Optimal Control in the Treatment of Retinitis Pigmentosa

Numerous therapies have been implemented in an effort to minimize the debilitating effects of the degenerative eye disease Retinitis Pigmentosa (RP), yet none have provided satisfactory long-term solution. To date there is no treatment that can halt the degeneration of photoreceptors. The recent discovery of the RdCVF protein has provided researchers with a potential therapy that could slow the secondary wave of cone death. In this work, we build on an existing mathematical model of photoreceptor interactions in the presence of RP and incorporate various treatment regiments via RdCVF. Our results show that an optimal control exists for the administration of RdCVF. In addition, our numerical solutions show the experimentally observed rescue effect that the RdCVF has on the cones

Optimal control with MANF treatment of photoreceptor degeneration

People afflicted with diseases such as retinitis pigmentosa and age-related macular degeneration experience a decline in vision due to photoreceptor degeneration, which is currently unstoppable and irreversible. Currently there is no cure for diseases linked to photoreceptor degeneration. Recent experimental work showed that mesencephalic astrocyte-derived neurotrophic factor (MANF) can reduce neuron death and, in particular, photoreceptor death by reducing the number of cells that undergo apoptosis. In this work, we build on an existing system of ordinary differential equations that represent photoreceptor interactions and incorporate MANF treatment for three experimental mouse models having undergone varying degrees of photoreceptor degeneration. Using MANF treatment levels as controls, we investigate optimal control results in the three mouse models. In addition, our numerical solutions match the experimentally observed surviving percentage of photoreceptors and our uncertainty and sensitivity analysis identifies significant parameters in the math model both with and without MANF treatment

Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae

We investigated the dynamics of a gene regulatory network controlling the cold shock response in budding yeast, Saccharomyces cerevisiae. The medium-scale network, derived from published genome-wide location data, consists of 21 transcription factors that regulate one another through 31 directed edges. The expression levels of the individual transcription factors were modeled using mass balance ordinary differential equations with a sigmoidal production function. Each equation includes a production rate, a degradation rate, weights that denote the magnitude and type of influence of the connected transcription factors (activation or repression), and a threshold of expression. The inverse problem of determining model parameters from observed data is our primary interest. We fit the differential equation model to published microarray data using a penalized nonlinear least squares approach. Model predictions fit the experimental data well, within the 95 % confidence interval. Tests of the model using randomized initial guesses and model-generated data also lend confidence to the fit. The results have revealed activation and repression relationships between the transcription factors. Sensitivity analysis indicates that the model is most sensitive to changes in the production rate parameters, weights, and thresholds of Yap1, Rox1, and Yap6, which form a densely connected core in the network. The modeling results newly suggest that Rap1, Fhl1, Msn4, Rph1, and Hsf1 play an important role in regulating the early response to cold shock in yeast. Our results demonstrate that estimation for a large number of parameters can be successfully performed for nonlinear dynamic gene regulatory networks using sparse, noisy microarray data

HIV-1 Replication Rate

This issue was undated. The date given is an estimate.20 pages, 1 article*HIV-1 Replication Rate* (Arias, Michelle J.; Inguez, Delmy; Camacho, Erika T.; Castillo, Rafael B.; Melon, Eliel; Parra, Luz E.) 20 page

Humanized Mice Recapitulate Key Features of HIV-1 Infection: A Novel Concept Using Long-Acting Anti-Retroviral Drugs for Treating HIV-1

BACKGROUND: Humanized mice generate a lymphoid system of human origin subsequent to transplantation of human CD34+ cells and thus are highly susceptible to HIV infection. Here we examined the efficacy of antiretroviral treatment (ART) when added to food pellets, and of long-acting (LA) antiretroviral compounds, either as monotherapy or in combination. These studies shall be inspiring for establishing a gold standard of ART, which is easy to administer and well supported by the mice, and for subsequent studies such as latency. Furthermore, they should disclose whether viral breakthrough and emergence of resistance occurs similar as in HIV-infected patients when ART is insufficient. METHODS/PRINCIPAL FINDINGS: NOD/shi-scid/γ(c)null (NOG) mice were used in all experimentations. We first performed pharmacokinetic studies of the drugs used, either added to food pellets (AZT, TDF, 3TC, RTV) or in a LA formulation that permitted once weekly subcutaneous administration (TMC278: non-nucleoside reverse transcriptase inhibitor, TMC181: protease inhibitor). A combination of 3TC, TDF and TMC278-LA or 3TC, TDF, TMC278-LA and TMC181-LA suppressed the viral load to undetectable levels in 15/19 (79%) and 14/14 (100%) mice, respectively. In successfully treated mice, subsequent monotherapy with TMC278-LA resulted in viral breakthrough; in contrast, the two LA compounds together prevented viral breakthrough. Resistance mutations matched the mutations most commonly observed in HIV patients failing therapy. Importantly, viral rebound after interruption of ART, presence of HIV DNA in successfully treated mice and in vitro reactivation of early HIV transcripts point to an existing latent HIV reservoir. CONCLUSIONS/SIGNIFICANCE: This report is a unique description of multiple aspects of HIV infection in humanized mice that comprised efficacy testing of various treatment regimens, including LA compounds, resistance mutation analysis as well as viral rebound after treatment interruption. Humanized mice will be highly valuable for exploring the antiviral potency of new compounds or compounds targeting the latent HIV reservoir

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.Peer reviewedFinal Published versio

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

AimComprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW).LocationGlobal.TaxonAll extant mammal species.MethodsRange maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species).ResultsRange maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use.Main conclusionExpert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate