Modification of the approach to the technology of preparation of samples of milk and dairy prod- ucts for the determination of the fatty acid profile using the gas chromatography method

The objects of the study are extractants and optimal extraction conditions that contribute to the full release of the substances being determined: the concentration and volume of the extractant, the extraction time and temperature regime.   This work includes the technology of sample preparation for determining the fatty acid composition of milk with a fat mass fraction of more than 3 %, which is centrifuged for 10 minutes at 10000 rpm, 20 µl of oil is taken from the centrifuged laboratory sample into a test tube from the upper part, then dissolved in 2 cm3 of organic solvent (hexane), then mixed manually for 1-2 minutes, 100 ml of sodium methylate solution of 2 molar concentration is added to the resulting solution with a pipette and the tube is closed with a stopper, then intensively mixed manually for 2 minutes, insist for 5 minutesand filter through a paper filter the top layer containing methyl esters, the resulting solution will be ready for examination by gas chromatography. The proposed new approach to technology development reduces the sample preparation time (~19 min), reduces the amount of solvent consumed by more than 10 times, minimizes the number of actions when working with samples, and requires a minimum amount of equipment

Potassium Ions are More Effective than Sodium Ions in Salt Induced Peptide Formation

Prebiotic peptide formation under aqueous conditions in the presence of metal ions is one of the plausible triggers of the emergence of life. The salt-induced peptide formation reaction has been suggested as being prebiotically relevant and was examined for the formation of peptides in NaCl solutions. In previous work we have argued that the first protocell could have emerged in KCl solution. Using HPLC-MS/MS analysis, we found that K(+) is more than an order of magnitude more effective in the L-glutamic acid oligomerization with 1,1'-carbonyldiimidazole in aqueous solutions than the same concentration of Na(+), which is consistent with the diffusion theory calculations. We anticipate that prebiotic peptides could have formed with K(+) as the driving force, not Na(+), as commonly believed

Ubiquitin-independent proteosomal degradation of myelin basic protein contributes to development of neurodegenerative autoimmunity

© The Author(s). Recent findings indicate that the ubiquitin-proteasome system is involved in the pathogenesis of cancer as well as autoimmune and several neurodegenerative diseases, and is thus a target for novel therapeutics. One disease that is related to aberrant protein degradation is multiple sclerosis, an autoimmune disorder involving the processing and presentation of myelin autoantigens that leads to the destruction of axons. Here, we show that brainderived proteasomes from SJL mice with experimental autoimmune encephalomyelitis (EAE) in an ubiquitinindependent manner generate significantly increased amounts of myelin basic protein peptides that induces cytotoxic lymphocytes to target mature oligodendrocytes ex vivo. Ten times enhanced release of immunogenic peptides by cerebral proteasomes from EAE-SJL mice is caused by a dramatic shift in the balance between constitutive and β1ihigh immunoproteasomes in the CNS of SJL mice with EAE. We found that during EAE, β1i is increased in resident CNS cells, whereas β5i is imported by infiltrating lymphocytes through the blood-brain barrier. Peptidyl epoxyketone specifically inhibits brain-derived β1ihigh immunoproteasomes in vitro (kobs/[I] = 240 M-1s-1), and at a dose of 0.5 mg/kg, it ameliorates ongoing EAE in vivo. Therefore, our findings provide novel insights into myelin metabolism in pathophysiologic conditions and reveal that the β1i subunit of the immunoproteasome is a potential target to treat autoimmune neurologic diseases

Диагностика заболеваний легких на основе протеомного анализа конденсата выдыхаемого воздуха

Investigation of exhaled breath condensate (EBC) is a noninvasive diagnostic method in respiratory diseases. The objective of this study was to compare EBC protein spectrum in healthy volunteers and in patients with chronic obstructive pulmonary disease (COPD), pneumonia and lung cancer (NSCLC), as well as to assess a role of proteomic analysis of EBC for diagnosis and differential diagnosis of these diseases. Methods. We examined 18 patients with COPD, 13 patients with community-acquired pneumonia, 26 patients with lung cancer and 24 healthy non-smoking volunteers. EBC was collected using ECoScreen system (VIASYS Healthcare, Germany) and a standardized method. EBC-samples were lyophilized, hydrolyzed and analyzed by HPLC and tandem mass spectrometry. To identify proteins, we used Mascot (Matrix Science, UK) and IPI-human (version 3.82) databases provided by the European Bioinformatics Institute. Results. Proteomic analysis of EBC identified more than 300 different proteins; most of them were types I and II cytoskeletal keratins. Cytokeratin 5, 6, and 14 concentrations in EBC of NSCLC patients were significantly higher than that in healthy volunteers. Dermcidin, immunoglobulin alpha, kininogen, cytoplasmic actin, serum albumin, and Zn-alpha2-glycoprotein were identified in EBC of healthy volunteers and patients with COPD and pneumonia. High concentration of peroxiredoxin in EBC of COPD patients could be due to severe oxidative stress. High levels of acute-phase and hypoxia proteins (annexins A1 and A2, HSP90B, cystatins M and B, collagen and histones fragments) were detected in EBC of pneumonia patients. Also, β- и α-subunit of hemoglobin, nuclear ubiquitin casein (NUCKS), POTEE, high mobility group protein (HMG-I/HMG-Y) and lactoferrin were identified in EBC of NSCLC patients. Conclusion. We found that EBC in healthy nonsmokers and in patients with COPD, pneumonia and NSCLC had characteristic protein spectrum. Most of the identified proteins could be used for diagnosis of these diseases.Исследование конденсата выдыхаемого воздуха (КВВ) является неинвазивным методом диагностики заболеваний органов дыхания. Протеомный анализ КВВ – перспективный метод диагностики, позволяющий понять патологические механизмы и выявить различные фенотипы легочных заболеваний. Цель. Сравнительное изучение белкового спектра КВВ у здоровых добровольцев и пациентов с хронической обструктивной болезнью легких (ХОБЛ), пневмонией и немелкоклеточным раком легкого (НМРЛ), а также оценка возможности использования протеомного анализа КВВ для диагностики и дифференциальной диагностики этих заболеваний. Материалы и методы. Обследованы лица с ХОБЛ (n = 18), внебольничной пневмонией (n = 13), НМРЛ (n = 26) и здоровые некурящие добровольцы (n = 24). КВВ собран стандартизованным методом с помощью аппарата ECoScreen (Viasys Healthcare, Германия). Лиофилизированные и подвергнутые гидролизу трипсином образцы КВВ проанализированы с помощью нанопоточной высокоэффективной жидкостной хроматографии и тандемной масс-спектрометрии. Для поиска и идентификации белков использованы предоставленные Европейским институтом биоинформатики базы данных Mascot (Matrix Science, Великобритания) и IPI-human (version 3.82). Результаты. При протеомном анализе КВВ обследованных доноров 4 групп выявлено > 300 различных белков, бoльшую часть которых составляют цитоскелетные кератины I и II типов. Отмечено значительно более высокое содержание некоторых кератинов (5, 6 и 14) в образцах КВВ больных НМРЛ по сравнению с таковым у здоровых добровольцев. В КВВ у здоровых добровольцев, а также у больных ХОБЛ и пневмонией идентифицированы дермцидин, иммуноглобулин-α, кининоген, цитоплазматический актин, сывороточный альбумин, цинк-α2-гликопротеин. Высокое содержание пероксиредоксина в КВВ у больных ХОБЛ указывает на выраженный окислительный стресс. В образцах КВВ у пациентов с пневмонией обнаружен высокий уровень белков острой фазы воспаления и гипоксии (аннексины A1 и A2, HSP90B, цистатины М и В, фрагменты коллагенов и гистонов). В КВВ у больных НМРЛ определены β- и α-субъединицы гемоглобина, ядерный убиквитиновый казеин, POTEE, белки группы высокой мобильности (HMG-I / HMG-Y), лактоферрин. Заключение. В образцах КВВ у здоровых людей, больных ХОБЛ, пневмонией и НМРЛ обнаружен характерный белковый спектр. Большинство выявленных белков могут быть предложены в качестве панели для диагностики указанных заболеваний

СРАВНИТЕЛЬНЫЙ ПРОТЕОМНЫЙ АНАЛИЗ КОНДЕНСАТА ВЫДЫХАЕМОГО ВОЗДУХА У ПАЦИЕНТОВ С РАКОМ ЛЕГКОГО МЕТОДОМ МАСС-СПЕКТРОМЕТРИИ ВЫСОКОГО РАЗРЕШЕНИЯ

Analysis of exhaled breath condensate (EBC) is a promising non-invasive method to diagnose respiratory diseases. Most researchers emphasize the importance of proteomic analysis of EBC for early diagnosis of certain respiratory diseases including lung cancer. This study was aimed at identification of potential biomarkers of neoplastic disorders in EBC of patients with lung cancer using high-performance liquid chromatography and high resolution mass-spectrometry. The study involved 26 patients with lung carcinoma (21 males, 5 females, mean age 57 ± 12 years) and 23 healthy non-smokers (19 males, 4 females, mean age 30 ± 7 years). EBC samples were collected using a disposable portable condenser R-Tube. The most of proteins identified (65 %) belonged to keratin family including type 1 (1; 2; 5 and 6А) and type 2 (9; 10; 14; 16 and 17) cytoskeletal keratins and transport proteins (albumin, lipocalin-1). Keratin family proteins (5, 6 and 14) prevailed in lung cancer patients compared to controls (p < 0.05). Other 6 proteins were also detected predominantly in lung cancer patients including b-subunit and a-subunit of haemoglobin, nuclear ubiquitous casein (NUCKS), high-mobility group proteins (HMG-I/HMG-Y), and lactoferrin. Most of these proteins could be used as a diagnostic panel to detect lung cancer. Further investigations are needed to estimate diagnostic values of these biomarkers and their role in pathogenesis of lung cancer.Анализ конденсата выдыхаемого воздуха (КВВ) является перспективным неинвазивным методом оценки состояния дыхательной системы. Многие исследователи указывают на важность анализа протеома КВВ для раннего выявления заболеваний респираторного тракта, в т. ч. диагностики рака легкого (РЛ). В исследовании, в которое были включены 2 группы доноров: основная – больные РЛ (n = 26; 21 мужчина, 5 женщин; средний возраст – 56,5 ± 11,5 года) и контрольная (n = 23; 19 мужчин, 4 женщины; средний возраст – 30,0 ± 7,0 года) – здоровые некурящие добровольцы, у больных РЛ методом высокоэффективной жидкостной хроматографии и тандемной масс-спектрометрии была проведена идентификация потенциальных белков-онкомаркеров в КВВ. Образцы КВВ были собраны с помощью одноразового портативного конденсора R-Tube. Основную часть (65 %)  идентифицированных белков составили белки кератиновой группы, в т. ч. кератины цитоскелетные 1-го (1, 2, 5 и 6А) и 2-го (9, 10, 14, 16 и 17) типов, а также группа транспортных белков (альбумин, липокалин-1). Было показано, что группа кератинов (5, 6 и 14) более значительно выражена (р < 0,05) у онкологических больных по сравнению со здоровым контролем. Также 6 белков были преимущественно определены в КВВ доноров основной группы, в т. ч. b- и a-субъединицы гемоглобина, ядерный убиквитиновый казеин (NUCKS), белки группы высокой мобильности (HMG-I/HMG-Y), лактоферрин. Большинство выявленных белков может быть предложено в качестве панели для диагностики РЛ. Однако необходимы дальнейшие исследования для определения диагностической значимости предложенных биомаркеров и их роли в патогенезе РЛ

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning br

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reli-able tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and con-trols and, strikingly, a significant difference between sur-vivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a ma-chine learning multi-omic model that considers the con-centrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospi-talized COVID-19 patients.Proteomic