Consumer Food Choices as a Reflection of Concerns about Nutritional Attributes

Economic growth changed household food consumption patterns in the Republic of Korea. Consumer survey data were used to identify concerns about fat, saturated fat, sodium, sugar, calories and protein consumption. Results showed income, age, household size and the geographic location significantly influenced consumer concerns with regard to these nutritional attributes.Consumer/Household Economics,

Differing Expectations for Corporate Moral Responsibility: A Product Category Analysis

The moral responsibility theory of corporate sustainability (MRCS) argues that according to the concept of corporate personhood, a corporation has moral responsibilities toward society and the environment, and can determine its level of commitment to meet those responsibilities (Ha-Brookshire, 2015). Using the MRCS theory, Jung and Ha-Brookshire (2017) attempted to empirically demonstrate U.S. consumers’ perceptions on a variety of corporate moral responsibility activities performed by consumer product companies, to determine whether each activity is a perfect or imperfect duty. Therefore, this exploratory study raised the following research question: What are the differences in consumers’ expectations toward corporate moral responsibility, from perfect, imperfect, or no duty, for various sustainability activities carried out by different consumer product companies? With 4,000 invitations, 1,046 complete responses were returned and analyzed (26.15% of response rate). U.S. consumers believe working conditions support to be a firm’s most important responsibility to fulfill. At the same time, transparency had the lowest mean, suggesting it is viewed as something good to do but not a necessary duty to fulfill all the time. Consumer responses to clothing and food product companies were fairly similar to each other, potentially rejecting our assumption that there are different expectations for these products. Further research is recommended to investigate consumer expectations for sustainability in diverse product categories in relation to their intimacy to consumers and/or perceived health risks

Introduction to Large Language Models (LLMs) for dementia care and research

Introduction: Dementia is a progressive neurodegenerative disorder that affects cognitive abilities including memory, reasoning, and communication skills, leading to gradual decline in daily activities and social engagement. In light of the recent advent of Large Language Models (LLMs) such as ChatGPT, this paper aims to thoroughly analyse their potential applications and usefulness in dementia care and research. Method: To this end, we offer an introduction into LLMs, outlining the key features, capabilities, limitations, potential risks, and practical considerations for deployment as easy-to-use software (e.g., smartphone apps). We then explore various domains related to dementia, identifying opportunities for LLMs to enhance understanding, diagnostics, and treatment, with a broader emphasis on improving patient care. For each domain, the specific contributions of LLMs are examined, such as their ability to engage users in meaningful conversations, deliver personalized support, and offer cognitive enrichment. Potential benefits encompass improved social interaction, enhanced cognitive functioning, increased emotional well-being, and reduced caregiver burden. The deployment of LLMs in caregiving frameworks also raises a number of concerns and considerations. These include privacy and safety concerns, the need for empirical validation, user-centered design, adaptation to the user's unique needs, and the integration of multimodal inputs to create more immersive and personalized experiences. Additionally, ethical guidelines and privacy protocols must be established to ensure responsible and ethical deployment of LLMs. Results: We report the results on a questionnaire filled in by people with dementia (PwD) and their supporters wherein we surveyed the usefulness of different application scenarios of LLMs as well as the features that LLM-powered apps should have. Both PwD and supporters were largely positive regarding the prospect of LLMs in care, although concerns were raised regarding bias, data privacy and transparency. Discussion: Overall, this review corroborates the promising utilization of LLMs to positively impact dementia care by boosting cognitive abilities, enriching social interaction, and supporting caregivers. The findings underscore the importance of further research and development in this field to fully harness the benefits of LLMs and maximize their potential for improving the lives of individuals living with dementia

Process Algebraic Approach to the Schedulability Analysis and Workload Abstraction of Hierarchical Real-Time Systems

Real-time embedded systems have increased in complexity. As microprocessors become more powerful, the software complexity of real-time embedded systems has increased steadily. The requirements for increased functionality and adaptability make the development of real-time embedded software complex and error-prone. Component-based design has been widely accepted as a compositional approach to facilitate the design of complex systems. It provides a means for decomposing a complex system into simpler subsystems and composing the subsystems in a hierarchical manner. A system composed of real-time subsystems with hierarchy is called a hierarchical real-time system This paper describes a process algebraic approach to schedulability analysis of hierarchical real-time systems. To facilitate modeling and analyzing hierarchical real-time systems, we conservatively extend an existing process algebraic theory based on ACSR-VP (Algebra of Communicating Shared Resources with Value-Passing) for the schedulability of real-time systems. We explain a method to model a resource model in ACSR-VP which may be partitioned for a subsystem. We also introduce schedulability relation to define the schedulability of hierarchical real-time systems and show that satisfaction checking of the relation is reducible to deadlock checking in ACSR-VP and can be done automatically by the tool support of ERSA (Verification, Execution and Rewrite System for ACSR). With the schedulability relation, we present algorithms for abstracting real-time system workloads

Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic

In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using the assimilated AOD based on the linear relationship between the particulate matters and AODs. In comparison to the MODIS observation, the assimilated AOD was much improved compared with the modeled AOD (e.g., increase in correlation coefficients from −0.15–0.26 to 0.17–0.76 over the Arctic). The newly inferred monthly averages of PM10 and PM2.5 for April–September 2008 were 2.18–3.70 μg m−3 and 0.85–1.68 μg m−3 over the Arctic, respectively. These corresponded to an increase of 140–180%, compared with the modeled PMs. In comparison to in-situ observation, the inferred PMs showed better performances than those from the simulations, particularly at Hyytiala station. Therefore, combining the model simulation and data assimilation provided more accurate concentrations of AOD, PM10, and PM2.5 than those only calculated from the model simulations

Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic

In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using the assimilated AOD based on the linear relationship between the particulate matters and AODs. In comparison to the MODIS observation, the assimilated AOD was much improved compared with the modeled AOD (e.g., increase in correlation coefficients from −0.15–0.26 to 0.17–0.76 over the Arctic). The newly inferred monthly averages of PM10 and PM2.5 for April–September 2008 were 2.18–3.70 μg m−3 and 0.85–1.68 μg m−3 over the Arctic, respectively. These corresponded to an increase of 140–180%, compared with the modeled PMs. In comparison to in-situ observation, the inferred PMs showed better performances than those from the simulations, particularly at Hyytiala station. Therefore, combining the model simulation and data assimilation provided more accurate concentrations of AOD, PM10, and PM2.5 than those only calculated from the model simulations

Janus-faced Sestrin2 controls ROS and mTOR signalling through two separate functional domains

Sestrins are stress-inducible metabolic regulators with two seemingly unrelated but physiologically important functions: reduction of reactive oxygen species (ROS) and inhibition of the mechanistic target of rapamycin complex 1 (mTORC1). How Sestrins fulfil this dual role has remained elusive so far. Here we report the crystal structure of human Sestrin2 (hSesn2), and show that hSesn2 is twofold pseudo-symmetric with two globular subdomains, which are structurally similar but functionally distinct from each other. While the N-terminal domain (Sesn-A) reduces alkylhydroperoxide radicals through its helix–turn–helix oxidoreductase motif, the C-terminal domain (Sesn-C) modified this motif to accommodate physical interaction with GATOR2 and subsequent inhibition of mTORC1. These findings clarify the molecular mechanism of how Sestrins can attenuate degenerative processes such as aging and diabetes by acting as a simultaneous inhibitor of ROS accumulation and mTORC1 activation

Treatment with a Catalytic Superoxide Dismutase (SOD) Mimetic Improves Liver Steatosis, Insulin Sensitivity, and Inflammation in Obesity-Induced Type 2 Diabetes

Oxidative stress and persistent inflammation are exaggerated through chronic over-nutrition and a sedentary lifestyle, resulting in insulin resistance. In type 2 diabetes (T2D), impaired insulin signaling leads to hyperglycemia and long-term complications, including metabolic liver dysfunction, resulting in non-alcoholic fatty liver disease (NAFLD). The manganese metalloporphyrin superoxide dismustase (SOD) mimetic, manganese (III) meso-tetrakis (N-ethylpyridinium-2-yl) porphyrin (MnP), is an oxidoreductase known to scavenge reactive oxygen species (ROS) and decrease pro-inflammatory cytokine production, by inhibiting nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation. We hypothesized that targeting oxidative stress-induced inflammation with MnP would assuage liver complications and enhance insulin sensitivity and glucose tolerance in a high-fat diet (HFD)-induced mouse model of T2D. During 12 weeks of feeding, we saw significant improvements in weight, hepatic steatosis, and biomarkers of liver dysfunction with redox modulation by MnP treatment in HFD-fed mice. Additionally, MnP treatment improved insulin sensitivity and glucose tolerance, while reducing serum insulin and leptin levels. We attribute these effects to redox modulation and inhibition of hepatic NF-κB activation, resulting in diminished ROS and pro-inflammatory cytokine production. This study highlights the importance of controlling oxidative stress and secondary inflammation in obesity-mediated insulin resistance and T2D. Our data confirm the role of NF-κB-mediated inflammation in the development of T2D, and demonstrate the efficacy of MnP in preventing the progression to disease by specifically improving liver pathology and hepatic insulin resistance in obesit

The telomere maintenance mechanism spectrum and its dynamics in gliomas

Background : The activation of the telomere maintenance mechanism (TMM) is one of the critical drivers of cancer cell immortality. In gliomas, TERT expression and TERT promoter mutation are considered to reliably indicate telomerase activation, while ATRX mutation and/or loss indicates an alternative lengthening of telomeres (ALT). However, these relationships have not been extensively validated in tumor tissues. Methods : Telomerase repeated amplification protocol (TRAP) and C-circle assays were used to profile and characterize the TMM cross-sectionally (n = 412) and temporally (n = 133) across glioma samples. WES, RNA-seq, and NanoString analyses were performed to identify and validate the genetic characteristics of the TMM groups. Results : We show through the direct measurement of telomerase activity and ALT in a large set of glioma samples that the TMM in glioma cannot be defined solely by the combination of telomerase activity and ALT, regardless of TERT expression, TERT promoter mutation, and ATRX loss. Moreover, we observed that a considerable proportion of gliomas lacked both telomerase activity and ALT. This telomerase activation-negative and ALT negative group exhibited evidence of slow growth potential. By analyzing a set of longitudinal samples from a separate cohort of glioma patients, we discovered that the TMM is not fixed and can change with glioma progression. Conclusions : This study suggests that the TMM is dynamic and reflects the plasticity and oncogenicity of tumor cells. Direct measurement of telomerase enzyme activity and evidence of ALT should be considered when defining TMM. An accurate understanding of the TMM in glioma is expected to provide important information for establishing cancer management strategies.This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF), funded by the Ministry of Science & ICT (NRF-2018M3A9H3021707), and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI21C0239)