Modeling "frailty": can a simple feedback model suffice?

This commentary offers several views of frailty, and provides an excerpt of the dynamic model proposed by Varadhan et al., noting that it is of a traditional, causal feedback type. Key features of the authors' model are examined, and some limitations identified. (Other more modern approaches are suggested, but not expanded.) In spite of its simplicity, the deterministic feedback model as presented does indicate that weakened connectivity among feedback loops is a possible basis of frailty. In contrast, a nodal-network style of modeling might emphasize nodal failure as well as (or instead of) connectivity failure as the dynamic signature of frailty.

Progress and prospects: gene transfer into embryonic stem cells.

With the isolation of human embryonic stem cells (hESCs) in 1998 came the realization of a long-sought aspiration for an unlimited source of human tissue. The difficulty of differentiating ESCs to pure, clinically exploitable cell populations to treat genetic and degenerative diseases is being solved in part with the help of genetically modified cell lines. With progress in genome editing and somatic cell nuclear transfer, it is theoretically possible to obtain genetically repaired isogenic cells. Moreover, the prospect of being able to select, isolate and expand a single cell to a vast population of cells could achieve a unique level of quality control, until now unattainable in the field of gene therapy. Most of the tools necessary to develop these strategies already exist in the mouse ESC system. We review here the advances accomplished in those fields and present some possible applications to hESC research.

Gene therapy of severe combined immunodeficiencies.

Recent advances in gene transfer in human hematopoietic cells, combined with a better understanding of the genetic aspects of several immunodeficiencies, has offered new opportunities in the domain of gene therapy. Severe combined immunodeficiency (SCID) appear to represent a good model for the application of gene therapy, combining an expected selective advantage for transduced cells, an absence of immunological response to the vector and/or the therapeutic transgene, together with accessibility to hematopoietic stem cells (HSC). Ex vivo retroviral transduction of a therapeutic transgene in HSC prior to transplantation appears to be a particularly effective and long-lasting means of restoring the expression of a mutated gene in the lymphoid lineage. Furthermore, encouraging therapeutic benefits as a result of a gene therapy protocol for the treatment of X-linked severe combined immunodeficiencies (SCID-X1) invites many questions as to the reasons for this therapeutic benefit. This review outlines the results that have been achieved in gene therapy for SCID-X1, ADA-SCID as well as other types of SCID, and discusses the possible relationship between the physiopathology of each disease and the success of relevant trials.

Ultradian rhythms of alternating cerebral hemispheric EEG dominance are coupled to rapid eye movement and non-rapid eye movement stage 4 sleep in humans.

Objective: To replicate the left minus right (L-R) hemisphere EEG power shifts coupled to rapid eye movement (REM) and non-rapid eye movement (NREM) sleep observed in 1972 by Goldstein (Physiol Behav (1972) 811), and to characterize the L-R EEG power spectra for total EEG, delta, theta, alpha and beta bands.Background: Ultradian alternating cerebral hemispheric dominance rhythms are observed using EEG during both waking and sleep, and with waking cognition. The question of whether this cerebral rhythm is coupled to the REM-NREM sleep cycle and the basic rest-activity cycle (BRAC) deserves attention.Methods: L-R EEG signals for ten young, normal adult males were converted to powers and the means were normalized, smoothed and subtracted. Sleep hypnograms were compared with L-R EEGs, and spectra were computed for C3, C4 and L-R EEG powers.Results: Significant peaks were found for all C3, C4 and L-R frequency bands at the 280-300, 75-125, 55-70 and 25-50 min bins, with power dominating in the 75-125 min bin. L-R EEG rhythms were observed for all bands. Greater right hemisphere EEG dominance was found during NREM stage 4 sleep, and greater left during REM for total EEG, delta and alpha bands (Chi-squares, P<0.001). Theta was similar, but not significant (P=0.163), and beta was equivocal.Conclusions: Earlier ultradian studies show that lateral EEG and L-R EEG power have a common pacemaker, or a mutually entrained pacemaker with the autonomic, cardiovascular, neuroendocrine and fuel-regulatory hormone systems. These results for L-R EEG coupling to sleep stages and multi-variate relations may present a new perspective for Kleitman's BRAC and for diagnosing variants of pathopsychophysiological states.

Kinetics of human aging: I. Rates of senescence between ages 30 and 70 years in healthy people.

A calculation of loss rates is reported for human structural and functional variables from a substantially larger data set than has been previously studied. Data were collected for healthy, nonsmoking human subjects of both sexes from a literature search of cross-sectional, longitudinal, and cross-sequential studies. The number of studies analyzed was 469, and the total number of subjects was 54,274. A linear model provided a fit of the data, for each variable, that was not significantly different from the best polynomial fit. Therefore, linear loss rates (as a percent decline per year from the reference value at age 30) were calculated for 445 variables from 13 organ systems, and additionally for 24 variables even more integrative, such as maximum oxygen consumption and exercise performance, that express effects of multiple contributing variables and systems. The frequency distribution of the 13 individual system linear loss rates (as percent loss per year) for a very healthy population has roughly a unimodal, right-skewed shape, with mean 0.65, median 0.5, and variance 0.32. (The actual underlying distribution could be a truncated Gaussian, an exponential, Poisson, gamma or some other). The linear estimates of loss rates were clustered between 0% and 2% per year for variables from most organ systems, with exceptions being the endocrine, thermoregulatory, and gastrointestinal systems, for which wider ranges (up to approximately 3% per year) of loss rates were found. We suggest that this set of linear losses over time, observed in healthy individuals between ages (approximately) 30 to 70 years, exposes the underlying kinetics of human senescence, independent of effects of substantial disease.

Ultradian sleep rhythms of lateral EEG, autonomic, and cardiovascular activity are coupled in humans.

This study compared the dynamics of multiple systems during sleep with earlier results during waking rest. Three consecutive nights of data were collected from three healthy adults for 10 variables: left and right central EEGs; the nasal cycle (NC); beat-to-beat measures of CO, SV, HR, SBP, DBP, MAP, and hemoglobin-oxygen saturation. Time series analysis detected periods at 280-300, 215-275, 165-210, 145-160, 105-140, 70-100, and 40-65 min bins with the greatest spectral power in longer periods. We found significance across subjects with all parameters at 280-300, 105-140 (except left EEG power, left minus right EEG power, and HR), 70-100, and 40-65 min. Significant periods were reported earlier during waking for the NC, pituitary hormones, catecholamines, insulin, and cardiovascular function in five bins at 220-340, 170-215, 115-145, 70-100, and 40-65 min, with 115-145, 70-100, and 40-65 min common across all variables. These results suggest that lateral EEG power during sleep has a common pacemaker (the hypothalamus), or a mutually entrained pacemaker, with the cardiovascular and autonomic nervous systems (ANS), and that the waking ultradians of the neuroendocrine and fuel regulatory hormones may also be coupled to lateral EEG activity. Taken together these results present a new perspective for the Basic Rest-Activity Cycle and the physiology of the ANS-central nervous system during both waking and sleep.

Low-frequency ultradian insulin rhythms are coupled to cardiovascular, autonomic, and neuroendocrine rhythms.

Plasma insulin levels were assayed to compare with earlier reported rhythms of the cardiovascular, autonomic, and neuroendocrine systems in 10 resting normal adults over 5-6 h. Our earlier report included time-series analysis for impedance cardiography measures of stroke volume, heart rate, cardiac output, thoracic fluid index, ejection velocity index, and ventricular ejection time; automated cuff measures of systolic, diastolic, and mean arterial pressures; the nasal cycle as a marker of lateralized autonomic tone; and indwelling venous catheters for sampling blood every 7.5 min to assay for adrenocorticotropic hormone, luteinizing hormone, epinephrine, and norepinephrine. Insulin was later assayed from the same plasma samples. Time-series analysis using the fast orthogonal search method of Korenberg detected insulin periodicities at ranges of 220-340, 115-145, 70-100, and 40-65, with significance across subjects at ranges of 115-145, 70-100, and 40-65 min. Significant periods for the other parameters were reported earlier at 220-340, 170-215, 115-145, 70-100, and 40-65 min, with periods at 115-145, 70-100, and 40-65 min dominating across parameters. These results suggest that insulin secretion has a common pacemaker (the hypothalamus) or a mutually entrained pacemaker with the autonomic, cardiovascular, and neuroendocrine systems.

Ultradian rhythms of autonomic, cardiovascular, and neuroendocrine systems are related in humans.

Autonomic, cardiovascular, and neuroendocrine activities were monitored for 5-6 h in 10 normal adult resting humans (8 males, 2 females). The nasal cycle, a measure of lateralized autonomic tone, was measured at 4 Hz. Impedance cardiography (BoMed NCCOM3) was used to measure cardiac output, thoracic fluid index, heart rate, ejection velocity index, stroke volume, and ventricular ejection time (averages of 12 heart beats). Systolic, diastolic, and mean arterial pressures were measured with an automated cuff at 7.5-min intervals. Separate blood samples were taken every 7.5 min simultaneously from both arms with the use of indwelling venous catheters. Assays for adrenocorticotropic hormone, luteinizing hormone, norepinephrine, epinephrine, and dopamine were performed on samples from each arm. Time-series analysis, using the fast orthogonal search method of Korenberg, was used to detect variance structure. Significant spectral periods were observed in five windows at 220-340, 170-215, 115-145, 70-100, and 40-65 min. The greatest spectral power was observed in the lower frequencies, but periods at 115-145, 70-100, and 40-65 min were common across variables. Significant correlation coefficients for linear regressions of all paired variables in each subject were observed in 38.87% of the comparisons (subject range, 18.05-48-9.70%) with r > 0.30. These results suggest that either a common oscillator (the hypothalamus) or mutually entrained oscillators regulate these systems.

Ultradian rhythmic models of blood pressure variation in normal human daily life.

To examine levels and variance structure of systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR), we measured those 3 variables every 7.5 min for 24 h (approximately 192 samples each subject) by ambulatory monitoring in 2 nominated groups of normal volunteers: younger (Y; 8 men, 5 women, 24-44 years) and older (O; 13 men, 12 women, 50-95 years). Y and O did not differ in either sleep or wake means for HR and DBP. Mean SBP in O was 17 mm Hg higher than in Y during wakefulness. Thirty-four subjects had significant low frequency variations (presumably the circadian rhythm) in SBP, DBP and HR, regardless of age. A periodic model fitting the time series required a 9 h feature (rhythm) for Y and O in DBP for best reduction of mean square error. In addition, O regularly showed 3 h features in both SBP and DBP, a 6 h feature in DBP and a 9 h feature in SBP, which were absent in Y. Our results suggest that low-power ultradian rhythms may appear in both SBP and DBP after age 50, and possibly serve as dynamic markers of normal cardiovascular aging.

Ultradian adrenocortical and circulatory oscillations in conscious dogs.

We examined adrenal blood flow, cortisol secretion rate, concentration of cortisol in adrenal venous blood, mean arterial blood pressure, and heart rate in unrestrained conscious dogs, sampling at 15-20 s, 5 min, or 10 min during experiments lasting from 30 min to 8 h. Time history analysis designed for short, noisy time series detected three significant ultradian oscillatory periods: approximately 3, 6, and 90 min. Circulatory variables (systemic mean arterial pressure, heart rate, and adrenal blood flow) showed all three. Cortisol secretion rate showed the 3- and 90-min oscillations but not the 6-min oscillation. Adrenal glucocorticoid secretion rate and adrenal blood flow were not strongly coupled. However, at one extreme of blood flow (close to zero) and at the opposite extreme (very high blood flow stimulated by adrenocorticotropic hormone) adrenal blood flow and cortisol secretion were tightly coupled. In the normal physiological range, the multiperiodic, rhythmic organization of circulatory variables and adrenal glucocorticoid function arises from independent or only weakly coupled oscillators, not necessarily harmonically related, manifesting near-periodicity with wobble and intermittency.