Core Stabilization Exercise Prescription, Part 2: A Systematic Review of Motor Control and General (Global) Exercise Rehabilitation Approaches for Patients with Low Back Pain

Context: Therapeutic exercises are frequently prescribed to patients with low back pain. Numerous exercise programs for patients with low back pain have been described. Many of these treatment programs are based on 1 of 2 popular rehabilitation strategies: a motor control exercise approach or a general exercise approach. Data Sources: PubMed clinical queries from 1966 to March 2013 for keyword combinations including motor control exercise, core stability exercise, therapeutic exercise, general exercise, global exercise, local exercise, transversus abdominis, segmental stabilization, and low back pain. Study Selection: Randomized controlled trials that assessed the effects of a motor control exercise approach, a general exercise approach, or both for patients with low back pain that were published in scientific peer-reviewed journals. Data Extraction: Included studies underwent appraisal for exercise intervention and outcomes. Results: Fifteen studies were identified (8, motor control exercise approach without general exercise comparison; 7, general exercise approach with or without motor control exercise approach comparison). Current evidence suggests that exercise interventions may be effective at reducing pain or disability in patients with low back pain. Conclusion: Stabilization exercises for patients with low back pain may help to decrease pain and disability. It may not be necessary to prescribe exercises purported to restore motor control of specific muscles

Parametric hazard rate models for long-term sickness absence

PURPOSE: In research on the time to onset of sickness absence and the duration of sickness absence episodes, Cox proportional hazard models are in common use. However, parametric models are to be preferred when time in itself is considered as independent variable. This study compares parametric hazard rate models for the onset of long-term sickness absence and return to work. METHOD: Prospective cohort study on sickness absence with four follow-up years of 53,830 employees working in the private sector in the Netherlands. The time to onset of long-term (>6 weeks) sickness absence and return to work were modelled by parametric hazard rate models. RESULTS: The exponential parametric model with a constant hazard rate most accurately described the time to onset of long-term sickness absence. Gompertz-Makeham models with monotonically declining hazard rates best described return to work. CONCLUSIONS: Parametric models offer more possibilities than commonly used models for time-dependent processes as sickness absence and return to work. However, the advantages of parametric models above Cox models apply mainly for return to work and less for onset of long-term sickness absence

MOF-mediated synthesis of supported Fe-doped Pd nanoparticles under mild conditions for magnetically recoverable catalysis

Metal-organic framework (MOF)-driven synthesis is considered as a promising alternative for the development of new catalytic materials with well-designed active sites. This synthetic approach is used here to gradually transform a new bimetallic MOF, with Pd and Fe as the metal components, by the in situ generation of aniline under mild conditions. This methodology results in a compositionally homogeneous nanocomposite formed by Fe-doped Pd nanoparticles that, in turn, are supported on iron oxide-doped carbon. The nanocomposite has been fully characterized by several techniques such as IR and Raman spectroscopy, TEM, XPS, and XAS. The performance of this nanocomposite as an heterogeneous catalyst for hydrogenation of nitroarenes and nitrobenzene coupling with benzaldehyde has been evaluated, proving it to be an efficient and reusable catalyst

Cell-intrinsic depletion of Aml1-ETO-expressing pre-leukemic hematopoietic stem cells by K-Ras activating mutation

Somatic mutations in acute myeloid leukemia are acquired sequentially and hierarchically. First, pre-leukemic mutations, such as t(8;21) that encodes AML1-ETO, are acquired within the hematopoietic stem cell (HSC) compartment, while signaling pathway mutations, including KRAS activating mutations, are late events acquired during transformation of leukemic progenitor cells and are rarely detectable in HSC. This raises the possibility that signaling pathway mutations are detrimental to clonal expansion of pre-leukemic HSC. To address this hypothesis, we used conditional genetics to introduce Aml1-ETO and K-RasG12D into murine HSC, either individually or in combination. In the absence of activated Ras, Aml1-ETO-expressing HSC conferred a competitive advantage. However, activated K-Ras had a marked detrimental effect on Aml1-ETO-expressing HSC, leading to loss of both phenotypic and functional HSC. Cell cycle analysis revealed a loss of quiescence in HSC co-expressing Aml1-ETO and K-RasG12D, accompanied by an enrichment in E2F and Myc target gene expression and depletion of HSC self-renewal-associated gene expression. These findings provide a mechanistic basis for the observed absence of KRAS signaling mutations in the pre-malignant HSC compartment

Automatic diagnosis of the 12-lead ECG using a deep neural network

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice