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Objective: To develop an inflammation-based risk stratification tool for operative mortality in patients with acute type A aortic dissection. Methods: Between January 1, 2016 and December 31, 2021, 3124 patients from Beijing Anzhen Hospital were included for derivation, 571 patients from the same hospital were included for internal validation, and 1319 patients from other 12 hospitals were included for external validation. The primary outcome was operative mortality according to the Society of Thoracic Surgeons criteria. Least absolute shrinkage and selection operator regression were used to identify clinical risk factors. A model was developed using different machine learning algorithms. The performance of the model was determined using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves, and Brier score for calibration. The final model (5A score) was tested with respect to the existing clinical scores. Results: Extreme gradient boosting was selected for model training (5A score) using 12 variables for prediction—the ratio of platelet to leukocyte count, creatinine level, age, hemoglobin level, prior cardiac surgery, extent of dissection extension, cerebral perfusion, aortic regurgitation, sex, pericardial effusion, shock, and coronary perfusion—which yields the highest AUC (0.873 [95% confidence interval (CI) 0.845-0.901]). The AUC of 5A score was 0.875 (95% CI 0.814-0.936), 0.845 (95% CI 0.811-0.878), and 0.852 (95% CI 0.821-0.883) in the internal, external, and total cohort, respectively, which outperformed the best existing risk score (German Registry for Acute Type A Aortic Dissection score AUC 0.709 [95% CI 0.669-0.749]). Conclusion: The 5A score is a novel, internally and externally validated inflammation-based tool for risk stratification of patients before surgical repair, potentially advancing individualized treatment. Trial Registration: clinicaltrials.gov Identifier: NCT04918108

Chronic myelogenous leukemia (CML) is a type of cancer with a series of characteristics that make it particularly suitable for observations on leukemogenesis. Research have exhibited that the occurrence and progression of CML are associated with the dynamic alterations of histone modification (HM) patterns. In this study, we analyze the distribution patterns of 11 HM signals and calculate the signal changes of these HMs in CML cell lines as compared with that in normal cell lines. Meanwhile, the impacts of HM signal changes on expression level changes of CML-related genes are investigated. Based on the alterations of HM signals between CML and normal cell lines, the up- and down-regulated genes are predicted by the random forest algorithm to identify the key HMs and their regulatory regions. Research show that H3K79me2, H3K36me3, and H3K27ac are key HMs to expression level changes of CML-related genes in leukemogenesis. Especially H3K79me2 and H3K36me3 perform their important functions in all 100 bins studied. Our research reveals that H3K79me2 and H3K36me3 may be the core HMs for the clinical treatment of CML.

Empirical likelihood as a nonparametric approach has been demonstrated to have many desirable merits for constructing a confidence region. The purpose of this article is to apply the empirical likelihood method to study the generalized functional-coefficient regression models with multiple smoothing variables when the response is subject to random right censoring. The coefficient functions with multiple smoothing variables can accommodate various nonlinear interaction effects between covariates. The empirical log-likelihood ratio of an unknown parameter is constructed and shown to have a standard chi-squared limiting distribution at the true parameter. Based on this, the confidence region of the unknown parameter can be constructed. Simulation studies are carried out to indicate that the empirical likelihood method performs better than a normal approximation-based approach for constructing the confidence region.

In practical applications, lots of data such as sequentially collected economic data often exhibit some evident dependence. This paper studies the varying-coefficient regression models with different smoothing variables when the data form a stationary α-mixing sequence. Both the averaged and integrated estimators of coefficient functions are proposed. The asymptotic normalities of the proposed averaged and integrated estimators are also established.

The chemical shift is sensitive to changes in the local environments and can report the structural changes. The structure information of a protein can be represented by the average chemical shifts (ACS) composition, which has been broadly applied for enhancing the prediction accuracy in protein subcellular locations and protein classification. However, different kinds of ACS composition can solve different problems. We established an online web server named acACS, which can convert secondary structure into average chemical shift and then compose the vector for representing a protein by using the algorithm of auto covariance. Our solution is easy to use and can meet the needs of users.

Background: Peripheral platelet-white blood cell ratio (PWR) integrating systemic inflammatory and coagulopathic pathways is a key residual inflammatory measurement in the management of acute DeBakey type I aortic dissection (AAD); however, trajectories of PWR in AAD is poorly defined. Methods: Two AAD cohorts were included in two cardiovascular centers (2020-2022) if patients underwent emergency total arch replacement with frozen elephant trunk implantation. PWRdata were collected over time at baseline and five consecutive days after surgery. Trajectory patterns of PWR were determined using the latent class mixed modelling (LCMM). Cox regression was used to determine independent risk factors. By adding PWR Trajectory, a user-friendly nomogram was developed for predicting mortality after surgery. Results: Two hundred forty-six patients with AADwere included with a median follow-up of 26 (IRQ 20-37) months. Three trajectories of PWRwere identified [cluster α 45(18.3%), β105 (42.7%), and α 96 (39.0%)]. Cluster γ was associatedwith higher risk of mortality at follow-up (crude HR, 3.763; 95% CI: 1.126-12.574; P=0.031) than cluster a. By the addition of PWR trajectories, an inflammatory nomogram, composed of age, hemoglobin, estimated glomerular filtration rate, and cardiopulmonary time was developed and internally validated, with adequate discrimination [the area under the receiver-operating characteristic curve 0.765, 95%CI: 0.660-0.869)], calibration, and clinical utility. Conclusion: Based on PWR trajectories, three distinct clusters were identified with short-term outcomes, and longitudinal residual inflammatory shed some light to individualize treatment strategies for AAD. [ABSTRACT FROM AUTHOR]

A theoretical study of the negative-donor center (D–) at the hetero-interface in a magnetic field is presented. The energy of a spin triplet state (p-like) of the D– center is calculated by a variational approach. The polaron correction to the D–state is discussed within second-order perturbation theory. Numerical results are produced for the heterostructure of some III–V crystals. We find that the polaron correction is very important and the contribution of the polaron is not negligible. [ABSTRACT FROM AUTHOR]