The purpose of this study was to investigate the effects of 8-week green tea extract (GTE) supplementation on promoting postexercise muscle glycogen resynthesis and systemic energy substrate utilisation in young college students. A total of eight healthy male participants (age: 22·0 (se 1·0) years, BMI: 24·2 (se 0·7) kg/m2, VO2max: 43·2 (se 2·4) ml/kg per min) participated in this study. GTE (500 mg/d for 8 weeks) was compared with placebo in participants in a double-blind/placebo-controlled and crossover study design with an 8-week washout period. Thereafter, all participants performed a 60-min cycling exercise (75 % VO2max) and consumed a carbohydrate-enriched meal immediately after exercise. Vastus lateralis muscle samples were collected immediately (0 h) and 3 h after exercise, and blood and gaseous samples were collected during the 3-h postexercise recovery period. An 8-week oral GTE supplementation had no effects on further promoting muscle glycogen resynthesis in exercised human skeletal muscle, but the exercise-induced muscle GLUT type 4 (GLUT4) protein content was greater in the GTE supplementation trial (P<0·05). We observed that, during the postexercise recovery period, GTE supplementation elicited an increase in energy reliance on fat oxidation compared with the placebo trial (P<0·05), although there were no differences in blood glucose and insulin responses between the two trials. In summary, 8-week oral GTE supplementation increases postexercise systemic fat oxidation and exercise-induced muscle GLUT4 protein content in response to an acute bout of endurance exercise. However, GTE supplementation has no further benefit on promoting muscle glycogen resynthesis during the postexercise period.

Background: The caregiver burden on foreign paid caregivers (FPCs) is currently not well understood. This study identified predictors and differences in caregiver burden between FPCs and family caregivers who provided care for patients with dementia.

Methods: We recruited 489 patients with dementia (diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition) and used the Neuropsychiatric Inventory (NPI) and Clinical Dementia Rating (CDR) Scale to assess their neuropsychiatric behavioral problems and severity of dementia. All caregivers [FPCs (n = 42) and family caregivers with (n = 42) and without (n = 447) FPCs] completed three questionnaires: the Zarit Burden Interview (ZBI), the Center for Epidemiological Studies–Depression Scale (CES-D), and caregivers’ knowledge of dementia (KD). To understand caregiver burden, we analyzed the correlations between ZBI and other variables and investigated the differences between family caregivers and FPCs.

Results: NPI and CDR scores were higher among patients assisted by FPCs than among those whose families did not employ FPCs. Burdens were greater among family caregivers assisted by FPCs than among FPCs and family caregivers who were not assisted by FPCs. Family caregivers had greater knowledge of dementia than did FPCs. For family caregivers, CES-D scores (Spearman's r = 0.650; p < 0.01) and patients’ NPI scores (Spearman's r = 0.471; p < 0.01) were correlated with caregiver burden. For FPCs, only CES-D scores (Spearman's r = 0.511; p < 0.01) were correlated with caregiver burden. A linear regression model showed that CES-D scores contributed most to caregiver burden in all groups [β = 0.560 (family caregivers without FPCs), 0.546 (family caregivers with FPCs), and 0.583 (FPCs); p < 0.005].

Conclusion: Both family caregivers and FPCs need emotional support. Adequate treatment to reduce the neuropsychiatric symptoms of patients with dementia might reduce the burden on family caregivers.

Background: Neuropsychiatric symptoms (NPS) are common in patients with dementia associated with Parkinson's disease (PDD). The relationship between cognition and NPS in PDD has not been well studied.

Methods: Patients diagnosed with PDD were assessed for cognitive function and NPS. The instruments used were the Neuropsychiatric Inventory (NPI), Mini-Mental State Examination (MMSE), and semantic verbal fluency according to the recommendation of the Movement Disorder Society Task Force.

Results: We evaluated 127 PDD patients (76 males/51 females; mean age 77 ± 6.3 years). Their mean MMSE score was 17 ± 6.5 and the mean NPI score was 19 ± 20.4. The most prevalent NPI items were anxiety (57.5%), sleep problems (53.5%), and apathy (52.0%). Principal component factor analysis revealed that 12 items formed three factors, namely “mood and psychosis” (delusion, hallucination, agitation, depression, anxiety, apathy, and irritability), “vegetative” (sleep and appetite problems), and “frontal” (euphoria, disinhibition, and aberrant motor behavior). Symptoms of hallucination were significantly associated with MMSE score, even after controlling for the confounding variables.

Conclusion: NPS are common and diverse among patients with PDD. Three specific subgroups of NPS were identified. Hallucination was significantly correlated with cognitive impairment, and could be a predictor of cognition in PDD patients.

Background: The Montreal Cognitive Assessment (MoCA) is an instrument for screening mild cognitive impairment (MCI). This study examined the psychometric properties and the validity of the Taiwan version of the MoCA (MoCA-T) in an elderly outpatient population.

Methods: Participants completed the MoCA-T, Mini-Mental State Examination (MMSE), and the Chinese Version Verbal Learning Test. The diagnosis of Alzheimer's disease (AD) was made based on the NINCDS-ADRDA criteria, and MCI was diagnosed through the criteria proposed by Petersen et al. (2001).

Results: Data were collected from 207 participants (115 males/92 females, mean age: 77.3 ± 7.5 years). Ninety-eight participants were diagnosed with AD, 71 with MCI, and 38 were normal controls. The area under the receiver operator curves (AUC) for predicting AD was 0.98 (95% confidence interval [CI] = 0.97–1.00) for the MMSE, and 0.99 (95% CI = 0.98–1.00) for the MoCA-T. The AUC for predicting MCI was 0.81 (95% CI = 0.72–0.89) using the MMSE and 0.91 (95% CI = 0.86–1.00) using the MoCA-T. Using an optimal cut-off score of 23/24, the MoCA-T had a sensitivity of 92% and specificity of 78% for MCI. Item response theory analysis indicated that the level of information provided by each subtest of the MoCA-T was consistent. The frontal and language subscales provided higher discriminating power than the other subscales in the detection of MCI.

Conclusion: Compared to the MMSE, the MoCA-T provides better psychometric properties in the detection of MCI. The utility of the MoCA-T is optimal in mild to moderate cognitive dysfunction.