In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

[EX Q]: binds to angiotensin-converting enzyme 2 which serves as a cellular receptor. Epidemiological analysis of a hospital outbreak in Hong Kong revealed that blood group O was associated with a low risk of infection. In this study, we used a cellular model of adhesion to investigate whether natural antibodies of the ABO system could block the S protein and angiotensin-converting enzyme 2 interaction. To this aim, a C-terminally EGFP-tagged S protein was expressed in chinese hamster ovary cells cotransfected with an α1,2fucosyltransferase and an A-transferase in order to coexpress the S glycoprotein ectodomain and the A antigen at the cell surface. We observed that the S protein/angiotensinconverting enzyme 2-dependent adhesion of these cells to an angiotensin-converting enzyme 2 expressing cell line was specifically inhibited by either a monoclonal or human natural anti-A antibodies, indicating that these antibodies may block the interaction between the virus and its receptor, thereby providing protection. In order to more fully appreciate the potential effect of the ABO polymorphism on the epidemiology of SARS, we built a mathematical model of the virus transmission dynamics that takes into account the protective effect of ABO natural antibodies. The model indicated that the ABO polymorphism could contribute to substantially reduce the virus transmission, affecting both the number of infected individuals and the kinetics of the epidemic. 1085 P Guillon et al.
[EX A]: Inhibition of the interaction between the SARS-CoV Spike protein and its cellular receptor by anti-histo-blood group antibodies

[EX Q]: Fast and slow axonal transport of protein have been studied in the optic nerves of mice infected with Semliki Forest Virus (SFV) that causes patchy demyelination throughout the CNS. Intravitreal injections of [3H]proline were given at regular intervals after virus inoculation, the labelled protein in the superior colliculi was then measured after survival periods of 18 h or 10 days, for fast and slow axonal transport studies, respectively. Fast transport studies showed an enhanced amount of protein arriving at the optic nerve terminals (superior colliculus) of the SFV-infected mice prior to the onset of demyelination. In contrast, the slow transport studies showed an enhanced amount of protein at the superior colliculus of the SFV-infected mice during the demyelination period. There was no concomitant increase in labelled protein in the retina at any time after the SFV infection. It is proposed that alteration in the transport of the protein constituents other than major myelin specific components may cause disruption of myelin maintenance in SFV infection.
[EX A]: The Relationship between Axonal Transport of Protein and Demyelination in the Optic Nerves of Mice Infected with Semliki Forest Virus

[EX Q]: Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct complex networks on which stochastic spreading dynamics take place. We apply the methodology to a large number of model and real networks, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing. Further, we demonstrate that a hidden source that triggers the spreading process but is externally inaccessible can be ascertained and located with high confidence in the absence of direct routes of propagation from it. Our approach thus establishes a paradigm for tracing and controlling epidemic invasion and information diffusion in complex networked systems. ½S i ðt 2 Þ þ S i ðt 6 Þ=2 and hS i ðt 2 þ 1Þi ¼ ½S i ðt 12 Þ þ S i ðt 14 Þ=2 based on the remaining strings marked in different colours (see Methods for more details). CST can be used to reconstruct the neighbouring vector X of node 2 from Y and U from Y ¼ U . X.
[EX A]:
ARTICLE Reconstructing propagation networks with natural diversity and identifying hidden sources