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]: The Sec7 domain ADP-ribosylation factor (Arf) guanine nucleotide exchange factors (GEFs) are found in all eukaryotes, and are involved in membrane remodeling processes throughout the cell. This review is focused on members of the GBF/Gea and BIG/Sec7 subfamilies of Arf GEFs, all of which use the class I Arf proteins (Arf1-3) as substrates, and play a fundamental role in traYcking in the endoplasmic reticulum (ER)-Golgi and endosomal membrane systems. Members of the GBF/Gea and BIG/Sec7 subfamilies are large proteins on the order of 200 kDa, and they possess multiple homology domains. Phylogenetic analyses indicate that both of these subfamilies of Arf GEFs have members in at least Wve out of the six eukaryotic supergroups, and hence were likely present very early in eukaryotic evolution. The homology domains of the large Arf1 GEFs play important functional roles, and are involved in interactions with numerous protein partners. The large Arf1 GEFs have been implicated in several human diseases. They are crucial host factors for the replication of several viral pathogens, including poliovirus, coxsackievirus, mouse hepatitis coronavirus, and hepatitis C virus. Mutations in the BIG2 Arf1 GEF have been linked to autosomal recessive periventricular heterotopia, a disorder of neuronal migration that leads to severe malformation of the cerebral cortex. Understanding the roles of the Arf1 GEFs in membrane dynamics is crucial to a full understanding of traYcking in the secretory and endosomal pathways, which in turn will provide essential insights into human diseases that arise from misregulation of these pathways.
[EX A]: Large Arf1 guanine nucleotide exchange factors: evolution, domain structure, and roles in membrane traYcking and human disease

[EX Q]: The worldwide prevalence of herpes simplex virus (HSV) and the shortage of efficient vaccines and novel therapeutic strategies against HSV are widely global concerns. The abundance on the virion and the major stimulus for the virus-neutralizing antibodies makes gD a predominant candidate for cure of HSV infection. In this study, we generated a monoclonal antibody (mAb), termed m27f, targeting to glycoprotein D (gD) of HSV-2, which also has cross-reactivity against HSV-1 gD. It has a high level of neutralizing activity against both HSV-1 and HSV-2, and binds to a highly conserved region (residues 292-297) within the pro-fusion domain of gD. It can effectively block HSV cell-to-cell spread in vitro. The pre-or post-attachment neutralization assay and syncytium formation inhibition assay revealed that m27f neutralizes HSV at the post-binding stage. Moreover, therapeutic administration of m27f completely prevented infection-related mortality of mice challenged with a lethal dose of HSV-2. Our newly identified epitope for the neutralizing antibody would facilitate studies of gD-based HSV entry or vaccine design, and m27f itself demonstrated a high potential for adaptation as a protective or therapeutic drug against HSV.
[EX A]: A novel glycoprotein D-specific monoclonal antibody neutralizes herpes simplex virus

[EX Q]: Tables S4.1 and S4.2 show the goodness-of-fit results (burn-in 1,000,000 iterations, 1,000,000 iterations per graph, 1000 graphs) for the multilevel exponential random graph model (ERGM) for the relationships network. Results were generated using MPNet [1] [2] [3] . Table S4 .1 shows the results for just the bipartite network. Column 1 lists the various statistics that are evaluated. Column 2 shows the value of the statistic for the empirical network ("Sample"). Columns 3 and 4 show the mean ("Mean") and sample standard deviation ("Std. Dev."), respectively, of the statistic over simulated networks. Column 5 shows the "t-ratio", defined as (observed value-mean value)/standard deviation. For each parameter, using standard methodology, the model is a good fit for the empirical network if the "t-ratio" has absolute value less than 0.1 for parameters explicitly in the model (shown in boldface) and less than 2 otherwise.
[EX A]:
S4 Appendix: Multilevel ERGM Goodness of Fit