SPME-Based C_a‑History Method for Measuring SVOC Diffusion Coefficients in Clothing Material

Clothes play an important role in dermal exposure to indoor semivolatile organic compounds (SVOCs). The diffusion coefficient of SVOCs in clothing material (<i>D</i>_m) is essential for estimating SVOC sorption by clothing material and subsequent dermal exposure to SVOCs. However, few studies have reported the measured <i>D</i>_m for clothing materials. In this paper, we present the solid-phase microextraction (SPME) based C_a-history method. To the best of our knowledge, this is the first try to measure <i>D</i>_m with known relative standard deviation (RSD). A thin sealed chamber is formed by a circular ring and two pieces of flat SVOC source materials that are tightly covered by the targeted clothing materials. <i>D</i>_m is obtained by applying an SVOC mass transfer model in the chamber to the history of gas-phase SVOC concentrations (<i>C</i>_a) in the chamber measured by SPME. <i>D</i>_m’s of three SVOCs, di-iso-butyl phthalate (DiBP), di-<i>n</i>-butyl phthalate (DnBP), and tris­(1-chloro-2-propyl) phosphate (TCPP), in a cotton T-shirt can be obtained within 16 days, with RSD less than 3%. This study should prove useful for measuring SVOC <i>D</i>_m in various sink materials. Further studies are expected to facilitate application of this method and investigate the effects of temperature, relative humidity, and clothing material on <i>D</i>_m

Predicting Dermal Exposure to Gas-Phase Semivolatile Organic Compounds (SVOCs): A Further Study of SVOC Mass Transfer between Clothing and Skin Surface Lipids

Dermal exposure to indoor gas-phase semivolatile organic compounds (SVOCs) has recently received a great deal of attention, and this has included evaluating the role of clothing in this process. Several models have been developed to assess dermal exposure to SVOCs, based on the transient mass transfer of SVOCs from air to dermal capillaries. Assumptions of these models are either that clothing completely retards SVOC transport, or that there is an air gap of constant thickness between the clothing and the surface of the skin, which may lead to errors in the model calculations. To solve this problem, we tried to describe SVOC transport between clothing and epidermis by considering two parallel processes: partitioning of SVOCs by direct contact (ignored in existing models), and Fickian diffusion through the air gap. Predictions from the present model agree well with the experimental data found in the literature (dermal uptake of diethyl phthalate (DEP) and di-<i>n</i>-butyl phthalate (DnBP) of a clothed participant). This study provides a useful tool to accurately assess dermal exposure to indoor SVOCs, especially for evaluating the effects of clothing on dermal exposure

<i>C</i>_m‑History Method, a Novel Approach to Simultaneously Measure Source and Sink Parameters Important for Estimating Indoor Exposures to Phthalates

The concentration of a gas-phase semivolatile organic compound (SVOC) in equilibrium with its mass-fraction in the source material, <i>y</i>₀, and the coefficient for partitioning of an SVOC between clothing and air, <i>K</i>, are key parameters for estimating emission and subsequent dermal exposure to SVOCs. Most of the available methods for their determination depend on achieving steady-state in ventilated chambers. This can be time-consuming and of variable accuracy. Additionally, no existing method simultaneously determines <i>y</i>₀ and <i>K</i> in a single experiment. In this paper, we present a sealed-chamber method, using early-stage concentration measurements, to simultaneously determine <i>y</i>₀ and <i>K</i>. The measurement error for the method is analyzed, and the optimization of experimental parameters is explored. Using this method, <i>y</i>₀ for phthalates (DiBP, DnBP, and DEHP) emitted by two types of PVC flooring, coupled with <i>K</i> values for these phthalates partitioning between a cotton T-shirt and air, were measured at 25 and 32 °C (room and skin temperatures, respectively). The measured <i>y</i>₀ values agree well with results obtained by alternate methods. The changes of <i>y</i>₀ and <i>K</i> with temperature were used to approximate the changes in enthalpy, Δ<i><i>H</i></i>, associated with the relevant phase changes. We conclude with suggestions for further related research

Transient Method for Determining Indoor Chemical Concentrations Based on SPME: Model Development and Calibration

Solid-phase microextraction (SPME) is regarded as a nonexhaustive sampling technique with a smaller extraction volume and a shorter extraction time than traditional sampling techniques and is hence widely used. The SPME sampling process is affected by the convection or diffusion effect along the coating surface, but this factor has seldom been studied. This paper derives an analytical model to characterize SPME sampling for semivolatile organic compounds (SVOCs) as well as for volatile organic compounds (VOCs) by considering the surface mass transfer process. Using this model, the chemical concentrations in a sample matrix can be conveniently calculated. In addition, the model can be used to determine the characteristic parameters (partition coefficient and diffusion coefficient) for typical SPME chemical samplings (SPME calibration). Experiments using SPME samplings of two typical SVOCs, dibutyl phthalate (DBP) in sealed chamber and di­(2-ethylhexyl) phthalate (DEHP) in ventilated chamber, were performed to measure the two characteristic parameters. The experimental results demonstrated the effectiveness of the model and calibration method. Experimental data from the literature (VOCs sampled by SPME) were used to further validate the model. This study should prove useful for relatively rapid quantification of concentrations of different chemicals in various circumstances with SPME

Early-Stage Emissions of Formaldehyde and Volatile Organic Compounds from Building Materials: Model Development, Evaluation, and Applications

Emissions of formaldehyde and volatile organic compounds (VOCs) from building materials may result in poor indoor air quality. The emission process can be divided into three stages over time: early, transition, and equilibrium stages. In existing studies, mass transfer models without distinguishing the early and transition stages have been widely used for characterizing the formaldehyde/VOC emissions, with three key parameters involved in these models. Many methods have been proposed for determining these parameters by fitting the corresponding models to experimental data. However, multiple groups of best-fit parameters might coexist if experimental data are obtained at the early stage (to shorten the experimental time). Therefore, we developed a novel mass transfer model to describe the early-stage emissions by assuming the building material as semi-infinite medium. The novel model indicated that the early-stage emission was governed by only two parameters, instead of three parameters, which explained the reason for the multi-solution problem of existing methods. Subsequently, the application condition of the early-stage model was clarified, showing that the early stage was very common in the emissions of formaldehyde/VOCs. Finally, a novel approach for characterizing the emissions of formaldehyde/VOCs from building materials was proposed to eliminate the negative effects of the multi-solution problem

Phylogenetic analysis.

<p>18S rRNA sequences from the respective <i>Cryptosporidium</i> isolates identified were compared phylogenetically using the MEGA 4.1 software. The phylogenetic tree obtained demonstrates the genetic diversity of the <i>Cryptosporidium</i> genotype II isolates identified from stool samples from Shanghai (SH1–10) and Shaoxing (SX11–16). Analysis was based on the nested-PCR of the18S rRNA locus sequence using the tree method of Neighbor Joining.</p

Additional file 4: of Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice

Figure S1. The lncRNA NONMMUT021591 was predicted to cis-regulate the protein-coding gene Rb1. Red dots, genomic location of lncRNAs; blue dots, the corresponding genes; rho value, correlation coefficient. (TIF 13 kb

Additional file 2: of Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice

Table S2. Significantly and differentially expressed lncRNAs in M-MDSCs. (XLSX 49 kb

Equilibrium Relationship between SVOCs in PVC Products and the Air in Contact with the Product

Phthalates and phthalate alternatives are semivolatile organic compounds (SVOCs) present in many PVC products as plasticizers to enhance product performance. Knowledge of the mass-transfer parameters, including the equilibrium concentration in the air in contact with the product surface (<i>y</i>₀), will greatly improve the ability to estimate the emission rate of SVOCs from these products and to assess human exposure. The objective of this study was to measure <i>y</i>₀ for different PVC products and to evaluate its relationship with the material-phase concentrations (<i>C</i>₀). Also, <i>C</i>₀ and <i>y</i>₀ data from other sources were included, resulting in a substantially larger data set (<i>N</i>_total = 34, <i>T</i> = 25 °C) than found in previous studies. The results show that the material/gas equilibrium relationship does not follow Raoult’s law and that therefore the assumption of an ideal solution is invalid. Instead, Henry’s law applies, and the Henry’s law constant for all target SVOCs consists of the respective pure liquid vapor pressure and an activity coefficient γ, which accounts for the nonideal nature of the solution. For individual SVOCs, a simple partitioning relationship exists, but Henry’s law is more generally applicable and will be of greater value in rapid exposure assessment procedures

Additional file 3: of Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice

Table S3. Significantly and differentially expressed mRNAs in M-MDSCs. (XLSX 83 kb