Lin28A induces energetic switching to glycolytic metabolism in human embryonic kidney cells

Background: Loss of a cell’s capacity to generate sufficient energy for cellular functions is a key hallmark of the ageing process and ultimately leads to a variety of important age-related pathologies such as cancer, Parkinson’s disease and atherosclerosis. Regenerative medicine has sought to reverse these pathologies by reprogramming somatic cells to a more juvenile energetic state using a variety of stem cell factors. One of these factors, Lin28, is considered a candidate for modification in the reprogramming of cellular energetics to ameliorate the ageing process while retaining cell phenotype. Results: Over-expression of Lin28A resulted in key changes to cellular metabolism not observed in wild-type controls. Extracellular pH flux analysis indicated that Lin28A over expression significantly increased the rate of glycolysis, whilst high resolution oxygen respirometry demonstrated a reduced oxygen consumption. Western blot and real-time PCR analysis identified Hexokinase II as one of the key modulators of glycolysis in these cells which was further confirmed by increased glucose transport. A metabolic switching effect was further emphasised by Western blot analysis where the oxygen consuming mitochondrial complex IV was significantly reduced after Lin28A over expression. Conclusions: Results from this study confirm that Lin28A expression promotes metabolic switching to a phenotype that relies predominantly on glycolysis as an energy source, while compromising oxidative phosphorylation. Mechanisms to augment regulated Lin28A in age related pathologies that are characterised by mitochondria dysfunction or in differentiated and aged post-mitotic cells is the future goal of this work

Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure

Optimized lockdown strategies for curbing the spread of COVID-19: A South African case study

To curb the spread of COVID-19, many governments around the world have implemented tiered lockdowns with varying degrees of stringency. Lockdown levels are typically increased when the disease spreads and reduced when the disease abates. A predictive control approach is used to develop optimized lockdown strategies for curbing the spread of COVID-19. The strategies are then applied to South African data. The South African case is of interest as the South African government has defined five distinct levels of lockdown, which serves as a discrete control input. An epidemiological model for the spread of COVID-19 in South Africa was previously developed, and is used in conjunction with a hybrid model predictive controller to optimize lockdown management under different policy scenarios. Scenarios considered include how to flatten the curve to a level that the healthcare system can cope with, how to balance lives and livelihoods, and what impact the compliance of the population to the lockdown measures has on the spread of COVID-19. The main purpose of this paper is to show what the optimal lockdown level should be given the policy that is in place, as determined by the closed-loop feedback controller.Comment: 11 pages, 7 figures, 4 table

An industrial implementation of a C4 hydrocarbon soft sensor to optimise a debutaniser column

The bottoms product of a debutaniser column in a Fischer-Tropsch refining catpoly unit should be maximised to ensure optimal operation of the downstream units. An accurate estimate of the C4 hydrocarbons in the bottoms product is required to ensure that the specification is not violated. This work demonstrates a practical implementation of a soft sensor to estimate the %C4 material in the bottoms product of the debutaniser using the General Distillation Shortcut (GDS) method and a random forest (RF) machine learned model. The paper highlights practical challenges when deploying a soft sensor to an industrial plant. It is shown how the GDS method soft sensor had to be refitted after unit maintenance was carried out. In comparison the RF model soft sensor uses more reliable measurements and did not require refitting after unit commissioning. Both soft sensors performed well and the choice of soft sensor depends on the available measurements and measurement reliability.https://www.journals.elsevier.com/ifac-papersonlineam2022Electrical, Electronic and Computer Engineerin

2,2,7-Trichloro-3,4-dihydro­naphthalen-1(2H)-one

The title compound, C10H7Cl3O, obtained as a major byproduct from a classical Schmidt reaction. The cyclohexyl ring is distorted from a classical chair conformation, as observed for monocyclic analogues, presumably due to conjugation of the planar annulated benzo ring and the ketone group (r.m.s. deviation 0.024 Å). There are no significant intermolecular interactions

Energy reduction for a dual circuit cooling water system using advanced regulatory control

Various process utilities are used in the petrochemical industry as auxiliary variables to facilitate the addition/removal of energy to/from the process, power process equipment and inhibit unwanted reaction. Optimisation activities usually focus on the process itself or on the utility consumption though the generation and distribution of these utilities are often overlooked in this regard. Many utilities are prepared or generated far from the process plant and have to be transported or transmitted, giving rise to more losses and potential inefficiencies. To illustrate the potential benefit of utility optimisation, this paper explores the control of a dual circuit cooling water system with focus on energy reduction subject process constraints. This is accomplished through the development of an advanced regulatory control (ARC) and switching strategy which does not require the development of a system model, only rudimentary knowledge of the behaviour of the process and system constraints. The novelty of this manuscript lies in the fact that it demonstrates that significant energy savings can be obtained by applying ARC to a process utility containing both discrete and continuous dynamics. Furthermore, the proposed ARC strategy does not require a plant model, uses only existing plant equipment, and can be implemented on control system hardware commonly used in industry. The simulation results indicate energy saving potential in the region of 30% on the system under investigation.http://www.elsevier.com/locate/apenergy2017-06-30hb2016Electrical, Electronic and Computer Engineerin

Disturbance propagation through a grinding-flotation circuit

The propagation of common disturbances in a grinding circuit connected to a flotation circuit and the effects of these disturbances on flotation cell levels were simulated and analysed. The disturbances include changes in the mineral ore feed as well as a step change in the cyclone operating condition and spillage water added to the sump. The effect of the disturbances on the cell levels remains relatively small, but it is clear that multivariable control is required to prevent the propagation of the disturbances through the cells. The simulation of a grinding-flotation circuit is useful to simulate the effects of disturbance propagation and will be helpful when designing plant-wide controllers.This work is based on research supported by the National Research Foundation of South Africa (Grant number 130380).https://www.journals.elsevier.com/ifac-papersonlineam2022Electrical, Electronic and Computer Engineerin

Nonlinear model predictive control for improved water recovery and throughput stability for tailings reprocessing

The reprocessing of tailings aims to recover residual wealth, reclaim or rehabilitate valuable land, or mitigate safety and environmental risks. These aims all support environmental, social, and governance measures that are increasingly placed at the centre of corporate strategy. Tailings reprocessing operations are water intensive, and typically include surge tanks with both level and density averaging objectives to improve the efficiency of downstream water and mineral recovery. In this study, a rigorous dynamic model is derived to describe the rate of change of both the volume and density in these surge tanks. By simulation with industrial data it is demonstrated that the significant input disturbances typical to tailings reprocessing circuits drive a gain inversion in the density model of the surge tank. Since conventional linear averaging control approaches are not ideally suited to deal with gain inversion and multivariable control objectives a nonlinear model predictive controller (NMPC) was derived and implemented on an industrial tailings reprocessing surge tank. Results show a 5 % improvement in water recovery from the plant tailings product, and a 27 % reduction in the standard deviation of the tailings product mass flow.http://www.elsevier.com/locate/conengprachj2023Electrical, Electronic and Computer Engineerin

Evaporation, seepage and water quality management in storage dams: a review of research methods

One of the most significant sources of water wastage in Australia is loss from small storage dams, either by seepage or evaporation. Over much of Australia, evaporative demand routinely exceeds precipitation. This paper outlines first, methodologies and measurement techniques to quantify the rate of evaporative loss from fresh water storages. These encompass high-accuracy water balance monitoring; determination of the validity of alternative estimation equations, in particular the FAO56 Penman- Monteith ETo methodology; and the commencement of CFD modeling to determine a 'dam factor' in relation to practical atmospheric measurement techniques. Second, because the application of chemical monolayers is the only feasible alternative to the high cost of physically covering the storages to retard evaporation, the use of cetyl alcohol-based monolayers is reviewed, and preliminary research on their degradation by photolytic action, by wind break-up and by microbial degradation reported. Similarly, preliminary research on monolayer visualisation techniques for field application is reported; and potential enhancement of monolayers by other chemicals and attendant water quality issues are considered

Extremum seeking control for optimization of an open-loop grinding mill using grind curves

A semi-autogenous grinding mill is simulated with gradient and non-gradient based extremum seeking controllers to maximize the mill performance using grind curves. Grind curves map the essential performance measures of a grinding mill to the mill load and rotational speed. The curves vary with the changes in the feed ore characteristic but show generic parabolic features with extremums. The extremum seeking controllers search along the unknown input–output map to steer the process towards an unknown optimum. In this study, a classical perturbation-based method, a time-varying parameter estimation-based method and the Nelder–Mead simplex method are employed as extremum seeking control (ESC) methods to search along the grind curves to either optimize the mill throughput or grind by means of manipulating the mill feed or rotational speed. The proposed extremum seeking controller could reduce the need for a plant operator to manually select the optimal operating conditions that maximize the performance measures of a grinding mill. Since the controller is agnostic to the process model, the grinding mill can be optimized without the need for a detailed process model. The simulated results show that the extremum seeking controllers steer the mill operating conditions toward the steady-state optimum and can be used to satisfy operational objectives. However, the slow grinding mill dynamics result in a long convergence rate when the initial conditions are far from the optimal operating conditions.The National Research Foundation of South Africa.http://www.elsevier.com/locate/jproconthj2022Electrical, Electronic and Computer Engineerin