Aortic pressure wave reconstruction during exercise is improved by adaptive filtering: a pilot study

Reconstruction of central aortic pressure from a peripheral measurement by a generalized transfer function (genTF) works well at rest and mild exercise at lower heart rates, but becomes less accurate during heavy exercise. Particularly, systolic and pulse pressure estimations deteriorate, thereby underestimating central pressure. We tested individualization of the TF (indTF) by adapting its resonance frequency at the various levels of exercise. In seven males (age 44–57) with coronary artery disease, central and peripheral pressures were measured simultaneously. The optimal resonance frequency was predicted from regression formulas using variables derived from the individual’s peripheral pressure pulse, including a pulse contour estimation of cardiac output (pcCO). In addition, reconstructed pressures were calibrated to central mean and diastolic pressure at each exercise level. Using a genTF and without calibration, the error in estimated aortic pulse pressure was −7.5 ± 6.4 mmHg, which was reduced to 0.2 ± 5.7 mmHg with the indTFs using pcCO for prediction. Calibration resulted in less scatter at the cost of a small bias (2.7 mmHg). In exercise, the indTFs predict systolic and pulse pressure better than the genTF. This pilot study shows that it is possible to individualize the peripheral to aortic pressure transfer function, thereby improving accuracy in central blood pressure assessment during exercise

Baroreflex sensitivity is higher during acute psychological stress in healthy subjects under β-adrenergic blockade

Acute psychological stress challenges the cardiovascular system with an increase in BP (blood pressure), HR (heart rate) and reduced BRS (baroreflex sensitivity). β-adrenergic blockade enhances BRS during rest, but its effect on BRS during acute psychological stress is unknown. This study tested the hypothesis that BRS is higher during acute psychological stress in healthy subjects under β-adrenergic blockade. Twenty healthy novice male bungee jumpers were randomized and studied with (PROP, n=10) or without (CTRL, n=10) propranolol. BP and HR responses and BRS [cross-correlation time-domain (BRSTD) and cross-spectral frequency-domain (BRSFD) analysis] were evaluated from 30 min prior up to 2 h after the jump. HR, cardiac output and pulse pressure were lower in the PROP group throughout the study. Prior to the bungee jump, BRS was higher in the PROP group compared with the CTRL group [BRSTD: 28 (24–42) compared with 17 (16–28) ms·mmHg−1, P<0.05; BRSFD: 27 (20–34) compared with 14 (9–19) ms·mmHg−1, P<0.05; values are medians (interquartile range)]. BP declined after the jump in both groups, and post-jump BRS did not differ between the groups. In conclusion, during acute psychological stress, BRS is higher in healthy subjects treated with non-selective β-adrenergic blockade with significantly lower HR but comparable BP

Base and nucleotide excision repair facilitate resolution of platinum drugs-induced transcription blockage

Sensitivity and resistance of cells to platinum drug chemotherapy are to a large extent determined by activity of the DNA damage response (DDR). Combining chemotherapy with inhibition of specific DDR pathways could therefore improve treatment efficacy. Multiple DDR pathways have been implicated in removal of platinum-DNA lesions, but it is unclear which exact pathways are most important to cellular platinum drug resistance. Here, we used CRISPR/Cas9 screening to identify DDR proteins that protect colorectal cancer cells against the clinically applied platinum drug oxaliplatin. We find that besides the expected homologous recombination, Fanconi anemia and translesion synthesis pathways, in particular also transcription-coupled nucleotide excision repair (TC-NER) and base excision repair (BER) protect against platinum-induced cytotoxicity. Both repair pathways are required to overcome oxaliplatin- and cisplatin-induced transcription arrest. In addition to the generation of DNA crosslinks, exposure to platinum drugs leads to reactive oxygen species production that induces oxidative DNA lesions, explaining the requirement for BER. Our findings highlight the importance of transcriptional integrity in cells exposed to platinum drugs and suggest that both TC-NER and BER should be considered as targets for novel combinatorial treatment strategies

Tilt table design for rapid and sinusoidal posture change with minimal vestibular stimulation

Introduction: Cardiovascular response to fast posture change can be used to model individual orthostatic response under normal circumstances and after spaceflight. We set out to construct a computercontrolled tilt table suitable for repeated sinusoidal tilt motion as well as fast, single head-up tilt (HUT). The movement profile of the table was designed to prevent muscle tensing and limit vestibular stimulation. Methods: On the new table, 20 healthy subjects underwent a protocol of fast HUT and sinusoidal tilt motion at 2.5 tilts per minute. BP was measured non-invasively (Finapres). Time domain dynamic response to HUT and frequency domain response to sinusoidal tilts were derived from the beat-to-beat BP and from interbeat-interval (IBI) series. Results: Tilt motion did not induce dizziness and was experienced by all subjects as smooth. The systolic BP response to fast HUT correlated mildly with the systolic BP spectral power at the sinusoical tilt frequency (R = 0.47). The IBI response to fast HUT correlated well with the IBI power at the sinusoidal tilt frequency (R = 0.74). Discussion. In this study we presented a computer controlled tilt table capable of fast posture change and sinusoidal tilts. An exploratory protocol demonstrated that the table is suitable for obtaining cardiovascular response to posture change for modeling purpose

Detecting central hypovolemia in simulated hypovolemic shock by automated feature extraction with principal component analysis

Assessment of the volume status by blood pressure (BP) monitoring is difficult, since baroreflex control of BP makes it insensitive to blood loss up to about one liter. We hypothesized that a machine learning model recognizes the progression of central hypovolemia toward presyncope by extracting information of the noninvasive blood pressure waveform parametrized through principal component analysis. This was tested in healthy volunteers exposed to simulated hemorrhage by lower body negative pressure (LBNP). Fifty-six healthy volunteers were subjected to progressive central hypovolemia. A support vector machine was trained on the blood pressure waveform. Three classes of progressive stages of hypovolemia were defined. The model was optimized for the number of principal components and regularization parameter for penalizing misclassification (cost): C. Model performance was expressed as accuracy, mean squared error (MSE), and kappa statistic (inter-rater agreement). Forty-six subjects developed presyncope of which 41 showed an increase in model classification severity from baseline to presyncope. In five of the remaining nine subjects (1 was excluded) it stagnated. Classification of samples during baseline and end-stage LBNP had the highest accuracy (95% and 50%, respectively). Baseline and first stage of LBNP demonstrated the lowest MSE (0.01 respectively 0.32). Model MSE and accuracy did not improve for C values exceeding 0.01. Adding more than five principal components did not further improve accuracy or MSE. Increment in kappa halted after 10 principal components had been added. Automated feature extraction of the blood pressure waveform allows modeling of progressive hypovolemia with a support vector machine. The model distinguishes classes between baseline and presyncope

Arterial pressure variations as parameters of brain perfusion in response to central blood volume depletion and repletion

Rationale: A critical reduction in central blood volume (CBV) is often characterized by hemodynamic instability. Restoration of a volume deficit may be established by goal-directed fluid therapy guided by respiration-related variation in systolic- and pulse pressure (SPV and PPV). Stroke volume index (SVI) serves as a surrogate end-point of a fluid challenge but tissue perfusion itself has not been addressed. Objective: To delineate the relationship between arterial pressure variations, SVI and regional brain perfusion during CBV depletion and repletion in spontaneously breathing volunteers. Methods: This study quantified in 14 healthy subjects (11 male) the effects of CBV depletion [by 30 and 70 degrees passive head-up tilt (HUT)] and a fluid challenge (by tilt back) on CBV (thoracic admittance), mean middle cerebral artery (MCA) blood flow velocity (V-mean), SVI, cardiac index (Cl), PPV, and SPV. Results: PPV (103 +/- 89%, p = 15% reduction in MCAV(mean) and SVI with comparable sensitivity (67/67% vs. 63/68%, respectively) and specificity (89/94 vs. 89/94%, respectively). A rapid fluid challenge by tilt-back restored all parameters to baseline values within 1 min. Conclusion: In spontaneously breathing subjects, a reduction in MCAVmean was related to an increase in PPV and SPV during graded CBV depletion and repletion. Specifically, PPV and SPV predicted changes in both SVI and MCAV(mean) comparable sensitivity and specificity, however the predictive value is limited in spontaneously breathing subject

Detecting central hypovolemia in simulated hypovolemic shock by automated feature extraction with principal component analysis

Assessment of the volume status by blood pressure (BP) monitoring is difficult, since baroreflex control of BP makes it insensitive to blood loss up to about one liter. We hypothesized that a machine learning model recognizes the progression of central hypovolemia toward presyncope by extracting information of the noninvasive blood pressure waveform parametrized through principal component analysis. This was tested in healthy volunteers exposed to simulated hemorrhage by lower body negative pressure (LBNP). Fifty-six healthy volunteers were subjected to progressive central hypovolemia. A support vector machine was trained on the blood pressure waveform. Three classes of progressive stages of hypovolemia were defined. The model was optimized for the number of principal components and regularization parameter for penalizing misclassification (cost): C. Model performance was expressed as accuracy, mean squared error (MSE), and kappa statistic (inter-rater agreement). Forty-six subjects developed presyncope of which 41 showed an increase in model classification severity from baseline to presyncope. In five of the remaining nine subjects (1 was excluded) it stagnated. Classification of samples during baseline and end-stage LBNP had the highest accuracy (95% and 50%, respectively). Baseline and first stage of LBNP demonstrated the lowest MSE (0.01 respectively 0.32). Model MSE and accuracy did not improve for C values exceeding 0.01. Adding more than five principal components did not further improve accuracy or MSE. Increment in kappa halted after 10 principal components had been added. Automated feature extraction of the blood pressure waveform allows modeling of progressive hypovolemia with a support vector machine. The model distinguishes classes between baseline and presyncope

Time-domain cross-correlation baroreflex sensitivity: performance on the EUROBAVAR data set

Objective To test a new method (cross-correlation baroreflex sensitivity, xBRS) for the computation of time-domain baroreflex sensitivity on spontaneous blood pressure and heart interval variability using the EUROBAVAR data set. Methods We applied xBRS to the 42 records in the EUROBAVAR data set, obtained from 21 patients in the lying and standing positions. One patient had a recent heart transplant and one was diabetic with evident cardiac autonomic neuropathy. xBRS computes the correlation between beat-to-beat systolic blood pressure and R - R interval, resampled at 1 Hz, in a sliding 10 s window, with delays of 0-5 s for interval. The delay with the greatest positive correlation is selected and, when significant at P = 0.01, slope and delay are recorded as one xBRS value. Each 1 s of the recording is the start of a new computation. Non-parametric tests are used. Results With patients in the lying position, xBRS yielded a value of 12.4 ms/mmHg compared with the EUROBAVAR sequential 16.2 ms/mmHg, and for the standing positions the respective values were 6.2 and 6.7 ms/mmHg, giving lying to standing ratios of 1.96 and 2.10, respectively. xBRS yielded results for all files, with 20 values per minute on average at a lower within-patient variance. Best delays were 0, 1 and 2 s, and the delay increased by 102 ms when the patient was in the standing position. The xBRS method was successful in the patients with diabetes and the heart transplant. Conclusion The xBRS method should be considered for experimental and clinical use, because it yielded values that correlated strongly with and were close to the EUROBAVAR averages, yielded more values per minute, had lower within-patient variance and measured baroreflex dela

Slow sinusoidal tilt movements demonstrate the contribution to orthostatic tolerance of cerebrospinal fluid movement to and from the spinal dural space

Standing up elicits a host of cardiovascular changes which all affect the cerebral circulation. Lowered mean arterial blood pressure (ABP) at brain level, change in the cerebral venous outflow path, lowered end-tidal P CO 2 (P ET CO 2 ), and intracranial pressure (ICP) modify cerebral blood flow (CBF). The question we undertook to answer is whether gravity-induced blood pressure (BP) changes are compensated in CBF with the same dynamics as are spontaneous or induced ABP changes in a stable position. Twenty-two healthy subjects (18/4 m/f, 40 ± 8 years) were subjected to 30° and 70° head-up tilt (HUT) and sinusoidal tilts (SinTilt, 0°↨60° around 30° at 2.5–10 tilts/min). Additionally, at those three tilt levels, they performed paced breathing at 6–15 breaths/min to induce larger than spontaneous cardiovascular oscillations. We measured continuous finger BP and cerebral blood flow velocity (CBFv) in the middle cerebral artery by transcranial Doppler to compute transfer functions (TFs) from ABP- to CBFv oscillations. SinTilt induces the largest ABP oscillations at brain level with CBFv gains strikingly lower than for paced breathing or spontaneous variations. This would imply better autoregulation for dynamic gravitational changes. We demonstrate in a mathematical model that this difference is explained by ICP changes due to movement of cerebrospinal fluid (CSF) into and out of the spinal dural sack. Dynamic cerebrovascular autoregulation seems insensitive to how BP oscillations originate if the effect of ICP is factored in. CSF-movement in-and-out of the spinal dural space contributes importantly to orthostatic tolerance by its effect on cerebral perfusion pressure