Effectiveness of a healthy lifestyle program based on a mobile serious game for childhood cancer survivors: A quasi-randomized trial.

PURPOSE: This study aimed to develop and evaluate the effectiveness of a healthy lifestyle program based on a mobile serious game (HLP-MSG) to enhance the lifestyles of childhood cancer survivors (CCSs). METHODS: This program proceeded in two stages: development and evaluation, using a non-synchronized design with a quasi-randomized trial. The participants were CCSs aged 6-13 years whose treatment was terminated at least 12 months prior. Data were collected at baseline, and post-intervention, with a follow-up after four weeks using the Child Healthy Lifestyle Profile (CHLP). The experimental (n = 26) and control groups (n = 25) were compared. Data were analyzed using descriptive statistics, chi-squared tests, t-tests, and repeated-measures ANOVA. RESULTS: The HLP-MSG promoted a healthy lifestyle by solving 26 quests, including seven sub-elements (nutrition, exercise, hygiene, interpersonal relationships, stress management, meaning of life, and health responsibility). This study revealed significant differences in the interaction between measurement time and group assignment in the CHLP (p = .006) and physical activity (p = .013), one of the seven sub-dimensions. CONCLUSIONS: A healthy lifestyle program based on a mobile serious game is a feasible health education modality to enhance the physical, psychological, social, and spiritual health of CCSs. IMPLICATIONS TO PRACTICE: The findings add to scientific evidence on a mobile serious game for health education among CCSs. The HLP-MSG provides an evolutionary educational modality that can be delivered non-face-to-face to promote CCSs' continuous healthy behavior maintenance. Moreover, the HLP-MSG is adolescent-friendly and can be utilized as a healthcare tool for parents and children to cooperate.

Retrogradation-induced physicochemical changes in pre-cooked rice noodles stored at different temperatures: a viewpoint from water dynamics and structure.

BACKGROUND: There has been significant interest in pre-cooked noodles that have a long shelf life and are convenient to cook. However, the thermal processes during preparation, and their high moisture content, can lead to significant quality deterioration during storage. Nevertheless, a comprehensive evaluation of these quality losses has not yet been conducted. RESULTS: The effects of different storage temperatures (25, 4, and -20 °C) on the retrogradation-related physicochemical changes in pre-cooked rice noodles were elucidated mainly from the water dynamics and structural viewpoints. Thermal analysis demonstrated that amylopectin recrystallization took place in the noodles stored at refrigerated temperature, followed by room temperature. The refrigerated storage accelerated the starch retrogradation that caused the water molecules to become entrapped within the crystalline structure by lowering the water hydration properties and weighted T2 relaxation times of the pre-cooked noodles. These water mobility patterns were correlated with the textural changes in the noodles (greater hardness and Rmax /extensibility). Furthermore, the higher structural density and thickness derived from starch retrogradation were observed in the tomographic and microscopic images of the refrigerated noodles. The principal component analysis demonstrated that various physicochemical changes of the pre-cooked noodles during storage showed high correlations with the degree of starch retrogradation (r > 0.83). CONCLUSION: The physicochemical features of the precooked noodles stored under refrigerated conditions were involved in the molecular dynamics of water, showing a notable water mobility reduction derived from the starch retrogradation, which contributed to their thermal, tomographical, and textural changes. © 2023 Society of Chemical Industry.

Artificial intelligence-based prediction of the rheological properties of hydrocolloids for plant-based meat analogues.

BACKGROUND: Methylcellulose has been applied as a primary binding agent to control the quality attributes of plant-based meat analogues. H owever, a great deal of effort has been made to search for hydrocolloids to replace methylcellulose because of increasing awareness of clean labels. In this study, a machine learning framework was proposed in order to describe and predict the flow behavior of six hydrocolloid solutions, and the predicted viscosities were correlated with the textural features of their corresponding plant-based meat analogues. RESULTS: Different shear-thinning and Newtonian behaviors were observed depending on the type of hydrocolloid and the shear rate. Methylcellulose exhibited an increasing viscosity pattern with increasing temperature, compared to the other hydrocolloids. The machine learning algorithms (random forest and multilayer perceptron models) showed a better viscosity fitting performance than the constitutive equations (power law and Cross models). In addition, three hyperparameters of the multilayer perceptron model (optimizer, learning rate, and the number of hidden layers) were tuned using the Bayesian optimization algorithm. CONCLUSION: The optimized multilayer perceptron model exhibited superior performance in viscosity prediction (R2 = 0.9944-0.9961/RMSE = 0.0545-0.0708). Furthermore, the machine learning-predicted viscosities overall showed similar patterns to the textural parameters of the meat analogues. © 2024 Society of Chemical Industry.

Bound for Gaussian-state quantum illumination using a direct photon measurement.

It is important to find feasible measurement bounds for quantum information protocols. We present analytic bounds for quantum illumination with Gaussian states when using an on-off detection or a photon number resolving (PNR) detection, where its performance is evaluated with signal-to-noise ratio. First, for coincidence counting measurement, the best performance is given by the two-mode squeezed vacuum (TMSV) state which outperforms the coherent state and the classically correlated thermal (CCT) state. However, the coherent state can beat the TMSV state with increasing signal mean photon number in the case of the on-off detection. Second, the performance is enhanced by taking Fisher information approach with all counting probabilities including non-detection events. In the Fisher information approach, the TMSV state still presents the best performance but the CCT state can beat the TMSV state with increasing signal mean photon number in the case of the on-off detection. Furthermore, we show that it is useful to take the PNR detection on the signal mode and the on-off detection on the idler mode, which reaches similar performance of using PNR detection on both modes.

Lutein fortification of wheat bread with marigold powder: impact on rheology, water dynamics, and structure.

BACKGROUND: Demands for foods conducive to eye health have been on the increase in the global healthcare sector. Marigold powder as a major source of lutein was utilized to produce lutein-fortified breads for ocular health. The physicochemical characteristics of the doughs and breads were investigated in terms of rheology, water mobility, and protein secondary structures. RESULTS: The incorporation of marigold powder decreased the water absorption of doughs without significantly altering thermomechanical properties. With a range of fortification levels (1-3%), marigold powder led to decreased storage and loss modulus of doughs by weakening their gluten network, which was supported by their T2 relaxation times. The resistance of the doughs weakened with increasing levels of marigold powder, while their extensibilities significantly incremented. Fourier transform infrared spectral deconvolution revealed the changes in wheat protein structures upon marigold powder incorporation, in which the proportion of ß-turn increased at the expense of ß-sheet ratio. The breads with marigold powder displayed increased specific volume from 4.034 to 4.368 mL g-1 , accompanied by softer textures. The baking process led to heat-induced losses in lutein concentration of less than 10% within the crumb and approximately 30% in the crust. CONCLUSION: The use of marigold powder induced changes in protein secondary structure and extensional features of doughs, contributing to increased loaf volume and softer texture. Overall, this study provides fundamental information on the rheological and structural effects of marigold powder in a wheat bread system, consequently encouraging the food industry to utilize marigold power as a functional food ingredient. © 2023 Society of Chemical Industry.

Effects of textured food masticatory performance in older people with different dental conditions.

BACKGROUND: Physiological deterioration (aging, poor dental status, and reduced tongue pressure) makes chewing difficult. This study aimed to investigate the chewing patterns of older people with or without dentures, evaluate the textural and masticatory properties of texture-modified radish Kimchi, and investigate the correlation between dental status and tongue pressure. Additionally, differences in the subjective-objective concordance of texture-modified Kimchi were investigated using the preference test. METHODS: This study included 32 Korean women aged between 65 and 85 years. Masticatory behavior was recorded by electromyography, and tongue pressure was measured using the Iowa Oral Performance Instrument. A preference test, with hardness as the relevant textural property, determined the participants' preferences among the test samples (food with a homogeneous structure-radish Kimchi). To assess preference differences, a questionnaire suitable for older people was designed. The preference for cooked radish Kimchi with various blanching times based on overall acceptability and self-reporting of preference was investigated to develop elderly-friendly food. The subjective scores indicated whether the sample (radish Kimchi) was hard or soft based on the chewing ability of the participants. Dental status, muscle activities, and tongue pressure were considered for the food design with optimized texture. The relationship between subject score and mastication properties were examined using multiple regression analysis. RESULTS: The number of chews and chewing time increased with hardness, significantly activating the masseter and temporalis muscles. The evaluation of masseter muscle activity, particularly for level-6 radish Kimchi, showed that older people with complete dentures chewed less actively than those with natural teeth (p < 0.05). The older people with natural teeth (18.94 ± 10.27 kPa) exhibited higher tongue pressure than those with complete dentures (10.81 ± 62.93 kPa), and the difference was statistically significant (p < 0.01). Older people preferred food with familiar tastes and textures. An association was found between the subjective hardness score and the objective hardness level. The perceived hardness intensity was linked to the chewing ability of the participant. Denture wearers exhibited a lower chewing ability, and at level 6, they perceived greater hardness of food than those with natural teeth. CONCLUSIONS: Developing food with a modified texture can bridge the gap between physiological and psychological aspects of food texture; texture-modified radish Kimchi, with limited blanching time, may be favorable for older people.

Surviving entanglement in optic-microwave conversion by an electro-optomechanical system.

In recent development of quantum technologies, a frequency conversion of quantum signals has been studied widely. We investigate the optic-microwave entanglement that is generated by applying an electro-optomechanical frequency conversion scheme to one mode in an optical two-mode squeezed vacuum state. We quantify entanglement of the converted two-mode Gaussian state, where surviving entanglement of the state is analyzed with respect to the parameters of the electro-optomechanical system. Furthermore, we show that there exists an upper bound for the entanglement that survives after the conversion of highly entangled optical states. Our study provides a theoretical platform for a practical quantum illumination system.

Elucidation of the reduced oil uptake of frying batters made from wheat and brown rice flour blends in terms of rheology and surface roughness.

BACKGROUND: Negative impressions toward fried foods are prevalent due to their high oil absorption and caloric values. A great deal of effort has been thus made to reduce the oil uptake of fried foods. In this study, the effect of wheat and brown rice flour blends on the oil uptake of frying batters was elucidated in terms of rheology and surface roughness. RESULTS: The blends with higher proportions of brown rice flour had higher values of pasting parameters and also exhibited a more elastic nature. When a food matrix was deep-fat-fried with frying batters made from wheat and brown rice flour blends, the oil uptake was significantly reduced by 28% compared to wheat flour batter. Based on imaging analysis, the surface properties of the fried crusts were quantitatively measured, demonstrating that the degree of surface roughness distinctly became lower with increasing levels of brown rice flour. Furthermore, the surface roughness parameters (Ra and Rq ) had a strong relationship with the reduced oil uptake. Also, a high proportion of brown rice flour in the blends produced fried samples with a firmer and crispy texture. CONCLUSIONS: A reduced oil uptake of batter-coated fried foods was distinctly observed with increasing levels of brown rice flour in the blends and well correlated with the degree of surface roughness (R2 > 0.85). © 2021 Society of Chemical Industry.

A Method to Compute the Schrieffer-Wolff Generator for Analysis of Quantum Memory.

Quantum illumination uses entangled light that consists of signal and idler modes to achieve higher detection rate of a low-reflective object in noisy environments. The best performance of quantum illumination can be achieved by measuring the returned signal mode together with the idler mode. Thus, it is necessary to prepare a quantum memory that can keep the idler mode ideal. To send a signal towards a long-distance target, entangled light in the microwave regime is used. There was a recent demonstration of a microwave quantum memory using microwave cavities coupled with a transmon qubit. We propose an ordering of bosonic operators to efficiently compute the Schrieffer-Wolff transformation generator to analyze the quantum memory. Our proposed method is applicable to a wide class of systems described by bosonic operators whose interaction part represents a definite number of transfer in quanta.

Effect of shortening replacement with oleogels on the rheological and tomographic characteristics of aerated baked goods.

BACKGROUND: A great deal of effort has been made to reduce the use of shortening owing to the high level of saturated fats as well as the presence of trans fats. Grape seed oil high in unsaturated fats was structured with candelilla wax to form solid-like oleogels that were utilized as a shortening replacer in aerated baked goods, specifically muffins. RESULTS: Muffin batters with greater amounts of oleogels exhibited lower viscosity, greater shear-thinning behavior and less elastic nature. The shortening replacement with oleogels significantly increased the specific gravity of the batters, consequently affecting the muffin volume after baking. X-ray tomography indicated a lower fragmentation index (i.e. a more connected solid structure) in the oleogel-incorporated muffins, which was correlated with more enclosed and isolated air cells. A stress relaxation test showed that the shortening replacement with oleogels produced muffins with a firmer and springier texture. Based on fatty acid compositions, the ratio of saturated to unsaturated fatty acids was significantly reduced from 2.81 to 0.41. CONCLUSION: Use of the oleogels as a shortening replacer at a ratio of 1:3 by weight was effective in producing muffins with comparable quality attributes to the control with shortening. © 2017 Society of Chemical Industry.

The establishment of efficient bioconversion, extraction, and isolation processes for the production of phyllodulcin, a potential high intensity sweetener, from sweet hydrangea leaves (Hydrangea macrophylla Thunbergii).

INTRODUCTION: Hydrangea leaf tea has been traditionally consumed in the far-east Asian countries and is favoured for its distinct minty-sweet taste. Phyllodulcin is identified as a key sweet-tasting compound; it is 400-800 times sweeter than sucrose. However, its extraction has not been well-documented. In an effort to optimise phyllodulcin production, pretreatment processes to accumulate phyllodulcin as a final metabolite in leaf tissue were studied, and an efficient process was established for the extraction and purification of phyllodulcin. METHODS: Phyllodulcin was structurally identified using an LC/MS system. Hydrangea leaves were processed by either hand rolling or mechanical blending, by exposing them at different drying temperatures (25 and 70°C), and even by inducing bioconversion in leaf tissue. The leaf powder was extracted with various solvents (methanol, ethanol, and water) by soaking at 25°C for 12 h, ultrasonication at 35°C for 1 h or accelerated solvent extraction (ASE). Extracts were purified with ion exchange resins and purified using preparative HPLC. RESULTS: Traditional hand rolling and drying at 70°C significantly increased phyllodulcin accumulation in the leaves. Meanwhile, more phyllodulcin was obtained from the leaves blended mechanically or converted enzymatically compared to traditionally processed ones (P < 0.05). Methanol and ethanol were superior to water as extraction media, and the greatest phyllodulcin yields obtained by ASE, soaking and ultrasonication were 21.28, 21.20 and 19.33 mg/g, respectively, when methanol was used. Highly pure phyllodulcin powder was obtained with a yield of 2.12%. CONCLUSIONS: This promising result would be beneficial to the industrial utilisation of phyllodulcin as a potential high-intensity sweetener.

Development of a gluten-free rice noodle by utilizing protein-polyphenol interaction between soy protein isolate and extract of Acanthopanax sessiliflorus.

BACKGROUND: The potential of the protein-polyphenol interaction was applied to crosslinking reinforced protein networks in gluten-free rice noodles. Specifically, inter-component interaction between soy protein isolate and extract of Acanthopanax sessiliflorus fruit (ogaja) was examined with a view to improving its quality. RESULTS: In a components-interacting model system, a mixture of soy protein isolate (SPI) and ogaja extract (OE) induced a drastic increase in absorbance at 660 nm by haze formation, while the major anthocyanin of ogaja, cyanidin-3-O-sambubioside, sparsely interacted with SPI or gelatin. Individual or combined treatment of SPI and OE on rice dough decreased all the viscosity parameters in rapid visco analysis. However, SPI-OE treatment significantly increased all the texture parameters of rice dough derived from Mixolab(®) analysis (P < 0.05). Incorporation of SPI in rice dough significantly reduced endothermic ΔH, and SPI-OE treatment further decreased this value. SPI-OE interaction significantly increased the tensile properties of cooked noodle and decreased 53.7% of cooking loss compared to the untreated rice noodle. CONCLUSION: SPI-OE treatment caused a considerable reinforcement of the network as shown by reducing cooking loss and suggested the potential for utilizing protein-polyphenol interaction for gluten-free rice noodle production.

Utilisation of preharvest dropped apple peels as a flour substitute for a lower glycaemic index and higher fibre cake.

Fibre-enriched materials (FEMs) obtained from preharvest dropped apple peels were utilised as a source of dietary fibre in baked cakes and their effects on the textural/nutritional qualities and starch digestibility (glucose release behaviour, starch digestion fraction, predicted glycaemic index) of the cakes were evaluated. When FEMs were incorporated into the cake formulation (3 g and 6 g of dietary fibre per serving (100 g)), the volume of the cakes seemed to be reduced and their texture become harder. However, 3 g of FEMs did not degrade the cake qualities. The use of FEMs in cakes significantly reduced the levels of rapidly digestible starch and slowly digestible starch, while the levels of resistant starch increased. Additionally, the cake samples prepared with FEMs exhibited a lower predicted glycaemic index. This study may give rise to multi-functional bakery products with acceptable quality and low glycaemic index.

Evaluation of wheat gluten hydrolysates as taste-active compounds with antioxidant activity.

Wheat gluten was subjected to enzymatic hydrolysis with various proteases (Alcalase, Flavourzyme, Protamex) and the taste-enhancing properties and antioxidant activities of the resulting wheat gluten hydrolysates (WGHs) were characterized. The contents of the hydrophobic amino acid of the WGHs were highly correlated with the degree of hydrolysis by Flavourzyme and Protamex, except Alcalase. The taste profiles of the Alcalase-treated WGHs showed decreased bitterness while umami and overall acceptability increased. On the other hand, the WGHs produced by Flavourzyme and Protamex showed increased bitterness with increasing hydrolysis duration. However, taste profiles, such as umami, kokumi, and overall acceptability of the WGHs by Flavourzyme and Protamex were unaffected by the degree of hydrolysis. The WGH treated by Alcalase for 24 h (A24h) exhibited taste-enhancing property and its antioxidant effects were concentration-dependent. As a result, the A24h may be used as a multi-functional seasoning ingredient having potential antioxidant activity.

Machine learning identification of edible vegetable oils from fatty acid compositions and hyperspectral images.

Hyperspectral imaging analysis combined with machine learning was applied to identify eight edible vegetable oils, and its classification performance was compared with the chemical method based on fatty acid compositions. Furthermore, the degree of adulteration in vegetable oils was quantitatively investigated using machine learning-enabled hyperspectral approaches. The hyperspectral absorbance spectra of palm oil with a high degree of saturation were distinctly different from those of the other liquid oils. The flaxseed and olive oils exhibited the dominant hyperspectral intensities at 1170/1671 and 1212/1415 nm, respectively. Linear discriminant analysis demonstrated that two linear discriminants could explain a significant portion of the total variability, accounting for 96.0% (fatty acid compositions) and 98.9% (hyperspectral images). When the hyperspectral results were used as datasets for three machine learning models (decision tree, random forest, and k-nearest neighbor), several instances to incorrectly classify grapeseed and sunflower oils were detected, while olive, palm, and flaxseed oils were successfully identified. The machine learning models showed a great classification performance that exceeded 98.9% from the hyperspectral images of the vegetable oils, which was comparable to the fatty acid composition-based chemical method in identifying edible vegetable oils. In addition, the random forest model was the most effective in ascertaining adulteration levels in binary oil blends (R2 > 0.992 and RMSE < 2.75).

Machine learning-enabled hyperspectral approaches for structural characterization of precooked noodles during refrigerated storage.

The structural features of precooked noodles during refrigerated storage were non-destructively characterized using hyperspectral imaging (HSI) technology along with conventional analytical methods. The precooked noodles displayed a more rigid texture and restricted water mobility over the storage period, derived from the recrystallization of starch. Dimensionality reduction techniques revealed robust correlations between the storage duration and HSI absorbance of the noodles, and from their loading plots, the specific peaks of the noodles related to their structural changes were identified at wavelengths of around 1160 and 1400 nm. The strong relationships between the HSI results of the noodles and their storage period/texture were confirmed by training four machine learning models on the HSI data. In particular, the support vector algorithm displayed the best prediction performance for classifying precooked noodles by storage period (98.3% accuracy) and for predicting the noodle texture (R2 = 0.914).

Effect of high pressure pretreatment on the inhibition of ice nucleation and biochemical changes in pork loins during supercooling preservation.

In this study, the effect of high pressure (HP) pretreatment on the stability of pork loins during supercooling (SC) preservation was investigated, and the freshness and postmortem metabolism of pork loins preserved by SC was evaluated. Based on the differential scanning calorimetry (DSC), the peak enthalpies of 200 MPa treatment were lower than those of 50 MPa treatment (P < 0.05). For the nuclear magnetic resonance (NMR) relaxometry, extramyofibrillar water in pork loins was decreased with increasing intermyofibrillar water at >100 MPa (P < 0.05). Compared to unpressurized control all HP treatment had less α-helix structure while random coil was dominated from the Fourier transform infrared (FTIR) spectroscopy (P < 0.05). A 200 MPa was selected to estimate the relationship between HP pretreatment and stability of SC preservation of pork loins. The HP-treated pork loins showed high stability during SC preservation under the relatively low temperature algorithm. Compared to fresh control, HP pretreatment caused physicochemical changes of pork loins which did not recover even after 2 weeks of preservation. Nevertheless, HP followed by SC preservation was able to reduce property changes better than pork loins preserved by normal refrigeration. According to the analyses of transmission electron microscopy (TEM), the HP pretreatment influenced the postmortem biochemical metabolism of pork loins, however, it did not affect the freshness and quality parameters of pork loins due to the subsequently applied low preservation temperature of SC. Therefore, this study demonstrated that moderate HP pretreatment was a potential pretreatment for SC preservation of pork loins.

Potentials of Ulva spp.-derived sulfated polysaccharides as gelling agents with promising therapeutic effects.

Ulvan, a sulfated polysaccharide extracted from Ulva spp., has garnered significant attention in the food and pharmaceutical industries due to its potential health benefits. These include immunomodulation, antiviral, anti-inflammatory, anti-hyperlipidemic, and anti-cancer effects. Nonetheless, practical applications in these fields remain limited due to an incomplete understanding of its gelation mechanisms. Additionally, the underlying mechanisms of its gelation have not been completely understood and thoroughly reviewed. The primary objective is to provide current insights into ulvan's gelling mechanisms and potential health impacts. This review also delves into the existing applications of ulvan polysaccharides. By unraveling these aspects, the information provided in this work is expected to deepen our understanding of ulvan's gelation mechanisms and its prospective role in enhancing health, holding promise for advancements in the fields of food science and disease prevention. This work's theoretical insights contribute significantly to a deeper understanding of these aspects, which holds paramount importance in unleashing the full potential of ulvan and elevating its scientific significance.

Distributed quantum sensing of multiple phases with fewer photons.

Distributed quantum metrology has drawn intense interest as it outperforms the optimal classical counterparts in estimating multiple distributed parameters. However, most schemes so far have required entangled resources consisting of photon numbers equal to or more than the parameter numbers, which is a fairly demanding requirement as the number of nodes increases. Here, we present a distributed quantum sensing scenario in which quantum-enhanced sensitivity can be achieved with fewer photons than the number of parameters. As an experimental demonstration, using a two-photon entangled state, we estimate four phases distributed 3 km away from the central node, resulting in a 2.2 dB sensitivity enhancement from the standard quantum limit. Our results show that the Heisenberg scaling can be achieved even when using fewer photons than the number of parameters. We believe our scheme will open a pathway to perform large-scale distributed quantum sensing with currently available entangled sources.

Preparation of dietary fibre-enriched materials from preharvest dropped apples and their utilisation as a high-fibre flour substitute.

BACKGROUND: Preharvest dropped apples from a weather disaster are generally discarded or used in animal feed due to reduced market value. In this study, they were utilised to produce dietary fibre-enriched materials (DFEMs) and their baking performance in a food system was then evaluated as a high-fibre and low-calorie flour substitute. RESULTS: Hydrothermal treatment and fractionation of preharvest dropped apple powder produced fibre-rich fractions (856.2 g kg(-1)). The use of DFEMs increased the pasting properties of wheat flour and improved dough mixing stability. When DFEMs were incorporated in the cookie formulation (2, 4 and 6 g dietary fibre per serving), the cookie dough exhibited increased elongational viscosity and solid-like behaviour which became more pronounced with increasing levels of DEFMs. After baking, reduced spread was observed in DFEM cookies which could be readily attributed to their rheological characteristics. However, greater moisture retention by DFEMs produced cookie samples with softer texture. CONCLUSION: DFEMs prepared from preharvest dropped apples could be successfully evaluated in a cookie model system as a high-fibre and low-calorie substitute for wheat flour. This study suggests a new value-added application of preharvest dropped fruits, positively extending their use for better healthful diets.