Properties and Microstructure of an Interfacial Transition Zone Enhanced by Silica Fume in Concrete Prepared with Coal Gangue as an Aggregate.

The wide application of concrete prepared with coal gangue (CG) as an aggregate (CPCGA) is limited because of the low mechanical strength and strong water absorption capacity of CG. This paper used silica fume (SF) to improve the performance of the interfacial transition zone (ITZ) in CPCGA and revealed the enhancement mechanism. The results showed that the compressive strength of CPCGA prepared with cement replaced by a suitable amount of SF at the age of 28 days increased by more than 30%, and the flexural strength increased by over 20%. The SF could effectively reduce the porosity and micropore size in the ITZ of CPCGA, and the porosity of the ITZ in CPCGA added with 7.50% SF decreased by 44.22, 46.16, and 24.46% at distances from the aggregate surface of 10, 50, and 100 µm, respectively, compared with CPCGA without SF. Further research showed that Ca(OH)2 (CH) generated in the cement hydration reaction reacted with a large amount of active SiO2 in SF to restrain the formation of coarse CH in the ITZ of CPCGA, and the calcium silicate hydrate (C-S-H) gel generated filled the ITZ micropores to reduce the ITZ porosity further. Moreover, the reaction of SF and CH helped to promote the hydration reaction of cement to proceed thoroughly in CPCGA, thus improving CPCGA performance.

Influence of ligands within Al-based metal-organic frameworks for selective separation of methane from unconventional natural gas.

Efficient CH4/N2 separation from unconventional natural gas is vital for both energy recycling and climate change control. Figuring out the reason for the disparity between ligands in the framework and CH4 is the crucial problem for developing adsorbents in PSA progress. In this study, a series of eco-friendly Al-based MOFs, including Al-CDC, Al-BDC, CAU-10, and MIL-160, were synthesized to investigate the influence of ligands on CH4 separation through experimental and theoretical analyses. The hydrothermal stability and water affinity of synthetic MOFs were explored through experimental characterization. The active adsorption sites and adsorption mechanisms were investigated via quantum calculation. The results manifested that the interactions between CH4 and MOFs materials were affected by the synergetic effects of pore structure and ligand polarities, and the disparities of ligands within MOFs determined the separation efficiency of CH4. Especially, the CH4 separation performance of Al-CDC with high sorbent selection (68.56), moderate isosteric adsorption heat for CH4 (26.3 kJ/mol), and low water affinity (0.1 g/g at 40% RH) was superior to most porous adsorbents, which was attributed to its nanosheet structure, proper polarity, reduced local steric hindrance, and extra functional groups. The analysis of active adsorption sites indicated that hydrophilic carboxyl groups and hydrophobic aromatic ring were the dominant CH4 adsorption sites for liner ligands and bent ligands, respectively. The methylene groups with saturated C-H bonds enhanced the wdV interaction between ligands and CH4, resulting in the highest binding energy of CH4 for Al-CDC. The results provided valuable guidance for the design and optimization of high-performance adsorbents for CH4 separation from unconventional natural gas.

Exploring the Mechanism of Yi-Jing Decoction in Treating Polycystic Ovary Syndrome by Using Network Pharmacology.

BACKGROUND: Yi-Jing decoction (YJD), a traditional Chinese medicine prescription, has been reported to be effective in the treatment of polycystic ovary syndrome (PCOS). However, the underlying mechanisms of YJD in treating PCOS are still unclear. OBJECTIVE: In the present work, the effective ingredients of YJD and their treatment mechanisms on PCOS were systematically analyzed. METHODS: The effective ingredients of YJD and targets of PCOS were selected from public databases. The network pharmacology method was used to analyze the ingredients, potential targets, and pathways of YJD for the treatment of PCOS. RESULTS: One hundred and three active ingredients were identified from YJD, of which 82 were hit by 65 targets associated with PCOS. By constructing the disease-common targetcompound network, five ingredients (quercetin, arachidonate, beta-sitosterol, betacarotene, and cholesterol) were selected out as the key ingredients of YJD, which can interact with the 10 hub genes (VEGFA, AKT1, TP53, ALB, TNF, PIK3CA, IGF1, INS, IL1B, PTEN) against PCOS. These genes are mainly involved in prostate cancer, steroid hormone biosynthesis, and EGFR tyrosine kinase inhibitor resistance pathways. In addition, the results of molecular docking showed that the ingredients of YJD have a good binding affinity with the hub genes. CONCLUSION: These results demonstrate that the treatment of PCOS by YJD is through regulating the levels of androgen and insulin and improving the inflammatory microenvironment.

Integrated transcriptomics unravels implications of glycosylation-regulating signature in diagnosis, prognosis and therapeutic benefits of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) patients, featured by markedly heterogeneous tumor microenvironment (TME), meet diverse clinical outcome and neoadjuvant response. Yet the comprehensive influences of aberrant glycosylation on the TME of HCC remain elusive. In this study, by integrated transcriptome profiling, we systemically analyzed the considerable value of glycosylation-regulating signature in diagnosis and prognosis of HCC. A diagnostic model for HCC based on glycosylation-regulating REOs (relative expression orderings) was constructed. A robust glycoscore system was developed to evaluate distinct glycosylation patterns of patients in both the discovery and independent validation cohorts. Mechanisms for prognostic discrepancies between these patterns were dissected in tumor immunoediting, metabolic reprogramming, somatic mutations, and copy number variation (CNV). An individual survival prediction webserver based on a nomogram model (https://survpredict.shinyapps.io/DynNom/) was also established, which facilitates the translational and clinical application of glycoscore. The glycoscore could also effectively predict therapeutic response to sorafenib, Transhepatic Arterial Chemotherapy and Embolization (TACE), and anti-PD-1 therapies in patients with divergent glycosylation patterns, which was validated by a machine learning model. In summary, our study provided a unique insight into the HCC diagnosis and prognostic stratification based on integrated glycosylation-regulating signature. The robust glycosylation scoring system could comprehensively evaluate TME traits, predict prognosis and clinical benefits from neoadjuvant therapies, which may hold promise for promoting personalized clinical decision-making.

TCMPG: an integrative database for traditional Chinese medicine plant genomes.

Because of their great therapeutic and economic value, medicinal plants have attracted increasing scientific attention. With the rapid development of high-throughput sequencing technology, the genomes of many medicinal plants have been sequenced. Storing and analyzing the increasing volume of genomic data has become an urgent task. To solve this challenge, we have proposed the Traditional Chinese Medicine Plant Genome database (TCMPG, http://cbcb.cdutcm.edu.cn/TCMPG/), an integrative database for storing the scattered genomes of medicinal plants. TCMPG currently includes 160 medicinal plants, 195 corresponding genomes, and 255 herbal medicines. Detailed information on plant species, genomes, and herbal medicines is also integrated into TCMPG. Popular genomic analysis tools are embedded in TCMPG to facilitate the systematic analysis of medicinal plants. These include BLAST for identifying orthologs from different plants, SSR Finder for identifying simple sequence repeats, JBrowse for browsing genomes, Synteny Viewer for displaying syntenic blocks between two genomes, and HmmSearch for identifying protein domains. TCMPG will be continuously updated by integrating new data and tools for comparative and functional genomic analysis.

INPUT: An intelligent network pharmacology platform unique for traditional Chinese medicine.

The application of network pharmacology has greatly promoted the scientific interpretation of disease treatment mechanism of traditional Chinese medicine (TCM). However, the data required by network pharmacology analysis were scattered in different resources. In the present work, by integrating and reorganizing the data from multiple resources, we developed the intelligent network pharmacology platform unique for traditional Chinese medicine, called INPUT (http://cbcb.cdutcm.edu.cn/INPUT/), for automatically performing network pharmacology analysis. Besides the curated data collected from multiple resources, a series of bioinformatics tools for network pharmacology analysis were also embedded in INPUT, which makes it become the first automatic platform able to explore the disease treatment mechanisms of TCM. With the built-in tools, researchers can also analyze their own in-house data and obtain the results of pivotal ingredients, GO and KEGG pathway, protein-protein interactions, etc. In addition, as a proof-of-principle, INPUT was applied to decipher the antidepressant mechanism of a commonly used prescription. In summary, INPUT is a powerful platform for network pharmacology analysis and will facilitate the researches on drug discovery.

Computational Analysis Illustrates the Mechanism of Qingfei Paidu Decoction in Blocking the Transition of COVID-19 Patients from Mild to Severe Stage.

BACKGROUND: The epidemic of SARS-CoV-2 has made COVID-19 a serious threat to human health around the world. The severe infections of SARS-CoV-2 are usually accompanied by higher mortality. Although the Qingfei Paidu Decoction (QFPDD) has been proved to be effective in blocking the transition of COVID-19 patients from mild to severe stage, its mechanism remains unclear. OBJECTIVE: This study aims to explore the mechanism of QFPDD in blocking the transition of COVID- 19 patients from mild to severe stage. MATERIALS AND METHODS: In the process of screening active ingredients, oral bioavailability (OB) and drug likeness (DL) are key indicators, which can help to screen out pivotal compounds. Therefore, with the criteria of OB≥30% and DL≥0.18, we searched active ingredients of QFPDD in the Traditional Chinese Medicine Systems Pharmacology (TCMSP, https://tcmspw.com/) by using its 21 herbs as keywords. RESULTS: We filtered out 6 pivotal ingredients from QFPDD by using the bioinformatics method, namely quercetin, luteolin, berberine, hederagenin, shionone and kaempferol, which can inhibit the highly expressed genes (i.e. CXCR4, ICAM1, CXCL8, CXCL10, IL6, IL2, CCL2, IL1B, IL4, IFNG) in severe COVID-19 patients. By performing KEGG enrichment analysis, we found seven pathways, namely TNF signaling pathway, IL-17 signaling pathway, Toll-like receptor signaling pathway, NFkappa B signaling pathway, HIF-1 signaling pathway, JAK-STAT signaling pathway, and Th17 cell differentiation, by which QFPDD could block the transition of COVID-19 patients from mild to severe stage. CONCLUSION: QFPDD can prevent the deterioration of COVID-19 in the following mechanisms, i.e. inhibiting SARS-CoV-2 invasion and replication, anti-inflammatory and immune regulation, and repairing body damage. These results will be helpful for the prevention and treatment of COVID-19.

Study on Preparation and Interfacial Transition Zone Microstructure of Red Mud-Yellow Phosphorus Slag-Cement Concrete.

Open stockpiling and the continual production of industrial solid wastes such as red mud (RM) and yellow phosphorus slag (YPS) have caused serious environmental pollution issues. Additionally, concrete prepared easily and with high strength is a widely applied building material. Therefore, replacing part or all of the cement for preparing concrete with RM and YPS will greatly reduce this kind of solid waste and, thus, decrease environmental pressures. This study investigated the best ratio for the replacement of concrete with RM and YPS, testing the mechanical properties as well as the morphology, material composition, and microporous structure of the interface transition zone (ITZ). The results showed for the concrete prepared with ordinary Portland cement replaced by 10.00 wt.% RM and 18 wt.% YPS, compared to ordinary Portland cement concrete, the compressive strength of concrete with basalt aggregate and dolomite aggregate increased by 25.04% and 27.27%, respectively, when the concrete was cured with steam for 28 days. Furthermore, it had a smaller average pore diameter and crystal size in the ITZ. The aggregate and matrix were more closely intertwined. This was because RM had a low cementitious activity and mainly had a filling effect when added to concrete, while the highly active silica in YPS could react with the Ca(OH)2 crystal (CH) produced from cement hydration to form calcium silicate hydrate (CSH) gel, improving the mechanical properties and microstructure of the concrete.

Decoding the Mechanism of Huanglian Jiedu Decoction in Treating Pneumonia Based on Network Pharmacology and Molecular Docking.

Huang-Lian-Jie-Du decoction (HLJDD) has been used to treat pneumonia for thousands of years in China. However, our understanding of its mechanisms on treating pneumonia is still unclear. In the present work, network pharmacology was used to analyze the potential active ingredients and molecular mechanisms of HLJDD on treating pneumonia. A total of 102 active ingredients were identified from HLJDD, among which 54 were hit by the 69 targets associated with pneumonia. By performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we obtained the main pathways associated with pneumonia and those associated with the mechanism of HLJDD in the treatment of pneumonia. By constructing the protein-protein interaction network of common targets, 10 hub genes were identified, which were mainly involved in the tumor necrosis factor (TNF) signaling pathway, interleukin 17 (IL-17) signaling pathway, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway. Moreover, the results of molecular docking showed that the active ingredients of HLJDD had a good affinity with the hub genes. The final results indicate that HLJDD has a greater effect on bacterial pneumonia than on viral pneumonia. The therapeutic effect is mainly achieved by regulating the host immune inflammatory response and oxidative stress reaction, antibacterial microorganisms, alleviating the clinical symptoms of pneumonia, repairing damaged cells, and inhibiting cell migration.

Investigation of the bond strength and microstructure of the interfacial transition zone between cement paste and aggregate modified by Bayer red mud.

In this study, a method is proposed for modifying aggregate with Bayer red mud (RM), and the bond strength and microstructure of the interfacial transition zone (ITZ) in the concrete prepared using the modified aggregate is determined. Compared to concrete prepared using natural basalt aggregate, concrete prepared with RM-modified basalt aggregate aged for 7 and 28 days had a 25.08 % and 21.75 %, respectively, higher compressive strength and a 39.53 % and 15.30 %, respectively, flexural strength. Compared to concrete prepared using natural limestone aggregate, the compressive and flexural strengths of concrete prepared with RM-modified limestone aggregate increased by over 10.00 % and 20 % respectively, after aging of both 7 and 28 days. The RM had a higher wettability to cement paste than basalt and limestone, implying that cement paste on the surface of RM-modified aggregate had a correspondingly stronger microflow and filling capacity. In addition, concrete prepared with the RM-modified aggregate had a low voidage, a compact ITZ structure and strong interfacial adhesion, resulting in considerably enhanced mechanical properties. This study provides novel applications for RM that can be widely used in building materials and waste reduction and a new method for improving the mechanical properties of concrete.

Identifying Antioxidant Proteins by Combining Multiple Methods.

Antioxidant proteins play important roles in preventing free radical oxidation from damaging cells and DNA. They have become ideal candidates of disease prevention and treatment. Therefore, it is urgent to identify antioxidants from natural compounds. Since experimental methods are still cost ineffective, a series of computational methods have been proposed to identify antioxidant proteins. However, the performance of the current methods are still not satisfactory. In this study, a support vector machine based method, called Vote9, was proposed to identify antioxidants, in which the sequences were encoded by using the features generated from 9 optimal individual models. Results from jackknife test demonstrated that Vote9 is comparable with the best one of the existing predictors for this task. We hope that Vote9 will become a useful tool or at least can play a complementary role to the existing methods for identifying antioxidants.

DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.

MOTIVATION: DNA N4-methylcytosine (4mC) is a crucial epigenetic modification. However, the knowledge about its biological functions is limited. Effective and accurate identification of 4mC sites will be helpful to reveal its biological functions and mechanisms. Since experimental methods are cost and ineffective, a number of machine learning-based approaches have been proposed to detect 4mC sites. Although these methods yielded acceptable accuracy, there is still room for the improvement of the prediction performance and the stability of existing methods in practical applications. RESULTS: In this work, we first systematically assessed the existing methods based on an independent dataset. And then, we proposed DNA4mC-LIP, a linear integration method by combining existing predictors to identify 4mC sites in multiple species. The results obtained from independent dataset demonstrated that DNA4mC-LIP outperformed existing methods for identifying 4mC sites. To facilitate the scientific community, a web server for DNA4mC-LIP was developed. We anticipated that DNA4mC-LIP could serve as a powerful computational technique for identifying 4mC sites and facilitate the interpretation of 4mC mechanism. AVAILABILITY AND IMPLEMENTATION: http://i.uestc.edu.cn/DNA4mC-LIP/. CONTACT: hlin@uestc.edu.cn or hj@uestc.edu.cn or chenweiimu@gmail.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Correlation between the expressions of gastrin, somatostatin and cyclin and cyclin-depend kinase in colorectal cancer.

AIM: To explore the correlation between the expressions of gastrin (GAS), somatostatin (SS) and cyclin, cyclin-dependent kinase (CDK) in colorectal cancer, and to detect the specific regulatory sites where gastrointestinal hormone regulates cell proliferation. METHODS: Seventy-nine resected large intestine carcinomatous specimens were randomly selected. Immunohistochemical staining for GAS, SS, cyclin D1, cyclin E, cyclin A, cyclin B1, CDK2 and CDK4 was performed according to the standard streptavidin-biotin-peroxidase (S-P) method. According to the semi-quantitative integral evaluation, SS and GAS were divided into high, middle and low groups. Cyclin D1, cyclin E, cyclin A, cyclin B1, CDK2, CDK4 expressions in the three GAS and SS groups were assessed. RESULTS: The positive expression rate of cyclin D1 was significantly higher in high (78.6%, 11/14) and middle GAS groups (73.9%, 17/23) than in low GAS group (45.2%, 19/42) (P<0.05, c2(high vs low) = 4.691; P<0.05, c2(middle vs low) = 4.945). The positive expression rate of cyclin A was significantly higher in high (100%, 14/14) and middle GAS groups (82.6%, 19/23) than in low GAS group (54.8%, 23/42) (P<0.01, c2(high vs low) = 9.586; P<0.05, c2(middle vs low) = 5.040). The positive expression rate of CDK2 was significantly higher in high (92.9%, 13/14) and middle GAS groups (87.0%, 20/23) than in low GAS group (50.0%, 21/42) (P<0.01, c2(high vs low) = 8.086; P<0.01, c2(middle vs low) = 8.715). The positive expression rate of CDK4 was significantly higher in high (78.6%, 11/14) and middle GAS groups (78.3%, 18/23) than in low GAS group (42.9%, 18/42) (P<0.05, c2(high vs low) = 5.364; P<0.01, c2(middle vs low) = 7.539). The positive expression rate of cyclin E was prominently higher in low SS group (53.3%, 24/45) than in high (9.1%, 1/11) and middle (21.7%, 5/23) SS groups (P<0.05, c2(high vs low) = 5.325; P<0.05, c2(middle vs low) = 6.212). The positive expression rate of CDK2 was significantly higher in low SS group (77.8%, 35/45) than in high SS group (27.3%, 3/11) (P<0.01, c2(high vs low) = 8.151). There was a significant positive correlation between the integral ratio of GAS to SS and the semi-quantitative integral of cyclin D1, cyclin E, cyclin A, CDK2, CDK4 (P<0.05, (D1)r(s) = 0.252; P<0.01, (E)r(s) = 0.387; P<0.01, (A)r(s) = 0.466; P<0.01, (K2)r(s) = 0.519; P<0.01, (K4)r(s) = 0.434). CONCLUSION: The regulation and control of gastrin, SS in colorectal cancer cell growth may be directly related to the abnormal expressions of cyclins D1, A, E, and CDK2, CDK4. The regulatory site of GAS in the cell cycle of colorectal carcinoma may be at the G(1), S and G(2) phases. The regulatory site of SS may be at the entrance of S phase.