Group Active Engagements Using Quantitative Modeling of Physiology Concepts in Large-Enrollment Biology Classes.
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ABSTRACT:
SUBMITTER: Carleton KL
PROVIDER: S-EPMC5134960 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature
Publications
Group Active Engagements Using Quantitative Modeling of Physiology Concepts in Large-Enrollment Biology Classes.
Carleton Karen L KL Rietschel Carly H CH Marbach-Ad Gili G
Journal of microbiology & biology education 20161202 3
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Project description:Active-learning pedagogies often require group work. We tested aspects of forming groups in a nonmajors Biology class. We asked whether large or small groups affected student learning outcomes and attitudes towards working in groups. We placed students in groups of three or six and students stayed in their groups for the term. We measured learning outcomes using a pre/postassessment as well as two-stage exams. Attitudes towards working in groups were measured using a previously published pre/post survey and an exit survey. We found that students in large groups did better on group exams and large groups had higher highest scores on the individual part of two-stage exams. Group size had no effect on students' postassessment scores or attitudes towards working in groups. We next assigned students to permanent or nonpermanent groups. We used the same metrics as the group size experiment. Students in permanent groups had higher group exam scores and better attitudes towards working in groups. Group permanence had no effect on students' postassessment scores. Students preferred working in permanent groups due to positive group interactions that developed over the quarter. Optimal group size and permanence are likely context-specific and dependent on the types of group work used in class.
| S-EPMC10756034 | biostudies-literature
Project description:The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.
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Project description:Using laser capture microdissection to isolate over 100 specific cell populations, we report the profiling of prostate cancer progression from benign epithelium to metastatic disease. By analyzing these expression signatures in the context of over 15,000 “molecular concepts”, or sets of biologically connected genes, we generated an integrative model of prostate cancer progression. Keywords: disease state analysis
2006-12-17 | GSE6099 | GEO
Project description:IntroductionWe classified individuals based on their baseline performance on cognitive measures and investigated the association between cognitive classifications and neuropathological findings ∼7 years later, as an external validator.MethodsBrain autopsies of 779 decedents were examined. Baseline latent class analysis on 10 neuropsychological measures was previously assigned: mixed-domains impairment (n = 39, 5%), memory-specific impairment (n = 210, 27%), frontal impairment (n = 113, 14.5%), average cognition (n = 360, 46.2%), and superior cognition (n = 57, 7.3%). Linear regressions and risks ratios were used to examine the relation of latent class assignment at enrollment with neuropathological indices.ResultsAmyloid β, tau, and transactive response DNA-binding protein 43 were associated with mixed-domains impairment and memory-specific impairment classes ∼7 years before death. Moderate arteriolosclerosis was associated with membership in the frontal impairment class.DiscussionOur findings support the use of latent class models that incorporate more comprehensive neuropsychological measures to classify cognitive impairment.
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Project description:Although the factors involved in cirrhotic ascites have been studied for a century, a number of observations are not understood, including the action of diuretics in the treatment of ascites and the ability of the plasma-ascitic albumin gradient to diagnose portal hypertension. This communication presents an explanation of ascites based solely on pathophysiological alterations within the peritoneal cavity. A quantitative model is described based on experimental vascular and intraperitoneal pressures, lymph flow, and peritoneal space compliance. The model's predictions accurately mimic clinical observations in ascites, including the magnitude and time course of changes observed following paracentesis or diuretic therapy.
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Project description: Not available
| S-EPMC5976055 | biostudies-literature
Project description:Using laser capture microdissection to isolate over 100 specific cell populations, we report the profiling of prostate cancer progression from benign epithelium to metastatic disease. By analyzing these expression signatures in the context of over 15,000 â??molecular conceptsâ??, or sets of biologically connected genes, we generated an integrative model of prostate cancer progression. Keywords: disease state analysis Experiment Design: â?¢ Type of experiment: This study used microarray experiments to profile prostate cancer progression through the isolation of pure cell populations using laser capture microdissection (LCM) and OmniPlex Whole Transcriptome (WTA) Amplification. â?¢ Experimental factors: This study profiled various pure cell populations isolated by LCM from prostate tissue. â?¢ The number of hybridizations performed in the experiment: A total of 104 hybridizations were performed. â?¢ The type of reference used for the hybridizations: A single commercially available pool of benign prostate tissue (CPP, Clontech) was used as the reference in all hybridizations. For the reference sample, 10 ng of CPP total RNA was converted into a WTA cDNA library in a volume of 25 µl and five 5 µl aliquots were amplified by WTA PCR and purified. Five ng aliquots of the pooled products were subjected to a second WTA PCR amplification in the presence of amino-allyl dUTP and all products were pooled before labeling to ensure equal representation across all of the hybridizations. â?¢ Hybridization design: For all hybridizations, the experimental prostate sample isolated by LCM was labeled with Cy5 and the common reference of benign pooled prostate as described above was labeled with Cy3. â?¢ Quality control steps taken: In order to assess biological and technical reproducibility, we captured identical regions from two specimens (PCA_11 and MET_HR_3) and subjected one sample, PCA_30, to two hybridizations. For PCA_11, adjacent regions of the same section were captured and treated as separate samples. For MET_HR_3, two separate foci of the liver metastasis (from separate frozen blocks) were captured and treated as separate samples. For PCA_30, two aliquots of the primary WTA PCR products were separately subjected to a second round of WTA PCR amplification. Replicates from PCA_30 and MET_HR_3 were also hybridized to arrays from each of the print runs utilized in this study. Samples used, extract preparation and labeling: â?¢ The origin of the biological sample (for instance, name of the organism, the provider of the sample) and its characteristics: All samples used were of human origin. The table in the MIAME Checklist (Supplmentary Methods) summarizes the samples used. Hybridizations are named according to the class of sample profiled and the background color is the same as shown in Figure S3. Two print runs were used during the course of the study and the indicated run for each hybridization is given. For prostate cancer samples, the Gleason patterns present on the sample section used are indicated, as well as the Gleason patterns of the actual cells isolated by LCM. A unique case number for all profiled samples is given. Descriptions of samples are given where applicable, including the location of metastatic foci. â?¢ Manipulation of biological samples and protocols used: Laser Capture Microdissection (LCM) was performed from frozen tissue sections with the SL Microtest device using µCUT software (MMI). Approximately 10,000 cells were captured for each sample. Serial sections were used if cells could not be obtained from a single section. Total RNA was isolated from captured cells with the RNAqueous Micro kit (Ambion) and treated with DNAse I according to the manufacturer's instructions. RNA quantification was perfomed using Ribogreen (Molecular Probes). â?¢ Protocol for preparing the hybridization extract: For each sample, total RNA (~10ng) in a volume of 25 µl was converted into an OmniPlex WTA cDNA library and amplified by WTA PCR using reagents and protocols according to the beta-commercial TransPlex WTA kit (Rubicon Genomics, Ann Arbor, MI). For each sample, a single 10 µl aliquot of the WTA cDNA library was amplified by WTA PCR and products were purified. Four or five 5 ng aliquots of product were subjected to a second WTA PCR amplification in the presence of amino-allyl dUTP for post amplification labeling and products were pooled before proceeding with the hybridization. Yields after all WTA PCR amplifications were between 2 to 5 μg per reaction, and reaction progress was monitored in real time using SYBR green I (Molecular Probes) on the iCycler IQ (BioRad) or ABI 7300 Real Time PCR system (Applied Biosystems). Real-time PCR amplifications were terminated at or before plateau phase as measured by fluorescence incorporation to preserve maximum representation. â?¢ Labeling protocol(s): For all WTA amplified cDNA samples with amino-allyl dUTP incorporated (10-20 ï?g), nuclease free water was added to 500 ï?l, the sample was transferred to a Microcon YM-30 filter, and centrifuged at 13,000 rcf at RT for 12 minutes. The spin column was inverted in a new collection tube and centrifuged at 13,000 rcf for 2 min at RT. The amount of sample was measured and the volume was adjusted to 5 ï?l with nuclease free water. For labeling, 5 ï?l of 1 M sodium bicarbonate (pH 9.0) was added and allowed to incubate at RT for 15 min. Nine ï?l of anhydrous DMSO were added to Mono Reactive Cy3 and Cy5 dye packs (Amersham, Buckinghamshire, England), mixed thoroughly, and 1 ï?l of the proper dye was added to each sample. The labeling mixture was incubated in the dark at RT for 1 hour. The reaction was stopped by the addition of 9 ï?l of 4 M Hydroxylamine for 15 min. For each labeling mixture, RNase free water was added to 100 ï?l, 500 ï?l of PB buffer was added and Cy3 and Cy5 mixtures were added to separate Qiaquick (Qiagen, Valencia, CA) spin columns and centrifuged at 13,000 rcf. Columns were washed twice with 700 ï?l of buffer PE, and centrifuged dry at 13,000 rcf for 2 min. To elute, 60 ï?l of EB buffer was placed on the column, incubated for 5 min and centrifuged at 13,000 rcf for 1 min. The Cy3 labeled and Cy5 labeled cDNA for each hybridization were mixed and 1.5 ï?l were used for analysis on a ND-1000 spectrophotometer. â?¢ External controls (spikes): Not utilized Hybridization procedures and parameters: â?¢ The protocol and conditions used during hybridization, blocking and washing: For hybridization, 40 ï?g of human Cot-1 DNA (Invitrogen, Carlsbad, CA) was added to 120 ï?l of labeled cDNA, the probe was transferred to a Microcon YM-30 filter and centrifuged at 13,000 rcf for 6 min at RT. The spin column was inverted in a new collection tube and centrifuged at 13,000 rcf for 2 min at RT. The eluted probe volume was adjusted to 18.6 ï?l with nuclease free water and the following were added: 4 ï?l of yeast tRNA (10 ï?g/ï?l, Invitrogen, Carlsbad, CA), 4.9 ï?l of 20X SSC and 0.84 ï?l of 10% SDS. The probe was denatured at 100 Co for 3 min and centrifuged at 13,000 rcf for 45 sec. The probe was added directly to the microarray and a cover slip was added. Slides were hybridized overnight in DIE-TECH 1 or 5 slide hybridization chambers in a 65 Co water bath. After hybridization, cover slips were removed by incubation in 2x SSC / 0.05% SDS. Slides were then washed in 2x SSC / 0.05% SDS for 5 min and 0.2x SSC / 0.05% SDS for five minutes. Slides were then washed in 0.2x SSC for 10 sec and centrifuged dry at 500 rpm for 5 min. Measurement data and specifications: â?¢ Type of scanning hardware and software used: Microarrays were scanned using a GenePix 4000B scanner (Axon Instruments, Union City, CA). â?¢ Type of image analysis software used: Images were gridded and spots were quantified using GenePix Pro 4.0 software (Axon Instruments, Union City, CA). â?¢ A description of the measurements produced by the image-analysis software and a description of which measurements were used in the analysis: The measurements made by GenePix Pro 4.0 are described in the sample files. For all hybridizations, the log2 normalized Median of Ratios (as described below) was used. â?¢ Data selection and transformation procedures: Arrays were auto-gridded by GenePix 4.0. Features flagged by GenePix as not found during grid
2010-06-05 | E-GEOD-6099 | biostudies-arrayexpress
Project description:Active matter comprises individual units that convert energy into mechanical motion. In many examples, such as bacterial systems and biofilament assays, constituent units are elongated and can give rise to local nematic orientational order. Such "active nematics" systems have attracted much attention from both theorists and experimentalists. However, despite intense research efforts, data-driven quantitative modeling has not been achieved, a situation mainly due to the lack of systematic experimental data and to the large number of parameters of current models. Here, we introduce an active nematics system made of swarming filamentous bacteria. We simultaneously measure orientation and velocity fields and show that the complex spatiotemporal dynamics of our system can be quantitatively reproduced by a type of microscopic model for active suspensions whose important parameters are all estimated from comprehensive experimental data. This provides unprecedented access to key effective parameters and mechanisms governing active nematics. Our approach is applicable to different types of dense suspensions and shows a path toward more quantitative active matter research.
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Project description:Quantitative skills are an important competency for undergraduate biology students and should be incorporated early and frequently in an undergraduate's career. Community colleges (CCs) are responsible for teaching introductory biology to a large proportion of biology and prehealth students, and quantitative skills are critical for their careers. However, we know little about the challenges and affordances that CC instructors encounter when incorporating quantitative skills into their courses. To explore this, we interviewed CC biology instructors (n = 20) about incorporating quantitative biology (QB) instruction into their classes. We used a purposeful sampling approach to recruit instructors who were likely to have tried evidence-based pedagogies and were likely aware of the importance of QB instruction. We used open coding to identify themes related to the affordances to and constraints on teaching QB. Overall, our study participants met with challenges typical of incorporating new material or techniques into any college-level class, including perceptions of student deficits, tension between time to teach quantitative skills and cover biology content, and gaps in teacher professional knowledge (e.g., content and pedagogical content knowledge). We analyze these challenges and offer potential solutions and recommendations for professional development to support QB instruction at CCs.
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