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ABSTRACT Motor skill expertise can facilitate more automatic movement, engaging less cortical activity while producing appropriate motor output. Accordingly, cortical-evoked N1 responses to balance perturbation, assessed using electroencephalography (EEG), are smaller in young and older adults with better balance. These responses may thus reflect individual balance challenge versus functional, or objective, task difficulty. However, the effect of balance expertise on cortical responses to balance perturbation has not been studied. We hypothesized that balance ability gained though long-term training facilitates more automatic balance control. Using professional modern dancers as balance experts, we compared cortical-evoked responses and biomechanics of the balance-correcting response between modern dancers and nondancers. We predicted that modern dancers would have smaller cortical-evoked responses and better balance recovery at equivalent levels of balance challenge. Support-surface perturbations were normalized to individual challenge levels by delivering perturbations scaled to 60% and 140% of each individual’s step threshold. In contrast to our prediction, dancers exhibited larger N1 responses compared to nondancers while demonstrating similar biomechanical responses. Our results suggest dancers have greater cortical sensitivity to balance perturbations than nondancers. Further, dancer N1 responses modulated across perturbation magnitudes according to differences in objective task difficulty. In contrast, nondancer N1 responses modulated as a function of individual challenge level. Our findings suggest dance training increases sensitivity of the initial, cortical N1 response to balance perturbation, supporting postural alignment to an objective reference. The N1 response may reflect differences in balance-error processing that are altered with specific long-term training and may have implications for rehabilitation. NEW & NOTEWORTHYModern dancers show larger cortical responses to balance perturbations than nondancers, suggesting a greater sensitivity to perturbations. These results contrast with evidence of larger cortical-evoked responses in young adults with poorer balance, consistent with the cortical N1 response being a balance error assessment signal. Whereas nondancers scaled cortical responses by individual differences in N1 amplitude, dancers’ cortical responses were scaled to objective differences in perturbation magnitude, suggesting increased postural awareness due to training. 

Student motivation within a STEM course is dependent on their perceived relevance and utility of the topics learned. This paper presents an Informative Utility Value Intervention (IUVI) designed to promote perceptions of utility. The IUVI was designed as a series of assignments for general chemistry students in large lecture courses, but the method can be adapted to other science disciplines. The intervention begins by establishing a baseline of students’ utility-value of chemistry then scaffolds new connections to their field of interest. The scaffold includes directing students to published articles demonstrating real-world connections between topics they are learning and their career interests. Student responses indicate they were able to make connections between the topic and their career interests and they perceived the articles as relevant to their career interests. 

Chemistry instruction should provide students a rationale for appreciating chemistry as a useful discipline, which is a particular challenge given the diverse student interests within introductory chemistry courses. In this study, we introduce and evaluate an interactive assignment, called an Informative Utility Value Intervention (IUVI), meant to improve students’ perceptions of the utility of chemistry. IUVI provides students with web-based articles describing how chemistry topics are relevant to the students’ chosen career interests. IUVI was administered to second-semester general chemistry students with a quasiexperimental study design in which one section from each instructor was given the intervention, and pre-intervention measures were used to account for potential differences between groups. The results indicate that students who received the intervention reported higher perceptions of the utility of chemistry at the end of the semester and higher scores on a common final exam than students who did not receive the intervention. Results from a structural equation model indicated the IUVI was associated with improved utility perceptions and final exam scores; however, these improvements were potentially independent of each other. Therefore, the theoretical explanation that improved perceptions of utility value resulted in improved academic performance could not be supported. Overall, IUVI offers an effective and highly portable intervention which can be adopted and adapted by instructors to promote students’ utility perceptions of chemistry. 

Electrostatic potential maps (EPM) have the potential to support organic chemistry students in seeing reaction mechanisms through the perspective of electrostatic attraction. Prior to any pedagogical changes, foundational knowledge on how students use EPMs in particular contexts would be needed to inform how to integrate EPMs into instruction. This study describes an exploration into how organic chemistry students use EPMs during two card sort tasks. Seventeen undergraduate organic chemistry students participated in an interview that included an open and closed card sort. The interviews were inductively coded to identify students’ usage of EPMs, and usage change based on the open sort compared to the closed sort. Viewed from a resources framework, this study demonstrated how students’ use of EPMs shifted depending on the task structure. Variations were observed both among students and within students between tasks in terms of whether EPMs were utilized and when utilized whether information from EPMs were used in isolation or integrated with other chemistry concepts. The results of this study imply that more formal integration of EPMs into instruction and assessment would be needed for students who did not use EPMs. Instruction that models and assesses translation of representations may begin activating a more integrated perspective of EPMs which could be productive for students who had an isolated use of EPMs. The introduction of EPMs independent of specific chemistry tasks (e.g.during a general introduction of molecular representations) could lead some students to focus only on explicit features of the EPM representation and not tie features of the representation to their existing chemical knowledge. 

Reaction mechanisms are a difficult and foundational topic students encounter in organic chemistry. Consequently, students often memorize when attempting to learn the array of organic reactions. While interventions have been offered to encourage mechanistic reasoning as an alternative approach, a deeper struggle pertaining to students’ comprehension of the underlying chemical principles driving reaction mechanisms is still prevalent. In this study, electrostatic potential maps (EPMs) were explored as a tool students could use to reason with some of these principles to predict and explain the outcomes of a reaction. Through semistructured interviews, 19 students’ sense-making strategies were recorded and analyzed to uncover how they used the features of EPMs with concealed atomic identities and how they reconciled their answers once the identities were made explicit. Analysis revealed that the absence of atomic identities generated approaches centered around electron densities and their utility in predicting reaction mechanisms and outcomes. As the atomic identities were revealed, the majority of participants reverted to memorized mechanisms, while six participants attempted to relate the atomic identities to the interactions of the electron densities. These findings suggest utility in implementing EPMs in the organic chemistry curriculum and offer a feasible intervention to promote sense-making when students reason with organic reactions. 

Identifying functionally important cell states and structure within heterogeneous tumors remains a significant biological and computational challenge. Current clustering or trajectory-based models are ill-equipped to address the notion that cancer cells reside along a phenotypic continuum. We present Archetypal Analysis network (AAnet), a neural network that learns archetypal states within a phenotypic continuum in single-cell data. Unlike traditional archetypal analysis, AAnet learns archetypes in simplex-shaped neural network latent space. Using pre-clinical models and clinical breast cancers, AAnet resolves distinct cell states and processes, including cell proliferation, hypoxia, metabolism and immune interactions. Primary tumor archetypes are recapitulated in matched liver, lung and lymph node metastases. Spatial transcriptomics reveal archetypal organization within the tumor, and, intra-archetypal mirroring between cancer and adjacent stromal cells. AAnet identifies GLUT3 within the hypoxic archetype that proves critical for tumor growth and metastasis. AAnet is a powerful tool, capturing complex, functional cell states from multimodal data.