Polychlorinated biphenyls (PCBs) are legacy pollutants that exert toxicities through various mechanisms. In the recent years exposure to PCBs via inhalation has been recognized as a hazard. Those PCBs with lower numbers of chlorine atoms (LC-PCBs) are semi-volatile, and have been reported in the urban air, as well as in the indoor air of older buildings. LC-PCBs are bioactivated to phenols and further to quinone electrophiles with genotoxic/carcinogenic potential. We hypothesized that phenolic LC-PCBs are subject to conjugation and excretion in the urine. PCB3, often present in high concentrations in air, is a prototypical congener for the study of the metabolism and toxicity of LC-PCBs. Our objective was to identify metabolites of PCB3 in urine that could be potentially employed in the estimation of exposure to LC-PCBs. Male Sprague Dawley rats (150–175 g) were housed in metabolism cages and received a single intraperitoneal injection of 600 µmol/kg body weight of PCB3. Urine was collected every four hours; rats were euthanized at 36 h and serum was collected. LC-MS analysis of urine before and after incubation with β-glucuronidase and sulfatase showed that sulfate conjugates were in higher concentrations than glucuronide conjugates and free phenolic forms. At least two major metabolites, and two minor metabolites were identified in urine that could be attributed to mercapturic acid metabolites of PCB3. Quantitation by authentic standards confirmed that approximately 3% of the dose was excreted in the urine as sulfates over 36 hours; with peak excretion occurring at 10–20 h after exposure. The major metabolites were 4’PCB3 sulfate, 3’PCB3 sulfate, 2’PCB3 sulfate, and presumably a catechol sulfate. The serum concentration of 4’PCB3 sulfate was 6.18±2.16 µg/mL. This is the first report that sulfated metabolites of PCBs are formed in vivo. These findings suggest a prospective approach for exposure assessment of LC- PCBs by analysis of phase II metabolites in urine.

Nanoscale metal–organic frameworks (nMOF) materials represent an attractive tool for various biomedical applications. Due to the chemical versatility, enormous porosity, and tunable degradability of nMOFs, they have been adopted as carriers for delivery of imaging and/or therapeutic cargos. However, the relatively low stability of most nMOFs has limited practical in vivo applications. Here we report the production and characterization of an intrinsically radioactive UiO-66 nMOF (89Zr-UiO-66) with incorporation of positron-emitting isotope zirconium-89 (89Zr). 89Zr-UiO-66 was further functionalized with pyrene-derived polyethylene glycol (Py–PGA-PEG) and conjugated with a peptide ligand (F3) to nucleolin for targeting of triple-negative breast tumors. Doxorubicin (DOX) was loaded onto UiO-66 with a relatively high loading capacity (1 mg DOX/mg UiO-66) and served as both a therapeutic cargo and a fluorescence visualizer in this study. Functionalized 89Zr-UiO-66 demonstrated strong radiochemical and material stability in different biological media. Based on the findings from cellular targeting and in vivo positron emission tomography (PET) imaging, we can conclude that 89Zr-UiO-66/Py–PGA-PEG-F3 can serve as an image-guidable, tumor-selective cargo delivery nanoplatform. In addition, toxicity evaluation confirmed that properly PEGylated UiO-66 did not impose acute or chronic toxicity to the test subjects. With selective targeting of nucleolin on both tumor vasculature and tumor cells, this intrinsically radioactive nMOF can find broad application in cancer theranostics.

Background: The displacement of l-thyroxine (T4) from binding sites on transthyretin (TTR) is considered a significant contributing mechanism in polychlorinated biphenyl (PCB)-induced thyroid disruption. Previous research has discovered hydroxylated PCB metabolites (OH-PCBs) as high-affinity ligands for TTR, but the binding potential of conjugated PCB metabolites such as PCB sulfates has not been explored.Objectives: We evaluated the binding of five lower-chlorinated PCB sulfates to human TTR and compared their binding characteristics to those determined for their OH-PCB precursors and for T4.Methods: We used fluorescence probe displacement studies and molecular docking simulations to characterize the binding of PCB sulfates to TTR. The stability of PCB sulfates and the reversibility of these interactions were characterized by HPLC analysis of PCB sulfates after their binding to TTR. The ability of OH-PCBs to serve as substrates for human cytosolic sulfotransferase 1A1 (hSULT1A1) was assessed by OH-PCB–dependent formation of adenosine-3´,5´-diphosphate, an end product of the sulfation reaction.Results: All five PCB sulfates were able to bind to the high-affinity binding site of TTR with equilibrium dissociation constants (Kd values) in the low nanomolar range (4.8–16.8 nM), similar to that observed for T4 (4.7 nM). Docking simulations provided corroborating evidence for these binding interactions and indicated multiple high-affinity modes of binding. All OH-PCB precursors for these sulfates were found to be substrates for hSULT1A1.Conclusions: Our findings show that PCB sulfates are high-affinity ligands for human TTR and therefore indicate, for the first time, a potential relevance for these metabolites in PCB-induced thyroid disruption.

Aromatic organosulfates are identified and quantified in fine particulate matter (PM2.5) from Lahore, Pakistan, Godavari, Nepal, and Pasadena, California. To support detection and quantification, authentic standards of phenyl sulfate, benzyl sulfate, 3-and 4-methylphenyl sulfate and 2-, 3-, and 4-methylbenzyl sulfate were synthesized. Authentic standards and aerosol samples were analyzed by ultra-performance liquid chromatography (UPLC) coupled to negative electrospray ionization (ESI) quadrupole time-of-flight (ToF) mass spectrometry. Benzyl sulfate was present in all three locations at concentrations ranging from 4 – 90 pg m−3. Phenyl sulfate, methylphenyl sulfates and methylbenzyl sulfates were observed intermittently with abundances of 4 pg m−3, 2-31 pg m−3, 109 pg m−3, respectively. Characteristic fragment ions of aromatic organosulfates include the sulfite radical (•SO3−, m/z 80) and the sulfate radical (•SO4−,m/z 96). Instrumental response factors of phenyl and benzyl sulfates varied by a factor of 4.3, indicating that structurally-similar organosulfates may have significantly different instrumental responses and highlighting the need to develop authentic standards for absolute quantitation organosulfates. In an effort to better understand the sources of aromatic organosulfates to the atmosphere, chamber experiments with the precursor toluene were conducted under conditions that form biogenic organosulfates. Aromatic organosulfates were not detected in the chamber samples, suggesting that they form through different pathways, have different precursors (e.g. naphthalene or methylnaphthalene), or are emitted from primary sources.

This paper introduces Prec‐DWARF (Precipitation Downscaling With Adaptable Random Forests), a novel machine‐learning based method for statistical downscaling of precipitation. Prec‐DWARF sets up a nonlinear relationship between precipitation at fine resolution and covariates at coarse/fine resolution, based on the advanced binary tree method known as Random Forests (RF). In addition to a single RF, we also consider a more advanced implementation based on two independent RFs which yield better results for extreme precipitation. Hourly gauge‐radar precipitation data at 0.125° from NLDAS‐2 are used to conduct synthetic experiments with different spatial resolutions (0.25°, 0.5°, and 1°). Quantitative evaluation of these experiments demonstrates that Prec‐DWARF consistently outperforms the baseline (i.e., bilinear interpolation in this case) and can reasonably reproduce the spatial and temporal patterns, occurrence and distribution of observed precipitation fields. However, Prec‐DWARF with a single RF significantly underestimates precipitation extremes and often cannot correctly recover the fine‐scale spatial structure, especially for the 1° experiments. Prec‐DWARF with a double RF exhibits improvement in the simulation of extreme precipitation as well as its spatial and temporal structures, but variogram analyses show that the spatial and temporal variability of the downscaled fields are still strongly underestimated. Covariate importance analysis shows that the most important predictors for the downscaling are the coarse‐scale precipitation values over adjacent grid cells as well as the distance to the closest dry grid cell (i.e., the dry drift). The encouraging results demonstrate the potential of Prec‐DWARF and machine‐learning based techniques in general for the statistical downscaling of precipitation.

This study assessed the uncertainty in estimating long-term (1971-2010) mean precipitation, its inter-annual variability, and linear trend of three network observation datasets over West Africa. A reference data, defined as a multi-dataset ensemble of precipitation observations of the Climate Research Unit (CRU) of the University of East Anglia, the Global Precipitation Climatology Centre (GPCC) and the University of Delaware (UDEL), all at horizontal resolutions of 0.5 ° by 0.5 ° were obtained and used in this study. Uncertainties in these climatological parameters of precipitation at both annual and seasonal time scales were examined in terms of inter-dataset variability using signal-to-noise ratio (SNR), correlation, root-mean-square errors and the normalised standard deviation. Results showed that the mean, inter-annual variability and trends climatology varied for different datasets. The three datasets had good agreement (SNR>5) in terms of the annual mean precipitation and its inter-annual variability in most parts of West Africa. However, the agreement between the datasets was poor in the very dry Sahel parts of northern Niger, Mali, and Mauritania (SNR ≤ 1) due to very little precipitation and possibility of relatively low station density in these regions of complex terrain. In terms of correlation (0.89 ≤ r ≤ 0.98), and normalised standard deviation, NSD (0.8 ≤ NSD ≤ 1.7), the uncertainties in the spatial variations in linear trend were larger than mean precipitation and their inter-annual variability for both annual and seasonal scales. The long-term annual precipitation trend in the region is highly uncertain except in a few small areas. observational errors are much more problematic, because their effects become relatively more pronounced as greater numbers of observations are aggregated. In this case, the author believed that averaging observations together from many different instruments/sources would tend to reduce the contribution of systematic observational errors to the uncertainty of the average. A number of researchers and institutions have developed observation-based gridded analysis datasets of global or regional coverage with fine spatial resolutions [8-14]. These network of observation datasets provide precipitation and/or surface air temperatures over extended periods of multiple decades at spatial resolutions of 0.5 ° or finer. This is, of course, a substantial improvement over previous generation data sets that are typically at much coarser (e.g. 2.5 °) horizontal resolutions [15]. These recent fine-scale datasets allow us to better examine the regional precipitation and temperature climatology and to perform more reliable evaluations of today's high-resolution climate simulations, especially over the regions of complex terrain, that are important for climate-change impact assessments and climate model evaluations [16].

Background-Atherosclerosis is a complex disease requiring improvements in diagnostic techniques and therapeutic treatments. Both improvements will be facilitated by greater exploration of the biology of atherosclerotic plaque. To this end, we carried out large-scale gene expression analysis of human atherosclerotic lesions. Methods and Results-Whole genome expression analysis of 101 plaques from patients with peripheral artery disease identified a robust gene signature (1514 genes) that is dominated by processes related to Toll-like receptor signaling, T-cell activation, cholesterol efflux, oxidative stress response, inflammatory cytokine production, vasoconstriction, and lysosomal activity. Further analysis of gene expression in microdissected carotid plaque samples revealed that this signature is differentially expressed in macrophage-rich and smooth muscle cell-containing regions. A quantitative PCR gene expression panel and inflammatory composite score were developed on the basis of the atherosclerotic plaque gene signature. When applied to serial sections of carotid plaque, the inflammatory composite score was observed to correlate with histological and morphological features related to plaque vulnerability. Conclusions-The robust mRNA expression signature identified in the present report is associated with pathological features of vulnerable atherosclerotic plaque and may be useful as a source of biomarkers and targets of novel antiatherosclerotic therapies. (Circ Cardiovasc Genet. 2011;4:595-604.)Key Words: plaque Ⅲ macrophage Ⅲ smooth muscle cell Ⅲ correlation Ⅲ coexpression A therosclerosis and its clinical sequelae, coronary heart disease, stroke, and peripheral vascular disease, represent significant medical problems. In the United States, approximately 13 million patients have diagnosed coronary heart disease, and almost 800 000 deaths in 2007 were due to cardiovascular disease or its complications. 1 Despite recent advances in pharmacological intervention, identification and prevention of processes leading to atherosclerotic plaque rupture remain incomplete. Understanding the molecular mechanisms that drive this process is a critical step toward development of therapies to slow or reverse progression of atherosclerosis. Clinical Perspective on p 604Currently, few validated targets are available for pharmacological treatment of atherosclerosis, and a limited number of diagnostic techniques can accurately predict either plaque progression or response to treatment. Gene expression microarray technology and systems biology allow comprehensive characterization of the pathological processes associated with atherosclerosis, making possible the identification of new targets to treat this disease and new diagnostic measures of disease progression. 2 To understand the underlying disease pathophysiology and gain insights into plaque biology that could facilitate the discovery of new therapies, we have undertaken gene expression profiling of human plaque. Because of its availability and documented similarity ...

Background-Recent successes in the treatment of in-stent restenosis (ISR) by drug-eluting stents belie the challenges still faced in certain lesions and patient groups. We analyzed human coronary atheroma in de novo and restenotic disease to identify targets of therapy that might avoid these limitations. Methods and Results-We recruited 89 patients who underwent coronary atherectomy for de novo atherosclerosis (nϭ55) or in-stent restenosis (ISR) of a bare metal stent (nϭ34). Samples were fixed for histology, and gene expression was assessed with a dual-dye 22 000 oligonucleotide microarray. Histological analysis revealed significantly greater cellularity and significantly fewer inflammatory infiltrates and lipid pools in the ISR group. Gene ontology analysis demonstrated the prominence of cell proliferation programs in ISR and inflammation/immune programs in de novo restenosis. Network analysis, which combines semantic mining of the published literature with the expression signature of ISR, revealed gene expression modules suggested as candidates for selective inhibition of restenotic disease. Two modules are presented in more detail, the procollagen type 1 ␣2 gene and the ADAM17/tumor necrosis factor-␣ converting enzyme gene. We tested our contention that this method is capable of identifying successful targets of therapy by comparing mean significance scores for networks generated from subsets of the published literature containing the terms "sirolimus" or "paclitaxel." In addition, we generated 2 large networks with sirolimus and paclitaxel at their centers. Both analyses revealed higher mean values for sirolimus, suggesting that this agent has a broader suppressive action against ISR than paclitaxel. Conclusions-Comprehensive