Comparison of Traditional and Industrial Sausages Baranjski Kulen and Kulenova Seka Using Comprehensive Proteome, Peptidome and Metabolome Techniques.

Research background: Baranjski kulen is one of the most popular fermented meat sausages originating from Croatia. It has protected geographical indication, and is traditionally produced in the Baranja region of Croatia. Kulenova seka is a fermented sausage very similar to baranjski kulen, but it has a different calibre and consequently, a shorter time of production. In recent decades, due to the high demand and popularity of these products, industrially produced baranjski kulen and kulenova seka have become available on the market. This work aims to identify specific characteristics of traditional and industrial sausages baranjski kulen and kulenova seka on proteome, peptidome and metabolome level, which could potentially lead to better optimization of the industrial production process in order to obtain an equivalent to the traditional product. Experimental approach: Protein profiles of baranjski kulen and kulenova seka (traditional and industrial) were analysed using two-dimensional gel electrophoresis followed by differential display analysis and protein identification by mass spectrometry. Peptidomic profile was analysed via liquid chromatography-tandem mass spectrometry. Furthermore, aroma profiles were investigated via headspace solid phase microextraction and gas chromatography-mass spectrometry. Results and conclusions: The major identified characteristics of each product were: industrial baranjski kulen: specific degradation of myosin-1 and titin, overabundance of stress-related proteins and increased phenylalanine degradation; traditional baranjski kulen: decreased concentration of phenylalanine and overabundance of fructose-bisphosphate aldolase A and carbonic anhydrase 3; industrial kulenova seka - specific myosin-4 and haemoglobin subunit alpha degradation process; traditional kulenova seka - overabundance of dihydropyrimidine dehydrogenase [NADP(+)] and myosin light chain 1/3, skeletal muscle isoform, degradation of albumin and myoglobin, decreased concentrations of almost all free amino acids and increased amounts of smoke-derived volatile compounds. Presented results showed that potential product type-specific quality markers for each sausage could be found. Novelty and scientific contribution: In this preliminary communication, the first insights into protein degradation processes and generation of peptides, free amino acids and aroma compounds of industrial and traditional baranjski kulen and kulenova seka are presented. Although further research is needed to draw general conclusions, the specific profile of proteins, peptides, amino acids and volatile compounds represents the first step in the industrial production of sausages that meet the characteristics of traditional flavour.

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

Background and Objectives: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not necessarily have hyperinsulinemia. It is considered a condition of pre-diabetes and represents a condition of increased risk of developing DM (diabetes mellitus); it can exist for many years without people having the appropriate symptoms. This study aims to determine the risk of developing hyperinsulinemia at an early age in adolescents by examining which factors are crucial for its occurrence. Materials and Methods: The cross-sectional study lasting from 2019 to 2021 (2 years) was realized at the school children's department in the Valjevo Health Center, which included a total of 822 respondents (392 male and 430 female) children and adolescents aged 12 to 17. All respondents underwent a regular, systematic examination scheduled for school children. BMI is a criterion according to which respondents are divided into three groups. Results: After summary analyzes of OGTT test respondents and calculated values of HOMA-IR (homeostatic model assessment for insulin resistance), the study showed that a large percentage of respondents, a total of 12.7%, are at risk for hyperinsulinemia. The research described in this paper aimed to use the most popular AI (artificial intelligence) model, ANN (artificial neural network), to show that 13.1% of adolescents are at risk, i.e., the risk is higher by 0.4%, which was shown by statistical tests as a significant difference. Conclusions: It is estimated that a model using three different ANN architectures, based on Taguchi's orthogonal vector plans, gives more precise and accurate results with much less error. In addition to monitoring changes in each individual's risk, the risk assessment of the entire monitored group is updated without having to analyze all data.

Lipid Profiling and Stable Isotopic Data Analysis for Differentiation of Extra Virgin Olive Oils Based on Their Origin.

To differentiate extra virgin olive oils (EVOO) according to the origin of purchase, such as monocultivar Italian EVOO with protected denomination of origin (PDO) and commercially-blended EVOO purchased in supermarkets, a number of samples was subjected to the analysis of various lipid species by liquid chromatography/mass spectrometry (LC-ESI-MS/MS, LC-ESI-IT-MS) and proton nuclear magnetic resonance analysis (1H-NMR). Many putative chemical markers were extracted as differentiators by uni- and multivariate statistical analysis. Commercially-blended EVOO contained higher concentrations of the majority of minor lipids, including free fatty acids, their alkyl (methyl and ethyl) esters, monoglycerides, and diglycerides, which may be indicative of a higher degree of triglyceride lipolysis in these than in monocultivar PDO EVOO. Triterpenoids and particular TAG species were also found in higher proportions in the samples from the commercially-blended EVOO class, suggesting a possible influence of factors such as the cultivar and geographical origin. The largest differences between the classes were determined for the concentrations of uvaol and oleanolic acid. The results of the analysis by isotopic ratio mass spectrometry (IRMS) were reasonably consistent with the information about the geographical origin declared on the labels of the investigated EVOOs, showing considerable variability, which possibly also contributed to the differences in lipid composition observed between the two investigated classes of EVOO.

Complementary Untargeted and Targeted Metabolomics for Differentiation of Extra Virgin Olive Oils of Different Origin of Purchase Based on Volatile and Phenolic Composition and Sensory Quality.

In order to differentiate the extra virgin olive oils (EVOO) of different origin of purchase, such as monovarietal Italian EVOO with protected denomination of origin (PDO) and commercial-blended EVOO purchased in supermarkets, a number of samples was subjected to the analysis of volatile aroma compounds by both targeted gas chromatography/mass spectrometry (GC-MS) and untargeted profiling by comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-TOF-MS), analysis of phenols by targeted high-performance liquid chromatography/mass spectrometry (HPLC-DAD-ESI/MS), and quantitative descriptive sensory analysis. Monovarietal PDO EVOOs were characterized by notably higher amounts of positive LOX-derived C6 and C5 volatile compounds, which corresponded to the higher intensities of all the assessed positive fruity and green odor sensory attributes. Commercial-blended EVOOs had larger quantities of generally undesirable esters, alcohols, acids, and aldehydes, which coincided with the occurrence of sensory defects in many samples. Many minor volatile compounds that were identified by GC×GC-TOF-MS were found to differentiate each of the two investigated groups. The differences between the groups with respect to phenols and taste characteristics were evident, but less pronounced. The results that were obtained in this study have undoubtedly confirmed the existence of the large heterogeneity of oils that are sold declared as EVOO. It was shown that GC-MS, GC×GC-TOF-MS, and HPLC-DAD-ESI/MS analyses have complementary outputs, and that their use in combination has advantages in supporting the results of sensory analysis and objectively differentiating these groups of EVOO.

Effect of Different Clarification Methods on Volatile Aroma Compound Composition of Virgin Olive Oil.

This study investigates the effect of industrial scale filtration of fresh monovarietal virgin olive oil from Buza and Istarska bjelica cultivars on their volatiles, total phenols and sensory characteristics, and compares the oil samples clarified by filtration with those clarified by natural sedimentation/decantation after six months of storage. Filtration had a different effect on volatiles from the oil samples obtained from different cultivars. In the oil from Buza cultivar immediately after filtration only the amount of (Z)-2-pentenol slightly increased, but in Istarska bjelica the oil filtration affected eight compounds (the amount of hexanal, (E)-2-pentenal, (Z)-3-hexenal, (Z)-2-pentenol and (Z)-3-hexen-1-ol increased, while of hexyl acetate, (E)-2-penten-1-ol and (E)-2-hexen-1-ol decreased). In fresh filtered oil from Buza cultivar a slight decrease of total phenols was observed, while in those from Istarska bjelica the decrease was sharp, causing a decrease in the pungency and bitterness. Sedimentation/decantation had advantages over oil filtration of both cultivars, due to improved effect on the preservation of the sensory profile and the level of total phenols. Tentative aroma profiles based on odorant series obtained from the odour activity values were compared to the actual olive oil sensory profiles. These results could have a high level of applications in the olive oil industry for the optimization of the technology for obtaining monovarietal virgin olive oil with preserved specific and typical sensory characteristics, but also may serve experts to choose an appropriate virgin olive oil clarification method prior to analysis of volatile compounds.

Enhancement of Istrian Malvasia wine aroma and hydroxycinnamate composition by hand and mechanical leaf removal.

BACKGROUND: Leaf removal is a viticultural practice that promotes the biosynthesis of several important grape constituents by improving fruit zone microclimate. The purpose of this study was to assess the effects of hand and mechanical leaf removal, applied at the pea-size stage of berry development, on fruit zone microclimate, volatile aroma compounds, hydroxycinnamates and sensory characteristics of Istrian Malvasia (Vitis vinifera L.) wines. Three different sunlight exposure conditions were applied: hand leaf removal (HLR), mechanical leaf removal (MLR) and untreated control (UC). RESULTS: Both leaf removal treatments, and especially the more intense HLR, significantly increased the concentration of varietal thiol 3-sulfanylhexan-1-ol, monoterpenes, ß-damascenone and esters. The higher concentration of these aromas contributed to the improvement of wine sensory quality, as expressed by more enhanced floral, fruity and tropical sensory attributes in leaf removal treatments. Hydroxycinnamates were increased only by HLR, a treatment with a greater degree of fruit exposure to sunlight than MLR. CONCLUSION: Leaf removal applied at the pea-size stage of berry development in a season characterized by abundant rainfall improves both the chemical composition and sensory quality of Istrian Malvasia wine, even when performed by machine, implying that this technique might be successfully applied in large-scale viticultural production. © 2018 Society of Chemical Industry.

Differentiation of Commercial PDO Wines Produced in Istria (Croatia) According to Variety and Harvest Year Based on HS-SPME-GC/MS Volatile Aroma Compound Profiling.

To differentiate monovarietal wines made from native and introduced varieties in Istria (Croatia), samples of Malvazija istarska, Chardonnay and Muscat yellow from two harvest years (2013 and 2014) were subjected to headspace solid-phase microextraction and gas chromatographic/mass spectrometric analysis (HS-SPME-GC/MS) of volatile aroma compounds. Significant effects of variety and harvest year were determined, but their interaction complicated the differentiation. Particular compounds were consistent as markers of variety in both years: nerol for Malvazija, ethyl cinnamate and a tentatively identified isomer of dimethylbenzaldehyde for Chardonnay, and terpenes for Muscat yellow. Wines from 2013 contained higher concentrations of the majority of important volatiles. A 100% correct differentiation of Malvazija istarska and Chardonnay wines according to both variety and harvest year was achieved by stepwise linear discriminant analysis.

Phenolic and Aroma Composition of White Wines Produced by Prolonged Maceration and Maturation in Wooden Barrels.

To investigate the phenolic and aroma composition of Malvazija istarska (Vitis vinifera L.) white wines produced by an unconventional technology comprising prolonged maceration followed by maturation in wooden barrels, representative samples were subjected to analysis by UV/Vis spectrometry, high-performance liquid chromatography, and gas chromatography-mass spectrometry. When compared to standard wines, the investigated samples contained higher levels of dry extract, volatile acidity, lactic acid, phenols, colour intensity, antioxidant activity, majority of monoterpenes, C13-norisoprenoids, methanol, higher alcohols, ethyl acetate, branched-chain esters and esters of hydroxy and dicarboxylic acids, ethylphenols, furans, and acetals, as well as lower levels of malic acid, ß-damascenone, straight-chain fatty acids, ethyl and acetate esters. It was estimated that maceration had a stronger influence on phenols, and maturation on volatile aromas. Despite different vintages and technological details, the investigated wines showed a relative homogeneity in the composition, representing a clear and distinctive type.

Complexity of the effects of pre-fermentation oxygenation, skin contact and use of pectolytic enzymes in white winemaking as revealed by comprehensive proteomics and volatilomics analysis.

Ion exchange chromatography and SDS-PAGE followed by identification by MALDI-TOF/TOF, and two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOF-MS) were used for comprehensive proteomics and volatilomics evaluation of the effects of pre-fermentative oxygenation, skin contact and use of pectolytic enzymes in production of Malvazija istarska white wine, respectively. Many protein species and an unprecedented number of volatiles have been identified and (semi)quantified, revealing high complexity of the observed effects. Compared to a standard control wine, oxygenation treatment modulated the protein composition and resulted with a volatilome characterized by decreased levels of several important volatiles. Skin contact treatments, especially in combination with pectolytic enzymes, significantly increased the levels of a large number of proteins, but were also deprived of particular protein species found in other wines. Wines obtained by skin contact with exogenous enzymes exhibited the most complex volatile composition with increased levels of many key monoterpenoids, alcohols and esters.

Innovation in Hyperinsulinemia Diagnostics with ANN-L(atin square) Models.

Hyperinsulinemia is a condition characterized by excessively high levels of insulin in the bloodstream. It can exist for many years without any symptomatology. The research presented in this paper was conducted from 2019 to 2022 in cooperation with a health center in Serbia as a large cross-sectional observational study of adolescents of both genders using datasets collected from the field. Previously used analytical approaches of integrated and relevant clinical, hematological, biochemical, and other variables could not identify potential risk factors for developing hyperinsulinemia. This paper aims to present several different models using machine learning (ML) algorithms such as naive Bayes, decision tree, and random forest and compare them with a new methodology constructed based on artificial neural networks using Taguchi's orthogonal vector plans (ANN-L), a special extraction of Latin squares. Furthermore, the experimental part of this study showed that ANN-L models achieved an accuracy of 99.5% with less than seven iterations performed. Furthermore, the study provides valuable insights into the share of each risk factor contributing to the occurrence of hyperinsulinemia in adolescents, which is crucial for more precise and straightforward medical diagnoses. Preventing the risk of hyperinsulinemia in this age group is crucial for the well-being of the adolescents and society as a whole.

Exploring the Connection between the Occurrence and Intensity of "Grubby" Defect and Volatile Composition of Olive Oil.

In order to investigate the relationship between the occurrence of the "grubby" sensory defect caused by olive fruit fly (Bactrocera oleae (Rossi)) infestation and the resulting volatile composition, virgin olive oils were extracted from olives of the Leccino cultivar with 0%, 50%, and 100% olive fly infestations and subjected to analysis of the basic chemical quality parameters, fatty acids and volatiles, and sensory analysis by the Panel test. A 100% olive fly infestation reduced the basic chemical quality of the oil, while the fatty acid composition was not affected in any case. The overall sensory quality score and intensity of the positive sensory attributes decreased, while the intensity of the "grubby" defect increased proportionally to the degree of infestation. The occurrence and intensity of this defect were clearly causally related to the concentrations of 3-methylbutanal, 2-methylbutanal, ß-ocimene, ethyl 2-methylbutyrate, dimethyl sulfoxide, 4-methyl-5H-furan-2-one, α-farnesene, 6-methyl-5-hepten-2-one, 1-octanol, E-2-nonen-1-ol, benzeneacetaldehyde, heptanal, and octanal, implying that the perception of "grubby" comes from their joint contribution to the overall olive oil flavour. In addition to contributing to the understanding of the chemical origin of "grubby", the results obtained could potentially be used to develop strategies to support sensory analysis in the classification of olive oil quality and the confirmation of the presence of this sensory defect in oil samples.

Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks.

In previous years, significant attempts have been made to enhance computer-aided diagnosis and prediction applications. This paper presents the results obtained using different machine learning (ML) algorithms and a special type of a neural network map to uncover previously unknown comorbidities associated with chronic diseases, allowing for fast, accurate, and precise predictions. Furthermore, we are presenting a comparative study on different artificial intelligence (AI) tools like the Kohonen self-organizing map (SOM) neural network, random forest, and decision tree for predicting 17 different chronic non-communicable diseases such as asthma, chronic lung diseases, myocardial infarction, coronary heart disease, hypertension, stroke, arthrosis, lower back diseases, cervical spine diseases, diabetes mellitus, allergies, liver cirrhosis, urinary tract diseases, kidney diseases, depression, high cholesterol, and cancer. The research was developed as an observational cross-sectional study through the support of the European Union project, with the data collected from the largest Institute of Public Health "Dr. Milan Jovanovic Batut" in Serbia. The study found that hypertension is the most prevalent disease in Sumadija and western Serbia region, affecting 9.8% of the population, and it is particularly prominent in the age group of 65 to 74 years, with a prevalence rate of 33.2%. The use of Random Forest algorithms can also aid in identifying comorbidities associated with hypertension, with the highest number of comorbidities established as 11. These findings highlight the potential for ML algorithms to provide accurate and personalized diagnoses, identify risk factors and interventions, and ultimately improve patient outcomes while reducing healthcare costs. Moreover, they will be utilized to develop targeted public health interventions and policies for future healthcare frameworks to reduce the burden of chronic diseases in Serbia.

Comprehensive Volatilome Signature of Various Brassicaceae Species.

To investigate in detail the volatilomes of various Brassicaceae species, landraces, and accessions, and to extract specific volatile markers, volatile aroma compounds were isolated from plant samples by headspace solid-phase microextraction and analyzed by gas chromatography/mass spectrometry (HS-SPME-GC/MS). The data obtained were subjected to uni- and multivariate statistical analysis. In general, two cabbage (Brassica oleracea L. var. capitata) landraces emitted the lowest amounts of volatiles generated in the lipoxygenase (LOX) pathway. Wild species Brassica incana Ten. and Brassica mollis Vis. were characterized by relatively high trans-2-hexenal/cis-3-hexen-1-ol ratio in relation to other investigated samples. A Savoy cabbage (Brassica oleracea L. var. sabauda) cultivar and three kale (Brassica oleracea L. var. acephala) accessions exhibited particular similarities in the composition of LOX volatiles, while the LOX volatilome fraction of B. incana and B. mollis partially coincided with that of another wild species, Diplotaxis tenuifolia L. Regarding volatiles formed in the glucosinolate (GSL) pathway, Savoy cabbage and wild species B. incana, B. mollis, and D. tenuifolia showed more intense emission of isothiocyanates than cabbage and kale. Diplotaxis tenuifolia showed a rather limited production of nitriles. The results of this study contribute to the general knowledge about volatile composition from various Brassicaceae species, which could be exploited for their better valorization. Future studies should focus on the influence of various environmental, cultivation, and post-harvest factors to obtain data with a higher level of applicability in practice.

Ensemble model for predicting chronic non-communicable diseases using Latin square extraction and fuzzy-artificial neural networks from 2013 to 2019.

Background: The presented study tracks the increase or decrease in the prevalence of seventeen different chronic non-communicable diseases in Serbia. This analysis considers factors such as region, age, and gender and is based on data from two national cross-sectional studies conducted in 2013 and 2019. The research aims to accurately identify the regions with the highest percentage of affected individuals, as well as their respective age and gender groups. The ultimate goal is to facilitate organized, free preventive screenings for these population categories within a very short time-frame in the future. Materials and methods: The study analyzed two cross-sectional studies conducted between 2013 and 2019, using data obtained from the Institute of Public Health of Serbia. Both studies involved a total of 27801 participants. The study compared the performance of Decision Tree and Support Vector Regressor models with artificial neural network (ANN) models that employed two encoding functions. The new methodology for the ANN-L36 model was based on artificial neural networks constructed using a Latin square (L36) design, incorporating Taguchi's robust design optimization. Results: The results of the analysis from three different models have shown that cardiovascular diseases are the most prevalent illnesses among the population in Serbia, with hypertension as the leading condition in all regions, particularly among individuals aged 64 to 75 years, and more prevalent among females. In 2019, there was a decrease in the percentage of the leading disease, hypertension, compared to 2013, with a decrease from 34.0% to 32.2%. The ANN-L36 model with Fuzzy encoding function demonstrated the highest precision, achieving the smallest relative error of 0.1%. Conclusion: To date, no studies have been conducted at the national level in Serbia to comprehensively track and identify chronic diseases in the manner proposed by this study. The model presented in this research will be implemented in practice and is set to significantly contribute to the future healthcare framework in Serbia, shaping and advancing the approach towards addressing these conditions. Furthermore, experimental evidence has shown that Taguchi's optimization approach yields the best results for identifying various chronic non-communicable diseases.

Applying Different Vinification Techniques in Teran Red Wine Production: Impact on Bioactive Compounds and Sensory Attributes.

Six different vinification treatments, including a control treatment (7-day standard maceration) (K7), were performed to study the effects of non-standard techniques on bioactive compounds and sensory attributes of Teran red wine. Pre-fermentative mash cooling (8 °C; 48 h) and heating (50 °C; 48 h) followed by prolonged post-fermentative maceration of 13 days (C15;H15) or 28 days (C30;H30) were applied. In another treatment, after cooling, saignée was performed followed by 13-day prolonged maceration (CS15). Wine phenols and vitamins were analyzed by HPLC-DAD-FLD, minerals by ICP-OES, and sensory analysis was performed using the QDA and 100-point O.I.V./U.I.O.E. methods. Obtained results showed total phenolic concentration was the highest in the H30 treatment. The concentration of anthocyanins, flavan-3-ols and phenolic acids was significantly higher in wines of all vinification techniques compared to the control. Stilbene content was highly affected by pre-fermentative heating. Treatments CS15, H15, C30 and H30 resulted in the highest scores by both the QDA and 100-point sensory methods. The obtained results suggest that advanced non-standard vinification techniques have a significant impact on Teran wine by enhancing its composition of bioactive compounds and improving its sensory profile, which gives it an additional market value. Furthermore, a comprehensive comparison of such techniques applied simultaneously in one study is of substantial importance for additional research in wine production.

Tissue-specific calcium and magnesium allocation to explain differences in bulk concentration in leaves of one-year-old seedlings of two olive (Olea europaea L.) cultivars.

Olive tree (Olea europaea L.) leaves have recently been recognised as a valuable source in cosmetic and pharmaceutical industry as well as in preparation of health-supporting beverages. Little is known about the element composition of olive leaves and almost nothing about tissue-specific allocation of elements. Element composition and tissue-specific distribution were determined in leaves of two olive cultivars, Leccino and Istarska bjelica using micro-particle induced X-ray emission (micro-PIXE). In leaves of the Istarska bjelica cultivar larger bulk concentrations of potassium, sodium, molybdenum and boron, but smaller concentrations of calcium and magnesium were found than in leaves of the Leccino cultivar. Tissue-specific investigation revealed that larger concentration of calcium in epidermis and in leaf blade tissues (secondary veins, palisade and spongy mesophyll) contributed to the larger leaf bulk calcium concentration in the Leccino cultivar. For magnesium, all leaf tissues, except the bundle sheath cells and consequently the main vascular bundle, contributed to the larger bulk concentration in the Leccino cultivar. Potassium was not predominant in any of the leaf tissues examined, while sodium and molybdenum were below the limit of detection, and boron not detectable by micro-PIXE. The results indicate that sinks for calcium and magnesium are stronger in specific leaf tissues of the Leccino than of the Istarska bjelica cultivar. The new understanding of tissue-specific allocation of elements in leaves of olive will serve as a basis for detailed studies into the effects of foliar and/or soil fertilisers in olive.

A Novel Approach of Determining the Risks for the Development of Hyperinsulinemia in the Children and Adolescent Population Using Radial Basis Function and Support Vector Machine Learning Algorithm.

Hyperinsulinemia is a condition with extremely high levels of insulin in the blood. Various factors can lead to hyperinsulinemia in children and adolescents. Puberty is a period of significant change in children and adolescents. They do not have to have explicit symptoms for prediabetes, and certain health indicators may indicate a risk of developing this problem. The scientific study is designed as a cross-sectional study. In total, 674 children and adolescents of school age from 12 to 17 years old participated in the research. They received a recommendation from a pediatrician to do an OGTT (Oral Glucose Tolerance test) with insulinemia at a regular systematic examination. In addition to factor analysis, the study of the influence of individual factors was tested using RBF (Radial Basis Function) and SVM (Support Vector Machine) algorithm. The obtained results indicated statistically significant differences in the values of the monitored variables between the experimental and control groups. The obtained results showed that the number of adolescents at risk is increasing, and, in the presented research, it was 17.4%. Factor analysis and verification of the SVM algorithm changed the percentage of each risk factor. In addition, unlike previous research, three groups of children and adolescents at low, medium, and high risk were identified. The degree of risk can be of great diagnostic value for adopting corrective measures to prevent this problem and developing potential complications, primarily type 2 diabetes mellitus, cardiovascular disease, and other mass non-communicable diseases. The SVM algorithm is expected to determine the most accurate and reliable influence of risk factors. Using factor analysis and verification using the SVM algorithm, they significantly indicate an accurate, precise, and timely identification of children and adolescents at risk of hyperinsulinemia, which is of great importance for improving their health potential, and the health of society as a whole.

Diversity of Volatile Aroma Compound Composition Produced by Non-Saccharomyces Yeasts in the Early Phase of Grape Must Fermentation.

There is a lack of studies evaluating the metabolic contribution of non-Saccharomyces yeasts in early fermentation phases. This study aimed to investigate the volatile aroma profiles produced by various non-Saccharomyces yeasts just before sequential inoculation with Saccharomyces cerevisiae to provide an insight into the particular effects they induce at this stage. The grape must of Malvazija istarska was inoculated with monocultures of Torulaspora delbrueckii, Metschnikowia pulcherrima, Pichia kluyveri, Lachancea thermotolerans, and Schizosaccharomyces pombe, alongside a S. cerevisiae control. Eighty volatile compounds were quantified via headspace solid-phase microextraction and gas chromatography-mass spectrometry, and the data were statistically elaborated. Volatile profiles of non-Saccharomyces yeasts differed significantly from the S. cerevisiae control. Most treatments caused increases in linalool and ß-damascenone, decreases in higher alcohols and fatty acids, and improved synthesis of odoriferous esters. Torulaspora delbrueckii and M. pulcherrima produced compounds not commonly found in S. cerevisiae fermented wines. Multivariate statistical analysis linked the investigated yeasts to specific, particularly abundant compounds. Future studies should explore to what degree these contributions persist after sequential inoculation with S. cerevisiae in diverse grape must matrices.

Bioactive Compounds and Antioxidant Activity of Red and White Wines Produced from Autochthonous Croatian Varieties: Effect of Moderate Consumption on Human Health.

Moderate wine consumption is often associated with healthy lifestyle habits. The role of wine as a healthy drink is mainly due to its bioactive compounds, which differ according to various viticultural and enological factors. The aim of the present study was to observe the differences in bioactive compounds of white and red autochthonous Croatian wines, differing in terms of the grape variety and production technology. Our further aim was to explore the effect of their moderate consumption (200 mL per day) over the course of six weeks on some aspects of health in sixty-six healthy individuals. Participants were divided into eight groups depending on the wines consumed, while one group formed a non-consuming control group. Medical examination and laboratory tests were performed before the start and at the end of the consumption period. Systolic and diastolic blood pressure, total cholesterol, and LDL concentrations decreased. Additionally, an increase in HDL concentrations, and serotonin and dopamine levels, was observed. ALT, ALP, and GGT levels did not significantly increase in consumer groups, although alcohol concentration was relatively high in all the wines. Such results support the beneficial effects of wine-derived bioactive compounds on some health aspects resulting from moderate white and red wine consumption.

Biophenolic Profile Modulations in Olive Tissues as Affected by Manganese Nutrition.

Manganese (Mn) is an essential element that intervenes in several plant metabolic processes. The olive tree, and its fruits and leaves, are known as a source of nutraceuticals since they are rich in biophenols. However, there is still a serious lack of data about biophenolic distribution in olive stems and roots under Mn fertilisation. In this context, our study aimed to examine the effects of Mn fertilisation on the biophenolic profile in the leaves, stems, and roots of the 'Istarska bjelica' olive cultivar. The experiment was set up in a greenhouse, during a period of five months, as a random block design consisting of three treatments with varying Mn concentrations in full-strength Hoagland's nutrient solution (0.2 µM Mn, 12 µM Mn, and 24 µM Mn). The obtained results indicate that the amount of Mn in the examined olive plant tissues was significantly higher under 12 µM Mn and 24 µM Mn treatments compared to that of the 0.2 µM Mn treatment. While the concentration of biophenols varied in roots depending on the compound in question, a strong positive impact of the increased Mn concentration in nutrient solution (12 µM Mn and 24 µM Mn) on the concentrations of the main biophenolic compounds was observed in stems. The concentration of oleuropein in leaves almost doubled at 24 µM Mn, with the highest Mn concentration, as compared to the 0.2 µM Mn treatment. The obtained results led to the conclusion that the supply of Mn could enhance the concentration of some biologically active compounds in olives grown hydroponically, implying a critical need for further investigation of Mn fertilisation practices in the conventional olive farming system.