Toward objective monitoring of Parkinson's disease motor symptoms using a wearable device: wearability and performance evaluation of PDMonitor®.

Parkinson's disease (PD) is characterized by a variety of motor and non-motor symptoms. As disease progresses, fluctuations in the response to levodopa treatment may develop, along with emergence of freezing of gait (FoG) and levodopa induced dyskinesia (LiD). The optimal management of the motor symptoms and their complications, depends, principally, on the consistent detection of their course, leading to improved treatment decisions. During the last few years, wearable devices have started to be used in the clinical practice for monitoring patients' PD-related motor symptoms, during their daily activities. This work describes the results of 2 multi-site clinical studies (PDNST001 and PDNST002) designed to validate the performance and the wearability of a new wearable monitoring device, the PDMonitor®, in the detection of PD-related motor symptoms. For the studies, 65 patients with Parkinson's disease and 28 healthy individuals (controls) were recruited. Specifically, during the Phase I of the first study, participants used the monitoring device for 2-6 h in a clinic while neurologists assessed the exhibited parkinsonian symptoms every half hour using the Unified Parkinson's Disease Rating Scale (UPDRS) Part III, as well as the Abnormal Involuntary Movement Scale (AIMS) for dyskinesia severity assessment. The goal of Phase I was data gathering. On the other hand, during the Phase II of the first study, as well as during the second study (PDNST002), day-to-day variability was evaluated, with patients in the former and with control subjects in the latter. In both cases, the device was used for a number of days, with the subjects being unsupervised and free to perform any kind of daily activities. The monitoring device produced estimations of the severity of the majority of PD-related motor symptoms and their fluctuations. Statistical analysis demonstrated that the accuracy in the detection of symptoms and the correlation between their severity and the expert evaluations were high. As a result, the studies confirmed the effectiveness of the system as a continuous telemonitoring solution, easy to be used to facilitate decision-making for the treatment of patients with Parkinson's disease.

Clinical Evaluation in Parkinson's Disease: Is the Golden Standard Shiny Enough?

Parkinson's disease (PD) has become the second most common neurodegenerative condition following Alzheimer's disease (AD), exhibiting high prevalence and incident rates. Current care strategies for PD patients include brief appointments, which are sparsely allocated, at outpatient clinics, where, in the best case scenario, expert neurologists evaluate disease progression using established rating scales and patient-reported questionnaires, which have interpretability issues and are subject to recall bias. In this context, artificial-intelligence-driven telehealth solutions, such as wearable devices, have the potential to improve patient care and support physicians to manage PD more effectively by monitoring patients in their familiar environment in an objective manner. In this study, we evaluate the validity of in-office clinical assessment using the MDS-UPDRS rating scale compared to home monitoring. Elaborating the results for 20 patients with Parkinson's disease, we observed moderate to strong correlations for most symptoms (bradykinesia, rest tremor, gait impairment, and freezing of gait), as well as for fluctuating conditions (dyskinesia and OFF). In addition, we identified for the first time the existence of an index capable of remotely measuring patients' quality of life. In summary, an in-office examination is only partially representative of most PD symptoms and cannot accurately capture daytime fluctuations and patients' quality of life.

An empirical mean-field model of symmetry-breaking in a turbulent wake.

Improved turbulence modeling remains a major open problem in mathematical physics. Turbulence is notoriously challenging, in part due to its multiscale nature and the fact that large-scale coherent structures cannot be disentangled from small-scale fluctuations. This closure problem is emblematic of a greater challenge in complex systems, where coarse-graining and statistical mechanics descriptions break down. This work demonstrates an alternative data-driven modeling approach to learn nonlinear models of the coherent structures, approximating turbulent fluctuations as state-dependent stochastic forcing. We demonstrate this approach on a high-Reynolds number turbulent wake experiment, showing that our model reproduces empirical power spectra and probability distributions. The model is interpretable, providing insights into the physical mechanisms underlying the symmetry-breaking behavior in the wake. This work suggests a path toward low-dimensional models of globally unstable turbulent flows from experimental measurements, with broad implications for other multiscale systems.

Clinical value of significance of Hypoxia Inducible Factor-1α, Glucose Transporter-1 and Carbonic Anhydrase IX in rectal cancer after preoperative chemoradiotherapy.

PURPOSE: The standard treatment of rectal cancer is surgery along with preoperative radiotherapy, administered alone or in combination with chemotherapy. Preoperative chemoradiotherapy (preCRT) is widely used as it allows better local control and the use of sphincter-saving surgery. Pathological response after preCRT has been shown to be a significant prognostic factor of rectal cancer recurrence and survival. In this review we will assess the value of Hypoxia Induced Factor 1α (HIF-1α), Carbonic Anhydrase IX (CA-9) and Glucose Transporter 1 (GLUT-1) genes as predictive markers of the course of local advanced rectal cancer in patients who underwent pre-CRT. METHODS: We searched studies, from Pubmed and in English language, obtained the information by using "HIF-1 alpha", "Carbonic Anhydrase IX (CA-9)", "Glucose Transporter 1 (GLUT-1)" and "rectal cancer" as key words. RESULTS: 27 relevant articles were retrieved in initial stage. After full-text review, 13 articles were selected for the final analysis. CONCLUSIONS: HIF-1α, GLUT-1 and CA-IX may be connected with tumor response to preCRT, however, there is still skepticism towards their clinical use as predictors of outcome. Therefore, there is a need to conduct larger and more extensive cohort studies in order to find whether these predictors can be used in practice.

Addressing the post-irradiation hypothalamic-pituitary endocrine abnormalities of brain tumors in pediatric patients.

PURPOSE: Hypothalamic-pituitary axis is susceptible to radiotherapy, causing endocrine disorders to childhood cancer survivors. We conducted a systematic review in order to assess the radiation-induced toxicity that leads to hormone secretion abnormalities and their severity in children with brain tumors. METHODS: The data were collected by relevant studies on PubMed and EMBASE. Articles up to December 2016 were included. We selected studies which focused on children patients (<18 yr old) with brain tumors treated with radiotherapy and the consequences for their endocrine system. RESULTS: Growth hormone (GH) deficiency was the most common post-irradiation abnormality among children cancer survivors, followed by gonadotrophin (GT), thyroid stimulating hormone (TSH), corticotropin (ACTH) and prolactin (PRL) disorders. CONCLUSIONS: The age of the patient, total radiotherapy dose, number of fractions, fraction size and the duration of treatment seem to determine the severity of these disturbances.

Predicting rapid progression of Parkinson's Disease at baseline patients evaluation.

The rate of Parkinson's Disease (PD) progression in the initial post-diagnosis years can vary significantly. In this work, a methodology for the extraction of the most informative features for predicting rapid progression of the disease is proposed, using public data from the Parkinson's Progression Markers Initiative (PPMI) and machine learning techniques. The aim is to determine if a patient is at risk of expressing rapid progression of PD symptoms from the baseline evaluation and as close to diagnosis as possible. By examining the records of 409 patients from the PPMI dataset, the features with the best predictive value at baseline patient evaluation are found to be sleep problems, daytime sleepiness and fatigue, motor symptoms at legs, cognition impairment, early axial and facial symptoms and in the most rapidly advanced cases speech issues, loss of smell and affected leg muscle reflexes.

Sequential vs concurrent epirubicin and docetaxel as adjuvant chemotherapy for high-risk, node-negative, early breast cancer: an interim analysis of a randomised phase III study from the Hellenic Oncology Research Group.

BACKGROUND: Sequential anthracyclines and taxanes are standard adjuvant chemotherapy for patients with high-risk axillary node-positive breast cancer. We compared a sequential to a concurrent regimen in high-risk node-negative early breast cancer. METHODS: Patients were eligible if they had tumours >2 cm or T1c with two of the following characteristics: no oestrogen receptor (ER) and progesterone receptor (PR) expression, histological grade III, Ki67 >40% and vascular, lymphovascular or perineural invasion. They were randomised to receive four cycles of epirubicin 90 mg m-2 followed by four cycles of docetaxel 75 mg m-2 (sequential regimen) or six cycles of epirubicin 75 mg m-2 plus docetaxel 75 mg m-2 (concurrent regimen). All chemotherapy cycles were administered every 21 days with G-CSF prophylaxis only for the concurrent arm. The primary endpoint was disease-free survival (DFS). RESULTS: Between 2001 and 2013, 658 women received the sequential (n=329) or the concurrent (n=329) regimen. The median age was 53 years, 43.9% of the patients were premenopausal and of the tumours 44.2% were ⩽2 cm, 52.7% histological grade 3 and 35.3% hormone receptor-negative. After a median follow-up of 70.5 months, there were 29 (8.8%) vs 42 (12.8%) disease relapses (P=0.102) and 11 (3.3%) vs 19 (5.8%) deaths (P=0.135), in the sequential and concurrent arm, respectively. The 5-year DFS rates were 92.6% vs 88.2% for sequential and concurrent arm, respectively (hazard ratio (HR): 1.591; 95% confidence interval (CI): 0.990-2.556; P=0.055). Toxicity included grade 2-4 neutropenia in 54% vs 41% (P=0.001), febrile neutropenia 2.7% vs 6.1% (P=0.06), nausea/vomiting 18.5% vs 12.4% (P=0.03) of patients in the sequential and concurrent arm. There were no toxic deaths. CONCLUSIONS: Sequential compared with the concurrent administration of anthracyclines and taxanes is associated with a non-significant but possibly clinically meaningful improvement in DFS. In the era of molecular selection of patients for adjuvant chemotherapy, this study offers valuable information for the optimal administration of anthracyclines and taxanes in patients with node-negative disease.

Biweekly Carboplatin Plus Gemcitabine as First-Line Treatment of Elderly Patients With Advanced Squamous Non-Small-cell Lung Cancer: A Multicenter Phase I-II Trial by the Hellenic Oncology Research Group.

BACKGROUND: The present study was a phase I/II study to determine the maximum tolerated doses (MTDs) and dose-limiting toxicities of the biweekly carboplatin/gemcitabine combination and evaluate its safety and efficacy in patients aged ≥ 70 years with advanced squamous non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS: Patients aged ≥ 70 years with advanced or metastatic squamous NSCLC received escalated doses of carboplatin (area under the curve [AUC] 2-2.5 intravenously) and gemcitabine (800-1100 mg/m2 intravenously) every 2 weeks (phase I). In the phase II, the drugs were administered at their previously defined MTDs (carboplatin, AUC 2.5; gemcitabine, 1100 mg/m2). The primary endpoint was the overall response rate. RESULTS: A total of 69 patients were enrolled (phase I, n = 15). The median age was 76 years (range, 70-84 years); 52 patients had stage IV disease, and 61 and 8 patients had Eastern Cooperative Oncology Group performance status of 0 to 1 and 2, respectively. The MTDs could not be reached at the predefined last dose levels. The dose-limiting toxicities were grade 5 renal toxicity and grade 3 thrombocytopenia. In the phase II study, the overall response rate was 35.8% (95% confidence interval [CI], 23.0%-48.8%). In the intention-to-treat analysis, the median progression-free survival was 6.7 months (95% CI, 4.2-8.8 months), and the median overall survival was 13.3 months (95% CI, 7.1-19.6 months). Grade 3 or 4 neutropenia was observed in 7 patients (12.3%), grade 3 or 4 thrombocytopenia in 4 patients (7.1%), and grade 2 or 3 fatigue in 10 patients (17.5%). One toxic death occurred in the phase I of the study. CONCLUSION: The biweekly regimen of gemcitabine and carboplatin showed satisfactory efficacy and a favorable toxicity profile in elderly patients with advanced or metastatic squamous cell NSCLC.

A multiscale approach for modeling atherosclerosis progression.

Progression of atherosclerotic process constitutes a serious and quite common condition due to accumulation of fatty materials in the arterial wall, consequently posing serious cardiovascular complications. In this paper, we assemble and analyze a multitude of heterogeneous data in order to model the progression of atherosclerosis (ATS) in coronary vessels. The patient's medical record, biochemical analytes, monocyte information, adhesion molecules, and therapy-related data comprise the input for the subsequent analysis. As indicator of coronary lesion progression, two consecutive coronary computed tomography angiographies have been evaluated in the same patient. To this end, a set of 39 patients is studied using a twofold approach, namely, baseline analysis and temporal analysis. The former approach employs baseline information in order to predict the future state of the patient (in terms of progression of ATS). The latter is based on an approach encompassing dynamic Bayesian networks whereby snapshots of the patient's status over the follow-up are analyzed in order to model the evolvement of ATS, taking into account the temporal dimension of the disease. The quantitative assessment of our work has resulted in 93.3% accuracy for the case of baseline analysis, and 83% overall accuracy for the temporal analysis, in terms of modeling and predicting the evolvement of ATS. It should be noted that the application of the SMOTE algorithm for handling class imbalance and the subsequent evaluation procedure might have introduced an overestimation of the performance metrics, due to the employment of synthesized instances. The most prominent features found to play a substantial role in the progression of the disease are: diabetes, cholesterol and cholesterol/HDL. Among novel markers, the CD11b marker of leukocyte integrin complex is associated with coronary plaque progression.

PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease.

In this paper, we describe the PERFORM system for the continuous remote monitoring and management of Parkinson's disease (PD) patients. The PERFORM system is an intelligent closed-loop system that seamlessly integrates a wide range of wearable sensors constantly monitoring several motor signals of the PD patients. Data acquired are pre-processed by advanced knowledge processing methods, integrated by fusion algorithms to allow health professionals to remotely monitor the overall status of the patients, adjust medication schedules and personalize treatment. The information collected by the sensors (accelerometers and gyroscopes) is processed by several classifiers. As a result, it is possible to evaluate and quantify the PD motor symptoms related to end of dose deterioration (tremor, bradykinesia, freezing of gait (FoG)) as well as those related to over-dose concentration (Levodopa-induced dyskinesia (LID)). Based on this information, together with information derived from tests performed with a virtual reality glove and information about the medication and food intake, a patient specific profile can be built. In addition, the patient specific profile with his evaluation during the last week and last month, is compared to understand whether his status is stable, improving or worsening. Based on that, the system analyses whether a medication change is needed--always under medical supervision--and in this case, information about the medication change proposal is sent to the patient. The performance of the system has been evaluated in real life conditions, the accuracy and acceptability of the system by the PD patients and healthcare professionals has been tested, and a comparison with the standard routine clinical evaluation done by the PD patients' physician has been carried out. The PERFORM system is used by the PD patients and in a simple and safe non-invasive way for long-term record of their motor status, thus offering to the clinician a precise, long-term and objective view of patient's motor status and drug/food intake. Thus, with the PERFORM system the clinician can remotely receive precise information for the PD patient's status on previous days and define the optimal therapeutical treatment.

Extraction of consensus protein patterns in regions containing non-proline cis peptide bonds and their functional assessment.

BACKGROUND: In peptides and proteins, only a small percentile of peptide bonds adopts the cis configuration. Especially in the case of amide peptide bonds, the amount of cis conformations is quite limited thus hampering systematic studies, until recently. However, lately the emerging population of databases with more 3D structures of proteins has produced a considerable number of sequences containing non-proline cis formations (cis-nonPro). RESULTS: In our work, we extract regular expression-type patterns that are descriptive of regions surrounding the cis-nonPro formations. For this purpose, three types of pattern discovery are performed: i) exact pattern discovery, ii) pattern discovery using a chemical equivalency set, and iii) pattern discovery using a structural equivalency set. Afterwards, using each pattern as predicate, we search the Eukaryotic Linear Motif (ELM) resource to identify potential functional implications of regions with cis-nonPro peptide bonds. The patterns extracted from each type of pattern discovery are further employed, in order to formulate a pattern-based classifier, which is used to discriminate between cis-nonPro and trans-nonPro formations. CONCLUSIONS: In terms of functional implications, we observe a significant association of cis-nonPro peptide bonds towards ligand/binding functionalities. As for the pattern-based classification scheme, the highest results were obtained using the structural equivalency set, which yielded 70% accuracy, 77% sensitivity and 63% specificity.

Automated Levodopa-induced dyskinesia assessment.

An automated methodology for Levodopa-induced dyskinesia (LID) assessment is presented in this paper. The methodology is based on the analysis of the signals recorded from accelerometers and gyroscopes, which are placed on certain positions on the subject's body. The obtained signals are analyzed and several features are extracted. Based on these features a classification technique is used for LID detection and classification of its severity. The method has been evaluated using a group of 10 subjects. Results are presented related to each individual sensor as well as for various sensor combinations. The obtained results indicate high classification ability (93.73% classification accuracy).

Wilson's disease and benign epilepsy of childhood with centrotemporal (rolandic) spikes.

Cases with a clinical and electroencephalographic phenotype of benign epilepsy of childhood with centrotemporal spikes (BECTS) in association with a proven organic brain lesion have rarely been reported. To our knowledge, we herein describe for the first time a patient with Wilson's disease who subsequently manifested BECTS. Our case bolsters the argument that in at least some cases, BECTS is associated with organic brain disease.