Positive correlation between PKCζ and HER2 levels in breast cancer cell lines.

<p>Expression of PKCζ and HER2 were determined using western blots. ß-actin served as a loading control.</p

Correlation between PKCζ expression and clinicopathologic characteristics of human breast carcinomas.

<p>@:Fisher's exact test.</p

PKCζ expressed strongly in carcinoma tissue, but weakly/not in normal tissue and in lymph node metastasis.

<p>Samples of IHC images were from two independent individuals (I and II). Arrows point to PKCζ signals.</p

Survival analysis of breast cancer patients with different PKCζ levels.

<p>Survival status of patients was tracked for 132 months post-operatively. 1, low expression group; 2, high expression group. The survival statistical analysis was concluded by SPSS method. Survival curves were obtained using the Kaplan-Meier method. Differences in survival curves were assessed according to the log rank test. Differences were considered significant at values of P<0.05. <b>A)</b> Disease-free survival plot. <b>B)</b> Overall survival plot. Survival rates were calculated and obtained using SPSS software.</p

PKCζ is expressed strongly in invasive tissue, but weakly/not in normal tissue.

<p>A) IHC images of TMA analysis from a paired invasive ductal carcinoma case. Arrows point to areas of carcinoma (C) or normal (N) tissue. B) Positive ratio of PKCζ staining in TMA, 56.7% (17 of 30 cases) in invasive samples and 10% (3 of 30 cases) in normal samples. **, p<0.001 by Fisher's exact test. C) Western blots of PKCζ and actin from four paired cases; carcinoma (C) and normal (N) samples. D) Relative PKCζ levels in western blots. PKCζ levels were normalized by ß-actin levels as loading control. PKCζ levels were much higher in cancer than in normal specimens (5.09±4.42 vs 0.52±0.39). **, p<0.01 by t-test.</p

Locations of investigated lakes in Qaidam Basin.

<p>In Figure, K, T, D, M, X and G referred to Lake Keluke, Lake Tuosu, Lake Dasugan, Lake Gahai, Lake Xiaochaidan and Lake Gsikule, respectively.</p

High Genetic Diversity and Novelty in Eukaryotic Plankton Assemblages Inhabiting Saline Lakes in the Qaidam Basin

<div><p>Saline lakes are intriguing ecosystems harboring extremely productive microbial communities in spite of their extreme environmental conditions. We performed a comprehensive analysis of the genetic diversity (18S rRNA gene) of the planktonic microbial eukaryotes (nano- and picoeukaryotes) in six different inland saline lakes located in the Qaidam Basin. The novelty level are high, with about 11.23% of the whole dataset showing <90% identity to any previously reported sequence in GenBank. At least 4 operational taxonomic units (OTUs) in mesosaline lakes, while up to eighteen OTUs in hypersaline lakes show very low CCM and CEM scores, indicating that these sequences are highly distantly related to any existing sequence. Most of the 18S rRNA gene sequence reads obtained in investigated mesosaline lakes is closely related to Holozoa group (48.13%), whereas Stramenopiles (26.65%) and Alveolates (10.84%) are the next most common groups. Hypersaline lakes in the Qaidam Basin are also dominated by Holozoa group, accounting for 26.65% of the total number of sequence reads. Notably, Chlorophyta group are only found in high abundance in Lake Gasikule (28.00%), whereas less represented in other hypersaline lakes such as Gahai (0.50%) and Xiaochaidan (1.15%). Further analysis show that the compositions of planktonic eukaryotic assemblages are also most variable between different sampling sites in the same lake. Out of the parameters, four show significant correlation to this CCA: altitude, calcium, sodium and potassium concentrations. Overall, this study shows important gaps in the current knowledge about planktonic microbial eukaryotes inhabiting Qaidam Basin (hyper) saline water bodies. The identified diversity and novelty patterns among eukaryotic plankton assemblages in saline lake are of great importance for understanding and interpreting their ecology and evolution.</p></div

Taxa assignments at Class rank or below of investigated sample sits and the most abundant taxa in each habitat.

<p>(A) Taxa assignments at Class rank or below of investigated sample sits. (B) Taxa assignments at Class rank or below in each habitat. The class “other” means group that could not be precisely assigned to any known eukaryotic taxonomic group. The class “norank” means group that could not be precisely assigned to eukaryotic taxonomic group at least at the class level within kingdom. “Incertae sedis” is a term used for a taxonomic group where its broader relationships are unknown or undefined.</p

Novelty pattern plot for the different eukaryal classes found in mesosaline lake and hypersaline lake.

<p>(A) mesosaline saline, (B) hypersaline. Closest environmental match (CEM) and the closest cultured match (CCM) available in GenBank (BLAST search, May 2014). Dots below 61% similarity in both axes indicated no similarity sequences.</p

PCA analyses on DO, pH, TN and ion percentages of investigated Tibetan lakes.

<p>DO dissolved oxygen, TN total nitrogen, TDS total dissolved solid. K, Na, Ca, Mg, Cl, SO4 was represent for ions potassium (K⁺), sodium (Na⁺), calcium (Ca²⁺), magnesium(Mg²⁺), chloride (Cl⁻), and sulfate (SO₄²⁻), respectively. The numbers 1 to 13 refer to investigated lakes, Lake Keluke (G1, G3), Lake Gahai (M1, M7), Lake Dasugan (D10, D11), Lake Tuosu (T3, T11, T12), and Lake Keluke (K11, K13), respectively.</p