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Biological information processing is generally assumed to be classical. Measured cellular energy budgets of both prokaryotes and eukaryotes, however, fall orders of magnitude short of the power required to maintain classical states of protein conformation and localization at the Å, fs scales predicted by single-molecule decoherence calculations and assumed by classical molecular dynamics models. We suggest that decoherence is limited to the immediate surroundings of the cell membrane and of intercompartmental boundaries within the cell, and that bulk cellular biochemistry implements quantum information processing. Detection of Bell-inequality violations in responses to perturbation of recently-separated sister cells would provide a sensitive test of this prediction. If it is correct, modeling both intra- and intercellular communication requires quantum theory., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Phosphate homeostasis is a requirement for normal life. Phosphate is involved in the synthesis of membrane lipids, DNA, RNA, and energy-rich molecules (ATP and GTP), and the regulation of protein activity by phosphorylation/dephosphorylation. Moreover, phosphate is a component of apatite crystals, which provide stability to the bone, and is essential for normal growth. Phosphate balance in the body is the difference between net phosphate absorption through the intestine and phosphate excretion through the kidney. Numerous disorders, both genetic and acquired, may alter phosphate homeostasis. In affected individuals, it is crucial to identify the underlying mechanism(s) to provide adequate treatment; however, phosphate homeostasis assessment remains challenging. Besides the measurement of key hormones involved in the control of phosphate homeostasis (parathyroid hormone, vitamin D and metabolites, fibroblast growth factor 23), assessing the magnitude of phosphate reabsorption by the kidney is a crucial step. It makes it possible to distinguish between a primary disorder of renal phosphate reabsorption, associated with an intrinsic defect or endocrine disturbance, and a nutritional cause of phosphate deficiency. This strategy is described, and the potential consequences for therapeutic decisions are discussed., (Copyright © 2021. Published by Elsevier Masson SAS.)

Background: Coronavirus Disease 2019 (COVID-19) has variable clinical presentation, from asymptomatic to severe disease leading to death. Biochemical markers may help with management and prognostication of COVID-19 patients; however, their utility is still under investigation., Methods: A retrospective study was conducted to evaluate alanine aminotransferase, C-reactive protein (CRP), ferritin, lactate, and high sensitivity troponin T (TnT) levels in 67 patients who were admitted to a Canadian tertiary care centre for management of COVID-19. Logistic, cause-specific Cox proportional-hazards, and accelerated failure time regression modelling were performed to assess the associations of initial analyte concentrations with in-hospital death and length of stay in hospital; joint modelling was performed to assess the associations of the concentrations over the course of the hospital stay with in-hospital death., Results: Initial TnT and CRP concentrations were associated with length of stay in hospital. Eighteen patients died (27%), and the median initial TnT concentration was higher in patients who died (55 ng/L) than those who lived (16 ng/L; P < 0.0001). There were no survivors with an initial TnT concentration > 64 ng/L. While the initial TnT concentration was predictive of death, later measurements were not. Only CRP had prognostic value with both the initial and subsequent measurements: a 20% increase in the initial CRP concentration was associated with a 14% (95% confidence interval (CI): 1-29%) increase in the odds of death, and the hazard of death increased 14% (95% CI: 5-25%) for each 20% increase in the current CRP value. While the initial lactate concentration was not predictive of death, subsequent measurements were., Conclusion: CRP, lactate and TnT were associated with poorer outcomes and appear to be useful biochemical markers for monitoring COVID-19 patients., (Copyright © 2021. Published by Elsevier Inc.)

Background: It was shown that single repetition, contraction-phase specific and total time-under-tension (TUT) can be extracted reliably and validly from smartphone accelerometer-derived data of resistance exercise machines using user-determined resistance exercise velocities at 60% one repetition maximum (1-RM). However, it remained unclear how robust the extraction of these mechano-biological descriptors is over a wide range of movement velocities (slow- versus fast-movement velocity) and intensities (30% 1-RM versus 80% 1-RM) that reflect the interindividual variability during resistance exercise., Objective: In this work, we examined whether the manipulation of velocity or intensity would disrupt an algorithmic extraction of single repetitions, contraction-phase specific and total TUT., Methods: Twenty-seven participants performed four sets of three repetitions of their 30% and 80% 1-RM with velocities of 1 s, 2 s, 6 s and 8 s per repetition, respectively. An algorithm extracted the number of repetitions, single repetition, contraction-phase specific and total TUT. All exercises were video-recorded. The video recordings served as the gold standard to which algorithmically-derived TUT was compared. The agreement between the methods was examined using Limits of Agreement (LoA). The Pearson correlation coefficients were used to calculate the association, and the intraclass correlation coefficient (ICC 2.1) examined the interrater reliability., Results: The calculated error rate for the algorithmic detection of the number of single repetitions derived from two smartphones accelerometers was 1.9%. The comparison between algorithmically-derived, contraction-phase specific TUT against video, revealed a high degree of correlation (r > 0.94) for both exercise machines. The agreement between the two methods was high on both exercise machines, intensities and velocities and was as follows: LoA ranged from -0.21 to 0.22 seconds for single repetition TUT (2.57% of mean TUT), from -0.24 to 0.22 seconds for concentric contraction TUT (6.25% of mean TUT), from -0.22 to 0.24 seconds for eccentric contraction TUT (5.52% of mean TUT) and from -1.97 to 1.00 seconds for total TUT (5.13% of mean TUT). Interrater reliability for single repetition, contraction-phase specific TUT was high (ICC > 0.99)., Conclusion: Neither intensity nor velocity disrupts the proposed algorithmic data extraction approach. Therefore, smartphone accelerometers can be used to extract scientific mechano-biological descriptors of dynamic resistance exercise with intensities ranging from 30% to 80% of the 1-RM with velocities ranging from 1 s to 8 s per repetition, respectively, thus making this simple method a reliable tool for resistance exercise mechano-biological descriptors extraction., Competing Interests: Kieser Training AG provided support in the form of salaries for author DA, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. ieffects AG provided support in the form of salaries for author BA, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Photosynthesis is not only essential for plants, but it also sustains life on Earth. Phytohormones play crucial roles in developmental processes, from organ initiation to senescence, due to their role as growth and developmental regulators, as well as their central role in the regulation of photosynthesis. Furthermore, phytohormones play a major role in photoprotection of the photosynthetic apparatus under stress conditions. Here, in addition to discussing our current knowledge on the role of the phytohormones auxin, cytokinins, gibberellins, and strigolactones in promoting photosynthesis, we will also highlight the role of abscisic acid beyond stomatal closure in modulating photosynthesis and photoprotection under various stress conditions through crosstalk with ethylene, salicylates, jasmonates, and brassinosteroids. Furthermore, the role of phytohormones in controlling the production and scavenging of photosynthesis-derived reactive oxygen species, the duration and extent of photo-oxidative stress and redox signaling under stress conditions will be discussed in detail. Hormones have a significant impact on the regulation of photosynthetic processes in plants under both optimal and stress conditions, with hormonal interactions, complementation, and crosstalk being important in the spatiotemporal and integrative regulation of photosynthetic processes during organ development at the whole-plant level., (© The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

Insulin-like growth factor-binding protein (IGFBP)-2 is a circulating biomarker of cardiometabolic health. Here, we report that circulating IGFBP-2 concentrations robustly increase after different bariatric procedures in humans, reaching higher levels after biliopancreatic diversion with duodenal switch (BPD-DS) than after Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG). This increase is closely associated with insulin sensitization. In mice and rats, BPD-DS and RYGB operations also increase circulating IGFBP-2 levels, which are not affected by SG or caloric restriction. In mice, Igfbp2 deficiency significantly impairs surgery-induced loss in adiposity and early improvement in insulin sensitivity but does not affect long-term enhancement in glucose homeostasis. This study demonstrates that the modulation of circulating IGFBP-2 may play a role in the early improvement of insulin sensitivity and loss of adiposity brought about by bariatric surgery., Competing Interests: A.C.C. has received consultant fees from Janssen (2017 and 2018), Novartis (2018), Novo Nordisk (2018), HLS Therapeutics (2019), and Eli Lilly (2020). A.-M.C. has received consultant fees from Pfizer (2017). A.T. received consulting fees from Novo Nordisk and Bausch Health. A.T. and L.B. are the recipients of research grant support from Johnson & Johnson Medical Companies and Medtronic for studies on bariatric surgery and the Research Chair in Bariatric and Metabolic Surgery, respectively, at l’Institut Universitaire de Cardiologie et de Pneumologie de Québec (IUCPQ) and Laval University. All of the other authors reported no competing financial interests in relation to the work described herein., (© 2021 The Author(s).)

Ethnopharmacological Relevance: Many species within the family Combretaceae are popular medicinal plants that are used traditionally to treat various conditions, of which many are related to bacterial infections. Global concerns regarding the increasing resistance of pathogens towards currently available antibiotics have encouraged researchers to find new drugs with antibacterial activity, particularly from plant sources., Aim of the Study: This study was aimed at exploring the broad-spectrum antibacterial potential of methanol extracts of species representing four genera of Combretaceae (Combretum, Pteleopsis, Quisqualis, Terminalia), indigenous to South Africa, using a biochemometric approach., Materials and Methods: The microdilution assay was used to determine the antibacterial activities, measured as minimum inhibitory concentrations (MICs), of the 51 methanol extracts representing 35 Combretaceae species, against nine species of pathogenic bacteria. Integrative biochemometric analysis was performed, thereby correlating the MIC values with the metabolomic data obtained from ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) analysis. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models were constructed for six pathogens displaying variation in their susceptibility towards the extracts., Results: Evaluation of the overall MIC values obtained indicated that extracts of species from the four genera displayed the highest activity towards Bacillus cereus ATCC 11778 (average MIC 0.52 mg/mL) and Salmonella typhimurium ATCC 14028 (average MIC 0.63 mg/mL). These bacteria were the most sensitive Gram-positive and Gram-negative bacteria, respectively. Extracts from Combretum acutifolium, Combretum imberbe and Combretum elaeagnoides were the most active, with average MIC values of 0.70 mg/mL, 0.52 mg/mL and 0.45 mg/mL, respectively. Five triterpenoid compounds were tentatively identified as biomarkers from the biochemometric analysis., Conclusion: Correlation of the phytochemistry of species from four genera in the Combretaceae family with antibacterial activity revealed that triterpenoids are responsible for the broad-spectrum antibacterial activity observed., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In 2019 California's Office of Environmental Health Hazard Assessment (OEHHA) initiated a review of the carcinogenic hazard potential of acetaminophen. In parallel with this review, herein we evaluated the mechanistic data related to the steps and timing of cellular events following therapeutic recommended (≤4 g/day) and higher doses of acetaminophen that may cause hepatotoxicity to evaluate whether these changes indicate that acetaminophen is a carcinogenic hazard. At therapeutic recommended doses, acetaminophen forms limited amounts of N-acetyl-p-benzoquinone-imine (NAPQI) without adverse cellular effects. Following overdoses of acetaminophen, there is potential for more extensive formation of NAPQI and depletion of glutathione, which may result in mitochondrial dysfunction and DNA damage, but only at doses that result in cell death - thus making it implausible for acetaminophen to induce the kind of stable, genetic damage in the nucleus indicative of a genotoxic or carcinogenic hazard in humans. The collective data demonstrate a lack of a plausible mechanism related to carcinogenicity and are consistent with rodent cancer bioassays, epidemiological results reviewed in companion manuscripts in this issue, as well as conclusions of multiple international health authorities., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Continuous-time stationary Markov jump processes among discrete sites are encountered in disparate biochemical ambits. Sites and connecting dynamical events form a 'network' in which the sites are the available system's states, and the events are site-to-site transitions, or even neutral processes in which the system does not change site but the event is however detectable. Examples include conformational transitions in single biomolecules, stochastic chemical kinetics in the space of the molecules copy numbers, and even macroscopic steady-state reactive mixtures if one adopts the viewpoint of a tagged molecule (or even of a molecular moiety) whose state may change when it is involved in a chemical reaction. Among the variety of dynamical descriptors, here we focus on the first occurrence times (starting from a given site) and on the recurrence times of an event of interest. We develop the sensitivity analysis for the lowest moments of the statistical distribution of such times with respect to the rate constants of the network. In particular, simple expressions and inequalities allow us to establish a direct relationship between selective variation of rate constants and effect on average times and variances. As illustrative cases we treat the substrate inhibition in enzymatic catalysis in which a tagged enzyme molecule jumps between three states, and the basic two-site model of stochastic gene expression in which the single gene switches between active and inactive forms., Competing Interests: Declaration of Competing Interest The author declares that he has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Inc. All rights reserved.)

In this chapter, we provide a practical guide on how to plan, execute, and interpret atomistic and coarse-grained molecular dynamics (MD) simulations of lipid-modified proteins in model membranes. After outlining some key practical considerations when planning such simulations, we survey resources and techniques to obtain force field parameters for nonconventional amino acids, such as posttranslationally lipid-modified amino acids that are unique to this class of proteins. We then describe the protocols to build, setup, and run the simulations, followed by a brief comment on the analysis and interpretation of the simulations. Finally, examples of insights that could be gained from atomistic and coarse-grained MD simulations of lipidated proteins will be provided, using RAS proteins as illustrative examples. Throughout the chapter, we highlight the main advantages and limitations of simulating RAS and related lipid-modified G-proteins in biomimetic membranes., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)

Combining artificial neural networks with evolutive/bioinspired approaches is a technique that can solve a variety of issues regarding the topology determination and training for neural networks or for process optimization. In this chapter, the main mechanisms used in neuroevolution are discussed and some biochemical separation examples are given to underline the efficiency of these tools. For the current case studies (reactive extraction of folic acid and pertraction of vitamin C), the bioinspired metaheuristic included in the neuroevolutive procedures is represented by Differential Evolution, an algorithm that has shown a great potential to solve a variety of problems from multiple domains.

Background & Objective: Nanoparticles are used in cosmetic and dermatologic products, due to better skin penetration properties. Incorporation of natural products exhibiting medicinal properties in nano-preparations could significantly improve the efficacy of these products and improve the quality of life without the side effects of synthetic formulations., Methods: We here report the green synthesis of Copper Oxide nanoparticles, using Cucumber extract, and their detailed bio-physical and bio-chemical characterization., Results: These Copper Oxide-Cucumber nanoparticles exhibit significant anti-bacterial and anti-fungal properties, Ultra Violet-radiation protection ability and reactive-oxygen species inhibition properties. Importantly, these nanoparticles do not exhibit significant cellular toxicity and, when incorporated in skin cream, exhibit skin rejuvenating properties., Conclusion: Our findings have implications for nanoparticle-based cosmetics and dermatologic applications., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Progress in cell-free protein synthesis (CFPS) has spurred resurgent interest in engineering complex biological metabolism outside of the cell. Unlike purified enzyme systems, crude cell-free systems can be prepared for a fraction of the cost and contain endogenous cellular pathways that can be activated for biosynthesis. Endogenous activity performs essential functions in cell-free systems including substrate biosynthesis and energy regeneration; however, use of crude cell-free systems for bioproduction has been hampered by the under-described complexity of the metabolic networks inherent to a crude lysate. Physical and chemical cultivation parameters influence the endogenous activity of the resulting lysate, but targeted efforts to engineer this activity by manipulation of these nongenetic factors has been limited. Here growth medium composition was manipulated to improve the one-pot in vitro biosynthesis of phenol from glucose via the expression of Pasteurella multocida phenol-tyrosine lyase in crude E. coli lysates. Crude cell lysate metabolic activity was focused toward the limiting precursor tyrosine by targeted growth medium dropouts guided by proteomics. The result is the activation of a 25-step enzymatic reaction cascade involving at least three endogenous E. coli metabolic pathways. Additional modification of this system, through CFPS of feedback intolerant AroG improves yield. This effort demonstrates the ability to activate a long, complex pathway in vitro and provides a framework for harnessing the metabolic potential of diverse organisms for cell-free metabolic engineering. The more than 6-fold increase in phenol yield with limited genetic manipulation demonstrates the benefits of optimizing growth medium for crude cell-free extract production and illustrates the advantages of a systems approach to cell-free metabolic engineering.

Purpose of Review: To summarize the underlying biochemical basis for low-carbohydrate and ketogenic diets (LC/KD) and provide mechanisms to account for demonstrated effectiveness., Recent Findings: LC/KD continue to have success, to outperform other diets as well as most drugs for weight loss and diabetes treatment. In many cases, LC/KD can effect remission (absence of drugs) or reversal (only metformin or nondiabetes drugs) of type 2 diabetes and can provide a significant adjunct to pharmacology in type 1. Medication is reduced or eliminated in most cases. The results are consistent with the biochemical rationale which stresses the global effects of the glucose-insulin axis., Summary: Evidence for the superior effectiveness of LC/KD for metabolic disease is now overwhelming. At the same time, the approach has received only limited support, and in many cases, persistence of the traditional opposition. Clinical practice or research must confront this crisis in order to bring practice in line with current science and to avoid continued harm to medicine and ultimately, the patient.

Cells build fatty acids with biocatalytic assembly lines in which a subset of enzymes often exhibit overlapping activities (e.g., two enzymes catalyze one or more identical reactions). Although the discrete enzymes that make up fatty acid pathways are well characterized, the importance of catalytic overlap between them is poorly understood. We developed a detailed kinetic model of the fatty acid synthase (FAS) of Escherichia coli and paired that model with a fully reconstituted in vitro system to examine the capabilities afforded by functional redundancy in fatty acid synthesis. The model captures-and helps explain-the effects of experimental perturbations to FAS systems and provides a powerful tool for guiding experimental investigations of fatty acid assembly. Compositional analyses carried out in silico and in vitro indicate that FASs with multiple partially redundant enzymes enable tighter (i.e., more independent and/or broader range) control of distinct biochemical objectives-the total production, unsaturated fraction, and average length of fatty acids-than FASs with only a single multifunctional version of each enzyme (i.e., one enzyme with the catalytic capabilities of two partially redundant enzymes). Maximal production of unsaturated fatty acids, for example, requires a second dehydratase that is not essential for their synthesis. This work provides a kinetic, control-theoretic rationale for the inclusion of partially redundant enzymes in fatty acid pathways and supplies a valuable framework for carrying out detailed studies of FAS kinetics., Competing Interests: The authors declare no competing interest.

Intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behavior. Characterization of this movement through averaging methods over an ensemble of trajectories or over the course of a single trajectory often fails to capture this heterogeneity. Here, we developed a deep learning feedforward neural network trained on fractional Brownian motion, providing a novel, accurate and efficient method for resolving heterogeneous behavior of intracellular transport in space and time. The neural network requires significantly fewer data points compared to established methods. This enables robust estimation of Hurst exponents for very short time series data, making possible direct, dynamic segmentation and analysis of experimental tracks of rapidly moving cellular structures such as endosomes and lysosomes. By using this analysis, fractional Brownian motion with a stochastic Hurst exponent was used to interpret, for the first time, anomalous intracellular dynamics, revealing unexpected differences in behavior between closely related endocytic organelles., Competing Interests: DH, NK, RC, MJ, AG, VA, SF, TW No competing interests declared, (© 2020, Han et al.)

Edaravone is a potent free radical scavenger that has a promising role in combating many acute lung injuries. Ischemia/reperfusion process is a serious condition that may lead to multiple organ dysfunctions. This work was designed to investigate novel mechanisms underlying ischemia/reperfusion-induced lung injury and to evaluate the protective role of edaravone. Thirty adult male rats were divided into three experimental groups; operated with no ischemia (Sham-group), ischemia/reperfusion (I/R) group and edaravone-I/R group. Hind limb ischemia was carried out by clamping the femoral artery. After two hours of ischemia for the hind limb, the rat underwent 24h of reperfusion. Rats in the edaravone-I/R group received edaravone (3mg/kg), 30min before induction of ischemia. At the end of the I/R trial, specimens from the lungs were processed for histological, immunohistochemical, enzyme assay, and RT-qPCR studies. Specimens from I/R group showed focal disruption of the alveolar architecture. Extensive mononuclear cellular infiltration particularly with neutrophils and dilated congested blood capillaries were observed. A significant increase in iNOS, NF-κB, and COX-2 immunoreaction was detected and confirmed by RT-qPCR. Ultrastructural examination showed RBCs and fluid inside alveoli, cellular infiltration, and vacuolations of the inter-alveolar septum. In addition to the presence of extravasated neutrophils and RBCs within the inter-alveolar septum. In contrast, minimal changes were observed in rats which received edaravone before the onset of the ischemia. It could be concluded that edaravone exerted a potent protective effect against lung injury induced by a hind limb I/R in rats through its antioxidant and anti-inflammatory activities., (Copyright © 2019 Elsevier GmbH. All rights reserved.)

Microbial photoautotroph-heterotroph interactions underlie marine food webs and shape ecosystem diversity and structure in upper ocean environments. Here, bacterial community composition, lifestyle preference, and genomic- and proteomic-level metabolic characteristics were investigated for an open ocean Synechococcus ecotype and its associated heterotrophs over 91 days of cocultivation. The associated heterotrophic bacterial assembly mostly constituted five classes, including Flavobacteria , Bacteroidetes , Phycisphaerae , Gammaproteobacteria , and Alphaproteobacteria The seven most abundant taxa/genera comprised >90% of the total heterotrophic bacterial community, and five of these displayed distinct lifestyle preferences (free-living or attached) and responses to Synechococcus growth phases. Six high-quality genomes, including Synechococcus and the five dominant heterotrophic bacteria, were reconstructed. The only primary producer of the coculture system, Synechococcus , displayed metabolic processes primarily involved in inorganic nutrient uptake, photosynthesis, and organic matter biosynthesis and release. Two of the flavobacterial populations, Muricauda and Winogradskyella , and an SM1A02 population, displayed preferences for initial degradation of complex compounds and biopolymers, as evinced by high abundances of TonB-dependent transporters (TBDTs), glycoside hydrolase, and peptidase proteins. Polysaccharide utilization loci present in the flavobacterial genomes influence their lifestyle preferences and close associations with phytoplankton. In contrast, the alphaproteobacterium Oricola sp. population mainly utilized low-molecular-weight dissolved organic carbon (DOC) through ATP-binding cassette (ABC), tripartite ATP-independent periplasmic (TRAP), and tripartite tricarboxylate transporter (TTT) transport systems. The heterotrophic bacterial populations exhibited complementary mechanisms for degrading Synechococcus- derived organic matter and driving nutrient cycling. In addition to nutrient exchange, removal of reactive oxygen species and vitamin trafficking might also contribute to the maintenance of the Synechococcus -heterotroph coculture system and the interactions shaping the system. IMPORTANCE The high complexity of in situ ecosystems renders it difficult to study marine microbial photoautotroph-heterotroph interactions. Two-member coculture systems of picocyanobacteria and single heterotrophic bacterial strains have been thoroughly investigated. However, in situ interactions comprise far more diverse heterotrophic bacterial associations with single photoautotrophic organisms. In the present study, combined metagenomic and metaproteomic data supplied the metabolic potentials and activities of uncultured dominant bacterial populations in the coculture system. The results of this study shed light on the nature of interactions between photoautotrophs and heterotrophs, improving our understanding of the complexity of in situ environments., (Copyright © 2020 Zheng et al.)

An environment far from equilibrium is thought to be a necessary condition for the origin and persistence of life. In this context we report open-flow simulations of a non-enzymic proto-metabolic system, in which hydrogen peroxide acts both as oxidant and driver of thermochemical cycling. We find that a Gaussian perturbed input produces a non-Boltzmann output fluctuation distribution around the mean oscillation maximum. Our main result is that net biosynthesis can occur under fluctuating cyclical but not steady drive. Consequently we may revise the necessary condition to "dynamically far from equilibrium".

Advances in machine learning and deep learning methods, together with the increasing availability of large-scale pharmacological, genomic, and chemical datasets, have created opportunities for identifying potentially useful relationships within biochemical networks. Knowledge embedding models have been found to have value in detecting knowledge-based correlations among entities, but little effort has been made to apply them to networks of biochemical entities. This is because such networks tend to be unbalanced and sparse, and knowledge embedding models do not work well on them. However, to some extent, the shortcomings of knowledge embedding models can be compensated for if they are used in association with graph embedding. In this paper, we combine knowledge embedding and graph embedding to represent biochemical entities and their relations as dense and low-dimensional vectors. We build a cascade learning framework which incorporates semantic features from the knowledge embedding model, and graph features from the graph embedding model, to score the probability of linking. The proposed method performs noticeably better than the models with which it is compared. It predicted links and entities with an accuracy of 93%, and its average hits@10 score has an average of 8.6% absolute improvement compared with original knowledge embedding model, 1.1% to 9.7% absolute improvement compared with other knowledge and graph embedding algorithm. In addition, we designed a meta-path algorithm to detect path relations in the biomedical network. Case studies further verify the value of the proposed model in finding potential relationships between diseases, drugs, genes, treatments, etc. Amongst the findings of the proposed model are the suggestion that VDR (vitamin D receptor) may be linked to prostate cancer. This is backed by evidence from medical databases and published research, supporting the suggestion that our proposed model could be of value to biomedical researchers., Competing Interests: The authors have declared that no competing interests exist.

The metabolism of antitumor-active 5-diethylaminoethylamino-8-hydroxyimidazoacridinone (C-1311) has been investigated widely over the last decade but some aspects of molecular mechanisms of its metabolic transformation are still not explained. In the current work, we have reported a direct and rapid analytical tool for better prediction of C-1311 metabolism which is based on electrochemistry (EC) coupled on-line with electrospray ionization mass spectrometry (ESI-MS). Simulation of the oxidative phase I metabolism of the compound was achieved in a simple electrochemical thin-layer cell consisting of three electrodes (ROXY ™ , Antec Leyden, the Netherlands). We demonstrated that the formation of the products of N-dealkylation reactions can be easily simulated using purely instrumental approach. Newly reported products of oxidative transformations like hydroxylated or oxygenated derivatives become accessible. Structures of the electrochemically generated metabolites were elucidated on the basis of accurate mass ion data and tandem mass spectrometry experiments. In silico prediction of main sites of C-1311 metabolism was performed using MetaSite software. The compound was evaluated for cytochrome P450 1A2-, 3A4-, and 2D6-mediated reactions. The results obtained by EC were also compared and correlated with those of reported earlier for conventional in vitro enzymatic studies in the presence of liver microsomes and in the model peroxidase system. The in vitro experimental approach and the in silico metabolism findings showed a quite good agreement with the data from EC/ESI-MS analysis. Thus, we conclude here that the electrochemical technique provides the promising platform for the simple evaluation of drug metabolism and the reaction mechanism studies, giving first clues to the metabolic transformation of pharmaceuticals in the human body., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The global population growth of the bed bug, Cimex lectularius (L.), is attributed to their cryptic behavior, diverse insecticide resistance mechanisms, and lack of public awareness. Bed bug control can be challenging and typically requires chemical and non-chemical treatments. One common non-chemical method for bed bug management is thermal remediation. However, in certain instances, bed bugs are known to survive heat treatments. Bed bugs may be present after a heat treatment due to (i) abiotic factors associated with the inability to achieve lethal temperatures in harborage areas for a sufficient time period, (ii) re-infestation from insects that escaped to cooler areas during a heat treatment or (iii) development of physiological resistance that allows them to survive heat exposure. Previous research has investigated the optimal temperature and exposure time required for either achieving complete mortality or sublethally affecting their growth and development. However, no research has examined bed bug populations for their ability to develop resistance to heat exposure and variation in thermo-tolerance between different bed bug strains. The goals of this study were: i) to determine if bed bugs could be selected for heat resistance under a laboratory selection regime, and ii) to determine if bed bug populations with various heat exposure histories, insecticide resistance profiles, and geographic origins have differential temperature tolerances using two heat exposure techniques (step-function and ramp-function). Selection experiments found an initial increase in bed bug survivorship; however, survivorship did not increase past the fourth generation. Sublethal exposure to heat significantly reduced bed bug feeding and, in some cases, inhibited development. The step-function exposure technique revealed non-significant variation in heat tolerance between populations and the ramp-function exposure technique provided similar results. Based on these study outcomes, the ability of bed bugs to develop heat resistance appears to be limited., Competing Interests: The authors have declared that no competing interests exist. Merit-based student scholarship from the commercial funder J. T. Eaton and Company does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Cdc14 enzymes compose a family of highly conserved phosphatases that are present in a wide range of organisms, including yeast and humans, and that preferentially reverse the phosphorylation of Cyclin-Dependent Kinase (Cdk) substrates. The budding yeast Cdc14 orthologue has essential functions in the control of late mitosis and cytokinesis. In mammals, however, the two Cdc14 homologues, Cdc14A and Cdc14B, do not play a prominent role in controlling late mitotic events, suggesting that some Cdc14 functions are not conserved across species. Moreover, in yeast, Cdc14 is regulated by changes in its subcellular location and by phosphorylation events. In contrast, little is known about the regulation of human Cdc14 phosphatases. Here, we have studied how the human Cdc14A orthologue is regulated during the cell cycle. We found that Cdc14A is phosphorylated on Ser411, Ser453 and Ser549 by Cdk1 early in mitosis and becomes dephosphorylated during late mitotic stages. Interestingly, in vivo and in vitro experiments revealed that, unlike in yeast, Cdk1-mediated phosphorylation of human Cdc14A did not control its catalytic activity but likely modulated its interaction with other proteins in early mitosis. These findings point to differences in Cdk1-mediated mechanisms of regulation between human and yeast Cdc14 orthologues.

We have shown previously that different homeostatic mechanisms in biochemistry create input-output curves with a "chair" shape. At equilibrium, for intermediate values of a parameter (often an input), a variable, Z, changes very little (the homeostatic plateau), but for low and high values of the parameter, Z changes rapidly (escape from homeostasis). In all cases previously studied, the steady state was stable for each value of the input parameter. Here we show that, for the feedback inhibition motif, stability may be lost through a Hopf bifurcation on the homeostatic plateau and then regained by another Hopf bifurcation. If the limit cycle oscillations are relatively small in the unstable interval, then the variable Z maintains homeostasis despite the instability. We show that the existence of an input interval in which there are oscillations, the length of the interval, and the size of the oscillations depend in interesting and complicated ways on the properties of the inhibition function, f, the length of the chain, and the size of a leakage parameter., (Copyright © 2018 Elsevier Inc. All rights reserved.)

We apply to Michaelis-Menten kinetics an alternative approach to the study of Singularly Perturbed Differential Equations, that is based on the Renormalization Group (SPDERG). To this aim, we first rebuild the perturbation expansion for Michaelis-Menten kinetics, beyond the standard Quasi-Steady-State Approximation (sQSSA), determining the 2nd order contributions to the inner solutions, that are presented here for the first time to our knowledge. Our main result is that the SPDERG 2nd order uniform approximations reproduce the numerical solutions of the original problem in a better way than the known results of the perturbation expansion, even in the critical matching region. Indeed, we obtain analytical results nearly indistinguishable from the numerical solutions of the original problem in a large part of the whole relevant time window, even in the case in which the kinetic constants produce an expansion parameter value as large as ɛ=0.5., (Copyright © 2017 Elsevier Inc. All rights reserved.)

This was a pilot study to examine pre- and postoperative stress experienced by women who were undergoing autologous breast reconstruction and how stress might impact wound healing, specifically examining cytokines and other chemical mediators in the wound environment. A nonexperimental descriptive design over time was utilized. Participants were women who were undergoing autologous abdominal breast reconstruction for breast cancer (N = 20). Data were collected preoperatively and at 24, 48, 72, and 96 hr postsurgery. Complications were monitored intraoperatively and up to 30 days postsurgery. Psychological stress was measured with the 10-item Perceived Stress Scale (PSS), the Impact of Events Scale-Revised (IES-R), and a 100-mm Visual Analog Scale (VAS). Cytokines were assayed using the 27-plex kit with a Bio-Plex Plus. Although breast cancer is considered a stressor, in this sample of women, scores of the PSS, IES-R, and VAS showed that in fact these participants experienced low levels of psychological stress. All measured biochemical mediators in serum and wound fluid were detected and trends were identified. IL-1ra, IL-6, IL-8, G-CSF, IP-10, MCP-1, MIP-1β, RANTES, and VEGF were present in the highest concentrations. Significant changes in levels of cytokines in wound fluid were observed in IL-1β, IL-2, IL-5, IL-6, IL-8, IL-9, IL-10, IL-17, FGF-basic, G-CSF, MIP-1α, PDGF-bb, MIP-1β, RANTES, and TNF-α. The remaining cytokine concentrations stayed stable over time. These findings suggest that although these women were not experiencing high levels of stress, meaningful cytokine patterns were detected.

Although animal experiments are indispensable for preclinical screening in the drug discovery process, various issues such as ethical considerations and species differences remain. To solve these issues, cell-based assays using human-derived cells have been actively pursued. However, it remains difficult to accurately predict drug efficacy, toxicity, and organs interactions, because cultivated cells often do not retain their original organ functions and morphologies in conventional in vitro cell culture systems. In the μTAS research field, which is a part of biochemical engineering, the technologies of organ-on-a-chip, based on microfluidic devices built using microfabrication, have been widely studied recently as a novel in vitro organ model. Since it is possible to physically and chemically mimic the in vitro environment by using microfluidic device technology, maintenance of cellular function and morphology, and replication of organ interactions can be realized using organ-on-a-chip devices. So far, functions of various organs and tissues, such as the lung, liver, kidney, and gut have been reproduced as in vitro models. Furthermore, a body-on-a-chip, integrating multi organ functions on a microfluidic device, has also been proposed for prediction of organ interactions. We herein provide a background of microfluidic systems, organ-on-a-chip, Body-on-a-chip technologies, and their challenges in the future., (Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.)

The extracellular matrix is a complex network of hydrated macromolecular proteins and sugars that, in concert with bound soluble factors, comprise the acellular stromal microenvironment of tissues. Rather than merely providing structural information to cells, the extracellular matrix plays an instructive role in development and is critical for the maintenance of tissue homeostasis. In this chapter, we review the composition of the extracellular matrix and summarize data illustrating its importance in embryogenesis, tissue-specific development, and stem cell differentiation. We discuss how the biophysical and biochemical properties of the extracellular matrix ligate specific transmembrane receptors to activate intracellular signaling that alter cell shape and cytoskeletal dynamics to modulate cell growth and viability, and direct cell migration and cell fate. We present examples describing how the extracellular matrix functions as a highly complex physical and chemical entity that regulates tissue organization and cell behavior through a dynamic and reciprocal dialogue with the cellular constituents of the tissue. We suggest that the extracellular matrix not only transmits cellular and tissue-level force to shape development and tune cellular activities that are key for coordinated tissue behavior, but that it is itself remodeled such that it temporally evolves to maintain the integrated function of the tissue. Accordingly, we argue that perturbations in extracellular matrix composition and structure compromise key developmental events and tissue homeostasis, and promote disease., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Context: Successful elite sprint to long-distance runners are known to have shorter ground-contact time (GCT) than their less successful counterparts., Purpose: To investigate whether augmented feedback (aF) about GCT can reduce the time on ground (TOG) per minute in long-distance runners and, if so, whether this reduction improves running performance., Methods: Thirty well-trained runners were allocated to 3 groups. The intervention group (IG) received visual aF about their GCT during 8 high-intensity interval sessions in the 4-wk training period and were instructed to minimize GCT. The 1st control group (CG1) trained with the IG but was not given any feedback. The 2nd control group (CG2) followed their own training routine. Data were obtained pre- and postintervention for all 3 groups. The dependent variable was TOG per minute, computed from step frequency and GCT., Results: The IG significantly reduced TOG (P = .043, -1.7%, 90%CL -3.1;-0.3) and improved their mean 10 × 400-m performance time (P < .001, -1.5%, 90%CL -1.9;-1.1). In contrast, the 2 control groups revealed unchanged values, indicating that normal high-intensity training and an individualized routine without aF were not able to reduce TOG. The fact that CG1 received the same instructions and participated in the same training sessions as the IG underlined that aF was crucial to reduce TOG., Conclusions: The provision of aF about GCT seems to be a promising approach that should be considered during training practice of well-trained runners.

Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de.

Background: Positive surgical margins are a strong prognostic marker of disease outcome following radical prostatectomy, though prior evidence is largely from a PSA-screened population. We therefore aim to evaluate the biochemical recurrence in men with positive surgical margins (PSM) after minimally-invasive radical prostatectomy (MIRP) in a UK tertiary centre., Methods: Retrospective study of men undergoing laparoscopic or robotic-assisted radical prostatectomy between 2002 and 2014. Men with positive surgical margins (PSM) were identified and their biochemical recurrence (BCR) rate compared with men without PSM. The primary outcome measures were BCR rates and time to BCR. Cox regression was used to estimate adjusted hazard ratios for biochemical recurrence rate (BCR), accounting for potential confounders., Results: Five hundred ninety-two men were included for analysis. Pre-operative D'Amico risk stratification showed 37.5%, 53.3% and 9.3% of patients in the low, intermediate and high-risk groups, respectively. On final pathological analysis, the proportion of patients with local staging pT2, pT3a and pT3b was 68.8%, 25.2% and 6.1% respectively. Overall positive margin rate was 30.6%. On multivariate analysis, the only pre-operative factor associated with PSM was age >65years. Patients with PSM were more likely to have higher tumour volume and more advanced pathological local stage. The BCR rate was 10.7% in margin-positive patients and 5.1% in margin-negative patients, at median 4.4-year follow-up. Upon multivariate analysis, high pre-operative PSA and high Gleason group were the only significant predictors of BCR (P<0.05)., Conclusions: In comparison to patients with negative surgical margins, those with PSM do not translate into worse medium-term oncological outcomes in the majority of cases amongst our cohort. We found that high pre-operative PSA and high Gleason group were the only significant predictors of BCR.

The Dicer family of ribonucleases plays a key role in small RNA-based regulatory pathways by generating short dsRNA fragments that modulate expression of endogenous genes, or protect the host from invasive nucleic acids. Beginning with its initial discovery, biochemical characterization of Dicer has provided insight about its catalytic properties. However, a comprehensive understanding of how Dicer's domains contribute to substrate-specific recognition and catalysis is lacking. One reason for this void is the lack of high-resolution structural information for a metazoan Dicer in the apo- or substrate-bound state. Both biochemical and structural studies are facilitated by large amounts of highly purified, active protein, and Dicer enzymes have historically been recalcitrant to overexpression and purification. Here we describe optimized procedures for the large-scale expression of Dicer in baculovirus-infected insect cells. We then outline a three-step protocol for the purification of large amounts (3-4mg of Dicer per liter of insect cell culture) of highly purified and active Dicer protein, suitable for biochemical and structural studies. Our methods are general and are extended to enable overexpression, purification and biochemical characterization of accessory dsRNA binding proteins that interact with Dicer and modulate its catalytic activity., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Cytochrome c oxidase (C c O) catalyzes the reduction of oxygen to water and uses the released free energy to pump protons against the transmembrane proton gradient. To better understand the proton-pumping mechanism of the wild-type (WT) C c O, much attention has been given to the mutation of amino acid residues along the proton translocating D-channel that impair, and sometimes decouple, proton pumping from the chemical catalysis. Although their influence has been clearly demonstrated experimentally, the underlying molecular mechanisms of these mutants remain unknown. In this work, we report multiscale reactive molecular dynamics simulations that characterize the free-energy profiles of explicit proton transport through several important D-channel mutants. Our results elucidate the mechanisms by which proton pumping is impaired, thus revealing key kinetic gating features in C c O. In the N139T and N139C mutants, proton back leakage through the D-channel is kinetically favored over proton pumping due to the loss of a kinetic gate in the N139 region. In the N139L mutant, the bulky L139 side chain inhibits timely reprotonation of E286 through the D-channel, which impairs both proton pumping and the chemical reaction. In the S200V/S201V double mutant, the proton affinity of E286 is increased, which slows down both proton pumping and the chemical catalysis. This work thus not only provides insight into the decoupling mechanisms of C c O mutants, but also explains how kinetic gating in the D-channel is imperative to achieving high proton-pumping efficiency in the WT C c O., Competing Interests: The authors declare no conflict of interest.

Numerous plant polyphenols have potential applications as pharmaceuticals or nutraceuticals. Stilbenes and flavonoids as most abundant polyphenols are synthesized from phenylpropanoids, which are exclusively derived from aromatic amino acids in nature. Several microorganisms were engineered for the synthesis of biotechnologically interesting plant polyphenols; however, low activity of heterologous ammonia lyases, linking endogenous microbial aromatic amino acid biosynthesis to phenylpropanoid synthesis, turned out to be the limiting step during microbial synthesis. We here developed an alternative strategy for polyphenol production from cheap benzoic acids by reversal of a β-oxidative phenylpropanoid degradation pathway avoiding any ammonia lyase activity. The synthetic pathway running in the non-natural direction is feasible with respect to thermodynamics and involved reaction mechanisms. Instantly, product titers of 5 mg/L resveratrol could be achieved in recombinant Corynebacterium glutamicum strains indicating that phenylpropanoid synthesis from 4-hydroxybenzoic acid can in principle be implemented independently from aromatic amino acids and ammonia lyase activity.

For dynamical systems arising from chemical reaction networks, persistence is the property that each species concentration remains positively bounded away from zero, as long as species concentrations were all positive in the beginning. We describe two graphical procedures for simplifying reaction networks without breaking known necessary or sufficient conditions for persistence, by iteratively removing so-called intermediates and catalysts from the network. The procedures are easy to apply and, in many cases, lead to highly simplified network structures, such as monomolecular networks. For specific classes of reaction networks, we show that these conditions for persistence are equivalent to one another. Furthermore, they can also be characterized by easily checkable strong connectivity properties of a related graph. In particular, this is the case for (conservative) monomolecular networks, as well as cascades of a large class of post-translational modification systems (of which the MAPK cascade and the n-site futile cycle are prominent examples). Since one of the aforementioned sufficient conditions for persistence precludes the existence of boundary steady states, our method also provides a graphical tool to check for that.

The production and use of nanoparticles, as titanium dioxide (nanoTiO 2 ) is growing exponentially in the last years and their release into aquatic environment seem be inevitable. Once into environment, this nanomaterial can interact with other contaminant, as arsenic, and to exert toxic effect in living organisms. So, the objective of present study was to evaluate if the co-exposure to nanoTiO 2 (1mg/L) can alter the As effect (nominal concentration of 50μg/L) in the estuarine polychaeta Laeonereis acuta after 48h of exposure. Were performed biochemical analyses such ROS production, enzymatic activities (GST, GR and GSTΩ), total antioxidant capacity against peroxyl radicals and damage to macromolecules (lipid and DNA), besides also were determined the accumulation of total arsenic and arsenic speciation in the worms. The results showed that co-exposure induced an increase in the ROS levels, decrease in total antioxidant capacity, increase in GR activity, and damage in lipid and DNA. Also, the co-exposure showed to affect the metabolization capacity of arsenic characterized by increase in dimethylated arsenic forms, a compound moderately toxic. So, these results suggest that the co-exposure to both contaminants is harmful to this species and the use of nanoTiO 2 to treatment of contaminated water by arsenic should be considered of a toxicological point of view., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

The quasi-steady state approximation and time-scale separation are commonly applied methods to simplify models of biochemical reaction networks based on ordinary differential equations (ODEs). The concentrations of the "fast" species are assumed effectively to be at steady state with respect to the "slow" species. Under this assumption the steady state equations can be used to eliminate the "fast" variables and a new ODE system with only the slow species can be obtained. We interpret a reduced system obtained by time-scale separation as the ODE system arising from a unique reaction network, by identification of a set of reactions and the corresponding rate functions. The procedure is graphically based and can easily be worked out by hand for small networks. For larger networks, we provide a pseudo-algorithm. We study properties of the reduced network, its kinetics and conservation laws, and show that the kinetics of the reduced network fulfil realistic assumptions, provided the original network does. We illustrate our results using biological examples such as substrate mechanisms, post-translational modification systems and networks with intermediates (transient) steps.

Sensitivity analysis characterizes the dependence of a model's behaviour on system parameters. It is a critical tool in the formulation, characterization, and verification of models of biochemical reaction networks, for which confident estimates of parameter values are often lacking. In this paper, we propose a novel method for sensitivity analysis of discrete stochastic models of biochemical reaction systems whose dynamics occur over a range of timescales. This method combines finite-difference approximations and adaptive tau-leaping strategies to efficiently estimate parametric sensitivities for stiff stochastic biochemical kinetics models, with negligible loss in accuracy compared with previously published approaches. We analyze several models of interest to illustrate the advantages of our method., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

A brief overview of the work in the research group of the present author on extracting knowledge from chemical reaction data is presented. Methods have been developed to calculate physicochemical effects at the reaction site. It is shown that these physicochemical effects can quite favourably be used to derive equations for the calculation of data on gas phase reactions and on reactions in solution such as aqueous acidity of alcohols or carboxylic acids or the hydrolysis of amides. Furthermore, it is shown that these physicochemical effects are quite effective for assigning reactions into reaction classes that correspond to chemical knowledge. Biochemical reactions constitute a particularly interesting and challenging task for increasing our understanding of living species. The BioPath.Database is a rich source of information on biochemical reactions and has been used for a variety of applications of chemical, biological, or medicinal interests. Thus, it was shown that biochemical reactions can be assigned by the physicochemical effects into classes that correspond to the classification of enzymes by the EC numbers. Furthermore, 3D models of reaction intermediates can be used for searching for novel enzyme inhibitors. It was shown in a combined application of chemoinformatics and bioinformatics that essential pathways of diseases can be uncovered. Furthermore, a study showed that bacterial flavor-forming pathways can be discovered., (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Electron transport, or oxidative phosphorylation, is one of the hallmarks of life. To this end, prokaryotes evolved a vast variety of protein complexes, only a small part of which have been discovered and studied. These protein complexes allow them to occupy virtually every ecological niche on Earth. Here, we applied the method of proteomics-based complexome profiling to get a better understanding of the electron transport systems of the anaerobic ammonium-oxidizing (anammox) bacteria, the N2-producing key players of the global nitrogen cycle. By this method nearly all respiratory complexes that were previously predicted from genome analysis to be involved in energy and cell carbon fixation were validated. More importantly, new and unexpected ones were discovered. We believe that complexome profiling in concert with (meta)genomics offers great opportunities to expand our knowledge on bacterial respiratory processes at a rapid and massive pace, in particular in new and thus far poorly investigated non-model and environmentally-relevant species., (Copyright © 2016 Elsevier B.V. All rights reserved.)

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Three stereoisomeric inhibitors of Pin1: (2R,5S)-, (2S,5R)- and (2S,5S)-Ac-pSer-Ψ[(Z)CH = C]-pipecolyl(Pip)-2-(2-naphthyl)ethylamine 1, that mimic L-pSer-D-Pro, D-pSer-L-Pro, and D-pSer-D-Pro amides respectively, were synthesized by a 13-step route. The newly formed stereogenic centers in the pipecolyl ring were introduced by Luche reduction, followed by stereospecific [2,3]-Still-Wittig rearrangement. The (Z)- to (E)-alkene ratio in the rearrangements were consistently 5.5 to 1. The stereochemistry at the original Ser α-carbon controlled the stereochemistry of the Luche reduction, but it did not affect the stereochemical outcome of the rearrangement, which consistently gave the (Z)-alkene. The epimerized by-product, (2S,5S)-10, resulting from the work-up after Na/NH3 debenzylation of (2S,5R)-9, was carried on to the (2S,5S)-1 isomer. Compound (2S,5S)-10 was resynthesized from the Luche reduction by-product, (2R,3R)-3, and the stereochemistry was confirmed by comparison of the optical rotations. The IC50 values for (2R,5S)-1, (2S,5R)-1 and (2S,5S)-1 Pin1 inhibition were: 52, 85, and 140 μM, respectively.

Erythrocytes are the key target in 5'-AMP induced hypometabolism. To understand how regulation of endogenous erythrocyte AMP levels modulates systemic metabolism, we generated mice deficient in both CD73 and AMPD3, the key catabolic enzymes for extracellular and intra-erythrocyte AMP, respectively. Under physiological conditions, these mice displayed enhanced capacity for physical activity accompanied by significantly higher food and oxygen consumption, compared to wild type mice. Erythrocytes from Ampd3(-/-) mice exhibited higher half-saturation pressure of oxygen (p50) and about 3-fold higher levels of ATP and ADP, while they maintained normal 2,3-bisphosphoglycerate (2,3-BPG), methemoglobin levels and intracellular pH. The affinity of mammalian hemoglobin for oxygen is thought to be regulated primarily by 2,3-BPG levels and pH (the Bohr effect). However, our results show that increased endogenous levels of ATP and ADP, but not AMP, directly increase the p50 value of hemoglobin. Additionally, the rise in erythrocyte p50 directly correlates with an enhanced capability of systemic metabolism.

A biological complex organism is involuntarily guided from all sides by measure and regulation systems. The human being is such a complex organism. Many cyclical processes are simultaneously at work, making it unclear how and why which process takes place at which moment. Noticeable examples are the 28-day menstrual cycle and the 40-week pregnancy. The time of activation in the middle of the menstrual is fairly clear. Hormonal changes also occur in this period. Why the hormonal changes occur, and what their relationship is with the activation of the processes is unclear. That is also the case during pregnancies. What is it that determines that a pregnancy should last an average of 40 weeks? What causes the changes in a complicated pregnancy? What are those changes? Prostaglandin concentrations have been found to have some relationship with these changes, but the activation of these changes and how to examine them is unknown. Using an example from practical experience, this article illustrates what Horrobin and Manku already reported in 1977, namely, the properties of prostaglandin E1 and 6-keto pgF1α: reversal effect with elevated concentration. The properties described is exceptionally suitable for the time of activation in a biochemically regulated measure and regulation system. These properties can help explain the occurrence of physiological cycles. The known electronic saw-tooth wave has a biochemical analogue with this. This paper describes the presumed relationship between hormones and the accompanying prostaglandins with the hormone effects based on what is known regarding their concentrations progress. This relationship reveals the practical consequences of the experimentally found sensitivity of biochemical effects with regard to the accompanying prostaglandins. This paper shows how the theoretical relationship between effects of oestrogens and progestagens result in a curve that comprise observable aspects of the Basal Body Temperature Curve. The modulating and activating prostaglandins also affect local changes in blood circulation. These changes are visible on specific sites on the abdominal skin via viscerocutaneous reflex pathways. Changes in blood circulation at specific areas of the skin can be representative of pain. Pain that also frequently arises during activation processes. These changes can be seen and measured with non-contactual infrared thermography on the cutaneous surface, and moments of activation and pain can be determined., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Homologous recombination provides high-fidelity DNA repair throughout all domains of life. Live cell fluorescence microscopy offers the opportunity to image individual recombination events in real time providing insight into the in vivo biochemistry of the involved proteins and DNA molecules as well as the cellular organization of the process of homologous recombination. Herein we review the cell biological aspects of mitotic homologous recombination with a focus on Saccharomyces cerevisiae and mammalian cells, but will also draw on findings from other experimental systems. Key topics of this review include the stoichiometry and dynamics of recombination complexes in vivo, the choreography of assembly and disassembly of recombination proteins at sites of DNA damage, the mobilization of damaged DNA during homology search, and the functional compartmentalization of the nucleus with respect to capacity of homologous recombination., (Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.)

In this article, we will discuss the biochemistry of mitosis in eukaryotic cells. We will focus on conserved principles that, importantly, are adapted to the biology of the organism. It is vital to bear in mind that the structural requirements for division in a rapidly dividing syncytial Drosophila embryo, for example, are markedly different from those in a unicellular yeast cell. Nevertheless, division in both systems is driven by conserved modules of antagonistic protein kinases and phosphatases, underpinned by ubiquitin-mediated proteolysis, which create molecular switches to drive each stage of division forward. These conserved control modules combine with the self-organizing properties of the subcellular architecture to meet the specific needs of the cell. Our discussion will draw on discoveries in several model systems that have been important in the long history of research on mitosis, and we will try to point out those principles that appear to apply to all cells, compared with those in which the biochemistry has been specifically adapted in a particular organism., (Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.)