The growing use of nanomaterials has sparked significant interest in assessing the insect toxicities of nanoparticles. The silkworm, as an economically important insect, serves as a promising model ...for studying how insects respond to harmful substances. Here, we conducted a comprehensive investigation on the impact of graphene oxide (GO) on silkworms using a combination of physiological and transcriptome analyses. GO can enter the midguts and posterior silk glands of silkworms. High GO concentrations (> 25 mg/L) significantly (P < 0.01) inhibited larval growth. Additionally, GO (> 5 mg/L) significantly reduced the cocooning rate, and GO (> 15 mg/L) hindered oviduct development and egg laying in silkworms. GO increased the reactive oxygen species content and regulated catalase activity, suggesting that it may affect insect growth by regulating reactive oxygen detoxification. The transcriptome data analysis showed that 35 metabolism-related genes and 20 ribosome biogenesis-related genes were differentially expressed in response to GO, and their expression levels were highly correlated. Finally, we propose that a Ribosome biogenesis–Metabolic signaling network is involved in responses to GO. The research provides a new perspective on the molecular responses of insects to GO.
•Graphene oxide (GO) has obvious inhibitory effect on the growth and reproduction of silkworms.•GO may affect the growth of silkworms by regulating ROS detoxification.•The genes involved in single-organism process, cellular process, cell, and cell part showed response to GO.•A GO response regulatory network mediated by the Ribosome biogenesis–Metabolic module is proposed.•GO exposure leads to reduced oviposition of silkworms.
With the rapid advancement of remote-sensing technology, the spectral information obtained from hyperspectral remote-sensing imagery has become increasingly rich, facilitating detailed spectral ...analysis of Earth's surface objects. However, the abundance of spectral information presents certain challenges for data processing, such as the "curse of dimensionality" leading to the "Hughes phenomenon", "strong correlation" due to high resolution, and "nonlinear characteristics" caused by varying surface reflectances. Consequently, dimensionality reduction of hyperspectral data emerges as a critical task. This paper begins by elucidating the principles and processes of hyperspectral image dimensionality reduction based on manifold theory and learning methods, in light of the nonlinear structures and features present in hyperspectral remote-sensing data, and formulates a dimensionality reduction process based on manifold learning. Subsequently, this study explores the capabilities of feature extraction and low-dimensional embedding for hyperspectral imagery using manifold learning approaches, including principal components analysis (PCA), multidimensional scaling (MDS), and linear discriminant analysis (LDA) for linear methods; and isometric mapping (Isomap), locally linear embedding (LLE), Laplacian eigenmaps (LE), Hessian locally linear embedding (HLLE), local tangent space alignment (LTSA), and maximum variance unfolding (MVU) for nonlinear methods, based on the Indian Pines hyperspectral dataset and Pavia University dataset. Furthermore, the paper investigates the optimal neighborhood computation time and overall algorithm runtime for feature extraction in hyperspectral imagery, varying by the choice of neighborhood k and intrinsic dimensionality d values across different manifold learning methods. Based on the outcomes of feature extraction, the study examines the classification experiments of various manifold learning methods, comparing and analyzing the variations in classification accuracy and Kappa coefficient with different selections of neighborhood k and intrinsic dimensionality d values. Building on this, the impact of selecting different bandwidths t for the Gaussian kernel in the LE method and different Lagrange multipliers λ for the MVU method on classification accuracy, given varying choices of neighborhood k and intrinsic dimensionality d, is explored. Through these experiments, the paper investigates the capability and effectiveness of different manifold learning methods in feature extraction and dimensionality reduction within hyperspectral imagery, as influenced by the selection of neighborhood k and intrinsic dimensionality d values, identifying the optimal neighborhood k and intrinsic dimensionality d value for each method. A comparison of classification accuracies reveals that the LTSA method yields superior classification results compared to other manifold learning approaches. The study demonstrates the advantages of manifold learning methods in processing hyperspectral image data, providing an experimental reference for subsequent research on hyperspectral image dimensionality reduction using manifold learning methods.
Sutures have been at the forefront of surgical medicine throughout time. With recent advances in suture technology, it is possible to incorporate biologically active substances to enhance suture ...function and capability. Bioactive sutures represent a modality interest in controlled drug and cell delivery to traumatic sites. In this article, a comprehensive literature search of key bibliographic databases focusing on suture material fabrication and advanced modification was performed. The history, manufacturing process and cost-effectiveness of bioactive sutures are presented. Several novel modifications to enhance function in drug and growth factor delivery and cell therapy are also reviewed. Different antimicrobial drugs and anaesthetics have been shown to be effective in reducing inflammation and bacterial infection. Cellular therapy represents a unique modality augmenting the surgical repair of various soft tissue injuries. We propose a definition of bio-active sutures as biomaterials that are engineered to have controlled tissue interaction to optimise wound/defect healing, in addition to their essential function in tissue approximation.
The Coronavirus Disease 2019 (COVID-19) has proved a globally prevalent outbreak since December 2019. As a focused country to alleviate the epidemic impact, China implemented a range of public health ...interventions to prevent the disease from further transmission, including the pandemic lockdown in Wuhan and other cities. This paper establishes China's mobility network by a flight dataset and proposes a model without epidemiological parameters to indicate the spread risks through the network, which is termed as epidemic strength. By simply adjusting an intervention parameter, traffic volumes under different travel-restriction levels can be simulated to analyze how the containment strategy can mitigate the virus dissemination through traffic. This approach is successfully applied to a network of Chinese provinces and the epidemic strength is smoothly interpreted by flow maps. Through this node-to-node interpretation of transmission risks, both overall and detailed epidemic hazards are properly analyzed, which can provide valuable intervention advice during public health emergencies.
This study reveals a new finding on the impact of reputation growth on crowdsourcing vendors’ sustainable performance in different modes of markets using fixed-effect panel data regression models. To ...this end, we extract data from a large Chinese crowdsourcing platform named
zbj.com
for the period of 2012–2014, which was a key stage for the establishment of market diversification. Based on different transaction modes, the study divides the markets on the crowdsourcing platform into task-based market (TBM) and employment market (EPM). By applying the multiple framework, the empirical results exhibit a negative and significant effect of vendors’ reputation on participation rate (PR) in TBM and EPM. At the same time, reputation also has a consistent effect on vendors’ revenue share (RS) of each market. Moreover, this study shows that the significant reputation impact on PR and RS of EPM will be, respectively, weakened and strengthened in fixed-price mode and customized mode when vendors participate more in large-scale projects. The findings suggest that the growth of reputation will promote market transfer of vendors, that is, showing different sustainability in different markets, which will lead to uneven development of the crowdsourcing markets. By adopting the perspective of transaction cost theory (TCT), this study elaborates and analyses these phenomena and derives corresponding policy implications.
Background:
Intervertebral disc degeneration (IDD) is a major cause of low back pain, but the onset and progression of IDD are unknown. Long non-coding RNA (lncRNA) has been validated to play a ...critical role in IDD, while an increasing number of studies have linked oxidative stress (OS) to the initiation and progression of IDD. We aim to investigate key lncRNAs in IDD through a comprehensive network of competing endogenous RNA (ceRNA) and to identify possible underlying mechanisms.
Methods:
We downloaded IDD-related gene expression data from the Gene Expression Omnibus (GEO) database and obtained differentially expressed-lncRNAs (DE-lncRNA), -microRNAs (DE-miRNA), and -messenger RNAs (DE-mRNA) by bioinformatics analysis. The OS-related lncRNA-miRNA-mRNA ceRNA interaction axis was constructed and key lncRNAs were identified based on ceRNA theory. We performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses on mRNAs regulated by lncRNAs in the ceRNA network. Single sample gene set enrichment analysis (ssGSEA) was used to reveal the immune landscape. Expression of key lncRNAs in IDD was assessed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).
Results:
In this study, 111 DE-mRNAs, 20 DE-lncRNAs, and 502 DE-miRNAs were identified between IDD patients and controls, and 16 OS-related DE-lncRNAs were also identified. The resulting lncRNA-miRNA-mRNA network consisted of eight OS-related DE-lncRNA nodes, 24 DE-miRNA nodes, 70 DE-mRNA nodes, and 183 edges. Functional enrichment analysis suggested that the ceRNA network may be involved in regulating biological processes related to cytokine secretion, lipid, and angiogenesis. We also identified four key lncRNAs, namely lncRNA GNAS-AS1, lncRNA MIR100HG, lncRNA LINC01359, and lncRNA LUCAT1, which were also found to be significantly associated with immune cells.
Conclusion:
These results provide novel insights into the potential applications of OS-related lncRNAs in patients with IDD.
Biocompatible poly(
l-lactic acid) (PLA) was successfully covalently grafted onto the convex surfaces and tips of the multi-walled carbon nanotubes (MWNTs) by one step based on in situ ...polycondensation of the commercially available
l-lactic acid monomers. The functional groups in the carboxylic multi-walled carbon nanotubes (MWNT-COOH) showed active enough for participating the polycondensation of
l-lactic acid. The resulting PLA-
grafted-MWNTs were characterized with Raman spectroscopy, Fourier-transform IR (FTIR), UV–vis,
1H NMR, thermogravimetric analyses (TGA) and transmission electron microscopy (TEM). Raman, FTIR and
1H NMR spectroscopies revealed that the PLA was covalently attached to the MWNT. TGA showed that the grafted PLA content could be controlled by the reaction time. The core/shell structures with MWNT as the “hard” core and the PLA polymer layer as the “soft” shell can be clearly seen through HRTEM.
To explore the association between liver metabolism-related indicators in maternal serum and neonatal hyperbilirubinemia (NHB), and further investigate the predictive value of these indicators in ...NHB-related amino acid metabolism disorders.
51 NHB and 182 No-NHB newborns and their mothers who treated in the Fourth Hospital of Shijiazhuang from 2018 to 2022 were participated in the study. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square test. Multivariate logistic regression was used to analyze the relationship between maternal serum indicators and the occurrence of NHB. The correlation analysis and risk factor assessment of maternal serum indicators with NHB-related amino acid metabolic disorders were performed using Spearman correlation analysis and multivariate logistic regression.
Compared to the non NHB group, the NHB group had higher maternal serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST, and total bile acid (TBA), while lower levels of serum albumin (ALB), total cholesterol (TC) and high-density lipoprotein (HDL). The levels of alanine (ALA), valine (VAL), ornithine (ORN), and proline (PRO) in the newborns were reduced in NHB group, while arginine (ARG) showed a tendency to be elevated. Multiple logistic regression analysis showed that maternal ALT, AST, ALT/AST, and TBA levels were all at higher risk with the development of NHB, whereas ALB, TC, and HDL levels were negatively associated with NHB development. Increasing maternal TBA level was associated with lower ALA (r=-0.167, p = 0.011), VAL (r=-0.214, p = 0.001), ORN (r=-0.196, p = 0.003), and PRO in the newborns (r=-0.131, p = 0.045). Maternal ALT level was negatively associated with ALA (r=-0.135, p = 0.039), VAL (r=-0.177, p = 0.007), ORN (r=-0.257, p < 0.001), while ALT/AST was positively correlated with ARG (r = 0.133, p = 0.013). After adjustment for confounding factors, maternal serum TBA and ALT were the independent risk factor for neonatal ORN metabolic disorders (adjusted odds ratio (AOR) = 0.379, 95%CI = 0.188-0.762, p = 0.006), (AOR = 0.441, 95%CI = 0.211-0.922, p = 0.030). Maternal ALT level was an independent risk factor for neonatal VAL metabolic disorders (AOR = 0.454, 95%CI = 0.218-0.949, p = 0.036).
The levels of high TBA, ALT, AST, and low HDL, TC of maternal were associated with the risk of NHB. Maternal TBA and ALT levels were independent risk factors for NHB-related amino acid disturbances which have value as predictive makers.
•Paleoenvironment was reconstructed for a non-monsoon region in West China.•Groundwater evolution is well constrained to support the paleo-environment study.•Isotopes indicate air temperature was ...lower in the late Pleistocene.•13C of groundwater suggests there were more C4 plants in the late Pleistocene.
Isotopic and geochemical evidence of paleoclimatic conditions from the Pleistocene (∼30ka BP) has been obtained from groundwater in a non-monsoon area in the East Junggar Basin, NW China. The major ion chemistry of groundwater is controlled by some processes including ion exchange in clay minerals and dissolution of gypsum as well as other evaporites in the desert groundwater, while carbonate minerals seem to be essentially absent in the aquifers. The water chemistry, oxygen and deuterium, deuterium excess, and stable carbon isotopes of groundwater show distinctive excursions inferred to be related to environmental variations such as air temperature and land cover change. Shallow groundwater bears an isotopic signature similar to that of the mean annual rainfall in Urumqi, suggesting recharge under warm climate conditions in the Holocene. Deep groundwater in the central part of the basin is characterized by depleted heavy isotopes, lower deuterium excess and low 14C content, indicating lower air temperature in the late Pleistocene, after correction for altitude effect. Old groundwater with enriched 13C indicates the higher proportion of C4 species in the late Pleistocene.
Water flooding is an economic method commonly used in secondary recovery, but a large quantity of crude oil is still trapped in reservoirs after water flooding. A deep understanding of the ...distribution of residual oil is essential for the subsequent development of water flooding. In this study, a pore-scale model is developed to study the formation process and distribution characteristics of residual oil. The Navier–Stokes equation coupled with a phase field method is employed to describe the flooding process and track the interface of fluids. The results show a significant difference in residual oil distribution at different wetting conditions. The difference is also reflected in the oil recovery and water cut curves. Much more oil is displaced in water-wet porous media than oil-wet porous media after water breakthrough. Furthermore, enhanced oil recovery (EOR) mechanisms of both surfactant and polymer flooding are studied, and the effect of operation times for different EOR methods are analyzed. The surfactant flooding not only improves oil displacement efficiency, but also increases microscale sweep efficiency by reducing the entry pressure of micropores. Polymer weakens the effect of capillary force by increasing the viscous force, which leads to an improvement in sweep efficiency. The injection time of the surfactant has an important impact on the field development due to the formation of predominant pathway, but the EOR effect of polymer flooding does not have a similar correlation with the operation times. Results from this study can provide theoretical guidance for the appropriate design of EOR methods such as the application of surfactant and polymer flooding.
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