Analysis of gene copy number changes in tumor phylogenetics

Backgound

Evolution of cancer cells is characterized by large scale and rapid changes in the chromosomal  landscape. The fluorescence in situ hybridization (FISH) technique provides a way to measure the copy numbers of preselected genes in a group of cells and has been found to be a reliable source of data to model the evolution of tumor cells. Chowdhury et al. (Bioinformatics 29(13):189–98, 23; PLoS Comput Biol 10(7):1003740, 24) recently develop a computational model for tumor progression driven by gains and losses in cell count patterns obtained by FISH probes. Their model aims to find the rectilinear Steiner minimum tree (RSMT) (Chowdhury et al. in Bioinformatics 29(13):189–98, 23) and the duplication Steiner minimum tree (DSMT) (Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) that describe the progression of FISH cell count patterns over its branches in a parsimonious manner. Both the RSMT and DSMT problems are NP-hard and heuristics are required to solve the problems efficiently.

Methods

In this paper we propose two approaches to solve the RSMT problem, one inspired by iterative methods to address the “small phylogeny” problem (Sankoff et al. in J Mol Evol 7(2):133–49, 27; Blanchette et al. in Genome Inform 8:25–34, 28), and the other based on maximum parsimony phylogeny inference. We further show how to extend these heuristics to obtain solutions to the DSMT problem, that models large scale duplication events.

Results

Experimental results from both simulated and real tumor data show that our methods outperform previous heuristics (Chowdhury et al. in Bioinformatics 29(13):189–98, 23; Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) in obtaining solutions to both RSMT and DSMT problems.

Conclusion

The methods introduced here are able to provide more parsimony phylogenies compared to earlier ones which are consider better choices.

     

Life-cycle assessment of the soybean-sunflower production system in the Brazilian Cerrado

Purpose

In the “Cerrado” (Brazilian savanna), sunflower comes mostly from a cropping system where its seeding follows soybean harvest. Soybean has a much higher economic value, but this association with sunflower reduces the environmental impacts from both crops by sharing resources. This study performed a life-cycle assessment (LCA) of the soybean-sunflower cropping system, identified its hotspots, and compared its environmental performance with two hypothetical monocultures, in order to corroborate its benefits.

Methods

Soybean-sunflower cropping system inventory used data from farms of the Parecis region, consolidated by experts. Inventories for soybean and sunflower monocultures were estimated from the cropping system inventory. LUC (land-use changes) were calculated from CONAB (2015), FAOSTAT (2012), and Macedo et al. (P Natl Acad Sci USA 109:1341–1346, 2012). Emissions estimation followed Nemecek and Schnetzer (2011), Milà i Canals (2003), and EC (2010). Land occupation, land-use changes, and liming were allocated by occupation time, but a sensitivity analysis was performed for yield and gross margin as allocation criteria. ReCiPe Midpoint (H) v1.12/World ReCiPe H was the impact assessment method, and some categories were disregarded as not relevant. We used pedigree matrix to estimate uncertainties for inventory and Monte Carlo method for impact uncertainty analysis as in Goedkoop et al. (2008). We used SimaPro 8.0.5.13.

Results and discussion

The soybean-sunflower cropping system generate relevant human toxicity, freshwater toxicity, freshwater eutrophication, climate change, and terrestrial acidification impacts, related to emissions derived from nitrogen and phosphate fertilizers and emissions generated by LUC. Sunflower-soybean cropping system has better environmental performance when compared to the combination of monocultures because of a number of synergies made possible by sharing land use and other resources. Changing the allocation criteria altered the relative performance of some categories, but in all categories the environmental impacts of the cropping system were lower than those of the corresponding monoculture impacts, regardless of the allocation criteria implemented.

Conclusions

We concluded that the environmental performance of the soybean-sunflower cropping system can be improved by optimizing the use of chemical fertilizers. Climate change impacts, which are mostly driven by LUC, could be reduced by production intensification, preventing the clearing of native vegetation for agricultural purposes. This study confirmed the environmental benefits of cropping systems when compared to monocultures and the advantages of association of nitrogen-fixing legumes with other plant species in a production system.

     

Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM)

Objectives

In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions.

Introduction

All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. in Omics 15:173–182, 2011; Fan et al. in Metabolomics 7(2):257–269, 2011a, in Pharmacol Ther 133:366–391, 2012a, in Metabolomics 8(3):517–527, b; Xie et al. in Cell Metab 19:795–809, 2014; Ren et al. in Sci Rep 4:5414, 2014; Sellers et al. in J Clin Investig 125(2):687–698, 2015). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by Warburg (Biochem Z 142:317–333, 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014). As the microenvironment of the target human tissue is retained and individual patient’s response to drugs is obtained, this platform promises to transcend current limitations of drug selection for clinical trials or treatments

Conclusions

Development of ex vivo human tissue and animal models with humanized organs including bone marrow and liver show considerable promise for analyzing drug responses that are more relevant to humans. Similarly using stable isotope tracer methods with these improved models in advanced stages of the drug development pipeline, in conjunction with tissue biopsy is expected significantly to reduce the high failure rate of experimental drugs in Phase II and III clinical trials.

     

Using the product environmental footprint for supply chain management: lessons learned from a case study on pork

Purpose

The purpose of this study was to test the chain-organization environmental footprint (chain-OEF) approach by applying it to part of a pork production chain in Belgium. The approach is supposed to provide insight into the environmental impact of a specific production chain in an efficient manner by applying pragmatic data collection throughout the chain. This is achieved by allocating the environmental impact of each of the production sites to the product of interest using straightforward allocation rules.

Methods

The cradle-to-gate (up to retail) environmental impact of pork was determined by life cycle assessment (LCA), in line with the product and organisation environmental footprint guidelines (PEF and OEF; European Commission 2013b). Foreground data was gathered at a feed production site, two farmers, a slaughterhouse and a meat processing site. All foreground operations are part of the same pork production chain in Belgium. The chain was completed using background data from Ecoinvent v3.01 (Wernet et al. 2016), Agri-Footprint v1.0 (Blonk 2014), European Life Cycle Database v3.0, LCA Food Database (Nielsen et al. 2003) and OEF Sector Rules Retail (Humbert et al. 2015b). The impact was quantified using the international reference life cycle data system (ILCD) midpoint method for 14 impact categories, but focussing on climate change.

Results and discussion

The total carbon footprint of the cradle-to-gate pork production system equals 0.46 kg CO₂-eq. (100 g pork)^?1. This result is quite similar to that of earlier studies analysing the pork production chain: 0.58 and 0.57 kg CO₂-eq. (100 g pork)^?1 (Bracquené et al. 2011, Agri-Footprint 2014). Most of the carbon footprint was caused by feed production and more specifically, by the feed ingredients and their transport. Grains, soy and palm oil have the largest impact contributions. The farms are responsible for most of the remaining impact. N₂O and CH₄ emissions are the largest cause of greenhouse gas emissions at the farms. Also, in the other 13 considered impact categories, feed production and farming are responsible for more than half of the total impact, mostly followed by meat processing.

Conclusions

Applying the chain-OEF approach in this study has shown that a chain LCA can be performed successfully and pragmatic data collection allows obtaining LCA results relatively fast, especially for small or medium-sized enterprises (SMEs). Whereas data availability was not such an issue, the main bottlenecks identified are data management and the link of LCA to other disciplines such as engineering, policy, etc. which could increase the added value of LCA studies.

     

Extending the geopolitical supply risk method: material “substitutability” indicators applied to electric vehicles and dental X-ray equipment

Purpose

While environmental LCA is relatively well developed, impact assessment methods for the “natural resources” AoP are weak. In particular, resource “criticality” is not addressed in conventional environmental impact assessment methods, though it could be captured within life cycle sustainability assessment. In that regard, the present article extends the previously developed geopolitical supply risk (GPSR) method by demonstrating the connection of criticality to a functional unit while incorporating measures of material substitutability to reflect the “vulnerability” dimension of criticality.

Methods

The GPSR method developed by Gemechu et al. (J Ind Ecol 20:154–165, 2015a) and subsequently extended by Helbig et al. (J Clean Prod 137:1170–1178, 2016a), and Cimprich et al. (J Clean Prod, 2017) is integrated into an LCIA characterization model. Further, semi-quantitative material substitutability indicator values based on a study by Graedel et al. (PNAS 112:6295–6300, 2015) are incorporated to represent the vulnerability dimension of criticality. The method is demonstrated with an update of a previously published case study of a European-manufactured electric vehicle by Gemechu et al. (Int J Life Cycle Assess 22:31–39, 2015b), along with a new case study of dental X-ray equipment. Due to novel aspects of the GPSR method, the latter case involves constructing an unusually comprehensive bill of materials by tracing unit processes to input commodities with identification codes for collecting commodity trade data.

Results and discussion

Supply risk “hotspots” are often associated with “minor” commodities such as neodymium in an electric vehicle and cesium iodide in a dental X-ray system. Though difficult to measure, material substitutability can mitigate supply risk. Environmental loads of a dental X-ray system are dominated by production of relatively small specialized functional components like capacitors and printed circuit boards, which are far more environmentally intensive per unit of mass than common structural and mechanical components. Thus, small components comprised of minor materials can “pack a punch” from a supply risk and environmental perspective.

Conclusions

The GPSR method presented in the present article brings resource criticality assessment to a product-level while addressing a gap in conventional LCIA methods regarding short-run, socioeconomic availability of natural resources. Further, the case studies illustrate the significance of material substitutability in supply risk assessment. Several complications and limitations of the GPSR method offer directions for future research. Nonetheless, the GPSR method complements environmental LCA to better inform design and management decisions on a product-level.

     

Algorithms for computing the double cut and join distance on both gene order and intergenic sizes

Background

Combinatorial works on genome rearrangements have so far ignored the influence of intergene sizes, i.e. the number of nucleotides between consecutive genes, although it was recently shown decisive for the accuracy of inference methods (Biller et al. in Genome Biol Evol 8:1427–39, 2016; Biller et al. in Beckmann A, Bienvenu L, Jonoska N, editors. Proceedings of Pursuit of the Universal-12th conference on computability in Europe, CiE 2016, Lecture notes in computer science, vol 9709, Paris, France, June 27–July 1, 2016. Berlin: Springer, p. 35–44, 2016). In this line, we define a new genome rearrangement model called wDCJ, a generalization of the well-known double cut and join (or DCJ) operation that modifies both the gene order and the intergene size distribution of a genome.

Results

We first provide a generic formula for the wDCJ distance between two genomes, and show that computing this distance is strongly NP-complete. We then propose an approximation algorithm of ratio 4/3, and two exact ones: a fixed-parameter tractable (FPT) algorithm and an integer linear programming (ILP) formulation.

Conclusions

We provide theoretical and empirical bounds on the expected growth of the parameter at the center of our FPT and ILP algorithms, assuming a probabilistic model of evolution under wDCJ, which shows that both these algorithms should run reasonably fast in practice.

     

A representation of a compressed de Bruijn graph for pan-genome analysis that enables search

Background

Recently, Marcus et al. (Bioinformatics 30:3476–83, 2014) proposed to use a compressed de Bruijn graph to describe the relationship between the genomes of many individuals/strains of the same or closely related species. They devised an \(O(n\log g)\) time algorithm called splitMEM that constructs this graph directly (i.e., without using the uncompressed de Bruijn graph) based on a suffix tree, where n is the total length of the genomes and g is the length of the longest genome. Baier et al. (Bioinformatics 32:497–504, 2016) improved their result.

Results

In this paper, we propose a new space-efficient representation of the compressed de Bruijn graph that adds the possibility to search for a pattern (e.g. an allele—a variant form of a gene) within the pan-genome. The ability to search within the pan-genome graph is of utmost importance and is a design goal of pan-genome data structures.

     

Superbubbles revisited

Background

Superbubbles are distinctive subgraphs in direct graphs that play an important role in assembly algorithms for high-throughput sequencing (HTS) data. Their practical importance derives from the fact they are connected to their host graph by a single entrance and a single exit vertex, thus allowing them to be handled independently. Efficient algorithms for the enumeration of superbubbles are therefore of important for the processing of HTS data. Superbubbles can be identified within the strongly connected components of the input digraph after transforming them into directed acyclic graphs. The algorithm by Sung et al. (IEEE ACM Trans Comput Biol Bioinform 12:770–777, 2015) achieves this task in \(\mathcal {O}(m~log(m))\)-time. The extraction of superbubbles from the transformed components was later improved to by Brankovic et al. (Theor Comput Sci 609:374–383, 2016) resulting in an overall \(\mathcal {O}(m+n)\)-time algorithm.

Results

A re-analysis of the mathematical structure of superbubbles showed that the construction of auxiliary DAGs from the strongly connected components in the work of Sung et al. missed some details that can lead to the reporting of false positive superbubbles. We propose an alternative, even simpler auxiliary graph that solved the problem and retains the linear running time for general digraph. Furthermore, we describe a simpler, space-efficient \(\mathcal {O}(m+n)\)-time algorithm for detecting superbubbles in DAGs that uses only simple data structures.

Implementation

We present a reference implementation of the algorithm that accepts many commonly used formats for the input graph and provides convenient access to the improved algorithm. https://github.com/Fabianexe/Superbubble.

     

The use of chlorogenic acid and its analogues as inhibitors: an investigation of the inhibition of sortase A of <Emphasis Type="Italic">Staphylococcus aureus</Emphasis> using molecular docking and dynamic simulation

Objectives

To use molecular docking and dynamic simulation to investigate the inhibitory action of chlorogenic acid (CHA) and its analogues against sortase A of Staphylococcus aureus.

Results

Five novel, natural inhibitors with different activities were discovered for sortase A (SrtA). The inhibition mechanism of the novel inhibitors was consistent with the mechanism of CHA, which was reported previously by Wang et al. (Front Microbiol 6:1031, 2015). Based on structure–activity relationship analysis, the hydroxyl moiety (C1) of the inhibitors is critical in the catalytic region of SrtA, which could be confirmed by the calculation of the binding free energy between SrtA and the inhibitors.

Conclusions

The mechanism obtained by molecular dynamics simulation is thus useful for the development of novel, selective SrtA inhibitors.

     

Low cholesterol efflux capacity and abnormal lipoprotein particles in youth with type 1 diabetes: a case control study

Background

Patients with type 1 diabetes (T1DM) have increased mortality from cardiovascular disease (CVD). Risk factors for CVD include an elevation of LDL (LDLp) and small HDL (sHDLp) particles, and a decrease in reverse cholesterol transport i.e. HDL-cholesterol efflux capacity (CEC). Our objective was to compare lipoprotein particles and CEC between T1DM and healthy controls (HC) and to explore the associations between NMR lipid particles and cholesterol efflux.

Methods

78 patients with T1DM and 59 HC underwent fasting lipoprotein profile testing by NMR and measurements of CEC by cell-based method. The associations between NMR lipid particles with CEC were analyzed using multivariable linear regression models.

Results

Youth with T1DM had higher total LDLp 724 [(563–985) vs 622 (476–794) nmol/L (P?=?0.011)] (Maahs et al. in Circulation 130(17):1532–58, 2014; Shah et al. in Pediatr Diabetes 16(5):367–74, 2015), sHDLp [11.20 (5.7–15.3) vs 7.0 (3.2–13.1) μmol/L (P?=?0.021)], and lower medium HDLp [11.20 (8.5–14.5) vs 12.3 (9–19.4), (P?=?0.049)] and lower CEC (0.98?±?0.11% vs 1.05?±?0.15%, P?=?0.003) compared to HC. Moreover, CEC correlated with sHDLp (β?=???0.28, P?=?0.045) and large HDLp (β?=?0.46, P?<?0.001) independent of age, sex, ethnicity, BMIz, HbA1c, hsCRP and total HDLp in the diabetic cohort.

Conclusions

Youth with T1DM demonstrated a more atherogenic profile including higher sHDL and LDLp and lower CEC. Future efforts should focus on considering adding lipoprotein particles and CEC in CVD risk stratification of youth with T1DM.Trial registration Clinical Trials Registration Number NCT02275091

     

Interaction profile-based protein classification of death domain

Background

The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experimental and computational efforts on the creation and analysis of information derived from 3D structure. In particular, the high-throughput generation of protein-protein interaction data from a few organisms makes such an approach very important towards understanding the molecular recognition that make-up the entire protein-protein interaction network. Since the generation of sequences, and experimental protein-protein interactions increases faster than the 3D structure determination of protein complexes, there is tremendous interest in developing in silico methods that generate such structure for prediction and classification purposes. In this study we focused on classifying protein family members based on their protein-protein interaction distinctiveness. Structure-based classification of protein-protein interfaces has been described initially by Ponstingl et al. [1] and more recently by Valdar et al. [2] and Mintseris et al. [3], from complex structures that have been solved experimentally. However, little has been done on protein classification based on the prediction of protein-protein complexes obtained from homology modeling and docking simulation.

Results

We have developed an in silico classification system entitled HODOCO (Homology modeling, Docking and Classification Oracle), in which protein Residue Potential Interaction Profiles (RPIPS) are used to summarize protein-protein interaction characteristics. This system applied to a dataset of 64 proteins of the death domain superfamily was used to classify each member into its proper subfamily. Two classification methods were attempted, heuristic and support vector machine learning. Both methods were tested with a 5-fold cross-validation. The heuristic approach yielded a 61% average accuracy, while the machine learning approach yielded an 89% average accuracy.

Conclusion

We have confirmed the reliability and potential value of classifying proteins via their predicted interactions. Our results are in the same range of accuracy as other studies that classify protein-protein interactions from 3D complex structure obtained experimentally. While our classification scheme does not take directly into account sequence information our results are in agreement with functional and sequence based classification of death domain family members.

     

Positive impacts in social life cycle assessment: state of the art and the way forward

Purpose

Social life cycle assessment (SLCA) is a methodology under continuous development, which may be applied at different scales: from products to economic sectors up to systems at region (meso) and country (macro) scales. Traditionally, SLCA has been focusing on the assessment of negative social externalities, whereas also positive social impacts could be associated to human interventions. The purpose of the present study is to understand how positive impacts are defined in published literature and how they could be assessed through indicators. The aim is to clarify the concept among scholars and to support decision making in business and policy context.

Methods

The study uses a systematic review approach in order to analyse the types of indicators adopted. In the field of SLCA and according to Paragahawewa et al. (2009), “[I]ndicators are ‘pointers’ to the state of the impact categories (and/or subcategories) being evaluated by the SLCA”. Indicators can be quantitative, semi-quantitative or qualitative (UNEP/SETAC 2009). This review was carried out in order to identify and analyse positive impacts and indicators. After careful scrutiny, 47 papers containing theoretical frameworks were considered, as well as 46 papers presenting case studies.

Results and discussion

Compared to environmental life cycle assessment (E-LCA), where the presence of positive impacts is lower, evaluating benefits or positive impacts can still play a major role in SLCA (Benoît et al. 2010). A quarter of the analysed papers on theoretical frameworks take into account the topic of positive impacts and indicators. Results from case study analysis highlight as “workers”, was the most considered stakeholder (in 100 % of the analysed papers), and as the majority of positive indicators used in the case study analysed are recorded in relation to “other value chain actors”. Within the concept of “positive impacts”, no reference should be made merely to the utility of a product or service. In a broader sense, we could refer to solutions improving the conditions of one or various stakeholders involved. In other words, these are solutions that carry a positive contribution to one or more stakeholders without harming others.

Conclusions

So far, positive impacts are barely covered in literature. There is a clear need of streamlining definition and indicators, especially if they should be applied in a policy context complementing traditional—and often monetary-based, cost-benefit analysis (CBA).

     

Soil under nurse plants is always better than outside: a survey on soil amelioration by a complete guild of nurse plants across a long environmental gradient

Aims

Soil under nurse plants is more fertile than in the harsh surroundings. This is a primary mechanism involved in plant to plant facilitation and it is critical in structuring plant communities under stressful conditions. However we do not know how this soil enrichment process varies along complex environmental gradients and among coexisting nurse plants.

Methods

Soil properties related to structure, resource stocks and microbial activity, were compared among up to ten nurse plant species and adjacent barren soil areas, along a 1600 m elevation gradient above the treeline in central Chilean Andes. Shifts in Relative Interaction Index (RII) sensu Armas (Ecology 85: 2682–2686, 2004) and in coefficient of variation on soil properties were also modelled.

Results

Soil under nurse plants was always richer than on barren areas irrespective of altitude, except in the case of texture with more small particles in the intermediate altitude. β-glucosidase activity was higher under cushion plants than under nurse plants with other growth habit. Besides β-glucosidase and phosphatase activities were more variable at higher altitudes. Nitrogen was more variable under nurse plants than in barren areas and its RII values were lower at intermediate altitudes.

Conclusions

Soil amelioration by nurse plants occurred all along the studied environmental gradient promoting islands of fertility and a general increase on soil niches heterogeneity.

     

Nasal gene expression differentiates COPD from controls and overlaps bronchial gene expression

Background

Nasal gene expression profiling is a promising method to characterize COPD non-invasively. We aimed to identify a nasal gene expression profile to distinguish COPD patients from healthy controls. We investigated whether this COPD-associated gene expression profile in nasal epithelium is comparable with the profile observed in bronchial epithelium.

Methods

Genome wide gene expression analysis was performed on nasal epithelial brushes of 31 severe COPD patients and 22 controls, all current smokers, using Affymetrix Human Gene 1.0 ST Arrays. We repeated the gene expression analysis on bronchial epithelial brushes in 2 independent cohorts of mild-to-moderate COPD patients and controls.

Results

In nasal epithelium, 135 genes were significantly differentially expressed between severe COPD patients and controls, 21 being up- and 114 downregulated in COPD (false discovery rate?<?0.01). Gene Set Enrichment Analysis (GSEA) showed significant concordant enrichment of COPD-associated nasal and bronchial gene expression in both independent cohorts (FDR_GSEA <?0.001).

Conclusion

We identified a nasal gene expression profile that differentiates severe COPD patients from controls. Of interest, part of the nasal gene expression changes in COPD mimics differentially expressed genes in the bronchus. These findings indicate that nasal gene expression profiling is potentially useful as a non-invasive biomarker in COPD.

Trial registration

ClinicalTrials.gov registration number NCT01351792 (registration date May 10, 2011), ClinicalTrials.gov registration number NCT00848406 (registration date February 19, 2009), ClinicalTrials.gov registration number NCT00807469 (registration date December 11, 2008).

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Using human case studies to teach evolution in high school A.P. biology classrooms

Background

While recent research indicates that using human examples can be an engaging way to teach core evolutionary concepts such as natural selection and phylogenetic thinking, teachers still face potential conflicts and challenges that arise from cultural barriers to teaching and learning about evolution. The “Teaching Evolution through Human Examples” (TEtHE) project developed (1) a set of four curriculum mini-units for advanced placement (A.P.) biology that use human examples to teach evolutionary principles (Adaptation to Altitude, Evolution of Human Skin Color, Malaria, and What Does It Mean To Be Human?), and (2) a cultural and religious sensitivity (CRS) teaching strategies resource that includes background materials and two in-class activities to help teachers create a classroom environment to increase student willingness to engage the topic.

Methods

This paper reports on the development and field test of the TEtHE materials in A.P. biology classes in 10 schools in 8 states during the 2012–2013 school year using a design-based research framework (cf. Anderson and Shattuck in Educ Res 41:16–25, 2012). We chose A.P. classrooms to study the potential impacts of the materials in a “best case scenario” and analyzed data about understanding and acceptance of evolution from pre-post assessments in the 10 classrooms separately to mitigate potential validity concerns arising from the design (Anderson and Shattuck in Educ Res 41:16–25, 2012; Shadish et al. in Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin, Boston, 2002). These data were treated as a secondary source of formative data to add additional perspective to teacher self-reports, observations, student and teacher questionnaires, teacher interviews, and student focus groups.

Results

Results indicate that the use of the three curriculum mini-units which focus on natural selection and the CRS classroom activities generally increased A.P. biology students’ understanding and acceptance of evolution. Students whose teachers used one of the CRS activities showed generally larger increases in understanding of evolution than those whose teachers did not use one of the CRS activities.

Conclusions

Although the utility of using human examples to teach evolution in college-level classes has been demonstrated in a few previous studies, this is the first national project of which we are aware to systematically explore the effect of a similar approach in high school biology classes. While we recognize that the results may be mitigated by the limitations of design-based research, particularly the absence of a comparison or control group, the general effectiveness of this approach suggested by qualitative and quantitative data in increasing student understanding and acceptance of evolution suggests that using human examples and explicitly creating a classroom environment to help students engage the topic of evolution are worth considering for further development and more robust testing.

     

Generalized enhanced suffix array construction in external memory

Background

Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory.

Results

In this article we present and analyze \(\mathsf {eGSA}\) [introduced in CPM (External memory generalized suffix and \(\mathsf {LCP}\) arrays construction. In: Proceedings of CPM. pp 201–10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, \(\mathsf {eGSA}\) showed a competitive performance when compared to \(\mathsf {eSAIS}\) and \(\mathsf {SAscan}\), which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm.

Conclusions

The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time.

     

rDolphin: a GUI R package for proficient automatic profiling of 1D <Superscript>1</Superscript>H-NMR spectra of study datasets

Introduction

Adoption of automatic profiling tools for ¹H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.

     

Accumulation of Fascin<Superscript>+</Superscript> cells during experimental autoimmune neuritis

Background

Experimental autoimmune neuritis (EAN) is a well-known animal model of human demyelinating polyneuropathies and is characterized by inflammation and demyelination in the peripheral nervous system. Fascin is an evolutionarily highly conserved cytoskeletal protein of 55 kDa containing two actin binding domains that cross-link filamentous actin to hexagonal bundles.

Methods

Here we have studied by immunohistochemistry the spatiotemporal accumulation of Fascin?+?cells in sciatic nerves of EAN rats.

Results

A robust accumulation of Fascin?+?cell was observed in the peripheral nervous system of EAN which was correlated with the severity of neurological signs in EAN.

Conclusion

Our results suggest a pathological role of Fascin in EAN.

Virtual slides

The virtual slides for this article can be found here: http://www.diagnosticphatology.diagnomx.eu/vs/6734593451114811