Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD). Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity. Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort from January 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL: 1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8). Results: Four hundred and thirty-nine PD patients (62.05 +/- 7.84 years old; 59% males) were included. MNCD stage was: stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advanced MNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p < 0.0001) and EUROHIS-QOL8 (p < 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages. Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD

Mendelian Randomisation Confirms the Role of Y-Chromosome Loss in Alzheimer’s Disease Aetiopathogenesis in Men

Mosaic loss of chromosome Y (mLOY) is a common ageing-related somatic event and has been previously associated with Alzheimer’s disease (AD). However, mLOY estimation from genotype microarray data only reflects the mLOY degree of subjects at the moment of DNA sampling. Therefore, mLOY phenotype associations with AD can be severely age-confounded in the context of genome-wide association studies. Here, we applied Mendelian randomisation to construct an age-independent mLOY polygenic risk score (mloy-PRS) using 114 autosomal variants. The mloy-PRS instrument was associated with an 80% increase in mLOY risk per standard deviation unit (p = 4.22 × 10−20) and was orthogonal with age. We found that a higher genetic risk for mLOY was associated with faster progression to AD in men with mild cognitive impairment (hazard ratio (HR) = 1.23, p = 0.01). Importantly, mloy-PRS had no effect on AD conversion or risk in the female group, suggesting that these associations are caused by the inherent loss of the Y chromosome. Additionally, the blood mLOY phenotype in men was associated with increased cerebrospinal fluid levels of total tau and phosphorylated tau181 in subjects with mild cognitive impairment and dementia. Our results strongly suggest that mLOY is involved in AD pathogenesis.P.G.-G. (Pablo García-González) is supported by CIBERNED employment plan CNV-304-PRF-866. CIBERNED is integrated into ISCIII (Instituto de Salud Carlos III). I.d.R is supported by a national grant from the Instituto de Salud Carlos III FI20/00215. A.C. (Amanda Cano) acknowledges the support of the Spanish Ministry of Science, Innovation, and Universities under the grant Juan de la Cierva (FJC2018-036012-I). M.B. (Mercé Boada) and A.R. (Agustín Ruiz) are also supported by national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240, and PI19/01301. The Genome Research @ Fundació ACE project (GR@ACE) is supported by Grifols SA, Fundación bancaria “La Caixa”, Fundació ACE, and CIBERNED. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación—and the Fondo Europeo de Desarrollo Regional (FEDER—“Una manera de hacer Europa”). Genotyping of the ACE MCI-EADB samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). This work was supported by a grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neurodegenerative Disease Research (JPND). Partial funding for open access charge: Universidad de Málag

Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

© 2023 – The authors. Published by IOS Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC 4.0).Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD).Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity.Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort fromJanuary 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL:1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8).Results: Four hundred and thirty-nine PD patients (62.05±7.84 years old; 59% males) were included. MNCD stage was:stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advancedMNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p< 0.0001) and EUROHIS-QOL8 (p< 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages.Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD.COPPADIS and the present study were developed with the help of Fundación Española de Ayuda a la Investigación en Enfermedades Neurodegenerativas y/o de Origen Genético (https://fundaciondegen.org/) and Alpha Bioresearch (www.alphabioresearch.com). Also, we received grants from the Spanish Ministry of Economy and Competitiveness [PI16/01575] co-founded by ISCIII (Concesión de subvenciones de Proyectos de Investigación en Salud de la convocatoria 2020 de la Acción Estratégica en Salud 2017-2020 por el Proyecto “PROGRESION NO MOTORA E IMPACTO EN LA CALIDAD DE VIDA EN LA ENFERMEDAD DE PARKINSON”) to develop a part of the COPPADIS project.Peer reviewe

Surface temperature multiscale monitoring by thermal infrared satellite and ground images at Campi Flegrei volcanic area (Italy)

The Campi Flegrei volcanic area (Italy) is part of the Neapolitan volcanic district, a high volcanic risk area where population and human activities are exposed. It is monitored by INGV multi-platform surveillance networks systems. In this work we performed a comparison of the surface temperature in volcanic areas between satellite imagery in the Thermal Infrared (TIR) bandwidth and infrared thermal scenes acquired by ground cameras network (TIRNet). TIRS on LANDSAT and ASTER on NASA-TERRA provide thermal IR channels to monitor the evolution of the surface temperatures on Campi Flegrei area. The spatial resolution of the TIR LANDSAT8 data is 100 m and ASTER resolution is 90 m. Temporal resolution is 16 days for both satellites. TIRNet network has been developed by INGV-Osservatorio Vesuviano for long-term volcanic surveillance of Campi Flegrei caldera through the acquisition of thermal infrared images. The system is currently composed of 5 permanent stations equipped with FLIR A645SC cameras using a 640x480 resolution IR sensor. Acquisitions and data transmission are managed remotely through technology specially developed at INGV laboratories in Naples. To improve the systematic use of satellite data in the monitoring procedures of Volcanic Observatories, a suitable integration and validation strategy is needed, also considering that current satellite missions do not provide TIR data with optimal characteristics to observe small thermal anomalies that may indicate changes in the volcanic activity. The presented procedure has been applied to the analysis of Solfatara Crater and is based on 2 different steps: 1) two parallel processing chains to produce ground temperature data both from satellite and ground cameras; 2) data integration and comparison. The ground cameras images generally acquire scenes of portion of the crater slopes characterized by significant thermal anomalies due to fumarole fields. In order to compare the satellite and ground cameras scenes, it has been necessary to take into account the observation geometries. All thermal images of the TIRNet have been georeferenced to the UTM WGS84 system, a regular grid of 30x30 meters has been created to select polygonal areas corresponding only to the cells containing the georeferenced TIR images acquired by different TIRnet stations. The surface temperature images retrieved by ASTER and LANDSAT data, have been georeferenced and resampled in cells of 30x30 with a careful control in maintaining the original cell values. The results show a good correspondence between trends of surface ground temperatures and satellite temperatures. This allow to calibrate the surface temperatures of the satellite imagery and to extend the area of analysis of thermal anomalies in the Campi Flegrei caldera. The effectiveness of this methodology allow to integrate the temperature data acquired by TIRNet with the satellite temperature data acquiredbefore the installation of TIRNet ground network.PublishedVienna5V. Processi eruttivi e post-eruttivi6SR VULCANI – Servizi e ricerca per la società5IT. Osservazioni satellitar

Surface Temperature Multiscale Monitoring by Thermal Infrared Satellite and Ground Images at Campi Flegrei Volcanic Area (Italy)

Land Surface Temperature (LST) from satellite data is a key component in many aspects of environmental research. In volcanic areas, LST is used to detect ground thermal anomalies providing a supplementary tool to monitor the activity status of a particular volcano. In this work, we describe a procedure aimed at identifying spatial thermal anomalies in thermal infrared (TIR) satellite frames which are corrected for the seasonal influence by using TIR images from ground stations. The procedure was applied to the volcanic area of Campi Flegrei (Italy) using TIR ASTER and Landsat 8 satellite imagery and TIR ground images acquired from the Thermal Infrared volcanic surveillance Network (TIRNet) (INGV, Osservatorio Vesuviano). The continuous TIRNet time-series images were processed to evaluate the seasonal component which was used to correct the surface temperatures estimated by the satellite&#8217;s discrete data. The results showed a good correspondence between de-seasoned time series of surface ground temperatures and satellite temperatures. The seasonal correction of satellite surface temperatures allows monitoring of the surface thermal field to be extended to all the satellite frames, covering a wide portion of Campi Flegrei volcanic area

Nonmotor Symptoms In Lrrk2 G2019s Associated Parkinson's Disease

Background: Idiopathic Parkinson's disease (IPD) and LRRK2-associated PD (LRRK2-PD) might be expected to differ clinically since the neuropathological substrate of LRRK2-PD is heterogeneous. The range and severity of extra-nigral nonmotor features associated with LRRK2 mutations is also not well-defined. Objective: To evaluate the prevalence and time of onset of nonmotor symptoms (NMS) in LRRK2-PD patients. Methods: The presence of hyposmia and of neuropsychiatric, dysautonomic and sleep disturbances was assessed in 33 LRRK2-G2019S-PD patients by standardized questionnaires and validated scales. Thirty-three IPD patients, matched for age, gender, duration of parkinsonism and disease severity and 33 healthy subjects were also evaluated. Results: University of Pennsylvania Smell Identification Test (UPSIT) scores in LRRK2-G2019S-PD were higher than those in IPD (23.5 +/- 6.8 vs 18.4 +/- 6.0; p = 0.002), and hyposmia was less frequent in G2019S carriers than in IPD (39.4% vs 75.8%; p = 0.01). UPSIT scores were significantly higher in females than in males in LRRK2-PD patients (26.9 +/- 4.7 vs 19.4 +/- 6.8; p < 0.01). The frequency of sleep and neuropsychiatric disturbances and of dysautonomic symptoms in LRRK2-G2019S-PD was not significantly different from that in IPD. Hyposmia, depression, constipation and excessive daytime sleepiness, were reported to occur before the onset of classical motor symptoms in more than 40% of LRRK2-PD patients in whom these symptoms were present at the time of examination. Conclusion: Neuropsychiatric, dysautonomic and sleep disturbances occur as frequently in patients with LRRK2-G2019S-PD as in IPD but smell loss was less frequent in LRRK2-PD. Like in IPD, disturbances such as hyposmia, depression, constipation and excessive daytime sleepiness may antedate the onset of classical motor symptoms in LRRK2-G2019S-PD

A neural network for glomerulus classification based on histological images of kidney biopsy

Abstract Background Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results. CAD systems play an important role in digital pathology supporting pathologists in analyzing biopsy slides by means of standardized and objective workflows. In the proposed work, we designed and tested a novel CAD system module based on image processing techniques and machine learning, whose objective was to classify the condition affecting renal corpuscles (glomeruli) between sclerotic and non-sclerotic. Such discrimination is useful for the biopsy slides evaluation performed by pathologists. Results We collected 26 digital slides taken from the kidneys of 19 donors with Periodic Acid-Schiff staining. Expert pathologists have conducted the slides preparation, digital acquisition and glomeruli annotations. Before setting the classifiers, we evaluated several feature extraction techniques from the annotated regions. Then, a feature reduction procedure followed by a shallow artificial neural network allowed discriminating between the glomeruli classes. We evaluated the workflow considering an independent dataset (i.e., processing images not used in the training procedure). Ten independent runs of the training algorithm, and evaluation, allowed achieving MCC and Accuracy of 0.95 (± 0.01) and 0.99 (standard deviation < 0.00), respectively. We also obtained good precision (0.9844 ± 0.0111) and recall (0.9310 ± 0.0153). Conclusions Results on the test set confirm that the proposed workflow is consistent and reliable for the investigated domain, and it can support the clinical practice of discriminating the two classes of glomeruli. Analyses on misclassifications show that the involved images are usually affected by staining artefacts or present partial sections due to slice preparation and staining processes. In clinical practice, however, pathologists discard images showing such artefacts