Search Results (72)

Chestnut (Castanea sativa Mill.) is an edible nut recognized for its nutritional attributes, particularly its elevated levels of carbohydrates (starch) and proteins. Chestnuts are popular for their health-promoting properties and hold significant environmental and economic importance in Europe. During this study, after the characterization of the fruit, attention was directed toward the valorization of chestnut shells, a predominant by-product of industrial chestnut processing that is typically discarded. Valuable bioactive compounds were extracted from the shells using Pressurized Liquid Extraction (PLE), a green, efficient, scalable method. Response surface methodology (RSM) was utilized to determine optimal extraction conditions, identified as 40% v/v ethanol as the solvent at a temperature of 160 °C for 25 min under a constant pressure of 1700 psi. High total polyphenol content (113.68 ± 7.84 mg GAE/g dry weight) and notable antioxidant activity—determined by FRAP (1320.28 ± 34.33 μmol AAE/g dw) and DPPH (708.65 ± 24.8 μmol AAE/g dw) assays—were recorded in the optimized extracts. Ultrahigh-performance liquid chromatography coupled with a hybrid trap ion mobility-quadrupole time-of-flight mass spectrometer (UHPLC-TIMS-QTOF-MS) was applied to further characterize the compound profile, enabling the identification of phenolic and antioxidant compounds. These findings highlight the possibility of using chestnut shell residues as a long-term resource to make valuable products for the food, medicine, cosmetics, and animal feed industries. This study contributes to the advancement of waste valorization strategies and circular bioeconomy approaches. Full article

Background: Dietary intake plays a crucial role in health research, yet existing methods for its measurement can lead to participant burden, lengthy recording, and human errors, and do not account for age-specific variations. Libro is a real-time diet-tracking mobile-based app offering flexible features. An automated food recording program within Libro was customized for young people vulnerable to eating misbehaviour. This preliminary study assessed its relative validity using a self-administered 24 h recall method as the reference method. Methods: The relative validity of Libro was tested by adopting a cross-over design that recorded food intake over a period of 3 non-consecutive weekdays and 1 weekend day with both methods. The participants were recruited online through a mental health research charity, and this study was conducted fully online. The primary outcome was the concordance of total energy intake between the two methods, with secondary outcomes focusing on the intake of protein, carbohydrates, fats, free sugars, fibre, and trans-fatty acids. Test–retest validity was assessed per method with the intraclass correlation coefficient; a Bland–Altman plot and t-test were performed to test agreement at the group level; correlation coefficient and cross-classification were performed to assess agreement at the individual level. Results: Forty-seven participants were included in the final analysis. The average intraclass correlation coefficient for energy intake measured by Libro over four days was 0.85 (95% CI: 0.76–0.91). Compared to Intake24, the average energy intake recorded using Libro was significantly lower (mean difference: −554 Kcal, 95% CI: −804.1 to −305.6 Kcal, p < 0.001), potentially driven by the reduced reporting of foods rich in free sugars. The correlation coefficient for average energy intake measured by Libro vs. Intake24 was 0.32 (95% CI: 0.03, 0.55), with only 27.7% of subjects classified in the same quartile with both methods (κ = 0.31, 95% CI: −0.03, 0.55). Concordance varied across specific dietary component measures. Conclusions: While Libro had good test–retest reliability if adopting a multiple administration method, it underreported energy and other aspects of dietary intake, along with poor classification performance compared to Intake24 in a population vulnerable to eating misbehaviour. We suggest that future studies improve user experience to increase compliance and data accuracy. Full article

The detection of fish freshness is crucial for ensuring food safety. This study addresses the limitations of traditional detection methods, which rely on laboratory equipment and complex procedures, by proposing a smartphone-based detection method, termed FreshFusionNet, that utilizes a pitaya peel pH intelligent indicator film in conjunction with multimodal deep learning. The pitaya peel indicator film, prepared using high-pressure homogenization technology, demonstrates a significant color change from dark red to yellow in response to the volatile alkaline substances released during fish spoilage. To construct a multimodal dataset, 3600 images of the indicator film were captured using a smartphone under various conditions (natural light and indoor light) and from multiple angles (0° to 120°), while simultaneously recording pH values, total volatile basic nitrogen (TVB-N), and total viable count (TVC) data. Based on the lightweight MobileNetV2 network, a Multi-scale Dilated Fusion Attention module (MDFA) was designed to enhance the robustness of color feature extraction. A Temporal Convolutional Network (TCN) was then used to model dynamic patterns in chemical indicators across spoilage stages, combined with a Context-Aware Gated Fusion (CAG-Fusion) mechanism to adaptively integrate image and chemical temporal features. Experimental results indicate that the overall classification accuracy of FreshFusionNet reaches 99.61%, with a single inference time of only 142 ± 40 milliseconds (tested on Xiaomi 14). This method eliminates the need for professional equipment and enables real-time, non-destructive detection of fish spoilage through smartphones, providing consumers and the food supply chain with a low-cost, portable quality-monitoring tool, thereby promoting the intelligent and universal development of food safety detection technology. Full article

Background: Unhealthy food consumption in long-term care facilities (LTCFs) contributes to poor health outcomes among residents. This study aimed to assess its prevalence, identify demographic and physical risk factors, and propose targeted interventions. Methods: A mixed-methods study (2017–2021) analyzed data from 1000 Polish LTCF residents (aged 35–105 years). Anthropometric measurements, bioimpedance analyses, dietary assessments, and physical activity records were collected. Food items were classified as “healthy” or “unhealthy” using an AI-based Large Language Model (LLM), applying WHO guidelines and the NOVA classification system. Logistic regression and chi-square tests assessed associations between unhealthy food consumption and marital status, education level, mobility aid use, and portion control. Results: Unhealthy food consumption prevalence was 15.6%. Married residents had significantly higher rates than unmarried individuals (22.6% vs. 14.3%, p < 0.01). Lower educational attainment correlated with increased risk (partial primary education: 34.7% vs. tertiary education: 8.1%). Mobility aid users exhibited elevated consumption (cane: 34.6%; walker: 22.6%). Poor portion control showed the strongest association (OR = 3.2, 95% CI: 1.8–5.7). Conclusions: Marital status, educational disparities, mobility limitations, and portion control were key modifiable risk factors. Findings suggest the need for targeted nutrition programs, caregiver education, and policy reforms to improve dietary literacy and meal portioning. Future research should validate AI-based food classification methods, assess long-term intervention outcomes, and expand studies to diverse LTCF settings. These findings align with Poland’s National Health Programme and provide actionable insights for global LTCF populations. Full article

Aim: Mobile health (mHealth) applications have been reported to be effective in improving glycaemic control and cardiometabolic health, but mainly as part of shorter-term intervention studies. The aim of this study is to examine the effect of the ongoing Defeat Diabetes mHealth low-carbohydrate diet (LCD) intervention on clinical markers and cardiometabolic risk after 6 months of intervention. Methods: Data were collected via primary care physicians as part of routine T2D monitoring. These included HbA1c (primary outcome), blood pressure, blood lipids, and markers of kidney and liver function. Anthropometrics, as well as changes in the prescription of diabetes, hypertension, and dyslipidaemia medication, were also recorded. Calculated variables, total cholesterol to HDL-c, triglyceride to HDL-c, and waist to height ratios, were analysed to examine changes in cardiometabolic risk profile. Three-day food records were used to assess dietary intake and intervention adherence. Univariate regression models examined changes from baseline to 6 months. Results: Ninety-four participants remained in the study out of the ninety-nine at baseline (mean age 59 ± 11 years, 55 females). After 6 months of intervention, there were significant reductions in HbA1c by −1.0% (95% CI: −1.3 to −0.6), as well as in the liver enzymes ALT (−9.3 U/L 95% CI −16.3 to −2.4) and GGT (−18.8 U/L 95% CI: −31.4 to −6.3) across the cohort. In addition, there was a significant reduction in cardiometabolic risk, as measured by the calculated variables and a decrease in waist circumference (−4.6 cm 95% CI: −8.9 to −0.2). Conclusions: People with T2D receiving LCD education and resources through the Defeat Diabetes mHealth app (version 3.3.8) improved their glycaemic control after 6 months of intervention. Cardiometabolic risk profile and liver function also showed significant improvement. These findings indicate that the use of an LCD digital app is a valuable adjunct in the management of T2D. Full article

Measurements of the properties of soft materials are important from the point of view of medical diagnostics of soft tissues as well as testing the quality of food products and many technical materials. One of the frequently used techniques for testing such materials, attractive due to its non-invasive nature, is the indentation technique, which does not puncture the material. The difficulty of testing soft materials, which affects the objectivity of the results, is related to the problems of stable positioning of the studied material in relation to the indentation apparatus, especially with a device held by the operator. This work concerns the comparison of test results using an indentation apparatus mounted on mobile and stationary handles. The tested materials are cylindrical samples of polyurethane foams with three different stiffnesses and the same samples with a 0.5 or 1 mm thick silicone layer. The study presented uses an apparatus with a flat cylindrical indenter, with a surface area of 1 cm², pressed to a depth of 10 mm (so-called deep tests). Based on the recorded force changes over time, five descriptors of the indentation test were determined and compared for both types of handles. The tests performed showed that the elastic properties of foam materials alone and with a silicone layer can be effectively characterized by the maximum forces during recessing and retraction and the slopes of the recessing and retraction curves. In the case of two-layer materials, these descriptors reflect both the characteristics of the foams and the silicone layer. The results show that the above property of the deep indentation method distinguishes it from the shallow indentation method. The repeatability of the tests performed in the mobile and stationary holders were determined to be comparable. Full article

The olive fruit fly, known as Bactrocera oleae (Rossi) (Diptera: Tephritidae), is causing substantial economic losses in olive crops worldwide. Studying the activity patterns of the insect may expand our knowledge to eventually adopt more sustainable and effective pest control approaches. In the present study, we investigated the impact of food and water deprivation on the mobility of olive fruit flies using a modified version of the LAM25 system (locomotor activity monitor)—Trikinetics, an automated locomotor activity electronic device. Both male and female flies at four different age groups, reared on olives in the laboratory, were individually placed in glass tubes. Their locomotor activity was recorded every minute by three monitors within the digital device over a three-day period. Our observations revealed that adults exhibited significantly reduced movement during nighttime compared to daytime. The greatest mobility was observed during the period of 15:00 to 20:59. Additionally, younger flies demonstrated higher levels of mobility compared to older ones. Flies subjected to both food and water deprivation exhibited higher mobility compared to the control group. These insights offer valuable insights for enhancing pest management strategies aimed at controlling olive fruit flies adopting a more sustainable approach. Full article

Technology-assisted dietary assessment has the potential to improve the accuracy of self-reported dietary intake. This study evaluates MealScan3D (MS3D), a mobile device-based food recording system, which uses three-dimensional images to obtain food volumes and an application to capture algorithm-driven food intake data. Participants (n = 179) were randomly assigned and trained to record three meals using either MS3D or a written food record (WFR). Generous amounts of standardized meals were provided, and participants self-selected portions for each food. The weights of provided and uneaten/leftover foods were used to determine true intake. For total energy intake (three meals combined), validity (Pearson correlation) was significantly higher for MS3D vs. the WFR (p < 0.001); when interpreted as the percentage of variance in energy intake explained, MS3D explained 84.6% of true variance, a 25.3% absolute and 42.6% relative increase over the 59.3% explained by the WFR. For 9 of 15 individual foods, the Pearson correlations between true and reported portion size estimates were significantly larger for MS3D than the WFR. Bias was smaller (intercepts were closer to the means) for 9 of 15 foods and the regression coefficients for 10 of 15 foods were significantly closer to 1.0 in the MS3D arm. MS3D is feasible for dietary assessment and may provide improvements in accuracy compared to WFRs. Full article

During adolescence, many young people commence making more independent food purchases. Subsequently, these independent food choices will increasingly contribute to their overall diet quality; little is known, however, about this relationship. This study aimed to (1) understand the role adolescents’ independent food purchases play in their overall diet quality and (2) explore if these relationships vary according to socioeconomic status (SES). A one-week observational study was conducted with 108 adolescents, aged 11–18 years, from Hampshire, UK. Participants completed a demographic questionnaire and a validated 20-item Food Frequency Questionnaire, which assessed diet quality. Participants also used a mobile phone app to record their food purchases. The healthfulness of food purchases was assessed against UK healthy eating guidelines. Linear regression models were used to investigate associations between the healthfulness of food purchases and diet quality. An interaction term was used to determine the modification effect of SES. During the study week, 583 food/drink items were purchased on 273 food-purchasing occasions by 80 participants. The majority of purchases (n = 359, 62%) were coded as ‘not adhering’ to the UK Eatwell Guide, 30% were coded as ‘adhering’ and 8% were coded as uncategorised foods. No notable differences were observed in the healthfulness of food purchases according to age, gender, ethnicity or SES. Healthier food purchasing was associated with better diet quality (β 0.52, (95% CI 0.06, 0.99) p = 0.03); the results were attenuated after adjustment (β 0.41, (95% CI −0.08, 0.91) p = 0.10). Interaction analysis showed that the healthfulness of purchases was more strongly associated with diet quality among young people of lower SES (p = 0.06). Discussion: The majority of purchases made by adolescents were categorised as ‘not adhering’ to healthy eating guidelines. For adolescents experiencing disadvantage, these food choices had a more detrimental impact on their overall diet. We speculate this is because independent food choices represent a greater proportion of the foods consumed by these adolescents compared to those who are less disadvantaged. Finding ways to support more healthful independent food choices among adolescents, particularly those from disadvantaged backgrounds, is important to improve dietary quality and reduce inequalities. Full article

Sensitive, intelligent point-of-care test (iPOCT) methods for small molecules like aflatoxin B1 (AFB1) are urgently needed for food and the environment. The challenge remains of surface control in iPOCT. Herein, we developed an electrochemical sensor based on the DNA pyramid (DNP), combining a smartphone, app, and mobile electrochemical workstations to detect AFB1. The DNP’s structure can reduce local overcrowding and entanglement between neighboring probes, control the density and orientation of recognition probes (antibodies), produce uniform and orientational surface assemblies, and improve antigen–antibody-specific recognition and binding efficiency. Simultaneously, the hollow structure of the DNP enhances the electron transfer capacity and increases the sensitivity of electrochemical detection. In this work, the biosensor based on DNP was first combined with electrochemical (Ec) iPOCT to simultaneously achieve ordered interface modulation of recognition probes and intelligent detection of AFB1. Under optimal conditions, we found a detection limit of 3 pg/mL and a linear range of 0.006–30 ng/mL (R² = 0.995). Further, using peanut, soybean, corn, and lake water as complex matrices, it recorded recoveries of 82.15–100.53%, excellent selectivity, acceptable stability, and good reproducibility. Finally, this Ec iPOCT provides consistent results compared to the high-performance liquid chromatography-tandem mass spectrometry method. Full article

Photo-based dietary assessment is becoming more feasible as artificial intelligence methods improve. However, advancement of these methods for dietary assessment in research settings has been hindered by the lack of an appropriate dataset against which to benchmark algorithm performance. We conducted the Surveying Nutrient Assessment with Photographs of Meals (SNAPMe) study (ClinicalTrials ID: NCT05008653) to pair meal photographs with traditional food records. Participants were recruited nationally, and 110 enrollment meetings were completed via web-based video conferencing. Participants uploaded and annotated their meal photos using a mobile phone app called Bitesnap and completed food records using the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24^®) version 2020. Participants included photos before and after eating non-packaged and multi-serving packaged meals, as well as photos of the front and ingredient labels for single-serving packaged foods. The SNAPMe Database (DB) contains 3311 unique food photos linked with 275 ASA24 food records from 95 participants who photographed all foods consumed and recorded food records in parallel for up to 3 study days each. The use of the SNAPMe DB to evaluate ingredient prediction demonstrated that the publicly available algorithms FB Inverse Cooking and Im2Recipe performed poorly, especially for single-ingredient foods and beverages. Correlations between nutrient estimates common to the Bitesnap and ASA24 dietary assessment tools indicated a range in predictive capacity across nutrients (cholesterol, adjusted R² = 0.85, p < 0.0001; food folate, adjusted R² = 0.21, p < 0.05). SNAPMe DB is a publicly available benchmark for photo-based dietary assessment in nutrition research. Its demonstrated utility suggested areas of needed improvement, especially the prediction of single-ingredient foods and beverages. Full article

According to the National Family Health Survey of 2021, about 57% of women aged 15–49 in India currently suffer from anemia, marking a significant increase from the 53% recorded in 2016. Similarly, a study conducted in southern India reported a 32.60% prevalence of preeclampsia. Several community-based initiatives have been launched in India to address these public health challenges. However, these interventions have yet to achieve the desired results. Could the challenges faced by traditional healthcare interventions be overcome through a technological leap? This study assesses pregnant mothers’ perceptions regarding mobile health interventions for managing anemia and preeclampsia. Additionally, the study captures their health awareness and knowledge. We conducted a survey with 131 pregnant mothers in three underserved villages in Jharkhand, India. Statistical analysis was conducted using the SEMinR package in R (Version 2023.06.0), utilizing the non-parametric partial least squares-structural equation modeling. We found that every household had at least one smartphone, with the respondents being the primary users. The main uses of smartphones were for calling, messaging, and social media. A total of 61% of respondents showed interest in a nutrition and pregnancy app, while 23.66% were uncertain. Regarding nutritional knowledge during pregnancy, 68.7% reported having some knowledge, but only 11.45% claimed comprehensive knowledge. There was a considerable knowledge gap regarding the critical nutrients needed during pregnancy and the foods recommended for a healthy pregnancy diet. Awareness of pregnancy-related conditions such as anemia and preeclampsia was low, with most respondents unsure of these conditions’ primary causes, impacts, and symptoms. This study serves as a critical step towards leveraging technology to enhance public health outcomes in low-resource settings. With the accessibility of mobile devices and an apparent willingness to utilize mHealth apps, compounded by the pressing need for improved maternal health, the impetus for action is indisputable. It is incumbent upon us to seize this opportunity, ensuring that the potential of technology is fully realized and not squandered, thus circumventing the risk of a burgeoning digital divide. Full article

Responsive feeding is associated with a reduced risk of childhood obesity. The objective of this qualitative study was to determine parental preferences for mobile health (mHealth) app content and features designed to improve responsive feeding practices. Parents of 0–2-year-old children were interviewed individually. Interview questions were informed by the Technology Acceptance Model, and parents provided feedback on sample app content and features. Interviews were audio-recorded, transcribed verbatim, and coded by two researchers using thematic analysis; responses were compared by parent gender and income. Parents (n = 20 fathers, n = 20 mothers) were, on average, 33 years old, low-income (50%), identified as non-white (52.5%), and had a bachelor’s degree or higher (62%). Overall, parents were most interested in feeding tips and recipe content, and app features that allowed tracking child growth and setting feeding goals. Fathers were most interested in content about first foods, choking hazards, and nutrition information, while mothers preferred content on breastfeeding, picky eating, and portion sizes. Parents with lower incomes were interested in nutrition guidelines, breastfeeding, and introducing solids. Non-low-income parents preferred information related to food allergies, portion sizes, and picky eating. The findings of this study provide considerations when developing mHealth apps to improve responsive feeding practices in parents. Full article

A metabolic disorder is due to a gene mutation that causes an enzyme deficiency which leads to metabolism problems. Maple Syrup Urine Disease (MSUD) is one of the most common and severe hereditary metabolic disorders in Saudi Arabia. Patients and families were burdened by complex and regular dietary therapy menus because of the lack of information on food labels, it was also difficult to keep track of MSUD’s typical diet. The prototype smart plate system proposed in this work may help patients with MSUD and their caregivers better manage the patients’ MSUD diet. The use of knowledge-based, food identification techniques and a device could provide a support tool for self-nutrition management in pediatric patients. The requirements of the system are specified by using questionaries. The design of the prototype is divided into two parts: software (mobile application) and hardware (3D model of the plate). The knowledge-based mobile application contains knowledge, databases, inference, food recognition, food plan, monitor food plan, and user interfaces. The hardware prototype is represented in a 3D model. All the patients agreed that a smart plate system connected to a mobile application could help to track and record their daily diet. A self-management application can help MSUD patients manage their diet in a way that is more pleasant, effortless, accurate, and intelligent than was previously possible with paper records. This could support dietetic professional practitioners and their patients to achieve sustainable results. Full article

Background and Objectives: Pain during and after the procedure remains the leading concern among women undergoing cesarean section. Numerous studies have concluded that the type of anesthesia used during a cesarean section undoubtedly affects the intensity and experience of pain after the operation. Materials and Methods: This prospective cohort study was conducted at the Clinic for Gynecology and Obstetrics, Clinical Center “Dragisa Misovic—Dedinje”, Belgrade, Serbia. Patients at term pregnancy (37–42 weeks of gestation) with an ASA I score who delivered under general (GEA) or regional anesthesia (RA) by cesarean section were included in the study. Following the procedure, we assessed pain using the Serbian McGill questionnaire (SF–MPQ), Visual Analogue Scale (VAS) and the pain attributes questionnaire at pre-established time intervals of 2, 12, and 24 h after the procedure. Additionally, time to patient’s functional recovery was noted. We also recorded the time to the first independent mobilization, first oral intake, and lactation establishment. Results: GEA was performed for 284 deliveries while RA was performed for 249. GEA had significantly higher postoperative sensory and affective pain levels within intervals of 2, 12, and 24 h after cesarean section. GEA had significantly higher postoperative VAS pain levels. On pain attribute scale intensity, GEA had significantly higher postoperative pain levels within all intervals. Patients who received RA had a shorter time to first oral food intake, first independent mobilization, and faster lactation onset in contrast to GEA. Conclusions: The application of RA presented superior postoperative pain relief, resulting in earlier mobilization, shorter time to first oral food intake, and faster lactation onset in contrast to GEA. Full article