In the medicine of many countries, the use of herbal healing agents included a significant contribution to improving human health and well-being. Many antibiotics have been widely used to treat infectious diseases caused by various pathogenic bacteria. However, increased multidrug resistance has led to increased severity of diseases caused by bacterial pathogens. Bacteria remain the main causative agents of diseases that cause human death, even in the present day. This cause prompted scientists to investigate alternative new molecules against bacterial strains. The significant interest for the study is Portulaca oleracea L. (family Portulacaceae), a widespread annual plant used in folk medicine. Thus, the production and study of CO2 extract of Portulaca oleracea is an actual problem. Methods. Raw materials were collected from Almaty and Zhambyl regions (Southeast and South Kazakhstan) in phase flowering. Portulaca oleracea herb’s CO2 extract was obtained by subcritical carbon dioxide extraction (installation of carbon dioxide flow-through extraction- 5L). The Wiley 7th edition and NIST’02 library were used to identify the mass spectra obtained. The antimicrobial activity study was conducted by the micromethod of serial dilution and disco-diffuse method. Standard test strains of microorganisms were used: Bacillus subtilis ATCC 6633, Staphylococcus aureus ATCC 6538-P, Candida albicans ATCC 10231, and Escherichia coli ATCC 8739. Results. The use of carbon dioxide extraction (further CO2 extract) is a promising direction of obtaining total medicinal substances containing biologically active substances, from fractions of volatile esters of various composition and functional purpose until a fraction of fatty acids and fat-soluble vitamins. In the current study, we obtained CO2 extract at subcritical conditions from aboveground organs of Portulaca oleracea and investigated the component composition for the first time. From 41 to 66 components were identified in the composition of Portulaca oleracea‘s CO2 extract. Studies of antimicrobial activity showed that CO2 extract of Portulaca oleracea had the expressed effect against clinically significant microorganisms such as Escherichia coli, Staphylococcus aureus, Bacillus subtilis, and Candida albicans. Conclusions. This study showed that CO2 extract of Portulaca oleracea’s raw material contained biological active compounds exhibiting a significant antimicrobial effect.
Present paper describes optimization of the method of quantitative determination of total petroleum hydrocarbons in soil samples using headspace solid - phase microextraction (SPME) in combination with gas chromatography - mass spectrometry (GC-MS). Effects of moisture content and solvent additives<br />were studied. It was established that an increase of the moisture content in soil leads to an increase of the response of petroleum hydrocarbons reaching its maximum at 15-20% depending on the soil type and concentration of total petroleum hydrocarbons followed by its gradual decrease. For the same concentration of petroleum hydrocarbons, an increase of moisture content in soil from 0 to 20% may lead to a 15x increase of total petroleum hydrocarbons response by solid - phase microextraction. Determination of total petroleum hydrocarbons in soils by SPME -GC-MS without moisture control of samples may lead to large errors, especially at low concentrations. It was established that addition of the solvent to a soil-water mixture allows dissolution of an oil film on the water surface and provides better extraction of hydrocarbons from soil to water phase. To avoid effect of moisture content on the extraction efficiency and more precise analysis of the real samples, addition of the excess distilled water must be done. Addition of the polar organic solvent to a soil-water mixture (10% isopropanol) allows dissolution of an oil film on the water surface and provides linear dependence of extraction efficiency vs total petroleum hydrocarbons content in soil. Testing of the optimized method on model soil samples provided quantitative data, results being in 30-120% range from the real values.
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