K-Nearest Neighbors (KNN) – to guide rehabilitation planning for home care clients.Targeting older clients for rehabilitation is a clinical challenge and a research priority. We investigate the potential of machine learning algorithms – Support Vector Machine (SVM) and This study is a secondary analysis of data on 24,724 longer-term clients from eight home care programs in Ontario. Data were collected with the RAI-HC assessment system, in which the Activities of Daily Living Clinical Assessment Protocol (ADLCAP) is used to identify clients with rehabilitation potential. For study purposes, a client is defined as having rehabilitation potential if there was: i) improvement in ADL functioning, or ii) discharge home. SVM and KNN results are compared with those obtained using the ADLCAP. For comparison, the machine learning algorithms use the same functional and health status indicators as the ADLCAP.The KNN and SVM algorithms achieved similar substantially improved performance over the ADLCAP, although false positive and false negative rates were still fairly high . Results are used to suggest potential revisions to the ADLCAP.Machine learning algorithms achieved superior predictions than the current protocol. Machine learning results are less readily interpretable, but can also be used to guide development of improved clinical protocols. Targeting older clients for rehabilitation is a clinical challenge and a research priority . For cliResource constraints will inevitably limit the provision of rehabilitation services, but gaps in service also reflect gaps and shortcomings in the management and use of available health information. More appropriate targeting of rehabilitation therapy could be achieved through more informed care planning, but rehabilitation decisions are particularly challenging. For acute care patients, diagnoses are often clearly defined. By contrast, rehabilitation patients have considerable variability even within specific diagnostic categories. Assessment of rehabilitation potential and the potential success of rehabilitation for older patients is not always straightforward, is often complicated by medical complexity and multiple co-morbidities ,8, and rIn this paper, we are continuing to investigate the potential for machine learning algorithms to guide rehabilitation planning for home care clients. Machine learning involves computer programs that use experience gained from exploration of a dataset to improve performance or predictive ability. These techniques are now being used extensively in biomedical applications , for exaK-nearest neighbors (KNN) algorithm, which, we argued, resembles clinical logic in that predictions are based on outcomes experienced for similar patients [In our previous work on the prediction of rehabilitation potential, we applied a simple machine-learning algorithm known as the patients . We founpatients . In thisFor both studies reported below, ethics approval was obtained from the Office of Research Ethics at the University of Waterloo.K-nearest neighbors (KNN) algorithm in two ways. First, being a state-of-the-art machine-learning algorithm and a much more flexible kernel method than KNN, SVM may give more accurate predictions. Second, the decision rule from SVM will only depend on a subset of observations – called support vectors; these support vectors can be regarded as prototypes and, if the total number of support vectors turns out to be small, SVM will produce a much more parsimonious and interpretable model.In our earlier paper , we specy) of these clients can be reliably assessed from linked health service utilization data. For study purposes, a client is defined as having rehabilitation potential if there was: i) improvement in ADL functioning, or ii) discharge home. Improvement in ADL functioning was defined as any improvement in the interRAI ADL Long Form scale derived from the RAI-HC [We use the same data as used in our earlier report : RAI-HC e RAI-HC , over a e RAI-HC . The CAPIn our earlier work we compared results using the ADLCAP with results obtained using the KNN machine learning algorithm . In ordeif h2a = 2, 3, 4, 5, 6, or 8 (indicating levels of dependence);then consider as dependent;else  consider as independent.In other words, suppose that client A has h2a = 2 and client B has h2a = 6. The ADLCAP does not distinguish these two clients with regard to h2a. Therefore, we can recode h2a as a binary variable as follows: recode 2, 3, 4, 5, 6, and 8 as one and recode all other values 0 and 1) as zero. Table  as zero.xnew is a vector containing all the covariates for a new observation. To predict its outcome, SVM uses quadratic programming to construct a model of the following form:The SVM  is a prew0 and wi are model coefficients; and K is a kernel function. Once the parameters w0 and wi are estimated, the final model depends only on a subset of the training data, denoted above by "SV" – they are called support vectors and are automatically determined by the SVM algorithm. To fit the SVM, we use a library called "e1071" in R [where 71" in R .a priori: one that controls the width of the kernel function, which we denote here by γ; and another that essentially controls how many support vectors the algorithm will ultimately select, which we denote here by C. The performance of SVM is sensitive to these tuning parameters and the optimal value of these parameters are problem-specific.To fit an SVM model, we choose the default kernel function, the radial basis kernel. Among the four options provided by the "e1071" library – linear, polynomial, radial basis, and sigmoid – the radial basis kernel is also the most compatible with a distance-based method such as the KNN. To use SVM with the radial basis kernel, there are two tuning parameters that we must specify To determine the best values of these parameters for our problem and evaluate the final predictive power of SVMs, we use the same analytic framework as in our earlier study . In partγ = 0.06 and C = 0.24.Since we construct and use different training sets to make predictions for different regions, we have a total of eight different training sets. After performing cross-validation on each of them, eight slightly different sets of optimal tuning parameters are obtained. They turn out to be quite close to each other. Generally, the optimal parameters are around Prediction accuracy is then evaluated using exactly the same four criteria as in , namely,not differentiate among the values 2, 3, 4, 5, 6 and 8. This might lead to a loss of information. We speculated that one could possibly improve the prediction accuracy of various machine-learning algorithms if no such arbitrary restrictions were imposed [We have pointed out that the ADLCAP seemed to interpret the covariates in a rather restrictive manner . For exa imposed .original RAI-HC datasets without recoding the variables according to Table We use the K in KNN, and the numbers γ and C in SVM – have to be re-calibrated. Again, we do this with cross-validation. The parameters chosen are: K = 20, C = 1.25, and γ = 0.01.We apply both the KNN and the SVM algorithms to the relaxed datasets and do so in exactly the same way as before, except the optimal tuning parameters – that is, the number Contrary to our speculations , we findHowever, this does not mean that SVM is completely useless for our problem. In SVM, observations chosen as support vectors are either very close to or on the wrong side of the decision boundary. Non-support vectors, on the other hand, are on the correct side of the boundary and at least a certain distance away from it; they are the easy-to-classify observations in the dataset . In our We build an SVM with a random sample of 10,000 observations from all eight CCAC datasets and examine the resulting two groups of support vectors. In Table all eight subsets are h2j – independent in bathing, h7a – client optimistic about functional improvement, and h7c – client rated as having good prospects of recovery.We then perform a slightly different analysis to verify this result. Recall that, along our earlier analyses, we have created eight different training datasets, each consisting of 2500 observations. On each of these eight datasets, we perform stepwise variable selection on a standard logistic regression model using the Akaike Information Criterion (AIC) as the selection criterion. This is done with the functions "glm" and "stepAIC" in R . We thusLike KNN, SVM predicts rehabilitation potential better than the ADLCAP, but there is little statistical difference between KNN and SVM. Analysis using the SVM reveals that the most important variables for predicting rehabilitation potential are h2j – independent in bathing, h7a – client optimistic about functional improvement, and h7c – client rated as having good prospect of recovery.The Study 2 results are peculiar and at first counter-intuitive. When the original scales are used, SVM performs slightly better but KNN performs slightly worse than before Tables  and 5.In order to understand this peculiar behavior, a series of in-depth exploratory analyses are performed on the datasets. The analysis that provides us with an insight into this peculiarity is described below. The insight gained from this analysis not only resolves this mystery for us; it also suggests a new method of defining the ADLCAP.Take the covariate h2a for example. Using all the data, we can estimate the following ratio:If ratio profile of h2a. For the sake of argument, suppose the ratio profile of h2a looks like this: {5, 4, 3, 2, 0.5, 0.2, 0.1}. Such a profile would mean that clients with rehabilitation potential are 5 times more likely than those without potential to score a 0 on item h2a, 4 times more likely to score a 1, 3 times more likely to score a 2, and 2 times more likely to score a 3. On the other hand, clients without rehabilitation potential are 10 times more likely to score a 6, 5 times more likely to score a 5 and 2 times more likely to score a 4.Call y ? The obvious answer is as follows:Based on such a profile, how would one use h2a  to predict rehabilitation potential orratio profile score for h2a asNow, define the Sh2a = 5 ÷ (0.5) = 10. This score can be treated as a rough measure of how accurately one can predict rehabilitation potential using the covariate h2a. The higher the score, the better.In the hypothetical illustration above, we would have Figure Sh7c = 4.14), h2j – bathing (Sh2j = 3.12), and h7a – client optimistic about functional improvement (Sh7a = 3.01). This is, again, in exact agreement with our results from Study 1.1. The three covariates with the highest ratio profile scores are: h7c – good prospect of recovery . Based on its ratio profile, the best way to use h2i for prediction is as follows: h2i = 0 ; h2i = 1, 2, 3, 4, 5, 6. That is, for h2i, the recoded scale is almost the best. It would have been better to separate 0 from 1–6 rather than grouping 0 and 1 together , h2i has the second highest score Sh2i = .41. Base5. The ratio profiles of c3 and p6 indicate that the recoded scales severely mask the information contained in these covariates for predicting rehabilitation potential. There is extra information in the original scale. In both cases, it would have been better to recode "0" into "0" and everything else into "1".These observations suggest that there is a tradeoff between using the original and the recoded scales. On the one hand, there is some extra information useful for prediction if the original scales are used. On the other hand, the recoded scales are optimal for the most influential covariates and there is a considerable amount of added noise if the original scales are used.x) asNotice that our definition of the ratio profile score here is not general. Generally speaking, it would have been better to define the ratio profile score , the ADLCAP is triggered for 8,913 clients, i.e., about 36.05%. To allow us to make a fair comparison, we reason backwards by asking: what would the threshold have to be so that 36.05% of all the clients would score above this threshold value on the alternative ADLCAP as well? The answer turns out to be 15.8. Table The use of Clients requiring rehabilitation are at a critical turning point in terms of their future functioning and quality of life, and their potential to live independently. If information systems are used to ensure appropriate and equitable access to rehabilitation services, there will be major benefits to the health, quality of life and independence of rehabilitation clients. There will also be major health system benefits through decreased costs, more appropriate resource use, and avoided institutional placements.K-nearest neighbors (KNN) algorithm [In the first study reported here, we found that the support vector machine (SVM) predicts rehabilitation potential better than the ADLCAP, but there is little statistical difference between SVM and the lgorithm . In addiWe believe our work to date supports continued investigation of the potential for advanced statistical techniques, including machine learning algorithms, to support care planning for rehabilitation. Both of the machine learning techniques we have explored, the KNN and SVM algorithms, have achieved substantially improved performance over a currently used clinical protocol. Reservations about the use of these methods include the interpretability of their results, and the resulting potential for clinical resistance to a "black box" approach. For this reason we have so far chosen methods that could be seen as analogous to clinical reasoning (KNN) or that could identify prototypical cases that could aid interpretation (SVM). In addition to improved statistical prediction, our work points to an additional, and possibly more important, benefit of these methods. Our analyses of the machine learning results have provided insights into the factors that may be most influential in predicting rehabilitation potential – "the contents of the black box" – and also into optimal ways to categorize these variables . We have also shown how these results could be used to redefine the clinical protocol to achieve results similar to that achieved using machine learning algorithms.Machine learning algorithms achieved superior predictions than the current protocol, although the results are less readily interpretable. We recognize that targeting clients for rehabilitation remains a challenge, and any manageable health information system will be limited in its ability to predict rehabilitation potential. We suggest however that we have illustrated how machine learning techniques can "set the bar" for clinical predictions, and also how machine learning can be used to refine clinical protocols to achieve comparable performance.The author(s) declare that they have no competing interests.MZ, JPH and PS all participated in the conceptualization and design of the study. MZ led the statistical analysis with assistance from ZZ. All authors participated in interpreting the results of the analyses. The manuscript was drafted by MZ and PS. All authors have read and approved the final manuscript.x1, x2) and a binary outcome y. The first 1000 samples belong to one class (y = 0) and the remaining 250 belong to the other (y = 1). The two predictors are generated independently using probability distributions specified in Table We repeatedly conduct 10 simulation experiments. In each experiment, we first generate a training sample of 1250 observations, each with two predictors  =  or .The predictor x1, x2) are deliberately made somewhat noisy and irregular for x1 ≥ 2 and x2 ≥ 1. As a result, we can see that there is a small but noticeable bump in the true decision surface around  =  and   in their original scale and once with the predictors recoded according to Table We then fit a KNN and an SVM model on the training sample and use them to predict the test sample. We do this once with the predictors x, x2 in tThe overall error rates of KNN and SVM from the 10 simulations are shown using boxplots in Figure x1, x2) = . In addition, when the original scales are used, SVM can be seen to have a much better chance of making the correct prediction of x1, x2) = .Figure Finally, it is worth noting that there is considerable noise in our simulated data. Even if we used the true underlying decision surface Figure  to make The pre-publication history for this paper can be accessed here:


Here we demonstrate that UCH L1 up-regulates β-catenin/TCF signaling: UCH L1 forms endogenous complexes with β-catenin, stabilizes it and up-regulates β-catenin/TCF-dependent transcription. We also show that, reciprocally, β-catenin/TCF signaling up-regulates expression of endogenous UCH L1 mRNA and protein. Moreover, using ChIP assay and direct mutagenesis we identify two TCF4-binding sites on the uch l1 promoter that are involved in this regulation. Since the expression and deubiquitinating activity of UCH L1 are required for its own basic promoter activity, we propose that UCH L1 up-regulates its expression by activation of the oncogenic β-catenin/TCF signaling in transformed cells.Deubiquitinating enzymes (DUBs) are involved in the regulation of distinct critical cellular processes. Ubiquitin C-terminal Hydrolase L1 (UCH L1) has been linked to several neurological diseases as well as human cancer, but the physiological targets and the regulation of UCH L1 expression  Wnt pathway c-myc, cyclin D, c-jun, survivin and others, which indicates that β-catenin/TCF/Lef signaling up-regulates oncogenic cellular pathways The lifetime of many central components of intracellular signaling is regulated by the ubiquitin system The nonjunctional pool of β-catenin is normally a target for destruction by the ubiquitin-proteasome system, and the process of β-catenin regulation through ubiquitination has been studied intensively in vivo, and this function is independent of the enzymatic activity of UCH L1 Among the large family of DUBs are Ubiquitin C-terminal Hydrolases–cysteine hydrolases that contain the typical active site triad of cysteine, histidine, and aspartic acid and that catalyze hydrolysis of C-terminal esters and amides of ubiquitin uch l1 gene was cloned and partially characterized in neurons uch l1 on the promoter level in vitro and in vivouch l1 expression in cancer cells is still largely unexplored.There is also growing evidence indicating that UCH L1 is overexpressed in a number of cancers Here we demonstrate a positive feedback between UCH L1 and oncogenic β-catenin/TCF signaling, providing evidence that in transformed cells UCH L1 up-regulates its own expression through β-catenin/TCF-dependent transcription.Previously we have demonstrated that in virus-transformed B-cells β-catenin is physically associated with an active DUB with a molecular weight of ∼26 kDa, and proposed that this DUB is UCH L1 http://www.proteinatlas.org/cell_if_unit.php?antibody_id=5993&mainannotation_id=200003070). Co-immunostaining with HA and myc antibodies after co-transfection with HA-UCH L1 and myc-β-catenin expression vectors revealed similar, mostly nuclear co-localization of overexpressed UCH L1 and β-catenin .Additional information supporting the hypothesis of UCH L1-dependent regulation of β-catenin/TCF signaling was provided from gene expression profiling of stable 293 cell lines expressing control and UCH L1 siRNA: inhibition of UCH L1 reveals reduced expression of several known physiological targets of β-catenin/TCF transcriptional activity such as uch l1 gene might be subject to transcriptional regulation during cellular transformation by oncogenic pathways such as β-catenin/TCF. Analysis of the uch l1 promoter using Patch 1.0 has revealed two 5′-TTTGA-3′ putative Lef-1 binding sites on the negative strand uch l1 gene regulation. To examine this possibility, we utilized a reporter construct carrying the luciferase gene under the direction of the 5′ minimal promoter  unable to bind β-catenin To confirm the role of β-catenin signaling in the up-regulation of endogenous UCH L1 expression, we employed two different approaches. First, inhibition of β-catenin expression by transient transfection of β-catenin siRNAs in 293 cells (expressing high levels of UCH L1): To determine whether the β-catenin/TCF complex up-regulates UCH L1 expression through direct binding to its promoter, we performed a ChIP assay using the TCF4 antibody followed by DNA isolation and PCR with primers for both putative TCF/Lef sites on the uch l1 promoter in lymphoid KR4 and epithelial 293 cells . Non-immTo verify the significance of the putative TCF/Lef binding sites for β-catenin/TCF-dependent activation of the uch l1 promoter, we mutated each of two sites in the promoter, as well as both sites using the wild type uch l1 promoter reporter (UCHL1p-WT) as a template. We transiently transfected wild type and mutant reporters into 3T3 cells and compared their activities . To actiWhile the roles of the multifunctional molecule β-catenin in normal and cancer cells have been studied intensively, the potential impact of UCH L1 in oncogenesis is largely unexplored. Moreover, information on UCH L1 expression in different cancer cell lines is contradictory: on the one hand, silencing of UCH L1 expression by the methylation of its promoter was observed in some cancer cell lines and primary tumors UCH L1 appears to be a multi-functional protein that might contribute to more diverse cellular processes than were previously thought. Our results indicate that UCH L1 and β-catenin/TCF can positively regulate each other , support2 in air. MG101, recombinant UCH L1, LiCl and Ubiquitin-AMC were purchased from Calbiochem, Boston Biochem, Sigma and Biomol respectively.Human 293 embryonic kidney cells and NIH 3T3 mouse fibroblast cells were cultured in DMEM (Sigma) supplemented with 10% FBS (Sigma) and penicillin–streptomycin. Lymphoblastoid cell line KR4 Wild-type pcDNA3-HA-UCH L1 was a gift from Dr. P. T. Lansbury. pcDNA3-HA-UCH L1 C90S and H161D mutants were generated by inserting a specific mutation at the Cys 90 and H161 sites in wild-type pcDNA3-HA-UCH L1 plasmid with the use of the Quik-Change Site Directed Mutagenesis Kit following the manufacturer's instructions (Stratagene). UCH L1 siRNA was obtained from OriGene Technologies, Inc, in the form of a shRNA expression plasmid. The control siRNA targeted against GFP and was also obtained from OriGene Technologies, Inc. pSuper-retro β-catenin siRNA was constructed as described by the manufactor. TCF reporter plasmids, TOPFlash  and FOPFlash (mutated TCF-binding site) were obtained from Upstate Biotechnology. Wild type and deltaN pcDNA3.1-Flag-TCF4 expression vectors were gift from H. Clevers. The UCH L1 promoter region 5′TGTGGCACAATCGGACTTATTCACGCAGT 3′UCH L1 siRNA–1: CCATGATGCCGTGGCACAGGAAGGCCAAT 3′5′ UCH L1 siRNA–2: 5′CCATGGAACCAGACAGAAA 3′β-Catenin siRNA–1: 5′CCCACTAATGTCCAGCGTT 3′β-Catenin siRNA–2: 5′GGTACCAAAACGAACCTCGGTACTGGUCH L1 promoter–KpnI: 5′AAGCTTCTCACCTCGGGGTTGATCTUCH L1 promoter–Hind III: 293 cells were grown on poly-L-Lysine (Sigma)-coated coverslips in 12-well dishes until 75% confluent. The cells were washed with PBS, fixed with 4% paraformaldehyde for 10 min, permeablized with 0.5% triton, washed three times with PBS and blocked with 5% normal donkey serum. Cells were then incubated with rabbit anti-UCH L1 antibody , mouse anti-β-catenin antibody , rabbit anti-HA , mouse anti-myc  in 1∶5 dilution of blocking solution for 1 h at 37°C and then washed three times with PBS. Next, cells were incubated with Alexafluor-594-conjugated goat anti-rabbit and Alexafluor-488-conjugated goat anti-mouse antibodies  for 1 h at 37°C, washed four times with PBS and mounted. Fluorescent images were created using Openlab software .Total cell lysates or immunocomplexes were resolved on SDS-PAGE, transferred to nitrocellulose membrane (Osmonics), blocked in 5% milk-Tris-buffered saline solution, and incubated at 4°C overnight with β-catenin , UCH L1 , GAPDH  antibodies. After washing with TBST for 10 min three times, the membrane was incubated with appropriate secondary antibody at room temperature for 1 h, washed three times with TBST as before, treated with SuperSignal (Pierce) detection reagents, and exposed to Kodak XAR-5 film.3VO4, 1 mM NaF and complete protease inhibitor mixture (Roche Diagnostics). After pre-clearing, cell lysates were incubated with β-catenin (Zymed) or UCH L1 antibody (Zymed) or control Ig G for 1 h in 4°C; immune complexes were then incubated with protein A/G Sepharose beads (Santa Cruz) at 4°C overnight, washed four times with protein lysis buffer, and then eluted from the protein G-Sepharose with 2× Laemmli's buffer by boiling for 3 min.Cells were lysed with buffer containing of 50 mM, pH 7.6 Tris-HCl, 1% NP-40, 0.25% Na-deoxycholate, 1 mM EDTA, 1 mM NaIn-vitro translated β-catenin (2 µl) was pre-incubated with 10 mM DTT for 15 min and for 2 h at 30°C in 20 µl of Ub reaction mixture containing: 50 mM Tris-HCl (pH 7.5), 50 mM NaCl, 2 mM Mg-ATP, 20 µM mammalian ubiquitin, 25 µM MG101, 100 nM rabbit E1 and 3 µl reticulocyte lysate, and then incubated with different amounts of UCH L1 recombinant protein (Boston Biochem) The reactions were stopped by adding equal volumes of 2× SDS sample loading buffer followed by Western blot analysis with mouse β-catenin antibody (BD Pharmingen).Endogenous β-catenin was immunoprecipitated from 293 cells treated with 25 µM MG101 for 3 h with specific or control antibodies. Exogenous β-catenin protein was translated in a TNT-coupled reticulocyte-lysate system (Promega) with pCMV β-catenin as template. Overexpressed HA-UCH L1s were immunoprecipitated with HA antibody from 293 cells transfected with wild type, C90S and H161D uch l1 expression vectors. Immunoprecipitates were incubated with 1 µM of ubiquitin-AMC in reaction buffer containing 50 mM Tris pH 7.5, 2 mM ATP, and 2 mM DTT for 30 min at 37°C. Samples in triplicate were excited by exposure to light at a wavelength of 340 nm, and emission was measured at 460 nm.For the establishment of UCH L1 siRNA and control siRNA stable lines, 293 cells were transfected with 2 µg of respective plasmid using the Fugene HD (Roche Diagnostics). Cells were passaged 24 h post transfections and selection was started 48 h post transfections. The cells were always maintained in the selective media containing 2 µg/ml puromycin (InvivoGen).Cells were transiently transfected with total 2 µg of DNA with Fugene HD reagent (Roche Diagnostics) according to the manufacturer's instructions. Cells were collected 48 h post transfections.For Luciferase reporter assay, cells were plated in 6-well plates and transiently transfected with the use of Fugene with TCF reporter plasmids, TOPFlash or FOPFlash or Uchl1p-Luc promoter plasmid, and the effector plasmid. The total amount of DNA in all transfection was kept constant with empty vector. Luciferase activities were monitored in cell lysates with the use of Luciferase assay reagents (Promega) 48 h post transfections as described by the manufacturer. All reporter assay results presented here are from three independent experiments prepared in triplicate and have been normalized for β-Gal activity.HEK 293 and NIH 3T3 cells were treated with 25 mM LiCl for 24 h. Total RNA was extracted with the use of Agilent's Total RNA isolation mini kit (Agilent Technologies). 500 ng of total RNA were used to perform RT-PCR reactions with Qiagen's one step RT-PCR kit (Qiagen) as per manufacturer's instructions at an annealing temperature of 55°C. The samples were analyzed on 1% agarose gel. Primers used:5′-GGATGGCCACCTCTATGAAC-3′, 5′-AGACCTTGGCAGCGTCCT-3′, GAPDH: 5′-AGGTGAAGGTCGGAGTCAACG-3′, 5′-AGGGGTCATTGATGGCAACA-3′.UCH L1: NIH 3T3 cells were treated with 25 mM LiCl for 6 h and RNA was isolated. Reverse transcription reaction was performed with 500 ng of total RNA using the iScript cDNA synthesis kit (Bio-Rad). A 1∶25 dilution of cDNA was used in the QRT PCR reaction. QRT-PCR was carried out in a 15 µl reaction mixture with gene-specific primers for UCH L1 and GAPDH  using iQ-SYBR green kit (Bio-Rad). The PCR conditions were 95°C for 3 min, and 45 cycles of 95°C for 15 s, 55°C for 45 s on the ABI HT 7600 PCR instrument. All samples were assayed in triplicate. The differences in expression of UCH L1 were evaluated using a relative quantification method where the expression of UCH L1 was normalized to the reference gene GAPDH.5′ CATTTACATTCATTCGTATT 3′, 5′ CCTTTCACCATCCCAATTAC 3′) and Site 2 .ChIP assay was carried out using Active Motif ChIP-IT enzymatic kit. KR4 and 293 cells were fixed with 37% formaldehyde for 10 min at 37°C, the reaction was stopped with cold 0.125 M Glycine solution for 5 min at RT. The cells were then washed twice with PBS and collected in 0.5 ml of Digestion buffer with protease inhibitors. Chromatin with sheared with shearing enzyme for 10 min at 37°C to obtain an average of 200–1000 bp fragments. Sheared chromatin was incubated overnight at 4°C with Protein G magnetic beads, sheared chromatin, TCF4 antibody . Immunoprecipitation was performed as per the manufacturer's instructions, cross-linking was reversed by incubated the immunoprecipitated complexes with 5 M NaCL for 2 h at 65°C followed by Proteinase-K treatment for 2 h at 42°C. PCR reaction was performed with 5 µl precipitated DNA using the primer pairs flanking consensus TCF sites in UCH L1 promoter. PCR conditions: one cycle, 95°C for 2 min; 30 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 2 m, and a final extension at 72°C for 10 min. The primers used in the reaction are: Site 1 . The TCF4/Lef1 binding site


An overview is presented of the different aspects of the role ofanalytical chemistry in process monitoring and control. On-linemonitoring is currently the most attractive option in this area,especially with unsegmented-flow techniques. In addition toallowing automation of these systems, the variety of ways in whichcalibration and recalibration can be performed allows theiradaptation to any situation by using extremely simple, home-mademanifolds. The most relevant designs are presented and criticallydiscussed in this paper.


A similar EGF concentration increased AR mRNA level to 550% and 980% of control in MCF-7 and MDA-MB231 cells, respectively. This was accompanied by an accumulation of AR into conditioned culture media. However, HMECs secreted in response to EGF, 5–10 fold more AR than tumour cells. Furthermore, the potential participation of AR in the regulation of the plasminogen activator (PA)/plasmin system was investigated. Whereas HMEC-proliferation was stimulated by AR, the levels of secreted urokinase-type plasminogen activator (uPA) and type-1 plasminogen activator inhibitor (PAi-1) remained unaffected. Conversely, AR failed to regulate the proliferation of tumoral cell lines but induced an accumulation of uPA and PAi-1 into culture media. This was accompanied by an increase of the number of tumoral cells that invaded matrigel in vitro. Moreover, the presence of a neutralizing anti-uPA receptor antibody reversed the increased invasiveness of MDA-MB231 cells induced by AR. These data reveal differential behaviour of normal versus tumoral breast epithelial cells in regard to the action of AR and demonstrate that, in a number of cases, AR might play a significant role in tumour progression through the regulation of the PA/plasmin system. © 2001 Cancer Research Campaign http://www.bjcancer.comAmphiregulin (AR) is a heparin-binding epidermal growth factor (EGF)-related peptide that seems to play an important role in mammary epithelial cell growth regulation. We have investigated the regulation of AR-gene expression and -protein secretion by EGF in normal breast epithelial cells (HMECs), as well as in the tumoral breast epithelial cell lines MCF-7 and MDA-MB231. EGF induced a dose-dependent increase of AR mRNA level in both normal and tumoral cells. Thus, 10


Prostate tumour growth is almost always dependent upon the androgen receptor pathway and hence therapies aimed at blocking this signalling axis are useful tools in the management of this disease. Unfortunately such therapies invariably fail; and the tumour progresses to an “androgen-independent” stage. In such cases androgen receptor expression is almost always maintained and much evidence exists to suggest that it may still be driving growth. One mechanism by which the receptor is thought to remain active is mutation. This review summarises the present data on androgen receptor mutations in prostate cancer, and how such substitutions offer a growth advantage by affecting cofactor interactions or by reducing ligand specificity. Such alterations appear to have a subsequent effect upon gene expression suggesting that tumours may “behave” differently dependent upon the ligand promoting growth and if a mutation is present. The AR gene is situated at Xq11-12 and consists of 8 exons with exon 1 encoding the N-terminal domain and the entire 5’ untranslated region, exons 2 and 3 encoding the DNA binding domain (DBD) and exons 4-8 encoding the “hinge” region and ligand binding domain (LBD) [The Nuclear Receptor family is the largest group of eukaryotic transcription factors, with 48 human receptors presently described . The and1.1via TAU5 [The N-terminal domain contains activation function-1 (AF-1), which is composed of 2, to some extent separable, transcription activation units (TAUs) – TAU1 and TAU5 (residues 1-485 and 360-528 respectively) [in vitro [A polymorphic polyglutamine (CAG) tract is present in the N-terminus of the AR and ranges from 8 to 30 repeats in normal individuals, with a modal length of 20 . The rarin vitro .The N-terminal region of the AR appears to be highly unstructured. A more folded and subsequently proteosome resistant conformation can be achieved by incubation with folding-inducing solvents , and also by binding of the cofactor TFIIF (Transcription Factor IIF) , 11. Thi1.2577, Ser578 Cys579, Lys580 and Val581 of the AR), which from studies using hybrid receptors has been found to confer receptor response element specificity [via interaction of the D-box  with the sugar-phosphate backbone of DNA [The DNA binding domains (DBD) of nuclear receptors have high sequence homology, with differences in the amino acids that contact the DNA eliciting specificity . The DBDcificity , 15-17. 1.3et al. found that amino acids 629-636 of the hinge region are also important in nuclear localisation, protein interactions and the ligand dependent N-/C-terminal interaction [The hinge region of nuclear receptors was originally thought to be a flexible linker region important in DNA binding and dimerisation. Detailed analysis of the region, however, has demonstrated that the region plays a more diverse role than initially thought , 19. Usi1.4The ligand binding domain of nuclear receptors is comprised of 11-12 α-helices and 1 β-sheet that fold to form a triple-layered anti-parallel α-helical sandwich. This folding forms a hydrophobic pocket into which the ligand fits; crystallographic analysis of various members of the family have revealed a highly conserved structure with the exact dimensions of the pocket varying according to the cognate ligand -30. LigaThe predominant activation function in the AR appears to be AF-1, since deletion of AF-2 and the LBD results in a constitutively active receptor with similar activity to the wild-type receptor in the presence of agonist , 35. Rec1.52). Ligand binding promotes dissociation from this complex, dimerisation, nuclear localisation and intra- and inter-receptor interactions [23FQNLF27 motif interacting with the AF-2 cofactor-interaction surface. It is important for transcriptional activity since it increases receptor stability, reduces ligand off-rate and creates interaction sites for accessory proteins [The unliganded AR is predominantly cytoplasmic , 38 and ractions . The AR,proteins , 42.via LxxLL motifs (where L is leucine and x is any amino acid), which form an amphipathic α-helix that binds directly to the hydrophobic AF-2 coactivator groove [The AR has been found to interact with a large number of proteins that enhance receptor activity, termed coactivators. Such factors often have, or recruit proteins that have, histone acetyltransferase activity and are hence believed to increase receptor activity in part by relaxing chromatin structure. The best characterised are the p160 family of coactivators, consisting of SRC-1/NCOA1 (Steroid Receptor Coactivator-1 / Nuclear Receptor Coactivator 1), SRC-2/NCOA2/TIF-2/GRIP-1  and SRC-3/NCOA3/AIB1/pCIP/RAC-3 (Amplified In Breast Cancer-1 Protein / CBP-Interacting Protein / Receptor-Associated Coactivator 3) . Many cor groove , 45. Unlr groove , 47. Stur groove . This devia recruitment of histone deacetylases to condense chromatin structure, and via nuclear exclusion of the receptor [Conversely, corepressor proteins have also been identified, for example Nuclear Co-Repressor Protein (NCoR) and Silencing Mediator for Retinoid and Thyroid Hormone Receptor (SMRT), which have been found to bind to both agonist- and antagonist-bound receptors and reduce their activity. There are multiple mechanisms by which corepressors appear to inhibit receptor signalling - for example, receptor .via response elements located within the regulatory regions of target genes. The AR has been found to bind strongly to an inverted repeat of a 5’-TGTTCT-3’ half site (termed the core recognition sequence) separated by 3 base pairs [PSA (Prostate Specific Antigen) and SC (Secretory Component) [The AR interacts with DNA se pairs -52. Thisse pairs , 53, 54.mponent) -58.2The prostate is a secretory gland located at the base of the bladder with a composition that is approximately 70% glandular elements  and 30% fibromuscular stroma . The str2.1Prostate cancer is the most common cancer in men in the United Kingdom, with approximately 35,000 men diagnosed every year . The big2.2via the pituitary-hypothalamus signalling axis to block androgen production. These analogues successfully reduce circulating levels of testosterone by more than 95%, but levels of adrenally produced androgen precursors such as dehydroepiandrosterone remain unaffected, and these can be effectively converted in the prostate into the potent androgen dihydrotestosterone [Approximately 25% of prostate cancer patients have organ-confined disease upon presentation and for such patients radical prostatectomy  offers the highest likelihood of long-term disease free survival . Unfortuosterone , 66. Henvia the recruitment of corepressors to the regulatory regions of target genes. Shang et al. for example, found that the corepressors NCoR and SMRT were recruited to the promoter region of the PSA gene following treatment with the antiandrogen Bicalutamide [Antiandrogens are ligands that can bind to the AR and hold it in an inactive state. The exact mechanisms of antiandrogen action are not completely understood, but they appear to function at least in part lutamide . In cont2.3Hormone therapy is successful in the majority of patients, resulting in both symptomatic and pathological improvement. Unfortunately this therapy invariably fails after a median of 2 years and the tumour progresses to a more aggressive “androgen-independent” stage. To call this stage androgen- or hormone- independent is perhaps misleading since in most cases the AR is expressed and much data suggests that the receptor is still functional. Several mechanisms have been proposed to explain how the AR may still be driving growth even in the androgen-depleted environment and these include AR amplification, alterations in cofactor levels and AR mutation .2.4et al. for example, found that out of 99 patients in the early stages of prostate cancer, none had mutation(s) in the AR coding sequence [In early stages of prostate cancer mutations of the AR are rare but their frequency is significantly increased in advanced, androgen-independent tumours suggesting that AR mutations play a role in tumour progression -72. Marcsequence . In advaet al. compared the activity of 44 such mutations and found that 20 had a gain of function [Over 70 different somatic missense AR mutations have been described in patients with prostate cancer . Shi et function . Cells c2.4.11). Tilley et al. for example, identified dual somatic missense mutations within the N-terminal polyglutamine tract [Although most mutations lie in the LBD, more than 30 substitutions associated with PCa have been identified in other parts of the receptor , but has higher affinity for the latter. We have studied the preference of several of the most commonly identified mutant receptors  for these motifs and found striking differences in motif utilisation dependent upon which ligand is activating the receptor . In the 3). The charge clamp residues form electrostatic interactions with the main chain atoms at either end of phenylalanine-rich motifs whereas LxxLL motifs only form hydrogen bonds with Lys720. Charge clamp residue Glu897 is located in helix 12, the positioning of which is likely to be affected by the agonist bound. Therefore if an agonist is bound that does not induce the correct positioning of the charge clamp residues for interaction with phenylalanine rich motifs, then the site appears to be available for LxxLL motif binding.The coactivator interaction groove of the AR is comprised of an L-shaped cleft comprised of three distinct subsites  that bind hydrophobic groups at the +1, +4 and +5 positions in cognate peptides . The conKallikrein 2, KLK2, and Differentiation Regulated Gene-1, DRG-1) and cell cycle progression  in the LNCaP prostate cancer cell line, which endogenously expresses the T877A mutant AR [KLK2 and CDK2 in response to different ligands was similar – induced most strongly by androgen, then the antiandrogen hydroxyflutamide then cyproterone acetate. Evidence of CDK4 being an androgen-regulated gene is contradictory, with upregulation in response to androgen reported in some studies [CDK4 in response to androgen, but interestingly the two antiandrogens did induce expression. Even more striking was the regulation of DRG-1, which we found to be highly upregulated by androgen (more than 12-fold) and only weakly by hydroxyflutamide (approximately 1.7-fold). Hence the mutant AR induced different “patterns” of regulation of a subset of androgen-regulated genes according to the ligand. Since this includes genes that are involved in tumour growth, there may be implications for tumour progression and treatment.Several studies have demonstrated that inter- and intra-receptor interactions made by the AR have differential effects dependent upon promoter context -88. We hutant AR . The exp studies  but not  studies . In agre3The findings summarised here have important implications for the treatment of prostate cancer. The data suggest that tumours may behave differently dependent upon (i) which mutation, if any, is present and (ii) which ligand is driving growth, since different subsets of genes may be regulated. We suggest that it would therefore be useful to screen patients for AR mutations following hormone therapy failure, so that subsequent treatment could be adjusted accordingly. Understanding of how AR mutations alter androgen signalling at the molecular level will also be useful in the development of novel therapies, in particular Selective Androgen Receptor Modulators (SARMs). Knowledge of how such molecules affect the structure of the AR, interactions that the receptor makes and subsequently gene expression could aid in designing drugs that regulate certain subsets of genes. For example, it would be desirable to design a SARM that blocks expression of androgen target genes that promote tumour growth, whilst up-regulating transcription of beneficial genes (for example those important for maintenance of bone density).


In the industrial world, non-specific back and neck pain (BNP) is the largest diagnostic group underlying sick-listing. For patients with subacute and chronic  BNP, cognitive-behavioural rehabilitation was compared with primary care. The specific aim was to answer the question: within an 18-month follow-up, will the outcomes differ in respect of sick-listing and number of health-care visits?Return-to-work share (percentage) and Return-to-work chance (hazard ratios) over 18 months, Net days (crude sick-listing days × degree), and the number of Visits  over 18 months and the three component six-month periods. Descriptive statistics, Cox regression and mixed-linear models were used.After stratification by age (≤ 44/≥ 45 years) and subacute/chronic BNP, 125 Swedish primary-care patients were randomly allocated to cognitive-behavioural rehabilitation (rehabilitation group) or continued primary care (primary-care group). Outcome measures were Return-to-work share and Return-to-work chance were equivalent between the groups. Net days and Visits were equivalent over 18 months but decreased significantly more rapidly for the rehabilitation group over the six-month periods (p < .05). Subacute patients: Return-to-work share was equivalent. Return-to-work chance was significantly greater for the rehabilitation group (hazard ratio 3.5 [95%CI1.001 – 12.2]). Net days were equivalent over 18 months but decreased significantly more rapidly for the rehabilitation group over the six-month periods and there were 31 days fewer in the third period. Visits showed similar though non-significant differences and there were half as many in the third period. Chronic patients: Return-to-work share, Return-to-work chance and Net days were equivalent. Visits were equivalent over 18 months but tended to decrease more rapidly for the rehabilitation group and there were half as many in the third period (non-significant).All patients: The results were equivalent over 18 months. However, there were indications that cognitive-behavioural rehabilitation in the longer run might be superior to primary care. For subacute BNP, it might be superior in terms of sick-listing and health-care visits; for chronic BNP, in terms of health-care visits only. More conclusive results concerning this possible long-term effect might require a longer follow-up.NCT00488735. In Sweden, as all over the industrial world, back and neck pain is the largest diagnostic group underlying sick-listing . The vasAs 93% of the societal costs of back and neck pain are connected with sick-listing . HoweverConcerning treatment of BNP, the 1990s saw a breakthrough for the biopsychosocial model, which pinpoints time off work as an important disabling factor. Acute, subacute and chronic BNP are defined as BNP with full-time sick-listing for 0 – 21 days, 22 – 84 days and more than 12 weeks, respectively . Acute BThe high frequency of relapses after rehabilitation of BNP is associated with inadequate follow-ups. A short program might fail to achieve long-standing behavioural changes . In the Primary care is the appropriate source of treatment for BNP . In SwedOur project started in 2000 with the aim of comparing a multidisciplinary programme of cognitive-behavioural rehabilitation for subacute and chronic BNP with primary care. The specific aim of this study was to answer the question: within an 18-month follow-up, will the outcomes differ in terms of sick-listing and number of health-care visits?In Sweden, publicly provided, tax-financed social insurance compensates loss of income due to illness. The ultimate decisions about sick-listing benefits, including sickness benefit, rehabilitation benefit, temporary disability pension and disability pension, are made by the Social Insurance Agency. For sick-listing exceeding seven calendar days, a physician's certificate is required. The certificate comprises a detailed description of symptoms and signs and a recommendation of the degree ) and duration of sick-listing.The rehabilitation centre of this study was situated at Haninge, a municipality 25 kilometres south-east of Stockholm city. As the centre was well known to the local residents, the study participants were recruited within the primary care of the adjoining municipalities. One-hundred-and-twenty five patients were recruited by 42 family doctors at 12 health centres.The criteria for inclusion: 1. Working age up to and including 59 years. 2. Sick-listed full-time for BNP at least six weeks (42 days) and at most two years (730 days). 3. Able to fill in forms. The criteria for exclusion: 1. Temporary disability pension or disability pension being paid or in preparation. 2. A primary need for a hospital specialist . 3. Pregnancy and diseases (other than BNP) that might make rehabilitation impracticable . 4. Whiplash-associated disorders as a primary obstacle to working. 5. Previous rehabilitation at the rehabilitation centre. 6. Other multidisciplinary rehabilitation current or planned.One treatment group was allocated to cognitive-behavioural rehabilitation at the rehabilitation centre (rehabilitation group). The other treatment group was allocated to continued primary care (primary-care group).The rehabilitation centre was opened in 1991 within Stockholm County Council. From 2002 it operated as a private company and the number of rehabilitation teams was decreased from four to one, comprising four team members: a physician (OL), a physiotherapist trained in manual therapy, a psychologist or a social worker trained in cognitive-behavioural therapy and a health-care adviser. Manual therapy includes manipulation, mobilisation and stabilizing training . The cenParticipation in the rehabilitation group did not exclude the patient from seeking other care, including primary care, during the follow-up period.The hubs of Swedish primary care are the health centres. They serve the local population and cater to its needs, with no restrictions as to illness, age or patient category, for basic medical treatment, nursing, preventive work or rehabilitation that does not require the medical and technical resources of hospitals or other special competences . Most prParticipation in the primary-care group excluded the patient from turning to the rehabilitation centre during the follow-up period but not from any other health-care, including multidisciplinary rehabilitation at units other than the rehabilitation centre.The percentage of patients who regained any degree of work ability for at least 30 days in succession over 18 months. This was the primary outcome measure. Secondary outcome measures were:The chance, as expressed in hazard ratios, of achieving any degree of work ability over 18 months, irrespective of the duration of that work ability.Net days = crude days × degree %) respectively, and multidisciplinary rehabilitation at other units than the rehabilitation centre by 1/50 (2 [-2 – 6]%) and 4/43 (9 [0 – 18]%) respectively. The differences were non-significant.Return-to-work share increased to 44 [28 – 59]% for the chronic rehabilitation-group patients, and decreased to 44 [30 – 59]% for the chronic primary-care-group patients. This differed only marginally from the intention-to-treat analyses.When the incorrectly included rehabilitation-group patient Figure  was counThis randomized controlled trial concerned primary-care patients with subacute and chronic BNP. A programme of cognitive-behavioural rehabilitation was compared with continued primary care. The results were equivalent over 18 months. However, analyses of the three component six-month periods indicated that the rehabilitation programme might be superior to primary care in the longer run, especially for subacute patients.Return-to-work share substantially lower than expected for the rehabilitation group and higher than expected for the primary-care group? According to Englund et al. [Return-to-work share for the primary-care group ? One explanation might be a project that was initiated by the Swedish government in 2002 to halve the extent of sick-listing by 2008 [Return-to-work share in the rehabilitation group was disappointing, and even if the primary-care group had shown as low a Return-to-work share as predicted, the difference between the groups would have remained non-significant.Why was the d et al. , sick-li by 2008 . The foc by 2008 ,41. AnyhReturn-to-work share for the subacute rehabilitation-group patients was as expected, but the share for the chronic rehabilitation-group patients was far lower. The significantly better Return-to-work chance at 18 months and the more rapid reduction in Net days among the subacute rehabilitation-group patients highlighted this. Previous research supports the view that cognitive-behavioural interventions at an early stage of disabling BNP can prevent long-term disability [However, when subacute and chronic patients were analysed separately, a different picture emerged: the sability ,10,14,42sability  concludesability .What components of our programme could explain its possible superiority in the long run for subacute patients? Previous research on graded activity had an occupational-care setting and concerned subacute patients only ,18,44,45Unlike previous research on graded activity, we also included chronic BNP. Most of the rehabilitation-group patients (43/63 (68%)) had a current sick-listing exceeding 12 weeks at baseline. Our programme did not reduce their sick-listing. Why? One reason could be its comparatively limited extent. Haldorsen et al.  showed tby the book includes: two sessions/week over a maximum of 3–6 months until lasting full-time return-to-work, an early agreement with the patient on a return-to-work date regardless of the actual pain on that particular day, and a hands-off approach [Net days during the first period. It has recently been pointed out that suboptimal rehabilitation items in the pre-phase of return-to-work entail the risk of a counterproductive effect [Another reason could be methodological defects. Graded activity approach ,18. As oapproach ), the poVisits in the long run. Also, although the differences were not significant, the rehabilitation group tended to experience less surgery and other multidisciplinary rehabilitation. For patients with subacute BNP, this agrees with Linton et al. [In total, the rehabilitation group had more consultations by a physician, which is more costly than other staff categories. However, the resources spent on the rehabilitation group in the first six-month period were balanced by fewer consultations in primary care and a trend towards fewer n et al. , whose cn et al. .The design of our study, a randomized controlled trial, is the gold standard for evaluating treatment methods for back and neck pain .Visits over 18 months should be interpreted with some caution as 32% were non-responders, but in other respects the follow-up rate of the primary-care group was also satisfactory. The non-responders in the rehabilitation group had characteristics that may have increased health-care use (longer sick-listing periods and higher unemployment). In the primary-care group the non-responders were younger, which could have decreased utilization, whereas the lower health-related quality of life could possibly increase utilization. However, for the great majority, there were no significant differences at baseline between the non-responders and responders.The sick-listing data were complete. We also consider the health-care data to be acceptably representative. The response rate was higher than 80% except at 12 months, when it was nearly 80% for the primary-care group. Even when the missing data for the two deceased patients were included, the rehabilitation group met drop-out criteria . For theThe inclusion plan was not fulfilled. A possible consequence may have been that some differences between the groups could not be demonstrated. However, certain differences in favour of the rehabilitation group were clear with the number of patients actually included.Comparison of health-care visits gives only a limited idea of cost effectiveness. A complete health-economic evaluation is planned in a future study, including a cost-benefit analysis in which the direct costs (mainly of the interventions themselves), the indirect costs (mainly of the sick-listing), and the health-related quality of life are compared .Net days and Visits were also equivalent over 18 months. As differences in the results of various interventions tend to even out after 12 – 18 months [The primary outcome measure showed no difference. Notwithstanding the positive trends in favour of the rehabilitation group, especially for the subacute patients, 8 months , more coFor patients with subacute and chronic BNP, cognitive-behavioural rehabilitation was compared with primary care. The results were equivalent over 18 months. However, there were indications that cognitive-behavioural rehabilitation in the longer run might be superior. For subacute BNP, it might be superior in terms of both sick-listing and health-care visits; for chronic BNP, in terms of health-care visits only. More conclusive results concerning this possible long-term effect might require a longer follow-up.The authors declare that they have no competing interests.OL was the main investigator, carried out the study, performed the analysis, and drafted the manuscript. SEJ contributed to the statistical analysis. LES, as supervisor for OL, participated in all phases of the study. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Pranayama (Voluntary Regulated Breathing) and Yogasana (Yoga Postures) that range from very dynamic, active movements that go from one posture to another (and result in a thorough aerobic workout) to more slow-paced practices that hold postures for several minutes and form an intense strength training and balanced workout. Twenty male junior footballers younger than 15 years of age, belonging to the Mohun Bagan Athletic Club, Kolkata, were selected for the study at Haridwar. They had to play in a Football Cup organized in UK and they were here to practice yoga sequences taught by Swami Ramdevji.[yogic practices before this yoga training session. There was a significant reduction in the levels of serum cholesterol, Low-density lipoprotein (LDL) cholesterol, serum triglycerides, and very-low-density lipoprotein (VLDL)-cholesterol at the end of the yoga session. The results indicated that the fasting blood sugar (FBS) level was positively elevated in junior footballers. This demonstrated that Pranayama and Yogasana were helpful in regulating sugar level also [There are many styles of Ramdevji. They wervel also .Yoga)- Pranayama and Yogasana sequences on blood lipid profiles in normal healthy footballers. Pranayama and Yogasana can be used as supportive therapy in patients with lipid disorders, heart diseases, hypoglycemia, and so on. There is a need for conducting the experiments on a larger number of participants, to explore the results and mode of action.The present study demonstrates the efficacy of SRY (Swami Ramdev


Introduction. Post-prostatectomy erectile dysfunction affects a considerable number of men and is a significant quality of life issue. There has been a substantial amount of research on the treatment of post-prostatectomy ED, and now there is a rising interest in the concept of penile rehabilitation. The goal of penile rehabilitation is to moderate the destructive processes that occur after prostatectomy in order to preserve erectile function, either through spontaneous or assisted means. Methods. We reviewed published data and experiences of post-prostatectomy penile rehabilitation using regimented interventions of phosphodiesterase inhibitors, vacuum erectile device, and intracavernosal agents, and we present and analyze the research conducted. Results. These studies show improved objective and subjective clinical outcomes in regards to physical parameters, sexual satisfaction, and rates of spontaneous erections. Conclusion. These studies are often limited by small size, study period, and study design. There continues to be a need for large, randomized, placebo controlled trials with adequate followup to fully evaluate the efficacy and cost-effectiveness of the various proposed penile rehabilitation regiments before a clear standard can be established. Erectile dysfunction following prostatectomy remains asignificant quality of life issue for men undergoing prostatectomy. It isestimated to affect 26–100% of patientsafter surgery [Progress has been made in identifying the events that contribute to erectiledysfunction after prostatectomy. The changes of neuropraxia, ischemic andhypoxic insults, fibrotic remodeling, and apoptosis are all believed tocontribute to erectile dysfunction , 4. ThesHowever, the research has yet to be translated into acoherent clinical strategy for penile rehabilitation. As such, there areno currently accepted guidelines for penile rehabilitation regiments.Certainly, there exist several popular options that are currently in use.In practice, three principle modalities of treating post-prostatectomy erectiledysfunction are employed. This paper will review the efficacy of theseoptions in this patient population for the purposes of penile rehabilitation.The introduction of phosphodiesterase inhibitors (PDEi) revolutionizedthe treatment of erectile dysfunction. Since entering the market in 1998,these medications have become nearly synonymous with erectiledysfunction. Their ease of use and relatively safe profile have made thempervasive in the treatment of erectile dysfunction. They have also beenextensively investigated. A Cochrane meta-analysis looking at many large,randomized clinical trials concluded that PDEi are efficacious in the treatmentof erectile dysfunction and are generally safe . HoweverOne of the first studies on PDEi in rehabilitation lookedat objective data to support this use. Schwartz et al. conducted a study on 40 men who had undergone nervesparing prostatectomy . Prior tBannowski et al. conducted a randomized trial following 43men who underwent nerve-sparing radical prostatectomy . All menN = 18), 50 mg Sildenafil (N = 17), or placebo (N = 19). The groups were then analyzed at16, 28, and 40 weeks. Then after 40weeks, all medications were discontinued and the groups were again analyzed at48 weeks. At each point, theparticipants were evaluated by NPTR and IIEF . The study found that the groups receiving daily Sildenafil were able tohave return of rigidity (R > 55%) at seven times the nadir value compared to minimalimprovement in the control group. Thisimprovement of erection was also seen by the investigators for RAU , with the additional finding that the 100 mg group experienced continuedimprovement after the discontinuation phase, while the 50 mg group began toexperience decline in RAU. Importantly,the men on daily Sildenafil were five times more likely to have return of spontaneous,unassisted erection sufficient for intercourse compared to placebo. The authors were able to link objectivemeasurements of erections with subjective, clinical response. They noted that tip rigidity >55% clearlyseparated responders versus nonresponders . This study may mark objective validation as an important component offuture clinical trials. These initialresults are from a subset analysis performed on men who showed normal EF andNPTR on baseline, and we await further data and analysis on the entire studypatients.A stringent, randomized,double-blinded, placebo controlled study was performed by McCullough et al.evaluating the efficacy of daily Sildenafil in men after bilateral nerve-sparingradical prostatectomy . This stTaken together,these studies seem to indicate that phosphodiesterase inhibitors have a role inpenile rehabilitation for men after prostatectomy. There may also be a dose-dependent relationship between the medication and outcomes. The studies also confirm the tolerability andsafety of such a regiment, as discontinuation rates were very minimal and noadverse events were reported.The Vacuum erectile device assists erections by drawing blood flow into thecavernous sinuses through negative pressure, physically causing anerection. A constrictive band can also be placed at the base of thepenis, preventing backflow and maintaining corporal pressures. Thisdirect mechanism of action can circumvent the limitation of oral agents, whichrequires an intact and functioning neuronal connection to produceerections. This can be a significant factor even in men undergoing nervesparing prostatatectomy, as neuropraxia still occurs and can diminish theeffectiveness of PDEi.Thistreatment modality can also be extended to men who have undergone nonnervesparing prostatectomy, though not in the context, in penile rehabilitation withthe expectation of return of potency.If not for potency itself, VED usage has also been advocated due to itspossible efficacy in preventing penile shrinkage and maintaining length.Studies have shown significant shrinkage of penile length, with onestudy finding that nearly 20% of men experience a loss of length greater than15% . In anotN = 74) versus no erectogenic aid (N = 35) [n = 4) of the control group that had sucherections. In regard of the effect ofVED on penile length, the men who adhered to VED regiment experienced lesssubjective penile shrinkage, with 23% reporting less length compared to 85% ofthe men who quit treatment and 65% of the control. No objective data was collected concerninglength. The authors conclude that earlyuse of VED with the purpose of penile rehabilitation improves sexual andpartner satisfaction and allow for earlier return of spontaneous erections. Although,the rate of return of spontaneous erection is low for both groups, thosenumbers include men who had undergone nonnerve sparing prostatectomies. This distinction is necessary, as penilerehabilitation is more directed for NS men and the inclusion of nonnerve sparingprostatectomy patients diluted the response to rehabilitation.Raina et al. randomized 109 post-prostatectomy men toeither early VED use daily ((N = 35) . The menThe timing of when to initiate VED has been questioned,with some advocating an earlier intervention. Köhler et al. randomized 28men to either receive early VED regiment (1 month after RP) or delayed VEDregiment (6 months) . The regThe value of VED in penilerehabilitation remains uncertain. Dailyregimented use of VED requires a motivated patient and does improve sexualsatisfaction in those who responds. Ifthe stated goal of penile rehabilitation is the return of preexisting potency,then further studies are needed to show that VED improves the rate of return oferection. However, VED use may also be advocated for its effects on preventingpenile shrinkage after prostatectomy.Intracorporeal injection of vasoactive agents increase blood flow into thecavernous sinuses locally, either through increasing cAMP, by antagonizing alpha-adrenergicreceptors, or by direct smooth muscle relaxation. Like VED, they also donot require an intact, functional nervous system to produce erections.Thus, they can also be offered in men who have undergone nonnerve sparing surgeryand men who do not respond to oral agents.Montorsi et al. conducted a randomized trialinvestigating whether a regiment of intracavernosal injections improveserectile function in post-prostatectomy men . 30 men Mulhall et al. conducted a trialthat may be more clinically applicable, even though it was not randomized . InthisStudies have examined the feasibility and efficacy ofemploying two treatment modalities during penilerehabilitation. Nandipati et al. incorporated both intracavernosaltherapy and PDEi in a group of 22 men who underwent nerve sparing prostatectomy. All parOther therapies outside of these three mainstreammodalities have been investigated for penile rehabilitation afterprostatectomy. Recently, investigators in Korea looked at statins for treatingerectile dysfunction after prostatectomy . The basSexual potency after prostatectomy remains a significant quality of life issueafter prostatectomy. There exist many studies on the efficacy of thevarious treatment options on this patient population. There are much less data looking on theeffects of regimented usage of PDEi, VED, and/or ICI in improving erectilefunction in this group, and no guidelines exist to help steer theclinician. We are still in need of large, randomized, controlled, clinicaltrial with adequate, long-term followup to evaluate this question. Moreover, even after each treatment can beestablished to be efficacious in penile rehabilitation, the exact regiment amount andduration will still be open to further investigations for optimization. This isa especially important question in dealing with phosphodiesterase inhibitors,where the cost of treatment is substantial. However, even though currently sparse, the consistent, growing body ofevidence does support penile rehabilitation in improving return of sexualfunctioning. As awareness of penilerehabilitation increases and becomes more accepted, it is becoming moredifficult to conduct placebo or nonintervention controlled trial. There arestill several ongoing trials evaluating penile rehabilitation, including alarge multicenter study examining penile rehabilitation with medicated urethral system for erection (MUSE), and several of the studies presented here will further analyze with additional data from which the urology community may further define when and how toimplement penile rehabilitation in post-prostatectomy men.Currently, the body of evidence doesseem to suggest a beneficial role for penile rehabilitation after prostatectomyin improving return of potency. Such a program should begin with a detailedevaluation on the preoperative sexual performance characteristic of the patientand then a thoroughdiscussion of the available rehabilitation regiments. The practitioner should consider factors thatare important to the patient including ease of use and compliance, patientmotivation, conditioning, cost and patient expectations about sexual function,and penile length. Penile rehabilitationmay continue to remain investigative until more standardized clinical databecomes available.


The androgen receptor (AR) plays important roles in the development of male phenotype and in different human diseases including prostate cancers. The AR can act either as a promoter or a tumor suppressor depending on cell types. The AR proliferative response program has been well studied, but its prohibitive response program has not yet been thoroughly studied.CGAGCTCTTC, which together mapped to 27.3% of AR binding regions . In contrast, only about 2.9%  of AR binding sites contains the canonical AR matrix M00481, M00447 and M00962 (from the Transfac database), which is derived mostly from AR proliferative responsive genes in androgen dependent cells. In addition, we identified four top ranking co-occupancy transcription factors in the AR binding regions, which include TEF1 , GATA (GATA transcription factors), OCT (octamer transcription factors) and PU1 (PU.1 transcription factor).Previous studies found that PC3 cells expressing the wild-type AR inhibit growth and suppress invasion. We applied expression profiling to identify the response program of PC3 cells expressing the AR (PC3-AR) under different growth conditions (i.e. with or without androgens and at different concentration of androgens) and then applied the newly developed ChIP-seq technology to identify the AR binding regions in the PC3 cancer genome. A surprising finding was that the comparison of MOCK-transfected PC3 cells with AR-transfected cells identified 3,452 differentially expressed genes (two fold cutoff) even without the addition of androgens (i.e. in ethanol control), suggesting that a ligand independent activation or extremely low-level androgen activation of the AR. ChIP-Seq analysis revealed 6,629 AR binding regions in the cancer genome of PC3 cells with an FDR  cut off of 0.05. About 22.4%  can be mapped to within 2 kb of the transcription start site (TSS). Three novel AR binding motifs were identified in the AR binding regions of PC3-AR cells, and two of them share a core consensus sequence Our data provide a valuable data set in understanding the molecular basis for growth inhibition response program of the AR in prostate cancer cells, which can be exploited for developing novel prostate cancer therapeutic strategies. Androgens and the androgen receptor (AR) play important biological roles in the development of male phenotype and urogenital tissues, including prostate, and in the initiation and progression of many human diseases. Alterations in AR sequences and expression levels and perturbations in AR signaling networks have significant roles in the genesis and maintenance of prostate cancers (PCa) In contrast, Yuan et al. showed an androgen-induced inhibition of cell proliferation in an androgen-insensitive prostate cancer cell line (PC3) transfected with a human androgen receptor complementary DNA. They showed that in PC3 cells expressing the transfected androgen receptor (PC3-AR) under the simian virus 40 (SV40) promoter, androgen decreased the proliferation rate and cloning efficiency and induced a more differentiated phenotype. Their data demonstrated that PC3 cells have retained the cellular machinery required to respond to the activated androgen receptor. Similar results were obtained showing that androgens suppress the proliferation of PC3-AR cells using two other promoters: cytomegalovirus (CMV) promoter in vitro and in vivo invasion capabilities. All these data generated in PC3 cells seem to contradict the traditional belief that the AR functions as a stimulator in prostate tumor growth and metastasis. As PC3 cells expressed the basal marker-CK5 Niu et al. recently found that AR is a tumor suppressor or a proliferator in prostate cancer depending on cellular contexts We hypothesize that PC3 cells possess cellular machinery that turn the AR in PC3-AR cells into growth suppressor. We applied expression profiling to identify the response program of PC3-AR cells to different growth conditions (i.e. with or without androgens and different concentration of androgens) and then applied the newly developed ChIP-seq technology to identify the AR binding regions under androgen deprivation conditions. Out data provide a valuable data set in understanding the molecular basis for the growth prohibitive response program of the AR in advanced prostate cancers. The growth prohibitive properties of the AR or its response program can be exploited for developing novel prostate cancer therapeutic strategies.In an effort to characterize androgen-induced growth inhibition mechanism and to identify targets that could be used to induce growth inhibition and differentiation in advanced prostate cancer cells, we used PC3 cells transfected with the wild-type AR as a model and performed gene expression profiling analysis. We compared PC3 cells with or without harboring the wild-AR construct in the growth conditions of 1 nM R1881, 10 nM R1881 and ethanol (the solvent for R1881). The MOCK control is PC3 cells transfected with empty vectors.http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15091).To our surprise, the comparison of MOCK-transfected PC3 cells with AR-transfected cells showed 3,452 genes with differential expression (two fold cutoff) even without addition of androgens (i.e. in ethanol control) . A carefUsing GOminer analysis The GO terms enriched by the down regulated genes include GO terms involved in transport and cellular localizations, and in general metabolic process such as the TCA (GO:0006099 tricarboxylic acid cycle) cycle, which again is consistent with the growth inhibition phenotype observed .In order to identify the direct targeted genes of AR in the ligand-independent AR response program, we performed ChIP-seq of the DNAs from anti-AR chromatin IP, as described by Barski et al. The same transfected PC3 cells as we used for gene expression profiling were used for ChIP-seq analysis. Transfected PC3 cells were grown without the addition of androgens. After ChIP-seq analysis, we obtained a total of 5,354,469 20-nucleotide (nt) sequence tags that can be mapped uniquely to the human genome allowing up to two mismatches to accommodate normal polymorphisms. We also performed ChIP-seq analysis for IgG negative controls and obtained 1,089,089 tags.BACH1 on chromosome 21. We used the CisGenome program The top 10 mostly strong AR binding regions by the number of sequence tags mapped contain the genes for ATIC (IMP cyclohydrolase), TUSC1 (Tumor suppressor candidate 1), AQP2 (Aquaporin 2), GFRA1 , PACRG (PARK2 co-regulated), OR1J1  and genes with unknown functions such as KIAA0350 and FAM118A . Interestingly, among the top ten AR binding regions, there are two AR binding regions (chr2: 19587584–19587634 and chr16: 74498964–74498992) that seem not mapped to any known genes. However, chr16: 74498964–74498992 is about 46 kb away form spliced EST BX094831, and chr2: 19587584–19587634 is about 35 kb from spliced EST BG219799, suggesting that these two genes may be the genes yet to be fully characterized and possibly regulated by the AR.To confirm that ChIP-seq is able to identify AR binding in genes, we randomly picked 5 genes and confirmed enrichment of 4 genes in the ChIP DNA pulled down by the AR antibody compared to ChIP DNA pulled down by the mouse IgG control . The FDRWe then mapped these binding regions to the human genome and categorized these binding regions based on their locations relative to the genes in the human genome using the CisGenome's annotation functions. The mapping was done with the gene annotations from the UCSC genome annotation database (09/05/2008) for the human genome . We tabulated the frequencies of AR binding sites to the transcription start sites (TSSs) for every two kilo bases. A histogram of AR binding sites residing within the downstream 50 kb or upstream 50 kb genomic regions relative to annotated TSSs is shown in To answer the question whether ligand-independent AR binding to the genomic regions exerts functional consequences through changes in the expression level of the targeted genes, we integrated the ChIP-seq data with gene expression profiling data.2163 AR binding genes (2679 AR binding regions) identified by ChIP-seq have corresponding genes on the array we used for expression profiling analysis. Comparing the expression profiling data with the ChIP-seq data, we identified a total of 727 genes (937 AR binding regions) for which the genes were changed by two fold in the ETOH vs. Mock comparison; among them, 543 genes (716 AR binding regions) were down regulated, and 184 genes (221AR binding regions) were up-regulated. Addition of 1 nM R1881 generated an additional 43 genes (28 down regulated and 15 up regulated), and addition of 10 nM R1881 identified a further 89 genes (66 down regulated and 23 up regulated). The union of the three analyses identified a total of 859 genes (1114 AR binding regions)  that are differentially expressed at various concentrations of androgens by at least two fold (in vitro binding data or from a limited numbers of human promoters: the M00481 (consensus: GGTACANNRTGTTCT)AGWACATNWTGTTCT)WGAGCANRN). To see how many AR motifs were found in the AR binding regions, we loaded the AR matrix (obtained from the Transfac TF database) tables for M00481, M00447 and M00962 into the CisGenome program to compare to all AR binding regions that we identified in PC3 cells with a likelihood (LR) ratio of 500 compared to genomic background. We identified 40, 21, 147 respectively for M00481, M00447 and M00962  d M00962 . The unitif CGAGCTCTTC. We were curious whether the sequence motif shows any similarities to known binding motifs. Using JASPAR: an open-access database for eukaryotic transcription factor binding profiles (http://jaspar.genereg.net/)http://scop.mrc-lmb.cam.ac.uk/scop/data/scop.b.b.cdh.b.b.html). They are very similar in structure, with the RMSD (root mean square deviation) between two structures being 1.35 angstrom although the sequence similarity is only 47%. However, a search using the NR3C1 matrix using the CisGenome program with the same criteria we used previously only identified 53 matches to NR3C1 motif, suggesting that the NR3C1 motif, although is the highest ranking matches of known TFs, is different from the new motifs we identified. The new motif we identified with the core sequence CGAGCTCTTC is truly a novel motif not previously defined.Since the percentage of the ARE identified in our AR binding regions is low, we asked the question whether there exists novel AR binding motifs in the AR binding regions of PC3 cells. We hypothesize that the AR binding motif in the prohibitive responsive PC3-AR cells might be different from that in the proliferative prostate cancer cells. We therefore used the Gibbs Motif Sampler of the CisGenome program to identify novel AR binding motifs. With a likelihood (LR) ratio of 500 compared to AR IGG ChIP-Seq background, we identified five novel putative AR binding motifs. Two of these motifs are general GC rich or AT rich sequence motifs and may not be specific and were discarded. The reminding three new motifs were named AR new motif Gib1 to 3. AR new motif Gib1 to 3 can be mapped to 1448, 1012, 317 AR binding regions respectively , S6, S7.http://homes.esat.kuleuven.be/~thijs/download.html) and scanned all TF motifs (PWM databases) using the human transcription factor subset of the Transfac professional 7.0. The matrices with the top ranking matches include TF matrix TEF1_Q6 , GATA_Q6 (GATA transcription factors), OCT_Q6 (octamer transcription factors) and PU1_Q6 (PU.1 transcription factor) with frequencies of 7.8%, 6.3%, 5.2%, 5.2%, respectively. The result of motif scanning is provided as We were curious whether other known TFs could be bind to the AR binding regions that we identified and act as AR cooperators for regulation of gene expression. In order to systematically search for potential bindings of other transcription factors, we used the MotifScanner program  even without addition of androgens . This obThe PC3-AR expression model is in contrast to the androgen-sensitive and widely used LNCaP cell line, which, although expresses AR, but harbors a mutated AR (a missense mutation T877A) that confers promiscuity in its ligand binding. The mutated AR in LNCaP cells can be activated not only by androgens but also by progesterone, estrogen, adrenal androgens, and hydroxyf lutamide We applied ChIP-seq technology to build a genome-wide high-resolution map of the AR binding regions in PC-3 cell line transfected with the AR. About 22.4% (638 of 2849) of the AR binding regions in PC3-AR cells can be mapped to within 2 kb of the transcription start site (TSS)  and abouet al. used ChIP to chip to identify and map 90 AR binding sites on chromosomes 21 and 22 in a prostate cancer cell line LNCaP under the treatment of 100 nM of androgen 5a-dihydrotestosterone (DHT) for 1 hour and 16 hours AR binding sites could be mapped to 27 genes; we identified only three of them  overlapping with our ChIP-seq data. The big difference between our ChIP-seq data and other's data is probably due to several factors. First, different technologies (ChIP-seq v.s. ChIP-chip) were used. Using NRSF as an example, Ji et al. showed that 5,517 (78%) of 7,114 ChIP-chip peaks did not overlap with the ChIP-seq peak We also compared our data to a global AR binding data set from Massie et al., who identified 1,532 potential AR-binding sites in AR responsive and proliferative LNCaP cells using the NimbleGen promoter array that contains 1.5 kb promoter regions of about 25K human genes We integrated the ChIP data with the gene expression data of PC3-AR cells in response to androgens. We found that 859 AR binding genes (1114 AR binding regions)  are differentially expressed at various concentrations of androgens by at least two fold , GATA_Q6 (GATA transcription factors), OCT_Q6 (octamer transcription factors) and PU1_Q6 (PU.1 transcription factor). Wang et al. identified GATA2 and Oct1 as cooperators of AR in mediating the androgen response in LNCaP cells AGAACAnnnTGTTCT) binding motif when allowing up to two positions to vary from the palindromic consensus with 3 nucleotide spacing GGTACANNRTGTTCT) in vitro binding data or from a limited numbers of human promoters: the M00481 (consensus: GGTACANNRTGTTCT) was built from 29 binding sites selected from random oligonucleotides AGWACATNWTGTTCT) was derived from AR binding sites in mouse crisp3 (cysteine-rich secretory protein 3)WGAGCANRN) is derived from 30 compiled AR regulated genes but only four of them are human genes  (from the Transfac database). Non-consensus ARE sequences such as 5′-GTAAAGTACTCCAAGAA-3′ were previously identified for the androgen-regulated gene probasin We found that 190 sites  contain the proliferative AR consensus matrix M00481, M00447 and M00962 (from the Transfac database) with a likelihood (LR) ratio of 500 compared to genomic background. Our data is similar to Wang et al.'s findings that only 10% of the binding regions that they identified have a canonical class I NR (CGAGCTCTTC. Motif Gib1 extends 3′ end two nucleotides (CG) and motif Gib2 extends 5′ end two nucleotides (TN)  (We therefore proceed to see whether we can identify novel AR consensus that explain the AR bindings in PC3-AR cells. We identified three novel AR matrices  that canleotide) . The unihttp://www.atcc.org/). We transfected a full-length wild-type AR into PC3 prostate cancer cells that do not express the AR. The AR construct is a generous gift from Dr. Donald J. Tindall at the Mayo Clinic in Rochester. In this construct (pCMVhAR), the wide-type AR is placed under the CMV promoter. LipofectimineTM 2000 reagent (Promega Inc.) was used for transfection according to the manufacturer's protocol. For chromatin immunoprecipitation (ChIP), two anti-AR antibodies from BD Pharmagen were tested for their performance (data not shown). The specificities of the chromatin IP of the two AR antibodies were tested by PCR amplification of the promoter of the prostate specific antigen (PSA) gene, a gene that is directly regulated by the AR PC3 cells  were obtained from ATCC . Human upstream sequences from EPD (The Eukaryotic Promoter Database) (epd_homo_sapiens_499_chromgenes_non_split_3.bg) were downloaded from the motif scanner web site and used as the background model. The human subset of the Transfac professional 7.0 PWM matrices was used. Matched matrices with likelihood (LR) ratios of 500 or higher were tabulated and frequency calculated.To scan for matched of single TF position-weight matrix, we used Cisgenome program using the “single matrix → FASTA” function. The matching criteria was set at likelihood ratio (LR)> = 500, and the order of background Markov Chain was set to three. We used the Gibbs Motif Sampler of the CisGenome program to identify novel AR binding motifs in the AR binding regions with a likelihood (LR) ratio of 500 compared to IGG ChIP-Seq background. For a systematic search for all potential transcription binding sites, we used the stand-alone motif scanner software  using lipofectimineTM 2000 reagent (Promega Inc.) according to the manufacturer's protocol. Twenty-four hours after transfection, the culture media were replaced with culture media containing ETOH (solvent for R1881), or 1 nM R1881 or 10 nM R1881. Cells were harvested 48 hours transfection (i.e. 24 hours after change of media) and RNAs isolated according to the method we described previously Affymetrix U133Plus2 chips were used and standard array hybridization protocol as suggested by the manufacturer as used. Array data were normalized by the GCRMA method We applied one-sided Fisher's exact test for testing the significant of enrichment. In additional, we also calculated the P values from Gaussian fitting using 10000 randomizations by randomly sampling. We identified 152 genes that overlap between the 2328 PC3 AR DEGs and 757 LNCAP AR DEGs. The union of these two gene lists gave a list of 2933 genes. The following procedure was performed to compute the probability that the number of overlapping genes in the two lists exceed the observed 152 genes by chance: 1) we randomly sampled 757 genes independently from 2933 AR-regulated genes, 2) the number of overlapping genes between the two randomly sampled gene sets was counted, 3) the above steps were repeated 10000 times, 4) an empirical probability density function was fitted to the 10000 numbers of overlapping genes from random experiments, 4) a p-value was computed as 1- normcdf  where m and s are the mean and standard deviation estimated from the normal distribution fitting.Table S14166 differentially expressed genes in PC3-AR cells compared to Mock-transfected PC3 cells and compared to themselves at 1 nM and 10 nM androgen treatment conditions.(0.85 MB XLS)Click here for additional data file.Table S2Gene Ontology Enrichment analysis of differentially expressed genes.(0.05 MB XLS)Click here for additional data file.Table S3AR binding regions identified in PC3-AR cells.(3.60 MB XLS)Click here for additional data file.Table S4Known AR consensus matrice from the Transfac Database mapped to AR binding regions identified.(0.01 MB TXT)Click here for additional data file.Table S5Mapping of novel AR motif Gib1 to the AR binding regions of PC3-AR cells(0.08 MB XLS)Click here for additional data file.Table S6Mapping of novel AR motif Gib2 to the AR binding regions of PC3-AR cells.(0.05 MB XLS)Click here for additional data file.Table S7Mapping of novel AR motif Gib3 to the AR binding regions of PC3-AR cells.(0.02 MB XLS)Click here for additional data file.Table S8Ranking of known TF matches to the AR binding regions of PC3-AR cells identified by MotifScanner.(0.06 MB XLS)Click here for additional data file.Table S9Comparison of AR binding regions of PC3-AR cells and LNCaP cells within 1.5 kb of TSS sites.(0.05 MB XLS)Click here for additional data file.Figure S1ChIP with the AR antibody generated a band that is the same size as the positive (input) control. ChIP without the primary AR antibody (without Ab) but with the 2nd antibody IgG alone generate no-specific PCR product, suggesting the AR ChIP is specific. The negative control (no template) showed negative. The bottom bands across the lanes are primer dimmer.(0.15 MB TIF)Click here for additional data file.Figure S2Quality control scatter plot of replicate array hybridization showing the replicates are of good qualities.(1.68 MB TIF)Click here for additional data file.Figure S3Scatter plot comparing Mock (empty vector) vs. AR transfected PC3 cells in different androgen conditions. When compared with the scatter plot of the replicates, differential expression of genes is evident.(1.72 MB TIF)Click here for additional data file.


Down-regulation of AR protein expression occurred already after 8 h of bFGF treatment and a maximal inhibition was observed 24 h after addition of bFGF to culture media. As AR expression can be reduced by an increase in intracellular calcium levels, we investigated whether the bFGF effect on AR protein is mediated by this mechanism. Calcium release from intracellular stores and store-operated calcium influx after treatment with either bFGF or calcium ionophore A 23187 were measured by single cell fluorescence technique. The ionophore A 23187 was able to induce calcium influx and an increase in cytoplasmic calcium concentration in LNCaP cells. In contrast, bFGF was incapable of eliciting a similar effect. In contrast to AR protein, AR mRNA levels were not affected by bFGF as shown by semiquantitative reverse transcription polymerase chain reaction. In summary, these studies show that bFGF is a potent negative regulator of AR protein expression in the human prostate cancer cell line LNCaP. © 2000 Cancer Research CampaignInteractions between polypeptide growth factors and the androgen receptor (AR) are important for regulation of cellular events in carcinoma of the prostate. Basic fibroblast growth factor (bFGF), the prototype of heparin-binding growth factors, and the AR are commonly expressed in prostate cancer. bFGF diminished prostate-specific antigen protein in the supernatants of androgen-stimulated human prostate cancer cells LNCaP by 80%. In the present study, we asked whether the bFGF effect on prostate-specific antigen is preceded by action on AR expression. LNCaP cells were treated with bFGF and AR protein expression was determined by immunoblotting and ligand binding assay. bFGF down-regulated AR protein in a dose-dependent manner showing a maximal effect at 50 ng ml