High density lipoprotein promotes proliferation of adipose-derived stem cells via S1P1 receptor and Akt, ERK1/2 signal pathways

Introduction: Adipose-derived stem cells (ADSC) are non-hematopoietic mesenchymal stem cells that have shown great promise in their ability to differentiate into multiple cell lineages. Their ubiquitous nature and the ease of harvesting have attracted the attention of many researchers, and they pose as an ideal candidate for applications in regenerative medicine. Several reports have demonstrated that transplanting ADSC can promote repair of injured tissue and angiogenesis in animal models. Survival of these cells after transplant remains a key limiting factor for the success of ADSC transplantation. Circulating factors like High Density Lipoprotein (HDL) has been known to promote survival of other stems cells like bone marrow derived stem cells and endothelial progenitor cells, both by proliferation and by inhibiting cell apoptosis. The effect of HDL on transplanted adipose-derived stem cells in vivo is largely unknown. Methods: This study focused on exploring the effects of plasma HDL on ADSC and delineating the mechanisms involved in their proliferation after entering the bloodstream. Using the MTT and BrdU assays, we tested the effects of HDL on ADSC proliferation. We probed the downstream intracellular Akt and ERK1/2 signaling pathways and expression of cyclin proteins in ADSC using western blot. Results: Our study found that HDL promotes proliferation of ADSC, by binding to sphingosine-1-phosphate receptor-1(S1P1) on the cell membrane. This interaction led to activation of intracellular Akt and ERK1/2 signaling pathways, resulting in increased expression of cyclin D1 and cyclin E, and simultaneous reduction in expression of cyclin-dependent kinase inhibitors p21 and p27, therefore promoting cell cycle progression and cell proliferation. Conclusions: These studies raise the possibility that HDL may be a physiologic regulator of stem cells and increasing HDL concentrations may be valuable strategy to promote ADSC transplantation.'973' National ST Major Project [2011CB503900]; National Natural Science Foundation of China [81270321, 81170101, 81370235]; Natural Science Foundation of Beijing, China [7122106]SCI(E)[email protected]; [email protected]

Generation Mechanism of Belief in Conspiracy Theories: Three Explanations from Social Cognitive Perspective

Social psychology treats conspiracy theories as an ideological belief which is defined as people’s tendency to interpret major social and political events as powerful groups or individuals who secretly deliberately plan to achieve their intended purpose. Belief in conspiracy theories is not just about believing in a specific conspiracy theory, but a general belief in all kinds of conspiracy theories. The following two findings in previous studies are sufficient to prove this point: one is the strong correlation between beliefs about the conspiracy theories behind different events; the other is that people may simultaneously embrace contradictory conspiracy theories about the same event. These two findings also indicate that belief in conspiracy theories is an integral and coherent psychological structure, which can be included into the category of psychological research as an independent variable. The negative influence of conspiracy theories is greater than the positive influence has become the consensus of researchers. To make a reasonable intervention in belief in conspiracy theories, we must first clarify the mechanism it generates. Previous studies have attempted to explain why people choose to believe in conspiracy theories from different perspectives. The results of studies on the relationship between belief in conspiracy theories and the Big Five personality are often difficult to replicate, so it seems that belief in conspiracy theories cannot be simply described by the Big Five personality dimensions. From the perspective of motivation, cognitive motives of reducing cognitive uncertainty and understanding the external world, existential motives of avoiding external threats and enhancing the sense of control and security, social motives of maintaining the positive image of competence and morality of individuals and inner groups can induce individuals to generate belief in conspiracy theories. Compared with other research perspectives, the perspective of social cognition seems to better reflect the internal psychological process of forming an ideological belief. This paper mainly introduces three explanations for the emergence of individual’s belief in conspiracy theories from the perspective of social cognition. Illusory pattern perception leads to people's cognitive tendency to establish connections between unrelated events and even impose causal relationships to generate belief in conspiracy theories. Hypersensitive agency detection affects people to look for the agency in the environment, and even over-perceive and assume the agency, purpose and intention behind the event, thus generating belief in conspiracy theories. Projection s people to infer the thoughts and behaviors of others in the event based on their own understanding and knowledge, and project their self-perception of "I am willing to participate in this event" onto others, thus promoting the belief in conspiracy theories that "others really plotted this event”. Although these three factors have corresponding theoretical and empirical support and have certain explanatory power for the generation of belief in conspiracy theories, it is difficult to explain that any of them are independent of other psychological mechanisms and independently generate belief in conspiracy theories. In the future study, it is suggested to combine social cognition, motivation, personality and other research perspectives, attach importance to experimental design and vertical research, expand the group of subjects, broaden measurement methods, and carry out cross-perspective, interdisciplinary and cross-cultural in-depth and systematic research on the generation mechanism of belief in conspiracy theories

Conceptual and Methodological Framework for a Digital Identity and Life-Course Study

The Digital Identity and Life-Course Study (DIALCS) project seeks to set the conceptual, theoretical and methodological foundations for a longitudinal life-course study focused on perceptions of, attitudes to, and behaviours with digital identity technology. This longitudinal study will repeatedly record data from a cohort of participants over a period of time to detect changes in the way they perceive and engage with digital identity technologies. No research has previously examined the adoption and engagement with digital identity technologies over the life-course. Generating such data would be essential not only to better understand citizens’ perceptions, attitudes and behaviours towards digital identity, and how these change over time, but also to analyse the impact of emerging and future digital identity technologies in the way people perceive, feel and develop their ‘self’ identity in digital settings. The research design of this project is structured in three stages. First, we undertook a rapid evidence assessment of studies on digital identity over the life-course. This was done to identify common themes in the literature, and most importantly, to highlight important gaps in research, which our study will aim to address. Second, we completed a conceptual mapping exercise aimed at linking the most common key terms in psycho-social theories of ‘self’ and digital identity IT frameworks. This second stage allowed us to identify key constructs that form the core of digital identity, both in psycho-social and technology frameworks. Finally, we ran a series of consultation meetings with domain experts in digital identity and longitudinal research methods. This was done to reach expert consensus on the conceptual, theoretical and methodological foundations for a longitudinal cohort study of digital identity over the life-course. After completing all of these, the following top-level recommendations were reached: ● The study should, where possible, enable descriptive analysis of key terms included in digital identity IT frameworks, government policies, and psycho-social theories of ‘self’. ● The study should follow a longitudinal life-course research design. ● The sample size should be large enough to enable population-level estimates and anticipate common attrition issues. Participants will be recruited at the age of 10. ● The sampling approach should follow a stratified random sampling. ● The study should use a combination of computer-assisted telephone interviewing (CATI), computer-assisted personal interviewing (CAPI), and face-to-face interviewing. ● The questionnaire should have two parts: ‘general screening form’ and ‘digital identity form(s)’. ● The study should include measures of use of digital devices, digital access to various platforms, perceptions about digital identity technologies, digital literacy, parental control, experiences with digital technologies, and detailed follow-up questions about the various observed ‘digital identities’ of respondents. The impact of the DIALCS will be substantial for scholarly understanding of digital identity, as well as for industry and policy. From an academic perspective, recording longitudinal data on perceptions, attitudes and behaviours with digital identity, both quantitative and qualitative, will enable researchers to address vital questions such as “what drives digital ‘self’ identity over the life-course?”, “how do people construct their ‘self’ identity in cyberspace?”, “what drives people’s decisions to engage with certain digital identity technologies but not others?”, “what are people’s perceptions of security and privacy with respect to digital identity technologies (and how these affect the construction of digital identity)?”, and “what indicators represent use and experience of digital identity (e.g., interactions per pseudonym, pseudonym time-lived, etc.)?

Conceptual and Methodological Framework for a Digital Identity and Life-Course Study

The Digital Identity and Life-Course Study (DIALCS) project seeks to set the conceptual, theoretical and methodological foundations for a longitudinal life-course study focused on perceptions of, attitudes to, and behaviours with digital identity technology. This longitudinal study will repeatedly record data from a cohort of participants over a period of time to detect changes in the way they perceive and engage with digital identity technologies. No research has previously examined the adoption and engagement with digital identity technologies over the life-course. Generating such data would be essential not only to better understand citizens’ perceptions, attitudes and behaviours towards digital identity, and how these change over time, but also to analyse the impact of emerging and future digital identity technologies in the way people perceive, feel and develop their ‘self’ identity in digital settings. The research design of this project is structured in three stages. First, we undertook a rapid evidence assessment of studies on digital identity over the life-course. This was done to identify common themes in the literature, and most importantly, to highlight important gaps in research, which our study will aim to address. Second, we completed a conceptual mapping exercise aimed at linking the most common key terms in psycho-social theories of ‘self’ and digital identity IT frameworks. This second stage allowed us to identify key constructs that form the core of digital identity, both in psycho-social and technology frameworks. Finally, we ran a series of consultation meetings with domain experts in digital identity and longitudinal research methods. This was done to reach expert consensus on the conceptual, theoretical and methodological foundations for a longitudinal cohort study of digital identity over the life-course. After completing all of these, the following top-level recommendations were reached: ● The study should, where possible, enable descriptive analysis of key terms included in digital identity IT frameworks, government policies, and psycho-social theories of ‘self’. ● The study should follow a longitudinal life-course research design. ● The sample size should be large enough to enable population-level estimates and anticipate common attrition issues. Participants will be recruited at the age of 10. ● The sampling approach should follow a stratified random sampling. ● The study should use a combination of computer-assisted telephone interviewing (CATI), computer-assisted personal interviewing (CAPI), and face-to-face interviewing. ● The questionnaire should have two parts: ‘general screening form’ and ‘digital identity form(s)’. ● The study should include measures of use of digital devices, digital access to various platforms, perceptions about digital identity technologies, digital literacy, parental control, experiences with digital technologies, and detailed follow-up questions about the various observed ‘digital identities’ of respondents. The impact of the DIALCS will be substantial for scholarly understanding of digital identity, as well as for industry and policy. From an academic perspective, recording longitudinal data on perceptions, attitudes and behaviours with digital identity, both quantitative and qualitative, will enable researchers to address vital questions such as “what drives digital ‘self’ identity over the life-course?”, “how do people construct their ‘self’ identity in cyberspace?”, “what drives people’s decisions to engage with certain digital identity technologies but not others?”, “what are people’s perceptions of security and privacy with respect to digital identity technologies (and how these affect the construction of digital identity)?”, and “what indicators represent use and experience of digital identity (e.g., interactions per pseudonym, pseudonym time-lived, etc.)?

Why Existential Threats Increase Conspiracy Beliefs: Evidence for the Mediating Roles of Agency Detection and Pattern Perception

This research investigates the cognitive mechanisms linking health-related existential threats to conspiracy beliefs within a Chinese context. Study 1 (N = 199) demonstrated that the relationship between perceived existential threats and outgroup conspiracy beliefs is mediated by hypersensitive agency detection through an experimental manipulation involving a monkeypox virus threat. Studies 2a (N = 198) and 2b (N = 200) revealed that illusory pattern perception also mediates this relationship. In Study 3 (N = 278, using a manipulation of threatening information about genetically modified foods) and in Study 4 (N = 296, using information about Japan’s discharge of nuclear sewage), both hypersensitive agency detection and illusory pattern perception mediated this relationship. Additional mini-meta-analyses further corroborated these findings. We conclude that the effects of existential threats on outgroup conspiracy beliefs are mediated by hypersensitive agency detection and illusory pattern perception

Metabonomic Evaluation of ZHENG Differentiation and Treatment by Fuzhenghuayu Tablet in Hepatitis-B-Caused Cirrhosis

In Traditional Chinese Medicine (TCM), treatment based on ZHENG (also called TCM syndrome and pattern) differentiation has been applied for about 3 thousand years, while there are some difficulties to communicate with western medicine. In the present work, metabonomic methods were utilized to differentiate ZHENG types and evaluate the therapeutic efficiency of Fuzhenghuayu (FZHY) tablet in hepatitis-B-caused cirrhosis (HBC). Urine samples of 12 healthy volunteers (control group, CG) and 31 HBC patients (HBCG) were analyzed by gas chromatography mass spectrometry (GC/MS) and multivariate statistical analysis. The significantly changed metabolites between CG and HBCG were selected by PLS-DA loading plot analysis. Moreover, 4 ZHENGs were differentiated mutually, suggesting that there was urine metabolic material basis in ZHENG differentiation. The efficiency of FZHY tablet on subjects with spleen deficiency with dampness encumbrance syndrome (SDDES) and liver-kidney yin deficiency syndrome (LKYDS) was better than that of other syndromes. The efficiency of FZHY treatment based on ZHENG differentiation indicated that accurately ZHENG differentiating could guide the appropriate TCM treatment in HBC

Shoulder muscle activation pattern recognition based on sEMG and machine learning algorithms

BACKGROUND AND OBJECTIVE: Surface electromyography (sEMG) has been used for robotic rehabilitation engineering for volitional control of hand prostheses or elbow exoskeleton, however, using sEMG for volitional control of an upper limb exoskeleton has not been perfectly developed. The long-term goal of our study is to process shoulder muscle bio-electrical signals for rehabilitative robotic assistive device motion control. The purposes of this study included: 1) to test the feasibility of machine learning algorithms in shoulder motion pattern recognition using sEMG signals from shoulder and upper limb muscles, 2) to investigate the influence of motion speed, individual variability, EMG recording device, and the amount of EMG datasets on the shoulder motion pattern recognition accuracy. METHODS: A novel convolutional neural network (CNN) structure was constructed to process EMG signals from 12 muscles for the pattern recognition of upper arm motions including resting, drinking, backward-forward motion, and abduction motion. The accuracy of the CNN models for pattern recognition under different motion speeds, among individuals, and by EMG recording devices was statistically analyzed using ANOVA, GLM Univariate analysis, and Chi-square tests. The influence of EMG dataset number used for CNN model training on recognition accuracy was studied by gradually increasing dataset number until the highest accuracy was obtained. RESULTS: Results showed that the accuracy of the normal speed CNN model in motion pattern recognition was 97.57% for normal speed motions and 97.07% for fast speed motions. The accuracy of the cross-subjects CNN model in motion pattern recognition was 79.64%. The accuracy of the cross-device CNN model in motion pattern recognition was 88.93% for normal speed motion and 80.87% for mixed speed. There was a statistical difference in pattern recognition accuracy between different CNN models. CONCLUSION: The EMG signals of shoulder and upper arm muscles from the upper limb motions can be processed using CNN algorithms to recognize the identical motions of the upper limb including drinking, forward/backward, abduction, and resting. A simple CNN model trained by EMG datasets of a designated motion speed accurately detected the motion patterns of the same motion speed, yielding the highest accuracy compared with other mixed CNN models for various speeds of motion pattern recognition. Increase of the number of EMG datasets for CNN model training improved the pattern recognition accuracy

Cross-layer Attention Sharing for Large Language Models

As large language models (LLMs) evolve, the increase in model depth and parameter number leads to substantial redundancy. To enhance the efficiency of the attention mechanism, previous works primarily compress the KV cache or group attention heads, while largely overlooking redundancy between layers. Our comprehensive analyses across various LLMs show that highly similar attention patterns persist within most layers. It's intuitive to save the computation by sharing attention weights across layers. However, further analysis reveals two challenges: (1) Directly sharing the weight matrix without carefully rearranging the attention heads proves to be ineffective; (2) Shallow layers are vulnerable to small deviations in attention weights. Driven by these insights, we introduce LiSA, a lightweight substitute for self-attention in well-trained LLMs. LiSA employs tiny feed-forward networks to align attention heads between adjacent layers and low-rank matrices to approximate differences in layer-wise attention weights. Evaluations encompassing 13 typical benchmarks demonstrate that LiSA maintains high response quality in terms of accuracy and perplexity while reducing redundant attention calculations within 53-84% of the total layers. Our implementations of LiSA achieve a 6X compression of Q and K, with maximum throughput improvements of 19.5% for LLaMA3-8B and 32.3% for LLaMA2-7B.Comment: Working in proces