Relative flux trade-offs and optimization of metabolic network functionalities

Trade-offs between traits are present across different levels of biological systems and ultimately reflect constraints imposed by physicochemical laws and the structure of underlying biochemical networks. Yet, mechanistic explanation of how trade-offs between molecular traits arise and how they relate to optimization of fitness-related traits remains elusive. Here, we introduce the concept of relative flux trade-offs and propose a constraint-based approach, termed FluTOr, to identify metabolic reactions whose fluxes are in relative trade-off with respect to an optimized fitness-related cellular task, like growth. We then employed FluTOr to identify relative flux trade-offs in the genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae, and Arabidopsis thaliana. For the metabolic models of E. coli and S. cerevisiae we showed that: (i) the identified relative flux trade-offs depend on the carbon source used and that (ii) reactions that participated in relative trade-offs in both species were implicated in cofactor biosynthesis. In contrast to the two microorganisms, the relative flux trade-offs for the metabolic model of A. thaliana did not depend on the available nitrogen sources, reflecting the differences in the underlying metabolic network as well as the considered environments. Lastly, the established connection between relative flux trade-offs allowed us to identify overexpression targets that can be used to optimize fitness-related traits. Altogether, our computational approach and findings demonstrate how relative flux trade-offs can shape optimization of metabolic tasks, important in biotechnological applications. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.Peer reviewe

Subsidization of substance use treatment: Comparison of methadone maintenance treatment and abstinence-based residential treatment in Iran

Background: Subsidization is a policy to encourage the purchase and use of goods and services and to promote their affordability for the poor. The Welfare Organization of Iran subsidizes substance use treatment in order to increase coverage and adherence to treatment. Objectives: This study aimed to answer the following questions: is the model efficient? Has the policy resulted in increased coverage and higher adherence to substance use treatment? How could the model be improved? Methods: We compared two types of substance use treatments of abstinence-based residential program and outpatient methadone maintenance. Based on their severity of addiction and retention in treatment clients who benefited from subsidization were compared with other clients. Therefore, 109 clients, 78 from methadone maintenance and 31 from residential abstinence-based programs were interviewed. Results: Subsidization had an encouraging effect on clients to enter substance use treatment in both treatment programs (P = 0.001). However, we were unable to find evidence that subsidization helped retention in the treatment (P = 0.389), or that concomitant use of illegal substances in clients on methadone maintenance was lower (P = 0.500). Based on economic status of clients (P = 0.05) their criminal record (P = 0.001), length of use of substances (P = 0.05), and comorbid psychiatric conditions (P = 0.05), it was evident that assignment to subsidization in methadone maintenance services was significantly more reasonable, while it was almost random in abstinence-based residential facilities assignment. Conclusions: The current model of substance use treatment subsidization is not efficient. Addiction severity subscales and socioeconomic status of clients could be considered appropriate factors for assignment to the subsidization program. Copyright © 2020, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited

Acute bone response to whole body vibration in healthy pre-pubertal boys

The skeleton responds to mechanical stimulation. We wished to ascertain the magnitude and speed of the growing skeleton’s response to a standardised form of mechanical stimulation, vibration. 36 prepubertal boys stood for 10 minutes in total on one of two vibrating platforms (high (>2 g) or low (<1 g) magnitude vibration) on either 1, 3 or 5 successive days (n=12 for each duration); 15 control subjects stood on an inactive platform. Blood samples were taken at intervals before and after vibration to measure bone formation (P1NP, osteocalcin) and resorption (CTx) markers as well as osteoprotegerin and sclerostin. There were no significant differences between platform and control groups in bone turnover markers immediately after vibration on days 1, 3 and 5. Combining platform groups, at day 8 P1NP increased by 25.1% (CI 12.3 to 38.0; paired t-test p=0.005) and bone resorption increased by 10.9% (CI 3.6 to 18.2; paired t-test p=0.009) compared to baseline. Osteocalcin, osteoprotogerin and sclerostin did not change significantly. The growing skeleton can respond quickly to vibration of either high or low magnitude. Further work is needed to determine the utility of such “stimulation-testing” in clinical practice

The role of the intensive care unit environment and health-care workers in the transmission of bacteria associated with hospital acquired infections

The goal of this study was to attempt to determine the rate of contamination of health-care workers' (HCWs) hands and environmental surfaces in intensive care units (ICU) by the main bacteria associated with hospital acquired infections (HAIs) in Tehran, Iran. A total of 605 and 762 swab samples were obtained from six ICU environments and HCWs' hands. Identification of the bacterial isolates was performed according to standard biochemical methods, and their antimicrobial susceptibility was determined based on the guidelines recommended by clinical and laboratory standards institute (CLSI). The homology of the resistance patterns was assessed by the NTSYSsp software. The most frequent bacteria on the HCWs' hands and in the environmental samples were Acinetobacter baumannii (1.4 and 16.5, respectively), Staphylococcus aureus (5.9 and 8.1, respectively), S. epidermidis (20.9 and 18.7, respectively), and Enterococcus spp. (1 and 1.3, respectively). Patients' oxygen masks, ventilators, and bed linens were the most contaminated sites. Nurses' aides and housekeepers were the most contaminated staff. Imipenem resistant A. baumannii (94 and 54.5), methicillin-resistant S. aureus (MRSAs, 59.6 and 67.3), and vancomycin resistant Enterococci (VREs, 0 and 25) were detected on the hands of ICU staff and the environmental samples, respectively. Different isolates of S. aureus and Enterococcus spp. showed significant homology in these samples. These results showed contamination of the ICU environments and HCWs with important bacterial pathogens that are the main risk factors for HAIs in the studied hospitals. © 2015 King Saud Bin Abdulaziz University for Health Sciences

Nanopore native RNA sequencing of a human poly(A) transcriptome

High-throughput complementary DNA sequencing technologies have advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and modifications are not retained. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies. Our study generated 9.9 million aligned sequence reads for the human cell line GM12878, using thirty MinION flow cells at six institutions. These native RNA reads had a median length of 771 bases, and a maximum aligned length of over 21,000 bases. Mitochondrial poly(A) reads provided an internal measure of read-length quality. We combined these long nanopore reads with higher accuracy short-reads and annotated GM12878 promoter regions to identify 33,984 plausible RNA isoforms. We describe strategies for assessing 3′ poly(A) tail length, base modifications and transcript haplotypes

Simulation of CZTSSe thin-film solar cells in COMSOL: three-dimensional optical, electrical, and thermal models

The Cu $_2$ ZnSnS $_x$ Se $_{4-x}$ (CZTSSe) thin-film solar cells have attracted the attention of researchers due to its earth-abundant composition containing Copper, Zinc, Tin and Sulfur, and Selenide with 12.6% record efficiency (2013-IBM). A 3-D simulation analysis is presented here on the optical, electrical, and thermal characteristics of CZTSSe solar cell using COMSOL multiphysics 3-D simulation package. COMSOL is capable of calculating the optical–electrical–thermal models through electromagnetic wave, semiconductor, and heat transfer modules for a finely meshed structure. Using this capability, we have calculated the optical photogeneration rate of the a Mo/Mo(S,Se) $_2$ /CZTSSe/CdS/ZnO/ITO/air structure by inserting the refractive index and extinction coefficient of every layer in Wave optic module in COMSOL. We also calculated the total optical generation rate for two structures with and without Mo(S,Se) $_2$ layer at the junction of Mo and CZTSSe layers. The current–voltage curve, electric field profile, and the recombination rate of the cell has also been calculated by Semiconductor module coupled to wave optic module. The current–voltage characteristics show an improvement in $V_{\text{oc}}$ for the cell with Mo(S,Se) $_2$ layer (0.46 to 0.513 V) which was also suggested by IBM for a record cell efficiency. Finally, the thermal maps of the cell has been calculated by heat transfer module coupled to semiconductor module considering the Shockley–Read–Hall (SRH) recombination heat, Joule Heat, and conductive heat flux. The total heat flux magnitude of the cell was also mapped as a result out of these heat generation and cooling sources. The SRH heat is maximum within the depletion width at the CZTSSe/CdS interface, whereas the Joule heating is intensive at the Mo/Mo(S,Se) $_2$ /CZTSSe side. Interesting is to see that the heat is mainly conducted to environment from Mo side presented by the conductive heat map. The total heat flux is intensive at both top and bottom interfaces which means the heat is generated at both top and bottom sides of the cells and not only from the illuminated par

Combination of network and molecule structure accurately predicts competitive inhibitory interactions

Mining of metabolite-protein interaction networks facilitates the identification of design principles underlying the regulation of different cellular processes. However, identification and characterization of the regulatory role that metabolites play in interactions with proteins on a genome-scale level remains a pressing task. Based on availability of high-quality metabolite-protein interaction networks and genome-scale metabolic networks, here we propose a supervised machine learning approach, called CIRI that determines whether or not a metabolite is involved in a competitive inhibitory regulatory interaction with an enzyme. First, we show that CIRI outperforms the naive approach based on a structural similarity threshold for a putative competitive inhibitor and the substrates of a metabolic reaction. We also validate the performance of CIRI on several unseen data sets and databases of metabolite-protein interactions not used in the training, and demonstrate that the classifier can be effectively used to predict competitive inhibitory interactions. Finally, we show that CIRI can be employed to refine predictions about metabolite-protein interactions from a recently proposed PROMIS approach that employs metabolomics and proteomics profiles from size exclusion chromatography in E. coli to predict metabolite-protein interactions. Altogether, CIRI fills a gap in cataloguing metabolite-protein interactions and can be used in directing future machine learning efforts to categorize the regulatory type of these interactions

YASS: Yet Another Spike Sorter

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