Louisiana State University

About: Louisiana State University is a education organization based out in Baton Rouge, Louisiana, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 40206 authors who have published 76587 publications receiving 2566076 citations. The organization is also known as: LSU & Louisiana State University and Agricultural and Mechanical College.

Gibbon genome and the fast karyotype evolution of small apes

Abstract: Gibbons are small arboreal apes that display an accelerated rate of evolutionary chromosomal rearrangement and occupy a key node in the primate phylogeny between Old World monkeys and great apes. Here we present the assembly and analysis of a northern white-cheeked gibbon (Nomascus leucogenys) genome. We describe the propensity for a gibbon-specific retrotransposon (LAVA) to insert into chromosome segregation genes and alter transcription by providing a premature termination site, suggesting a possible molecular mechanism for the genome plasticity of the gibbon lineage. We further show that the gibbon genera (Nomascus, Hylobates, Hoolock and Symphalangus) experienced a near-instantaneous radiation ~5 million years ago, coincident with major geographical changes in southeast Asia that caused cycles of habitat compression and expansion. Finally, we identify signatures of positive selection in genes important for forelimb development (TBX5) and connective tissues (COL1A1) that may have been involved in the adaptation of gibbons to their arboreal habitat.

Influenza A Inhibits Th17-Mediated Host Defense against Bacterial Pneumonia in Mice

Abstract: Staphylococcus aureus is a significant cause of hospital and community acquired pneumonia and causes secondary infection after influenza A. Recently, patients with hyper-IgE syndrome, who often present with S. aureus infections of the lung and skin, were found to have mutations in STAT3, required for Th17 immunity, suggesting a potential critical role for Th17 cells in S. aureus pneumonia. Indeed, IL-17R(-/-) and IL-22(-/-) mice displayed impaired bacterial clearance of S. aureus compared with that of wild-type mice. Mice challenged with influenza A PR/8/34 H1N1 and subsequently with S. aureus had increased inflammation and decreased clearance of both virus and bacteria. Coinfection resulted in greater type I and II IFN production in the lung compared with that with virus infection alone. Importantly, influenza A coinfection resulted in substantially decreased IL-17, IL-22, and IL-23 production after S. aureus infection. The decrease in S. aureus-induced IL-17, IL-22, and IL-23 was independent of type II IFN but required type I IFN production in influenza A-infected mice. Furthermore, overexpression of IL-23 in influenza A, S. aureus-coinfected mice rescued the induction of IL-17 and IL-22 and markedly improved bacterial clearance. These data indicate a novel mechanism by which influenza A-induced type I IFNs inhibit Th17 immunity and increase susceptibility to secondary bacterial pneumonia.

Targeted interactomics reveals a complex core cell cycle machinery in Arabidopsis thaliana

Abstract: Cell proliferation is the main driving force for plant growth. Although genome sequence analysis revealed a high number of cell cycle genes in plants, little is known about the molecular complexes steering cell division. In a targeted proteomics approach, we mapped the core complex machinery at the heart of the Arabidopsis thaliana cell cycle control. Besides a central regulatory network of core complexes, we distinguished a peripheral network that links the core machinery to up- and downstream pathways. Over 100 new candidate cell cycle proteins were predicted and an in-depth biological interpretation demonstrated the hypothesis-generating power of the interaction data. The data set provided a comprehensive view on heterodimeric cyclin-dependent kinase (CDK)–cyclin complexes in plants. For the first time, inhibitory proteins of plant-specific B-type CDKs were discovered and the anaphase-promoting complex was characterized and extended. Important conclusions were that mitotic A- and B-type cyclins form complexes with the plant-specific B-type CDKs and not with CDKA;1, and that D-type cyclins and S-phase-specific A-type cyclins seem to be associated exclusively with CDKA;1. Furthermore, we could show that plants have evolved a combinatorial toolkit consisting of at least 92 different CDK–cyclin complex variants, which strongly underscores the functional diversification among the large family of cyclins and reflects the pivotal role of cell cycle regulation in the developmental plasticity of plants.

Consequences of Climate Change on the Ecogeomorphology of Coastal Wetlands

Abstract: Climate impacts on coastal and estuarine systems take many forms and are dependent on the local conditions, including those set by humans. We use a biocomplexity framework to provide a perspective of the consequences of climate change for coastal wetland ecogeomorphology. We concentrate on three dimensions of climate change affects on ecogeomorphology: sea level rise, changes in storm frequency and intensity, and changes in freshwater, sediment, and nutrient inputs. While sea level rise, storms, sedimentation, and changing freshwater input can directly impact coastal and estuarine wetlands, biological processes can modify these physical impacts. Geomorphological changes to coastal and estuarine ecosystems can induce complex outcomes for the biota that are not themselves intuitively obvious because they are mediated by networks of biological interactions. Human impacts on wetlands occur at all scales. At the global scale, humans are altering climate at rapid rates compared to the historical and recent geological record. Climate change can disrupt ecological systems if it occurs at characteristic time scales shorter than ecological system response and causes alterations in ecological function that foster changes in structure or alter functional interactions. Many coastal wetlands can adjust to predicted climate change, but human impacts, in combination with climate change, will significantly affect coastal wetland ecosystems. Management for climate change must strike a balance between that which allows pulsing of materials and energy to the ecosystems and promotes ecosystem goods and services, while protecting human structures and activities. Science-based management depends on a multi-scale understanding of these biocomplex wetland systems. Causation is often associated with multiple factors, considerable variability, feedbacks, and interferences. The impacts of climate change can be detected through monitoring and assessment of historical or geological records. Attribution can be inferred through these in conjunction with experimentation and modeling. A significant challenge to allow wise management of coastal wetlands is to develop observing systems that act at appropriate scales to detect global climate change and its effects in the context of the various local and smaller scale effects.

Visual aids and structured criteria for improving visual inspection and interpretation of single-case designs.

Abstract: Because behavior analysis is a data-driven process, a critical skill for behavior analysts is accurate visual inspection and interpretation of single-case data. Study 1 was a basic study in which we increased the accuracy of visual inspection methods for A-B designs through two refinements of the split-middle (SM) method called the dual-criteria (DC) and conservative dual-criteria (CDC) methods. The accuracy of these visual inspection methods was compared with one another and with two statistical methods (Allison & Gorman, 1993; Gottman, 1981) using a computer-simulated Monte Carlo study. Results indicated that the DC and CDC methods controlled Type I error rates much better than the SM method and had considerably higher power (to detect real treatment effects) than the two statistical methods. In Study 2, brief verbal and written instructions with modeling were used to train 5 staff members to use the DC method, and in Study 3, these training methods were incorporated into a slide presentation and were used to rapidly (i.e., 15 min) train a large group of individuals (N 5 87). Interpretation accuracy increased from a baseline mean of 55% to a treatment mean of 94% in Study 2 and from a baseline mean of 71% to a treatment mean of 95% in Study 3. Thus, Study 1 answered basic questions about the accuracy of several methods of interpreting A-B designs; Study 2 showed how that information could be used to increase the accuracy of human visual inspectors; and Study 3 showed how the training procedures from Study 2 could be modified into a format that would facilitate rapid training of large groups of individuals to interpret single-case designs. DESCRIPTORS: assessment, behavior analysis, data analysis, interrater agreement, visual inspection