Many group–living species display strong sex biases in dispersal tendencies. However, gene flow mediated by apparently philopatric sex may still occur and potentially alters population structure. In our closest living evolutionary relatives, dispersal of adult males seems to be precluded by high levels of territoriality between males of different groups in chimpanzees, and has only been observed once in bonobos. Still, male–mediated gene flow might occur through rare events such as extra–group matings leading to extra–group paternity (EGP) and female secondary dispersal with offspring, but the extent of this gene flow has not yet been assessed.Pan troglodytes verus) and bonobos (Pan paniscus), we found low genetic differentiation among groups for both males and females. Characterization of Y–chromosome microsatellites revealed levels of genetic differentiation between groups in bonobos almost as high as those reported previously in eastern chimpanzees, but lower levels of differentiation in western chimpanzees. By using simulations to evaluate the patterns of Y–chromosomal variation expected under realistic assumptions of group size, mutation rate and reproductive skew, we demonstrate that the observed presence of multiple and highly divergent Y–haplotypes within western chimpanzee and bonobo groups is best explained by successful male–mediated gene flow.Using autosomal microsatellite genotyping of samples from multiple groups of wild western chimpanzees (The similarity of inferred rates of male–mediated gene flow and published rates of EGP in western chimpanzees suggests this is the most likely mechanism of male–mediated gene flow in this subspecies. In bonobos more data are needed to refine the estimated rate of gene flow. Our findings suggest that dispersal patterns in these closely related species, and particularly for the chimpanzee subspecies, are more variable than previously appreciated. This is consistent with growing recognition of extensive behavioral variation in chimpanzees and bonobos. Dispersal, the shift in residence of an individual from one area or social group to another, is a fundamental process affecting population structure. It is typically considered an inbreeding avoidance mechanism Dispersal is an intrinsically infrequent event that is seldom observed, particularly for species with slow life histories such as primates, and may be difficult to distinguish from the disappearance or death of individuals. Advances in the use of non–invasive samples to genetically characterize individuals and in the analysis of genetic data offer an opportunity to investigate this important, often cryptic aspect of life history in wild animal populations There are many mechanisms by which the putatively nondispersing sex may contribute to gene flow between groups. In most taxa, the dispersal bias between the sexes is observed to be strong but not absolute, and some adult individuals of the typically philopatric sex may successfully join new groups  and paternally–transmitted Y–chromosome in eastern chimpanzees and bonobos suggested that male–mediated gene flow is absent in eastern chimpanzees and potentially rare in bonobos Pan troglodytes verus) and bonobos (Pan paniscus). We used autosomal, as well as Y–chromosomal microsatellite markers to characterize genetic variation in multiple social groups. For investigation of genetic differentiation, in both species we applied a small scale sampling regime, and for the western chimpanzees also examined groups over a slightly larger geographical range to assess whether, as might be expected, genetic differentiation increases as geographic distance increases. Our goal was then to assess the evidence for male–mediated gene flow in these two male–philopatric primates. Potential sharing of Y–chromosomal variants is not necessarily evidence for male gene flow, but could also represent the retention of ancestral haplotypes in different social groups. We therefore employed a simulation approach to examine, under realistic estimates of relevant demographic factors , expected levels of within–group Y–chromosomal genetic variation and to identify potentially immigrant types. By comparing our simulation results to our empirical data, we derived a potential range of levels of male–mediated gene flow in both study populations.In this study, we investigated potential differences in the amount of genetic differentiation and of male–mediated gene flow between wild western chimpanzees  with slight modifications Sex was determined or confirmed using polymerase chain reaction pIDsib, the probability that two identical multi–locus genotypes do not come from the same individual but rather from siblings. Estimated average pIDsib values were <0.01 for our five most informative autosomal loci (chimpanzees and bonobos), or for the six (bonobo) or seven (chimpanzee) least variable loci, indicating that even partially complete genotypes from close relatives would be distinguishable (data not shown). Genotypes from different samples that were found to come from the same individual (pIDsib <0.01) were combined into a consensus genotype. In total we genotyped 203 individual chimpanzees (genotypes 97.0 % complete) and 101 bonobos (genotypes 92.8% complete) at 19 autosomal loci  and 97.2%  complete.Each male was then genotyped at 13 (chimpanzee) or 10 (bonobo) Y–chromosomal loci developed in humans and previously assayed in eastern Previous research on habituated bonobos and chimpanzees has shown that it is difficult to obtain samples from young individuals, particularly dependent infants . Therefore, we assumed that our sample of unhabituated chimpanzees and bonobos would primarily consist of adult, adolescent and some juvenile individuals. To obtain comparable, approximately single–generation data sets from the habituated research groups, we used only genotypes from individuals present in 2001 and 2009 for the chimpanzees and bonobos, respectively, and the samples from unhabituated individuals were collected over a span of several months. We thereby excluded individuals that were known or estimated to be younger than 5 years.ST between pairs of social groups at the autosomes, for males and females separately, and at Y–chromosomal loci using ARLEQUIN 3.11 p–values of group pairwise FST were obtained from the permutation procedure implemented in ARLEQUIN. We also examined overall genetic differentiation in an AMOVA framework. Here, inspection of the overlap in the 95% confidence limits generated by bootstrapping genetic differentiation values obtained in a locus–by–locus AMOVA was used to evaluate whether (a) autosomal genetic differentiation between males and females was different within species and when comparing bonobos and chimpanzees and (b) genetic differentiation of Y–chromosomal loci differed between bonobo and chimpanzee males.We measured genetic differentiation FST–based genetic differentiation measures are not entirely independent of the amount of genetic variation present within groups, with high levels of genetic variation potentially leading to lower FST estimates than low levels of variation ST can therefore be biased and should be corrected. To allow for a meaningful comparison of genetic differentiation at the haploid Y–chromosome, where levels of variation are relatively low and slight differences between the species might be consequential for FST estimation, we also used a standardized measure of genetic differentiation for the Y–chromosomal data. Standardized FST expresses genetic differentiation as the maximum amount of genetic differentiation possible given the amount of within–group variation We examined genetic differentiation at two hierarchical levels in the more widespread chimpanzee sample to (a) obtain a data set readily comparable to the more local bonobo sampling and (b) examine whether the amount of genetic differentiation increased at the larger scale as might be predicted To minimize stochasticity, for all analyses of genetic differentiation between communities we excluded social groups with fewer than four sampled individuals. We chose four because in some of the completely sampled habituated groups only four individuals of the respective category  were present.within empirical bonobo and chimpanzee groups could be generated through mutation or must originate externally through male–mediated gene flow. Starting groups of a fixed number of males, with all males possessing identical Y–haplotypes, were simulated over discrete generations in which the individuals of one generation were used as the fathers for the next generation. Starting the simulations with groups that contained only dissimilar, highly divergent haplotypes produced identical results, as most haplotypes were lost rapidly and new, similar ones were subsequently generated by mutation. Therefore, we only report results for starting groups with one haplotype. The following factors were included in the simulations:There are two ways to investigate gene flow between social groups; one is to focus on variation shared between different groups, and the other is to look at the number and types of variants present within groups. We performed simulations  to examine whether the Y–chromosomal variation present i) Mutation generates new haplotypes in groups. Individual Y–haplotypes mutate with a probability derived as the product of mutation rate and the number of Y–chromosomal loci  typed in our empirical data, following a stepwise mutation model. We used the most recent published human mutation rate . Analyses using both mutation rates produced similar results, so we report here the results based on the better–substantiated human mutation rate estimate.ii) Skewed reproduction removes haplotypes from groups. Reproduction among Pan males is expected to be skewed over the short term with males of higher social dominance rank enjoying a reproductive advantage . However, over an entire generation skew should be lower, as individual opportunities to reproduce change iii) Male–mediated gene flow adds new divergent haplotypes to groups. In our model, male–mediated gene flow adds unique, infinitely distant (divergent) Y–haplotypes to the group at a specified constant rate. We chose to make the immigrant haplotypes highly divergent so that they can be distinguished from new haplotypes that arise via mutation and are highly similar to those already present. Since we thus consider any highly similar haplotypes as arising via mutation and highly divergent haplotypes as products of immigration, we may underestimate the rate of male migration that contributes haplotypes to the group similar to ones already there.The habituated Taï chimpanzee groups contain nine reproductively active males on average , as does the one bonobo research group investigated here. We therefore considered simulations of groups containing 5, 9, 10 and 15 males as realistic for the examined populations.All simulations reached stability after less then 100 generations and we simulated 1000 identical starting groups of the above sizes for 1000 generations. In order to see how much haplotypic variation could arise and be maintained in these closed groups with no gene flow, we averaged generations 100–1000 to examine the proportions of groups containing variation (more than one Y–haplotype) and the maximum number of mutations typically (more than 1% of the observations) found between any different Y–haplotypes present in the same group. From this simulation we thus inferred how many different haplotypes might be found in a group and how different they would be from one another. We then used our empirical data to examine how frequently groups contained multiple haplotypes that were more different from one another than we would expect given these simulation results, representing potentially immigrant haplotypes. In a second step we incorporated male–mediated gene flow by adding unique, infinitely distant Y–haplotypes to the simulated groups at pre–defined rates and then examined which rates of male–mediated gene flow were compatible with the frequency with which we observed empirical groups to contain ‘immigrant’ haplotypes. The source code for the simulation is available as electronic ST was similarly low among male and female chimpanzees and bonobos , even though several groups had small sample sizes. Y–chromosomal variants did not reliably delineate social groups in either species and were shared not only between neighboring groups, but also over distances of ∼50 km in our chimpanzee sample  and over a sustained period in the absence of male–mediated gene flow. Using varied size groups of reproductively active males and realistic assumptions for the mutation rate and distribution of reproductive skew, we found that 20 – 78 and 17 – 69% of simulated chimpanzee and bonobo groups, respectively, contained multiple Y–haplotypes, overlapping with the empirical data in bonobos and approaching the levels observed in wild chimpanzee groups . As expeWe next examined how often highly divergent Y–haplotypes are likely to be observed within groups, and whether such divergent types are likely to be observed in the absence of male–mediated gene flow. We therefore determined the maximum number of mutational steps between Y–haplotypes arising within groups over time in the absence of gene flow, using the simulation conditions specified above. The simulations suggest that maximum numbers of mutations between Y–haplotypes observed within simulated groups at frequencies >1%, were 6 mutations in chimpanzees  and 5 mutations in bonobos  of groups in chimpanzees or 2/6 (33.3%) in bonobos, rates of male–mediated gene flow of 3.5 – 7% or 14.5 – 28.5% immigrant Y–haplotypes/generation, depending upon the group size, are necessary in chimpanzees and bonobos, respectively .Pan dispersal patterns We explored patterns of genetic differentiation and specifically the potential for male–mediated gene flow among social groups of western chimpanzees and bonobos. Autosomal genetic differentiation was similarly low in both species, and slightly but not significantly higher in males than in females. While this finding is consistent with Pan populations. Variation in the effective extent of male philopatry has been suggested for other primates exhibiting some form of male philopatry, such as hamadryas baboons We found significantly less genetic differentiation at the Y–chromosome in western chimpanzees than in bonobos and eastern chimpanzees ; 62. ThiOur observations of sharing of Y-chromosome haplotypes among nearby groups as well as those separated by ∼50 km, the lack of increased genetic differentiation at larger geographic scales , and theThe simulations also showed that when using realistic mutation rates and reproductive skew parameters, social groups would not be expected to contain Y–haplotypes as divergent as those we observed in our empirical data. Thus, we estimated male–mediated gene flow to be, on average, 4.8% immigrant Y–haplotypes/generation in chimpanzees and 19.8% immigrant Y–haplotypes/generation in bonobos. This lower estimate of gene flow among western chimpanzees as compared to bonobos seems, at first look, inconsistent with lower overall levels of Y–chromosomal differentiation among this chimpanzee population, and several explanations are possible. However, both estimates are based on a small number of observations and are associated with a large degree of uncertainty, and the bonobo gene flow estimation in particular was based on fewer social groups, thus potentially harboring a larger stochastic component due to sampling variance. An alternative explanation would point to differences in male effective population sizes as contributing to differences in these estimates of Y-chromosomal genetic differentiation or male-mediated gene flow. However, male effective population size is not expected to differ greatly between western chimpanzees and bonobos as the long-term effective population sizes of both taxa are similar Finally, we estimated gene flow by considering only highly dissimilar haplotypes as originating outside the group. It seems likely, however, that some of the highly similar haplotypes might also originate from outside the group. Our simulations showed that, particularly in smaller groups with 5 males, most often only one haplotype is present  because mutation does not suffice to generate new variants frequently enough to counteract the loss of haplotypes when not all males get to reproduce. Thus, our estimated rate of male–mediated gene flow in the western chimpanzee population might be considered a minimum estimate and further study is needed in both western chimpanzees and bonobos.Several mechanisms can facilitate male–mediated gene flow among groups. Despite years of cumulative study, quantitative data on population dynamic processes like group splits or takeovers that might redistribute genetic variation are limited in chimpanzees and bonobos . However, more information exists on individual behaviors that may allow male–mediated gene flow. Dispersal by adults of the more philopatric sex, as seen in many other mammals Click here for additional data file.Table S2Simulated distributions of reproductive skew among bonobo and chimpanzee males for groups of different sizes. Values represent probabilities of transmission of an individual haplotype to the next generation and were derived from the original data using a best-fit log-function adjusted to the respective group sizes. Data were derived from human hunter-gatherer populations (DOC)Click here for additional data file.Table S3ST) in western chimpanzee (A) and bonobo (B) groups.Pairwise autosomal genetic differentiation  are shown in bold. To minimize stochasticity, for all analyses of genetic differentiation between communities we excluded social groups with fewer than four individuals genotyped at the respective marker . Therefore, the number of pairwise comparisons differs between the autosomal and Y-chromosomal data Click here for additional data file.Table S4Y-chromosomal microsatellite haplotypes of bonobo and western chimpanzee males. Locality indicates sampling locations as shown in a, Y-chromosomal loci DYS; b, Indel, coded as highest repeat number due to insufficient knowledge of mutational pattern.(DOC)Click here for additional data file.Table S5ST) in western chimpanzee (A) and bonobo (B) groups.Pairwise Y–chromosomal genetic differentiation (F Significantly differentiated pairs (p<0.05) are shown in bold. Sample sizes are indicated in brackets. To minimize stochasticity, for all analyses of genetic differentiation between communities we excluded social groups with fewer than four individuals genotyped at the respective marker . Therefore, the number of pairwise comparisons differs between the Y-chromosomal and autosomal data Click here for additional data file.Information S1Supplementary analytical procedures. Two-step amplification of DNA from fecal samples.(DOC)Click here for additional data file.Information S2Simulation source code. The code is written in Java (Sun Microsystems Inc. 1994–2009).(DOC)Click here for additional data file.


Whether in religious reverence for the beauty of science or impish delight fueled by the martini breaks of which he was so fond, Francis coined the term “original antigenic sin” to describe a curious new immunologic phenomenon. Elsewhere in this issue, Adalja and Henderson propose that original antigenic sin has altered the population age–specific incidence of infection and disease caused by influenza A pandemic (H1N1) 2009 virus and that public health responses must account for the disruption ; that contemporary human and swine viruses were closely related; and that over a lifetime of repeated exposures, different human birth cohorts were acquiring fundamentally different influenza infection experiences. The surprise appearance in 1946 of a new and antigenically different influenza A virus (designated influenza A′ and recently shown to be a subtype H1N1 intrasubtypic reassortant) provided Francis a unique opportunity. College students participating in a 1946 trial of the old 1946 virus vaccine were infected in March 1947 with the new A′ virus. Surprisingly, these students developed low serologic titers to the new infecting virus and higher seroconverting titers to old viruses with which they previously had been infected. Moreover, recent recipients of the old virus vaccine had the highest seroconverting titers of all to the old—but not to the new—virus , and increased incidence of influenza in 2009 after vaccination with a related virus in 2008–2009 (15). On a positive note, original antigenic sin has also been linked to vaccine-induction of heterosubtypic neutralizing antibodies (16).Original antigenic sin seems to be most pronounced when sequential viruses are of intermediate antigenic relatedness; when they are antigenically complex; and when sequential exposure intervals are long, consistent with ongoing selection and expansion of lymphocyte clones that have increasing antibody avidity at key cross-reactive epitopes  subtypes : “Lord make me chaste—but not yet.”


Introduction: cytokines and their receptor genes are very polymorphic. SNPs in the promotor region of the gene may influence the rate of cytokine secretion and may affect the biological activity of the encoded cytokine. A number of cytokines and cytokine receptors have been directly linked to the development of human cancers. The aim of our study was to determine the cytokine gene polymorphism in Romanian multiple myeloma patients. Material and methods: cytokine genotyping was performed in 80 patients and 100 healthy blood donors using molecular biology methods . Results: analyzing each polymorphic site, there was an increased frequency of the following genotypes in patients compared to control group: Interleukin–1beta (IL–1β) pos.+3962 TT, IL–12 pos.–1188 CC, gamma–Interferon (γ–IFN) pos.+874 AA, Transforming Growth Factor– beta1 (TGF– β1) codon10 TT, IL–2 pos.–330 TG and pos.+166 TT, Interleukin–4Receptor alpha (IL–4Rα) pos.–33 TC, IL–10 pos.–1082 GG and pos.–592 CC, IL𢀓6 pos.–174 GG. It should be noted that almost one third of multiple myeloma patients had IL–6 pos.–174 GG genotype and 62% IL–10 GCC haplotype. These identified haplotypes are high interleukins producer, and this fact was confirmed by serum IL–6 and IL–10 levels performed by ELISA and enhanced chemiluminiscence methods. Conclusion: these markers could be successfully used, together with other specific clinical and biological parameters, as reliable individualized prognostic factors in multiple myeloma patients. The cytokines and their receptor genes are very polymorphic. Single nucleotide polymorphisms (SNPs) in the promotor region of the gene may influence the rate of cytokine secretion and may affect the biological activity of the encoded cytokines. A number of cytokines and cytokine receptors have been directly linked to the development of human cancers . Multiple myeloma (MM) is a malignancy arising from post–germinal mature B cells characterized by an excess of monotypic plasma cells in the bone marrow secreting monoclonal immunoglobulins in the serum and/or urine, with a concomitant decrease in normal immunoglobulins and lytic bone lesions. Multiple myeloma is a clonal plasma cell neoplasm, which remains incurable despite conventional therapy. MM cells are predominantly localized in bone marrow (BM), and their interaction with bone marrow stromal cells (BMSCs) stimulates transcription and secretion of cytokines from BMSCs. Cytokines in turn not only promote the growth and survival of MM cells, but also reduce the efficacy of conventional drugs .Plasma cells may produce Interleukin–6 ILx2013;6) by an autocrine mechanism whereas a paracrine mechanism is believed to be involved in the production of IL–6 by bone marrow stromal cells through an interaction between adhesion molecules present on myeloma plasma cells and their respective receptors that are present on bone marrow stromal cells ;6 by an . Among tInterleukin (IL)–10 is a critical cytokine involved in the terminal differentiation of B cells into plasma cells, but is also a growth factor of malignant plasma cells, produced by myeloma cells from about half the patients and is detected in the plasma of patients with plasma cell leukemia or solitary plasmacytoma. The myeloma cell growth activity of IL–10 is mediated through a gp130 cytokine, oncostatin M (OSM) that is frequently produced by myeloma cells .The aim of our study was to determine the cytokine gene polymorphism in Romanian multiple myeloma patients and if there is any correlation between certain genotypes, serum levels of cytokines and disease evolution and prognosis. Eighty patients (F/M: 39/41) diagnosed with multiple myeloma and treated in Fundeni Clinical Institute, Department of Hematology between 2007 and 2011, and 100 healthy blood donors were included in this study. Mean age of the patients was 59 years (36 – 79 years).  The clinical manifestations of the onset of disease were highly variable, bone pain, secondary anemia and extramedullary infiltration being on the top .Depending on the type of secreted immunoglobulin, distribution in the study group was the following .Most patients were in advanced stages of the disease .TM Cytokine Genotyping Kit. The InvitrogenTM Cytokine Genotyping Kit is a PCR–based method designed to detect polymorphisms of thirteen cytokine genes. The kit consists of various formulations of lyophilized primer mixes that are used to amplify genomic DNA by using a 96 well thermal tray. After cycling is complete, the PCR products are loaded onto a 2% agarose gel for electrophoresis and then were visualized under UV illumination and documented by photography. DNA was extracted from the whole peripheral blood by using Qiagen reagents. Cytokine genotyping was performed by InvitrogenIn addition, to have a complete overview of the patients' immunological status we have analyzed the association of cytokine gene polymorphisms with serum levels of cytokines (IL–6 and IL–10) measured by enhanced chemiluminescence (Immulite). The Immulite System assay uses specific antibody or antigen, coated plastic beads as the solid phase, alkaline phosphatase labeled reagent and a chemiluminiscent enzyme substrate. After incubating the sample with the alkaline phosphatase reagent, the liquid reaction mixture, in the Test Unit, is rapidly separated from the bead when the bead is washed, and the Test Unit is spinned at a high speed on its vertical axis. The bead is left with no residual, unbound label. The bound label is then quantitated with a dioxetane substrate, which produces light. A photomultiplier tube detects light emission and the specific designated software generates printed reports for each sample.Frequency assessment of each polymorphic site, in patients and control group, revealed significant differences in the following cytokines It should be noted that 23  of multiple myeloma patients (of which only 2 in the early stages of disease) had IL–6 pos.–174 GG genotype and this genotype was associated with increased serum levels of IL–6 . In addition, 17 of these patients also showed increased serum levels of IL–10, and these values were well correlated with the high producer IL–10 – GCC haplotype. Moreover, it should be noted that 64% of all patients had this haplotype, while in controls the frequency was of only 38%.Cytokines play a crucial role in the regulation of key pathways of immunity, the balance between cell–mediated (Th1) and humoral (Th2) responsiveness. Genetic variation is common across the human genome. It is estimated that there are more than 7 million single nucleotide polymorphisms (SNPs) with a minor allele frequency of 5% to 10%. Although most SNPs are not functionally important, there is a subset of variants that alter the expression or function of a gene product. Several studies have shown a link between polymorphisms in IL–1β, IL–6, IL–10 and cancer risk. They may also be central to the pathogenesis of MM .The interaction between the myeloma cell and the BM microenvironment is central to the growth and survival of myeloma cells. The myeloma cell adheres to the bone marrow (BM) microenvironment, and thereby stimulates angiogenesis and enhances the stimulation of cytokines such as IL–1β, IL–6 and IL–10 [In this study, we address the importance of the polymorphisms  IL–6 GC–174, IL–10  G–1082, C–819, C– 592,  which are known to affect the transcription levels of the genes and are also known to be important for cancer cell growth.There was no significant difference between patients and the control group on IL–6 –174 GG genotype frequency, but patients who showed this genotype, accompanied by increased serum levels of IL–6, had severe disease needing aggressive chemotherapyOn the other hand, IL–10 –1082GG genotype, was identified as being associated with a better overall survival of patients, together with the favorable prognostic factors.During the last decade, new treatments with immunomodulatory drugs and proteosome inhibitors have been introduced and have improved the patients' survival. These drugs induce apoptosis of myeloma cells, interrupt the interaction between myeloma cells and stromal cells in the BM, inhibit angiogenesis and inhibit the secretion of IL–1β and IL–6. The treatment effects of the new drugs support the importance of these key regulators of the immune response in the pathogenesis of MM. Inborn genetic variation in these genes may therefore be important for the risk, prognosis and treatment outcome of MM.Our findings showed that in almost one third of the studied patients had IL–6 pos.–174 GG genotype and was associated with clinical and biological worsening of MM. IL–6 pos.–174 GG genotype was correlated with increased serum levels of IL–6 in some of the patients and in others with significantly high levels of IL–10.64% of the multiple myeloma patients had IL–10 – GCC haplotype compare to the controls.We conclude that these markers could be successfully used, together with other specific clinical and biological parameters, as reliable individualized prognostic factors in multiple myeloma patients


The aim of this study was to validate a model for optimal birth weight derived from neonatal records, and to test the assumption that preterm births may be considered optimally grown if they are not exposed to common factors that perturb fetal growth.Weights of fetuses were estimated from serial biometric ultrasound scans  and combined with neonatal weights for a prospective pregnancy cohort (N = 691). Non-Caucasians, fetuses subsequently born preterm and those with diagnosed or suspected determinants of aberrant growth were excluded leaving fetuses assumed to have experienced normal growth. A generalised linear longitudinal growth model for optimal weight was derived, including terms for gestational duration, infant sex, maternal height and birth order. This model was compared to a published model derived solely from birth weights.Prior to 30 weeks gestation, the published model yielded systematically lower weights than the model derived from both fetal weight and neonatal weight. From 30 weeks gestation the two models were indistinguishable.The model for optimal birth weight was valid for births that have attained at least 30 weeks gestation. The model derived from both fetal and neonatal weights is recommended prior to this gestation. Standards for fetal weight are typically derived from birth weights of neonates born at different gestational ages ,2. HowevOptimal weight may be interpreted as a result of growth achieved in the absence of any factors that pathologically affect growth. We have previously reported a method of assessing the appropriateness of fetal growth using the proportion of optimal birth weight . With thThe aim of this study was to validate a model for optimal birth weight derived from neonatal records, and to query the assumption that preterm births may be considered optimally grown if they are not exposed to common factors that perturb fetal growth.Our analytic approach is summarised by the following steps:i. We selected a sample of optimally grown term births from a randomised controlled trial of serial biometric ultrasound scans in pregnancy. Weight was estimated from biometric measurements made during each ultrasound scan during pregnancy and obtained at the time of birth.US refers to optimal weights derived with this model.ii. A model for optimal weight was derived at each of these measurement occasions using the fetal and neonatal weights as the response variable and non-pathologic determinants of growth as explanatory variables. OWBW.iii. Optimal weight was then derived at each of these measurement occasions using the published model derived using only birth weights from an independent population, OWiv. The difference in optimal weight estimated by the two models was calculated at each week of gestation.A total of 9,222 serial ultrasound scans were obtained between 1989 and 1991 in Perth Western Australia for 2,860 pregnancies that resulted in a live birth  were appended to the ultrasounds , resulting in 3,539 measurements , femur length (FL), head circumference (HC) and biparietal diameter (BPD) measurements were obtained from the ultrasounds. Hadlock’s formula was applied to estimate fetal weight using AC, FL, HC and BPD measurements taken at or after 27 weeks gestation . In a coUS) derived from both the fetal ultrasound scans and neonatal measurements was determined using gestational age, maternal height, birth order and infant sex as predictors. All first order interactions between the predictor variables were considered along with polynomial forms of gestational age. Box-Cox transformations were applied to improve the fit of the model [A predictive model for the expected fetal weight  was calculated for each record using a previously published model that relied on birth weight measurements [The optimal weight , Third refers to the third birth (para 2), and More refers to the fourth birth or more. Height is maternal height measured during pregnancy.In that study, similar exclusion criteria were applied: multiple birth (3%), maternal smoking during pregnancy 27%), maternal vascular disease (7%), congenital anomaly (6%) and maternal pre-existing or gestational diabetes (4%) [%, maternBW from OWUS was calculated at each gestational age as:The proportional deviation of OWBW was considered an appropriate representation of OWUS at gestational ages where the 95% bootstrap confidence interval [The formula for OWinterval  for the Ethics approval was obtained by the Department of Health Western Australia, Human Research Ethics Committee.There was an approximately equal ratio of male to female births (51:49) Table . Mothersρ = 0.007191, SD = 0.001657).The Box-Cox procedure suggested the square root as the optimal transformation. The Pearson correlation between the observed and predicted fetal weights was 0.97. The square of this correlation, a pseudo R-squared, indicated that the model explained 95% of the variation in fetal weights. The autocorrelation in the residuals between consecutive days was low but statistically significant, and therefore systematic and non-ignorable (US (grams) expressed as:Parameter estimates are shown in Table where Time is the time of gestation represented in days since the last menstrual period.BW, OWUS, and proportional deviation of OWBW from OWUS were calculated from 16 to 39 weeks gestation because few ultrasound scans were conducted outside this interval  was non-zero (p < 0.0001) at 10 g (SD = 26 g) using fetometric ultrasound measurements taken before 27 weeks gestation. The mean difference between estimated fetal weight based on Scott’s model and the previously published model (Scott – OWBW) was also non-zero (p < 0.0001) at 197 g (SD = 68 g) using fetometric ultrasound measurements taken before 27 weeks gestation.Hadlock’s formula was applied to estimate fetal weight from ultrasound scans at or after 27 weeks gestation  and ScotOur study made use of a large prospectively collected sample of serial ultrasounds to derive an estimate of the optimal fetal weight and thereby also a method to ascertain the adequacy of fetal growth. We adopted a multi-faceted approach: weight was derived from ultrasound scans taken at multiple occasions during pregnancy and supplemented with weight measured at the time of birth, rather than sole reliance on birth weights and we excluded fetuses subsequently (i) born preterm, (ii) that died before 28 days of life, or (iii) that experienced pathologies affecting growth. We found that estimates of optimal weight based on a population of birth weights also subject to exclusions (ii) and (iii) but not (i) were systematically lower than fetal weight estimated using biometric ultrasounds prior to 30 weeks gestation.US and OWBW . Among this group, the recorded antepartum factors that might have contributed to growth restriction but were not excluded as common causes of growth restriction were: threatened abortion (antepartum haemorrhage before 30 weeks gestation), N = 13; urinary tract infection, N = 2; antepartum haemorrhage (not attributed to placenta previa or abruption), N = 39; asthma, N = 12; genital tract infection, N = 9; vaginitis, N = 4; significant psychological morbidity, N = 11; anaemia, N = 5; neoplasms, N = 7. Approximately 63% of this cohort experienced at least one of these factors. Among all term neonates in Western Australia, the prevalence of asthma was 9.7% and neoplasms  was 0.02%, which were both lower than the prevalence in this cohort. Further studies are required to confirm whether maternal asthma, cervical cancers and depression are disproportionately stronger risk factors for growth restriction at such early gestations in other populations. It remains to be demonstrated that preterm births, particularly very preterm births, can be considered optimally grown if they are not exposed to common factors that perturb fetal growth.It is plausible that the difference between OWW Figure  suggestslow-risk preterm births before 28 weeks gestation. This meant that a formal validation of the model used to estimate fetal weight from ultrasound measurements could not be conducted. However, we confirmed that results were not sensitive to the choice of Hadlock’s versus Scott’s method to estimate fetal weight from ultrasound measurements. Before 27 weeks gestation, Scott’s method and Hadlock’s method to estimate fetal weight from ultrasound measurements differed by only 10 g, whereas the difference between estimates obtained from Scott’s method and the model for optimal weight derived from birth weight measurements was almost 200 g.Although it is plausible that there is an increasing proportion of unusual causes of growth restriction with decreasing gestation of delivery before 28 to 30 weeks gestation, there are other explanations for the findings. Radiographers may have systematically over or under-estimated fetal biometric measurements. However, the measurements were taken by a limited number of experienced radiographers at a tertiary obstetric hospital. While both Hadlock’s and Scott’s models were selected because they performed favourably compared to alternative formulae, it is possible that both of these methods used to estimate fetal weight from ultrasound measurements systematically over-estimated true fetal weight in our study. Few ultrasound scans were taken within a week of birth among early BW was developed predominantly on a sample of births from 33 weeks gestation whereas the model for OWUS was based on measurements from ultrasounds that start typically from much earlier gestations  who reported that the median of the fetal weight distribution provided an upper bound for the median of the birth weight distribution between 25 and 35 weeks of gestation . HoweverThe methodology that we applied differs from those suggested by others in that centiles and z-scores were not produced . HoweverIt remains to be demonstrated that preterm births can be considered optimally grown if they are not exposed to common factors that perturb fetal growth. The model derived from both fetal and neonatal weights in this study is recommended before 30 weeks of gestation. From 30 weeks gestation the two models were indistinguishable.The authors declare that they have no competing interests.GP participated in the design of the study, performed the statistical analysis, and wrote the initial manuscript and later revisions. EB conceived the study, participated in its design and helped to draft and revise the manuscript. DL participated in the design of the study and helped to revise the manuscript. All authors read and approved the final manuscript.


We appreciate Kawada’s interest in our study . His letKawada notes that the small number of participants with low ankle–brachial index (ABI) provided low power to detect an association; this is a limitation that we acknowledged in our article . Kawada Kawada’s second argument involves the consideration of multicollinearity in the fully adjusted model (model 2), in which systolic and diastolic blood pressure were included. Systolic and diastolic blood pressure were only moderately correlated , and according to the variance inflation factor (VIF), there were no multicollinearity problems (VIF was 2.45 for systolic blood pressure and 1.98 for diastolic blood pressure).2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), black smoke, and traffic intensity] and three indicators of vascular damage . We consider, however, that these do not constitute results contradictory to the positive association between air pollution and subclinical markers of atherosclerosis found in the six studies thoroughly discussed in our article (Kawada points at “contradictory results” in the association between air pollution and carotid intima media thickness (IMT), mainly based on the null and weak associations found by  article , 2010 asFinally, we agree with Kawada’s closing remark on the need for longitudinal studies, as we concluded in our article.


The structure and function of human gut microbiota is currently inferred from metagenomic and metatranscriptomic analyses. Recovery of intact DNA and RNA is therefore a critical step in these studies. Here, we evaluated how different storage conditions of fecal samples affect the quality of extracted nucleic acids and the stability of their microbial communities.We assessed the quality of genomic DNA and total RNA by microcapillary electrophoresis and analyzed the bacterial community structure by pyrosequencing the 16S rRNA gene. DNA and RNA started to fragment when samples were kept at room temperature for more than 24 h. The use of RNAse inhibitors diminished RNA degradation but this protection was not consistent among individuals. DNA and RNA degradation also occurred when frozen samples were defrosted for a short period (1 h) before nucleic acid extraction. The same conditions that affected DNA and RNA integrity also altered the relative abundance of most taxa in the bacterial community analysis. In this case, intra-individual variability of microbial diversity was larger than inter-individual one.Though this preliminary work explored a very limited number of parameters, the results suggest that storage conditions of fecal samples affect the integrity of DNA and RNA and the composition of their microbial community. For optimal preservation, stool samples should be kept at room temperature and brought at the laboratory within 24 h after collection or be stored immediately at −20°C in a home freezer and transported afterwards in a freezer pack to ensure that they do not defrost at any time. Mixing the samples with RNAse inhibitors outside the laboratory is not recommended since proper homogenization of the stool is difficult to monitor. The human gut microbiome is a highly dense microbial ecosystem, largely outnumbering our own eukaryotic body cells. Its intimate contact with our digestive system and its potential role in health and disease states makes this ecosystem very attractive for a deep characterization of its composition and function. In recent years, high-throughput sequencing has been the catalyst for analyzing microbial population diversity and functions. While bacterial 16S rRNA gene survey can answer the question “which species are there” -4. TheseFunctional metagenomic projects are highly interdisciplinary and involve numerous procedures, ranging from clinical protocols for sample collection to bioinformatics tools for data interpretation. Strong biases can be introduced in each of these steps. Sample storage conditions, one of the first steps, is critical for downstream analyses. Previous studies had indicated that storing conditions of stool samples only modestly affect the structure of their microbial community -8. HowevIn the present study, we compared the effect of different storage conditions of stool samples on microbial community composition, genomic DNA and total RNA integrity.In order to investigate the effect of storage conditions on the quality of genomic DNA, we chose a subset of stool samples collected by 4 volunteers  and that had been stored in the following 6 conditions: immediately frozen at −20°C (F); immediately frozen (UF) and then unfrozen during 1 h and 3 h; kept at room temperature (RT) during 3 h, 24 h and 2 weeks. In this case, all 24 samples were kept at −80°C in the laboratory until genomic DNA was extracted and its integrity analyzed using microcapillary electrophoresis.p < 0.01, Poisson regression analysis) for all storage conditions compared to frozen samples except those kept at room temperature for 3 h. Therefore, storing fecal samples at room temperature over 3 h after collection or allowing them to thaw and refreeze is not recommended for shotgun metagenomic sequencing, since DNA extracted from these samples can be significantly fragmented. In all the tested conditions the amount of DNA obtained was in the range of 70–235 μg/250 mg of fecal sample, which is sufficient for downstream analysis such as metagenomic library construction or shotgun sequencing . This model is appropriate for modeling paired count data. P values < 0.05 were referred as significant.The Kolmogorov-Smirnov test was used to check the normality of data distribution. Comparisons of parametric normally distributed data were made by the Student’s test, paired tests for intra-group comparisons and unpaired tests for inter-group comparisons; otherwise the Wilcoxon signed rank test was used for paired data, and the Mann–Whitney SC, MC, MG, CA carried out the sample collection and the molecular genetic studies, AE participated in the sequence and statistical analyses. JD, FA, FG participated in the design of the study. JR and CM participated in the design of the study, the interpretation of the results and the writing of the manuscript. All authors read and approved the final manuscript. Table S1. Detailed taxonomy assignment at the species level of the 24 samples. The taxonomy analysis is based on alignment performed using PyNast against Silva 108 release database and OTUs assignment using blast and the Silva 108 release taxa mapping file.Click here for file Figure S1. Taxonomy analysis at the phylum level of the 24 samples based on alignment performed using PyNast against Silva 108 release database and OTUs assignment using blast and the Silva 108 release taxa mapping file.Click here for file Supplementary Methods. Detailed description of extraction of total RNA from fecal samples.Click here for file


Since the 1980s numerous large randomized trials involving tens of thousands of patients have demonstrated that fibrinolytic therapy can reduce mortality and preserved left ventricular function in patients with suspected acute myocardial infarction.2 Furthermore, it has been well established that the earlier reperfusion therapy is started after symptom onset, the larger the mortality reduction, with the absolute mortality reduction greatest among patients who presented within 1 hour of symptom onset.3Early animal studies demonstrated that temporary coronary artery occlusion does not lead to irreversible myocardial damage. Delayed reperfusion resulted in a wave of myocardial necrosis extending from the subendocardium to the subepicardium. With increasing occlusion times the amount of transmural necrosis increased.4 The mortality benefit after reperfusion with PCI in patients with acute ST elevation myocardial infarction (STEMI) is the greatest in the first 1 to 3 hours after the onset of symptoms. This is believed to be related to the amount of salvaged myocardium during this time.5 With the advent of this therapy, the focus of early reperfusion turned to door‐to‐balloon times. Review of the National Registry of Myocardial Infarction from 1990 to 2006, showed an overall reduction in door‐to‐balloon and door‐to‐needle time for administration of fibrinolytic therapy. There was also a decline in in‐hospital mortality in patients who underwent reperfusion therapy; both fibrinolysis and primary PCI.6 This mortality benefit is significantly reduced or even lost beyond 1 hour. Nallamouth and Bates7 showed that for every 10 minutes of added delay in performing PCI, the mortality benefit of the PCI compared to fibrinolysis decreased by 1% with the reperfusion strategies becoming equivalent at 62 minutes. Shorter time to reperfusion is associated with smaller infarct size and less microvascular obstruction by cardiac MRI resulting in more salvaged myocardium. After 90 minutes this was markedly reduced.8 Longer time to reperfusion is also associated with increase in transmural necrosis.9The benefit of early reperfusion with percutaneous coronary intervention (PCI) has demonstrated incremental improvement in mortality.10 Potential delays include time to obtain the electrocardiogram (ECG), time to diagnosis of STEMI, time to transport the patient to the cardiac catheterization laboratory, and time for performing the PCI. For patients arriving by ambulance, obtaining a pre‐hospital ECG and allowing emergency department physicians to activate the cardiac catheterization laboratory have been key in streamlining the process and ultimately reducing time to reperfusion.11 After implementation of such strategies, there have been marked improvements in median door‐to‐ door to balloon times balloon time nationally. Krumkolz et al,12 reported a reduction in D2D from 96 minutes in 2005 to 64 minutes in 2010 in patients with STEMI presenting to primary PCI centers. There were corresponding increases in the percentage of patients who had D2D time <90 minutes (44.2% to 91.4%). In our hospital, the median D2D is now less than 45 minutes with 100% of patients having D2D times of less than 90 minutes.Metrics for treatment of patients with STEMI have focused on reducing the time to reperfusion after the patient arrives at the hospital. Practice guidelines recommend that time from arrival at the hospital to mechanical reperfusion or “door‐to‐device time” (D2D) be less than 90 minutes.13 Implementation of regional STEMI systems of care resulting in further reductions in D2D time can be achieved by increasing pre‐hospital ECGs and direct activation of the cardiac catheterization laboratory by EMS. Expansion of such a system to an entire state has shown increases in pre‐hospital ECGs, modest reduction in median D2D times, and a decline in first medical contact to device time.14 This reduction in D2D time observed within regional STEMI systems of care is similar to national trends.15Recognizing that D2D does not accurately measure coronary occlusion to perfusion time, the key time for myocardial salvage, efforts have been made to further streamline the process by implementing reperfusion strategies that incorporate first medical contact with emergency medical services and transfer protocols to primary PCI centers. A survey from the American Heart Association Mission: Lifeline reports 381 STEMI systems of care in the United States. These systems involve collaboration between emergency medical services (EMS), non‐PCI hospitals, and PCI hospitals.16 Thus, the new metric for STEMI care has become the first medical contact to reperfusion time. In the future the metric might be symptom onset to reperfusion, as shorter symptom onset to reperfusion times would result in more salvaged myocardium. In a large observational study from Japan, patients presenting within 3 hours of symptom onset had a lower incidence of composite death and congestive heart failure than those presenting later.17While D2D times have continued to improve nationally with implementations of STEMI systems and improvement in processes of care, it is likely that the benefit of further improvements in D2D will plateau. A recent report from National Cardiovascular Data Registry showed that short‐term mortality is unchanged.18 In well‐developed STEMI systems, first door‐to‐device times within 90 to 120 minutes can be attained for hospitals within 30 minutes transfer‐drive time to a PCI hospital.19 For patients outside this window it is possible that a facilitated PCI approach involving initiation of fibrinolysis and transfer to PCI center would be the reperfusion strategy of choice. A recent study demonstrated the value of pre‐hospital fibrinolysis with timely coronary angiography and PCI for patients unable to undergo PCI within 1 hour of first medical contact and presenting within 3 hours of symptom.20One challenge that remains for out‐of‐hospital STEMI is the patient who presents to a non‐PCI hospital either directly or by EMS. Direct transport to a PCI center after prehospital diagnosis of STEMI has been shown to result in a higher percentage of patients having first medical contact to device time <90 minutes than those requiring interfacility transfer.JAHA, Dai et al,21 report a single center, retrospective analysis of patients with inpatient STEMI. This study highlights another challenge in STEMI care, the patient hospitalized for noncardiac conditions. The authors identify 2 sources of delay for reperfusion for the patient with inpatient STEMI: recognition of STEMI and time to reperfusion once STEMI was diagnosed. For inpatient STEMI, they report longer median time to obtain ECG (41 versus 5 minutes), ECG to angiography time (91 versus 35 minutes), and ECG to device or reperfusion (140 versus 60 minutes) compared to outpatient STEMI.In this issue of Despite these delays, the inpatient STEMI group had lower biomarkers and no difference in ejection fraction compared to the outpatient group. This may be due to a delay in all patients resulting in the time of occlusion to reperfusion being outside the window for significant salvage. The inpatient STEMI group had higher in‐hospital adjusted mortality, 39.6% compared to 4% in the outpatient group. This higher mortality for inpatient STEMI is attributed by the authors to atypical presentation and more comorbid disease. Emergent coronary angiography was performed on 71% of patients with inpatient STEMI of which only 56% underwent PCI. Inpatients who had an ECG within 1 hour were more likely to have symptoms and had a higher rate of revascularization (87% versus 56%). This further illustrates the complexity of these patients. Improvement in the care of the inpatient STEMI might include earlier recognition, earlier ECG acquisition and interpretation along with improved processes to reduce ECG to reperfusion times. However, whether these changes will improve outcomes is unknown. The lack of association between time to reperfusion and myocardial salvage in this study suggests the hypothesis that poor outcomes in inpatients with STEMI are primarily driven by factors other than time to reperfusion.The present study is an important contribution to insight concerning this next frontier in STEMI care. Further studies addressing this topic are eagerly awaited.


This paper aims to identify factors that systematically predict why some countries that have tried to scale up oral rehydration solution (ORS) have succeeded, and others have not.We examined ORS coverage over time, across countries, and through case studies. We conducted expert interviews and literature and data searches to better understand the history of ORS scale–up efforts and why they failed or succeeded in nine countries. We used qualitative, pairwise (or three–country) comparisons of geographically or otherwise similar countries that had different outcomes in terms of ORS scale–up. An algorithm was developed which scored country performance across key supply, demand and financing activities to quantitatively assess the scale–up efforts in each country.The vast majority of countries have neither particularly low nor encouragingly high ORS use rates. We observed three clearly identifiable contrasts between countries that achieved and sustained high ORS coverage and those that did not. Key partners across sectors have critical roles to play to effectively address supply– and demand–side barriers. Efforts must synchronize demand generation, private provider outreach and public sector work. Many donor funds are either suspended or redirected in the event of political instability, exacerbating the health challenges faced by countries in these contexts. We found little information on the cost of scale–up efforts.We identified a number of characteristics of successful ORS scale–up programs, including involvement of a broad range of key players, addressing supply and demand generation together, and working with both public and private sectors. Dedicated efforts are needed to launch and sustain success, including monitoring and evaluation plans to track program costs and impacts. These case studies were designed to inform programmatic decision–making; thus, rigorous academic methods to qualitatively and quantitatively evaluate country ORS scale–up programs might yield additional, critical insights and confirm our conclusions. Oral rehydration therapy (ORT) for dehydrating diarrhea came into routine use at Bangladesh’s Cholera Research Laboratory  in 1969. Nine years later, the World Health Organization recommended a standardized version of the therapy – Oral Rehydration Salts, or ORS – for all acute watery diarrhea in children .The Lancet child survival series of 2003 identified it as the single intervention available at that time with the greatest potential to save lives [These low rates of ORS use are surprising given the emphasis given to this product in the years after its introduction. The product was one of the foci of UNICEF’s “GOBI–FFF” selective primary health care strategy of 1982 (the “O” in GOBI refers to ORS) . In the ve lives . Yet thrve lives , MEASUREve lives  and otheTwenty countries  ) have enThe objective of the present study was to address the question: Why have some countries succeeded in scaling up ORS for diarrhea, when others tried and failed? We hypothesized that countries would be more likely to have been successful in scaling up ORS if they simultaneously: 1) made significant improvements to the standard product offering, including lowering the price; 2) conducted wide–reaching marketing campaigns; 3) acted to remove regulatory barriers to the sale and promotion of ORS in the private sector; 4) improved private provider knowledge of rational diarrhea management; 5) improved public provider knowledge of rational diarrhea management; 6) made a concerted effort to improve the regularity of supply; and 7) mobilized partner funding as well as taking country ownership of the program. Some of these concepts have been examined in previous case studies  but we aWe categorized every country with ORS coverage data into three categories: countries that exceeded 50% coverage for ≥5 years and now have achieved >66% coverage were defined as “sustained success”  that they do not significantly contribute to mortality and morbidity . CaregivNine countries were purposively selected for in–depth case studies, including Bangladesh , Guyana In each country, literature reviews and expert interviews were conducted to better understand the history of ORS scale–up efforts and why they failed or succeeded. The review included peer–reviewed articles, conference presentations, and grant reports available to the Bill & Melinda Gates Foundation and partners. An initial search was conducted in PubMed in April 2012 and the titles and abstracts of all the retrieved citations were examined for relevance to ORS scale–up efforts in each country. Following the initial search, multiple searches were conducted in PubMed and Google through October 2012 to identify studies and reports related to ORS scale–up in the selected countries. The search strategy was restricted to documents written in English and French. The following keyword terms (in English) were used with each country: ORS, ORT, and diarrhea.Additional articles and reviews related to the relevant topics were identified by hand–searching the references in the articles and reports identified through the search engines. We also sought additional literature from the United Nations Children’s Fund , the WorData for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition were obtained from Demographic and Health Surveys , MultiplThe “snowball” technique was used to identify informants. An initial list of potential key informants was generated through personal communication with experts in the field of diarrhea management, with the aim of interviewing individuals from a range of sectors to provide a broad range of perspectives. Potential key informants from governments, donors, multilateral and bilateral organizations, non–governmental organizations (NGO), the local private sector, and academic and clinical institutions were contacted individually via email to request telephone or, in some cases, in–person interviews. Between April and September 2012, key informant interviews were conducted with 58 experts  comparisons of geographically or otherwise similar countries that had different outcomes in terms of ORS scale–up. In addition to the qualitative pairwise (or three–country) comparisons of country case studies, the scale–up efforts in each country were quantitatively assessed, based on a numeric scoring of country performance across various key supply, demand and financing activities. For each case study, we scored the country on their efforts along seven dimensions of implementation, with a range of scores from 0 (low/no effort) to 2 (high effort). The sum of these scores yields an implementation score ranging from 0 to 14. The seven dimensions of implementation included the following: made significant improvements to the standard product offering, including lowering price; conducted wide–reaching marketing campaigns; acted to remove regulatory barriers to sale and promotion of ORS in the private sector; improved private provider knowledge of rational diarrhea management; improved public provider knowledge of rational diarrhea management; made a concerted effort to improve the regularity of supply; mobilized partner funding as well as taking country ownership of the program.sustained_success>scoreunsustained_success>scorenon–starter). The test used was Cuzick’s non–parametric trend, which is an extension of the Wilcoxon rank–sum test [The quantitative portion of evaluation was conducted through a scoring algorithm. Scoring was made as consistent as possible across countries by developing precise definitions of what was included in “0”, “1” or “2” scores for each dimension  were trained to promote hygiene and treat diarrhea with ORT. During the conflict, which displaced as many as 2 million out of the 5.5 million population, ORS was pushed heavily on displaced populations in camps. After the civil war, the primary health care system was “reinvented”, with multi–donor support. Recurrent cholera outbreaks were managed with ORS and efforts were made to ensure that the supply chain was maintained at each level: the Ministry of Health and Sanitation increased the intensity of tracking ORS distribution, districts and communities were in charge of ordering supplies, and peer supervisors facilitated re–stocking ORS in Community Based Distributors’ (CBDs) kits. The population learned about the product via interpersonal communications with very active community promoters (BFVs and or CBDs). Integrated community case management of childhood illness was introduced to some districts in late 2000s and free health care for pregnant and lactating women and children under–five was introduced in 2010 [ in 2010 –37.Senegal is a West African country of 13 million people where ORS scale–up efforts have not succeeded (“non–starter”). The country is very stable, with a well–organized health system and relatively good infrastructure. The United States provided over half of all bilateral aid for health (basic) in the 2000s. USAID has been promoting ORS in Senegal since 1985, through multiple, successive, standalone “Technical Assistance” programs in “USAID regions” in the West – including PRITECH (1985–1993), BASICS (1994–2006), Child Survival Program (1998–2002), Fatick Partnership (2007–2009), Community Health Program (2006–2011). UNICEF supplied all ORS in the country until 2000 and Integrated Management of Childhood Illness (IMCI) was introduced in the 2000s, but the guidelines resulted in no change in clinical practice. The “health hut” program was launched in the late 1990s, including activities to promote both ORS and home fluids . However, ORS was not widely available in Senegal due to a weak distribution system that caused frequent shortages and stock–outs: availability of essential drugs was highest at the storage facilities and decreased at the more peripheral health facilities . There aThere are four key lessons from this comparison. First, interpersonal communications led to universal familiarity with ORS in Sierra Leone, whereas 41% of the population in Senegal still does not know about this product . In SierSecond, basic supply chain management kept ORS widely available in Sierra Leone; in Senegal, it was unavailable in the private sector because ORS does not have a “visa” required to register drug products  and therComparison 2: Guyana vs Trinidad and Tobago. Guyana is a “sustained success” country of just 742 thousand people, in South America but culturally of the Caribbean. The country is susceptible to flooding and experienced a cholera epidemic in 1992 [ in 1992 . After tTrinidad and Tobago is an “unsustained success” Caribbean country of 1.2 million people and is relatively wealthy with abundant oil and gas. Key informants recalled that a single local champion established Oral Rehydration Units in three major hospitals/health centers in the capital in 1981, in conjunction with an early 1980s ORS marketing campaign funded by the International Development Research Center , which used a logo on printed materials and also ran radio and television spots. One radio station hosted a call–in program with health care providers and focused on diarrhea prevention. Key informants suggested that the campaign was intended to be both relevant to and empowering for mothers, and relied on mother–to–mother interpersonal communication to disseminate messages. Messaging switched to promoting “rehydration”, and there was even distracting debate over merits of coconut water as a source of liquidand electrolytes . UltimatThis comparison illustrates that ORS is very hard to promote if it is not epidemiologically relevant. Although both countries experienced declines in mortality to low levels, ORS retained relevance in Guyana because of repeated outbreaks of diarrheal disease after flooding. This comparison underscores the essential nature of broad national buy–in. The program in Trinidad and Tobago relied on one person and external funding, whereas Guyana has embraced ORS as part of its commitment to universal primary health care, with the government even taking on responsibility for regular communication campaigns. Finally, clarity of message is essential. In Trinidad and Tobago, the messaging was inconsistent between ORS, breastfeeding, and even coconut water, whereas Guyana made a strong and lasting commitment to ORS, and folded this seamlessly into integrated programs such as Integrated Management of Childhood Illness (IMCI).Comparison 3: Malawi, Tanzania and Madagascar. Malawi is a land–locked country in Eastern/Southern Africa with 16.3 million people and successfully sustained scale–up. The country has never had significant civil unrest or natural disasters. Malawi implemented a National Control of Diarrheal Disease Program in 1985 and stopped promoting sugar–salt solution in 1989, using multiple channels to popularize ORS (so that 90% of the population was familiar with it by 1992). Integrated Management of Childhood Illness (IMCI) was rolled out comprehensively to all districts and a cadre of “Cholera Assistants” was instituted in the 1970s. These were developed into Health Surveillance Assistants now present in all “hard–to–reach” communities of the country [ country . From th country .Tanzania has 46.9 million people and was classified as an “unsustained success” for ORS scale up because it achieved greater than 50% coverage and then declined. Tanzania implemented a National Control of Diarrheal Diseases Program in the 1980s, with “Diarrhea Treatment Corners” in health centers and hospitals and achieved 93% familiarity with ORS by 1991 . AlthougMadagascar is an island of 22.0 million people and was classified as a “non–starter” for ORS scale–up because it never reached greater than 23.1% coverage. It has experienced a relentless series of natural disasters, and, in 2009, widely perceived to have been unconstitutional transfer of power. There was no ORS in country at all until 1988. UNICEF then supported a local producer with limited capacity, which eventually went out of business, leaving the country wholly dependent on imported supply. While many countries import health products, key informants suggested that the frequency with which Madagascar experienced natural disasters and the political turmoil that led to import disruptions resulted in poor accessibility of ORS. Early radio campaigns promoted both ORS and home–made sugar–salt solution. USAID supported co–packaged products only through the POUZN Project from 2008 to 2010 but diverted support to non–government entities following a transfer of power, which severely weakened program efforts to scale–up ORS .This divThis comparison reveals that once universal familiarity with ORS is achieved, availability is extremely important. Malawi achieved very high levels of availability in both public and private sectors, whereas in Madagascar, uptake has been crippled by lack of availability. In Tanzania, the weakening public sector supply chain may explain recent declines in ORS use. An organized cadre of trained community–based distributors can greatly extend the reach of the public sector to achieve market penetration at scale. It is possible to capitalize on floods and cholera epidemics to increase familiarity with and trust in ORS, but countries enmeshed in political unrest are not conducive to ORS scale–up. Reliance on a single donor is risky because support may be abruptly terminated before programs are mature.Comparison 4: Bangladesh vs India. Bangladesh, a South Asian country of 161 million people, was the first country in the world to accumulate large–scale experience using ORT. It is home to the world renowned International Centre for Diarrhoeal Disease Research . ICDDR,B developed ORT and continues to research and promote the approach, modeling successful control of diarrhea mortality. In 1981, the government created the National Oral Rehydration Project and distributed packets of ORS to health centers in 100/509 sub–districts [istricts . Betweenistricts . Bangladistricts . Accordiistricts . Bangladistricts .India’s 1.2 billion people reside in 28 states and seven Union Territories, each with hugely different public health systems and health outcomes. India was classified as a “nonstarter” through 2005 then had dramatic increases in coverage. India’s multiple large scale government programs – including Diarrheal Disease Control Program (1978), Child Survival and Safe Motherhood Program (1992), Reproductive and Child Health Program (1997), and National Rural Health Mission (2005) – have resulted in high ORS availability in the public sector and training and stocking of outreach workers such as Anganwadi Workers and, more recently, Accredited Social Health Activists (ASHAs). In the 1980s, UNICEF promoted sugar–salt solution , which iThis comparison underscores that even in countries where the market for diarrhea treatment is dominated by the informal private sector; it is possible to achieve high levels of use of ORS by changing social norms. It is likely that intensive interpersonal communication is a critical part of this behavior change, and it is also important to directly reach frontline providers at scale. Conversely, an excessive emphasis on public sector providers, in a context where, according to key informants, the public sector is under–valued and under–utilized, is not likely to be very effective, at least in the short term. Branded marketing can be very helpful, but must be explicitly directed at the mass market .Unambiguous messaging that home–made sugar salt solution is not an adequate substitute for ORS is critical for successful scale–up. Bangladesh benefited from the leadership of a highly respected local institutional champion for ORS  and managed to create a broad alliance of major local stakeholders. In India, the major champions of ORS have been mostly external, and there is no equivalent of BRAC that reaches beyond the public sector.P = 0.042, Cuzick’s non–parametric test for trend; There was strong evidence that the aggregate scale up scores were more favorable in the countries that achieved more sustainable scale–up, ie, countries that exceeded 50% coverage for ≥5 years and now have achieved >66% coverage  ensured both broad national buy–in and collaboration between government, non–government and private sectors; (ii) made significant efforts to synchronize demand generation, private provider outreach, and public sector work; and (iii) the context at the time of the interventions was conducive to scale up, including funding directed to ORS scale–up and the absence of political turmoil. We also drew some preliminary conclusions about specific elements of scale–up programs, though we believe these will need further validation. While these concepts are not entirely original and novel, we are not aware of any other work that has examined all of them simultaneously.Key informant interviews suggested that partner collaboration was especially critical to success in Sierra Leone, Bangladesh and Guyana. The governments in all three countries collaborated with a range of development partners in the public and private sectors, reducing potential for “donor dependency”. Senegal’s reportedly weak government engagement in the early stages of ORS scale–up efforts and reliance on USAID were both cited by key informants as drivers of continuing low ORS use rates. Similar findings were reported from a case study in Philippines as our findings from Trinidad and Tobago: hospital admissions attributable to severe diarrhea declined and ORS became less epidemiologically relevant as income and sanitation improved .The results of the quantification of scale–up factors analysis, despite relying heavily on qualitative information, suggested a correlation between high ORS use rates and synchronicity of demand– and supply–side interventions. All four “sustained successes”  focused on community–level delivery , promoted ORS through health worker communications and mass media, provided ORS free of charge in public sector and had secure supply of the product. Malawi and Bangladesh have historically had robust community– and household–level interventions that highlight the importance of interpersonal communications to increasing uptake of ORS, and ensuring availability in areas close to where people live. Malawi also utilized tracking mechanisms to reduce stock–outs, and Bangladesh had a sales force for private sector outreach. “Non–starter” countries generally lacked coordinated, sustained efforts to improve supply and demand, and efforts were reportedly hindered by poor country ownership and insufficient financing. For example, the ADDOs in Tanzania can extend the reach of drug shops to rural areas, but given the vast distances in the country, gaps remain for certain segments of the population. Both Madagascar and, more recently, Tanzania struggled to maintain product availability at public health facilities, which may have contributed to low ORS use in those countries.One of the most surprising findings was the importance of the context in which the scale–up efforts were implemented. The case studies show how clearly it played a role in the outcomes of scale–up efforts, and how there is no “one–size–fits–all” approach or program for ORS. The case study of Madagascar demonstrates how difficult it is to implement successful treatment programs when the health system is passing through a period of acute destabilization. This highlights the importance of fully understanding the risks of working in potential high–impact, volatile countries, where the need is great but the risk of program disruption is very high. However, we should note that many of the countries that we included in the case studies were relatively stable compared to Madagascar, so further studies to support or negate this hypothesis, and to better understand how to successfully operate in high–risk, high–need areas, will be critical moving forward.We identified four other findings that merit further investigation. First, ambiguous messaging about the relative value of ORS vs home–made sugar–salt solution can stifle ORS utilization. The definition of “oral rehydration therapy” changed four times within a decade , and mayWe found little information on the cost of scale–up efforts, primarily because this information has not historically been well–documented. We know that scale–up was done sustainably (and presumably affordably) in the five “successful” (>66% coverage) countries studied, and we have some anecdotal evidence from interviews and reports from major funders, but this is a gap in knowledge within the global community. To address this gap in future work, donors and governments would be wise to develop a rigorous monitoring and evaluation plan to track the impact of their investments and begin to improve our understanding of cost and sustainability.There are several important limitations of this study. These case studies were initially conceived to inform programmatic decisions for the Bill & Melinda Gates Foundation; we recognize that the methods used did not emphasize repeatability as strongly as they would have done had our initial purpose been to publish these results in an academic journal. However, as important results came to light through this work, sharing the findings through academic means seemed appropriate. We therefore urge other researchers to look again at these and similar experiences with a view to obtaining further policy–relevant findings on factors leading to successful ORS scale–up.As previously noted, ORS coverage rates in the 1980s were available for few countries, but have since improved with MICS and DHS [Finally, we relied on impressions from key informants, who undoubtedly had extensive knowledge of the historical contexts, the actors involved and the issues. We cannot rule out the potential reporting bias inherent in the role that the key informants or their organizations played in promoting ORS use. We did not maintain tape recorded interviews, as we suspected that key informants would not be as open to sharing their perceptions if they were being recorded. Although we developed one interview guide, given the semi–structured nature of the interviews interview questions were not completely standardized across countries.This study was an in–depth effort to objectively gather and compare the limited data available on the factors associated with successful and unsuccessful scale–up of ORS programs. We identified a number of characteristics of successful ORS scale–up programs, including involvement of a broad range of key players, addressing supply and demand generation together, and working with both public and private sectors. Failure to involve key partners will often result in major gaps in the scale–up plan and critically affect sustainability. We found that the cost of scale–up efforts has not historically been well–documented. There are implications for the way that future ORS scale–up efforts should be directed to avoid some of the mistakes of the past. Efforts must synchronize demand generation, private provider outreach and public sector work. Rigorous monitoring and evaluation plans to track program impacts should be developed to address the gap in knowledge within the global community and improve our understanding of cost and sustainability. Future studies revealing lessons from other country experiences could also contribute to efforts to scale–up access to ORS and ultimately improve the lives of children who benefit the most from these efforts.


New national standards for K–12 science education have been finalized and are set for release in spring 2013.In February 2013 the North Carolina Senate approved a bill that would lift the state’s moratorium on hydraulic fracturing (“fracking”) for oil and gas by 2015 and overturn a 40-year-old ban on underground injection of waste.A Belgian investigation of birth outcomes before, during, and after smoking bans found an association between implemention of such bans and lower rates of preterm birth.A study conducted near an Arizona Superfund site found that certain families of vegetables are especially effective at accumulating arsenic from soil, with the Asteraceae  and Brassicaceae  families of vegetables packing the most arsenic into their edible portions.In March 2013 the Minnesota Pollution Control Agency announced that within three months state agencies will no longer purchase hand, dish, or laundry soaps containing triclosan.


Accurate assessment of gestational age at birth is critical to the identification of neonates at high risk. In resource‐poor settings, postnatal techniques are commonly used but may be difficult to apply and have not been well validated against ultrasound in community studies. The aim of this study was to evaluate postnatal assessment of gestational age in rural Africa using the external criteria of the Ballard examination against 1st/early 2nd‐trimester ultrasound and date of last menstrual period.n = 80), the precision of gestational age estimates using the external Ballard examination was compared with those derived from 1st and early 2nd‐trimester ultrasound examination and date of last menstrual period.In a sample of women from Kiang West, The Gambia  of 15.6 (10.9) days compared with that derived from ultrasound and to underestimate by 15.4 (23.1) days compared with that derived from date of last menstrual period. The differences between the methods varied with gestation.In this rural, community‐born population of infants, postnatal assessment of gestational age by external Ballard examination performed poorly compared with ultrasound and last menstrual period. No reliable gestational age could be derived from its estimate and it failed to detect a significant proportion of high‐risk infants. The development of an accurate but simple method of postnatally assessing gestational age specifically for use by health workers in rural Africa is required. Many of the four million newborns who die each year, mostly in developing countries, are born prematurely, growth‐restricted or both.Sonographic determination of the estimated date of delivery (EDD), based on fetal growth parameters measured during a 1st or early 2nd‐trimester ultrasound scan (USS), is considered to be the ‘gold standard’ method of pregnancy dating but is seldom available in rural sub‐Saharan Africa. Clinical dating based on the last menstrual period (LMP) or measurement of fundal height is frequently inaccurate.An alternative, simplified postnatal scoring system was proposed by Ballard and has been further adapted.A simple postnatal examination to identify neonates at risk of fetal growth restriction or prematurity which is applicable at community level rather than in hospital would be of great benefit to health workers required to make clinical decisions about referral for limited but more specialised paediatric care.The aim of this study was to evaluate the utility of EBE performed by an experienced midwife in a rural African setting. The specific objective was to compare postnatal assessments of gestational age by EBE with those derived prenatally by USS.The study was conducted at the Medical Research Council's (MRC) station in Keneba, Kiang West, an isolated district of Lower River Division in The Gambia. Kiang West is a holo‐endemic malarial zone inhabited predominantly by ethnic Mandinka who typically exist as subsistence cultivators. Antenatal health care is provided by government nurse‐trekking teams in collaboration with the MRC.This method‐comparison study was nested within a randomised, controlled trial investigating the effect of periconceptual multi‐micronutrient supplementation on placental function in rural Gambian women  (ISRCTN 13687662); all data were collected as part of the existing protocol for that study. Postnatal GA assessments were derived from EBE performed by an experienced community midwife (SB) who was previously familiar with the Dubowitz technique and who had been trained in EBE. These were compared with GA assessments derived from 1st/early 2nd‐trimester ultrasound measurements performed by a trained clinician (SO), and from LMP. The midwife was blinded to the results derived from USS and LMP.All liveborn, singleton infants born between 1 May and 30 November 2007 with sonographically determined EDD and without major congenital anomalies were eligible for inclusion. Recruitment was opportunistic and not based on prior calculation of sample size.Dating USS was performed at antenatal booking visits when LMP was also recorded. All neonates were seen and assessed using EBE within 72 hours of birth.EBE scored neonates on the six observational, external criteria described in the full Ballard examination: skin appearance, presence of lanugo hair, plantar creases, breast tissue, ear formation, and external genitalia formation. The range of possible scores was ‐8 to 25. EBE scores were then doubled to account for the absence of neurological assessment, and GA extrapolated from the standardised Ballard scoring chart.6Training in EBE was provided by a paediatrician (SO). Data collection for the study did not begin until the EBE scores attributed by SB and SO on ten consecutive deliveries had achieved good correlation R = 0.7.GA by USS was derived from crown–rump length (CRL) measurements at less than 14 weeks gestation, and biparietal diameter (BPD) measurements at 14–24 weeks gestation using charts validated in African populations.GA by LMP was calculated from the dates given by pregnant women at booking. Neonates were classified as term (⩾37 weeks) or preterm (<37 weeks). SGA infants were defined as those with a birthweight below the 10th centile for gestation based on standardised charts.11After GA had been assessed, infants' weights were measured to the nearest 10 g using a spring balance.p<0.05.Data analysis was performed using Microsoft Excel and Graph Pad Prism . Data were entered using Microsoft Access database software. Bland–Altman plots were used to assess agreement of gestational age estimates.The study was approved by the MRC Scientific Coordinating Committee and by the Gambian Government Ethics Committee. Informed consent was obtained from all mothers at recruitment.A flowchart of subject recruitment is shown in The distribution of SGA diagnoses by EBE and USS is illustrated in p = 0.966, R2 = −0.013).Linear regression showed that the bias between EBE and USS assessments of GA was unrelated to birthweight.  in a rural West African population. We have demonstrated that GA assessments derived from EBE performed by a midwife compared poorly with those derived from the ‘gold standard’ of antenatal USS. We therefore conclude that EBE is not a reliable method of assessing GA in this resource‐poor community setting and other methods ought to be explored.To estimate the level of agreement between two GA assessments, Bland–Altman analysis was used to plot the difference between the methods against the average in order to give the bias. Correlation statistics were not used because they measure the strength of a linear association and not the level of agreement between two methods.12Using this technique, the mean bias between USS and EBE was 15.6 days with unacceptably wide limits of agreement. However, bias between the two methods increased significantly as GA increased, such that there was progressive underestimation of GA by EBE at 40 weeks gestation and beyond. Conversely, bias tended to decrease before 40 weeks. This finding is in keeping with the fact that EBE correctly identified the two infants who were born preterm but also incorrectly identified a further 18 term infants as preterm.et al. who found that when GA exceeded 270 days, LMP overestimated GA by a mean 12.7 days (literate women) and 18.8 days (illiterate women).et al. who obtained LMP data in fewer than 15% of cases.14EBE likewise underestimated GA derived from LMP by a mean 15.4 days and the bias increased as GA increased. This confirmed a previous study by Verhoeff The incidence of SGA defined by USS was high (35%) and confirms the previously described peak incidence of 31% in November, defined using the Dubowitz scoring.One of the significant problems with EBE is that one incorrect score shifts the calculated GA by 5.6 days as opposed to 1.8 days with Dubowitz, for example.et al. which consisted of infants delivered in a large urban hospital and which spanned a maximum GA range of 135–349 days, based on fundal height measurements.Infants in this study were born within a narrow range of gestational ages  with most infants born at or around term and there was a low incidence of prematurity (2.4%). Our population therefore contrasts with that described by Verhoeff The main weakness in this study is the use of a single operator to assess GA using EBE. It could be argued that the poor precision of the estimates was primarily a function of the examiner rather than the examination. However, the midwife chosen to carry out the measurements was experienced in assessing newborn infants and there was good correlation between the EBE scores calculated by himself and the paediatrician for ten infants assessed before the study commenced. The midwife in question might be considered typical of those working in rural community settings in many parts of West Africa. The findings in the current study were also supported by those in our previous analysis in which EBE compared poorly with Dubowitz.8Postnatal GA assessments were the focus of a great deal of attention in the 1970s, pre‐dating the advent of accurate sonographic dating. As developed countries move away from the use of such methods, their focus in the literature has dwindled; however, the need for accurate postnatal assessments in developing countries, particularly in rural settings, has not changed. Further validation of their applicability in the field is essential. While some investigators have been impressed by the correlation between Dubowitz and LMP5By assessing the use of EBE in the community, we have tested the applicability of a simplified method of postnatal GA assessment in a setting where the results are most relevant. Whilst we are able to comment only on its applicability across a narrow range of GA, EBE does not appear to be a suitable method for our population. If our findings are repeated, we would propose the development of a simplified postnatal scoring system, adapted for the African newborn, specifically for use by community health workers.