MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study.

OBJECTIVE: This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor stroma-based MRI manifestations in molecular subtype prediction. METHODS: 57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections. The stromal distribution patterns among molecular subtypes were compared with the MRI manifestations of BC with different stroma distribution types (SDTs). RESULTS: SDTs were significantly different and depended on the BC hormone receptor (HR) (P<0.001). There were also significant differences among five SDTs on T2WI, ADC map, internal delayed enhanced features (IDEF), marginal delayed enhanced features (MDEF), and time signal intensity (TSI) curves. Spiculated margin and the absence of type-I TSI were independent predictors for BC with star grid type stroma. The appearance frequency of hypo-intensity on T2WI in HR- BCs was significantly lower (P=0.043) than in HR+ BCs. Star grid stroma and spiculated margin were key factors in predicting HR+ BCs, and the AUC was 0.927 (95% CI: 0.867-0.987). CONCLUSION: Breast MRI can be used to predict BC's stromal distribution and molecular subtypes.

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

BACKGROUND: The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity. METHODS: A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain ß coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) and net reclassification index (NRI) were calculated and compared with TI-RADS. RESULTS: 572 thyroid nodules were included (training cohort: n = 397, validation cohort: n = 175). Age, low signal intensity on T2WI, restricted diffusion, reversed halo sign in delay phase, cystic degeneration and wash-out pattern were independent predictors of malignancy. The nomogram demonstrated good discrimination and calibration both in the training cohort (AUC = 0.972) and the validation cohort (AUC = 0.968). The accuracy, sensitivity, specificity, PPV, NPV and AUC of MRI-based prediction were 94.4%, 96.0%, 93.4%, 89.9%, 96.5% and 0.947, respectively. The MRI-based prediction model exhibited enhanced accuracy (NRI>0) in comparison to TI-RADSs. CONCLUSIONS: The prediction model for diagnosis of benign and malignant thyroid nodules demonstrated a more notable diagnostic efficacy than TI-RADS. Compared with the TI-RADSs, predictive model had better specificity along with a high sensitivity and can reduce overdiagnosis and unnecessary biopsies.

Study on Thermal Risk of Coal-Based Activated Carbon after Adsorbing Acetone, Cyclohexane, and Butyl Acetate.

Combustion and explosion accidents of the mixture may occur after the adsorption of volatile organic compounds (VOCs) by coal-based activated carbon (CBAC). It is of great significance to explore the oxidation and combustion performance of CBAC before and after adsorbing VOCs in order to prevent the reoccurrence of fire and explosion. Based on the CBAC sample commonly used in industrial production, three types of CBAC samples after adsorbing VOCs, i.e., acetone, cyclohexane, and butyl acetate, were prepared. The oxidation and combustion characteristics of the samples before and after adsorbing VOCs are measured and analyzed by thermal analyzer and cone calorimeter. Thermal analysis results indicate that during the oxidation process, the VOCs in the adsorbed samples will burn in the early stage, generating amounts of heat which may accelerate the oxidation and combustion of CBAC. According to the combustion performance experiments by cone calorimeter, it is also found that the combustion rate of CBAC after adsorbing VOCs is significantly enhanced. The time to ignition is shortened, the heat release rate becomes larger, and the time to reach the peak of heat release rate is significantly moved forward. In addition, the CO yield of the adsorbed sample is significantly improved. In general, VOC adsorption in CBAC can promote oxidation reactions and may result in an enhanced combustibility of CBAC.

Study of the Microstructure of Coal at Different Temperatures and Quantitative Fractal Characterization.

In order to understand the influence of underground coal fires on coal fractures and pores, mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) are combined to study the development of coal pore and fracture under high-temperature treatment and calculate the fractal dimension to analyze the relationship between the development of coal pore and fracture and the fractal dimension. The results show that the volume of pores and fractures of the coal sample (C200) treated at 200 °C (0.1715 mL/g) is greater than that of the coal sample (C400) treated at 400 °C (0.1209 mL/g), and both are greater than the original coal sample (RC) (0.1135 mL/g). The volume increase is mainly due to mesopores and macropores, and the proportions of mesopores and macropores in C200 were 70.15 and 59.97% in C400. The MIP fractal dimension shows a decreasing trend with the increase of temperature, and the connectivity of coal samples improved with the increase of temperature. The changes in volume and three-dimensional fractal dimension of C200 and C400 showed the opposite trend and are related to the different stress of coal matrix at different temperatures. The experimental SEM images confirm that the connectivity of coal fractures and pores improves with the increase of temperature. Based on the SEM experiment, the larger the fractal dimension, the more complex the surface is. The SEM surface fractal dimensions indicate that the surface fractal dimension of C200 is the smallest and that of C400 is the largest, which is consistent with the observations made by SEM. The combination of the two fractal dimensions is used to characterize the self-similarity of coal using the fractal dimension difference. When the temperature increased to 200 °C, the unordered expansion of the coal sample resulted in the largest fractal dimension difference and the lowest self-similarity. When heated to 400 °C, the fractal dimension difference of the coal sample is the smallest, and the microstructure of coal shows a regular groove-like development.

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis.

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM). For LNM prediction, the radiomics model was constructed by SVM, and Multi-Omics Graph cOnvolutional NETworks (MOGONET) was used for the effective classification of multiradiomics data. Multivariable logistic regression incorporating multiradiomics signatures and clinical risk factors was used to generate a nomogram, whose performance and clinical utility were assessed. Results showed that the nine most predictive features were separately selected from US, T2WI, DWI, and CE-T1WI images, and 18 features were selected in the combined model. The combined radiomics model showed better performance than models based on US, T2WI, DWI, and CE-T1WI. In a comparison of the combined radiomics and MOGONET model, receiver operating curve analysis showed that the area under the curve (AUC) value (95% CI) was 0.84 (0.76-0.93) and 0.84 (0.71-0.96) for the MOGONET model in the training and validation cohorts, respectively. The corresponding values (95% CI) for the combined radiomics model were 0.82 (0.74-0.90) and 0.77 (0.61-0.94), respectively. The MOGONET model had better performance and better prediction specificity compared with the combined radiomics model. The nomogram including the MOGONET signature showed a better predictive value (AUC: 0.81 vs. 0.88) in the training and validation (AUC: 0.74vs. 0.87) cohorts, as compared with the clinical model. Calibration curves showed good agreement in both cohorts. The applicability of the clinical multimodal radiomics (CMR) nomogram in clinical settings was validated by decision curve analysis. In patients with PTC, the CMR nomogram could improve the prediction of cervical LNM preoperatively and may be helpful in clinical decision-making.

Thermodynamic and Kinetic Effects of Quaternary Ammonium and Phosphonium Ionic Liquids on CO2 Hydrate Formation.

The paper elaborates the effects of ionic liquids (ILs) on the phase equilibrium temperature, induction time, gas consumption, gas consumption rate, and water to hydrate conversion in the presence of 0.25, 0.63, 0.95, 1.25, 3.75, 6.25, and 10.00 wt % ethyltributylphosphonium hexafluorophosphate ([P2 4 4 4][PF6]), tributylhexylphosphonium hexafluorophosphate ([P6 4 4 4][PF6]), tetraethylammonium bromide ([N2 2 2 2]Br), tetraethylammonium bistrifluoromethanesulfonimide ([N2 2 2 2][NTf2]), and tetraethylammonium hexafluorophosphate ([N2 2 2 2][PF6]) under a pressure of 2 MPa. The results indicate that all five ILs could increase CO2 consumption and enhance the water to hydrate conversion. Compared with the pure water system, [P2 4 4 4][PF6] and [P6 4 4 4][PF6] shifted the phase equilibrium temperature of CO2 hydrates to a slightly higher temperature with reduced induction times by boosting CO2 hydrate nucleation, showing the dual function promotion effects. In contrast, [N2 2 2 2]Br, [N2 2 2 2][NTf2], and [N2 2 2 2][PF6] shifted the phase equilibrium temperature of CO2 hydrates to a lower temperature and prolonged the induction time by slowing down CO2 hydrate nucleation. The inhibition effects of anions on CO2 hydrates follow an order of Br- > [NTf2]- > [PF6]-. Besides, the density functional theory and molecular dynamic calculations were conducted to explain the inconsistent influences of [N2 2 2 2]Br and [N4 4 4 4]Br on CO2 hydrate formation. It was found that the anion-cation interaction of [N2 2 2 2]Br was stronger than that of [N4 4 4 4]Br, and Br- in [N2 2 2 2]Br is less likely to participate in the formation of hydrate cages in the [N2 2 2 2]Br + H2O + CO2 system according to the intermolecular anion-water, anion-CO2, and water-water radial distribution function in [N2 2 2 2]Br + H2O + CO2 and [N4 4 4 4]Br + H2O + CO2 systems.

Histogram-based analysis of diffusion-weighted imaging for predicting aggressiveness in papillary thyroid carcinoma.

BACKGROUND: To assess the potential of apparent diffusion coefficient (ADC) map in predicting aggressiveness of papillary thyroid carcinoma (PTC) based on whole-tumor histogram-based analysis. METHODS: A total of 88 patients with PTC confirmed by pathology, who underwent neck magnetic resonance imaging, were enrolled in this retrospective study. Whole-lesion histogram features were extracted from ADC maps and compared between the aggressive and non-aggressive groups. Multivariable logistic regression analysis was performed for identifying independent predictive factors. Receiver operating characteristic curve analysis was used to evaluate the performances of significant factors, and an optimal predictive model for aggressiveness of PTC was developed. RESULTS: The aggressive and non-aggressive groups comprised 67 (mean age, 44.03 ± 13.99 years) and 21 (mean age, 43.86 ± 12.16 years) patients, respectively. Five histogram features were included into the final predictive model. ADC_firstorder_TotalEnergy had the best performance (area under the curve [AUC] = 0.77). The final combined model showed an optimal performance, with AUC and accuracy of 0.88 and 0.75, respectively. CONCLUSIONS: Whole-lesion histogram analysis based on ADC maps could be utilized for evaluating aggressiveness in PTC.

A Review of the Effect of Porous Media on Gas Hydrate Formation.

Most gas hydrates on the earth are in sediments and permafrost areas, and porous media are often used industrially as additives to improve gas hydrate formation. For further understanding its exploration and exploitation under natural conditions and its application in industry, it is necessary to study the effect of porous media on hydrate formation. The results show that the stacked porous media affects the phase equilibrium of hydrate formation depending on the competition water activity and large specific surface areas, while integrated porous media, such as metal foam, can transfer the hydration heat rapidly and moderate the hydrate phase equilibrium. A supersaturated metal-organic framework is able to significantly improve gas storage performance and can be used as a new material to promote hydrate formation. However, the critical particle size should be studied further for approaching the best promotion effect. In addition, together with the kinetic accelerators, porous media has a synergistic effect on gas hydrate formation. The carboxyl and hydroxyl groups on the surface of porous media can stabilize hydrate crystals through hydrogen bonding. However, the hydroxyl radicals on the silica surface inhibit the combination of CH4 and free water, making the phase equilibrium conditions more demanding.

A Radiomics Nomogram for Distinguishing Benign From Malignant Round-Like Breast Tumors.

Objective: The objective of this study is to develop a radiomics nomogram for the presurgical distinction of benign and malignant round-like solid tumors. Methods: This retrospective trial enrolled patients with round-like tumors who had received preoperative digital mammography (DM) no sooner than 20 days prior to surgery. Breast tumors were segmented manually on DM images in order to extract radiomic features. Four machine learning classification models were constructed, and their corresponding areas under the receiver operating characteristic (ROC) curves (AUCs) for differential tumor diagnosis were calculated. The optimal classifier was then selected for the validation set. After this, predictive machine learning models that employed radiomic features and/or patient features were applied for tumor assessment. The models' AUC, accuracy, negative (NPV) and positive (PPV) predictive values, sensitivity, and specificity were then derived. Results: In total 129 cases with benign and malignant tumors confirmed by pathological analysis were enrolled in the study, including 91 and 38 in the training and test sets, respectively. The DM images yielded 1,370 features per patient. For the machine learning models, the Least Absolute Shrinkage and Selection Operator for Gradient Boosting Classifier turned out to be the optimal classifier (AUC=0.87, 95% CI 0.76-0.99), and ROC curves for the radiomics nomogram and the DM-only model were statistically different (P<0.001). The radiomics nomogram achieved an AUC of 0.90 (95% CI 0.80-1.00) in the test cohort and was statistically higher than the DM-based model (AUC=0.67, 95% CI 0.51-0.84). The radiomics nomogram was highly efficient in detecting malignancy, with accuracy, sensitivity, specificity, PPV, and NPV in the validation set of 0.868, 0.950, 0.778, 0.826, and 0.933, respectively. Conclusions: This radiomics nomogram that combines radiomics signatures and clinical characteristics represents a noninvasive, cost-efficient presurgical prediction technique.

Experiment Investigation of SiO2 Containing Amino Groups as a Kinetic Promoter for CO2 Hydrates.

To diminish the greenhouse effect by reducing CO2 emission into the air based on a capture and sequestration method through hydrates, the thermodynamic and kinetic effects of additives on CO2 hydrate formation under 1.5 MPa in the presence of 5, 6, 8, 10, and 20 wt % RNS-A (reactive SiO2 containing amino groups) were studied, and the stirrer speed was set to 800 rpm. This paper calculated the gas consumption and explained the possible mechanisms of RNS-A on CO2 hydrates. The results showed that RNS-A was a kinetic additive instead of a thermodynamic one. It was found that 5-10 wt % RNS-A all shortened the induction time of hydrates, but only 5 and 6 wt % RNS-A increased the gas consumption of CO2 hydrates. Although we observed the shortest induction time at a 10 wt % RNS-A system, the lowest gas consumption indicated its weak CO2 capture and storage ability. In addition, when the concentration was 6 wt %, RNS-A had the highest gas consumption and its reaction time was relatively short. Considering the induction time and gas consumption, 6 wt % RNS-A was the optimal RNS-A concentration for CO2 capture and sequestration, which was the most suitable for practical applications.

Thermal Properties and Key Groups Evolution of Low-Temperature Oxidation for Bituminous Coal under Lean-Oxygen Environment.

To deeply explore the spontaneous combustion disaster of coal caused by air leakage and oxygen supply, low-temperature coal oxidation experiments under different oxygen concentrations (DOC) were carried out. Within the coal spontaneous combustion characteristic measurement system, a synchronous thermal analyzer (STA) and a Fourier transform infrared spectrometer (FTIR), the macro laws of gas and heat generation under DOC are analyzed, and the mechanism of the development of coal spontaneous combustion restricted by the lean-oxygen environment is also revealed. The results show that the change of oxygen concentration (OC) does not affect the critical temperature value and gas index change trend, but the lean-oxygen environment reduces the gas concentration and heat production rate very obviously. According to the temperature of the intersection, OC needs to be lowered to less than 5% when preventing spontaneous combustion of coal. The chain thermal reaction lags in the lean-oxygen environment, and the pyrolysis activity is significantly reduced. Meanwhile, the temperature points at T 6 and T 7 show significant differences. Furthermore, with increasing OC and temperature, the content of the aliphatic hydrocarbon presents an overall trend of first increasing, then decreasing, and continuously increasing after stage IV. It is concluded that •OH, aliphatic hydrocarbons, aromatic hydrocarbons, and carboxyl groups are the key groups for the coal spontaneous combustion evolution under DOC. To combine the spontaneous combustion reaction of coal in the DOC environment, the reaction path of the index gas in the macroscopic phenomenon and the reason for the concentration differences are revealed, the mechanism for exotherm varies caused by OC is clarified, and the microscopic inhibition affection on the chain reaction within the lean-oxygen environment is also explored. The results put forward the key groups evolution mechanism under the DOC for coal oxidation, which could provide the technical guidance for the fire prevention and control on coal mines.

Effect of the reignition characteristics on long-flame coal by oxidization and water immersion.

After a coal seam is mined, the coal remaining in the goaf is prone to flooding and spontaneous combustion accidents. To explore the reignition (secondary oxidation) characteristics of long-flame coal after oxidation and water immersion, the experimental methods of thermogravimetric analysis and infrared spectroscopy were used to analyze coal samples of oxidation first and then water immersion (FO) and samples of water immersion first and then oxidization (FI) at different pre-oxidation temperatures. The results showed that the content of main oxygen-containing functional groups (hydroxyl, carbonyl, and carboxyl groups) of the FO120 (oxidation 120 °C first and then water immersion) coal sample increased, and the FI 90 (water immersion first and then oxidization 90 °C) coal sample decreased. Pre-oxidation at 120 °C will slow down the decrease in the extent of low-temperature secondary oxidation TG, as the pre-oxidation temperature increases, the total heat release of the FO coal samples first increase and then decrease, and the heat released is high at 120 °C. The FI coal samples transfer active sites during the water immersion process, and the high pre-oxidation temperature leads to the rapid increase of the speed of the primary active site, which leads to the transformation between the secondary active site and the oxygen-containing group, resulting in the cleavage of the oxygen-containing group and increasing the heat production. Water immersion pre-oxidation performed under different conditions has the dual effects of promoting and inhibiting spontaneous coal combustion. This result provides a theoretical basis for preventing spontaneous combustion in coal-mined areas in shallow coal seams after soaking in water.

Are Ionic Liquids Suitable for Suppressing Coal Spontaneous Combustion?

Due to the reported fact that the active functional groups in coal can be dissolved and destroyed by ionic liquids, it is expected that the spontaneous combustion of coal can be affected from a thermodynamic perspective. However, ionic liquids with different thermal stabilities have distinct influences on coal combustion. Here, the thermal stability of long-flame coal in the presence of five pure ionic liquids ([Bmim][BF4], [Bmim][Ac], [Bmim][NO3], [Hoemim][BF4], and [Pmim][BF4]) was analyzed by thermogravimetric analysis, and the flammability of the raw coal, pure ionic liquids, and coal-IL mixtures (mass ratio of 1:1) were tested using a cone calorimeter according to the indexes of the time to ignition (TTI), mass loss rate (MLR), heat release rate (HRR), total heat release rate (THR), specific extinction area (SEA), and CO production. It is shown that the TTIs of mixtures containing coal-[Bmim][BF4], coal-[Hoemim][BF4], and coal-[Pmim][BF4] are relatively long, and the MLR, HRR, THR, and SEA values are relatively low, indicating that these fluorine-containing ionic liquids have a better flame-retardant effect than the other two fluorine-free ones, which may be ascribed to their similar role to halogen inhibitors. In addition, the endothermic process of [Bmim][BF4], [Hoemim][BF4], and [Pmim][BF4] can reduce the temperature of the coal surface and delay the ignition time of coal. In contrast, the TTI of coal-[Bmim][NO3] and coal-[Bmim][Ac] mixtures is much shorter than that of coal alone, and the MLR, HRR, and THR values are larger. This may be caused by the poor thermal stability of the two nonfluorine ionic liquids that began to decompose and release heat prior to coal, providing a large amount of heat for the low-temperature oxidation of coal and thus accelerating coal oxidation and combustion. Although the F-containing ionic liquids show the ability to inhibit spontaneous combustion of coal to some extent, their organic cations are potentially combustible and release large amounts of heat, smoke, and CO under high temperatures.

Radiomics based on multiparametric MRI for extrathyroidal extension feature prediction in papillary thyroid cancer.

BACKGROUND: To determine the predictive capability of MRI-based radiomics for extrathyroidal extension detection in papillary thyroid cancer (PTC) pre-surgically. METHODS: The present retrospective trial assessed individuals with thyroid nodules examined by multiparametric MRI and subsequently administered thyroid surgery. Diagnosis and extrathyroidal extension (ETE) feature of PTC were based on pathological assessment. The thyroid tumors underwent manual segmentation, for radiomic feature extraction. Participants were randomized to the training and testing cohorts, at a ratio of 7:3. The mRMR (maximum correlation minimum redundancy) algorithm and the least absolute shrinkage and selection operator were utilized for radiomics feature selection. Then, a radiomics predictive model was generated via a linear combination of the features. The model's performance in distinguishing the ETE feature of PTC was assessed by analyzing the receiver operating characteristic curve. RESULTS: Totally 132 patients were assessed in this study, including 92 and 40 in the training and test cohorts, respectively). Next, the 16 top-performing features, including 4, 7 and 5 from diffusion weighted (DWI), T2-weighted (T2 WI), and contrast-enhanced T1-weighted (CE-T1WI) images, respectively, were finally retained to construct the radiomics signature. There were 8 RLM, 5 CM, 2 shape, and 1 SZM features. The radiomics prediction model achieved AUCs of 0.96 and 0.87 in the training and testing sets, respectively. CONCLUSIONS: Our study indicated that MRI radiomics approach had the potential to stratify patients based on ETE in PTCs preoperatively.

MRI-based radiomics analysis to predict preoperative lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: The aim of the present study was to develop a magnetic resonance imaging (MRI) radiomics model and evaluate its clinical value in predicting preoperative lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC). METHODS: Data of 129 patients with histopathologically confirmed PTC were retrospectively reviewed in our study (90 in training group and 39 in testing group). 395 radiomics features were extracted from T2 weighted imaging (T2WI), diffusion weighted imaging (DWI) and T1 weighted multiphase contrast enhancement imaging (T1C+) respectively. Minimum redundancy maximum relevance (mRMR) was used to eliminate irrelevant and redundant features and least absolute shrinkage and selection operator (LASSO), to additionally select an optimized features' subset to construct the radiomics signature. Predictive performance was validated using receiver operating characteristic curve (ROC) analysis, while decision curve analyses (DCA) were conducted to evaluate the clinical worth of the four models according to different sequences. A radiomics nomogram was built using multivariate logistic regression model. The nomogram's performance was assessed and validated in the training and validation cohorts, respectively. RESULTS: Seven key features were selected from T2WI, five from DWI, ten from T1C+ and seven from the combined images. The scores (Rad-scores) of patients with LNM were significantly higher than patients with non-LNM in both the training cohort and the validation cohort. The combined model performed better than the T2WI, DWI, and T1C+ models alone in both cohorts. In the training cohort, the area under the ROC (AUC) values of T2WI, DWI, T1C+ and combined features were 0.819, 0.826, 0.808, and 0.835, respectively; corresponding values in the validation cohort were 0.798, 0.798, 0.789, and 0.830. The clinical utility of the combined model was confirmed using the radiomics nomogram and DCA. CONCLUSIONS: MRI radiomic model based on anatomical and functional MRI images could be used as a non-invasive biomarker to identify PTC patients at high risk of LNM, which could help to develop individualized treatment strategies in clinical practice.

Experimental Study on Organic Sulfur Removal in Bituminous Coal by a 1-Carboxymethyl-3-methyl Imidazolium Bisulfate Ionic Liquid and Hydrogen Peroxide Solution.

In order to improve the total sulfur removal rate in coal combustion, an acidic ionic liquid (IL) 1-carboxymethyl-3-methylimidazolium hydrogen sulfate ([HOOCCH2mim][HSO4]) as the extractant combined with the oxidant 30% hydrogen peroxide (H2O2) was applied to reduce the total sulfur content, and its microscopic mechanism of desulfurization was analyzed. The experimental results show that the desulfurization rate of the [HOOCCH2mim][HSO4]-H2O2 (1:10) solution was 45.12% and the organic sulfur removal rate was 16.26%, which were significantly higher than those of only H2O2 or pure [HOOCCH2mim][HSO4]. Fourier-transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy analyses showed that the mercaptan -SH and disulfide -S-S- in coal decreased after being treated with IL-H2O2. In particular, the results of FTIR spectroscopy indicated that the relative proportion of -S-S-and -SH treated with IL-H2O2 (1:10) decreased by 31.9 and 27.2%, respectively, compared with that of a pure IL. This is due to H2O2 oxidation; -SH and -S-S- were oxidized to sulfoxide and then the sulfoxide transferred from the coal phase to the IL phase, which improved organic sulfur removal from coal. Therefore, the combination of an ionic liquid and H2O2 could increase the total desulfurization rate. In addition, the thermogravimetric analysis of coal is divided into four different stages; the weight loss during the combustion stage and the residues show that the IL-H2O2 could improve the coal combustion because of good previous swelling and destruction of bridge bonds and hydrogen bonding of coal. Besides, the fewer residues in IL-H2O2-treated coals also indicate that a less amount of inorganic substance is left in coal after IL-H2O2 desulfurization, which is consistent with the desulfurization results.

Characteristics for Oxygen-Lean Combustion and Residual Thermodynamics in Coalfield-Fire Zones within Axial Pressure.

Coalfield fires during coal mining have become a major problem in the world today. To effectively prevent such disasters, we established an experimental platform to measure the spontaneous combustion characteristics of large-scale pressurized coal; thermal analysis experiments and microscopic analysis of briquettes under different axial pressures were carried out. It can be seen from the results that when the axial pressure is 4 MPa, the heating rate of the oxidative combustion of coal samples is accelerated, the crossing point temperature is lower (reduced by 71.09 °C), the activation energy is reduced (the second stage is decreased by 21.3 kJ/mol), and the oxidative combustion is more intense. Simultaneously, the porosity evolution process of briquettes under different axial pressures is simulated. Through calculation, it can be seen that the porosity and thermal conductivity show a linear increasing trend. The basis for the increase in the internal oxygen supply channels and increase in oxygen consumption when the axial pressure is 4 MPa is given. Through thermogravimetric-differential scanning calorimetry analysis, it is found that the maximum mass loss rate and maximum mass growth rate of residual coal after combustion under an axial pressure of 4 MPa are low, the residual rate after combustion is large, and the flammability rate is low when reoxidized, while complete combustion oxidation releases more heat. The application of axial pressure will change the combustion characteristics of briquettes, and the promotion effect is more obvious at 4 MPa. Analyzing the laws of the coal-oxygen composite reaction under different axial pressures provides theoretical guidance for the prevention and control of multistress coupling fields in coalfield-fire areas.

SO2 absorption in pure ionic liquids: Solubility and functionalization.

The SO2 solubility in ionic liquids and absorption mechanisms with different functionalities, including ether, halide, carboxylate, dicarboxylate, thiocynate, phenol, amino, azole groups, etc., are presented in this review. Strategies of improving SO2 capture with low binding energy and the separation performance from CO2 are also concluded. Generally, moderate basicity is favourable for enhancing SO2 capacity and the water (below 6 wt%) effect on absorption is indefinite but generally slight. Introducing electron-withdrawing substituents such as nitrile, halogen, aldehyde and carboxylic groups are proposed to decrease the chemical absorption enthalpy between ionic liquid and SO2 in order to reduce regeneration power consumption. Although it is promising, the absorption enthalpy is still much higher than the physisorption performance especially of the ether-functionalized ones. The biocompatible choline-based, betaine-based, and amino acid ionic liquids have clear trends to be applied in SO2 capture due to their biodegradability, nontoxicity and easy accessibility. Generally, comparing to the traditional solvents, ionic liquids have made great improvement in SO2 capacity, however, the high viscosity and desorption energy are two main obstacles for SO2 absorption and separation. Molecular simulations have been applied to reveal the absorption regimes involving the roles of basic functionalities and physical interactions especially the hydrogen bonds, which could be referred for structure designing of the available ionic liquids with readily fluid characteristics and absorption ability.

Application of digital mammography-based radiomics in the differentiation of benign and malignant round-like breast tumors and the prediction of molecular subtypes.

BACKGROUND: This study aimed to investigate the diagnostic performance of radiomic features based on digital mammography (DM) in the differential diagnosis of benign and malignant round-like (round and oval) solid tumors with circumscribed or obscured margins but without suspicious malignant or benign macrocalcifications and to investigate whether quantitative radiomic features can distinguish triple-negative breast cancer (TNBC) from non-TNBC (NTNBC). METHODS: This retrospective study included 112 patients with round-like tumors who underwent DM within 20 days preoperatively. Breast masses were segmented manually on the DM images, then radiomic features were extracted. The predictive models were used to distinguish between benign and malignant tumors and to predict TNBC in invasive ductal carcinoma. The receiver operating characteristic curves (ROCs) for these models were obtained for initial DM characteristics, radiomic features to predict malignant tumors and TNBC. The decision curve was obtained to evaluate the clinical usefulness of the model for the prediction of benign or malignant tumors. RESULTS: The study cohort included 79 patients with pathologically confirmed malignant masses and 33 patients with benign (training cohort: n=79; testing cohort: n=33). A total of 396 features were extracted from the DM images for each patient. The radiomics model for the prediction of malignant tumors achieved an area under the receiver operating characteristic curve (AUC) of 0.88 [95% confidence interval (CI), 0.76-1.00] in the testing cohort; the radiomics model for the prediction of TNBC achieved an AUC of 0.84 (95% CI, 0.73-0.96). In contrast, DM characteristics alone poorly predicted malignant tumors, with the density achieving an AUC 0.69 (95% CI, 0.59-0.79); there was no significant difference in DM characteristics between TNBC and NTNBC (P>0.05, all). The decision curve showed the good clinical usefulness of the model for the prediction of malignant tumors. CONCLUSIONS: This study showed that DM-based radiomics can accurately discriminate between benign and malignant round-like tumors with circumscribed or obscured margins but without suspicious malignant or benign macrocalcifications. Additionally, it can be used to predict TNBC in invasive ductal carcinoma. DM-based radiomics can aid radiologists in mammogram reading, clinical diagnosis and decision-making.

Enhanced N-doped Porous Carbon Derived from KOH-Activated Waste Wool: A Promising Material for Selective Adsorption of CO2/CH4 and CH4/N2.

Separation of impurities (CO2 and N2) from CH4 is an important issue for natural gas alternatives (such as coalbed gas, biogas, and landfill gas) upgrading. It is notably challenging to synthesize high N-doped porous carbon with an appropriate porous structure. In this work, high N content (14.48 wt %) porous carbon with micropore size of 0.52 and 1.2 nm and specific surface area of 862 m² g-1 has been synthesized from potassium hydroxide (KOH) activated waste wool upon the urea modification. Pure component adsorption isotherms of CO2, CH4, and N2 are systematically measured on this enhanced N-doped porous carbon at 0 and 25 °C, up to 1 bar, to evaluate the gases adsorption capability, and correlated with the Langmuir model. These data are used to estimate the separation selectivities for binary mixtures of CO2/CH4 and CH4/N2 at different mixing ratios according to the ideal adsorbed solution theory (IAST) model. At an ambient condition of 25 °C and 1 bar, the predicted selectivities for equimolar CO2/CH4 and CH4/N2 are 3.19 and 7.62, respectively, and the adsorption capacities for CO2, CH4, and N2 are 2.91, 1.01, and 0.13 mmol g-1, respectively. This report introduces a simple pathway to obtain enhanced N-doped porous carbon with large adsorption capacities for gas separation of CO2/CH4 and CH4/N2.