Modeling therapy resistance in genetically engineered mouse cancer models

Resistance to anti-cancer drugs is a major obstacle in successful treatment of cancer. Multidrug resistance is not only observed with clinically established chemotherapeutics, but also with novel targeted therapies. Although a range of drug resistance mechanisms have been identified up till now, for most drugs it is still controversial which mechanisms are responsible for resistance and therapy failure in patients. Hence, the development of strategies to circumvent drug resistance is often unfocused. Since several years genetically engineered mouse models have been generated which develop tumors that closely resemble cancer in humans. We argue that such models can be used to investigate relevant in vivo mechanisms of resistance. This includes the analysis of intrinsic and acquired resistance, and the characterization of residual cells which survive the treatment. In such model systems different drugs and therapy combinations can be optimized prior to clinical trials.     

Clinical significance of urethral instability

Variations of urethral pressure were registered with microtransducers in 427 gynecologic patients with lower urinary tract symptoms during urethrocystometry. Urethral instability (variation of urethral pressure greater than 15 cm of water) was found in 16.4% of patients. The comparison of the urinary symptoms and the urodynamic data between patients with urethral instability (without previous surgery for incontinence, N = 57), and patients with stable urethra (variation of urethral pressure less than 5 cm of water, N = 269) showed that urethral instability was related to frequency, nycturia, urgency, and a history of urethral syndrome. In 27% of patients, the urethral instability was associated with a bladder instability. The comparison between patients with urethral instability and stable bladder (N = 51) and patients with bladder instability and stable urethra (N = 41) revealed that bladder instability seems to be more important than urethral instability as a factor associated with nycturia, urgency, and urge incontinence.     

17 Beta-estradiol suppresses AMPA-induced increases in regional cerebral O2 consumption

We tested the hypothesis that 17 beta-estradiol would reduce the cerebral O2 consumption response resulting from glutamate receptor stimulation by alpha amino-3-hydroxy-5-methyl-isoxazole-4-propionate (AMPA). Fourteen ovariectomized rats were separated into 17 beta-estradiol (0.5 mg 21 day release pellet) and control (placebo pellet) groups to determine cerebral blood flow (14C-iodoantipyrine) and O2 consumption (microspectrophotometry). After topical cortical stimulation with 10(-3) M and 10(-4) M AMPA, cerebral blood flow increased significantly in both groups in a concentration-dependent manner. Cerebral O2 extraction was not significantly different in any region of the 17 beta-estradiol treated group. In the placebo treated group, the O2 extraction in the saline treated cortex and in the 10(-3) M AMPA treated cortex was significantly higher when compared to the 10(-4) M AMPA treated cortex. Cerebral O2 consumption in the control group increased by 20%, from 5.2 +/- 0.6 to 6.1 +/- 0.7, with 10(-4) M AMPA and significantly increased by 64% to 8.5 +/- 0.8 ml O2 min-1 100 g-1 with 10(-3) M AMPA. The 17 beta-estradiol group demonstrated no statistically significant difference in O2 consumption between the saline treated and AMPA treated cortex. Thus, 17 beta-estradiol reduced the effects of AMPA in increasing cerebral O2 consumption.     

DESIGN OF A PHOTOAFFINITY LABEL FOR THE HORMONE BINDING SITE OF NEUROPHYSIN

The photolabile peptide, L-methionyl-L-tyrosyl-p-azido-L-phenylalaninamide, was synthesized by solution methods. This peptide, as well as the analogous species containing tritiated methionine, were found to bind reversibly and specifically, in the dark, to bovine neurophysin II. The dissociation constant, stoichiometry, and pH-dependence of this noncovalent interaction are typical of those properties for hormone (oxytocin) and hormone-like ligand binding to neurophysin II. Under photolytic conditions, methionyl-tyrosyl-p-azidophenylalaninamide causes irreversible inhibition of the noncovalent ligand binding activity of neurophysin II. This inactivation was achieved to the extent of about 90%. Both the dark and light (photolytic) interactions of the photolabile peptide with neurophysin II indicate its reaction at the hormone binding site of the protein and thus its potential use to identify amino acid residues at this site by covalent photoaffinity labelling.     

Sagittal sinus thrombosis as a complication of regional enteritis

A young woman with regional enteritis and a history of recurrent thrombophlebitis and pulmonary embolism developed sagittal sinus thrombosis during an acute exacerbation of her illness. Repeated attempts to document a hypercoagulable state were unsuccessful.     

Quantitative comparison of four brain extraction algorithms

In a companion paper (Rehm et al., 2004), we introduced Minneapolis Consensus Strip (McStrip), a hybrid algorithm for brain/non-brain segmentation. In this paper, we compare the performance of McStrip and three brain extraction algorithms (BEAs) in widespread use within the neuroimaging community--Statistical Parametric Mapping v.2 (SPM2), Brain Extraction Tool (BET), and Brain Surface Extractor (BSE)--to the "gold standard" of manually stripped T1-weighted MRI brain volumes. Our comparison was based on quantitative boundary and volume metrics, reproducibility across repeat scans of a single subject, and assessments of performance consistency across datasets acquired on different scanners at different institutions. McStrip, a hybrid method incorporating warping to a template, intensity thresholding, and edge detection, consistently outperformed SPM2, BET, and BSE, all of which rely on a single algorithmic strategy.     

Optimizing the fMRI data-processing pipeline using prediction and reproducibility performance metrics: I. A preliminary group analysis

We argue that published results demonstrate that new insights into human brain function may be obscured by poor and/or limited choices in the data-processing pipeline, and review the work on performance metrics for optimizing pipelines: prediction, reproducibility, and related empirical Receiver Operating Characteristic (ROC) curve metrics. Using the NPAIRS split-half resampling framework for estimating prediction/reproducibility metrics (Strother et al., 2002), we illustrate its use by testing the relative importance of selected pipeline components (interpolation, in-plane spatial smoothing, temporal detrending, and between-subject alignment) in a group analysis of BOLD-fMRI scans from 16 subjects performing a block-design, parametric-static-force task. Large-scale brain networks were detected using a multivariate linear discriminant analysis (canonical variates analysis, CVA) that was tuned to fit the data. We found that tuning the CVA model and spatial smoothing were the most important processing parameters. Temporal detrending was essential to remove low-frequency, reproducing time trends; the number of cosine basis functions for detrending was optimized by assuming that separate epochs of baseline scans have constant, equal means, and this assumption was assessed with prediction metrics. Higher-order polynomial warps compared to affine alignment had only a minor impact on the performance metrics. We found that both prediction and reproducibility metrics were required for optimizing the pipeline and give somewhat different results. Moreover, the parameter settings of components in the pipeline interact so that the current practice of reporting the optimization of components tested in relative isolation is unlikely to lead to fully optimized processing pipelines.