Combined effect of heat moisture and ultrasound treatment on the physicochemical, thermal and structural properties of new variety of purple rice starch.

The advantages of physically modifying starch are evident: minimal environmental impact, no by-products, and straightforward control. The impact of dual modification on starch properties is contingent upon modification conditions and starch type. Herein, we subjected purple rice starch (PRS) to heat-moisture treatment (HMT, 110 °C, 4 h) with varying moisture content, ultrasound treatment (UT, 50 Hz, 30 min) with different ultrasonic power, and a combination of HMT and UT. Our findings reveal that UT following HMT dispersed starch granules initially aggregated by HMT and resulted in a rougher granule surface. Rheological analysis showcased a synergistic effect of HMT and UT, enhancing the fluidity of PRS and reinforcing its resistance to deformation in paste form. The absorbance ratio R1047/1015 indicates that increased moisture content during HMT and high ultrasound power for UT reduced the short-range order degree (1.69). However, the combined HMT-UT exhibited an increased R1047/1015 (1.38-1.64) compared to HMT alone (1.29-1.45), likely due to short-chain rearrangement. Notably, the A-type structure of PRS remained unaltered, but overall crystallinity significantly decreased (23.01 %-28.56 %), consistent with DSC results. In summary, physical modifications exerted significant effects on PRS, shedding light on the mechanisms governing the transformation of structural properties during HMT-UT.

Purple rice starch in wheat: Effect on retrogradation dependent on addition amount.

While individual starch types may not possess the ideal gelatinization and retrogradation properties for specific applications, the amalgamation of multiple starch varieties might bestow desirable physicochemical properties upon resulting starch-based products. This study explored the impact of incorporating purple rice starch (PRS), as a novel starch variant (up to 15 % PRS), on the gelatinization and retrogradation (within 14 days) of regular wheat starch (WS). Rheological and texture assessments demonstrated that the introduction of PRS diminished the viscoelasticity and hardness of fresh WS paste. Additionally, in the case of retrograded WS pastes stored at 4 °C for 1-14 days, the incorporation of 10 % or 15 % PRS effectively retarded the reduction in transparency and significantly reduced hardness, retrogradation degree, the ratio of absorbance at 1047/1017 cm-1, and relative crystallinity. Notably, 10 % PRS results in a more pronounced effect. Conversely, 5 % PRS induced an opposing impact on retrograded WS post-storage. Moreover, scanning electron microscopy revealed that as the proportion of PRS increased, the microstructure of gelatinized WS-PRS closely resembled that of pure PRS. In conclusion, the diverse effects of varying PRS proportions on WS alter the texture and characteristics of starch-based foods, underscoring the potential of starch blending for improved applications.

Structure and physicochemical properties of a new variety of purple rice (Oryza sativa L. indica) starch.

The investigation of the structure and physicochemical properties of starch extracted from a new variety of purple rice was the aim of this study. Starch extracted from a new variety of purple rice named Tianzi No. 1 (PRS) is different in structure and physicochemical properties compared with waxy rice starch (WRS), japonica rice starch (JRS), and indica rice starch (IRS). PRS granules were diversified in shape, and the birefringence of starch particles were clearly observed. Fourier-transform infrared (FT-IR) spectroscopy exhibited the degree of double helix and low short-range order structure of PRS differed from IRS, JRS and WRS. X-ray diffraction analysis shows that PRS presented a typical A-type XRD pattern and possessed lower crystallinity. Based on rheological experiment results, PRS had the highest apparent viscosity, storage modulus (G') and loss modulus (G″). According to textural experiments, PRS gels had higher textural paraments before and after retrogradation. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-022-01205-w.

Profiling hearing aid users through big data explainable artificial intelligence techniques.

Debilitating hearing loss (HL) affects ~6% of the human population. Only 20% of the people in need of a hearing assistive device will eventually seek and acquire one. The number of people that are satisfied with their Hearing Aids (HAids) and continue using them in the long term is even lower. Understanding the personal, behavioral, environmental, or other factors that correlate with the optimal HAid fitting and with users' experience of HAids is a significant step in improving patient satisfaction and quality of life, while reducing societal and financial burden. In SMART BEAR we are addressing this need by making use of the capacity of modern HAids to provide dynamic logging of their operation and by combining this information with a big amount of information about the medical, environmental, and social context of each HAid user. We are studying hearing rehabilitation through a 12-month continuous monitoring of HL patients, collecting data, such as participants' demographics, audiometric and medical data, their cognitive and mental status, their habits, and preferences, through a set of medical devices and wearables, as well as through face-to-face and remote clinical assessments and fitting/fine-tuning sessions. Descriptive, AI-based analysis and assessment of the relationships between heterogeneous data and HL-related parameters will help clinical researchers to better understand the overall health profiles of HL patients, and to identify patterns or relations that may be proven essential for future clinical trials. In addition, the future state and behavioral (e.g., HAids Satisfiability and HAids usage) of the patients will be predicted with time-dependent machine learning models to assist the clinical researchers to decide on the nature of the interventions. Explainable Artificial Intelligence (XAI) techniques will be leveraged to better understand the factors that play a significant role in the success of a hearing rehabilitation program, constructing patient profiles. This paper is a conceptual one aiming to describe the upcoming data collection process and proposed framework for providing a comprehensive profile for patients with HL in the context of EU-funded SMART BEAR project. Such patient profiles can be invaluable in HL treatment as they can help to identify the characteristics making patients more prone to drop out and stop using their HAids, using their HAids sufficiently long during the day, and being more satisfied by their HAids experience. They can also help decrease the number of needed remote sessions with their Audiologist for counseling, and/or HAids fine tuning, or the number of manual changes of HAids program (as indication of poor sound quality and bad adaptation of HAids configuration to patients' real needs and daily challenges), leading to reduced healthcare cost.

High Fat Diet Aggravates AD-Related Pathogenic Processes in APP/PS1 Mice.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disorder and negative lifestyle factors may contribute to its etiopathogenesis. Substantial evidence from humans and murine models reveals that Insulin Resistance (IR) associated with a high fat diet (HFD) increases the risk of developing AD and age-related amyloidogenesis. OBJECTIVE: The aim of the study was to corroborate and clarify the influence of HFD on amyloidogenesis and cognitive deficits in AD model mice. METHODS: We here show that a four months HFD-feeding increases IR in both the periphery and brain of APP/PS1 mice, which are used as AD models. Meanwhile, long-term HFD exacerbates cognitive defects and impairs dendritic integrity and expressions of synaptic proteins in APP/PS1 mice. Furthermore, HFD induces an increase in ß-secretase (BACE1) expression and a decrease in insulin-degrading enzyme (IDE) expression, resulting in ß-amyloid (Aß) accumulation. CONCLUSION: Our data suggest that long-term HFD, with the accompanying IR, promotes Aß toxicity and cognitive deficits, indicating that modifiable lifestyle hazards such as HFD-induced IR might contribute to AD pathogenesis.