Quantum mechanical considerations on the mechanism of the P450 conversion of 11-deoxycorticosterone to Aldosterone

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Can surgical oncologists reliably predict the likelihood for non-SLN metastases in breast cancer patients?

Contains fulltext : 52950.pdf (publisher's version ) (Closed access)BACKGROUND: In approximately 40% of the breast cancer patients with sentinel lymph node (SLN) metastases, additional nodal metastases are detected in the completion axillary lymph node dissection (cALND). The MSKCC nomogram can help to quantify a patient's individual risk for non-SLN metastases with fairly accurate predicted probability. The aim of this study was to compare the predictions of surgical oncologists for non-SLN metastases with nomogram results and to clarify the impact of nomogram results on clinical decision-making. METHODS: Questionnaires, containing patient scenarios, were sent to surgical oncologists involved in breast cancer care. The surgeon was asked to predict the probability for non-SLN metastases for the first five scenarios. For the remaining scenarios, the patient's actuarial likelihood, calculated by the nomogram, was supplied. The surgeon was asked whether or not (s)he would perform a cALND. The type of hospital and the surgeon's experience were registered. RESULTS: The concordance-index amounted to 0.78, indicating moderate concurrence between the surgical predictions and nomogram results. The intersurgeon variation was important. About 25% of the surgeons was influenced by nomogram information and decided in one or more patients to abandon the cALND. Neither the type of hospital nor experience influenced predicting abilities or the clinical decision-making process. CONCLUSION: Individual predictions of surgical oncologists for non-SLN metastases do not correlate well with the MSKCC nomogram. The distribution between intersurgeon predictions for one scenario is important. Therefore, the nomogram is superior to clinical estimations for predicting the likelihood for non-SLN metastases

A Prospective Cross-Screening Study on G Protein-Coupled Receptors: Lessons Learned in Virtual Compound Library Design

Contains fulltext : 103510.pdf (Publisher’s version ) (Closed access)We present the systematic prospective evaluation of a protein-based and a ligand-based virtual screening platform against a set of three G-protein-coupled receptors (GPCRs): the beta-2 adrenoreceptor (ADRB2), the adenosine A(2A) receptor (AA2AR), and the sphingosine 1-phosphate receptor (S1PR1). Novel bioactive compounds were identified using a consensus scoring procedure combining ligand-based (frequent substructure ranking) and structure-based (Snooker) tools, and all 900 selected compounds were screened against all three receptors. A striking number of ligands showed affinity/activity for GPCRs other than the intended target, which could be partly attributed to the fuzziness and overlap of protein-based pharmacophore models. Surprisingly, the phosphodiesterase 5 (PDE5) inhibitor sildenafil was found to possess submicromolar affinity for AA2AR. Overall, this is one of the first published prospective chemogenomics studies that demonstrate the identification of novel cross-pharmacology between unrelated protein targets. The lessons learned from this study can be used to guide future virtual ligand design efforts