Understanding urban mobility patterns is crucial for designing efficient and sustainable transportation systems. Motivated by an application to the municipality of Padova and its surroundings, we propose a novel statistical framework for the analysis and clustering of mobility trajectories derived from telephonic data. We introduce a compositional representation of individual movements that integrates the uncertain device location with information on the surrounding road network, encoding at each time point the proportions of different road types compatible with the observed position. This formulation naturally accounts for measurement uncertainty and yields trajectories evolving in the simplex. To model these data, we develop a state-space framework for compositional time series that captures both the telephonic measurement error and the temporal dynamics of the latent mobility process. Building on this representation, we propose a model-based clustering approach based on mixtures of state-space models to identify groups of trajectories with similar evolution. This allows us to aggregate individual movements into interpretable mobility patterns at the population level. The results of the case study demonstrate the ability of the approach to uncover meaningful mobility behaviors, providing insights that are potentially relevant to policy makers.

Compositional data are drawing increasing interest for their ability to depict interdependent and constrained observations. While time series analysis has sometimes been employed for the study of individual compositional trajectories, little attention has been given to finding and modeling groups of trajectories. Driven by a sustainable mobility motivation, we propose a model-based approach, relying on a state space model representation and an Expectation-Maximization algorithm, for clustering compositional trajectories according to their evolution in the simplex. Trajectory covariates, not captured by the compositional representation, can be included in the component weights in a mixture of experts fashion. The method is applied to urban movement data, where people's movements are represented in the simplex by the proportions of road types in their surroundings.

Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a dataset with annual seasonal best performances of male middle distance runners for a period of 14 years and provide a modelling framework that accounts for both the fact that each runner has typically run in 3 distance events (800, 1,500, and 5,000 m) and the presence of periods of no running activities. We propose a latent class matrix-variate state space model and we empirically demonstrate that accounting for missing data patterns in runners' careers improves the out of sample prediction of their performances over time. In particular, we demonstrate that for this analysis, the missing data patterns provide valuable information for the prediction of runner's performance.

Objectives Neck pain is extremely common and represents a substantial economic burden to our society. We aimed to investigate risk factors for nondisabling and disabling neck pain in a large cohort of Italian adolescents with a cross-sectional study. Design Six thousand two hundred eighty-one students (14–19 yrs old) answered an online questionnaire, investigating the following: anthropometric data, lifestyle-related items, neck pain frequency and intensity, need for medical examination, and several risk factors. Students who had to give up social activities because of neck complaints constituted the disabling neck pain group. Results Our findings revealed that sex, age, sports practice, hours of sleep, and family history were risk factors (P < 0.001) for neck pain in our cohort. Moreover, disabling neck pain group experienced neck pain more frequently (P < 0.001) and with higher levels of pain (P < 0.001) compared with the nondisabling group. The number of hours of sleep was the only risk factor that showed a trend to differ comparing the disabling neck pain group with the nondisabling neck pain one (P = 0.057). Conclusions Different risk factors for neck pain were detected in a very large cohort of adolescents. This study may pave the way for future prospective studies and for the development of preventive strategies for neck pain in adolescents. To Claim CME Credits Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME Objectives Upon completion of this article, the reader should be able to: (1) Identify different risk factors for neck pain in adolescents; (2) Determine the differences between adolescents with nondisabling neck pain and disabling neck pain; and (3) Recognize that most risk factors for disabling neck pain are still unknown, but insufficient sleep quantity could potentially contribute to the development of this condition. Level Advanced Accreditation The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Rhabdomyosarcoma (RMS) is an aggressive pediatric soft tissue sarcoma characterized by a very poor prognosis when relapses occur after front-line therapy. Therefore, a major challenge for patients’ management remains the identification of markers associated with refractory and progressive disease. In this context, cancer autoantibodies are natural markers of disease onset and progression, useful to unveil novel therapeutic targets. Herein, we matched autoantibody profiling of alveolar RMS (ARMS) patients with genes under regulatory control of PAX3-FOXO1 transcription factor and revealed fibroblast growth factor 8 (FGF8) as a novel ARMS tumor antigen of diagnostic, prognostic, and therapeutic potential. We demonstrated that high levels of FGF8 autoantibodies distinguished ARMS patients from healthy subjects and represented an independent prognostic factor of better event-free survival. FGF8 was overexpressed in ARMS tumors compared to other types of pediatric soft tissue sarcomas, acting as a positive regulator of cell signaling. Indeed, FGF8 was capable of stimulating ARMS cells migration and expression of pro-angiogenic and metastasis-related factors, throughout MAPK signaling activation. Of note, FGF8 was found to increase in recurrent tumors, independently of PAX3-FOXO1 expression dynamics. Risk of recurrence correlated positively with FGF8 expression levels at diagnosis and reduced FGF8 autoantibodies titer, almost as if to suggest a failure of the immune response to control tumor growth in recurring patients. This study provides evidence about the crucial role of FGF8 in ARMS and the protective function of natural autoantibodies, giving new insights into ARMS biology and laying the foundations for the development of new therapeutic strategies.

Background Many nonconclusive studies have been conducted on low back pain (LBP) in adolescents and associated factors. Objective The aim was to assess the lifetime prevalence and associated factors of LBP in adolescents. Materials and Methods A questionnaire was administered in high school students (14–19-yr-old participants) in Veneto region (Italy). The self-administered, structured questionnaire included anthropometric data; psychologic factors and lifestyle; presence, intensity, and family history of LBP; referral to professional health care for LBP; and a short version of the International Physical Activity Questionnaire. Results A total of 6281 adolescents were recruited; 5204 questionnaires were included in the final analysis. A total of 2549 (48.98%) students reported one or more LBP episodes and 723 (13.89%) reported nonspecific disabling lumbar pain (i.e., no underlying pathology); 1040 (41.11%) subjects with LBP consulted a healthcare professional. A significant association emerged for LBP with sex (female), positive family history, time spent sitting or using electronic devices, sleep deprivation (<5 hrs/night), and low level of physical activity. Conclusion In a large sample of adolescents, LBP lifetime prevalence is high and often associated with disabling pain and sedentary lifestyle, requiring professional care. These findings may support the development of prevention and treatment strategies of LBP in adolescents, reducing the risk of developing chronic pain.

BACKGROUND:Many nonconclusive studies have been conducted on low back pain (LBP) in adolescents and associated factors.OBJECTIVE:The aim was to assess the lifetime prevalence and associated factors of LBP in adolescents.MATERIALS AND METHODS:A questionnaire was administered in high school students (14-19-yr-old participants) in Veneto region (Italy). The self-administered, structured questionnaire included anthropometric data; psychologic factors and lifestyle; presence, intensity, and family history of LBP; referral to professional health care for LBP; and a short version of the International Physical Activity Questionnaire.RESULTS:A total of 6281 adolescents were recruited; 5204 questionnaires were included in the final analysis. A total of 2549 (48.98%) students reported one or more LBP episodes and 723 (13.89%) reported nonspecific disabling lumbar pain (i.e., no underlying pathology); 1040 (41.11%) subjects with LBP consulted a healthcare professional. A significant association emerged for LBP with sex (female), positive family history, time spent sitting or using electronic devices, sleep deprivation (<5 hrs/night), and low level of physical activity.CONCLUSION:In a large sample of adolescents, LBP lifetime prevalence is high and often associated with disabling pain and sedentary lifestyle, requiring professional care. These findings may support the development of prevention and treatment strategies of LBP in adolescents, reducing the risk of developing chronic pain.

Falls are the second most frequent cause of injury in the elderly. Physiological processes associated with aging affect the elderly's ability to respond to unexpected balance perturbations, leading to increased fall risk. Every year, approximately 30% of adults, 65 years and older, experiences at least one fall. Investigating the neurophysiological mechanisms underlying the control of static and dynamic balance in the elderly is an emerging research area. The study aimed to identify cortical and muscular correlates during static and dynamic balance tests in a cohort of young and old healthy adults. We recorded cortical and muscular activity in nine elderly and eight younger healthy participants during an upright stance task in static and dynamic (core board) conditions. To simulate real-life dual-task postural control conditions, the second set of experiments incorporated an oddball visual task. We observed higher electroencephalographic (EEG) delta rhythm over the anterior cortex in the elderly and more diffused fast rhythms (i.e., alpha, beta, gamma) in younger participants during the static balance tests. When adding a visual oddball, the elderly displayed an increase in theta activation over the sensorimotor and occipital cortices. During the dynamic balance tests, the elderly showed the recruitment of sensorimotor areas and increased muscle activity level, suggesting a preferential motor strategy for postural control. This strategy was even more prominent during the oddball task. Younger participants showed reduced cortical and muscular activity compared to the elderly, with the noteworthy difference of a preferential activation of occipital areas that increased during the oddball task. These results support the hypothesis that different strategies are used by the elderly compared to younger adults during postural tasks, particularly when postural and cognitive tasks are combined. The knowledge gained in this study could inform the development of age-specific rehabilitative and assistive interventions.

Alveolar rhabdomyosarcoma (ARMS) is a highly aggressive subtype of childhood cancer for which efficacious treatments are needed. Immunotherapy represents a new therapeutic opportunity to pursue, but it requires the identification of worthwhile tumor antigens. Herein, we exploited the capacity of ARMS autoantibodies to recognize tumor self-antigens, probing human protein microarrays with plasma from ARMS patients and healthy subjects. We assessed the autoantibody response in ARMS, validated data with independent techniques, and estimated autoantibodies diagnostic and prognostic significance by receiver-operator characteristic curves (ROC), uni- and multivariate analysis. Of the 48 tumor antigens identified, General Transcription Factor II-I (GTF2i) and Protocadherin Gamma Subfamily C5 (PCDHGC5) were selected as candidate targets to validate tumor-restricted antigen expression and autoantibody reactivity through an independent technique and wider cohort of cases. GTF2i and PCDHGC5 overexpression was observed in tumor tissues compared to normal counterparts, and anti-GTF2i and -PCDHGC5 autoantibodies were found able to distinguish ARMS patients from healthy subjects as well as cases with different histology. Moreover, low levels of PCDHGC5 autoantibodies characterized patients with worse event-free survival and proved to be an independent negative prognostic factor. This approach provided the first comprehensive autoantibody profile of ARMS, gave novel insights into the immune response of this malignancy and paved the way toward novel potential antibody-based therapeutic applications suitable to improve the survival of ARMS patients.

BackgroundPatient preferences regarding their involvement in shared treatments decisions is fundamental in clinical practice. Previous evidences demonstrated a large heterogeneity in these preferences. However, only few studies have analysed the influence of patients’ individual differences, contextual and situational qualities, and their complex interaction in explaining this variability.MethodsWe assessed the role of the interaction of patient’s sociodemographic and psychological factors with a physician’s gender. Specifically, we focused on patient gender and attitudes toward male or female physicians. One hundred fifty‐three people participated in this randomised controlled study and were randomly assigned to one of two experimental conditions in which they were asked to imagine discussing their treatment with a male and a female doctor.ResultsAnalyses showed an interplay between attitude towards women and the gender of patients and doctors, explaining interindividual variability in patient preferences.ConclusionsIn conclusion, patients’ attitudes toward the physicians’ gender constitutes a relevant characteristic that may influence the degree of control patients want to have and the overall patient‐physician relationship.

Insulin-like growth factor-binding protein 2 (IGFBP2) is a tumor-associated protein measurable in patients' biopsies and blood samples. Increased IGFBP2 expression correlates with tumor severity in rhabdomyosarcoma (RMS). Thus, we examined the plasmatic IGFBP2 levels in 114 RMS patients and 15 healthy controls by ELISA assay in order to evaluate its value as a plasma biomarker for RMS. Additionally, we looked for the presence of a humoral response against IGBFP2 protein measurable by the production of anti-IGFBP2 autoantibodies. We demonstrated that both circulating IGFBP2 protein and autoantibodies were significantly higher in RMS patients with respect to controls and their combination showed a better discriminative capacity. IGFBP2 protein identified metastatic patients with worse event-free survival, whereas both IGFBP2 and anti-IGFBP2 antibodies negatively correlated with overall survival. Our study suggests that IGFBP2 and anti-IGFBP2 antibodies are useful for diagnostic and prognostic purposes, mainly as independent negative prognostic markers in metastatic patients. This is the first study that reports a specific humoral response in RMS plasma samples and proves the value of blood-based biomarkers in improving risk assessment and outcome of metastatic RMS patients.

Severe acquired brain injury (ABI) is a major cause of long-term disability and is the main determinant of health and societal costs. Early identification of favourable long-term recovery would allow personalized rehabilitative programs and better health care resources allocation. In light of the higher survival rate from intensive care units (ICU) in recent years, there is a growing need for early prognostication markers of functional recovery; to date, these data have been mainly collected at rehabilitation unit admission and not during the acute phase. We present the protocol and methodology to develop prediction models in people with severe acquired brain injury (GCS at admission to ICU < 8) for the functional and cognitive outcome at 12 months from the event. Predictors will be collected during the acute stage. Participants will be recruited within the first 72 h from the event in the ICUs of two teaching hospitals (Padova and Treviso). Participants will be followed up at discharge from ICU, admission and discharge from Neurorehabilitation and after 12 months from the event. Clinical and functional scales, electroencephalography, evoked potentials, magnetic resonance imaging and serological markers will be entered into a digital registry. Survival will be estimated using the Cox proportional hazard model. A multivariate prediction model will be developed for each of the functional and cognitive outcomes at 12 months from the event.

Rhabdomyosarcoma (RMS) arises from myogenic precursors that fail to complete muscle differentiation and represents the most frequent soft tissue sarcoma in children. Two major histological subtypes are recognized: alveolar RMS, characterized by a more aggressive behavior and a greater proneness to metastasis, and embryonal RMS which accounts for the 80% of cases and carries a better prognosis. Despite the survival of patients with localized tumors has progressively improved, RMS remains a challenging disease especially for metastatic patients and in case of progressive or recurrent disease after front-line therapy. MicroRNAs, a class of small non-coding RNA, have emerged as crucial players in cancer development and progression, and their detection in plasma (circulating miRNAs) represents a promising minimally invasive approach that deserve to be exploited in clinical practice. We evaluated the utility of circulating miRNAs as diagnostic and prognostic biomarkers in children with RMS profiling miRNAs from plasma of a small cohort of RMS patients and healthy donors (HD) using a qPCR Cancer Panel. An assessment of hemolysis status of plasma using miR-451/miR-23a ratio was performed as pre-analytical analysis. Statistical analysis revealed that miRNAs expression pattern clearly distinguished RMS patients from HD (p < 0.05). Interestingly, plasma levels of muscle-specific miR-206 were found to be significantly increased in RMS patients compared to HD, whereas levels of three potential tumor-suppressor miRNAs, miR-26a and miR-30b/30c, were found lower. Reduced levels of circulating miR-26a and miR-30b/c were further measured in an independent larger cohort of patients (validation set) by digital droplet PCR. In particular, we evidenced that miR-26a absolute plasma levels were associated with fusion status and adverse outcome (p < 0.05). Taken together, these findings demonstrate the potential of circulating miRNA as diagnostic and prognostic biomarker in children affected by this malignancy and enforced the key role of miR-26a in pediatric rhabdomyosarcoma.

Fibromyalgia syndrome (FMS) is a complex pain disorder, characterized by diffuse pain and cognitive disturbances. Abnormal cortical oscillatory activity may be a promising biomarker, encouraging non-invasive neurostimulation techniques as a treatment. We aimed to modulate abnormal slow cortical oscillations by delivering transcranial alternating current stimulation (tACS) and physiotherapy to reduce pain and cognitive symptoms. This was a double-blinded, randomized, crossover trial conducted between February and September 2018 at the Rehabilitation Unit of a teaching Hospital (NCT03221413). Participants were randomly assigned to tACS or random noise stimulation (RNS), 5 days/week for 2 weeks followed by ad hoc physiotherapy. Clinical and cognitive assessments were performed at T 0 (baseline), T 1 (after stimulation), T 2 (1 month after stimulation). Electroencephalogram (EEG) spectral topographies recorded from 15 participants confirmed slow-rhythm prevalence and provided tACS tailored stimulation parameters and electrode sites. Following tACS, EEG alpha1 ([8–10] Hz) activity increased at T 1 ( p = 0.024) compared to RNS, pain symptoms assessed by Visual Analog Scale decreased at T 1 ( T 1 vs T 0 p = 0.010), self-reported cognitive skills and neuropsychological scores improved both at T 1 and T 2 (Patient-Reported Outcomes in Cognitive Impairment, T 0 – T 2 , p = 0.024; Everyday memory questionnaire, T 1 compared to RNS, p = 0.012; Montréal Cognitive Assessment, T 0 vs T 1 , p = 0.048 and T 0 vs T 2 , p = 0.009; Trail Making Test B T 0 – T 2 , p = 0.034). Psychopathological scales and other neuropsychological scores (Trail Making Test-A; Total Phonemic Fluency; Hopkins Verbal Learning Test-Revised; Rey–Osterrieth Complex Figure) improved both after tACS and RNS but earlier improvements ( T 1 ) were registered only after tACS. These results support tACS coupled with physiotherapy in treating FMS cognitive symptoms, pain and subclinical psychopathology.

Abnormal cortical oscillations are markers of Parkinson’s Disease (PD). Transcranial alternating current stimulation (tACS) can modulate brain oscillations and possibly impact on behaviour. Mapping of cortical activity (prevalent oscillatory frequency and topographic scalp distribution) may provide a personalized neurotherapeutic target and guide non-invasive brain stimulation. This is a cross-over, double blinded, randomized trial. Electroencephalogram (EEG) from participants with PD were recorded. TACS frequency/site were individually defined based on statistical comparison of EEG power spectra maps with normative data from our laboratory. Participants were randomized to tACS or random noise stimulation (RNS), 5 days/week for 2-weeks followed by ad hoc physical therapy. EEG, motor (Unified Parkinson’s Disease Rating Scale-motor: UPDRS III), neuropsychological (frontal, executive and memory tests) performance and mood were measured before (T0), after (T1) and 4-weeks after treatment (T2). A linear model with random effects and Wilcoxon test were used to detect differences. Main results include a reduction of beta rhythm in theta-tACS vs. RNS group at T1 over right sensorimotor area (p = 0.014) and left parietal area (p = 0.010) and at T2 over right sensorimotor area (p = 0.004) and left frontal area (p = 0.039). Bradykinesia items improved at T1 (p = 0.002) and T2 (p = 0.047) compared to T0 in the tACS group. In the tACS group the Montréal Cognitive Assessment (MoCA) improved at T2 compared with T1 (p = 0.049). Individualized tACS in PD improves motor and cognitive performance. These changes are associated with a reduction of excessive fast oscillations.

Abnormal cortical oscillations are markers of Parkinson's Disease (PD). Transcranial alternating current stimulation (tACS) can modulate brain oscillations and possibly impact on behaviour. Mapping of cortical activity (prevalent oscillatory frequency and topographic scalp distribution) may provide a personalized neurotherapeutic target and guide non-invasive brain stimulation. This is a cross-over, double blinded, randomized trial. Electroencephalogram (EEG) from participants with PD referred to Specialist Clinic, University Hospital, were recorded. TACS frequency and electrode position were individually defined based on statistical comparison of EEG power spectra maps with normative data from our laboratory. Stimulation frequency was set according to the EEG band displaying higher power spectra (with beta excess on EEG map, tACS was set at 4 Hz; with theta excess, tACS was set at 30 Hz). Participants were randomized to tACS or random noise stimulation (RNS), 5 days/week for 2-weeks followed by ad hoc physical therapy. EEG, motor (Unified Parkinson's Disease Rating Scale-motor: UPDRS III), neuropsychological (frontal, executive and memory tests) performance and mood were measured before (T0), after (T1) and 4-weeks after treatment (T2). A linear model with random effects and Wilcoxon test were used to detect differences. Main results include a reduction of beta rhythm in theta-tACS vs. RNS group at T1 over right sensorimotor area (p = .014) and left parietal area (p = .010) and at T2 over right sensorimotor area (p = .004) and left frontal area (p = .039). Bradykinesia items improved at T1 (p = .002) and T2 (p = .047) compared to T0 in the tACS group. In the tACS group the Montréal Cognitive Assessment (MoCA) improved at T2 compared with T1 (p = .049). Individualized tACS in PD improves motor and cognitive performance. These changes are associated with a reduction of excessive fast EEG oscillations.

Background Pediatric oncohematologic patients are a high-risk population for clinical deterioration that might require pediatric intensive care unit (PICU) admission. Several studies have described outcomes and mortality predictors for patients post hematopoietic stem cell transplantation (HSCT), but fewer data exist regarding the category of non-HSCT patients. Procedure All oncohematologic non-HSCT patients <= 18 years requiring PICU admission from 1998 to 2015 in our tertiary-care academic hospital were retrospectively evaluated by means of the pediatric hematology-oncology unit database and the Italian PICUs data network database. We assessed the relation between demographic and clinical characteristics and 90-day mortality after PICU admission. Results Of 3750 hospitalized oncohematologic patients, 3238 were non-HSCT and 63 (2%) of them were admitted to the PICU. Patients were mainly affected by hematological malignancies (70%) and mostly were in the induction-therapy phase. The main reasons for admission were respiratory failure (40%), sepsis (25%), and seizures (16%). The median PICU stay was 5 days (range 1-107). The mortality rate at PICU discharge was 30%, and at 90 days it was 35%. Fifty-five percent of deaths happened in the first 2 days of the PICU stay. Cardiac arrest (P = .007), presence of disseminated intravascular coagulation (DIC, P = .007), and acute kidney injury (AKI) at PICU admission (P < .001) and during PICU stay (P = .021) were significant predictors of mortality in the multivariate analysis. Respiratory failure and mechanical ventilation were not associated with mortality. Conclusions A relatively small percentage of non-HSCT patients required PICU admission, but the mortality rate was still high. Hemodynamic instability, DIC, and AKI, but not respiratory failure, were significant predictors of mortality.

Clustered data are often analysed under the assumption that observations from distinct clusters are independent. The assumption may not be correct when the clusters are associated with different locations within a study region, as, for example, in epidemiological studies involving subjects nested within larger units such as hospitals, districts or villages. In such cases, correct inferential conclusions critically depend on the amount of spatial dependence between locations. We develop a modification of the method of generalized estimating equations to detect and account for spatial dependence between clusters in logistic regression for binary data. The approach proposed is based on parametric modelling of the lorelogram as a function of the distance between clusters. Model parameters are estimated by the hybrid pairwise likelihood method that combines optimal estimating equations for the regression parameters and pairwise likelihood for the lorelogram parameters. The methodology is illustrated with an analysis of prevalence disease survey data.

Clustered data are often analysed under the assumption that observations from distinct clusters are independent. The assumption may not be correct when the clusters are associated with different locations within a study region, as, for example, in epidemiological studies involving subjects nested within larger units such as hospitals, districts or villages. In such cases, correct inferential conclusions critically depend on the amount of spatial dependence between locations. We develop a modification of the method of generalized estimating equations to detect and account for spatial dependence between clusters in logistic regression for binary data. The approach proposed is based on parametric modelling of the lorelogram as a function of the distance between clusters. Model parameters are estimated by the hybrid pairwise likelihood method that combines optimal estimating equations for the regression parameters and pairwise likelihood for the lorelogram parameters. The methodology is illustrated with an analysis of prevalence disease survey data.