Automated detection of toxicophores and prediction of mutagenicity using PMCSFG algorithm

Maximum common substructures (MCS) have received a lot of attention in the chemoinformatics community. They are typically used as a similarity measure between molecules, showing high predictive performance when used in classification tasks, while being easily explainable substructures. In the present work, we applied the Pairwise Maximum Common Subgraph Feature Generation (PMCSFG) algorithm to automatically detect toxicophores (structural alerts) and to compute fingerprints based on MCS. We present a comparison between our MCS-based fingerprints and 12 well-known chemical fingerprints when used as features in machine learning models. We provide an experimental evaluation and discuss the usefulness of the different methods on mutagenicity data. The features generated by the MCS method have a state-of-the-art performance when predicting mutagenicity, while they are more interpretable than the traditional chemical fingerprints.

Ureteric stent versus percutaneous nephrostomy for acute ureteral obstruction - clinical outcome and quality of life: a bi-center prospective study

BACKGROUND

To compare quality of life (QoL) indices between ureteral stent (DJS) and nephrostomy tube (PCN) inserted in the setting of acute ureteral obstruction.

METHODS

Prospective bi-centered study. Over the span of 2 years, 45 DJS and 30 PCN patients were recruited. Quality of life was assessed by 2 questionnaires, EuroQol EQ-5D and 'Tube symptoms' questionnaire, at 2 time points (at discharge after drainage and before definitive treatment).

RESULTS

Patients' demographics and pre-drainage data were similar. There were no clinically significant differences in patient's recovery between the groups, including post procedural pain, defeverence, returning to baseline renal function, and septic shock complications. More DJS patients presented to the emergency room with complaints related to their procedure compared to PCN patients. At first, DJS patients complained more of urinary discomfort while PCN patients had worse symptoms relating to mobility and personal hygiene, with both groups achieving similar overall QoL score. At second time point, PCN patients' symptoms ameliorated while symptoms in the DJS group remained similar, translating to higher overall QoL score in the PCN group.

CONCLUSIONS

The two techniques had a distinct and significantly different impact on quality of life. Over time, PCN patients' symptoms relieve and their QoL improve, while DJS patients' symptoms persist. Specific tube related symptoms, and their dynamics over time, should be a major determinant in choosing the appropriate drainage method, especially when definitive treatment is not imminent.

IncGraph: Incremental graphlet counting for topology optimisation

MOTIVATION

Graphlets are small network patterns that can be counted in order to characterise the structure of a network (topology). As part of a topology optimisation process, one could use graphlet counts to iteratively modify a network and keep track of the graphlet counts, in order to achieve certain topological properties. Up until now, however, graphlets were not suited as a metric for performing topology optimisation; when millions of minor changes are made to the network structure it becomes computationally intractable to recalculate all the graphlet counts for each of the edge modifications.

RESULTS

IncGraph is a method for calculating the differences in graphlet counts with respect to the network in its previous state, which is much more efficient than calculating the graphlet occurrences from scratch at every edge modification made. In comparison to static counting approaches, our findings show IncGraph reduces the execution time by several orders of magnitude. The usefulness of this approach was demonstrated by developing a graphlet-based metric to optimise gene regulatory networks. IncGraph is able to quickly quantify the topological impact of small changes to a network, which opens novel research opportunities to study changes in topologies in evolving or online networks, or develop graphlet-based criteria for topology optimisation.

AVAILABILITY

IncGraph is freely available as an open-source R package on CRAN (incgraph). The development version is also available on GitHub (rcannood/incgraph).

A machine learning based framework to identify and classify long terminal repeat retrotransposons

Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of eukaryotic genomes. They can move and duplicate within a genome, increasing genome size and contributing to genetic diversity within and across species. Accurate identification and classification of TEs present in a genome is an important step towards understanding their effects on genes and their role in genome evolution. We introduce TE-Learner, a framework based on machine learning that automatically identifies TEs in a given genome and assigns a classification to them. We present an implementation of our framework towards LTR retrotransposons, a particular type of TEs characterized by having long terminal repeats (LTRs) at their boundaries. We evaluate the predictive performance of our framework on the well-annotated genomes of Drosophila melanogaster and Arabidopsis thaliana and we compare our results for three LTR retrotransposon superfamilies with the results of three widely used methods for TE identification or classification: RepeatMasker, Censor and LtrDigest. In contrast to these methods, TE-Learner is the first to incorporate machine learning techniques, outperforming these methods in terms of predictive performance, while able to learn models and make predictions efficiently. Moreover, we show that our method was able to identify TEs that none of the above method could find, and we investigated TE-Learner’s predictions which did not correspond to an official annotation. It turns out that many of these predictions are in fact strongly homologous to a known TE.

Over the years, with the increase of the acquisition of biological data, the extraction of knowledge from this data is getting more important. To understand how biology works is very important to increase the quality of the products and services which use biological data. This directly influences companies and governments, which need to remain in the knowledge frontier of an increasing competitive economy. Transposable Elements (TEs) are an example of very important biological data, and to understand their role in the genomes of organisms is very important for the development of products based on biological data. As an example, we can cite the production biofuels such as the sugar-cane-based ones. Many studies have revealed the presence of active TEs in this plant, which has gained economic importance in many countries. To understand how TEs influence the plant should help researchers to develop more resistant varieties of sugar-cane, increasing the production. Thus, the development of computational methods able to help biologists in the correct identification and classification of TEs is very important from both theoretical and practical perspectives.

Non a Priori Automatic Discovery of 3D Chemical Patterns: Application to Mutagenicity

This article introduces a new type of structural fragment called a geometrical pattern. Such geometrical patterns are defined as molecular graphs that include a labelling of atoms together with constraints on interatomic distances. The discovery of geometrical patterns in a chemical dataset relies on the induction of multiple decision trees combined in random forests. Each computational step corresponds to a refinement of a preceding set of constraints, extending a previous geometrical pattern. This paper focuses on the mutagenicity of chemicals via the definition of structural alerts in relation with these geometrical patterns. It follows an experimental assessment of the main geometrical patterns to show how they can efficiently originate the definition of a chemical feature related to a chemical function or a chemical property. Geometrical patterns have provided a valuable and innovative approach to bring new pieces of information for discovering and assessing structural characteristics in relation to a particular biological phenotype.

Postoperative Urinary Leakage Following Partial Nephrectomy for Renal Mass: Risk Factors and a Proposed Algorithm for the Diagnosis and Management

OBJECTIVES

To evaluate the current incidence, risk factors, management, and long-term follow-up of urinary leakage following partial nephrectomy, in order to propose an algorithm for diagnosis and evaluation of postoperative urinary leakage.

MATERIALS AND METHODS

The study included 752 patients who underwent elective partial nephrectomies for renal masses between the years 1988 and 2013. Patients' demographics, clinico-pathologic variables, and operative details were collected retrospectively. The associations between urinary leakage and patients' variables were assessed by univariate and multivariate analyses.

RESULTS

Of the 752 patients, 21 (2.8%) experienced urinary leakage; 4 of the 21 patients with urinary leakage had spontaneous resolution, 1 patient underwent nephrectomy, and 16 patients were treated by retrograde ureteral stents insertion. One of them necessitated insertion of an additional percutaneous nephrostomy and another one deserved concomitant percutaneous drainage of a perirenal urinoma. The average period of time that elapsed from the operation until the insertion of stent was 8.5 ± 4.5 days. Stents were removed 68 ± 20.5 days postoperatively. None of the patients had either persistent or repeated leakage. On univariate analysis, hilar renal masses (p < 0.04) and higher preoperative creatinine levels (p < 0.01) were found to be associated with higher rates of urinary leakage. None of these variables was significant on a multivariate analysis. Review of the urinary leakage rate over time revealed it has been constantly decreasing over time, from 4% in early cases to 1.3% among the most recent ones.

CONCLUSION

None of the preoperative variables that were examined in this study was significantly associated with increased risk of urinary leakage. However, cumulative surgical experience was associated with lower rates of urinary leakage, suggesting that the decrease in its incidence is related to the improved surgical skills, rather than to differences in tumors' or patients' characteristics.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist ‘Eve’ designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

Daily exposure to summer temperatures affects the motile subpopulation structure of epididymal sperm cells but not male fertility in an in vivo rabbit model

High temperatures have negative effects on sperm quality leading to temporary or permanent sterility. The aim of the study was to assess the effect of long exposure to summer circadian heat stress cycles on sperm parameters and the motile subpopulation structure of epididymal sperm cells from rabbit bucks. Twelve White New Zealand rabbit bucks were exposed to a daily constant temperature of the thermoneutral zone (from 18 °C to 22 °C; control group) or exposed to a summer circadian heat stress cycles (30 °C, 3 h/day; heat stress group). Spermatozoa were flushed from the epididymis and assessed for sperm quality parameters at recovery. Sperm total motility and progressivity were negatively affected by high temperatures (P < 0.05), as were also specific motility parameters (curvilinear velocity, linear velocity, mean velocity, straightness coefficient, linearity coefficient, wobble coefficient, and frequency of head displacement; P < 0.05, but not the mean amplitude of lateral head displacement). Heat stress significantly increased the percentage of less-motile sperm subpopulations, although the percentage of the high-motile subpopulation was maintained, which is consistent with the fact that no effect was detected on fertility rates. However, prolificacy was reduced in females submitted to heat stress when inseminated by control bucks. In conclusion, our results suggest that environmental high temperatures are linked to changes in the proportion of motile sperm subpopulations of the epididymis, although fertility is still preserved despite the detrimental effects of heat stress. On the other hand, prolificacy seems to be affected by the negative effects of high temperatures, especially by altering female reproduction.

Correlation between premature ejaculation and female vaginal penetration difficulties

Male and female sexual dysfunctions encompass biological, psychological and interpersonal aspects. Premature ejaculation (PE) and female vaginal penetration difficulties (VPD) are problems that may concurrently impair the couple's sexual relationship. We have studied the correlation between PE and VPD in the female partner, in a cross-sectional study of 125 heterosexual couples (male age 35.01±10.63; female age 32.36±10.07). VPD included tampon insertion, gynecological examination, inserting self-finger or partner-finger and penile-vaginal intercourse. Female sexual function index (FSFI) and a validated PE questionnaire were used to measure the female sexual function and PE in their male partners. We found that female partners of men with anteportal ejaculation were found to experience significantly more VPDs, especially with regard to difficulties in penile penetration and tampon use. The intensity of pain in VPD was higher in females whose male partners presented anteportal ejaculation. No significant correlation was found between total male PE score and the total FSFI or separate domains of female sexual function. The results suggest that female VPD and male anteportal ejaculation are interrelated. Such severe couple sexual problems should be addressed in parallel. Further research is required to study the causation of PE and VPD.

A new ensemble coevolution system for detecting HIV-1 protein coevolution

BACKGROUND

A key challenge in the field of HIV-1 protein evolution is the identification of coevolving amino acids at the molecular level. In the past decades, many sequence-based methods have been designed to detect position-specific coevolution within and between different proteins. However, an ensemble coevolution system that integrates different methods to improve the detection of HIV-1 protein coevolution has not been developed.

RESULTS

We integrated 27 sequence-based prediction methods published between 2004 and 2013 into an ensemble coevolution system. This system allowed combinations of different sequence-based methods for coevolution predictions. Using HIV-1 protein structures and experimental data, we evaluated the performance of individual and combined sequence-based methods in the prediction of HIV-1 intra- and inter-protein coevolution. We showed that sequence-based methods clustered according to their methodology, and a combination of four methods outperformed any of the 27 individual methods. This four-method combination estimated that HIV-1 intra-protein coevolving positions were mainly located in functional domains and physically contacted with each other in the protein tertiary structures. In the analysis of HIV-1 inter-protein coevolving positions between Gag and protease, protease drug resistance positions near the active site mostly coevolved with Gag cleavage positions (V128, S373-T375, A431, F448-P453) and Gag C-terminal positions (S489-Q500) under selective pressure of protease inhibitors.

CONCLUSIONS

This study presents a new ensemble coevolution system which detects position-specific coevolution using combinations of 27 different sequence-based methods. Our findings highlight key coevolving residues within HIV-1 structural proteins and between Gag and protease, shedding light on HIV-1 intra- and inter-protein coevolution.

Machine learning applications in proteomics research: how the past can boost the future

Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that allow computers to learn solving a (complex) problem from existing data. This ability can be used to generate a solution to a particularly intractable problem, given that enough data are available to train and subsequently evaluate an algorithm on. Since MS-based proteomics has no shortage of complex problems, and since publicly available data are becoming available in ever growing amounts, machine learning is fast becoming a very popular tool in the field. We here therefore present an overview of the different applications of machine learning in proteomics that together cover nearly the entire wet- and dry-lab workflow, and that address key bottlenecks in experiment planning and design, as well as in data processing and analysis.

Detection of prostate cancer by radio-frequency near-field spectroscopy in radical prostatectomy ex vivo specimens

BACKGROUND

The aim of radical prostatectomy (RP) is the complete removal of the prostate gland with negative surgical margins. The presence of cancer at the surgical margin is associated with higher probability of disease progression. Current methods of intraoperative margin assessment are inaccurate or time-consuming.The study goal was to evaluate the ability of a novel device (Dune Medical Devices) to differentiate between cancer and BPH.

METHODS

A total of 49 patients undergoing RP in four medical centers between November 2007 and May 2008 were enrolled in this study.The device was applied to numerous intra- and extra-capsular sites of freshly excised RP specimens. Measurement sites were accurately marked and analyzed histologically. The ability of the device to differentiate between malignant and nonmalignant sites was assessed.

RESULTS

A total of 15,156 measurements from 45 patients were analyzed. Differentiation of the intra-capsular malignant sites from extra-capsular nonmalignant sites (bladder neck and apex regions) depends on the cancer feature size. Differentiation was achieved with sensitivity and specificity of 93.6 (95% confidence interval (CI): 88-98) and 94.1 (95% CI: 93-95), respectively, at feature sizes at or >0.8 mm in diameter. The device was able to discriminate between all intra-capsular malignant (with feature sizes down to a few cells) and nonmalignant measurement sites, with sensitivity and specificity of 80.8 (95% CI: 73-87) and 68.4 (95% CI: 67-69), respectively.

CONCLUSIONS

First results from a radio-frequency near-field spectroscopy sensor look promising for differentiation between cancer and benign prostate tissue. The sensor's dimensions (radius of ~ 1 mm) and design enable use in open, laparoscopic and robotic RP to evaluate the surgical margins intraoperatively.

Hypovitaminosis D as a risk factor of hip fracture severity

SUMMARY

In a cross-sectional study including 324 patients older than 65 years admitted to our hospital for osteoporotic hip fracture, we found that those patients with a more severe vitamin D deficiency had more severe osteoporotic hip fractures (Garden grades III-IV and Kyle III-IV).

INTRODUCTION

To identify possible differences in baseline characteristics of patients with different types of osteoporotic hip fracture.

METHODS

Cross-sectional study including consecutive individuals over 65 admitted to our hospital for osteoporotic hip fracture over a year. Demographic data, fracture type, comorbidities, history of osteoporosis, functional capacity, nutritional status and vitamin D storage were evaluated.

RESULTS

We included 324 patients (83 ± 7 years, 80% women). Two hundred sixteen patients (67%) had vitamin D deficiency (25OHD3 <25 ng/ml). In patients with severe femoral neck or intertrochanteric fractures (Garden III-IV and Kyle III-IV), vitamin D deficiency was more frequent (74%) and severe (25OHD3 20 ± 15 ng/ml) than in patients with less severe fractures (57%, 25OHD3 26 ± 21 ng/ml). Forty-three percent of patients had previous fractures. Only 15% of patients had been previously diagnosed with osteoporosis and 10% were receiving treatment. Patients receiving vitamin D supplements have higher 20OHD3 levels and less severe fractures.

CONCLUSIONS

Although vitamin D levels are not different between patients with intracapsular or extracapsular hip fractures, a more severe vitamin D deficiency seems to be associated to more severe osteoporotic hip fractures. A prior vitamin D supplementation could avoid a higher severity of these fractures.

Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model

Background

The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP), a machine learning technique.

Methods

Non-interventional study. Predictive modeling, separate development (n = 461) and validation (n = 499) cohort. GP models were developed to predict the probability of ICU discharge the day after surgery (classification task), and to predict the day of ICU discharge as a discrete variable (regression task). GP predictions were compared with predictions by EuroSCORE, nurses and physicians. The classification task was evaluated using aROC for discrimination, and Brier Score, Brier Score Scaled, and Hosmer-Lemeshow test for calibration. The regression task was evaluated by comparing median actual and predicted discharge, loss penalty function (LPF) ((actual-predicted)/actual) and calculating root mean squared relative errors (RMSRE).

Results

Median (P25-P75) ICU length of stay was 3 (2-5) days. For classification, the GP model showed an aROC of 0.758 which was significantly higher than the predictions by nurses, but not better than EuroSCORE and physicians. The GP had the best calibration, with a Brier Score of 0.179 and Hosmer-Lemeshow p-value of 0.382. For regression, GP had the highest proportion of patients with a correctly predicted day of discharge (40%), which was significantly better than the EuroSCORE (p < 0.001) and nurses (p = 0.044) but equivalent to physicians. GP had the lowest RMSRE (0.408) of all predictive models.

Conclusions

A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a classification as well as a regression task. The GP model demonstrated a significantly better discriminative power than the EuroSCORE and the ICU nurses, and at least as good as predictions done by ICU physicians. The GP model was the only well calibrated model.

New prospective for non-invasive detection, grading, size evaluation, and tumor location of prostate cancer

BACKGROUND

PSA blood test and other present screening tools fail to provide the required sensitivity and specificity and, at early stages, lack correlation with tumor grade, volume, and location. Thus alternative approaches are highly desired. We present and assess a novel method for PCa detection, grading, volume evaluation and tumor location, based on non-invasive zinc concentration mapping in the gland by means of a dedicated rectal probe.

METHODS

Zinc-concentration values measured in histologically examined tissue fragments from needle biopsy of 598 patients were analyzed. They were used to generate computer simulated zinc-concentration maps, further analyzed with image-processing tools. The tumor detection performances versus Gleason grade were assessed.

RESULTS

A significant increase of zinc depletion with increasing Gleason pattern (grade) classification was established. Tumor detection performance in zinc-concentration maps progressively improves with the cancer's first component score. Reliable information on the location, size and Gleason-grade combination of the lesion can be extracted for clinically relevant volumes.

CONCLUSIONS

Zinc depletion in the prostate peripheral zone is the basis for a novel, non-invasive PCa detection, localization, volume evaluation and grading method. Its realization and application as a pre-biopsy and pre-treatment examination, or a follow-up tool, relies on the development of a dedicated transrectal probe. It should have significant impact on biopsy effectiveness, point at a possible extraprostatic extension and provide critical data for focal treatment. The information on tumor grade and distribution may have an important impact on disease management.

Machine learning techniques to examine large patient databases

Computerization in healthcare in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential applications for these techniques in medicine is large, few medical doctors are familiar with their methodology, advantages and pitfalls. A general overview of machine learning techniques, with a more detailed discussion of some of these algorithms, is presented in this review.

Crossbreeding parameters for growth and feed consumption traits from a five diallel mating scheme in rabbits

Twenty-five genetic groups of young rabbits originated from a diallel-crossbreeding scheme among 5 selected lines: 3 maternal and 2 terminal sire lines belonging to 2 Spanish research institutions. A sample of 2,773 young rabbits from 525 litters was controlled during the fattening period lasting from 5 to 9 wk. Growth and feed consumption traits were evaluated throughout different biweekly batches. A Bayesian approach was used for inference from an animal model with common litter effects. On average, genetic groups coming from lines selected for growth rate were heavier (+58.9 g at 32 d and +315.5 g at 60 d), had greater growth rate (9.24 and 8.15 g/d from individual or cage analysis, respectively) and feed intake (+13.24 g/d), and showed better feed conversion ratio (-0.21 g of intake/g of gain), than the genetic groups originated from crosses among lines selected for litter size. Crossbreeding parameters were estimated from the samples of the marginal posterior distribution of the genetic group effect according to the Dickerson model. Maternal genetic and individual heterosis effects were null or very low. Direct genetic effects mainly regulated the expression of growth traits.

Evaluating the cancer detection and grading potential of prostatic-zinc imaging: a simulation study

The present work deals with the analysis of prostatic-zinc-concentration images. The goal is to evaluate potential clinically relevant information that can be extracted from such images. In the absence of experimental images, synthetic ones are produced from clinically measured zinc-concentration distributions in certified benign and cancerous tissue samples, classified by the lesion grade. We describe the method for producing the images and model the effect of counting statistics noise. We present in detail the image analysis, which is based on a combination of standard image processing and segmentation tools, optimized for this particular application. The information on lowest zinc value obtained from the image analysis is translated to clinical data such as tumour presence, location, size and grade. Their confidence is evaluated with the help of standard statistical tools such as receiver operating characteristic analysis. The present work predicts a potential for detecting small prostate-cancer lesions, of grade (4+3) and above, with very good specificity and sensitivity. The present analysis further provides data on the pixel size and image counting statistics requested from the trans-rectal probe that will record in vivo prostatic-zinc maps in patients.

Dynamic data analysis and data mining for prediction of clinical stability

This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than nine hours. On the basis of five physiological variables different dynamic features were extracted. These sets of features served subsequently as inputs for a Gaussian process and the prediction results were compared with the case where only admission data was used for the classification. The dynamic features, especially the cepstral coefficients (aROC: 0.749, Brier score: 0.206), resulted in higher performances when compared to static admission data (aROC: 0.547, Brier score: 0.247). In all cases, the Gaussian process classifier outperformed logistic regression.

Clinical assessment of the cancer diagnostic value of prostatic zinc: a comprehensive needle-biopsy study

BACKGROUND

The correlation between Zinc concentration in the prostate's peripheral zone to the onset or presence of malignant process needs to be evaluated in detail.

METHODS

Zinc concentration was measured in approximately 1-4 mm3 segments of fresh needle-biopsy cores, with X-ray fluorescence, and correlated with the histological findings of these tissue segments.

RESULTS

Local Zinc concentration is correlated with the presence of cancer (PCa); the higher the Gleason score the greater the Local Zinc depletion. The Zinc value averaged over the entire extracted tissue is specific only to Gleason score 8-9 PCa. The results refer to patients avoiding Zinc-rich supplements since those show elevated prostatic Zinc concentration in identified cancer tissue. A computer simulation analysis of randomly located 0.03-3.3 cm3 lesions, with particular Gleason score and the measured Local Zinc concentration, revealed a potential diagnostic approach definitely superior to PSA, with sensitivity to the tumor grade and with excellent detection capability for Gleason score >6. Further clinical studies have been designed, both on full prostates after radical prostatectomy as well as on biopsy cores at higher resolution, to establish the accuracy of the method for Gleason score = 6.

CONCLUSIONS

The PCa diagnostic potential of Local Zinc concentration is confirmed and there is indication that the amount of Zinc depletion could be used as a measure of the Gleason score of the tumor. Local Zinc concentration mapping has the potential to improve patient selection for biopsy, biopsy site selection and local therapy (e.g., Cryotherapy, Brachytherapy) site selection.

Orthopedic shoes improve gait in Friedreich's ataxia: a clinical and quantified case study

Our aim was to evaluate with modern tools the efficacy of orthopedic shoes on gait disorders in Friedreich's ataxia. The case of a 26-year-old woman with Friedreich's ataxia is described. She mainly complained of fatigability, ankle instability, frequent falls and pain. Impairments involved a cerebellar syndrome, a proprioceptive deficit, an upper motor neurone syndrome and osteoarticular deformities. Gait disabilities included ataxia and requirement of a cane. Handicap concerned outings, altering quality of life. Orthopedic shoes combined with physical therapy were prescribed. Assessment of treatment was planned after one month. Self-assessment by the patient was noted. Clinical assessment was provided by physical examination and clinical gait analysis supported by video. Quantified assessment was performed with a Gaitrite system recording spatiotemporal gait parameters. Our results demonstrated that orthopedic shoes improved gait disorders in this patient with Friedreich's ataxia. Pain decreased, walking distance increased, falls were less frequent, going out became possible, stability was better, speed, step length and cadence increased. Both clinical and quantified assessment confirmed functional improvement felt by the patient. In conclusion complete medical and social assessment determines quality of prescription in physical and rehabilitation medicine.

Testicular prosthesis insertion following testicular loss or atrophy during early childhood--technical aspects and evaluation of patient satisfaction

INTRODUCTION

The absence of a testis may be a major traumatic experience with possible consequent negative behavioral impact. The current study is aimed to assess young adults who had lost their testicles early in childhood and subsequently underwent testicular prosthesis (TP) implantation at the end of their adolescence.

MATERIALS AND METHODS

Nineteen patients aged 19.4 years on average underwent TP implantation following testicular loss at early childhood. A postal anonymous questionnaire was sent to the patients and 13 (68%) replied.

RESULTS

Average follow-up was 50 months. Sixty-two percent of patients believed TP size were equal or close to the size of their native testicle, while 23% claimed it was too small. Similarly, 54% had the impression its weight was appropriate, while 38% claimed it was too heavy and 38% supposed its location was too high in the scrotum. However, 85% considered it "very comfortable" or "comfortable" and 77% got used to its presence within 1-4 weeks following surgery. All patients precluded any obstacle in intimate relationships. In accordance, all of them would recommend the operation to a friend with a similar problem.

CONCLUSIONS

TP implantation in adolescents with an undeveloped scrotum is a highly successful surgical procedure. The operation positively influences self-confidence, inter-personal interactions and intimate relationships.

Individual efficiency for the use of feed resources in rabbits

A Bayesian procedure, which allows consideration of the individual variation in the feed resource allocation pattern, is described and implemented in 2 sire lines of rabbit (Caldes and R). The procedure is based on a hierarchical Bayesian scheme, where the first stage of the model consists of a multiple regression model of feed intake on metabolic BW and BW gain. In a second stage, an animal model was assumed including batch, parity order, litter size, and common environmental litter effects. Animals were reared during the fattening period (from weaning at 32 d of age to 60 d of age) in individual cages on an experimental farm, and were fed ad libitum with a commercial diet. Body weight (g) and cumulative feed intake (g) were recorded weekly. Individual BW gain (g) and average BW (ABW, g) were calculated from these data for each 7-d period. Metabolic BW (g(0.75)) was estimated as ABW(0.75). The number of animals actually measured was 444 and 445 in the Caldes and R lines, respectively. Marginal posterior distributions of the genetic parameters were obtained by Gibbs sampling. Posterior means (posterior SD) for heritabilities for partial coefficients of regression of feed intake on metabolic BW and feed intake on BW gain were estimated to be 0.35 (0.17) and 0.40 (0.17), respectively, in the Caldes line and 0.26 (0.19) and 0.27 (0.14), respectively, in line R. The estimated posterior means (posterior SD) for the proportion of the phenotypic variance due to common litter environmental effects of the same coefficients of regression were respectively, 0.39 (0.14) and 0.28 (0.13) in the Caldes line and 0.44 (0.22) and 0.49 (0.14) in line R. These results suggest that efficiency of use of feed resources could be improved by including these coefficients in an index of selection.

Bicalutamide (Casodex) 150 mg plus standard care in early non-metastatic prostate cancer: results from Early Prostate Cancer Trial 24 at a median 7 years' follow-up

Trial 24, one of three ongoing trials in the Early Prostate Cancer programme, is evaluating the efficacy and tolerability of bicalutamide (Casodex) 150 mg following standard care (radiotherapy, radical prostatectomy or watchful waiting) in patients with early, non-metastatic prostate cancer. At 7 years' median follow-up, addition of bicalutamide significantly improved objective progression-free survival (PFS) for patients with locally advanced disease, reducing the risk of progression by 34% versus standard care alone (hazard ratio 0.66; 95% confidence interval 0.55, 0.79; P<0.001). In localized disease, a significant difference in objective PFS was not found. There was no significant difference in overall survival.