Assessing the Effects of Acupuncture by Comparing Needling the Hegu Acupoint and Needling Nearby Nonacupoints by Spectral Analysis of Microcirculatory Laser Doppler Signals

We aimed to assess the effects of acupuncture by analyzing the frequency content of skin blood-flow signals simultaneously recorded at the Hegu acupoint and two nearby nonacupoints following acupuncture stimulation (AS). Laser Doppler flowmetry (LDF) signals were measured in male healthy volunteers in two groups of experiments: needling the Hegu acupoint (n = 13) and needling a nearby nonacupoint (control experiment; n = 10). Each experiment involved recording a 20 min baseline-data sequence and two sets of effects data recorded 0–20 and 50–70 min after stopping AS. Wavelet transform with Morlet mother wavelet was applied to the measured LDF signals. Needling the Hegu acupoint significantly increased the blood flow, significantly decreased the relative energy contribution at 0.02–0.06 Hz and significantly increased the relative energy contribution at 0.4–1.6 Hz at Hegu, but induced no significant changes at the nonacupoints. Also, needling a nearby nonacupoint had no effect in any band at any site. This is the first time that spectral analysis has been used to investigate the microcirculatory blood-flow responses induced by AS, and has revealed possible differences in sympathetic nerve activities between needling the Hegu acupoint and its nearby nonacupoint. One possible weakness of the present design is that different De-Qi feelings following AS could lead to nonblind experimental setup, which may bias the comparison between needling Hegu and its nearby nonacupoint. Our results suggest that the described noninvasive method can be used to evaluate sympathetic control of peripheral vascular activity, which might be useful for studying the therapeutic effects of AS

Understanding Knowledge Outcome Improvement in Virtual Communities: an Integrative Model from a Relational Development Perspective

This study seeks to understand how relational virtual communities (RVC) members improve knowledge outcomes, including reuse and new use of knowledge. We propose a model by integrating dedication/constraint mechanisms into social cognitive theory. This model delineates the relationship between members’ self-belief, motivation, and knowledge outcomes. In particular, self-belief is conceptualized as individual factors and environments factors. Motivation is based on one’s evaluation on interpersonal relationship development, in terms of relationship rewards and identity verification. Empirical results from survey data support most proposed hypotheses. We discuss the implications of our results

Understanding Clients’ Intentions to Explore Software-as-a-Service (SaaS) Features: A Social Capital Theory Perspective

The pervasive post-adoption of on-demand software-as-a-service (SaaS) products via the Internet has provided clients with sufficient convenience and functional flexibility to rent and build the multifunctional services they require. Prior research has called for a deeper understanding of how client firms encourage the exploration of SaaS applications in the workplace. However, exploring the best service combinations depends on the clients’ socially related motivation. Hence, we draw on social capital theory in this study to examine clients’ intentions to explore new SaaS service features. We use service quality to complement structural capital as an indicator, as it is more suitable for assessing the service structure of systems. Drawing on a sample of 246 employees in the IT service departments of small- and medium-sized companies in Taiwan, we generate the following empirical results. First, most of the main effect paths only show significant positive signs for the effect of relational capital on the intention to explore, and the effect of environmental quality on social capital is not supported. Second, we rebuild the mediation model to test the non-supported hypotheses and find that relational capital partially mediates the relationship between service quality and the intention to explore. The theoretical and practical implications of these findings are discusse

UNDERSTANDING POST-ADOPTION OF ONLINE SHOPPING CONTINUANCE USAGE THROUGH THE SOCIAL EXCHANGE THEORY

Electronic commerce researchers have retention of Consumers post-adoption continuance behavior attendees induce deep trust and service quality of online shopping behavior, thereby contributing to higher revenue and marketing strategy based on social exchange theory. This study provides additional information about the path from the service quality and trust to continuous usage. Also, this study investigates the different tendencies to continuance behavior by habit as a moderating effect within the conceptual model. According to the structural invariance test across moderating effect, it showed that: First, most of main effect paths showed significant positive signs only habit as moderator on trust in service provider is negative support. Second, the habit was supported as a moderator except for the trust in shopping-site to online shopping continuance interaction path. Unexpectedly, the positive moderating effect of habit tendency towards the path of trust in shopping-site to online shopping continuance in not significant. The theoretical and practical implications are discussed

Paper-Based ELISA: A Novel Diagnostic Approach for Monitoring Aqueous Humour VEGF Level in Ocular Diseases

We commonly diagnose ocular diseases via both morphological changes and symptoms. It is necessary to develop biochemically based assays for early or follow-up diagnosis of these diseases with a focus on robustness and ease of handling. To lay out a prospective path toward this goal, we describe and propose the use of ultrahigh sensitive paper-based ELISA (p-ELISA), which uses a treated piece of filter paper to monitor the activity of ocular diseases (i.e., detecting the vascular endothelial growth factor (VEGF) concentration in aqueous humour for proliferative diabetic retinopathy or age-related macular degeneration diagnosis). The advantages of p-ELISA include the following: (1) the capacity to directly measure biomarker concentrations in aqueous humour using only a tiny sample volume (as little as 2 μL); (2) significantly increased sensitivity compared to conventional ELISA (fg/mL levels); and (3) inexpensive materials and a short operation duration. P-ELISA is a novel point-of-care diagnostic tool with the significant potential to advance ophthalmological treatment guidelines by facilitating early detection and routinely monitoring therapeutic response

Apoptosis Induction in Primary Human Colorectal Cancer Cell Lines and Retarded Tumor Growth in SCID Mice by Sulforaphane

We have investigated the anticancer effects of the dietary isothiocyanate sulforaphane (SFN) on colorectal cancer (CRC), using primary cancer cells lines isolated from five Taiwanese colorectal cancer patients as the model for colorectal cancer. SFN-treated cells accumulated in metaphase (SFN 6.25 μM) and subG1 (SFN 12.5 and 25 μM) as determined by flow cytometry. In addition, treated cells showed nuclear apoptotic morphology that coincided with an activation of caspase-3, and loss of mitochondrial membrane potential (ΔΨm). Incubations at higher SFN doses (12.5 and 25 μM) resulted in cleavage of procaspase-3 and elevated caspase-2, -3, -8, and -9 activity, suggesting that the induction of apoptosis and the sulforaphane-induced mitosis delay at the lower dose are independently regulated. Daily SFN s.c. injections (400 micromol/kg/d for 3 weeks) in severe combined immunodeficient mice with primary human CRC (CP1 to CP5) s.c. tumors resulted in a decrease of mean tumor weight by 70% compared with vehicle-treated controls. Our findings suggest that, in addition to the known effects on cancer prevention, sulforaphane may have antitumor activity in established colorectal cancer

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%