Clinical correlates and advanced processing of the dopamine transporter spect - applications in parkinsonism.

La visualización del transportador de dopamina (DAT) a través del SPECT con [123I]FP-CIT es una prueba de imagen ampliamente usada en el diagnóstico de la enfermedad de Parkinson (EP) y otros trastornos del movimiento que cursan con síntomas parkinsonianos. Dicha imagen permite visualizar y cuantificar los niveles de DAT en el estriado y sus regiones putamen y caudado, y es por tanto una herramienta útil para evaluar in-vivo el estado de las terminales presinápticos dopaminérgicos de la vía nigroestriada. En la práctica clínica es comúnmente utilizado para la diferenciación de parkinsonismos neurodegenerativos con afectación presináptica y otros trastornos del movimiento con síntomas similares pero sin afectación presináptica como el temblor esencial. En la imagen se suele observar un patrón de degeneración postero-anterior que se corresponde con la progresión de síntomas en la EP debido a la afectación progresiva de los circuitos de los ganglios basales. De hecho, numerosos estudios han mostrado que la falta de DAT en el putamen y caudado se correlacionan con síntomas motores y cognitivos, respectivamente. Sin embargo, a pesar de su uso extendido, su uso clínico dado los métodos de evaluación actuales se limita a determinar la presencia o no de degeneración nigroestriada. En esta tesis se plantea como hipótesis que el uso de métodos de procesamiento y evaluación más sofisticados, utilizando técnicas de procesamiento de imágenes y de reconocimiento de patrones a nivel de vóxel, podría potenciar el desarrollo de nuevas aplicaciones clínicas; incluyendo la evaluación de síntomas y el diagnóstico diferencial entre parkinsonismos. Para ello, hemos caracterizado clínicamente y recogido imágenes de SPECT de cientos de pacientes con EP y otros parkinsonismos, persiguiendo dos objetivos globales: i) investigar ciertos conceptos actuales sobre los síntomas motores y cognitivos en la EP; y ii) desarrollar nuevos métodos de procesamiento y evaluación que permitan extender el rango actual de aplicaciones clínicas de dicha prueba. Se presentan un total de 5 publicaciones agrupadas en dos temáticas, una para cada objetivo global. En la primera temática, se engloban dos trabajos con títulos: 1) Lower levels of uric acid and striatal dopamine in non-tremor dominant Parkinson's disease subtype, Plos One 2017 Mar 30;12(3):e0174644; y 2) Genetic factors influencing frontostriatal dysfunction and the development of dementia in Parkinson's disease, Plos One 2017 Apr 11;12(4):e0175560. En el trabajo 1 se investigaron las diferencias entre los niveles de ácido úrico y dopamina estriatal en los subtipos motores de EP: tremorígeno, intermedio, y con trastorno de la marcha e inestabilidad postural. Estudiamos 75 pacientes con EP de larga evolución y encontramos que aquellos que presentaron un predominio de temblor al inicio y mantuvieron este fenotípo clinico durante el curso de la enfermedad, tuvieron niveles de ácido úrico y dopamina estriatal mayores que aquellos que desarrollaron trastorno de la marcha e inestabilidad postural. Además, los niveles de ácido úrico y de dopamina estriatal se correlacionaron. Como conclusión, especulamos que niveles bajos de este antioxidante natural (el ácido úrico) puede reducer los niveles de neuroprotección y por tanto influenciar el perfil y curso de fenotipo motor en la EP. En el trabajo 2 se investigó la contribución de los principales factores genéticos descritos en la literatura en los síndromes duales de deterioro cognitivo en la EP (fronto-estriatal que conlleva un alto riesgo de síndrome disejecutivo – causado por falta de dopamina – y posterior-cortical que conlleva un alto riesgo de demencia). Evaluamos la imagen, el estado cognitivo y el genotipo de 298 pacientes con EP. Como resultado, observamos que el alelo APOE2, los polimorfismos SNCA rs356219 y COMT Val158Met, y las variantes patogénicas en GBA se asociaron con los niveles de denervación dopaminérgica estriatal, mientras que el alelo APOE4 y de nuevo las variaciones patogénicas en GBA se asociaron con el desarrollo de demencia (sugiriendo un doble rol del gen GBA). No encontramos ninguna relación del haplotipo MAPT H1 en ninguno de los síndromes. Concluimos que la dicotomía de los síndromes duales puede estar conducida por una dicotomía en estos factores genéticos. En la segunda temática, se presentan otros 3 trabajos más centrados en el desarrollo de metodología, titulados: 3) Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson's disease using [123I]FP-CIT SPECT, European Journal of Nuclear Medicine and Molecular Imaging, 2015 Jan;42(1):112-9; 4) A Bayesian spatial model for neuroimaging using multiscale functional parcellations, En revisión en la revista euroimage; y un último trabajo que está en elaboración y cuyos resultados preliminares fueron presentados recientemente: 5) Probabilistic intensity normalization of PET/SPECT images via Variational mixture of Gamma distributions, 30th Neural Information and Processing Systems Conference, November 2016, Barcelona, Spain. En el trabajo 3 se desarrollaron algoritmos usando imágenes de SPECT para distinguir un parkinsonismo secundario – el parkinsonismo vascular (PV) – de la EP. Observamos que una simple regresión logística – incluyendo los valores medios de captación estriatales, junto con el sexo, la edad, y los años de evolución – diferenció ambas entidades con un 90% de exactitud. De manera similar, encontramos que el uso de algoritmos objetivos y automáticos usando técnicas de machine learning basadas en vóxeles también discriminaron ambas entidades con un 90% de exactitud. Concluimos que el diagnóstico diferencial de ambas enfermedades puede ser asistido por algoritmos automáticos basados en imagen. En el trabajo 4 se desarrolló una nueva metodología, más allá del método estándar basado en vóxeles, para realizar inferencias en neuroimagen funcional. Se desarrolló un modelo multivariado espacial que permitió modelar imágenes de SPECT de sujetos sanos de manera muy eficiente con un número de parámetros muy inferior al número de vóxeles. Dicho modelo consiste en una superposición lineal de funciones base utilizando subparcelaciones multi-escala del estriado, éstas obtenidas tras procesar imágenes de resonancia magnética funcional. También demostramos la utilidad de nuestro modelo para desarrollar aplicaciones clínicas mediante la construcción de clasificadores para diferenciar la EP de controles sanos y un parkinsonismo atípico: la parálisis supranuclear progresiva. Esta nueva metodología ofrece ventajas sin precedentes para el análisis de neuroimagen con respecto al clásico modelo lineal general univariado basado en vóxel, incluyendo: i) mayor interpretabilidad de las señales cerebrales; ii) modelos parsimoniosos y por tanto incremento del poder estadístico; y iii) modelado de la correlación espacial entre regiones y a distintos niveles de granuralidad en neuroimagen funcional. Además, desarrollamos metodología bayesiana para detectar de manera automática (y cuantificar la incertidumbre) las regiones cerebrales que estén relacionadas con ciertas variables fenotípicas. En el trabajo 5 se desarrolló un método para armonizar la intensidad de las imágenes de SPECT producidas por distintos fabricantes (y calibración) de cámaras Gamma. El método se basa en modelar el histograma de la imagen con un modelo mixto de distribuciones Gamma. Se utilizó la función de densidad acumulada de la distribución Gamma que modela la región específica de captación para reparametrizar la imagen con valores de vóxel entre 0 y 1. Observamos que dicha normalización mejoró sustancialmente (hasta un 10%) el diagnóstico de EP cuando los algoritmos se desarrollaron usando imágenes de distintas cámaras y/o calibraciones. Dicha normalización puede suponer un paso clave en pre-procesado de estas imágenes de cara a la realización de estudios multicéntricos y el desarrollo de aplicaciones clínicas generalizables. Como conclusión es importante resaltar la relevancia de los trabajos. En los trabajos 1 y 2 hemos aportado resultados con biomarcadores de valor pronóstico en la progresión de la EP. En los trabajos 3, 4 y 5, hemos aportado una nueva metodología, muy superior a la existente, de procesamiento y evaluación de esta prueba de imagen. La metodología desarrollada en el trabajo 4 permite explorar regiones cerebrales a un de nivel de complejidad espacial y granularidad sin precedentes. Por ello, nuestro modelo podría captar las diferencias entre las imágenes de pacientes con distintas patologías y/o entre síntomas específicos residir en patrones espaciales sutiles y complejos. De hecho, en los trabajos 3 y 4 aportamos resultados excelentes en la diferenciación de la EP con otros síndromes parkinsonianos. Además, el trabajo 5 tiene el potencial de constituirse en el campo como un paso fundamental de pre-procesado, especialmente en estudios ulticéntricos y estudios que pretendan desarrollar aplicaciones clínicas generalizables, independientemente de la cámara Gamma y el centro donde se realice la prueba. Es importante señalar además que los métodos desarrollados se podrían igualmente aplicar para procesar y evaluar otro tipo de imágenes de medicina nuclear y/u otras regiones cerebrales. Es por ello que esperamos que este trabajo tenga un gran impacto en general en la evaluación de este tipo de imágenes y en el desarrollo de algoritmos que den soporte a la decisiones clínicas en trastornos del movimiento y potencialmente en otras enfermedades.The imaging of the dopamine transporter (DAT) with [123I]FP-CIT SPECT is a routinely used assessment in the diagnostic pipeline of Parkinson’s disease (PD) and other movement disorders that present with parkinsonian symptoms. In this scan, the levels of striatal DAT can be visualized and quantified, also at the region-of-interest (ROI) level in putamen and caudate, and therefore it constitutes an useful tool to assess in-vivo the state of the dopaminergic presynaptic terminals in the nigrostriatal pathway. In routine clinical practice it is especially utilized for the differential diagnlosis of presynaptic neurodegenerative disorders like PD and other non-presynaptic movement disorders like essential tremor. Also, numerous research studies have shown that striatal DAT deficits quantitatively correlate with motor and cognitive impairment in PD. Indeed, it can be seen in the image a posterior-to-anterior pattern of degeneration that well corresponds with disease progression due to the progressive lost of dopaminergic input into the motor and associative loops between the basal ganglia and the cortex. However, despite its known utility and widespread availability, its use with current assessment methods in real clinical practice is limited to determining the presence of nigrostriatal degeneration at a single-subject level in a binary fashion. We hypothesized in this thesis that an enhanced processing and assessment of this scan with modern image processing and pattern recognition techniques may help to boost its use in the clinic with new and more accurate applications, including symptom risk assessment and differential diagnosis with other parkinsonisms. We collected DAT scans of several hundreds of well-clinicallyphenotyped patients with PD and other parkinsonims, envisaging two main global objectives: i) to investigate some trending hypotheses and concepts about the motor and cognitive impairment in PD; and ii) to develop new processing and evaluation strategies with computational techniques to shed light into new clinical applications. A total of 5 publications are herein presented and grouped in two themes, one for each global objective. In the first theme, two works are presented, entitled: 1) Lower levels of uric acid and striatal dopamine in non-tremor dominant Parkinson's disease subtype, Plos One 2017 Mar 30;12(3):e0174644; and 2) Genetic factors influencing frontostriatal dysfunction and the development of dementia in Parkinson's disease, Plos One 2017 Apr 11;12(4):e0175560. In work 1 we investigated the differences in uric acid and striatal DAT in PD motor subtypes: tremor-dominant, intermediate, or postural instability and gait disorder (PIGD). We studied 75 PD patients of long-term evolution and found that those who presented with a tremor onset and maintained predominance of tremor, or, to a lesser extent, evolved to an intermediate phenotype, had higher levels of uric acid and striatal DAT binding than those who developed a IGD phenotype. We also found that uric acid and striatal DAT levels were highly correlated. We speculate that low levels of this natural antioxidant may lead to a lesser degree of neuroprotection and could therefore influence the motor phenotype and course. In work 2 we investigated the contribution to the dual syndromes of cognitive impairment in PD (frontostriatal dopamine-mediated and posterior cortical leading to dementia) of the main genetic risk factors decribed in the literature. We evaluated the scans, the cognitive status, and the genotypes of 298 PD patients and found that APOE2 allele, SNCA rs356219 and COMT Val158Met polymorphisms, and deleterious variants in GBA influenced striatal dopaminergic depletion, and that APOE4 allele and deleterious variants in GBA influenced dementia, thus suggesting a doubleedged role for GBA. We did not found any role of MAPT H1 haplotype. We conclude that the dichotomy of the dual syndromes may be driven by a broad dichotomy in these genetic factors. In the second theme, we present three other works with more focus on methodology, entitled: 3) Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson's disease using [123I]FP-CIT SPECT, European Journal of Nuclear Medicine and Molecular Imaging, 2015 Jan;42(1):112-9; 4) A Bayesian spatial model for neuroimaging using multiscale functional parcellations, Under Review in Neuroimage; and a last piece of work that it is in preparation for submission and that I have adapted for this thesis from 5) Probabilistic intensity normalization of PET/SPECT images via Variational mixture of Gamma distributions, 30th Neural Information and Processing Systems Conference, November 2016, Barcelona, Spain. In work 3 we developed analytical models using DAT SPECT data to discriminate vascular parkinsonism (VP) from PD. We collected scans from 80 VP and 164 PD and found that a simple logistic regression using the quantification of the striatal subregions putamen and caudate together with age, sex and disease duration discriminated both entities with over 90% accuracy. Also, we found that the use of more automated and rater-independent machine learning algorithms such as support vector machines with the voxel-wise data of the striatum also gives discrimination accuracy over 90%. We conclude that the differential diagnosis of both diseases can be aided by automated image-based algorithms. In work 4 we developed a new anaylsis framework to perform inferences with functional neuroimaging data. We developed a multivariate spatial model by which an imaged brain region can be efficiently represented in low dimensions with a linear superposition of basis functions. To demonstrate, we accurately modeled DATSCAN images from healthy subjects with a linear combination of multi-resolutional striatum parcellations derived from functional MRI experiments. We also demonstrate the utility of our model to develop clinical application by constructing accurate classifiers to differentiate PD from normal controls and patients with an atypical parkinsonism: the progressive supranuclear palsy. This approach offers unprecedent benefits with respect to classical univariate voxel methods, including: i) greater biological interpretability of the detected brain signals ii) parsimonity in the models and hence gain in statistical power; and iii) multi-range modeling of the spatial dependencies in brain images. Furthermore, we provide a bayesian analysis framework to automatically identifying brain subregions/subnetworks that are meaningful for particular phenotypic variables. In work 5 we developed a voxel-based intensity normalization method for DAT SPECT images aiming at overcoming the liminations of the current ROI-based normalization standard, namely ROI delineation dependence and intensity values dependence on Gamma camera. We found that the intensity histogram of a DAT SPECT image can be modeled as a mixture model of Gamma distributions. The cumulative distribution function (CDF) of the fitted Gamma distributions can be used to re-cast the voxel intensity values into a new normalized feature space between 0 and 1. We found that this re-parametrization equalized intensity across cameras and drastically improved the accuracy of PD diagnosis (up to 10%) when images from different cameras were pooled. Importantly, our method may constitute a key pre-processing step for group-level and multi-center studies. As a final remark, it is important to stress the relevance of the work. In the works 1 and 2, we have provided new insights on biomarkers that have prognostic value in the progression of PD. In the works 3, 4 and 5, which set the grounds of a new powerful approach to process and evaluate these images. The machine learning framework developed in work 4) allows to exploring brain regions at a unprecedent level of spatial complexity and granurality. Thus, challenging tasks such as the differential diagnosis between different parkinsonian disorders or the identification of fine-grained regions/networks responsible for specific parkinsonian symptoms can be tackled with the proposed approach. In fact, we obtained excellent results in works 3 and 4 in the differentiation of PD from other parkinsonian syndromes. Also, the work 5 may constitute a fundamental pre-processing step, especially in multi-center studies and studies aiming at developing generalizable clinical applications, regardless of the Gamma camera manufacturer and site where the scan is made. It is important to note that, besides DATSCAN, these methods could be also applied to other nuclearmedicine images and/or brain regions. We hope that this work will have an impact in the assessment of this type of images and in the development of algorithms supporting clinical decisions in movement disorders and potentially in other diseases as well.Premio Extraordinario de Doctorado U

Quantitative Intensity Harmonization of Dopamine Transporter SPECT Images Using Gamma Mixture Models

PURPOSE: Differences in site, device, and/or settings may cause large variations in the intensity profile of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images. However, the current standard to evaluate these images, the striatal binding ratio (SBR), does not efficiently account for this heterogeneity and the assessment can be unequivalent across distinct acquisition pipelines. In this work, we present a voxel-based automated approach to intensity normalize such type of data that improves on cross-session interpretation. PROCEDURES: The normalization method consists of a reparametrization of the voxel values based on the cumulative density function (CDF) of a Gamma distribution modeling the specific region intensity. The harmonization ability was tested in 1342 SPECT images from the PPMI repository, acquired with 7 distinct gamma camera models and at 24 different sites. We compared the striatal quantification across distinct cameras for raw intensities, SBR values, and after applying the Gamma CDF (GDCF) harmonization. As a proof-of-concept, we evaluated the impact of GCDF normalization in a classification task between controls and Parkinson disease patients. RESULTS: Raw striatal intensities and SBR values presented significant differences across distinct camera models. We demonstrate that GCDF normalization efficiently alleviated these differences in striatal quantification and with values constrained to a fixed interval [0, 1]. Also, our method allowed a fully automated image assessment that provided maximal classification ability, given by an area under the curve (AUC) of AUC = 0.94 when used mean regional variables and AUC = 0.98 when used voxel-based variables. CONCLUSION: The GCDF normalization method is useful to standardize the intensity of DAT SPECT images in an automated fashion and enables the development of unbiased algorithms using multicenter datasets. This method may constitute a key pre-processing step in the analysis of this type of images.Instituto de Salud Carlos III FI14/00497 MV15/00034Fondo Europeo de Desarrollo Regional FI14/00497 MV15/00034ISCIII-FEDER PI16/01575Wellcome Trust UK Strategic Award 098369/Z/12/ZNetherland Organization for Scientific Research NWO-Vidi 864-12-00

GBA Variants Influence Motor and Non-Motor Features of Parkinson’s Disease.

The presence of mutations in glucocerebrosidase (GBA) gene is a known factor increasing the risk of developing Parkinson’s disease (PD). Mutations carriers have earlier disease onset and are more likely to develop neuropsychiatric symptoms than other sporadic PD cases. These symptoms have primarily been observed in Parkinson’s patients carrying the most common pathogenic mutations L444P and N370S. However, recent findings suggest that other variants across the gene may have a different impact on the phenotype as well as on the disease progression. We aimed to explore the influence of variants across GBA gene on the clinical features and treatment related complications in PD. In this study, we screened the GBA gene in a cohort of 532 well-characterised PD patients and 542 controls from southern Spain. The potential pathogeniticy of the identified variants was assessed using in-silico analysis and subsequently classified as benign or deleterious. As a result, we observed a higher frequency of GBA variants in PD patients (12.2% vs. 7.9% in controls, p = 0.021), earlier mean age at disease onset in GBA variant carriers (50.6 vs. 56.6 years; p = 0.013), as well as more prevalent motor and non-motor symptoms in patients carrying dele- terious variants. In addition, we found that dopaminergic motor complications are influenced by both benign and deleterious variants. Our results highlight the fact that the impact on the phenotype highly depends on the potential pathogenicity of the carried variants. Therefore, the course of motor and non-motor symptoms as well as treatment-related motor complica- tions could be influenced by GBA variants.Ministerio de Economı́a y Competitividad SAF2007-60700.Instituto de Salud Carlos III PI10/01674, PI13/01461, PI14/01823.Consejerı́a de Economı́a, Innovación, Ciencia y Empleo CVI-02526, CTS- 7685Consejería de Igualdad, Salud y Políticas Sociales PI-0377/2007, PI-0741/2010, PI-0437-2012, PI-0471-201

GDNF gene is associated with tourette syndrome in a family study

Huertas-Fernández, Ismael et al.[Background] Tourette syndrome is a disorder characterized by persistent motor and vocal tics, and frequently accompanied by the comorbidities attention deficit hyperactivity disorder and obsessive-compulsive disorder. Impaired synaptic neurotransmission has been implicated in its pathogenesis. Our aim was to investigate the association of 28 candidate genes, including genes related to synaptic neurotransmission and neurotrophic factors, with Tourette syndrome.[Methods] We genotyped 506 polymorphisms in a discovery cohort from the United States composed of 112 families and 47 unrelated singletons with Tourette syndrome (201 cases and 253 controls). Genes containing significant polymorphisms were imputed to fine-map the signal(s) to potential causal variants. Allelic analyses in Tourette syndrome cases were performed to check the role in attention deficit hyperactivity disorder and obsessive-compulsive disorder comorbidities. Target polymorphisms were further studied in a replication cohort from southern Spain composed of 37 families and three unrelated singletons (44 cases and 73 controls).[Results] The polymorphism rs3096140 in glial cell line–derived neurotrophic factor gene (GDNF) was significant in the discovery cohort after correction (P = 1.5 × 10−4). No linkage disequilibrium was found between rs3096140 and other functional variants in the gene. We selected rs3096140 as target polymorphism, and the association was confirmed in the replication cohort (P = 0.01). No association with any comorbidity was found.[Conclusions] As a conclusion, a common genetic variant in GDNF is associated with Tourette syndrome. A defect in the production of GDNF could compromise the survival of parvalbumin interneurons, thus altering the excitatory/inhibitory balance in the corticostriatal circuitry. Validation of this variant in other family cohorts is necessary. © 2015 International Parkinson and Movement Disorder SocietyThis study was supported by New Jersey Center for Tourette Syndrome and Associated Disorders (NJCTS), the National Institute of Mental Health (R01MH092293), the Instituto de Salud Carlos III (PI10/01674, PI13/01461, PI14/01823), the Consejería de Economía, Innovación, Ciencia y Empresa de la Junta de Andalucía (CVI-02526, CTS-7685), the Consejería de Salud y Bienestar Social de la Junta de Andalucía (PI-0741/2010, PI-0437-2012, PI-0471-2013), the Sociedad Andaluza de Neurología, the Fundación Alicia Koplowitz, the Fundación Mutua Madrileña and the Jaques and Gloria Gossweiler Foundation. Ismael Huertas Fernández was supported by the “PFIS” program, Pilar Gómez Garre was supported by the “Miguel Servet” program, and Juan Francisco Martín Rodríguez was supported by the “Sara Borrell” program, all 3 from the Instituto de Salud Carlos III.Peer Reviewe

Levodopa-Induced Dyskinesia in Parkinson Disease Specifically Associates with Dopaminergic Depletion in Sensorimotor-Related Functional Subregions of the Striatum

[Purpose] To determine whether the development of levodopa-induced dyskinesia (LID) in Parkinson disease (PD) specifically relates to dopaminergic depletion in sensorimotor-related subregions of the striatum.[Methods] Our primary study sample consisted of 185 locally recruited PD patients, of which 73 (40%) developed LID. Retrospective 123I-FP-CIT SPECT data were used to quantify the specific dopamine transporter (DAT) binding ratio within distinct functionally defined striatal subregions related to limbic, executive, and sensorimotor systems. Regional DAT levels were contrasted between patients who developed LID (PD + LID) and those who did not (PD-LID) using analysis of covariance models controlled for demographic and clinical features. For validation of the findings and assessment of the evolution of LID-associated DAT changes from an early disease stage, we also studied serial 123I-FP-CIT SPECT data from 343 de novo PD patients enrolled in the Parkinson Progression Marker’s Initiative using mixed linear model analysis.[Results] Compared with PD-LID, DAT level reductions in PD + LID patients were most pronounced in the sensorimotor striatal subregion (F = 5.99, P = 0.016) and also significant in the executive-related subregion (F = 5.30, P = 0.023). In the Parkinson Progression Marker’s Initiative cohort, DAT levels in PD + LID (n = 161, 47%) were only significantly reduced compared with PD-LID in the sensorimotor striatal subregion (t = −2.05, P = 0.041), and this difference was already present at baseline and remained largely constant over time.[Conclusion] Measuring DAT depletion in functionally defined sensorimotor-related striatal regions of interest may provide a more sensitive tool to detect LID-associated dopaminergic changes at an early disease stage and could improve individual prognosis of this common clinical complication in PD.Peer reviewe

Gaya Desain Kolonial Belanda Dan Cina Pada Interior Hotel Ganefo Surabaya

Ganefo Hotel was originally a residence of an ex- lieutenant of China who was assigned by the Dutch to oversee the activities of the local population. Although at this time the building has functioned as a hotel, the styles of Dutch Colonial and Chinese are applied to the building is still maintained until now. The combination of styles in this hotel makes it an interesting object to be researched. This study aims to analyze the Dutch Colonial and Chinese styles which still exist in this building. The method used in this study is descriptive qualitative method. The result demonstrates the application of Dutch Colonial design styles and China on the interior Ganefo Hotel Surabaya which is seen on the building orientation, layout, organization of space, space-forming elements, transition elements, furniture, and decorative elements

5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

El V Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2019, realizado del 6 al 8 de febrero de 2019 y organizado por la Universidad Politécnica Salesiana, ofreció a la comunidad académica nacional e internacional una plataforma de comunicación unificada, dirigida a cubrir los problemas teóricos y prácticos de mayor impacto en la sociedad moderna desde la ingeniería. En esta edición, dedicada a los 25 años de vida de la UPS, los ejes temáticos estuvieron relacionados con la aplicación de la ciencia, el desarrollo tecnológico y la innovación en cinco pilares fundamentales de nuestra sociedad: la industria, la movilidad, la sostenibilidad ambiental, la información y las telecomunicaciones. El comité científico estuvo conformado formado por 48 investigadores procedentes de diez países: España, Reino Unido, Italia, Bélgica, México, Venezuela, Colombia, Brasil, Estados Unidos y Ecuador. Fueron recibidas un centenar de contribuciones, de las cuales 39 fueron aprobadas en forma de ponencias y 15 en formato poster. Estas contribuciones fueron presentadas de forma oral ante toda la comunidad académica que se dio cita en el Congreso, quienes desde el aula magna, el auditorio y la sala de usos múltiples de la Universidad Politécnica Salesiana, cumplieron respetuosamente la responsabilidad de representar a toda la sociedad en la revisión, aceptación y validación del conocimiento nuevo que fue presentado en cada exposición por los investigadores. Paralelo a las sesiones técnicas, el Congreso contó con espacios de presentación de posters científicos y cinco workshops en temáticas de vanguardia que cautivaron la atención de nuestros docentes y estudiantes. También en el marco del evento se impartieron un total de ocho conferencias magistrales en temas tan actuales como la gestión del conocimiento en la universidad-ecosistema, los retos y oportunidades de la industria 4.0, los avances de la investigación básica y aplicada en mecatrónica para el estudio de robots de nueva generación, la optimización en ingeniería con técnicas multi-objetivo, el desarrollo de las redes avanzadas en Latinoamérica y los mundos, la contaminación del aire debido al tránsito vehicular, el radón y los riesgos que representa este gas radiactivo para la salud humana, entre otros

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

Parieto-motor cortical dysfunction in primary cervical dystonia

Dystonia is considered as a motor network disorder involving the dysfunction of the posterior parietal cortex, a region involved in preparing and executing reaching movements

A genetic analysis of a Spanish population with early onset Parkinson’s disease

[Introduction] Both recessive and dominant genetic forms of Parkinson’s disease have been described. The aim of this study was to assess the contribution of several genes to the pathophysiology of early onset Parkinson’s disease in a cohort from central Spain.[Methods/patients] We analyzed a cohort of 117 unrelated patients with early onset Parkinson’s disease using a pipeline, based on a combination of a next-generation sequencing panel of 17 genes previously related with Parkinson’s disease and other Parkinsonisms and CNV screening.[Results] Twenty-six patients (22.22%) carried likely pathogenic variants in PARK2, LRRK2, PINK1, or GBA. The gene most frequently mutated was PARK2, and p.Asn52Metfs*29 was the most common variation in this gene. Pathogenic variants were not observed in genes SNCA, FBXO7, PARK7, HTRA2, DNAJC6, PLA2G6, and UCHL1. Co-occurrence of pathogenic variants involving two genes was observed in ATP13A2 and PARK2 genes, as well as LRRK2 and GIGYF2 genes.[Conclusions] Our results contribute to the understanding of the genetic architecture associated with early onset Parkinson’s disease, showing both PARK2 and LRRK2 play an important role in Spanish Parkinson’s disease patients. Rare variants in ATP13A2 and GIGYF2 may contribute to PD risk. However, a large proportion of genetic components remains unknown. This study might contribute to genetic diagnosis and counseling for families with early onset Parkinson’s disease.This study was supported by grants from the Spanish Ministry of Economy and Competitiveness [PI14/01823, PI16/01575, PI18/01898] co-founded by ISCIII (Subdirección General de Evaluación y Fomento de la Investigación) and by Fondo Europeo de Desarrollo Regional (FEDER), the Consejería de Economía, Innovación, Ciencia y Empleo de la Junta de Andalucía [CVI-02526, CTS-7685], the Consejería de Salud y Bienestar Social de la Junta de Andalucía [PI-0437-2012, PI-0471-2013], the Sociedad Andaluza de Neurología, the Fundación Alicia Koplowitz, the Fundación Mutua Madrileña. Pilar Gómez-Garre was supported by the "Miguel Servet" (from ISCIII-FEDER) and “Nicolás Monardes” (from Andalusian Ministry of Health) programs. Silvia Jesús Maestre was supported by the "Juan Rodés" program (from ISCIII-FEDER). Cristina Tejera was supported by VPPI-US from the Universidad de Sevilla