Floral Aromatics of Ptelea: Chemical Identification and Human Response

Many members of the citrus family (Rutaceae) are valued for the aromatic compounds emitted by their flowers. Ptelea species are unusually cold-hardy members of the Rutaceae, but conflicting descriptions of the fragrance of their unisexual flowers may discourage the use of these trees. We analyzed floral volatiles and human response to these chemicals to test the hypothesis that the fragrance of staminate and pistillate flowers of these species differs. Gas chromatography and mass spectrometry showed that most volatile chemicals emitted by flowers of Ptelea trifoliata and Ptelea crenulata are monoterpenes, sesquiterpenes, and esters. Most volatiles were emitted from flowers of both sexes, but ethyl benzoate and estragole were emitted only from pistillate flowers. When concentrations of aromatics differed between sexes, they were higher for pistillate flowers, except for cis-3-hexenyl butanoate and an unidentified terpene. For P. crenulata and P. trifoliata, respectively, 81% and 77% of survey responses were from volunteers who liked the fragrance. Panelists most frequently described the scent of flowers of P. crenulata of both sexes with the words citrus, lime, and sweet. Panelists distinguished between pistillate and staminate flowers of P. trifoliata, describing the odor of pistillate flowers most frequently with the words damp-earthy, spicy, and sweet; staminate flowers were perceived as light, fresh, grassy, and pleasant. This work represents the first analysis of floral volatiles of P. crenulata and resolves conflicting prior reports regarding the floral fragrance of P. trifoliata. We conclude that differences among people rather than the sex of flowers account for conflicting prior reports of floral fragrance. The scents of flowers of P. crenulata and P. trifoliata appeal to most people and are horticultural assets of these trees.

EXTRACTION, ISOLATION, CHEMICAL IDENTIFICATION AND IN VITRO UROLITHIATIC ACTIVITY OF PIPERINE FROM PIPER NIGRUM

Piper nigrum is belongs to the family Piperaceae. The aim of the present study was to extract, isolate and investigate in vitro urolithiatic activity of alkaloid (piperine) from black pepper and identification by chemical reagents. In vitro urolithiatic evaluation of piperine was performed by percentage dissolution and turbidity methods. Calcium oxalate crystals were synthetically prepared and packed in a semipermeable membrane in both methods. Results were compared statistically and it showed significant P​

Dark-Field Hyperspectral Microscopy for Carbon Nanotubes Bioimaging

Carbon nanotubes have emerged as a versatile and ubiquitous nanomaterial, finding applications in industry and biomedicine. As a result, biosafety concerns that stimulated the research focused on evaluation of carbon nanotube toxicity. In addition, biomedical applications of carbon nanotubes require their imaging and identification in biological specimens. Among other methods, dark-field microscopy has become a potent tool to visualise and identify carbon nanotubes in cells, tissues, and organisms. Based on the Tyndall effect, dark-field optical microscopy at higher magnification is capable of imaging nanoscale particles in live objects. If reinforced with spectral identification, this technology can be utilised for chemical identification and mapping of carbon nanotubes. In this article we overview the recent advances in dark-field/hyperspectral microscopy for the bioimaging of carbon nanotubes.

A BERT-Based Hybrid System for Chemical Identification and Indexing in Full-Text Articles

Identification and indexing of chemical compounds in full-text articles are essential steps in biomedical article categorization, information extraction, and biological text mining. BioCreative Challenge was established to evaluate methods for biological text mining and information extraction. Track 2 of BioCreative VII (summer 2021) consists of two subtasks: chemical identification and chemical indexing in full-text PubMed articles. The chemical identification subtask also includes two parts: chemical named entity recognition (NER) and chemical normalization. In this paper, we present our work on developing a hybrid pipeline for chemical named entity recognition, chemical normalization, and chemical indexing in full-text PubMed articles. Specifically, we applied BERT-based methods for chemical NER and chemical indexing, and a sieve-based dictionary matching method for chemical normalization. For subtask 1, we used PubMedBERT with data augmentation on the chemical NER task. Several chemical-MeSH dictionaries including MeSH.XML, SUPP.XML, MRCONSO.RFF, and PubTator chemical annotations are used in a specific order to get the best performance on chemical normalization. We achieved an F1 score of 0.86 and 0.7668 on chemical NER and chemical normalization, respectively. For subtask 2, we formulated it as a binary prediction problem for each individual chemical compound name. We then used a BERT-based model with engineered features and achieved a strict F1 score of 0.4825 on the test set, which is substantially higher than the median F1 score (0.3971) of all the submissions.

Life sciences and mass spectrometry: some personal reflections

Molecular analysis of biological systems by mass spectrometry was in focus of technological developments in the second half of the 20th century, in which the issues of chemical identification of high molecular diversity by biophysical instrumental methods appeared as a mission impossible. By developing dialogs between researchers dealing with life sciences and medicine on one side and technology developers on the other, new horizons toward deciphering, identifying and quantifying of complex systems became a reality. Contributions toward this goal can be today considered as pioneering efforts delivered by a number of researchers, including generations of motivated students and associates.

Large scale enzyme based xenobiotic identification for exposomics

Advances in genomics have revealed many of the genetic underpinnings of human disease, but exposomics methods are currently inadequate to obtain a similar level of understanding of environmental contributions to human disease. Exposomics methods are limited by low abundance of xenobiotic metabolites and lack of authentic standards, which precludes identification using solely mass spectrometry-based criteria. Here, we develop and validate a method for enzymatic generation of xenobiotic metabolites for use with high-resolution mass spectrometry (HRMS) for chemical identification. Generated xenobiotic metabolites were used to confirm identities of respective metabolites in mice and human samples based upon accurate mass, retention time and co-occurrence with related xenobiotic metabolites. The results establish a generally applicable enzyme-based identification (EBI) for mass spectrometry identification of xenobiotic metabolites and could complement existing criteria for chemical identification.