Morphological and Structural Aspects of the Extremely Halophilic Archaeon Haloquadratum walsbyi

Ultrathin square cell Haloquadratum walsbyi from the Archaea domain are the most abundant microorganisms in the hypersaline water of coastal salterns and continental salt lakes. In this work, we explore the cell surface of these microorganisms using amplitude-modulation atomic-force microscopy in nearly physiological conditions. We demonstrate the presence of a regular corrugation with a periodicity of 16–20 nm attributed to the surface layer (S-layer) protein lattice, striped domains asymmetrically distributed on the cell faces and peculiar bulges correlated with the presence of intracellular granules. Besides, subsequent images of cell evolution during the drying process indicate the presence of an external capsule that might correspond to the giant protein halomucin, predicted by the genome but never before observed by other microscopy studies

Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study

GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Background The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. Methods This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions’ range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. Results The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Conclusion Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system

Imaging of hydrothermal altered zones in Wadi Al-Bana, in southern Yemen, using remote sensing techniques and very low frequency–electromagnetic data

© 2019, Saudi Society for Geosciences. Economic mineralization and hydrothermally altered zones are areas of great economic interests. This study focusses on hydrothermal altered zones of high mineralization potentials in Wadi Al-Bana, in southern Yemen. An azimuthal very low frequency–electromagnetic (AVLF-EM) data acquisition was conducted in search for mineralization in the study area. The study integrated observations from geophysical field data with others extracted from object-oriented principal component analysis (PCA) to better map and understand mineralization in the investigated area. This technique was applied to two data sets, ASTER and Landsat 8 Operational Land Imager (OLI) imagery. The results of PCA revealed high accuracy in detecting alteration minerals and for mapping zones of high concentration of these minerals. The PCA-based distribution of selected alteration zones correlated spatially with high conductivity anomalies in the subsurface that were detected by VLF measurements. Finally, a GIS model was built and successfully utilized to categorize the resulted altered zones, into three levels. [Figure not available: see fulltext.]

Acetylation Regulates WRN Catalytic Activities and Affects Base Excision DNA Repair

Background: The Werner protein (WRN), defective in the premature aging disorder Werner syndrome, participates in a number of DNA metabolic processes, and we have been interested in the possible regulation of its function in DNA repair by post-translational modifications. Acetylation mediated by histone acetyltransferases is of key interest because of its potential importance in aging, DNA repair and transcription. Methodology/Principal Findings: Here, we have investigated the p300 acetylation mediated changes on the function of WRN in base excision DNA repair (BER). We show that acetylation of WRN increases in cells treated with methyl methanesulfonate (MMS), suggesting that acetylation of WRN may play a role in response to DNA damage. This hypothesis is consistent with our findings that acetylation of WRN stimulates its catalytic activities in vitro and in vivo, and that acetylated WRN enhances pol b-mediated strand displacement DNA synthesis more than unacetylated WRN. Furthermore, we show that cellular exposure to the histone deacetylase inhibitor sodium butyrate stimulates long patch BER in wild type cells but not in WRN depleted cells, suggesting that acetylated WRN participates significantly in this process. Conclusion/Significance: Collectively, these results provide the first evidence for a specific role of p300 mediated WRN acetylation in regulating its function during BER

Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps

A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km). Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes). For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis) these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The “additive” model assumes no interaction; the “minimax” model assumes maximum relative risk due to any vector in a cell; and the “competitive exclusion” model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

BACKGROUND: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. METHODS AND FINDINGS: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. CONCLUSIONS: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior

Host Immune Responses to a Viral Immune Modulating Protein: Immunogenicity of Viral Interleukin-10 in Rhesus Cytomegalovirus-Infected Rhesus Macaques

, consistent with a central role for rhcmvIL-10 during acute virus-host interactions. Since cmvIL-10 and rhcmvIL-10 are extremely divergent from the cIL-10 of their respective hosts, vaccine-mediated neutralization of their function could inhibit establishment of viral persistence without inhibition of cIL-10.As a prelude to evaluating cmvIL-10-based vaccines in humans, the rhesus macaque model of HCMV was used to interrogate peripheral and mucosal immune responses to rhcmvIL-10 in RhCMV-infected animals. ELISA were used to detect rhcmvIL-10-binding antibodies in plasma and saliva, and an IL-12-based bioassay was used to quantify plasma antibodies that neutralized rhcmvIL-10 function. rhcmvIL-10 is highly immunogenic during RhCMV infection, stimulating high avidity rhcmvIL-10-binding antibodies in the plasma of all infected animals. Most infected animals also exhibited plasma antibodies that partially neutralized rhcmvIL-10 function but did not cross-neutralize the function of rhesus cIL-10. Notably, minimally detectable rhcmvIL-10-binding antibodies were detected in saliva.This study demonstrates that rhcmvIL-10, as a surrogate for cmvIL-10, is a viable vaccine candidate because (1) it is highly immunogenic during natural RhCMV infection, and (2) neutralizing antibodies to rhcmvIL-10 do not cross-react with rhesus cIL-10. Exceedingly low rhcmvIL-10 antibodies in saliva further suggest that the oral mucosa, which is critical in RhCMV natural history, is associated with suboptimal anti-rhcmvIL-10 antibody responses

Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3

Background: Sustainable Development Goal (SDG) 3 aims to “ensure healthy lives and promote well-being for all at all ages”. While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available. Methods: We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in 106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from 1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until 2030. We report all spending estimates in inflation-adjusted 2019 US$, unless otherwise stated. Findings: Since the development and implementation of the SDGs in 2015, global health spending has increased, reaching$7·9 trillion (95% uncertainty interval 7·8–8·0) in 2017 and is expected to increase to $11·0 trillion (10·7–11·2) by 2030. In 2017, in low-income and middle-income countries spending on HIV/AIDS was$20·2 billion (17·0–25·0) and on tuberculosis it was $10·9 billion (10·3–11·8), and in malaria-endemic countries spending on malaria was$5·1 billion (4·9–5·4). Development assistance for health was $40·6 billion in 2019 and HIV/AIDS has been the health focus area to receive the highest contribution since 2004. In 2019,$374 million of DAH was provided for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis, and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence, and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to increase from 81·6% (81·6–81·7) in 2015 to 83·1% (82·8–83·3) in 2030. Interpretation: Health spending on SDG3 priority areas has increased, but not in all countries, and progress towards meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do not always results in improvements in outcomes. Although countries will probably need more resources to achieve SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be addressed. Funding: The Bill & Melinda Gates Foundatio