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1.
Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.  相似文献   
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Purpose

This study aimed to investigate 3 planning target volume (PTV) margin expansions and determine the most appropriate volume to be used in bladder preservation therapy when using daily cone beam computed tomography (CBCT). We aimed to establish whether a smaller PTV expansion is feasible without risking geographical miss.

Methods and materials

The study included patients with bladder cancer who were treated with a hypofractionated course of radiation therapy delivered with intensity modulated radiation therapy. The clinical target volume (CTV) was the whole empty bladder, and the PTV consisted of a 1.5-cm margin around the bladder (PTV1.5 cm). Patients underwent daily CBCT imaging before treatment to assess the bladder volume and ensure accurate positioning. We investigated 2 additional smaller PTV margin expansions to determine the most appropriate volume to be used with CBCT as a daily image guided radiation therapy modality. These margins were created retrospectively on every CBCT. The first additional volume was a uniform PTV margin of the surrounding 1 cm (PTV1 cm). When considering that the majority of the internal bladder movement was due to the variation in filling that occurs in the superior and anterior directions, a second volume of an anisotropic PTV margin with a 1.5-cm superior/anterior and 1 cm in other directions (PTV1/1.5 cm) was created. We recorded the frequency and measured the volume of bladder falling out of each PTV based on the daily CBCT.

Results

For the purpose of this study, we considered an arbitrary 5 cm3 of CTV falling out of the designated PTV as a clinically significant volumetric miss. The frequency of such a miss when applying the uniform PTV1 cm was 1%. However, when applying the uniform PTV1.5 cm and anisotropic PTV1/1.5 cm margins, the frequency was 0.5% and 0.5%, respectively.

Conclusions

The anisotropic PTV expansion of 1.5 cm superiorly and anteriorly and 1 cm in all other directions around the bladder (CTV) provides a safe PTV approach when daily CBCT imaging is used to localize an empty bladder.  相似文献   
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Quality of Life Research - This study investigated the PROMIS Self-Efficacy Measure for Managing Chronic Conditions (PROMIS-SE) domain distributions and examined the factor structure of the...  相似文献   
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Background

Available models for predicting lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP) might not be applicable to men diagnosed via magnetic resonance imaging (MRI)-targeted biopsies.

Objective

To assess the accuracy of available tools to predict LNI and to develop a novel model for men diagnosed via MRI-targeted biopsies.

Design, setting, and participants

A total of 497 patients diagnosed via MRI-targeted biopsies and treated with RP and extended pelvic lymph node dissection (ePLND) at five institutions were retrospectively identified.

Outcome measurements and statistical analyses

Three available models predicting LNI were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses. A nomogram predicting LNI was developed and internally validated.

Results and limitations

Overall, 62 patients (12.5%) had LNI. The median number of nodes removed was 15. The AUC for the Briganti 2012, Briganti 2017, and MSKCC nomograms was 82%, 82%, and 81%, respectively, and their calibration characteristics were suboptimal. A model including PSA, clinical stage and maximum diameter of the index lesion on multiparametric MRI (mpMRI), grade group on targeted biopsy, and the presence of clinically significant PCa on concomitant systematic biopsy had an AUC of 86% and represented the basis for a coefficient-based nomogram. This tool exhibited a higher AUC and higher net benefit compared to available models developed using standard biopsies. Using a cutoff of 7%, 244 ePLNDs (57%) would be spared and a lower number of LNIs would be missed compared to available nomograms (1.6% vs 4.6% vs 4.5% vs 4.2% for the new nomogram vs Briganti 2012 vs Briganti 2017 vs MSKCC).

Conclusions

Available models predicting LNI are characterized by suboptimal accuracy and clinical net benefit for patients diagnosed via MRI-targeted biopsies. A novel nomogram including mpMRI and MRI-targeted biopsy data should be used to identify candidates for ePLND in this setting.

Patient summary

We developed the first nomogram to predict lymph node invasion (LNI) in prostate cancer patients diagnosed via magnetic resonance imaging-targeted biopsy undergoing radical prostatectomy. Adoption of this model to identify candidates for extended pelvic lymph node dissection could avoid up to 60% of these procedures at the cost of missing only 1.6% patients with LNI.  相似文献   
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