Our results indicate that measuring the system's detection performance with consideration of background variability may lead to differences in system performance estimates and comparisons. For the assessment of 3D systems, to accurately determine trade offs between image quality and radiation dose, it is critical to incorporate randomness arising from the imaging chain including background variability into system performance calculations.

In any drug discovery effort, the identification of hits for further optimisation is of crucial importance. For peptide therapeutics, display technologies such as mRNA display have emerged as powerful methodologies...

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Many of the currently available COVID-19 vaccines and therapeutics are not effective against newly emerged SARS-CoV-2 variants. Here, we developed the metallo-enzyme domain of angiotensin converting enzyme 2 (ACE2)—the cellular receptor of SARS-CoV-2—into an IgM-like inhalable molecule (HH-120). HH-120 binds to the SARS-CoV-2 Spike (S) protein with exceptionally high avidity and confers potent and broad-spectrum neutralization activity against all known SARS-CoV-2 variants of concern. HH-120 was successfully developed as an inhaled formulation that achieves appropriate aerodynamic properties for respiratory system delivery, and we found that aerosol inhalation of HH-120 significantly reduced viral loads and lung pathology scores in golden Syrian hamsters infected by the SARS-CoV-2 wild-type strain and the Delta variant. Our study presents a breakthrough for the inhalation delivery of large biologics like HH-120 (molecular weight ~ 1000kDa) and demonstrates that HH-120 can serve as a highly efficacious, safe, and convenient agent against all SARS-CoV-2 variants. Finally, given the known role of ACE2 in viral reception, it is conceivable that HH-120 will be efficacious against additional emergent coronaviruses.

For task specific evaluation of imaging systems it is necessary to obtain detailed descriptions of their noise and deterministic properties. In the past we have developed an experimental and theoretical methodology to estimate the deterministic detector response of a digital x-ray imaging system, also known as the H matrix. In this paper we have developed the experimental methodology for the evaluation of the quantum and electronic noise of digital radiographic detectors using the covariance matrix K. Using the H matrix we calculated the transfer of a simulated coronary artery constriction through an imaging system's detector, and with the covariance matrix we calculated the detectability (or Signal-to-Noise Ratio) and the detection probability. The eigenvalues and eigenvectors of the covariance matrix were presented and the electronic and quantum noise were analyzed. We found that the exposure at which the electronic noise equals the quantum noise at 90 kVp was 0.2 μR. We compared the ideal Hotelling observer with the Fourier definition of the SNR for a toroidal stenosis on a cylindrical vessel. Because of the shift-invariance and cyclo-stationarity assumptions, the Fourier SNR overestimates the performance of imaging systems. This methodology can be used for task specific evaluation and optimization of a digital x-ray imaging system.