Metabolism and DNA methylation (DNAm) are closely linked. The value of the metabolism-DNAm interplay in stratifying glioma patients has not been explored. In the present study, we aimed to stratify ...lower-grade glioma (LGG) patients based on the DNAm associated with metabolic reprogramming. Four data sets of LGGs from three databases (TCGA/CGGA/GEO) were used in this study. By screening the Kendall’s correlation of DNAm with 87 metabolic processes from KEGG, we identified 391 CpGs with a strong correlation with metabolism. Based on these metabolism-associated CpGs, we performed consensus clustering and identified three distinct subgroups of LGGs. These three subgroups were characterized by distinct molecular features and clinical outcomes. We also constructed a subgroup-related, quantifiable CpG signature with strong prognostic power to stratify LGGs. It also serves as a potential biomarker to predict the response to immunotherapy. Overall, our findings provide new perspectives for the stratification of LGGs and for understanding the mechanisms driving malignancy.
Graphene-based nanomaterials have shown wide applications in antimicrobial fields due to their accelerated rate of pathogen resistance and good antimicrobial properties. To apply graphene materials ...in the antimicrobial test, the graphene materials are usually fabricated as two-dimensional (2D) membranes. In addition, to improve the antimicrobial efficiency, graphene membranes are modified with various functional nanomaterials, such as nanoparticles, biomolecules, polymers, etc. In this review, we present recent advances in the fabrication, functional tailoring, and antimicrobial applications of graphene-based membranes. To implement this goal, we first introduce the synthesis of graphene materials and then the fabrication of 2D graphene-based membranes with potential techniques such as chemical vapor deposition, vacuum filtration, spin-coating, casting, and layer-by-layer self-assembly. Then, we present the functional tailoring of graphene membranes by adding metal and metal oxide nanoparticles, polymers, biopolymers, metal–organic frameworks, etc., with graphene. Finally, we focus on the antimicrobial mechanisms of graphene membranes, and demonstrate typical studies on the use of graphene membranes for antibacterial, antiviral, and antifungal applications. It is expected that this work will help readers to understand the antimicrobial mechanism of various graphene-based membranes and, further, to inspire the design and fabrication of functional graphene membranes/films for biomedical applications.
Hydrogen peroxide (H2O2) is one of the intermediates or final products of biological metabolism and participates in many important biological processes of life activities. The detection of H2O2 is of ...great significance in clinical disease monitoring, environmental protection, and bioanalysis. In this study, Ti3C2-based nanohybrids are prepared by the biological modification and self-assembled peptide nanosheets (PNSs)-based biomimetic synthesis of copper sulfide nanoparticles (CuS NPs), which show potential application in the fabrication of low-cost and high-performance electrochemical H2O2 biosensors. The synthesized CuS-PNSs/Ti3C2 nanohybrids exhibit excellent electrochemical performance towards H2O2, in which CuS NPs can catalyze the decomposition of H2O2 and realize the transformation from a chemical signal to an electrical signal to achieve the purpose of H2O2 detection. The prepared CuS-PNSs/Ti3C2-based electrochemical biosensor platform exhibits a wide detection range (5 μM–15 mM) and a low detection limit (0.226 μM). In addition, it reveals good selectivity and stability and can realize the monitoring of H2O2 in a complex environment. The successful biomimetic synthesis of CuS-PNSs/Ti3C2 hybrid nanomaterials provides a green and friendly strategy for the design and synthesis of functional nanomaterials and also provides a new inspiration for the construction of highly effective electrochemical biosensors for practical detection of H2O2 in various environments.
Individual effects of application of nitrogen (N) and plant densities (PD) were reported in various studies; however an interactive effect of N and PD in cotton was not studied. To explore the ...benefits of interactive effects of N fertilizer and PD to increase the quality of cotton. This study was carried out in randomized complete block design (RCBD) with split plot arrangement. In split plot arrangement, main plot was consisted of N application rate and in sub plots different PD were done. There were two nitrogen levels; low N level (F1) 120 kg ha−1 and high N level (F2) 180 kg ha−1 and three planting densities; 8 plants m−2 as low density (LD), 10 plants m−2 as medium density (MD) and 12 plants m−2 as high density (HD). In this study we observed the interactive effect of N application levels and PD on cotton photosynthetic and agronomic traits of various stages of development. Results showed that cotton growth and N contents was varied among treatments on different development stages. Plant biomass production, photosynthetic rate (Pn), intercellular CO2 (Ci), water use efficiency (WUE) and N contents were unaffected at the seedling stage by N application rate and PD, however, the highest Pn, Ci and N contents was at squaring stage followed by blooming stage. Higher seed cotton yield and lint yield were obtained F1 with HD, and F2 with MD yielded the highest N contents and cotton yield among treatments. We found that the squaring stage was more critical, followed by the blooming stage when considering N rate and PD.
Cross‐chain is the key technology to achieve interconnectivity and interoperability across various blockchain networks. It surpasses traditional single‐chain architecture in terms of the performance, ...capacity, privacy, economic and technical scalability. Cross‐chain can break barriers between institutions, industries, and regions. This paper integrates existing blockchain interoperability technologies and proposes a distributed fusion cross‐chain model in financial industry. In order to support large scale computing and high availability requirements in financial industry, the model is built on a decentralized architecture and highly scalable. It supports large‐scale isomorphic or heterogeneous blockchain cross‐chain data and state interaction. And it achieves reliable financial value circulation in various underlying blockchain networks.
Blood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on ...functional outcome is unclear.
This multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.
Three hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198.
This study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.
Planting with non-film mulching is the fundamental means to eliminate the pollution of residual film in cotton fields. However, this planting approach should have regional adaptability. Therefore, ...the calibrated WOFOST model and an early mature cultivar CRI619 (Gossypium hirsutum Linn) were employed to simulate the cotton growth, and regions were then evaluated for planting in Xinjiang. A field experiment was conducted in 2019–2020 at the experimental irrigation station of Alar City, and the data were used to calibrate and validate the WOFOST model. The field validation results showed that the errors of the WOFOST simulation for emergence, flowering, and maturity were +1 day, +2 days, and +1 day, respectively, with good simulation accuracy of phenological development time. The simulated WLV, WST, WSO, and TAGP agreed well with measured values, with R2 = 0.96, 0.97, 0.99, and 0.99, respectively. The RMSE values of simulated versus measured WLV, WST, WSO, and TAGP were 175, 210, 199, and 251 kg ha−1, and showed high accuracy. The simulated soil moisture (SM) agreed with the measured value, with R2 = 0.87. The calibration model also showed high SM simulation accuracy, with RMSE = 0.022 (cm3 cm−3). Under all treatments, the simulated TAGP and yield agreed well with the measured results, with R2 of 0.76 and 0.70, respectively. RMSE of simulated TAGP and yield was 465 and 200 kg ha−1, and showed high accuracy. The percentage RMSE values (ratio of RMSE to the average measured value, NRMSE) of ETa and WUE were 9.8% and 11.7%, indicating extremely high precision (NRMSE < 10%) and high precision (10% < NRMSE ≤ 20%), respectively. The simulated results for phenology length at the regional scales showed that the effective accumulation temperature in counties such as Yingjisha and Luntai was not enough for the phenological maturity of the studied cotton cultivar. The southern area of Xinjiang had a generally higher yield than the northern area but required more irrigation. This research can provide a method for evaluating the adaptability of filmless cultivation techniques for cotton in different counties.
Nitrogen application rates and plant density are vital factors that influence cotton production considerably. The aim of the experiment was to study the effect of varied nitrogen (N) rate and ...planting densities (PD) on growth and yield performance of two cotton cultivars from different origins. The research was laid out in Randomized Complete Block Design (RCBD) with split plot arrangements. There were two nitrogen levels; low N level (F1 with 120 kg ha−1) and high N level (F2 with 180 kg ha−1) with three plant densities; 8 plants m−2 as low plant density (LPD), 10 plants m−2 as medium plant density (MPD) and 12 plants m−2 as high plant density (HPD). During this study we observed the interactive effect of N application levels and PD on cotton growth, yield performance. Results showed that FH-142 took more number of days to reach maturity as compared with Huamian-3109. Cotton plant dry biomass and crop growth rate (CGR) was also considerably influenced by N and PD levels. FH-142 produced maximum dry biomass under F1 with HPD and F2 with MPD respectively while least plant dry biomass production was noted under F1 with LPD. High CGR was noted in FH-142 under F2 with MPD. Another side, Huamian-3109 showed maximum plant dry biomass only under F1 with HPD. Least plant dry biomass production was noted under F1 with LPD. Higher total yield produced by FH-142 under F2 with MPD while Huamian-3109 produced similar and relatively higher seed cotton yield and lint yield in F1 with HPD and F2 with MPD. These combinations were recommended for better production of both cotton cultivars in agro climatic conditions of Pakistan.
In contrast to encrypting the full secret image in classic image secret sharing (ISS), partial image secret sharing (PISS) only encrypts part of the secret image due to the situation that, in ...general, only part of the secret image is sensitive or secretive. However, the target part needs to be selected manually in traditional PISS, which is human-exhausted and not suitable for batch processing. In this paper, we introduce an adaptive PISS (APISS) scheme based on salience detection, linear congruence, and image inpainting. First, the salient part is automatically and adaptively detected as the secret target part. Then, the target part is encrypted into n meaningful shares by using linear congruence in the processing of inpainting the target part. The target part is decrypted progressively by only addition operation when more shares are collected. It is losslessly decrypted when all the n shares are collected. Experiments are performed to verify the efficiency of the introduced scheme.
The rapid development of information techniques has lead to more and more high-dimensional datasets, making classification more difficult. However, not all of the features are useful for ...classification, and some of these features may even cause low classification accuracy. Feature selection is a useful technique, which aims to reduce the dimensionality of datasets, for solving classification problems. In this paper, we propose a modified bat algorithm (BA) for feature selection, called MBAFS, using a SVM. Some mechanisms are designed for avoiding the premature convergence. On the one hand, in order to maintain the diversity of bats, they are guided by the combination of a random bat and the global best bat. On the other hand, to enhance the ability of escaping from local optimization, MBAFS employs one mutation mechanism while the algorithm trapped into local optima. Furthermore, the performance of MBAFS was tested on twelve benchmark datasets, and was compared with other BA based algorithms and some well-known BPSO based algorithms. Experimental results indicated that the proposed algorithm outperforms than other methods. Also, the comparison details showed that MBAFS is competitive in terms of computational time.
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