Disease Progression in MRL/lpr Lupus-Prone Mice Is Reduced by NCS 613, a Specific Cyclic Nucleotide Phosphodiesterase Type 4 (PDE4) Inhibitor

Systemic lupus erythematosus is a polymorphic and multigenic inflammatory autoimmune disease. Cyclic AMP (cAMP) modulates inflammation and the inhibition of cyclic nucleotide phosphodiesterase type 4 (PDE4), which specifically hydrolyzes cAMP, inhibits TNFα secretion. This study was aimed at investigating the evolution of PDE activity and expression levels during the course of the disease in MRL/lpr lupus-prone mice, and to evaluate in these mice the biological and clinical effects of treatments with pentoxifylline, denbufylline and NCS 613 PDE inhibitors. This study reveals that compared to CBA/J control mice, kidney PDE4 activity of MRL/lpr mice increases with the disease progression. Furthermore, it showed that the most potent and selective PDE4 inhibitor NCS 613 is also the most effective molecule in decreasing proteinuria and increasing survival rate of MRL/lpr mice. NCS 613 is a potent inhibitor, which is more selective for the PDE4C subtype (IC50 = 1.4 nM) than the other subtypes (PDE4A, IC50 = 44 nM; PDE4B, IC50 = 48 nM; and PDE4D, IC50 = 14 nM). Interestingly, its affinity for the High Affinity Rolipram Binding Site is relatively low (Ki = 148 nM) in comparison to rolipram (Ki = 3 nM). Finally, as also observed using MRL/lpr peripheral blood lymphocytes (PBLs), NCS 613 inhibits basal and LPS-induced TNFα secretion from PBLs of lupus patients, suggesting a therapeutic potential of NCS 613 in systemic lupus. This study reveals that PDE4 represent a potential therapeutic target in lupus disease

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Diversification and historical demography of Rhampholeon spectrum in West-Central Africa.

Pygmy Chameleons of the genus Rhampholeon represent a moderately diverse, geographically circumscribed radiation, with most species (18 out of 19 extant taxa) limited to East Africa. The one exception is Rhampholeon spectrum, a species restricted to West-Central African rainforests. We set out to characterize the geographic basis of genetic variation in this disjunctly distributed Rhampholeon species using a combination of multilocus Sanger data and genomic sequences to explore population structure and range-wide phylogeographic patterns. We also employed demographic analyses and niche modeling to distinguish between alternate explanations to contextualize the impact of past geological and climatic events on the present-day distribution of intraspecific genetic variation. Phylogenetic analyses suggest that R. spectrum is a complex of five geographically delimited populations grouped into two major clades (montane vs. lowland). We found pronounced population structure suggesting that divergence and, potentially, speciation began between the late Miocene and the Pleistocene. Sea level changes during the Pleistocene climatic oscillations resulted in allopatric divergence associated with dispersal over an ocean channel barrier and colonization of Bioko Island. Demographic inferences and range stability mapping each support diversification models with secondary contact due to population contraction in lowland and montane refugia during the interglacial period. Allopatric divergence, congruent with isolation caused by geologic uplift of the East African rift system, the "descent into the Icehouse," and aridification of sub-Saharan Africa during the Eocene-Oligocene are identified as the key events explaining the population divergence between R. spectrum and its closely related sister clade from the Eastern Arc Mountains. Our results unveil cryptic genetic diversity in R. spectrum, suggesting the possibility of a species complex distributed across the Lower Guinean Forest and the Island of Bioko. We highlight the major element of species diversification that modelled today's diversity and distributions in most West-Central African vertebrates

Grewia spp. Biopolymer as Low-Cost Biosorbent for Hexavalent Chromium Removal

In this study, Grewia spp. biopolymer was utilized as a biosorbent for elimination of hexavalent chromium from water. Fourier-transform infrared spectrometry (FTIR) and X-ray diffraction (XRD) were performed for characterization of the biosorbent. Experiments were conducted in a batch mode at room temperature (25 ± 2°C) and agitation speed of 100 rpm to determine the influence of biosorbent dose, contact time, Cr(VI) concentration, and initial solution pH. It was found that equilibrium was attained in 50 min. A pseudo-first-order model suited well than a pseudo-second-order model. Biosorption capacity of Grewia spp. biopolymer increased with increase in concentration and depended on the solution pH. Langmuir and Freundlich models described experimental data very well. These findings showed that Grewia spp. biopolymer can serve as a biosorbent for elimination of Cr(VI) from water

Translating Predictions of Zoonotic Viruses for Policymakers.

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers