Data and programming code from the studies on the learning curve for radical prostatectomy

Our group analyzed a multi-institutional data set to address the question of how the outcomes of surgery for prostate cancer are affected by surgeon-specific factors. The cohort consists of 9076 patients treated by open radical prostatectomy at one of four US academic institutions 1987 - 2003. The primary analyses focused on 7765 patients without neoadjuvant therapy. The most well-known finding is that of a surgical "learning curve", with rates of prostate cancer cure strongly dependent on surgeon experience. In this "data note", we provide the raw data set, as well as well-annotated programming code for the main analyses. Data include markers of cancer severity (stage, grade and prostate-specific antigen level), cancer outcome, and surgeon variables such as training and experience

A Direct Comparison of Two Densely Sampled HIV Epidemics: The UK and Switzerland

Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes

Construction of an In Silico Structural Profiling Tool Facilitating Mechanistically Grounded Classification of Aquatic Toxicants.

The performance of chemical safety assessment within the domain of environmental toxicology is often impeded by a shortfall of appropriate experimental data describing potential hazards across the many compounds in regular industrial use. In silico schemes for assigning aquatic-relevant modes or mechanisms of toxic action to substances, based solely on consideration of chemical structure, have seen widespread employment─including those of Verhaar, Russom, and later Bauer (MechoA). Recently, development of a further system was reported by Sapounidou, which, in common with MechoA, seeks to ground its classifications in understanding and appreciation of molecular initiating events. Until now, this Sapounidou scheme has not seen implementation as a tool for practical screening use. Accordingly, the primary purpose of this study was to create such a resource─in the form of a computational workflow. This exercise was facilitated through the formulation of 183 structural alerts/rules describing molecular features associated with narcosis, chemical reactivity, and specific mechanisms of action. Output was subsequently compared relative to that of the three aforementioned alternative systems to identify strengths and shortcomings as regards coverage of chemical space

A scheme to evaluate structural alerts to predict toxicity – Assessing confidence by characterising uncertainties

Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are an essential tool in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification

Evolving cell models for systems and synthetic biology

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm’s results as well as of the resulting evolved cell models

The Great American Biotic Interchange: Dispersals, Tectonics, Climate, Sea Level and Holding Pens

The biotic and geologic dynamics of the Great American Biotic Interchange are reviewed and revised. Information on the Marine Isotope Stage chronology, sea level changes as well as Pliocene and Pleistocene vegetation changes in Central and northern South America add to a discussion of the role of climate in facilitating trans-isthmian exchanges. Trans-isthmian land mammal exchanges during the Pleistocene glacial intervals appear to have been promoted by the development of diverse non-tropical ecologies

A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients

INTRODUCTION: The Oncotype DX assay was recently reported to predict risk for distant recurrence among a clinical trial population of tamoxifen-treated patients with lymph node-negative, estrogen receptor (ER)-positive breast cancer. To confirm and extend these findings, we evaluated the performance of this 21-gene assay among node-negative patients from a community hospital setting. METHODS: A case-control study was conducted among 4,964 Kaiser Permanente patients diagnosed with node-negative invasive breast cancer from 1985 to 1994 and not treated with adjuvant chemotherapy. Cases (n = 220) were patients who died from breast cancer. Controls (n = 570) were breast cancer patients who were individually matched to cases with respect to age, race, adjuvant tamoxifen, medical facility and diagnosis year, and were alive at the date of death of their matched case. Using an RT-PCR assay, archived tumor tissues were analyzed for expression levels of 16 cancer-related and five reference genes, and a summary risk score (the Recurrence Score) was calculated for each patient. Conditional logistic regression methods were used to estimate the association between risk of breast cancer death and Recurrence Score. RESULTS: After adjusting for tumor size and grade, the Recurrence Score was associated with risk of breast cancer death in ER-positive, tamoxifen-treated and -untreated patients (P = 0.003 and P = 0.03, respectively). At 10 years, the risks for breast cancer death in ER-positive, tamoxifen-treated patients were 2.8% (95% confidence interval [CI] 1.7–3.9%), 10.7% (95% CI 6.3–14.9%), and 15.5% (95% CI 7.6–22.8%) for those in the low, intermediate and high risk Recurrence Score groups, respectively. They were 6.2% (95% CI 4.5–7.9%), 17.8% (95% CI 11.8–23.3%), and 19.9% (95% CI 14.2–25.2%) for ER-positive patients not treated with tamoxifen. In both the tamoxifen-treated and -untreated groups, approximately 50% of patients had low risk Recurrence Score values. CONCLUSION: In this large, population-based study of lymph node-negative patients not treated with chemotherapy, the Recurrence Score was strongly associated with risk of breast cancer death among ER-positive, tamoxifen-treated and -untreated patients

To Each According to His Need? Variability in the Responses to Inequity in Nonhuman Primates

While it is well established that humans respond to inequity, it remains unclear the extent to which this behavior occurs in our nonhuman primate relatives. By comparing a variety of species, spanning from New World and Old World monkeys to great apes, scientists can begin to answer questions about how the response to inequity evolved, what the function of this response is, and why and how different contexts shape it. In particular, research across nonhuman primate species suggests that the response is quite variable across species, contexts and individuals. In this paper, we aim to review these differences in an attempt to identify and better understand the patterns that emerge from the existing data with the goal of developing directions for future research. To begin, we address the importance of considering socio-ecological factors in nonhuman primates in order to better understand and predict expected patterns of cooperation and aversion to inequity in different species, following which we provide a detailed analysis of the patterns uncovered by these comparisons. Ultimately, we use this synthesis to propose new ideas for research to better understand this response and, hence, the evolution of our own responses to inequity

Using viral vectors as gene transfer tools (Cell Biology and Toxicology Special Issue: ETCS-UK 1 day meeting on genetic manipulation of cells)

In recent years, the development of powerful viral gene transfer techniques has greatly facilitated the study of gene function. This review summarises some of the viral delivery systems routinely used to mediate gene transfer into cell lines, primary cell cultures and in whole animal models. The systems described were originally discussed at a 1-day European Tissue Culture Society (ETCS-UK) workshop that was held at University College London on 1st April 2009. Recombinant-deficient viral vectors (viruses that are no longer able to replicate) are used to transduce dividing and post-mitotic cells, and they have been optimised to mediate regulatable, powerful, long-term and cell-specific expression. Hence, viral systems have become very widely used, especially in the field of neurobiology. This review introduces the main categories of viral vectors, focusing on their initial development and highlighting modifications and improvements made since their introduction. In particular, the use of specific promoters to restrict expression, translational enhancers and regulatory elements to boost expression from a single virion and the development of regulatable systems is described