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In the preparation of large-sized ceramics, the use of a green body with relatively high plasticity is crucial to minimize the risk of cracking during processing. To achieve this goal, glycerol and polyethylene glycol (PEG) were utilized as plasticizers in the shaping of green bodies of oxide ceramics through spontaneous coagulation casting (SCC). This study investigated the effects of plasticizers and particle sizes ranging from the submicron to nanoscale on the slurry viscosity, drying shrinkage of wet gels, and mechanical properties of green bodies. The plasticity of the green bodies was assessed by measuring the impact toughness and flexural stress‒strain curves. By incorporating an appropriate plasticizer, the peak width of the flexural stress‒strain curve for dried green bodies from particles of different sizes was nearly twice that without plasticizers, and the impact toughness was enhanced by approximately 71%, 34%, and 41% when the particle size decreased from the submicron scale to the nanoscale (0.45 μm, 0.18 μm, and 50 nm, respectively). The drilling test revealed that there was nearly no cracking around the holes in the green bodies with plasticizers. The plasticity mechanism of the green bodies was examined based on ultraviolet–visible (UV–Vis) spectroscopy and scanning electron microscopy (SEM). It was discovered that plasticizers might mitigate the brittleness of green bodies by adjusting the interactions between molecules and modifying the gel network properly.

Objectives Older individuals with multimorbidity are at an elevated risk of infection and complications from COVID-19. Effectiveness of post-COVID-19 interventions or care models in reducing subsequent adverse outcomes in these individuals have rarely been examined. This study aims to examine the effectiveness of attending general outpatient within 30 days after discharge from COVID-19 on 1-year survival among older adults aged 85 years or above with multimorbidity.Design Retrospective cohort study emulating a randomised target trial using electronic health records.Setting We used data from the Hospital Authority and the Department of Health in Hong Kong, which provided comprehensive electronic health records, COVID-19 confirmed case data, population-based vaccination records and other individual characteristics for the study.Participants Adults aged 85 years or above with multimorbidity who were discharged after hospitalisation for COVID-19 between January 2020 and August 2022.Interventions Attending a general outpatient within 30 days of last COVID-19 discharge defined the exposure, compared to no outpatient visit.Main outcome measures Primary outcome was all-cause mortality within one year. Secondary outcomes included mortality from respiratory, cardiovascular and cancer causes.Results A total of 6183 eligible COVID-19 survivors were included in the analysis. The all-cause mortality rate following COVID-19 hospitalisation was lower in the general outpatient visit group (17.1 deaths per 100 person-year) compared with non-visit group (42.8 deaths per 100 person-year). After adjustment, primary care consultations within 30 days after discharge were associated with a significantly greater 1-year survival (difference in 1-year survival: 11.2%, 95% CI 8.1% to 14.4%). We also observed significantly better survival from respiratory diseases in the general outpatient visit group (difference in 1-year survival: 6.3%, 95% CI 3.5% to 8.9%). In a sensitivity analysis for different grace period lengths, we found that the earlier participants had a general outpatient visit after COVID-19 discharge, the better the survival.Conclusions Timely primary care consultations after COVID-19 hospitalisation may improve survival following COVID-19 hospitalisation among older adults aged 85 or above with multimorbidity. Expanding primary care services and implementing follow-up mechanisms are crucial to support this vulnerable population’s recovery and well-being.

Abstract Interplanetary shocks (IPS) can initiate prompt acceleration of relativistic electrons in the Earth's radiation belt, which is related to the generation and propagation of impulsive electric field (IEF). We investigate the effect of IEF on accelerating radiation belt electrons in the 6 September 2017 IPS event. A “surfing” effect of electrons with respect to the electric field, referring to electrons that drift together with the tailward‐propagating IEF in the duskside, is investigated in this study. Our results show that the maximum increase of electron differential flux is at 3.4 MeV by a factor of 2.2, corresponding to a drift velocity of 531 km/s, which is more consistent with the IPS propagating speed of 621 km/s rather than the fast‐mode speed of 1,074 km/s. We suggest that the effect of IPS propagation is important for radiation belt dynamics, and we highlight the potential importance of the parameter of IPS propagation speed.

The on-the-fly machine learning force field approach, based on the Gaussian approximation potential and Bayesian error estimation, was used to study the diffusion of self-interstitial atoms in α-zirconium. Ab initio molecular dynamics simulations of lattice vibration and interstitial diffusion at different temperatures were employed to develop the force field. The radial and angular descriptors of the potential were further optimized to achieve better agreement with first-principles results. Subsequent long-term diffusion simulations were performed to assess the diffusion behavior based on the obtained force field. Tracer diffusion coefficients and diffusion anisotropy were studied at temperatures of 600–1200 K, and the Bayesian errors were estimated throughout the diffusion simulations. The mean and maximum estimated Bayesian errors of atomic force were approximately twice as large as those observed during the learning period. The basal diffusion was greatly favored compared to the interstitial diffusion along the c-axis, consistent with previous simulations based on first-principles results and classical potentials. The accuracy and applicability of the current on-the-fly machine learning approach were critically evaluated.

Summary: Background: By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory. Methods: Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age. Findings: A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages. Interpretation: The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively. Funding: The Research Grants Council of Hong Kong under the Early Career Scheme 27110519.

Background: Group 2 innate lymphoid cells (ILC2s) have been found to take part in type 2 inflammation by secreting TH2 cytokines. Apolipoprotein A-I (Apo-AI), a major structural and functional protein of high-density lipoproteins, has anti-inflammatory effects on neutrophils, monocytes, macrophages, and eosinophils. However, its effects on ILC2s are not well characterized. Objective: We aimed to investigate the effect of Apo-AI on the proliferation and function of ILC2s as well as its possible mechanism. Methods: The protein expression of Apo-AI and the percentage of ILC2s in peripheral blood between 20 allergic rhinitis patients and 20 controls were detected by ELISA and flow cytometry. The effect of Apo-AI and miR-155 on ILC2 proliferation and function was detected by tritiated thymidine incorporation and ELISA. Anima models were adopted to verify the effect of Apo-AI in vivo. Results: Elevated expression of Apo-AI was observed in allergic rhinitis patients. Apo-AI promotes ABCA1 expression by ILC2s, which can be inhibited by anti–Apo-AI. Apo-AI decreased ILC2 proliferation and the microRNA levels of GATA3 and RORα from ILC2s. The miR-155 overexpression promoted the upregulation of GATA3 and type II cytokines from ILC2s, while the addition of Apo-AI or miR-155 inhibitor significantly inhibited expression of GATA3 and type II cytokines by ILC2s. Apo-AI−/− mice showed as enhanced allergen-induced airway inflammation. The miR-155 inhibitor can reverse the enhanced allergen-induced airway inflammation in Apo-AI−/− mice, while miR-155 mimics can reverse the decreased allergen-induced airway inflammation in Apo-AI–treated mice. Conclusion: Apo-AI suppressed the proliferation and function of ILC2s through miR-155 in allergic rhinitis. Our data provide new insights into the mechanism of allergen-induced airway inflammation.

With the popularity of edge computing devices and increasing complexity of convolutional neural network (CNN) models, the need for model compression and acceleration has become increasingly urgent. As an effective model compression technique, CANDECOMP/PARAFAC (CP) decomposition relies heavily on the preset rank for its compression effectiveness. However, no direct algorithm is currently available for determining the optimal tensor rank. Therefore, a novel method for CP rank selection based on deep reinforcement learning is proposed. This method utilizes the DecG single-player game framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm to achieve automation and intelligence in rank selection. In this process, a pre-trained model is introduced, which fuses and reshapes several historical tensors as network inputs. Additionally, a hybrid greedy strategy based on singular value decomposition (SVD) was designed in the exploration phase to enhance the efficiency of finding ideal rank selection results. This method can automatically determine the rank according to the weight tensor characteristics of the convolution layer and optimize the compression efficiency and performance of the model. In addition, a compression efficiency index is developed to visually demonstrate the performance of the various compression methods. Finally, on the CIFAR-10 and CIFAR-100 datasets, CP decomposition experiments are conducted on various convolutional neural network models, and the decomposed models undergo iterative fine-tuning for retraining. The experimental results show that the rank values determined by the DecG method achieve significant optimization and enhancement in the compression efficiency of the models compared to other methods, exhibiting strong robustness.

In the process of promoting China’s rural energy reform, there will be a power gap problem, and the power companies will reduce the policy effect in disguise from their interests. To promote clean power supply in rural areas, this paper constructs an evolutionary game model between electric power companies and solar investment companies under the background of energy reform in rural areas, systematically deduces the possible different strategy combinations of both parties, and uses real data to conduct simulation and parameter sensitivity analysis. The results show that: (1) Under the current market mechanism, the system will evolve into (0,0), and there may be four different strategy combinations when government regulation is introduced. (2) Under the condition that the system evolves into the optimal state in the initial state, the local government’s subsidy to the investment company is no less than ¥0.11/kW h, and the penalty to the power company is ¥0.18/ kW h. (3) Compared with power companies, investment companies are more sensitive to government subsidies, so it is suggested that the government pay more attention to subsidies to investment companies. This study can provide theoretical support and policy references for promoting rural energy reform.

Abstract Introduction Sinuvertebral nerve overactivation is one of the mechanisms of neck pain caused by cervical disc herniation. Radiofrequency ablation (RFA) of sinuvertebral nerves has shown efficacy for the treatment of discogenic low back pain. However, relatively few studies evaluated the efficacy of RFA of sinuvertebral nerves for the treatment of chronic neck pain caused by cervical disc herniation. Methods Clinical data were retrospectively collected from 168 patients diagnosed with cervical disc herniated neck pain from January 1, 2019, to September 1, 2022, who were treated with computed tomography (CT)-guided cervical disc RFA of at the Pain Medicine Center of Zhejiang Provincial People’s Hospital. A 22-G RFA needle (Inomed, Emmendingen, Germany) was inserted between the carotid artery and trachea to the intervertebral disc under the direction of CT the scanner. Depending on the position of the protruding nucleus pulposus or the rupture of the annulus fibrosus, the needle was inserted into the posterior side of the intervertebral disc until the tip of the needle reached the target position. The numeric rating scale (NRS) score, pain relief and appearance of complications after RFA were evaluated. Results A total of 168 patients underwent CT-guided RFA for cervical disc herniation. The average duration of pain was 67.07 ± 70.42 months. At 6 months of follow-up, the median preoperative NRS score decreased significantly from preoperative 5.41 ± 1.08 to postoperative 1.341 ± 1.25 at 1 month, 1.4 ± 1.38 at 3 months and 1.72 ± 1.41 at 6 months after RFA (p

Abstract The side‐chain has a significant influence on the optical properties and aggregation behaviors of the organic small molecule acceptors, which becomes an important strategy to optimize the photovoltaic performance of organic solar cells. In this work, we designed and synthesized three brand‐new nonfused ring electron acceptors (NFREAs) OC4‐4Cl‐Ph, OC4‐4Cl‐Th, and OC4‐4Cl‐C8 with hexylbenzene, hexylthiophene, and octyl side chains on the π‐bridge units. Compared with OC4‐4Cl‐Ph and OC4‐4Cl‐Th, OC4‐4Cl‐C8 with linear alkyl side chain has more red‐shift absorption, which is conducive to obtaining higher short‐circuit current density. Additionally, the OC4‐4Cl‐C8 film exhibits a longer exciton diffusion distance, and the D18:OC4‐4Cl‐C8 blend film displays faster hole transfer, weaker bimolecular recombination, and more efficient exciton transport. Furthermore, The D18:OC4‐4Cl‐C8 blend films may effectively form interpenetrating networks that resemble nanofibrils, which can facilitate exciton dissociation and charge transport. Finally, OC4‐4Cl‐C8‐based devices can be created a marvellously power conversion efficiency (PCE) of 16.56%, which is much higher than OC4‐4Cl‐Ph (12.29%)‐ and OC4‐4Cl‐Th‐based (11.00%) ones, being the highest PCE among the NFREA based binary devices. All in all, we have validated that side‐chain engineering is an efficient way to achieve high‐performance NFREAs.

X-linked adrenoleukodystrophy (X-ALD) is a rare genetic disorder caused by pathogenic variants in the ABCD1 gene. The symptoms include primary adrenal insufficiency (PAI), progressive spinal cord disease, inflammatory demyelinating cerebral disease, and primary hypogonadism. It is exceptionally rare that pediatric PAI is accompanied by central precocious puberty (CPP). The purpose of this study was to better understand the diversity of clinical manifestations of X-ALD and to identify the ABCD1 gene mutation in a case of a boy with X-ALD accompanied by CPP. We collected clinical, laboratory and imaging data, and used whole-exome sequencing (WES) analysis to evaluate the pathogenicity of the variant. We also predicted the potential deleterious effects of the novel mutation using Mutation Taster and generated three-dimensional protein structures using Swiss-Model and PyMOL Viewer software. The patient presented with PAI accompanied by CPP. Adrenal gland CT revealed adrenal hypoplasia. Gonadotropin-releasing hormone stimulation tests revealed CPP. WES revealed a novel variant (c.1376dup) in the ABCD1 gene, which resulted in a reading frameshift and a premature termination codon (p.Leu461ProfsTer95). Sanger sequencing confirmed that the variant was inherited from his heterozygous mother. Mutation Taster predicted that the variant could be harmful. The overall three-dimensional structures of the mutant wild-type proteins were visually distinct. Our results shed light on additional aspects of X-ALD. The premature activation of the hypothalamic-pituitary-gonadal axis may possibly be related to the pathogenic ABCD1 gene mutation.

Abstract Radial diffusion (RD) induced by ULF waves can contribute to particle acceleration and scattering. Past global simulations that incorporate RD often use dipole magnetic fields, which could not realistically reveal the role of RD. To better understand the effects of RD and identify whether a background magnetic field model matters in understanding the ring current dynamics in response to RD, we simulate a storm event with different magnetic configurations using a global kinetic ring current model. Results indicate that RD can effectively diffuse protons of hundreds of keV to inner regions (L ∼ 3.5), especially in recovery phase. Comparisons with in‐situ observations demonstrate that simulations with TS05 overall capture both the intensity and variations of proton fluxes with the aid of RD, whereas that with a dipole field significantly overestimates low‐L region fluxes. This study implies adopting realistic magnetic fields is important for correctly interpreting the role of RD.

A practical method of the carbon emission reduction ratio evaluation of expressway service areas considering future infrastructures is proposed to quantify the carbon emission reduction benefits of advanced power technologies. Taking an expressway service area in Guangxi as an example, based on its new infrastructure and low-carbon micro energy network construction scheme, the carbon emission reduction ratio of the service area is calculated and analyzed. The results show that the majority of carbon emissions in the expressway service area are contributed to electric carbon emissions, while little non-electric carbon emission exists, and there is little impact on the results if non-electric carbon emissions are neglected, which can also simplify the calculation process. This evaluation method takes into account both new loads brought by the new infrastructure and the improvement of the overall energy efficiency in the region by the advanced energy conservation and carbon reduction technologies. Emission reduction benefits can be quickly, intuitively and quantitatively achieved with advanced energy technologies such as distributed renewable energy, integrated energy system and AC/DC mixed supply. The error caused by simplified calculation is so small that is applicable to the early stage of project construction, predict and evaluate the carbon reduction benefits of advanced energy technologies to assist the orientation of the project.

In this study, FeCrCoNiMo0.5W0.75 HEAs functional gradient materials were prepared by the direct energy deposition (DED) technique, and the phase transition, microstructure and mechanical properties of the materials along the building direction were investigated. The material realizes a transition from a single FCC phase to an FCC + TCP phase from the bottom to the top. The bottom and middle of the material are typical dendritic (DR)-interdendritic (ID) structures, and at the top, due to the precipitation of the eutectic structure σ phase and μ phase, the material transforms into a hypoeutectic structure of FCC + eutectic. According to the EBSD results, the interior of the material is mainly columnar crystals that grow vertically to the molten pool. This unidirectional columnar growth makes the material have a strong texture in the direction. In addition, a large degree of grain refinement is exhibited from the bottom to the top, with the grain size reduced from 19 μm to 6.5 μm. According to the TEM results, the density of dislocations is much higher near the phase and grain boundaries than in other regions, and dislocation entanglement is formed by the continuous accumulation of loose dislocations. The micro-hardness of the material increased along the construction direction up to 892.5HV0.5, and the material has good compressive strength up to 2041 ± 45 MPa. The material has excellent wear resistance and high-temperature wear resistance, forming a continuous oxide layer at 800 °C, which greatly reduces the friction coefficient and wear rate.

Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the standardized precipitation index (SPI) and the standardized baseflow index (SBI) for the Jiaojiang River Basin (JRB) using the copula function. The prediction model was established by training random forests on past data, and the driving force behind the combined drought index was explored through the LIME algorithm. The results show that the established composite drought index combines the advantages of SPI and SBI in drought forecasting. The monthly and annual droughts in the JRB showed an increasing trend from 1991 to 2020, but the temporal characteristics of the changes in each subregion were different. The accuracies of the trained random forest model for heavy drought in Baizhiao (BZA) and Shaduan (SD) stations were 83% and 88%, respectively. Furthermore, the Local Interpretable Model-Agnostic Explanations (LIME) interpretation identified the essential precipitation, baseflow, and evapotranspiration features that affect drought. This study provides reliable and valid multivariate indicators for drought monitoring and can be applied to drought prediction in other regions.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

Solar extreme-ultraviolet (EUV) irradiance is the dominant energy source for ionizing and heating the Earth’s upper atmosphere. It is common to assume that the spectra of different EUV lines have the same trend to fill the solar EUV irradiance gap for modeling purposes due to inadequate EUV irradiance measurements. However, the spectra across the EUV bands may not vary in the same trend. The flare radiation energy release in the EUV (10–120 nm) is about twice as much as X-rays (0.1–10 nm) during flare interval ∼03–06 UT on 2012 October 23. By assimilating the observed nonuniform varying, time-dependent, and high-resolution solar spectrum from the Solar Dynamics Observatory mission into the modeling framework, we provide the first direct evidence of nonuniform varying solar EUV fluxes during the solar flare EUV late phase (ELP) having appreciable effects on the dayside ionosphere. The total EUV radiation energy release (5.838 × 10 ^28 erg) during the flare ELP is larger than that (5.698 × 10 ^28 erg) during the flare main phase. The ELP of an X1.8-class solar flare on 2012 October 23 can increase the dayside ionospheric density at the subsolar point by ∼5 TECU and the ionospheric density enhancements extend from the bottom to the peak of the F2 region at low latitudes with relative changes ranging from ∼20% to ∼100%. Our results highlight the importance of incorporating a realistic, high spectral and temporal resolution solar irradiance spectrum into numerical models to capture the observed time-varying ionospheric response to solar flares.

Abstract Background Acute rhinosinusitis (ARS) is one of the common diseases of upper respiratory tract infection in children. Bacterial infection is a significant aggravating factor in pediatric ARS. In this research, our goal was to detected the bacterial flora and antibiotic sensitivity of ARS in Chinese children. Methods We recruited 133 children with ARS between January 2020 and January 2022 from our hospital. Sinus secretion were collected and cultured for Gram stain as well as antimicrobial susceptibility tests. Results Moraxella catarrhalis, Staphylococcus aureus, Haemophilus influenzae, Streptococcus pneumoniae and Pseudomonas aeruginosa were detected in order in children with ARS, of which 25% were negative for bacterial culture and 10% were positive for two strains. Amoxicillin and clavulanate potassium were useful for Haemophilus influenzae, Streptococcus pneumoniae and Moraxella catarrhalis. Quinolones are useful for Staphylococcus aureus, Haemophilus influenzae, Streptococcus pneumoniae and Pseudomonas aeruginosa. Conclusions This research updates the proportion of ARS bacterial infection in children in southern China and the antibiotic sensitivity.

A bioadsorbent with a high specific surface area and high content of oxygen-containing functional groups was prepared from silica depleted rice straw ash (SDRSA). The starting material was a by-product of rice straw after alkoxysilane extraction. The maximum adsorption capacity of SDRSA for copper ions was 26.7 mg/g, which was higher than previously reported biomass adsorbents. The effects of adsorbent dose, pH, contact time, and other conditions on the adsorption performance of SDRSA on Cu2+ were investigated. The adsorption process of Cu2+ on SDRSA was well fitted by the Langmuir isotherm model and the pseudo-second-order kinetic model. The physicochemical properties and adsorption mechanism of SDRSA were investigated by specific surface area testing (BET), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Boehm titration methods. Electrostatic interaction, complexation, ion exchange, and precipitation are the possible Cu2+ removal mechanisms. The preparation method requires only simple washing and drying, and the alcohol can be distilled and recycled. Thus, SDRSA is very low cost and convenient to prepare in large quantities. This work presents a novel approach to optimize adsorbent production to mitigate heavy metal pollution.

To simultaneously solve the problems of low utilization of agricultural waste rice husk and heavy metal pollution, this investigation synthesized a high-performance copper ion adsorbent using rice husk ash(RA) as raw material. Its maximum Cu2+ adsorption capacity is 19.78 mg/g. XPS, FTIR, and BET were used to characterize the composition and structure of the material of silica depleted rice husk ash(SDRA). The thermodynamics and kinetics of copper ions' adsorption by SDRA were studied for their relevance to the adsorption mechanism. The adsorption of copper ions by SDRA is in accordance with the Langmuir model and the pseudo-second-order kinetic model. The adsorption process is mainly chemisorption. And increases in specific surface area and oxygen-containing functional groups following silica removal were primarily responsible for SDRA's enhanced adsorption ability. SDRA is a highly effective adsorbent. And the preparation technique of SDRA is a revolutionary method of adsorbent creation that is both economical and environmentally benign.

To address the challenges associated with corn stover utilization and the synthesis of phenyl- and methacryloyloxy-based silsesquioxanes (SQs) with difficulty and poor controllability, the authors present a novel approach that combines advanced biorefining techniques and innovative chemical synthesis methods. Spirocyclic alkoxysilane synthesized from corn stover ash was subsequently utilized for the synthesis of phenylSQs. The resulting phenylSQs were then subjected to fluorine ion-catalyzed rearrangement with 3-(trimethoxysilyl)propyl methacrylate (KH570) to yield SQs containing phenyl and methacryloyloxy functional groups. Through manipulating the ratio of phenylSQs and KH570, the authors successfully achieved a desired ratio of functional groups on individual SQ cages. Optimization of the ratio significantly impacted product collection, with a range of 5.5:1 to 8.5:1 recommended for efficient and effective synthesis. This study represents an important advancement in the field of high-value conversion of biomass, offering an easy means of tailoring the structure of phenyl- and methacryloyloxy-based cage SQs.

Abstract Nanomedicine technology is a rapidly developing field of research and application that uses nanoparticles as a platform to facilitate the diagnosis and treatment of diseases. Nanoparticles loaded with drugs and imaging contrast agents have already been used in clinically, but they are essentially passive delivery carriers. To make nanoparticles smarter, an important function is the ability to actively locate target tissues. It enables nanoparticles to accumulate in target tissues at higher concentrations, thereby improving therapeutic efficacy and reducing side effects. Among the different ligands, the CREKA peptide (Cys-Arg-Glu-Lys-Ala) is a desirable targeting ligand and has a good targeting ability for overexpressed fibrin in different models, such as cancers, myocardial ischemia-reperfusion, and atherosclerosis. In this review, the characteristic of the CREKA peptide and the latest reports regarding the application of CREKA-based nanoplatforms in different biological tissues are described. In addition, the existing problems and future application perspectives of CREKA-based nanoplatforms are also addressed.

Recently, convolutional neural networks (CNNs) have been widely applied in the seismic facies classification. However, even state-of-the-art CNN architectures often encounter classification confusion distinguishing seismic facies at their boundaries. In addition, the annotation is a highly time-consuming task, especially when dealing with 3-D seismic data volumes. While traditional semisupervised methods reduce dependence on annotation, they are susceptible to interference from unreliable pseudolabels. To address these challenges, we propose a semisupervised seismic facies classification method called CONSS, which effectively mitigates classification confusion through contrastive learning. Our proposed method requires only 1% of labeled data, significantly reducing the demand for annotation. To minimize the influence of unreliable pseudolabels, we also introduce a confidence strategy to select positive and negative sample pairs from reliable regions for contrastive learning. Experimental results on the publicly available seismic datasets, the Netherlands F3 and SEAM AI challenge datasets, demonstrate that the proposed method outperforms classic semisupervised methods, including self-training and consistency regularization, achieving exceptional classification performance.

Hydrophobic materials have promising applications. However, fluorine present in hydrophobic materials can lead to health risks and environmental pollution. This study investigated an environmentally friendly route to produce fluorine-free hydrophobic coatings with good wear resistance. Wear-resistant hydrophobic coatings were prepared by introducing different ratios of spirocyclic alkoxysilane into the epoxy resin. Characterization by Fourier transform infrared spectroscopy, water contact angle measurement, scanning electron microscope, tape adhesion test, and abrasion testing showed that the multi-methyl group and double-ring rigid skeleton structure of spirocyclic alkoxysilane can remarkably improve the hydrophobic performance and wear resistance of the epoxy resin. The modified hydrophobic coatings can withstand more than 1600 instances of controlled rubbing. Furthermore, the maximum water contact angle can reach 110° after substantial abrasion. The novelty of the work is that the authors successfully synthesized spirocyclic alkoxysilane for the first-time using corn straw ash. The prepared spirocyclic alkoxysilane was then used as a modifier to prepare hydrophobic epoxy resin coating. This approach can broaden the utilization of corn straw ash. Therefore, this method can achieve a green and low-cost preparation of wear-resistant hydrophobic coatings without the introduction of fluorine.

Context Schisandra chinensis (Turcz.) Baill. (Magnoliaceae) essential oil (SCEO) composition is rich in lignans that are believed to perform protective effects in the liver.Objective This study investigates the effects of SCEO in the treatment of acetaminophen (APAP)-induced liver injury in mice.Materials and methods C57BL/6 mice (n = 56) were randomly divided into seven groups: normal; APAP (300 mg/kg); APAP plus bicyclol (200 mg/kg); APAP plus SCEO (0.25, 0.5, 1, 2 g/kg). Serum biochemical parameters for liver function, inflammatory factors, and antioxidant activities were determined. The protein expression levels of Nrf2, GCLC, GCLM, HO-1, p62, and LC3 were assessed by western blotting. Nrf2, GCLC, HO-1, p62, and LC3 mRNA were detected by real-time PCR.Results Compared to APAP overdose, SCEO (2 g/kg) pre-treatment reduced the serum levels of AST (79.4%), ALT (84.6%), TNF-α (57.3%), and IL-6 (53.0%). In addition, SCEO (2 g/kg) markedly suppressed cytochrome P450 2E1 (CYP2E1) (15.4%) and attenuated the exhaustion of GSH (43.6%) and SOD (16.8%), and the accumulation of MDA (22.6%) in the liver, to inhibit the occurrence of oxidative stress. Moreover, hepatic tissues from our experiment revealed that SCEO pre-treatment mitigated liver injury caused by oxidative stress by increasing Nrf2, HO-1, and GCL. Additionally, SCEO activated autophagy, which upregulated hepatic LC3-II and decreased p62 in APAP overdose mice (p

Abstract Constraining the stress related to lithospheric deformation in natural rocks is key to develop and test a geodynamic model. However, the cautions of extrapolating piezometers that are established on experimental samples to natural rocks are less addressed. In this study, we investigated the microstructures of a natural harzburgite sample using the electron backscatter diffraction (EBSD) technique. Subgrain boundary (SGB) geometries suggest large percentages of (010)[100] and {0kl}[100] dislocation slip systems in olivines. More importantly, multiple low-angle misorientation boundaries (LAMBs) variants are recognized for the first time in olivine based on their distinctive characteristics with the change of EBSD mapping step size. The LAMBs that exist at a small step size (≤ 1 μm) are mostly equivalent to real SGBs, while other LAMBs that appear only when the step size is larger (> 1 μm) are artificial SGBs. Besides, the former develop mainly in the high LAMB density grains, whereas the latter are mostly found in the low LAMB density grains. This result reinforces the previous knowledge that the stress calculated using subgrain-related piezometers is meaningful only when real SGBs are captured at sufficiently small step size. Furthermore, we provide a proof of concept that SGB density and kernel average misorientation (KAM) are two viable metrics to estimate stress. These two alternative piezometers, which still need calibrations using the experimentally deformed samples, are anticipated to have wide applications in natural rocks.

Two THEMIS (Time History of Events and Macroscale Interactions during Substorms) spacecraft, B and C, began orbiting the Moon in 2011 and have since provided routine measurements of the plasma conditions in the lunar orbit. In this study, we systematically compare these measurements in near-Earth space with solar wind measurements obtained from the Lagrangian 1 (L1) point and propagated to the Earth, including measurements in the OMNI database and from the Wind spacecraft. A statistical comparison between THEMIS data and data from the OMNI database from September 2011 to December 2017 showed that the Y and Z components of the magnetic field and the flow speed are generally consistent between the two data sets. The ion number density and the dynamic pressure measured by THEMIS in near-Earth space are lower than those in the OMNI database, suggesting possible variation in the solar wind environment while propagating from the L1 point to near-Earth space. We further show two examples in which near-Earth solar wind measurements are applied in calculating the magnetopause location and in quantifying the magnetic field response to interplanetary shocks. Both examples suggest that using solar wind data from near-Earth space achieves better results than using solar wind data from the L1 point. These results provide validation of THEMIS-B and THEMIS-C as an alternative monitor of the near-Earth solar wind environment.

Background: Allergen-specific immunotherapy, including subcutaneous immunotherapy (SCIT) and sublingual immunotherapy (SLIT), improves the disease progression of allergic rhinitis (AR). SCIT and SLIT exhibit similar efficacy, but SLIT has less systemic reactions. However, few studies have investigated the underlying mechanisms of SLIT treatment. In this study, we explored the efficacy of SLIT under different treatment durations and immunological changes. Methods: This retrospective study was conducted from August 2017 to August 2022 in our hospital. A total of 314 children who underwent SLIT were divided into the following groups based on their treatment duration: the 1 year group (6 months–1 year), the 2 years group (1–2 years), and the 3 years group (2–3 years). The treatment efficacy was confirmed using a combined symptom and medication score (SMS). Multiple serum cytokines were measured using Luminex. Various immune cells in PBMCs were determined using flow cytometry. Results: The total nasal symptom score (TNSS), rescue medication score (RMS), and SMS of the 3 years group was significantly different from those of the 1 years and 2 years groups. At the end of the 2 years following cessation of SLIT, the following results were observed in the 3 years group: 1) the TNSS, RMS, and SMS had significantly improved, 2) the serum IL-10, TGF-beta, and IL-35 levels had increased significantly, and 3) the percentages of regulatory T cell, regulatory B cell, and follicular regulatory T cell increased significantly. Conclusion: Our results suggest that 3 years of SLIT is necessary for long-term effects and continued immunological changes.

Introduction: Shuanghuanglian injection (lyophilized) (SHLI) is commonly used to treat respiratory tract infection. Shenmai injection (SMI) is mainly used to treat cardiovascular diseases. Despite their widespread clinical use, anaphylactoid reactions (ARs) induced by SHLI and SMI have been reported, which have attracted broad attention. However, the impact of ARs on metabolic changes and the underlying mechanisms are still unclear.Methods: ICR mice were used as model animals and were treated with normal saline, C48/80, SHLI and SMI, respectively. The behavior of mice, auricle blue staining and Evans Blue exudation were used as indexes to evaluate the sensitization of SHLI and SMI and determine the optimal sensitization dose. Anaphylactoid mice model was established based on the optimal dose and enzyme-linked immunosorbent assay (ELISA) was used to model verification. Afterwards, plasma samples of administered mice were profiled by LC-MS metabolomics and analyzed to evaluate the changes in metabolites.Results: High doses of both SHLI and SMI can induce severe anaphylactoid reactions while the reaction induced by SMI was weaker. A Partial Least-Squares Discriminant Analysis (PLS-DA) score plot indicated that following administration, significant metabolic changes occurred in mice. 23 distinct metabolites, including deoxycholic acid, histamine, and 5-hydroxytryptophan, were identified in the SHLI groups. 11 distinct metabolites, including androsterone, 17α-hydroxypregnenolone, and 5-hydroxyindoleacetate, were identified in the SMI groups. Meanwhile, different metabolic pathways of SHLI and SMI were predicted by different metabolites. The associated metabolic pathways include steroid hormone biosynthesis, tryptophan metabolism, histidine metabolism, arachidonic acid metabolism, nicotinate and nicotinamide metabolism, and primary bile acid biosynthesis.Conclusion: Study showed that both SHLI and SMI can induce varying degrees of anaphylactoid reactions, a positive correlation between response intensity and dose was observed. Metabolomics showed that SHLI and SMI may promote the simultaneous release of hormones and inflammatory factors by disturbing relevant metabolic pathways, while SMI may also inhibit the release of inflammatory factors in arachidonic acid metabolic pathway, indicating both pro-inflammatory and anti-inflammatory effects. This study will serve as a reference for developing a new approach to evaluate the safety of SHLI and SMI from perspective of susceptible drug varieties. However, ARs mechanism requires further verification.

Abstract Background More and more studies had suggested that dyslipidemia was closely related to allergic diseases. High density lipoprotein (HDL) often plays anti-inflammatory and anti-oxidative roles by suppressing immune cell chemotaxis and activation. We aimed to explore the role of HDL in the regulation of group II innate lymphoid cells (ILC2) in allergic rhinitis (AR). Methods The blood lipid levels and their correlation with symptom scores of 20 AR subjects and 20 controls were analyzed. Purified ILC2 were stimulated by HDL and cytokines production were examined by enzyme-linked immunosorbent assay (ELISA) and flow cytometry. The mRNA levels of GATA binding protein 3(GATA3) and retinoid-related orphan receptor α (RORα) expressed by ILC2 were detected using reverse transcription polymerase chain reaction (RT-PCR). Results HDL level was significantly lower in AR than controls and correlated with the symptom scores. The serum HDL levels were negatively related to the increased number of ILC2, IL-5+ ILC2, and IL-13+ ILC2 in AR patients. HDL decreased the number of ILC2 and type II cytokines levels significantly by inhibiting expression of GATA3 and RORα. Conclusions Our data provide preliminary evidence that HDL may play a negative role in ILC2 inflammation in AR, suggesting that HDL may serve as promising treatment target in AR.

In this study, bipolar membrane electrodialysis was proposed to directly convert L-ornithine monohydrochloride to L-ornithine. The stack configuration was optimized in the BP-A (BP, bipolar membrane; A, anion exchange membrane) configuration with the Cl− ion migration through the anion exchange membrane rather than the BP-A-C (C, cation exchange membrane) and the BP-C configurations with the L-ornithine+ ion migration through the cation exchange membrane. Both the conversion ratio and current efficiency follow BP-A > BP-A-C > BP-C, and the energy consumption follows BP-A < BP-A-C < BP-C. Additionally, the voltage drop across the membrane stack (two repeating units) and the feed concentration were optimized as 7.5 V and 0.50 mol/L, respectively, due to the low value of the sum of H+ ions leakage (from the acid compartment to the base compartment) and OH− ions migration (from the base compartment to the acid compartment) through the anion exchange membrane. As a result, high conversion ratio (96.1%), high current efficiency (95.5%) and low energy consumption (0.31 kWh/kg L-ornithine) can be achieved. Therefore, bipolar membrane electrodialysis is an efficient, low energy consumption and environmentally friendly method to directly convert L-ornithine monohydrochloride to L-ornithine.

Abstract Background Coronavirus disease (COVID‐19) is a global infectious disease with a large burden of illness and high health care costs. This study aimed to compare clinical features among adult COVID‐19 patients in different age groups. Methods Laboratory‐confirmed adult COVID‐19 infection cases between December 31, 2019 to March 8, 2020 obtained from Neighboring Cities. Patients were divided into five age groups. Clinical characteristics were compared among different age groups. Results Of 299 cases, median age was 44 and 158 (53%) were male. A total of 53.3% of 30–40 years, 50% of 40–50 years, 36.6% of

Solar coronal waves frequently appear as bright disturbances that propagate globally from the eruption center in the solar atmosphere, just like the tsunamis in the ocean on Earth. Theoretically, coronal waves can sweep over the underlying chromosphere and leave an imprint in the form of Moreton wave, due to the enhanced pressure beneath their coronal wave front. Despite the frequent observations of coronal waves, their counterparts in the chromosphere are rarely detected. Why the chromosphere rarely bears the imprints of solar tsunamis remained a mystery since their discovery three decades ago. To resolve this question, all coronal waves and associated Moreton waves in the last decade have been initially surveyed, though the detection of Moreton waves could be hampered by utilizing the low-quality H α data from the Global Oscillations Network Group. Here, we present eight cases (including five in the Appendix) of the coexistence of coronal and Moreton waves in inclined eruptions where it is argued that the extreme inclination is key to providing an answer to address the question. For all these events, the lowest part of the coronal wave front near the solar surface appears very bright, and the simultaneous disturbances in the solar transition region and the chromosphere predominantly occur beneath the bright segment. Therefore, evidenced by observations, we propose a scenario for the excitation mechanism of the coronal-Moreton waves in highly inclined eruptions, in which the lowest part of a coronal wave can effectively disturb the chromosphere even for a weak (e.g., B-class) solar flare.

Background. Interleukin-37b is a fundamental inhibitor of innate and acquired immunity. Type 2 innate lymphoid cells (ILC2s) can secret type 2 cytokines and regulate allergic rhinitis (AR). However, the role of IL-37b in ILC2s in children with AR was not clear. Methods. We recruited 15 AR children and controls. The serum IL-37b levels and its relation with the frequency and functional phenotype of ILC2s. The regulation of IL-37b on ILC2s proliferation and function was confirmed using flow cytometry and enzyme-linked immunosorbent assay (ELISA). The mRNA expression of IL-1R8, IL-18Rα, and ICOSL was examined using RCR. The change of IL-37b protein level in serum during subcutaneous allergen immunotherapy (SCIT) was determined by ELISA. Results. We have demonstrated that both of the frequencies of blood ILC2s, IL-5+ILC2s, and IL-13+ILC2s in AR children were elevated compared with controls. The serum protein level of IL-37b was downregulated in AR, and it was negatively related to the frequency of ILC2s, IL-5+ILC2s, and IL-13+ILC2s. IL-37b increased the mRNA levels of IL-1R8, IL-18Rα, and ICOSL expressed by ILC2s. IL-37b suppressed the proliferation of ILC2s and the secretion of IL-5 and IL-13 from ILC2s. Finally, we found that IL-37b was increased in AR children after 3 years’ SLIT, especially in the good response group. Conclusion. Our findings highlight the role of IL-37b in the suppression of ILC2s and establish a new therapeutic target in AR.

The biological functions of N6-methyladenosine (m6A) modification of mRNA have recently received a great deal of attention. In previous studies, m6A methylation modification has been shown to regulate mRNA fate and to be crucial for the progression and development of tumors. BTG2 (B-cell translocation gene 2) is a member of BTG/TOB anti-proliferative protein family. BTG2 could inhibit cell proliferation and migration and regulate the cell cycle progression. In this study, we confirm that BTG2 is frequently down-regulated in renal cell carcinoma (RCC) tissues and its low expression is associated with unfavorable prognosis and decreased m6A level. Moreover, we found that m6A methylation modifies the 5’UTR of BTG2 to promote its mRNA stability by binding to IGF2BP2. It has been shown that CRISPR/dCas13b-METLL3 can specifically increase BTG2 m6A modification to significantly increase its m6A and expression levels. Then m6A hypermethylation in BTG2 mRNA could dramatically inhibit RCC cells proliferation and migration, and induce cells apoptosis. Taken together, our data show that BTG2 functions as a tumor suppressor and is frequently silenced via m6A modification in RCC.

The main clinical manifestations of coronavirus disease 2019 (COVID-19) onset are respiratory symptoms, including cough, sputum, and dyspnea. However, a significant proportion of patients initially manifested non-respiratory symptoms, such as fever, myalgia, and diarrhea. Here, we compared the different characteristics and outcomes between the patients with respiratory symptoms and non-respiratory symptoms at illness onset. The patients admitted to the respiratory departments from eight hospitals in Hunan and Guangxi Province with nucleic acid-positive severe acute respiratory syndrome coronavirus (SARS-CoV-2) were recruited. Epidemiological information, clinical manifestations, laboratory findings, and radiological characteristics, treatment regimens, and outcomes data were recorded and analyzed. The median age of the recruited 541 subjects was 43 years (IQR, 33–55). Of the 541 subjects, 404 (74.5%) subjects had initial symptom that were respiratory, while 137 (25.5%) subjects had non-respiratory symptoms. Respiratory COVID-19 subjects had more secondary bacterial infections (8.7% vs 0.0%, P

The attainment of clean heating in the rural areas of northern China is of great significance for environmental governance and the realization of the dual carbon goal. Based on the evolutionary game theory, this study constructs a three-party evolutionary game model of the central government, local government, and farmers, introduces key parameters, such as the local government’s governance strength, central government’s inspection strength, and two levels of government subsidy strength, into the model, systematically deduces different possible strategy combinations of the three parties, and analyzes the possible scenarios and stability conditions of each scenario. Finally, the study numerically simulates each scenario and analyzes the influence of the key parameters on the strategies of the three parties. The study conclusions are as follows. 1) The system is optimized in Scenario 6 (1,1,0). 2) The strategy of the local government has a decisive influence on farmers, and the central government’s inspector strength has a weak effect on farmers. 3) The cost of clean heating over coal-fired heating has a significant effect on farm households but not on the two levels of government. 4) The low perception that farmers hold regarding the benefits of the indoor environment weakens the government’s subsidy effect. This study provides effective practical guidance and policy references for governments to promote clean heating in rural areas.

For countries with small farmers as the main body of agricultural production, green production transformation of small farmers is crucial to achieve green agricultural development. Based on the prospect theory, this paper builds an evolutionary game model of cooperative leading the green production transformation of small farmers, systematically deduces the possible combination of different strategies of both sides, and puts forward targeted countermeasures for improvement. Finally, the simulation is verified, and the influence of relevant parameters on the decision-making of both sides is analyzed. In the initial stage of green production transformation, the local government’s support to the cooperative supervision and incentive strategy is the key to the successful transformation. Cooperatives can effectively promote small farmers’ transition to green production by reducing green production costs and increasing their perceived ecological benefits, moral benefits and brand benefits, but the effect of simply increasing the proportion of dividends is not obvious. Under the supervision and incentive strategy of cooperatives, there is an interval in which small farmers adopt cooperation strategy but fail to realize income increase, so cooperatives should increase the benefit distribution of small farmers. The research results provide reference for the green production transformation of small farmers, and also have strong enlightenment for the cooperative hitchhiking governance.

The Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) inhabiting the Yantze River, China is critically endangered because of the influences of infectious disease, human activity, and water contamination. Viral diseases are one of the crucial factors that threatening the health of Yangtze finless porpoise. However, there are few studies which elaborate the viral diversity of Yangtze finless. Therefore, this study was performed to investigate the viral diversity of Yangtze finless by metagenomics. Results indicated that a total of 12,686,252 high-quality valid sequences were acquired and 2,172 virus reads were recognized. Additionally, we also obtained a total of 10,600 contigs. Phages was the most abundant virus in the samples and the ratio of DNA and RNA viruses were 69.75 and 30.25%, respectively. Arenaviridae, Ackermannviridae and Siphoviridae were the three most predominant families in all the samples. Moreover, the majority of viral genus were Mammarenavirus, Limestonevirus and Lambdavirus. The results of gene prediction indicated that these viruses play vital roles in biological process, cellular component, molecular function, and disease. To the best of our knowledge, this is the first report on the viral diversity of Yangtze finless porpoise, which filled the gaps in its viral information. Meanwhile, this study can also provide a theoretical basis for the establishment of the prevention and protection system for virus disease of Yangtze finless porpoise.

Background: Osteopontin (OPN) can regulate Th2 inflammation in allergic rhinitis (AR). A recent study suggested that group II innate lymphoid cells (ILC2s) were very important for airway inflammation. But the role of OPN in ILC2s regulation is not explored. Methods: Purified ILC2s were stimulated by human recombinant OPN. The expression of GATA3 and RORα was assayed using real-time polymerase chain reaction (PCR) and enzyme linked immunosorbent assay. MiR-181a was transfected into eosinophils to test the OPN production. The protein concentrations of interleukin (IL)-5 and IL-13 were examined using ELISA. Purified eosinophils and ILC2s were cocultured and stimulated by OPN and the activation of eosinophils was detected by ELISA. Results: After OPN stimulation, the ILC2s proliferation, the mRNA levels of GATA3 and RORα, the protein of GATA3, RORα, IL-5 and IL-13 expression were up-regulated significantly in a dose dependent manner. Eosinophils cultured alone transfected with miR-181a mimics produced less OPN protein compared with eosinophils transfected with miR-control, whereas OPN production was significantly promoted when miR-181a inhibitor was transfected. In the eosinophils and ILC2s coculture system, eosinophil cationic protein (ECP) production induced by OPN or IL-33 were significantly higher than ECP production in eosinophils culture system. OPN presented similar potency with IL-33 in the activation of eosinophils. When anti-IL-5 antibody was added, the production of ECP was significantly inhibited. Conclusions: Our data for the first time provided new evidence that OPN played important roles in innate immunity of AR by regulation of ILC2s and the interaction between ILC2s and eosinophils.

It is a huge difficulty to improve the comprehensive dielectric performance of barium strontium titanate (BST) films for applications in energy storage, microwave, etc. Herein, on Pt/Ti/SiO2/Si substrate strontium titanate (ST), manganese (Mn) doped BST and yttrium (Y) doped BST layers were attempted to be designed as ST/MnBST/YBST/ … /MnBST/YBST/ST films and prepared by a modified sol–gel method, and structures and performances of the films were studied. X-ray diffraction shows that the films are ABO3 perovskite polycrystalline with Ti4+ at B sites replaced by some Mn2+ and exhibit dense nodular microstructures observed by a scanning electron microscope. The films exhibit optimized comprehensive performance with leakage current density of less than 1E-10 A/cm2 at 20 V and dielectric losses of 0.3%–0.4% at 100 kHz and about 1.8% at 1 GHz, meeting the needs of some applications.

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders whose etiology and pathogenesis are not fully understood. To gain insight into the molecular basis of ASD, we performed comparative integrated proteomic and metabolomic analyses of urine samples from children diagnosed with ASD and healthy children. All 160 samples underwent proteomics analysis and 60 were analyzed by liquid chromatography-mass spectrometry to obtain metabolite profiles. We identified 77 differentially expressed proteins (DEPs; 21 downregulated and 56 upregulated) and 277 differentially expressed metabolites; 31 of the DEPs including glutathione, leukocyte antigens, glycoproteins, neural adhesion factors, and immunoglobulins, have been implicated in neuroinflammation. The proteomic analysis also revealed 8 signaling pathways that were significantly dysregulated in ASD patients; 3 of these (transendothelial leukocyte migration, antigen processing and presentation, and graft vs. host disease) were associated with the neuroimmune response. The metabolism of tryptophan, which is also related to the neuroimmune response, has been found to play a potential role in ASD. Integrated proteome and metabolome analysis showed that 6 signaling pathways were significantly enriched in ASD patients, 3 of which were correlated with impaired neuroinflammation (glutathione metabolism, metabolism of xenobiotics by cytochrome P450 and transendothelial migration of leukocyte). We also found a correlation between prostaglandin (PG) E2 levels and the inflammatory response in ASD. These results underscore the prominent role of the neuroimmune response in ASD and provide potential biomarkers that can be used for diagnosis or as targets for early intervention.

Background: Allergic rhinitis (AR) is a frequent inflammatory disorder of the upper respiratory tract, which has complex patterns of inheritance. Accumulating evidence has shown the key roles of DNA damage in inflammatory diseases, and the base excision repair (BER) is the primary pathway responsible for DNA repair during inflammation. Methods: Here, we performed a case-control study to investigate the associations between 20 potentially functional single nucleotide polymorphisms (SNPs) in 6 BER pathway genes (PARP1, hOGG1, FEN1, APEX1, LIG3, and XRCC1) and AR susceptibility in 508 AR cases and 526 controls which originated in China. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for evaluating the association strength. Results: We found that hOGG1 rs1052133 G > C and XRCC1 rs2682585 G > A polymorphisms were associated with decreased AR risk (adjusted OR = 0.67, 95% CI = 0.47–0.94, P = 0.022; and adjusted OR = 0.21, 95% CI = 0.06–0.79, P = 0.022, respectively). Stratification analysis suggested that: hOGG1 rs1052133 GC/CC genotype reduced AR risk in subjects among following subgroups: age ≤60 months, females, and moderate AR; XRCC1 rs2682585 GG genotype decreased AR risk in subjects age >60 months, and LIG3 rs1052536 TT genotype increased AR risk in subjects of severe AR. Conclusion: Our findings indicated that the genetic variants of hOGG1, XRCC1, and LIG3 genes might affect AR susceptibility in the Chinese population, which will provide novel insight into the genetic underpinnings of AR from the DNA damage level.

Bipolar membrane electrodialysis (BMED) is a promising process for the cleaner production of organic acid. In this study, the separation mechanism of BMED with different cell configurations, i.e., BP-A, BP-A-C, and BP-C (BP, bipolar membrane; A, anion exchange membrane; C, cation exchange membrane), to produce diprotic malic acid from sodium malate was compared in consideration of the conversion ratio, current efficiency and energy consumption. Additionally, the current density and feed concentration were investigated to optimize the BMED performance. Results indicate that the conversion ratio follows BP-C > BP-A-C > BP-A, the current efficiency follows BP-A-C > BP-C > BP-A, and the energy consumption follows BP-C < BP-A-C < BP-A. For the optimized BP-C configuration, the current density was optimized as 40 mA/cm2 in consideration of low total process cost; high feed concentration (0.5–1.0 mol/L) is more feasible to produce diprotic malic acid due to the high conversion ratio (73.4–76.2%), high current efficiency (88.6–90.7%), low energy consumption (0.66–0.71 kWh/kg) and low process cost (0.58–0.59 USD/kg). Moreover, a high concentration of by-product NaOH (1.3497 mol/L) can be directly recycled to the upstream process. Therefore, BMED is a cleaner, high-efficient, low energy consumption and environmentally friendly process to produce diprotic malic acid.

Abstract The vestibular receptor of cupula acts an important role in maintaining body balance. However, the cupula buried in the semicircular canals (SCCs) will be destroyed if it is detached from the relevant environment. The mechanical properties of human cupula still remain ambiguous. In this paper, we explored the cupula responses changing with temperature by experiments and numerical simulation of SCCs model. We obtained 3 volunteers’ nystagmus induced by constant angular acceleration when the temperature of volunteers’ SCCs was 36 °C and 37 °C respectively. The slow-phase velocity of 3 volunteers decreased by approximately 3°/s when the temperature of SCCs reduced by 1 °C, which corresponded to the reduction of cupula deformation by 0.3–0.8 μm in the numerical model. Furthermore, we investigated the effects of the variation of endolymphatic properties induced by temperature reduction on cupula deformation through numerical simulation. We found that the decrease of cupula deformation was not caused by the change of endolymphatic properties, but probably by the increase of cupula’s elastic modulus. With the temperature reducing by 1 °C, the cupula’s elastic modulus may increase by 6–20%, suggesting that the stiffness of cupula is enhanced. This exploration of temperature characteristic of human cupula promotes the research of alleviating vestibular diseases.

Background: The reports about valuable oligosaccharides in ginseng are quite limited. There is an urgent need to develop a practical procedure to detect and analyze ginseng oligosaccharides. Methods: The oligosaccharide extracts from ginseng were permethylated by solid-phase methylation method and then were analyzed by ultra-high-performance liquid chromatography-Q-Orbitrap/MS. The sequence, linkage, and configuration information of oligosaccharides were determined by using accurate m/z value and tandem mass information. Several standard references were used to further confirm the identification. The oligosaccharide composition in white ginseng and red ginseng was compared using a multivariate statistical analysis method. Results: The nonreducing oligosaccharide erlose among 12 oligosaccharides identified was reported for the first time in ginseng. In the comparison of the oligosaccharide extracts from white ginseng and red ginseng, a clear separation was observed in the partial least squares-discriminate analysis score plot, indicating the sugar differences in these two kinds of ginseng samples. The glycans with variable importance in the projection value large than 1.0 were considered to contribute most to the classification. The contents of oligosaccharides in red ginseng were lower than those in white ginseng, and the contents of maltose, maltotriose, maltotetraose, maltopentaose, maltohexaose, maltoheptaose, maltooctaose, maltononaose, sucrose, and erlose decreased significantly (p

Solar wind is important for the space environment between the Sun and the Earth and varies with the sunspot cycle, which is influenced by solar internal dynamics. We study the impact of latitude-dependent sunspot data on solar wind speed using the Granger causality test method and a machine-learning prediction approach. The results show that the low-latitude sunspot number has a larger effect on the solar wind speed. The time delay between the annual average solar wind speed and sunspot number decreases as the latitude range decreases. A machine-learning model is developed for the prediction of solar wind speed considering latitude and time effects. It is found that the model performs differently with latitude-dependent sunspot data. It is revealed that the timescale of the solar wind speed is more strongly influenced by low-latitude sunspots and that sunspot data have a greater impact on the 30 day average solar wind speed than on a daily basis. With the addition of sunspot data below 7.°2 latitude, the prediction of the daily and 30 day averages is improved by 0.23% and 12%, respectively. The best correlation coefficient is 0.787 for the daily solar wind prediction model.

Ground level enhancements (GLEs) are extreme solar energetic particle (SEP) events that are of particular importance in space weather. In solar cycle 24, two GLEs were recorded on 2012 May 17 (GLE 71) and 2017 September 10 (GLE 72), respectively, using a range of advanced modern instruments. Here we conduct a comparative analysis of the two events by focusing on the effects of large-scale magnetic field configuration near active regions on particle acceleration and release. Although the active regions are both located near the western limb, temporal variations of SEP intensities and energy spectra measured in situ display different behaviors at early stages. By combining a potential field model, we find the coronal mass ejection (CME) in GLE 71 originated below the streamer belt, while in GLE 72 it originated near the edge of the streamer belt. We reconstruct the CME shock fronts with an ellipsoid model based on nearly simultaneous coronagraph images from multiple viewpoints and further derive the 3D shock geometry at the GLE onset. The highest-energy particles are primarily accelerated in the shock–streamer interaction regions, i.e., likely at the nose of the shock in GLE 71 and the eastern flank in GLE 72, due to quasi-perpendicular shock geometry and confinement of closed fields. Subsequently, they are released to the field lines connecting to near-Earth spacecraft when the shocks move through the streamer cusp region. This suggests that magnetic structures in the corona, especially shock–streamer interactions, may have played an important role in the acceleration and release of the highest-energy particles in the two events.

Epithelial–mesenchymal transition (EMT) profoundly impacts prognosis and immunotherapy of clear cell renal cell carcinoma (ccRCC). However, not every patient is tested for EMT status because this requires additional genetic studies. In this study, we developed an EMT gene signature to classify the H&E-stained slides from The Cancer Genome Atlas (TCGA) into epithelial and mesenchymal subtypes, then we trained a deep convolutional neural network to classify ccRCC which according to our EMT subtypes accurately and automatically and to further predict genomic data and prognosis. The clinical significance and multiomics analysis of the EMT signature was investigated. Patient cohorts from TCGA (n = 252) and whole slide images were used for training, testing, and validation using an algorithm to predict the EMT subtype. Our approach can robustly distinguish features predictive of the EMT subtype in H&E slides. Visualization techniques also detected EMT-associated histopathological features. Moreover, EMT subtypes were characterized by distinctive genomes, metabolic states, and immune components. Deep learning convolutional neural networks could be an extremely useful tool for predicting the EMT molecular classification of ccRCC tissue. The underlying multiomics information can be crucial in applying the appropriate and tailored targeted therapy to the patient.