Search

Abstract Background DNA methylation is a crucial epigenetic mechanism that regulates gene expression during plant growth and development. However, the role of DNA methylation in regulating the organ-specific functions of the invasive weed Mikania micrantha remains unknown. Results Here, we generated DNA methylation profiles for M. micrantha and a local congeneric species, Mikania cordata, in three vegetative organs (root, stem, and leaf) using whole-genome bisulfite sequencing. The results showed both differences and conservation in methylation levels and patterns between the two species. Combined with transcriptome data, we found that DNA methylation generally inhibited gene expression, with varying effects depending on the genomic region and sequence context (CG, CHG, and CHH). Genes overlapping with differentially methylated regions (DMRs) were more likely to be differentially expressed between organs, and DMR-associated upregulated differentially expressed genes (DEGs) were enriched in organ-specific pathways. A comparison between photosynthetic (leaf) and non-photosynthetic (root) organs of M. micrantha further confirmed the regulatory role of DNA methylation in leaf-specific photosynthesis. Integrating small RNA-Seq data revealed that 24-nt small interfering RNAs (siRNAs) were associated with CHH methylation in gene-rich regions and regulated CHH methylation in the flanking regions of photosynthesis-related genes. Conclusion This study provides insights into the complex regulatory role of DNA methylation and siRNAs in organ-specific functions and offers valuable information for exploring the invasive characteristics of M. micrantha from an epigenetic perspective.

Abstract Classifying malicious traffic, which can trace the lineage of attackers’ malicious families, is fundamental to safeguarding cybersecurity. However, the deep learning approaches currently employed require substantial volumes of data, conflicting with the challenges in acquiring and accurately labeling malicious traffic data. Additionally, edge network devices vulnerable to cyber-attacks often cannot meet the computational demands required to deploy deep learning models. The rapid mutation of malicious activities further underscores the need for models with strong generalization capabilities to adapt to evolving threats. This paper introduces an innovative few-shot malicious traffic classification method that is precise, lightweight, and exhibits enhanced generalization. By refining traditional transfer learning, the source model is segmented into public and private feature extractors for stepwise transfer, enhancing parameter alignment with specific target tasks. Neuron importance is then sorted based on the task of each feature extractor, enabling precise pruning to create an optimal lightweight model. An adversarial network guiding principle is adopted for retraining the public feature extractor parameters, thus strengthening the model’s generalization power. This method achieves an accuracy of over 97% on few-shot datasets with no more than 15 samples per class, has fewer than 50 K model parameters, and exhibits superior generalization compared to baseline methods.

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a group of chronic interstitial pulmonary diseases characterized by myofibroblast proliferation and extracellular matrix (ECM) deposition. However, current treatments are not satisfactory. Therefore, more effective therapies need to be explored. Cepharanthine (CEP) is a naturally occurring alkaloid that has recently been reported to have multiple pharmacological effects, particularly in chronic inflammation. Methods For in vivo experiments, first, a pulmonary fibrosis murine model was generated via tracheal injection of bleomycin (BLM). Second, the clinical manifestations and histopathological changes of the mice were used to verify that treatment with CEP might significantly reduce BLM-induced fibrosis. Furthermore, flow cytometric analysis was used to analyze the changes in the number of M2 macrophages in the lung tissues before and after treatment with CEP to explore the relationship between macrophage M2 polarization and pulmonary fibrosis. In vitro, we constructed two co-culture systems (THP-1 and MRC5 cells, RAW264.7 and NIH 3T3 cells), and measured the expression of fibrosis-related proteins to explore whether CEP could reduce pulmonary fibrosis by regulating macrophage M2 polarization and fibroblast activation. Results The results showed that the intranasal treatment of CEP significantly attenuated the symptoms of pulmonary fibrosis induced by BLM in a murine model. Our findings also indicated that CEP treatment markedly reduced the expression of fibrosis markers, including TGF-β1, collagen I, fibronectin and α-SMA, in the mouse lung. Furthermore, in vitro studies demonstrated that CEP attenuated pulmonary fibrosis by inhibiting fibroblast activation through modulating macrophage M2 polarization and reducing TGF-β1 expression. Conclusions This study demonstrated the potential and efficacy of CEP in the treatment of pulmonary fibrosis. In particular, this study revealed a novel mechanism of CEP in inhibiting fibroblast activation by regulating macrophage M2 polarization and reducing the expression of fibrosis-associated factors. Our findings open a new direction for future research into the treatment of pulmonary fibrosis.

Abstract While previous observational studies have suggested a link between leukocyte counts and vascular dementia (VD), the causal relationship between leukocyte counts and various subtypes of VD remains elusive. This study aimed to investigate the causal relationship between five types of leukocyte counts and VD, with the goal of improving prevention and treatment strategies. In this study, leukocyte counts were used as the exposure variable, with genome-wide association study (GWAS) data sourced from both the UK Biobank and the Blood Cell Consortium. Additionally, GWAS data for five subtypes of vascular dementia were obtained from the FinnGen database. We conducted rigorous statistical analysis and visualization using Mendelian randomization (MR) to elucidate the potential causal relationship between leukocyte counts and vascular dementia. This study, utilizing MR analysis with data from the UK Biobank and Blood Cell Consortium, identified significant causal associations between increased lymphocyte counts and VD. Specifically, lymphocyte counts were found to be causally related to multiple and mixed VD subtypes. Sensitivity analyses, including MR-Egger regression and MR-PRESSO tests, confirmed the robustness of these findings, with no evidence of reverse causality or significant horizontal pleiotropy detected. The results underscore a potential inflammatory or immunological mechanism in the pathogenesis of VD, highlighting lymphocytes as a key component in their etiology. This investigation establishes a robust association between elevated lymphocyte and leukocyte counts and an increased risk of VD, emphasizing the roles of inflammation, immune activation, and hematological factors in disease pathogenesis.

During the Russia-Ukraine war, Ukrainian President Volodymyr Zelenskyy has strategically used social media to appeal for international support. This reflects a broader trend of political figures relying on digital platforms to shape public opinion and influence global narratives during crises. This work uses three main analysis methods, content, sentiment and social network analysis. The searched and collected dataset consists 604 valid tweets and 58,100 corresponding comments. The findings show that Zelenskyy employs both textual and visual narratives to construct a war-related agenda, influencing international public discourse. His agenda-setting is most effective in the early stages of the conflict but weakens over time. This study highlights Zelenskyy’s flexibility and adaptability in his media strategy, illustrating the evolving nature of political performance in a globalized media landscape. To maintain effective communication and image-building, leaders must balance audience psychology with the characteristics of digital media.

Study Region: Endorheic and exorheic basins of the Tibetan Plateau (TP). Study Focus: Reanalysis and satellite precipitation products provide alternatives for regions of sparse ground precipitation observation, but pose a tough task to select a suitable one for the TP. This study conducts a multi-scale evaluation of six reanalysis and satellite precipitation products in endorheic and exorheic basins using water balance and extended triple collocation (ETC) methods. The reanalysis precipitation products include ECMWF Re-Analysis version 5 (ERA5-Land), China Meteorological Forcing Dataset (CMFD), Global Land Data Assimilation Systems (GLDAS), and High-resolution Precipitation dataset for the Third Pole region (TPHiPr). The satellite precipitation data include Global Precipitation Measurements (GPM) and Tropical Rainfall Measuring Mission (TRMM) products. New Hydrological Insights for the Region: The precipitation products vary in accuracy from basin to basin, with better performance in exorheic than endorheic basins. Reanalysis-based ERA5-land, TPHiPr, and CMFD perform well in most basins at annual scale, among which TPHiPr performs best at daily scale. At regional scale, GPM performs well in endorheic region, and ERA5-land in exorheic region. While all the products increase significantly in accuracy from basin to regional scale in endorheic region, ERA5-land shows best performance at annual and multi-year scales in the entire region. Our findings provide valuable supports for precipitation product selection in the Tibetan endorheic and exorheic basins.

Background Intrahepatic cholangiocarcinoma (ICC) is a disease with poor prognosis and limited therapeutic options. We investigated the tumor immune microenvironment (TIME) to identify predictors of disease outcome and to explore targets for therapeutic modulation.Methods Liver tissue samples were collected during 2008–2019 from patients (n = 139) diagnosed with ICC who underwent curative intent surgery without neoadjuvant chemotherapy. Samples from the discovery cohort (n = 86) were immunohistochemically analyzed on tissue microarrays (TMAs) for the expression of CD68, CD3, CD4, CD8, Foxp3, PD-L1, STAT1, and p-STAT1 in tumor core and stroma areas. Results were digitally analyzed using QuPath software and correlated with clinicopathological characteristics. For validation of TIME-related biomarkers, we performed multiplex imaging mass cytometry (IMC) in a validation cohort (n = 53).Results CD68+ cells were the predominant immune cell type in the TIME of ICC. CD4+high T cell density correlated with better overall survival (OS). Prediction modeling together with validation cohort confirmed relevance of CD4+ cells, PD-L1 expression by immune cells in the stroma and N-stage on overall disease outcome. In turn, IMC analyses revealed that silent CD3+CD4+ clusters inversely impacted survival. Among annotated immune cell clusters, PD-L1 was most relevantly expressed by CD4+FoxP3+ cells. A subset of tumors with high density of immune cells (“hot” cluster) correlated with PD-L1 expression and could identify a group of candidates for immune checkpoint inhibition (ICI). Ultimately, higher levels of STAT1 expression were associated with higher lymphocyte infiltration and PD-L1 expression.Conclusions These results highlight the importance of CD4+ T cells in immune response against ICC. Secondly, a subset of tumors with “hot” TIME represents potential candidates for ICI, while stimulation of STAT1 pathway could be a potential target to turn “cold” into “hot” TIME in ICC.

Abstract Natural antimicrobial peptides (AMPs) and enzymes (AMEs) are promising non-antibiotic candidates against antimicrobial resistance but suffer from low efficiency and poor stability. Here, we develop peptide nanozymes which mimic the mode of action of AMPs and AMEs through de novo design and peptide assembly. Through modelling a minimal building block of IHIHICI is proposed by combining critical amino acids in AMPs and AMEs and hydrophobic isoleucine to conduct assembly. Experimental validations reveal that IHIHICI assemble into helical β-sheet nanotubes with acetate modulation and perform phospholipase C-like and peroxidase-like activities with Ni coordination, demonstrating high thermostability and resistance to enzymatic degradation. The assembled nanotubes demonstrate cascade antifungal actions including outer mannan docking, wall disruption, lipid peroxidation and subsequent ferroptotic death, synergistically killing >90% Candida albicans within 10 min on disinfection pad. These findings demonstrate an effective de novo design strategy for developing materials with multi-antimicrobial mode of actions.

Reinforcement learning, a cornerstone in the expansive landscape of artificial intelligence, has asserted its dominance as the prevailing methodology in contemporary multiagent system decision-making because of its formidable efficacy. However, the path to the zenith of algorithmic excellence is fraught with challenges intrinsic to traditional multiagent reinforcement learning algorithms, such as dimensionality explosion, scarcity of training samples, and the labyrinthine nature of migration processes. In a concerted effort to surmount these formidable challenges and propel the evolution of algorithmic prowess, this paper unfurls its inquiry from the perspective of learning mechanisms and undertakes an exhaustive exploration of the symbiotic integration of learning mechanisms and reinforcement learning. At the inception of this scholarly expedition, we meticulously delineate the rudimentary principles underpinning multiagent algorithms, present a historical trajectory tracing their developmental evolution, and cast a discerning eye upon the salient challenges that have been formidable impediments in their trajectory. The ensuing narrative charts a course into the avant-garde realm of multiagent reinforcement learning methods anchored in learning mechanisms, a paradigmatic shift that emerges as an innovative frontier in the field. Among these learning mechanisms, meta-learning and transfer learning are empirically validated as useful instruments in hastening the learning trajectory of multiagent systems and simultaneously mitigating the intricate challenges posed by dimensionality explosion. This paper assumes the role of a sagacious guide through the labyrinthine landscape of multiagent reinforcement learning, focusing on the manifold applications of learning mechanisms across diverse domains. A comprehensive review delineates the impact of learning mechanisms in curriculum learning, evolutionary games, meta-learning, hierarchical learning, and transfer learning. The research outcomes within these thematic realms are methodically cataloged, with a discerning eye cast upon the limitations inherent in each methodology and erudite propositions for the trajectory of future improvements. The discourse pivots toward synthesizing advancements and accomplishments wrought by fusion algorithms in practical milieus. This paper meticulously examines the transformative impact of fusion algorithms in real-world applications, with a detailed exposition of their deployment in domains as diverse as traffic control and gaming. Simultaneously, an incisive analysis charting the future trajectory of fusion algorithms is conducted. This prediction encompasses exploring nascent theories, refining algorithmic efficacy, and expanding dissemination and application across a broader spectrum of domains. Through this scholarly odyssey, this paper provides an invaluable compass for navigating the uncharted waters of future research endeavors and the judicious deployment of multiagent reinforcement learning algorithms in pragmatic scenarios.

Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) is an novel non-invasive functional imaging technique that features more flexible sensor configurations and wearability; however, this also increases the requirement for environmental noise suppression. Subspace projection algorithms are widely used in MEG to suppress noise. However, in OPM-MEG systems with a limited number of channels, subspace projection methods that rely on spatial oversampling exhibit reduced performance. The homogeneous field correction (HFC) method resolves this problem by constructing a low-rank spatial model; however, it cannot address complex non-homogeneous noise. The spatiotemporal extended homogeneous field correction (teHFC) method uses multiple orthogonal projections to suppress disturbances. However, the signal and noise subspace are not completely orthogonal, limiting enhancement in the capabilities of the teHFC. Therefore, we propose an extended homogeneous field correction method based on oblique projection (opHFC), which overcomes the issue of non-orthogonality between the signal and noise subspace, enhancing the ability to suppress complex interferences. The opHFC constructs an oblique projection operator that divides the signals into internal and external components, eliminating complex interferences through temporal extension. We compared the opHFC with four benchmark methods by simulations and auditory and somatosensory evoked OPM-MEG experiments. The results demonstrate that opHFC provides superior noise suppression with minimal distortion, enhancing the signal quality at the sensor and source levels. Our method offers a novel approach to reducing interference in OPM-MEG systems, expanding their application scenarios, and providing high-quality signals for scientific research and clinical applications based on OPM-MEG.

The optically pumped magnetometer (OPM) based magnetoencephalography (MEG) system offers advantages such as flexible layout and wearability. However, the position instability or jitter of OPM sensors can result in bad channels and segments, which significantly impede subsequent preprocessing and analysis. Most common methods directly reject or interpolate to repair these bad channels and segments. Direct rejection leads to data loss, and when the number of sensors is limited, interpolation using neighboring sensors can cause significant signal distortion and cannot repair bad segments present in all channels. Therefore, most existing methods are unsuitable for OPM-MEG systems with fewer channels. We introduce an automatic bad segments and bad channels repair method for OPM-MEG, called Repairbads. This method aims to repair all bad data and reduce signal distortion, especially capable of automatically repairing bad segments present in all channels simultaneously. Repairbads employs Riemannian Potato combined with joint decorrelation to project out artifact components, achieving automatic bad segment repair. Then, an adaptive algorithm is used to segment the signal into relatively stable noise data chunks, and the source-estimate-utilizing noise-discarding algorithm is applied to each chunk to achieve automatic bad channel repair. We compared the performance of Repairbads with the Autoreject method on both simulated and real auditory evoked data, using five evaluation metrics for quantitative assessment. The results demonstrate that Repairbads consistently outperforms across all five metrics. In both simulated and real OPM-MEG data, Repairbads shows better performance than current state-of-the-art methods, reliably repairing bad data with minimal distortion. The automation of this method significantly reduces the burden of manual inspection, promoting the automated processing and clinical application of OPM-MEG.

BackgroundThe existing evidence concerning the correlation between dietary β-carotene intake and Parkinson’s disease (PD) is currently deemed insufficient. Thus, this research aims to investigate the relationship between dietary β-carotene intake and both the prevalence of PD and all-cause mortality within the US (United States) population.MethodsThe research employed cross-sectional analysis and cohort studies utilizing data from 16,852 participants in the National Health and Nutrition Examination Survey (NHANES) spanning from 2001 to 2018. Weighted logistic regression, weighted cox regression, restricted cubic splines (RCS), subgroup analysis, and sensitivity analyses were employed to validate the research objectives.ResultsAmong all eligible subjects, the mean age was 59.62 ± 11.77 years, with a prevalence of PD at 1.82% overall, with 43.88% in males. In the fully adjusted model, dietary β-carotene intake exhibited a negative association with PD prevalence [odds ratio (OR) = 0.95; 95% confidence interval (CI): 0.90 ~ 0.997; p = 0.040]. Utilizing RCS analysis, a negative linear correlation between dietary β-carotene intake and PD prevalence was observed (non-linear p = 0.857). Furthermore, after controlling for multiple variables, dietary β-carotene intake was inversely associated with all-cause mortality [Hazard ratios (HR) = 0.98; 95% CI: 0.97 ~ 0.99; p = 0.002], with RCS curves indicating a negative linear relationship (nonlinear: p = 0.082). Comparable patterns of association were noted in subgroup analyses, and consistent findings were derived from additional sensitivity analyses.ConclusionThe cross-sectional and cohort study reveals a significant negative correlation between dietary β-carotene intake and both the prevalence of PD and all-cause mortality in the general population. This suggested that supplementing with dietary β-carotene might have certain benefits for reducing the prevalence of PD and all-cause mortality. However, further rigorously designed expected studies are needed to establish the causal relationship between them.

Background Adverse left ventricular remodeling is a significant cardiovascular predictor for patients with coronary artery disease and preserved left ventricular ejection fraction (LVEF). However, the remodeling indexes reflecting left ventricular spherization by myocardial perfusion imaging are underexplored. Methods and Results 727 patients (mean age 59.8±13.5 years, 329 women) diagnosed or suspected coronary artery disease with preserved LVEF who underwent resting myocardial perfusion imaging were retrospectively enrolled. The myocardial perfusion imaging findings including the total perfusion deficit and sphericity indexes (shape index (SI) and eccentricity index (EI) obtained from gated (QGS) and non‐gated (QPS) images) were collected. Major adverse cardiovascular events (MACE) were followed up for 45.1±22.0 months. All patients were divided into 4 subgroups based on total perfusion deficit at 10% and LVEF at 65%. Univariable comparative analyses were performed in 5 cohorts (all patients and 4 subgroups). Patients who experienced MACE displayed higher SI and/or lower EI (all P

Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices.A comprehensive analysis of metal artifact characteristics from time, frequency, and time–frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5–8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process.The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.

ABSTRACT: Exosome-mediated horizontal and vertical transmission of subgroup J avian leukosis virus (ALV-J) in poultry flocks can lead to growth inhibition and severe immunosuppression. However, there are few reports on the early infection of chicken embryonic stem cells (cESCs) with ALV-J. In this study, we confirmed that early infection with ALV-J can accelerate the differentiation of cESCs and promote the secretion of exosomes. To investigate the modulation strategy of ALV-J in cESCs, circRNA sequencing was performed for further analysis. A total of 305 differentially expressed circRNAs (DECs) were obtained, including 71 upregulated DECs. Circ-CCDC7 was found to be the most upregulated DEC and was assessed by qRT-PCR, with the result consistent with the result of circRNA-seq. Based on qRT-PCR, gga-miR-6568-3p was found to be the target of the top 3 DECs, including circ-CCDC7, and the stem cell marker gene Pax7 was identified as the target gene of gga-miR-6568-3p. This study demonstrated that exosomal circ-CCDC7/gga-miR-6568-3p/Pax7 accelerates the differentiation of cESCs after early infection with ALV-J.

Background: Currently, the existing evidence on the correlation between serum total bilirubin (STB) and Parkinson's disease (PD) is insufficient. The objective of this study was to clarify the relationship between STB levels and PD within the US (United States) population. Methods: A cross-sectional analysis was conducted using data from 25,637 participants in the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Weighted logistic regression, smooth curve fitting, subgroup analysis, and sensitivity analyses were employed to validate the research objectives. Results: Among all eligible subjects, the mean age was 57.11 ± 11.78 years. The prevalence of PD was 1.18 % overall, with 47.86 % in males. After adjusting for multiple variables, the odds ratio [OR] (95 % confidence interval [CI]) for PD associated with STB levels in T2 and T3 were 0.59 (95 % CI = 0.40–0.85, p = 0.006) and 0.67 (95 % CI = 0.45–0.99, p = 0.045), respectively, when compared to STB levels in T1. The analysis using restricted cubic splines (RCS) indicated an L-shaped relationship between STB levels and the prevalence of PD (p for nonlinearity = 0.004), with the lowest risk observed at 10.84 μmol/L. Comparable patterns of association were noted in subgroup analyses. Furthermore, consistent findings were derived from additional sensitivity analyses. Conclusions: Our study findings indicated that the level of STB is significantly negatively correlated with the prevalence of PD. Therefore, more prospective studies need to be designed to prove the causal relationship between them.

Abstract Background Ciliary body tumor is extremely rare and treatment is challenging. The aim of this study is to present our experience in treating this rare entity, especially large tumors with more than 5 clock hours of involvement, and to evaluate the surgical outcomes and complications of local resection via partial lamellar sclerouvectomy in four cases of ciliary body tumors in China. Methods Four patients with ciliary body tumors underwent partial lamellar sclerouvectomy between October 2019 and April 2023 in Shanghai General Hospital, China. Tumor features, histopathologic findings, complications, visual acuity, and surgical outcomes were reviewed at a mean follow-up of 20.8 months. Results Four patients with a mean age of 31.8 years were included in this study. The histopathological diagnosis was adenoma of non-pigmented ciliary epithelium (ANPCE), schwannoma, and multiple ciliary body pigment epithelial cysts. The mean largest tumor base diameter was 6.00 mm (range: 2.00–10.00) and the mean tumor thickness was 3.50 mm (range: 2.00–5.00). Preoperative complications included cataract in 3 (75%) eyes, lens dislocation in 2 (50%), and secondary glaucoma in 1 (25%). Temporary ocular hypotonia was observed in one case and no other postoperative complications were observed. At a mean follow-up of 20.8 months, the best corrected visual acuity increased in 3 eyes and was stable in 1 eye. Tumor recurrence was absent in all eyes. All patients were alive at the end of follow-up. Conclusions Local tumor resection via PLSU is useful in the treatment of ciliary body tumors, including large tumors occupying more than five clock hours of pars plicata. Surgery-related complications were manageable with adequate preoperative assessment and careful operation during surgery.

Abstract Background The prevalence of ischemia with non-obstructive coronary artery disease (INOCA) is substantial, but its risk stratification has been suboptimal. Resting SPECT myocardial perfusion imaging (MPI) could provide useful heart information including spherical indices. We aimed to evaluate the prognostic value of spherical indices in individuals with INOCA. Results During a median follow-up of 47.2 ± 20.8 months, 49 (17.2%) patients experienced major adverse cardiac events (MACE). Compared to those without MACE, those with MACE had a higher shape index (SI) (0.60 ± 0.07 vs. 0.58 ± 0.06; P = 0.028) and a lower E2 (eccentricity index calculated by the QPS) (0.81 ± 0.05 vs. 0.83 ± 0.04; P = 0.019). MACE event-free survival analysis revealed significant differences in the SI and E2 among all patients (all log-rank P 0.05). Conclusion For patients with INOCA, spherical indices (especially the SI) were associated with long-term MACE, which could be a preferable indicator for risk stratification and prognostic prediction.

Climate warming induces temporally varying atmospheric water vapor (WV), yet the spatial distribution of opposing trends across global land remains elusive. Here, we use the monthly European Centre for Medium-range Weather Forecasts Reanalysis v5 dataset to discern the responses of WV changes to the rising air temperature from 1982 to 2020. Simultaneous increases in both the WV and air temperature are observed over approximately three-quarters of global land, with a median of 0.21 mm·K ^–1 , particularly evident in the tropics. Strong positive responses are primarily influenced by increasing trends in evapotranspiration (ET) and low-elevation areas. About one-fifth of global land shows a decline in WV with a median of −0.62 mm·K ^–1 , predominantly in southeastern South America and southwestern North America. Negative responses are also driven by ET trends, where strong ET enhances these effects that are less pronounced in high-altitude regions. The prevalence of a positive response is highest during September–October–November (81%), while a negative response was observed most in December–January–February (35%). The spatial distribution of negative responses generally aligns with soil desiccation patterns; soil desiccation exacerbates negative responses in humid regions due to evaporative cooling but mitigates them in arid regions due to intensified warming. This study enhances our comprehension regarding the divergent responses of atmospheric WV toward global warming.

The spontaneous oscillations within the brain are intimately linked to the hierarchical structures of the cortex, as evidenced by the cross-cortical gradient between parametrized spontaneous oscillations and cortical locations. Despite the significance of both peak frequency and peak time in characterizing these oscillations, limited research has explored the relationship between peak time and cortical locations. And no studies have demonstrated that the cross-cortical gradient can be measured by optically pumped magnetometer-based magnetoencephalography (OPM-MEG). Therefore, the cross-cortical gradient of parameterized spontaneous oscillation was analyzed for oscillations recorded by OPM-MEG using restricted maximum likelihood estimation with a linear mixed-effects model. It was validated that OPM-MEG can measure the cross-cortical gradient of spontaneous oscillations. Furthermore, results demonstrated the difference in the cross-cortical gradient between spontaneous oscillations during eye-opening and eye-closing conditions. The methods and conclusions offer potential to integrate electrophysiological and structural information of the brain, which contributes to the analysis of oscillatory fluctuations across the cortex recorded by OPM-MEG.

A millimeter-wave radar is widely accepted by the public due to its low susceptibility to interference, such as changes in light, and the protection of personal privacy. With the development of the deep learning theory, the deep learning method has been dominant in the millimeter-wave radar field, which usually uses convolutional neural networks for feature extraction. In recent years, transformer networks have also been highly valued by researchers due to their parallel processing capabilities and long-distance dependency modeling capabilities. However, traditional convolutional neural networks (CNNs) and vision transformers each have their limitations: CNNs usually overlook the global features of images and vision transformers may neglect local image continuity, and both of them may impede gesture recognition performance. In addition, whether CNN or transformer, their implementation is hindered by the scarcity of public radar gesture datasets. To address these limitations, this paper proposes a new recognition method using a local pyramid visual transformer (LPVT) based on millimeter-wave radar. LPVT can capture global and local features in dynamic gesture spectrograms, ultimately improving the recognition ability of gestures. In this paper, we mainly carried out the following two tasks: building the corresponding datasets and executing gesture recognition. First, we constructed a gesture dataset for training. In this stage, we use a 77 GHz radar to collect the echo signals of gestures and preprocess them to build a dataset. Second, we propose the LPVT network specifically designed for gesture recognition tasks. By integrating local sensing into the globally focused transformer, we improve its capacity to capture both global and local features in dynamic gesture spectrograms. The experimental results using the dataset we constructed show that the proposed LPVT network achieved a gesture recognition accuracy of 92.2%, which exceeds the performance of other networks.

Objective To investigate asymptomatic infection of hepatitis B virus(HBV) among hepatitis B vaccinated donors in Shenzhen, and analyze its serological and molecular characteristics. Methods The HBsAg ELISA positive blood samples of blood donors born after 1992 were collected. HBsAg, anti-HBs, HBeAg, anti-HBe and anti-HBc were further detected by Roche electrochemiluminescence immunoassay (ECL). BCP/PC and S regions were amplified by Nested-PCRs, HBV DNA quantification were adopted by qPCR simultaneously, and the sequences were also analyzed. Results A total of 46 632 blood samples of donors(31 612 males and 15 020 females) from December 2020 to January 2022 collected, and 99 samples with HBsAg ELISA positive were screened out. After tested by ECL, Nested-PCRs, and real-time fluorescence PCR, 61 were confirmed HBsAg positive, with the positive rate at 0.13% (61/46 632), including 49 males (0.16%, 49/31 612) and 12 females (0.08%, 12/15 020). The HBsAg positive rate of males was higher than that of females (P

Broomcorn millet (Panicum miliaceum L.) is a crop with a good ability to adapt to the environment. Over 8800 accessions have been collected in the national gene bank of China. The huge quantity of germplasms made it difficult for analysis and evaluation. Although a broomcorn millet core collection (CC) comprising 780 accessions was established, the number is still too large for researchers to explore in depth. In this study, the genetic diversity of 634 broomcorn millet accessions from the core collection was analyzed based on SSR markers. A mini-core collection (MC) containing 256 accessions was extracted. The mini-core collection accounted for less than half of the original core collection and only about 2.8% of the total resources but still provided a good representation. In addition, the results of this study validated that Shanxi is the origin of broomcorn millet, and accessions from the South region may contain novel genes. In conclusion, this study provides a comprehensive characterization of the genetic diversities of broomcorn millet core collection in China. Moreover, an MC may aid in reasonably and efficiently selecting materials for broomcorn millet breeding as researchers could screen for aimed genetic characters within a smaller scope.

Atmospheric water vapor is not only a key element of the global hydrological cycle but also the most abundant greenhouse gas. The phase transition and transportation of water vapor are essential for maintaining global energy balance and regulating hydrological processes. However, due to insufficient meteorological observational data, climate research in Africa faces significant limitations despite its substantial contribution to changes in global precipitable water vapor (PWV). In this study, we used MODIS near-infrared (NIR) PWV products and Berkeley temperature data to depict the spatial–temporal variability in PWV across Africa from 2001 to 2020. The results reveal a significant increasing trend in PWV over Africa, with an increase of 0.0158 cm/year. Nearly 99.96% of Africa shows an increase in PWV, with 88.95% of these areas experiencing statistically significant changes, particularly in central regions of Africa. The increase in PWV is more pronounced in high-value months compared to low-value months. The equatorial region of the Congo Basin exhibits higher PWV, which gradually decreases as latitude increases. Despite significant warming (0.0162 °C/year) in Africa, there is no consistent positive correlation between temperature and water vapor. A positive relationship between PWV and temperature is observed in western Africa, while a negative relationship is noted in eastern and southern Africa on an annual scale. Additionally, an increasing trend in precipitation (4.6669 mm/year) is observed, with a significant positive correlation between PWV and precipitation across most of Africa, although this relationship varies by month. These findings provide valuable insights into the comprehension of the hydrothermal variation in Africa amidst climate warming.

Ecological and environmental protection is a key issue that cannot be ignored in the process of urbanization. To achieve the goal of urban sustainable development, the dynamic and complex relationship between urbanization and the ecological environment must be coordinated. A comprehensive evaluation of 16 cities within the Chengdu-Chongqing urban agglomeration from 2011 to 2020 utilized the entropy weight method, super-SBM model, and coupling coordination degree model to analyze urbanization levels, ecological efficiency, and their interplay. The findings reveal a fluctuating descent in urbanization levels with a fluctuating upward in eco-efficiency across Chengdu-Chongqing from 2011 to 2020. The coupling coordination degree, exhibiting a dynamic, bimodal distribution, reflects the intricate balance between urbanization and ecological efficiency. A kernel density model and Tobit model further elucidate the evolving nature of the coordination degree and its principal determinants. This research underscores the role of green initiatives and consumption patterns in enhancing coordination, while governmental intervention and industrial structure emerge as critical factors undermining coordination. The study provides insights for government policy formulation, offering substantial contributions to the recalibration of urban development strategies and the optimization of city planning paradigms.

Abstract Xylanolytic enzymes, with both endo‐xylanase and arabinoxylan arabinofuranohydrolase (AXH) activities, are attractive for the economically feasible conversion of recalcitrant arabinoxylan. However, their characterization and utilization of these enzymes in biotechnological applications have been limited. Here, we characterize a novel bifunctional enzyme, rAbf43A, cloned from a bacterial consortium that exhibits AXH and endo‐xylanase activities. Hydrolytic pattern analyses revealed that the AXH activity belongs to AXHd3 because it attacked only the C(O)‐3‐linked arabinofuranosyl residues of double‐substituted xylopyranosyl units of arabinoxylan and arabinoxylan‐derived oligosaccharides, which are usually resistant to hydrolysis. The enzyme rAbf43A also liberated a series of xylo‐oligosaccharides (XOSs) from beechwood xylan, xylohexaose and xylopentaose, indicating that rAbf43A exhibited endo‐xylanase activity. Homology modelling based on AlphaFold2 and site‐directed mutagenesis identified three non‐catalytic residues (H161, A270 and L505) located in the substrate‐binding pocket essential for its dual‐functionality, while the mutation of A117 located in the −1 subsite to the proline residue only affected its endo‐xylanase activity. Additionally, rAbf43A showed significant synergistic action with the bifunctional xylanase/feruloyl esterase rXyn10A/Fae1A from the same bacterial consortium on insoluble wheat arabinoxylan and de‐starched wheat bran degradation. When rXyn10A/Fae1A was added to the rAbf43A pre‐hydrolyzed reactions, the amount of released reducing sugars, xylose and ferulic acid increased by 9.43% and 25.16%, 189.37% and 93.54%, 31.39% and 32.30%, respectively, in comparison with the sum of hydrolysis products released by each enzyme alone. The unique characteristics of rAbf43A position it as a promising candidate not only for designing high‐performance enzyme cocktails but also for investigating the structure–function relationship of GH43 multifunctional enzymes.

During vascular development, endothelial cells (ECs) undergo arterialization in response to genetic programs and shear stress-triggered mechanotransduction, forming a stable vasculature. Although the Notch receptor is known to sense shear stress and promote EC arterialization, its downstream mechanisms remain unclear. In this study, the Notch downstream miR-342-5p was found to respond to shear stress and promote EC arterialization. Shear stress upregulated miR-342-5p in a Notch-dependent manner in human umbilical vein endothelial cells (HUVECs). miR-342-5p overexpression upregulated the shear stress-associated transcriptomic signature. Moreover, miR-342-5p upregulated arterial markers and promoted EC arterialization in a Matrigel plug assay and retinal angiogenesis model. In contrast, miR-342-5p knockdown downregulated arterial markers, compromised retinal arterialization, and partially abrogated shear stress and Notch activation-induced arterial marker upregulation. Mechanistically, miR-342-5p overexpression suppressed MYC to repress EC proliferation and promote arterialization, achieved by promoting MYC protein degradation by targeting the EYA3. Consistently, EYA3 overexpression rescued miR-342-5p-mediated MYC downregulation and EC arterialization. In vivo, miR-342-5p expression was notably decreased in the ligated artery in a hindlimb ischemia model, and an intramuscular injection of miR-342-5p promoted EC arterialization and improved perfusion. In summary, miR-342-5p, a mechano-miR, mediates the effects of shear stress-activated Notch on EC arterialization and is a potential therapeutic target for ischemic diseases.

Abstract Background Various nonpharmaceutical interventions (NPIs) against COVID-19 continue to have an impact on socioeconomic and population behaviour patterns. However, the effect of NPIs on notifiable infectious diseases remains inconclusive due to the variability of the disease spectrum, high-incidence endemic diseases and environmental factors across different geographical regions. Thus, it is of public health interest to explore the influence of NPIs on notifiable infectious diseases in Yinchuan, Northwest China. Methods Based on data on notifiable infectious diseases (NIDs), air pollutants, meteorological data, and the number of health institutional personnel in Yinchuan, we first fitted dynamic regression time series models to the incidence of NIDs from 2013 to 2019 and then estimated the incidence for 2020. Then, we compared the projected time series data with the observed incidence of NIDs in 2020. We calculated the relative reduction in NIDs at different emergency response levels in 2020 to identify the impacts of NIPs on NIDs in Yinchuan. Results A total of 15,711 cases of NIDs were reported in Yinchuan in 2020, which was 42.59% lower than the average annual number of cases from 2013 to 2019. Natural focal diseases and vector-borne infectious diseases showed an increasing trend, as the observed incidence in 2020 was 46.86% higher than the estimated cases. The observed number of cases changed in respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases were 65.27%, 58.45% and 35.01% higher than the expected number, respectively. The NIDs with the highest reductions in each subgroup were hand, foot, and mouth disease (5854 cases), infectious diarrhoea (2157 cases) and scarlet fever (832 cases), respectively. In addition, it was also found that the expected relative reduction in NIDs in 2020 showed a decline across different emergency response levels, as the relative reduction dropped from 65.65% (95% CI: -65.86%, 80.84%) during the level 1 response to 52.72% (95% CI: 20.84%, 66.30%) during the level 3 response. Conclusions The widespread implementation of NPIs in 2020 may have had significant inhibitory effects on the incidence of respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases. The relative reduction in NIDs during different emergency response levels in 2020 showed a declining trend as the response level changed from level 1 to level 3. These results can serve as essential guidance for policy-makers and stakeholders to take specific actions to control infectious diseases and protect vulnerable populations in the future.

Abstract It is challenging to grow atomically thin non-van der Waals perovskite due to the strong electronic coupling between adjacent layers. Here, we present a colloid-driven low supersaturation crystallization strategy to grow atomically thin Cs3Bi2Br9. The colloid solution drives low-concentration solute in a supersaturation state, contributing to initial heterogeneous nucleation. Simultaneously, the colloids provide a stable precursor source in the low-concentration solute. The surfactant is absorbed in specific crystal nucleation facet resulting in the anisotropic growth of planar dominance. Ionic perovskite Cs3Bi2Br9 is readily grown from monolayered to six-layered Cs3Bi2Br9 corresponding to thicknesses of 0.7, 1.6, 2.7, 3.6, 4.6 and 5.7 nm. The atomically thin Cs3Bi2Br9 presents layer-dependent nonlinear optical performance and stacking-induced second harmonic generation. This work provides a concept for growing atomically thin halide perovskite with non-van der Waal structures and demonstrates potential application for atomically thin single crystals’ growth with strong electronic coupling between adjacent layers.

Time–frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time–frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time–frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time–frequency spectrum with Superlet transform. Then, the time–frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation.

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.

ABSTRACTThe antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual’s susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

Abstract Purpose This single-arm, prospective, exploratory study investigated the effectiveness of ultra-low-dose radiotherapy in the treatment of ocular adnexal lymphoma (OAL). Patients and methods Patients with pathologically confirmed ocular adnexal low-grade non-Hodgkin lymphoma (predominantly mucosa-associated lymphoid tissue, MALT or follicular lymphoma) were included and treated with ultra-low-dose radiotherapy consisting of 2 successive fractions of 2 Gy at our institution between 2019 and 2021. Disease response was assessed clinically and radiographically within 4 months and at 3 to 6-month intervals after treatment. Data collected included rates of overall response, complete response (CR), partial response (PR), lesion size, and acute/chronic ocular toxic effects. Results Sixteen patients with median age of 63 years (range 23–86 years) were included in the study. The histological subtypes included MALT (11 patients; 69%); follicular lymphoma (2 patients; 12%); Lymphoid hyperplasia (3 patient, 19%). At a median follow-up time of 15.5 months (range 5.0–30.0 months), the overall response rate was 88%, with a CR rate of 75% (n = 12) and a PR rate of 13% (n = 2). The average lesion area was reduced from 117.9 ± 60.4 mm2 before radiation therapy to 38.7 ± 46.0mm2 at initial evaluation post radiation therapy (P = 0.002, n = 16), and to 8.5 ± 21.2 mm2 (P

Self-collection of saliva samples has attracted considerable attention in recent years, particularly during the coronavirus disease 2019 pandemic. However, studies investigating the detection of other common respiratory pathogens in saliva samples are limited. In this study, nasopharyngeal swabs (NPS), oropharyngeal swabs (OPS), and “hock-a-loogie” saliva (HLS) were collected from 469 patients to detect 13 common respiratory pathogens. Overall positivity rates for NPS (66.1 %), HLS (63.5 %), and OPS (57.8 %) were statistically different (P = 0.028), with an overall concordance of 72.7 %. Additionally, detection rates for NPS (85.9 %) and HLS (83.2 %) for all pathogens were much higher than for OPS (73.3 %). Coronavirus and human rhinovirus were most frequently detected pathogens in NPS (P

BackgroundThyroid eye disease (TED) is the most frequent orbital disease in adults and is characterized by the accumulation of orbital adipose tissue (OAT). It can lead to eyelid retraction or even vision loss. Orbital decompression surgery serves as the primary treatment for inactive TED by removing the excess OAT. However, there is a lack of alternative treatments to surgery due to the unclear understanding of the pathogenesis, particularly the metabolic features. Accordingly, our study was implemented to explore the content and features of metabolites of OATs from TED patients.MethodThe OATs used in the current study were obtained from the orbital decompression surgery of seven patients with inactive TED. We also collected control OATs from eye surgical samples of five individuals with no history of autoimmune thyroid diseases, TED, or under non-inflammatory conditions. The liquid chromatography mass spectrometer was used for the measurements of the targeted metabolites. Afterwards, we performed differential metabolite assay analysis and related pathway enrichment analysis.ResultsIn our study, a total of 149 metabolite profiles were detected in all participants. There were significant differences in several metabolite profiles between the TED group and the control group, mainly including uric acid, oxidized glutathione, taurine, dGMP, oxidized glutathione 2, uracil, hexose-phosphate, 1-methylnicotinamide, D-sedoheptulose 1,7-bisphosphate, and uridine 5′-monophosphate (all p-value < 0.05). The TED-related pathways identified included purine metabolism, beta-alanine metabolism, glutathione metabolism (p-values < 0.05). Our study found overlaps and differences including uric acid and uracil, which are in accordance with metabolites found in blood of patients with TED from previous study and several newly discovered metabolite by our study such as hexose-phosphate, 1-methylnicotinamide, D-sedoheptulose 1,7-bisphosphate, compared to those tested from blood, OAT, or urine samples reported in previous studies.ConclusionThe findings of our study shed light on the metabolic features of OAT in individuals with TED. These results may help identify new treatment targets for TED, providing potential avenues for developing alternative treatments beyond ophthalmic surgery.

A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy. Therefore, this study proposes a method to automatically estimate a suitable threshold. Time–frequency transformations are performed on the evoked state data to obtain the neural signal of interest and the noise signal in a specific time–frequency band, which are then used to construct the objective function describing the degree of noise suppression and signal distortion. The optimal value of the threshold in the selected range is obtained using the weighted-sum method. Our method was tested on two classical subspace projection algorithms using simulation and two sensory stimulation experiments. The thresholds estimated by the proposed method enabled the algorithms to achieve the best waveform recovery and source location error. Therefore, the threshold selected in this method enables subspace projection algorithms to achieve the best balance between noise removal and neural signal preservation in subsequent MEG analyses.

Background and purpose: Golgi membrane protein 1 (GOLM1) plays the role of an oncogene in lung adenocarcinoma (LUAD), however, the effects of GOLM1 on the proliferation, invasion and migration of LUAD cells and its mechanism are not clear yet. This study investigated the effects of GOLM1 on the proliferation, invasion and migration of LUAD cells and its mechanism of action. Methods: We selected cancer tissues and corresponding paracancerous tissue specimens from 90 LUAD patients who underwent surgical resection in Karamay Central Hospital from April 2019 to April 2021. The expression of GOLM1 protein in LUAD tissues and paracancerous tissues was detected by immunohistochemistry, and the relationship between GOLM1 protein expression and clinicopathological characteristics of LUAD tissues was analyzed. Western blot was used to detect the expression of GOLM1 protein in human lung epithelial cells BEAS-2B and human lung adenocarcinoma H460, A549, PG49 and H1299 cells. Lung adenocarcinoma A549 cells in logarithmic growth stage were randomly divided into blank group (cells not transfected), GOLM1 small interfering RNA negative control (si-NC) group (cells transfected with si-NC), GOLM1 small interfering RNA (si-GOLM1) group (cells transfected with si-GOLM1), insulin-like growth factor-1 (IGF-1) group [10 μmol/L phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway activator IGF-1 for 30 min] and si-GOLM1+IGF-1 group (after treatment with 10 μmol/L IGF-1 for 30 min, si-GOLM1 was transfected). Cell counting kit-8 method was used to detect cell proliferation in each group of lung adenocarcinoma A549 cells. Scratch test was used to detect cell migration in each group of lung adenocarcinoma A549 cells. Transwell experiment was used to detect cell invasion in each group of lung adenocarcinoma A549 cells. Western blot was used to detect the expressions of GOLM1 and PI3K/AKT/mTOR signaling pathway related proteins in each group of lung adenocarcinoma A549 cells. Xenograft model was constructed by subcutaneously injecting A549 cells on the right side of BALB/c nude mice, which were divided into: nude mice blank group, nude mice si-NC group, nude mice si-GOLM1 group, nude mice IGF-1 group, nude mice si-GOLM1+IGF-1 group, with 6 mice in each group. The nude mice were sacrificed six weeks after injection, the tumor was collected, and the weight and volume of the tumor were measured. Results: The results of immunohistochemistry showed that the positive expression rate of GOLM1 protein was significantly higher in LUAD tissues than in adjacent tissues (P0.05). Compared with BEAS-2B cells, the relative expression level of GOLM1 protein in human lung adenocarcinoma H460, A549, PG49 and H1299 cells was significantly increased (P0.05). Compared with the nude mice blank group and nude mice si-NC group, the mass and volume of transplanted tumors in the nude mice si-GOLM1 group were significantly reduced, while the mass and volume of transplanted tumors in the nude mice IGF-1 group were significantly increased (P

BackgroundNeutrophil/high-density lipoprotein (HDL) ratio (NHR), monocyte/HDL ratio (MHR), lymphocyte/HDL ratio (LHR), platelet/HDL ratio (PHR), systemic immune-inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) have been recently investigated as novel inflammatory markers. Herein, the correlation was investigated between these inflammatory biomarkers and peripheral arterial disease (PAD) in type 2 diabetes mellitus (T2DM) patients.MethodsIn this retrospective observational study, the hematological parameter data of 216 T2DM patients without PAD (T2DM-WPAD) and 218 T2DM patients with PAD (T2DM-PAD) at Fontaine stages II, III or IV stage had been collected. Differences in NHR, MHR, LHR, PHR, SII, SIRI, and AISI were analyzed, and receiver operating characteristic (ROC) curves were used to analyze the diagnostic potential of these parameters.ResultsThe levels of NHR, MHR, PHR, SII, SIRI and AISI in T2DM-PAD patients were significantly higher than in T2DM-WPAD patients (P < 0.001). They were correlated with disease severity. Further, multifactorial logistic regression analyses showed that higher NHR, MHR, PHR, SII, SIRI, and AISI might be independent risk factors for T2DM-PAD (P < 0.001). The areas under the curve (AUCs) of the NHR, MHR, PHR, SII, SIRI, and AISI for T2DM-PAD patients was 0.703, 0.685, 0.606, 0.648, 0.711, and 0.670, respectively. The AUC of the NHR and SIRI combined model was 0.733.ConclusionThe levels of NHR, MHR, PHR, SII, SIRI, and AISI were higher in T2DM-PAD patients, and they were independently linked with its clinical severity. The combination model of NHR and SIRI was most valuable for predicting T2DM – PAD.

Lactate dehydrogenase (LDH) is one of the important enzymes for anaerobic glycolysis and gluconeogenesis. It could catalyze pyruvate to form lactic acid, which had high application value in food fermentation industry. However, LDH was easily affected by high temperature, which leaded to the decline of lactic acid production. To study the effects of different temperature on the conformation and activity of LDH, molecular dynamics simulations at four different temperatures (37, 55, 70 and 85 °C) were performed for 80 ns, respectively. The overall conformational changed and the differences of enzyme active centers were analyzed. The results showed that LDH was relatively stable at 37 and 55 °C, and the root mean square error, root mean square fluctuation, radius gyration and solvent accessible surface area of LDH increased significantly at 70 and 85 °C. Moreover, the secondary structure of protein had changed greatly at 85 °C, which indicated that high temperature would lead to protein conformational instability. Comparing the binding ability of pyruvate at 37 and 85 °C, which was the substrate of the enzyme, we found that high temperature would increase the distance between the residues of pyruvate binding sites, and then destroy the microenvironment of substrate molecular binding. Therefore, the denaturation of LDH occurred when the temperature exceeded 70 °C, and the denaturation degree was positively correlated with the increase of temperature. This would lead to the loss of its enzyme activity, which was not conducive to the application value in food industry. In this study, the effects of four different temperatures on LDH were analyzed at atomic level, and the key information of enzyme activity and conformation changes were revealed, which provided theoretical support for the selection of appropriate temperature in the fermentation process of lactic acid products.

Abstract A dopant-free hole transport layer with high mobility and a low-temperature process is desired for optoelectronic devices. Here, we study a metal–organic framework material with high hole mobility and strong hole extraction capability as an ideal hole transport layer for perovskite solar cells. By utilizing lifting-up method, the thickness controllable floating film of Ni3(2,3,6,7,10,11-hexaiminotriphenylene)2 at the gas–liquid interface is transferred onto ITO-coated glass substrate. The Ni3(2,3,6,7,10,11-hexaiminotriphenylene)2 film demonstrates high compactness and uniformity. The root-mean-square roughness of the film is 5.5 nm. The ultraviolet photoelectron spectroscopy and the steady-state photoluminescence spectra exhibit the Ni3(HITP)2 film can effectively transfer holes from perovskite film to anode. The perovskite solar cells based on Ni3(HITP)2 as a dopant-free hole transport layer achieve a champion power conversion efficiency of 10.3%. This work broadens the application of metal–organic frameworks in the field of perovskite solar cells. Graphical Abstract

Synthetic aperture radar (SAR) images have special physical scattering characteristics owing to their unique imaging mechanism. Traditional deep learning algorithms usually extract features from real-valued SAR images in a purely data-driven manner, which may ignore some important physical scattering characteristics and sacrifice some useful target information in SAR images. This undoubtedly limits the improvement in performance for SAR target recognition. To take full advantage of the physical information contained in SAR images, a complex-valued network guided with sub-aperture decomposition (CGS-Net) for SAR target recognition is proposed. According to the fact that different targets have different physical scattering characteristics at different angles, the sub-aperture decomposition is used to improve accuracy with a multi-task learning strategy. Specifically, the proposed method includes main and auxiliary tasks, which can improve the performance of the main task by learning and sharing useful information from the auxiliary task. Here, the main task is the target recognition task, and the auxiliary task is the target reconstruction task. In addition, a complex-valued network is used to extract the features from the original complex-valued SAR images, which effectively utilizes the amplitude and phase information in SAR images. The experimental results obtained using the MSTAR dataset illustrate that the proposed CGS-Net achieved an accuracy of 99.59% (without transfer learning or data augmentation) for the ten-classes targets, which is superior to the other popular deep learning methods. Moreover, the proposed method has a lightweight network structure, which is suitable for SAR target recognition tasks because SAR images usually lack a large number of labeled data. Here, the experimental results obtained using the small dataset further demonstrate the excellent performance of the proposed CGS-Net.

• Intercropping intercepted more light than sole peanut but less than sole maize.• Maize light use efficiency (LUE) increased with plant density in the intercropping.• Intercropping did not affect LUE of maize but increased peanut LUE.Intercropping increases crop yields by optimizing light interception and/or use efficiency. Although intercropping combinations and metrics have been reported, the effects of plant density on light use are not well documented. Here, we examined the light interception and use efficiency in maize-peanut intercropping with different maize plant densities in two row configurations in semiarid dryland agriculture over a two-year period. The field experiment comprised four cropping systems, i.e. monocropped maize, monocropped peanut, maize-peanut intercropping with two rows of maize and four rows of peanut, intercropping with four rows of maize and four rows of peanut, and three maize plant densities (3.0, 4.5 and 6.0 plants m−1 row) in both monocropped and intercropping maize. The mean total light interception in intercropping across years and densities was 779 MJ·m−2, 5.5% higher than in monocropped peanut (737 MJ·m−2) and 7.6% lower than in monocropped maize (843 MJ·m−2). Increasing maize density increased light interception in monocropped maize but did not affect the total light interception in the intercrops. Across years the LUE of maize was 2.9 g·MJ−1 and was not affected by cropping system but increased with maize plant density. The LUE of peanut was enhanced in intercropping, especially in a wetter year. The yield advantage of maize-peanut intercropping resulted mainly from the LUE of peanut. These results will help to optimize agronomic management and system design and provide evidence for system level light use efficiency in intercropping.

Natural extracellular vesicles (EVs) play important roles in many life processes such as in the intermolecular transfer of substances and genetic information exchanges. Investigating the origins and working mechanisms of natural EVs may provide an understanding of life activities, especially regarding the occurrence and development of diseases. Additionally, due to their vesicular structure, EVs (in small molecules, nucleic acids, proteins, etc.) could act as efficient drug-delivery carriers. Herein, we describe the sources and biological functions of various EVs, summarize the roles of EVs in disease diagnosis and treatment, and review the application of EVs as drug-delivery carriers. We also assess the challenges and perspectives of EVs in biomedical applications.

Salinity severely inhibits growth and reduces yield of salt-sensitive plants like wheat, and this effect can be alleviated by plant growth regulators and phytohormones, among which abscisic acid (ABA) plays a central role in response to various stressful environments. ABA is highly photosensitive to light disruption, which this limits its application. Here, based on pyrabactin (a synthetic ABA agonist), we designed and synthesized a functional analog of ABA and named B2, then evaluated its role in salt resistance using winter wheat seedlings. The phenotypes showed that B2 significantly improved the salt tolerance of winter wheat seedlings by elevating the biomass. The physiological analysis found that B2 treatment reduced the generation rate of O2–, electrolyte leakage, the content of proline, and the accumulation of malonaldehyde (MDA) and H2O2 and also significantly increased the contents of endogenous hormones zeatin riboside (ZA) and gibberellic acid (GA). Further biochemical analysis revealed that the activities of various antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), and ascorbate peroxidase (APX), were enhanced by B2, and the activities of antioxidase isozymes SOD3, POD1/2, and APX1/2 were particularly increased, largely resembling ABA treatment. The abiotic stress response-related gene TaSOS1 was significantly upregulated by B2, while the TaTIP2;2 gene was suppressed. In conclusion, an ABA analog B2 was capable to enhance salt stress tolerance in winter wheat seedlings by stimulating the antioxidant system, providing a novel regulator for better survival of crops in saline soils and improving crop yield.

Abstract Dominant species in intercropping experience less resource competition compared with its monoculture. This reduced competition for resources may allow cultivating the dominant species at an increased density in intercropping to obtain greater yield. However, experimental results are inconclusive when the optimal within row density in the sole crop is not well established. Here, we conducted a two‐year experiment to test the hypothesis that optimal within row plant density of dominant species in intercropping would be higher in the intercrop than in the sole crop. We tested three maize densities (3, 4.5, and 6 plants m−1) in both sole maize and two replacement designed intercrops. The row configurations of two intercrops are two rows maize intercropped with four rows peanut (M2P4) and four rows maize intercropped with four rows peanut (M4P4). Peanut was grown at the same plant density of 12 plants m−1 row in both sole crop and intercrops. The results indicated that increasing maize density from the optimal density in monoculture is not worthy of promotion to improve yield in intercropping, which denied our hypothesis. The land equivalent ratios (LER) in the dry year (2017) were higher than the wet year (2016). Maize yields per unit area of the whole intercropping system were highest with densities of 4.5 and 6 plants m−1 row, with no significant difference between these two densities. Maximum maize yields in sole cropping were obtained with maize densities of 6 plants m−1 row. Intercropping provided higher yields at low and intermediate sole crop maize densities, but not at high sole crop maize density. Average land equivalent ratios at 3, 4.5, and 6 plants m−1 of maize were 1.09, 1.04, and 0.95 in 2016, and 1.07, 1.10, and 1.02 in 2017. Our results suggest that intercropping performs better at conditions with less resources than adequate resources.

Glass Fiber reinforced polymers (GFRPs) are widely used and play an important role in modern society. The multilayer structure of GFRPs can lead to delamination defects during production and service, which can have a significant impact on the integrity and safety of the equipment. Therefore, it is important to monitor these delamination defects during equipment service in order to evaluate their effects on equipment performance and lifespan. Microwave imaging testing, with its high sensitivity and noncontact nature, shows promise as a potential method for detecting delamination defects in GFRPs. However, there is currently limited research on the quantitative characterization of defect images in this field. In order to achieve visual quantitative nondestructive testing (NDT), we propose a 2D-imaging visualization and quantitative characterization method for delamination defects in GFRP, and realize the combination of visual detection and quantitative detection. We built a microwave testing experimental system to verify the effectiveness of the proposed method. The results of the experiment indicate the effectiveness and innovation of the method, which can effectively detect all delamination defects of 0.5 mm thickness inside GFRP with high accuracy, the signal-to-background ratio (SBR) of 2D imaging can reach 4.41 dB, the quantitative error of position is within 0.5 mm, and the relative error of area is within 11%.

Glass fiber-reinforced polymer (GFRP) is widely used in engineering fields involving aerospace, energy, transportation, etc. If internal buried defects occur due to hostile environments during fabrication and practical service, the structural integrity and safety of GFRP structures would be severely undermined. Therefore, it is indispensable to carry out effective quantitative nondestructive testing (NDT) of internal defects buried within GFRP structures. Along with the development of composite materials, microwave NDT is promising in non-intrusive inspection of defects in GFRPs. In this paper, quantitative screening of the subsurface impact damage and air void in a unidirectional GFRP via microwave reflectometry was intensively investigated. The influence of the microwave polarization direction with respect to the GFRP fiber direction on the reflection coefficient was investigated by using the equivalent relative permittivity calculated with theoretical analysis. Following this, a microwave NDT system was built up for further investigation regarding the imaging and quantitative evaluation of buried defects in GFRPs. A direct-wave suppression method based on singular-value decomposition was proposed to obtain high-quality defect images. The defect in-plane area was subsequently assessed via a proposed defect-edge identification method. The simulation and experimental results revealed that (1) the testing sensitivity to buried defects was the highest when the electric-field polarization direction is parallel to the GFRP fiber direction; and (2) the averaged evaluation accuracy regarding the in-plane area of the buried defect reached approximately 90% by applying the microwave reflectometry together with the proposed processing methods.