Comparative lipidome study of maternal plasma, milk, and lamb plasma in sheep

Lipids play a critical role in neonate development and breastmilk is the newborn\u27s major source of lipids. Milk lipids directly influence the neonate plasma lipid profile. The milk lipidome is dynamic, influenced by maternal factors and related to the maternal plasma lipidome. The close inter-relationship between the maternal plasma, milk and neonate plasma lipidomes is critical to understanding maternal-child health and nutrition. In this exploratory study, lipidomes of blood and breast milk from Suffolk sheep and matched lamb blood (n = 13), were profiled on day 34 post birth by untargeted mass spectrometry. Comparative multivariate analysis of the three matrices identified distinct differences in lipids and class of lipids amongst them. Paired analysis identified 346 differential lipids (DL) and 31 correlated lipids (CL) in maternal plasma and milk, 340 DL and 32 CL in lamb plasma and milk and 295 DL and 16 CL in maternal plasma and lamb plasma. Conversion of phosphatidic acid to phosphatidyl inositol was the most active pathway in lamb plasma compared to maternal plasma. This exploratory study illustrates the partitioning of lipids across maternal plasma, milk and lamb plasma and the dynamic relationship between them, reiterating the need to study these three matrices as one biological system

Original Article

Phosphodiesterase specific for the hydrolysis of diphenylphosphate, one of aromatic phosphodiesters, was obtained from hog kidney by following procedure. To hog kidney homogenized in a Waring blendor with 3 volumes of distilled water was added solid sodium chloride to a final concentration of 1% and after adjusting of pH to 5 with ca. 5 N hydrochloric acid, it was shaken for 10 minutes with an equal volume of n-butanol, allowed to stand for one hour, and centrifuged. The aqueous extract present beneath the floating gel layer of protein and butanol mixture, was siphoned out and fractionated with ammonium sulfate. The precipitate obtained between 45 and 70 % saturation was dissolved in a small volume of distilled water, dialyzed for 48 hours against running tap water, and then, to inactivate the monoesterase, heated in water bath of 100° for 5 minutes, whereby the solution became faintly turbid. The enzyme solution, thus prepared, hydrolyzed diphenylphosphate, liberating phenol but no inorganic phosphate, while it was inactive to monophenylphosphate. Diphenylphosphate of a final concentration of 0.0005M could be hydrolyzed in one hour at the optimum pH 7 to the extent of 40%. At this pH, the enzyme activity was not influenced by addition of Mg^, Ca^, or CN^. Bis-dichloroisopropylphosphate, dibenzylphosphate, diethylphosphate, lysolecithin, RNA, and DNA were resistant to this enzyme. It is conceivable that these diesters are hydrolyzed by other enzymes different from the aromatic phosphodiesterase, presented in this paper

Multiple synchronous verrucous carcinomas of the scalp in the background of generalized verruca vulgaris

Verrucous carcinoma (VC) is a clinicopathologic entity which is defined as a locally aggressive, clinically exophytic, slow-growing, well-differentiated, squamous cell carcinoma with negligible metastatic potential. The cutaneous form of VC is typically known to arise from the palmoplantar and the genitocrural areas. Involvement of the scalp is extremely rare. Multiple synchronous involvement of the scalp by VC along with associated generalized verruca vulgaris has possibly never been reported before. We present this unique report of VC in a 38-year-old male patient with emphasis on its atypical clinical presentation and the resultant challenges in management. Interestingly, the tumor cells of our patient were confirmed to be positive for human papillomavirus infection by polymerase chain reaction and by p16 immunohistochemistry

Breast tumors with elevated expression of 1q candidate genes confer poor clinical outcome and sensitivity to Ras/PI3K inhibition.

Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K / AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA-drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors

Primers used for Real-time quantitative PCR.

<p>Primers used for Real-time quantitative PCR.</p

E-cadherin expression at ITF vs MMP9 expression.

<p>E-cadherin expression at ITF vs MMP9 expression.</p

MMP 9 expression vs Pattern of Recurrence.

<p>MMP 9 expression vs Pattern of Recurrence.</p

Top up-regulated genes in OTSCC compared to normal.

<p>Top up-regulated genes in OTSCC compared to normal.</p

Univariate Cox Regression Analysis for prognostic variables.

<p>Univariate Cox Regression Analysis for prognostic variables.</p

Heat map showing DEG.

<p>The up regulated (red) and down regulated genes (green) shown after meta-analysis. The top bar shows the GEO dataset ID and the second bar shows the classification of tumor vs. normal. The gene list is shown in the right.</p