Code-free cloud computing service to facilitate rapid biomedical digital signal processing and algorithm development.

BACKGROUND AND OBJECTIVE: Cloud computing has the ability to offload processing tasks to a remote computing resources. Presently, the majority of biomedical digital signal processing involves a ground-up approach by writing code in a variety of languages. This may reduce the time a researcher or health professional has to process data, while increasing the barrier to entry to those with little or no software development experience. In this study, we aim to provide a service capable of handling and processing biomedical data via a code-free interface. Furthermore, our solution should support multiple file formats and processing languages while saving user inputs for repeated use. METHODS: A web interface via the Python-based Django framework was developed with the potential to shorten the time taken to create an algorithm, encourage code reuse, and democratise digital signal processing tasks for non-technical users using a code-free user interface. A user can upload data, create an algorithm and download the result. Using discrete functions and multi-lingual scripts (e.g. MATLAB or Python), the user can manipulate data rapidly in a repeatable manner. Multiple data file formats are supported by a decision-based file handler and user authentication-based storage allocation method. RESULTS: The proposed system has been demonstrated as effective in handling multiple input data types in various programming languages, including Python and MATLAB. This, in turn, has the potential to reduce currently experienced bottlenecks in cross-platform development of bio-signal processing algorithms. The source code for this system has been made available to encourage reuse. A cloud service for digital signal processing has the ability to reduce the apparent complexity and abstract the need to understand the intricacies of signal processing. CONCLUSION: We have introduced a web-based system capable of reducing the barrier to entry for inexperienced programmers. Furthermore, our system is reproducable and scalable for use in a variety of clinical or research fields.

Frailty in end-stage renal disease: comparing patient, caregiver, and clinician perspectives.

BACKGROUND: Frailty is associated with poor outcomes for patients on dialysis and is traditionally measured using tools that assess physical impairment. Alternate measurement tools highlight cognitive and functional domains, requiring clinician, patient, and/or caregiver input. In this study, we compared frailty measures for incident dialysis patients that incorporate patient, clinician, and caregiver perspectives with an aim to contrast the measured prevalence of frailty using tools derived from different conceptual frameworks. METHODS: A prospective cohort study of incident dialysis patients was conducted between February 2014 and June 2015. Frailty was assessed at dialysis onset using: 1) modified definition of Fried Phenotype (Dialysis Morbidity Mortality Study definition, DMMS); 2) Clinical Frailty Scale (CFS); 3) Frailty Assessment Care Planning Tool (provides CFS grading, FACT-CFS); and 4) Frailty Index (FI). Measures were compared via correlation and sensitivity/specificity analyses. RESULTS: A total of 98 patients participated (mean age of 61 ± 14 years). Participants were primarily Caucasian (91%), male (58%), and the majority started on hemodialysis (83%). The median score for both the CFS and FACT-CFS was 4 (interquartile range of 3-5). The mean FI score was 0.31 (standard deviation ± 0.16). The DMMS identified 78% of patients as frail. The FACT-CFS demonstrated highest correlation (r = 0.71) with the FI, while the DMMS was most sensitive (97%, 100%) and a CFS ≥ 5 most specific (100%, 77%) at corresponding FI cutoff values (>0.21, >0.45). CONCLUSIONS: Frailty assessments of incident dialysis patients that include clinician, caregiver and patient perspectives have moderate to strong correlation with the FI. At specified FI cutoff values, the FACT-CFS and DMMS are highly sensitive measures of frailty. The CFS and FACT-CFS may represent viable alternative screening tools in dialysis patients.

Aldehyde dehydrogenase 1A3 influences breast cancer progression via differential retinoic acid signaling.

Aldehyde dehydrogenase (ALDH) 1A enzymes produce retinoic acid (RA), a transcription induction molecule. To investigate if ALDH1A1 or ALDH1A3-mediated RA signaling has an active role in breast cancer tumorigenesis, we performed gene expression and tumor xenograft studies. Analysis of breast patient tumors revealed that high levels of ALDH1A3 correlated with expression of RA-inducible genes with retinoic acid response elements (RAREs), poorer patient survival and triple-negative breast cancers. This suggests a potential link between ALDH1A3 expression and RA signaling especially in aggressive and/or triple-negative breast cancers. In MDA-MB-231, MDA-MB-468 and MDA-MB-435 cells, ALDH1A3 and RA increased expression of RA-inducible genes. Interestingly, ALDH1A3 had opposing effects in tumor xenografts, increasing tumor growth and metastasis of MDA-MB-231 and MDA-MB-435 cells, but decreasing tumor growth of MDA-MB-468 cells. Exogenous RA replaced ALDH1A3 in inducing the same opposing tumor growth and metastasis effects, suggesting that ALDH1A3 mediates these effects by promoting RA signaling. Genome expression analysis revealed that ALDH1A3 induced largely divergent gene expression in MDA-MB-231 and MDA-MB-468 cells which likely resulted in the opposing tumor growth effects. Treatment with DNA methylation inhibitor 5-aza-2'deoxycytidine restored uniform RA-inducibility of RARE-containing HOXA1 and MUC4 in MDA-MB-231 and MDA-MB-468 cells, suggesting that differences in epigenetic modifications contribute to differential ALDH1A3/RA-induced gene expression in breast cancer. In summary, ALDH1A3 induces differential RA signaling in breast cancer cells which affects the rate of breast cancer progression.

Cognitive restructuring and graded behavioural exposure for delusional appraisals of auditory hallucinations and comorbid anxiety in paranoid schizophrenia.

The prevalence of diagnostic comorbidity between psychosis and anxiety disorders has been found to be considerable. Cognitive models of psychosis suggest that anxiety does not arise directly from positive symptoms of schizophrenia but rather from an individual interpretation of such experiences. In the United Kingdom, cognitive-behavioural therapy for psychosis (CBTp) has been recommended within clinical guidelines as a psychological treatment of choice for those diagnosed with schizophrenia. However, despite empirical evidence supporting CBTp, the treatment provision remains infrequent and not routinely available. This case describes a successful implementation of CBTp. Sixteen sessions were delivered to a 40-year-old male with diagnoses of paranoid schizophrenia and comorbid anxiety, focusing primarily on cognitive restructuring of paranoid appraisals of auditory hallucinations and behavioural experiments employed progressively via graded exposure to anxiety-inducing stimuli. Standardised measurements, behavioural frequency sampling, and subjective data indicated a considerable reduction in both paranoia and anxiety. Also, the client's psychosocial functioning improved substantially. This report indicates that the treatment may help those with experiences of psychosis and comorbid anxiety reach a significant improvement in their quality of life and offers an encouraging and innovative perspective on direct engagement with the content of paranoia and voices at the onset of therapy.

The inverse problem utilizing the boundary element method for a nonstandard female torso.

This paper proposes a new method of rapidly deriving the transfer matrix for the boundary element method (BEM) forward problem from a tailored female torso geometry in the clinical setting. The method allows rapid calculation of epicardial potentials (EP) from body surface potentials (BSP). The use of EPs in previous studies has been shown to improve the successful detection of the life-threatening cardiac condition--acute myocardial infarction. The MRI scanning of a cardiac patient in the clinical setting is not practical and other methods are required to accurately deduce torso geometries for calculation of the transfer matrix. The new method allows the noninvasive calculation of tailored torso geometries from a standard female torso and five measurements taken from the body surface of a patient. This scaling of the torso has been successfully validated by carrying out EP calculations on 40 scaled torsos and ten female subjects. It utilizes the BEM in the calculation of the transfer matrix as the BEM depends only upon the topology of the surfaces of the torso and the heart, the former can now be accurately deduced, leaving only the latter geometry as an unknown.

Detection of cardiac arrest using a simplified frequency analysis of the impedance cardiogram recorded from defibrillator pads.

An algorithm based only on the impedance cardiogram (ICG) recorded through two defibrillation pads, using the strongest frequency component and amplitude, incorporated into a defibrillator could determine circulatory arrest and reduce delays in starting cardiopulmonary resuscitation (CPR). Frequency analysis of the ICG signal is carried out by integer filters on a sample by sample basis. They are simpler, lighter and more versatile when compared to the FFT. This alternative approach, although less accurate, is preferred due to the limited processing capacity of devices that could compromise real time usability of the FFT. These two techniques were compared across a data set comprising 13 cases of cardiac arrest and 6 normal controls. The best filters were refined on this training set and an algorithm for the detection of cardiac arrest was trained on a wider data set. The algorithm was finally tested on a validation set. The ICG was recorded in 132 cardiac arrest patients (53 training, 79 validation) and 97 controls (47 training, 50 validation): the diagnostic algorithm indicated cardiac arrest with a sensitivity of 81.1% (77.6-84.3) and specificity of 97.1% (96.7-97.4) for the validation set (95% confidence intervals). Automated defibrillators with integrated ICG analysis have the potential to improve emergency care by lay persons enabling more rapid and appropriate initiation of CPR and when combined with ECG analysis they could improve on the detection of cardiac arrest.

Assessment of the impedance cardiogram recorded by an automated external defibrillator during clinical cardiac arrest.

OBJECTIVE: To assess the impedance cardiogram recorded by an automated external defibrillator during cardiac arrest to facilitate emergency care by lay persons. Lay persons are poor at emergency pulse checks (sensitivity 84%, specificity 36%); guidelines recommend they should not be performed. The impedance cardiogram (dZ/dt) is used to indicate stroke volume. Can an impedance cardiogram algorithm in a defibrillator determine rapidly circulatory arrest and facilitate prompt initiation of external cardiac massage? DESIGN: Clinical study. SETTING: University hospital. PATIENTS: Phase 1 patients attended for myocardial perfusion imaging. Phase 2 patients were recruited during cardiac arrest. This group included nonarrest controls. INTERVENTIONS: The impedance cardiogram was recorded through defibrillator/electrocardiographic pads oriented in the standard cardiac arrest position. MEASUREMENTS AND MAIN RESULTS: Phase 1: Stroke volumes from gated myocardial perfusion imaging scans were correlated with parameters from the impedance cardiogram system (dZ/dt(max) and the peak amplitude of the Fast Fourier Transform of dZ/dt between 1.5 Hz and 4.5 Hz). Multivariate analysis was performed to fit stroke volumes from gated myocardial perfusion imaging scans with linear and quadratic terms for dZ/dt(max) and the Fast Fourier Transform to identify significant parameters for incorporation into a cardiac arrest diagnostic algorithm. The square of the peak amplitude of the Fast Fourier Transform of dZ/dt was the best predictor of reduction in stroke volumes from gated myocardial perfusion imaging scans (range = 33-85 mL; p = .016). Having established that the two pad impedance cardiogram system could detect differences in stroke volumes from gated myocardial perfusion imaging scans, we assessed its performance in diagnosing cardiac arrest. Phase 2: The impedance cardiogram was recorded in 132 "cardiac arrest" patients (53 training, 79 validation) and 97 controls (47 training, 50 validation): the diagnostic algorithm indicated cardiac arrest with sensitivities and specificities (+/- exact 95% confidence intervals) of 89.1% (85.4-92.1) and 99.6% (99.4-99.7; training) and 81.1% (77.6-84.3) and 97% (96.7-97.4; validation). CONCLUSIONS: The impedance cardiogram algorithm is a significant marker of circulatory collapse. Automated defibrillators with an integrated impedance cardiogram could improve emergency care by lay persons, enabling rapid and appropriate initiation of external cardiac massage.

The impedance cardiogram recorded through two electrocardiogram/defibrillator pads as a determinant of cardiac arrest during experimental studies.

OBJECTIVE: Laypersons are poor at emergency pulse checks (sensitivity 84%, specificity 36%). Guidelines indicate that pulse checks should not be performed. The impedance cardiogram (dZ/dt) is used to assess stroke volume. Can a novel defibrillator-based impedance cardiogram system be used to distinguish between circulatory arrest and other collapse states? DESIGN: Animal study. SETTING: University research laboratory. SUBJECTS: Twenty anesthetized, mechanically ventilated pigs, weight 50-55 kg. INTERVENTIONS: Stroke volume was altered by right ventricular pacing (160, 210, 260, and 305 beats/min). Cardiac arrest states were then induced: ventricular fibrillation (by rapid ventricular pacing) and, after successful defibrillation, pulseless electrical activity and asystole (by high-dose intravenous pentobarbitone). MEASUREMENTS AND MAIN RESULTS: The impedance cardiogram was recorded through electrocardiogram/defibrillator pads in standard cardiac arrest positions. Simultaneously recorded electro- and impedance cardiogram (dZ/dt) along with arterial blood pressure tracings were digitized during each pacing and cardiac arrest protocol. Five-second epochs were analyzed for sinus rhythm (20 before ventricular fibrillation, 20 after successful defibrillation), ventricular fibrillation (40), pulseless electrical activity (20), and asystole (20), in two sets of ten pigs (ten training, ten validation). Standard impedance cardiogram variables were noncontributory in cardiac arrest, so the fast Fourier transform of dZ/dt was assessed. During ventricular pacing, the peak amplitude of fast Fourier transform of dZ/dt (between 1.5 and 4.5 Hz) correlated with stroke volume (r2 = .3, p < .001). In cardiac arrest, a peak amplitude of fast Fourier transform of dZ/dt of < or = 4 dB x ohm x rms indicated no output with high sensitivity (94% training set, 86% validation set) and specificity (98% training set, 90% validation set). CONCLUSIONS: As a powerful clinical marker of circulatory collapse, the fast Fourier transformation of dZ/dt (impedance cardiogram) has the potential to improve emergency care by laypersons using automated defibrillators.

Synthesis and characterization of biocompatible, thermoresponsive ABC and ABA triblock copolymer gelators.

The synthesis of doubly thermoresponsive PPO-PMPC-PNIPAM triblock copolymer gelators by atom transfer radical polymerization using a PPO-based macroinitiator is described. Provided that the PPO block is sufficiently long, dynamic light scattering and differential scanning calorimetry studies confirm the presence of two separate thermal transitions corresponding to micellization and gelation, as expected. However, these ABC-type triblock copolymers proved to be rather inefficient gelators: free-standing gels at 37 degrees C required a triblock copolymer concentration of around 20 wt%. This gelator performance should be compared with copolymer concentrations of 6-7 wt% required for the PNIPAM-PMPC-PNIPAM triblock copolymers reported previously. Clearly, the separation of micellar self-assembly from gel network formation does not lead to enhanced gelator efficiencies, at least for this particular system. Nevertheless, there are some features of interest in the present study. In particular, close inspection of the viscosity vs temperature plot obtained for a PPO43-PMPC160-PNIPAM81 triblock copolymer revealed a local minimum in viscosity. This is consistent with intramicelle collapse of the outer PNIPAM blocks prior to the development of the intermicelle hydrophobic interactions that are a prerequisite for macroscopic gelation.

Efficacy of distinct energy delivery protocols comparing two biphasic defibrillators for cardiac arrest.

Limited data have been published on the use of external defibrillators that deliver impedance compensated biphasic (ICB) waveforms in patients. We compared 2 ICB defibrillators, the Heartstream XL (150-150-150 J protocol) and Heartsine Samaritan (100-150-200 J protocol) in 78 consecutive patients in cardiac arrest. The performance of the 2 devices over the first 2 shocks was statistically equivalent. By the third shock, the Heartsine Samaritan had significantly better performance in removing ventricular fibrillation (p = 0.029). Energy selection for ICB waveforms requires further validation.

The use of calculated epicardial potentials improves significantly the sensitivity of a diagnostic algorithm in the detection of acute myocardial infarction.

Inverse electrocardiography can calculate epicardial potentials (EP) from body surface potentials (BSP) taking into account a thoracic volume conductor model (TVCM). Previous studies have shown that a tailored TVCM is superior to a general TVCM in calculating EP. However, construction of a tailored TVCM for a patient in an acute clinical setting is impractical. In this study we used a general TVCM in our EP calculations to determine whether this improves detection of acute myocardial infarction (AMI) using a diagnostic algorithm. BSP were derived from the 80-lead body surface map (BSM). Consecutive patients (n=379) with ischemic type chest pain were recruited. The BSM and a 12-lead electrocardiogram (ECG) were recorded at initial presentation and creatine kinase (CK) and/or CK-MB were measured initially, 12 and 24 hours postsymptom onset. A physician interpreted the 12-lead electrocardiogram and documented ST elevation if present. AMI was defined by the World Health Organization (WHO) criteria. The diagnostic algorithm result for each patient using BSP and calculated EP were documented. AMI occurred in 171 patients. The diagnostic algorithm using BSP identified 106 of these as ST elevation AMI (STEMI) (sensitivity 62%, specificity 80%). The same algorithm using EP identified 133 as STEMI (sensitivity 78%, specificity 80%). Calculated EP improved the algorithm's diagnostic sensitivity by a factor of 1.25 (P<.001) with no significant difference in specificity. Calculated EP using a general TVCM significantly improves the sensitivity of a diagnostic algorithm based on BSP in detection of AMI with no significant loss in specificity.