Among Parkinson’s disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient’s treatment plan. This paper presents a new algorithm to detect FoG with a machine learning approach based on Support Vector Machines (SVM) and a single tri-axial accelerometer worn at the waist. The method is evaluated through the acceleration signals in an outpatient setting gathered from 21 PD patients at their home and evaluated under two different conditions: first, a generic model is tested by using a leave-one-out approach and, second, a personalised model that also uses part of the dataset from each patient. Results show a significant improvement in the accuracy of the personalised model compared to the generic model, showing enhancement in the specificity and sensitivity geometric mean (GM) of 7.2%. Furthermore, the SVM approach adopted has been compared to the most comprehensive FoG detection method currently in use (referred to as MBFA in this paper). Results of our novel generic method provide an enhancement of 11.2% in the GM compared to the MBFA generic model and, in the case of the personalised model, a 10% of improvement with respect to the MBFA personalised model. Thus, our results show that a machine learning approach can be used to monitor FoG during the daily life of PD patients and, furthermore, personalised models for FoG detection can be used to improve monitoring accuracy.

Here, we identify such an enzyme in human cells and show that this activity efficiently restores 5'-phosphate termini at DNA double-strand breaks in preparation for DNA ligation. We reveal that this enzyme is TTRAP, a member of the Mg 2+ /Mn 2+ -dependent family of phosphodiesterases, and show that cellular depletion of TTRAP results in increased susceptibility and sensitivity to topoisomerase II-induced DNA double-strand breaks. TTRAP is the first human 5'-tyrosine phosphodiesterase to be identified and we suggest this enzyme additionally be denoted tyrosyl DNA phosphodiesterase-2 (TDP2).In an attempt to identify novel human tyrosyl DNA phosphodiesterase activities, we exploited the hypersensitivity of Saccharomyces cerevisiae tdp1Δ rad1Δ double mutant cells to camptothecin (CPT), a topoisomerase I (Top1) poison that induces single-strand breaks (SSBs) with Top1 covalently linked to the 3'-terminus 3, 10 . This strain lacks not only Tdp1 but also Rad1-Rad10 nuclease, which in yeast provides an alternative (endonucleolytic) pathway for removing Top1 from 3'-termini 11,12 . We transformed this strain with a human cDNA library 3 and screened the resulting population of transformants for cellular resistance to CPT. Of six tdp1Δ rad1Δ transformants displaying wild-type levels of CPT resistance, three harboured cDNA clones encoding TDP1 and three harboured cDNA clones encoding TTRAP (TRAF and TNF receptor-associated protein), a protein of unknown function and a putative member of the Mg 2+ /Mn 2+ -dependent phosphodiesterase super-family, with the DNA repair protein AP endonuclease-1 (APE1) being its closest relative 13,14 (Fig.1a and Supplementary Fig.1).The TDP1 and TTRAP cDNA clones recovered in the genetic screen suppressed the CPT sensitivity of tdp1Δ rad1Δ cells to a similar extent (Fig. 1b & data not shown). Whilst the pACT-TTRAP clones encoded TTRAP protein that lacked eight (pACT-TTRAP-2, pACT-TTRAP-3) or twenty-two (pACT-TTRAP-1) residues from the amino-terminus (data not shown), full-length TTRAP similarly suppressed the CPT sensitivity of tdp1Δ rad1Δ (Fig. 1c, left). In contrast, human APE1 protein failed to suppress this sensitivity, suggesting that ability to complement CPT sensitivity in tdp1Δ rad1Δ cells is not a generic feature of metaldependent phosphodiesterases (Fig. 1c, left). Conversely, whereas human APE1 suppressed the sensitivity of AP endonuclease-defective apn1Δapn2Δ tpp1Δ yeast cells to methyl methanesulphonate (MMS)-induced DNA base damage, human TTRAP did not, suggesting that the impact of TTRAP in these experiments was restricted to topoisomerase-mediated DNA damage ( Fig. 1c, right). TTRAP contains four highly conserved motifs that putatively assign this protein to the metal-dependent phosphodiesterase superfamily (see Fig.1a and Supplementary Fig.1). We thus examined whether mutation of two predicted catalytic residues (Fig.1a; E152 and D262) within two of these motifs impacted on the complementation of CPT sensitivity by TTRAP. Indeed, in contrast to wild-type TTRAP protein, ne...

Among Parkinson’s disease (PD) motor symptoms, freezing of gait (FOG) may\ud be the most incapacitating. FOG episodes may result in falls and reduce patients’\ud quality of life. Accurate assessment of FOG would provide objective information\ud to neurologists about the patient’s condition and the symptom’s characteristics,\ud while it could enable non-pharmacologic support based on rhythmic\ud cues.\ud This paper is, to the best of our knowledge, the first study to propose a\ud deep learning method for detecting FOG episodes in PD patients. This model\ud is trained using a novel spectral data representation strategy which considers information from both the previous and current signal windows. Our approach\ud was evaluated using data collected by a waist-placed inertial measurement unit\ud from 21 PD patients who manifested FOG episodes. These data were also employed\ud to reproduce the state-of-the-art methodologies, which served to perform\ud a comparative study to our FOG monitoring system.\ud The results of this study demonstrate that our approach successfully outperforms\ud the state-of-the-art methods for automatic FOG detection. Precisely, the\ud deep learning model achieved 90% for the geometric mean between sensitivity\ud and specificity, whereas the state-of-the-art methods were unable to surpass the\ud 83% for the same metric.Peer ReviewedPostprint (published version

Neuropsychiatric signs and symptoms occur frequently in individuals with multiple sclerosis (MS), either as the initial presenting complaint prior to a definitive neurological diagnosis or more commonly with disease progression. However, the pathogenesis of these comorbid conditions remains unclear and it remains difficult to accurately elucidate if neuropsychiatric symptoms or conditions are indicators of MS illness severity. Furthermore, both the disease process and the treatments of MS can adversely impact an individual's mental health. In this review, we discuss the common neuropsychiatric syndromes that occur in MS and describe the clinical symptoms, aetiology, neuroimaging findings and management strategies for these conditions.

N-methyl-D-aspartate receptor (NR) activation in the hippocampus and neocortex plays a central role in memory and cognitive function. We analyzed the cellular expression of the five NR subunit (NR1 and NR2A-D) mRNAs in these regions with in situ hybridization and human ribonucleotide probes. Film autoradiograms demonstrated a distinct pattern of hybridization signal in the hippocampal complex and the neocortex with probes for NR1, NR2A, and NR2B mRNA. NR2C and NR2D probes yielded scattered signals without a distinct organization. At the emulsion level, the NR1 probe produced high-density hybridization signals across the hippocampal complex. NR2A mRNA was higher in dentate granule cells and pyramidal cells in CA1 and subiculum compared to hilus neurons. NR2B mRNA expression was moderate throughout, with higher expression in dentate granule cells, CA1 and CA3 pyramidal cells than in hilus neurons. In the hippocampal complex, the NR2C probe signal was not different from background in any region, whereas the NR2D probe signal resulted in low to moderate grain densities. We analyzed NR subunit mRNA expression in the prefrontal, parietal, primary visual, and motor cortices. All areas displayed strong NR1 hybridization signals. NR2A and NR2B mRNAs were expressed in cortical areas and layers. NR2C mRNA was expressed at low levels in distinct layers that differed by region and the NR2D signal was equally moderate throughout all regions. Pyramidal cells in both hippocampus and neocortex express NR1, NR2A, NR2B, and, to a lesser extent, NR2D mRNA. Interneurons or granular layer neurons and some glial cells express NR2C mRNA.