Determinants of sedentary behavior in community-dwelling older adults with type 2 diabetes based on the behavioral change wheel: a path analysis.

BACKGROUND: Sedentary behavior (SB) is deeply ingrained in the daily lives of community-dwelling older adults with type 2 diabetes mellitus (T2DM). However, the specific underlying mechanisms of the determinants associated with SB remain elusive. We aimed to explore the determinants of SB based on the behavior change wheel framework as well as a literature review. METHODS: This cross-sectional study recruited 489 community-dwelling older adults with T2DM in Jinan City, Shandong Province, China. Convenience sampling was used to select participants from relevant communities. This study used the Measure of Older Adults' Sedentary Time-T2DM, the Abbreviated-Neighborhood Environment Walkability Scale, the Social Support Rating Scale, the Lubben Social Network Scale 6, the Subjective Social Norms Questionnaire for Sedentary Behavior, the Functional Activities Questionnaire, the Numerical Rating Scale, the Short Physical Performance Battery, and the Montreal Cognitive Assessment Text to assess the levels of and the determinants of SB. Descriptive statistical analysis and path analysis were conducted to analyze and interpret the data. RESULTS: Pain, cognitive function, social isolation, and social support had direct and indirect effects on SB in community-dwelling older adults with T2DM (total effects: ß = 0.426, ß = -0.171, ß = -0.209, and ß = -0.128, respectively), and physical function, walking environment, and social function had direct effects on patients' SB (total effects: ß = -0.180, ß = -0.163, and ß = 0.127, respectively). All the above pathways were statistically significant (P < 0.05). The path analysis showed that the model had acceptable fit indices: RMSEA = 0.014, χ 2/df = 1.100, GFI = 0.999, AGFI = 0.980, NFI = 0.997, RFI = 0.954, IFI = 1.000, TLI = 0.996, CFI = 1.000. CONCLUSION: Capability (physical function, pain, and cognitive function), opportunity (social isolation, walking environment, and social support), and motivation (social function) were effective predictors of SB in community-dwelling older adults with T2DM. Deeper knowledge regarding these associations may help healthcare providers design targeted intervention strategies to decrease levels of SB in this specific population.

Online continual decoding of streaming EEG signal with a balanced and informative memory buffer.

Electroencephalography (EEG) based Brain Computer Interface (BCI) systems play a significant role in facilitating how individuals with neurological impairments effectively interact with their environment. In real world applications of BCI system for clinical assistance and rehabilitation training, the EEG classifier often needs to learn on sequentially arriving subjects in an online manner. As patterns of EEG signals can be significantly different for different subjects, the EEG classifier can easily erase knowledge of learnt subjects after learning on later ones as it performs decoding in online streaming scenario, namely catastrophic forgetting. In this work, we tackle this problem with a memory-based approach, which considers the following conditions: (1) subjects arrive sequentially in an online manner, with no large scale dataset available for joint training beforehand, (2) data volume from the different subjects could be imbalanced, (3) decoding difficulty of the sequential streaming signal vary, (4) continual classification for a long time is required. This online sequential EEG decoding problem is more challenging than classic cross subject EEG decoding as there is no large-scale training data from the different subjects available beforehand. The proposed model keeps a small balanced memory buffer during sequential learning, with memory data dynamically selected based on joint consideration of data volume and informativeness. Furthermore, for the more general scenarios where subject identity is unknown to the EEG decoder, aka. subject agnostic scenario, we propose a kernel based subject shift detection method that identifies underlying subject changes on the fly in a computationally efficient manner. We develop challenging benchmarks of streaming EEG data from sequentially arriving subjects with both balanced and imbalanced data volumes, and performed extensive experiments with a detailed ablation study on the proposed model. The results show the effectiveness of our proposed approach, enabling the decoder to maintain performance on all previously seen subjects over a long period of sequential decoding. The model demonstrates the potential for real-world applications.

"All about the value?" Decisional needs of breast reconstruction for breast cancer patients in the Chinese context: A mixed-methods study.

OBJECTIVE: To explore breast cancer (BC) patients' participation in breast reconstruction (BR) decision-making and specific decisional needs, especially the manifestations and causes of decisional conflicts, in China. METHODS: A mixed-methods study was conducted using triangulation of data from interviews and a questionnaire survey with health care professionals (HCPs) and BC patients with BR decision-making experience at 5 Beijing centers. The Ottawa Decision Support Framework guided (ODSF) the qualitative and quantitative data analyses. RESULTS: A total of 82.53% of Chinese BC patients would consider BR. Seven themes captured patients' BR decisional needs per the ODSF: inadequate support/resources (100%, 58.82%) and knowledge (75%, 52.94%) were most frequently cited. Health beliefs (unclear values) reflected Chinese characteristics. Patients had inadequate knowledge (M=19.99/50, SD=8.67) but positive BR attitudes (M=59.48/95, SD=10.45). CONCLUSIONS: BR decisions for Chinese BC patients are complex and often accompanied by decisional conflicts. Inadequate knowledge and inadequate support and resources contribute to these conflicts, emphasizing the need for culturally tailored information and support to promote SDM. PRACTICE IMPLICATIONS: HCPs need specialized training in SDM to guide patients in decision-making. It is essential to provide relevant resources and support that are culturally and clinically appropriate for Chinese patients.

Shared decision-making in healthcare in mainland China: a scoping review.

Background: Shared decision-making (SDM) facilitates the participation of healthcare professionals and patients in treatment decisions. We conducted a scoping review to assess SDM's current status in mainland China, referencing the Ottawa Decision Support Framework (ODSF). Methods: Our review encompassed extensive searches across six English and four Chinese databases, and various gray literature until April 30, 2021. Results were synthesized using thematic analysis. Results: Out of the 60 included studies, we identified three key themes based on the ODSF framework: decisional needs, decision support, and decisional outcomes. However, there appears to be a lack of comprehensive understanding of concepts related to decisional needs in China. Only a few studies have delved into feasibility, preference, choice, and outcome factors in the SDM process. Another challenge emerges from an absence of uniform standards for developing patient decision aids (PDAs). Furthermore, regarding health outcome indicators, their predominant focus remains on physiological needs. Conclusion: SDM is in its infancy in mainland China. It is important to explore the concept and expression of decisional needs in the context of Chinese culture. Subsequent studies should focus on constructing a scientifically rigorous and systematic approach for the development of PDAs, and considering the adaptation of SDM steps to the clinical context in China during SDM implementation. Concurrently, The focus on health outcomes in Chinese SDM studies, driven by the unique healthcare resource landscape, underscores the necessity of prioritizing basic needs within limited resources. Systematic review registration: https://inplasy.com/?s=202130021.

Understanding the Configurational Entropy Evolution in Metal-Phosphorus Solid Solution for Highly Reversible Li-Ion Batteries.

The high-entropy materials (HEM) have attracted increasing attention in catalysis and energy storage due to their large configurational entropy and multiunique properties. However, it is failed in alloying-type anode due to their Li-inactive transition-metal compositions. Herein, inspired by high-entropy concept, the Li-active elements instead of transition-metal ones are introduced for metal-phosphorus synthesis. Interestingly, a new Znx Gey Cuz Siw P2 solid solution is successfully synthesized as proof of concept, which is first verified to cubic system in F-43m. More specially, such Znx Gey Cuz Siw P2 possesses wide-range tunable region from 9911 to 4466, in which the Zn0.5 Ge0.5 Cu0.5 Si0.5 P2 accounts for the highest configurational entropy. When served as anode, Znx Gey Cuz Siw P2 delivers large capacity (>1500 mAh g-1 ) and suitable plateau (≈0.5 V) for energy storage, breaking the conventional view that HEM is helpless for alloying anode due to its transition-metal compositions. Among them, the Zn0.5 Ge0.5 Cu0.5 Si0.5 P2 exhibits the highest initial coulombic efficiency (ICE) (93%), Li-diffusivity (1.11 × 10-10 ), lowest volume-expansion (34.5%), and best rate performances (551 mAh g-1 at 6400 mA g-1 ) owing to its largest configurational entropy. Possible mechanism reveals the high entropy stabilization enables good accommodation of volume change and fast electronic transportation, thus supporting superior cyclability and rate performances. This large configurational entropy strategy in metal-phosphorus solid solution may open new avenues to develop other high-entropy materials for advanced energy storage.

Advances and Perspectives of Transgenic Technology and Biotechnological Application in Forest Trees.

Transgenic technology is increasingly used in forest-tree breeding to overcome the disadvantages of traditional breeding methods, such as a long breeding cycle, complex cultivation environment, and complicated procedures. By introducing exogenous DNA, genes tightly related or contributed to ideal traits-including insect, disease, and herbicide resistance-were transferred into diverse forest trees, and genetically modified (GM) trees including poplars were cultivated. It is beneficial to develop new varieties of GM trees of high quality and promote the genetic improvement of forests. However, the low transformation efficiency has hampered the cultivation of GM trees and the identification of the molecular genetic mechanism in forest trees compared to annual herbaceous plants such as Oryza sativa. In this study, we reviewed advances in transgenic technology of forest trees, including the principles, advantages and disadvantages of diverse genetic transformation methods, and their application for trait improvement. The review provides insight into the establishment and improvement of genetic transformation systems for forest tree species. Challenges and perspectives pertaining to the genetic transformation of forest trees are also discussed.

Metabolomics and Transcriptomics Integration of Early Response of Populus tomentosa to Reduced Nitrogen Availability.

Nitrogen (N) is one of the most crucial elements for plant growth and development. However, little is known about the metabolic regulation of trees under conditions of N deficiency. In this investigation, gas chromatography-mass spectrometry (GC-MS) was used to determine global changes in metabolites and regulatory pathways in Populus tomentosa. Thirty metabolites were found to be changed significantly under conditions of low-N stress. N deficiency resulted in increased levels of carbohydrates and decreases in amino acids and some alcohols, as well as some secondary metabolites. Furthermore, an RNA-sequencing (RNA-Seq) analysis was performed to characterize the transcriptomic profiles, and 1,662 differentially expressed genes were identified in P. tomentosa. Intriguingly, four pathways related to carbohydrate metabolism were enriched. Genes involved in the gibberellic acid and indole-3-acetic acid pathways were found to be responsive to low-N stress, and the contents of hormones were then validated by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Coordinated metabolomics and transcriptomics analysis revealed a pattern of co-expression of five pairs of metabolites and unigenes. Overall, our investigation showed that metabolism directly related to N deficiency was depressed, while some components of energy metabolism were increased. These observations provided insights into the metabolic and molecular mechanisms underlying the interactions of N and carbon in poplar.

Identification and validation of miRNA reference genes in poplar under pathogen stress.

Quantitative real time polymerase chain reaction (qRT-PCR) is a common method to analyze gene expression. Due to differences in RNA quantity, quality, and reverse transcription efficiency between qRT-PCR samples, reference genes are used as internal standards to normalize gene expression. However, few universal genes, especially miRNAs, have been identified as reference so far. Therefore, it is essential to identify reference genes that can be used across various experimental conditions, stress treatments, or tissues. In this study, 14 microRNAs (miRNAs) and 5.8S rRNA were assessed for expression stability in poplar trees infected with canker pathogen. Using geNorm, NormFinder and Bestkeeper reference gene analysis programs, we found that miR156g and miR156a exhibited stable expression throughout the infection process. miR156g, miR156a and 5.8S rRNA were then tested as internal standards to measure the expression of miR1447 and miR171c, and the results were compared to small RNA sequencing (RNA-seq) data. We found that when miR156a and 5.8S rRNA were used as the reference gene, the expression of miR1447 and miR171c were consistent with the small RNA-seq expression profiles. Therefore, miR156a was the most stable miRNAs examined in this study, and could be used as a reference gene in poplar under canker pathogen stress, which should enable comprehensive comparisons of miRNAs expression and avoid the bias caused by different length between detected miRNAs and traditional reference genes. The present study has expanded the miRNA reference genes available for gene expression studies in trees under biotic stress.