Observing populations and testing predictions about genetic drift in a computer simulation improves college students’ conceptual understanding

Background

Evolution is a difficult subject for students, with well-documented confusion about natural selection, tree thinking, and genetic drift among other topics. Here we investigate the effect of a simulation-based module about the conservation of black-footed ferrets, a module designed with pedagogical approaches that have been demonstrated to be effective, for teaching genetic drift. We compared performance on the Genetic Drift Inventory (GeDI) of students who completed the module and students who were in classes that used other methods for teaching genetic drift.

Results

Students in 19 courses using the simulation-based module improved their understanding of genetic drift significantly after completing the Ferrets module, as measured by the GeDI. Students in five control courses actually performed significantly worse on the GeDI after instruction. The lower scores in the control courses were driven by a decrease in these students’ understanding of key concepts.

Conclusions

The Ferrets module appears to be an effective way to teach genetic drift. In the control courses, students’ progress in understanding genetic drift may pass through a stage where their understanding of key concepts is worse than it was prior to instruction. However, students who learned genetic drift in courses that used the Ferrets module showed a more rapid increase in their understanding of key concepts related to genetic drift. This result suggests that the paths that students can take to move from novice to expert understanding may be more varied than was previously predicted.

     

Applying modern measurement approaches to constructs relevant to evidence-based practice among Canadian physical and occupational therapists

Background

Evidence-based practice (EBP) is a complex process. To quantify it, one has to also consider individual and contextual factors using multiple measures. Modern measurement approaches are available to optimize the measurement of complex constructs. This study aimed to develop a robust measurement approach for constructs around EBP including practice, individual (e.g. knowledge, attitudes, confidence, behaviours), and contextual factors (e.g. resources).

Methods

One hundred eighty-one items arising from 5 validated EBP measures were subjected to an item analysis. Nominal group technique was used to arrive at a consensus about the content relevance of each item. Baseline questionnaire responses from a longitudinal study of the evolution of EBP in 128 new graduates of Canadian physical and occupational therapy programmes were analysed. Principles of Rasch Measurement Theory were applied to identify challenges with threshold ordering, item and person fit to the Rasch model, unidimensionality, local independence, and differential item functioning (DIF).

Results

The nominal group technique identified 70/181 items, and modified Delphi approach identified 68 items that fit a formative model (2 related EBP domains: self-use of EBP (9 items) and EBP activities (7 items)) or a reflective model (4 related EBP domains: attitudes towards EBP (17 items), self-efficacy (9 items), knowledge (11 items) and resources (15 items)). Rasch analysis provided a single score for reflective construct. Among attitudes items, 65% (11/17) fit the Rasch model, item difficulties ranged from ??7.51 to logits (least difficult) to +?5.04 logits (most difficult), and person separation index (PSI)?=?0.63. Among self-efficacy items, 89% (8/9) fit the Rasch model, item difficulties ranged from ??3.70 to +?4.91, and PSI?=?0.80. Among knowledge items, 82% (9/11) fit the Rasch model, item difficulties ranged from ??7.85 to 4.50, and PSI?=?0.81. Among resources items, 87% (13/15) fit the Rasch model, item difficulties ranged from ??3.38 to 2.86, and PSI?=?0.86. DIF occurred in 2 constructs: attitudes (1 by profession and 2 by language) and knowledge (1 by language and 2 by profession) arising from poor wording in the original version leading to poor translation.

Conclusions

Rasch Measurement Theory was applied to develop a valid and reliable measure of EBP. Further modifications to the items can be done for subsequent waves of the survey.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome

Background

Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.

Aim

Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.

Methods

Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.

Results

Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.

Conclusion

Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.

     

Effects of specific allergen immunotherapy on biological markers and clinical parameters in asthmatic children: a controlled-real life study

Background

Allergen-specific immunotherapy (AIT) is the only treatment able to change the natural course of allergic diseases. We aimed at investigating the clinical efficacy of SLITOR (Serbian registered vaccine for sublingual allergen specific immunotherapy).

Methods

7–18 years old children with allergic asthma and rhinitis were enrolled and addressed to the active (AIT plus pharmacological treatment) or control (standard pharmacological treatment only) group. Clinical and medications scores, lung function and exhaled FeNO were measured at baseline and at every follow-up.

Results

There was a significant improvement in both nasal and asthma symptom scores as well as in medication score in SLIT group. SLIT showed an important influence on lung function and airway inflammation.

Conclusions

Our data showed that SLITOR was effective not only in terms of patient reported outcomes but an improvement of pulmonary function and decrease of lower airway inflammation were also observed.

     

Using multitask classification methods to investigate the kinase-specific phosphorylation sites

Background

Identification of phosphorylation sites by computational methods is becoming increasingly important because it reduces labor-intensive and costly experiments and can improve our understanding of the common properties and underlying mechanisms of protein phosphorylation.

Methods

A multitask learning framework for learning four kinase families simultaneously, instead of studying each kinase family of phosphorylation sites separately, is presented in the study. The framework includes two multitask classification methods: the Multi-Task Least Squares Support Vector Machines (MTLS-SVMs) and the Multi-Task Feature Selection (MT-Feat3).

Results

Using the multitask learning framework, we successfully identify 18 common features shared by four kinase families of phosphorylation sites. The reliability of selected features is demonstrated by the consistent performance in two multi-task learning methods.

Conclusions

The selected features can be used to build efficient multitask classifiers with good performance, suggesting they are important to protein phosphorylation across 4 kinase families.

     

Development and psychometric testing of a theory-based tool to measure self-care in diabetes patients: the Self-Care of Diabetes Inventory

Background

Self-care is essential for patients with diabetes mellitus. Both clinicians and researchers must be able to assess the quality of that self-care. Available tools have various limitations and none are theoretically based. The aims of this study were to develop and to test the psychometric properties of a new instrument based on the middle range-theory of self-care of chronic illness: the Self-Care of Diabetes Inventory (SCODI).

Methods

Forty SCODI items (5 point Likert type scale) were developed based on clinical recommendations and grouped into 4 dimensions: self-care maintenance, self-care monitoring, self-care management and self-care confidence based on the theory. Content validity was assessed by a multidisciplinary panel of experts. A multi-centre cross-sectional study was conducted in a consecutive sample of 200 type 1 and type 2 diabetes patients. Dimensionality was evaluated by exploratory factor analyses. Multidimensional model based reliability was estimated for each scale. Multiple regression models estimating associations between SCODI scores and glycated haemoglobin (HbA1c), body mass index, and diabetes complications, were used for construct validity.

Results

Content validity ratio was 100%. A multidimensional structure emerged for the 4 scales. Multidimensional model-based reliabilities were between 0.81 (maintenance) and 0.89 (confidence). Significant associations were found between self-care maintenance and HbA1c (p?=?0.02) and between self-care monitoring and diabetes complications (p?=?0.04). Self-care management was associated with BMI (p?=?0.004) and diabetes complications (p?=?0.03). Self-care confidence was a significant predictor of self-care maintenance, monitoring and management (all p?<?0.0001).

Conclusion

The SCODI is a valid and reliable theoretically-grounded tool to measure self-care in type 1 and type 2 DM patients.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

The reliability and validity of a Japanese version of symptom checklist 90 revised

Objective

To examine the validity and reliability of a Japanese version of the Symptom Checklist 90 Revised (SCL-90-R (J)).

Methods

The English SCL-90-R was translated to Japanese and the Japanese version confirmed by back-translation. To determine the factor validity and internal consistency of the nine primary subscales, 460 people from the community completed SCL-90-R(J). Test-retest reliability was examined for 104 outpatients and 124 healthy undergraduate students. The convergent-discriminant validity was determined for 80 inpatients who replied to both SCL-90-R(J) and the Minnesota Multiphasic Personality Inventory (MMPI).

Results

The correlation coefficients between the nine primary subscales and items were .26 to .78. Cronbach's alpha coefficients were from .76 (Phobic Anxiety) to .86 (Interpersonal Sensitivity). Pearson's correlation coefficients between test-retest scores were from .81 (Psychoticism) to .90 (Somatization) for the outpatients and were from .64 (Phobic Anxiety) to .78 (Paranoid Ideation) for the students. Each of the nine primary subscales correlated well with their corresponding constructs in the MMPI.

Conclusion

We confirmed the validity and reliability of SCL-90-R(J) for the measurement of individual distress. The nine primary subscales were consistent with the items of the original English version.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

The Association Between Depression,Suicidal Ideation and Psychological Strains in College Students: A Cross-National Study

Objective

This study examined the differences of psychological strains between Chinese and American college students and discussed how strains may influence individuals’ suicidal ideation and depression.

Participants/methods

A total of 539 college students (298 from China and 241 from the U.S.) were recruited in March 2016 to complete the survey study. Multiple linear regressions were used in data analysis.

Results

Students in America had higher scores on depression and stress than students in China, while students in China rated higher on suicidal ideation than students in America. In contrast of students in America facing more coping strains, students in China were confronting more value strains in their life.

Conclusion

The cross-cultural variations in the effect of psychological strains have been substantiated in current study, indicating that understanding the psychological strains in different cultural contexts is necessary for the early intervention and prevention in college aged populations.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics

Introduction

Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

Objectives

We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

Methods

Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA^® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

Results

A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

Conclusion

Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Investigating undergraduate health sciences students’ acceptance of evolution using MATE and GAENE

Background

Despite the overwhelming agreement among scientists regarding the fundamental importance of evolution to all areas of biology, a lack of evolution understanding and acceptance has been reported in studies of students, educators, and members of society. In the present study, we investigate and report evolution acceptance in a population of undergraduate health sciences students enrolled in a first-year foundational biology course. Two published instruments—The Measure of Acceptance of the Theory of Evolution (MATE) and the Generalized Acceptance of Evolution Evaluation (GAENE)—were used to quantify evolution acceptance. A confirmatory factor analysis (CFA) was performed on both instruments to test whether the items measured the underlying construct sufficiently. Additionally, Rasch scaling was used to investigate fit between the data and the measurement model, and to determine if the MATE should be treated as a unidimensional or bidimensional instrument. Using correlation and regression analysis, we examined the relationships between the two measures of evolution acceptance, and between measures of evolution acceptance with other student variables of interest.

Results

The health sciences students in this study demonstrated high acceptance of evolution at the start of term, as well as a significant increase in evolution acceptance from pre- to post-test. CFA and Rasch scaling provided some evidence that the MATE is a bidimensional instrument, but considering MATE as a bidimensional instrument provided little additional insight compared to treating MATE as a unidimensional instrument. Measures of evolution acceptance resulting from the MATE and GAENE instruments were significantly and strongly correlated. Multiple regression modeling identified underrepresented minority status as a demographic variable predictive of evolution acceptance, and provided further evidence of the strong association between the MATE and GAENE instruments.

Conclusions

The undergraduate health sciences students in this study demonstrated a significant increase in evolution acceptance from pre- to post-test after one semester of instruction in general biology. Measures of evolution acceptance from the MATE and GAENE instruments were strongly correlated whether MATE was treated as a unidimensional or bidimensional instrument. This work provides initial indications that the MATE and GAENE instruments perform comparably as measures of evolution acceptance. Although the instruments are closely related, this work found more psychometric evidence for interpreting and using GAENE scores than MATE scores as a measure of evolution acceptance.