Shared decision making in sarcopenia treatment

The implementation of shared decision making (SDM) in management of sarcopenia is still in its nascent stage, especially compared to other areas of medical research. Accumulating evidence has highlighted the importance of SDM in older adults care. The current study overviews general SDM practices and explores the potential advantages and dilemmas of incorporating these concepts into sarcopenia management. We present common patient decision aids available for sarcopenia management and propose future research directions. SDM can be effectively integrated into daily practice with the aid of structured techniques, such as the “seek, help, assess, reach, evaluate” approach, “making good decisions in collaboration” questions, “benefits, risks, alternatives, doing nothing” tool, or “multifocal approach to sharing in shared decision making.” Such techniques fully consider patient values and preferences, thereby enhancing adherence to and satisfaction with the intervention measures. Additionally, we review the barriers to and potential solutions to SDM implementation. Further studies are required to investigate measurement and outcomes, coordination and cooperation, and digital technology, such as remote SDM. The study concludes that sarcopenia management must go beyond the single dimension of “Paternalism” choice. Integrating SDM into clinical practice offers promising opportunities to improve patient care, with patient-centered care and partnership of care approaches positively impacting treatment outcomes

Morphological and phylogenetic analyzes reveal two new species of Melanconiella from Fujian Province, China

IntroductionSpecies of Melanconiella include a diverse array of plant pathogens as well as endophytic fungi. Members of this genus have been frequently collected from the family Betulaceae (birches) in Europe and North America. Little, however, if known concerning the distribution of Melanconiella and/or their potential as pathogens of other plant hosts.MethodsFungi were noted and isolated from diseased leaves of Loropetalum chinense (Chinese fringe flower) and Camellia sinensis (tea) in Fujian Province, China. Genomic DNA was extracted from fungal isolates and the nucleotide sequences of four loci were determined and sued to construct phylogenetic trees. Morphological characteristics of fungal structures were determined via microscopic analyses.ResultsFour strains and two new species of Melanconiella were isolated from infected leaves of L. chinense and C. sinensis in Fujian Province, China. Based on morphology and a multi-gene phylogeny of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF1-α), Melanconiellaloropetali sp. nov. and Melanconiellacamelliae sp. nov. were identified and described herein. Detailed descriptions, illustrations, and a key to the known species of Melanconiella are provided.DiscussionThese data identify new species of Melanconiella, expanding the potential range and distribution of these dark septate fungi. The developed keys provide a reference source for further characterization of these fungi

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions

IntroductionUnderstanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province.MethodsA total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline.ResultsOur data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. β-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy.DiscussionOur findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors

Healthy Grocery Shopping Experience via Augmented Reality

This paper presents how augmented reality can facilitate the modern grocery shopping experience in a fast-paced environment. Grocery shopping customers are facing several problems. Firstly, filtering necessary information by eyes while shopping in grocery stores. Secondly, being distracted by overwhelming information leads to time-consuming deviation in an unfamiliar shopping environment. Thirdly, losing track of purchased food at home and buying the same ingredient repeatedly. Fourthly, neglecting ingredient lists that contain allergic or unhealthy food. To solve these problems, increase the efficiency of decision-making, and achieve shopping goals, this project aims to utilize augmented reality as the primary tool to complete a shopping list efficiently and demonstrate essential information end-to-end from navigation, comparing different products to the checkout stage. Augmented Reality (AR) applications have become more widely used in various aspects of lives worldwide. As it provides the ability to view the information in a three-dimensional space, users can understand complex concepts faster and more efficiently with highlighted animated information with readily available devices (e.g., smartphones, tablets) or futuristic wearable devices (e.g., HoloLens, Oculus). Usability testing, including online surveys and interviews, is planned to be conducted as the project\u27s next step to evaluate the effectiveness and ease of use of this visual design solution. The demo video can be viewed at Imagine RIT via the following link https://designed.cad.rit.edu/vcdthesis/project/iq_great?preview_id=10053&preview=tru

High-speed rail and stock return comovement in China

This study explores the impact of China’s high-speed rail network on reducing local bias and fostering capital market integration. Our research reveals that implementing high-speed rail in a city decreases the return comovement of its local stocks but increases its return comovement with the national stock market. Our results are robust and consistent across various model specifications. After examining the underlying economic mechanism, we find that the impact of high-speed rail on stock return comovement is stronger for small firms, non-state-owned enterprises (non-SOEs), firms with poor corporate governance, and firms’ headquarters in more segmented and less-developed regions. This effect did not change after controlling for other information-dissemination channels and regional economic development. Overall, geographical proximity contributes to information transfer and market efficiency

Dynamic Changes of Bacterial Communities and Microbial Association Networks in Ready-to-Eat Chicken Meat during Storage

Ready-to-eat (RTE) chicken is a popular food in China, but its lack of food safety due to bacterial contamination remains a concern, and the dynamic changes of microbial association networks during storage are not fully understood. This study investigated the impact of storage time and temperature on bacterial compositions and microbial association networks in RTE chicken using 16S rDNA high-throughput sequencing. The results show that the predominant phyla present in all samples were Proteobacteria and Firmicutes, and the most abundant genera were Weissella, Pseudomonas and Proteus. Increased storage time and temperature decreased the richness and diversity of the microorganisms of the bacterial communities. Higher storage temperatures impacted the bacterial community composition more significantly. Microbial interaction analyses showed 22 positive and 6 negative interactions at 4 °C, 30 positive and 12 negative interactions at 8 °C and 44 positive and 45 negative interactions at 22 °C, indicating an increase in the complexity of interaction networks with an increase in the storage temperature. Enterobacter dominated the interactions during storage at 4 and 22 °C, and Pseudomonas did so at 22 °C. Moreover, interactions between pathogenic and/or spoilage bacteria, such as those between Pseudomonas fragi and Weissella viridescens, Enterobacter unclassified and Proteus unclassified, or those between Enterobacteriaceae unclassified and W.viridescens, were observed. This study provides insight into the process involved in RTE meat spoilage and can aid in improving the quality and safety of RTE meat products to reduce outbreaks of foodborne illness

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia