How interactive workshops shape women and non-binary students’ sense of belonging in physics

SENSE OF BELONGING IS A PREDICTOR OF RETENTION IN STEM MAJORS Researchers have identified students’ sense of belonging as an important factor in whether or not they persist in STEM majors (Rainey et al., 2018), yet women can report lower senses of belonging than men in their classes (Lewis et al., 2016). A MIXED-METHOD STUDY OF STUDENTS’ RETENTION IN PHYSICS At Monash University, we have begun a longitudinal, mixed-methods study of students’ experience in physics and astrophysics major units. In semester 1, 2023, students in our first-semester unit in the physics major sequence completed pre and post surveys addressing sense of belonging alongside other measures linked to retention (including physics identity, self-efficacy, and demographic factors). Among students responding to the first survey, 23.2% identified as women, 72.1% as men, and 4.7% as non-binary and other gender identities (response rate was 79% of enrolled students, students could identify as more than one gender and did not have to select a gender). 16 students participated in two interviews, one near the beginning of the semester and one near the end. Of these, eleven did not identify as men, including seven who identified as women and four who identified as non-binary or genderfluid. In the second interview, participants were asked about their sense of belonging in the interactive physics workshops and labs. WOMEN AND NON-BINARY STUDENTS REPORT WORKING WITH OTHER NON-MALE STUDENTS IS ASSOCIATED WITH FEELINGS OF BELONGING In interviews, most women and non-binary students reported they felt like they belonged and were welcomed by their peers. Furthermore, most described opting to sit at tables with mostly other women and non-binary people when the choice was available. Multiple students cited greater comfort in sharing their ideas and expressing uncertainty when in discussion with other “non-men.” This was true both among students who attended all-girls high schools and those who attended co-educational high schools. At the time of abstract submission, survey analysis was ongoing. INTERACTIVE SETTINGS WHERE STUDENTS SELF-SELECT GROUPS MAY SUPPORT WOMEN AND NON-BINARY STUDENTS’ BELONGING IN PHYSICS The streams of this unit were large enough (70-100 students each) that there were substantial numbers of women and at least two non-binary students in all sections. These initial results suggest that interactive instructional settings where students can self-select their groups may support sense of belonging among gender minorities in physics, including women and non-binary people. REFERENCES Lewis, K. L., Stout, J. G., Pollock, S. J., Finkelstein, N. D., & Ito, T. A. (2016). Fitting in or opting out: A review of key social-psychological factors influencing a sense of belonging for women in physics. Physical Review Physics Education Research, 12(2), 020110. Rainey, K., Dancy, M., Mickelson, R., Stearns, E., & Moller, S. (2018). Race and gender differences in how sense of belonging influences decisions to major in STEM. International Journal of STEM Education, 5, 1-14

Integrating computation through first- and second-year physics major units

COMPUTATION AS A TARGET FOR PHYSICS INSTRUCTION Computation is increasingly recognized as a core aspect of physics practice and target for physics instruction. Literature on computation in physics often focuses on separate computational physics units or courses (see Atherton, 2023, for a review) rather than integrating computation throughout curricula. We document the process of integrating computation in the context of first- and second-year physics units at Monash University to provide a model for embedding computation throughout a three-year Australian Bachelor of Science in physics. GOALS FOR COMPUTATIONAL PHYSICS INSTRUCTION AT MONASH Naturally, computational physics instruction aims to develop a solid foundation of the coding skills that students will require in their careers and to develop literacy with a chosen language. However, we set out more importantly and broadly, to develop the skills needed to break down a task into its separate steps and develop an algorithm (free of syntax) and to develop student’s ability to create interactive visualisations and models, in order to augment their understanding of various physical phenomena. This approach enhances engagement by showcasing the benefits of computational approaches and augments learning through linking interesting phenomena and the coding process. IMPLEMENTATION OF COMPUTATIONAL ACTIVITIES IN APPLIED AND LABORATORY ACTIVITIES Our vertical integration of computational skills begins in first year, where primarily we focus on developing coding skills in support of laboratory data analysis. Here, the activities begin with a basic introduction to coding in the chosen language (originally the Wolfram Language in Mathematica, and currently Python) tailored to lab analysis (plotting, fitting, error analysis). Subsequent tasks build upon this, supported by a mix of examples and exercises that ask students to follow along, modify previously used code, or fill in gaps in templates for each laboratory they complete. This approach is followed in second year with the applications broadened tremendously into fortnightly sessions that serve to create fully interactive demonstrations/visualisations of the physics discussed in other aspects of the unit. These include creating time evolutions of wavefunctions for the common quantum tunnelling problems, visualizations of random walks, manipulable ray traces, and much more. Through this, students not only learn a variety of coding techniques and principles but see very interesting and often hard to imagine aspects of physics come to life through their code! EVALUATING THE SUCCESS OF COMPUTATIONAL INSTRUCTION We assess our success in achieving both computational and physics learning outcomes, as well as enhance engagement, based on feedback provided annually by students in their evaluations of teaching units, on its follow through in higher year level units, and on the difference in achievement in the unit as a whole for years/students where computational applied sessions have been attended, in comparison to those cases where applied sessions were not offered or not attended. REFERENCE Atherton, T. J. (2023). Resource Letter CP-3: Computational physics. American Journal of Physics, 91(1), 7-27

Modelling the Evolution and Spread of HIV Immune Escape Mutants

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

Present state and future perspectives of using pluripotent stem cells in toxicology research

The use of novel drugs and chemicals requires reliable data on their potential toxic effects on humans. Current test systems are mainly based on animals or in vitro–cultured animal-derived cells and do not or not sufficiently mirror the situation in humans. Therefore, in vitro models based on human pluripotent stem cells (hPSCs) have become an attractive alternative. The article summarizes the characteristics of pluripotent stem cells, including embryonic carcinoma and embryonic germ cells, and discusses the potential of pluripotent stem cells for safety pharmacology and toxicology. Special attention is directed to the potential application of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) for the assessment of developmental toxicology as well as cardio- and hepatotoxicology. With respect to embryotoxicology, recent achievements of the embryonic stem cell test (EST) are described and current limitations as well as prospects of embryotoxicity studies using pluripotent stem cells are discussed. Furthermore, recent efforts to establish hPSC-based cell models for testing cardio- and hepatotoxicity are presented. In this context, methods for differentiation and selection of cardiac and hepatic cells from hPSCs are summarized, requirements and implications with respect to the use of these cells in safety pharmacology and toxicology are presented, and future challenges and perspectives of using hPSCs are discussed

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A prospective examination of sex differences in posttraumatic autonomic functioning.

Background: Cross-sectional studies have found that individuals with posttraumatic stress disorder (PTSD) exhibit deficits in autonomic functioning. While PTSD rates are twice as high in women compared to men, sex differences in autonomic functioning are relatively unknown among trauma-exposed populations. The current study used a prospective design to examine sex differences in posttraumatic autonomic functioning. Methods: 192 participants were recruited from emergency departments following trauma exposure ( Results: 2-week systolic BP was significantly higher in men, while 2-week HR was significantly higher in women, and a sex by PTSD interaction suggested that women who developed PTSD demonstrated the highest HR levels. Two-week HF-HRV was significantly lower in women, and a sex by PTSD interaction suggested that women with PTSD demonstrated the lowest HF-HRV levels. Skin conductance response in the emergency department was associated with 2-week HR and HF-HRV only among women who developed PTSD. Conclusions: Our results indicate that there are notable sex differences in autonomic functioning among trauma-exposed individuals. Differences in sympathetic biomarkers (BP and HR) may have implications for cardiovascular disease risk given that sympathetic arousal is a mechanism implicated in this risk among PTSD populations. Future research examining differential pathways between PTSD and cardiovascular risk among men versus women is warranted

Genetically Predicted Body Mass Index and Breast Cancer Risk : Mendelian Randomization Analyses of Data from 145,000 Women of European Descent

Background Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m(2) increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 x 10(-10)). The associations were similar for both premenopausal (OR = 0.44, 95% CI: 0.31-0.62, p = 9.91x10(-8)) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88x10(-8)). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 x 10(-7)). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p <0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. Conclusions BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.Peer reviewe