A general equilibrium model for Atlantic herring (Clupea harengus) with ecosystem considerations

A framework is presented for assessing the economic ramifications of ecosystem-based management decisions, with attention focused on Atlantic herring (Clupea harengus) in New England. The Atlantic herring has often been referred to as the most important fish in the northeastern United States because it is a filter-feeder, is believed to improve water quality, and is very important to the health, growth, and abundance of major gamefish, marine mammals, seabirds, and several species of fish. Although many approaches for examining the potential economic ramifications of ecosystem-based management are possible, attention is focused on one method that can be used given existing data. A static, deterministic input/output (I/O) optimization (IOLP, input/output linear programming) model is developed that breaks out the impact of different decisions on herring allocation on the 2006 New England regional economy of Maine, New Hampshire, Massachusetts, and Rhode Island. The IOLP model is a promising approach for informing policy-makers of the economic implications of various allocation choices. The framework is also flexible enough to allow further disaggregation of the small model presented to include additional fishing and non-fishing sectors

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

Reconstructing nonparametric productivity networks

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes. We fill this gap by developing a general framework to infer the network structure in a Bayesian sense, in order to better understand the underlying relationships driving system performance. Our approach draws on recent advances in information science, machine learning and statistical inference from the physics of complex systems to estimate unobserved network linkages. To illustrate, we apply our framework to analyze the production of knowledge, via own and cross-disciplinary research, for a world-country panel of bibliometric data. We find significant interactions between related disciplinary research output, both in terms of quantity and quality. In the context of research productivity, our results on cross-disciplinary linkages could be used to better target research funding across disciplines and institutions. More generally, our framework for inferring the underlying network production technology could be applied to both public and private settings which entail spillovers, including intra-and inter-firm managerial decisions and public agency coordination. This framework also provides a systematic approach to model selection when the underlying network structure is unknown

Productivity change in Nigerian seaports after reform: a Malmquist productivity index decomposition approach

During the 1990s, Nigerian seaports were considered inefficient, unsafe due to massive cargo theft (wharf rat phenomenon) and one of the most expensive port systems in the world. This resulted in long turnaround times for ships and increased container dwell times. As a result, port operations were transferred to the private sector through concession contracts. This paper employs a Malmquist productivity index (MPI) technique to benchmark pre-and post-reform total factor productivity growth of the six major Nigeria seaports (Apapa, Calabar, Onne, Port Harcourt, TinCan Island and Warri) for the period 2000–2011 which represents six years before (2000–2005) and six years after (2006–2011) the reform. The results indicate progress in technical efficiency of the ports after reform but deterioration in technological progress. Overall productivity growth was higher in the pre-concession period compared to the post-concession period. The source of pre-concession period productivity growth was technological progress while the change in productivity of the post-concession period is generated by an increase in scale efficiency. This suggests that concessionaires have not brought in the much anticipated investment in modern technology to drive port efficiency. The ports of Calabar and Apapa experienced the highest productivity growth while lowest result was Onne

3D printing of thermo-responsive methylcellulose hydrogels for cell-sheet engineering

A possible strategy in regenerative medicine is cell-sheet engineering (CSE), i.e., developing smart cell culture surfaces from which to obtain intact cell sheets (CS). The main goal of this study was to develop 3D printing via extrusion-based bioprinting of methylcellulose (MC)-based hydrogels. Hydrogels were prepared by mixing MC powder in saline solutions (Na2SO4 and PBS). MC-based hydrogels were analyzed to investigate the rheological behavior and thus optimize the printing process parameters. Cells were tested in vitro on ring-shaped printed hydrogels; bulk MC hydrogels were used for comparison. In vitro tests used murine embryonic fibroblasts (NIH/3T3) and endothelial murine cells (MS1), and the resulting cell sheets were characterized analyzing cell viability and immunofluorescence. In terms of CS preparation, 3D printing proved to be an optimal approach to obtain ring-shaped CS. Cell orientation was observed for the ring-shaped CS and was confirmed by the degree of circularity of their nuclei: cell nuclei in ring-shaped CS were more elongated than those in sheets detached from bulk hydrogels. The 3D printing process appears adequate for the preparation of cell sheets of different shapes for the regeneration of complex tissues

Comparison study of microarray meta-analysis methods

<p>Abstract</p> <p>Background</p> <p>Meta-analysis methods exist for combining multiple microarray datasets. However, there are a wide range of issues associated with microarray meta-analysis and a limited ability to compare the performance of different meta-analysis methods.</p> <p>Results</p> <p>We compare eight meta-analysis methods, five existing methods, two naive methods and a novel approach (mDEDS). Comparisons are performed using simulated data and two biological case studies with varying degrees of meta-analysis complexity. The performance of meta-analysis methods is assessed via ROC curves and prediction accuracy where applicable.</p> <p>Conclusions</p> <p>Existing meta-analysis methods vary in their ability to perform successful meta-analysis. This success is very dependent on the complexity of the data and type of analysis. Our proposed method, mDEDS, performs competitively as a meta-analysis tool even as complexity increases. Because of the varying abilities of compared meta-analysis methods, care should be taken when considering the meta-analysis method used for particular research.</p

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 &lt; 0.001), versus 8 months for patients receiving ICI beyond progression (HR = 0.13, p &lt; 0.001), and 2 months for patients who did not receive further active treatment (p &lt; 0.001). Conclusions: Chemotherapy administered after ICI progression for mUC patients is advisable irrespective of the treatment line

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

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