Solid-phase Synthesis of Visible-light-driven BiVO4 Photocatalyst and Photocatalytic Reduction of Aqueous Cr(VI)

This communication reports a pioneering study on the synthesis of BiVO4 and photocatalytic reduction of Cr(VI)-polluted wastewaters. Monoclinic phase BiVO4 micron-crystals with adjustable morphology were synthesized via a solid-phase route. The structures, morphology, optical properties of the BiVO4 micron-crystals were characterized by X-ray diffraction, field emission scanning electron microscopy, UV-vis diffuse reflectance spectra, Fourier transform infrared spectroscopy spectra, and photocurrent measurements. Besides, their photocatalytic properties were tested for the reduction of aqueous Cr(VI) under visible light (l > 420 nm) irradiation. The photocatalytic tests showed that the photocatalytic activities of BiVO4 powders in aqueous Cr(VI) depended on the dark adsorption amount for Cr(VI) and number of photogenerated carriers. BiVO4-(c) exhibited the highest photocatalytic reduction efficiency that attributed to highest separation and transfer efficiency of photogenerated electrons and holes. Besides, effects of photocatalytic experiment parameters (including dosage of photocatalyst and coexistent anions and cations) on the Cr(VI) removal rate by BiVO4-(c) were also investigated, and •OH play an important role in the BiVO4 photocatalytic reduction Cr(VI). Copyright © 2019 BCREC Group. All rights reserved

Linking Incomplete Reprogramming to the Improved Pluripotency of Murine Embryonal Carcinoma Cell-Derived Pluripotent Stem Cells

Somatic cell nuclear transfer (SCNT) has been proved capable of reprogramming various differentiated somatic cells into pluripotent stem cells. Recently, induced pluripotent stem cells (iPS) have been successfully derived from mouse and human somatic cells by the over-expression of a combination of transcription factors. However, the molecular mechanisms underlying the reprogramming mediated by either the SCNT or iPS approach are poorly understood. Increasing evidence indicates that many tumor pathways play roles in the derivation of iPS cells. Embryonal carcinoma (EC) cells have the characteristics of both stem cells and cancer cells and thus they might be the better candidates for elucidating the details of the reprogramming process. Although previous studies indicate that EC cells cannot be reprogrammed into real pluripotent stem cells, the reasons for this remain unclear. Here, nuclei from mouse EC cells (P19) were transplanted into enucleated oocytes and pluripotent stem cells (P19 NTES cells) were subsequently established. Interestingly, P19 NTES cells prolonged the development of tetraploid aggregated embryos compared to EC cells alone. More importantly, we found that the expression recovery of the imprinted H19 gene was dependent on the methylation state in the differential methylation region (DMR). The induction of Nanog expression, however, was independent of the promoter region DNA methylation state in P19 NTES cells. A whole-genome transcriptome analysis further demonstrated that P19 NTES cells were indeed the intermediates between P19 cells and ES cells and many interesting genes were uncovered that may be responsible for the failed reprogramming of P19 cells. To our knowledge, for the first time, we linked incomplete reprogramming to the improved pluripotency of EC cell-derived pluripotent stem cells. The candidate genes we discovered may be useful not only for understanding the mechanisms of reprogramming, but also for deciphering the transition between tumorigenesis and pluripotency

Association of the LEP gene with immune infiltration as a diagnostic biomarker in preeclampsia

Objective: Preeclampsia (PE) is a serious condition in pregnant women and hence an important topic in obstetrics. The current research aimed to recognize the potential and significant immune-related diagnostic biomarkers for PE.Methods: From the Gene Expression Omnibus (GEO) data sets, three public gene expression profiles (GSE24129, GSE54618, and GSE60438) from the placental samples of PE and normotensive pregnancy were downloaded. Differentially expressed genes (DEGs) were selected and determined among 73 PE and 85 normotensive control pregnancy samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analysis. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the expression levels and diagnostic value of biomarkers in PE were verified in the GSE75010 data set (80 PE and 77 controls) and validated by qRT-RCR, Western blot, and immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in PE.Results: In total, 15 DEGs were recognized. The GO and KEGG analyses revealed that the DEGs were enriched in the steroid metabolic process, receptor ligand activity, GnRH secretion, and neuroactive ligand−receptor interaction. The recognized DEGs were primarily implicated in cell-type benign neoplasm, kidney failure, infertility, and PE. Gene sets related to hormone activity, glycosylation, multicellular organism process, and response to BMP were activated in PE. The LEP gene was distinguished as a diagnostic biomarker of PE (AUC = 0.712) and further certified in the GSE75010 data set (AUC = 0.850). The high expression of LEP was associated with PE in clinical samples. In addition, the analysis of the immune microenvironment showed that gamma delta T cells, memory B cells, M0 macrophages, and regulatory T cells were positively correlated with LEP expression (P < 0.05).Conclusion:LEP expression can be considered to be a diagnostic biomarker of PE and can offer a novel perspective for future studies regarding the occurrence and molecular mechanisms of PE

Simulation of Electrochemical Impedance Spectra of Solid Oxide Fuel Cells Using Transient Physical Models

A general electrochemical impedance spectroscopy ͑EIS͒ modeling approach by directly solving a one-dimensional transient model based on physical conservation laws was applied for simulating EIS spectra of an anode-supported solid oxide fuel cell ͑SOFC͒ button cell consisting of Ni-yttria-stabilized zirconia ͉Ni-scandia-stabilized zirconia ͑ScSZ͉͒ScSZ͉lanthanum strontium manganate ͑LSM͒-ScSZ multiple layers. The transient SOFC model has been solved for imposed sinusoidal voltage perturbations at different frequencies. The results have then been transformed into EIS spectra. Six parameters had to be tuned ͑three for the cathode and three for the anode͒ and have been estimated using data from a symmetric cathode cell and from a button cell. The experimental and simulated EIS spectra were in good agreement for a range of temperatures ͑750-850°C͒, of feed compositions ͑mixture of H 2 /H 2 O/N 2 ͒, and of oxidants ͑air and oxygen͒. This approach can help in interpreting EIS spectra, as illustrated by identifying the contribution of transport limitation. Fuel cell electrochemical systems are usually complex and are governed by coupled physicochemical processes such as chemical and electrochemical reactions, charge transport, and mass transport. 1,2 Because polarization curves can only provide a general description of the cell performance, electrochemical impedance spectroscopy ͑EIS͒ has become widely used in fuel cell research and development because it involves a relatively simple electrical measurement that gives detailed information about the fuel cell system, from mass-transport properties, chemical reaction rates, and dielectric properties to defects, microstructure, compositional influences, etc. 3 In this dynamic technique, usually a voltage perturbation is applied to a system and the amplitude and phase shift of the resulting current response are measured. Measurements can be conducted over a wide range of frequencies, resulting in the construction of impedance spectra. 5 Although the approach is useful and quite powerful, it often has limitations such as: 1. The approach can lead to ambiguities in data interpretations because the equivalent circuits are seldom unique except for only the simplest circuits. An equivalent circuit involving several circuit elements could often be rearranged in various configurations while still yielding the same impedance. 2. Detailed physical and chemical processes in the system cannot be predicted by equivalent-circuit models. For instance, the effects of current distributions and concentration distributions cannot be taken into account when interpreting data from equivalent-circuit models. 3. The measured system could only be approximated by circuit elements when assuming linear response of the system. The impedance is supposed to be independent of the amplitude of the applied signals. However, the electrochemical system could be highly nonlinear, especially for sinusoidal perturbations with high amplitudes. It was suggested that nonlinear EIS ͑NLEIS͒ measurements have several potential advantages. To investigate solid oxide fuel cell ͑SOFC͒ electrode reaction kinetics, Miterdorfer and Gauckler 7-9 used a state-space model ͑SSM͒, which is widely used in control theory for solving complex differential equations. Bieberle and Gauckler 5 studied in depth elementary electrochemical reactions in SOFC anode by both experimental and SSM approaches. To simulate the electrochemical impedance spectra, the models were solved directly through the SSM approach. Bessler 10 presented a computational method for simulating EIS spectra based on transient numerical simulations of the reaction system. The impedance was then calculated in the time domain from the simulated periodic response of the system, maintaining its full nonlinear response. This method has been further validated by detailed modeling studies on SOFC EIS spectra achieved from gas-transport processes. 11 Gewies et al. 12 also applied this method on Ni/yttria-stabilized zirconia ͑YSZ͒ cermet anodes. Zhu and Kee 13 developed a time-accurate model to analyze EIS spectra in anode-supported button cells with internal methane reforming. This model represented significant advantages regarding physical conservation laws, porous media transport within the electrode, and heterogeneous chemistry reactions mechanisms, all of those being solved in the time domain. However, the spatial variations of ion and electron transport throughout the electrode structures were not considered. In this paper, a general approach for EIS spectra simulation is applied by solving a comprehensive set of coupled transient models based on physical conservation laws. This simulation approach is illustrated by considering a transient model of an anode-supported SOFC button cell consisting of Ni-YSZ͉Ni-scandia-stabilized zirconia ͑ScSZ͉͒ScSZ͉LSM-ScSZ multiple layers. The simulation results of the EIS spectra were then compared to the measured EIS spectra under various conditions to prove the validity of both the transient model and the EIS simulation approach. Experimental Testing cell.-The anode-supported SOFC button cell used in this study consisted of a Ni/YSZ anode support layer ͑680 m͒, a Ni/ScSZ anode active interlayer ͑15 m͒, a ScSZ thin-film electrolyte layer ͑20 m͒, and a lanthanum strontium manganate ͑LSM͒/ ScSZ cathode layer ͑15 m͒. 14,1

Beneficial Effect of Young Oocytes for Rabbit Somatic Cell Nuclear Transfer

Abstract This study was designed to examine the effect of the age of rabbit oocytes on the developmental potential of cloned embryos. The metaphase II oocytes used for nuclear transfer (NT) were collected at 10, 12, 14, and 16h post-hCG injection (hpi). The total number of oocytes collected per donor (21.4-23.7) at 12 to 16 hpi was similar, but significantly higher than that collected at 10 hpi (16.2). Additionally, a significant improvement in blastocyst development was achieved with embryos generated by electrically mediated cell fusion (56.0%), compared to those from nuclear injection (13.1 %) (Experiment 1). Markedly higher blastocyst development (45.8-54.5%) was also achieved with oocytes collected at 10-12 hpi than from those collected 14-16 hpi (8.3-14.3%) (Experiment 2). In Experiment 3, the blastocyst rates of NT embryos derived from oocytes harvested 12 hpi (39.2-42.8 %) were significantly higher than from those collected at 16 hpi (6.8-8.4 %) (p<0.05), regardless of the donor cell age. Kinase activity assays showed variable changes of activity in rabbit oocytes over the period of 10-16 hpi; however, there was no correlation with preimplantational development (blastocyst rate vs. MPF, R=0.326; blastocyst rate vs. MAPK, R=0.131). Embryo transfer of NT embryos utilizing 12 hpi oocytes resulted in one full-term but stillborn, and one live cloned rabbit; thus, an efficiency of 1.7 % (n=117) (Experiment 4). These results demonstrated that NT utilizing relatively young rabbit oocytes, harvested at 10-12h after hCG injection, was beneficial for the development of NT embryos.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78139/1/clo.2008.0042.pd

Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease

IntroductionCardiovascular disease (CVD) is a group of diseases involving the heart or blood vessels and represents a leading cause of death and disability worldwide. Carotid plaque is an important risk factor for CVD that can reflect the severity of atherosclerosis. Accordingly, developing a prediction model for carotid plaque formation is essential to assist in the early prevention and management of CVD.MethodsIn this study, eight machine learning algorithms were established, and their performance in predicting carotid plaque risk was compared. Physical examination data were collected from 4,659 patients and used for model training and validation. The eight predictive models based on machine learning algorithms were optimized using the above dataset and 10-fold cross-validation. The Shapley Additive Explanations (SHAP) tool was used to compute and visualize feature importance. Then, the performance of the models was evaluated according to the area under the receiver operating characteristic curve (AUC), feature importance, accuracy and specificity.ResultsThe experimental results indicated that the XGBoost algorithm outperformed the other machine learning algorithms, with an AUC, accuracy and specificity of 0.808, 0.749 and 0.762, respectively. Moreover, age, smoke, alcohol drink and BMI were the top four predictors of carotid plaque formation. It is feasible to predict carotid plaque risk using machine learning algorithms.ConclusionsThis study indicates that our models can be applied to routine chronic disease management procedures to enable more preemptive, broad-based screening for carotid plaque and improve the prognosis of CVD patients

Single-shot time-gated fluorescence lifetime imaging using three-frame images

Qualitative and quantitative measurements of complex flows demand for fast single-shot fluorescence lifetime imaging (FLI) technology with high precision. A method, single-shot time-gated fluorescence lifetime imaging using three-frame images (TFI-TGFLI), is presented. To our knowledge, it is the first work to combine a three-gate rapid lifetime determination (RLD) scheme and a four-channel framing camera to achieve this goal. Different from previously proposed two-gate RLD schemes, TFI-TGFLI can provide a wider lifetime range 0.6 ~ 13ns with reasonable precision. The performances of the proposed approach have been examined by both Monte-Carlo simulations and toluene seeded gas mixing jet diagnosis experiments. The measured average lifetimes of the whole excited areas agree well with the results obtained by the streak camera, and they are 7.6ns (N2 = 7L/min; O2 < 0.1L/min) and 2.6ns (N2 = 19L/min; O2 = 1L/min) with the standard deviations of 1.7ns and 0.8ns among the lifetime image pixels, respectively. The concentration distributions of the quenchers and fluorescent species were further analyzed, and they are consistent with the experimental settings