The systemic inflammatory response plays an important role in cancer development and progression. An original inflammation-based staging system for predicting survival in patients undergoing ...transarterial chemoembolization (TACE) combined with recombinant human type-5 adenovirus H101 is not available. This study aimed to validate the prognostic value of inflammation scores for patients with hepatocellular carcinoma (HCC) who were treated with TACE combined with H101.
The data from 216 patients with HCC who underwent TACE combined with H101 from January 2007 to July 2015 were retrospectively collected, and the association of the inflammation scores with overall survival (OS) was analyzed. Univariate and multivariate analyses were performed to identify variables associated with OS. The prognostic value of the inflammation scores, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), neutrophil/ platelet-to-lymphocyte ratio (NLR-PLR), modified Glasgow Prognostic Score (mGPS), prognostic nutritional index (PNI), prognostic index (PI), tumor-node-metastasis (TNM), Barcelona Clinic Liver Cancer (BCLC) and Cancer of the Liver Italian Program (CLIP) staging systems were analyzed and compared using the areas under the receiver operating characteristic curves (AUROCs).
The estimated 1-, 2-, and 3-year OS rates were 61.3%, 44.2%, and 40.5% for the entire study cohort, respectively; the median OS was 17 months. According to the multivariate Cox proportional hazards model, the pretreatment NLR, tumor diameter and pretreatment alpha-fetoprotein (AFP) levels were independent predictors of OS. The CLIP score had superior discriminative abilities compared with other staging systems, and the NLR-PLR score consistently displayed a higher AUROC value than the other inflammation-based prognostic scores. The combination of the NLR-PLR and CLIP scores exhibited a superior prognostic ability for OS compared to the NLR-PLR or CLIP scores alone.
The NLR-PLR score is a more powerful predictive system than the other inflammation-based scores for patients with HCC who were treated with TACE and H101. The predictive ability may be improved by utilizing a combination of the NLR-PLR and CLIP scores.
Many polarisation techniques have been harnessed for decades in biological and clinical research, each based upon measurement of the vectorial properties of light or the vectorial transformations ...imposed on light by objects. Various advanced vector measurement/sensing techniques, physical interpretation methods, and approaches to analyse biomedically relevant information have been developed and harnessed. In this review, we focus mainly on summarising methodologies and applications related to tissue polarimetry, with an emphasis on the adoption of the Stokes-Mueller formalism. Several recent breakthroughs, development trends, and potential multimodal uses in conjunction with other techniques are also presented. The primary goal of the review is to give the reader a general overview in the use of vectorial information that can be obtained by polarisation optics for applications in biomedical and clinical research.
Summer monsoon rainfall supplies over 55% of annual precipitation to global monsoon regions. As shown by more than 70% of models, including 30 models from CMIP5 and 30 models from CMIP6 under ...high-emission scenarios, North American (NAM) monsoon rainfall decreases in a warmer climate, in sharp contrast to the robust increase in Asian–African monsoon rainfall. A hierarchy of model experiments is analyzed to understand the mechanism for the reduced NAM monsoon rainfall in this study. Modeling evidence shows that the reduction of NAM monsoon rainfall is related to both direct radiative forcing of increased CO₂ concentration and SST warming, manifested as fast and slow responses to abrupt CO₂ quadrupling in coupled GCMs. A cyclone anomaly forms over the Eurasian–African continental area due to enhanced land–sea thermal contrast under increased CO₂ concentration, and this leads to a subsidence anomaly on its western flank, suppressing the NAM monsoon rainfall. The SST warming acts to further reduce the rainfall over the NAM monsoon region, and the El Niño–like SST warming pattern with enhanced SST warming over the equatorial Pacific plays a key role in suppressing NAM rainfall, whereas relative cooling over the subtropical North Atlantic has no contribution. A positive feedback between monsoon precipitation and atmospheric circulation helps to amplify the responses of monsoon rainfall.
Subtropical anticyclones dominate the subtropical ocean basins in summer. Using the multimodel output from phase 5 of the Coupled Model Intercomparison Project (CMIP5), the future changes of the ...subtropical anticyclones as a response to global warming are investigated, based on the changes in subsidence, low-level divergence, and rotational wind. The subtropical anticyclones over the North Pacific, South Atlantic, and south Indian Ocean are projected to become weaker, whereas the North Atlantic subtropical anticyclone (NASA) intensifies, and the South Pacific subtropical anticyclone (SPSA) shows uncertainty but is likely to intensify. Diagnostic analyses and idealized simulations suggest that the projected changes in the subtropical anticyclones are well explained by the combined effect of increased tropospheric static stability and changes in diabatic heating. Increased static stability acts to reduce the intensity of all the subtropical anticyclones, through the positive mean advection of stratification change (MASC) over the subsidence regions of the subtropical anticyclones. The pattern of change in diabatic heating is dominated by latent heating associated with changes in precipitation, which is enhanced over the western North Pacific under the “richest get richer” mechanism but is reduced over subtropical North Atlantic and South Pacific due to a local minimum of SST warming amplitude. The change in the diabatic heating pattern substantially enhances the subtropical anticyclones over the North Atlantic and South Pacific but weakens the North Pacific subtropical anticyclone.
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•Recovery of REEs from e-waste using IL extraction is summarized.•Roles of ionic liquid in REEs recovery are analyzed.•Design of task-specific ILs for selective extraction of REEs is ...presented.•Prospects on industrialization of IL for REEs recovery from e-waste are proposed.
Increasing generation of electronic waste (e-waste) is a major concern for emerging rare earth elements (REEs) pollution if not appropriately disposed of. Nevertheless, e-waste could be considered as a secondary source for critical REEs mining. Under the context of circular economy, this review focuses on selective recovery of REEs from e-waste using ionic liquid (IL) extraction. ILs demonstrate a sustainable alternative to organic volatiles used in traditional solvent extraction process. Despite insufficient literature on applications of ILs for REEs extraction from limited categories of real e-waste, the review comprehensively summarizes the latest studies on recovery of REEs from e-waste (mostly uncontaminated) using IL extraction and the existing data indicate encouraging outcomes in terms of extractability and selectivity. Roles of ILs in REEs recovery have been critically analyzed. The review has systematically illustrated the fundamental design of ILs for selective extraction of REEs, including bifunctional and task-specific ILs, incorporation of dilutant/extractant, non-fluorinated ILs, etc. This fundamental knowledge could greatly facilitate cost-effective and selective extraction of REEs from e-waste. ILs must be completely assessed in terms of extractability, selectivity, and reusability. Synergistic extraction based on quaternary phosphonium salts are discussed to realize excellent extraction of REEs into IL phase leaving non-REEs in the aqueous phase for easier separation. Overall, regeneration of spent ILs and subsequent separation of extracted REEs from ILs are also crucial to selective recovery of REEs from e-waste using novel ILs. Nevertheless, industrialization of this technology would require more fundamental data on extraction efficiency and recovery rate of REEs from real e-waste.
Notch and size effects generally show great influence on the fatigue behavior of engineering structures, which plays a vital role during their structural integrity and reliability evaluations. In ...this study, the influence of notch size effect on fatigue life and critical distance values were investigated. Particularly, a novel method for fatigue life distribution assessment of notched specimens was proposed based on Weibull model and critical distance theory. Experimental data of Al 2024-T351 smooth plate specimens and center hole plate (CHP) specimens with four different notch radii were utilized for model validation and comparison. Results show that all predicted lives of Al 2024-T351 CHP specimens are within the ±2 life scatter bands of experimental ones.
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•Weibull model describes well the dispersity of fatigue lives of Al 2024-T351 alloys.•Influence of notch size effect on critical distance and fatigue strength were characterized.•Proposed model by coupling Weibull with critical distance theories for considering notch size effect.•Proposed model predictions of Al 2024-T351 center hole plate specimens are within ±2 life scatter bands of experimental ones.
Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems ...(BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.
Abstract
Coronal mass ejections (CMEs) are violent ejections of magnetized plasma from the Sun that can trigger geomagnetic storms, endanger satellite operations, and destroy electrical ...infrastructures on the Earth. After systematically searching Sun-as-a-star spectra observed by the Extreme Ultraviolet Variability Experiment on board the Solar Dynamics Observatory (SDO) from 2010 May to 2022 May, we identified eight CMEs associated with flares and filament eruptions by analyzing the blue-wing asymmetry of the O
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52.58 nm line profiles. Combined with images simultaneously taken by the 30.4 nm channel of the Atmospheric Imaging Assembly on board SDO, the full velocity and propagation direction for each of the eight CMEs are derived. We find a strong correlation between geomagnetic indices (
Kp
and Dst) and the angle between the CME propagation direction and the Sun–Earth line, suggesting that Sun-as-a-star spectroscopic observations at extreme-ultraviolet wavelengths can potentially help to improve the prediction accuracy of the geoeffectiveness of CMEs. Moreover, an analysis of synthesized long-exposure Sun-as-a-star spectra implies that it is possible to detect CMEs from other stars through blue-wing asymmetries or blueshifts of spectral lines.
Deep eutectic solvents (DESs), a novel category of sustainable solvents, are expected to achieve the design of the chemical processes without utilizing or generating harmful chemicals. In this work, ...based on the mathematical model inspired by the transition state theory, the group contribution method is used to accurately predict the viscosity of DESs. The model is constrained by Eyring rate theory and hard sphere free volume theory. A dataset of 2229 experimental viscosity data points of 183 DESs from literature is used to determine the model parameters and subsequently verify the model. The rules introduced by this model are simple and easy to follow. The results show that the proposed model is capable to predict the viscosity of DESs with very high accuracy, using only temperature and composition as inputs. The average absolute relative deviations (AARDs) of the model are 8.12% and 8.64% over the training and test sets, respectively, and the maximum ARD is 34.63%. Therefore, the as‐proposed model can be considered a highly reliable tool for predicting the viscosity of DESs when experimental data are absent. It will provide useful guidance for the synthesis of DESs with specific viscosity to meet different application requirements and promote their industrial‐scale implementation.
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•Fe(II)-bearing minerals can support Cr(VI) bio-reduction in groundwater.•Mackinawite performs best in Cr(VI) removal.•Groundwater chemistry and hydrodynamics influence the ...process.•Biotic and abiotic contributions to Cr(VI) reduction are quantified.•Synergistic mechanisms between microbial consortia are revealed.
To date, comparatively little is known about the role of natural Fe(II)-bearing minerals in bioremediation of chromium (VI) contaminated aquifers subject to chemoautotrophic conditions. This work employed four kinds of Fe(II)-bearing minerals (pyrite, mackinawite, wustite, and magnetite) as inorganic electron donors to support Cr(VI) bio-reduction. In batch experiments, mackinawite (FeS) performed best, with Cr(VI) removal efficiency of 98.1 ± 1.21 % in 96 h. Continuous column experiments lasting 180 d implied that groundwater chemistry and hydrodynamics influenced the Cr(VI) removal process. A breakthrough study suggested that biotic and abiotic contributions to Cr(VI) reduction were 76.0 ± 1.12 % and 24.1 ± 1.43 %, respectively. Cr(VI) was reduced to insoluble Cr(III), whereas Fe(II) and S(-II) in mackinawite were finally oxidized to Fe(III) and sulfate. Mackinawite evolved progressively into pyrrhotite. High-throughput 16S rRNA gene sequencing indicated that mackinawite-driven Cr(VI) reduction was mediated through synergistic interactions of microbial consortia; i.e. autotrophs as Acidovorax synthesized volatile fatty acids as metabolic intermediates, which were consumed by Cr(VI) reducers as Geobacter. Genes encoding enzymes for S oxidation (soxB) and Cr(VI) reduction (chrA, yieF) were upregulated. Cytochrome c participating in Fe(II) oxidation increased significantly. This work advances the development of sustainable techniques for Cr(VI) polluted groundwater remediation.
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