Noise from spatial heterogeneity changes signal amplification magnitude and increases the variability in dose responses

In most molecular level simulations, spatial heterogeneity is neglected by the well-mixed condition assumption. However, the signals of biomolecular networks are affected from both time and space, which are responsible for diverse physiological responses. To account the spatial heterogeneity in the kinetic model, we consider multiple subvolumes of a reaction, introduce parameters representing transfer of ligands between the volumes, and reduce this to an error-term representing the difference between the well-mixed condition and the actual spatial factors. The error-term approach allows modelling of varying spatial heterogeneity without increasing computational burden exponentially. The effect of varying this term, d, between 0 (well-mixed) and 1 (no mixing) and of adding noise to the kinetic constants was then investigated and correlated with knowledge of the behaviour of real systems and situations where network models are inadequate. The spatial distribution effects on the epidermal growth factor receptor (EGFR) in human mammary epithelial tissue, which is involved in proliferation and tumorigenesis, are studied by introducing noisy kinetic constants. The steady-state of the dose response in the EGFR is strongly affected by spatial fluctuations. The ligand-bound receptor is reduced up to 50% from the response without spatial fluctuations and the variance of the steady-state is increased at least 2-fold from the one for no spatial fluctuations. On the other hand, dynamic properties such as the rising time and overshoot are less sensitive to spatial noise

Validation of a model of regulation in the tryptophan operon against multiple experiment data using global optimisation

This paper is concerned with validating a mathematical model of regulation in the tryptophan operon using global optimization. Although a number of models for this biochemical network are proposed, in many cases only qualitative agreement between the model output and experimental data was demonstrated, since very little information is currently available to guide the selection of parameter values for the models. This paper presents a model validating method using both multiple experimental data and global optimization

Individual employment histories and subsequent cause specific hospital admissions and mortality: a prospective study of a cohort of male and female workers with 21 years follow up

It is a widely held view that the labour market is demanding increased levels of flexibility, and that this is causing greater psychosocial stress among employees.1 Such stress may affect health, either through neuroendocrine pathways, or through increases in behaviours linked with poor health.2 Previously we presented evidence linking an unstable employment history, as measured by a greater number of job changes and shorter duration of current job, with a greater prevalence of smoking and greater alcohol consumption, in male and female workers.3 4 Despite this, we did not observe clear detrimental effects of such instability on health related physiological measures (body mass index, diastolic blood pressure, cholesterol, and lung function), nor on current cardiovascular health (electrocardiogram determined ischaemia and reported symptoms of angina). Finding work is easier for healthy persons, and those persons who need to find work repeatedly will be particularly likely to drop out of the workforce if their health deteriorates. Consequently, an occupational cohort, upon which our previous work was based, is least likely to include people of poor health with an unstable work history. If such people are underrepresented, attempts to determine the association between health and individual work histories will mislead. This study links the same cohort to information on the hospitalisations and deaths experienced over a 21 year follow up period. While those people whose health deteriorated before the enrolment of this cohort must remain poorly represented, these prospective data permit unbiased observation of those cases who experienced ill health subsequently, whether or not this resulted in an exit from the workforce. We hypothesise that an employment history characterised by frequent job changes, whatever the motivation for those changes, will require the person to be more focused on work, and less focused on maintaining personal health, with consequent poorer health for such people

Least-squares methods for identifying biochemical regulatory networks from noisy measurements

<b>Background</b>: We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS). The Total Least Squares (TLS) technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks. <b>Results</b>: The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and <i>mdm2</i> messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL)-6 and (IL)-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL)-6 and (IL)-12b by ATF3. <b>Conclusion</b>: The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable more accurate and reliable identification and modelling of biochemical networks

OPEs and 3-point correlators of protected operators in N=4 SYM

Two- and three-point correlation functions of arbitrary protected operators are constructed in N=4 SYM using analytic superspace methods. The OPEs of two chiral primary multiplets are given. It is shown that the $n$-point functions of protected operators for $n\leq4$ are invariant under $U(1)_Y$ and it is argued that this implies that the two- and three-point functions are not renormalised. It is shown explicitly how unprotected operators can be accommodated in the analytic superspace formalism in a way which is fully compatible with analyticity. Some new extremal correlators are exhibited

Psychological stress and cardiovascular disease: empirical demonstration of bias in a prospective observational study of Scottish men

Objectives: To examine the association between self perceived psychological stress and cardiovascular disease in a population where stress was not associated with social disadvantage. Design: Prospective observational study with follow up of 21 years and repeat screening of half the cohort 5 years from baseline. Measures included perceived psychological stress, coronary risk factors, self reported angina, and ischaemia detected by electrocardiography. Setting: 27 workplaces in Scotland. Participants: 5606 men (mean age 48 years) at first screening and 2623 men at second screening with complete data on all measures Main outcome measures: Prevalence of angina and ischaemia at baseline, odds ratio for incident angina and ischaemia at second screening, rate ratios for cause specific hospital admission, and hazard ratios for cause specific mortality. Results: Both prevalence and incidence of angina increased with increasing perceived stress (fully adjusted odds ratio for incident angina, high versus low stress 2.66, 95% confidence interval 1.61 to 4.41; P for trend <0.001). Prevalence and incidence of ischaemia showed weak trends in the opposite direction. High stress was associated with a higher rate of admissions to hospital generally and for admissions related to cardiovascular disease and psychiatric disorders (fully adjusted rate ratios for any general hospital admission 1.13, 1.01 to 1.27, cardiovascular disease 1.20, 1.00 to 1.45, and psychiatric disorders 2.34, 1.41 to 3.91). High stress was not associated with increased admission for coronary heart disease (1.00, 0.76-1.32) and showed an inverse relation with all cause mortality, mortality from cardiovascular disease, and mortality from coronary heart disease, that was attenuated by adjustment for occupational class (fully adjusted hazard ratio for all cause mortality 0.94, 0.81 to 1.11, cardiovascular mortality 0.91, 0.78 to 1.06, and mortality from coronary heart disease 0.98, 0.75 to 1.27). Conclusions: The relation between higher stress, angina, and some categories of hospital admissions probably resulted from the tendency of participants reporting higher stress to also report more symptoms. The lack of a corresponding relation with objective indices of heart disease suggests that these symptoms did not reflect physical disease. The data suggest that associations between psychosocial measures and disease outcomes reported from some other studies may be spurious

Cause-specific hospital admission and mortality among working men: association with socioeconomic circumstances in childhood and adult life, and the mediating role of daily stress

BACKGROUND: The aim of this study was to investigate the association of childhood and adulthood social class with the occurrence of specific diseases, including those not associated with a high mortality rate, and to investigate daily stress as the mechanism for that part of any association which cannot be accounted for by established risk factors. METHODS: This was a prospective cohort study with 25 years of follow-up for cause-specific morbidity and mortality. A total of 5577 Scottish men were recruited from 27 workplaces in the West of Scotland. Childhood social class was determined from the occupation held by the individual's father, and adulthood social class from the individual's occupation at enrolment. Daily stress was measured at enrolment using the Reeder Stress Inventory. RESULTS: Health differentials were found for cardiovascular diseases, lung cancer, peptic ulcer, asthma, accidents and violence, alcohol-related diseases, and perhaps psychiatric illness. Adulthood circumstances were associated with the incidence of most diseases in adulthood, the exception being stroke, which was strongly associated with less privileged circumstances in childhood. Both childhood and adulthood circumstances contributed to the incidence of coronary heart disease. Daily stress did not underlie any of these associations once the influence of established risk factors had been taken into account. CONCLUSIONS: Socioeconomic circumstances in childhood and adulthood both contribute to health differentials in adulthood, the relative contributions depending upon the particular disease. Where known risk factors explained only part of the excess of a disease among individuals raised or living in less-privileged circumstances, there was no evidence to suggest that daily stress was the reason for the unexplained excess

Limitations of adjustment for reporting tendency in observational studies of stress and self reported coronary heart disease

Recently, observational evidence has been suggested to show a causal association between various "psychosocial" exposures, including psychological stress, and heart disease. Much of this evidence derives from studies in which a self reported psychosocial exposure is related to an outcome dependent on the subjective experience of coronary heart disease (CHD) symptoms. Such outcomes may be measured using standard symptom questionnaires (like the Rose angina schedule). Alternatively they may use diagnoses of disease from medical records, which depend on an individual perceiving symptoms and reporting them to a health worker. In these situations, reporting bias may generate spurious exposure-outcome associations. For example if people who perceive and report their life as most stressful also over-report symptoms of cardiovascular disease then an artefactual association between stress and heart disease will result