Self-organizing & stochastic behaviors during the regeneration of hair stem cells

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs

Research Data Management 'Green Shoots' Pilot Programme, Final Reports

This document contains the final reports of six Research Data Management Green Shoots projects run at Imperial College in 2014

Clinical Outcomes of Patients With Metastatic Urothelial Carcinoma After Progression to Immune Checkpoint Inhibitors: A Retrospective Analysis by the Meet-Uro Group (Meet-URO 1 Study)

Background: Immune checkpoint inhibitors (ICIs) are currently the standard of care for metastatic urothelial cancer (mUC) after the failure of previous platinum-based chemotherapy. The choice of further therapy after ICI progression is a new challenge, and scarce data support it. We aimed to examine the outcomes of mUC patients after progression to ICI, especially when receiving chemotherapy. Methods: Data were retrospectively collected from clinical records of mUC patients whose disease progressed to anti-programmed death 1 (PD-1)or programmed death ligand 1 (PD-L1) therapy at 14 Italian centers. Patients were grouped according to ICI therapy setting into SALVAGE (ie, ICI delivered ⩾ second-line therapy after platinum-based chemotherapy) and NAÏVE (ie, first-line therapy) groups. Progression-free survival (PFS) and overall survival (OS) rates were calculated using the Kaplan-Meier method and compared among subgroups. Cox regression assessed the effect of treatments after progression to ICI on OS. Objective response rate (ORR) was calculated as the sum of partial and complete radiologic responses. Results: The study population consisted of 201 mUC patients who progressed after ICI: 59 in the NAÏVE cohort and 142 in the SALVAGE cohort. Overall, 52 patients received chemotherapy after ICI progression (25.9%), 20 (9.9%) received ICI beyond progression, 115 (57.2%) received best supportive care only, and 14 (7.0%) received investigational drugs. Objective response rate to chemotherapy in the post-ICI setting was 23.1% (28.0% in the NAÏVE group and 18.5% in the SALVAGE group). Median PFS and OS to chemotherapy after ICI-PD was 5 months (95% confidence interval [CI]: 3-11) and 13 months (95% CI: 7-NA) for the NAÏVE group; 3 months (95% CI: 2-NA) and 9 months (95% CI: 6-NA) for the SALVAGE group, respectively. Overall survival from ICI initiation was 17 months for patients receiving chemotherapy (hazard ratio [HR] = 0.09, p < 0.001), versus 8 months for patients receiving ICI beyond progression (HR = 0.13, p < 0.001), and 2 months for patients who did not receive further active treatment (p < 0.001). Conclusions: Chemotherapy administered after ICI progression for mUC patients is advisable irrespective of the treatment line

Washing scaling of GeneChip microarray expression

BACKGROUND Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. RESULTS We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM) and mismatch (MM) probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. CONCLUSIONS Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental 'washing data set' which might be used by the community for developing amendments of the washing correction.This publication is supported by the Leipzig Interdisciplinary Research Cluster of Genetic Factors, Clinical Phenotypes and Environment (LIFE Center, Universität Leipzig) and an Australian Academy of Science Visits to Europe grant. LIFE is funded by means of the European Union, by the European Regional Development Fund (ERFD) and by means of the Free State of Saxony within the framework of the excellence initiative

Structure and microstructure evolution of Al-Mg-Si alloy processed by equal-channel angular pressing

An ultrafine grained Al–Mg–Si alloy was prepared by severe plastic deformation using the equal-channel angular pressing (ECAP) method. Samples were ECAPed through a die with an inner angle of F = 90° and outer arc of curvature of ¿ = 37° from 1 to 12 ECAP passes at room temperature following route Bc. To analyze the evolution of the microstructure at increasing ECAP passes, X-ray diffraction and electron backscatter diffraction analyses were carried out. The results revealed two distinct processing regimes, namely (i) from 1 to 5 passes, the microstructure evolved from elongated grains and sub-grains to a rather equiaxed array of ultrafine grains and (ii) from 5 to 12 passes where no change in the morphology and average grain size was noticed. In the overall behavior, the boundary misorientation angle and the fraction of high-angle boundaries increase rapidly up to 5 passes and at a lower rate from 5 to 12 passes. The crystallite size decreased down to about 45 nm with the increase in deformation. The influence of deformation on precipitate evolution in the Al–Mg–Si alloy was also studied by differential scanning calorimetry. A significant decrease in the peak temperature associated to the 50% of recrystallization was observed at increasing ECAP passes.Peer ReviewedPreprin

Gene expression analyses in breast cancer epidemiology: the Norwegian Women and Cancer postgenome cohort study

Introduction The introduction of high-throughput technologies, also called -omics technologies, into epidemiology has raised the need for high-quality observational studies to reduce several sources of error and bias. Methods The Norwegian Women and Cancer (NOWAC) postgenome cohort study consists of approximately 50,000 women born between 1943 and 1957 who gave blood samples between 2003 and 2006 and filled out a two-page questionnaire. Blood was collected in such a way that RNA is preserved and can be used for gene expression analyses. The women are part of the NOWAC study consisting of 172,471 women 30 to 70 years of age at recruitment from 1991 to 2006 who answered one to three questionnaires on diet, medication use, and lifestyle. In collaboration with the Norwegian Breast Cancer Group, every NOWAC participant born between 1943 and 1957 who is admitted to a collaborating hospital for a diagnostic biopsy or for surgery of breast cancer will be asked to donate a tumor biopsy and two blood samples. In parallel, at least three controls are approached for each breast cancer case in order to obtain blood samples from at least two controls per case. The controls are drawn at random from NOWAC matched by time of follow-up and age. In addition, 400 normal breast tissues as well as blood samples will be collected among healthy women participating at the Norwegian Mammography Screening program at the Breast Imaging Center at the University Hospital of North-Norway, Tromsø. Results The NOWAC postgenome cohort offers a unique opportunity (a) to study blood-derived gene expression profiles as a diagnostic test for breast cancer in a nested case-control design with adjustment for confounding factors related to different exposures, (b) to improve the reliability and accuracy of this approach by adjusting for an individual's genotype (for example, variants in genes coding for hormone and drug-metabolizing and detoxifying enzymes), (c) to study gene expression profiles from peripheral blood as surrogate tissue to biomonitor defined exposure (for example, hormone) and its association with disease risk (that is, breast cancer), and (d) to study gene variants (single nucleotide polymorphisms and copy number variations) and environmental exposure (endogenous and exogenous hormones) and their influence on the incidence of different molecular subtypes of breast cancer. Conclusion The NOWAC postgenome cohort combining a valid epidemiological approach with richness of biological samples should make an important contribution to the study of the etiology and system biology of breast cancer

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course

Eco-efficiency measurement and material balance principle:an application in power plants Malmquist Luenberger Index

Incorporating Material Balance Principle (MBP) in industrial and agricultural performance measurement systems with pollutant factors has been on the rise in recent years. Many conventional methods of performance measurement have proven incompatible with the material flow conditions. This study will address the issue of eco-efficiency measurement adjusted for pollution, taking into account materials flow conditions and the MBP requirements, in order to provide ‘real’ measures of performance that can serve as guides when making policies. We develop a new approach by integrating slacks-based measure to enhance the Malmquist Luenberger Index by a material balance condition that reflects the conservation of matter. This model is compared with a similar model, which incorporates MBP using the trade-off approach to measure productivity and eco-efficiency trends of power plants. Results reveal similar findings for both models substantiating robustness and applicability of the proposed model in this paper