Fernando T. Camacho

Estimation of pressure pulse amplification between aorta and brachial artery using stepwise multiple regression models.

The pressure pulse is amplified between the aorta and peripheral sites. This study compares two methods to estimate pressure pulse amplification (PPA) between the aorta and the brachial artery. Method 1: PPA was determined from a multi-parameter linear regression of subject parameters (gender, age, height, weight, heart rate (HR), brachial systolic pressure (BSP), diastolic pressure (BDP), mean pressure (MP)). Method 2: PPA was calculated from central aortic pressure waveforms (CW) estimated from the same subject parameters. The sample population (1421 male, 992 female) was selected from a database where aortic pressure was estimated by mathematical transformation of a peripheral (radial) pulse calibrated to sphygmomanometric BSP and BDP. The two methods were consistent in showing HR and MP as the most important parameters to estimate PPA. Correlation coefficients (R2) of 0.48 (method 1) and 0.44 (method 2) were obtained using height, weight, HR, BSP, BDP and age. Inclusion of MP increased R2 to 0.77 (method 1) and 0.71 (method 2). This study shows that databases containing peripheral and central aortic pressure waveforms can be used to construct multiple regression models for PPA estimation. These models could be applied to studies of similar subject groups where peripheral waveforms may not be available.

Hollow-fiber assay for ligand-mediated Cell adhesion

The investigation of receptor‐ligand interactions in the cellular context presents significant technical challenges, first, to immobilize the ligand in a manner that preserves functional properties and, second, to relate ligand properties to cell adhesion and other cellular processes.

Price Regulation and Investment: A Real Options Approach

This paper examines a three-period model of an investment decision in a network industry characterized by demand uncertainty, economies of scale and sunk costs. In the absence of regulation we identify the market conditions under which a monopolist decides to invest early as well as the underlying overall welfare output. In a regulated environment, we first consider a monopolist facing no downstream competition but subject to a price cap on the downstream retail (final good) market. We identify the welfare-maximising regulated prices using the unregulated market output as a benchmark. In particular, we show that the optimal regulation depends on market conditions (that is, the nature of demand) and there are three possible outcomes: (i) price regulation does not improve welfare; (ii) regulated prices include an option to delay value and provide a positive payoff to the firm; and (iii) regulated prices yield a zero payoff to the firm. Second, we consider a vertically integrated network provider that is required to provide access to downstream competitors. We show that when the regulator has only one instrument, namely the access price, an option-to-delay pricing rule generates (weakly) higher welfare than the Efficient Component Pricing Rule (ECPR), except under very specific conditions.

Retail Price Regulation and the Option to Delay

This paper examines a two-period model of an investment decision in a network industry characterized by demand uncertainty, economies of scale and sunk costs. In the absence of regulation we identify the market conditions under which a monopolist decides to invest early as well as the underlying overall welfare output. In a regulated environment, we consider a monopolist who faces no downstream (final good) competition but is subject to retail price regulation. We identify the welfare-maximizing regulated prices when the unregulated market outcome is set as the benchmark. We show that if the regulator can commit to ex post regulation – that is, regulated prices that are contingent to future demand realization – then regulated prices that allow the firm to recover its total costs of production are welfare-maximizing. Thus, under ex post price regulation there is no need to compensate the regulated firm for the option to delay that it foregoes when investing today. We argue, however, that regulators cannot make this type of commitment and, therefore, price regulation is often ex ante – that is, regulated prices are not contingent to future demand. We show that the optimal ex ante regulation, and the extent to which regulated prices need to incorporate an option to delay, depend on the nature of demand uncertainty.

A linear regression model for assessment of interdependent parameters of central pressure determined from the peripheral pulse

The central aortic pressure waveform (CW) is determined by cardiac and vascular parameters. In the intact circulatory system, the influence of individual parameters on CW cannot be readily assessed because of parameter interdependence. This study presents a linear regression model for estimating CW from a range of measurements of heart rate (HR), brachial systolic pressure (BSP) and frequency components of previous CWs for an individual subject. The model was constructed using data from 34 subjects (age 20-76 years) in whom multiple CWs were determined from the radial pulse waveform over a given range of HR (42-77 bpm) and BSP (90-172 mmHg). For each subject a model was created to estimate the particular CW for any given heart rate and BSP. All models were validated independently using a cross validation technique. The model was able to estimate CW to within a mean error of <1 mmHg. The models were used to compare the influence of BSP on the late systolic pressure augmentation (augmentation index (AIx)) for a fixed HR. This study suggests that a linear regression model that estimates the CW can be used to assess the effect of individual parameters on specific waveform features. This allows the characterization of the effect of individual parameters on CW features, such that the response can be quantified independently of other parameters as a family of CWs over a specified range.