Modeling Cardiac Muscle Mechanics

The heart is a complex electro-mechanical system which is intrinsically and intimately linked to physiology and pathology. Cardiac muscle tissue underlies the dynamics of the heart; understanding cardiac muscle tissue allows insight into the working of the heart at a fundamental level. Indeed, models allow a theoretical understanding of systems which necessarily exceeds that of experiment. Here, we describe a novel mathematical model of cardiac muscle mechanics based on functional relations

Worldwide Disparities in Recovery of Cardiac Testing 1 Year Into COVID-19

FUNDING SUPPORT AND AUTHOR DISCLOSURES Dr Williams is supported by the British Heart Foundation (FS/ICRF/ 20/26002). Dr Einstein has received speaker fees from Ionetix; has received consulting fees from W. L. Gore & Associates; has received authorship fees from Wolters Kluwer Healthcare – UpToDate; and has received grants or grants pending to his institution from Attralus, Canon Medical Systems, Eidos Therapeutics, GE Healthcare, Pfizer, Roche Medical Systems, W. L. Gore & Associates, and XyloCor Ther- apeutics. Dr Williams has received speaker fees from Canon Medical Systems. Dr Dorbala has received honoraria from Pfizer and GE Healthcare; and has received grants to her institution from Pfizer and GE Healthcare. Dr Sinitsyn has received congress speaker honoraria from Bayer, GE Healthcare, Siemens, and Philips. Dr Kudo has received research grants from Nihon Medi-physics and FUJIFILM Toyama Chemical. Dr Bucciarelli-Ducci is CEO (part-time) of the So- ciety for Cardiovascular Magnetic Resonance; and has received speaker fees from Circle Cardiovascular Imaging, Bayer, and Siemens Healthineers. All other authors have reported that they have no re- lationships relevant to the contents of this paper to disclose.Peer reviewedPublisher PD

Tracking smell loss to identify healthcare workers with SARS-CoV-2 infection

Introduction Healthcare workers (HCW) treating COVID-19 patients are at high risk for infection and may also spread infection through their contact with vulnerable patients. Smell loss has been associated with SARS-CoV-2 infection, but it is unknown whether monitoring for smell loss can be used to identify asymptomatic infection among high risk individuals. In this study we sought to determine if tracking smell sensitivity and loss using an at-home assessment could identify SARS-CoV-2 infection in HCW. Methods and findings We performed a prospective cohort study tracking 473 HCW across three months to determine if smell loss could predict SARS-CoV-2 infection in this high-risk group. HCW subjects completed a longitudinal, behavioral at-home assessment of olfaction with household items, as well as detailed symptom surveys that included a parosmia screening questionnaire, and real-time quantitative polymerase chain reaction testing to identify SARS-CoV-2 infection. Our main measures were the prevalence of smell loss in SARS-CoV-2-positive HCW versus SARS-CoV- 2-negative HCW, and timing of smell loss relative to SARS-CoV-2 test positivity. SARS-CoV-2 was identified in 17 (3.6%) of 473 HCW. HCW with SARS-CoV-2 infection were more likely to report smell loss than SARS-CoV-2-negative HCW on both the at-home assessment and the screening questionnaire (9/17, 53% vs 105/456, 23%, P < .01). 6/9 (67%) of SARS-CoV-2-positive HCW reporting smell loss reported smell loss prior to having a positive SARS-CoV-2 test, and smell loss was reported a median of two days before testing positive. Neurological symptoms were reported more frequently among SARS-CoV-2-positive HCW who reported smell loss compared to those without smell loss (9/9, 100% vs 3/8, 38%, P < .01). Conclusions In this prospective study of HCW, self-reported changes in smell using two different measures were predictive of SARS-CoV-2 infection. Smell loss frequently preceded a positive test and was associated with neurological symptoms

Gut Microbiome Dysbiosis in Antibiotic-Treated COVID-19 Patients is Associated with Microbial Translocation and Bacteremia

Although microbial populations in the gut microbiome are associated with COVID-19 severity, a causal impact on patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. We first demonstrate SARS-CoV-2 infection induces gut microbiome dysbiosis in mice, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, including blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19