tillage and abandonment have significant influences on soil aggregate structure. (2) Compared with temperate grassland, alpine grassland had richer soil organic carbon, and a higher ratio of macro-aggregates and aggregate stability. (3) Soil organic carbon and sand content had distinct influences on the fractions and stability of aggregates during land use change. These results suggested that cultivation can substantially reduce the soil aggregate stability in alpine grassland, whereas abandonment can effectively improve soil aggregate structure.

In cryogenic fluid storage and delivery, the rapid contraction and rebound of bubbles are prone to occur during bubble collapse due to the pressure saltation. With the contraction and rebound of bubbles, the pressure and temperature in the bubbles fluctuate greatly, which affects the service life of fluid machinery. During bubble contraction and rebound, there is an accompanied complex heat and mass transfer process. According to the thermal properties of cryogenic fluids, a single-bubble collapse model is proposed considering the temperature variations inside the bubble. In order to study the variation in temperature and pressure during bubble collapse in cryogenic fluids, the contraction and rebound of a single bubble in liquid hydrogen are investigated numerically under various operating pressures and supercooling degrees. The numerical results of the model indicate that there are periodic contraction and rebound of the bubble when the pressure rises suddenly. Furthermore, the periods and attenuation rates of bubbles in different media are studied and compared. For the most concerned pressure and temperature characteristics, the relationship between the peak pressure, the attenuation rate of the temperature and the dimensionless number is proposed.

Steel plate shear walls (SPSW) structures have been widely employed in multistory residential buildings. The traditional welding process may lead to serious welding deformation due to the thinness of the plate. In this study, a new welding process is proposed to ensure that the stiffeners and SPSWs bend as a whole, and the number of welds is reduced from 3 to 2. This process has better integrity than the traditional process owing to less welding residual stress and deformation. On the basis of low-cycle reciprocating load tests on four full-scale specimens, the shear failure pattern, hysteresis characteristics, and load-carrying capacity of SPSWs affected by the new process are studied, and the new welding process used in the vertical stiffener can meet the requirements of shear capacity. The influences of various parameters on the shear resistance of the SPSWs made by the new welding process are compared and analyzed. The results indicate that the lateral stiffness of the frame and the width–height ratios of the wall significantly influence the load-carrying capacity of the SPSWs. The SPSWs adopting the new manufacturing process are numerically simulated using ANSYS software. The same conclusions can be obtained by comparing the numerical results with the experimental results.

Accurately mastering the power transmission characteristics of the cutting arm transmission shaft system is key to improving the reliability and working capacity of the cantilever roadheader. Based on the rigid–flexible coupling vibration characteristic modeling of the roadheader cutting arm, the vibration characteristics of different substructures in the transmission shaft system of the roadheader cutting arm were considered, the dynamic characteristic model was comprehensively constructed, and the numerical analysis was carried out with the parameters of the XTR260 tunnel hard rock roadheader to compare the vibration characteristics of the cutting head under different cutting conditions. The experiment was carried out by using an artificial concrete wall, and the measurement results verify the established dynamic model that lays the foundation for the dynamic design of a high-performance roadheader.

Human living environments and health are seriously affected by the odor produced from fermentation of livestock and poultry manure. In order to reduce the odor pollution caused by livestock and poultry manure, efficient strains were screened and two methods were tried in this study. The orthogonal test design was used to analyze the gas produced by pig manure under different conditions of temperature, time, wheat straw doping amount and calcium carbonate doping amount. Then, according to ammonia, hydrogen sulfide and comprehensive odor removal effects, the high efficiency of deodorizing strains were screened. The results showed that pig manure produced the least odor when the temperature was 20 °C, added 0% calcium carbonate, 20% wheat straw and waited for 48 h. Three strains were screened to inhibit the odor production of pig manure: Paracoccus denitrificans, Bacillus licheniformis and Saccharomyces cerevisiae, showed that their highest removal rate of ammonia and hydrogen sulfide gas could reach 96.58% and 99.74% among them; while for three strains of end-control pig manure stench: Pichia kudriavzevii, P. denitrificans and Bacillus subtilis, the highest removal rate of ammonia and hydrogen sulfide gas reached 85.91% and 90.80% among them. This research provides bacteria resources as the high-efficiency deodorizing function for the source suppression and the end treatment of the odor gas of pig manure, which has high application value for the control of odor pollution.

Electrostatic voltage is a vital parameter in industrial production lines, for reducing electrostatic discharge harms and improving yields. Due to such drawbacks as package shielding and low resolution, previously reported electric field microsensors are still not applicable for industrial static monitoring uses. In this paper, we introduce a newly designed microsensor package structure, which enhances the field strength inside the package cavity remarkably. This magnification effect was studied and optimized by both theoretical calculation and ANSYS simulation. By means of the digital synthesizer and digital coherent demodulation method, the compact signal processing circuit for the packaged microsensor was also developed. The meter prototype was calibrated above a charged metal plate, and the electric field resolution was 5 V/m, while the measuring error was less than 3 V, from −1 kV to 1 kV in a 2 cm distance. The meter was also installed into a production line and showed good consistency with, and better resolution than, a traditional vibratory capacitance sensor.

Pomelo is rich in bioactive compounds (carotenoids, phenolics and essential oil) in the early stage of fruit development, but it is often wasted in the cultivation and management process. To gain an insight into the carotenoid metabolism pathway in pomelo, the carotenoid profiles and the expression patterns of carotenogenic genes were investigated in two genotypes of pomelo during early fruit development. The results showed that a higher carotenoid content was observed in honey pomelo as compared with golden pomelo, which may be related to different gene regulation mechanisms. Lutein, α-carotene, and β-carotene were the main carotenoids in pomelo young fruit, and lutein was the highest one. The accumulation of carotenoids during fruit early development in honey pomelo is related to the transcriptional regulation of ZISO and LUT5. In golden pomelo, the rate-limiting gene for carotenoids is PDS and ZDS. In addition, the expression of seven genes except CRTISO in honey pomelo was higher than that in golden pomelo. The results are helpful to further clarify the regulatory mechanism of carotenoid accumulation during early fruit development and provide a direction for the high-value utilization of young fruits in pomelo.

Pomelo is an important cultivar of the genus Citrus that contains a variety of beneficial nutrients, and its young fruit is an agricultural by-product that is currently not fully utilized because it is often thrown away during cultivation and management. In this study, the dynamics of tocochromanol during young pomelo development were investigated by measuring chlorophyll content, tocochromanol accumulation, and expression levels of related genes during early fruit development. The results showed that chlorophyll content decreased overall during these four developmental stages and had some synergism with tocochromanol. Four tocochromanol components were detected in pomelo of both genotypes, and α-tocopherol was the main component. The tocochromanol content of honey pomelo was highest in the first period, reaching 70 ± 5 μg/g in dry weight (DW), and golden pomelo peaked in the second period at 86.10 ± 0.18 μg/g DW, with an overall decreasing trend in both genotypes. The different gene expression patterns of the tocochromanol biosynthesis pathway could partially explain the changes in these components and further elucidate the regulatory mechanisms of tocochromanol accumulation during early fruit development. As a natural product, young pomelo fruit is an attractive source of tocochromanol and has potential application in industrial production. The results of this study may provide directions for the high additional value utilization of young pomelo fruit.

Women are at a significantly higher risk of developing osteoarthritis (OA) compared to males. The pathogenesis of osteoarthritis (OA) in women is poorly understood. Extracellular vesicles (EVs) have been shown to play an essential role in numerous signaling processes during the pathogenesis of age-related diseases via paracrine signaling. Molecular profiling of the synovial fluid-derived EVs cargo in women may help in the discovery of novel biomarkers and therapeutics for the treatment of OA in women. Previously, we reported that synovial fluid-derived EV miRNA cargo differs in a sex-specific manner. This study aims to characterize synovial fluid-derived EV protein cargo in OA patients. Our data showed sex-specific EVs protein content in OA. We found haptoglobin, orosomucoid, and ceruloplasmin significantly up-regulated, whereas apolipoprotein down-regulated in female OA EVs. In males, we discovered β-2-glycoprotein, and complement component 5 proteins significantly up-regulated and Spt-Ada-Gcn5 acetyltransferase (SAGA)-associated factor 29 down-regulated in male OA EVs. Database for Annotation, Visualization, and Integrated Discovery (DAVID) and QuickGO analysis revealed OA-specific protein involvement in several biological, molecular, and cellular pathways, specifically in inflammatory processes. In conclusion, synovial fluid EV protein content is altered in a sex-specific manner with OA, explaining the increased prevalence and severity of OA in women.

Fertilization influences the soil microbiome. However, little is known about the effects of long-term fertilization on soil microbial metabolic pathways. In this study, we investigated the soil microbiome composition and function and microbial participation in the N cycle according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) functional annotation of different genes in a metagenomic analysis after long-term fertilization. Fertilizer application significantly changed the soil C/N ratio. Chemical fertilizer (NPK) treatment decreased soil pH, and chemical fertilizer combined with straw (NPK+S0.5) treatment increased ammonium nitrogen (NH4+-N) but decreased nitrate nitrogen (NO3−-N). NPK, NPK+S0.5 and S0.5 applications did not change the soil microbiome composition or dominant phylum but changed the relative abundances of microbiome components. Moreover, fertilizer significantly influenced metabolic processes, cellular processes and single-organism processes. Compared with a no-fertilizer treatment (CK), the NPK treatment resulted in more differentially expressed gene (DEG) pathways than the NPK+S0.5 and S0.5 treatments, and these pathways significantly correlated with soil nitrate nitrogen (NO3−-N), available phosphorus (AP) and the moisture content of soil (MC). KEGG analysis found that fertilizer application mainly affected the ribosome, photosynthesis and oxidative phosphorylation pathways. S0.5 and NPK+S0.5 increased microbial nitrogen fixation, and NPK and NPK+S0.5 decreased amoA and amoB and accelerated denitrification. Thus, organic fertilizer increased N fixation and nitrification, and inorganic N fertilizer accelerated denitrification. We found that the function of the soil microbiome under different fertilizer applications could be important for the rational application of fertilizer and for environmental and sustainable development.

During hydraulic fracturing, there is a temperature difference between the injected water and formation rock for shale gas wells. The objective of this study is to investigate how this temperature difference changes with time, and how it affects multiphase-flow modeling during the shut-in and flowback periods. We conducted numerical simulations to investigate the behaviors of fracture temperature in shale gas wells. The results show a significant increase in fracture temperature during the shut-in and flowback periods. Sensitivity analysis suggests that this temperature increase is strongly related to the thermal conductivity of formation rock, matrix permeability, and initial reservoir temperature. Simulation scenarios were further compared to investigate the effect of temperature on flowback data analysis. Without considering the thermal effect, flowback data analysis may yield an earlier fracture cleanup and overestimated fracture volume. In addition, this study suggests that the thermal effect may also have implications for optimizing flowback operations.