Possibilities of Correction of Alimentary Status in the Era of Digitalisation

A balanced diet contributes to the prevention of nutritionallyrelated diseases. The purpose of this paperwas to demonstrate how tools of the digital economy could be used to help improve nutritional status, using the example of Microsoft Excel. To improve nutritional status, reliable digital information is needed on the content of macronutrients and micronutrients in raw materials and foodproducts. Then the correction of the diet or formulation of an individual product can be carried out. The database “Chemical composition of food raw materials and food products” was developed using Microsoft Excel; this database is a digital tool for quick and reliable information about the nutrient profile of Russian raw materials and food products. Itobtained official state registration under the number 2012620334. The database is a series of spreadsheets that are interconnected by common key fields. For each type of food raw material or food product, the database contains descriptors: the main chemical composition (mass fraction of water, protein, fat, saturated fatty acids, polyunsaturated fatty acids, cholesterol, mono- and disaccharides, starch, digestible carbohydrates, dietary fibre, ash, organic acids); minerals (sodium, potassium, calcium, magnesium, phosphorus, iron); vitamins (A, B1 , B2 , PP, C, beta-carotene, retinol equivalent, tocopherol equivalent, niacin equivalent); and energy value. Using the database can help to speed up and facilitate calculating individual and group diets and can assist in adjusting the nutritional status for healthier outcomes. Keywords: healthy nutrition, nutritional status, chemical composition, database, digitalisation, Microsoft Exce

Studying the features of the use of neural networks and machine learning in the design of food systems

The features of the use of neural networks and machine learning methods for the design of food systems are studied using the example of processed cheese. A database has been developed that includes 869 cheese recipes, and a program for managing an electronic recipe directory. A neural network has been developed, for the training of which the method “Training with a teacher”, the activation function “ReLu” and the author’s program written in the Python programming language were used. The neural network consisted of 9 neurons in the input layer, two hidden layers of 65 neurons each, and an output layer consisting of 1 neuron. To determine the linear correlation between columns, a matrix was used showing the relationship between values using the Pearson coefficient. A training sample containing 80% of the total number of recipes, a test sample of 10% of the total number of recipes, and a test sample of 10% of the total number of recipes were selected from the primary data set. As a result of training the neural network, an information-advising system for a food technologist has been developed. The system is designed to predict the quality of food recipes. The information-advising system will speed up the correction of existing recipes and the development of recipes for new products, theoretically predict their quality before launching into production. The information-advising system was tested on a test recipe of a new processed cheese. It has been established that with a certainty of 63.6%, the integral indicator of the quality of the new cheese will be 7.7 conventional units. This predicted value was confirmed during the practical production of cheese according to the designed recipe in laboratory conditions and during approbation in production conditions. The new cheese is really distinguished by high quality, good organoleptic and physico-chemical parameters

Study of Survival During Drying of Bacterial Cells of Starter Culture for Probiotic Fermented Milk Drinks

Five proprietary variants of bacterial starter culture with the following species composition were studied: No. 1 – Lac. diacetilactis, Lac. cremoris, Lac. acidophilus, No. 2 – Lb. plantarum, B. adolescentis, No. 3 – Lac. cremoris, No. 4 – Lac. lactis, Lac. diacetilactis, Lb. plantarum, No. 5 – Lac. lactis, Lac. diacetilactis, Lb. cremoris. Survival was assessed immediately after freeze-drying and during storage after 30, 90 and 180 days. It was found that the lactococci included in the bacterial starter culture of variants No. 1, 3-5 after drying and during storage showed the maximum survival of bacterial cells. Their number varied within the limits: after drying – 3.3-6.5 × 109 CFU/g, after 180 days – 1.0-2.0 × 109 CFU/g. A high degree of survival was noted in L. acidophilus (variant No. 1) – the number of viable cells after drying, as well as after 180 days of storage at the level of 1.0×108 CFU/g. The total amount of probiotic microflora of Lb. plantarum and B. adolescentis bacterial starter culture (variant No. 2) after drying was 3.2×109 CFU/g, and after 180 days of storage 1.0×109 CFU/g. Both cultures showed high survival of bacterial cells. The number of Lb. plantarum (variant No. 4) after drying and during storage was only 1.0×106 CFU / g, but it should be taken into account that this culture in the starter composition is additional, while the dominant microflora is represented by lactococci

Primjena ekstrakta proteina sirutke u proizvodnji smrznutog mliječnog deserta

The aim of this work was to substantiate the use of whey protein extract (WPE), a by-product of dairy industry, combined with different berry purees in the formulation of a whipped frozen dairy dessert (WFDD). After freezing, the swelling ability of WPE decreased significantly while at higher temperatures of the dispersion medium, the degree of swelling increased. A mixture containing 55±2 % WPE and 45±2 % milk presented a homogeneous consistency while the further processing did not improve the structure of the mixture. Final formulations of WFDD containing different berry purees (i.e. 10 % black¬currant puree, 25 % cherry puree, or 30 % strawberry puree) were proposed for which the nutritional facts were calculated. Recommended shelf life of the developed desserts at -18 °C is suggested to be 20 days. Regulatory requirements and recommendations for the production of WFDD in an industrial scale were also developed. Recommended shelf life of the developed desserts at -18 °C is suggested to be 20 days. In conclusion, a WFDD was developed using WPE as a by-product of dairy industry.Svrha ovog rada bila je ispitati mogućnost primjene kombinacije pirea bobičastog voća i ekstrakta proteina sirutke (WPE), inače nusproizvoda mljekarske industrije, u proizvodnji smrznutog mliječnog deserta (WFDD). Nakon smrzavanja, sposobnost bubrenja WPE značajno je pala, međutim pri višim temperaturama medija za raspršivanje sposobnost bubrenja ponovno je rasla. U pogledu konzistencije najboljom se pokazala mješavina koja se sastojala od 55±2 % WPE i 45±2 % mlijeka te daljnja prera¬da nije rezultirala poboljšanjem teksture mješavine. Za konačne recepture WFDD s različitim udjelima pirea bobičastog voća (10 % pirea crnog ribizla, 25 % pirea višnje ili 30 % pirea jagode) napravljeni su izračuni prehrambene vrijednosti. Preporučeni rok trajanja za proizvedene deserte iznosio je 20 dana na temperaturi čuvanja -18 °C. Osim toga, uspostavljeni su zahtjevi sukladno zakonskim propisima kao i odgovarajuće preporuke za proizvodnju WFDD u industrijskom mjerilu. Zaključno, razvoj proizvodnje WFDD uključuje primjenu nusprizvoda mljekarske industrije - WPE

Primjena ekstrakta proteina sirutke u proizvodnji smrznutog mliječnog deserta

The aim of this work was to substantiate the use of whey protein extract (WPE), a by-product of dairy industry, combined with different berry purees in the formulation of a whipped frozen dairy dessert (WFDD). After freezing, the swelling ability of WPE decreased significantly while at higher temperatures of the dispersion medium, the degree of swelling increased. A mixture containing 55±2 % WPE and 45±2 % milk presented a homogeneous consistency while the further processing did not improve the structure of the mixture. Final formulations of WFDD containing different berry purees (i.e. 10 % black¬currant puree, 25 % cherry puree, or 30 % strawberry puree) were proposed for which the nutritional facts were calculated. Recommended shelf life of the developed desserts at -18 °C is suggested to be 20 days. Regulatory requirements and recommendations for the production of WFDD in an industrial scale were also developed. Recommended shelf life of the developed desserts at -18 °C is suggested to be 20 days. In conclusion, a WFDD was developed using WPE as a by-product of dairy industry.Svrha ovog rada bila je ispitati mogućnost primjene kombinacije pirea bobičastog voća i ekstrakta proteina sirutke (WPE), inače nusproizvoda mljekarske industrije, u proizvodnji smrznutog mliječnog deserta (WFDD). Nakon smrzavanja, sposobnost bubrenja WPE značajno je pala, međutim pri višim temperaturama medija za raspršivanje sposobnost bubrenja ponovno je rasla. U pogledu konzistencije najboljom se pokazala mješavina koja se sastojala od 55±2 % WPE i 45±2 % mlijeka te daljnja prera¬da nije rezultirala poboljšanjem teksture mješavine. Za konačne recepture WFDD s različitim udjelima pirea bobičastog voća (10 % pirea crnog ribizla, 25 % pirea višnje ili 30 % pirea jagode) napravljeni su izračuni prehrambene vrijednosti. Preporučeni rok trajanja za proizvedene deserte iznosio je 20 dana na temperaturi čuvanja -18 °C. Osim toga, uspostavljeni su zahtjevi sukladno zakonskim propisima kao i odgovarajuće preporuke za proizvodnju WFDD u industrijskom mjerilu. Zaključno, razvoj proizvodnje WFDD uključuje primjenu nusprizvoda mljekarske industrije - WPE

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Studying the features of the use of neural networks and machine learning in the design of food systems

The features of the use of neural networks and machine learning methods for the design of food systems are studied using the example of processed cheese. A database has been developed that includes 869 cheese recipes, and a program for managing an electronic recipe directory. A neural network has been developed, for the training of which the method “Training with a teacher”, the activation function “ReLu” and the author’s program written in the Python programming language were used. The neural network consisted of 9 neurons in the input layer, two hidden layers of 65 neurons each, and an output layer consisting of 1 neuron. To determine the linear correlation between columns, a matrix was used showing the relationship between values using the Pearson coefficient. A training sample containing 80% of the total number of recipes, a test sample of 10% of the total number of recipes, and a test sample of 10% of the total number of recipes were selected from the primary data set. As a result of training the neural network, an information-advising system for a food technologist has been developed. The system is designed to predict the quality of food recipes. The information-advising system will speed up the correction of existing recipes and the development of recipes for new products, theoretically predict their quality before launching into production. The information-advising system was tested on a test recipe of a new processed cheese. It has been established that with a certainty of 63.6%, the integral indicator of the quality of the new cheese will be 7.7 conventional units. This predicted value was confirmed during the practical production of cheese according to the designed recipe in laboratory conditions and during approbation in production conditions. The new cheese is really distinguished by high quality, good organoleptic and physico-chemical parameters

Extracting Hydrophilic Components from Pomegranate Peel and Pulp

Pomegranate (Punica granatum L.) processing focuses on the extraction of polyphenols from peel. However, pomegranate peel is also rich in other biologically active water-soluble components, and their commercial extraction remains understudied. The research objective was to evaluate the degree of extraction of hydrophilic substances, such as simple sugars, organic acids, and polyphenols, from raw pomegranate peel and pulp under different experimental conditions in order to select the optimal extraction parameters. The study featured pomegranates of the Iridanaly variety (Geokchay, Azerbaijan). Raw peel and pulp were crushed to the state of a coarse gruel. Extraction occurred by maceration at a hydromodulus of 1:2 and a temperature of 40 or 60°C with pure water and aqueous ethanol solutions (10–14 % vol.). The process lasted 30, 60, or 90 min in one or two stages with separate extraction at each stage. The research involved standard physicochemical methods. In 31.0 ± 2.0 g/100 g of dry peel, the hydrophilic fraction accounted for 85.32%; in 35.7 ± 2.8 g/100 g of dry pulp, it was 59.36%. Only 54.6% solids were extracted from raw peel after 30 min of extraction with pure water at a hydromodulus of 1:2 and 60°C. Pomegranate peel contained hydrophilic colloids, which caused water absorption and reduced the yield. The optimal extraction included an aqueous solution of ethanol with an ethanol concentration of 10–14 % vol. and two thirty-minute stages. The coagulating effect of ethyl alcohol on water-soluble pectin made it possible to increase the degree of extraction of water-soluble substances to 83.93 and 91.4% of their initial content in raw peel and raw pulp, respectively. Such extraction yielded 4 kg of mixed extract from 1 kg of raw pulp. The extract was boiled under vacuum and yielded 260 g of concentrate with 60 wt.% solids, including 46.70 g/100 g simple sugars, 4.73 g/100 g organic acids, 3.70 g/100 g polyphenols, and 10.10 mg/100 g vitamin C. The extraction of raw pomegranate peel and pulp with aqueous ethanol (10–14 % vol.) provided the maximal degree of extraction of hydrophilic substances and facilitated the separation of the resulting extracts. However, strong alcohol solutions may increase the cost of distillation of alcohol from the extract. To eliminate this shortcoming, the extraction can be carried out with pure water and a pectolytic enzyme