Group work in science, technology, engineering, and mathematics courses is an effective means of improving student outcomes, and many different factors can influence the dynamics of student discussions and, ultimately, the success of collaboration. The substance and dynamics of group discussions are commonly examined using qualitative methods such as discourse analysis. To complement existing work in the literature, we developed a quantitative methodology that uses graph theory to map the progression of talk-turns of discussions within a group. We observed groups of students working with peer facilitators to solve problems in biological sciences, with three iterations of data collection and two major refinements of graph theory calculations. Results include general behaviors based on the turns in which different individuals talk and graph theory parameters to quantify group characteristics. To demonstrate the potential utility of the methodology, we present case studies with distinct patterns: a centralized group in which the peer facilitator behaves like an authority figure, a decentralized group in which most students talk their fair share of turns, and a larger group with subgroups that have implications for equity, diversity, and inclusion. Together, these results demonstrate that our adaptation of graph theory is a viable quantitative methodology to examine group discussions.

Learning assistant (LA) programs train undergraduate students to foster peer discussion and facilitate active-learning activities in undergraduate science, technology, engineering, and mathematics (STEM) classes. Students who take courses that are supported by LAs demonstrate better conceptual understanding, lower failure rates, and higher satisfaction with the course. There is less work, however, on the impact that participating in LA programs has on the LAs themselves. The current study implements a pretest-posttest design to assess changes in LAs' metacognition and motivation to succeed in STEM across their first and second quarters as an LA. Our findings suggest that participating in this program may help LAs become more reflective learners, as was demonstrated by an increase in their scores on the Metacognitive Awareness Inventory (MAI) after the first quarter. LAs also showed increases on the Intrinsic Motivation and Self-Efficacy subscales of the Science Motivation Questionnaire. Students who participated in the program for an additional quarter continued to show increases in their MAI scores and maintained the gains that were observed in their motivation. Taken together, this work suggests that, in addition to benefiting the learner, LA programs may have positive impacts on the LAs themselves.

Introduction

Women are under-represented in the surgical disciplines and gender bias is believed to play a factor. We aimed to understand the gender distribution of membership, leadership opportunities, and scientific contributions to annual trauma professional meetings as a case study of gender issues in trauma surgery.

Methods

Retrospective collection of membership, leadership, presentation and publication data from 2016 to 2018 Trauma/Acute Care Surgery/Surgical Critical Care (TACSCC) Annual Meetings. Gender was assigned based on self-identification in demographic information, established relationships, or public sources.

Results

Women remain under-represented with only 28.1% of those ascertaining American Board of Surgery certification in critical care self-identifying as female. The proportion of female members in Eastern Association for the Surgery of Trauma (EAST) was comparable (29.4%), slightly lower for Western Trauma Association (WTA) (19.0%), and lowest for American Association for the Surgery of Trauma (AAST) (12.8%, p<0.05). In contrast, AAST had the highest proportion of female participants in executive leadership (AAST 32.5%, WTA 19.0%, EAST 18.8%) and WTA the highest for committee chairs (WTA 33.3%, AAST 27.8%, EAST 20.5%). AAST had the most significant increase in executive leadership during the last 3 years (AAST 28.6% to 41.6%). Invited lectureships, masters, panelists and senior author scientific contributions demonstrated the largest gap of academic representation of female TACSCC surgeons.

Conclusion

Fewer women than men pursue careers in the trauma field. Continuing to provide mentorship, leadership, and scientific recognition will increase gender diversity in TACSCC. We must continue to promote, sponsor, recognize, invite, and elect 'her'.

Level of evidence

III, Epidemiology.

Calculus is typically one of the first college courses encountered by science, technology, engineering, and mathematics (STEM) majors. Calculus often presents major challenges affecting STEM student persistence, particularly for students from groups historically underrepresented in STEM. For life sciences majors, calculus courses may not offer content that is relevant to biological systems or connect with students' interests in biology. We developed a transformative approach to teaching college-level math, using a dynamical systems perspective that focuses first on demonstrating why students need math to understand living systems, followed by providing quantitative and computational skills, including concepts from calculus, that students need to build and analyze mathematical models representing these systems. We found that students who complete these new math courses perform better in subsequent science courses than their counterparts who take traditional calculus courses. We also provide evidence that the new math curriculum positively impacts students' academic performance, with data that show narrowing of the achievement gap, based on students' math grades, between student subgroups in the new math courses. Moreover, our results indicate that students' interest in the concepts and skills critical to the quantitative preparation of 21st-century life sciences majors increases after completing the new contextualized math curriculum.

Patient-reported outcomes (PROs) capture subjective social determinants of health (SDOHs), which can affect health outcomes through the stress response pathway. The conserved transcriptional response to adversity (CTRA) is a stress-mediated proinflammatory transcriptomic pattern that has been linked to adverse hematopoietic cell transplant (HCT) outcomes. This study examined the association of pretransplant CTRA with patient-reported SDOHs in allogeneic HCT recipients. In this cross-sectional study, pre-HCT SDOH-related PROs included the 36-Item Short Form Health Survey and the Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT). CTRA was assessed by RNA sequencing of whole blood specimens, with mixed effects linear regression models relating CTRA expression to PRO scores while controlling for age, sex, race, disease, and performance status. Among 121 patients, the median age was 54 years, 42% were female, and 91% were White. CTRA was elevated in participants reporting lower scores on the FACT-BMT (P = .003), including the general (P = .003) and BMT-specific (P = .014) components. Effects were driven by the social well-being domain (P = .0001). This corresponded to an 8% to 15% difference in CTRA RNA expression across a 4 standard deviation range in patient-reported SDOHs. Ancillary bioinformatics analyses confirmed the association of well-being with reduced proinflammatory transcription pathway activity [cyclic AMP response element-binding protein, (CREB), NF-κB, and activating protein-1 (AP-1)]. In conclusion, HCT-treated patients who experience unfavorable social conditions show elevated CTRA expression in pretransplant blood samples. These data highlight the biologic sequelae of social well-being and community context and suggest a potential molecular mechanism for the impact of social gradients in HCT outcomes. Targeting this pathway could optimize outcomes in this high-risk population.

Because medical illness is associated with increased inflammation and an increased risk for treatment-resistant major depressive disorder, anti-cytokine therapy may represent a novel, and especially efficacious, treatment for depression. We hypothesized that blockade of the interleukin (IL)-6 signaling pathway with tocilizumab would decrease depression and related symptomatology in a longitudinal cohort of allogeneic hematopoietic stem cell transplantation (HCT) patients, a medically ill population with a significant inflammation and psychopathology. Patients undergoing allogeneic HCT received either a single dose of tocilizumab one day prior to HCT (n = 25), or HCT alone (n = 62). The primary outcome included depressive symptoms at 28 days post HCT; anxiety, fatigue, sleep, and pain were assessed at pretreatment baseline and days +28, +100, and +180 post HCT as secondary outcomes. Multivariate regression demonstrated that preemptive treatment with tocilizumab was associated with significantly higher depression scores at D28 vs. the comparison group (β = 5.74; 95% CI 0.75, 10.73; P = 0.03). Even after adjustment for baseline depressive symptoms, propensity score, and presence of acute graft-versus-host disease (grades II-IV) and other baseline covariates, the tocilizumab-exposed group continued to have significantly higher depression scores compared to the nonexposed group at D28 (β = 4.73; 95% CI 0.64, 8.81; P = 0.02). Despite evidence that IL-6 antagonism would be beneficial, blockade of the IL-6 receptor with tocilizumab among medically ill patients resulted in significantly more-not less-depressive symptoms.

Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (∼5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization.

Racial/ethnic minorities have demonstrated worse survival after allogeneic hematopoietic cell transplantation (HCT) compared to whites. Whether the racial disparity in HCT outcomes persists in long-term survivors and possibly may be even exacerbated in this population, which frequently transitions back from the transplant center to their local healthcare providers, is unknown. In the current study, we compared long-term outcomes among 1-year allogeneic HCT survivors by race/ethnicity and socioeconomic status (SES). The Center for International Blood and Marrow Transplant Research database was used to identify 5473 patients with acute myeloid leukemia, acute lymphocytic leukemia, chronic myeloid leukemia, or myelodysplastic syndromes who underwent their first allogeneic HCT between 2007 and 2017 and were alive and in remission for at least 1 year after transplantation. The study was restricted to patients who underwent HCT in the United States. SES was defined using patient neighborhood poverty level estimated from the recipients ZIP code of residence; a ZIP code with ≥20% of persons below the federal poverty level was considered a high poverty area. The primary outcome was to evaluate the associations of race/ethnicity and neighborhood poverty level with overall survival (OS), relapse, and nonrelapse mortality (NRM). Cox regression models were used to determine associations of ethnicity/race and SES with OS, relapse, and NRM. Standardized mortality ratios were calculated to compare mortality rates of the study patients and their general population peers matched on race/ethnicity, age, and sex. The study cohort was predominately non-Hispanic white (n = 4385) and also included non-Hispanic black (n = 338), Hispanic (n = 516), and Asian (n = 234) patients. Overall, 729 patients (13%) resided in high-poverty areas. Significantly larger proportions of non-Hispanic black (37%) and Hispanic (26%) patients lived in high-poverty areas compared to non-Hispanic whites (10%) and Asians (10%) (P < .01). Multivariable analysis revealed no significant associations between OS, PFS, relapse, or NRM and race/ethnicity or poverty level when adjusted for patient-, disease- and transplantation-related covariates. Our retrospective cohort registry study shows that among adult allogeneic HCT recipients who survived at least 1 year in remission, there were no associations between race/ethnicity, neighborhood poverty level, and long-term outcomes.

There has been an increase in volume as well as an improvement in overall survival (OS) after hematopoietic cell transplantation (HCT) for hematologic disorders. It is unknown if these changes have affected racial/ethnic minorities equally. In this observational study from the Center for International Blood and Marrow Transplant Research of 79 904 autologous (auto) and 65 662 allogeneic (allo) HCTs, we examined the volume and rates of change of autoHCT and alloHCT over time and trends in OS in 4 racial/ethnic groups: non-Hispanic Whites (NHWs), non-Hispanic African Americans (NHAAs), and Hispanics across 5 2-year cohorts from 2009 to 2018. Rates of change were compared using Poisson model. Adjusted and unadjusted Cox proportional hazards models examined trends in mortality in the 4 racial/ethnic groups over 5 study time periods. The rates of increase in volume were significantly higher for Hispanics and NHAAs vs NHW for both autoHCT and alloHCT. Adjusted overall mortality after autoHCT was comparable across all racial/ethnic groups. NHAA adults (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.04-1.22; P = .004) and pediatric patients (HR 1.62; 95% CI 1.3-2.03; P < .001) had a higher risk of mortality after alloHCT than NHWs. Improvement in OS over time was seen in all 4 groups after both autoHCT and alloHCT. Our study shows the rate of change for the use of autoHCT and alloHCT is higher in NHAAs and Hispanics than in NHWs. Survival after autoHCT and alloHCT improved over time; however, NHAAs have worse OS after alloHCT, which has persisted. Continued efforts are needed to mitigate disparities for patients requiring alloHCT.