A Novel Iron Phosphate Cement Derived from Copper Smelting Slag and its Early Age Hydration Mechanism

Copper slag (CS), a by-product of copper smelting, is normally stockpiled, leading to wastes of resource and space as well as environment pollution. It has not been massively reutilized as a supplementary cementitious material in Portland cement due to its low reactivity. In the present study, CS is for the first time utilized as the base component to prepare an iron phosphate cement (IPC) by reacting with ammonium dihydrogen phosphate (ADP) at room temperature. The influence of the raw materials mass ratio (CS/ADP) on the microstructure and performance of IPC pastes are investigated. It is found that the compressive strength of IPC pastes at all ages is not a monotonic function of CS/ADP, and the paste with CS/ADP of 2.0 gives the highest strengths, i.e., 26.8, 38.9 and 47.5 MPa at 1, 3 and 28 d, respectively. The crystalline phases including FeH2P3O10·H2O and FePO4 are formed as the main reaction products to bind the unreacted CS particles. The early age hydration of IPC is found to be a multi-stage process, involving the initial dissolution of ADP and iron-containing phases of CS, the formation of FeH2P3O10·H2O, the initial generation of FePO4, and the attainment of the hydration reaction equilibrium. Unlike the magnesium phosphate cement, a redox reaction of Fe(Ⅱ) into Fe(Ⅲ) occurs due to the suitable range of pH and oxidation-reduction potential of the IPC system during the hydration reaction

Potential pitfalls in the accuracy of analysis of natural sense-antisense RNA pairs by reverse transcription-PCR

<p>Abstract</p> <p>Background</p> <p>The ability to accurately measure patterns of gene expression is essential in studying gene function. The reverse transcription polymerase chain reaction (RT-PCR) has become the method of choice for the detection and measurement of RNA expression patterns in both cells and small quantities of tissue. Our previous results show that there is a significant production of primer-independent cDNA synthesis using a popular RNase H^-RT enzyme. A PCR product was amplified from RT reactions that were carried out without addition of RT-primer. This finding jeopardizes the accuracy of RT-PCR when analyzing RNA that is expressed in both orientations. Current literature findings suggest that naturally occurring antisense expression is widespread in the mammalian transcriptome and consists of both coding and non-coding regulatory RNA. The primary purpose of this present study was to investigate the occurrence of primer-independent cDNA synthesis and how it may influence the accuracy of detection of sense-antisense RNA pairs.</p> <p>Results</p> <p>Our findings on cellular RNA and <it>in vitro </it>synthesized RNA suggest that these products are likely the results of RNA self-priming to generate random cDNA products, which contributes to the loss of strand specificity. The use of RNase H⁺RT enzyme and carrying the RT reaction at high temperature (50°C) greatly improved the strand specificity of the RT-PCR detection.</p> <p>Conclusion</p> <p>While RT PCR is a basic method used for the detection and quantification of RNA expression in cells, primer-independent cDNA synthesis can interfere with RT specificity, and may lead to misinterpretation of the results, especially when both sense and antisense RNA are expressed. For accurate interpretation of the results, it is essential to carry out the appropriate negative controls.</p

Bis{1-[(o-tol­yl)imino­meth­yl]-2-naphthol­ato}copper(II)

In the title complex, [Cu(C18H14NO)2], the CuII ion lies on a crystallographic inversion centre and is bonded to the O- and N-donor atoms of the two bidentate chelate 1-[(o-tol­yl)imino­meth­yl]-2-naphtho­late ligands in a trans arrangement. The distorted square-planar geometry about CuII has normal dimensions, with Cu—O = 1.8881 (15) Å and Cu—N = 1.9804 (17) Å

Bis{1-[(4-methyl­phen­yl)imino­meth­yl]-2-naphtho­lato-κ2 N,O}copper(II)

In the title complex, [Cu(C18H14NO)2], the CuII ion lies on an inversion center and is coordinated in a slightly distorted square-planar environment. The 1-[(4-methyl­phen­yl)imino­meth­yl]-2-naphtho­late ligands are coordinated in a trans arrangement with respect to the N and O atoms

Altered gene-expression profile in rat plasma and promoted body and brain development by environmental enrichment

Environmental enrichment (EE) refers to the exposure of laboratory animals to physical and social stimulation, which can improve animals’ well-being. The study was aimed to explore how the prenatal EE impacts affect the development, behavior, hormones and gene expression of the offspring. 28 pregnant rats were randomized into an EE group (EEG) housed in cages with EE or a control group (CG) housed in normal cages. Measurements included offspring development parameters (body weight, body length, and tail length) and behavior (open-field test, OFT), hormone levels (cortisol, dopamine, 5-HT, and growth hormone) and gene expression profile. Results showed that the development parameters of EEG offspring were statistically superior to the CG offspring. OFT count of EEG offspring was more than CG. EEG and CG offspring did not differ on cortisol, dopamine, 5-HT or growth factor. Gene expression profile chip test showed that 25 genes were up-regulated and 23 genes down-regulated in the EEG vs CG comparison, among which five GO annotations and four KEGG pathways were annotated. Findings indicate that EE during pregnancy could positively promote the body and nervous system development of offspring, involving the evidence for altered gene expression profile.Keywords: Environmental enrichment, rats, gene expression, behavior, developmentAfrican Journal of Biotechnology Vol. 12(20), pp. 3071-308

Estimation of NO2_{2} emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO$_{2}$) air pollution provides valuable information for quantifying NOx (NOx = NO +NO$_{2}$) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO$_{2}$emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s−1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s−1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory. Weekly variations in NO$_{2}$emission are highly related to anthropogenic activities, such as the transport sector. The NO$_{2}$emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO$_{2}$emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO$_{2}$emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO$_{2}$decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s−1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s−1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory.We wish to acknowledge the Joint R&D and Talents Program project, funded by the Qingdao Sino-German Institute of Intelligent Technologies (grant no. kh0100020213319); the Deutsche Forschungsgemeinschaft; and the Open Access Publishing Fund of the Karlsruhe Institute of Technology for their support

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 – March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory.We also acknowledge the project of Joint R&D and Talents Program funded by the Qingdao Sino-German Institute of Intelligent Technologies (kh0100020213319) and the project of Transnational Interoperability Rules and Solution Patterns in Collaborative Production Networks based on IDS and GAIA-X funded by Ministry of Science and Technology, PRC (SQ2021YFE010470)

Resveratrol Activated Sonic Hedgehog Signaling to Enhance Viability of NIH3T3 Cells in Vitro via Regulation of Sirt1

Background/Aims: Injuries of the brain and spinal cord result in the formation of glial (reactive gliosis) and fibrotic (formed by fibroblasts) scars. Recent studies have shown that the fibrotic scar was much more important for hindering regeneration after brain or spinal cord injury than the astrocytic scar. However, it has been given much less attention for effects and mechanism of fibroblasts during formation of the fibrotic scar. Resveratrol may be a potential anti-scarring agent in burn-related scarring and keloid fibroblasts. However, it is unclear whether and how resveratrol affects formation of the fibrotic scar after brain or spinal cord injury. Earlier studies have shown that the activated Shh signaling has anti-apoptosis, anti-oxidation, anti-inflammation properties. Moreover, resveratrol can activate the Shh signaling. However, it is unclear how resveratrol activates the Shh signaling. Resveratrol is a activator of Sirt1. It is unknown whether resveratrol activates the Shh signaling via Sirt1. Methods: NIH3T3 cells, a fibroblast cell line, were used as model cells and treated with drugs. Cell viability was assessed by Cell Counting Kit 8. The expressions and activity of Shh signaling pathway proteins were evaluated by immunocytochemistry and Western blotting. Transcriptional activity of Gli-1 was detected with Dual-Luciferase Reporter Gene Assay Kit. Results: Resveratrol, Sirt1 agonist STR1720 and recombinant mouse Shh protein, an activator of hedgehog signaling, enhanced the viability of NIH3T3 cells, promoted Smo to translocated to the primary cilia and Gli-1 entered into the nuclei from cytoplasm, and upregulated expressions of Shh, Ptc-1, Smo, and Gli-1 proteins, which can be reversed by Smo antagonist cyclopamine and Sirt1 antagonist Sirtinol. Additionally, resveratrol increased transcriptional activity of Gli-1. Conclusion: We indicate in the first time that it may be mediated by Sirt1 for resveratrol activating the Shh signaling to enhance viability of NIH3T3 cells, and Sirt1 may be a regulator for upstream of the Shh signaling pathway.This study provides a basis for further investigating effects and mechanism of resveratrol during the formation of fibrous scar after brain or spinal cord injury