Iodine dynamics in soils

We investigated changes in iodine (129I) solubility and speciation in nine soils with contrasting properties (pH, Fe/Mn oxides, organic carbon and iodine contents), incubated for nine months at 10 and 20 °C. The rate of 129I sorption was greater in soils with large organic carbon contents (%SOC), low pH and at higher temperatures. Loss of iodide (I−) from solution was extremely rapid, apparently reaching completion over minutes–hours; iodate () loss from solution was slower, typically occurring over hours–days. In all soils an apparently instantaneous sorption reaction was followed by a slower sorption process for . For iodide a faster overall reaction meant that discrimination between the two processes was less clear. Instantaneous sorption of was greater in soils with high Fe/Mn oxide content, low pH and low SOC content, whereas the rate of time-dependent sorption was greatest in soils with higher SOC contents. Phosphate extraction (0.15 M KH2PO4) of soils, ∼100 h after 129I spike addition, indicated that concentrations of sorbed inorganic iodine (129I) were very low in all soils suggesting that inorganic iodine adsorption onto oxide phases has little impact on the rate of iodine assimilation into humus. Transformation of dissolved inorganic 129 and 129I− to sorbed organic forms was modelled using a range of reaction- and diffusion-based approaches. Irreversible and reversible first order kinetic models, and a spherical diffusion model, adequately described the kinetics of both and I− loss from the soil solution but required inclusion of a distribution coefficient (kd) to allow for instantaneous adsorption. A spherical diffusion model was also collectively parameterised for all the soils studied by using pH, soil organic carbon concentration and combined Fe + Mn oxide content as determinants of the model parameters (kd and D/r2). The kinetic model parameters were not directly related to a single soil parameter; inclusion of pH, SOC, oxide content and temperature was necessary to describe the observed behaviour. From the temperature-dependence of the sorption data the activation energy (Ea) for 129 transformation to organic forms was estimated to be ∼43 kJ mol−1. The Ea value was independent of %SOC and was consistent with a reaction mechanism slower than pore diffusion or physical adsorption, but faster than most surface reactions

Differential gene expression of activating Fcγ receptor classifies active tuberculosis regardless of human immunodeficiency virus status or ethnicity.

New diagnostics and vaccines for tuberculosis (TB) are urgently needed, but require an understanding of the requirements for protection from/susceptibility to TB. Previous studies have used unbiased approaches to determine gene signatures in single-site populations. The present study utilized a targeted approach, reverse transcriptase multiplex ligation-dependent probe amplification (RT-MLPA), to validate these genes in a multisite study. We analysed ex vivo whole blood RNA from a total of 523 participants across four sub-Saharan countries (Ethiopia, Malawi, South Africa, and The Gambia) with differences in TB and human immunodeficiency virus (HIV) status. We found a number of genes that were expressed at significantly lower levels in participants with active disease than in those with latent TB infection (LTBI), with restoration following successful TB treatment. The most consistent classifier of active disease was FCGR1A (high-affinity IgG Fc receptor 1 (CD64)), which was the only marker expressed at significantly higher levels in participants with active TB than in those with LTBI before treatment regardless of HIV status or genetic background. This is the first study to identify a biomarker for TB that is not affected by HIV status or geo-genetic differences. These data provide valuable clues for understanding TB pathogenesis, and also provide a proof-of-concept for the use of RT-MLPA in rapid and inexpensive validation of unbiased gene expression findings

Reconstructing susceptible and recruitment dynamics from measles epidemic data

Dynamical epidemic studies are often based on the reported number of cases. For various purposes it would be helpful to have information about the numbers of susceptibles, but these data are rarely available. We show that under general theoretical assumptions it is possible to reconstruct, up to linear scaling parameters, the dynamics of the susceptible class, as well as the rate of recruitment to the susceptible class, based only on case report data. We demonstrate that susceptible data reconstructed by our method improve the performance of forecasting models. Our estimate of susceptible class dynamics also can be used to estimate the age distribution of recruitment into the susceptible class, if the birth rate is known from independent data. Simulation experiments show that the reconstruction is robust to errors in the reporting scheme. This work was motivated by measles in large developed-world cities prior to immunization programs; our theoretical assumptions are empirically justified for measles but should also be applicable to some other diseases with permanent immunity.Mathematical epidemiology, measles, susceptibility, forecasting, modeling,