Reproductive Parameters and Maternal Investment in Mandrills (Mandrillus sphinx)

We report on 14 years of reproductive data for semifree-ranging mandrills (Mandrillus sphinx) in Gabon, and we explore relationships between female rank, age and parity, and reproductive strategies. Most births (61% of 132) occurred during the wet season in Gabon, between January and March. Female rank and parity were unrelated to the timing of parturition. Gestation lengths average 175 days (SE = ±1 day; N = 61) and were similar irrespective of female rank, parity, or sex of offspring. Birth sex ratio did not differ significantly from unity (52% male), and was unrelated to maternal rank or parity. Stillbirths and neonatal mortality tended to be more common among lower-ranking females than among either mid-ranking or dominant females. Median age at first birth is 4.71 years, at a median body mass of 7.6 kg, ca 5 years before females attain their adult body mass (median 12 kg). Age at first reproduction is significantly correlated with dominance rank, with dominant females giving birth on average 1.3 years earlier than lower-ranking females do. Interbirth intervals (IBI) average 405 days (range 184–1159 days, N = 103), and are independent of the sex of the offspring. Infant death within 6 months shortened IBI to 305 days. Increasing age and parity are also associated with short IBI, as is higher rank. Maternal rank and parity appear to influence reproductive success in female mandrills, but there is no apparent differential maternal investment by sex.     

On meta-analytic assessment of surrogate outcomes

We discuss the strengths and weaknesses of the meta-analytic approach to estimating the effect of a new treatment on a true clinical outcome measure, T, from the effect of treatment on a surrogate response, S. The meta-analytic approach (see Daniels and Hughes (1997) 16, 1965-1982) uses data from a series of previous studies of interventions similar to the new treatment. The data are used to estimate relationships between summary measures of treatment effects on T and S that can be used to infer the magnitude of the effect of the new treatment on T from its effects on S. We extend the class of models to cover a broad range of applications in which the parameters define features of the marginal distribution of (T, S). We present a new bootstrap procedure to allow for the variability in estimating the distribution that governs the between-study variation. Ignoring this variability can lead to confidence intervals that are much too narrow. The meta-analytic approach relies on quite different data and assumptions than procedures that depend, for example, on the conditional independence, at the individual level, of treatment and T, given S (see Prentice (1989) 8, 431-440). Meta-analytic calculations in this paper can be used to determine whether a new study, based only on S, will yield estimates of the treatment effect on T that are precise enough to be useful. Compared to direct measurement on T, the meta-analytic approach has a number of limitations, including likely serious loss of precision and difficulties in defining the class of previous studies to be used to predict the effects on T for a new intervention.     

Computation of model-dependent tolerance bands for ambulatorily monitored blood pressure

The construction of time-specified reference limits requires systematic sampling in clinical health, particularly for those variables characterized by a circadian rhythm of large amplitude, as it is the case for blood pressure (BP). For the detection of false negatives, tolerance intervals (limits that will include at least a specified proportion of the population with a stated confidence) are important and should substitute when possible for prediction limits. We have previously described a nonparametric method for the computation of model-independent tolerance intervals that are constructed by first dividing the sampling range in several time spans in which no appreciable changes in population characteristics (namely, mean and variance) take place. The tolerance interval is then computed for each of the time spans. The limits thus computed, as well as results of any comparison of a given individual's profile against such tolerance intervals, are highly dependent on the sampling scheme of both the reference individuals and the test subject. To avoid this problem, we have developed an alternative method that allows the computation of model-dependent tolerance bands for hybrid time series. Assuming that a set X of longitudinal series monitored from a given group of reference individuals can be fitted with the same individual model, a population model C(X,t) can be also determined, as well as the deviation S(X,t) of each individual curve from the population model. The tolerance band will then have the form C(X,t) ± kS(X,t), where k is here estimated following a nonparametric approach based on bootstrap techniques. Alternatively, two different values of k can be estimated (for the lower and upper limits of the tolerance interval, respectively) in cases for which we cannot assume symmetry. The method is generally applicable for any population model describing the reference population (including the fit of multiple significant components, nonsinusoidal waveforms, and/or trends). The method was used to establish time-specified tolerance bands for time series of blood pressure monitored automatically in healthy individuals of both genders. Model-dependent intervals are preferred to the model-independent limits when reliance on a specified sampling rate needs to be avoided. These limits may serve for an objective and positive definition of health, for the screening and diagnosis of disease, and for gauging the subject's response to treatment. (Chronobiology International, 17(4), 567-582, 2000)     

Confidence bands for cumulative incidence curves under the additive risk model

In the context of competing risks, the cumulative incidence function is often used to summarize the cause-specific failure-time data. As an alternative to the proportional hazards model, the additive risk model is used to investigate covariate effects by specifying that the subject-specific hazard function is the sum of a baseline hazard function and a regression function of covariates. Based on such a formulation, we present an approach to constructing simultaneous confidence intervals for the cause-specific cumulative incidence function of patients with given risk factors. A melanoma data set is used for the purpose of illustration.     

Computational analysis of CFSE proliferation assay

CFSE based tracking of the lymphocyte proliferation using flow cytometry is a powerful experimental technique in immunology allowing for the tracing of labelled cell populations over time in terms of the number of divisions cells undergone. Interpretation and understanding of such population data can be greatly improved through the use of mathematical modelling. We apply a heterogenous linear compartmental model, described by a system of ordinary differential equations similar to those proposed by Kendall. This model allows division number-dependent rates of cell proliferation and death and describes the rate of changes in the numbers of cells having undergone j divisions. The experimental data set that we specifically analyze specifies the following characteristics of the kinetics of PHA-induced human T lymphocyte proliferation assay in vitroL (1) the total number of live cells, (2) the total number of dead but not disintegrated cells and (3) the number of cells divided j times. Following the maximum likelihood approach for data fitting, we estimate the model parameters which, in particular, present the CTL birth- and death rate “functions”. It is the first study of CFSE labelling data which convincingly shows that the lymphocyte proliferation and death both in vitro and in vivo are division number dependent. For the first time, the confidence in the estimated parameter values is analyzed by comparing three major methods: the technique based on the variance–covariance matrix, the profile-likelihood-based approach and the bootstrap technique. We compare results and performance of these methods with respect to their robustness and computational cost. We show that for evaluating mathematical models of differing complexity the information-theoretic approach, based upon indicators measuring the information loss for a particular model (Kullback–Leibler information), provides a consistent basis. We specifically discuss methodological and computational difficulties in parameter identification with CFSE data, e.g. the loss of confidence in the parameter estimates starting around the sixth division. Overall, our study suggests that the heterogeneity inherent in cell kinetics should be explicitly incorporated into the structure of mathematical models.      

Do rats time filled and empty intervals of equal duration differently?

The goal was to determine whether rats time filled and empty intervals of equal duration differently. Each of five rats was trained for 50 sessions on an instrumental appetitive head entry procedure in which food was available (primed) every 120 s. On "empty" cycles, 30s prior to the next food prime, a 0.5-s pulse of white noise was presented. On "filled" cycles, 30s prior to the next food prime, white noise came on and stayed on until food was delivered. The two types of cycles were presented with equal probability. The results showed that the rats timed both the food-to-food interval and the stimulus-to-food interval. A comparison of the response gradients on filled and empty cycles following stimulus presentation showed better temporal discrimination on filled cycles. The results were modeled using a Packet theory of timing, with a linear averaging rule to combine the temporal information provided by the stimulus and food. The model fits to the individual response gradients were evaluated with a Turing test.     

The presence of a paternal grandmother lengthens interbirth interval following the birth of a granddaughter in Krummhörn (18th and 19th centuries)

Because only daughters inherit the paternal X-chromosome, an asymmetry in adaptive investment decisions has been suggested for certain patrilineal kin. Namely, paternal grandmothers (PGMs) may favor a granddaughter over a grandson, because (within the limits of paternity uncertainty) the former definitely carries one of their X-chromosomes, while the latter definitely does not. Here, we test the hypothesis that the PGMs' sex-specific favoritism influences reproductive scheduling. Using family-reconstitution data, we analyzed interbirth intervals (IBIs) in the historical population from the Krummhörn (Ostfriesland, Germany). In order to account for potentially timevarying effects on IBIs we applied (and combined) both the additive hazards regression of Aalen and the Cox proportional hazards model. We found that the presence of the PGM but not that of the maternal grandmother (MGM), correlates with the IBI following the birth of a grandchild as a function of the grandchild's sex. Specifically, in the presence of a PGM, the IBIs following the birth of a granddaughter are longer than in her absence. However, contrary to predictions from theoretical life history framework, model estimates for a PGM's effect on a mother's IBI did not significantly vary over time This study supports the hypothesis that PGM behavior differs according to her grandchild's sex. Further research should now explore the biological mechanism underlying this phenomenon.     

Association of glutathione S-transferase M1/T1 polymorphisms with susceptibility to vitiligo

Background

Some studies suggested that Glutathione S-transferases M1/T1(GSTM1/T1) null polymorphisms may be associated with the risk of vitiligo.

Aims

The purpose of this study is to further evaluate the association between GSTM1/T1 null polymorphisms and the susceptibility to vitiligo.

Methods

We carried out a retrieval of studies in the databases. Odds ratios (OR) and 95% confidence intervals (95% CIs) were used to assess the strength of this association. We analyzed the data using Stata 11.0.

Results

Six case–control studies including 1358 cases and 1673 controls were included in this meta-analysis. Our overall results showed the GSTM1 or GSTT1 null polymorphism was associated with vitiligo (GSTM1:OR = 1.59, 95% CI: 1.21–2.08, P = 0.001; GSTT1: OR = 1.30, 95% CI: 1.12–1.51, P = 0.001). In the subgroup analysis, the GSTM1 null polymorphism might be a genetic risk factor to vitiligo in East Asian (OR = 1.71, 95% CI: 1.12–2.63, P = 0.014) but not in the Mediterranean, however individuals with the GSTT1 null polymorphism in the Mediterranean (OR = 1.76, 95% CI: 1.15–2.71, P = 0.010) but not in East Asian have a greater predisposition to vitiligo. In addition there was also a significant trend toward an association with the combination of the GSTM1 null and GSTT1 null in either East Asians or Mediterraneans.

Conclusion

The GSTM1/T1 null polymorphisms may be associated with vitiligo. More studies are needed to confirm this conclusion.     

The XRCC1 Arg280His polymorphism contributes to cancer susceptibility: an update by meta-analysis of 53 individual studies

The X-ray repair cross-complementing group 1 (XRCC1) protein plays a central role in DNA repair pathways. Epidemiological studies have revealed the association between XRCC1 Arg280His polymorphism and cancer risk, but the results were inconsistent. We conducted this meta-analysis to assess the effect of XRCC1 Arg280His polymorphism on cancer susceptibility with accumulated data. Up to January 2012, 53 case‐control studies with 21,349 cases and 23,649 controls were available for our study. Summary odds ratios (OR) and corresponding 95% confidence intervals (CIs) for XRCC1 Arg280His polymorphism and cancer were estimated using fixed‐ or random-effects models when appropriate. Our meta-analysis identified that elevated cancer risk was statistically associated with the minor variant His allele and Arg–His/His–His genotypes both in the overall population (allele comparison, His versus Arg: OR = 1.16; 95% CI: 1.08–1.25; dominant comparison, Arg–His/His–His versus Arg–Arg: OR = 1.17; 95% CI: 1.08–1.27) and in terms of subgroup analyses by ethnicity for both Caucasians and non‐Caucasians. However, no significant result was observed in the stratified analysis by cancer type. Moreover, significantly increased cancer risk was observed in smokers. These findings indicated that XRCC1 Arg280His polymorphism may play a role in cancer development.     

Association between interleukin-10 promoter polymorphisms and endometriosis: A meta-analysis

To investigate the influence of the interleukin-10 gene promoter polymorphisms on the susceptibility of endometriosis, we examined the association by performing a meta-analysis. The PubMed, Embase, HuGE Navigator and CNKI were searched to identify eligible studies. We then conducted a meta-analysis to examine the association between interleukin-10 gene promoter polymorphisms and endometriosis. Eight case–control studies which examined the association between the IL-10 gene promoter polymorphisms and the susceptibility to endometriosis were finally included in the meta-analysis. Meta-analysis of the IL-10 − 592 A/C polymorphisms showed a significant increased risk of endometriosis in the overall and Asian population in all genetic models and allele contrast. However, meta-analysis of the IL-10 − 1082 A/G and IL-10 − 819 T/C polymorphisms showed no association with endometriosis in all genetic models and allele contrast in the overall and Asian population samples. In addition, there was not a significant association between the IL-10 − 592 A/C gene promoter polymorphisms with the severity of endometriosis.