Understanding Mainland Chinese tourists’ motivation and constraints of visiting Taiwan

China has been by far the fastest growing source market in recent years, and now is the biggest tourism source market in the world. Mainland Chinese travellers were permitted to directly visit Taiwan in 2008. Within a short period of time, the Mainland Chinese travel market has become the top source market for Taiwan’s tourism industry. However, limited attention has been paid to the travel behaviour of this significant market, such as why and why not Mainland Chinese travellers visit Taiwan. Using interviews, this study identified a list of motivation factors and travel constraint factors. Three themes, intrapersonal, interpersonal, and contextual factors, influenced Mainland Chinese tourists’ intention to visit Taiwan. Particularly, contextual factors, such as ‘the cross-strait relations’ between Mainland China and Taiwan, play a key role in influencing tourists’ visit intention. Like two sides of the same coin, ‘the cross-strait relations’ could be the facilitator to attract Mainland Chinese tourists or the inhibitor to stop Mainland Chinese visiting Taiwan

Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.

Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on capturing the low-dimensional feature vectors for both herbs and proteins by network embedding, which incorporate the topological properties of nodes across multi-layered heterogeneous network, and then performs supervised learning based on these low-dimensional feature representations. HTINet obtains performance improvement over a well-established random walk based herb-target prediction method. Furthermore, we have manually validated several predicted herb-target interactions from independent literatures. These results indicate that HTINet can be used to integrate heterogeneous information to predict novel herb-target interactions

Functional decline and mortality in long-term care settings: Static and dynamic approach

AbstractBackground/PurposeFunctional impairment is known to be associated with higher mortality risk and adverse health outcomes. However, little is known about whether functional decline could predict mortality among the elderly in the long-term care setting.MethodsThis is a prospective cohort study in two veteran homes in northern Taiwan with active use of the minimum data set (MDS). Evaluation tools retrieved from the MDS, including MDS Resource Utilization Group-III for Activities of Daily Living (RUG-III ADL), MDS Cognitive Scale, MDS Social engagement, triggers for resident assessment protocol (RAP) and Pain scale, were utilized for the analysis.ResultsA total of 1125 male participants were included in this study. The mean age of the participants was 83.1 ± 5.1 years, and 65 (5.8%) developed physical functional decline within a 6-month period. Participants with functional decline [odds ratio (OR) 2.305, 95% confidence interval (CI) 1.002–5.303], poor baseline functional status (OR 1.116, 95% CI 1.002–1.242), positive RAP triggers for dehydration (OR 13.857, 95% CI 3.07–62.543), and underlying chronic lung diseases (OR 2.279, 95% CI 1.149–4.522), depression (OR 2.994, 95% CI 1.161–7.721), and cancer (OR 3.23, 95% CI 1.078–9.682) were more likely to have an additional 12-month mortality. By contrast, Parkinsonism (OR 3.875, 95% CI 1.169–12.841), increase in sum of RAP triggers (OR 6.096, 95% CI 2.741–13.562), and positive RAP triggers for cognitive loss (OR 3.164, 95% CI 1.612–6.212) and mood (OR 2.894, 95% CI 1.466–5.71) are strong predictors for functional decline within 6 months.ConclusionPhysical function decline within 6 months predicted the subsequent 1-year mortality, whereas increased sum of RAP triggers and positive trigger for cognitive loss and mood were associated with functional decline

Estimating systemic fibrosis by combining galectin-3 and ST2 provides powerful risk stratification value for patients after acute decompensated heart failure

Background: Two fibrosis biomarkers, galectin-3 (Gal-3) and suppression of tumorigenicity 2 (ST2), provide prognostic value additive to natriuretic peptides and traditional risk factors in patients with heart failure (HF). However, it is to be investigated whether their combined measurement before discharge provides incremental risk stratification for patients after acute HF. Methods: A total of 344 patients with acute HF were analyzed with Gal-3, and ST2 measured. Patients were prospectively followed for 3.7 ± 1.3 years for deaths, and composite events (death/HF-related re-hospitalizations). Results: The levels of Gal-3 and ST2 were only slightly related (r = 0.20, p < 0.001). The medians of Gal-3 and ST2 were 18 ng/mL and 32.4 ng/mL, respectively. These biomarkers compensated each other and characterized patients with different risk factors. According to the cutoff at median values, patients were separated into four subgroups based on high and low Gal-3 (HG and LG, respectively) and ST2 levels (HS and LS, respectively). Kaplan-Meier survival curves showed that HGHS powerfully identified patients at risk of mortality (Log rank = 21.27, p < 0.001). In multivariable analysis, combined log(Gal-3) and log(ST2) was an in­dependent predictor. For composite events, Kaplan-Meier survival curves showed a lower event- -free survival rate in the HGHS subgroup compared to others (Log rank = 34.62, p < 0.001; HGHS vs. HGLS, Log rank = 4.00, p = 0.045). In multivariable analysis, combined log(Gal-3) and log(ST2) was also an independent predictor. Conclusions: Combination of biomarkers involving heterogeneous fibrosis pathways may identify patients with high systemic fibrosis, providing powerful risk stratification value

Undiagnosed diabetes mellitus among residents in Taiwanese long-term care facilities: A comparison of fasting glucose, postprandial plasma glucose, and hemoglobin A1c

AbstractBackgroundThe prevalence of diabetes mellitus (DM) is escalating with an aging population, and the chances of diabetic older patients admitted to long-term care facilities (LTCFs) are increased because of DM-related complications. However, undiagnosed DM among LTCF residents is a recognized hidden problem in this setting and may result in adverse outcomes.MethodsIn May 2011, 10 private LTCFs in northern Taipei participated in this study. Trained research nurses reviewed the medical records and performed physical examinations and blood sampling for all participants. Diabetes mellitus was diagnosed, based on the levels of fasting glucose, 2-hour postprandial plasma glucose, and hemoglobin A1c (HbA1c). Patients were categorized as having DM if they met the diagnostic cut-offs of the aforementioned criteria.ResultsOne hundred and ninety-nine residents (mean age, 79.6 ± 10.5 years; 52.3% males) participated in this study. They were all moderately/severely disabled (Karnofsky Performance Scale mean score was 50 ± 13). Forty-six (23.1%) residents were diabetic, based on their medical records, or were current users of antidiabetic agents. The prevalence was 29.6% after testing with a mean HbA1c level of 6.9% ± 0.9%. The overall undiagnosed DM rate was 4%, 3.5%, and 4.5%, based on fasting glucose, 2-hour postprandial plasma glucose, and HbA1c criteria, respectively. Diabetic patients had significantly higher serum levels of prealbumin, compared to nondiabetic patients (220.8 ± 45.9 vs. 201.1 ± 62.2 mg/L; p = 0.03), but there were no differences in the levels of hemoglobin, serum albumin, or total cholesterol. Diabetic patients had a significantly higher serum triglyceride level, compared to the nondiabetic patients (1.6 ± 0.7 vs. 1.1 ± 0.5 mmol/L; p < 0.01) and a lower high-density lipoprotein level (1.0 ± 0.3 vs. 1.2 ± 0.3 mmol/L; p < 0.01). Among 43 pharmacologically treated diabetic patients, 65.1% (28/43) of patients were using oral antidiabetic agents and 41.9% (18/43) of patients had been prescribed insulin, whereas 32.6% of the patients were managed by combination therapy.ConclusionThe prevalence of DM among LTCF residents in Taipei was 29.6%, and the undiagnosed rate was no more than 5%, based on fasting glucose, 2-hour postprandial plasma glucose, or HbA1c. Further study is needed for the optimal treatment strategy of DM in LTCFs

The design of a prospective, randomized, open-labeled study to compare the efficacy of lercanidipine with amlodipine on renal function in hypertensive patients aged at least 55 years (LEADER study)

AbstractBackgroundAlthough all classes of antihypertensive treatment can successfully reduce morbidity and mortality of cardiac pathology, prevention of target organ damages is of great importance beyond blood pressure lowering. Unlike most dihydropyridines, lercanidipine dilates both afferent and the efferent arterioles of nephrons, so it may provide renoprotective effects, which other CCBs may not have. The main purpose of this study is to compare the renoprotective effect of lercanidipine and amlodipine among hypertensive people aged 55years and older with newly diagnosed hypertension or those who were treatment-naïve for one month.MethodsThe study is a prospective, open-labelled, randomized, controlled trial to enrol 232 hypertensive patients aged ≥55 years. Subjects will be randomized into lercanidipine arm (10–20mg/day) and amlodipine arm (5–10mg/day) by 1:1 ratio. The dosage can be up-titrated to 20mg/day (lercanidipine group) and 10mg/day (amlodipine group), respectively, at week 4 or any following visit thereafter. Efficacy and safety data will be collected at week 4, 12 and 24 by evaluating the blood pressure lowering, estimated glomerular filtration rate, creatinine clearance, and urine albumin-creatinine ratio.ConclusionsThe reno-protective effects of new generation of CCBs such as lercanidipine administered to patients with hypertension are not investigated well. After all, this study will bring benefit to older patients who need drugs with both excellent anti-hypertensive and reno-protective efficacy. And the results will be provided for future treatment guideline of elder population in Taiwan

A smart chicken farming platform for chicken behavior identification and feed residual estimation

It is very potential to develop digital villages for promoting smart agriculture. As one of the important research fields of smart agriculture, smart chicken farms encounter management problems such as difficulties in quickly and accurately warning of sick and dead chickens and estimating feed residuals. Therefore, this study not only respectively proposed CKTrack and FRCM to detect sick and dead chickens and estimate feed residuals, but also developed a smart chicken farming platform for automagical management. Our main results include (1) the proposed CKTrack method can effectively identify sick and dead chickens under the condition of limited data volume and computing capacity; (2) the proposed FRCM method can accurately estimate the feed residuals; and (3) the smart chicken farming platform developed can provide farmers with functions such as early warning of sick and dead chickens, visualization of the chicken quantity inventory, and feed residual estimation.<br/

Association between the neutrophil-to-lymphocyte ratio and cognitive impairment: a meta-analysis of observational studies

BackgroundSystemic inflammation is one of the underlying mechanisms of cognitive impairment. The neutrophil-to-lymphocyte ratio (NLR) has emerged as a systemic inflammation indicator. This meta-analysis aimed to evaluate the association between high NLR and cognitive impairment (CI) risk.MethodA comprehensive systematic search was conducted to identify eligible studies published until May 30, 2023. The reference group comprised patients with the lowest NLR level, whereas the exposure group comprised those with the highest NLR level. The main outcome was to examine the relationship between NLR and CI risk. The secondary outcome included the association between patient characteristics or comorbidities and CI risk.ResultsThis meta-analysis included 11 studies published between 2018 and 2023, involving 10,357 patients. Patients with CI had a higher NLR than those without (mean difference=0.35, 95% confidence interval [CI]: 0.26–0.44, p &lt; 00001, I2 = 86%). Consistently, pooled results revealed an association between high NLR and CI risk (odds ratio [OR]=2.53, 95% CI:1.67–3.82, p&lt;0.0001, I2 = 84%). Furthermore, aging (mean difference =4.31 years, 95% CI:2.83–5.8, p &lt; 0.00001, I2 = 92%), diabetes (OR=1.59, 95% CI:1.35–1.88, p &lt; 0.00001, I2 = 66%), and hypertension (OR=1.36, 95% CI:1.19–1.57, p &lt; 0.00001, I2 = 0%) were significant risk factors for CI. However, no significant associations were observed between CI and male gender (OR = 0.84, 95% CI:0.64–1.11, p = 0.22, I2 = 81%), body mass index (mean = −0.32 kg/m2, 95% CI: −0.82, 0.18, p = 0.2, I2 = 82%), alcohol consumption (OR = 1.11, 95% CI:0.95−1.3, p = 1.35, I2 = 0%), and smoking (OR = 0.99, 95% CI:0.87–1.13, p = 0.86, I2 = 0%). Meta-regression found that diabetes and hypertension, but not age, significantly moderated the association between NLR and CI.ConclusionThis meta-analysis showed a significant association between high NLR and increased CI risk. Moreover, meta-regression identified diabetes and hypertension, but not age, as significant moderating factors in the relationship between NLR and CI. To validate and strengthen these findings, further large-scale studies are required.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023430384, identifier CRD42023430384