The functional views on response of host rabbit post coronavirus vaccination via ACE2 PET.

Molecular imaging can dynamically and quantitatively record the biochemical changes in a systemic view. In this research, SARS-CoV-2 pseudovirus was intramuscularly injected to simulate the vaccination with inactivated virus. New Zealand white rabbits were evaluated with 18F-FDG PET for inflammation and 68Ga-cyc-DX600 PET for ACE2 fluctuation, which were performed before and at 3, 7 and 14 days post injection (d P.I.); furthermore, one rabbit was vaccinated with two cycles with interval of 14 days for a longer period evaluation. Different with the vaccination-induced inflammatory response that was random and individual, ACE2 regulation was systemic and organ-specific: the liver and spleen were of a moderate decrease post injection but rebound at 14 d P.I., while there were a downward trend in heart, testis and bone marrow; besides, similar pattern of ACE2 regulation were recorded after the second injection with a relatively greater volatility. In conclusion, ACE2 PET gave a more comprehensive view on host response post vaccination, hold substantial promise in continuous monitoring of coronavirus vaccine administration and effectiveness.

ACE2 PET to reveal the dynamic patterns of ACE2 recovery in an infection model with pseudocorona virus.

Due to the COVID-19 pandemic, a series of sequelae, such as fatigue, tachypnea, and ageusia, appeared in long COVID patients, but the pathological basis was still uncertain. The targeted radiopharmaceuticals were of potential to systemically and dynamically trace the pathological changes. For the key ACE2 protein in the virus-host interaction, 68 Ga-cyc-DX600 was developed on the basis of DX600 as a PET tracer of ACE2 fluctuation and maintained the ability in differentiating ACE and ACE2. In the temporary infection model inhaled with the radio-traceable pseudovirus in the upper respiratory tract of male humanized ACE2 (hACE2) mice, organ-specific ACE2 dysfunction in acute period and the following ACE2 recovery in a relatively long period was visualized and quantified by ACE2 PET, revealing a complex pattern of virus concentration-dependent degree and time period-dependent tendency of ACE2 recovery, mainly a sudden decrease of apparent ACE2 in the heart, liver, kidneys, lungs, and so on, but the liver was of a quick functional compensation on ACE2 expression after a temporary decrease. ACE2 expression of most organs has recovered to a normal level at 15 days post inhalation, with brain and genitals still of a decreased SUVACE2 ;  meanwhile, kidneys were of an increased SUVACE2 . These findings on ACE2 PET were further verified by western blot. When compared with high-resolution computed tomography on structural changes and FDG PET on glycometabolism, ACE2 PET was superior in an earlier diagnostic window during infection and more comprehensive understanding of functional dysfunction post-infection. In the respective ACE2 PET/CT and ACE2 PET/MR scans of a volunteer, the repeatability of SUVACE2 and the ACE2 specificity were further confirmed. In conclusion, 68 Ga-cyc-DX600 was developed as an ACE2-specific tracer, and the corresponding ACE2 PET revealed the dynamic patterns of functional ACE2 recovery and provided a reference and approach to explore the ACE2-related pathological basis of sequelae in long COVID.

Molecular imaging on ACE2-dependent transocular infection of coronavirus.

A transocular infection has been proved as one of the main approaches that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) invades the body, and angiotensin-converting enzyme 2 (ACE2) plays a key role in this procedure. Dynamic and quantitative details on virus distribution are lacking for virus prevention and drug design. In this study, a radiotraceable pseudovirus packed with an enhanced green fluorescent protein (EGFP) gene, 125 I-CoV, was prepared and inoculated in the unilateral eye of humanized ACE2 (hACE2) mice or ACE2-knockout (ACE2-KO) mice. Single-photon emission computed tomography/computed tomography images were acquired at multiple time points to exhibit ACE2-dependent procedures from invasion to clearance. Positron emission tomography (PET) and western blot were performed to quantify ACE2 expression and verify the factors affecting transocular infection. For the transocular infection of coronavirus (CoV), the renin-angiotensin-aldosterone system (RAAS), lungs, intestines, and genital glands were the main targeted organs. Due to the specific anchor to ACE2-expressed host cells, virus concentrations in genital glands, liver, and lungs ranked the top three most and stabilized at 3.75 ± 0.55, 3.30 ± 0.25, and 2.10 ± 0.55% inoculated dose (ID)/mL at 48 h post treatment. Meanwhile, ACE2-KO mice had already completed the in vivo clearance. In consideration of organ volumes, lungs (14.50 ± 3.75%ID) and liver (10.94 ± 0.71%ID) were the main in-store reservoirs of CoV. However, the inoculated eye (5.52 ± 1.85%ID for hACE2, 5.24 ± 1.45%ID for ACE2-KO, p > 0.05) and the adjacent brain exhibited ACE2-independent virus infection at the end of 72 h observation, and absolute amount of virus played a key role in host cell infection. These observations on CoV infection were further manifested by infection-driven intracellular EGFP expression. ACE2 PET revealed an infection-related systematic upregulation of ACE2 expression in the organs involved in RAAS (e.g., brain, lung, heart, liver, and kidney) and the organ that was of own local renin-angiotensin system (e.g., eye). Transocular infection of CoV is ACE2-dependent and constitutes the cause of disturbed ACE2 expression in the host. The brain, genital glands, and intestines were of the highest unit uptake, potentially accounting for the sequelae. Lungs and liver were of the highest absolute amount, closely related to the respiratory diffusion and in vivo duplication. ACE2 expression was upregulated in the short term after infection with CoV. These visual and quantitative results are helpful to fully understanding the transocular path of SARS-CoV-2 and other CoVs.

A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.

OBJECTIVE: To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease 2019 (COVID-19) in the emergency department (ED). METHODS: We developed in a 12-hospital system a model using training and validation followed by a real-time assessment. The LASSO guided feature selection included demographics, comorbidities, home medications, vital signs. We constructed a logistic regression-based ML algorithm to predict "severe" COVID-19, defined as patients requiring intensive care unit (ICU) admission, invasive mechanical ventilation, or died in or out-of-hospital. Training data included 1,469 adult patients who tested positive for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within 14 days of acute care. We performed: 1) temporal validation in 414 SARS-CoV-2 positive patients, 2) validation in a PUI set of 13,271 patients with symptomatic SARS-CoV-2 test during an acute care visit, and 3) real-time validation in 2,174 ED patients with PUI test or positive SARS-CoV-2 result. Subgroup analysis was conducted across race and gender to ensure equity in performance. RESULTS: The algorithm performed well on pre-implementation validations for predicting COVID-19 severity: 1) the temporal validation had an area under the receiver operating characteristic (AUROC) of 0.87 (95%-CI: 0.83, 0.91); 2) validation in the PUI population had an AUROC of 0.82 (95%-CI: 0.81, 0.83). The ED CDS system performed well in real-time with an AUROC of 0.85 (95%-CI, 0.83, 0.87). Zero patients in the lowest quintile developed "severe" COVID-19. Patients in the highest quintile developed "severe" COVID-19 in 33.2% of cases. The models performed without significant differences between genders and among race/ethnicities (all p-values > 0.05). CONCLUSION: A logistic regression model-based ML-enabled CDS can be developed, validated, and implemented with high performance across multiple hospitals while being equitable and maintaining performance in real-time validation.

Parental burnout and remote learning at home during the COVID-19 pandemic: Parents' motivations for involvement.

Given the chronic stress that families experienced during the Coronavirus disease (COVID-19) pandemic accompanied by school closures, many parents were vulnerable to parental burnout as they supervised their children's remote learning in addition to other roles. According to self-determination theory (SDT), when parents' basic needs are met, they are optimally motivated to support their children's learning and create environments that support their children's needs. Using a variable- and person-centered approach, we explored associations between parents' burnout, academic concern, motivational styles and profiles, and need-supportive behavior. Considering the pandemic, we expected parents with increased burnout and academic concern to report higher levels of controlled motivation or belong to a low-quality motivation profile and report less support for their children's needs. Parents with 5- to 8-year-olds were recruited, targeting states in the U.S. with the longest shelter-in-place restrictions (CA, NY), to complete an online survey, resulting in a sample (N = 218) of parents from 38 states in the U.S. Results showed parents exhibiting more autonomous motivation and two latent profiles denoting only motivation quantity but not quality. Higher burnout was related to nonoptimal motivation styles and profiles, while academic concern was related to increased motivation. Parents of older children had increased motivation. Findings highlight that even during a global pandemic, parents showed some levels of optimal motivation to support their children's remote learning. Results also highlight the importance of meeting parents' basic needs in order for them to support the developmental and learning needs of their children. (PsycInfo Database Record (c) 2022 APA, all rights reserved).