Chemical composition of leaf and root essential oils of Boenninghausenia albiflora Reichb. from northern India
The leaf and root essential oil composition of Boenninghausenia albiflora Reichb and Meissner (family: Rutaceae), collected from Uttarakhand, India, was analysed by capillary gas chromatography and gas chromatography–mass spectrometry. The major constituents identified in the leaf essential oil were β-myrcene, (Z)-β-guaiene, (Z)-β-ocimene and β-caryophyllene, whereas bicyclogermacrene, α-terpinyl acetate, geijerene and β-copaene-4α-ol were identified as the major constituents of the root essential oil. This is the first time that the chemical compositions of leaf and root essential oils of B. albiflora have been investigated in detail. The results show significant qualitative and quantitative variations in leaf and root oil composition.
VOC Profiles of Saliva in Assessment of Halitosis and Submandibular Abscesses Using HS-SPME-GC/MS Technique
Halitosis and submandibular abscesses are examples of mouth-related diseases with the possible bacterial origin. Salivary volatile organic compounds (VOCs) are potential biomarkers of them, once they can be addressed as metabolites of bacterial activity. Healthy patients (n = 15), subjects with submandibular abscesses located in fascial deep space (n = 10), and subjects with halitosis (n = 5) were enrolled in the study. Saliva samples were subjected to headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled to mass spectrometry (GC/MS) analysis. A total number of 164 VOCs was detected by the developed methodology, 23 specific for halitosis and 41 for abscess. Halitosis’ profiles were characterized by a larger number of sulfur compounds, while for abscess they had a higher variety of alcohols, aldehydes, and hydrocarbons—biomarkers of inflammatory processes. Principal components analysis allowed visualization of clusters formed according to the evaluated conditions. Kruskal-Wallis test indicated that 39 VOCs presented differentiated responses between the studied groups, with statistical relevance (p < 0.05). Random forest was applied, and a prediction model based on eight VOCs (2-butanone, methyl thioacetate, 2-methylbutanoic acid, S-methyl pentanethioate, dimethyl tetrasulfide, indolizine, pentadecane, and octadecanal) provided 100% of sensitivity, 82% of specificity, and 91% of balanced accuracy, indicating the specific presence of submandibular abscess.
Instrumentation and Automated Photometric Titration Procedure for Total Acidity Determination in Red Wine Employing a Multicommuted Flow System
An automated procedure for photometric titration of red wine and associated instrumentation is described. The procedure was based on the flow-batch approach implemented employing multicommutation. The photometric detection was carried out using a homemade LED-based photometer. The mixing device, LED, and photodetector were attached to the titration chamber in order to form a compact and small-sized unit. The flow system comprised an automatic injector and three-way solenoid valves, which were controlled by a microcomputer through an electronic interface card. The software, written in Quick BASIC 4.5, was designed with abilities to accomplish all steps of the titration procedure including data acquisition and real-time processing to decide about the course of titration in the following step and so forth, until the titration endpoint was reached. The usefulness of the proposed titration system was demonstrated by analyzing red wine samples. When results were compared with those obtained using the AOAC reference method, no significant difference was observed at the 95% confidence level. A relative standard deviation of ca  2% (n=9 ) was obtained when processing a typical red wine sample containing 7.3 gl -1 total acidity expressed as tartaric acid.