MultiSero: An Open-Source Multiplex-ELISA Platform for Measuring Antibody Responses to Infection.

A multiplexed enzyme-linked immunosorbent assay (ELISA) that simultaneously measures antibody binding to multiple antigens can extend the impact of serosurveillance studies, particularly if the assay approaches the simplicity, robustness, and accuracy of a conventional single-antigen ELISA. Here, we report on the development of multiSero, an open-source multiplex ELISA platform for measuring antibody responses to viral infection. Our assay consists of three parts: (1) an ELISA against an array of proteins in a 96-well format; (2) automated imaging of each well of the ELISA array using an open-source plate reader; and (3) automated measurement of optical densities for each protein within the array using an open-source analysis pipeline. We validated the platform by comparing antibody binding to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antigens in 217 human sera samples, showing high sensitivity (0.978), specificity (0.977), positive predictive value (0.978), and negative predictive value (0.977) for classifying seropositivity, a high correlation of multiSero determined antibody titers with commercially available SARS-CoV-2 antibody tests, and antigen-specific changes in antibody titer dynamics upon vaccination. The open-source format and accessibility of our multiSero platform can contribute to the adoption of multiplexed ELISA arrays for serosurveillance studies, for SARS-CoV-2 and other pathogens of significance.

Diversity under the microscope: Lessons for building belonging in interdisciplinary spaces from the Women in Imaging + Industry bootcamp.

As scientific projects and labs benefit from increasingly interdisciplinary expertise, students and trainees find themselves navigating a myriad of academic spaces, each with its own workplace culture and demographics. A clear example is the interdisciplinary field of optics and biological microscopy which bridges biology, physics and engineering. While Biology PhDs are now >50% women, men in physics and engineering fields still significantly outnumber women, resulting in an imbalance of gender representation among microscopists and other 'tool innovators' in the interdisciplinary field of biological microscopy and biomedical optics. In addition to the cultural and cognitive whiplash that results from disparate representation between fields such as Biology, Engineering, and Physics, indifference from institutional leaders to implement equity-focused initiatives further contributes to cultures of exclusion, rather than belonging, for women. Here we elaborate on the motivation, structure, and outcomes of building a specific affinity-based bootcamp as an intervention to create an inclusive, welcoming learning environment for women in optics. Considering the presence of nonbinary, trans and other gender minoritised scientists, we recognise that women are not the only gender group underrepresented in biological microscopy and biomedical optics; still, we focus our attention on women in this specific intervention to improve gender parity in biological microscopy and biomedical optics. We hope that these strategies exemplify concrete paths forward for increasing belonging in interdisciplinary fields, a key step towards improving and diversifying graduate education.

What factors impact student performance in introductory physics?

In a previous study, we found that students' incoming preparation in physics-crudely measured by concept inventory prescores and math SAT or ACT scores-explains 34% of the variation in Physics 1 final exam scores at Stanford University. In this study, we sought to understand the large variation in exam scores not explained by these measures of incoming preparation. Why are some students' successful in physics 1 independent of their preparation? To answer this question, we interviewed 34 students with particularly low concept inventory prescores and math SAT/ACT scores about their experiences in the course. We unexpectedly found a set of common practices and attitudes. We found that students' use of instructional resources had relatively little impact on course performance, while student characteristics, student attitudes, and students' interactions outside the classroom all had a more substantial impact on course performance. These results offer some guidance as to how instructors might help all students succeed in introductory physics courses.

Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning.

Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from bacterial cells and numerous bacterial species and phenotypes. Here we generate an extensive dataset of bacterial Raman spectra and apply deep learning approaches to accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve average isolate-level accuracies exceeding 82% and antibiotic treatment identification accuracies of 97.0±0.3%. We also show that this approach distinguishes between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89±0.1% accuracy. We validate our results on clinical isolates from 50 patients. Using just 10 bacterial spectra from each patient isolate, we achieve treatment identification accuracies of 99.7%. Our approach has potential for culture-free pathogen identification and antibiotic susceptibility testing, and could be readily extended for diagnostics on blood, urine, and sputum.