Mendelian randomization analyses implicate biogenesis of translation machinery in human aging

Reduced provision of protein translation machinery promotes healthy aging in a number of animal models. In humans, however, inborn impairments in translation machinery are a known cause of several developmental disorders, collectively termed ribosomopathies. Here, we use casual inference approaches in genetic epidemiology to investigate whether adult, tissue-specific biogenesis of translation machinery drives human aging. We assess naturally occurring variation in the expression of genes encoding subunits specific to the two RNA polymerases (Pols) that transcribe ribosomal and transfer RNAs, namely Pol I and III, and the variation in expression of ribosomal protein (RP) genes, using Mendelian randomization. We find each causally associated with human longevity (β = −0.15 ± 0.047, P = 9.6 × 10−4, q = 0.015; β = −0.13 ± 0.040, P = 1.4 × 10−3, q = 0.023; β = −0.048 ± 0.016, P = 3.5 × 10−3, q = 0.056, respectively), and this does not appear to be mediated by altered susceptibility to a single disease. We find that reduced expression of Pol III, RPs, or Pol I promotes longevity from different organs, namely visceral adipose, liver, and skeletal muscle, echoing the tissue specificity of ribosomopathies. Our study shows the utility of leveraging genetic variation in expression to elucidate how essential cellular processes impact human aging. The findings extend the evolutionary conservation of protein synthesis as a critical process that drives animal aging to include humans

Multi-omics insights into host-viral response and pathogenesis in Crimean-Congo hemorrhagic fever viruses for novel therapeutic target.

The pathogenesis and host-viral interactions of the Crimean-Congo hemorrhagic fever orthonairovirus (CCHFV) are convoluted and not well evaluated. Application of the multi-omics system biology approaches, including biological network analysis in elucidating the complex host-viral response, interrogates the viral pathogenesis. The present study aimed to fingerprint the system-level alterations during acute CCHFV-infection and the cellular immune responses during productive CCHFV-replication in vitro. We used system-wide network-based system biology analysis of peripheral blood mononuclear cells (PBMCs) from a longitudinal cohort of CCHF patients during the acute phase of infection and after one year of recovery (convalescent phase) followed by untargeted quantitative proteomics analysis of the most permissive CCHFV-infected Huh7 and SW13 cells. In the RNAseq analysis of the PBMCs, comparing the acute and convalescent-phase, we observed system-level host's metabolic reprogramming towards central carbon and energy metabolism (CCEM) with distinct upregulation of oxidative phosphorylation (OXPHOS) during CCHFV-infection. Upon application of network-based system biology methods, negative coordination of the biological signaling systems like FOXO/Notch axis and Akt/mTOR/HIF-1 signaling with metabolic pathways during CCHFV-infection were observed. The temporal quantitative proteomics in Huh7 showed a dynamic change in the CCEM over time and concordant with the cross-sectional proteomics in SW13 cells. By blocking the two key CCEM pathways, glycolysis and glutaminolysis, viral replication was inhibited in vitro. Activation of key interferon stimulating genes during infection suggested the role of type I and II interferon-mediated antiviral mechanisms both at the system level and during progressive replication

Systems-level temporal immune-metabolic profile in Crimean-Congo hemorrhagic fever virus infection.

Crimean-Congo hemorrhagic fever (CCHF) caused by CCHF virus (CCHFV) is one of the epidemic-prone diseases prioritized by the World Health Organisation as public health emergency with an urgent need for accelerated research. The trajectory of host response against CCHFV is multifarious and remains unknown. Here, we reported the temporal spectrum of pathogenesis following the CCHFV infection using genome-wide blood transcriptomics analysis followed by advanced systems biology analysis, temporal immune-pathogenic alterations, and context-specific progressive and postinfection genome-scale metabolic models (GSMM) on samples collected during the acute (T0), early convalescent (T1), and convalescent-phase (T2). The interplay between the retinoic acid-inducible gene-I-like/nucleotide-binding oligomerization domain-like receptor and tumor necrosis factor signaling governed the trajectory of antiviral immune responses. The rearrangement of intracellular metabolic fluxes toward the amino acid metabolism and metabolic shift toward oxidative phosphorylation and fatty acid oxidation during acute CCHFV infection determine the pathogenicity. The upregulation of the tricarboxylic acid cycle during CCHFV infection, compared to the noninfected healthy control and between the severity groups, indicated an increased energy demand and cellular stress. The upregulation of glycolysis and pyruvate metabolism potentiated energy generation through alternative pathways associated with the severity of the infection. The downregulation of metabolic processes at the convalescent phase identified by blood cell transcriptomics and single-cell type proteomics of five immune cells (CD4+ and CD8+ T cells, CD14+ monocytes, B cells, and NK cells) potentially leads to metabolic rewiring through the recovery due to hyperactivity during the acute phase leading to post-viral fatigue syndrome

Engineering Education Considering Environmental Issues: Development of Holistic (Ecological) Paradigm

The education of engineers, who are aware of today’s challenges and future opportunities, plays an important role in economical and social development of different societies. The current engineering education system tries to increase professional engineering knowledge in related fields and does not consider the side effects of engineering activities which commonly impact the environment. This thinking structure, called the Newtonian paradigm is vertical thinking based on linear and sequential phenomena. In the Newtonian paradigm, the engineering education program is developed on the basis of maximum usage of available environmental opportunities and control of natural events. In time, the undesirable effects of this engineering paradigm on the environment become visible and also some signs of un-sustainability in engineering systems appear to make some problems in the long time performance of these systems. These impacts force the engineering education system to develop engineering knowledge and pay more attention to the environment. The holistic paradigm has been developed in response to these requirements. The holistic paradigm is based on parallel and non-linear phenomena. In this paradigm in addition to increasing professional knowledge, engineers are made familiar with the interactions between engineering activities and the environment. This way the maximum profit will be obtained from available opportunities and also the engineering activity impacts are minimized. In this paper the paradigm shift trend and its future vision in engineering education and its effects on the development

Development of an algorithm for risk-based management of wastewater reuse alternatives

Due to water resources limitations, special attention has been paid to wastewater reuse in recent years. The risks associated with wastewater reuse alternatives should be considered in decision-making. Even when selecting the alternative with the least risk, risk management issues are of high importance. This study aims to develop an algorithm for risk-based management of wastewater reuse alternatives. This algorithm uses a three-step risk assessment and management approach. Risks are identified, then risks of alternatives are assessed, and, finally, risk management measures are proposed for risk reduction in the selected alternative. In risk identification, economic, social, health, and environmental aspects are taken into account. In risk assessment, its three components of likelihood, severity, and vulnerability are considered through a fuzzy inference system. Alternatives are prioritized based on calculated risks using a fuzzy VIKOR method. A case study is presented in which the proposed algorithm is used to select the best alternative for reuse of treated wastewater from Ekbatan Town, located in the western part Tehran in Iran. The results showed that the proposed approach provides the users with an easier understanding of risks and increases the relative confidence of decision-makers about the selection of the best alternatives for wastewater reuse and their risk control methods

Development of a Reliability Based Dynamic Model of Urban Water Supply System: A Case Study

Dramatic population growth in urban areas with limited water resources with adequate quality and quantity especially in arid and semi-arid areas have resulted in increasing tensions in a reliable water supply. Growth and change of a comprehensive water supply system makes the complex relationship among system\u27s components more sensitive to the operating policies. All changing factors and variables should be considered in system operation in order to provide an understanding of system performance over time to provide reliable urban water supply schemes toward its improvement. In this study, systems dynamic modeling approach is used to simulate the system behavior through time at an integrated fashion. The simplified water supply system of Tehran metropolitan area, the capital of Iran, has been considered as the case study of this paper. The considered water supply system consists of several components which are connected with complicated interactions to satisfy water demands such as drinking water, agricultural farming and industrial requirements as well as many other possible needs. Reliability of this system is evaluated. The results of the developed model can be used as an indicator of the system\u27s state to decide about the implementation of system rehabilitation and reconstruction projects

Optimum reliable operation of water distribution networks by minimising energy cost and chlorine dosage

In recent decades much attention has been paid to optimal operation of water distribution networks (WDNs). In this regard, the system operation costs, including energy and disinfection chemicals, as well as system reliability should be simultaneously considered in system performance optimisation, to provide the minimum required level of performance in failure condition and to manage economic limitations. In this study, multi-objective optimisation of water distribution network performance in 3 different scenarios was considered. In these scenarios the effects of time-dependent chlorine injection and pump speed, as well as different combinations of objective functions for minimising energy and disinfection costs and for maximising hydraulic reliability and quality-based reliability are incorporated. As the optimisation method, a multi-objective ant colony optimisation (ACO) algorithm was used because of its high efficiency. For better managing the hydraulic behaviour and water quality in the WDN, considering temporal variations of demand, it is suggested to use variable speed pumps (VSP) as well as to inject chlorine at a variable rate. Application of VSP and time-dependent chlorine injection results in improvements such as reduction in energy and disinfection costs, and decrease in disinfection costs in application of HDSM (head-driven simulation method). In HDSM simulation of WDN, a decrease in hydraulic reliability because of shortages in water supply can be mitigated through extra chlorine injection and increase in quality-based reliability. To deal with this challenge, it is recommended to satisfy the hydraulic reliability first and then to evaluate the quality reliability. Furthermore it is necessary to modify the hydraulic reliability relationship to incorporate different components of the WDN other than pumps. This will provide more reliable results for evaluation of the system performance

Reliability Assessment of the Water Supply Systems under Uncertain Future Extreme Climate Conditions

Increase in global mean temperature and changes in rainfall amount, pattern, and distribution over the world are all indicative of climate change events. These changes alter the hydroclimatic condition of regions as well as the availability of water resources. In this study, the data generated by 14 general circulation models (GCMs) developed under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B2 are downscaled and utilized to evaluate climate change impact on the hydroclimatic system of the Karaj River basin located in central Iran. The precipitation and temperature of the study region are downscaled using the change factor approach (CFA). The study analyzes future climate data, extreme changes of future climatic conditions of precipitation, and temperature. The Hydrologiska Byråns Vattenbalansavdelning (HBV) model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is used to simulate streamflow under extreme climate change conditions. Two different sources of uncertainty are investigated in this study. First, the model parameters uncertainty is analyzed with the Monte Carlo procedure, and then different datasets of GCMs projection are investigated under the climate of the twentieth-century climate simulation (20C3M). Results show the GCMs projections range can almost capture the historical records during the 1980s through 2000 for the Karaj basin. By applying the HBV model, considerable range of streamflow changes in the future can be projected that will affect the operation scheme of Karaj Reservoir. In this study, the system dynamics (SD) modeling approach is used to simulate the system behavior through time in an integrated fashion and evaluate its overall reliability in supplying water. The results of this study show that the runoff will decrease in the future under the climate change impact. This will result in more than 50% decrease in reliability of the Karaj Reservoir system under the extreme conditions. As a result, this research predicts that the Karaj Reservoir system will face more than 50% decrease in its reliability under the extreme conditions. Consequently, meeting the increasing water demands would be difficult and application of demand management strategies will be unavoidable

Determining the robust optimal set of BMPs for urban runoff management in data-poor catchments

<p>Mismanagement of urban runoff can result in inundation which causes serious problems in providing urban services. Best management practices (BMPs) are used for urban runoff management. In this study, a method is proposed to determine the robust optimal set of BMPs for runoff management in data-poor catchments in urban areas. This method includes five main steps: (1) Sensitivity analysis to determine effective parameters in rainfall-runoff simulation model, (2) Calibration of the rainfall-runoff model based on selected effective parameters, (3) Developing a multi-objective optimization model to obtain the optimal sets of BMPs, (4) Selecting the final solutions using the Nash approach for ranking, (5) Evaluation of the robustness of the selected solution using the Management Option Rank Equivalence method. The proposed method is examined in an urban basin located in the north of Tehran, Iran. The results show that the proposed approach provides reliable results for urban runoff management in data-poor areas.</p