Diagnostic significance of CK19, TG, Ki67 and galectin-3 expression for papillary thyroid carcinoma in the northeastern region of China

<p>Abstract</p> <p>Background</p> <p>To evaluate the expression and differential diagnostic significance of CK19, TG, Ki67 and galectin-3 in papillary thyroid carcinoma (PTC) (metastatic and non metastatic), follicular adenoma and nodular goiter in patients from the northeastern part of China.</p> <p>Methods</p> <p>441 PTC specimens and 151 other benign thyroid specimens (97 cases of nodular goiter, 54 cases of nonmalignant follicular adenoma) were collected. Immunohistochemistry for CK19, TG, Ki67 and galectin-3 was performed.</p> <p>Results</p> <p>CK19, TG, Ki67 and galectin-3 expression was 96.37% (425/441), 82.77% (365/441), and 40.59% (179/441), 96.82% (427/441), respectively, for the PTC group and the expression of these markers in the benign thyroid lesions group was 25.83% (39/151), 79.47% (120/151), and 37.09% (56/151), 50.99% (77/151), respectively. The expression of CK19 and galectin-3 in PTC was much higher than that in the nonmalignant group (p < 0.05). However, the expression of TG, Ki67 did not differ among these two groups (p > 0.05). The diagnostic efficiency of CK19 and galectin-3 for PTC was 96.37% (537/592) and 84.63% (501/592). CK19 and galectin-3 expression rate in PTC was higher than that in benign disease cases.</p> <p>Conclusions</p> <p>The diagnostic efficiency of CK19 for PTC was slightly better than galectin-3. The utilization of these markers combined with morphologic evaluation may be helpful in the differential diagnosis of papillary thyroid carcinoma in the northeastern region of China.</p

Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions

In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean

Qualitative and Quantitative Detection of Chlamydophila pneumoniae DNA in Cerebrospinal Fluid from Multiple Sclerosis Patients and Controls

A standardized molecular test for the detection of Chlamydophila pneumoniae DNA in cerebrospinal fluid (CSF) would assist the further assessment of the association of C. pneumoniae with multiple sclerosis (MS). We developed and validated a qualitative colorimetric microtiter plate-based PCR assay (PCR-EIA) and a real-time quantitative PCR assay (TaqMan) for detection of C. pneumoniae DNA in CSF specimens from MS patients and controls. Compared to a touchdown nested-PCR assay, the sensitivity, specificity, and concordance of the PCR-EIA assay were 88.5%, 93.2%, and 90.5%, respectively, on a total of 137 CSF specimens. PCR-EIA presented a significantly higher sensitivity in MS patients (p = 0.008) and a higher specificity in other neurological diseases (p = 0.018). Test reproducibility of the PCR-EIA assay was statistically related to the volumes of extract DNA included in the test (p = 0.033); a high volume, which was equivalent to 100 µl of CSF per reaction, yielded a concordance of 96.8% between two medical technologists running the test at different times. The TaqMan quantitative PCR assay detected 26 of 63 (41.3%) of positive CSF specimens that tested positive by both PCR-EIA and nested-PCR qualitative assays. None of the CSF specimens that were negative by the two qualitative PCR methods were detected by the TaqMan quantitative PCR. The PCR-EIA assay detected a minimum of 25 copies/ml C. pneumoniae DNA in plasmid-spiked CSF, which was at least 10 times more sensitive than TaqMan. These data indicated that the PCR-EIA assay possessed a sensitivity that was equal to the nested-PCR procedures for the detection of C. pneumoniae DNA in CSF. The TaqMan system may not be sensitive enough for diagnostic purposes due to the low C. pneumoniae copies existing in the majority of CSF specimens from MS patients

Machines vs. Ensembles: Effective MAPK Signaling through Heterogeneous Sets of Protein Complexes

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author’s publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively will ultimately shape how we conceptualize the function, evolution and engineering of signaling networks

Short-Lived Trace Gases in the Surface Ocean and the Atmosphere

The two-way exchange of trace gases between the ocean and the atmosphere is important for both the chemistry and physics of the atmosphere and the biogeochemistry of the oceans, including the global cycling of elements. Here we review these exchanges and their importance for a range of gases whose lifetimes are generally short compared to the main greenhouse gases and which are, in most cases, more reactive than them. Gases considered include sulphur and related compounds, organohalogens, non-methane hydrocarbons, ozone, ammonia and related compounds, hydrogen and carbon monoxide. Finally, we stress the interactivity of the system, the importance of process understanding for modeling, the need for more extensive field measurements and their better seasonal coverage, the importance of inter-calibration exercises and finally the need to show the importance of air-sea exchanges for global cycling and how the field fits into the broader context of Earth System Science

Estimating PM 2.5 concentrations in Xi'an City using a generalized additive model with multi-source monitoring data

© 2015 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5

Fostering multidisciplinary research on interactions between chemistry, biology, and physics within the coupled cryosphere-atmosphere system

The cryosphere, which comprises a large portion of Earth’s surface, is rapidly changing as a consequence of global climate change. Ice, snow, and frozen ground in the polar and alpine regions of the planet are known to directly impact atmospheric composition, which for example is observed in the large influence of ice and snow on polar boundary layer chemistry. Atmospheric inputs to the cryosphere, including aerosols, nutrients, and contaminants, are also changing in the anthropocene thus driving cryosphere-atmosphere feedbacks whose understanding is crucial for understanding future climate. Here, we present the Cryosphere and ATmospheric Chemistry initiative (CATCH) which is focused on developing new multidisciplinary research approaches studying interactions of chemistry, biology, and physics within the coupled cryosphere – atmosphere system and their sensitivity to environmental change. We identify four key science areas: (1) micro-scale processes in snow and ice, (2) the coupled cryosphere-atmosphere system, (3) cryospheric change and feedbacks, and (4) improved decisions and stakeholder engagement. To pursue these goals CATCH will foster an international, multidisciplinary research community, shed light on new research needs, support the acquisition of new knowledge, train the next generation of leading scientists, and establish interactions between the science community and society