Div-BLAST: Diversification of Sequence Search Results

Sequence similarity tools, such as BLAST, seek sequences most similar to a query from a database of sequences. They return results significantly similar to the query sequence and that are typically highly similar to each other. Most sequence analysis tasks in bioinformatics require an exploratory approach, where the initial results guide the user to new searches. However, diversity has not yet been considered an integral component of sequence search tools for this discipline. Some redundancy can be avoided by introducing non-redundancy during database construction, but it is not feasible to dynamically set a level of non-redundancy tailored to a query sequence. We introduce the problem of diverse search and browsing in sequence databases that produce non-redundant results optimized for any given query. We define diversity measures for sequences and propose methods to obtain diverse results extracted from current sequence similarity search tools. We also propose a new measure to evaluate the diversity of a set of sequences that is returned as a result of a sequence similarity query. We evaluate the effectiveness of the proposed methods in post-processing BLAST and PSI-BLAST results. We also assess the functional diversity of the returned results based on available Gene Ontology annotations. Additionally, we include a comparison with a current redundancy elimination tool, CD-HIT. Our experiments show that the proposed methods are able to achieve more diverse yet significant result sets compared to static non-redundancy approaches. In both sequence-based and functional diversity evaluation, the proposed diversification methods significantly outperform original BLAST results and other baselines. A web based tool implementing the proposed methods, Div-BLAST, can be accessed at cedar.cs.bilkent.edu.tr/Div-BLAST     

Contextual Challenges to Dual-Language Education: A Case Study of a Developing Middle School Program

This article describes how a team of urban middle school educators in Philadelphia were developing a dual-language program to address the needs of their low-income, predominantly Puerto Rican population. It demonstrates how the structural, sociolinguistic, and ideological context influenced the way that this bilingual program functioned on the local level, and it challenges the dichotomous thinking that characterizes most discussions of bilingual education.     

高中生物课开展探究性实验活动策略初探

新的高中课程标准的理念强调提高每个高中学生的生物科学素养,倡导开展探究性学习.因此,在高中生物课中开展探究性实验活动显得十分重要.本文阐述了开展探究性实验活动的基本策略和方法.     

Evaluating Spatial Overlap and Relatedness of White-tailed Deer in a Chronic Wasting Disease Management Zone

Wildlife disease transmission, at a local scale, can occur from interactions between infected and susceptible conspecifics or from a contaminated environment. Thus, the degree of spatial overlap and rate of contact among deer is likely to impact both direct and indirect transmission of infectious diseases such chronic wasting disease (CWD) or bovine tuberculosis. We identified a strong relationship between degree of spatial overlap (volume of intersection) and genetic relatedness for female white-tailed deer in Wisconsin’s area of highest CWD prevalence. We used volume of intersection as a surrogate for contact rates between deer and concluded that related deer are more likely to have contact, which may drive disease transmission dynamics. In addition, we found that age of deer influences overlap, with fawns exhibiting the highest degree of overlap with other deer. Our results further support the finding that female social groups have higher contact among related deer which can result in transmission of infectious diseases. We suggest that control of large social groups comprised of closely related deer may be an effective strategy in slowing the transmission of infectious pathogens, and CWD in particular.     

Combining Results of Multiple Search Engines in Proteomics

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.The most commonly used proteomics approach, shotgun proteomics, has become an invaluable tool for the high-throughput characterization of proteins in biological samples (1). This workflow relies on the combination of protein digestion, liquid chromatography (LC)¹ separation, tandem mass spectrometry (MS/MS), and sophisticated data analysis in its aim to derive an accurate and complete set of peptides and their inferred proteins that are present in the sample being studied. Although many variations are possible, the typical workflow begins with the digestion of proteins into peptides with a protease, typically trypsin. The resulting peptide mixture is first separated via LC and then subjected to mass spectrometry (MS) analysis. The MS instrument acquires fragment ion spectra on a subset of the peptide precursor ions that it measures. From the MS/MS spectra that measure the abundance and mass of the peptide ion fragments, peptides present in the mixture are identified and proteins are inferred by means of downstream computational analysis.The informatics component of the shotgun proteomics workflow is crucial for proper data analysis (2), and a wide variety of tools have emerged for this purpose (3). The typical informatics workflow can be summarized in a few steps: conversion from vendor proprietary formats to an open format, high-throughput interpretation of the MS/MS spectra with a search engine, and statistical validation of the results with estimation of the false discovery rate at a selected score threshold. Various tools for measuring relative peptide abundances may be applied, dependent on the type of quantitation technique applied in the experiment. Finally, the proteins present, and their abundance in the sample, are inferred based on the peptide identifications.One of the most computationally intensive and diverse steps in the computational analysis workflow is the use of a search engine to interpret the MS/MS spectra in order to determine the best matching peptide ion identifications (4), termed peptide-spectrum matches (PSMs). There are three main types of engines: sequence search engines such as X!Tandem (5), Mascot (6), SEQUEST (7), MyriMatch (8), MS-GFDB (9), and OMSSA (10), which attempt to match acquired spectra with theoretical spectra generated from possible peptide sequences contained in a protein sequence list; spectral library search engines such as SpectraST (11), X!Hunter (12), and Bibliospec (13), which attempt to match spectra with a library of previously observed and identified spectra; and de novo search engines such as PEAKS (14), PepNovo (15), and Lutefisk (16), which attempt to derive peptide identifications based on the MS/MS spectrum peak patterns alone, without reference sequences or previous spectra (17). Additionally, elements of de novo sequencing (short sequence tag extraction) and database searching have been combined to create hybrid search engines such as InSpecT (18) and PEAKS-DB (19).The goal of this review is to evaluate the potential improvement made possible by combining the search results of multiple search engines. On their own, most of the common search engines perform well on typical datasets, with the results having significant overlap between the algorithms (20); and yet, the degree to which there is divergence in the results of different search engines remains quite high. Disagreement between search engines, where multiple different peptide sequences are identified with high confidence, is quite rare. It is much more common to observe different engines being in agreement on the correct identification, yet with neither of the identifications having a probability high enough to allow it to pass the selected error criterion when analyzed independently. When the results are analyzed together, the agreement on the identification might propel the PSM to pass the same error criterion. In cases when only one engine scores the PSM highly enough that it passes an acceptance threshold, these identifications are reported within the acceptable error rate. Also, some engines use unique methods to consider peptides or modifications not considered by other engines. Even if the experimenter is careful to choose similar search parameters when running multiple tools, different search engines will allow one to set non-identical search parameters, which contributes to reduced overlap between the search results. Spectral library search engines tend to be far more sensitive and specific than sequence search engines, but only for peptide ions for which there is a spectrum in the library.Given that different search engines excel at identifying different subsets of PSMs, it seems natural to combine the power of multiple search engines to achieve a single, better result. Many algorithms and software tools have emerged that combine search results (21–28), each demonstrating an improved final result over any individual search engine alone. Such improved results come at the cost of the increased complexity of managing multiple searches in an analysis pipeline, as well as a several-fold increase in computational time in what is already the most computationally expensive step. However, with the ever-growing availability of fast computers, computing clusters, and cloud computing resources, researchers now have within reach the ability to quickly search their MS/MS data using several of the still-growing number of search engine algorithms. In some cases the open-source search engines are quite similar to their commercial alternatives; for example, Comet (29) is very similar to SEQUEST. Given the significant amount of time the average researcher takes to design an experiment, process the samples, and acquire the data, it is natural that a researcher would wish to maximize the number and confidence of peptide and protein identifications in each dataset with a rigorous computational analysis. Furthermore, when using label-free spectral counting for abundance analysis, maximizing the number of PSMs increases the dynamic range and accuracy of the quantitative approach (23). Therefore, the demand to use multiple search engines and integrate their results with the goal of maximizing the amount of information gleaned from each dataset is expected to continue growing.Also emerging are software tools that use several iterative database searching passes of the same data, combining multiple database search tools, searches with different post-translational modifications, and searches against different databases in an attempt to use each specific tool under ideal conditions, utilizing each for its specific strengths and integrating the results (30). Some relevant aspects of such strategies are discussed by Tharakan et al. (31).In the following sections, we review the various approaches and software programs available to assist with the merging of results from different search engines. We also provide a performance comparison of the various approaches described here on a test dataset to assess the expected performance gains from the various described methods.     

How to Use the Science of Snow to Engage Middle School Students in an Interdisciplinary Experience

In this interdisciplinary and field-based activity, grade 5 to 9 students engage in a comprehensive scientific study of snow. Through a series of in-class and out-of-class structured interdisciplinary and team-teaching lesson progressions, students will collect data to be able to analyze and apply knowledge about weather, the physical properties of snow, and the structure of matter that will increase understanding about the nature of science.     

Potential Use of School Absenteeism Record for Disease Surveillance in Developing Countries,Case Study in Rural Cambodia

Background

Disease surveillance allows prospective monitoring of patterns in disease incidence in the general community, specific institutions (e.g. hospitals, elderly care homes), and other important population subgroups. Surveillance activities are now routinely conducted in many developed countries and in certain easy-to-reach areas of the developing ones. However due to limited health resources, population in rural area that consisted of the most the vulnerable groups are not under surveillance. Cheaper alternative ways for disease surveillance were needed in resource-limited settings.

Methods and Findings

In this study, a syndromic surveillance system using disease specific absenteeism rates was established in 47 pre-schools with 1,417 students 3–6 y of age in a rural area of Kampot province, Cambodia. School absenteeism data were collected via short message service. Data collected between 1st January and 31st December 2012 was used for system evaluation for future potential use in larger scale. The system appeared to be feasible and acceptable in the rural study setting. Moderate correlation was found between rates of school absenteeism due to illness and the reference data on rates of attendance at health centers in persons <16 y (maximum cross-correlation coefficient = 0.231 at lag = −1 week).

Conclusions

School absenteeism data is pre-existing, easily accessible and requires minimum time and resources after initial development, and our results suggest that this system may be able to provide complementary data for disease surveillance, especially in resource limited settings where there is very little information on illnesses in the community and traditional surveillance systems are difficult to implement. An important next step is to validate the syndromic data with other forms of surveillance including laboratory data.     

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data.     

The Genetic Relatedness in Groups of Joint-Nesting Taiwan Yuhinas: Low Genetic Relatedness with Preferences for Male Kin

The relative importance of direct and indirect fitness and, thus, the role of kinship in the evolution of social behavior is much debated. Studying the genetic relatedness of interacting individuals is crucial to improving our understanding of these issues. Here, we used a seven-year data set to study the genetic structure of the Taiwan yuhina (Yuhina brunneciceps), a joint-nesting passerine. Ten microsatellite loci were used to investigate the pair-wised relatedness among yuhina breeding group members. We found that the average genetic relatedness between same-sex group members was very low (0.069 for male dyads and 0.016 for female dyads). There was also a low ratio of closely-related kin (r>0.25) in the cooperative breeding groups of yuhinas (21.59% and 9.68% for male and female dyads, respectively). However, the relatedness of male dyads within breeding groups was significantly higher than female dyads. Our results suggest that yuhina cooperation is maintained primarily by direct fitness benefits to individuals; however, kin selection might play a role in partner choice for male yuhinas. Our study also highlights an important, but often neglected, question: Why do animals form non-kin groups, if kin are available? We use biological market theory to propose an explanation for group formation of unrelated Taiwan yuhinas.     

鹤岗市中小学生性健康教育现状的调查研究

目的:了解鹤岗市中小学生性健康教育现状,为进一步开展青春期性健康教育提供依据。方法:分层随机整群抽取鹤岗市1735名中小学生进行无记名问卷调查。结果:被调查的学生已具备一定的青春期性知识,但其知晓率仍偏低;性知识获取途径以社会媒体为主。大多数被调查者性生理发育状况良好,对青少年中发生的恋爱行为持宽容和理解的态度,而对婚前性行为持谨慎和保守态度。结论:今后应加大对性健康教育的宣传和投入,加强对中小学生的性道德教育。     

Missing Links: A Commentary on Ward H. Goodenough's Moving Article "Anthropology in the 20th Century and Beyond"

Ward H. Goodenough's optimistic summary of anthropological knowledge during the 20th century leaves missing links around the inevitable political and processual nature of the discipline. Conflict within the discipline and response to public events also are part of the story. Effects of the Cold War highlight the relations of knowledge and power in anthropological practice. Common humanity remains the focal point of anthropology. [Keywords: U.S. anthropology, 20th century, complexity, world events, reflexivity]     

生物学教育中的科学过程技能

科学过程技能是科学家进行科学研究所运用的技能。基础教育阶段的生物学课程标准都倡导探究性学习,强调对学生进行科学过程技能的训练。因此,在实际教学中,教师应加强自身的专业化发展,充分利用各种课程资源对学生进行科学过程技能的训练,并通过评价的方式,了解学生的科学过程技能水平,以为教学提供反馈信息,并最终更加有效地落实课程标准中的能力目标。     

Reasons for Missing Antiretroviral Therapy: Results from a Multi-Country Study in Tanzania,Uganda, and Zambia

Objectives

To identify the reasons patients miss taking their antiretroviral therapy (ART) and the proportion who miss their ART because of symptoms; and to explore the association between symptoms and incomplete adherence.

Methods

Secondary analysis of data collected during a cross-sectional study that examined ART adherence among adults from 18 purposefully selected sites in Tanzania, Uganda, and Zambia. We interviewed 250 systematically selected patients per facility (≥18 years) on reasons for missing ART and symptoms they had experienced (using the HIV Symptom Index). We abstracted clinical data from the patients’ medical, pharmacy, and laboratory records. Incomplete adherence was defined as having missed ART for at least 48 consecutive hours during the past 3 months.

Results

Twenty-nine percent of participants reported at least one reason for having ever missed ART (1278/4425). The most frequent reason was simply forgetting (681/1278 or 53%), followed by ART-related hunger or not having enough food (30%), and symptoms (12%). The median number of symptoms reported by participants was 4 (IQR: 2–7). Every additional symptom increased the odds of incomplete adherence by 12% (OR: 1.1, 95% CI: 1.1–1.2). Female participants and participants initiated on a regimen containing stavudine were more likely to report greater numbers of symptoms.

Conclusions

Symptoms were a common reason for missing ART, together with simply forgetting and food insecurity. A combination of ART regimens with fewer side effects, use of mobile phone text message reminders, and integration of food supplementation and livelihood programmes into HIV programmes, have the potential to decrease missed ART and hence to improve adherence and the outcomes of ART programmes.     

A Plethora of Fungi: Teaching a Middle School Unit on Fungi

Abstract

While fungi play a vital role in Earth's ecosystems, they are not highlighted in the Next Generation Science Standards (NGSS). This article contains a unit plan to introduce students to the fungal kingdom, characteristics of fungi, and their role as decomposers. The unit plan is written in a 5E model format and can be adjusted for any type of lesson planning format. Students explore fungi through hands-on activities, a jigsaw activity that makes use of collaborative learning, and analysis of case studies. Teachers can use this unit without a strong background in mycology, the study of fungi, or costly materials. A summative assessment is included at the end of the unit plan.     

Characteristics of Internet Addiction/Pathological Internet Use in U.S. University Students: A Qualitative-Method Investigation

Studies have identified high rates and severe consequences of Internet Addiction/Pathological Internet Use (IA/PIU) in university students. However, most research concerning IA/PIU in U.S. university students has been conducted within a quantitative research paradigm, and frequently fails to contextualize the problem of IA/PIU. To address this gap, we conducted an exploratory qualitative study using the focus group approach and examined 27 U.S. university students who self-identified as intensive Internet users, spent more than 25 hours/week on the Internet for non-school or non-work-related activities and who reported Internet-associated health and/or psychosocial problems. Students completed two IA/PIU measures (Young’s Diagnostic Questionnaire and the Compulsive Internet Use Scale) and participated in focus groups exploring the natural history of their Internet use; preferred online activities; emotional, interpersonal, and situational triggers for intensive Internet use; and health and/or psychosocial consequences of their Internet overuse. Students’ self-reports of Internet overuse problems were consistent with results of standardized measures. Students first accessed the Internet at an average age of 9 (SD = 2.7), and first had a problem with Internet overuse at an average age of 16 (SD = 4.3). Sadness and depression, boredom, and stress were common triggers of intensive Internet use. Social media use was nearly universal and pervasive in participants’ lives. Sleep deprivation, academic under-achievement, failure to exercise and to engage in face-to-face social activities, negative affective states, and decreased ability to concentrate were frequently reported consequences of intensive Internet use/Internet overuse. IA/PIU may be an underappreciated problem among U.S. university students and warrants additional research.     

Evaluating the Use of Global Sensitivity Analysis in Dynamic MFA

Dynamic material flow analysis (MFA) provides information about material usage over time and consequent changes in material stocks and flows. In order to understand the effect of limited data quality and model assumptions on MFA results, the use of sensitivity analysis methods in dynamic MFA studies has been on the increase. So far, sensitivity analysis in dynamic MFA has been conducted by means of a one‐at‐a‐time method, which tests parameter perturbations individually and observes the outcomes on output. In contrast to that, variance‐based global sensitivity analysis decomposes the variance of the model output into fractions caused by the uncertainty or variability of input parameters. The present study investigates interaction and time‐delay effects of uncertain parameters on the output of an archetypal input‐driven dynamic material flow model using variance‐based global sensitivity analysis. The results show that determining the main (first‐order) effects of parameter variations is often sufficient in dynamic MFA because substantial effects attributed to the simultaneous variation of several parameters (higher‐order effects) do not appear for classical setups of dynamic material flow models. For models with time‐varying parameters, time‐delay effects of parameter variation on model outputs need to be considered, potentially boosting the computational cost of global sensitivity analysis. Finally, the implications of exploring the sensitivities of model outputs with respect to parameter variations in the archetypical model are used to derive model‐ and goal‐specific recommendations on choosing appropriate sensitivity analysis methods in dynamic MFA.     

The Impact of Suicidality-Related Internet Use: A Prospective Large Cohort Study with Young and Middle-Aged Internet Users

Background

There has been no study that has allowed clear conclusions about the impact of suicide-related or mental health consultation-related internet use.

Aim

To investigate the impacts of suicide-related or mental health consultation-related internet use.

Methods

We conducted prospective observational longitudinal study with data collection at baseline screening (T0), 1 week after T0 (T1) and 7 weeks after T0 (T2). Participants with a stratified random sampling from 744,806 internet users were 20–49 years of age who employed the internet for suicide-related or mental health consultation-related reasons and internet users who did not. The main outcome was suicidal ideation. Secondary outcome measures comprised hopelessness, depression/anxiety, and loneliness.

Results

The internet users who had employed the internet for suicide-related or mental health consultation-related reasons at T0 (n = 2813), compared with those who had not (n = 2682), showed a significant increase in suicidal ideation (β = 0.38, 95%CI: 0.20–0.55) and depression/anxiety (β = 0.37, 95%CI: 0.12–0.61) from T1 to T2. Those who disclosed their own suicidal ideation and browsed for information about suicide methods on the web showed increased suicidal ideation (β = 0.55, 95%CI: 0.23–0.88; β = 0.45, 95% CI: 0.26–0.63, respectively). Although mental health consultation with an anonymous other online did not increase suicidal ideation, increased depression/anxiety was observed (β = 0.34, 95%CI: −0.03–0.71).

Conclusions

An increased suicidal ideation was observed in the young and middle-aged who employed the internet for suicide-related or mental health consultation-related reasons. Mental health consultation via the internet was not useful, but those who did so showed worsened depression/anxiety.