GraphicalPatients with early- to middle-stage PD were enrolled for C-Gait assessment and traditional walking ability assessments. The correlation of C-Gait assessment and traditional walking tests were studied. Two models were established based on C-Gait assessment and traditional walking tests to explore the value of C-Gait assessment in predicting freezing of gait.ObjectiveEfficient methods for assessing walking adaptability in individuals with Parkinson’s disease are urgently needed. Therefore, this study aimed to assess C-Gait for detecting freezing of gait in patients with early- to (...) middle-stage PD.MethodPeople with PD diagnosis were recruited from April 2019 to November 2019 in Beijing Rehabilitation Hospital. The participants performed six items of walking adaptability on an instrumented treadmill augmented with visual targets and obstacles. The patient’s walking adaptability was evaluated by C-Gait assessment and traditional walking tests, and FOG-related indexes were collected as outcome measures. Two discriminant models were established by stepwise discriminant analysis; area under the receiver operating characteristic curve was used to validate the models.ResultIn total, 53 patients were included in this study. Most C-Gait assessment items had no or low correlations with traditional walking tests. The obstacle avoidance and speed of adaptation items could lead to FOG with high sensitivity. In addition, the C-Gait assessment model had slightly better discrimination of freezers from non-freezers compared with traditional walking test models ; specifically, obstacle avoidance and speed of adaptation have uniquely discriminant potential.ConclusionC-gait assessment could provide additional value to the traditional walking tests for PD. Gait adaptability assessment, as measured by C-Gait, may be able to help identify freezers in a PD population. (shrink)

With the rapid development of Internet of Things technology, RFID technology has been widely used in various fields. In order to optimize the RFID system hardware deployment strategy and improve the deployment efficiency, the prediction of the RFID system identification rate has become a new challenge. In this paper, a neighborhood rough set and random forest combination model is proposed to predict the identification rate of an RFID system. Firstly, the initial influencing factors of the RFID system identification rate are (...) reduced using neighborhood rough set theory combined with the principle of heuristic attribute reduction of neighborhood weighted dependency, thus obtaining a kernel factor subset. Secondly, a random forest prediction model is established based on the kernel factor subset, and a confusion matrix is established using out-of-bag data to evaluate the prediction results. The test is conducted under the constructed RFID experimental environment, whose results showed that the model can predict the identification rate of the RFID system in a fast and efficient way, and the classification accuracy can reach 90.5%. It can effectively guide the hardware deployment and communication parameter protocol setting of the system and improve the system performance. Compared with BP neural network and other prediction models, NRS-RF has shorter prediction time and faster calculation speed. Finally, the validity of the proposed model was verified by the RFID intelligent archives management platform. (shrink)

Ben shu yi Ming ru Li Cai de jiang xue huo dong yu xue pai jian gou wei zhong xin, tan tao cong shi liu shi ji chu dao shi qi shi ji mo li xue qun ti zhong xin xing xue shuo he xue pai de chan sheng, chuan bo, kuo zhan yu chuan cheng de mo shi, bing zhuo zhong cong si xiang shi de jiao du jie shi zhe zhong mo shi chan sheng he yun xing de (...) si xiang gen yuan yu nei zai dong li. Quan shu zheng wen gong qi zhang, zhu yao nei rong fen wei shang xia liang bian, shang bian yi hong guan zong lun de fang shi, cong li xue jing dian "Da xue" de wen ben bian dong he quan shi jing zheng qie ru, tan tao zhong wan Ming li xue xue shuo he xue pai jian gou de li lun gen ju; xia bian yi Li Cai de "zhi xiu" xue shuo ji qi jiang xue huo dong zuo wei ge an yan jiu, tan tao li xue xue shuo he xue pai de chuan bo ji chuan cheng de she hui hua tu jing. (shrink)

The results of the National Higher Education Entrance Examination have a life-long effect on most Chinese by labeling them clever or not. Some of the following rules of the Gaokao enhance the damage, for example, the rule of Who, What and Where. In general, Who you are and What you have done are of secondary importance, but Where you graduated from, especially the college of first-record is the most important, but discriminatory criterion in the recruitment courses of most of scientific (...) communities and social organizations in China. (shrink)

BackgroundNurses working in the intensive care unit clung tenaciously to their job during the COVID-19 pandemic in spite of enduring stressed psychological and physical effects as a result of providing nursing care for the infected patients, which indicates that they possessed a high degree of professionalism and career calling. The aim of this study was to explain the associations between resilience, thriving at work, and ethical leadership influencing the calling of ICU nurses.MethodsFrom December 2020 to January 2021 during the COVID-19 (...) pandemic, a cross-sectional survey of 15 provinces in China was conducted using an online questionnaire. A total of 340 ICU nurses completed sufficient responses to be used in the study. Sociodemographic factors, job demographic factors, resilience, calling, thriving at work, and ethical leadership were assessed using the questionnaire. General linear modeling, hierarchical linear regression analysis, and generalized additive model were performed to examine all the considered research hypotheses.ResultsResilience was positively and significantly associated with calling. Moreover, thriving at work partially mediated the relationship between resilience and calling. The indirect effect of resilience on calling was 0.204, and the direct effect of resilience on calling through thriving at work was 0.215. The total effect of resilience on calling was 0.419. In addition, ethical leadership played a moderating role in the relationship between resilience and calling.ConclusionGreater resilience can positively predict increased calling among Chinese ICU nurses during the COVID-19 pandemic. Moreover, thriving at work is a mechanism that partly transmits the positive effects of resilience on calling. Overall, nurses possessing greater resilience tend to maintain thriving at work in the face of such adversity, further resulting in subsequently increased calling. Besides, findings suggest that there is stronger influence of resilience on calling among nurses working in an organization managed by an ethical leader. The current findings may offer two insights for nursing practitioners and policymakers in the postpandemic world. First, resilience training and intervention are necessary to foster nurses' sense of thriving at work in the nursing industry, further promoting career calling. Second, better training and effort on the development of ethical leadership for leaders in nursing practice are essential to encourage followers to engage in social learning of ethical behaviors and abiding by normatively appropriate conduct, further enacting prosocial values and expressing moral emotions. (shrink)

ObjectiveThe study aimed to enhance the learning motivation of college physical education students and improve their learning outcomes. Based on the perspective of the self-determination theory, this study explores the influence of “Small Private Online Course + flipped classroom” teaching on the learning motivation of students majoring in physical education and profoundly analyzes the influencing factors and promotion paths of learning motivation using this model.Materials and methodsA total of four classes of physical education majors in a university were selected and (...) randomly divided into an experimental group and a control group. The experimental group received “SPOC + flipped classroom” teaching, the control group received traditional teaching. Before and after the 16-week intervention, learning motivation, teacher support perception, basic psychological need satisfaction, and academic emotions of the 64 students were measured, and the data were analyzed by repeated-measures analysis of variance and partial least square regression.Results The instructional intervention reduced non-regulation, external regulation, and introjected regulation, while increased identified regulation, intrinsic regulation, and self-determination levels in the students. The levels of non-regulation, external regulation, identified regulation, and self-determination were also significantly different from those of the control group. After the intervention, the scores of support for autonomy, support for competence, support for relatedness, and need for relatedness in the experimental group were significantly higher than those in the control group. Support for autonomy, support for competence, support for relatedness, need for competence and need for relatedness positively predicted the self-determination level, and intrinsic regulation and identified regulation negatively predicted non-regulation, external regulation, and introjected regulation.Conclusion“SPOC + flipped classroom” teaching has a positive impact on students’ learning motivation of basketball skills and promotes students’ motivation autonomy. The improvement of support for autonomy, support for competence, support for relatedness, need for competence, and need for relatedness may be related to the improvement of learning motivation of college students majoring in Physical Education. “SPOC + flipped classroom” teaching enables students to obtain more demand satisfaction by giving them more demand support, while demand support and demand satisfaction can promote the internalization of learning motivation so that students can maintain high autonomy motivation. (shrink)

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established (...) ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results. (shrink)

Poverty alleviation consumption, which we call altruistic consumption, has become a new effective way to help vulnerable groups, but there are a few empirical researches on poverty alleviation through consumption. This article takes China's poverty alleviation actions as the research object, investigates and studies the relationship between altruistic consumption motivations and altruistic consumption behaviors that aim for vulnerable groups. It is found that altruistic consumption behavior is mainly affected by benefit group motivation, benefit morality motivation, benefit demander motivation, and benefit (...) supplier motivation. There is a correspondence between the four altruistic consumption motivations and the four altruistic consumption behaviors. The strength of altruistic consumption motivations changes with changes in altruistic buying behavior. The strength of benefit group motivation decreases with the increase in the times of altruistic purchases, while the strength of benefit morality motivation, benefit demander motivation, and benefit supplier motivation increase with the increase in the times of altruistic purchases. Among the four kinds of altruistic consumption motivations that affect the times of altruistic purchases, the benefit demander motivation has a relatively greater influence. The results of this study have important guiding significance for vulnerable groups to formulating targeted proactive marketing strategies, preventing the altruistic consumption relationship dissolution, and realizing sustainable altruistic consumption. (shrink)

Evidence suggests divergent thinking is the cognitive basis of creative thoughts. Neuroimaging literature using resting-state functional connectivity has revealed network reorganizations during divergent thinking. Recent studies have revealed the changes of network organizations when performing creativity tasks, but such brain reconfigurations may be prolonged after task and be modulated by the trait of creativity. To investigate the dynamic reconfiguration, 40 young participants were recruited to perform consecutive Alternative Uses Tasks for divergent thinking and two resting-state scans were used for mapping (...) the brain reorganizations after AUT. We split participants into high- and low-creative groups based on creative achievement questionnaire and targeted on reconfigurations of the two brain networks: default-mode network and the network seeded at the left inferior frontal gyrus because the between-group difference of AUT-induced brain activation located at the left IFG. The changes of post-AUT RSFCs indicated the prolonged effect of divergent thinking. More specifically, the alterations of RSFCIFG−AG and RSFCIFG−IPL in the high-creative group had positive relationship with their AUT performances, but not found in the low-creative group. Furthermore, the RSFC changes of DMN did not present significant relationships with AUT performances. The findings not only confirmed the possibility of brain dynamic reconfiguration following divergent thinking, but also suggested the distinct IFGN reconfiguration between individuals with different creativity levels. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients (...) with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. (shrink)

As a way of human-computer interaction, game-based assessment is more suitable for young children because it is situational, interesting, and effective. National identity is an important factor affecting the overall development of young children and the future development of a country, which has attracted extensive attention from researchers. Nevertheless, the assessment of young children's national identity is still based on traditional evaluation, including questionnaires and interviews, which have the limitations of being inaccurate, dull, and time-consuming. To understand the characteristics of (...) children's national identity, it is necessary to use scientific and interactive assessment methods. The present study investigated whether the game-based assessment we developed specifically would be an appropriate tool to measure young children's national identity. The results show that the game-based assessment had good item discrimination. Exploratory factor analysis demonstrated the game covered three aspects: national cognition mastery, national emotion engagement, and national behavior tendency. The confirmatory factor analysis suggested that the model with three factors fit the data well. The internal consistency, the split-half reliability, and the test-retest reliability meet standards. Overall, the results indicated that this game can be successfully used to assess young children's national identity with acceptable validity and reliability. Our study provides strong evidence for the use of human-computer interaction in child measurement. These findings are the first to demonstrate the promise of game-based assessment in assessing children's national identity reliably and effectively. (shrink)

Introduction: Few studies are available on the prevalence and sleep-related factors of dementia with Lewy bodies (DLB) in Chinese older adults, aiming to explore the associations between sleep characteristics and DLB.Methods: A cross-sectional study with 7,528 individuals aged ≥65 years in 106 communities in Northern China was conducted from April 2019 to January 2020. Questionaries (including demographic characteristics, comorbidities, lifestyles, and sleep characteristics) were administered, and neuropsychological assessments and physical examination were conducted in phase I; screening for probable DLB was (...) done in phase II. Logistic regressions were used to assess associations.Results: A total of 919 (12.2%, 919/7,528) participants had dementia, and 101 (1.3%, 101/7,528) participants were diagnosed with DLB. The prevalence of dementia and DLB were slightly higher or equal in women, increased with age, and roughly decreased with nighttime sleep duration. Of the 101 participants, all of them (100.0%) had cognitive impairment, 46 (44.54%) displayed fluctuating cognition, 72 (71.29%) of them showed visual hallucination, 22 (21.78%) individuals reported RBD, and 27.71% showed Parkinsonism. Sleeping for 8 h had combined diagnostic value for DLB (AUC = 0.783, 95%CI: 0.734–0.831, p < 0.001).Conclusions: The current prevalence of DLB is 1.3% in Northern China. Short or long nighttime sleep duration is independently associated with the occurrence of dementia and DLB. (shrink)

Examining the nature of teachers’ emotions and how they are managed and regulated in the act of teaching is crucial to assess the quality of teacher’s instructions. Despite the essential role emotions play in teachers’ lives and instruction, research on teachers’ emotions has not paid much attention on teachers’ state emotions in the context of daily teaching. Significant portion of literature has described teachers’ emotions by foregrounding trait emotions through deductive methodological approaches. This paper explored elementary teachers’ state and trait (...) emotions while preparing for teaching and during teaching, reasons that underlie these emotions, and the relationship between their emotions and the quality of their mathematics instruction. Participants were seven elementary teachers working in the U.S. who participated in Holistic Individualized Coaching (HIC) professional development that consisted of 5 cycles of coaching over an year. For each coaching cycle pre-coaching conversation and post-coaching conversation data were collected regarding state emotions teachers felt in anticipation of teaching and during teaching retrospectively. Also, teachers responded adapted Teaching Emotion Scale (TES) that was aimed to measure trait emotions. In order to compare teachers’ emotions with instructional quality, coaching session were video recorded and analyzed to determine the quality of instruction. Findings of this study showed that teachers reported 6 categories of emotions (positive, negative, neutral, mixed-positive, mixed-negative, and mixed-complex), and often in non-typical ways (e.g., “not nervous”, “anxious but in a positive way”), and mixed emotions were the most dominant category. Also, teachers had more positive emotions anticipating teaching, than actually teaching the lesson, and there was no noticeable change of emotions across the 5 coaching cycles. The reason teachers felt mixed emotions reflected complex and context-specific nature of teaching, which was not articulated in the literature. There were no clear relationships between emotional experiences and instructional quality. This study allowed participants to freely describe their authentic, complex, overlapping, and ambiguous emotions in the context of active teaching, which contributes opening up the possibilities of diversifying teacher emotion research and shows the significance and usefulness of understanding teachers’ state emotions. (shrink)

Smart homes based on the Internet of Things have been rapidly developed. To improve the safety, comfort, and convenience of residents’ lives with minimal cost, daily activity recognition aims to know resident’s daily activity in non-invasive manner. The performance of daily activity recognition heavily depends on solving strategy of activity feature. However, the current common employed solving strategy based on statistical information of individual activity does not support well the activity recognition. To improve the common employed solving strategy, an activity (...) feature solving strategy based on TF-IDF is proposed in this paper. The proposed strategy exploits statistical information related to both individual activity and the whole of activities. Two distinct datasets have been commissioned, to mitigate against any possible effect of coupling between dataset and sensor configuration. Finally, a number of machine learning techniques and deep learning technique have been evaluated to assess their performance for residents activity recognition. (shrink)

BackgroundPatient-centred care and patient autonomy is one of the key factors to better quality of service provision, hence patient outcomes. It enables the development of patients’ trusts which is an important element to a better doctor-patient relationship. Given the increasing number of patient disputes and conflicts between patients and doctors in Chinese public hospital, it is timely to ensure patient-centred care is fully and successfully implemented. However, limited studies have examined the views and practice in different aspects of patient-centred care (...) among doctors in the Chinese public hospitals.MethodsA quantitative approach was adopted by distributing paper-based questionnaires to doctors and patients in two hospitals (Level III and Level II) in Jinan, Shandong province, China.ResultsIn total, 614 doctors from the surgical and internal medicine units of the two hospitals participated in the survey yielding 90% response rates. The study confirmed the inconsistent views among doctors in terms of their perception and practice in various aspects patient-centred care and patient autonomy regardless of the hospital where they work (category II or category III), their unit speciality (surgical or non-surgical), their gender or seniority. The high proportion of doctors (more than 20%) who did not perceive the importance of patient consultation prior to determining diagnostic and treatment procedure is alarming. This in in part due to the belief held by more than half of the doctors that patients were unable to make rational decisions and their involvement in treatment planning process did not necessarily lead to better treatment outcomes.ConclusionThe study calls for the development of system level policy and organisation wide strategies in encouraging and enabling the practice of patient-centred care and patient autonomy with the purposes of improving the quality of the service provided to patients by Chinese hospitals. (shrink)

Objectives: The corona virus disease-2019 pandemic spread globally, and we aimed to investigate the psychosocial impact on healthcare workers in China during the pandemic.Methods: In this systematic review and meta-analysis, we searched seven electronic databases for cross-sectional studies on psychosocial impact on HWs in relation to COVID-19 from January 1, 2020 to October 7, 2020. We included primary studies involving Chinese HWs during the pandemic, and data were extracted from the published articles. Our primary outcome was prevalence of anxiety, depression, (...) and stress disorders. We pooled prevalence value with their 95% confidence interval using random effect models and assessed study quality on the basis of an 11-item checklist recommended by the Agency for Healthcare Research and Quality. The study protocol was registered in PROSPERO.Results: We identified 25 articles comprising a total of 30,841 completed questionnaires and 22 studies for meta-analysis. The prevalence of anxiety, depression, and stress disorders was 34.4%, 31.1%, and 29.1% for HWs. The pooled prevalence of anxiety disorders for HWs from late January to early February was 46.4%, significantly higher than those in mid-term February and after late February. The pooled prevalence of depression disorders for HWs from late January to early February was 46.5%, significantly higher than those in mid-term February and after late February. HWs working in Hubei Province had a higher prevalence of anxiety and a lower prevalence of depression than those working in other regions. Nurses had a higher prevalence of anxiety and depression than other HWs.Conclusions: About one-third of HWs in China suffered anxiety, depression, and stress at the early epidemic of COVID-19. HWs in Hubei Province, especially nurses, had a higher prevalence of psychological disorders. During the pandemic, a negative psychological state may persist in a proportion of Chinese HWs, fluctuating with the control of the pandemic. The long-term impact should continue to be observed. Attention should be paid to HWs for their psychological impact due to the pandemic.Systematic Review Registration: The study protocol was registered with PROSPERO. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

We show that for any ω-r.e. degree d and n-r.e. degree b with d

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Biological pacemakers can be achieved by various gene‐based and cell‐based approaches. Embryonic stem cells (ESCs)‐derived pacemaker cells might be the most promising way to form biological pacemakers, but there are challenges as to how to control the differentiation of ESCs and to overcome the neoplasia, proarrhythmia, or immunogenicity resulting from the use of ESCs. As a potential approach to solve these difficult problems, tissue‐engineering techniques may provide a precise control on the different cell components of multicellular aggregates and the forming (...) of a construct with‐defined architectures and functional properties. The combined interactions between ESC‐derived pacemaker cells, supporting cells, and matrices may completely reproduce pacemaker properties and result in a steady functional unit to induce rhythmic electrical and contractile activities. As ESCs have a high capability for self‐renewal, proliferation, and potential differentiation, we hypothesize that ESCs can be used as a source of pacemaker cells for tissue‐engineering applications and the ambitious goal of biological cardiac pacemakers may ultimately be achieved with ESCs via tissue‐engineering technology. (shrink)

Biological pacemakers can be achieved by various gene‐based and cell‐based approaches. Embryonic stem cells (ESCs)‐derived pacemaker cells might be the most promising way to form biological pacemakers, but there are challenges as to how to control the differentiation of ESCs and to overcome the neoplasia, proarrhythmia, or immunogenicity resulting from the use of ESCs. As a potential approach to solve these difficult problems, tissue‐engineering techniques may provide a precise control on the different cell components of multicellular aggregates and the forming (...) of a construct with‐defined architectures and functional properties. The combined interactions between ESC‐derived pacemaker cells, supporting cells, and matrices may completely reproduce pacemaker properties and result in a steady functional unit to induce rhythmic electrical and contractile activities. As ESCs have a high capability for self‐renewal, proliferation, and potential differentiation, we hypothesize that ESCs can be used as a source of pacemaker cells for tissue‐engineering applications and the ambitious goal of biological cardiac pacemakers may ultimately be achieved with ESCs via tissue‐engineering technology. -/- . (shrink)

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

The present study critically evaluates whether school leadership influences student learning homogenously regardless of school contexts. It examined relationships between four principal leadership variables (envisioning, instructional management, promoting professional development, empowerment) and two types of student outcomes (enjoyment in learning science, science achievement,) in different school contexts (in terms of the availability of science resources, quality of science teachers, and school socioeconomic status (SES)). The sample comprised 248,620 students and 9,370 principals in 35 developed countries who participated in the Programme (...) for International Student Assessment (PISA) 2015. Latent profile analysis (LPA) showed that schools operated in three types of school contexts with different levels of science resources, proportion of quality science teachers, and school SES. There were also differences in the pattern of leadership practices across the three types of school contexts. Three-level hierarchical linear modeling (HLM) showed that among the four leadership variables, only instructional management was positively associated with students’ enjoyment of science in schools with less science resources and quality science teachers. Therefore, instructional management had compensatory effects for students in less-endowed schools. In contrast, principal leadership related to envisioning, teacher professional development, and empowerment was not positively related to students’ science learning in all three school contexts. (shrink)