Context: This study represents the largest compilation to date of clinical and postmortem data from decedents with coronavirus disease 2019 (COVID-19). It will augment previously published small series of autopsy case reports, refine clinicopathologic considerations, and improve the accuracy of future vital statistical reporting. Objective: To accurately reflect the pre-existing diseases and pathologic conditions of decedents with Sars-CoV-2 infection through autopsy. Design: Comprehensive data from 135 autopsy evaluations of COVID-19-positive decedents is presented, including histologic assessment. Postmortem examinations were performed by 36 pathologists at 19 medical centers or forensic institutions in the United States and Brazil. Data from each autopsy were collected through the online submission of multiple choice and openended survey responses. Results: Patients dying of or with COVID-19 had an average of 8.89 pathologic conditions documented at autopsy, spanning a combination of prior chronic disease and acute conditions acquired during hospitalization. Virtually all decedents were cited as having more than one preexisting condition, encompassing an average of 2.88 such diseases each. Clinical conditions during terminal hospitalization were cited 395 times for the 135 autopsied decedents and predominantly encompassed acute failure of multiple organ systems and/or impaired coagulation. Myocarditis was rarely cited. Conclusions: Cause-of-death statements in both autopsy reports and death certificates may not encompass the severity or spectrum of co-morbid conditions in those dying of or with COVID-19. If supported by additional research, this finding may have implications for public health decisions and reporting moving forward through the pandemic.

Bone tissue regeneration holds the potential to solve both osteoporosis and large skeletal defects, two problems associated with significant morbidity. The differentiation of mesenchymal stem cells into the osteogenic lineage requires a specific microenvironment and certain osteogenic growth factors. Neural EGF Like-Like molecule 1 (NELL-1) is a secreted glycoprotein that has proven, both in vitro and in vivo, to be a potent osteo-inductive factor. Furthermore, it has been shown to repress adipogenic differentiation and inflammation. NELL-1 can work synergistically with other osteogenic factors such as Bone Morphogenic Protein (BMP) −2 and −9, and has shown promise for use in tissue engineering and as a systemically administered drug for the treatment of osteoporosis. Here we provide a comprehensive up-to-date review on the molecular signaling cascade of NELL-1 in mesenchymal stem cells and potential applications in bone regenerative engineering.

As students do not qualify as essential health care workers, medical education faced severe disruptions during the COVID-19 pandemic including initial suspension of all in-person lectures and on-site rotations. Our Pathology Department was among the first at Northwestern to offer a completely virtual rotation with the goals of: (1) providing a comprehensive introduction to the practice of anatomic and clinical pathology, (2) emphasizing uninterrupted and continued excellence in education, and (3) minimizing exposure risk during the pandemic. The innovative 2-week curriculum incorporated diverse teaching modalities including live and recorded lectures; live and recorded video demonstrations; interactive small group discussions; interactive virtual sign-outs; and written and multimedia assignments, quizzes, and projects. The virtual elective ran from March to July 2020 with 52 total participating medical students. On post-rotation evaluations, students rated the pathology virtual elective 4.7/5.0 compared to other virtual rotations and 4.0/5.0 compared to all rotations (including in-person and virtual). Furthermore, continual improvements were made to the established framework based on rotation feedback such that curriculum content was more abundant and more favorably rated by the last cohort when compared to the first. Finally, although students identified interest in over 10 different medical specialties, all participants expressed increased interest in choosing pathology as a specialty and better understanding of pathology’s role in patient care. We hope our detailed description of creating and evaluating a completely virtual elective rotation serves as a model for other departments to improve pathology education and visibility.

Successful treatment of solid cancers relies on complete surgical excision of the tumor either for definitive treatment or before adjuvant therapy. Radial sectioning of the resected tumor and surrounding tissue is the most common form of intra-operative and post-operative margin assessment. However, this technique samples only a tiny fraction of the available tissue and therefore may result in incomplete excision of the tumor, increasing the risk of recurrence and distant metastasis and decreasing survival. Repeat procedures, chemotherapy, and other resulting treatments pose significant morbidity, mortality, and fiscal costs for our healthcare system. Mohs Micrographic Surgery (MMS) is used for the removal of basal cell and squamous cell carcinoma utilizing frozen sections for real-time margin assessment while assessing 100% of the peripheral and deep margins, resulting in a recurrence rate of less than one percent. Real-time assessment in many tumor types is constrained by tissue size and complexity and the time to process tissue and evaluate slides while a patient is under general anesthesia. In this study, we developed an artificial intelligence (AI) platform, ArcticAI, which augments the surgical workflow to improve efficiency by reducing rate-limiting steps in tissue preprocessing and histological assessment through automated mapping and orientation of tumor to the surgical specimen. Using basal cell carcinoma (BCC) as a model system, the results demonstrate that ArcticAI can provide effective grossing recommendations, accurately identify tumor on histological sections, map tumor back onto the surgical resection map, and automate pathology report generation resulting in seamless communication between the surgical pathology laboratory and surgeon. AI-augmented-surgical excision workflows may make real-time margin assessment for the excision of more complex and challenging tumor types more accessible, leading to more streamlined and accurate tumor removal while increasing healthcare delivery efficiency.