Splice Isoforms of the Polyglutamine Disease Protein Ataxin-3 Exhibit Similar Enzymatic yet Different Aggregation Properties

Protein context clearly influences neurotoxicity in polyglutamine diseases, but the contribution of alternative splicing to this phenomenon has rarely been investigated. Ataxin-3, a deubiquitinating enzyme and the disease protein in SCA3, is alternatively spliced to encode either a C-terminal hydrophobic stretch or a third ubiquitin interacting motif (termed 2UIM and 3UIM isoforms, respectively). In light of emerging insights into ataxin-3 function, we examined the significance of this splice variation. We confirmed neural expression of several minor 5′ variants and both of the known 3′ ataxin-3 splice variants. Regardless of polyglutamine expansion, 3UIM ataxin-3 is the predominant isoform in brain. Although 2UIM and 3UIM ataxin-3 display similar in vitro deubiquitinating activity, 2UIM ataxin-3 is more prone to aggregate and more rapidly degraded by the proteasome. Our data demonstrate how alternative splicing of sequences distinct from the trinucleotide repeat can alter properties of the encoded polyglutamine disease protein and thereby perhaps contribute to selective neurotoxicity

Citalopram reduces aggregation of ATXN3 in a YAC transgenic mouse model of Machado-Joseph disease

Machado-Joseph disease, also known as spinocerebellar ataxia type 3, is a fatal polyglutamine disease with no disease-modifying treatment. The selective serotonin reuptake inhibitor citalopram was shown in nematode and mouse models to be a compelling repurposing candidate for Machado-Joseph disease therapeutics. We sought to confirm the efficacy of citalopram to decrease ATXN3 aggregation in an unrelated mouse model of Machado-Joseph disease. Four-week-old YACMJD84.2 mice and non-transgenic littermates were given citalopram 8 mg/kg in drinking water or water for 10 weeks. At the end of treatment, brains were collected for biochemical and pathological analyses. Brains of citalopram-treated YACMJD84.2 mice showed an approximate 50% decrease in the percentage of cells containing ATXN3-positive inclusions in the substantia nigra and three examined brainstem nuclei compared to controls. No differences in ATXN3 inclusion load were observed in deep cerebellar nuclei of mice. Citalopram effect on ATXN3 aggregate burden was corroborated by immunoblotting analysis. While lysates from the brainstem and cervical spinal cord of citalopram-treated mice showed a decrease in all soluble forms of ATXN3 and a trend toward reduction of insoluble ATXN3, no differences in ATXN3 levels were found between cerebella of citalopram-treated and vehicle-treated mice. Citalopram treatment altered levels of select components of the cellular protein homeostatic machinery that may be expected to enhance the capacity to refold and/or degrade mutant ATXN3. The results here obtained in a second independent mouse model of Machado-Joseph disease further support citalopram as a potential drug to be repurposed for this fatal disorder.This work was funded by Becky Babcox Research Fund/pilot research award G015617, University of Michigan to M.C.C. and NINDS/NIH R01NS038712 to H.L.P. The work performed at the University of Minho was funded by the European Regional Development Funds (FEDER), through the Competitiveness Factors Operational Programme (COMPETE), and by National funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. This article was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Program (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the FEDER. This work was also supported by FCT and COMPETE through the projects [PTDC/SAU-GMG/112617/2009] (to P.M.) and [EXPL/BIM-MEC/ 0239/2012] (to A.T.C.); by FCT through the project [POCI-01-0145- FEDER-016818 (PTDC/NEU-NMC/3648/2014)] (to P.M.); by National Ataxia Foundation (to P.M. and to A.T.C.); and by Ataxia UK (to P.M.). S.D.S. and A.T.C. were supported by fellowships from FCT, SFRH/BD/ 78388/2011 and SFRH/BPD/102317/2014, respectively. FCT fellowships are co-financed by POPH, QREN, Governo da República Portuguesa and EU/FSE

Chronic treatment with 17-DMAG improves balance and coordination in a new mouse model of Machado-Joseph disease

Machado-Joseph disease (MJD) or spinocerebellar ataxia type 3 (SCA3) is a neurodegenerative disease currently with no treatment. We describe a novel mouse model of MJD which expresses mutant human ataxin-3 at near endogenous levels and manifests MJD-like motor symptoms that appear gradually and progress over time. CMVMJD135 mice show ataxin-3 intranuclear inclusions in the CNS and neurodegenerative changes in key disease regions, such as the pontine and dentate nuclei. Hsp90 inhibition has shown promising outcomes in some neurodegenerative diseases, but nothing is known about its effects in MJD. Chronic treatment of CMVMJD mice with Hsp90 inhibitor 17-DMAG resulted in a delay in the progression of their motor coordination deficits and, at 22 and 24 weeks of age, was able to rescue the uncoordination phenotype to wild-type levels; in parallel, a reduction in neuropathology was observed in treated animals. We observed limited induction of heat-shock proteins with treatment, but found evidence that 17-DMAG may be acting through autophagy, as LC3-II (both at mRNA and protein levels) and beclin-1 were induced in the brain of treated animals. This resulted in decreased levels of the mutant ataxin-3 and reduced intranuclear aggregation of this protein. Our data validate this novel mouse model as a relevant tool for the study of MJD pathogenesis and for pre-clinical studies, and show that Hsp90 inhibition is a promising therapeutic strategy for MJD.We would like to thank to Dr. Henry Paulson for providing the anti-ataxin-3 serum, Dr. Monica Sousa for the pCMV vector and to Eng. Lucilia Goreti Pinto, Lu s Martins, Miguel Carneiro and Celina Barros for technical assistance. This work was supported by Fundacao para a Ciencia e Tecnologia through the projects FEDER/FCT, POCI/SAU-MMO/60412/2004 and PTDC/SAU-GMG/64076/2006. This work was supported by Fundacao para a Ciencia e Tecnologia through fellowships SFRH/BPD/91562/2012 to A.S-F., SFRH/BD/78388/2011 to S. D-S., SFRH/BD/51059/2010 to A.N-C., and SFRH/BPD/79469/2011 to A.T-C.

Demographics of extra-articular calcaneal fractures: Including a review of the literature on treatment and outcome

Introduction: Extra-articular calcaneal fractures represent 25-40% of all calcaneal fractures and an even higher percentage of up to 60% is seen in children. A disproportionately small part of the literature on calcaneal fractures involves the extra-articular type. The aim of this study was to investigate the incidence of extra-articular calcaneal fractures in a Level 1 trauma centre, define the distribution of the various types of fractures and compare patient demographics between extra- and intra-articular calcaneal fractures. In addition the literature was reviewed for the most common types of extra-articular calcaneal fractures with regard to incidence, treatment and clinical outcome. Methods: The radiological records between 2003 and 2005 were reviewed for intra- and extra-articular calcaneal fractures. Patient gender-distribution and age were compared. A literature search was conducted for the treatment of extra-articular calcaneal fractures. Results: In this 3-year study period a total of 49 patients with 50 extra-articular calcaneal fractures and 91 patients with 101 intra-articular fractures were identified. The median age for the first group was 32.7 years, and for the second group 40.3 years; P = 0.04. Male predominance was significantly less pronounced for extra-articular (63%) compared with intra-articular fractures (79%; P = 0.04). Conclusion: One-third of all calcaneal fractures are extra-articular. Significant differences exist between the intra- and extra-articular groups, in terms of lower age and male-female ratio. The literature study shows inconsistencies in treatment options, but most extra-articular fractures are well manageable conservatively

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

Classification of Caesarean Section and Normal Vaginal Deliveries Using Foetal Heart Rate Signals and Advanced Machine Learning Algorithms

ABSTRACT – Background: Visual inspection of Cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% positive predictive value for the classification of pathological outcomes. This has a significant negative impact on the perinatal foetus and often results in cardio-pulmonary arrest, brain and vital organ damage, cerebral palsy, hearing, visual and cognitive defects and in severe cases, death. This paper shows that using machine learning and foetal heart rate signals provides direct information about the foetal state and helps to filter the subjective opinions of medical practitioners when used as a decision support tool. The primary aim is to provide a proof-of-concept that demonstrates how machine learning can be used to objectively determine when medical intervention, such as caesarean section, is required and help avoid preventable perinatal deaths. Methodology: This is evidenced using an open dataset that comprises 506 controls (normal virginal deliveries) and 46 cases (caesarean due to pH ≤7.05 and pathological risk). Several machine-learning algorithms are trained, and validated, using binary classifier performance measures. Results: The findings show that deep learning classification achieves Sensitivity = 94%, Specificity = 91%, Area under the Curve = 99%, F-Score = 100%, and Mean Square Error = 1%. Conclusions: The results demonstrate that machine learning significantly improves the efficiency for the detection of caesarean section and normal vaginal deliveries using foetal heart rate signals compared with obstetrician and midwife predictions and systems reported in previous studies