SimBiotic Software (United States)

Abstract Rationale: Rhinoviruses (RV) are the most common respiratory pathogen responsible for exacerbations of COPD and asthma. The antigenic diversity of the ∼180 circulating RV subtypes has thus far been a barrier to the development of an effective cross-protective vaccine. Our aim is to develop a vaccine, that will overcome this historic limitation. In a set of preclinical studies we evaluate the effect of including a Th1-polarising adjuvant in a broadly protective RV candidate vaccine formulation. Methods: The immune response to vaccination with adjuvanted or non-adjuvanted APL-10456, a vaccine based upon the VP0 sequence from an RV-C strain and to subsequent heterotypic RV infection was characterised in a mouse model. Results: Vaccination with adjuvanted APL-10456 evoked a high titer, IgG2c-dominant, humoral response. Lower titers and IgG1 dominance were observed following vaccination with non-adjuvanted APL-10456. Importantly, antibodies generated by adjuvanted APL-10456 bound both VP0 and whole virions from heterotypic RV-subtypes. Splenocytes from mice immunized with adjuvanted APL-10456 stimulated with peptide pools corresponding to full-length VP0 from 19 different heterotypic isolates secreted IFN-γ, but not IL-5. Conversely, splenocytes from mice immunized with non-adjuvanted APL-10456 secreted IL-5, but not IFN-γ, following stimulation, indicating the important role of the adjuvant in skewing the immune response towards a Th1 pathway. Following challenge with heterotypic RV-A01 virus, analysis of BAL samples taken from vaccinated mice showed that neutrophilia was reduced in favour of a stronger lymphocyte response. Infection after vaccination was also associated with rapid expansion of RV-A, -B and -C reactive antigen-specific T-cells in respiratory tissues, together with enhanced production of neutralizing antibodies to the heterotypic infecting virus. The overall impact of vaccination was accelerated virus clearance from the lungs after infection. Conclusions: Adjuvanted APL-10456 generates a robust immune response, offering protection from heterotypic RV infection. This protection is likely mediated by generation of cross-strain humoral and cellular immunity, polarized towards Th1 by the selected adjuvant. These data support the progression of APL-10456 into clinical development to establish if a similar response is generated in humans and to determine if the raised antibodies neutralize exemplars from RV-A, -B and -C species.

Assessing the competence of learners with the concepts and skills being learned is necessary for improving teaching practices in an evidence-based way. However, assessing competence is especially challenging for complex tasks like constructing graphs.&nbsp;Performance-based assessments, where users perform the skills being assessed, can be an effective way to determine which skills users are competent and which they struggle and need more support. This article includes six isomorphic GraphSmarts performance-based assessments of graph construction competence, designed to be used in undergraduate biology classrooms. Each assessment uses a scenario and data set from a different topic across the biology curriculum, but they are otherwise parallel to each other. In addition to the performance-based aspect, questions in intermediate constraint formats measure some aspects of graphing competence. GraphSmarts assessments can be used singly or in pairs in a pre-post style to look for changes in graphing competence. This article includes the assessment instruments, rubrics for scoring, as well as html, code, and scripts for incorporation into online platforms. Using these assessments, either on paper or online, will provide instructors with student learning data to guide their teaching of graphing skills in ways that better suit their students&rsquo; needs. <em>Primary Image:</em> A graph created as part of one of the GraphSmarts Assessments. This graph contains some elements of a well-constructed graph (plotting relevant variables, axis conventions, scaling), and some elements that could use improvement (graph type, data aggregation, showing variability; inappropriate trend line).

Artificial intelligence models have been increasingly used in the analysis of tumor histology to perform tasks ranging from routine classification to identification of molecular features. These approaches distill cancer histologic images into high-level features, which are used in predictions, but understanding the biologic meaning of such features remains challenging. We present and validate a custom generative adversarial network-HistoXGAN-capable of reconstructing representative histology using feature vectors produced by common feature extractors. We evaluate HistoXGAN across 29 cancer subtypes and demonstrate that reconstructed images retain information regarding tumor grade, histologic subtype, and gene expression patterns. We leverage HistoXGAN to illustrate the underlying histologic features for deep learning models for actionable mutations, identify model reliance on histologic batch effect in predictions, and demonstrate accurate reconstruction of tumor histology from radiographic imaging for a "virtual biopsy."

Environmental justice and sustainability have both become major concerns for water resource management, particularly with recent federal emphasis on environmental justice under the Biden administration in the United States. Texas, like many U.S. states, lags behind the federal government in this emphasis. While many localities have made progress in some respects—for example, some major Texas municipalities have included equity and sustainability metrics in their recent climate action plans—others have not. This has left a patchwork of persistent water management and availability issues that are exacerbated by extreme weather and worsening impacts of climate change. We provide a review of many of Texas’s water equity and sustainability challenges, both now and in a more extreme climate future. These include water access, affordability, contamination, flooding, drought, and aging infrastructure. For example, many Texas counties rank highest in the nation for flood risk, including coastal counties with high populations of disadvantaged communities and counties containing populations that live in persistent poverty in the Lower Rio Grande Valley. Additionally, approximately 44,000 Texans, or about 0.4% of the state population, lack access to complete plumbing facilities in their homes. The costs of water infrastructure leaks (estimated at about 51 gallons of water per day statewide) are shared across customers of all income levels, though they place a disproportionate burden on low-income customers. We then assess existing statewide and local policy and planning efforts and gaps in addressing these concerns in Texas. We focus particularly on the role of efforts to incorporate community voice—the ideas, concerns, needs, and expertise of impacted community members, dismantle causes of injustice, and improve equity in spending. If communities are not intentional with future development, new water infrastructure could continue to perpetuate existing harms. Thus, we provide a research agenda and recommendations for addressing some of the policy and planning gaps and persistent environmental justice issues. We aim to help water managers and policy makers identify and dismantle sources of inequity, particularly through including community voice.

582 Background: Despite substantial advances in the understanding of breast cancer biology, the decision to use NACT for EBC is based on tumor size, lymph node status, and subtype. Even with aggressive therapy, the majority of women will not achieve a pathologic complete response (pCR). Investigational treatment regimens, including immunotherapy, can increase pCR rates, but are associated with irreversible immune-related toxicities. Being able to accurately predict pCR could identify candidates for intensification or de-escalation of NACT, allowing for personalized medicine. SimBioSys TumorScope (TS) is a biophysical model that utilizes baseline MRI, receptor status, and planned treatment regimen to simulate response to NACT over time. TS has demonstrated accurate prediction of pCR in prior studies. Here, we describe an independent external validation of TS. Methods: We conducted a retrospective study of University of Chicago patients (pts) who received NACT for EBC from Jan 2010 - March 2020. Pts must have had a pretreatment breast MRI. Tumors were analyzed using TS by investigators who were blinded to response data. TS predicted pCR was predefined as a residual tumor volume &lt; 0.01 cm3 or a 99.9% or greater reduction in tumor volume. Performance metrics of TS were calculated. Results: 144 tumors from 141 pts were analyzed. Average age was 52 yrs; 65% had stage II and 19% had stage III disease. Sensitivity and specificity of TS for predicting pCR were 90.4% and 92.4%, respectively. Of the 7 patients who were predicted to achieve a pCR but did not, 5 had a tumor cellularity &lt; 5%. With a median follow-up of 4.7 yrs, the 4-yr distant disease free survival (DDFS) was 100% for patients predicted to achieve pCR, versus 81.5% for those predicted to have residual disease. Results were generally robust for all subgroups analyzed (Table). Conclusions: TS accurately predicts pCR and DDFS from baseline MRI and clinicopathologic data. Given the high sensitivity and specificity of this assay across breast cancer subtypes, TS can be used to aid in escalation/de-escalation strategies for EBC.[Table: see text]

Graphing is an important practice for scientists and in K-16 science curricula. Graphs can be constructed using an array of software packages as well as by hand, with pen-and-paper. However, we have an incomplete understanding of how students’ graphing practice vary by graphing environment; differences could affect how best to teach and assess graphing. Here we explore the role of two graphing environments in students’ graphing practice. We studied 43 undergraduate biology students’ graphing practice using either pen-and-paper (PP) (n = 21 students) or a digital graphing tool GraphSmarts (GS) (n = 22 students). Participants’ graphs and verbal justifications were analyzed to identify features such as the variables plotted, number of graphs created, raw data versus summarized data plotted, and graph types (e.g., scatter plot, line graph, or bar graph) as well as participants’ reasoning for their graphing choices. Several aspects of participant graphs were similar regardless of graphing environment, including plotting raw vs. summarized data, graph type, and overall graph quality, while GS participants were more likely to plot the most relevant variables. In GS, participants could easily make more graphs than in PP and this may have helped some participants show latent features of their graphing practice. Those students using PP tended to focus more on ease of constructing the graph than GS. This study illuminates how the different characteristics of the graphing environment have implications for instruction and interpretation of assessments of student graphing practices.

The basis for understanding neurophysiology is understanding ion movement across cell membranes. Students in introductory courses recognize ion concentration gradients as a driving force for ion movement but struggle to simultaneously account for electrical charge gradients. We developed a 17-multiple-choice item assessment of students' understanding of electrochemical gradients and resistance in neurophysiology, the Electrochemical Gradients Assessment Device (EGAD). We investigated the internal evidence validity of the assessment by analyzing item characteristic curves of score probability and student ability for each question, and a Wright map of student scores and ability. We used linear mixed-effect regression to test student performance and ability. Our assessment discriminated students with average ability (weighted likelihood estimate: -2 to 1.5 Θ); however, it was not as effective at discriminating students at the highest ability (weighted likelihood estimate: >2 Θ). We determined the assessment could capture changes in both assessment scores (model r2 = 0.51, P < 0.001, n = 444) and ability estimates (model r2 = 0.47, P < 0.001, n = 444) after a simulation-based laboratory and course instruction for 222 students. Differential item function analysis determined that each item on the assessment performed equitably for all students, regardless of gender, race/ethnicity, or economic status. Overall, we found that men scored higher (r2 = 0.51, P = 0.014, n = 444) and had higher ability scores (P = 0.003) on the EGAD assessment. Caucasian students of both genders were positively correlated with score (r2 = 0.51, P < 0.001, n = 444) and ability (r2 = 0.47, P < 0.001, n = 444). Based on the evidence gathered through our analyses, the scores obtained from the EGAD can distinguish between levels of content knowledge on neurophysiology principles for students in introductory physiology courses.