Waiting impulsivity in progressive supranuclear palsy-Richardson's syndrome.

Background: Waiting impulsivity in progressive supranuclear palsy-Richardson's syndrome (PSP-RS) is difficult to assess, and its regulation is known to involve nucleus accumbens (NAc) subregions. We investigated waiting impulsivity using the "jumping the gun" (JTG) sign, which is defined as premature initiation of clapping before the start signal in the three-clap test and compared clinical features of PSP-RS patients with and without the sign and analyzed neural connectivity and microstructural changes in NAc subregions. Materials and methods: A positive JTG sign was defined as the participant starting to clap before the start sign in the three-clap test. We classified participants into the JTG positive (JTG +) and JTG negative (JTG-) groups and compared their clinical features, microstructural changes, and connectivity between NAc subregions using diffusion tension imaging. The NAc was parcellated into core and shell subregions using data-driven connectivity-based methods. Results: Seventy-seven patients with PSP-RS were recruited, and the JTG + group had worse frontal lobe battery (FAB) scores, more frequent falls, and more occurrence of the applause sign than the JTG- group. A logistic regression analysis revealed that FAB scores were associated with a positive JTG sign. The mean fiber density between the right NAc core and right medial orbitofrontal gyrus was higher in the JTG + group than the JTG- group. Discussion: We show that the JTG sign is a surrogate marker of waiting impulsivity in PSP-RS patients. Our findings enrich the current literature by deepening our understanding of waiting impulsivity in PSP patients and introducing a novel method for its evaluation.

Extra-Basal Ganglia Brain Structures Are Related to Motor Reserve in Parkinson's Disease.

BACKGROUND: The "motor reserve" is an emerging concept based on the discrepancy between the severity of parkinsonism and dopaminergic degeneration; however, the related brain structures have not yet been elucidated. OBJECTIVE: We investigated brain structures relevant to the motor reserve in Parkinson's disease (PD) in this study. METHODS: Patients with drug-naïve, early PD were enrolled, who then underwent dopamine transporter (DAT) scan and diffusion tensor imaging (DTI). The severity of motor symptoms was evaluated with the Unified Parkinson's Disease Rating Scale score of bradykinesia and rigidity on the more affected side and dopaminergic degeneration of DAT uptake of the more affected putamen. Individual motor reserve estimate (MRE) was evaluated based on the discrepancy between the severity of motor symptoms and dopaminergic degeneration. Using DTI and the Brainnetome atlas, brain structures correlated with MRE were identified. RESULTS: We enrolled 193 patients with drug-naïve PD (mean disease duration of 15.6±13.2 months), and the MRE successfully predicted the increase of levodopa equivalent dose after two years. In the DTI analysis, fractional anisotropy values of medial, inferior frontal, and temporal lobes, limbic structures, nucleus accumbens, and thalamus were positively correlated with the MRE, while no brain structures were correlated with mean diffusivity. Additionally, degree centrality derived from the structural connectivity of the frontal and temporal lobes and limbic structures was positively correlated with the MRE. CONCLUSION: Our results show empirical evidence for MR in PD and brain structures relevant to MR, particularly, the extra-basal ganglia system including the limbic and frontal structures.

Enhanced neuroimaging genetics using multi-view non-negative matrix factorization with sparsity and prior knowledge.

Neuroimaging genetics is a powerful approach to jointly explore genetic features with rich brain imaging phenotypes for neurodegenerative diseases. Conventional imaging genetics approaches based on canonical correlation analysis cannot accommodate multimodal inputs effectively and have limited interpretability. We propose a novel imaging genetics approach based on non-negative matrix factorization (NMF). By leveraging the parsimonious property known as topic modeling in multi-view NMF, we add sparsity constraints and prior information to identify a sparse set of biologically related features across modalities. Thus, our approach incorporates prior knowledge and improves multimodal integration capabilities and interpretability. We applied our algorithm to simulated and real imaging genetics datasets of Parkinson's disease (PD) for performance evaluation. Our algorithm could identify important associated features mapped to interpretable distinct topics more robustly than other methods. It revealed promising features of single-nucleotide polymorphisms and brain regions related to a subset of PD-related clinical scores in a few topics using a real imaging genetic dataset. The proposed imaging genetics approach can reveal novel associations between genetic and neuroimaging features to improve understanding of various neurodegenerative diseases.

Multivariate association between brain function and eating disorders using sparse canonical correlation analysis.

Eating disorder is highly associated with obesity and it is related to brain dysfunction as well. Still, the functional substrates of the brain associated with behavioral traits of eating disorder are underexplored. Existing neuroimaging studies have explored the association between eating disorder and brain function without using all the information provided by the eating disorder related questionnaire but by adopting summary factors. Here, we aimed to investigate the multivariate association between brain function and eating disorder at fine-grained question-level information. Our study is a retrospective secondary analysis that re-analyzed resting-state functional magnetic resonance imaging of 284 participants from the enhanced Nathan Kline Institute-Rockland Sample database. Leveraging sparse canonical correlation analysis, we associated the functional connectivity of all brain regions and all questions in the eating disorder questionnaires. We found that executive- and inhibitory control-related frontoparietal networks showed positive associations with questions of restraint eating, while brain regions involved in the reward system showed negative associations. Notably, inhibitory control-related brain regions showed a positive association with the degree of obesity. Findings were well replicated in the independent validation dataset (n = 34). The results of this study might contribute to a better understanding of brain function with respect to eating disorder.

Prediction of age at onset in Parkinson's disease using objective specific neuroimaging genetics based on a sparse canonical correlation analysis.

The age at onset (AAO) is an important determinant in Parkinson's disease (PD). Neuroimaging genetics is suitable for studying AAO in PD as it jointly analyzes imaging and genetics. We aimed to identify features associated with AAO in PD by applying the objective-specific neuroimaging genetics approach and constructing an AAO prediction model. Our objective-specific neuroimaging genetics extended the sparse canonical correlation analysis by an additional data type related to the target task to investigate possible associations of the imaging-genetic, genetic-target, and imaging-target pairs simultaneously. The identified imaging, genetic, and combined features were used to construct analytical models to predict the AAO in a nested five-fold cross-validation. We compared our approach with those from two feature selection approaches where only associations of imaging-target and genetic-target were explored. Using only imaging features, AAO prediction was accurate in all methods. Using only genetic features, the results from other methods were worse or unstable compared to our model. Using both imaging and genetic features, our proposed model predicted the AAO well (r = 0.5486). Our findings could have significant impacts on the characterization of prodromal PD and contribute to diagnosing PD early because genetic features could be measured accurately from birth.

DEEP NETWORK-BASED FEATURE SELECTION FOR IMAGING GENETICS: APPLICATION TO IDENTIFYING BIOMARKERS FOR PARKINSON'S DISEASE.

Imaging genetics is a methodology for discovering associations between imaging and genetic variables. Many studies adopted sparse models such as sparse canonical correlation analysis (SCCA) for imaging genetics. These methods are limited to modeling the linear imaging genetics relationship and cannot capture the non-linear high-level relationship between the explored variables. Deep learning approaches are underexplored in imaging genetics, compared to their great successes in many other biomedical domains such as image segmentation and disease classification. In this work, we proposed a deep learning model to select genetic features that can explain the imaging features well. Our empirical study on simulated and real datasets demonstrated that our method outperformed the widely used SCCA method and was able to select important genetic features in a robust fashion. These promising results indicate our deep learning model has the potential to reveal new biomarkers to improve mechanistic understanding of the studied brain disorders.

Joint-Connectivity-Based Sparse Canonical Correlation Analysis of Imaging Genetics for Detecting Biomarkers of Parkinson's Disease.

Imaging genetics is a method used to detect associations between imaging and genetic variables. Some researchers have used sparse canonical correlation analysis (SCCA) for imaging genetics. This study was conducted to improve the efficiency and interpretability of SCCA. We propose a connectivity-based penalty for incorporating biological prior information. Our proposed approach, named joint connectivity-based SCCA (JCB-SCCA), includes the proposed penalty and can handle multi-modal neuroimaging datasets. Different neuroimaging techniques provide distinct information on the brain and have been used to investigate various neurological disorders, including Parkinson's disease (PD). We applied our algorithm to simulated and real imaging genetics datasets for performance evaluation. Our algorithm was able to select important features in a more robust manner compared with other multivariate methods. The algorithm revealed promising features of single-nucleotide polymorphisms and brain regions related to PD by using a real imaging genetic dataset. The proposed imaging genetics model can be used to improve clinical diagnosis in the form of novel potential biomarkers. We hope to apply our algorithm to cohorts such as Alzheimer's patients or healthy subjects to determine the generalizability of our algorithm.

Synthesis of edge-rich vertical multilayer graphene nanotube arrays towards high-performance supercapacitors.

In this work, we demonstrate the synthesis of edge-rich vertical multilayer graphene nanotube arrays and edge density-dependent capacitance in a supercapacitor application. We employ Ni-Au multi-block vertical nanotubes fabricated by anodic aluminum oxide template-assisted electrodeposition as a designer substrate for multilayer graphene growth. This edge generation of graphene relies on the distinct carbon solubility of Au and Ni under chemical vapor deposition. Therefore the graphene edge density is tailorable by controlling the total number of bimetallic interfaces of alternating electrodeposited Ni and Au blocks. In supercapacitor applications, we found that the capacitance heavily correlates to the graphene edge densities. Multilayer graphene nanotubes with 18 bimetallic interfaces exhibit 8.4 times higher capacitance than those without interfaces. This experimental evaluation shows great promise to significantly enhance the supercapacitor capacitance by creating high-density edges on multilayer graphene.

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease.

Depression is one of the most common and important neuropsychiatric symptoms in Parkinson's disease and often becomes worse as Parkinson's disease progresses. However, the underlying mechanisms of depression in Parkinson's disease are not clear. The aim of our study was to find genetic features related to depression in Parkinson's disease using an imaging genetics approach and to construct an analytical model for predicting the degree of depression in Parkinson's disease. The neuroimaging and genotyping data were obtained from an openly accessible database. We computed imaging features through connectivity analysis derived from tractography of diffusion tensor imaging. The imaging features were used as intermediate phenotypes to identify genetic variants according to the imaging genetics approach. We then constructed a linear regression model using the genetic features from imaging genetics approach to describe clinical scores indicating the degree of depression. As a comparison, we constructed other models using imaging features and genetic features based on references to demonstrate the effectiveness of our imaging genetics model. The models were trained and tested in a five-fold cross-validation. The imaging genetics approach identified several brain regions and genes known to be involved in depression, with the potential to be used as meaningful biomarkers. Our proposed model using imaging genetic features predicted and explained the degree of depression in Parkinson's disease appropriately (adjusted R2 larger than 0.6 over five training folds) and with a lower error and higher correlation than with other models over five test folds.

Synthesis of octahedral gold tip-blobbed nanoparticles and their dielectric sensing properties.

Site-selective synthesis of nanostructures is an important topic in the nanoscience community. Normally, the difference between seeds and deposition atoms in terms of crystallinity triggers the deposition atoms to grow initially at the specific site of nucleation. It is more challenging to control the deposition site of atoms that have the same composition as the seeds because the atoms tend to grow epitaxially, covering the whole surface of the seed nanoparticles. Gold (Au) nano-octahedrons used as seeds in this study possess obvious hierarchical surface energies depending on whether they are at vertices, edges, or terraces. Although vertices of Au nano-octahedrons have the highest surface energy, it remains a challenge to selectively deposit Au atoms at the vertices but not at the edges and faces; this selectivity is required to meet the ever-increasing demands of engineered nanomaterial properties. This work demonstrates an easy and robust method to precisely deposit Au nanoparticles at the vertices of Au nano-octahedrons via wet-chemical seed-mediated growth. The successful synthesis of octahedral Au tip-blobbed nanoparticles (Oh Au TBPs) benefited from the cooperative use of thin silver (Ag) layers at the surface of Au nano-octahedron seeds and iodide ions in the Au growth solution. As-synthesized Au nanostructures (i.e., Au TBPs) gave rise to hybrid optical properties, as evidenced from the UV-vis-NIR extinction spectra, in which a new extinction peak appeared after Au nanoparticles were formed at the vertices of Au nano-octahedrons. A sensitivity evaluation toward dielectric media of a mixture of dimethyl sulfoxide and water suggested that Au TBPs were more optically sensitive compared to the original Au nano-octahedrons. The method demonstrated in this work is promising in the synthesis of advanced Au nanostructures with hybrid optical properties for versatile applications, by engineering the surface energy of vertex-bearing Au nanostructures to trigger site-selective overgrowth of congener Au atoms.

Thyroid nodules and cancer in children and adolescents affected by Hashimoto's thyroiditis.

OBJECTIVE: To investigate the rates of thyroid nodules and cancer in pediatric cases of Hashimoto's thyroiditis (HT) in Korea. METHODS: We retrospectively reviewed 89 pediatric and adolescent patients (age, 3-18.0 years) with HT who underwent thyroid ultrasonography (US) at our institution from February 2006 to July 2016. The diagnosis of HT was based on the presence of thyroid autoantibodies. The presence of any thyroid nodules with US and cytopathologic features was analyzed. The malignancy rate was also determined. RESULTS: Thyroid nodules were in 20 of the 89 patients (22.4%). Eight of these 20 patients (40%) had colloid cysts, two (10%) had nodular hyperplasia, one (5%) had follicular adenoma, and two (10%) had lymphocytic thyroiditis. Seven of the 89 patients (7.9%) were confirmed to have a malignancy, all of which were papillary thyroid carcinoma (PTC); of those, five patients had diffuse sclerosing variant PTC, and two had conventional PTC on pathology. CONCLUSION: The prevalence of thyroid nodules in children and adolescents with HT was 22.4%. The malignancy rate of children with HT was 7.9%. The malignancy rate among thyroid nodules was 35%, which is higher than the 26% rate generally reported for children with nodules. Therefore, using thyroid US to survey known or suspected thyroid nodules might be helpful in children and adolescents with HT and may provide further useful diagnostic information. Advances in knowledge: Thyroid US could help to assess HT patients who have known or suspected thyroid nodules.

Accessory gallbladder in an intrahepatic location mimicking a cystic tumor of the liver: A case report.

BACKGROUND: Double gallbladder (GB) is a rare congenital anomaly of the biliary system characterized by the presence of an accessory GB. CLINICAL FINDINGS: A 38-year-old female presented with a history of right upper quadrant (RUQ) pain. Computed tomography (CT) showed a lobulated cystic mass involving the center portion of liver. Magnetic resonance imaging (MRI) additionally revealed a tubular structure of T2 bright signal intensity (SI), which connected the cystic lesion of the liver to the bile duct. Preoperative endoscopic retrograde cholangiopancreatography (ERCP) confirmed the connection between the intrahepatic cystic lesion and the left main hepatic duct. We regarded as a cystic mass with biliary communication, such as a cystic intraductal papillary neoplasm of the bile duct (IPNB) or localized Caroli disease. The patient underwent partial hepatectomy for the cystic mass of the liver and a final diagnosis of chronic inflammation of an intrahepatically located accessory GB was made. CONCLUSION: We report a case of an accessory GB in an intrahepatic location mimicking a cystic mass such as cystic IPNB or localized Caroli disease of the liver showing a cystic mass with biliary communication.

Primary Pleural Synovial Sarcoma with Metastatic Cardiac Involvement: A Case Report.

Primary pleuropulmonary synovial sarcomas are rare soft tissue malignancies; combined metastatic involvement of the heart is extremely rare. In this case report, a 17-year-old female presented with a history of chest pain. Chest radiographs revealed a round mass in the left upper hemithorax, and computed tomography (CT) showed a well-defined heterogeneous enhancing mass abutting the pleura. A core needle biopsy revealed malignant spindle cells. Surgical resection was performed, and a final diagnosis of primary pleural synovial sarcoma, monophasic fibrous type, was made. The patient underwent radical irradiation and chemotherapy and remained stable for 28 months until a follow-up chest CT showed a poorly enhancing nodule in the left pericardial region that enlarged after 5 months. Surgical resection was performed. Histological examination confirmed metastatic cardiac involvement from a primary pleural synovial sarcoma. We report this unusual case of a primary pleural synovial sarcoma metastasis to the heart.

Highly flexible, proton-conductive silicate glass electrolytes for medium-temperature/low-humidity proton exchange membrane fuel cells.

We demonstrate highly flexible, proton-conductive silicate glass electrolytes integrated with polyimide (PI) nonwoven fabrics (referred to as "b-SS glass electrolytes") for potential use in medium-temperature/low-humidity proton exchange membrane fuel cells (PEMFCs). The b-SS glass electrolytes are fabricated via in situ sol-gel synthesis of 3-trihydroxysilyl-1-propanesulfonic acid (THPSA)/3-glycidyloxypropyl trimethoxysilane (GPTMS) mixtures inside PI nonwoven substrates that serve as a porous reinforcing framework. Owing to this structural uniqueness, the b-SS glass electrolytes provide noticeable improvements in mechanical bendability and membrane thickness, in comparison to typical bulk silicate glass electrolytes that are thick and easily fragile. Another salient feature of the b-SS glass electrolytes is the excellent proton conductivity at harsh measurement conditions of medium temperature/low humidity, which is highly important for PEMFC-powered electric vehicle applications. This beneficial performance is attributed to the presence of a highly interconnected, proton-conductive (THPSA/GPTMS-based) silicate glass matrix in the PI reinforcing framework. Notably, the b-SS glass electrolyte synthesized from THPSA/GPTMS = 9/1 (mol/mol) exhibits a higher proton conductivity than water-swollen sulfonated polymer electrolyte membranes (here, sulfonated poly(arylene ether sulfone) and Nafion are chosen as control samples). This intriguing behavior in the proton conductivity of the b-SS glass electrolytes is discussed in great detail by considering its structural novelty and Grotthuss mechanism-driven proton migration that is strongly affected by ion exchange capacity (IEC) values and also state of water.

Hydrophilicity/porous structure-tuned, SiO2/polyetherimide-coated polyimide nonwoven porous substrates for reinforced composite proton exchange membranes.

Porous substrate-reinforced composite proton exchange membranes have drawn considerable attention due to their promising application to polymer electrolyte membrane fuel cells (PEMFCs). In the present study, we develop silica (SiO(2)) nanoparticles/polyetherimide (PEI) binders-coated polyimide (PI) nonwoven porous substrates (referred to as "S-PI substrates") for reinforced composite membranes. The properties of S-PI substrates, which crucially affect the performance of resulting reinforced composite membranes, are significantly improved by controlling the hygroscopic SiO(2) particle size. The 40 nm S-PI substrate (herein, 40 nm SiO(2) particles are employed) shows the stronger hydrophilicity and highly porous structure than the 530 nm S-PI substrate due to the larger specific surface area of 40 nm SiO(2) particles. Based on the comprehensive understanding of the S-PI substrates, the structures and performances of the S-PI substrates-reinforced composite membranes are elucidated. In comparison with the 530 nm S-PI substrate, the hydrophilicity/porous structure-tuned 40 nm S-PI substrate enables the impregnation of a large amount of a perfluorosulfonic acid ionomer (Nafion), which thus contributes to the improved proton conductivity of the reinforced Nafion composite membrane. Meanwhile, the reinforced Nafion composite membranes effectively mitigate the steep decline of proton conductivity with time at low humidity conditions, as compared to the pristine Nafion membrane. This intriguing finding is further discussed by considering the unusual features of the S-PI substrates and the state of water in the reinforced Nafion composite membranes.