Tracheal pressure, central airflow, and alveolar capsule pressures in cardiac lobes were measured in open-chest dogs during 0.1- to 20-Hz pseudorandom forced oscillations applied at the airway opening. In the interval 0.1-4.15 Hz, the input impedance data were fitted by four-parameter models including frequency-independent airway resistance and inertance and tissue parts featuring a marked negative frequency dependence of resistance and a slight elevation of elastance with frequency. The models gave good fits both in the control state and during histamine infusion. At the same time, the regional transfer impedances (alveolar pressure-to-central airflow ratios) showed intralobar and interlobar variabilities of similar degrees, which increased with frequency and were exaggerated during histamine infusion. Results of simulation studies based on a lung model consisting of a central airway and a number of peripheral units with airway and tissue parameters that were given independent wide distributions were in agreement with the experimental findings and showed that even an extremely inhomogeneous lung structure can produce virtually homogeneous mechanical behavior at the input.

In nine anesthetized and paralyzed cats, the mechanical impedances of the total respiratory system (Zrs) and the lungs (ZL) were measured with small-volume pseudorandom forced oscillations between 0.2 and 20 Hz. ZL was measured after thoracotomy, and chest wall impedance (Zw) was calculated as Zw = Zrs-ZL. All impedances were determined by using input airflow [input impedance (Zi)] and output flow measured with a body box [transfer impedance (Zt)]. The differences between Zi and Zt were small for Zrs and negligible for ZL. At 0.2 Hz, the real and imaginary parts of ZL amounted to 33 +/- 4 and 35 +/- 3% (SD), respectively, of Zrs. Up to 8 Hz, all impedances were consistent with a model containing a frequency-independent resistance and inertance and a constant-phase tissue part (G-jH)/omega alpha, where G and H are coefficients for damping and elastance, respectively, omega is angular frequency, and alpha determines the frequency dependence of the real and imaginary parts. G/H was higher for Zw than for ZL (0.29 +/- 0.05 vs. 0.22 +/- 0.04, P less than 0.01). In four cats, the amplitude dependence of impedances was studied: between oscillation volumes of 0.8 and 3 ml, GL, HL, Gw, and Hw decreased on average by 3, 9, 26, and 29%, respectively, whereas the change in G/H was small for both ZL (7%) and Zw (-4%). The values of H were two to three times higher than the quasistatic elastances estimated with greater volume changes (greater than 20 ml).

Respiratory mechanical impedances were determined during voluntary apnea in five healthy subjects, by means of 0.25- to 5-Hz pseudo/random oscillations applied at the mouth. The total respiratory impedance was partitioned into pulmonary (ZL) and chest wall components with the esophageal balloon technique; corrections were made for the upper airway shunt impedance and the compressibility of alveolar gas. Neglect of these shunt effects did not qualitatively alter the frequency dependence of impedances but led to underestimations in impedance, especially in the chest wall resistance (Rw), which decreased by 20-30% at higher frequencies. The total resistance (Rrs) was markedly frequency dependent, falling from 0.47 +/- 0.06 (SD) at 0.25 Hz to 0.17 +/- 0.01 at 1 Hz and 0.15 +/- 0.01 kPa X l-1 X s at 5 Hz. The changes in Rrs were caused by the frequency dependence of Rw almost exclusively between 0.25 and 2 Hz and in most part between 2 and 5 Hz. The effective total respiratory (Crs,e) and pulmonary compliance were computed with corrections for pulmonary inertance derived from three- and five-parameter model fittings of ZL. Crs,e decreased from the static value (1.03 +/- 0.18 l X kPa-1) to a level of approximately 0.35 l X kPa-1 at 2-3 Hz; this change was primarily caused by the frequency-dependent behavior of chest wall compliance.

Ageing has a huge impact on human health and economy, but its molecular basis – regulation and mechanism – is still poorly understood. By today, more than three hundred genes (almost all of them function as protein-coding genes) have been related to human ageing. Although individual ageing-related genes or some small subsets of these genes have been intensively studied, their analysis as a whole has been highly limited. To fill this gap, for each human protein we extracted 21000 protein features from various databases, and using these data as an input to state-of-the-art machine learning methods, we classified human proteins as ageing-related or non-ageing-related. We found a simple classification model based on only 36 protein features, such as the “number of ageing-related interaction partners”, “response to oxidative stress”, “damaged DNA binding”, “rhythmic process” and “extracellular region”. Predicted values of the model quantify the relevance of a given protein in the regulation or mechanisms of the human ageing process. Furthermore, we identified new candidate proteins having strong computational evidence of their important role in ageing. Some of them, like Cytochrome b-245 light chain (CY24A) and Endoribonuclease ZC3H12A (ZC12A) have no previous ageing-associated annotations.