The rapid shift from face-to-face to remote instruction in 2020 has resulted in recalibration of lecture and laboratory pedagogy. This research analyzed the impact of remote learning on student motivation and sense of belonging in large enrollment chemistry courses. Student responses were parsed according to specific demographics including gender, academic standing, first-generation status, and ethnicity. Research objectives included the analysis of how remote learning impacted specific demographics to develop guidelines for best practices moving forward for hybrid or online courses. Our findings show that second year students (sophomores) were the most impacted of the academic standing cohorts. Sophomores reported a statistically greater change in motivation after the start of the semester and statistically lower satisfaction with their performance on assignments. Females reported statistically lower motivation and a statistically lower sense of belonging in the course and science, technology, engineering, and mathematics (STEM) fields. Black/African students reported a statistically lower motivation for remote learning than Asian/Pacific Islander and White/Caucasian students. Finally, both White/Caucasian and Black/African students reported a statistically lower sense of belonging in the course and in STEM fields than Asian/Pacific islander students. Finally, statistical differences were not observed based upon first-generation status. The research indicates that students were differentially impacted by the shift to remote learning. From these findings, a stronger understanding of how specific demographics are differentially impacted by remote learning in STEM courses is provided, granting greater insight into best practices moving forward.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. Objective: We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. Methods: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. Results: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. Conclusions: Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.

Inflammatory breast cancer (IBC), an understudied and lethal breast cancer, is often misdiagnosed due to its unique presentation of diffuse tumor cell clusters in the skin and dermal lymphatics. Here, we describe a window chamber technique in combination with a novel transgenic mouse model that has red fluorescent lymphatics (ProxTom RFP Nu/Nu) to simulate IBC clinicopathological hallmarks. Various breast cancer cells stably transfected to express green or red fluorescent reporters were transplanted into mice bearing dorsal skinfold window chambers. Intravital fluorescence microscopy and the in vivo imaging system (IVIS) were used to serially quantify local tumor growth, motility, length density of lymph and blood vessels, and degree of tumor cell lymphatic invasion over 0–140 h. This short-term, longitudinal imaging time frame in studying transient or dynamic events of diffuse and collectively migrating tumor cells in the local environment and quantitative analysis of the tumor area, motility, and vessel characteristics can be expanded to investigate other cancer cell types exhibiting lymphovascular invasion, a key step in metastatic dissemination. It was found that these models were able to effectively track tumor cluster migration and dissemination, which is a hallmark of IBC clinically, and was recapitulated in these mouse models.

Complement is increasingly recognised as a driver and modulator of antitumour immunity, with context‐dependent effects across T cells, myeloid subsets, stromal elements and tumour cells. Although best known for pathogen clearance and membrane attack complex (MAC) formation, complement also acts intracellularly via the ‘complosome’ to regulate cellular homeostasis and gene expression. Complosome activity may dampen antitumour responses by rewiring single‐cell metabolism and transcription, altering nutrient flux and fostering an immunosuppressive microenvironment. Here, we synthesise advances in intracellular and extracellular complement, with emphasis on complement component 3 (C3) and receptors (C3aR1, C5aR1/CD88, C5aR2/C5L2), highlighting how these pathways shape T‐cell metabolism, exhaustion programmes and inflammatory tone within tumours. Evidence indicates that tonic C3/C5 signalling restrains cytotoxicity via C5aR1‐driven myeloid recruitment and cytokine cascades, while complosome signalling tunes T‐cell activation thresholds and bioenergetics. We outline considerations for selectively modulating intracellular versus extracellular complement, propose cell‐type‐resolved biomarker strategies and identify opportunities for complosome‐directed therapies in cancer, integrating roles across T cells, macrophages, B cells, neutrophils, NK cells, regulatory T cells, dendritic cells, myeloid‐derived suppressor cells and cancer‐associated fibroblasts. Key points: Intracellular complement (complosome) shapes the tumor immune microenvironment. Complosome's role in cancer is underrecognized yet central to tumor immunity. C3/C5‐driven complosome signals rewire T cell activation, fate, and metabolism. Complosome activity can promote pro‐tumor immune cell function. Blocking the complosome, alone or with checkpoint inhibitors, unveils a new tumor target.

BACKGROUND Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. OBJECTIVE We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. METHODS We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. RESULTS The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. CONCLUSIONS Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.