Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles of 0deg, 30deg, 45deg, 60deg and 90deg relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests

Improved Subcell Model for the Prediction of Braided Composite Response

In this work, the modeling of triaxially braided composites was explored through a semi-analytical discretization. Four unique subcells, each approximated by a "mosaic" stacking of unidirectional composite plies, were modeled through the use of layered-shell elements within the explicit finite element code LS-DYNA. Two subcell discretizations were investigated: a model explicitly capturing pure matrix regions, and a novel model which absorbed pure matrix pockets into neighboring tow plies. The in-plane stiffness properties of both models, computed using bottom-up micromechanics, correlated well to experimental data. The absorbed matrix model, however, was found to best capture out-of- plane flexural properties by comparing numerical simulations of the out-of-plane displacements from single-ply tension tests to experimental full field data. This strong correlation of out-of-plane characteristics supports the current modeling approach as a viable candidate for future work involving impact simulations

Synergistic effect of CD47 blockade in combination with cordycepin treatment against cancer

Cordycepin is widely considered a direct tumor-suppressive agent. However, few studies have investigated as the effect of cordycepin therapy on the tumor microenvironment (TME). In our present study, we demonstrated that cordycepin could weaken the function of M1-like macrophages in the TME and also contribute to macrophage polarization toward the M2 phenotype. Herein, we established a combined therapeutic strategy combining cordycepin and an anti-CD47 antibody. By using single-cell RNA sequencing (scRNA-seq), we showed that the combination treatment could significantly enhance the effect of cordycepin, which would reactivate macrophages and reverse macrophage polarization. In addition, the combination treatment could regulate the proportion of CD8+ T cells to prolong the progression-free survival (PFS) of patients with digestive tract malignancies. Finally, flow cytometry validated the changes in the proportions of tumor-associated macrophages (TAMs) and tumor-infiltrating lymphocytes (TILs). Collectively, our findings suggested that the combination treatment of cordycepin and the anti-CD47 antibody could significantly enhance tumor suppression, increase the proportion of M1 macrophages, and decrease the proportion of M2 macrophages. In addition, the PFS in patients with digestive tract malignancies would be prolonged by regulating CD8+ T cells

A multi-variable predictive warning model for cervical cancer using clinical and SNPs data

IntroductionCervical cancer is the fourth most common cancer among female worldwide. Early detection and intervention are essential. This study aims to construct an early predictive warning model for cervical cancer and precancerous lesions utilizing clinical data and simple nucleotide polymorphisms (SNPs).MethodsClinical data and germline SNPs were collected from 472 participants. Univariate logistic regression, least absolute shrinkage selection operator (LASSO), and stepwise regression were performed to screen variables. Logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), extreme gradient boosting(XGBoost) and neural network(NN) were applied to establish models. The receiver operating characteristic (ROC) curve was used to compare the models’ efficiencies. The performance of models was validated using decision curve analysis (DCA).ResultsThe LR model, which included 6 SNPs and 2 clinical variables as independent risk factors for cervical carcinogenesis, was ultimately chosen as the most optimal model. The DCA showed that the LR model had a good clinical application.DiscussionThe predictive model effectively foresees cervical cancer risk using clinical and SNP data, aiding in planning timely interventions. It provides a transparent tool for refining clinical decisions in cervical cancer management

A Novel N-Arylpyridone Compound Alleviates the Inflammatory and Fibrotic Reaction of Silicosis by Inhibiting the ASK1-p38 Pathway and Regulating Macrophage Polarization

Silicosis is one of the potentially fatal occupational diseases characterized by respiratory dysfunction, chronic interstitial inflammation, and fibrosis, for which treatment options are limited. Previous studies showed that a novel N-arylpyridone compound named AKEX0011 exhibited anti-inflammatory and anti-fibrotic effects in bleomycin-induced pulmonary fibrosis; however, it is unknown whether it could also be effective against silicosis. Therefore, we sought to investigate the preventive and therapeutic roles of AKEX0011 in a silicosis rodent model and in a silica-stimulated macrophage cell line. In vivo, our results showed that AKEX0011 ameliorated silica-induced imaging lung damages, respiratory dysfunction, reduced the secretion of inflammatory and fibrotic factors (TNF-α, IL-1β, IL-6, TGF-β, IL-4, and IL-10), and the deposition of fibrosis-related proteins (collagen I, fibronectin, and α-SMA), regardless of early or advanced therapy. Specifically, we found that AKEX0011 attenuated silicosis by inhibiting apoptosis, blocking the ASK1-p38 MAPK signaling pathway, and regulating polarization of macrophages. In vitro, AKEX0011 inhibited macrophages from secreting inflammatory cytokines and inhibited apoptosis of macrophages in pre-treated and post-treated models, concurrent with blocking the ASK1-p38 pathway and inhibiting M1 polarization. Collectively, AKEX0011, as a novel N-arylpyridone compound, exerted protective effects for silica-induced pulmonary inflammation and fibrosis both in vivo and in vitro, and hence, it could be a strong drug candidate for the treatment of silicosis