Type I interferon receptor deficiency in dendritic cells facilitates systemic murine norovirus persistence despite enhanced adaptive immunity

In order for a virus to persist, there must be a balance between viral replication and immune clearance. It is commonly believed that adaptive immunity drives clearance of viral infections and, thus, dysfunction or viral evasion of adaptive immunity is required for a virus to persist. Type I interferons (IFNs) play pleiotropic roles in the antiviral response, including through innate control of viral replication. Murine norovirus (MNoV) replicates in dendritic cells (DCs) and type I IFN signaling in DCs is important for early control of MNoV replication. We show here that the non-persistent MNoV strain CW3 persists systemically when CD11c positive DCs are unable to respond to type I IFN. Persistence in this setting is associated with increased early viral titers, maintenance of DC numbers, increased expression of DC activation markers and an increase in CD8 T cell and antibody responses. Furthermore, CD8 T cell function is maintained during the persistent phase of infection and adaptive immune cells from persistently infected mice are functional when transferred to Rag1-/- recipients. Finally, increased early replication and persistence are also observed in mixed bone marrow chimeras where only half of the CD11c positive DCs are unable to respond to type I IFN. These findings demonstrate that increased early viral replication due to a cell-intrinsic innate immune deficiency is sufficient for persistence and a functional adaptive immune response is not sufficient for viral clearance

Large-Scale Forest Inventories Of The United States And China Reveal Positive Effects Of Biodiversity On Productivity

Background With the loss of species worldwide due to anthropogenic factors, especially in forested ecosystems, it has become more urgent than ever to understand the biodiversity-ecosystem functioning relationship (BEFR). BEFR research in forested ecosystems is very limited and thus studies that incorporate greater geographic coverage and structural complexity are needed. Methods We compiled ground-measured data from approx. one half million forest inventory sample plots across the contiguous United States, Alaska, and northeastern China to map tree species richness, forest stocking, and productivity at a continental scale. Based on these data, we investigated the relationship between forest productivity and tree species diversity, using a multiple regression analysis and a non-parametric approach to account for spatial autocorrelation. Results In general, forests in the eastern United States consisted of more tree species than any other regions in the country. The highest forest stocking values over the entire study area were concentrated in the western United States and Central Appalachia. Overall, 96.4 % of sample plots (477,281) showed a significant positive effect of species richness on site productivity, and only 3.6 % (17,349) had an insignificant or negative effect. Conclusions The large number of ground-measured plots, as well as the magnitude of geographic scale, rendered overwhelming evidence in support of a positive BEFR. This empirical evidence provides insights to forest management and biological conservation across different types of forested ecosystems. Forest timber productivity may be impaired by the loss of species in forests, and biological conservation, due to its potential benefits on maintaining species richness and productivity, can have profound impacts on the functioning and services of forested ecosystems

Transfer Student Peer Mentorship Initiative

Transfer students have unique needs that differ from those of incoming freshmen. The TRAM Transfer Student Mentorship Program connects incoming transfer students with students who also began their VCU journey as transfer students. Through a one-on-one relationship with a trained mentor, transfer students who participate in this program will access guidance and information to help them navigate the university and its resources, programs, and culture

Persistent enteric murine norovirus infection is associated with functionally suboptimal virus-specific CD8 T cell responses

Norovirus (NV) gastroenteritis is a major contributor to global morbidity and mortality, yet little is known about immune mechanisms leading to NV control. Previous studies using the murine norovirus (MNV) model have established a key role for T cells in MNV clearance. Despite these advances, important questions remain regarding the magnitude, location, and dynamics of the MNV-specific T cell response. To address these questions, we identified MNV-specific major histocompatibility complex (MHC) class I immunodominant epitopes using an overlapping peptide screen. One of these epitopes (amino acids 519 to 527 of open reading frame 2 [ORF2(519-527)]) was highly conserved among all NV genogroups. Using MHC class I peptide tetramers, we tracked MNV-specific CD8 T cells in lymphoid and mucosal sites during infection with two MNV strains with distinct biological behaviors, the acutely cleared strain CW3 and the persistent strain CR6. Here, we show that enteric MNV infection elicited robust T cell responses primarily in the intestinal mucosa and that MNV-specific CD8 T cells dynamically regulated the expression of surface molecules associated with activation, differentiation, and homing. Furthermore, compared to MNV-CW3 infection, chronic infection with MNV-CR6 resulted in fewer and less-functional CD8 T cells, and this difference was evident as early as day 8 postinfection. Finally, MNV-specific CD8 T cells were capable of reducing the viral load in persistently infected Rag1(−/−) mice, suggesting that these cells are a crucial component of NV immunity. Collectively, these data provide fundamental new insights into the adaptive immune response to two closely related NV strains with distinct biological behaviors and bring us closer to understanding the correlates of protective antiviral immunity in the intestine

Commensal-dependent expression of IL-25 regulates the IL-23–IL-17 axis in the intestine

Alterations in the composition of intestinal commensal bacteria are associated with enhanced susceptibility to multiple inflammatory diseases, including those conditions associated with interleukin (IL)-17–producing CD4+ T helper (Th17) cells. However, the relationship between commensal bacteria and the expression of proinflammatory cytokines remains unclear. Using germ-free mice, we show that the frequency of Th17 cells in the large intestine is significantly elevated in the absence of commensal bacteria. Commensal-dependent expression of the IL-17 family member IL-25 (IL-17E) by intestinal epithelial cells limits the expansion of Th17 cells in the intestine by inhibiting expression of macrophage-derived IL-23. We propose that acquisition of, or alterations in, commensal bacteria influences intestinal immune homeostasis via direct regulation of the IL-25–IL-23–IL-17 axis

Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73839/1/j.1468-0262.2006.00696.x.pd

Galaxy cluster mass bias from projected mass maps: The Three Hundred-NIKA2 LPSZ twin samples

The determination of the mass of galaxy clusters from observations is subject to systematic uncertainties. Beyond the errors due to instrumental and observational systematic effects, in this work we investigate the bias introduced by modelling assumptions. In particular, we consider the reconstruction of the mass of galaxy clusters from convergence maps employing spherical mass density models. We make use of The Three Hundred simulations, selecting clusters in the same redshift and mass range as the NIKA2 Sunyaev-Zel'dovich Large Program sample: $3 \leq M_{500}/ 10^{14} \mathrm{M}_{\odot} \leq 10$ and $0.5 \leq z \leq 0.9$. We study different modelling and intrinsic uncertainties that should be accounted for when using the single cluster mass estimates for scaling relations. We confirm that the orientation of clusters and the radial ranges considered for the fit have an important impact on the mass bias. The effect of the projection adds uncertainties to the order of $10\%$ to $14\%$ to the mass estimates. We also find that the scatter from cluster to cluster in the mass bias when using spherical mass models is less than $20\%$ of the true mass of the clusters

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology

Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data. In particular, we perform the first study that involves more than two datasets. We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue types due to different dosages of an experimental panPPAR agonist in mouse. This study is of interest in toxicology because, whilst PPARs form potential therapeutic targets for diabetes, it is known that they can induce serious side-effects. Our results show that the practical simultaneous non-negative matrix factorization developed here can add value to the data analysis. In particular, we find that factorizing the data as a single object allows us to distinguish between the four tissue types, but does not correctly reproduce the known dosage level groups. Applying our new approach, which treats the four tissue types as providing distinct, but related, datasets, we find that the dosage level groups are respected. The new algorithm then provides separate gene list orderings that can be studied for each tissue type, and compared with the ordering arising from the single factorization. We find that many of our conclusions can be corroborated with known biological behaviour, and others offer new insights into the toxicological effects. Overall, the algorithm shows promise for early detection of toxicity in the drug discovery process