Fatigue and weight loss predict survival on circadian chemotherapy for metastatic colorectal cancer.

BACKGROUND: Chemotherapy-induced neutropenia has been associated with prolonged survival selectively in patients on a conventional schedule (combined 5-fluorouracil, leucovorin, and oxaliplatin [FOLFOX2]) but not on a chronomodulated schedule of the same drugs administered at specific circadian times (chronoFLO4). The authors hypothesized that the early occurrence of chemotherapy-induced symptoms correlated with circadian disruption would selectively hinder the efficacy of chronotherapy. METHODS: Fatigue and weight loss (FWL) were considered to be associated with circadian disruption based on previous data. Patients with metastatic colorectal cancer (nâeuro0/00=âeuro0/00543) from an international phase 3 trial comparing FOLFOX2 with chronoFLO4 were categorized into 4 subgroups according to the occurrence of FWL or other clinically relevant toxicities during the initial 2 courses of chemotherapy. Multivariate Cox models were used to assess the role of toxicity on the time to progression (TTP) and overall survival (OS). RESULTS: The proportions of patients in the 4 subgroups were comparable in both treatment arms (Pâeuro0/00=âeuro0/00.77). No toxicity was associated with TTP or OS on FOLFOX2. The median OS on FOLFOX2 ranged from 16.4 (95% confidence limits [CL], 7.2-25.6 months) to 19.8 months (95% CL, 17.7-22.0 months) according to toxicity subgroup (Pâeuro0/00=âeuro0/00.45). Conversely, FWL, but no other toxicity, independently predicted for significantly shorter TTP (Pâeuro0/00<âeuro0/00.0001) and OS (Pâeuro0/00=âeuro0/00.001) on chronoFLO4. The median OS on chronoFLO4 was 13.8 months (95% CL, 10.4-17.2 months) or 21.1 months (95% CL, 19.0-23.1 months) according to presence or absence of chemotherapy-induced FWL, respectively. CONCLUSIONS: Early onset chemotherapy-induced FWL was an independent predictor of poor TTP and OS only on chronotherapy. Dynamic monitoring to detect early chemotherapy-induced circadian disruption could allow the optimization of rapid chronotherapy and concomitant improvements in safety and efficacy.

In vivo 13C NMR spectroscopy and metabolic modeling in the brain: a practical perspective.

In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.

Pulmonary hypertension complicating isolated atrial septal defect.

Atrial septal defect (ASD) typically is asymptomatic in infancy and early childhood and elective defect closure usually is performed at an age between 4 - 6 years. Severe pulmonary hypertension (PHT) complicating an ASD is seen in adulthood and has only occasionally been reported in small children. A retrospective study was undertaken to evaluate the incidence of severe PHT complicating an isolated ASD and requiring early surgical correction in the fi rst year of life. 355 pediatric patients underwent treatment for an isolated ASD either surgically or by catheter intervention during a 10 year period (1996 - 2006) at two tertiary referral centers. 297 patients had secundum ASD and 58 primum ASD with mild to moderate mitral regurgitation. 8 infants were found with isolated ASD (six with secundum and two with primum ASD) associated with signifi cant PHT, accounting for 2.2% of all ASD patients in our centers. These 8 infants had invasively measured pulmonary artery pressures between 50 and 100% of systemic pressure. Median size of the ASD at the time of surgery was 14mm (7 - 20). They were operated in the fi rst year of life and had complicated postoperative courses requiring specifi c treatment for PHT for up to 16 weeks (median 12) postoperatively. Compared to ASD patients without PHT these infants had prolonged postoperative ICU stay of 5 - 9 days (median 8) and prolonged perioperative overall hospital stay of 8 - 32 days (median 15). Ultimate outcome in all 8 infants was good with persistent normalization of pulmonary pressures during mid-term follow-up of between 8 to 60 months (median 28). All other ASD patients had normal pulmonary pressures and mean age at defect closure was higher being 6.2 years for secundum ASD and 3.2 years for primum ASD. In conclusion, ASD is rarely associated with signifi cant PHT in infancy but then requires early surgery to normalize the prognosis of the patients.

Frequency of severe pulmonary hypertension complicating "isolated" atrial septal defect in infancy.

Atrial septal defects (ASDs) are typically asymptomatic in infancy and early childhood, and elective defect closure is usually performed at ages of 4 to 6 years. Severe pulmonary hypertension (PH) complicating an ASD is seen in adulthood and has only occasionally been reported in small children. A retrospective study was undertaken to evaluate the incidence of severe PH complicating an isolated ASD and requiring early surgical correction. During a 10-year period (1996 to 2006), 355 pediatric patients underwent treatment for isolated ASDs either surgically or by catheter intervention at 2 tertiary referral centers. Two hundred ninety-seven patients had secundum ASDs, and 58 had primum ASDs with mild to moderate mitral regurgitation. Eight infants were found with isolated ASDs (6 with secundum ASDs and 2 with primum ASDs) associated with significant PH, accounting for 2.2% of all patients with ASDs at the centers. These 8 infants had invasively measured pulmonary artery pressures of 50% to 100% of systemic pressure. They were operated in the first year of life and had complicated postoperative courses requiring specific treatment for PH for up to 16 weeks postoperatively. The ultimate outcomes in all 8 infants were good, with persistent normalization of pulmonary pressures during midterm follow-up of up to 60 months (median 28). All other patients with ASDs had normal pulmonary pressures, and the mean age at defect closure was significantly older, at 6.2 years for secundum ASDs and 3.2 years for primum ASDs. In conclusion, ASDs were rarely associated with significant PH in infancy but then required early surgery and were associated with excellent midterm outcomes in these patients.

Comparing ICA-based and single-trial topographic ERP analyses.

Single-trial analysis of human electroencephalography (EEG) has been recently proposed for better understanding the contribution of individual subjects to a group-analysis effect as well as for investigating single-subject mechanisms. Independent Component Analysis (ICA) has been repeatedly applied to concatenated single-trial responses and at a single-subject level in order to extract those components that resemble activities of interest. More recently we have proposed a single-trial method based on topographic maps that determines which voltage configurations are reliably observed at the event-related potential (ERP) level taking advantage of repetitions across trials. Here, we investigated the correspondence between the maps obtained by ICA versus the topographies that we obtained by the single-trial clustering algorithm that best explained the variance of the ERP. To do this, we used exemplar data provided from the EEGLAB website that are based on a dataset from a visual target detection task. We show there to be robust correspondence both at the level of the activation time courses and at the level of voltage configurations of a subset of relevant maps. We additionally show the estimated inverse solution (based on low-resolution electromagnetic tomography) of two corresponding maps occurring at approximately 300 ms post-stimulus onset, as estimated by the two aforementioned approaches. The spatial distribution of the estimated sources significantly correlated and had in common a right parietal activation within Brodmann's Area (BA) 40. Despite their differences in terms of theoretical bases, the consistency between the results of these two approaches shows that their underlying assumptions are indeed compatible.

The EuroSIDA study: Regional differences in the HIV-1 epidemic and treatment response to antiretroviral therapy among HIV-infected patients across Europe--a review of published results.

EuroSIDA is a pan-European observational study that follows 14,265 HIV-infected patients from 31 European countries, Israel and Argentina, of which 2,560 are patients from eastern Europe (EE). The study group has performed several analyses addressing regional differences in the HIV-epidemic across Europe, where all countries were divided into five regions: south, west central, north, east central Europe and EE. Significant regional differences in patients' characteristics and pattern of AIDS diagnoses were documented. More patients from EE were diagnosed with tuberculosis compared to other regions. Significantly fewer HIV-infected patients in EE, who fulfilled the criteria for starting combination antiretroviral therapy (cART), actually received cART as compared with other regions of Europe. Those, receiving cART in EE had a lower initial virologic response rate irrespectively of the regimen used, although it has improved within years. Besides, treatment failure was more common in this region. Thus, improvements in the clinical management of HIV patients in EE are urgently needed. Strategies include creating scientific collaborations for HIV clinicians as well as teaching clinicians about the most advanced HIV management at clinically oriented courses held in eastern Europe.

Pathogenesis of adult-onset Still's disease: new insights from the juvenile counterpart.

Adult-onset Still's disease (AOSD) is a rare inflammatory disease characterized by the classical triad of daily fever, arthritis, and typical salmon-colored rash. Recent accumulation of knowledge, mostly arising from hereditary autoinflammatory diseases and from the systemic-onset juvenile idiopathic arthritis (sJIA), has given raise to new hypotheses on the pathophysiology of AOSD. In this review, we first discuss on the continuum between AOSD and sJIA. Then, we summarize current hypotheses on the underlying pathogenesis: (1) an infectious hypothesis; (2) an autoinflammatory hypothesis; (3) a lymphohistiocytic hypothesis; and (4) a hyperferritinemic hypothesis. Finally, we present the recent data suggesting that patients with AOSD fall into two distinct subgroups with different courses, one with prominent systemic features and one with chronic arthritis.

Mastectomy, Body De-Construction and Impact on Identity: A qualitative study

Objectives: This qualitative study aims at understanding the consequences of body deconstruction through mastectomy on corporality and identity in women with breast cancer. Design: Nineteen women were contacted through the hospital. All had to undergo mastectomy. Some were offered immediate breast reconstruction, others, because of cancer treatments, had no planned reconstruction. A qualitative reflexive methodological background was chosen. Method: Women were invited to participate in three semi-structured interviews, one shortly before or after mastectomy, and the other interviews later in their illness courses, after surgery. All interviews were transcribed verbatim. Thematic analysis was performed. The analysis of the first interview of each woman is presented in this article. Results: Mastectomy provokes a painful experience of body deconstruction. Even when immediate reconstruction is proposed, contrasted feelings and dissonance are expressed when comparing the former healthy body to the present challenged body entity. Body transformations are accompanied with experiences of mutilation, strangeness, and modify the physical, emotional social, symbolic and relational dimensions of the woman's gendered identity. Although the opportunity of breast reconstruction is seen as a possible recovery of a lost physical symmetry and body integrity, grieving the past body and integrating a new corporality leads to a painful identity crisis. Conclusion: With mastectomy, the roots of the woman's identity are challenged, leading to a re-evaluation of her existential values. The consequences of mastectomy transform the woman's corporality and embodiment, and question her identity. Psychological support is discussed in the perspective of our results.

Diabetic macular edema : cases and diagnostics

In the new book series 'ESASO Course Series', the essentials of the courses of the European School for Advanced Studies in Ophthalmology (ESASO) are made available to interested ophthalmologists, optometrists, technicians and residents all over the world. In this volume, the seminars on surgical retina presented by renowned experts during ESASO's activities are collected. Many specialists have contributed their knowledge to make this volume a device to give practical support. The topics range from prevention to state-of-the-art diagnostic techniques and the latest surgical treatment options for many eye conditions such as diabetic retinopathy and rhegmatogenous retinal detachment. This publication provides the ophthalmologist with the main aspects of surgical retina in a simple and practical update.

Cation Transport Coupled to ATP Hydrolysis By the (Na, K)-ATPase : an integrated, animated model

An Adobe (R) animation is presented for use in undergraduate Biochemistry courses, illustrating the mechanism of Na+ and K+ translocation coupled to ATP hydrolysis by the (Na, K)-ATPase, a P-2c-type ATPase, or ATP-powered ion pump that actively translocates cations across plasma membranes. The enzyme is also known as an E-1/E-2-ATPase as it undergoes conformational changes between the E-1 and E-2 forms during the pumping cycle, altering the affinity and accessibility of the transmembrane ion-binding sites. The animation is based on Horisberger's scheme that incorporates the most recent significant findings to have improved our understanding of the (Na, K)-ATPase structure function relationship. The movements of the various domains within the (Na, K)-ATPase alpha-subunit illustrate the conformational changes that occur during Na+ and K+ translocation across the membrane and emphasize involvement of the actuator, nucleotide, and phosphorylation domains, that is, the "core engine" of the pump, with respect to ATP binding, cation transport, and ADP and P-i release.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

An international university network for online teaching of pathology in Frenchspeaking countries

Introduction: Building online courses is a highly time consuming task for teachers of a single university. Universities working alone create high-quality courses but often cannot cover all pathological fields. Moreover this often leads to duplication of contents among universities, representing a big waste of teacher time and energy. We initiated in 2011 a French university network for building mutualized online teaching pathology cases, and this network has been extended in 2012 to Quebec and Switzerland. Method: Twenty French universities (see & for details), University Laval in Quebec and University of Lausanne in Switzerland are associated to this project. One e-learning Moodle platform (http://moodle.sorbonne-paris-cite.fr/) contains texts with URL pointing toward virtual slides that are decentralized in several universities. Each university has the responsibility of its own slide scanning, slide storage and online display with virtual slide viewers. The Moodle website is hosted by PRES Sorbonne Paris Cité, and financial supports for hardware have been obtained from UNF3S (http://www.unf3s.org/) and from PRES Sorbonne Paris Cité. Financial support for international fellowships has been obtained from CFQCU (http://www.cfqcu.org/). Results: The Moodle interface has been explained to pathology teachers using web-based conferences with screen sharing. The teachers added then contents such as clinical cases, selfevaluations and other media organized in several sections by student levels and pathological fields. Contents can be used as online learning or online preparation of subsequent courses in classrooms. In autumn 2013, one resident from Quebec spent 6 weeks in France and Switzerland and created original contents in inflammatory skin pathology. These contents are currently being validated by senior teachers and will be opened to pathology residents in spring 2014. All contents of the website can be accessed for free. Most contents just require anonymous connection but some specific fields, especially those containing pictures obtained from patients who agreed for a teaching use only, require personal identification of the students. Also, students have to register to access Moodle tests. All contents are written in French but one case has been translated into English to illustrate this communication (http://moodle.sorbonne-pariscite.fr/mod/page/view.php?id=261) (use "login as a guest"). The Moodle test module allows many types of shared questions, making it easy to create personalized tests. Contents that are opened to students have been validated by an editorial committee composed of colleagues from the participating institutions. Conclusions: Future developments include other international fellowships, the next one being scheduled for one French resident from May to October 2014 in Quebec, with a study program centered on lung and breast pathology. It must be kept in mind that these e-learning programs highly depend on teachers' time, not only at these early steps but also later to update the contents. We believe that funding resident fellowships for developing online pathological teaching contents is a win-win situation, highly beneficial for the resident who will improve his knowledge and way of thinking, highly beneficial for the teachers who will less worry about access rights or image formats, and finally highly beneficial for the students who will get courses fully adapted to their practice.

T cell receptor-ligand interactions: a conformational preequilibrium or an induced fit.

Kinetic parameters of T cell receptor (TCR) interactions with its ligand have been proposed to control T cell activation. Analysis of kinetic data obtained has so far produced conflicting insights; here, we offer a consideration of this problem. As a model system, association and dissociation of a soluble TCR (sT1) and its specific ligand, an azidobenzoic acid derivative of the peptide SYIPSAEK-(ABA)I (residues 252-260 from Plasmodium berghei circumsporozoite protein), bound to class I MHC H-2K(d)-encoded molecule (MHCp) were studied by surface plasmon resonance. The association time courses exhibited biphasic patterns. The fast and dominant phase was assigned to ligand association with the major fraction of TCR molecules, whereas the slow component was attributed to the presence of traces of TCR dimers. The association rate constant derived for the fast phase, assuming a reversible, single-step reaction mechanism, was relatively slow and markedly temperature-dependent, decreasing from 7.0 x 10(3) at 25 degrees C to 1.8 x 10(2) M(-1).s(-1) at 4 degrees C. Hence, it is suggested that these observed slow rate constants are the result of unresolved elementary steps of the process. Indeed, our analysis of the kinetic data shows that the time courses of TCR-MHCp interaction fit well to two different, yet closely related mechanisms, where an induced fit or a preequilibrium of two unbound TCR conformers are operational. These mechanisms may provide a rationale for the reported conformational flexibility of the TCR and its unusual ligand recognition properties, which combine high specificity with considerable crossreactivity.

Toxicokinetic modeling of folpet fungicide and its ring-biomarkers of exposure in humans.

A human in vivo toxicokinetic model was built to allow a better understanding of the toxicokinetics of folpet fungicide and its key ring biomarkers of exposure: phthalimide (PI), phthalamic acid (PAA) and phthalic acid (PA). Both PI and the sum of ring metabolites, expressed as PA equivalents (PAeq), may be used as biomarkers of exposure. The conceptual representation of the model was based on the analysis of the time course of these biomarkers in volunteers orally and dermally exposed to folpet. In the model, compartments were also used to represent the body burden of folpet and experimentally relevant PI, PAA and PA ring metabolites in blood and in key tissues as well as in excreta, hence urinary and feces. The time evolution of these biomarkers in each compartment of the model was then mathematically described by a system of coupled differential equations. The mathematical parameters of the model were then determined from best fits to the time courses of PI and PAeq in blood and urine of five volunteers administered orally 1 mg kg(-1) and dermally 10 mg kg(-1) of folpet. In the case of oral administration, the mean elimination half-life of PI from blood (through feces, urine or metabolism) was found to be 39.9 h as compared with 28.0 h for PAeq. In the case of a dermal application, mean elimination half-life of PI and PAeq was estimated to be 34.3 and 29.3 h, respectively. The average final fractions of administered dose recovered in urine as PI over the 0-96 h period were 0.030 and 0.002%, for oral and dermal exposure, respectively. Corresponding values for PAeq were 24.5 and 1.83%, respectively. Finally, the average clearance rate of PI from blood calculated from the oral and dermal data was 0.09 ± 0.03 and 0.13 ± 0.05 ml h(-1) while the volume of distribution was 4.30 ± 1.12 and 6.05 ± 2.22 l, respectively. It was not possible to obtain the corresponding values from PAeq data owing to the lack of blood time course data.