Combined T2 and diffusion-weighted MR Imaging with template prostate biopsies in men suspected with prostate cancer but negative transrectal ultrasound-guided biopsies

PURPOSE: Transperineal template prostate (TPB) biopsy has been shown to improve prostate cancer detection in men with rising PSA and previous negative TRUS biopsies. Diagnostic performance of this approach especially MR imaging and using reliable reference standard remains scantly reported. MATERIALS AND METHODS: A total of 200 patients, who were previously TRUS biopsy negative, were recruited in this study. All the participants had at least 28-core TPB under general anesthetic within 8 weeks of previous negative TRUS biopsies. In 15 men undergoing laparoscopic radical prostatectomy, prostate specimens were sectioned using custom-made molds and analyzed by experienced pathologist as a feasibility study. RESULTS: In total, 120 of 200 patients (60 %) had positive TPB biopsy results. All of these men had at least one negative biopsy from transrectal route. T2 diffusion-weighted MR imaging showed no lesion in almost one-third of these men (61/200; 30.5 %). Out of these, 33 (33/61; 54 %) showed malignancy on TPB including high-grade tumors (>Gleason 7). Out of 15 patients underwent surgery with a total of 52 lesions (mean 3.5) on radical prostatectomy histology analyses, TPB detected 36 (70 %) lesions only. Some of these lesions were Gleason 7 and more mostly located in the posterior basal area of prostate. CONCLUSIONS: Transperineal template biopsy technique is associated with significantly high prostate cancer detection rate in men with previous negative TRUS biopsies, however compared to radical prostatectomy histology map, a significant number of lesions can still be missed in the posterior and basal area of prostate

The RIP140 Gene Is a Transcriptional Target of E2F1

RIP140 is a transcriptional coregulator involved in energy homeostasis and ovulation which is controlled at the transcriptional level by several nuclear receptors. We demonstrate here that RIP140 is a novel target gene of the E2F1 transcription factor. Bioinformatics analysis, gel shift assay, and chromatin immunoprecipitation demonstrate that the RIP140 promoter contains bona fide E2F response elements. In transiently transfected MCF-7 breast cancer cells, the RIP140 promoter is transactivated by overexpression of E2F1/DP1. Interestingly, RIP140 mRNA is finely regulated during cell cycle progression (5-fold increase at the G1/S and G2/M transitions). The positive regulation by E2F1 requires sequences located in the proximal region of the promoter (−73/+167), involves Sp1 transcription factors, and undergoes a negative feedback control by RIP140. Finally, we show that E2F1 participates in the induction of RIP140 expression during adipocyte differentiation. Altogether, this work identifies the RIP140 gene as a new transcriptional target of E2F1 which may explain some of the effect of E2F1 in both cancer and metabolic diseases

Assessing Computational Methods of Cis-Regulatory Module Prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods

Capsaicin-Induced Changes in LTP in the Lateral Amygdala Are Mediated by TRPV1

The transient receptor potential vanilloid type 1 (TRPV1) channel is a well recognized polymodal signal detector that is activated by painful stimuli such as capsaicin. Here, we show that TRPV1 is expressed in the lateral nucleus of the amygdala (LA). Despite the fact that the central amygdala displays the highest neuronal density, the highest density of TRPV1 labeled neurons was found within the nuclei of the basolateral complex of the amygdala. Capsaicin specifically changed the magnitude of long-term potentiation (LTP) in the LA in brain slices of mice depending on the anesthetic (ether, isoflurane) used before euthanasia. After ether anesthesia, capsaicin had a suppressive effect on LA-LTP both in patch clamp and in extracellular recordings. The capsaicin-induced reduction of LTP was completely blocked by the nitric oxide synthase (NOS) inhibitor L-NAME and was absent in neuronal NOS as well as in TRPV1 deficient mice. The specific antagonist of cannabinoid receptor type 1 (CB1), AM 251, was also able to reduce the inhibitory effect of capsaicin on LA-LTP, suggesting that stimulation of TRPV1 provokes the generation of anandamide in the brain which seems to inhibit NO synthesis. After isoflurane anesthesia before euthanasia capsaicin caused a TRPV1-mediated increase in the magnitude of LA-LTP. Therefore, our results also indicate that the appropriate choice of the anesthetics used is an important consideration when brain plasticity and the action of endovanilloids will be evaluated. In summary, our results demonstrate that TRPV1 may be involved in the amygdala control of learning mechanisms

At clinically relevant concentrations the anaesthetic/amnesic thiopental but not the anticonvulsant phenobarbital interferes with hippocampal sharp wave-ripple complexes

<p>Abstract</p> <p>Background</p> <p>Many sedative agents, including anesthetics, produce explicit memory impairment by largely unknown mechanisms. Sharp-wave ripple (SPW-R) complexes are network activity thought to represent the neuronal substrate for information transfer from the hippocampal to neocortical circuits, contributing to the explicit memory consolidation. In this study we examined and compared the actions of two barbiturates with distinct amnesic actions, the general anesthetic thiopental and the anticonvulsant phenobarbital, on in vitro SPW-R activity.</p> <p>Results</p> <p>Using an in vitro model of SPW-R activity we found that thiopental (50–200 μM) significantly and concentration-dependently reduced the incidence of SPW-R events (it increased the inter-event period by 70–430 %). At the concentration of 25 μM, which clinically produces mild sedation and explicit memory impairment, thiopental significantly reduced the quantity of ripple oscillation (it reduced the number of ripples and the duration of ripple episodes by 20 ± 5%, n = 12, <it>P </it>< 0.01), and suppressed the rhythmicity of SPWs by 43 ± 15% (n = 6, <it>P </it>< 0.05). The drug disrupted the synchrony of SPWs within the CA1 region at 50 μM (by 19 ± 12%; n = 5, <it>P </it>< 0.05). Similar effects of thiopental were observed at higher concentrations. Thiopental did not affect the frequency of ripple oscillation at any of the concentrations tested (10–200 μM). Furthermore, the drug significantly prolonged single SPWs at concentrations ≥50 μM (it increased the half-width and the duration of SPWs by 35–90 %). Thiopental did not affect evoked excitatory synaptic potentials and its results on SPW-R complexes were also observed under blockade of NMDA receptors. Phenobarbital significantly accelerated SPWs at 50 and 100 μM whereas it reduced their rate at 200 and 400 μM. Furthermore, it significantly prolonged SPWs, reduced their synchrony and reduced the quantity of ripples only at the clinically very high concentration of 400 μM, reported to affect memory.</p> <p>Conclusion</p> <p>We hypothesize that thiopental, by interfering with SPW-R activity, through enhancement of the GABA_Areceptor-mediated transmission, affects memory processes which involve hippocampal circuit activation. The quantity but not the frequency of ripple oscillation was affected by the drug.</p

Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during Early Drosophila Development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision