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.

Avian infectious bronchitis virus (IBV), a coronavirus, causes infectious bronchitis leading to enormous economic loss in the poultry industry worldwide. Hypericin (HY) is an excellent compound that has been investigated in antiviral, antineoplastic, and antidepressant. To investigate the inhibition effect of HY on IBV infection in chicken embryo kidney (CEK) cells, 3 different experimental designs: pre-treatment of cells prior to IBV infection, direct treatment of IBV-infected cells, and pre-treatment of IBV prior to cell infection were used. Quantitative real-time PCR (qRT-PCR), immunofluorescence assay (IFA), flow cytometry, and fluorescence microscopy were performed and virus titer was determined by TCID 50 . The re-sults revealed that HY had a good anti-IBV effect when HY directly treated the IBV-infected cells, and virus infectivity decreased in a dose-dependent manner. Furthermore, HY inhibited IBV-induced apoptosis in CEK cells, and significantly reduced the mRNA expression levels of Fas, FasL, JNK, Bax, Caspase 3, and Caspase 8, and significantly increased Bcl-2 mRNA expression level in CEK cells. In addition, HY treatment could decrease IBV-induced reactive oxygen species (ROS) generation in CEK cells. These results suggested that HY showed potential antiviral activities against IBV infection involving the inhibition of apoptosis and ROS generation in CEK cells.
Protective effects of hypericin against infectious bronchitis virus induced apoptosis and reactive oxygen species in chicken embryo kidney cells

Estimating temporal changes in a target population from phylogenetic or count data is an important problem in ecology and epidemiology. Reliable estimates can provide key insights into the climatic and biological drivers influencing the diversity or structure of that population and evidence hypotheses concerning its future growth or decline. In infectious disease applications, the individuals infected across an epidemic form the target population. The renewal model estimates the effective reproduction number, R, of the epidemic from counts of its observed cases. The skyline model infers the effective population size, N, underlying a phylogeny of sequences sampled from that epidemic. Practically, R measures ongoing epidemic growth while N informs on historical caseload. While both models solve distinct problems, the reliability of their estimates depends on p-dimensional piecewise-constant functions. If p is misspecified, the model might underfit significant changes or overfit noise and promote a spurious understanding of the epidemic, which might misguide intervention policies or misinform forecasts. Surprisingly, no transparent yet principled approach for optimising p exists. Usually, p is heuristically set, or obscurely controlled via complex algorithms. We present a computable and interpretable p-selection method based on the minimum description length (MDL) formalism of information theory. Unlike many standard model selection techniques, MDL accounts for the additional statistical complexity induced by how parameters interact. As a result, our method optimises p so that R and N estimates properly adapt to the available data. It also outperforms comparable Akaike and Bayesian information criteria on several classification problems. Our approach requires some knowledge of the parameter space and exposes the similarities between renewal and skyline models.
Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models

Coronaviruses infect animals and humans causing a wide range of diseases. The diversity of coronaviruses in many mammalian species is contributed by relatively high mutation and recombination rates during replication. This dynamic nature of coronaviruses may facilitate cross-species transmission and shifts in tissue or cell tropism in a host, resulting in substantial change in virulence. Feline enteric coronavirus (FECV) causes inapparent or mild enteritis in cats, but a highly fatal disease, called feline infectious peritonitis (FIP), can arise through mutation of FECV to FIP virus (FIPV). The pathogenesis of FIP is intimately associated with immune responses and involves depletion of T cells, features shared by some other coronaviruses like Severe Acute Respiratory Syndrome Coronavirus. The increasing risks of highly virulent coronavirus infections in humans or animals call for effective antiviral drugs, but no such measures are yet available. Previously, we have reported the inhibitors that target 3C-like protease (3CLpro) with broad-spectrum activity against important human and animal coronaviruses. Here, we evaluated the therapeutic efficacy of our 3CLpro inhibitor in laboratory cats with FIP. Experimental FIP is 100% fatal once certain clinical and laboratory signs become apparent. We found that antiviral treatment led to full recovery of cats when treatment was started at a stage of disease that would be otherwise fatal if left untreated. Antiviral treatment was associated with a rapid improvement in fever, ascites, lymphopenia and gross signs of illness and cats returned to normal health within 20 days or less of treatment. Significant reduction in viral titers was also observed in cats. These results indicate that continuous virus replication is required for progression of immune-mediated inflammatory disease of FIP. These findings may provide important insights into devising therapeutic strategies and selection of antiviral compounds for further development for important coronaviruses in animals and humans.
Reversal of the Progression of Fatal Coronavirus Infection in Cats by a Broad- Spectrum Coronavirus Protease Inhibitor