The Collaboration of Music Therapy and Physical Therapy: A Case Study for Rehabilitation Treatment of a Patient with Chronic Stroke

Background and Purpose: Strokes are the fifth leading cause of death in the United States and nearly 800,000 people suffered from a stroke last year alone. Even though two-thirds of those people had survived, many of the survivors were left with a number of activity limitations and participation restrictions. The research is extensive in the realm of physical therapy interventions and how it can help with those disabilities, but truly lacks the knowledge behind the effects of a collaboration of music therapy with physical therapy. Case Description: This case study follows an 85-year-old woman with lasting chronic impairments from a right cerebrovascular accident four years ago to measure the effects of a 13-week interdisciplinary intervention program. Interventions: Following an initial evaluation, the client performed 11 one-hour treatment sessions over an 11-week period. The patient was co-treated during each session by two music therapy students and two physical therapy students under the guidance and direction of a licensed music therapist and a licensed physical therapist. Interventions included gait training with rhythmic auditory stimulation, lower extremity strengthening, proprioceptive neuromuscular facilitation (PNF) patterns, balance training and core vii stability with musical components such as Rhythmic Auditory Stimulation (RAS), Patterned Sensory Enhancement (PSE) and Therapeutic Instrumental Music Performance/Playing (TIMP). Outcomes: After 11 weeks of music and physical therapy collaborative interventions, the client was reassessed, and outcomes were recorded. The client demonstrated increased competency for the Berg Balance Scale, decreased the amount of assist for transfers for all functional outcome measures, decreased time with Five Time Sit to Stand test and showed increase response and awareness of metronome during GaitRITE ®. Discussion: Collaboration of treatment between music therapy and physical therapy improved functional mobility, sitting and standing balance, decreased assist with transfers and increased awareness of RAS (Rhythmic Auditory Stimulation) in gait, with this client with a Chronic Stroke

Insights into Pharmacotherapy Management for Parkinson's Disease Patients Using Wearables Activity Data.

We investigate what supervised classification models using clinical and wearables data are best suited to address two important questions about the management of Parkinson's Disease (PD) patients: 1) does a PD patient require pharmacotherapy or not, and 2) whether therapies are having an effect. Currently, patient management is suboptimal due to using subjective patient reported episodes to answer these questions. METHODOLOGY: Clinical and real environment sensor data (memory, tapping, walking) was provided by the mPower study (6805 participants). From the data, we derived relevant clinical scenarios: S1) before vs. after initiating pharmacotherapy, and S2) before vs. after taking medication. For each scenario we designed and tested 6 methods of supervised classification. Precision, Accuracy and Area Under the Curve (AUC) were computed using 10-fold cross-validation. RESULTS: The best classification models were: S1) Decision Trees on Tapping activity data (AUC 0.95, 95% CI 0.05); and S2) K-Nearest Neighbours on Gait data (mean AUC 0.70, 95% CI 0.07, 46% participants with AUC > 0.70). CONCLUSIONS: Automatic patient classification based on sensor activity data can objectively inform PD medication management, with significant potential for improving patient care

Kinetic Analysis of Discrete Path Sampling Stationary Point Databases

Analysing stationary point databases to extract phenomenological rate constants can become time-consuming for systems with large potential energy barriers. In the present contribution we analyse several different approaches to this problem. First, we show how the original rate constant prescription within the discrete path sampling approach can be rewritten in terms of committor probabilities. Two alternative formulations are then derived in which the steady-state assumption for intervening minima is removed, providing both a more accurate kinetic analysis, and a measure of whether a two-state description is appropriate. The first approach involves running additional short kinetic Monte Carlo (KMC) trajectories, which are used to calculate waiting times. Here we introduce `leapfrog' moves to second-neighbour minima, which prevent the KMC trajectory oscillating between structures separated by low barriers. In the second approach we successively remove minima from the intervening set, renormalising the branching probabilities and waiting times to preserve the mean first-passage times of interest. Regrouping the local minima appropriately is also shown to speed up the kinetic analysis dramatically at low temperatures. Applications are described where rates are extracted for databases containing tens of thousands of stationary points, with effective barriers that are several hundred times kT.Comment: 28 pages, 1 figure, 4 table

The intracluster magnetic field power spectrum in A2199

We investigate the magnetic field power spectrum in the cool core galaxy cluster A2199 by analyzing the polarized emission of the central radio source 3C338. The polarized radiation from the radio emitting plasma is modified by the Faraday rotation as it passes through the magneto-ionic intracluster medium. We use Very Large Array observations between 1665 and 8415 MHz to produce detailed Faraday rotation measure and fractional polarization images of the radio galaxy. We simulate Gaussian random three-dimensional magnetic field models with different power-law power spectra and we assume that the field strength decreases radially with the thermal gas density as n_e^{\eta}. By comparing the synthetic and the observed images with a Bayesian approach, we constrain the strength and structure of the magnetic field associated with the intracluster medium. We find that the Faraday rotation toward 3C338 in A2199 is consistent with a magnetic field power law power spectrum characterized by an index n=(2.8 \pm 1.3) between a maximum and a minimum scale of fluctuation of \Lambda_{max}=(35 \pm 28) kpc and \Lambda_{min}=(0.7 \pm 0.1) kpc, respectively. By including in the modeling X-ray cavities coincident with the radio galaxy lobes, we find a magnetic field strength of =(11.7 \pm 9.0) \mu G at the cluster center. Further out, the field decreases with the radius following the gas density to the power of \eta=(0.9 \pm 0.5).Comment: 17 pages, 12 figures, A&A accepte

On model selection forecasting, Dark Energy and modified gravity

The Fisher matrix approach (Fisher 1935) allows one to calculate in advance how well a given experiment will be able to estimate model parameters, and has been an invaluable tool in experimental design. In the same spirit, we present here a method to predict how well a given experiment can distinguish between different models, regardless of their parameters. From a Bayesian viewpoint, this involves computation of the Bayesian evidence. In this paper, we generalise the Fisher matrix approach from the context of parameter fitting to that of model testing, and show how the expected evidence can be computed under the same simplifying assumption of a gaussian likelihood as the Fisher matrix approach for parameter estimation. With this `Laplace approximation' all that is needed to compute the expected evidence is the Fisher matrix itself. We illustrate the method with a study of how well upcoming and planned experiments should perform at distinguishing between Dark Energy models and modified gravity theories. In particular we consider the combination of 3D weak lensing, for which planned and proposed wide-field multi-band imaging surveys will provide suitable data, and probes of the expansion history of the Universe, such as proposed supernova and baryonic acoustic oscillations surveys. We find that proposed large-scale weak lensing surveys from space should be able readily to distinguish General Relativity from modified gravity models.Comment: 6 pages, 2 figure

The politics of economic policy making in Britain : a re-assessment of the 1976 IMF crisis

Many existing accounts of the IMF crisis have argued that British policy was determined either by the exercise of structural power by markets through the creation of currency instability and the application of loan conditionality, or by demonstrating that only policies of a broadly monetarist persuasion would be sufficient to sustain confidence, a recognition which was reached through a process of policy learning. This paper offers a re-assessment of economic policy-making in Britain during the 1976 IMF crisis to show that policy change did not occur as a result of disciplinary market pressure or a process of social learning. It argues that state managers have to manage the contradictions between the imperatives of accumulation and legitimation, and can do so through the politics of depoliticisation. It then uses archival sources to show how significant elements of the core-executive had established preferences for deflationary policies, which were implemented in 1976 by using market rhetoric and Fund conditionality to shape perceptions about the range of issues within the government‟s scope for discretionary control

Clinical correlates of high burden of general medical comorbidities in patients with bipolar disorder

Background: Bipolar disorder is associated with an increased burden of general medical conditions that might be related to a more severe illness course. Methods: This is a cross-sectional study that evaluated clinical correlates of general medical comorbidities in outpatients with bipolar disorder (BD) involving 203 adult patients with a DSM-IV diagnosis of BD, consecutively recruited from the Bipolar Research Program (PROTAHBI) in Porto Alegre, Brazil. Clinical, demographic and anthropometrical variables were systematically assessed, and general medical comorbidity was measured using the Cumulative Illness Rating Scale (CIRS). Results: The prevalence of one or more medical comorbidities was 90.1%. The most common were those from endocrine/metabolic/breast, neurologic and vascular categories. A high burden of general medical comorbidities (defined as CIRS total score ≥ 4) was related to increasing age and body mass index and longer duration of illness after controlling for confounding factors. Limitations: The cross-sectional design limits our ability to make causal conclusions. Also, our sample consisted of patients with longer illness duration from a tertiary clinic and may not generalize to the whole spectrum of bipolar disorder. Conclusions: BD was associated with a high burden of general medical conditions related to age, obesity and longer duration of illness. Medical comorbidities must be incorporated as a core feature in the development of effective treatment strategies for bipolar disorder

Artificial intelligence models for predicting cardiovascular diseases in people with type 2 diabetes: A systematic review

BACKGROUND: People with type 2 diabetes have a higher risk of cardiovascular disease morbidity and mortality. We aim to distil the evidence, summarize the developments, and identify the gaps in relevant research on predicting cardiovascular disease in type 2 diabetes people using AI techniques in the last ten years. METHODS: A systematic search was carried out for literature published between 1st January 2010 and 30th May 2021 in five medical and scientific databases, including Medline, EMBASE, Global Health (CABI), IEEE Xplore and Web of Science Core Collection. All English language studies describing AI models for predicting cardiovascular diseases in adults with type 2 diabetes were included. The retrieved studies were screened and the data from included studies were extracted by two reviewers. The survey and synthesis of extracted data were conducted based on predefined research questions. IJMEDI checklist was used for quality assessment. RESULTS: From 176 articles identified by the search, 5 studies with sample sizes ranging from 560 to 203,517 met our inclusion criteria. The models predicted the risk of multiple cardiovascular diseases over 5 or 10 years. Ensemble learning, particularly random forest, is the most used algorithm in these models and consistently provided competitive performance. Commonly used features include age, body mass index, blood pressure measurements, and cholesterol measurements. Only one study carried out external validation. The area under the receiver operating characteristic curve for derivation cohorts varied from 0.69 to 0.77. AI models achieved better performance than conventional models in some specific scenarios. CONCLUSIONS: AI technologies seem to show promising performance (AUROC in external validation: 0.75 compared to 0.69 from conventional risk scores) for cardiovascular disease prediction in type 2 diabetes people. However, only one of the reviewed models conducted an external validation. Quality of reporting was low in general, and all models lack reproducibility and reusability

Association between domestic water hardness, chlorine, and atopic dermatitis risk in early life: A population-based cross-sectional study.

BACKGROUND: Domestic water hardness and chlorine have been suggested as important risk factors for atopic dermatitis (AD). OBJECTIVE: We sought to examine the link between domestic water calcium carbonate (CaCO3) and chlorine concentrations, skin barrier dysfunction (increased transepidermal water loss), and AD in infancy. METHODS: We recruited 1303 three-month-old infants from the general population and gathered data on domestic water CaCO3 (in milligrams per liter) and chlorine (Cl2; in milligrams per liter) concentrations from local water suppliers. At enrollment, infants were examined for AD and screened for filaggrin (FLG) skin barrier gene mutation status. Transepidermal water loss was measured on unaffected forearm skin. RESULTS: CaCO3 and chlorine levels were strongly correlated. A hybrid variable of greater than and less than median levels of CaCO3 and total chlorine was constructed: a baseline group of low CaCO3/low total chlorine (CaL/ClL), high CaCO3/low total chlorine (CaH/ClL), low CaCO3/high total chlorine (CaL/ClH) and high CaCO3/high total chlorine (CaH/ClH). Visible AD was more common in all 3 groups versus the baseline group: adjusted odds ratio (AOR) of 1.87 (95% CI, 1.25-2.80; P = .002) for the CaH/ClL group, AOR of 1.46 (95% CI, 0.97-2.21; P = .07) for the CaL/ClH, and AOR of 1.61 (95% CI, 1.09-2.38; P = .02) for the CaH/ClH group. The effect estimates were greater in children carrying FLG mutations, but formal interaction testing between water quality groups and filaggrin status was not statistically significant. CONCLUSIONS: High domestic water CaCO3 levels are associated with an increased risk of AD in infancy. The influence of increased total chlorine levels remains uncertain. An intervention trial is required to see whether installation of a domestic device to decrease CaCO3 levels around the time of birth can reduce this risk

PASCal: A principal-axis strain calculator for thermal expansion and compressibility determination

We describe a web-based tool (PASCal; Principal Axis Strain Calculator) aimed at simplifying the determination of principal coefficients of thermal expansion and compressibilities from variable-temperature and variable-pressure lattice parameter data. In a series of three case studies, we use PASCal to re-analyse previously-published lattice parameter data and show that additional scientific insight is obtainable in each case. First, the two-dimensional metal-organic framework Cu-SIP-3 is found to exhibit the strongest area-negative thermal expansion (NTE) effect yet observed; second, the widely-used explosive HMX exhibits much stronger mechanical anisotropy than had previously been anticipated, including uniaxial NTE driven by thermal changes in molecular conformation; and, third, the high-pressure form of the mineral malayaite is shown to exhibit a strong negative linear compressibility (NLC) effect that arises from correlated tilting of SnO6 and SiO4 coordination polyhedra.Comment: 31 pages, 8 figures, formatted as preprint for J. Appl. Crys