Nan-an China

Keywords: Nan-an China
Description: Просмотреть профиль участника Nan An в LinkedIn. LinkedIn — крупнейшая в мире сеть бизнес-контактов, помогающая таким профессионалам как Nan An связываться с рекомендованными кандидатами на должность, отраслевыми экспертами и бизнес-партнёрами.

PhD Candidate of Chemistry at The George Washington University - Columbian College of Arts & Sciences

Role: Vice president for one year, chair of business department for one year, treasurer for one year.

Role: Entrepreneur lead for the team ToxSpec: low-cost, rapid method for predicting pharmaceutical compound activity and toxicity.

• 12/2010---07/2011 The comparison of ELISA(enzyme linked immunosorbent assay) and biological methods in detecting PSP(paralytic shellfish poison)

Responsibility: Shellfish product quality tests, including sampling, pretreatment of sample, detection of the number of bacteria, mice assay and ELISA of PSP

• 04/2009—04/2010 Participated in national-level Students Research Training at Jiangsu Provincial Key Laboratory of Tumor genesis and Intervention

Responsibility: Served as a group leader, studied the apoptosis of human gastric cancer cell BGC-823 induced by oroxylin-A using various methods..

Global Model for Octanol-Water Partition Coefficients from Proton Nuclear Magnetic Resonance Spectra Molecular Informatics

The ability to estimate chemical and physical properties from experimental spectra is highly desirable, as it eliminates the need for a priori knowledge of exact chemical structure and allows the property estimation of mixtures. Here we report the proof of principle that a predictive method for octanol-water partition coefficient (logP) based on 1H-NMR spectra in d3-chloroform is feasible and can yield accuracy comparable to in silico logP models. The Spectrometric Data-Activity Relationship (QSDAR) reported predicts logP of neutral organic chemicals using descriptors derived only from 1H-NMR chemical shifts, integrations and peak widths. Proton NMR spectra of 140 compounds with diverse structures were used to construct a Multiple Linear Regression (MLR) and a Partial Least Squares (PLS) model that predicts logP. The optimized models were internally validated by K-fold cross validation and leave-one-out validation, and externally with a test set of 28 chemicals. The squared regression coefficients of prediction for the MLR and PLS regression models were 0.970 and 0.971 respectively, showing that the method allows accurate prediction of logP values exclusively from predicted 1H NMR spectra.

Immobilization of imidazolium ionic liquids on hydrotalcites using silane linkers: retardation of memory effect RSC Advances

We report a new covalent surface immobilization of silane-modified imidazolium ionic liquids on hydrotalcite-like materials (HTs) and provide detailed characterization of the resulting surface chemistry using PXRD, CP-MAS, TGA and FT-IR. We show that this immobilization interferes with the “memory effect” of HTs and explore the stability of the resulting complexes to hydrolysis.

Fusilev,intravenous injections of levoleucovorin calcium,which belongs to Spectrum Pharmaceuticals Incorporation,got its FDA approval in 2008.It is indicated for rescue after high dose methotraxate therapy in osteosarcoma.We review the physical activity,the mechanism of action in the adjuvant treatment of cancer and its clinical applications in this article.

Meeting Abstract: Towards a model for predicting biological activity from 1H NMR Spectra: Quantitative spectra-​property model for octanol​/water partition coefficient using NMR-​derived descriptors 17th Annual Green Chemistry&Engineering Conference, Bethesda, MD, United States, June 18-20. p. GCE - 97.

The need for rational minimization of toxicity at the chem. design stage is clear. However, rational design for minimal toxicity requires the development of tools and guidelines that can be readily implemented by chemists alongside traditional synthesis and characterization steps. We aim to develop tools for predicting ecotoxicity based on spectroscopic characterization data, such as NMR, IR and UV-​visible spectroscopy. The first step is to develop a tool that predicts octanol​/water partition coeff. (logP)​, a key determinant of bioavailability, from NMR spectra. Here we report the development of a Quant. Spectra Property Relationship (QSPR) that predicts logP of org. chems. using only 1H NMR spectra. Proton NMR spectra of 202 compds. with diverse structure and functionality were digitized and used to build a multivariate model that uses features from the NMR spectra as the only descriptors. (R2 = 0.86)​. The model optimization and validation are discussed. This model is the first step in developing a Quant. Spectra Toxicity Relationship (QSPR) for aquatic toxicity and bioconcn.

Meeting Abstract: Rational design of green polar aprotic solvents: Synergistic in silico and experimental approach Abstracts of Papers, 246th ACS National Meeting & Exposition, Indianapolis, IN, United States, September 8-12, 2013 PagesCATL-99

The need to replace polar aprotic solvents such as DMF, NMP and DMAc is of utmost importance to industry, given the mounting evidence of their adverse biol. effects and the potential for regulatory action. The goal of this project was to develop polar aprotic solvents that accelerate synthetic reactions of interest, such as nucleophilic arom. substitution and Pd-​catalyzed couplings, but lack human​/eco-​toxicity. In addn. the alternative solvents must biodegrade and be competitively priced. Rationally designing a solvent that can meet these criteria can be a challenge; however, by taking advantage of recent advances in computational chem. synthetic chem. and mechanistic toxicol. we show it is feasible to optimize performance, toxicity and biodegradability simultaneously.

Meeting Abstract: Toward rational design of supports for single-​site catalysts: Probing electronic support interactions of palladium catalysts on tunable mixes metal oxides Abstracts of Papers, 250th ACS National Meeting & Exposition, Boston, MA, United States, August 16-20, 2015 PagesCATL-425

Single-​site heterogeneous catalysts (SSHCs) have tremendous potential to combine the advantages of homogeneous and heterogeneous catalysts, but often suffer from low activity, selectivity and stability. Our goal is to develop a rational understanding of how to predictably tune the electronic macroligand effect of the support. To this end, we systematically study the effect of modifying the acid-​base character of the support while controlling the support morphol. A class of supports that can be readily electronically tuned is hydrotalcites (HTs)​, layered double hydroxide basic clays. HTs doped with ∼15​% Zn, Cu, Fe, Ni, and Cr have been synthesized with high surface areas via a novel flow synthesis method, then characterized using PXRD, FT-​IR, TGA, Raman spectroscopy and gas adsorption. Micorcalorimetry studies confirm that the doping results in a gamut of distinct acid-​base properties. The immobilization of ligands to the HTs using four linkers (silanes, carboxylates, hydroxamates and sulfonates) has been studied to elucidate the surface chem. and hydrolytic stability assocd. with each. In addn. Pd(II)​-​ionic liq. catalysts have been immobilized on the a series HTs and studied by XAS, which shows significant differences in the Pd L2​/3 edges and Cl K-​edges resulting from the acid-​base properties of the support. The activity of this series of catalysts for Heck coupling is related to their electronic differences and leaching stability. SSHCs consisting of Pd and Ir CNC and CCC N-​heterocylic carbene pincer lignands immobilized via carboxylate and hydroxamate linkers have also been synthesized and studied. XPS results indicate an unusual spin orbit coupling reflective of electronic interactions between the HT support and the immobilized single-​site complexes. This work underscores the potential of exploiting electronic support interactions for optimization of catalytic activity and stability of supported homogeneous catalysts.

    Adelina Voutchkova, David Ramaker, Scott Daly, Nianqiang Wu, Joseph Bright, Nan An , Arturo Azua-Barrios, Matthew Finn

Meeting Abstract: Predictive tools for bioavailability and oxidative stress based on spectroscopic data Abstracts of Papers, 250th ACS National Meeting & Exposition, Boston, MA, United States, August 16-20, 2015 PagesENVR-13

In order to systematically approach the design of chemicals with minimal toxicity, we are in need of predictive tools that can be applied seamlessly during chemical synthesis and characterization. Our approach is to develop methods that utilize data from spectroscopic characterization to predict bioavailability and toxicity endpoints, referred to as Quantitative Spectrometric Data-Activity Relationships (QSDAR). These tools do not require knowledge of chemical structure and can be applied to predictions for mixtures. Here we report two models that predict octanol/water partition coefficient (log P) and skin permeability (log Kp) of organic chemicals using NMR spectra. These models are trained on a large training set with highly diverse structures and have been thoroughly externally validated (r2= 954 and q2 = 0.970 for log P; r2 = 0.838 and q2 = 0.837 for log Kp), which perform equally or better than prevailing structure-based methods. We now expand this work to develop QSDARs that predict Nrf2 (nuclear factor (erythroid-derived 2)-like 2) activity, which is associated with oxidative stress, a critical toxicological endpoint.

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