Table_1_Plasma Biomarkers Differentiate Parkinson’s Disease From Atypical Parkinsonism Syndromes.DOCX

<p>Objective: Parkinson’s disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS.</p><p>Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay.</p><p>Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-off value for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)², with an area under the curve (AUC) of 0.932. An α-synuclein cut-off of 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-off of 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87).</p><p>Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).</p

Image_4_Plasma Biomarkers Differentiate Parkinson’s Disease From Atypical Parkinsonism Syndromes.JPEG

<p>Objective: Parkinson’s disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS.</p><p>Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay.</p><p>Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-off value for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)², with an area under the curve (AUC) of 0.932. An α-synuclein cut-off of 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-off of 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87).</p><p>Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).</p

Image_1_Plasma Biomarkers Differentiate Parkinson’s Disease From Atypical Parkinsonism Syndromes.JPEG

<p>Objective: Parkinson’s disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS.</p><p>Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay.</p><p>Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-off value for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)², with an area under the curve (AUC) of 0.932. An α-synuclein cut-off of 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-off of 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87).</p><p>Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).</p

Image_3_Plasma Biomarkers Differentiate Parkinson’s Disease From Atypical Parkinsonism Syndromes.JPEG

<p>Objective: Parkinson’s disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS.</p><p>Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay.</p><p>Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-off value for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)², with an area under the curve (AUC) of 0.932. An α-synuclein cut-off of 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-off of 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87).</p><p>Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).</p

A Novel Detection Platform for Shrimp White Spot Syndrome Virus Using an ICP11-Dependent Immunomagnetic Reduction (IMR) Assay

<div><p>Shrimp white spot disease (WSD), which is caused by white spot syndrome virus (WSSV), is one of the world’s most serious shrimp diseases. Our objective in this study was to use an immunomagnetic reduction (IMR) assay to develop a highly sensitive, automatic WSSV detection platform targeted against ICP11 (the most highly expressed WSSV protein). After characterizing the magnetic reagents (Fe₃O₄ magnetic nanoparticles coated with anti ICP11), the detection limit for ICP11 protein using IMR was approximately 2 x 10⁻³ ng/ml, and the linear dynamic range of the assay was 0.1~1 x 10⁶ ng/ml. In assays of ICP11 protein in pleopod protein lysates from healthy and WSSV-infected shrimp, IMR signals were successfully detected from shrimp with low WSSV genome copy numbers. We concluded that this IMR assay targeting ICP11 has potential for detecting the WSSV.</p></div

IMR (%)–ϕ_ICP11 (spiked-rICP11-concentration in PBS) curve showing concentration-dependent IMR signals for ICP11 with standard deviations (duplicate measurements).

<p>IMR (%)–ϕ_ICP11 (spiked-rICP11-concentration in PBS) curve showing concentration-dependent IMR signals for ICP11 with standard deviations (duplicate measurements).</p

IMR detection of ICP11 protein in shrimp.

<p>(A) Measured ICP11 protein concentration (ϕ_ICP11-IMR) in non-challenged shrimp (normal control) and in shrimp with a light or severe WSSV infection. The cut-off value (the dashed line) was based on ROC curve analysis of the IMR results. (B) Sensitivity and specificity of the IMR assay as determined by ROC curve analysis.</p

Linear correlation between actual ICP11 concentration (ϕ_ICP11) and ICP11 concentration (ϕ_ICP11-c) as measured by IMR in Fig 5.

<p>Linear correlation between actual ICP11 concentration (ϕ_ICP11) and ICP11 concentration (ϕ_ICP11-c) as measured by IMR in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0138207#pone.0138207.g005" target="_blank">Fig 5</a>.</p

Correlation between detected ICP11-IMR concentration and WSSV copy number.

<p>Pleopod samples were collected from shrimp and subjected to IMR assay and real-time PCR. Dots indicate shrimp belonging to the non-challenged control group (0.08 ~ 7 WSSV copies/mg tissue); crosses indicate light infection (10 ~ 3100 WSSV copies/mg tissue); triangles indicate severe infection (1.57 x 10⁴ ~ 2.83 x 10⁵ WSSV copies/mg tissue).</p

Western blot analysis of WSSV ICP11 and VP28 in total lysates from shrimp pleopods (PL) collected from healthy (PBS) and WSSV-infected shrimp.

<p>After separation and transfer to PVDF membrane, samples were probed with (A) anti-ICP11 antibody or (B) anti-VP28 antibody. (C) To show the protein loading, the SDS-PAGE was stained with coomassie blue. M: Prestained Protein Ladder (10–170 kDa)</p