A case study of the decline of the Buddhist funeral ritual, the Guangdong Yuqie Yankou

AbstractThis article contextualizes the decline of the Buddhist death ritual, the Guangdong Yuqie Yankou (廣東瑜伽焰口), through an examination of external and internal factors that might have affected its development in contemporary Hong Kong. During the last two decades, its popularity has dramatically declined, so much so that it now occupies an insignificant place among the pool of local funeral rituals. Its waning is not only a result of changing socioeconomic factors, such as contemporary lifestyles, commercialization of the funeral industry, ?fast-food? mortuary practices, and diminished religiosity of the Hong Kong laity, but is also caused by the scarcity of presiding Buddhist masters and competition from Buddhist rituals imported from other provinces of China. These intertwining factors have worked together to foster the decline of the ritual. The data for this ethnographic study were mainly collected in interviews and through the observation of participants.postprin

The Pearl of the Tripitaka, Two Vaggas in the Sutta-Nipata

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Dharma therapy: an intervention program with mindfulness as one of its key components

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The Importance of the Buddhist Teaching on Three Kinds of Knowing: In a School-based Contemplative Education Program

Includes bibliographical references

The correlation between resting EEG power and nonattachment scale

E-Poster: no. 4453INTRODUCTION: Psychological activity is supported by the brain electronic activity, to some extent, recorded by electroencephalography (EEG) (Davidson, et al., 2000). Therefore, it is plausible that some psychological measurements could be correlated with EEG measurements. For example, previous studies have shown that patterns of the frontal and posterior alpha-wave can predict basic dimensions of personality, extraversion and neuroticism (Schmidtke and Heller, 2004). In this paper, we aimed to study the correlations between resting-state EEG and four popular psychological self-reported ...postprin

Using Wavelet Entropy To Demonstrate How Mindfulness Practice Increases Coordination Between Irregular Cerebral And Cardiac Activities

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, statistical parametric mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard mindfulness-based stress reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities

The impact of paratracheal lymph node metastasis in squamous cell carcinoma of the hypopharynx

The aim of this study was to analyze the prevalence and prognostic importance of paratracheal lymph nodes in squamous cell carcinoma of the hypopharynx. A retrospective review of 64 previously untreated patients with squamous cell carcinoma (SCC) of the hypopharynx that underwent surgery was performed. Ipsilateral paratracheal lymph node metastases occurred in 22% (14 out of 64) and the mean number of paratracheal lymph nodes dissected per side was 2.3 (range 1–6). Contralateral paratracheal lymph node metastases were present in 2% (1 out of 42). Sixty-seven percent with postcricoid SCC and 22% with pyriform sinus SCC developed clinical node-positive ipsilateral paratracheal lymph node metastases, whereas 11% with posterior pharyngeal wall SCC developed paratracheal metastases. There was a significant correlation between paratracheal lymph node metastasis and cervical metastasis (p = 0.005), and the primary tumor site (postcricoid, 57.1%; pyriform sinus, 20.0%; posterior pharyngeal wall, 8.3%) (p = 0.039). Patients with no evidence of paratracheal lymph node metastasis may have a survival benefit (5-year disease-specific survival rate, 60 vs. 29%). However, this result did not reach statistical significance (p = 0.071). The patients with SCC of the postcricoid and/or pyriform sinus were at risk for ipsilateral paratracheal lymph node metastasis; furthermore, patients with paratracheal node metastasis had a high frequency of cervical metastasis and a poorer prognosis. Therefore, routine ipsilateral paratracheal node dissection is recommended during the surgical treatment of patients with SCC of the postcricoid and/or pyriform sinus with clinical node metastases

LAP2 Is Widely Overexpressed in Diverse Digestive Tract Cancers and Regulates Motility of Cancer Cells

BACKGROUND: Lamina-associated polypeptides 2 (LAP2) is a nuclear protein that connects the nuclear lamina with chromatin. Although its critical roles in genetic disorders and hematopoietic malignancies have been described, its expression and roles in digestive tract cancers have been poorly characterized. METHODS: To examine the expression of LAP2 in patient tissues, we performed immunohistochemistry and real-time PCR. To examine motility of cancer cells, we employed Boyden chamber, wound healing and Matrigel invasion assays. To reveal its roles in metastasis in vivo, we used a liver metastasis xenograft model. To investigate the underlying mechanism, a cDNA microarray was conducted. RESULTS: Immunohistochemistry in patient tissues showed widespread expression of LAP2 in diverse digestive tract cancers including stomach, pancreas, liver, and bile duct cancers. Real-time PCR confirmed that LAP2β is over-expressed in gastric cancer tissues. Knockdown of LAP2β did not affect proliferation of most digestive tract cancer cells except pancreatic cancer cells. However, knockdown of LAP2β decreased motility of all tested cancer cells. Moreover, overexpression of LAP2β increased motility of gastric and pancreatic cancer cells. In the liver metastasis xenograft model, LAP2β increased metastatic efficacy of gastric cancer cells and mortality in tested mice. cDNA microarrays showed the possibility that myristoylated alanine-rich C kinase substrate (MARCKS) and interleukin6 (IL6) may mediate LAP2β-regulated motility of cancer cells. CONCLUSIONS: From the above results, we conclude that LAP2 is widely overexpressed in diverse digestive tract cancers and LAP2β regulates motility of cancer cells and suggest that LAP2β may have utility for diagnostics and therapeutics in digestive tract cancers

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p

Assessing learning and memory in pigs

In recent years, there has been a surge of interest in (mini) pigs (Sus scrofa) as species for cognitive research. A major reason for this is their physiological and anatomical similarity with humans. For example, pigs possess a well-developed, large brain. Assessment of the learning and memory functions of pigs is not only relevant to human research but also to animal welfare, given the nature of current farming practices and the demands they make on animal health and behavior. In this article, we review studies of pig cognition, focusing on the underlying processes and mechanisms, with a view to identifying. Our goal is to aid the selection of appropriate cognitive tasks for research into pig cognition. To this end, we formulated several basic criteria for pig cognition tests and then applied these criteria and knowledge about pig-specific sensorimotor abilities and behavior to evaluate the merits, drawbacks, and limitations of the different types of tests used to date. While behavioral studies using (mini) pigs have shown that this species can perform learning and memory tasks, and much has been learned about pig cognition, results have not been replicated or proven replicable because of the lack of validated, translational behavioral paradigms that are specially suited to tap specific aspects of pig cognition. We identified several promising types of tasks for use in studies of pig cognition, such as versatile spatial free-choice type tasks that allow the simultaneous measurement of several behavioral domains. The use of appropriate tasks will facilitate the collection of reliable and valid data on pig cognition