Pulse transit time (PTT) and pulse wave velocity (PWV), respectively, were shown to have a correlation with systolic blood pressure (SBP) and have been reported to be suitable for indirect BP measurements. The aim of this study was to create a function between SBP and PWV, and to test its reliability for the determination of absolute SBP using a non-linear algorithm and a one-point calibration. 63 volunteers performed exercise to induce rises in BP. Arterial PTT was measured between the R-spike of the ECG and the plethysmographic curve of finger pulse-oximetry. The reference BP was measured using a cuff-based sphygmomanometric aneroid device. Data from 13 of the 63 volunteers served for the detection of the PWV-BP relationship. The created non-linear function was used to calculate BP values after individual correction for the BP offset in a group of 50 volunteers. Individual correlation coefficients for SBP measured by PTT (SBP(PTT)) and by cuff (SBP(CUFF)) varied between r = 0.69 and r = 0.99. Taking all data together, we found r = 0.83 (276 measurements in 50 volunteers). In the Bland-Altman plot, the limits of agreement were [Formula: see text]± 19.8 mmHg. In conclusion, comparing SBP values using the PTT-based method and those measured by cuff resulted in a significant correlation. However, the Bland-Altman plot shows relevant differences between both methods, which are partly due to greater variability of the SBP(PTT) measurement during intensified exercise. Results suggest that PTT can be used for measuring absolute SBP when performing an individual correction for the offset of the BP-PWV relation.

Contrast-induced acute kidney injury (CIAKI) occurs in up to 30% of patients who receive iodinated contrast media and is generally considered to be the third most common cause of hospital-acquired AKI. Accurate assessment of the incidence of CIAKI is obscured, however, by the use of various definitions for diagnosis, the different populations studied and the prophylactic measures put in place. A deeper understanding of the mechanisms that underlie CIAKI is required to enable reliable risk assessment for individual patients, as their medical histories will determine the specific pathways by which contrast media administration might lead to kidney damage. Here, we highlight common triggers that prompt the development of CIAKI and the subsequent mechanisms that ultimately cause kidney damage. We also discuss effective protective measures, such as rapidly acting oral hydration schemes and loop diuretics, in the context of CIAKI pathophysiology. Understanding of how CIAKI arises in different patient groups could enable a marked reduction in incidence and improved outcomes. The ultimate goal is to shape CIAKI prevention strategies for individual patients.

We consider the problem of experimental detection of directionality of weak coupling between two self-sustained oscillators from bivariate data. We further develop the method introduced by Rosenblum and Pikovsky [Phys. Rev. E 64, 045202 (2001)], suggesting an alternative approach. Next, we consider another framework for identification of directionality, based on the idea of mutual predictability. Our algorithms provide directionality index that shows whether the coupling between the oscillators is unidirectional or bidirectional, and quantifies the asymmetry of bidirectional coupling. We demonstrate the efficiency of three different algorithms in determination of directionality index from short and noisy data. These techniques are then applied to analysis of cardiorespiratory interaction in healthy infants. The results reveal that the direction of coupling between cardiovascular and respiratory systems varies with the age within the first 6 months of life. We find a tendency to change from nearly symmetric bidirectional interaction to nearly unidirectional one (from respiration to the cardiovascular system).

Advances in technology have enabled us to take a fresh look at data acquired by traditional single experiments and to compare them with genomewide data. The differences can be tremendous, as we show here, in the field of proteomics. We have compared data sets of protein-protein interactions in Saccharomyces cerevisiae that were detected by an identical underlying technical method, the yeast two-hybrid system. We found that the individually identified protein-protein interactions are considerably different from those identified by two genomewide scans. Interacting proteins in the pooled database from single publications are much more closely related to each other with respect to transcription profiles when compared to genomewide data. This difference may have been introduced by two factors: by a selection process in individual publications and by false positives in the whole-genome scans. If we assume that the differences are a result of false positives in the whole-genome data, the scans would contain 47%, 44%, and 91% of false positives for the UETZ, ITO-core, and ITO-full data, respectively. If, however, the true fraction of false positives is considerably lower than estimated here, the data from hypothesis-driven experiments must have been subjected to a serious selection process.