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Abstract Atherosclerosis (AS) is one of the most common causes of death from cardiovascular disease, and low folic acid (FA) levels have been reported to be strongly associated with an increased risk of AS. We aimed to obtain causal estimates of the association between FA and AS and to quantify the mediating role of known modifiable risk factors. Based on the largest genome-wide association study (GWAS) from the IEU Open GWAS Project for all human studies, we conducted a two-sample Mendelian randomization (MR) study of genetically predicted FA and AS. A two-step MR design was then used to assess the causal mediating effect of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) on the relationship between FA and AS. This MR analysis showed that genetically determined FA levels [IVW: Odds Ratio (OR) = 0.623, 95% CI 0.421–0.924, P = 0.018] were associated with a reduced risk of AS. Inverse variance weighted (IVW) MR analysis also showed that genetically predicted FA was positively correlated with HDL-C levels (OR = 1.358, 95% CI 1.029–1.792, P = 0.031) and negatively correlated with LDL-C (OR = 0.956, 95% CI 0.920–0.994, P = 0.023) and TG levels (OR = 0.929, 95% CI 0.886–0.974, P = 0.003). LDL-C, HDL-C, and TG mediate 3.00%, 6.80%, and 4.40%, respectively, of the total impact of FA on AS. The combined effect of these three factors accounts for 13.04% of the total effect. Sensitivity analysis verifies the stability and reliability of the results. These results support a potential causal protective effect of FA on AS, with considerable mediation through many modifiable risk factors. Thus, interventions on levels of LDL-C, HDL-C, and TG have the potential to substantially reduce the burden of AS caused by low FA.

Abstract Bacterial diseases are one of the most common issues that result in crop loss worldwide, and the increasing usage of chemical pesticides has caused the occurrence of resistance in pathogenic bacteria and environmental pollution problems. Nanomaterial mediated gene silencing is starting to display powerful efficiency and environmental friendliness for improving plant disease resistance. However, the internalization of nanomaterials and the physiological mechanisms behind nano-improved plant disease resistance are still rarely understood. We engineered the polyethyleneimine (PEI) functionalized gold nanoparticles (PEI-AuNPs) with fluorescent properties and ROS scavenging activity to act as siRNA delivery platforms. Besides the loading, protection, and delivery of nucleic acid molecules in plant mature leaf cells by PEI-AuNPs, its fluorescent property further enables the traceability of the distribution of the loaded nucleic acid molecules in cells. Additionally, the PEI-AuNPs-based RNAi delivery system successfully mediated the silencing of defense-regulated gene AtWRKY1. Compared to control plants, the silenced plants performed better resistance to Pseudomonas syringae, showing a reduced bacterial number, decreased ROS content, increased antioxidant enzyme activities, and improved chlorophyll fluorescence performance. Our results showed the advantages of AuNP-based RNAi technology in improving plant disease resistance, as well as the potential of plant nanobiotechnology to protect agricultural production.

Abstract Soybean is a major source of protein and edible oil worldwide. Originating from the Huang-Huai-Hai region, which has a temperate climate, soybean has adapted to a wide latitudinal gradient across China. However, the genetic mechanisms responsible for the widespread latitudinal adaptation in soybean, as well as the genetic basis, adaptive differentiation, and evolutionary implications of theses natural alleles, are currently lacking in comprehensive understanding. In this study, we examined the genetic variations of fourteen major gene loci controlling flowering and maturity in 103 wild species, 1048 landraces, and 1747 cultivated species. We found that E1, E3, FT2a, J, Tof11, Tof16, and Tof18 were favoured during soybean improvement and selection, which explained 75.5% of the flowering time phenotypic variation. These genetic variation was significantly associated with differences in latitude via the LFMM algorithm. Haplotype network and geographic distribution analysis suggested that gene combinations were associated with flowering time diversity contributed to the expansion of soybean, with more HapA clustering together when soybean moved to latitudes beyond 35°N. The geographical evolution model was developed to accurately predict the suitable planting zone for soybean varieties. Collectively, by integrating knowledge from genomics and haplotype classification, it was revealed that distinct gene combinations improve the adaptation of cultivated soybeans to different latitudes. This study provides insight into the genetic basis underlying the environmental adaptation of soybean accessions, which could contribute to a better understanding of the domestication history of soybean and facilitate soybean climate-smart molecular breeding for various environments.

Abstract Background Neuropsychiatric disorders and cervical cancer exert substantial influences on women’s health. Furthermore, neuropsychiatric disorders frequently manifest as common symptoms in cancer patients, potentially increasing the risk of malignant neoplasms. This study aimed to identify neuropsychiatric disorders that are genetically and causally related to cervical cancer and to investigate the molecular mechanisms underlying these associations. Methods GWAS data related to nine neuropsychiatric disorders, namely, schizophrenia, bipolar disorder, autism spectrum disorder, Parkinson’s disease, anxiety, Alzheimer’s disease, mood disorders, depression, and alcohol dependence, were obtained to calculate heritability (h 2) and genetic correlation (rg) with cervical cancer using linkage disequilibrium score regression (LDSC). Mendelian randomization (MR) analysis of the two cohorts was employed to assess the causal effects. Shared gene expression pattern analysis was subsequently conducted to investigate the molecular mechanism underlying these significant associations. Results Anxiety, mood disorders, depression, and alcohol dependence were genetically correlated with cervical cancer (all adjusted P

Abstract Achieving effective manipulation of perpendicular exchange bias effect remains an intricate endeavor, yet it stands a significance for the evolution of ultra-high capacity and energy-efficient magnetic memory and logic devices. A persistent impediment to its practical applications is the reliance on external magnetic fields during the current-induced switching of exchange bias in perpendicularly magnetized structures. This study elucidates the achievement of a full electrical manipulation of the perpendicular exchange bias in the multilayers with an ultrathin antiferromagnetic layer. Owing to the anisotropic epitaxial strain in the 2-nm-thick IrMn3 layer, the considerable exchange bias effect is clearly achieved at room temperature. Concomitantly, a specific global uncompensated magnetization manifests in the IrMn3 layer, facilitating the switching of the irreversible portion of the uncompensated magnetization. Consequently, the perpendicular exchange bias can be manipulated by only applying pulsed current, notably independent of the presence of any external magnetic fields.

Abstract Human hippocampal organoids (hHOs) derived from human induced pluripotent stem cells (hiPSCs) have emerged as promising models for investigating neurodegenerative disorders, such as schizophrenia and Alzheimer’s disease. However, obtaining the electrical information of these free-floating organoids in a noninvasive manner remains a challenge using commercial multi-electrode arrays (MEAs). The three-dimensional (3D) MEAs developed recently acquired only a few neural signals due to limited channel numbers. Here, we report a hippocampal cyborg organoid (cyb-organoid) platform coupling a liquid metal-polymer conductor (MPC)-based mesh neuro-interface with hHOs. The mesh MPC (mMPC) integrates 128-channel multielectrode arrays distributed on a small surface area (~2*2 mm). Stretchability (up to 500%) and flexibility of the mMPC enable its attachment to hHOs. Furthermore, we show that under Wnt3a and SHH activator induction, hHOs produce HOPX+ and PAX6+ progenitors and ZBTB20+PROX1+ dentate gyrus (DG) granule neurons. The transcriptomic signatures of hHOs reveal high similarity to the developing human hippocampus. We successfully detect neural activities from hHOs via the mMPC from this cyb-organoid. Compared with traditional planar devices, our non-invasive coupling offers an adaptor for recording neural signals from 3D models.

Summary: The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. We used gene co-essentiality analysis to identify an unappreciated relationship between TSC22D2, WNK1, and NRBP1 in regulating cell volume homeostasis. All of these genes have paralogs and are functionally buffered for osmo-sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK, and NRBP family members physically associate into biomolecular condensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans revealed that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is accompanied by rapid IDR length expansion in WNK-family kinases. Our study reveals that TSC22D, WNK, and NRBP genes evolved in metazoans to co-regulate rapid cell volume changes in response to osmolarity.

BackgroundThis study aimed to determine the diagnostic accuracy of CA125, HE4, systemic immune-inflammation index (SII), prognostic nutritional index (PNI), fibrinogen-to-albumin ratio (FAR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and the combination of the six inflammatory-nutritional markers for ovarian cancer (OC) to identify the best diagnostic indicator for OC early diagnosis. An extensive study was performed to establish the connection between these indicators and the pathological aspects of OC.MethodsA total of 170 individuals were included in this study, with 87 diagnosed with OC and 83 with benign ovarian tumors (BOTs). The diagnostic abilities of the variables were evaluated by calculating sensitivity, specificity, and area under the ROC curves. Through the use of DCA, we evaluated the variables’ clinical value in the discrimination of ovarian masses.ResultsAll markers showed significant diagnostic power for OC. CA125, HE4, SII, FAR, and MLR levels significantly increased from the BOTs group to the early-stage OC group. The advanced-stage OC group had significantly lower PNI values compared to the early-stage OC group but significantly higher levels of CA125, HE4, SII, NLR, and FAR. Moreover, the OC group with lymph node metastasis exhibited significantly higher levels of CA125, HE4, SII, NLR, PLR, and FAR, in contrast to the non-metastatic group, while PNI levels were significantly lower. Categorical factors, such as histological grade and pathological classification, showed noticeable discrepancies in CA125 and HE4 levels. NLR was significantly different among the pathological type groups. Among the six inflammatory-nutritional markers, the FAR displayed the greatest diagnostic value. In the analysis of logistic regression, it was observed that a combination marker containing all six inflammatory-nutritional markers exhibited a notably higher AUC value (0.881; 95% CI, 0.823 - 0.926) than any of the individual marker.ConclusionPNI, NLR, PLR, MLR, SII, and FAR showed excellent diagnostic performance for OC. The combination of these markers demonstrated a superior diagnostic capability compared to each individual one. The systemic inflammatory indicators may be helpful to diagnose OC.

Abstract Background The balance of vaginal microecology is closely related to human papillomavirus (HPV) infection and cervical lesions. This study aims to investigate the relationship between bacterial vaginosis (BV) and HPV infection. Methods In total, 1,310 individuals from the National Health and Nutrition Examination Survey (NHANES, 2003–2004) were included in this study. Logistic regression and subgroup analyses were used to examine the association between BV and HPV infection. Results A significant positive association was observed between BV and HPV infection in women after adjustment for other confounders (OR = 1.47, 95% confidence interval [CI]: 1.15–1.88). In subgroup analyses, we have found this positive correlation was most prominent among Mexican Americans (OR = 1.83, 95% CI: 1.08–3.08) and non-Hispanic blacks (OR = 1.81, 95% CI: 1.08–3.04). Conclusions This cross-sectional study demonstrated a positive association between BV and HPV infection in women.

The instance segmentation of overlapping cells in smear images of epithelial cells is challenging due to the significant overlap and adhesion between the cells’ translucent cytoplasm. In this paper, an improved single-stage instance segmentation network called VoVNet-BiFPN-SOLO (VB-SOLO) is proposed to address this problem. The model takes SOLOv2 model as its main frame. Firstly, the backbone network uses Efficient Channel Attention (ECA) to optimize the VoVNetv2 network to increase the information interaction across channels and enhance the extraction of cell instance features. Secondly, the bi-directional feature pyramid network (BiFPN) is introduced to connect with the new backbone. BiFPN can achieve the weighted fusion of features with different resolutions from bottom to top and keep more shallow semantic information in the network. Finally, the Convolutional Block Attention Module (CBAM) is added to the mask branch to improve cell segmentation results in feature maps. Experimental results on the publicly available datasets CISD and Cx22 demonstrate the effectiveness of the VB-SOLO model, achieving a DCP of 0.966 and 0.940 and a FNRO of 0.055 and 0.03. Compared to the original SOLOv2 algorithm, the proposed method achieved improvements in DCP of 1.3% and 1.1% respectively. Additionally, comparative tests with multiple instance segmentation networks have shown that the proposed improved network can achieve a better balance between segmentation accuracy and efficiency. The experimental results demonstrate the effectiveness of the proposed network improvements and the potential of single-stage instance segmentation networks in overlapping cell image segmentation.

Trachinotus ovatus, a valuable marine fish, is primarily farmed in the South China Sea. Intensive aquaculture can lead to genetic uniformity and disease risks. Additionally, the high cost of genome sequencing restricts knowledge of genetic variation, hindering genetic analysis and breeding advancements. This study investigated the genetic diversity and structure of Trachinotus ovatus populations within the South China Sea aquaculture context, with the goal of strengthening sustainability. Additionally, the study also enhanced breeding strategies by developing a high-quality haplotype reference panel and an efficient imputation process. Through high-throughput sequencing (depth＞20X), 173 samples from three key breeding sites (SanYa, Hainan; Zhanjiang, Guangdong; and Beihai, Guangxi) were analyzed, revealing substantial genetic diversity and distinct population structures. Notably, the Beihai (BH) population exhibited significant stratification, suggesting regional genetic uniqueness. Low levels of genomic inbreeding coefficient and the identification of unique SNP loci across populations underscored the genetic richness within these Trachinotus ovatus communities. A major constructed of this work is the creation of the first high-quality haplotype reference panel for the species, demonstrating genotype imputation's viability as a cost-effective alternative for large-scale genetic studies in aquaculture. In particular, a Shapeit reference panel with 5476,550 SNPs was created, excelling in accuracy across various depths, notably achieving up to 95.8 % imputation accuracy at 1X sequencing depth. This high accuracy across populations shows the importance of genetic diversity in the panel. This research not only advances the understanding of Trachinotus ovatus genetic foundations but also provides crucial insights for conservation efforts and genetic analysis. By establishing a robust haplotype reference panel for Trachinotus ovatus helps lower the costs of future genetic research and variation studies, this study lays the foundation for sustainable aquaculture practices and breeding programs.

The assembly and succession of the gut microbiota are important events in animal growth and have a significant impact on the productivity of aquaculture organisms, which can be influenced by the environment, growth stages, and dietary changes. However, little is known about how the growth of aquaculture organisms and dietary differences during growth affect the assembly of the gut microbiota. In this study, we fed golden pompano (Trachinotus ovatus) a regular diet and a high-fat, high-protein diet, respectively. We then used bacterial 16 S rRNA gene sequencing to study the gut microbiota at different growth stages and under different dietary conditions. We found that the gut microbiota of T. ovatus changes in response to different dietary conditions. Moreover, this divergence does not change with the growth of the host. This suggests that dietary differences largely explained the gut microbiota succession, while growth stage had no significant influence on gut microbiota succession in T. ovatus from 30 to 120 dph. This study, which includes the effects of growth stage and diet, increases our understanding of how the gut microbiota of the T. ovatus assembles and colonizes and also provides new insights into the study of the gut microbiota of other aquaculture fish.

ObjectiveTo investigate the relationship between dietary inflammatory index (DII) scores and infertility in US adults aged 18 to 45.MethodsData were gathered from the 2013-2018 National Health and Nutrition Examination Survey (NHANES). In total, 3496 women were included in the study. To examine the relationship between DII, EDII and infertility, a weighted multivariable logistic regression analysis using continuous factors or categorical variables grouped by quartiles was conducted. Using subgroup analysis stratified based on DII and infertility features, the association between DII and infertility has been further studied. In order to determine whether there was a nonlinear relationship between DII and infertility, restricted cubic spline (RCS) analysis was carried out.ResultsFor statistical analysis, a total of 3496 individuals — 367 patients with infertility and 3129 persons without infertility — were included. A multivariable logistic regression study revealed a positive relationship between DII and infertility. A significant difference in subgroup analysis was shown in age group and race, although RCS analysis demonstrated nonlinear relationship between the DII and infertility.ConclusionFor participants aged 18-45 years, higher DII scores were positively correlated with infertility. In addition, anti-inflammatory diets might improve infertility outcomes.

Abstract Verticillium dahliae is a soil-borne hemibiotrophic fungal pathogen that threatens cotton production worldwide. In this study, we assemble the genomes of two V. dahliae isolates: the more virulence and defoliating isolate V991 and nondefoliating isolate 1cd3-2. Transcriptome and comparative genomics analyses show that genes associated with pathogen virulence are mostly induced at the late stage of infection (Stage II), accompanied by a burst of reactive oxygen species (ROS), with upregulation of more genes involved in defense response in cotton. We identify the V991-specific virulence gene SP3 that is highly expressed during the infection Stage II. V. dahliae SP3 knock-out strain shows attenuated virulence and triggers less ROS production in cotton plants. To control the disease, we employ polyethyleneimine-coated MXene quantum dots (PEI-MQDs) that possess the ability to remove ROS. Cotton seedlings treated with PEI-MQDs are capable of maintaining ROS homeostasis with enhanced peroxidase, catalase, and glutathione peroxidase activities and exhibit improved tolerance to V. dahliae. These results suggest that V. dahliae trigger ROS production to promote infection and scavenging ROS is an effective way to manage this disease. This study reveals a virulence mechanism of V. dahliae and provides a means for V. dahliae resistance that benefits cotton production.

Abstract Surface electromyography (sEMG) can provide multiplexed information about muscle performance. If current sEMG electrodes are stretchable, arrayed, and able to be used multiple times, they would offer adequate high-quality data for continuous monitoring. The lack of these properties delays the widespread use of sEMG in clinics and in everyday life. Here, we address these constraints by design of an adhesive dry electrode using tannic acid, polyvinyl alcohol, and PEDOT:PSS (TPP). The TPP electrode offers superior stretchability (~200%) and adhesiveness (0.58 N/cm) compared to current electrodes, ensuring stable and long-term contact with the skin for recording (>20 dB; >5 days). In addition, we developed a metal-polymer electrode array patch (MEAP) comprising liquid metal (LM) circuits and TPP electrodes. The MEAP demonstrated better conformability than commercial arrays, resulting in higher signal-to-noise ratio and more stable recordings during muscle movements. Manufactured using scalable screen-printing, these MEAPs feature a completely stretchable material and array architecture, enabling real-time monitoring of muscle stress, fatigue, and tendon displacement. Their potential to reduce muscle and tendon injuries and enhance performance in daily exercise and professional sports holds great promise.

Carbon quantum dots (CQDs), which belong to the category of zero-dimensional nanomaterials, exhibit remarkable properties including chemical stability, water dispersion, low cytotoxicity, small size, biocompatibility, and photoluminescence. Although there are several methods for production of CQDs, there is an increasing interest in using low-cost and environmentally friendly synthetic methods. Biomass-based CQDs are a branch of CQDs which are considered the most ideal fluorescent nanomaterial by green synthesis strategy. The typical green route can be the conversion of waste products into high-value biomass-based CQDs, reducing resource waste and enabling sustainable development. This review will emphasize the benefits of biomass-based CQDs in synthetic methods, material properties, and their research in the area of biology. Additionally, the applications of biomass-based CQDs as plant growth promoters and sensors, and for improving plant stress tolerance and bioimaging were also discussed. Herein, this review summarizes the current investigations on synthesis of biomass-based CQDs from 1970 to 2023 and their application in agriculture. The objective of the review article is to use different biomass-based CQDs to improve plant resistance in stressful environments, so as to make plant growth better. In a word, biomass-based CQDs have strong potential in sustainable agricultural development.

Summary: In some vertebrates and invertebrates, semen release factors affecting female physiology and behavior. Here, we report that semen delivered to females is potentially beneficial for promoting oocyte development in a viviparous teleost, Sebastes schlegelii. 88% of mated ovaries develop normally and give birth to larval fish, whereas 61% of non-mated ovaries are arrested in the previtellogenic stage. Semen’s significant role (p

ObjectiveTo investigate the mechanism of endothelial cell specific molecule 1 (ESM1) promoting cervical cancer cell proliferation and EMT characteristics through zinc finger E-box binding homeobox 1 (ZEB1)/EMT pathway.MethodsThe correlation between ESM1 expression and prognosis of cervical cancer patients was analyzed by bioinformatics. SiHa, HeLa cell lines and corresponding control cell lines with stable ESM1 expression were obtained. Cell proliferation ability was detected by CCK-8 assay. The invasion and migration ability of Hela and SiHa cells were detected by Transwell assay and scratch closure assay. Expressions of EMT-related markers E-cadherin and Vimentin were detected by real-time PCR. The ability of silenced ESM1 to tumor formation in vivo was detected by tumor formation in nude mice. The effects of aloe-emodin on inhibit ESM1 expression and its inhibitory effect on cervical cancer cells in vitro and in vivo were analyzed by the same method.ResultsESM1 was highly expressed in cervical cancer, and the high expression of ESM1 was associated with poor prognosis of cervical cancer patients. CCK-8 results showed that the proliferation, invasion and migration of Hela and SiHa cells were significantly reduced after siRNA interfered with ESM1 expression. Overexpression of ESM1 promoted the proliferation and migration of cervical cancer cells. Mechanism studies have shown that the oncogenic effect of ESM1 is realized through the ZEB1/PI3K/AKT pathway. High throughput drug screening found that aloe-emodin can target ESM1. Inhibitory effect of aloe emodin on ESM1/ZEB1/EMT signaling pathway and cervical cancer cells.ConclusionThe silencing of ESM1 expression may inhibit the proliferation, invasion, metastasis and epithelial-mesenchymal transformation of cervical cancer cells by inhibiting ZEB1/PI3K/AKT. Aloe-emodin is a potential treatment for cervical cancer, which can play an anti-tumor role by inhibiting ESM1/ZEB1.

BackgroundThe impact of bacterial vaginosis on women's health is an increasing concern; however, the effect of the obesity index on bacterial vaginosis is controversial. We investigated the association between body mass index and bacterial vaginosis in women in the United States.MethodsThis was a cross-sectional study which obtained the data from the National Health and Nutrition Examination Survey from 2001 to 2004, in which weighted multivariate regression and logistic regression analyses were performed to explore the independent relationship between body mass index and bacterial vaginosis. Subgroup analyses and smoothed curve fitting were also performed.ResultsA total of 5,428 participants were enrolled, and the findings show that the participants with higher body mass index tended to have a higher incidence of bacterial vaginosis. In the fully adjusted model, a positive association between bacterial vaginosis and body mass index was observed (Odd's ratio = 1.03, 95% Confidence interval, 1.01-1.04). The subgroup analysis showed that this positive association was significant in non-Hispanic White individuals (Odd's ratio = 1.0327, 95% Confidence interval, 1.0163, 1.0493).ConclusionIncreased bacterial vaginosis positivity may be associated with an increased body mass index.

Abstract Background The WHO grade and Ki-67 index are independent indices used to evaluate the malignant biological behavior of meningioma. This study aims to develop MRI-based machine learning models to predict the malignant biological behavior of meningioma from the perspective of the WHO grade, Ki-67 index, and their combination. Methods This multicenter, retrospective study included 313 meningioma patients, of which 70 were classified as high-grade (WHO II/III) and 243 as low-grade (WHO I). The Ki-67 expression was classified into low-expression (n = 216) and high-expression (n = 97) groups with a threshold of 5%. Among them, there were 128 patients with malignant biological behavior whose WHO grade or Ki-67 index increased either or both. Data from Center A and B are were utilized for model development, while data from Center C and D were used for external validation. Radiomic features were extracted from the maximum cross-sectional area (2D) region of Interest (ROI) and the whole tumor volume (3D) ROI using different paraments from the T1, T2-weighted, and T1 contrast-enhanced sequences (T1CE), followed by five independent feature selections and eight classifiers. 240 prediction models were constructed to predict the WHO grade, Ki-67 index and their combination respectively. Models were evaluated by cross-validation in training set (n = 224). Suitable models were chosen by comparing the cross-validation (CV) area under the curves (AUC) and their relative standard deviations (RSD). Clinical and radiological features were collected and analyzed; meaningful features were combined with radiomic features to establish the clinical-radiological-radiomic (CRR) models. The receiver operating characteristic (ROC) analysis was used to evaluate those models in validation set. Radiomic models and CRR models were compared by Delong test. Results 1218 and 1781 radiomic features were extracted from 2D ROI and 3D ROI of each sequence. The selected grade, Ki-67 index and their combination radiomic models were T1CE-2D-LASSO-LR, T1CE-3D-LASSO-NB, and T1CE-2D-LASSO-LR, with cross-validated AUCs on the training set were 0.857, 0.798, and 0.888, the RSDs were 0.06, 0.09, and 0.05, the validation set AUCs were 0.829, 0.752, and 0.904, respectively. Heterogeneous enhancement was found to be associated with high grade and Ki-67 status, while surrounding invasion was associated with the high grade status, peritumoral edema and cerebrospinal fluid space surrounding tumor were correlated with the high Ki-67 status. The Delong test showed that these significant radiological features did not significantly improve the predictive performance. The AUCs for CRR models predicting grade, Ki-67 index, and their combination in the validation set were 0.821, 0.753, and 0.906, respectively. Conclusions This study demonstrated that MRI-based machine learning models could effectively predict the grade, Ki-67 index of meningioma. Models considering these two indices might be valuable for improving the predictive sensitivity and comprehensiveness of prediction of malignant biological behavior of meningioma.

Understanding the composition and contents of carotenoids in various soybean seed accessions is important for their nutritional assessment. This study investigated the variability in the concentrations of carotenoids and chlorophylls and revealed their associations with other nutritional quality traits in a genetically diverse set of Chinese soybean accessions comprised of cultivars and landraces. Genotype, planting year, accession type, seed cotyledon color, and ecoregion of origin significantly influenced the accumulation of carotenoids and chlorophylls. The mean total carotenoid content was in the range of 8.15–14.72 µg g–1 across the ecoregions. The total carotenoid content was 1.2-fold higher in the landraces than in the cultivars. Soybeans with green cotyledons had higher contents of carotenoids and chlorophylls than those with yellow cotyledons. Remarkably, lutein was the most abundant carotenoid in all the germplasms, ranging from 1.35–37.44 µg g–1. Carotenoids and chlorophylls showed significant correlations with other quality traits, which will help to set breeding strategies for enhancing soybean carotenoids without affecting the other components. Collectively, our results demonstrate that carotenoids are adequately accumulated in soybean seeds, however, they are strongly influenced by genetic factors, accession type, and germplasm origin. We identified novel germplasms with the highest total carotenoid contents across the various ecoregions of China that could serve as the genetic materials for soybean carotenoid breeding programs, and thereby as the raw materials for food sectors, pharmaceuticals, and the cosmetic industry.

To meet the demand for energy diversity, the degree of coupling between cooling, heating, and electricity becomes more and more complex. The participation of multi-energy coupling components in economic dispatch, such as combined heat and power unit (CHP), thermal energy storage (TES), and ground source heat pump (GSHP), has become a research focus for scholars. It is worth noting that inappropriate control of GSHP can lead to an imbalance in soil heat, which in turn can change the soil temperature and affect the COP of the operation of GSHP in the coming year. However, the current research on GSHP is still limited to short-term dispatch, ignoring the influence of cross-seasonal heat balance on the coefficient of performance (COP) and lifespan of GSHP. Therefore, this paper first performs precise modeling for CHP and TES, in which we will introduce an operational region for CHP and analyze the heat loss of TES. Secondly, we analyze the working principle of the GSHP and illustrate the influence of cross-seasonal heat balance on the COP of GSHP and the necessity of its scheduling over a long period. Thirdly, we innovatively propose an economic dispatch model of a multi-energy microgrid considering cross-seasonal heat balance. Finally, numerical tests are given to verify the effectiveness of the proposed model. And the effect of TES and GSHP on the flexibility enhancement of CHP is discussed.

Abstract The accuracy assessment of land cover data is of significant value to accurately monitor and objectively reproduce spatio-temporal dynamic changes to land surface landscapes. In this study, the interpretation and applicability of CCI, MCD, and CGLS long time-series land cover data products for China were evaluated via consistency analysis and a confusion matrix system using NLUD-C periodic products as reference data. The results showed that CGLS had the highest overall accuracy, Kappa coefficient, and area consistency in the continuous time-series evaluation, followed by MCD, whereas CCI had the worst performance. For the accuracy assessment of subdivided land cover types, the three products could accurately describe the distribution of forest land in China with a high recognition level, but their recognition ability for water body and construction land was poor. Among the other types, CCI could better identify cropland, MCD for grassland, and CGLS for unused land. Based on these evaluation results and characteristics of the data products, we developed suitable selection schemes for users with different requirements.

Because switchable water is difficult to apply directly for oil removal, an enhanced approach to improve oil removal is proposed using a surfactant-free microemulsion (SFME) containing switchable water. The SFME is formed using switchable water (aqueous N, N-dimethylethanolamine (DMEA) or N,N-dimethylbutylamine (BDEA)) and a hydrophobic amine (N-butyldiethanolamine (DMBA)). The single-phase region for preparing the SFME is determined using a ternary phase diagram, and the microstructure types are distinguished using the conductivity method. The pH changes and dynamic laser scattering test results demonstrate that the SFME exhibits irreversible transformation behavior regulated by CO2. Moreover, the recovered SFME containing BDEA has a microstructure with a smaller particle size after removing the CO2 by bubbling N2 at 65 °C, which is attributed to the higher proportion of DMEA than that of BDEA. In addition, dodecane and diesel oil are shown to dissolve in the SFME, and the oil solubility of the SFME increases with increasing oil phase (DMBA) content. The interface free energy theory reveals that the oil is more easily detached with the addition of SFME than with switchable water only owing to the reduced interface free energy of oil on the solid surface. Thus, an enhanced approach for removing oil is proposed to wash oil sands, where the oil removal efficiency of switchable water can be improved by using SFMEs containing switchable water.

Soybeans are grown worldwide owing to their protein, oil, and beneficial bioactive compounds. Genetic and environmental factors influence soybean seed isoflavones. In the present study, we profiled the seed isoflavones in world diverse soybean germplasm grown in two locations over two years in China. Significant differences (p < 0.001) were observed between the accessions, accession origins, seed coat colors, and maturity groups for individual and total isoflavone (TIF) content. TIF content of the soybean accessions ranged from 677.25 μg g−1 to 5823.29 μg g−1, representing an 8-fold difference. USA soybean accessions showed the highest mean TIF content (3263.07 μg g−1), followed by Japan (2521.26 μg g−1). Soybean with black seed coat showed the highest (3236.08 μg g−1) TIF concentration. Furthermore, isoflavone levels were significantly higher in late-maturity groups. Correlation analysis revealed significant positive associations between individual and TIF content. Malonyldaidzin and malonylgenistin showed higher correlations with TIF content (r = 0.92 and r = 0.94, respectively). The soybean accessions identified as having high and stable TIF content can be utilized in the food and pharmaceutical industries and breeding programs to develop soybean varieties with enhanced isoflavone content.

The effectiveness of a wind turbine elastic support in reducing vibrations significantly impacts the unit’s lifespan. During the structural design process, it is necessary to consider the influence of structural design parameters on multiple performance indicators. While neural networks can fit the relationships between design parameters on multiple performance indicators, traditional modeling methods often isolate multiple tasks, hindering the learning on correlations between tasks and reducing efficiency. Moreover, acquiring training data through physical experiments is expensive and yields limited data, insufficient for effective model training. To address these challenges, this research introduces a data generation method using a digital twin model, simulating physical conditions to generate data at a lower cost. Building on this, a Multi-gate Mixture-of-Experts multi-task prediction model with Long Short-Term Memory (MMoE-LSTM) module is developed. LSTM enhances the model’s ability to extract nonlinear features from data, improving learning. Additionally, a dynamic weighting strategy, based on coefficient of variation weighting and ridge regression, is employed to automate loss weight adjustments and address imbalances in multi-task learning. The proposed model, validated on datasets created using the digital twin model, achieved over 95% predictive accuracy for multiple tasks, demonstrating that this method is effective.

Fish germ cell transplantation holds great potential for conserving endangered species, improving cultured fish breeds, and exploring reproductive techniques. However, low transplantation efficiency is a common issue in heterotransplantation. This study transplanted fat greenling (Hexagrammos otakii) spermatogonia into the testes of spotted sea bass (Lateolabrax maculatus) to investigate factors that might affect the colonization and fixation of heterologous transplanted germ cells. Results indicated that transplanted fat greenling spermatogonia cells were successfully detected in the early transplantation phase in spotted sea bass. Their numbers gradually decreased over time, and after 10 days post-transplantation, more than 90% of the transplanted cells underwent apoptosis. Transcriptome sequencing analysis of the testes of spotted sea bass and fat greenling spermatogonia on days 1 and 10 post-transplantation revealed that this apoptosis process involved many immune-related genes and their associated signaling pathways. Acute immune rejection marker genes prf1 and gzmb were detected in the spotted sea bass testes, while immune tolerance genes lck and zap-70 were expressed in the fat greenling spermatogonia. Additionally, differential expression of prf1 and gzmb genes was screened from spotted sea bass, with experimental evidence indicating that PRF1 and GZMB protein from spotted sea bass primarily induce apoptosis in transplanted fat greenling spermatogonia via the mitochondrial apoptosis pathway, at the protein level. This suggests that the difficulties in heterotransplantation are primarily related to acute immune rejection, with PRF1 and GZMB playing significant roles.

The gut microbiota has become an essential component of the host organism and plays a crucial role in the host immune system, metabolism, and physiology. Nevertheless, our comprehension of how the fish gut microbiota contributes to enhancing nutrient utilization in the diet and improving host growth performance remains unclear. In this study, we employed a comprehensive analysis of the microbiome, metabolome, and transcriptome to analyze intestines of the normal control group and the antibiotic-treated model group of T. ovatus to investigate how the gut microbiota enhances fish growth performance and uncover the underlying mechanisms. First, we found that the growth performance of the control group was significantly higher than that of the antibiotic-treated model under the same feeding conditions. Subsequent multiomics analyses showed that the gut microbiota can improve its own composition by mediating the colonization of some probiotics represented by Lactobacillus in the intestine, improving host metabolic efficiency with proteins and lipids, and also influencing the expression of genes in signaling pathways related to cell proliferation, which together contribute to the improved growth performance of T. ovatus. Our results demonstrated the important contribution of gut microbiota and its underlying molecular mechanisms on the growth performance of T. ovatus.

Meox1 is a critical transcription factor that plays a pivotal role in embryogenesis and muscle development. It has been established as a marker gene for growth-specific muscle stem cells in zebrafish. In this study, we identified the SsMeox1 gene in a large teleost fish, Sebastes schlegelii. Through in situ hybridization and histological analysis, we discovered that SsMeox1 can be employed as a specific marker of growth-specific muscle stem cells, which originate from the somite stage and are primarily situated in the external cell layer (ECL) and myosepta, with a minor population distributed among muscle fibers. The knockdown of SsMeox1 resulted in a significant increase in Ccnb1 expression, subsequently promoting cell cycle progression and potentially accelerating the depletion of the stem cell pool, which ultimately led to significant growth retardation. These findings suggest that SsMeox1 arrests the cell cycle of growth-specific muscle stem cells in the G2 phase by suppressing Ccnb1 expression, which is essential for maintaining the stability of the growth-specific muscle stem cell pool. Our study provides significant insights into the molecular mechanisms underlying the indeterminate growth of large teleosts.

Renewable, green, and safe natural biopolymer-derived materials are highly desired for the purification of pollutants, but significantly improving their performance without the introduction of additional harmful chemicals remains a huge challenge. Based on the concept of “structure optimization design”, environment-friendly composite beads (named SA/PASP/RE) with excellent adsorption performance and recyclability were rationally constructed through a green ionic crosslinking route, using the completely green biopolymer sodium alginate (SA), sodium salt of polyaspartic acid (PASP), and the natural nanoclay rectorite (RE) as starting materials. The nano-layered RE was embedded in the polymer matrix to prevent the polymer chain from becoming over-entangled so that more adsorption sites inside the polymer network were exposed, which effectively improved the mass transfer efficiency of the adsorbent and the removal rate of contaminants. The composite beads embedded with 0.6% RE showed high adsorption capacities of 211.78, 197.13, and 195.69 mg/g for Pb(II) and 643.00, 577.80, and 567.10 mg/g for methylene blue (MB) in Yellow River water, Yangtze River water, and tap water, respectively. And the beads embedded with 43% RE could efficiently adsorb Pb(II) and MB with high capacities of 187.78 mg/g and 586.46 mg/g, respectively. This study provides a new route to design and develop a green, cost-effective, and efficient adsorbent for the decontamination of wastewater.

Pulmonary fibrosis (PF) is the pathological structure of incurable fibroproliferative lung diseases that are attributed to the repeated lung injury-caused failure of lung alveolar regeneration (LAR). Here, we report that repetitive lung damage results in a progressive accumulation of the transcriptional repressor SLUG in alveolar epithelial type II cells (AEC2s). The abnormal increased SLUG inhibits AEC2s from self-renewal and differentiation into alveolar epithelial type I cells (AEC1s). We found that the elevated SLUG represses the expression of the phosphate transporter SLC34A2 in AEC2s, which reduces intracellular phosphate and represses the phosphorylation of JNK and P38 MAPK, two critical kinases supporting LAR, leading to LAR failure. TRIB3, a stress sensor, interacts with the E3 ligase MDM2 to suppress SLUG degradation in AEC2s by impeding MDM2-catalyzed SLUG ubiquitination. Targeting SLUG degradation by disturbing the TRIB3/MDM2 interaction using a new synthetic staple peptide restores LAR capacity and exhibits potent therapeutic efficacy against experimental PF. Our study reveals a mechanism of the TRIB3–MDM2–SLUG–SLC34A2 axis causing the LAR failure in PF, which confers a potential strategy for treating patients with fibroproliferative lung diseases.

Abstract Pellino-1 (PELI1) is an E3 ubiquitin ligase acting as a key regulator for the inflammation and autoimmunity via the ubiquitination of the substrate proteins. There is increasing evidence to support that PELI1 functions as an oncoprotein in tumorigenesis and metastasis. However, the molecular mechanism underlying the high expression and oncogenic roles of PELI1 in cancers remains limited. Herein, we revealed a novel regulation mechanism by which PELI1 and EGFR cooperate to promote breast cancer metastasis. EGFR is positively correlated with PELI1 expression in breast cancers, and its activation led to the phosphorylation of PELI1 at Tyr154 and Thr264, which subsequently activated its E3 ubiquitin ligase. Simultaneously, PELI1 physically interacted with and enhanced the stability of EGFR via the K63-linked polyubiquitination in reverse. The co-inhibition of the PELI1-EGFR showed synergetic effect to repress breast cancer metastasis. Furthermore, we identified a compound S62 as a small molecule disruptor of PELI1/EGFR that effectively repressed breast cancer metastasis. Our study not only uncovered the emerging roles of PELI1/EGFR interaction in the progression of breast cancer, but also provided an effective strategy for the inhibition of metastasis in breast cancer.

This paper proposes a double-layer structure RRT* algorithm based on objective bias called DOB-RRT*. The algorithm adopts an initial path with an online optimization structure for motion planning. The first layer of RRT* introduces a feedback-based objective bias strategy with segment forward pruning processing to quickly obtain a smooth initial path. The second layer of RRT* uses the heuristics of the initial tree structure to optimize the path by using reverse maintenance strategies. Compared with conventional RRT and RRT* algorithms, the proposed algorithm can obtain the initial path with high quality, and it can quickly converge to the progressive optimal path during the optimization process. The performance of the proposed algorithm is effectively evaluated and tested in real experiments on an actual wheeled robotic vehicle running ROS Kinetic in a real environment.

Background: The noninvasive computed tomography angiography–derived fractional flow reserve (CT-FFR) can be used to diagnose coronary ischemia. With advancements in associated software, the diagnostic capability of CT-FFR may have evolved. This study evaluates the effectiveness of a novel deep learning-based software in predicting coronary ischemia through CT-FFR. Methods: In this prospective study, 138 subjects with suspected or confirmed coronary artery disease were assessed. Following indication of 30%–90% stenosis on coronary computed tomography (CT) angiography, participants underwent invasive coronary angiography and fractional flow reserve (FFR) measurement. The diagnostic performance of the CT-FFR was determined using the FFR as the reference standard. Results: With a threshold of 0.80, the CT-FFR displayed an impressive diagnostic accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) of 97.1%, 96.2%, 97.7%, 0.98, 96.2%, and 97.7%, respectively. At a 0.75 threshold, the CT-FFR showed a diagnostic accuracy, sensitivity, specificity, AUC, PPV, and NPV of 84.1%, 78.8%, 85.7%, 0.95, 63.4%, and 92.8%, respectively. The Bland–Altman analysis revealed a direct correlation between the CT-FFR and FFR (p < 0.001), without systematic differences (p = 0.085). Conclusions: The CT-FFR, empowered by novel deep learning software, demonstrates a strong correlation with the FFR, offering high clinical diagnostic accuracy for coronary ischemia. The results underline the potential of modern computational approaches in enhancing noninvasive coronary assessment.

Abstract Background Our recent multi-omics analyses of glucoamylase biosynthesis in Aspergillus niger (A. niger) suggested that lipid catabolism was significantly up-regulated during high-yield period under oxygen limitation. Since the catabolism of fatty acids can provide energy compounds such as ATP and important precursors such as acetyl-CoA, we speculated that enhancement of this pathway might be beneficial to glucoamylase overproduction. Results Based on previous transcriptome data, we selected and individually overexpressed five candidate genes involved in fatty acid degradation under the control of the Tet-on gene switch in A. niger. Overexpression of the fadE, fadA and cyp genes increased the final specific enzyme activity and total secreted protein on shake flask by 21.3 ~ 31.3% and 16.0 ~ 24.2%, respectively. And a better inducible effect by doxycycline was obtained from early logarithmic growth phase (18 h) than stationary phase (42 h). Similar with flask-level results, the glucoamylase content and total extracellular protein in engineered strains OE-fadE (overexpressing fadE) and OE-fadA (overexpressing fadA) on maltose-limited chemostat cultivation were improved by 31.2 ~ 34.1% and 35.1 ~ 38.8% compared to parental strain B36. Meanwhile, intracellular free fatty acids were correspondingly decreased by 41.6 ~ 44.6%. The metabolomic analysis demonstrated intracellular amino acids pools increased 24.86% and 18.49% in two engineered strains OE-fadE and OE-fadA compared to B36. Flux simulation revealed that increased ATP, acetyl-CoA and NADH was supplied into TCA cycle to improve amino acids synthesis for glucoamylase overproduction. Conclusion This study suggested for the first time that glucoamylase production was significantly improved in A. niger by overexpression of genes fadE and fadA involved in fatty acids degradation pathway. Harnessing the intracellular fatty acids could be a strategy to improve enzyme production in Aspergillus niger cell factory.

Abstract Salinity is a global issue limiting efficient agricultural production. Nanobiotechnology has been emerged as an effective approach to improve plant salt tolerance. However, little known is about the shared mechanisms between different nanomaterials-enabled plant salt tolerance. In this study, we found that both PNC [polyacrylic acid coated nanoceria (CeO2 nanoparticles)] and PMO (polyacrylic acid coated Mn3O4 nanoparticles) nanozymes improved rapeseed salt tolerance. PNC and PMO treated rapeseed plants showed significantly fresh weight, dry weight, higher chlorophyll content, Fv/Fm, and carbon assimilation rate than control plants under salt stress. Results from confocal imaging with reactive oxygen species (ROS) fluorescent dye and histochemical staining experiments showed that the ROS over-accumulation level in PNC and PMO treated rapeseed was significantly lower than control plants under salt stress. Confocal imaging results with K+ fluorescent dye showed that significantly higher cytosolic and vacuolar K+ signals were observed in PNC and PMO treated rapeseed than control plants under salt stress. This is further confirmed by leaf K+ content data. Furthermore, we found that PNC and PMO treated rapeseed showed significantly lower cytosolic Na+ signals than control plants under salt stress. While, compared with significantly higher vacuolar Na+ signals in PNC treated plants, PMO treated rapeseed showed significantly lower vacuolar Na+ signals than control plants under salt stress. These results are further supported by qPCR results of genes of Na+ and K+ transport. Overall, our results suggest that besides maintaining ROS homeostasis, improvement of leaf K+ retention could be a shared mechanism in nano-improved plant salt tolerance.

A strategy for designing compositionally complex alloys (CCAs) achieving multiple objectives is articulated. In this specific case, the objectives are low density and cost, along with good strength, ductility, and aqueous corrosion resistance. The present strategy has produced a two-phase material, having a ductile FCC matrix and a L21 intermetallic reinforcing phase. A machine learning algorithm has been trained using attributes of binary phase diagrams as inputs and the existing experimentally informed CCA database as output values, which efficiently predicts the phases which will result from combinations of selected elements. Corrosion resistance is achieved through tailoring the composition such that solute partitioning promotes passivity of both phases. Surprising results of composition optimization, such as preferred levels of Mn and Mo in an Al-Cr-Fe-Mo-Mn-Ni-Ti alloy are presented. While raw material cost, density, corrosion resistance, and stiffness are strong functions of alloy chemistry, the strength and ductility are highly sensitive to microstructure as well. A genetic algorithm is used to optimize a crystal plasticity-based prediction of toughness, defined as the product of ultimate tensile strength and uniform elongation, by varying microstructural attributes. Surprising dependencies of this toughness on the microstructure inputs are highlighted. Experimental results demonstrate the efficacy of the approach.

Short-season cotton is a type of cotton variety characterized by its abbreviated cycle, rapid development, and concentrated flowering and boll setting. Compared with full-season cotton, short-season cotton facilitates an easier attainment of desirable maturation even when sown relatively late. This advantage of late sowing and early maturation eliminates the necessity for plastic film mulching, thereby creating opportunities for diversified double cropping, such as cotton–wheat, cotton–garlic, cotton–rape, and cotton–triticale systems. This paper provides a comprehensive review of the morphological, physiological, and molecular biological mechanisms underlying early maturity in short-season cotton. Furthermore, the significance and application of short-season cotton is discussed in relation to optimizing planting patterns and methods, promoting its cultivation in saline fields, developing machine-harvested cotton, and encouraging plastic mulch-free cotton planting. Based on these analyses and discussions, the paper proposes future strategies aimed at enhancing the breeding and cultivation of short-season cotton. These findings serve as valuable references for global breeding and cultivation research, and application of short-season cotton in the future.

IntroductionIsoflavones are the secondary metabolites synthesized by the phenylpropanoid biosynthesis pathway in soybean that benefits human and plant health.MethodsIn this study, we have profiled seed isoflavone content by HPLC in 1551 soybean accessions grown in Beijing and Hainan for two consecutive years (2017 and 2018) and in Anhui for one year (2017).ResultsA broad range of phenotypic variations was observed for individual and total isoflavone (TIF) content. The TIF content ranged from 677.25 to 5823.29 µg g-1 in the soybean natural population. Using a genome-wide association study (GWAS) based on 6,149,599 single nucleotide polymorphisms (SNPs), we identified 11,704 SNPs significantly associated with isoflavone contents; 75% of them were located within previously reported QTL regions for isoflavone. Two significant regions on chromosomes 5 and 11 were associated with TIF and malonylglycitin across more than 3 environments. Furthermore, the WGCNA identified eight key modules: black, blue, brown, green, magenta, pink, purple, and turquoise. Of the eight co-expressed modules, brown (r = 0.68***), magenta (r = 0.64***), and green (r = 0.51**) showed a significant positive association with TIF, as well as with individual isoflavone contents. By combining the gene significance, functional annotation, and enrichment analysis information, four hub genes Glyma.11G108100, Glyma.11G107100, Glyma.11G106900, and Glyma.11G109100 encoding, basic-leucine zipper (bZIP) transcription factor, MYB4 transcription factor, early responsive to dehydration, and PLATZ transcription factor respectively were identified in brown and green modules. The allelic variation in Glyma.11G108100 significantly influenced individual and TIF accumulation.DiscussionThe present study demonstrated that the GWAS approach, combined with WGCNA, could efficiently identify isoflavone candidate genes in the natural soybean population.

IntroductionGlobal malnutrition continues to be a canker owing to poor eating habits and over-reliance on the major staple crops. Vegetable soybean (maodou) is gaining popularity globally as an affordable snack and vegetable.MethodsIn this study, we profiled the nutritional composition of 12 soybean cultivars at the vegetable (R6-R7) and mature (R8) stages. We also conducted an RNA-seq analysis during seed development, focusing on key biosynthesis enzymes for quality traits.ResultsThe results showed that 100 g of maodou contained 66.54% moisture, 13.49% protein, 7.81% fatty acids, 2.47% soluble sugar, abundant content of minerals, and micronutrients, including folate (462.27 μg FW) and carotenoids (3,935.41 μg FW). Also, the isoflavone content of maodou ranged between 129.26 and 2,359.35 μg/g FW. With regard to the recommended daily allowance, 100 g fresh weight of maodou can contribute 26.98, 115.57, and 11.60% of protein, folate, and zinc, respectively, and significant proportions of other nutrients including linoleic acid (21.16%), linolenic acid (42.96%), zinc (11.60%), and iron (18.01%). On a dry weight basis, maodou has two to six folds higher contents of folate, tocopherol, and carotenoid than the mature soybean. Furthermore, RNA-seq analysis revealed that key biosynthesis enzymes of quality traits are differentially expressed during seed development and may contribute to variations in the content of quality traits at the vegetable and mature stages. Correlation analysis of quality traits at both stages revealed that protein only correlated positively with zinc at the vegetable stage but negatively correlated with total tocopherol and total fatty acid at the mature stage. Complex associations among folates, soluble sugar, and isoflavones were also identified.DiscussionThis study provides insight into the nutritional contents of vegetable soybean and demonstrates that maodou is essential for meeting the nutritional requirements of most countries.

Measurement(s) fossil fuel Technology Type(s) machine learning

The complete removal of low concentration organic pollutants from wastewater to obtain clean water has always been a highly desired but challenging issue. In response to this, we proposed a new strategy to fabricate a carbon-in-silicate nanohybrid composite by recycling dye-loaded layered clay adsorbent and converting them to new heterogeneous carbon-in-silicate nanocomposite through an associated calcination-hydrothermal activation process. It has been confirmed that most of the dye molecules were present in waste rectorite adsorbent using an intercalation mode, which can be in situ converted to carbon in the confined interlayer spacing of rectorite. The further hydrothermal activation process may further improve the pore structure and increase surface active sites. As expected, the optimal composite shows extremely high removal rates of 99.6% and 99.5% for Methylene blue (MB) and Basic Red 14 (BR) at low concentrations (25 mg/L), respectively. In addition, the composite adsorbent also shows high removal capacity for single-component and two-component dyes in deionized water and actual water (i.e., Yellow River water, Yangtze River water, and seawater) with a removal rate higher than 99%. The adsorbent has good reusability, and the adsorption efficiency is still above 93% after five regeneration cycles. The waste clay adsorbent-derived composite adsorbent can be used as an inexpensive material for the decontamination of dyed wastewater.

The performance of the underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) system is often restrained by time-varying channels with large delays. The existing frequency domain equalizers do not work well because of the high complexity and difficulty of finding the real-time signal-to-noise ratio. To solve these problems, we propose a low-complexity neural network (NN)-based scheme for joint equalization and detection. A simple NN structure is built to yield the detected symbols with the joint input of the segmented channel response and received symbol. The coherence bandwidth is investigated to find the optimal hyperparameters. By being completely trained offline with real channels, the proposed detector is applied independently in both simulations and sea trials. The results show that the proposed detector outperforms the ZF and MMSE equalizers and extreme learning machine (ELM)-based detectors in both the strongly reflected channels of the pool and time-variant channels of the shallow sea. The complexity of the proposed network is lower than the MMSE and ELM-based receiver.

With the rapid development and high therapeutic efficiency and biosafety of gas-involving theranostics, hydrogen medicine has been particularly outstanding because hydrogen gas (H2), a microbial-derived gas, has potent anti-oxidative, anti-apoptotic, and anti-inflammatory activities in many disease models. Studies have suggested that H2-enriched saline/water alleviates colitis in murine models; however, the underlying mechanism remains poorly understood. Despite evidence demonstrating the importance of the microbial hydrogen economy, which reflects the balance between H2-producing (hydrogenogenic) and H2-utilizing (hydrogenotrophic) microbes in maintaining colonic mucosal ecosystems, minimal efforts have been exerted to manipulate relevant H2–microbe interactions for colonic health. Consistent with previous studies, we found that administration of hydrogen-rich saline (HS) ameliorated dextran sulfate sodium–induced acute colitis in a mouse model. Furthermore, we demonstrated that HS administration can increase the abundance of intestinal-specific short-chain fatty acid (SCFA)–producing bacteria and SCFA production, thereby activating the intracellular butyrate sensor peroxisome proliferator–activated receptor γ signaling and decreasing the epithelial expression of Nos2, consequently promoting the recovery of the colonic anaerobic environment. Our results also indicated that HS administration ameliorated disrupted intestinal barrier functions by modulating specific mucosa-associated mucolytic bacteria, leading to substantial inhibition of opportunistic pathogenic Escherichia coli expansion as well as a significant increase in the expression of interepithelial tight junction proteins and a decrease in intestinal barrier permeability in mice with colitis. Exogenous H2 reprograms colonocyte metabolism by regulating the H2–gut microbiota–SCFAs axis and strengthens the intestinal barrier by modulating specific mucosa-associated mucolytic bacteria, wherein improved microbial hydrogen economy alleviates colitis.

MOOCs have attracted millions of learners worldwide by providing the public with convenient access to learning and quality educational resources, but the high dropout rate in MOOCs is still an urgent problem. Drawing upon Situation-Organism-Behavior-Consequence framework and interpersonal attraction theory, this study investigates the relationship between instructor attractiveness and MOOC course completion and further analyzes the impact of MOOC course completion on their career development. The results reveal that knowledge attractiveness and communication attractiveness significantly influence learners’ thirst for knowledge. Communication attractiveness and physical attractiveness significantly influence learners’ parasocial relationships. The thirst for knowledge and parasocial relationships are important antecedents of course completion for in-service learners and in-service learners’ completion of MOOC courses positively affects their workplace benefits. The findings provide new perspectives for the research domain of online education.

Air pollution control is crucial for promoting the modernization of governance systems and efficiency. To address the subjective contrived factors and errors in the gross domestic product (GDP) data in traditional statistical almanacs, our study aims to construct a panel data model of 287 prefecture-level cities for the period from 1998–2016 (using objective nighttime light data). We also used government work report words related to environmental regulation to characterize the constraints of government environmental regulations. For this purpose, we used instrumental variables (to explore the relationship and interaction between air pollution and economic growth) and a model setting, with which we carried out regression analysis and robustness tests; the findings were validated using a transmission mechanism hypothesis. We found that that economic growth and air pollution positively influence each other and government environmental regulations significantly reduce air pollution. We also found that to achieve high economic development, environmental pollution must be controlled to avoid further damage to human and material capital. Furthermore, government environmental regulations can help improve the environmental comfort level and economic development quality. First published online 7 June 2021

With Facebook’s name changing to Meta, the metaverse concept has become popular again. There are many indications that the current fashionableness of the metaverse is not driven by technical factors, rather related to the public hype. To clarify the reasons for the increasing popularity of the concept, this study develops a model based on embodied social presence theory. We surveyed 292 metaverse users, and analyzed the obtained data using partial least squares structural equation modeling (PLS-SEM). The results show that the main technical factors influencing the metaverse popularity do not significantly predict users’ embodied presence and embodied co-presence, while users’ imagination positively predicts their embodied presence in the metaverse and positively influences users’ willingness to continuously participate through the multiple mediating effects of embodied presence and co-presence. The results of this study confirm, to some extent, that user imagination triggered by public opinion drives the popularity of the metaverse.

Soybean cyst nematode (SCN) has devastating effects on soybean production, making it crucial to identify genes conferring SCN resistance. Here we employed next-generation sequencing-based bulked segregant analysis (BSA) to discover genomic regions, candidate genes, and diagnostic markers for resistance to SCN race 4 (SCN4) in soybean. Phenotypic analysis revealed highly significant differences among the reactions of 145 recombinant inbred lines (RILs) to SCN4. In combination with euclidean distance (ED) and Δsingle-nucleotide polymorphism (SNP)-index analyses, we identified a genomic region on Gm11 (designated as rhg1-paralog) associated with SCN4 resistance. Overexpression and RNA interference analyzes of the two candidate genes identified in this region (GmPLAC8 and GmSNAP11) revealed that only GmSNAP11 significantly contributes to SCN4 resistance. We developed a diagnostic marker for GmSNAP11. Using this marker, together with previously developed markers for SCN-resistant loci, rhg1 and Rhg4, we evaluated the relationship between genotypes and SCN4 resistance in 145 RILs and 30 soybean accessions. The results showed that all the SCN4-resistant lines harbored all the three loci, however, some lines harboring the three loci were still susceptible to SCN4. This suggests that these three loci are necessary for the resistance to SCN4, but they alone cannot confer full resistance. The GmSNAP11 and the diagnostic markers developed could be used in genomic-assisted breeding to develop soybean varieties with increased resistance to SCN4.