Incorporation of caffeine into a quantitative model of fatigue and sleep

A recent physiologically based model of human sleep is extended to incorporate the effects of caffeine on sleep-wake timing and fatigue. The model includes the sleep-active neurons of the hypothalamic ventrolateral preoptic area (VLPO), the wake-active monoaminergic brainstem populations (MA), their interactions with cholinergic/orexinergic (ACh/Orx) input to MA, and circadian and homeostatic drives. We model two effects of caffeine on the brain due to competitive antagonism of adenosine (Ad): (i) a reduction in the homestatic drive and (ii) an increase in cholinergic activity. By comparing the model output to experimental data, constraints are determined on the parameters that describe the action of caffeine on the brain. In accord with experiment, the ranges of these parameters imply significant variability in caffeine sensitivity between individuals, with caffeine's effectiveness in reducing fatigue being highly dependent on an individual's tolerance, and past caffeine and sleep history. Although there are wide individual differences in caffeine sensitivity and thus in parameter values, once the model is calibrated for an individual it can be used to make quantitative predictions for that individual. A number of applications of the model are examined, using exemplar parameter values, including: (i) quantitative estimation of the sleep loss and the delay to sleep onset after taking caffeine for various doses and times; (ii) an analysis of the system's stable states showing that the wake state during sleep deprivation is stabilized after taking caffeine; and (iii) comparing model output successfully to experimental values of subjective fatigue reported in a total sleep deprivation study examining the reduction of fatigue with caffeine. This model provides a framework for quantitatively assessing optimal strategies for using caffeine, on an individual basis, to maintain performance during sleep deprivation.     

Risk assessment for quantitative responses using a mixture model

A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment than others. A mixture model has traditionally been proposed to describe the distribution of responses in treatment groups for such experiments. Using a mixture dose-response model, we derive an upper confidence limit on additional risk, defined as the excess risk over the background risk due to an added dose. Our focus will be on experiments with continuous responses for which risk is the probability of an adverse effect defined as an event that is extremely rare in controls. The asymptotic distribution of the likelihood ratio statistic is used to obtain the upper confidence limit on additional risk. The method can also be used to derive a benchmark dose corresponding to a specified level of increased risk. The EM algorithm is utilized to find the maximum likelihood estimates of model parameters and an extension of the algorithm is proposed to derive the estimates when the model is subject to a specified level of added risk. An example is used to demonstrate the results, and it is shown that by using the mixture model a more accurate measure of added risk is obtained.     

Movements during sleep reveal the developmental emergence of a cerebellar-dependent internal model in motor thalamus

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Joint prediction of multiple quantitative traits using a Bayesian multivariate antedependence model

Predicting organismal phenotypes from genotype data is important for preventive and personalized medicine as well as plant and animal breeding. Although genome-wide association studies (GWAS) for complex traits have discovered a large number of trait- and disease-associated variants, phenotype prediction based on associated variants is usually in low accuracy even for a high-heritability trait because these variants can typically account for a limited fraction of total genetic variance. In comparison with GWAS, the whole-genome prediction (WGP) methods can increase prediction accuracy by making use of a huge number of variants simultaneously. Among various statistical methods for WGP, multiple-trait model and antedependence model show their respective advantages. To take advantage of both strategies within a unified framework, we proposed a novel multivariate antedependence-based method for joint prediction of multiple quantitative traits using a Bayesian algorithm via modeling a linear relationship of effect vector between each pair of adjacent markers. Through both simulation and real-data analyses, our studies demonstrated that the proposed antedependence-based multiple-trait WGP method is more accurate and robust than corresponding traditional counterparts (Bayes A and multi-trait Bayes A) under various scenarios. Our method can be readily extended to deal with missing phenotypes and resequence data with rare variants, offering a feasible way to jointly predict phenotypes for multiple complex traits in human genetic epidemiology as well as plant and livestock breeding.     

Gender and sleep in nightworkers: a quantitative analysis of sleep in days off

Differences in sleep patterns between workdays and days off contribute to shiftwork effects on workers' health and well-being. But regardless of shift schedules, female workers face more difficulties in fulfilling their sleep need because of housework. This study analyzes gender differences concerning sleep in days off by comparing sleep patterns in male and female nightworkers, analyzing sleep as related to the presence of children and testing the association of sleep features between workdays and days off. Male (n = 16) and female (n = 30) workers at a plastic plant, working from 10 p.m. to 6 a.m., on weekdays, filled sleep logs for seven consecutive weeks. Male and female samples did not differ in length of night sleep or in total length of sleep. For both samples, sleep length/day in days off increased, but the difference was lager among females. Also important were the relations between sleep in workdays and days off, specially among women. Among female workers, the results indicated that workers with children tended to sleep less in Saturday mornings, suggesting a negative effect of motherhood on sleep not restricted to workdays. The general results indicate that sleep need on the one hand, and social factors on the other determine the actual amount of sleep.     

Lymphangiogenesis quantification using quantitative PCR and breast cancer as a model.

The detection of lymphangiogenesis (formation of new lymphatics) has previously been difficult to measure, primarily due to the lack of specific markers for lymphatic endothelium. Using conventional PCR (polymerase chain reaction), DNA sequencing, plasmid synthesis, and real-time quantitative PCR (RTQPCR), we report a new approach to enable the measurement of lymphangiogenesis using LYVE-1, a novel, specific lymphatic marker in breast cancer tissue. By using a Scorpion-based probe system with the RTQPCR analyser, a highly sensitive and specific detection and quantitation of LYVE-1 was possible. It was found that lymphangiogenesis occurred in all breast specimens and that higher levels were found in tumours which had spread to the lymph nodes.     

Modeling epistasis of quantitative trait loci using Cockerham's model

We use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.     

Contribution of circadian physiology and sleep homeostasis to age-related changes in human sleep

The circadian pacemaker and sleep homeostasis play pivotal roles in vigilance state control. It has been hypothesized that age-related changes in the human circadian pacemaker, as well as sleep homeostatic mechanisms, contribute to the hallmarks of age-related changes in sleep, that is, earlier wake time and reduced sleep consolidation. Assessments of circadian parameters in healthy young (∼20-30 years old) and older people (∼65-75 years old)—in the absence of the confounding effects of sleep, changes in posture, and light exposure—have demonstrated that an earlier wake time in older people is accompanied by about a 1h advance of the rhythms of core body temperature and melatonin. In addition, older people wake up at an earlier circadian phase of the body temperature and plasma melatonin rhythm. The amplitude of the endogenous circadian component of the core body temperature rhythm assessed during constant routine and forced desynchrony protocols is reduced by 20-30% in older people. Recent assessments of the intrinsic period of the human circadian pacemaker in the absence of the confounding effects of light revealed no age-related reduction of this parameter in both sighted and blind individuals. Wake maintenance and sleep initiation are not markedly affected by age except that sleep latencies are longer in older people when sleep initiation is attempted in the early morning. In contrast, major age-related reductions in the consolidation and duration of sleep occur at all circadian phases. Sleep of older people is particularly disrupted when scheduled on the rising limb of the temperature rhythm, indicating that the sleep of older people is more susceptible to arousal signals genernpated by the circadian pacemaker. Sleep-homeostatic mechanisms, as assayed by the sleep-deprivation-induced increase of EEG slow-wave activity (SWA), are operative in older people, although during both baseline sleep and recovery sleep SWA in older people remains at lower levels. The internal circadian phase advance of awakening, as well as the age-related reduction in sleep consolidation, appears related to an age-related reduction in the promotion of sleep by the circadian pacemaker during the biological night in combination with a reduced homeostatic pressure for sleep. Early morning light exposure associated with this advance of awakening in older people could reinforce the advanced circadian phase. Quantification of the interaction between sleep homeostasis and circadian rhythmicity contributes to understanding age-related changes in sleep timing and quality. (Chronobiology International, 17(3), 285-311, 2000)     

A quantitative model of sleep-wake dynamics based on the physiology of the brainstem ascending arousal system

A quantitative, physiology-based model of the ascending arousal system is developed, using continuum neuronal population modeling, which involves averaging properties such as firing rates across neurons in each population. The model includes the ventrolateral preoptic area (VLPO), where circadian and homeostatic drives enter the system, the monoaminergic and cholinergic nuclei of the ascending arousal system, and their interconnections. The human sleep-wake cycle is governed by the activities of these nuclei, which modulate the behavioral state of the brain via diffuse neuromodulatory projections. The model parameters are not free since they correspond to physiological observables. Approximate parameter bounds are obtained by requiring consistency with physiological and behavioral measures, and the model replicates the human sleep-wake cycle, with physiologically reasonable voltages and firing rates. Mutual inhibition between the wake-promoting monoaminergic group and sleep-promoting VLPO causes ;;flip-flop' behavior, with most time spent in 2 stable steady states corresponding to wake and sleep, with transitions between them on a timescale of a few minutes. The model predicts hysteresis in the sleep-wake cycle, with a region of bistability of the wake and sleep states. Reducing the monoaminergic-VLPO mutual inhibition results in a smaller hysteresis loop. This makes the model more prone to wake-sleep transitions in both directions and makes the states less distinguishable, as in narcolepsy. The model behavior is robust across the constrained parameter ranges, but with sufficient flexibility to describe a wide range of observed phenomena.     

Development of a biochip for quantitative determination of two forms of prostate specific antigen using internal calibration curve

Three-dimensional gel-based microchip allowing simultaneous quantitative detection of total (PSAtot) and free (PSAfree) forms of prostate specific antigen in human serum (in a format "one patient-one biochip") was developed. A method, which doesn't require preliminary construction of calibration curves when performing an assay, was applied for quantitative determination of PSAtot and PSAfree. Gel elements with immobilized antigen (PSA) in different concentration, forming an internal calibration curve, were included in a structure of the microchip, in addition to the elements with immobilized antibodies specific against PSAtot and PSAfree. The specialized software "ImaGelAssay" was used for data processing and interpretation. The sensitivity of the assay performed on biochips was 0.3 ng/ml for PSAtot and 0.2 ng/ml for PSAfree. Variation coefficient for the measurements inside one series of microchips didn't exceed 10%. Correlation coefficient between the results of measurements in human sera obtained on biochips and by the standard ELISA method was 0.988 for PSAtot and 0.987 for PSAfree.     

Properties of spontaneous mutations affecting quantitative traits

Recent mutation accumulation results from invertebrate species suggest that mild deleterious mutation is far less frequent than previously thought, implying smaller expressed mutational loads. Although the rate (lambda) and effect (s) of very slight deleterious mutation remain unknown, most mutational fitness decline would come from moderately deleterious mutation (s approximately 0.2, lambda approximately 0.03), and this situation would not qualitatively change in harsh environments. Estimates of the average coefficient of dominance (h) of non-severe deleterious mutations are controversial. The typical value of h = 0.4 can be questioned, and a lower estimate (about 0.1) is suggested. Estimated mutational parameters are remarkably alike for morphological and fitness component traits (excluding lethals), indicating low mutation rates and moderate mutational effects, with a distribution generally showing strong negative asymmetry and little leptokurtosis. New mutations showed considerable genotype-environment interaction. However, the mutational variance of fitness-component traits due to non-severe detrimental mutations did not increase with environmental harshness. For morphological traits, a class of predominantly additive mutations with no detectable effect on fitness and relatively small effect on the trait was identified. This should be close to that responsible for standing variation in natural populations.     

Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model

The incorporation of developmental control mechanisms of growth has proven to be a powerful tool in mapping quantitative trait loci (QTL) underlying growth trajectories. A theoretical framework for implementing a QTL mapping strategy with growth laws has been established. This framework can be generalized to an arbitrary number of time points, where growth is measured, and becomes computationally more tractable, when the assumption of variance stationarity is made. In practice, however, this assumption is likely to be violated for age-specific growth traits due to a scale effect. In this article, we present a new statistical model for mapping growth QTL, which also addresses the problem of variance stationarity, by using a transform-both-sides (TBS) model advocated by Carroll and Ruppert (1984, Journal of the American Statistical Association 79, 321-328). The TBS-based model for mapping growth QTL cannot only maintain the original biological properties of a growth model, but also can increase the accuracy and precision of parameter estimation and the power to detect a QTL responsible for growth differentiation. Using the TBS-based model, we successfully map a QTL governing growth trajectories to a linkage group in an example of forest trees. The statistical and biological properties of the estimates of this growth QTL position and effect are investigated using Monte Carlo simulation studies. The implications of our model for understanding the genetic architecture of growth are discussed.     

Prediction of flowering time in Brassica oleracea using a quantitative trait loci-based phenology model

Uniformly developing plants with a predictable time to harvest or flowering under unfavourable climate conditions are a major breeding goal in crop species. The main flowering regulators and their response to environmental signals have been identified in Arabidopsis thaliana and homologues of flowering genes have been mapped in many crop species. However, it remains unclear which genes determine within and across genotype flowering time variability in Brassica oleracea and how genetic flowering time regulation is influenced by environmental factors. The goal of this study is model-based prediction of flowering time in a B. oleracea DH-line population using genotype-specific and quantitative trait loci (QTL) model input parameters. A QTL-based phenology model accounting for genotypic differences in temperature responses during vernalisation and non-temperature-sensitive durations from floral transition to flowering was evaluated in two field trials. The model was parameterised using original genotype-specific model input parameters and QTL effects. The genotype-specific model parameterisation showed accurate predictability of flowering time if floral induction was promoted by low temperature (R(2) = 0.81); unfavourably high temperatures reduced predictability (R(2) = 0.65). Replacing original model input parameters by QTL effects reduced the capability of the model to describe across-genotype variability (R(2) = 0.59 and 0.50). Flowering time was highly correlated with a model parameter accounting for vernalisation effects. Within-genotype variability was significantly correlated with the same parameter if temperature during the inductive phase was high. We conclude that flowering time variability across genotypes was largely due to differences in vernalisation response, although it has been shown elsewhere that the candidate FLOWERING LOCUS C (FLC) did not co-segregate with flowering time in the same population. FLC independent vernalisation pathways have been described for several species, but not yet for B. oleracea.     

A quantitative model for metabolic intervention using gut microbes

As medicine shifts toward precision-based and personalized therapeutics, utilizing more complex biomolecules to treat increasingly difficult and rare conditions, microorganisms provide an avenue for realizing the production and processing necessary for novel drug pipelines. More so, probiotic microbes can be co-opted to deliver therapeutics by oral administration as living drugs, able to survive and safely transit the digestive tract. As living therapeutics are in their nascency, traditional pharmacokinetic–pharmacodynamic (PK–PD) models for evaluating drug candidates are not appropriate for this novel platform. Using a living therapeutic in late-stage clinical development for phenylketonuria (PKU) as a case study, we adapt traditional oral drug delivery models to properly evaluate and inform the engineering of living therapeutics. We develop the adapted for living therapeutics compartmental absorption and transit (ALT-CAT) model to provide metrics for drug efficacy across nine age groups of PKU patients and evaluate model parameters that are influenced by patient physiology, microbe selection and therapeutic production, and dosing formulations. In particular, the ALT-CAT model describes the mathematical framework to model the behavior of orally delivered engineered bacteria that act as living therapeutics by adapting similar methods that have been developed and widely-used for small molecular drug delivery and absorption.     

A quantitative method for predicting shelf life of soft drinks using a model system

Summary A quantitative method for the prediction of growth of the food spoilage yeastZygosaccharomyces bailii in a model fruit-drink system is described. A factorially designed experiment was employed to produce polynomial equations relating pH and sugar concentration (°brix) to the lag period and doubling time of this yeast. Low pH values (<3.0) and high °brix values (>40) show a strong synergistic action on the extension of lag period, which could be used, along with the model presented, in the formulation of product preservation systems.     

In a rat model of night work, activity during the normal resting phase produces desynchrony in the hypothalamus

Internal synchrony among external cycles and internal oscillators allows adaptation of physiology to cyclic demands for homeostasis. Night work and shift work lead to a disrupted phase relationship between external time cues and internal rhythms, also losing internal coherence among oscillations. This process results in internal desynchrony (ID) in which behavioral, hormonal, and metabolic variables cycle out of phase. It is still not clear whether ID originates at a peripheral or at a central level. In order to determine the possible role of hypothalamic oscillators in ID, we explored with a rat model of "night work" daily rhythms of activity and clock gene expression in the hypothalamus. This study provides evidence that wakefulness and activity during the normal resting phase lead to a shift in the diurnal rhythms of c-Fos and induce a rhythm of PER1 in the arcuate and dorsomedial nucleus of the hypothalamus, both associated with metabolism and regulation of the sleep/wake cycle. Moreover, the number of orexin (ORX)-positive neurons and c-Fos in the perifornical area increased during the working period, suggesting a relevant switch of activity in this brain region induced by the scheduled activity; however, the colocalization of c-Fos in ORX-positive cells was not increased. In contrast, the suprachiasmatic nucleus and the paraventricular nucleus remained locked to the light/dark cycle, resulting in ID in the hypothalamus. Present data suggest that ID occurs already at the level of the first output projections from the SCN, relaying nuclei that transmit temporal signals to other brain areas and to the periphery.     

Immediate versus delayed midface distraction in a primate model using a new intraoral internal device

The theoretic advantage of distraction osteogenesis of the craniofacial skeleton, especially in cases of severe midface retrusion and in the presence of maxillary scarring, is prevention of relapse following significant advancements. The purpose of this study is to demonstrate the utility of a new low-profile, intraoral, internal device for midface distraction at the conventional or high Le Fort I level. In addition, the present study compares the efficacy of immediate versus delayed distraction on subsequent maxillary relapse. Four adult rhesus Macaca mulatta monkeys were divided into two groups. Group 1 underwent immediate midface distraction; group 2 underwent delayed distraction. All four monkeys underwent a modified Le Fort I osteotomy through an upper buccal sulcus incision and bilateral application of the intraoral midface distraction devices. No other osteotomies or incisions were necessary. Immediate distraction, performed in group 1, entailed intraoperative activation of the devices and distraction of 10 mm followed by a 5-day lag period before postoperative activation and distraction of an additional 10 mm at the rate of 1 mm/day. Delayed distraction, performed in group 2, entailed a 5-day postoperative lag period before device activation and distraction of 20 mm at the rate of 1 mm/day. Both groups thus underwent 20 mm of midface distraction. All devices were removed 6 weeks after completion of distraction. All monkeys tolerated the devices and daily distraction uneventfully. On the basis of serial cephalograms and dental models obtained throughout the experimental period, there was no evidence of relapse in either the immediate or delayed groups 6 months after distraction. In addition, on the basis of histologic, ultrastructural, and dry skull analysis, no significant differences were observed in the quality of regenerate bone obtained when comparing the immediate and delayed distraction groups. Significant midface advancement is thus feasible using this new internal, intraoral distraction device, which presents several advantages over other internal devices that require coronal incisions and additional osteotomies to achieve midface advancement. In addition, immediate distraction may abbreviate the distraction period without adverse sequelae.