Predicting major adverse cardiac events using radiomics nomogram of pericoronary adipose tissue based on CCTA: A multi-center study.

BACKGROUND: The evolution of coronary atherosclerotic heart disease (CAD) is intricately linked to alterations in the pericoronary adipose tissue (PCAT). In recent epochs, characteristics of the PCAT have progressively ascended as focal points of research in CAD risk stratification and individualized clinical decision-making. Harnessing radiomic methodologies allows for the meticulous extraction of imaging features from these adipose deposits. Coupled with machine learning paradigms, we endeavor to establish predictive models for the onset of major adverse cardiovascular events (MACE). PURPOSE: To appraise the predictive utility of radiomic features of PCAT derived from coronary computed tomography angiography (CCTA) in forecasting MACE. METHODS: We retrospectively incorporated data from 314 suspected or confirmed CAD patients admitted to our institution from June 2019 to December 2022. An additional cohort of 242 patients from two external institutions was encompassed for external validation. The endpoint under consideration was the occurrence of MACE after a 1-year follow-up. MACE was delineated as cardiovascular mortality, newly diagnosed myocardial infarction, hospitalization (or re-hospitalization) for heart failure, and coronary target vessel revascularization occurring more than 30 days post-CCTA examination. All enrolled patients underwent CCTA scanning. Radiomic features were meticulously extracted from the optimal diastolic phase axial slices of CCTA images. Feature reduction was achieved through a composite feature selection algorithm, laying the groundwork for the radiomic signature model. Both univariate and multivariate analyses were employed to assess clinical variables. A multifaceted logistic regression analysis facilitated the crafting of a clinical-radiological-radiomic combined model (or nomogram). Receiver operating characteristic (ROC) curves, calibration, and decision curve analyses (DCA) were delineated, with the area under the ROC curve (AUCs) computed to gauge the predictive prowess of the clinical model, radiomic model, and the synthesized ensemble. RESULTS: A total of 12 radiomic features closely associated with MACE were identified to establish the radiomic model. Multivariate logistic regression results demonstrated that smoking, age, hypertension, and dyslipidemia were significantly correlated with MACE. In the integrated nomogram, which amalgamated clinical, imaging, and radiomic parameters, the diagnostic performance was as follows: 0.970 AUC, 0.949 accuracy (ACC), 0.833 sensitivity (SEN), 0.981 specificity (SPE), 0.926 positive predictive value (PPV), and 0.955 negative predictive value (NPV). The calibration curve indicated a commendable concordance of the nomogram, and the decision curve analysis underscored its superior clinical utility. CONCLUSIONS: The integration of radiomic signatures from PCAT based on CCTA, clinical indices, and imaging parameters into a nomogram stands as a promising instrument for prognosticating MACE events.

Effect of peracetic acid generation in hydrogen peroxide-acetic acid pretreatment on production of xylooligosaccharides from poplar by organic acid hydrolysis.

Hydrogen peroxide-acetic acid (HPAA) compositions affect the peracetic acid generation and subsequent delignification of lignocellulosic materials. However, the effects of HPAA compositions on lignin removal and poplar hydrolyzability after HPAA pretreatment are not fully elucidated yet. In this work, different volume ratios of HP to AA were used to pretreat poplar, AA and lactic acid (LA) hydrolysis of delignified poplar to produce XOS was compared. Peracetic acid was mainly produced in 1 h of HPAA pretreatment. HPAA with HP to AA ratio of 8:2 (HP8AA2) generated 4.4% peracetic acid and removed 57.7% of lignin at 2 h. Furthermore, XOS production from HP8AA2-pretreated poplar by AA and LA hydrolysis was increased by 97.1% and 14.9% compared to those from raw poplar, respectively. After alkaline incubation, the glucose yield of HP8AA2-AA-pretreated poplar increased from 40.1% to 97.1%. The study results indicated that HP8AA2 was conducive to XOS and monosaccharides production from poplar..

New strategy to elucidate the positive effects of extractable lignin on enzymatic hydrolysis by quartz crystal microbalance with dissipation.

BACKGROUND: The presence of lignin normally affects enzymatic saccharification of lignocellulose detrimentally. However, positive effects of lignin on enzymatic hydrolysis have been recently reported. Enzyme-lignin interactions could be the key to reveal the underlying mechanism of their discrepant behaviors. In this study, to elucidate the positive effects of extractable lignin (EL) on enzymatic hydrolysis of ethanol organosolv-pretreated wood sawdust, two lignin fractions, EL and milled wood lignin (MWL), were isolated sequentially from pretreated substrates. Quartz crystal microbalance with dissipation (QCM-D) was then used to investigate the lignin aggregation effects on enzyme adsorption. RESULTS: We found that both EL and MWL had a narrow molecular weight distribution. However, MWL had an obviously higher molecular weight than EL. This indicated that EL and MWL likely represent two distinct lignin fractions from ethanol organosolv-pretreated substrates. HSQC NMR analysis revealed that less ß-O-4, ß-ß, and ß-5 linkages and a higher S/G ratio was present in EL, as compared to MWL. QCM-D analysis showed that the enzyme adsorption on lignin was highly relevant to these lignin structural characteristics. An obviously lower maximum enzyme adsorption capacity was observed on EL films (152.63-168.09 ng/cm2) compared to MWL films (196.71-224.73 ng/cm2). Furthermore, enzyme desorption on lignin films was determined. A significantly lower irreversible enzyme adsorption was observed on EL (75.40 ng/cm2) compared to MWL (137.35 ng/cm2). More importantly, two reconstructed lignin films were designed to investigate lignin assembly on enzyme adsorption. The results indicated that the presence of EL reduced irreversible enzyme adsorption on the reconstructed lignin films by 39.2-45.0%. CONCLUSIONS: Lignin structure determined the interaction between enzyme and lignins. A positive correlation was observed between molecular weight, the content of ß-5 linkages, and enzyme adsorption on lignin. EL, which was more depolymerized and less condensed, had the lower enzyme adsorption of the two preparations tested. Additionally, the presence of EL reduced enzyme adsorption on reconstructed lignin films, perhaps through a mechanism involving the blocking of non-productive enzyme binding sites on the MWL. This could be the mechanism for the positive effects of EL on enzymatic hydrolysis.