Search

Soluble ACE2 (sACE2) decoys are promising agents to inhibit SARS-CoV-2, as their efficiency is unlikely to be affected by escape mutations. However, their success is limited by their relatively poor potency. To address this challenge, multimeric sACE2 consisting of SunTag or MoonTag systems is developed. These systems are extremely effective in neutralizing SARS-CoV-2 in pseudoviral systems and in clinical isolates, perform better than the dimeric or trimeric sACE2, and exhibit greater than 100-fold neutralization efficiency, compared to monomeric sACE2. SunTag or MoonTag fused to a more potent sACE2 (v1) achieves a sub-nanomolar IC50, comparable with clinical monoclonal antibodies. Pseudoviruses bearing mutations for variants of concern, including delta and omicron, are also neutralized efficiently with multimeric sACE2. Finally, therapeutic treatment of sACE2(v1)-MoonTag provides protection against SARS-CoV-2 infection in an in vivo mouse model. Therefore, highly potent multimeric sACE2 may offer a promising treatment approach against SARS-CoV-2 infections., Koç University Isbank Center for Infectious Diseases (KUISCID); Koç University Research Center for Transla-tional Medicine (KUTTAM)

Soluble ACE2 (sACE2) decoy receptors are promising agents to inhibit SARS-CoV-2, as their efficiency is less likely to be affected by common escape mutations in viral proteins. However, their success may be limited by their relatively poor potency. To address this challenge, we developed a large decoy library of sACE2 fusion proteins, generated with several protease inhibitors or multimerization tags. Among these decoys, multimeric sACE2 consisting of SunTag or MoonTag systems, which were originally utilized for signal amplification or gene activation systems, were extremely effective in neutralizing SARS-CoV-2 in pseudoviral systems and in clinical isolates. These novel sACE2 fusion proteins exhibited greater than 100-fold SARS-CoV-2 neutralization efficiency, compared to monomeric sACE2. SunTag or MoonTag in combination with a more potent version of sACE2, which has multiple point mutations for greater binding (v1), achieved near complete neutralization at a sub-nanomolar range, comparable with clinical monoclonal antibodies. Pseudoviruses bearing mutant versions of Spike, alpha, beta, gamma or delta variants, were also neutralized efficiently with SunTag or MoonTag fused sACE2(v1). Finally, therapeutic treatment of sACE2(v1)-MoonTag provided protection against SARS-CoV-2 infection in an in vivo mouse model. Overall, we suggest that the superior activity of the sACE2-SunTag or sACE2-MoonTag fusions is due to the greater occupancy of the multimeric sACE2 receptors on Spike protein as compared to monomeric sACE2. Therefore, these highly potent multimeric sACE2 decoy receptors may offer a promising treatment approach against SARS-CoV-2 infections.One Sentence SummaryMultimerization of sACE2 markedly enhanced the neutralization of SARS-CoV-2 by blocking multiple viral spike proteins simultaneously.

Amelogenesis imperfecta (AI) is one of the developmental enamel defects. In patients with AI, as well as enamel defects, some dental anomalies are encountered and may affect tooth development. For children whose enamel structure is not normal, whether an accurate result can be obtained by dental age determination methods is not clear. The aims of this study are to determine the dental age for the assessment of tooth development in patients with AI by 3 different methods, to decide a method that will present the most accurate result to the chronological age, and to build a basis in terms of postmortem identification. The records of patients who were referred to the Department of Pediatric Dentistry between the years of 1999 and 2018, and diagnosed with AI were reviewed. At the age of 6-15 years, 58 patients (33 males-25 females) (Group I) with AI were determined. A total of 116 healthy individuals (66 males-50 females) (Group II) who were age and gender matched with the AI group were selected as the control group. Chronological age was calculated, and Nolla's, Demirjian's and Haavikko's methods were used to estimate dental age. Chronological and dental ages were compared according to the group and gender. The accuracy of three methods was also evaluated. There was no statistical significant differences for the tooth development in terms of group and gender. Dental age was over-estimated by Demirjian's method and under-estimated by Nolla's and Haavikko's methods. Haavikko's and Nolla's methods were more accurate in the dental age estimation. AI did not present an impact on the dental development. By using particularly Haavikko's method, the possible margin of error in evaluations of dental development can be reduced. Similar studies comprising other defects affecting the tooth structure and morphology are also necessary.

Pervasive computing is often mentioned in the context of improving healthcare. This paper presents a novel approach for diagnosing diabetes using neural networks and pervasive healthcare computing technologies. The recent developments in small mobile devices and wireless communications provide a strong motivation to develop new software techniques and mobile services for pervasive healthcare computing. A distributed end-to-end pervasive healthcare system utilizing neural network computations for diagnosing illnesses was developed. This work presents the initial results for a simple client (patient's PDA) and server (powerful desktop PC) two-tier pervasive healthcare architecture. The computations of neural network operations on both client and server sides and wireless network communications between them are optimized for real time use of pervasive healthcare services.