A realistic validation study of a new nitrogen multiple-breath washout system

Background For reliable assessment of ventilation inhomogeneity, multiple-breath washout (MBW) systems should be realistically validated. We describe a new lung model for in vitro validation under physiological conditions and the assessment of a new nitrogen (N2)MBW system. Methods The N2MBW setup indirectly measures the N2 fraction (FN2) from main-stream carbon dioxide (CO2) and side-stream oxygen (O2) signals: FN2 = 1−FO2−FCO2−FArgon. For in vitro N2MBW, a double chamber plastic lung model was filled with water, heated to 37°C, and ventilated at various lung volumes, respiratory rates, and FCO2. In vivo N2MBW was undertaken in triplets on two occasions in 30 healthy adults. Primary N2MBW outcome was functional residual capacity (FRC). We assessed in vitro error (√[difference]2) between measured and model FRC (100–4174 mL), and error between tests of in vivo FRC, lung clearance index (LCI), and normalized phase III slope indices (Sacin and Scond). Results The model generated 145 FRCs under BTPS conditions and various breathing patterns. Mean (SD) error was 2.3 (1.7)%. In 500 to 4174 mL FRCs, 121 (98%) of FRCs were within 5%. In 100 to 400 mL FRCs, the error was better than 7%. In vivo FRC error between tests was 10.1 (8.2)%. LCI was the most reproducible ventilation inhomogeneity index. Conclusion The lung model generates lung volumes under the conditions encountered during clinical MBW testing and enables realistic validation of MBW systems. The new N2MBW system reliably measures lung volumes and delivers reproducible LCI values.

The LPS receptor, CD14, in experimental autoimmune encephalomyelitis and multiple sclerosis

Innate immune receptors are crucial for defense against microorganisms. Recently, a cross-talk between innate and adaptive immunity has been considered. Here, we provide first evidence for a role of the key innate immune receptor, LPS receptor (CD14) in pathophysiology of experimental autoimmune encephalomyelitis, the animal model of multiple sclerosis. Indicating a functional importance in vivo, we show that CD14 deficiency increased clinical symptoms in active experimental autoimmune encephalomyelitis. Consistent with these observations, CD14 deficient mice exhibited a markedly enhanced infiltration of monocytes and neutrophils in brain and spinal cord. Moreover, we observed an increased immunoreactivity of CD14 in biopsy and post mortem brain tissues of multiple sclerosis patients compared to age-matched controls. Thus, the key innate immune receptor, CD14, may be of pathophysiological relevance in experimental autoimmune encephalomyelitis and multiple sclerosis.

Clinical and biochemical description of a novel CYP21A2 gene mutation 962_963insA using a new 3D model for the P450c21 protein

OBJECTIVE: A severely virilized 46, XX newborn girl was referred to our center for evaluation and treatment of congenital adrenal hyperplasia (CAH) because of highly elevated 17alpha-hydroxyprogesterone levels at newborn screening; biochemical tests confirmed the diagnosis of salt-wasting CAH. Genetic analysis revealed that the girl was compound heterozygote for a previously reported Q318X mutation in exon 8 and a novel insertion of an adenine between nucleotides 962 and 963 in exon 4 of the CYP21A2 gene. This 962_963insA mutation created a frameshift leading to a stop codon at amino acid 161 of the P450c21 protein. AIM AND METHODS: To better understand structure-function relationships of mutant P450c21 proteins, we performed multiple sequence alignments of P450c21 with three mammalian P450s (P450 2C8, 2C9 and 2B4) with known structures as well as with human P450c17. Comparative molecular modeling of human P450c21 was then performed by MODELLER using the X-ray crystal structure of rabbit P450 2B4 as a template. RESULTS: The new three dimensional model of human P450c21 and the sequence alignment were found to be helpful in predicting the role of various amino acids in P450c21, especially those involved in heme binding and interaction with P450 oxidoreductase, the obligate electron donor. CONCLUSION: Our model will help in analyzing the genotype-phenotype relationship of P450c21 mutations which have not been tested for their functional activity in an in vitro assay.

Closed-loop control of mean arterial blood pressure during surgery with alfentanil: clinical evaluation of a novel model-based predictive controller

BACKGROUND: In contrast to hypnosis, there is no surrogate parameter for analgesia in anesthetized patients. Opioids are titrated to suppress blood pressure response to noxious stimulation. The authors evaluated a novel model predictive controller for closed-loop administration of alfentanil using mean arterial blood pressure and predicted plasma alfentanil concentration (Cp Alf) as input parameters. METHODS: The authors studied 13 healthy patients scheduled to undergo minor lumbar and cervical spine surgery. After induction with propofol, alfentanil, and mivacurium and tracheal intubation, isoflurane was titrated to maintain the Bispectral Index at 55 (+/- 5), and the alfentanil administration was switched from manual to closed-loop control. The controller adjusted the alfentanil infusion rate to maintain the mean arterial blood pressure near the set-point (70 mmHg) while minimizing the Cp Alf toward the set-point plasma alfentanil concentration (Cp Alfref) (100 ng/ml). RESULTS: Two patients were excluded because of loss of arterial pressure signal and protocol violation. The alfentanil infusion was closed-loop controlled for a mean (SD) of 98.9 (1.5)% of presurgery time and 95.5 (4.3)% of surgery time. The mean (SD) end-tidal isoflurane concentrations were 0.78 (0.1) and 0.86 (0.1) vol%, the Cp Alf values were 122 (35) and 181 (58) ng/ml, and the Bispectral Index values were 51 (9) and 52 (4) before surgery and during surgery, respectively. The mean (SD) absolute deviations of mean arterial blood pressure were 7.6 (2.6) and 10.0 (4.2) mmHg (P = 0.262), and the median performance error, median absolute performance error, and wobble were 4.2 (6.2) and 8.8 (9.4)% (P = 0.002), 7.9 (3.8) and 11.8 (6.3)% (P = 0.129), and 14.5 (8.4) and 5.7 (1.2)% (P = 0.002) before surgery and during surgery, respectively. A post hoc simulation showed that the Cp Alfref decreased the predicted Cp Alf compared with mean arterial blood pressure alone. CONCLUSION: The authors' controller has a similar set-point precision as previous hypnotic controllers and provides adequate alfentanil dosing during surgery. It may help to standardize opioid dosing in research and may be a further step toward a multiple input-multiple output controller.

The well-being model: a new drug interaction model for positive and negative effects

BACKGROUND: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. METHODS: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs. RESULTS: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. CONCLUSIONS: The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

Optimized temperature and deadspace correction improve analysis of multiple breath washout measurements by ultrasonic flowmeter in infants

BACKGROUND: Assessment of lung volume (FRC) and ventilation inhomogeneities with ultrasonic flowmeter and multiple breath washout (MBW) has been used to provide important information about lung disease in infants. Sub-optimal adjustment of the mainstream molar mass (MM) signal for temperature and external deadspace may lead to analysis errors in infants with critically small tidal volume changes during breathing. METHODS: We measured expiratory temperature in human infants at 5 weeks of age and examined the influence of temperature and deadspace changes on FRC results with computer simulation modeling. A new analysis method with optimized temperature and deadspace settings was then derived, tested for robustness to analysis errors and compared with the previously used analysis methods. RESULTS: Temperature in the facemask was higher and variations of deadspace volumes larger than previously assumed. Both showed considerable impact upon FRC and LCI results with high variability when obtained with the previously used analysis model. Using the measured temperature we optimized model parameters and tested a newly derived analysis method, which was found to be more robust to variations in deadspace. Comparison between both analysis methods showed systematic differences and a wide scatter. CONCLUSION: Corrected deadspace and more realistic temperature assumptions improved the stability of the analysis of MM measurements obtained by ultrasonic flowmeter in infants. This new analysis method using the only currently available commercial ultrasonic flowmeter in infants may help to improve stability of the analysis and further facilitate assessment of lung volume and ventilation inhomogeneities in infants.

Predicting asthma control and exacerbations: chronic asthma as a complex dynamic model

PURPOSE OF REVIEW: Predicting asthma episodes is notoriously difficult but has potentially significant consequences for the individual, as well as for healthcare services. The purpose of this review is to describe recent insights into the prediction of acute asthma episodes in relation to classical clinical, functional or inflammatory variables, as well as present a new concept for evaluating asthma as a dynamically regulated homeokinetic system. RECENT FINDINGS: Risk prediction for asthma episodes or relapse has been attempted using clinical scoring systems, considerations of environmental factors and lung function, as well as inflammatory and immunological markers in induced sputum or exhaled air, and these are summarized here. We have recently proposed that newer mathematical methods derived from statistical physics may be used to understand the complexity of asthma as a homeokinetic, dynamic system consisting of a network comprising multiple components, and also to assess the risk for future asthma episodes based on fluctuation analysis of long time series of lung function. SUMMARY: Apart from the classical analysis of risk factor and functional parameters, this new approach may be used to assess asthma control and treatment effects in the individual as well as in future research trials.

Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines

Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

Drug-induced respiratory depression: an integrated model of drug effects on the hypercapnic and hypoxic drive

Drug-induced respiratory depression is a common side effect of the agents used in anesthesia practice to provide analgesia and sedation. Depression of the ventilatory drive in the spontaneously breathing patient can lead to severe cardiorespiratory events and it is considered a primary cause of morbidity. Reliable predictions of respiratory inhibition in the clinical setting would therefore provide a valuable means to improve the safety of drug delivery. Although multiple studies investigated the regulation of breathing in man both in the presence and absence of ventilatory depressant drugs, a unified description of respiratory pharmacodynamics is not available. This study proposes a mathematical model of human metabolism and cardiorespiratory regulation integrating several isolated physiological and pharmacological aspects of acute drug-induced ventilatory depression into a single theoretical framework. The description of respiratory regulation has a parsimonious yet comprehensive structure with substantial predictive capability. Simulations relative to the synergistic interaction of the hypercarbic and hypoxic respiratory drive and the global effect of drugs on the control of breathing are in good agreement with published experimental data. Besides providing clinically relevant predictions of respiratory depression, the model can also serve as a test bed to investigate issues of drug tolerability and dose finding/control under non-steady-state conditions.

Natalizumab: targeting alpha4-integrins in multiple sclerosis

In 1992, it was shown that monoclonal antibodies blocking alpha(4)-integrins prevent the development of experimental autoimmune encephalomyelitis, an animal model for multiple sclerosis (MS). As alpha(4)beta(1)-integrin was demonstrated to mediate the attachment of immune-competent cells to inflamed brain endothelium in experimental autoimmune encephalomyelitis, the therapeutic effect was attributed to the inhibition of immune cell extravasation and inflammation in the central nervous system. This novel therapeutic approach was rapidly and successfully translated into the clinic. The humanized anti-alpha(4)-integrin antibody natalizumab demonstrated an unequivocal therapeutic effect in preventing relapses and slowing down the pace of neurological deterioration in patients with relapsing-remitting MS in phase II and phase III clinical trials. The occurrence of 3 cases of progressive multifocal leukoencephalopathy in patients treated with natalizumab led to the voluntary withdrawal of the drug from the market. After a thorough safety evaluation of all patients receiving this drug in past and ongoing studies for MS and Crohn's disease, natalizumab again obtained approval in the US and the European Community. A treatment targeting leukocyte trafficking in MS has now re-entered the clinic. Further thorough evaluation is necessary for a better understanding of the risk-benefit balance of this new treatment option for relapsing MS. In this review, we discuss the basic mechanism of action, key clinical results of clinical trials and the emerging indication of natalizumab in MS.

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.

A prediction model for personal radio frequency electromagnetic field exposure

Radio frequency electromagnetic fields (RF-EMF) in our daily life are caused by numerous sources such as fixed site transmitters (e.g. mobile phone base stations) or indoor devices (e.g. cordless phones). The objective of this study was to develop a prediction model which can be used to predict mean RF-EMF exposure from different sources for a large study population in epidemiological research. We collected personal RF-EMF exposure measurements of 166 volunteers from Basel, Switzerland, by means of portable exposure meters, which were carried during one week. For a validation study we repeated exposure measurements of 31 study participants 21 weeks after the measurements of the first week on average. These second measurements were not used for the model development. We used two data sources as exposure predictors: 1) a questionnaire on potentially exposure relevant characteristics and behaviors and 2) modeled RF-EMF from fixed site transmitters (mobile phone base stations, broadcast transmitters) at the participants' place of residence using a geospatial propagation model. Relevant exposure predictors, which were identified by means of multiple regression analysis, were the modeled RF-EMF at the participants' home from the propagation model, housing characteristics, ownership of communication devices (wireless LAN, mobile and cordless phones) and behavioral aspects such as amount of time spent in public transports. The proportion of variance explained (R2) by the final model was 0.52. The analysis of the agreement between calculated and measured RF-EMF showed a sensitivity of 0.56 and a specificity of 0.95 (cut-off: 90th percentile). In the validation study, the sensitivity and specificity of the model were 0.67 and 0.96, respectively. We could demonstrate that it is feasible to model personal RF-EMF exposure. Most importantly, our validation study suggests that the model can be used to assess average exposure over several months.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Asymmetric Effects of Loss and Gain of a Floral Trait on Pollinator Preference

Shifts in pollination syndromes involve coordinated changes in multiple floral traits. This raises the question of how plants can cope with rapid changes in pollinator availability by the slow process of accumulation of mutations in multiple genes. Here we study the transition from bee to hawkmoth pollination in the genus Petunia. Interspecific crosses followed by single locus introgressions were used to recreate putative intermediate evolutionary stages in the evolution of moth pollination. The effect of the loss/gain of petal color was asymmetric: it had no influence on the established pollinator but enhanced visitation by the new pollinator. Therefore, shifts in pollination syndromes may proceed through intermediate stages of reduced specialization and consequently enhanced reproductive assurance. The loss of petal color in moth-pollinated Petunia involves null mutations in a single regulatory gene, An2. Such simple genetic changes may be sufficiently rapid and frequent to ensure survival during pollinator failure.

Immunogenomic analysis of insect bite hypersensitivity in a model horse population.

Equine insect bite hypersensitivity (IBH) is a seasonal IgE-mediated dermatosis caused by bites of insects of the genus Culicoides. A familial predisposition for the disease has been shown but, except for the MHC, the genes involved have not been identified so far. An immunogenomic analysis of IBH was performed in a model population of Old Kladruby horses, all living in the same environment. Clinical signs of IBH were used as phenotypic manifestation of IBH. Furthermore, total serum IgE levels were determined in the sera of these horses and used as an independent phenotypic marker for the immunogenetic analysis. Single nucleotide polymorphisms (SNPs) in candidate immunity-related genes were used for association analyses. Genotypes composed of two to five genes encoding interferon gamma -IFNG, transforming growth factor beta 1 -TGFB1, Janus kinase 2 -JAK2, thymic stromal lymphopoietin -TSLP, and involucrin -IVL were associated with IBH, indicating a role of the genes in the pathogenesis of IBH. These findings were supported by analysis of gene expression in skin biopsies of 15 affected and 15 unaffected horses. Two markers associated with IBH, IFNG and TGFB1, showed differences in mRNA expression in skin biopsies from IBH-affected and non-affected horses (p<0.05). Expression of the gene coding for the CD14 receptor molecule -CD14 was different in skin biopsies at p<0.06. When total IgE levels were treated as binary traits, genotypes of IGHE, ELA-DRA, and IL10/b were associated with this trait. When treated as a continuous trait, total IgE levels were associated with genes IGHE, FCER1A, IL4, IL4R, IL10, IL1RA, and JAK2. This first report on non-MHC genes associated with IBH in horses is thus supported by differences in expression of genes known to play a role in allergy and immunity.