Hydrogen bonding in cubic (H_2O)_8 and OH∙(H_2O)_7 clusters

A systematic study is presented for OH∙(H_2O)_7 clusters derived from the cubic (H_2O)_8 octamer by replacing one water with a hydroxyl radical. The system is a prototype for atmospheric water clusters containing the environmentally important OH species, and for OH adsorbed at the surface of ice. The full set of 39 symmetry-distinct cubic OH∙(H_2O)_7 clusters is enumerated, and the structures are determined using ab initio quantum chemical methods. Graph invariants are employed to obtain a unified analysis of the stability and structure of cubic (H_2O)_8 and OH∙(H_2O)_7, relating these physical properties to the various hydrogen-bond topologies present in these clusters. To accomplish this the graph invariant formalism is extended to treat a hydrogen bonding impurity within a pure water network

Analysis of the temperature dependence of the racemization of Eu(III) complexes through measurement of steady-state circularly polarized luminescence

The temperature dependence of the steady-state luminescence dissymmetry ratio, glum, has been measured for racemic Eu(III) complexes containing the terdentate ligands dipicolinate and phenylethynyl-dipicolinate. As the temperature is increased, the magnitude of the dissymmetry ratio for these species decreases due to racemization occurring during the excited state lifetime. The temperature dependence of glum is analyzed by a non-linear curve-fitting technique to determine the activation energies for the interconversion of the enantiomers. Comparison is made with previous measurements involving time-resolved circularly polarized luminescence

miR-19, miR-345, miR-519c-5p serum levels predict adverse pathology in prostate cancer patients eligible for active surveillance.

Serum microRNAs hold great promise as easily accessible and measurable biomarkers of disease. In prostate cancer, serum miRNA signatures have been associated with the presence of disease as well as correlated with previously validated risk models. However, it is unclear whether miRNAs can provide independent prognostic information beyond current risk models. Here, we focus on a group of low-risk prostate cancer patients who were eligible for active surveillance, but chose surgery. A major criteria for the low risk category is a Gleason score of 6 or lower based on pre-surgical biopsy. However, a third of these patients are upgraded to Gleason 7 on post surgical pathological analysis. Both in a discovery and a validation cohort, we find that pre-surgical serum levels of miR-19, miR-345 and miR-519c-5p can help identify these patients independent of their pre-surgical age, PSA, stage, and percent biopsy involvement. A combination of the three miRNAs increased the area under a receiver operator characteristics curve from 0.77 to 0.94 (p<0.01). Also, when combined with the CAPRA risk model the miRNA signature significantly enhanced prediction of patients with Gleason 7 disease. In-situ hybridizations of matching tumors showed miR-19 upregulation in transformed versus normal-appearing tumor epithelial, but independent of tumor grade suggesting an alternative source for the increase in serum miR-19a/b levels or the release of pre-existing intracellular miR-19a/b upon progression. Together, these data show that serum miRNAs can predict relatively small steps in tumor progression improving the capacity to predict disease risk and, therefore, potentially drive clinical decisions in prostate cancer patients. It will be important to validate these findings in a larger multi-institutional study as well as with independent methodologies

miR-19, miR-345, miR-519c-5p Serum Levels Predict Adverse Pathology in Prostate Cancer Patients Eligible for Active Surveillance

<div><p>Serum microRNAs hold great promise as easily accessible and measurable biomarkers of disease. In prostate cancer, serum miRNA signatures have been associated with the presence of disease as well as correlated with previously validated risk models. However, it is unclear whether miRNAs can provide independent prognostic information beyond current risk models. Here, we focus on a group of low-risk prostate cancer patients who were eligible for active surveillance, but chose surgery. A major criteria for the low risk category is a Gleason score of 6 or lower based on pre-surgical biopsy. However, a third of these patients are upgraded to Gleason 7 on post surgical pathological analysis. Both in a discovery and a validation cohort, we find that pre-surgical serum levels of miR-19, miR-345 and miR-519c-5p can help identify these patients independent of their pre-surgical age, PSA, stage, and percent biopsy involvement. A combination of the three miRNAs increased the area under a receiver operator characteristics curve from 0.77 to 0.94 (<i>p</i><0.01). Also, when combined with the CAPRA risk model the miRNA signature significantly enhanced prediction of patients with Gleason 7 disease. In-situ hybridizations of matching tumors showed miR-19 upregulation in transformed versus normal-appearing tumor epithelial, but independent of tumor grade suggesting an alternative source for the increase in serum miR-19a/b levels or the release of pre-existing intracellular miR-19a/b upon progression. Together, these data show that serum miRNAs can predict relatively small steps in tumor progression improving the capacity to predict disease risk and, therefore, potentially drive clinical decisions in prostate cancer patients. It will be important to validate these findings in a larger multi-institutional study as well as with independent methodologies.</p></div

Distribution plots for serum miR-19b, miR-19a, miR-345, and miR-519c-5p delta Ct values in case versus control for a) discovery cohort, b) validation cohort.

<p>Delta Ct represents difference between Ct of individual miRNA and median Ct value among detected miRNAs within each patient. Horizontal bars represent mean +/– SEM.</p

Summaries of logistic regression models for different combinations of miRNAs in validation cohort accounting for age, PSA, stage and biopsy characteristics.

<p>Summaries of logistic regression models for different combinations of miRNAs in validation cohort accounting for age, PSA, stage and biopsy characteristics.</p

MiRNAs consistently detected in serum from the discovery cohort.

<p>MiRNAs consistently detected in serum from the discovery cohort.</p

Summaries of logistic regression models for individual MiRNAs in the discovery and validation cohorts accounting for age, PSA, stage and biopsy characteristics.

<p>*MiRNAs were represented in models as binary indicators, with cut-offs selected using a classification tree.</p><p>**Estimated odds ratio from a logistic regression also controlling for age, PSA, stage and degree of biopsy involvement.</p>†<p>Estimated area under the ROC curve from a logistic regression also controlling for age, PSA, stage and degree of biopsy involvement.</p>‡<p>P-value comparing AUC for model including for miRNA, to model including only age, PSA, stage and degree of biopsy involvement.</p