Fluctuations in the interactions between pigments due to transitions in the TLS is the main dephasing pathway in glasses below 10 K. The TLS transitions can both influence the dipole interactions between the pigments (low frequency transitions in TLS corresponding to large https://www.selleckchem.com/products/MK-2206.html displacements in the protein) as well as the site energies (high frequency, smaller displacement). At low temperatures, the coherent energy transfer is mainly limited by this coupling. Above 10 K, the contribution of the TLS tunneling is of minor significance to the dephasing mechanism that are dominated by other processes. With

these measurements, the earlier results from a preliminary study by Louwe and Aartsma (1994) were confirmed. Table 13 Frequency-dependent accumulated photon echo decay times of Prosthecochloris aestuarii at 1.4 K (Louwe and Aartsma 1997) λmax of DASa (nm) Decay time (ps) 827 385 826 110 824 30 818 5 aDAS spectra originate from a global analysis were the amplitudes of the different

decay components are plotted against the AZD6738 solubility dmso wavelength resulting in distinct bands Several years later, interesting features were seen in low-temperature two-photon-echo (2PE) signals of both Chlorobium tepidum and Prosthecochloris aestuarii (Prokhorenko et al. 2002). At 1.27 K, the 2PE signals show oscillations that increase in intensity when the excitation is tuned to the red edge of the absorption spectrum (up to 40% of the total amplitude for excitation at 832 nm). These oscillations last up to 300 ps and are ascribed to vibrational states of the BChl a molecule in the ground state. Fourier transforms of the 2PE traces show that the obtained frequencies match those from previous studies (Savikhin et al. 1997). In the same study, it was shown that the general theory to describe the results of photon-echo experiments did not account for the current results. The typical δ shape for dynamics in the Markov limit at initial time delays was not observed. Therefore, the dynamics

were described beyond the Markov limit where system–bath memory effects occur which, among others, result in the delayed growing in of coherence in the system. At that time, it was unclear whether this had a specific function in light harvesting. Vulto et al. used a similar approach Liothyronine Sodium as was used previously by Louwe et al. in the simulation of the static spectra (see “Exciton nature of the BChl a excitations in the FMO protein” and “Coupling strengths, linewidth and exciton energies”); however, to introduce dynamics, coupling of the electronic excitations to the vibrational modes in the system was included (Vulto et al. 1999). Homogeneous broadening within the system was not incorporated in the model. Owing to the weak coupling, the exciton-vibrational coupling can be treated as a perturbative term in the Hamiltonian.

In this paper, we show that Eu silicate can be fabricated by optimizing the Eu2O3/Si multilayer nanostructure deposited on Si substrates. Both the structural and optical properties of nanostructures are studied in detail. Through precisely controlling the thickness of Eu2O3 and Si layer at nanometer scale, the Eu silicate with highly efficient room-temperature (RT) light emission associated to Eu2+ ions is obtained after annealing in N2 atmosphere.

Methods The Eu2O3 /Si multilayer films with five periods were grown on Si substrates at 400°C by RF magnetron sputtering. The thin films were deposited in 3.0-mTorr Ar atmosphere. The Eu2O3 layer and Si layer were prepared by alternately sputtering the Eu2O3 target and Si target. The thickness of Eu2O3 layers was kept the same in all samples, while the thickness of Si layers was varied in different samples, as shown in Table 1. After deposition, the samples were thermally treated at 1,000°C for 30 s in Caspase inhibitor N2 ambient by rapid thermal annealing. Transmission electron microscopy (TEM, Tecnai G2 F20 S-Twin, FEI Company, Hillsboro, OR, USA) was conducted to investigate the samples’ morphology. The distribution of elements selleck inhibitor in the film was detected by scanning TEM (STEM), and crystallization

was demonstrated by selected area electron diffraction pattern (SAED). Rutherford backscattering spectrometry (RBS) was carried out to investigate the film composition. The samples’ crystalline phases were identified by X-ray diffraction (XRD, D/max 2400, Rigaku Corporation, Tokyo, Japan) measurements. RT photoluminescence (PL) and photoluminescence excitation (PLE) measurements were performed by using a spectrofluorometer (Nano Log, HORIBA Ltd., Minami-Ku, Kyoto, Japan) equipped with a 450-W Xe lamp. Table 1 Eu 2 O 3 /Si multilayer structure Sample Thickness of Eu2O3layer (nm) Thickness of Si layer (nm) 1 5 8 2 5 17 3 5 25 4 5 42 Results and discussion The cross-sectional TEM images of as-deposited sample

GPX6 are shown in Figure 1a,b. The film thickness is about 150 nm, with 5 nm in the Eu2O3 layer and 25 nm in the Si layer in one period. The interface between Eu2O3 and Si is very sharp and clear. Moreover, multicrystalline Si has formed in Si layers in the as-deposited sample, which has also been confirmed by SAED, as shown in Figure 1c. The interplanar spacing (d) is about 3.11 Å from the radius of the primary diffraction ring, which agrees with the d of the Si (111) plane. We think that the high substrate temperature and the Eu2O3 layer may induce Si crystallization. Figure 1 Cross-sectional TEM images of as-deposited sample 3. (a) Full view of the film, (b) partial enlarged view of the film, and (c) the SAED image of the film. Figure 2a,b shows the TEM cross section of the sample with a Si layer thickness of about 25 nm after annealing at 1,000°C for 30 s in N2 ambient. The interfaces between Eu2O3 layers and Si layers became blurry. This indicates that the strong reaction between Eu2O3 and Si has happened.

In accordance with the Las bacterial titers, the amount of OTUs in Comamonadaceae significantly decreased in April 2011 when compared to the other sampling time points (October 2010 and October 2011); however, the amount of OTUs in the Enterobacteriaceae and Aquabacteriaceae families significantly increased. Figure 4 Operational taxonomic units (OTUs) for families detected by PhyloChip™ G3 hybridization of Huanglongbing (HLB)-affected citrus. The citrus plants were treated with different antibiotic combinations and leaf samples were collected at different times (October 2010, April 2011 and October 2011) over a year.

Proportions of OTUs for the Crizotinib nmr most highly represented families are represented over the sampling time points. The size of each block in the family abundance bar chart represents the number of detected OTUs in that family relative to the

total number of OTUs detected with the same treatment over the sampling time points. PS: 5 g/tree penicillin G potassium and 0.5 g/tree streptomycin; KO: 2 g/tree oxytetracycline and 1.0 g/tree kasugamycin; and CK: water as control. Specific OTUs associated with the antibiotic treatments and sampling time points Principal coordinate analysis (PCoA) based on the weighted Unifrac distances between samples was performed with PhyloChip community data sets, and the results suggested that there were significant differences among the treatments and the sampling time points. The 17 OTUs selected with filter-3, which includes selleck chemicals OTUs present in samples from one treatment but not detected in any click here samples of the other treatments, separated the antibiotic combinations (KO,

PS) and the control group (CK). There were eight OTUs (7444, 8217, 15010, 24693, 41872, 62344, 74687 and 77432) in the KO treatment, three in the PS treatment (24114, 40218 and 49638) and six in the water control (42278, 50217, 53352, 58803, 70400 and 75179). When compared with the Antibiotic Resistance Genes Database [22], three oxytetracycline-resistant bacteria (7444, 24693 and 72432) were found in the KO treatment (Table 1). No antibiotic-resistant bacteria were found in the PS treatment. Prediction analysis for microarrays (PAM) identified Bacillus OTU48007 within Firmicutes to have increased abundance in the control samples compared to the antibiotic treatments. A total of 118 OTUs with filter-5, based on abundance metrics, partitioned the samples into distinct groups corresponding to sampling time points. Using binary metrics, 344 OTUs selected with filter-5 were found in 100% of the samples from one time point and were consistently absent in other time point samples.

If all connections were produced by only carbon deposition, then electrical contact could not be obtained due to its high resistance. Therefore, a very thin carbon layer (ca. 100 nm thick) was deposited using the EB to minimize the resistance and prevent damage to the bismuth nanowire from the Ga ion beam irradiation during tungsten deposition. The thickness of the carbon deposition was determined by considering the resistance of carbon and the depth of Ga ion penetration (30 nm). It would be preferable that all electrical contacts

be composed of only tungsten deposition; however, the FIB-SEM apparatus that was utilized in this experiment could not deposit tungsten using the EB. Therefore, Copanlisib datasheet a combination of carbon and tungsten was utilized for the electrodes on the bismuth nanowire. The opposite side electrode was also fabricated using the same procedure, as shown in Figure 2f,k. Almost all of the bismuth nanowire was not irradiated with the Ga ion beam because the bismuth nanowire was

encapsulated within the quartz template. Finally, the electrodes https://www.selleckchem.com/products/VX-809.html were divided into two parts with a 2-μm-wide groove, as shown in Figure 2g, and all electrodes were divided into eight parts, as shown in Figure 2a. Figure 2 Schematic diagrams for FIB processing to fabricate Hall measurement electrodes on a 521-nm-diameter bismuth nanowire. (a) Overall view of the fabricated sample. (b-g) Procedure for the fabrication of electrodes by FIB. (h-k) Cross-sectional view during electrode fabrication. (l) 3-D view of processing with the dual-beam FIB-SEM. Figure 3a shows an optical micrograph of the sample after FIB processing. The Ti/Cu thin films on the quartz template are divided into eight-part electrodes by FIB processing. Figure 3b,c shows SEM images of the electrical connections that formed between the bismuth nanowire and Ti/Cu thin films using FIB. The pink diagonal lines in Figure 3b,c indicate the approximate position of the bismuth nanowire embedded in the quartz template. Both side surfaces of the bismuth nanowire were connected to Ti/Cu thin films on the quartz template

by tungsten deposition. The Ti/Cu thin films on the quartz template were divided by the groove formed using FIB to insulate each part. The connections 17-DMAG (Alvespimycin) HCl of all electrodes were tested using a digital multimeter, and the electrodes were confirmed to be successfully fabricated on the bismuth nanowire by FIB processing. The nanowire sample mounted on a Si wafer was fixed to an alumina plate (23 × 16 × 0.5 mm3) with an adhesive, and gold (Au) lead wires were attached to all electrodes using silver (Ag) epoxy, as shown in the inset of Figure 4h. Au wires were connected to the measurement system through electrodes on the alumina plate. The contacts of the electrodes on the nanowire were evaluated by measuring the relationship between the current passed and the voltage.

5Å resolution: architecture of a megadalton respiratory complex. Structure 14:1167–1177CrossRefPubMed Stahlberg H, Walz T (2008) Molecular electron microscopy: state of the art and current challenges. ACS Chem Biol 3:268–281CrossRefPubMed Stark H, Dube P, Lührmann R, Kastner B (2001) Arrangement of RNA and proteins in the spliceosomal particle. Nature 409:539–542CrossRefPubMed Unger V (2001) Electron cryomicroscopy methods. Curr Opin Struct Biol 11:548–554CrossRefPubMed Van Heel M, Gowen B, Matadeen R, Orlova EV, Finn R, Pape T, Cohen D, Stark H, Schmidt R, Schatz Lenvatinib order M, Patwardhan A (2000) Single-particle electron cryo-microscopy: towards atomic resolution. Q Rev Biophys

33:307–369CrossRefPubMed Yamaguchi M, Danev R, Nishiyama K, Sugawara K, Nagayama K (2008)

Zerike phase contrast electron microscopy of ice-embedded influenza A virus. Ultramicroscopy 162:271–276 Yeager M, Unger VM, Mitra AK (1999) Three-dimensional structure of membrane proteins determined by two-dimensional crystallization, electron cryomicropscopy, and image analysis. Methods Enzymol 294:135–180CrossRefPubMed Yeremenko N, Kouřil R, Ihalainen JA, D’Haene S, van Oosterwijk N, Andrizhiyevskaya EG, Keegstra W, Dekker HL, Hagemann M, Boekema EJ, Matthijs HCP, Dekker JP (2004) Supramolecular organization and dual function of the IsiA Metformin ic50 chlorophyll-binding protein in cyanobacteria. Biochemistry 43:10308–10313CrossRefPubMed Zhang X, Settembre E, Xu C, Dormitzer PR, Bellamy R, Harrison SC, Grigorieff N (2008) Near-atomic resolution using electron cryomicroscopy and single-particle reconstruction. Proc Natl Acad Sci USA 105:1867–1872CrossRefPubMed”
“Due to global warming and the limited resources of (fossil) fuels on Earth, it is highly important to gain a full understanding of all aspects of how biology utilizes solar energy. The field of photosynthesis research is very broad and comprises research at various levels—from eco-systems to isolated proteins. It begins with light capture, its conversion to chemical energy, leading to oxygen evolution, and carbon fixation. During almost 100 years of photosynthesis research, scientific “tools,” used in this research, have grown significantly

in number and complexity. In this very first of its kind educational special issue of Photosynthesis Research, we aim to give an overview about biophysical techniques currently Carnitine dehydrogenase employed in the field. With these biophysical methods, the structures of proteins and cofactors can be resolved, and kinetic and thermodynamic information on the processes can be obtained. All papers, no matter how complex the technique, are written by experts in the field in a way that we hope will be understood by students in biology, chemistry, and physics. In this way, these educational reviews are an important supplement to books in the field, which we recommend for more detailed information on the present topics [see, e.g., Biophysical Techniques in Photosynthesis, edited by J. Amesz and A. J.

These results are in contrast with results from strains Jor151 and Jor154 which also had α-glucosidase activity, but PCR results showed that gluB was present and not gluA, suggesting that the glucosidase activity of these strains was due solely to the expression of gluB. These results are also opposite to that for strain Jor204 which by PCR showed that its α-glucosidase activity was due to gluA and not gluB. Lastly, Strains Jor 26, Jor 100, Jor 103, Jor 109,

and Jor168 expressed no α-glucosidase HTS assay activity during growth on α-MUG or DFI yet produced typical chromogenic reactions on EsPM suggesting that these strain’s chromogenic activity on the latter medium was due to cellobiosidase activity or due to expression of sequence variants of α-glucosidase genes. The later outcome is the most probable reason for these conflicting results since all of these strains showed either α-glucosidase activity or palatinase activity by VITEK GN analysis (data not shown). These results support the finding by Iversen and Forsythe [2] that the chromogenic reaction of strains grown on DFI medium can be Smoothened Agonist in vivo misleading and that the new modified formulation of DFIA put forth by Iversen et

al [48] should alleviate the problems of strains producing atypical reactions on this medium. Table 6, depicts the characterization of the non Cronobacter spp. isolates. All the isolates were identified as putative Cronobacter spp. with API 20E biochemical profiling. However, chromogenic media (α-MUG and DFI) were negative for 8 isolates (Jor20A, Jor27, Jor45, Jor26 Jor100, Jor103, Jor109, and Jor168) while positive for the other 5 isolates (Jor115A, Jor115B, Jor51, Jor151 and Jor153B) and EsPM was negative for 6 samples and positive for 7 samples. These conflicting results stressed the inability of chromogenic methods Methane monooxygenase to provide a reliable test for confirming the

identity of the Cronobacter spp. isolates. Table 7 summarized the results obtained by the different methods used for the identification and confirmation of isolates and clearly highlights the inability of any single method to be used as a final confirmation method. Due to the above conflicting results, a final confirmation step was undertaken by sequencing the 16S rRNA gene of the isolates. As a result of final confirmation method only 29 isolates (Table 5) were confirmed as Cronobacter spp. while the other 13 isolates (Table 6) were confirmed as non-Cronobacter spp. The variation in the above results reflects the genetic heterogeneity among the Cronobacter spp. isolates and/or a high degree of similarity between Cronobacter spp. and some other closely related members of Enterobacteriaceae that tested positive with some of the confirmation tests as depicted in Table 6.

These results are consistent with correlation coefficients

(R 2 = 0.5–0.94) determined for the cross-manufacturer forearm DXA standardization effort commissioned by the International Committee of Standards in Bone Measurement [19] as well as with the results reported for similar algorithms developed for QCT [25]. True vBMD was less well correlated to aBMDdxa. This is not surprising given the size dependence inherent to projectional BMD measures. It follows that simulation of the projection process does significantly improve prediction of DXA-based BMD values. It is important to note that the standard VOI for a clinical HR-pQCT acquisition (9.02 mm in length) is shorter than the standard ultra-distal ROI prescribed by DXA manufacturers (20 and 15 mm in length for Lunar and Hologic, respectively). Furthermore, Dabrafenib price each manufacturer uses different anatomical landmarks to localize the ROI. These two facts may partly explain the discrepancy in the coefficients of determination for aBMDsim compared to Lunar and Hologic

(R 2 = 0.87 vs. R 2 = 0.82) and the difference in the regression intercept (0.04 vs. 0.11 g/cm2). As expected, the aBMDsim better predicted www.selleckchem.com/products/Gefitinib.html Lunar aBMDdxa values, where the ROI is more similar with respect to the longitudinal placement compared to the Hologic ROI. The difference in the correlation coefficients also likely reflects the relative variability in the patient cohorts scanned on either device. As expected, aBMDsim Erastin nmr and aBMDdxa of the UD radius were poor to moderate predictors of aBMD at axial skeletal sites (lumbar spine and proximal femur). Despite the significantly smaller analysis ROI, aBMDsim had an equivalent degree of predictive power for DXA aBMD in the lumbar spine and proximal femur. The magnitude of the predictive power for the Lunar cohort was

similar to previous studies comparing intersite BMD relations [26, 27]. This group spanned a larger age and BMD range, compared to the Hologic cohort, which was comprised exclusively of osteopenic women with a narrow range of aBMD values at axial skeletal sites. An important limitation is that this simulation technique is limited to anatomical sites that may be imaged by HR-pQCT. In this study, we have applied the technique to the distal radius, as this is a routine site for clinical densitometry and a common site of osteoporotic fracture (Colles’ fracture). This technique could also be applied to the distal tibia, which is routinely imaged during clinical HR-pQCT exams, and of interest as a load-bearing site. On the other hand, the proximal femur and lumbar spine—critical sites of osteoporotic fracture—are not accessible by HR-pQCT.

PubMedCrossRef 40. Grimson MJ, Barker

GC: A continuum model for the growth of bacterial colonies on a surface. J Phys A: Math Gen 1993, 26:5645–5654.CrossRef 41. Kreft JU, Booth G, Wimpenny JWT: BacSim, a simulator for individual-based modelling of bacterial colony growth. Microbiology 1998, 144:3275–3287.PubMedCrossRef 42. Panikov NS, Belova SE, Dorofeev AG: Nonlinearity in the growth of bacterial colonies: conditions and causes. Microbiology (Mikrobiologiya) 2002, 71:50–56. 43. Sekowska A, Masson JB, Celani A, Danchin A, Vergassola M: Repulsion and metabolic switches in the collective behavior of bacterial colonies. Biophys J 2009, 97:688–698.PubMedCrossRef selleckchem 44. Miyata S, Sasaki T: Asymptotic analysis of a chemotactic model of bacteria colonies. Math Biosci 2006, 201:184–194.PubMedCrossRef 45. Cho HJ, Jönsson H, Campbell K, Melke see more P, Williams JW, Jedynak B, Stevens AM, Groisman A, Levchenko A: Self-organization in high-density bacterial colonies: efficient crowd control. PLoS Biol 2007, 5:e302.PubMedCrossRef 46. Levine H, Ben-Jacob E: Physical schemata underlying biological pattern formation – examples, issues and strategies. Phys Biol 2004, 1:P14-P22.PubMedCrossRef 47. Pipe L, Grimson MJ: Spatial-temporal modelling of bacterial colony growth on solid media. Mol BioSyst 2008, 4:192–198.PubMedCrossRef 48. Odagiri K, Takatsuka K:

Threshold effect with stochastic fluctuation in bacteria-colony-like proliferation dynamics as analyzed through a comparative study of reaction-diffusion

equations and cellular automata. Phys Rev E 2009, 79:-026202. 49. Ayati BP: A structured-population model of Proteus mirabilis swarm-colony development. J Math Biol 2006, 52:93–114.PubMedCrossRef 50. Grammaticos B, Badoual M, Aubert M: An (almost) solvable model for bacterial pattern formation. Physica D 2007, 234:90–97.CrossRef 51. Arouh S: Analytic model for ring pattern formation by bacterial swarmers. Phys Rev E 2001, 63:031908.CrossRef 52. Python programming language – official website [http://​www.​python.​org] Authors’ contributions JC and IP contributed equally to the designing and performing the experiments and interpreting their results; FC developed the formal model and participated in writing the paper; AB participated in experiments and data interpretation and provided Guanylate cyclase 2C basic technical support; AM participated in study design and data interpretation and drafted the paper. All authors have read and approved the final manuscript.”
“Background Nitrogen is incorporated into glutamate and glutamine which form the major biosynthetic donors for all other nitrogen containing components in a cell. Glutamine is a source of nitrogen for the synthesis of purines, pyrimidines, a number of amino acids, glucosamine and ρ-benzoate, whereas glutamate provides nitrogen for most transaminases [1] and is responsible for 85% of nitrogenous compounds in a cell [2]. In most prokaryotes, there are two major routes for ammonium assimilation.

Expert Rev Cardiovasc GSI-IX solubility dmso Ther 2009, 9:373–379. 28. Haas NB, Lin X, Manola J, Pins M, Liu G, McDermott D, et al.: A phase II trial of doxorubicin and gemcitabine in renal cell carcinoma with sarcomatoid features: ECOG 8802. Med Oncol 2012, 29:761–767.PubMedCentralPubMedCrossRef 29. Yang Y, Padilla-Nash HM, Vira MA, Abu-Asab MS, Val D, Worrell R, et al.: The UOK 257 cell line: a novel model for studies of the human Birt-Hogg-Dube gene pathway. Cancer Genet Cytogenet 2008, 180:100–109.PubMedCentralPubMedCrossRef 30. Behrends C, Sowa ME, Gygi SP, Harper JW: Network organization of the human autophagy system. Nature 2010, 466:68–76.PubMedCentralPubMedCrossRef 31. Wu S, Wang X, Chen J,

Chen Y: Autophagy JNK inhibitor of cancer stem cells is involved with chemoresistance of colon cancer cells. Biochem Biophys Res Commun 2013, 434:898–903.PubMedCrossRef Competing interests The

authors declare that they have no competing interests. Authors’ contributions QZ and SHS performed the experiments. QZ, XBJ and GW designed the study. QZ and JDC performed data analysis. JDC and SS supervised the study. QZ, JDC, and GW wrote the manuscript. All authors read and approved the final manuscript.”
“Introduction Breast cancer is the most common cancer diagnosed in women. Although there were noteworthy advances in the early diagnosis and treatment during the past several decades, breast cancer still stands as the leading cause of cancer death in women worldwide [1, 2]. The underlying mechanism for breast cancer development and metastasis is far

from being completely understood. The high prevalence of this disease calls for Y 27632 more mechanistic insights for the development of new generation diagnostic and therapeutic strategies. Recently (after 2005), there is a growing interest in the roles of a new class of small non-coding RNAs, microRNAs (miRNAs) in breast cancer development [3, 4]. MicroRNAs are ubiquitously expressed small RNAs which exert negative regulatory effects on gene expression at a post-transcriptional level [5]. Given the fact that microRNAs theoretically target any mRNA, it is likely that microRNAs possess a very broad functional spectrum which includes cell cycle regulation, cell growth, apoptosis, cell differentiation and stress response [5–9]. Consistent with this notion, it is no surprise that microRNAs are extensively involved in human cancer development [10]. To date, there are over 1000 miRNAs that have been discovered in human, among which MiR-29 stands as one of the most intriguing miRNA families which may play pivotal roles in cancer biology [8, 11]. Composed of three mature members (MiR-29a, b and c), this family has been shown to be down-regulated in many different types of cancers and have been attributed predominantly tumor-suppressing properties.

7 μg/L).”
“Introduction Environmental tobacco smoke (ETS) is a widespread toxicant linked to approximately 4,000 cancer deaths per year in the US (United States, Public Health Service, Office of the Surgeon General 2006). ETS contains over 4,000 chemicals and 60 known carcinogens (IARC Working Group 2004). Polycyclic aromatic compounds (PAC) are a group of carcinogens found in ETS. When inhaled, Selleckchem Erlotinib these compounds are activated by phase I enzymes and can bind to DNA bases to form bulky products known as DNA adducts. DNA adducts can lead to mutations, which may disrupt normal cellular function and initiate carcinogenesis. Among active smokers,

individuals with higher adduct levels have an increased risk of developing lung cancer (Whyatt et al. 2000; Tang et al. 2001; Veglia et al. 2003). In addition, individuals who began smoking earlier in life have a higher disease rate; this is independent of whether they continue to smoke or stop smoking (Wiencke et al. 1999). Among adults who have never smoked, DNA adduct levels

are associated strongly with the development of lung cancer (Peluso et al. 2005). Children appear particularly susceptible to the genotoxic effects of ETS. Studies of mother–infant dyads have found higher DNA adduct levels in the newborns compared to the mothers despite a lower estimated exposure to ETS (Whyatt et al. 2001; Perera et this website al. 2004). As with many diseases, tobacco-related disorders are not equally distributed in humans. Despite lower levels of tobacco use, African American smokers suffer higher rates of lung cancer compared with White smokers (United States Department of Heath and Human Services 1998; Haiman et al. 2006). Even among lifetime non-smokers, African American women have a significantly higher lung cancer incidence than White women (Thun et al. 2006, 2008). These studies raise questions as to whether certain populations are more susceptible to the carcinogenic effects of tobacco or sustain exposures in excess of other groups. Weiserbs et al. reported a twofold higher level of DNA adducts among African Americans compared to White Americans and Latino Americans (Weiserbs et al. 2003). Among smokers, African

Americans have higher cotinine levels (nicotine metabolite) than Whites (Caraballo Ribonucleotide reductase et al. 1998; Benowitz et al. 1999, 2004; Ahijevych et al. 2002). There are also striking racial differences in cotinine among ETS-exposed children. In previous work, we demonstrated that African American children had higher levels of cotinine in their serum and hair than White children, despite similar levels of ETS exposure (Wilson et al. 2005, 2007). However, a few studies have tested for racial differences in DNA adducts among children adjusting carefully for ETS exposure. The factors that result in higher levels of ETS exposure within families are complex and not completely understood. Housing size and ventilation are known to impact children’s exposure to ETS, as measured by serum cotinine (Henschen et al.