Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

Oxygen uptake kinetics and middle distance swimming performance.

OBJECTIVE: The aim of this study was to determine whether V˙O(2) kinetics and specifically, the time constant of transitions from rest to heavy (τ(p)H) and severe (τ(p)S) exercise intensities, are related to middle distance swimming performance. DESIGN: Fourteen highly trained male swimmers (mean ± SD: 20.5 ± 3.0 yr; 75.4 ± 12.4 kg; 1.80 ± 0.07 m) performed an discontinuous incremental test, as well as square wave transitions for heavy and severe swimming intensities, to determine V˙O(2) kinetics parameters using two exponential functions. METHODS: All the tests involved front-crawl swimming with breath-by-breath analysis using the Aquatrainer swimming snorkel. Endurance performance was recorded as the time taken to complete a 400 m freestyle swim within an official competition (T400), one month from the date of the other tests. RESULTS: T400 (Mean ± SD) (251.4 ± 12.4 s) was significantly correlated with τ(p)H (15.8 ± 4.8s; r=0.62; p=0.02) and τ(p)S (15.8 ± 4.7s; r=0.61; p=0.02). The best single predictor of 400 m freestyle time, out of the variables that were assessed, was the velocity at V˙O(2max)vV˙O(2max), which accounted for 80% of the variation in performance between swimmers. However, τ(p)H and V˙O(2max) were also found to influence the prediction of T400 when they were included in a regression model that involved respiratory parameters only. CONCLUSIONS: Faster kinetics during the primary phase of the V˙O(2) response is associated with better performance during middle-distance swimming. However, vV˙O(2max) appears to be a better predictor of T400.

Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

Biokinetics and dosimetry of 111 In-DOTA-NOC-ATE compared with 111In-DTPA-Octreotide

Aim: Biokinetics and dosimetry of 111In-DOTA-NOC-ATE (NOCATE) and 111In-DTPA-octreotide (Octreoscan?, OCTREO) were comparatively studied in the same patients. Patients and Methods: Seventeen patients (10 males, 7 females), mean age 60 years referred for an Octreoscan? because of carcinoid (N=9), unspecified neurodendocrine tumors (N=6), thymoma (N=1) or medullary thyroid carcinoma (N=1) accepted a second study with NOCATE. Four patients had no detectable tumor at the time of scanning. Whole-body (WB) anterior-posterior scans were recorded 0.5 (100% reference scan), 4, 24 and 48 hrs (N=17) and 120 hrs (N=6) after injection. OCTREO (178±15 MBq) preceded NOCATE (108±14 MBq) imaging with 16±5 days in 16 patients while 1 patient had first NOCATE followed 14 days later by OCTREO. Blood samples were taken 5, 15, 30, 60, 240 and 1440 min after injection. Background corrected geometric mean counts of WB, lung, kidney, liver, spleen and blood counts expressed in % of the initial composite WB and blood counts, respectively were fitted to bi- or single exponential curves and dosimetry was performed for male and female patients using MIRDOSE3.1 and OLINDA/EXM. Results: Initially, WB, lung and kidney activity was similar but retention was significantly higher for NOCATE compared with OCTREO. Liver and spleen uptake of NOCATE was higher from beginning (p<0.001) and remained so over time. Activity in rest of body showed similar α and β half-lives, but the β half-life fraction of NOCATE was much higher than OCTREO (49% vs. 19%, respectively). Blood T1/2β was longer for NOCATE compared with OCTREO (19 vs. 6h). Residence times were similar in male and female patients while they were in both genders higher for NOCATE than OCTREO. Consequently, effective dose (ED) for NOCATE (ED 114 and 134 μSv/MBq for man and women, respectively) exceeded that of OCTREO (ED = 61 and 71 μSv/MBq), the latter results being close to the ICRP-published radiation dose of OCTREO (ED = 54 and 71 µSv/MBq, respectively). Differential activity measurement in blood cells and plasma showed that only a minor fraction of NOCATE and OCTREO (<5 % in the mean) was bound to globular blood components. Conclusions: NOCATE showed higher retention in normal organs and delivered roughly twice the radiation dose of OCTREO. The ED of OCTREO in these patients was similar to ICRP80 report when adopting a bladder voiding interval of 2 hours.

RsmY, a small regulatory RNA, is required in concert with RsmZ for GacA-dependent expression of biocontrol traits in Pseudomonas fluorescens CHA0.

In the plant-beneficial soil bacterium and biocontrol model organism Pseudomonas fluorescens CHA0, the GacS/GacA two-component system upregulates the production of biocontrol factors, i.e. antifungal secondary metabolites and extracellular enzymes, under conditions of slow, non-exponential growth. When activated, the GacS/GacA system promotes the transcription of a small regulatory RNA (RsmZ), which sequesters the small RNA-binding protein RsmA, a translational regulator of genes involved in biocontrol. The gene for a second GacA-regulated small RNA (RsmY) was detected in silico in various pseudomonads, and was cloned from strain CHA0. RsmY, like RsmZ, contains several characteristic GGA motifs. The rsmY gene was expressed in strain CHA0 as a 118 nt transcript which was most abundant in stationary phase, as revealed by Northern blot and transcriptional fusion analysis. Transcription of rsmY was enhanced by the addition of the strain's own supernatant extract containing a quorum-sensing signal and was abolished in gacS or gacA mutants. An rsmA mutation led to reduced rsmY expression, via a gacA-independent mechanism. Overexpression of rsmY restored the expression of target genes (hcnA, aprA) to gacS or gacA mutants. Whereas mutants deleted for either the rsmY or the rsmZ structural gene were not significantly altered in the synthesis of extracellular products (hydrogen cyanide, 2,4-diacetylphloroglucinol, exoprotease), an rsmY rsmZ double mutant was strongly impaired in this production and in its biocontrol properties in a cucumber-Pythium ultimum microcosm. Mobility shift assays demonstrated that multiple molecules of RsmA bound specifically to RsmY and RsmZ RNAs. In conclusion, two small, untranslated RNAs, RsmY and RsmZ, are key factors that relieve RsmA-mediated regulation of secondary metabolism and biocontrol traits in the GacS/GacA cascade of strain CHA0.

Dispersal strategies, few dominating or many coexisting: the effect of environmental spatial structure and multiple sources of mortality.

Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.

Amoeba/amoebal symbiont genetic transfers: lessons from giant virus neighbours.

Free-living amoebae serve as hosts for a variety of amoebae-resisting microorganisms, including giant viruses and certain bacteria. The latter include symbiotic bacteria as well as bacteria exhibiting a pathogenic phenotype towards amoebae. Amoebae-resisting bacteria have been shown to be widespread in water and to use the amoebae as a reservoir, a replication niche, a protective armour as well as a training ground to select virulence traits allowing survival in the face of microbicidal effects of macrophages, the first line of defense against invading pathogens. More importantly, amoebae play a significant role as a melting pot for genetic exchanges. These ecological and evolutionary roles of amoebae might also be at play for giant viruses and knowledge derived from the study of amoebae-resisting bacteria is useful for the study and understanding of interactions between amoebae and giant viruses. This is especially important since some genes have spread in all domains of life and the exponential availability of eukaryotic genomes and metagenomic sequences will allow researchers to explore these genetic exchanges in a more comprehensive way, thus completely changing our perception of the evolutionary history of organisms. Thus, a large part of this review is dedicated to report current known gene exchanges between the different amoebae-resisting organisms and between amoebae and the internalized bacteria.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Viral superantigen drives extrafollicular and follicular B cell differentiation leading to virus-specific antibody production.

Mouse mammary tumor virus (MMTV[SW]) encodes a superantigen expressed by infected B cells. It evokes an antibody response specific for viral envelope protein, indicating selective activation of antigen-specific B cells. The response to MMTV(SW) in draining lymph nodes was compared with the response to haptenated chicken gamma globulin (NP-CGG) using flow cytometry and immunohistology. T cell priming occurs in both responses, with T cells proliferating in association with interdigitating dendritic cells in the T zone. T cell proliferation continues in the presence of B cells in the outer T zone, and B blasts then undergo exponential growth and differentiation into plasma cells in the medullary cords. Germinal centers develop in both responses, but those induced by MMTV(SW) appear later and are smaller. Most T cells activated in the T zone and germinal centers in the MMTV(SW) response are superantigen specific and these persist for weeks in lymph nodes draining the site MMTV(SW) injection: this contrasts with the selective loss of superantigen-specific T cells from other secondary lymphoid tissues. The results indicate that this viral superantigen, when expressed by professional antigen-presenting cells, drives extrafollicular and follicular B cell differentiation leading to virus-specific antibody production.

Bargaining, coalitions and competition

We study a decentralized matching model in a large exchange economy,in which trade takes place through non--cooperative bargaining in coalitionsof finite size. Under essentially the same conditions of core equivalence, we show that the strategic equilibrium outcomes of our model coincide with theWalrasian allocations of the economy. Our method of proof exploits equivalenceresults between the core and Walrasian equilibria. Our model relaxes differentiability and convexity of preferences thereby covering the caseof indivisible goods.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A tractable consideration set structure for network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing from an offerset, have recently become popular in assortment optimization and revenue management. The dynamicprogram for these models is intractable and approximated by a deterministic linear program called theCDLP which has an exponential number of columns. When there are products that are being consideredfor purchase by more than one customer segment, CDLP is difficult to solve since column generationis known to be NP-hard. However, recent research indicates that a formulation based on segments withcuts imposing consistency (SDCP+) is tractable and approximates the CDLP value very closely. In thispaper we investigate the structure of the consideration sets that make the two formulations exactly equal.We show that if the segment consideration sets follow a tree structure, CDLP = SDCP+. We give acounterexample to show that cycles can induce a gap between the CDLP and the SDCP+ relaxation.We derive two classes of valid inequalities called flow and synchronization inequalities to further improve(SDCP+), based on cycles in the consideration set structure. We give a numeric study showing theperformance of these cycle-based cuts.

Variable Kernel estimates: On the impossibility of tuning the parameters

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem for variable bandwidth kernel estimates where the bandwidths are allowed to depend upon the location. We show in particular that for positive kernels on the real line, for any data-based bandwidth, there exists a densityfor which the ratio of expected L1 error over optimal L1 error tends to infinity. Thus, the problem of tuning the variable bandwidth in an optimal manner is ``too hard''. Moreover, from the class of counterexamples exhibited in the paper, it appears thatplacing conditions on the densities (monotonicity, convexity, smoothness) does not help.

On payoff heterogeneity in games with strategic complementarities

Payoff heterogeneity weakens positive feedback in binary choice models intwo ways. First, heterogeneity drives individuals to corners where theyare unaffected by strategic complementarities. Second, aggregate behaviouris smoother than individual behaviour when individuals are heterogeneous.However, this smoothing does not necessarily eliminate positive feedbackor guarantee a unique equilibrium. In games with an unbounded, continuouschoice space, heterogeneity may either weaken or strengthen positive feedback,depending on a simple convexity/concavity condition. We conclude that positivefeedback phenomena derived in representative agent models will often be robustto heterogeneity.

Radioimmunotherapy of human colon carcinoma by 131I-labelled monoclonal anti-CEA antibodies in a nude mouse model.

A mixture of 3 MAbs directed against 3 different CEA epitopes was radiolabelled with 131I and used for the treatment of a human colon carcinoma transplanted s.c. into nude mice. Intact MAbs and F(ab')2 fragments were mixed because it had been shown by autoradiography that these 2 antibody forms can penetrate into different areas of the tumor nodule. Ten days after transplantation of colon tumor T380 a single dose of 600 microCi of 131I MAbs was injected i.v. The tumor grafts were well established (as evidenced by exponential growth in untreated mice) and their size continued to increase up to 6 days after radiolabelled antibody injection. Tumor shrinking was then observed lasting for 4-12 weeks. In a control group injected with 600 microCi of 131I coupled to irrelevant monoclonal IgG, tumor growth was delayed, but no regression was observed. Tumors of mice injected with the corresponding amount of unlabelled antibodies grew like those of untreated mice. Based on measurements of the effective whole-body half-life of injected 131I, the mean radiation dose received by the animals was calculated to be 382 rads for the antibody group and 478 rads for the normal IgG controls. The genetically immunodeficient animals exhibited no increase in mortality, and only limited bone-marrow toxicity was observed. Direct measurement of radioactivity in mice dissected 1, 3 and 7 days after 131I-MAb injection showed that 25, 7.2 and 2.2% of injected dose were recovered per gram of tumor, the mean radiation dose delivered to the tumor being thus more than 5,000 rads. These experiments show that therapeutic doses of radioactivity can be selectively directed to human colon carcinoma by i.v. injection of 131I-labelled anti-CEA MAbs.