Yoxas/statistical_literacy huggingface dataset:
Biochemistry, being a vast and complex subject, can be challenging for Phase I MBBS students to comprehend and retain. Embracing rapidly evolving technology can facilitate a more accessible learning experience. In this study, we investigated the effectiveness of using Google Form-based multiple-choice question (MCQ) tests as a formative assessment tool after each biochemistry lecture series. The aim was to assess the improvement and gather feedback of Phase I MBBS students on the utility of this assessment tool. This educational prospective longitudinal study was conducted by the Department of Biochemistry at a university-affiliated medical college and tertiary care hospital. The study included 150 Phase I MBBS students as participants. Google Form-based MCQ tests were implemented as educational interventions after each lecture series during the study period. The study compared the internal assessment (IA) MCQ marks of students before and after the implementation of the intervention. In addition, feedback questionnaires were collected from the students. There was a significant improvement in students' scores between the first IA (mean ± standard deviation [SD], 8.16 ± 3.08) and second IA (mean ± SD, 17.64 ± 2.02) (P < 0.0001). According to students' feedback, 149 out of 150 (99.3%) students found the use of Google Form-based MCQ tests as a formative assessment tool in the teaching-learning process to be highly beneficial and motivated them to engage in their biochemistry studies. With the shift toward competency-based medical education (CBME) in India, it is crucial for educators to embrace novel teaching-learning and evaluation approaches. Our study highlighted the efficacy of employing Google Form-based MCQ tests in enhancing students' comprehension of the biochemistry subject, evaluating their scores and improving the overall quality of learning. Through this mode of assessment, teachers were able to provide targeted feedback on areas that required improvement, thereby enhancing the learning experience.
Bioelectricity is an interdisciplinary concept that encompasses the fields of chemistry, physics, and biology. It is the scientific study of membrane transport mechanisms that govern the formation and dissipation of ion gradients. Teaching and learning across disciplines, such as bioelectricity, are known among science teachers to be challenging and complex. One of the critical problems is that only a few teaching materials and learning resources specifically support interdisciplinary teaching, especially in science. This paper described the development of an improvised microbial fuel cell (iMFC) as an alternative activity that addresses scientific concepts of cellular respiration, reduction-oxidation reaction, and electricity generation in an interdisciplinary approach. In this activity, students designed, constructed, and tested their iMFCs. The learning gains of the students were measured using parallel pretest/post-test and analyzed using descriptive statistics and dependent t-tests. The perceptions of teachers and students on using the iMFC activity in teaching-learning bioelectricity were obtained from a survey questionnaire and interviews. Results revealed that the iMFC activity significantly improved students' learning gains in bioelectricity, for the topics cellular respiration (t(239)=45.03; P < 0.01), reduction-oxidation reaction (t(239)=39.85; P < 0.01), and electricity (t(239)=31.1; P < 0.01), with computed normalized gains of 0.45, 0.50, and 0.39, respectively. Furthermore, seven subthemes emerged from the teachers' and students' perceptions, namely, knowledge acquisition, student engagement, academic emotions, affordability, student satisfaction, distractions, and cleanliness. Overall results indicated that the iMFC activity can be an effective teaching material for providing an authentic learning experience in a multidisciplinary topic like bioelectricity. Future investigations on the iMFC activity and its impact on other aspects of learning, such as students' motivation, self-efficacy, and engagement, are recommended.
Biologic treatments can alleviate severe asthma symptoms and reduce health service use. However, service capacity limits and low referral rates from primary care indicate unmet patient need. We report a mixed-methods evaluation of an enhanced severe asthma pathway implemented in Staffordshire and Stoke-on-Trent, UK which aimed to optimise primary care referrals through training/education, and increased capacity in specialist clinics. Quantitative analysis assessed patient wait times between pathway stages, prescribing changes, exacerbations, hospital admissions and asthma control. Interviews with 12 stakeholders evaluated perceptions of the enhanced pathway across settings. In 12 months, 564 patients from 28 general practices were reviewed for biologics eligibility, of whom 125 (22.2%) were referred for specialist assessment. Wait times were significantly lower under the enhanced pathway when compared against historic patients following the standard pathway, and reduced overall from a mean of 76.4 to 26.7 weeks between referral and biologics initiation (p < 0.001). Patients commencing biologics (n = 46) showed significantly reduced reliever inhaler prescribing rates (p = 0.037), 60% lower oral steroid use (p < 0.001), significantly reduced exacerbation rates (p < 0.001) and fewer hospital admissions (p < 0.001) compared with the 12 months pre-treatment. Mean asthma control scores reduced from 3.13 pre-initiation to 1.89 post-initiation (p < 0.001) - a clinically significant improvement. Interviewees viewed the enhanced pathway positively, although ongoing issues related to difficulties engaging primary care amid concerns around increased workloads and pathway capacity. The large number of referrals generated from a comparatively small number of general practices confirms substantial unmet need that an enhanced severe asthma pathway could help address if implemented routinely.
Biological function depends on the composition and structure of the organism, the latter describing the organization of interactions between parts. While cells in multicellular organisms are capable of a remarkable degree of autonomy, most functions do require cell communication: the coordination of functions (growth, differentiation, and apoptosis), the compartmentalization of cellular processes, and the integration of cells into higher levels of structural organization. A wealth of data on putative cell interactions has become available, yet its biological interpretation depends on our expectations about the structure of interaction networks. Here, we attempt to formulate basic questions to ask when interpreting cell interaction data. We build on the understanding that cells fulfill two general functions: the integrity-maintaining and the organismal service function. We derive the expected patterns of cell interactions considering two intertwined aspects: the functional and the evolutionary. Based on these, we propose guidelines for analysis and interpretation of transcriptional cell-interactome data.
Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.
Biological maturity and relative age player selection biases are well documented in youth sports. However, there has been limited examination of the relationship between these biases. This study investigated the presence, strength, and independence of relative age and biological maturity selection biases in Gaelic football. A total of 247 male players from U14 to U16, from two talent academies were assessed for relative age (decimal age (DA)) and biological maturity (discrepancy between biological and chronological age (BA-CA)). Relative age effects (RAE) were observed in the U14 (DA = 0.62, d = 0.40) and U15 squads (DA = 0.57. d = 0.26) only. A bias towards advanced maturity status was present at U14 (BA-CA = 0.60, d = 0.83), U15 (BA-CA = 0.78, d = 0.89), and U16 (BA-CA, d = 1.01). There was a trivial (U14, r(83) = -0.210; U15, r(88) = 0.060) and low (U16, r(76) = 0.352) correlation between relative age and maturity status. Substantial maturity selection biases and, to a lesser degree, relative age biases are evident in youth Gaelic football. Critically, these biases are independent constructs. Coaches and policy makers should be educated on the distinct influences of relative age and maturation, and on strategies to address these biases.
Biological products have contributed to extraordinary advances in disease treatments over the last decade. However, the cost-saving potential of imitator products, so-called biosimilars, is still under-researched in Switzerland. This study aims to assess biosimilars' prescriptions at treatment initiation and their determinants, as well as biological therapy switches. The study included all patients who had at least one biosimilar available on the market at the time when they were prescribed a biological product. We analysed longitudinal data for biosimilar prescriptions in Switzerland using descriptive statistics and logistic regression to quantify the associations with individual, pharmaceutical and provider-related variables. The analysis is based on de-identified claims data of patients with mandatory health insurance at Helsana, one of the Swiss health insurance companies with a substantial enrollee base in mandatory health insurance. Overall, 18 953 patients receiving at least one biological product between 2016 and 2021 were identified. We differentiated between initial prescriptions and follow-up prescriptions. Our regression focused on initial prescriptions due to evidence indicating that patients tend to follow the medication prescribed at therapy initiation. Although biosimilars' market share was low (28.6%), the number of prescriptions has increased (from 1016 in 2016 to 6976 in 2021). Few patients with medication switches (n=1492, 8.5%) were detected. Increased relative price difference (difference in the price of available biosimilars relative to price of corresponding reference product) was associated with decreased probability of biosimilar prescriptions, whereas male sex, an increase of available imitator drugs on the market, larger packaging sizes, and prescriptions from specialists or physicians in outpatient settings were associated with increased biosimilar use. The low number of biosimilar prescriptions, despite the proliferating biosimilar market, indicates a high potential for biosimilar diffusion. The findings indicate that patients typically adhere to the therapy options initially chosen and are less inclined to make changes following the initiation of treatment. Our research highlights the need for awareness initiatives to improve understanding among patients and physicians, enabling informed, shared decision-making about biosimilar prescriptions.
Biologics and Janus kinase (JAK) inhibitors are immunomodulating and immunosuppressing medications utilized to treat atopic dermatitis (AD), psoriasis (PSO), psoriatic arthritis (PsA), and alopecia areata (AA). Special recommendations must be considered when prescribing vaccinations in this population, as the pneumococcal and herpes zoster vaccine are recommended to patients ≥ 19-years-old (rather than ≥ 65-years-old and ≥ 50-years-old as in the general population, respectively), along with a yearly influenza and up to date COVID-19 vaccination. Additionally, TNF-α and JAK-inhibitors may increase the risk of latent Hepatitis B virus (HBV) reactivation among high-risk patients. Prior to prescribing these medications, a quantitative HepB Surface Antibody (HepB SA) test is performed to determine immunity. This study utilized the SlicerDicer function on EPIC Medical Records to search for any patient ≥ 19-years-old prescribed a biologic or JAK inhibitor for AD, PSO, PsA, or AA between 10/2003 and 10/2023 at a large tertiary institution. Vaccination rates among patients on biologics and JAK inhibitors were low, with rates being significantly lower in patients 19-64 years-old, compared to those ≥ 65 years-old for most disease states (p < 0.01). Among AD, PSO/PsA, and AA patients, on average, 9.39% were vaccinated for influenza, 6.76% for herpes zoster, 16.56% for pneumococcal pneumonia, and 63.98% for COVID-19. Only 3.16% of patients were adequately vaccinated for HepB after an abnormal HepB SA test. Here, extremely low rates of vaccination among patients on biologics and JAK inhibitors at our institution were highlighted, emphasizing the imperative need for ensuring vaccination in this group.
Biology is an increasingly quantitative science. Thus, it is important that undergraduate biology curricula include frequent opportunities for students to practice their quantitative skills. This can create a substantial grading burden for faculty teaching online and/or large enrollment courses, but the "formula question" feature present in many learning management systems (LMS) offers a solution. Using this feature, faculty set up a basic scaffold for an algebraic word problem, and the LMS can then automatically generate and grade many different versions of the question. In this paper, we describe the use of "formula questions" in an undergraduate microbiology course and specifically focus on how the strategic use of algebraic word problems at multiple points throughout the semester can help build quantitative literacy. Key to the success of this approach is that faculty provide a review of foundational mathematical skills early in the semester, even in upper-level classes. This should include reacquainting students with formatting conventions (e.g., rounding and scientific notation), familiarizing them with any idiosyncrasies of the technology platforms, and demonstrating how to solve math problems using spreadsheets. This initial effort increases student success when more complex problems are introduced later in the semester. Though the tips summarized in this paper focus on undergraduate microbiology teaching laboratories using Canvas, the approach can easily be modified to help students develop their critical thinking and quantitative reasoning skills at other levels and in other disciplines.
Biology laboratory classes are designed to teach concepts and techniques through experiential learning. Students who have never performed a technique must be guided through the process, which is often difficult to standardize across multiple lab sections. Visual demonstration of laboratory procedures is a key element in teaching pedagogy. The main goals of the study were to create videos explaining and demonstrating a variety of lab techniques that would serve as teaching tools for undergraduate and graduate lab courses and to assess the impact of these videos on student learning. Demonstrations of individual laboratory procedures were videotaped and then edited with iMovie. Narration for the videos was edited with Audacity. Undergraduate students were surveyed anonymously prior to and following screening to assess the impact of the videos on student lab performance by completion of two Participant Perception Indicator surveys. A total of 203 and 171 students completed the pre- and posttesting surveys, respectively. Statistical analyses were performed to compare student perceptions of knowledge of, confidence in, and experience with the lab techniques before and after viewing the videos. Eleven demonstrations were recorded. Chi-square analysis revealed a significant increase in the number of students reporting increased knowledge of, confidence in, and experience with the lab techniques after viewing the videos. Incorporation of instructional videos as prelaboratory exercises has the potential to standardize techniques and to promote successful experimental outcomes.
Biology laboratory instructors play a key role in creating an optimal environment where college students try hard and enjoy their classroom experiences. This study used achievement goal perspective theory to examine the influence of instructor behaviors on science, technology, engineering, and mathematics (STEM) students' perceptions of the motivational climate (caring, task, ego) and their adaptive (i.e., effort, enjoyment, performance self-esteem, and social self-esteem) and maladaptive (i.e., shame) experiences in the biology laboratory setting. Students (N = 563; women, 65%; men, 35%) enrolled in biology laboratory courses voluntarily completed a survey during the final week of the semester. Results of two structural equation modeling analyses across gender and racial identities made two important contributions to the STEM higher education literature: 1) when instructors engaged in effective teaching behaviors, students were more likely to perceive a caring/task-involving climate and, in turn, report adaptive motivational responses (i.e., increased effort, enjoyment, self-esteem; decreased shame); and 2) neither gender nor race moderated the measurement of the latent parameters. This research has important pedagogical implications, as teaching assistants could be trained to engage in these effective behaviors to optimize students' STEM learning experiences.
Biology of the twenty-first century is an increasingly quantitative science. Undergraduate biology education therefore needs to provide opportunities for students to develop fluency in the tools and language of quantitative disciplines. Quantitative literacy (QL) is important for future scientists as well as for citizens, who need to interpret numeric information and data-based claims regarding nearly every aspect of daily life. To address the need for QL in biology education, we incorporated quantitative concepts throughout a semester-long introductory biology course at a large research university. Early in the course, we assessed the quantitative skills that students bring to the introductory biology classroom and found that students had difficulties in performing simple calculations, representing data graphically, and articulating data-driven arguments. In response to students' learning needs, we infused the course with quantitative concepts aligned with the existing course content and learning objectives. The effectiveness of this approach is demonstrated by significant improvement in the quality of students' graphical representations of biological data. Infusing QL in introductory biology presents challenges. Our study, however, supports the conclusion that it is feasible in the context of an existing course, consistent with the goals of college biology education, and promotes students' development of important quantitative skills.
Biomechanical analysis of human movement plays an essential role in understanding functional changes in people with Amyotrophic Lateral Sclerosis (ALS), providing information on muscle impairment. Studies suggest that surface electromyography (sEMG) may be able to quantify muscle activity, identify levels of fatigue, assess muscle strength, and monitor variation in limb movement. In this article, a systematic review protocol will analyze the psychometric properties of the sEMG regarding the clinical data on the skeletal muscles of people with ALS. This protocol uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological tool. A specific field structure was defined to reach each phase. Nine scientific databases (PubMed, Web of Science, Embase, Elsevier, IEEE, Google Scholar, SciELO, PEDro, LILACS E CENTRAL) were searched. The framework developed will extract data (i.e. study information, sample information, sEMG information, intervention, and outcomes) from the selected studies using a rigorous approach. The data will be described quantitatively using frequency and trend analysis methods, and heterogeneity between the included studies will be assessed using the I2 test. The risk of bias will be summarized using the most recent prediction model risk of bias assessment tool. Be sure to include relevant statistics here, such as sample sizes, response rates, P values or Confidence Intervals. Be specific (by stating the value) rather than general (eg, "there were differences between the groups"). This protocol will map out the construction of a systematic review that will identify and synthesize the advances in movement analysis of people with ALS through sEMG, using data extracted from articles.
Biometric monitoring technologies (BioMeTs) are becoming increasingly common to aid data collection in clinical trials and practice. The state of BioMeTs, and associated digitally measured biomarkers, is highly reminiscent of the field of laboratory biomarkers 2 decades ago. In this review, we have summarized and leveraged historical perspectives, and lessons learned from laboratory biomarkers as they apply to BioMeTs. Both categories share common features, including goals and roles in biomedical research, definitions, and many elements of the biomarker qualification framework. They can also be classified based on the underlying technology, each with distinct features and performance characteristics, which require bench and human experimentation testing phases. In contrast to laboratory biomarkers, digitally measured biomarkers require prospective data collection for purposes of analytical validation in human subjects, lack well-established and widely accepted performance characteristics, require human factor testing, and, for many applications, access to raw (sample-level) data. Novel methods to handle large volumes of data, as well as security and data rights requirements add to the complexity of this emerging field. Our review highlights the need for a common framework with appropriate vocabulary and standardized approaches to evaluate digitally measured biomarkers, including defining performance characteristics and acceptance criteria. Additionally, the need for human factor testing drives early patient engagement during technology development. Finally, use of BioMeTs requires a relatively high degree of technology literacy among both study participants and healthcare professionals. Transparency of data generation and the need for novel analytical and statistical tools creates opportunities for precompetitive collaborations.