Main biologically active substances of amaranth grain

The purpose of the study was to determine the nutritional value and main biologically active substances in amaranth grain from different geographical regions of growth and its processed products. Nine commercially available amaranth samples were selected for the study: 1-3. amaranth grain originated from Russia, Peru and India, respectively, 4. extruded flour, 5. high-protein flour, 30% protein 6. flour with a protein content of 20%, 7. flour, enriched with fiber, 8. cake flour, 9. amaranth grain that has not undergone technological purification (samples 4-9 - country of origin - Russia). The protein content in amaranth samples varied from 12.6 to 33.8%, the fat content was in the range of 5.6-8.1%, and the carbohydrate content was 50.4-72.2% , the ash content was 2.06-6.12% and moisture 2.1-7.1%. The main hydrocinnamic acids in amaranth samples were identified: caffeic, ferulic and p-coumaric. The main flavonoids in the studied samples were rutin pentoside, rutin and nicotiflorin (kaempferol-3-rutinoside). The main fatty acids identified: linoleic, oleic, palmitic, stearic, vaccenic, alpha-linolenic (ω-3)

Integrin Alpha 8 Recessive Mutations Are Responsible for Bilateral Renal Agenesis in Humans

Renal hypodysplasia (RHD) is a heterogeneous condition encompassing a spectrum of kidney development defects including renal agenesis, hypoplasia, and (cystic) dysplasia. Heterozygous mutations of several genes have been identified as genetic causes of RHD with various severity. However, these genes and mutations are not associated with bilateral renal agenesis, except for RET mutations, which could be involved in a few cases. The pathophysiological mechanisms leading to total absence of kidney development thus remain largely elusive. By using a whole-exome sequencing approach in families with several fetuses with bilateral renal agenesis, we identified recessive mutations in the integrin α8-encoding gene ITGA8 in two families. Itga8 homozygous knockout in mice is known to result in absence of kidney development. We provide evidence of a damaging effect of the human ITGA8 mutations. These results demonstrate that mutations of ITGA8 are a genetic cause of bilateral renal agenesis and that, at least in some cases, bilateral renal agenesis is an autosomal-recessive disease

Determination and Comparison of Soybean Lecithin and Bovine Brain Plasmalogens Effects in Healthy Male Wistar Rats

The aim of this study was to investigate the effects of soybean lecithin and plasmalogens concentrating on a variety of physiological tests and biochemical analyses in healthy Wistar rats. For six weeks, male Wistar rats were given a standard diet that included plasmalogens or soybean lecithin. We measured anxiety levels, overall exploratory activity, short- and long-term memory, cognitive abilities, and grip strength. Lecithin increased significantly anxiety and enhanced memory and cognitive functions. Plasmalogens significantly improved appetite and increased grip strength. When compared to plasmalogens, lecithin significantly raised HDL levels while lowering LDL levels. The plasmalogens group showed a significant increase in the C16:0DMA/C16:0 ratio, which led us to assume that plasmalogen consumption could increase their synthesis in neural tissue. The study’s findings imply that, despite their various modes of action, soy lecithin and plasmalogens may both be significant nutritional components for enhancing cognitive functions

Застосування штучної нейронної мережі для прогнозування врожайності пшениці

A given model of yield forecasting using an artificial neural network connects the wheat crop with the amount of productive moisture in the soil, soil fertility, weather, and factors in the presence of pests, diseases, and weeds. The difficulty of creating a yield forecast system is in the correct choice of predictors that have the greatest impact on yield. To build the model, moisture in the 100 cm layer of the soil, the content of nitrogen, phosphorus, humus, and soil acidity in the soil were used as input parameters. The amount of precipitation over 4 months, the average air temperature for the same period, as well as the presence of diseases, pests, and weeds were also taken into consideration. Data on 13 districts of the North Kazakhstan region in the period from 2008 to 2017 were used. The output parameter was the yield of spring wheat over the same time period. The relative importance of input variables in relation to the output variable was used to determine the weight values of input variables. An artificial neural network of error backpropagation was used as a method. The advantage of this method is that the quality of the forecast increases with a large amount of training data, as well as the ability to model nonlinear relationships between different data sources. After training the artificial neural network and obtaining predictive data, good results were achieved for predicting wheat yields (p=0.52, mean absolute error in percentage (MAPE)=12.02 %, root mean square error (RMSE)=3.368). Thus, it is assumed that the developed model for forecasting wheat yields based on data can be easily adapted for other crops and places and will allow the adoption of the right strategies to ensure food securityДана модель прогнозування врожайності з використанням штучної нейронної мережі пов’язує врожай пшениці з кількістю продуктивної вологи в ґрунті, родючістю ґрунту, погодою та факторами наявності шкідників, хвороб та бур’янів. Складність створення системи прогнозу врожайності полягає у правильному виборі предикторів, які найбільше впливають на врожайність. Для побудови моделі в якості вхідних параметрів використовувалися вологість в 100 см шарі ґрунту, вміст азоту, фосфору, гумусу та кислотність ґрунту. Також враховувалася кількість опадів за 4 місяці, середня температура повітря за аналогічний період, а також наявність хвороб, шкідників та бур’янів. Використовувалися дані 13 районів Північно-Казахстанської області у період з 2008 року до 2017 року. Вихідним параметром стала врожайність ярої пшениці за цей же часовий проміжок. Відносну важливість вхідних змінних по відношенню до вихідної змінної використовували для визначення вагових значень вхідних змінних. В якості методу була використана штучна нейронна мережа зворотного поширення помилки. Перевагою даного методу є те, що якість прогнозу збільшується за великої кількості навчальних даних, а також можливість моделювати нелінійні відносини між джерелами даних. Після навчання штучної нейронної мережі та отримання прогнозних даних було досягнуто хороших результатів для прогнозування врожайності пшениці (р=0,52, середня абсолютна помилка у відсотках (MAPE)=12,02 %, середньоквадратична помилка (RMSE)=3,368). Таким чином, передбачається, що розроблена модель прогнозування врожайності пшениці на основі даних може бути легко адаптована для інших культур і місць та дозволить приймати правильні стратегії щодо забезпечення продовольчої безпек

Complex of polyphenols sorbed on buckwheat flour as a functional food ingredient

An innovative approach to creating a new generation of specialised foods for dietary therapy of type 2 diabetes can involve planned adding of plant polyphenols to their formulafions. The marked antioxidant properties of polyphenols largely determine their potential antidiabetic effects. However, the use of food polyphenols for prophylactic purposes is limited by their low bioavailability, which makes it expedient to search for technological approaches aimed at obtaining polyphenolic matrices with high biological activity, increased digestibility, and stability. This study objective was to purposely extract and concentrate the polyphenols by sorbing them from an aqueous solution of the bilberry leaf extract (BLE) on buckwheat flour and to assess their storage stability. A number of experiments on optimal parameters selection for sorbing polyphenols from the BLE on buckwheat flour were performed. The parameters included the concentration of the extract solution, the solution/sorbent ratio, the pH of the solution, the temperature and the time of sorption. The sorption on the polyphenol matrix was determined from the difference in their contents in the initial solution of the extract and in the supernatant after centrifugation by the FolinCiocalteu method. The effects of exposure to light, temperatures, and humidity on the polyphenol compounds in the dry BLE and in the food matrix contents during storage was analysed by the FTIR spectroscopy. The experiments determined the optimal conditions for the BLE polyphenol sorption on buckwheat flour by incubation of a 2% BLE solution pH = 3.6 with the portion of buckwheat flour at the ratio of 1g/50 cm3 solution for 45 minutes at 25°C. When storing the food matrix, there was no significant degradation of the polyphenolic compounds in the food matrix, which indicates an increase in the stability of the polyphenols sorbed on buckwheat flour. This paper presents the results that are scientifically and practically relevant for the nutritiology experts who devise promising technological approaches to expanding the range of functional food ingredients of the antidiabetic character

Adaptogenic Properties of a Phytoecdysteroid-Rich Extract from the Leaves of Spinacia oleracea L.

Increasing the ability of the human body to adapt in conditions of physical or emotional stress is promising from the standpoint of the use of preventive nutrition containing functional food ingredients (FFI) with proven effectiveness in complex physiological in vivo studies. In this work, we developed FFI from spinach leaves (Spinacia oleracea L.) with a high content of polyphenols and adaptogens—phytoecdysteroids. Using in vivo models of increased physical activity and immobilization-induced emotional stress, we evaluated the nonspecific resistance of rats in response to the addition of the developed FFI to the diet. In the acute toxicity experiment, we found no signs of FFI toxicity up to 5000 mg/kg body weight. As a result of the daily 26-day consumption of FFI, we observed an anxiolytic effect in physiological studies. FFI prevented an increase in the content of biogenic amines in the blood, the main markers of the stress system, and had a positive effect on the lipid metabolism of the rats. The obtained results demonstrate a “smoothing” effect on the body’s reaction in response to induced stress conditions

The Characteristics of Ubiquitous and Unique Leptospira Strains from the Collection of Russian Centre for Leptospirosis

Background and Aim. Leptospira, the causal agent of leptospirosis, has been isolated from the environment, patients, and wide spectrum of animals in Russia. However, the genetic diversity of Leptospira in natural and anthropurgic foci was not clearly defined. Methods. The recent MLST scheme was used for the analysis of seven pathogenic species. 454 pyrosequencing technology was the base of the whole genome sequencing (WGS). Results. The most wide spread and prevalent Leptospira species in Russia were L. interrogans, L. kirschneri, and L. borgpetersenii. Five STs, common for Russian strains: 37, 17, 199, 110, and 146, were identified as having a longtime and ubiquitous distribution in various geographic areas. Unexpected properties were revealed for the environmental Leptospira strain Bairam-Ali. WGS of this strain genome suggested that it combined the features of the pathogenic and nonpathogenic strains and may be a reservoir of the natural resistance genes. Results of the comparative analysis of rrs and rpoB genes and MLST loci for different Leptospira species strains and phenotypic and serological properties of the strain Bairam-Ali suggested that it represented separate Leptospira species. Conclusions. Thus, the natural and anthropurgic foci supported ubiquitous Leptospira species and the pool of genes important for bacterial adaptivity to various conditions