Study of the Microbiome of the Cretan Sour Cream Staka Using Amplicon Sequencing and Shotgun Metagenomics and Isolation of Novel Strains with an Important Antimicrobial Potential.

Staka is a traditional Greek sour cream made mostly from spontaneously fermented sheep milk or a mixture of sheep and goat milk. At the industrial scale, cream separators and starter cultures may also be used. Staka is sometimes cooked with flour to absorb most of the fat. In this study, we employed culture-based techniques, amplicon sequencing, and shotgun metagenomics to analyze the Staka microbiome for the first time. The samples were dominated by Lactococcus or Leuconostoc spp. Most other bacteria were lactic acid bacteria (LAB) from the Streptococcus and Enterococcus genera or Gram-negative bacteria from the Buttiauxella, Pseudomonas, Enterobacter, Escherichia-Shigella, and Hafnia genera. Debaryomyces, Kluyveromyces, or Alternaria were the most prevalent genera in the samples, followed by other yeasts and molds like Saccharomyces, Penicillium, Aspergillus, Stemphylium, Coniospotium, or Cladosporium spp. Shotgun metagenomics allowed the species-level identification of Lactococcus lactis, Lactococcus raffinolactis, Streptococcus thermophilus, Streptococcus gallolyticus, Escherichia coli, Hafnia alvei, Streptococcus parauberis, and Enterococcus durans. Binning of assembled shotgun reads followed by recruitment plot analysis of single reads could determine near-complete metagenome assembled genomes (MAGs). Culture-dependent and culture-independent analyses were in overall agreement with some distinct differences. For example, lactococci could not be isolated, presumably because they had entered a viable but not culturable (VBNC) state or because they were dead. Finally, several LAB, Hafnia paralvei, and Pseudomonas spp. isolates exhibited antimicrobial activities against oral or other pathogenic streptococci, and certain spoilage and pathogenic bacteria establishing their potential role in food bio-protection or new biomedical applications. Our study may pave the way for additional studies concerning artisanal sour creams to better understand the factors affecting their production and the quality.

Investigation of the Microbiome of Industrial PDO Sfela Cheese and Its Artisanal Variants Using 16S rDNA Amplicon Sequencing and Shotgun Metagenomics.

Sfela is a white brined Greek cheese of protected designation of origin (PDO) produced in the Peloponnese region from ovine, caprine milk, or a mixture of the two. Despite the PDO status of Sfela, very few studies have addressed its properties, including its microbiology. For this reason, we decided to investigate the microbiome of two PDO industrial Sfela cheese samples along with two non-PDO variants, namely Sfela touloumotiri and Xerosfeli. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S rDNA amplicon sequencing and shotgun metagenomics analysis were used to identify the microbiome of these traditional cheeses. Cultured-based analysis showed that the most frequent species that could be isolated from Sfela cheese were Enterococcus faecium, Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus pentosaceus and Streptococcus thermophilus. Shotgun analysis suggested that in industrial Sfela 1, Str. thermophilus dominated, while industrial Sfela 2 contained high levels of Lactococcus lactis. The two artisanal samples, Sfela touloumotiri and Xerosfeli, were dominated by Tetragenococcus halophilus and Str. thermophilus, respectively. Debaryomyces hansenii was the only yeast species with abundance > 1% present exclusively in the Sfela touloumotiri sample. Identifying additional yeast species in the shotgun data was challenging, possibly due to their low abundance. Sfela cheese appears to contain a rather complex microbial ecosystem and thus needs to be further studied and understood. This might be crucial for improving and standardizing both its production and safety measures.

Food Safety and Management System Audits in Food Retail Chain Stores in Greece.

The present study aimed to assess the performance of food safety management systems in food retail stores via audits to reveal potential areas of improvement and to find out possible corrective actions to suggest to the top management. Two cycles of on-site audits took place in 106 stores to assess the requirements and hygiene conditions. After the first cycle of audits, improvements were suggested to the top management, and a second cycle of audits took place after a reasonable time. In the checklist, we recorded the temperatures of retail refrigerators and the scores from the inspection of hygiene and HACCP documentation. In the A' audit, the percentage of stores that had higher temperatures than the critical limits was equal to 51%, and those temperatures occurred in the refrigerators for salads, followed by the refrigerators for deli meat, yogurts and desserts. In the B' audit, only the refrigerators for salads exhibited percentages that were statistically significant lower (p-value < 0.05), and the stores were improved after the audit. High percentages of high-scoring stores were observed in the A' and B' audit in the inspection of HACCP documentation, although there was not a statistically significant improvement observed (p-value > 0.05). In the hygiene inspection, statistically significant improvement with 95% confidence appeared for "Refrigerator's products appearance", "Storage cleanliness", and "Grocery shelf cleanliness". The highest number of non-conformities without statistically significant improvement was found for "Checking temperatures of the receiving products" and "Labeling of fruit store products", with the percentages being lower than 15% in both of the audit cycles. Many employees of the stores did not check and record the temperatures of receiving products from suppliers. In addition, the storage of spoiled products beneath fresh products for selling in the same refrigerator is not a good practice. Greater efforts must be made by top management and employees to maintain and distribute food products in the best and safest possible hygiene conditions.

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning.

Background: Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully automated machine learning algorithms can achieve extremely high classification scores and disease-related predictive biosignature identification, in short time frames and scaled down to small datasets. Method: A fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper-parameter values, was applied on a preprocessed transcriptomics dataset, in order to produce a model for biosignature selection and to classify subjects into groups of patients and controls. The parent GEO datasets were originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and healthy controls, using Affymetrix Human Gene 1.0 ST Array. Results: Patients and controls were classified into two separate groups, with no close-to-the-boundary cases, and this classification was based on the cerebellar transcriptomic biosignature of 25 features (genes), with Area Under Curve 0.929 and Average Precision 0.955. The biosignature includes both genes connected before to bipolar disorder, depression, psychosis or epilepsy, as well as genes not linked before with any psychiatric disease. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed participation of 4 identified features in 6 pathways which have also been associated with bipolar disorder. Conclusion: Automated machine learning (AutoML) managed to identify accurately 25 genes that can jointly - in a multivariate-fashion - separate bipolar patients from healthy controls with high predictive power. The discovered features lead to new biological insights. Machine Learning (ML) analysis considers the features in combination (in contrast to standard differential expression analysis), removing both irrelevant as well as redundant markers, and thus, focusing to biological interpretation.

The effects of chemotherapy on resting energy expenditure, body composition, and cancer-related fatigue in women with breast cancer: a prospective cohort study.

BACKGROUND: Breast cancer (BC) is the most prevalent tumor in women. Improvements in treatment led to declined mortality, resulting in more survivors living with cancer- or therapy-induced comorbidities. In this study, we investigated the impact of neoplasia and chemotherapy on resting energy expenditure (REE) and body composition, in relation to cancer-related fatigue. Inflammatory parameters were checked as possible explanation for changes in REE. METHODS: Fifty-six women participated: 20 women with BC and 36 healthy controls. Patients were assessed at baseline (T0) and follow-up (T1) after 12 weeks of chemotherapy. Controls were measured once. REE was assessed with indirect calorimetry: body composition (body weight, fat mass, fat-free mass) by air plethysmography. The multidimensional fatigue index (MFI-20) was used to analyze fatigue. Baseline measurements of patients were compared to results of the healthy controls with the independent-samples T-test. The paired-samples T-test investigated the effects of chemotherapy from T0 to T1. A Pearson correlation analysis was conducted between REE, body composition, and fatigue and between REE, body composition, and inflammatory parameters. A linear regression analysis was fitted to estimate the contribution of the significantly correlated parameters. The measured REE at T0 and T1 was compared to the predicted REE to analyze the clinical use of the latter. RESULTS: At baseline, patients with BC had significantly higher REE in the absence of differences in body composition. From baseline to T1, REE and body weight did not change. In contrast, fat-free mass declined significantly with concordant increase in fat mass. Fatigue deteriorated significantly. C-reactive protein at baseline predicted the change in energy expenditure. Predicted REE significantly underestimated measured REE. CONCLUSIONS: Women with BC have higher REE in the tumor-bearing state compared to healthy controls. Chemotherapy does not affect REE but alters body composition. Predictive equations are invalid in the BC population. Results of our study can be used to implement personalized nutritional interventions to support energy expenditure and body composition and minimize long-term comorbidities.

16S and 18S rDNA Amplicon Sequencing Analysis of Aesthetically Problematic Microbial Mats on the Walls of the Petralona Cave: The Use of Essential Oils as a Cleaning Method.

The presence of microbial communities on cave walls and speleothems is an issue that requires attention. Traditional cleaning methods using water, brushes, and steam can spread the infection and cause damage to the cave structures, while chemical agents can lead to the formation of toxic compounds and damage the cave walls. Essential oils (EOs) have shown promising results in disrupting the cell membrane of bacteria and affecting their membrane permeability. In this study, we identified the microorganisms forming unwanted microbial communities on the walls and speleothems of Petralona Cave using 16S and 18S rDNA amplicon sequencing approaches and evaluated the efficacy of EOs in reducing the ATP levels of these ecosystems. The samples exhibited a variety of both prokaryotic and eukaryotic microorganisms, including Proteobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, the SAR supergroup, Opisthokonta, Excavata, Archaeplastida, and Amoebozoa. These phyla are often found in various habitats, including caves, and contribute to the ecological intricacy of cave ecosystems. In terms of the order and genus taxonomy, the identified biota showed abundances that varied significantly among the samples. Functional predictions were also conducted to estimate the differences in expressed genes among the samples. Oregano EO was found to reduce ATP levels by 87% and 46% for black and green spots, respectively. Consecutive spraying with cinnamon EO further reduced ATP levels, with reductions of 89% for black and 88% for green spots. The application of a mixture solution caused a significant reduction up to 96% in ATP levels of both areas. Our results indicate that EOs could be a promising solution for the treatment of microbial communities on cave walls and speleothems.

The Rising Role of Omics and Meta-Omics in Table Olive Research.

Table olives are often the result of fermentation, a process where microorganisms transform raw materials into the final product. The microbial community can significantly impact the organoleptic characteristics and safety of table olives, and it is influenced by various factors, including the processing methods. Traditional culture-dependent techniques capture only a fraction of table olives' intricate microbiota, prompting a shift toward culture-independent methods to address this knowledge gap. This review explores recent advances in table olive research through omics and meta-omics approaches. Genomic analysis of microorganisms isolated from table olives has revealed multiple genes linked to technological and probiotic attributes. An increasing number of studies concern metagenomics and metabolomics analyses of table olives. The former offers comprehensive insights into microbial diversity and function, while the latter identifies aroma and flavor determinants. Although proteomics and transcriptomics studies remain limited in the field, they have the potential to reveal deeper layers of table olives' microbiome composition and functionality. Despite the challenges associated with implementing multi-omics approaches, such as the reliance on advanced bioinformatics tools and computational resources, they hold the promise of groundbreaking advances in table olive processing technology.

The Low-FODMAP Diet, IBS, and BCFAs: Exploring the Positive, Negative, and Less Desirable Aspects-A Literature Review.

The literature about the association of branched short-chain fatty acids (BCFAs) and irritable bowel syndrome (IBS) is limited. BCFAs, the bacterial products of the catabolism of branched-chain amino acids, are proposed as markers for colonic protein fermentation. IBS is a gastrointestinal disorder characterized by low-grade inflammation and intestinal dysbiosis. The low-FODMAP diet (LFD) has increasingly been applied as first-line therapy for managing IBS symptoms, although it decreases the production of short-chain fatty acids (SCFA), well known for their anti-inflammatory action. In parallel, high protein consumption increases BCFAs. Protein fermentation alters the colonic microbiome through nitrogenous metabolites production, known for their detrimental effects on the intestinal barrier promoting inflammation. Purpose: This review aims to explore the role of BCFAs on gut inflammation in patients with IBS and the impact of LFD in BCFAs production. Methods: A literature search was carried out using a combination of terms in scientific databases. Results: The included studies have contradictory findings about how BCFAs affect the intestinal health of IBS patients. Conclusions: Although evidence suggests that BCFAs may play a protective role in gut inflammation, other metabolites of protein fermentation are associated with gut inflammation. Further research is needed in order to clarify how diet protein composition and, consequently, the BCFAs are implicated in IBS pathogenesis or in symptoms management with LFD+.

The Impact of Change Management in the Greek National Health System: A Quantitative Study.

INTRODUCTION:  Serious changes took place in Greece due to the economic crisis of 2008, which led to significant changes in Greece's health sector. The reforms and changes that were made to the National Health System (NHS) aimed to improve it, provide quality services to its users, and adapt it to Greece's new external environment. The aim of this study was to assess the management of these changes by the leadership of the NHS and to examine their effectiveness. MATERIAL AND METHODS: The survey was based on quantitative research methods, using a questionnaire as a research tool. The sample population comprised employees of a tertiary-care public hospital in northern Greece. RESULTS:  We recruited a sample size of 100 participants for the survey. The questionnaire's Cronbach's alpha was equal to 0.724. The overall change management was moderate, and Greece's NHS did not follow a specific change-management model that provided principles facilitating the success of the effort. The most serious problems identified by using the questionnaire were the following: the changes were not structured and clear, the management set unrealistic goals and objectives, the changes to the NHS were made without the appropriate financial support, and there is uncertainty about the future of health care in Greece. CONCLUSION: The present study showed that changes cannot be made randomly; rather, they require careful planning and organization. Further changes, continuous feedback, and development are required to improve the status of Greece's healthcare system.

A Repeated Cross-Sectional Pilot Study of Physical Activity, Levels of Depression and Anxiety during the COVID-19 Pandemic in Young Greek Adults.

Regular physical activity (PA) and, more specifically, exercise, is associated with lower levels of stress, depression, and anxiety. The aim of this repeated cross-sectional pilot study was to investigate the impact of participating in PA on the mental health of young adults in Greece during the COVID-19 pandemic. The study was carried out during two quarantine periods: Survey I on 5 May 2020, and Survey II on 30 April 2021. The Hamilton Anxiety (HAM-A) and Beck Depression Inventory-II (BDI-II) scales and the level of PA were used to assess a sample of individuals aged between 18 and 26 years old. In 2020 and 2021, a total of 268 (33.9% males) and 380 (37.1% females) subjects participated in the studies, respectively. According to the findings, the vast majority of the participants in both samples reported that they are physically active (p = 0.86), while they consider exercise as a significant health factor (p = 0.10). Moreover, anxiety levels statistically significant increased (p = 0.001), while depression levels remained relatively stable with a slight increase of approximately (p > 0.05). Additionally, in both surveys, individuals who engaged in a PA program exhibited reduced levels of depression and anxiety (p = 0.001). Also, gender appears to influence anxiety and depression levels, while a lack of exercise exacerbates these measures in both genders when compared to physically active individuals. Concludingly, it is crucial for public health strategies to include interventions that promote safe PA in the event of future lockdowns or similar emergencies.

Comparison of Ultra-Short Race Pace and High-Intensity Interval Training in Age Group Competitive Swimmers.

The aim of this study was tο examine the acute responses to an Ultra-Short Race Pace Training (USRPT) and a High-Intensity Interval Training (HIIT), both oriented for the event of 100 m freestyle. Eighteen national-level swimmers (8 boys, 10 girls) aged 13.5 ± 0.1 years, with 8.0 ± 0.5 years of experience participated in the study. All participants completed a USRPT and a HIIT protocol consisting of 2 × 10 × 25 m (USRPT1 & USRPT2) and 5 × 50 m. Significantly higher swimming velocity (SV) were achieved in USRPT compared to HIIT (p < 0.001), while significantly lower distance per stroke (DPS) and stroke index (SI) were obtained (p = 0.007 and p < 0.001). Also, significantly lower blood lactate and glucose (BL & BG) concentrations were found after USRPT (p ≤ 0.001 and p = 0.037). Heart rate (HR) and rate of perceived exertion (RPE) were significantly lower after USRPT than HIIT (p < 0.001 and p = 0.015). According to the results, an USRPT swimming set consisting of 20 × 25 m at a 100 m pace seems to induce more specific responses in kinematic characteristics, biomarkers, HR and RPE compared to a 5 × 50 m HIIT set.

Corrigendum to "A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning" [IBRO Neurosci Rep. 15 (2023) 77-89].

[This corrects the article DOI: 10.1016/j.ibneur.2023.06.008.].

Validation of liquid biopsy for ESR1-mutation analysis in hormone-sensitive breast cancer: a pooled meta-analysis.

Several retrospective and prospective studies have shown that genomic alterations in Estrogen-receptor one (ESR1) can be characterized not only in tissue samples but also by sequencing circulating tumor DNA (ctDNA) in liquid biopsy. Therefore, liquid biopsy is a potential noninvasive surrogate for tissue biopsy. This meta-analysis was designed to compare the prevalence of ESR 1 mutation detected with liquid biopsy and tissue biopsy. A pooled meta-analysis of studies published between 1 January 2007 and 1 March 2021 was conducted regarding the methodologies used for ESR1 mutation analysis. Liquid biopsy is a valid, inexpensive, and attractive noninvasive alternative to tumor biopsies for the identification of ESR1 mutations. Liquid biopsy for ESR 1 analysis would facilitate regular testing, allowing monitoring of the sensitivity to ET and guiding treatment strategies.

Nutritional Risk and Sarcopenia Features in Patients with Crohn's Disease: Relation to Body Composition, Physical Performance, Nutritional Questionnaires and Biomarkers.

Patients with Crohn's disease (CD) face malnutrition risk, which, combined with inflammation, can lead to sarcopenia, associated with a worse prognosis. The purpose of the present study was to assess malnutrition and sarcopenia in patients with CD. Fifty-three patients (26 women) participated (38.1 ± 10.9 years, 79% in remission). Body composition, physical performance, nutritional questionnaires, and biomarkers were performed. Malnutrition was screened with the Mini Nutritional Assessment (MNA) and the Malnutrition Inflammation Risk Tool (MIRT) and was assessed with the Global Leadership Initiative on Malnutrition (GLIM) tool using etiologic along with three different phenotypic criteria: low Body Mass Index (BMI), low Calf Circumference (CC), and low Fat-Free Mass Index (FFMI). To find cases and evaluate sarcopenia, the Sarcopenia Questionnaire (SARC-F) and European Working Group on Sarcopenia2 (EWGSOP2) criteria were used. Malnutrition rates were 11.3% (n = 6), 7.5% (n = 4), and 5.6% (n = 3) based on low FFMI, CC, and BMI, correspondingly. Four (7%) patients had low Hand-Grip Strength (HGS), n = 8 (14.8%) had low Appendicular Lean Mass (ALM), and n = 3 (5.6%) had low gait speed. No-one had sarcopenia. A high albumin and triceps skinfold pattern, identified by principal component analysis, was related to reduced C-Reactive Protein (CRP) levels (B = -0.180, SE = 0.085, p = 0.045). In conclusion, based on the studied anthropometric, nutritional, and functional variables, CD patients were not diagnosed with sarcopenia in the present study. Body composition patterns were related to the inflammatory burden, underlying the interplay of inflammation and malnutrition, even in remission states. Further studies on older populations and during disease exacerbation are necessary to explore the potential link between CD, inflammation, and sarcopenia.

Swimming Activity Alleviates the Symptoms of Attention: Deficit Hyperactivity Disorder (ADHD) a Case Report.

Attention deficit hyperactivity disorder (ADHD) is a neurobehavioral disorder characterized by inattention, hyperactivity, and impulsivity. Sport and physical activity have been shown to play a major role in the development of cognition, memory, selective attention, and motor reaction time, especially among adolescents with ADHD. In this context, the objective of this study was to investigate the effects of a swimming exercise program on the symptoms of ADHD in an adult with a diagnosis since childhood. The training intervention was performed for eight weeks, and the results demonstrated that the swimming-learning program significantly alleviated the symptoms of inattention and hyperactivity, as measured by the psychometric indices used in the study. Further studies are needed to establish and understand the association between physical activities and improved mental performance in adults with ADHD.

The Effects of Insect Infestation on Stored Agricultural Products and the Quality of Food.

In this review article, we focus on the effects of insect pests on the quality of stored cereals and legume grains. The changes in the amino-acid content, the quality of proteins, carbohydrates, and lipids, and the technological characteristics of the raw materials when infested by specific insects are presented. The differences reported concerning the rate and kind of infestation effects are related to the trophic habits of the infesting insect species, the variation of the component distribution in the different species of grains, and the length of the storage period. For example, wheat germ and brans feeders such as Trogoderma granarium may cause a higher reduction in proteins than endosperm feeders such as Rhyzopertha dominica, since the germ and brans contain higher concentrations of proteins. Trogoderma granarium may also cause higher reduction in lipids than R. dominica in wheat, maize and sorghum, in which most of the lipids exist in the germ. Furthermore, infestation with insects such as Tribolium castaneum may downgrade the overall quality of wheat flour, by increasing the moisture content, the number of insect fragments, the color change, the concentration of uric acid, the microbial growth, and the prevalence of aflatoxins. Whenever possible, the significance of the insect infestation and the concomitant compositional alterations on human health are presented. It should be highlighted that understanding the impact of insect infestation on stored agricultural products and the quality of food will be crucial for the required food security in the future.

Impact of Different Nutrition Strategies on Patients with Inflammatory Bowel Disease (IBD).

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SARS-CoV-2 Amino Acid Mutations Detection in Greek Patients Infected in the First Wave of the Pandemic.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel virus that belongs to the Coronoviridae family, emerged in December 2019, causing the COVID-19 pandemic in March 2020. Unlike previous SARS and Middle East respiratory syndrome (MERS) outbreaks, this virus has a higher transmissibility rate, albeit a lower case fatality rate, which results in accumulation of a significant number of mutations and a faster evolution rate. Genomic studies on the mutation rate of the virus, as well as the identification of mutations that prevail and their impact on disease severity, are of great importance for pandemic surveillance and vaccine and drug development. Here, we aim to identify mutations on the SARS-CoV-2 viral genome and their effect on the proteins they are located in, in Greek patients infected in the first wave of the pandemic. To this end, we perform SARS-CoV-2 amplicon-based NGS sequencing on nasopharyngeal swab samples from Greek patients and bioinformatic analysis of the results. Although SARS-CoV-2 is considered genetically stable, we discover a variety of mutations on the viral genome. In detail, 18 mutations are detected in total on 10 SARS-CoV-2 isolates. The mutations are located on ORF1ab, S protein, M protein, ORF3a and ORF7a. Sixteen are also detected in patients from other regions around the world, and two are identified for the first time in the present study. Most of them result in amino acid substitutions. These substitutions are analyzed using computational tools, and the results indicate minor or major impact on the proteins' structural stability, which could probably affect viral transmissibility and pathogenesis. The correlation of these variations with the viral load levels is examined, and their implication for disease severity and the biology of the virus are discussed.

Applying Image-Based Food-Recognition Systems on Dietary Assessment: A Systematic Review.

Dietary assessment can be crucial for the overall well-being of humans and, at least in some instances, for the prevention and management of chronic, life-threatening diseases. Recall and manual record-keeping methods for food-intake monitoring are available, but often inaccurate when applied for a long period of time. On the other hand, automatic record-keeping approaches that adopt mobile cameras and computer vision methods seem to simplify the process and can improve current human-centric diet-monitoring methods. Here we present an extended critical literature overview of image-based food-recognition systems (IBFRS) combining a camera of the user's mobile device with computer vision methods and publicly available food datasets (PAFDs). In brief, such systems consist of several phases, such as the segmentation of the food items on the plate, the classification of the food items in a specific food category, and the estimation phase of volume, calories, or nutrients of each food item. A total of 159 studies were screened in this systematic review of IBFRS. A detailed overview of the methods adopted in each of the 78 included studies of this systematic review of IBFRS is provided along with their performance on PAFDs. Studies that included IBFRS without presenting their performance in at least 1 of the above-mentioned phases were excluded. Among the included studies, 45 (58%) studies adopted deep learning methods and especially convolutional neural networks (CNNs) in at least 1 phase of the IBFRS with input PAFDs. Among the implemented techniques, CNNs outperform all other approaches on the PAFDs with a large volume of data, since the richness of these datasets provides adequate training resources for such algorithms. We also present evidence for the benefits of application of IBFRS in professional dietetic practice. Furthermore, challenges related to the IBFRS presented here are also thoroughly discussed along with future directions.