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Catalysis and deactivation of montmorillonite K10 in the aryl O -glycosylation of glycosyl trichloroacetoimidates

Xiaoliu LI, Xinhao YAN, Zhiwei LI, Hua CHEN, Pingzhu ZHANG,

Frontiers of Chemical Science and Engineering 2010, Volume 4, Issue 3,   Pages 342-347 doi: 10.1007/s11705-009-0279-1

Abstract: The catalysis of montmorillonite K10 (MK10) for aryl -glycosylation of glycosyl trichloroacetimidatesIt was found that the catalyst MK10 is deactivated gradually in the recycle glycosylation.

Keywords: photoelectron spectroscopy     adsorption-desorption     glycosylation     deactivated     diffraction    

Emerging roles of podoplanin in vascular development and homeostasis

Yanfang Pan,Lijun Xia

Frontiers of Medicine 2015, Volume 9, Issue 4,   Pages 421-430 doi: 10.1007/s11684-015-0424-9

Abstract:

Podoplanin (PDPN) is a mucin-type O-glycoprotein expressed in diverse cell types, suchtranscriptional activation of Pdpn by Prox1 and modification of PDPN with core 1-derived O<

Keywords: podoplanin     CLEC-2     Prox1     O-glycosylation     lymphatic vascular development and maintenance     lymphoid    

CAR T cells redirected against tumor-specific antigen glycoforms: can low-sugar antigens guarantee a sweet success?

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 322-338 doi: 10.1007/s11684-021-0901-2

Abstract: Immune-based therapies have experienced a pronounced breakthrough in the past decades as they acquired multiple US Food and Drug Administration (FDA) approvals for various indications. To date, six chimeric antigen receptor T cell (CAR-T) therapies have been permitted for the treatment of certain patients with relapsed/refractory hematologic malignancies. However, several clinical trials of solid tumor CAR-T therapies were prematurely terminated, or they reported life-threatening treatment-related damages to healthy tissues. The simultaneous expression of target antigens by healthy organs and tumor cells is partly responsible for such toxicities. Alongside targeting tumor-specific antigens, targeting the aberrantly glycosylated glycoforms of tumor-associated antigens can also minimize the off-tumor effects of CAR-T therapies. Tn, T, and sialyl-Tn antigens have been reported to be involved in tumor progression and metastasis, and their expression results from the dysregulation of a series of glycosyltransferases and the endoplasmic reticulum protein chaperone, Cosmc. Moreover, these glycoforms have been associated with various types of cancers, including prostate, breast, colon, gastric, and lung cancers. Here, we discuss how underglycosylated antigens emerge and then detail the latest advances in the development of CAR-T-based immunotherapies that target some of such antigens.

Keywords: cancer immunotherapy     chimeric antigen receptor     solid tumors     tumor-associated antigen     glycosylation     O-glycans     adoptive cell therapy    

Is atmospheric oxidation capacity better in indicating tropospheric O formation?

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 5, doi: 10.1007/s11783-022-1544-5

Abstract: ListItem>

● This study summarizes and evaluates different approaches that indicate O<

Keywords: O3     AOC     O3 formation regime    

Prediction of selected biodiesel fuel properties using artificial neural network

Solomon O. GIWA,Sunday O. ADEKOMAYA,Kayode O. ADAMA,Moruf O. MUKAILA

Frontiers in Energy 2015, Volume 9, Issue 4,   Pages 433-445 doi: 10.1007/s11708-015-0383-5

Abstract: Biodiesel is an alternative fuel to replace fossil-based diesel fuel. It has fuel properties similar to diesel which are generally determined experimentally. The experimental determination of various properties of biodiesel is costly, time consuming and a tedious process. To solve these problems, artificial neural network (ANN) has been considered as a vital tool for estimating the fuel properties of biodiesel, especially from its fatty acid (FA) composition. In this study, four ANNs have been designed and trained to predict the cetane number (CN), flash point (FP), kinematic viscosity (KV) and density of biodiesel using ANN with logsig and purelin transfer functions in the hidden layer of all the networks. The five most prevalent FAs from 55 feedstocks found in the literature utilized as the input parameters for the model are palmitic, stearic, oleic, linoleic and linolenic acids except for density network with a sixth parameter (temperature). Other FAs that are present in the biodiesels have been considered based on the number of carbon atom chains and the level of saturation. From this study, the prediction accuracy and the average absolute deviation of the networks are CN (96.69%; 1.637%), KV (95.80%; 1.638%), FP (99.07%; 0.997%) and density (99.40%; 0.101%). These values are reasonably better compared to previous studies on empirical correlations and ANN predictions of these fuel properties found in literature. Hence, the present study demonstrates the ability of ANN model to predict fuel properties of biodiesel with high accuracy.

Keywords: biodiesel     fuel properties     artificial neural network     fatty acid     prediction    

Availability of wind energy resource potential for power generation at Jos, Nigeria

O. O. Ajayi, R. O. Fagbenle, J. Katende, J. O. Okeniyi

Frontiers in Energy 2011, Volume 5, Issue 4,   Pages 376-385 doi: 10.1007/s11708-011-0167-5

Abstract: The objective of this study was to assess the potential viability of the wind resource potential in Jos, Plateau state, Nigeria for power generation. The monthly mean wind speeds that span from 1987 to 2007 were employed to statistically analyze the monthly, annual and seasonal potentials of the wind energy resources at the site. Besides, the results were employed together with two models of wind energy conversion system to simulate the likely average output power. The outcome showed that Jos was suitable as a site for wind farm projects of varying sizes and that MW·h to GW·h of electricity is likely to be produced per period of months, seasons and years. The average wind speed range at the site was also estimated to be between 6.7 and 11.8 m/s across the months, years and seasons.

Keywords: green electricity     renewable resources     Weibull statistics     Jos     Nigeria    

Selective oxidation of o -nitrotoluene to o -nitrobenzaldehyde with metalloporphyrins as biomimetic catalysts

Xinling WANG, Yuanbin SHE,

Frontiers of Chemical Science and Engineering 2009, Volume 3, Issue 4,   Pages 453-456 doi: 10.1007/s11705-009-0167-8

Abstract: Selective oxidation of -nitrotoluene to -nitrobenzaldehyde with metalloporphyrins as biomimetic catalysts was studied. The peripheral substituent around porphyrin rings and various process parameters of NaOH concentration, reaction temperature, reaction time and oxygen pressure all affect the selectivity of -nitrobenzaldehyde. Further, 82.0% selectivity of -nitrobenzaldehyde was achieved under the optimum conditions: 1.0×10mol•L of T(-NO)PPFeCl catalyst, 2.5mol•L of NaOH, 0.2mol•L of -nitrotoluene, 45°C and 2.0MPa for 6h.

Keywords: -nitrobenzaldehyde     temperature     biomimetic     selectivity     pressure    

Rh2O3/hexagonal CePO4 nanocatalysts for N2O decomposition

Huan Liu, Zhen Ma

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 4,   Pages 586-593 doi: 10.1007/s11705-017-1659-6

Abstract: Rh(NO ) was then used as a precursor for the impregnation of Rh O onto these CePO materials.The Rh O supported on the CePO nanowires was much more active for the catalytic decomposition of NO than the Rh O supported on CePO nanorods.of both catalysts as a function of time on stream was studied and the influence of the co-feed (CO , O, H O or O /H O) on the N O decomposition was also investigated.

Keywords: Rh2O3     CePO4     N2O decomposition    

IgG N-Glycosylation Cardiovascular Age Tracks Cardiovascular Risk Beyond Calendar Age Article

Zhiyuan Wu, Zheng Guo, Yulu Zheng, Yutao Wang, Haiping Zhang, Huiying Pan, Zhiwei Li, Lois Balmer, Xia Li, Lixin Tao, Xiuhua Guo, Wei Wang

Engineering 2023, Volume 26, Issue 7,   Pages 99-107 doi: 10.1016/j.eng.2022.12.004

Abstract: However, the usable capacity of IgG N-glycosylation profiles for the risk stratification of cardiovascularlearning (recursive feature elimination and penalized regression algorithms) and developed an IgG N-glycosylationThe GlyCage index developed in this study can thus be used to track cardiovascular health using IgG N-glycosylationbetween GlyCage and calendar age independently indicates the cardiovascular risk, suggesting that IgG N-glycosylation

Keywords: IgG N-glycosylation cardiovascular age     Cardiovascular aging     Immunoglobulin G     Glycosylation     Inflammation    

Spray Preparation, Microstructure and Properties of Al2O3-MxO Hard -

Wang Biao,Wang Yudong,Li Huiling,Zhang Zihua

Strategic Study of CAE 2002, Volume 4, Issue 9,   Pages 75-80

Abstract: steel substrate, base coating of nickel-coated aluminium and intermediate coating of 50% Al2O3 + 50% Ni were prepared by means of oxyacetylene spray, and final coating of Al2O3 ~ MxOy was prepared by means of plasma spray.mass) sulphuric acid with 60 % concentration, and 40% (mass) phosphoric ore powder, the Al2O3 ~ MxOy coating resistance to corrosion and wear, is 7.46 times as strong

Keywords: Al2O3-MxOy     coating     plasma     resistance to corrosion     resistance    

Mathematical Reasoning Challenges Artificial Intelligence

Sean O’Neill

Engineering 2019, Volume 5, Issue 5,   Pages 817-818 doi: 10.1016/j.eng.2019.08.009

Optimization of the O/HO process with response surface methodology for pretreatment of mother liquor

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 4, doi: 10.1007/s11783-020-1371-5

Abstract:

• Real ML-GFW with high salinity and high organics was degraded by O3/H2O2 process.

Keywords: High salinity     High organic matters     Gas field wastewater     O3/H2O2    

The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry

Tiago Miguel FERREIRA, João ESTÊVÃO, Rui MAIO, Romeu VICENTE

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 3,   Pages 609-622 doi: 10.1007/s11709-020-0623-6

Abstract: This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage, not with the goal of replacing existing approaches, but as a mean to improve the precision of empirical methods. For such, damage data collected in the aftermath of the 1998 Azores earthquake (Portugal) is used to develop a comparative analysis between damage grades obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks (ANNs). The analysis is carried out on the basis of a vulnerability index computed with a hybrid seismic vulnerability assessment methodology, which is subsequently used as input to both approaches. The results obtained are then compared with real post-earthquake damage observation and critically discussed taking into account the level of adjustment achieved by each approach. Finally, a computer routine that uses the ANN as an approximation function is developed and applied to derive a new vulnerability curve expression. In general terms, the ANN developed in this study allowed to obtain much better approximations than those achieved with the original vulnerability approach, which has revealed to be quite non-conservative. Similarly, the proposed vulnerability curve expression was found to provide a more accurate damage prediction than the traditional analytical expressions.

Keywords: Artificial Neural Networks     seismic vulnerability     masonry buildings     damage estimation     vulnerability curves    

Supersonic Travel Seeks an Encore

Sean O´Neill,

Engineering 2022, Volume 10, Issue 3,   Pages 1-3 doi: 10.1016/j.eng.2022.01.004

Handheld Ultrasound Advances Diagnosis

Sean O´Neill

Engineering 2021, Volume 7, Issue 11,   Pages 1505-1507 doi: 10.1016/j.eng.2021.09.001

Title Author Date Type Operation

Catalysis and deactivation of montmorillonite K10 in the aryl O -glycosylation of glycosyl trichloroacetoimidates

Xiaoliu LI, Xinhao YAN, Zhiwei LI, Hua CHEN, Pingzhu ZHANG,

Journal Article

Emerging roles of podoplanin in vascular development and homeostasis

Yanfang Pan,Lijun Xia

Journal Article

CAR T cells redirected against tumor-specific antigen glycoforms: can low-sugar antigens guarantee a sweet success?

Journal Article

Is atmospheric oxidation capacity better in indicating tropospheric O formation?

Journal Article

Prediction of selected biodiesel fuel properties using artificial neural network

Solomon O. GIWA,Sunday O. ADEKOMAYA,Kayode O. ADAMA,Moruf O. MUKAILA

Journal Article

Availability of wind energy resource potential for power generation at Jos, Nigeria

O. O. Ajayi, R. O. Fagbenle, J. Katende, J. O. Okeniyi

Journal Article

Selective oxidation of o -nitrotoluene to o -nitrobenzaldehyde with metalloporphyrins as biomimetic catalysts

Xinling WANG, Yuanbin SHE,

Journal Article

Rh2O3/hexagonal CePO4 nanocatalysts for N2O decomposition

Huan Liu, Zhen Ma

Journal Article

IgG N-Glycosylation Cardiovascular Age Tracks Cardiovascular Risk Beyond Calendar Age

Zhiyuan Wu, Zheng Guo, Yulu Zheng, Yutao Wang, Haiping Zhang, Huiying Pan, Zhiwei Li, Lois Balmer, Xia Li, Lixin Tao, Xiuhua Guo, Wei Wang

Journal Article

Spray Preparation, Microstructure and Properties of Al2O3-MxO Hard -

Wang Biao,Wang Yudong,Li Huiling,Zhang Zihua

Journal Article

Mathematical Reasoning Challenges Artificial Intelligence

Sean O’Neill

Journal Article

Optimization of the O/HO process with response surface methodology for pretreatment of mother liquor

Journal Article

The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry

Tiago Miguel FERREIRA, João ESTÊVÃO, Rui MAIO, Romeu VICENTE

Journal Article

Supersonic Travel Seeks an Encore

Sean O´Neill,

Journal Article

Handheld Ultrasound Advances Diagnosis

Sean O´Neill

Journal Article