Chemistry Central - Latest Articles

Measurement of volatile organic compounds emitted in libraries and archives: An inferential indicator of paper decay?

Lorraine T Gibson — 2012-05-15T00:00:00Z

Background; A sampling campaign of indoor air was conducted to assess the typical concentration of indoor air pollutants in 8 National Libraries and Archives across the U.K. and Ireland. At each site, two locations were chosen that contained various objects in the collection (paper, parchment, microfilm, photographic material etc.) and one location was chosen to act as a sampling reference location (placed in a corridor or entrance hallway). Results and Discussion; Of the locations surveyed, no measurable levels of sulfur dioxide were detected and low formaldehyde vapour (< 18 ug m-3) was measured throughout. Acetic and formic acids were measured in all locations with, for the most part, higher acetic acid levels in areas with objects compared to reference locations. A large variety of volatile organic compounds (VOCs) was measured in all locations, in variable concentrations, however furfural was the only VOC to be identified consistently at higher concentration in locations with paper-based collections, compared to those locations without objects. To cross-reference the sampling data with VOCs emitted directly from books, further studies were conducted to assess emissions from paper using solid phase microextraction fibres (SPME) fibres and a newly developed method of analysis; collection of VOCs onto a polydimethylsiloxane (PDMS) elastomer strip. Conclusions; In this study acetic acid and furfural levels were consistently higher in concentration when measured in locations which contained paper-based items. It is therefore suggested that both acetic acid and furfural (possibly also trimethylbenzenes, ethyltoluene, decane and camphor) may be present in the indoor atmosphere as a result of cellulose degradation and together may act as an inferential non-invasive marker for the deterioration of paper. Direct VOC sampling was successfully achieved using SPME fibres and analytes found in the indoor air were also identified as emissive by-products from paper. Finally a new non-invasive, method of VOC collection using PDMS strips was shown to be an effective, economical and efficient way of examining VOC emissions directly from the pages of a book and confirmed that toluene, furfural, benzaldehyde, ethylhexanol, nonanal and decanal were the most concentrated VOCs emitted directly from paper measured in this study.

In-silico Predictive Mutagenicity Model Generation Using Supervised Learning Approaches

Abhik Seal — 2012-05-15T00:00:00Z

Background: Experimental screening of chemical compounds for biological activity is a time consuming and expensive practice. In silico predictive models permit inexpensive, rapid "virtual screening" to prioritize selection of compounds for experimental testing. Both experimental and in silico screening can be used to test compounds for desirable or undesirable properties. Prior work on prediction of mutagenicity has primarily involved identification of toxicophores rather than whole-molecule predictive models. In this work, we examined a range of in silico predictive classification models for prediction of mutagenetic properties of compounds, including methods such as J48 and SMO which have not previously been widely applied in cheminformatics. Results: The Bursi mutagenicity data set containing 4337 compounds (Set 1) and a Benchmark data set of 6512 compounds (Set 2) were taken as input data seta in this work. A third data set (Set 3) was prepared by joining up the previous two sets. Classification algorithms including Naive Bayes, Random Forest, J48 and SMO with 10 fold cross-validation and default parameters were used for model generation on these data sets. Models built using the combined performed better than those developed from the Benchmark data set. Significantly, Random Forest outperformed other classifiers for all the data sets, especially for Set 3 with 89.27% accuracy, 89% precision and ROC of 95.3%. To validate the developed models two external data sets, AID1189 and AID1194, with mutagenicity data were tested showing 62% accuracy with 67% precision and 65% ROC area and 91% accuracy, 91% precision with 96.3% ROC area respectively. A Random Forest model was used the approved drugs from DrugBank and metabolites from the Zinc Database with True Positives rate almost 85% showing the robustness of the model. Conclusion: We have created a new mutagenicity benchmark data set with around 8,000 compounds. Our work shows that highly accurate predictive mutagenicity models can be built using machine learning methods based on chemical descriptors and trained using this set, and these models provide a complement to toxicophores based methods. Further, our work supports other recent literature in showing that Random Forest models generally outperform other comparable machine learning methods for this kind of application.

A chemical specialty semantic network for the unified medical language system

C. Paul Morrey — 2012-05-11T00:00:00Z

Background: Terms representing chemical concepts found the Unified Medical Language System (UMLS) are used to derive an expanded semantic network with mutually exclusive semantic types. The UMLS Semantic Network (SN) is composed of a collection of broad categories calledsemantic types (STs) that are assigned to concepts. Within the UMLS's coverage of the chemical domain, we find a great deal of concepts being assigned more than one ST. This leads to the situation where the extent of a given ST may contain concepts elaborating variegated semantics. A methodology for expanding the chemical subhierarchy of the SN into a finer-grained categorization of mutually exclusive types with semantically uniform extents is presented. We call this network a Chemical Specialty Semantic Network (CSSN). A CSSN is derived automatically from the existing chemical STs and their assignments. The methodology incorporates a threshold value governing the minimum size of a type's extent needed for inclusion in the CSSN. Thus, different CSSNs can be created by choosing different threshold values based on varying requirements. Results: A complete CSSN is derived using a threshold value of 300 and having 68 STs. It is used effectively to provide high-level categorizations for a random sample of compounds from the "Chemical Entities of Biological Interest" (ChEBI) ontology. The effect on the size of the CSSN using various threshold parameter values between one and 500 is shown. Conclusions: The methodology has several potential applications, including its use to derive a precoordinated guide for ST assignments to new UMLS chemical concepts, as a tool for auditing existing concepts, inter-terminology mapping, and to serve as an upper-level network for ChEBI.

Synthesis of naringin 6-ricinoleate using immobilized lipase

Veronica M Almeida — 2012-05-11T00:00:00Z

Background: Naringin is an important flavanone with several biological activities, including antioxidant action. However, this compound shows low solubility in lipophilic preparations, such as is used in the cosmetic and food industries. One way to solve this problem is to add fatty acids to the flavonoid sugar unit using immobilized lipase. However, there is limited research regarding hydroxylation of unsaturated fatty acids as an answer to the low solubility challenge. In this work, we describe the reaction of naringin with castor oil containing ricinoleic acid, castor oil's major fatty acid component, using immobilized lipase from Candida antarctica. Analysis of the 1H and 13 C NMR (1D and 2D) spectra and literature comparison were used to characterise the obtained acyl derivative. Results: After allowing the reaction to continue for 120 hours (in acetone media, 50degreesC), the major product obtained was naringin 6"-ricinoleate. In this reaction, either castor oil or pure ricinoleic acid was used as the acylating agent, providing a 33% or 24% yield, respectively. The chemical structure of naringin 6"-ricinoleate was determined using NMR analysis, including bidimensional (2D) experiments. Conclusion: Using immobilized lipase from C. antarctica, the best conversion reaction was observed using castor oil containing ricinoleic acid as the acylating agent rather than an isolated fatty acid.

Immobilization of tris(2 pyridyl) methylamine in PVC-membrane sensor and characterization of the membrane properties

Majid Rezayi — 2012-05-07T00:00:00Z

Due to the increasing industrial use of titanium compounds, its determination is the subject of considerable efforts. The ionophore or the membrane active recognition is the most important component of any polymeric membrane sensor. The sensor respond depends on the ionophore and bonding between the ionophore and the target ion. Ionophores with molecule-sized dimensions containing cavities or semi-cavities can surround the target ion. The bond between ionophore and target ion gives different selectivity and sensitivity toward the other ions. Therefore, ionophores with different binding strengths can be used in the sensor. In the present work, poly(vinyl chloride) (PVC) based membrane incorporating tris(2 pyridyl) methylamine (tpm) as an ionophore have been prepared and explored as a titanium(III) selective sensor. The strengths of the ion-ionophore (Ti(OH)2+-tpm) interactions and the role of ionophore on membrane was performed by various techniques such as elemental analysis, UV-Vis, Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and powder X-ray diffraction (XRD). All data approve the successful incorporation of organic group via covalent bond.

New monocyclic monoterpenoid glycosides from Mentha haplocalyx Briq.

Gaimei She — 2012-05-06T00:00:00Z

Two new monocyclic monoterpenoid glycosides, rel-(1R,2S,3R,4R) p-menthane-1,2,3-triol 3-O--D-glucopyranoside (1) and rel- (1S,2R,3S) terpinolene-1,2,3-triol 3-O--D-glucopyranoside (2) were isolated from aqueous acetone extract of the aerial parts of Mentha haplocalyx. Their structures were elucidated through spectral analysis using MS and NMR spectrometers.

New lanostane-type triterpene acids from wolfiporia extensa

Gaimei She — 2012-05-06T00:00:00Z

Three new lanostane-type triterpene acids, 3-epi-benzoyloxyl-dehydrotumulosic acid (1), 3-epi-(3'-O-methyl malonyloxy)-dehydrotumulosic acid (2) and 3-epi-(3'-hydroxy-3'-methylglutaryloxyl)-dehydrotumulosic acid (3), were isolated from the sclerotia of Wolfiporia extensa, together with 3 known lanostane derivatives (4-6). Their structures were elucidated on the basis of spectroscopic analysis, including 1D and 2D-NMR techniques.

Essential oils from Leptospermums of the Sunshine Coast and northern rivers regions

Sarah AM Windsor — 2012-05-06T00:00:00Z

Background: Around the turn of this century, the oil yield and chemical composition of Australian Leptospermum species was analysed. Since that time, research has been focused on their use as phytomedicines. The oil yield and composition of essential oils from Australian Leptospermum species directly impacts their commercialisation for medicinal use. Results: The essential oils from Leptospermum (L.) juniperinum, L. laevigatum, L. liversidgei, L. polygalifolium, L. semibaccatum, L. speciosum, L. trinervium and L. whitei have been examined from specimens in the Sunshine Coast (Queensland) and Northern Rivers (New South Wales) Regions. Both chemotypes of L. liversidgei were observed. However, only chemotype II of L. semibaccatum and chemotype I of L. trinervium were identified. The only subspecies observed of L. polygalifolium was L. polygalifolium wallum. Conclusions: L. liversidgei chemotypes I and II have the potential for phytomedical use as antibacterial or antiinflammatory agents. Chemotype I has the potential for use as an insect repellent and chemotype II may provideantifungal activity.

Detailed kinetic and chemometric study of the cellulose thermal breakdown in artificially aged and non aged commercial paper. Different methods for computing activation energy as an assessment model in archaeometric applications

Federico Marini — 2012-05-02T00:00:00Z

Background: The thermal oxidative degradation of aged and non aged cellulose samples of commercial paper was studied using thermogravimetry and derivative thermogravimetry under a forced air flow up to 800°C. Results: TG and DTG data were processed using two non-isothermal-based model-fitting methods and one based on linear least squares to calculate E a trend values, measured as a function of artificially induced sample age. The E a trends thus obtained were compared in order to assess their potential for yielding archaeometric curves. As the trends of first two methods show an inversion of the direction between non aged cellulose samples and artificially aged samples, while the third method does not, an in-depth study was carried out using a multilinearity assumption. Conclusions: The results are discussed and the outcomes indicate that the above cited inversion is real and not linked to the method. Additionally, it was evidenced that the number of points used for the estimation of linear least squares model parameters is of capital importance.

Preface to supplement, CMA4CH 2010: Multivariate Analysis and Chemometry to Cultural Heritage and Environment

Giovanni Visco — 2012-05-02T00:00:00Z

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