Hyperoxic exposure enhances airway reactivity in newborn animals, possibly due to altered relaxation. We sought to define the role of prostaglandinand nitric oxide-mediated mechanisms in impaired airway relaxation induced by hyperoxic stress. We exposed 7-day-old rat pups to either room air or hyperoxia (>95% O2) for 7 days to assess airway relaxation and cAMP and cGMP production after electrical field stimulation (EFS). EFS-induced relaxation of preconstricted trachea was diminished in hyperoxic vs. normoxic animals (P < 0.05). Indomethacin (a cyclooxygenase inhibitor) reduced EFS-induced airway relaxation in tracheae from normoxic (P < 0.05), but not hyperoxic, rat pups; however, in the presence of NG-nitro-L-arginine methyl ester (a nitric oxide synthase inhibitor) EFS-induced airway relaxation was similarly decreased in tracheae from both normoxic and hyperoxic animals. After EFS, the increase from baseline in the production of cAMP was significantly higher in tracheae from normoxic than hyperoxic rat pups, and this was accompanied by greater prostaglandin E2 release only in the normoxic group. cGMP production after EFS stimulation did not differ between normoxic and hyperoxic groups. We conclude that hyperoxia impairs airway relaxation in immature animals via a mechanism primarily involving the prostaglandin-cAMP signaling pathway with an impairment of prostaglandin E2 release and cAMP accumulation.
The Discrete Fourier Transform (DFT) is a mathematical procedure that stands at the center of the processing inside a Digital Signal Processor (DSP). It has been widely known and argued in relevant literature that the Fast Fourier Transform (FFT) is useless in detecting specific frequencies in a monitored signal of length N because most of the computed results are ignored. In this paper, we present an efficient FFT-based method to detect specific frequencies in a monitored signal, which will then be compared to the most frequently used method which is the recursive Goertzel algorithm that detects and analyses one selectable frequency component from a discrete signal. The proposed JM-Filter algorithm presents a reduction of iterations compared to the first and second order Goertzel algorithm by a factor of r, where r represents the radix of the JM-Filter. The obtained results are significant in terms of computational reduction and accuracy in fixed-point implementation. Gains of 15 dB and 19 dB in signal to quantization noise ratio (SQNR) were respectively observed for the proposed first and second order radix-8 JM-Filter in comparison to Goertzel algorithm.
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