Wnt-4, a member of the Wnt family of secreted signaling molecules, is essential for nephrogenesis, but its expression in the presumptive medulla suggests additional developmental roles in kidney organogenesis. We demonstrate here that Wnt-4 signaling plays also a role in the determination of the fate of smooth muscle cells in the medullary stroma of the developing kidney, as a differentiation marker, smooth muscle alpha-actin (alpha-SMA), is markedly reduced in the absence of its signaling. Wnt-4 probably performs this function by activating the Bmp-4 gene encoding a known differentiation factor for smooth muscle cells, since Bmp-4 gene expression was lost in the absence of Wnt-4 while Wnt-4 signaling led to a rescue of Bmp-4 expression and induction of alpha-SMA-positive cells in vitro. Recombinant Bmp-4 similarly rescued the differentiation of alpha-SMA-expressing cells in cultured Wnt-4-deficient embryonic kidney. The lack of smooth muscle cell differentiation leads to an associated deficiency in the pericytes around the developing vessels of the Wnt-4-deficient kidney and apparently leads to a secondary defect in the maturation of the kidney vessels. Thus, besides being critical for regulating mesenchymal to epithelial transformation in the cortical region in nephrogenesis, Wnt-4 signaling regulates the fate of smooth muscle cells in the developing medullary region.

BackgroundRespiratory effort belt measurement is a widely used method to monitor respiration. Signal waveforms of respiratory volume and flow may indicate pathological signs of several diseases and, thus, it would be highly desirable to predict them accurately. Calibrated effort belts are sufficiently accurate for estimating respiratory rate, but the respiratory volume and flow prediction accuracies degrade considerably with changes in the subject’s body position and breathing style.MethodsAn improved calibration method of respiratory effort belts is presented in this paper. It is based on an optimally trained FIR (Finite Impulse Response) filter bank constructed as a MISO system (Multiple-Input Single-Output) between respiratory effort belt signals and the spirometer in order to reduce waveform errors. Ten healthy adult volunteers were recruited. Breathing was varied between the following styles: metronome-guided controlled breathing rate of 0.1 Hz, 0.15 Hz, 0.25 Hz and 0.33 Hz, and a free rate that was felt normal by each subject. Body position was varied between supine, sitting and standing. The proposed calibration method was tested against these variations and compared with the state-of-the-art methods from the literature.ResultsRelative waveform error decreased 60-70% when predicting airflow under changing breathing styles. The coefficient of determination R2 varied between 0.88-0.95 and 0.65-0.79 with the proposed and the standard method, respectively. Standard deviation of respiratory volume error decreased even 80%. The proposed method outperformed other methods.ConclusionsResults show that not only the respiratory volume can be computed more precisely from the predicted airflow, but also the flow waveforms are very accurate with the proposed method. The method is robust to breathing style changes and body position changes improving greatly the accuracy of the calibration of respiratory effort belts over the standard method. The enhanced accuracy of the belt calibration offers interesting opportunities, e.g. in pulmonary and critical care medicine when objective measurements are required.

Respiratory disorders are a very common and growing health problem. Signal waveforms of respiratory airflow and volume may indicate pathological signs of several diseases and, thus, it would be important to measure them accurately. Currently, devices used in respiration measurements are mostly obtrusive in nature interfering with the natural respiration patterns. We used a depth camera for the continuous measurement of respiratory function without contact on a subject. We propose a novel calibration method which enables accurate estimates of the respiratory airflow waveforms from the depth camera data. Eight subjects were measured with the depth camera and spirometer at the same time using different breathing styles. Results show that not only the respiratory volume and respiratory rate (RR) can be computed precisely from the estimated respiratory airflow, but also the respiratory airflow waveforms are very accurate. This offers interesting opportunities, e.g. in pulmonary and critical care medicine, when objective measurements are required.

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Allergic rhinitis is a major chronic respiratory disease which more than 500 million people suffer from around the world. It is considered to be an immuno-neuronal disorder, but little is known about the part played by the neural system in nasal allergic reaction. This is due mainly to the lack of objective measurement techniques producing accurate, reliable and continuous measurement data about the dynamic changes in nasal respiratory function. Here, a method to assess the association of nasal airflow resistance and the underlying function of autonomic nervous system (ANS) is presented and used during the birch pollen provocation test. Ten allergic volunteers were challenged with allergen. Continuous nasal airflow resistance and spectral heart rate variability parameters were computed and analyzed for the dynamic changes. The derived signals show in detail the timing and intensity differences in subjects' reactions. After the provocation, the nasal airflow resistance rose gradually, whereas LF power and LF/HF ratio decreased gradually for all subjects. This implies gradually increasing sympathetic withdrawal in allergic patients during the provocation with allergen. The proposed method opens entirely new possibilities to assess accurately the dynamic and short-term changes in non-stationary nasal function and could increase the accuracy and reliability of diagnostics and assessment of the effect of nasal treatments.