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1.  Combotherapy and current concepts as well as future strategies for the treatment of Alzheimer’s disease 
It has been estimated that 35.6 million people globally had dementia in 2010 and the prevalence of dementia has been predicted to double every 20 years. Thus, 115.4 million people may be living with dementia in 2050. Alzheimer’s disease (AD) is the leading cause of dementia and is present in 60%–70% of people with dementia. Unfortunately, there are few approved drugs that can alleviate the cognitive or behavioral symptoms of AD dementia. Recent studies have revealed that pathophysiological changes related to AD occur decades before the appearance of clinical symptoms of dementia. This extended preclinical phase of AD provides a critical chance for disease-modifying agents to halt or delay the relentless process of AD. Although several trials targeting various pathological processes are ongoing, the examination of the combined use of different approaches to combat AD seems warranted. In this article, we will review current therapies, future strategies, and ongoing clinical trials for the treatment of AD with a special focus on combination therapies. Furthermore, preventive strategies for cognitively normal subjects in the presymptomatic stages of AD will also be addressed. In this review, we discuss current hypotheses of the disease process. In the decades since the approval of cholinesterase inhibitors, no new drug has ultimately demonstrated clear success in clinical trials. Given the difficulties that have been encountered in attempts to identify a single drug that can treat AD, we must pursue effective multi-target strategies, ie, combination therapies. The combination of cholinesterase inhibitors and memantine is considered well tolerated and safe, and this combination benefits patients with moderate-to-severe AD. In contrast, with the exception of adjuvant therapies of conventional drugs, combinations of different disease-modifying agents with different mechanisms may have promising synergic effects and benefit cognition, behavior, and daily living function.
PMCID: PMC3956689  PMID: 24648738
disease-modifying agent; combination therapy; Alzheimer’s disease
2.  Combined Plasma Biomarkers for Diagnosing Mild Cognition Impairment and Alzheimer’s Disease 
ACS Chemical Neuroscience  2013;4(12):1530-1536.
A highly sensitive immunoassay, the immunomagnetic reduction, is used to measure several biomarkers for plasma that is related to Alzheimer’s disease (AD). These biomarkers include Aβ-40, Aβ-42, and tau proteins. The samples are composed of four groups: healthy controls (n = 66), mild cognitive impairment (MCI, n = 22), very mild dementia (n = 23), and mild-to-serve dementia, all due to AD (n = 22). It is found that the concentrations of both Aβ-42 and tau protein for the healthy controls are significantly lower than those of all of the other groups. The sensitivity and the specificity of plasma Aβ-42 and tau protein in differentiating MCI from AD are all around 0.9 (0.88–0.97). However, neither plasma Aβ-42 nor tau-protein concentration is an adequate parameter to distinguish MCI from AD. A parameter is proposed, which is the product of plasma Aβ-42 and tau-protein levels, to differentiate MCI from AD. The sensitivity and specificity are found to be 0.80 and 0.82, respectively. It is concluded that the use of combined plasma biomarkers not only allows the differentiation of the healthy controls and patients with AD in both the prodromal phase and the dementia phase, but it also allows AD in the prodromal phase to be distinguished from that in the dementia phase.
PMCID: PMC3867966  PMID: 24090201
Immunomagnetic reduction; plasma; biomarkers; mild cognition impairment; Alzheimer’s disease
3.  A Nationwide Survey of Mild Cognitive Impairment and Dementia, Including Very Mild Dementia, in Taiwan 
PLoS ONE  2014;9(6):e100303.
An increasing population of dementia patients produces substantial societal impacts. We assessed the prevalence of mild cognitive impairment (MCI) and all-cause dementia, including very mild dementia (VMD), in Taiwan. In a nationwide population-based cross-sectional survey, participants were selected by computerized random sampling from all 19 Taiwan counties and were enrolled between December 2011 and March 2013. Cases were identified through in-person interviews based on the National Institute on Aging-Alzheimer’s Association clinical criteria. Demographic data and histories involving mental status and function in daily living were collected. The principal objective assessments were the Taiwanese Mental Status Examination and Clinical Dementia Rating. In all, 10,432 people aged 65 years or older (mean age 76.2±6.7, 52.3% women) were interviewed. The age-adjusted prevalence of all-cause dementia was 8.04% (95% CI 7.47–8.61), including a 3.25% (95% CI 2.89–3.61) prevalence of VMD; that of MCI was 18.76% (95% CI 17.91–19.61). Women had a higher prevalence than men of both all-cause dementia (9.71% vs. 6.36%) and MCI (21.63% vs. 15.57%). MCI affects a considerable portion of the population aged 65 and above in Taiwan. The inclusion of VMD yields dementia prevalence rates higher than those previously reported from Taiwan. Old age, female gender, and a low educational level are significant associated factors.
PMCID: PMC4062510  PMID: 24940604
4.  Lack of C9orf72 Repeat Expansion in Taiwanese Patients with Mixed Neurodegenerative Disorders 
Background: The hexanucleotide repeat expansion in intron 1 of the C9orf72 gene is recognized as the most common genetic cause of frontotemporal dementia (FTD). There are overlapping clinical and pathological characteristics between FTD and Parkinsonism syndrome, and some FTD patients may present with Parkinsonism. The aim of this study was to analyze the hexanucleotide repeat numbers of C9orf72 gene in a mixed Taiwanese cohort with FTD, Parkinsonism syndrome, Parkinson’s disease (PD), and Alzheimer’s dementia (AD).
Method: The number of hexanucleotide repeats was estimated in a total of 482 patients with mixed neurodegenerative disorders and 485 control subjects, using a two-step repeat-primed polymerase chain reaction-based genotyping strategy. The individual groups of patients included patients with Parkinsonism syndrome (n = 95), familial PD (n = 109), young-onset PD (n = 201), FTD (n = 9), sporadic AD (n = 61), and early-onset AD (n = 7).
Results: We did not identify any pathogenic repeats (>30 repeats) of C9orf72 in either the patients or control subjects. However, we found one young-onset PD patient and one control subject that each had an intermediate number of repeats (25 and 21 repeats, respectively). The clinical phenotype of the young-onset PD in this patient was similar to typical idiopathic PD without additional features, and the patient responded well to levodopa treatment.
Conclusion: The repeat expansion in C9orf72 is not a common cause of PD, Parkinsonism syndrome, or dementia in our population. Further studies are needed to investigate the clinical and biological significance of intermediate repeats in C9orf72.
PMCID: PMC4009437  PMID: 24803912
C9orf72; frontotemporal dementia; Alzheimer’s dementia; Parkinson’s disease; Parkinsonism; risk factor
5.  A Physiology-Based Seizure Detection System for Multichannel EEG 
PLoS ONE  2013;8(6):e65862.
Epilepsy is a common chronic neurological disorder characterized by recurrent unprovoked seizures. Electroencephalogram (EEG) signals play a critical role in the diagnosis of epilepsy. Multichannel EEGs contain more information than do single-channel EEGs. Automatic detection algorithms for spikes or seizures have traditionally been implemented on single-channel EEG, and algorithms for multichannel EEG are unavailable.
This study proposes a physiology-based detection system for epileptic seizures that uses multichannel EEG signals. The proposed technique was tested on two EEG data sets acquired from 18 patients. Both unipolar and bipolar EEG signals were analyzed. We employed sample entropy (SampEn), statistical values, and concepts used in clinical neurophysiology (e.g., phase reversals and potential fields of a bipolar EEG) to extract the features. We further tested the performance of a genetic algorithm cascaded with a support vector machine and post-classification spike matching.
Principal Findings
We obtained 86.69% spike detection and 99.77% seizure detection for Data Set I. The detection system was further validated using the model trained by Data Set I on Data Set II. The system again showed high performance, with 91.18% detection of spikes and 99.22% seizure detection.
We report a de novo EEG classification system for seizure and spike detection on multichannel EEG that includes physiology-based knowledge to enhance the performance of this type of system.
PMCID: PMC3683026  PMID: 23799053
6.  A Diagnostic Model Incorporating P50 Sensory Gating and Neuropsychological Tests for Schizophrenia 
PLoS ONE  2013;8(2):e57197.
Endophenotypes in schizophrenia research is a contemporary approach to studying this heterogeneous mental illness, and several candidate neurophysiological markers (e.g. P50 sensory gating) and neuropsychological tests (e.g. Continuous Performance Test (CPT) and Wisconsin Card Sorting Test (WCST)) have been proposed. However, the clinical utility of a single marker appears to be limited. In the present study, we aimed to construct a diagnostic model incorporating P50 sensory gating with other neuropsychological tests in order to improve the clinical utility.
We recruited clinically stable outpatients meeting DSM-IV criteria of schizophrenia and age- and gender-matched healthy controls. Participants underwent P50 sensory gating experimental sessions and batteries of neuropsychological tests, including CPT, WCST and Wechsler Adult Intelligence Scale Third Edition (WAIS-III).
A total of 106 schizophrenia patients and 74 healthy controls were enrolled. Compared with healthy controls, the patient group had significantly a larger S2 amplitude, and thus poorer P50 gating ratio (gating ratio = S2/S1). In addition, schizophrenia patients had a poorer performance on neuropsychological tests. We then developed a diagnostic model by using multivariable logistic regression analysis to differentiate patients from healthy controls. The final model included the following covariates: abnormal P50 gating (defined as P50 gating ratio >0.4), three subscales derived from the WAIS-III (Arithmetic, Block Design, and Performance IQ), sensitivity index from CPT and smoking status. This model had an adequate accuracy (concordant percentage = 90.4%; c-statistic = 0.904; Hosmer-Lemeshow Goodness-of-Fit Test, p = 0.64>0.05).
To the best of our knowledge, this is the largest study to date using P50 sensory gating in subjects of Chinese ethnicity and the first to use P50 sensory gating along with other neuropsychological tests to develop a diagnostic model for schizophrenia. Further research to validate the predictive accuracy of this model by applying it on other samples is warranted.
PMCID: PMC3584115  PMID: 23460831
7.  Biofunctionalized Magnetic Nanoparticles for Specifically Detecting Biomarkers of Alzheimer’s Disease in Vitro 
ACS Chemical Neuroscience  2011;2(9):500-505.
Magnetic nanoparticles biofunctionalized with antibodies against β-amyloid-40 (Aβ-40) and Aβ-42, which are promising biomarkers related to Alzheimer’s disease (AD), were synthesized. We characterized the size distribution, saturated magnetizations, and stability of the magnetic nanoparticles conjugated with anti-Aβ antibody. In combination with immunomagnetic reduction technology, it is demonstrated such biofunctionalized magnetic nanoparticles are able to label Aβs specifically. The ultralow-detection limits of assaying Aβs in vitro using the magnetic nanoparticles via immunomagnetic reduction are determined to a concentration of ∼10 ppt (10 pg/mL). Further, immunomagnetic reduction signals of Aβ-40 and Aβ-42 in human plasma from normal samples and AD patients were analyzed, and the results showed a significant difference between these two groups. These results show the feasibility of using magnetic nanoparticles with Aβs as reagents for assaying low-concentration Aβs through immunomagnetic reduction, and also provide a promising new method for early diagnosis of Alzheimer’s disease from human blood plasma.
PMCID: PMC3369781  PMID: 22860173
Magnetic nanoparticles; β-amyloid; immunomagnetic reduction
8.  Differentiation of Schizophrenia Patients from Healthy Subjects by Mismatch Negativity and Neuropsychological Tests 
PLoS ONE  2012;7(4):e34454.
Schizophrenia is a heterogeneous disorder with diverse presentations. The current and the proposed DSM-V diagnostic system remains phenomenologically based, despite the fact that several neurobiological and neuropsychological markers have been identified. A multivariate approach has better diagnostic utility than a single marker method. In this study, the mismatch negativity (MMN) deficit of schizophrenia was first replicated in a Han Chinese population, and then the MMN was combined with several neuropsychological measurements to differentiate schizophrenia patients from healthy subjects.
Methodology/Principal Findings
120 schizophrenia patients and 76 healthy controls were recruited. Each subject received examinations for duration MMN, Continuous Performance Test, Wisconsin Card Sorting Test, and Wechsler Adult Intelligence Scale Third Edition (WAIS-III). The MMN was compared between cases and controls, and important covariates were investigated. Schizophrenia patients had significantly reduced MMN amplitudes, and MMN decreased with increasing age in both patient and control groups. None of the neuropsychological indices correlated with MMN. Predictive multivariate logistic regression models using the MMN and neuropsychological measurements as predictors were developed. Four predictors, including MMN at electrode FCz and three scores from the WAIS-III (Arithmetic, Block Design, and Performance IQ) were retained in the final predictive model. The model performed well in differentiating patients from healthy subjects (percentage of concordant pairs: 90.5%).
MMN deficits were found in Han Chinese schizophrenia patients. The multivariate approach combining biomarkers from different modalities such as electrophysiology and neuropsychology had a better diagnostic utility.
PMCID: PMC3320618  PMID: 22496807
9.  Pathophysiology of Neuropathic Pain in Type 2 Diabetes 
Diabetes Care  2010;33(12):2654-2659.
Neuropathic pain due to small-fiber sensory neuropathy in type 2 diabetes can be diagnosed by skin biopsy with quantification of intra-epidermal nerve fiber (IENF) density. There is, however, a lack of noninvasive physiological assessment. Contact heat–evoked potential (CHEP) is a newly developed approach to record cerebral responses of Aδ fiber–mediated thermonociceptive stimuli. We investigated the diagnostic role of CHEP.
From 2006 to 2009, there were 32 type 2 diabetic patients (20 males and 12 females, aged 51.63 ± 10.93 years) with skin denervation and neuropathic pain. CHEPs were recorded with heat stimulations at the distal leg, where skin biopsy was performed.
CHEP amplitude was reduced in patients compared with age- and sex-matched control subjects (14.8 ± 15.6 vs. 33.7 ± 10.1 μV, P < 0.001). Abnormal CHEP patterns (reduced amplitude or prolonged latency) were noted in 81.3% of these patients. The CHEP amplitude was the most significant parameter correlated with IENF density (P = 0.003) and pain perception to contact heat stimuli (P = 0.019) on multiple linear regression models. An excitability index was derived by calculating the ratio of the CHEP amplitude over the IENF density. This excitability index was higher in diabetic patients than in control subjects (P = 0.023), indicating enhanced brain activities in neuropathic pain. Among different neuropathic pain symptoms, the subgroup with evoked pain had higher CHEP amplitudes than the subgroup without evoked pain (P = 0.011).
CHEP offers a noninvasive approach to evaluate the degeneration of thermonociceptive nerves in diabetic neuropathy by providing physiological correlates of skin denervation and neuropathic pain.
PMCID: PMC2992207  PMID: 20841612
10.  A Warm Footbath before Bedtime and Sleep in Older Taiwanese with Sleep Disturbance 
Research in nursing & health  2008;31(5):514-528.
A single-group crossover design was used to examine the effects of a warm footbath on body temperatures, distal-proximal skin temperature gradient (DPG), and sleep outcomes in 15 Taiwanese elders with self-reported sleep disturbance. Body temperatures and polysomnography were recorded for 3 consecutive nights. Participants were assigned randomly to receive a 41°C footbath for 40 minutes before sleep onset on night 2 or night 3. Mean DPG before lights off was significantly elevated on the bathing night. There were no significant differences in sleep outcomes between the two nights. However, when the first two non-rapid eye movement (NREM) sleep periods were examined, the amount of wakefulness was decreased in the second NREM period on the bathing night.
PMCID: PMC2574895  PMID: 18459154
sleep/rest; aging
11.  Dual-modality impairment of implicit learning of letter-strings versus color-patterns in patients with schizophrenia 
Implicit learning was reported to be intact in schizophrenia using artificial grammar learning. However, emerging evidence indicates that artificial grammar learning is not a unitary process. The authors used dual coding stimuli and schizophrenia clinical symptom dimensions to re-evaluate the effect of schizophrenia on various components of artificial grammar learning.
Letter string and color pattern artificial grammar learning performances were compared between 63 schizophrenic patients and 27 comparison subjects. Four symptom dimensions derived from a Chinese Positive and Negative Symptom Scale ratings were correlated with patients' artificial grammar implicit learning performances along the two stimulus dimensions. Patients' explicit memory performances were assessed by verbal paired associates and visual reproduction subtests of the Wechsler Memory Scales Revised Version to provide a contrast to their implicit memory function.
Schizophrenia severely hindered color pattern artificial grammar learning while the disease affected lexical string artificial grammar learning to a lesser degree after correcting the influences from age, education and the performance of explicit memory function of both verbal and visual modalities. Both learning performances correlated significantly with the severity of patients' schizophrenic clinical symptom dimensions that reflect poor abstract thinking, disorganized thinking, and stereotyped thinking.
The results of this study suggested that schizophrenia affects various mechanisms of artificial grammar learning differently. Implicit learning, knowledge acquisition in the absence of conscious awareness, is not entirely intact in patients with schizophrenia. Schizophrenia affects implicit learning through an impairment of the ability of making abstractions from rules and at least in part decreasing the capacity for perceptual learning.
PMCID: PMC1334227  PMID: 16343344

Results 1-11 (11)