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We consider the effects of noise on a model of epidemic outbreaks, where the outbreaks appear randomly. Using a constructive transition approach that predicts large outbreaks prior to their occurrence, we derive an adaptive control scheme that prevents large outbreaks from occurring. The theory is applicable to a wide range of stochastic processes with underlying deterministic structure.
A pharmacokinetic model for the accumulation of di-2-ethylhexyl phthalate (DEHP) by sheepshead minnow predicted a significant increase in the bioconcentration factor (BCF) of DEHP if its metabolism were inhibited. To test this prediction, fish were treated with either piperonyl butoxide (PBO) or bis-(p-nitrophenyl)phosphate (BNPP) before and during their exposure to DEHP. Compared with the controls, the PBO-treated fish showed no significant differences in either the amount of total metabolites in the fish and exposure water or the amount of DEHP in the fish. Conversely, the total amount of metabolites formed by BNPP-treated fish was only 23% of that in the control. This indicated that hydrolysis was a major pathway for DEHP metabolism in sheepshead minnow. The amount of DEHP accumulated by the BNPP-treated fish was almost twice that of the controls, which also agreed with the model prediction. A pharmacokinetic analysis of the time course of DEHP accumulation and metabolism indicated that BNPP altered the dynamics of DEHP in the fish beyond simply reducing the metabolic clearance. BNPP reduced the value of the absorption clearance to half that of the control, and the phthalate appeared to distribute more rapidly to the poorly perfused tissues. These effects may have been caused by the anticholinesterase activity of BNPP. The model-predicted BCF of DEHP in BNPP-treated fish was more than 6 times the control value, apparently as a consequence of decreased metabolic clearance and increased volume of distribution.
To clarify whether homeostasis model assessment (HOMA IR) and quantitative insulin sensitivity check index (QUICKI) may be indicators of insulin resistance in elderly patients with type 2 diabetes mellitus, their relationship with the glucose infusion rate during the euglycemic hyperinsulinemic clamp study (clamp IR) was assessed. This study comprised 56 Japanese patients with type 2 diabetes mellitus; of these, 28 were 70 yr of age or older (group 1) and 28 were less than 70 yr of age (group 2). Their blood sugars were in poor control (fasting plasma glucose levels: group 1, 9.0 +/- 2.6 mmol/liter; group 2, 8.9 +/- 2.3 mmol/liter; hemoglobin A1c: group 1, 9.5 +/- 2.0%; group 2, 9.2 +/- 1.7%). Log-transformed HOMA IR was significantly correlated with the clamp IR in group 2 patients (r = -0.51, P < 0.01), but not in group 1 patients (r = -0.28, P = 0.15). There was a significant positive correlation between QUICKI and clamp IR in group 2 patients (r = 0.50, P < 0.01). However, no significant correlation was observed between QUICKI and clamp IR in group 1 patients (r = 0.31, P = 0.12). There was a significant correlation between log-transformed HOMA IR (r = -0.37, P < 0.01) or QUICKI (r = 0.37, P < 0.01) and clamp IR when both groups were combined. In conclusion, neither HOMA IR nor QUICKI should be used as an index of insulin resistance in elderly patients with poorly controlled type 2 diabetes mellitus. The results of this study suggest the need for developing a new noninvasive method for evaluating insulin resistance in those patients.
A stochastic model for the dynamics of a plant-pathogen interaction is developed and fitted to observations of the fungal pathogen Rhizoctonia solani (Kühn) in radish (Raphanus sativus L.), in both the presence and absence of the antagonistic fungus Trichoderma viride (Pers ex Gray). The model incorporates parameters for primary and secondary infection mechanisms and for characterizing the time-varying susceptibility of the host population. A parameter likelihood is developed and used to fit the model to data from microcosm experiments. It is shown that the stochastic model accounts well for observed variability both within and between treatments. Moreover, it enables us to describe the time evolution of the probability distribution for the variability among replicate epidemics in terms of the underlying epidemiological parameters for primary and secondary infection and decay in susceptibility. Consideration of profile likelihoods for each parameter provides strong evidence that T. viride mainly affects primary infection. By using the stochastic model to study the dependence of the probability distribution of disease levels on the primary infection rate we are therefore able to predict the effectiveness of a widely used biological control agent.
Hypertensive patients' expressing themselves in their own words (Exposition) and providers' giving information (Explanation) during medical interviews were hypothesized to be associated with subsequent blood pressure control. Transcripts of routine return visits to clinics in low-income areas of Houston, TX, were coded using the Verbal Response Modes (VRM) system. VRM indexes of Patient Exposition and Provider Explanation were tested in relation to systolic and diastolic blood pressure obtained during home interviews 2 weeks after the clinic visits. Patient Exposition was significantly correlated with reductions in systolic and diastolic blood pressure from clinic visit to home interview, and Provider Explanation was significantly correlated with lower diastolic blood pressure at home interview. The results suggest that patients' and providers' verbal behavior in medical interviews should be included in predictive models of blood pressure control.
The cost-effective operation of an analytical system depends on quality-control (QC) practices such as the QC procedure itself (control rules, number of control measurements); the batch size or the run length; and the use of bracketed, nonbracketed, or pre-control modes of operation. Predictive value models that predict the defect rate and test yield of each test, as well as of the system as a whole, have been used to study these practices and to develop strategies for improving the quality and productivity of a multitest analyzer. Quality was optimized for most tests by achieving high error detection and low false rejection by the QC procedures. For a few tests where ideal QC performance could not be achieved, predictive models indicate that high quality is achieved, predictive models indicate that high quality is achieved as long as the observed stabilities (low frequencies of errors) of the measurement procedures are maintained. In our laboratories, productivity gains of 2.9% ($17,400/year) were achieved by changing QC procedures. Predictive models indicate that further gains are possible by increasing batch size and changing from bracketed to nonbracketed control operation. In general, the common practice of bracketed control on stable analytical systems may need to be re-examined owing to its effect on the cost of operation.
Expression of the pyrBI operon of Escherichia coli K-12, which encodes the subunits of the pyrimidine biosynthetic enzyme aspartate transcarbamylase, is negatively regulated by the intracellular levels of UTP. Previous experiments suggested a unique model for regulation of operon expression in which low UTP levels cause close coupling of transcription and translation of the pyrBI leader region. This close coupling suppresses transcriptional termination at an attenuator preceding the structural genes. In this study, we examined the regulatory role of translation and attenuation in operon expression. To determine whether the leader region is translated, we constructed a plasmid, designated pBHM17, in which the pyrBI promoter(s) and the first 11 codons for a putative 44-amino acid leader polypeptide are fused to codon 9 of lacZ. A transformant carrying this plasmid synthesized a beta-galactosidase fusion protein with the amino-terminal sequence of the leader polypeptide, demonstrating that the signals required for leader polypeptide synthesis function in vivo. Synthesis of the fusion protein was nearly insensitive to pyrimidine availability. In uracil-grown cells, the level of fusion protein synthesis encoded by plasmid pBHM17 was much greater than that encoded by a similar plasmid containing a pyrB::lacZ gene fusion, in which the pyrBI promoter-regulatory region is intact. These results indicate that the downstream leader sequence which includes the attenuator is required for regulation and functions as a transcriptional barrier. Oligonucleotide-directed mutagenesis was used to change the ATG leader polypeptide initiation codon of the intact pyrBI operon to ACG, which was shown to strongly inhibit translational initiation. This mutation greatly reduced operon expression and regulation as predicted by the attenuation control model.
Aaron Antonovsky's sense of coherence (SOC) [(1987) Unraveling the Mystery of Health, How People Manage Stress and Stay Well, Jossey-Bass, San Francisco] ought to explain why some people manage stress and stay well while others break down. According to Antonovsky's formulation, SOC is strongly developed if a person sees the world as comprehensible (i.e. rational, understandable, consistent and predictable), as manageable, and as meaningful (i.e. challenging and that things are worth making commitments for). Sense of coherence has gained widespread attention and has been used as an explanatory variable in many studies. This paper discusses some aspects that have not sufficiently been considered in the SOC literature. First, an outline of the construct is given. Next, overlaps and differences with other concepts in the same domain are discussed. Little empirical evidence concerning the stability of SOC is available. Therefore, findings from experimental social psychological studies on self-esteem are applied to SOC. Third, it can be assumed that SOC is an attitude of people who are well educated, are in rather privileged societal positions, and with opportunities for decision-making. Finally, the empirical basis is reviewed. Statistical relationships between SOC and symptoms/disease are in the predicted direction, but due to the simultaneous assessment of variables it is open to debate whether a low SOC has some effect on the probability of falling ill or whether it is the other way around. Very high negative correlations between SOC and depression/anxiety suggest that the instruments used may assess the same phenomenon, but with inverse signs. Based on these considerations, directions for further research are proposed.
We propose the use of artificial neural networks in an in silico epilepsy model of biological neural networks: 1) to predict the onset of state transitions from higher complexities, possibly chaotic to lower complexity possibly rhythmic activities; and 2) to restore the original higher complexity activity. A coupled nonlinear oscillators model (Bardakjian and Diamant, 1994) was used to represent the spontaneous seizure-like oscillations of CA3 hippocampal neurons (Bardakjian and Aschebrenner-Scheibe, 1995) to illustrate the prediction and control schemes of these state transition onsets. Our prediction scheme consists of a recurrent neural network having Gaussian nonlinearities. When the onset of lower complexity activity is predicted in the in silico model, then our control scheme consists of applying a small perturbation to a system variable (i.e., the transmembrane voltage) when it is sufficiently close to the unstable higher complexity manifold. The system state can be restored back to its higher complexity mode utilizing the forces of the system's vector field.
A mathematical model is described which calculates the alveolar concentration of CO2(FACO2) in a patient breathing through a Mapleson D anaesthesia system. The model is derived using a series of mass balances for CO2 in the alveolar space, dead space, breathing system limb volume and reservoir. The variables included in the model are tidal volume (VT), respiratory rate, fresh gas flow rate (Vf), dead space volume, I:E ratio, and expiratory limb volume (Vl) time constant of lung expiration, and carbon dioxide production rate. The model predictions are compared with measurements made using a mechanical lung simulator in both spontaneous and controlled ventilation. Both the model and the experimental data predict that at high fresh gas flow rates and low respiratory rates, FACO2 is independent of Vf; at low fresh gas flow rates and high respiratory rates, FACO2 is independent of respiratory rate. The model and the data show that the VT influences FACO2, independent of minute ventilation alone, during both partial re-breathing and non-rebreathing operation. Therefore, describing the operation in terms of minute ventilation is ambiguous. It is also shown that Vl influences FACO2 such that, for any combination of patient and breathing-system variables, there is a Vl that minimizes the Vf required to maintain FACO2. In addition, expiratory resistance can increase the fresh gas flow rate required to maintain a given FACO2. The respiratory patterns observed with spontaneous and controlled ventilation are responsible for the difference in Vf required with each mode of ventilation.
Investigations of plant-herbivore interactions continue to be popular; however, a bias neglecting root feeders may limit our ability to understand how herbivores shape plant life histories. Root feeders can cause dramatic plant population declines, often associated with secondary stress factors such as drought or grazing. These severe impacts resulted in substantial interest in root feeders as agricultural pests and increasingly as biological weed control agents, particularly in North America. Despite logistical difficulties, establishment rates in biocontrol programs are equal or exceed those of aboveground herbivores (67.2% for aboveground herbivores, 77.5% for belowground herbivores) and root feeders are more likely to contribute to control (53.7% versus 33.6%). Models predicting root feeders would be negatively affected by competitively superior aboveground herbivores may be limited to early successional habitats or generalist root feeders attacking annual plants. In later successional habitats, root feeders become more abundant and appear to be the more potent force in driving plant performance and plant community composition. Aboveground herbivores, even at high population levels, were unable to prevent buildup of root herbivore populations and the resulting population collapse of their host plants. Significant information gaps exist about the impact of root feeders on plant physiology and secondary chemistry and their importance in natural areas, particularly in the tropics.
In epidemiological investigations of infant diseases, data are usually collected on a large set of variables. The associations between presumptive risk factors and the outcome is commonly evaluated through statistical modeling, but the model-building strategies are seldom described. In the project, data collected in a case-control study of risk factors for dehydrating diarrhea in infants have been used to present a hierarchized approach to the assessment of risk factors. The variables were grouped into a hierarchy of categories, ranging from distal determinants to proximate ones. These categories included, in this order, socioeconomic, environmental, reproductive maternal, nutritional and demographic sets. According to the univariate analyses all variables were associated with the outcome. As the purpose was to identify a parsimonious model to explain the data, in each set the confounders were selected through backward elimination, according to an alpha level of 0.10. The risk factors were evaluated through logistic regression after adjustment for confounders in the same set or in hierarchically superior sets. This approach allows researchers to quantify the contribution of each level of adjustment, to understand the model-building strategy as well as interpret the independent associations. The goodness-of-fit assessed at each set showed significant improvements in the model. The gamma coefficient of association was employed to quantify the proportion of cases and controls correctly identified by comparing the observed value with that predicted by the variables in the model. The final model resulted in a gamma of 0.74. The children's ages did not improve the prediction of cases and controls, but they have been kept in the model as they affect some exposures such as breastfeeding.
This study examined the fear control/danger control responses that are predicted by the Extended Parallel Process Model (EPPM). In a campaign designed to inform college students about the symptoms and dangers of meningitis, participants were given either a high-threat/no-efficacy or high-efficacy/no-threat health risk message, thus testing the extreme assumptions of the EPPM. Although the study supports the main predictions of the EPPM in the context of meningitis, the results provide new evidence that only a marginal amount of threat is necessary in a health risk message to move the target audience toward the desired protective measures. In addition, the results also suggest that the messages containing only threat may only scare the target audience further into fear control. Implications and future research are discussed.
Ecology and population dynamics of Aedes vexans (Meigen), were studied for 3 yr in southern Switzerland. Demographic data were compiled into single and multicohort stage-frequency lifetables that indicated variability in individual developmental times and losses caused by mortality. The structure of life table matrices suggested an analysis using a timevarying distributed delay model with attrition. Field data then were used to construct and validate a simulation model that input the number of 1st instars and output the number of emerging adults. The delay was the time required to complete development and attrition corresponded to mortality. Under optimal food supply, temperature was the most important driving variable. The model was parameterized with data obtained from laboratory experiments and evaluated with field data. Development and survival of preimaginal Ae. vexans were simulated reasonably well under 2 different pool habitats. Addition of a hydrology component to the model would enhance control operations by predicting hatch rates in the field.
Using a computer simulation study, we have investigated the risk and dynamics of onchocerciasis recrudescence after stopping vector control, in order to provide guidelines for operational decision-making in the Onchocerciasis Control Programme in West Africa (OCP). For this purpose, we used the microsimulation model ONCHOSIM to predict for periods of 9-15 years of vector control the ensuing risk and dynamics of recrudescence in an onchocerciasis focus. The model was quantified and validated using OCP evaluation and field research data. A range of plausible values was determined for important confounding parameters, i.e., vector biting rate, variation in exposure between individuals, parasite life span, and the relation between skin microfilarial load and vector infection. Different model quantifications were used in order to take account of the possible confounding effect of these parameters on the prediction of recrudescence. In the absence of immigration of infected humans or invasion by infected flies, the model predicts that 14 years of full-scale vector control are required to reduce the risk of recrudescence to less than 1%. The risk depends, in particular, on the vector biting rate, and this has implications for the planning of post-larviciding surveillance. Recrudescence will be a relatively slow process, and its rate will depend on the duration of vector control. Even if vector control were stopped too early, i.e., after 12-13 years in a highly endemic area, it would take more than 20 years before the intensity of infection in the community would reach levels of public health importance.
Why are sperm small and eggs large? The dominant explanation for the evolution of gamete size dimorphism envisages two opposing selection pressures acting on gamete size: small gametes are favoured because many can be produced, whereas large gametes contribute to a large zygote with consequently increased survival chances. This model predicts disruptive selection on gamete size (i.e. selection for anisogamy) if increases in zygote size confer disproportional increases in fitness (at least over part of its size range). It therefore predicts that increases in adult size should be accompanied by stronger selection for anisogamy. Using data from the green algal order Volvocales, we provide the first phylogenetically controlled test of the model's predictions using a published phylogeny and a new phylogeny derived by a different method. The predictions that larger organisms should (i) have a greater degree of gamete dimorphism and (ii) have larger eggs are broadly upheld. However, the results are highly sensitive to the phylogeny and the mode of analysis used.
This paper proposes using a new recurrent neural network model (RNNM) to predict and control fed batch fermentations of Bacillus thuringiensis. The control variables are the limiting substrate and the feeding conditions. The multi-input multi-output RNNM proposed has twelve inputs, seven outputs, nineteen neurons in the hidden layer, and global and local feedbacks. The weight update learning algorithm designed is a version of the well known backpropagation through time algorithm directed to the RNNM learning. The error approximation for the last epoch of learning is 2% and the total learning time is 51 epochs, where the size of an epoch is 162 iterations. The RNNM generalization was carried out reproducing a B. thuringiensis fermentation not included in the learning process. It attains an error approximation of 1.8%.
In the present study a mathematical model of the chemical control of respiration is described which attempts to simulate periodic breathing during sleep. The model is an extension of an earlier model which has been shown to successfully reproduce the transient effects of CO2 inhalation on breathing, controlled changes in ventilation on arterial gas tension, and Cheyne-Stokes breathing. Included in the extended model are the effects of chemical stimuli during sleep on both chest wall and upper airway muscle activity. Data is presented indicating that simulations from the model reproduce reasonably well the essential features of the results obtained in eight subjects with periodic respiration during sleep when breathing room air, O2, or low concentrations of CO2. Simulations from the model and the experimental data suggest that periodic breathing during sleep results from unstable operation in the respiratory control system analogous to that seen during instabilities in physical control systems. The model indicates that obstructive as well as central apneas can be produced by control system instability. Furthermore, central apneas increase the likelihood of obstructive apneas while obstructive apneas tend to aggravate the control instability. The model results predict that the characteristics of the periodic breathing seen during sleep, such as apnea length, will depend on circulation time and the sensitivity of both upper airway and chest wall muscles to hypercapnia and hypoxia.