Advanced models of human skeletal muscle differentiation, development and disease: Three-dimensional cultures, organoids and beyond

Advanced in vitro models of human skeletal muscle tissue are increasingly needed to model complex developmental dynamics and disease mechanisms not recapitulated in animal models or in conventional monolayer cell cultures. There has been impressive progress towards creating such models by using tissue engineering approaches to recapitulate a range of physical and biochemical components of native human skeletal muscle tissue. In this review, we discuss recent studies focussed on developing complex in vitro models of human skeletal muscle beyond monolayer cell cultures, involving skeletal myogenic differentiation from human primary myoblasts or pluripotent stem cells, often in the presence of structural scaffolding support. We conclude with our outlook on the future of advanced skeletal muscle three-dimensional cultures (e.g. organoids and biofabrication) to produce physiologically and clinically relevant platforms for disease modelling and therapy development in musculoskeletal and neuromuscular disorders

Do Remittances Promote Economic Growth? New Evidence from India

This study investigates the empirical relationship between remittances and economic growth of India, placing special attention on the non-linearity of this association. Previous studies on India have ignored the non-linear nature of the remittance-growth nexus. The study employs methods from the ARDL model framework to explore the non-linearity and establishes that remittances do not exhibit any growth effect in lower quantiles and up to 0.50, but the impact increases monotonically, getting more pronounced as the quantile increases. In other words, inward remittances must exceed a threshold to start affecting economic growth positively. It is argued that this behaviour of the remittances is the consequence of a combination of factors like patterns of utilisation (or, misutilisation) of the receipts, India’s trade balance, a weak industrial sector, the lack of entrepreneurial opportunities, the lack of financial inclusion, and the exploitation of poor migrant workers

Dissociative Autoionization in (1+2)-photon Above Threshold Excitation of H2 Molecules

We have theoretically studied the effect of dissociative autoionization on the photoelectron energy spectrum in (1+2)-photon above threshold ionization(ATI) of H2 molecules. We have considered excitation from the ground state X-singlet-Sigma-g+(v=0,j) to the doubly excited autoionizing states of singlet-Sigma-u+ and singlet-Pi-u+ symmetry, via the intermediate resonant B-singlet-Sigma-u+(v=5,j) states. We have shown that the photoelectron energy spectrum is oscillatory in nature and shows three distinct peaks above the photoelectron energy 0.7 eV. This feature has been observed in a recent experiment by Rottke et al, J. Phys. B, Vol. 30, p-4049 (1997).Comment: 11 pages and 4 figure

Supporting Treatment Adherence Readiness through Training (START) for patients with HIV on antiretroviral therapy: study protocol for a randomized controlled trial.

BackgroundFew HIV antiretroviral adherence interventions target patients before they start treatment, assess adherence readiness to determine the timing of treatment initiation, or tailor the amount of adherence support. The Supporting Treatment Adherence Readiness through Training (START) intervention, based on the information-motivation-behavioral skills model of behavior change, is designed to address these gaps with the inclusion of (1) brief pill-taking practice trials for enhancing pretreatment adherence counseling and providing a behavioral criterion for determining adherence readiness and the timing of treatment initiation and (2) a performance-driven dose regulation mechanism to tailor the amount of counseling to the individual needs of the patient and conserve resources. The primary aim of this randomized controlled trial is to examine the effects of START on antiretroviral adherence and HIV virologic suppression.Methods/designA sample of 240 patients will be randomized to receive START or usual care at one of two HIV clinics. Primary outcomes will be optimal dose-taking adherence (>85 % prescribed doses taken), as measured with electronic monitoring caps, and undetectable HIV viral load. Secondary outcomes will include dose-timing adherence (>85 % prescribed doses taken on time) and CD4 count. Primary endpoints will be month 6 (short-term effect) and month 24 (to test durability of effect), though electronic monitoring will be continuous and a fully battery of assessments will be administered every 6 months for 24 months.DiscussionIf efficacious and cost-effective, START will provide clinicians with a model for assessing patient adherence readiness and helping patients to achieve and sustain readiness and optimal treatment benefits.Trial registrationClinicalTrials.gov identifier NCT02329782 . Registered on 22 December 2014

Technique for optimal placement of transducers for fault detection in rotating machines

Online fault detection and diagnosis of rotating machinery requires a number of transducers that can be significantly expensive for industrial processes. The sensitivity of various transducers and their appropriate positioning are dependent on different types of fault conditions. It is critical to formulate a method to systematically determine the effectiveness of transducer locations for monitoring the condition of a machine. In this article, number of independent sources analysis is used as an effective tool for reducing the number of vibration sources within the system, which is then followed by prin- cipal component analysis to identify the incoherent transducers to be employed for fault detection. This experiment is conducted on a machine fault simulator for unbalanced rotor, misaligned shaft, and cracked shaft. The validation of the proposed selection process is illustrated using spectral analysis for each defect.Peer reviewe

Automatic identification of epileptic and background EEG signals using frequency domain parameters

The analysis of electroencephalograms continues to be a problem due to our limited understanding of the signal origin. This limited understanding leads to ill-defined models, which in turn make it hard to design effective evaluation methods. Despite these shortcomings, electroencephalogram analysis is a valuable tool in the evaluation of neurological disorders and the evaluation of overall cerebral activity. We compared different model based power spectral density estimation methods and different classification methods. Specifically, we used the autoregressive moving average as well as from Yule-Walker and Burg's methods, to extract the power density spectrum from representative signal samples. Local maxima and minima were detected from these spectra. In this paper, the locations of these extrema are used as input to different classifiers. The three classifiers we used were: Gaussian mixture model, artificial neural network, and support vector machine. The classification results are documented with confusion matrices and compared with receiver operating characteristic curves. We found that Burg's method for spectrum estimation together with a support vector machine classifier yields the best classification results. This combination reaches a classification rate of 93.33%, the sensitivity is 98.33% and the specificy is 96.67%

Open-ended evolution to discover analogue circuits for beyond conventional applications

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10710-012-9163-8. Copyright @ Springer 2012.Analogue circuits synthesised by means of open-ended evolutionary algorithms often have unconventional designs. However, these circuits are typically highly compact, and the general nature of the evolutionary search methodology allows such designs to be used in many applications. Previous work on the evolutionary design of analogue circuits has focused on circuits that lie well within analogue application domain. In contrast, our paper considers the evolution of analogue circuits that are usually synthesised in digital logic. We have developed four computational circuits, two voltage distributor circuits and a time interval metre circuit. The approach, despite its simplicity, succeeds over the design tasks owing to the employment of substructure reuse and incremental evolution. Our findings expand the range of applications that are considered suitable for evolutionary electronics