Design of pH-responsive SAP polymer for pore solution chemistry regulation and crack sealing in cementitious materials.

The crack development is considered to be one of the most severe threats to the durability of concrete infrastructure. This study aims to enhance the durability performance of cementitious material with the pH-responsive Superabsorbent Polymer (SAP). The SAP was synthesized with acrylic acid (AA)-methyl acrylate (MA) precursors, and three type samples with different crosslinking levels were prepared. The examination on the pH sensitivity indicated that the swelling capacity of the prepared SAP would first increase and then decrease with solution alkalinity, and the peak swelling potential was achieved around pH value of 12 for all the three type SAP with solution/gel mass ratio of 500. Further examination indicated the alkalinity of the buffer solution was reduced during the adsorption test, which can be caused by the hydrolysis of the amide groups and the crosslinker. Besides that, it was also found the solution/gel ratio and the Ca(OH)2 content could affect the swelling potential of the SAP. After that, the performance tests were conducted for the evaluation of concrete with SAP. A wax-coating protocol for the SAP was designed by using the hot-water method to prevent its swelling during mixing process. It was found that the strength reduction for samples with wax-coated SAP was insignificant compared to that of the control samples. Furthermore, durability tests supported the wax-shell could be broken by the crack propagation in concrete. And further experimental studies are needed to optimize the wax-size and shell thickness for enhanced self-sealing efficiency.

Efficient generation of transgene- and feeder-free induced pluripotent stem cells from human dental mesenchymal stem cells and their chemically defined differentiation into cardiomyocytes.

Advance in stem cell research resulted in several processes to generate induced pluripotent stem cells (iPSCs) from adult somatic cells. In our previous study, the reprogramming of iPSCs from human dental mesenchymal stem cells (MSCs) including SCAP and DPSCs, has been reported. Herein, safe iPSCs were reprogrammed from SCAP and DPSCs using non-integrating RNA virus vector, which is an RNA virus carrying no risk of altering host genome. DPSCs- and SCAP-derived iPSCs exhibited the characteristics of the classical morphology with human embryonic stem cells (hESCs) without integration of foreign genes, indicating the potential of their clinical application. Moreover, induced PSCs showed the capacity of self-renewal and differentiation into cardiac myocytes. We have achieved the differentiation of hiPSCs to cardiomyocytes lineage under serum and feeder-free conditions, using a chemically defined medium CDM3. In CDM3, hiPSCs differentiation is highly generating cardiomyocytes. The results showed this protocol produced contractile sheets of up to 97.2% TNNT2 cardiomyocytes after purification. Furthermore, derived hiPSCs differentiated to mature cells of the three embryonic germ layers in vivo and in vitro of beating cardiomyocytes. The above whole protocol enables the generation of large scale of highly pure cardiomyocytes as needed for cellular therapy.

Discussion on molecular dynamics (MD) simulations of the asphalt materials.

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. This paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

Treatment Response Prediction Using Ultrasound-Based Pre-, Post-Early, and Delta Radiomics in Neoadjuvant Chemotherapy in Breast Cancer.

OBJECTIVE: To develop and validate a radiomics nomogram based on pre-treatment, early treatment ultrasound (US) radiomics features combined with clinical characteristics for early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer. METHOD: A total of 217 patients with histological results of breast cancer receiving four to eight cycles of NAC before surgery from January 2018 to December 2020 were enrolled. Patients from the study population were randomly separated into a training set (n = 152) and a validation set (n = 65) at a ratio of 7:3. A total of 788 radiomics features were extracted from each region of interest in the US image at pre-treatment baseline (radiomic signature, RS1), early treatment (after completion of two cycles of NAC, RS2) and delta radiomics (calculated between the pre-treatment and post-treatment features, Delta RS). The Max-Relevance and Min-Redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection. The predictive nomogram was built based on the radiomics signature combined with clinicopathological risk factors. Discrimination, calibration, and prediction performance were further evaluated in the validation set. RESULTS: Of the 217 breast masses, 127 (58.5%) were responsive to NAC and 90 (41.5%) were non-responsive. Following feature selection, nine features in RS1, 11 features in RS2, and eight features in Delta RS remained. With multivariate analysis, the RS1, RS2, Delta RS, and Ki-67 expression were independently associated with breast NAC response. However, the performance of the Delta RS (AUC Delta RS = 0.743) was not higher than RS1 (AUC RS1 = 0.722, PDelta vs RS1 = 0.086) and RS2 (AUC RS2 = 0.811, PDelta vs RS2 = 0.173) with the Delong test. The nomogram incorporating RS1, RS2, and Ki-67 expression showed better predictive ability for NAC response with an area under the curve (AUC) of 0.866 in validation cohorts than either the single RS1 (AUC 0.725) or RS2 (AUC 0.793) or Ki-67 (AUC 0.643). CONCLUSION: The nomogram incorporating pre-treatment and early-treatment US radiomics features and Ki-67 expression showed good performance in terms of NAC response in breast cancer, thereby providing valuable information for individual treatment and timely adjustment of chemotherapy regimens.

Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction.

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI. Methods: Based on microarray data from a public database, differential analysis and functional enrichment analysis were performed to identify aberrantly expressed genes in AMI and their potential functions. CIBERSORT was used for immune landscape analysis. We also obtained whole blood samples of 3 patients with AMI and performed second-generation sequencing (SGS) analysis. Weighted gene co-expression network analysis (WGCNA) and cross-tabulation analysis identified AMI-related key genes. Receiver operating characteristic (ROC) curves were used to assess the diagnostic power of key genes. Single-gene gene set enrichment analysis (GSEA) revealed the molecular mechanisms of diagnostic indicators. Results: A total of 53 AMI-related DEGs from a public database were obtained and found to be involved in immune cell activation, immune response regulation, and cardiac developmental processes. CIBERSORT confirmed that the immune microenvironment was altered between AMI and normal samples. A total of 77 hub genes were identified by WGCNA, and 754 DEGs were obtained from own SGS data. Seven diagnostic indicators of AMI were obtained, namely GZMA, NKG7, TBX21, TGFBR3, SMAD7, KLRC4, and KLRD1. The single-gene GSEA suggested that the diagnostic indicators seemed to be closely implicated in cell cycle, immune response, cardiac developmental, and functional regulatory processes. Conclusion: The present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis.