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Mitochondrial respiration is an energy producing process that involves the coordinated action of several protein complexes embedded in the inner membrane to finally produce ATP. Complex IV or Cytochrome c Oxidase (COX) is the last electron acceptor of the respiratory chain, involved in the reduction of O2 to H2O. COX is a multimeric complex formed by multiple structural subunits encoded in two different genomes, prosthetic groups (heme a and heme a3), and metallic centers (CuA and CuB). Tens of accessory proteins are required for mitochondrial RNA processing, synthesis and delivery of prosthetic groups and metallic centers, and for the final assembly of subunits to build a functional complex. In this review, we perform a comparative analysis of COX composition and biogenesis factors in yeast, mammals and plants. We also describe possible external and internal factors controlling the expression of structural proteins and assembly factors at the transcriptional and post-translational levels, and the effect of deficiencies in different steps of COX biogenesis to infer the role of COX in different aspects of plant development. We conclude that COX assembly in plants has conserved and specific features, probably due to the incorporation of a different set of subunits during evolution.

TCP proteins integrate a family of transcription factors involved in the regulation of developmental processes and hormone responses. It has been shown that most members of class I, one of the two classes in which the TCP family is divided, contain a conserved Cys that leads to inhibition of DNA binding when oxidized. In this work, we describe that the class-I TCP protein TCP15 inhibits anthocyanin accumulation during exposure of plants to high light intensity by modulating the expression of transcription factors involved in the induction of anthocyanin biosynthesis genes, as suggested by the study of plants that express TCP15 from the 35SCaMV promoter and mutants in TCP15 and the related gene TCP14. In addition, the effect of TCP15 on anthocyanin accumulation is lost after prolonged incubation under high light intensity conditions. We provide evidence that this is due to inactivation of TCP15 by oxidation of Cys-20 of the TCP domain. Thus, redox modulation of TCP15 activity in vivo by high light intensity may serve to adjust anthocyanin accumulation to the duration of exposure to high irradiation conditions

Purpose of ReviewMetabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding.Recent findingsFindings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses.SummaryMetabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.

TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factors (TFs) are plant-specific transcriptional regulators exerting multiple functions in plant growth and development. Ever since one of the founding members of the family was described, encoded by the CYCLOIDEA (CYC) gene from Antirrhinum majus and involved in the regulation of floral symmetry, the role of these TFs in reproductive development was established. Subsequent studies indicated that members of the CYC clade of TCP TFs were important for the evolutionary diversification of flower form in a multitude of species. In addition, more detailed studies of the function of TCPs from other clades revealed roles in different processes related to plant reproductive development, such as the regulation of flowering time, the growth of the inflorescence stem, and the correct growth and development of flower organs. In this review, we summarize the different roles of members of the TCP family during plant reproductive development as well as the molecular networks involved in their action.

Lateral-flow assays (LFAs) are quick, simple and cheap assays to analyze various samples at the point of care or in the field, making them one of the most widespread biosensors currently available. They have been successfully employed for the detection of a myriad of different targets (ranging from atoms up to whole cells) in all type of samples (including water, blood, foodstuff and environmental samples). Their operation relies on the capillary flow of the sample throughout a series of sequential pads, each with different functionalities aiming to generate a signal to indicate the absence/presence (and, in some cases, the concentration) of the analyte of interest. To have a user-friendly operation, their development requires the optimization of multiple, interconnected parameters that may overwhelm new developers. In this tutorial, we provide the readers with: (i) the basic knowledge to understand the principles governing an LFA and to take informed decisions during lateral flow strip design and fabrication, (ii) a roadmap for optimal LFA development independent of the specific application, (iii) a step-by-step example procedure for the assembly and operation of an LF strip for the detection of human IgG and (iv) an extensive troubleshooting section addressing the most frequent issues in designing, assembling and using LFAs. By changing only the receptors, the provided example procedure can easily be adapted for cost-efficient detection of a broad variety of targets. This tutorial describes how to design nanoparticle-based LFAs for detecting biomolecules. The authors provide guidance on how to select the appropriate lateral-flow strip components and bioreceptors as well as detection strategies.

We present a quantum simulation scheme for the Abelian-Higgs lattice gauge theory using ultracold bosonic atoms in optical lattices. The model contains both gauge and Higgs scalar fields, and exhibits interesting phases related to confinement and the Higgs mechanism. The model can be simulated by an atomic Hamiltonian, by first mapping the local gauge symmetry to an internal symmetry of the atomic system, the conservation of hyperfine angular momentum in atomic collisions. By including auxiliary bosons in the simulation, we show how the Abelian-Higgs Hamiltonian emerges effectively. We analyze the accuracy of our method in terms of different experimental parameters, as well as the effect of the finite number of bosons on the quantum simulator. Finally, we propose possible experiments for studying the ground state of the system in different regimes of the theory, and measuring interesting high energy physics phenomena in real time.

An understanding of the pharmacokinetic (PK) and pharmacodynamic (PD) principles that determine response to antimicrobial therapy can provide the clinician with better-informed dosing regimens. Factors influential on antibiotic disposition and clinical outcome are presented, with a focus on the primary site of infection. Techniques to better understand antibiotic PK and optimize PD are acknowledged. PubMed (inception–April 2016) was reviewed for relevant publications assessing antimicrobial exposures within different anatomic locations and clinical outcomes for various infection sites. A limited literature base indicates variable penetration of antibiotics to different target sites of infection, with drug solubility and extent of protein binding providing significant PK influences in addition to the major clearing pathway of the agent. PD indices derived from in vitro studies and animal models determine the optimal magnitude and frequency of dosing regimens for patients. PK/PD modeling and simulation has been shown an efficient means of assessing these PD endpoints against a variety of PK determinants, clarifying the unique effects of infection site and patient characteristics to inform the adequacy of a given antibiotic regimen. Appreciation of the PK properties of an antibiotic and its PD measure of efficacy can maximize the utility of these life-saving drugs. Unfortunately, clinical data remain limited for a number of infection site–antibiotic exposure relationships. Modeling and simulation can bridge preclinical and patient data for the prescription of optimal antibiotic dosing regimens, consistent with the tenets of personalized medicine.

TEOSINTE BRANCHED1, CYCLOIDEA, PROLIFERATING CELL FACTOR 1 and 2 (TCP) proteins constitute a plant-specific transcription factors family exerting effects on multiple aspects of plant development, such as germination, embryogenesis, leaf and flower morphogenesis, and pollen development, through the recruitment of other factors and the modulation of different hormonal pathways. They are divided into two main classes, I and II. This review focuses on the function and regulation of class I TCP proteins (TCPs). We describe the role of class I TCPs in cell growth and proliferation and summarize recent progresses in understanding the function of class I TCPs in diverse developmental processes, defense, and abiotic stress responses. In addition, their function in redox signaling and the interplay between class I TCPs and proteins involved in immunity and transcriptional and posttranslational regulation is discussed.

The optimal location and sizing of distributed generation is a suitable option for improving the operation of electric systems. This paper proposes a parallel implementation of the Population-Based Incremental Learning (PBIL) algorithm to locate distributed generators (DGs), and the use of Particle Swarm Optimization (PSO) to define the size those devices. The resulting method is a master-slave hybrid approach based on both the parallel PBIL (PPBIL) algorithm and the PSO, which reduces the computation time in comparison with other techniques commonly used to address this problem. Moreover, the new hybrid method also reduces the active power losses and improves the nodal voltage profiles. In order to verify the performance of the new method, test systems with 33 and 69 buses are implemented in Matlab, using Matpower, for evaluating multiple cases. Finally, the proposed method is contrasted with the Loss Sensitivity Factor (LSF), a Genetic Algorithm (GA) and a Parallel Monte-Carlo algorithm. The results demonstrate that the proposed PPBIL-PSO method provides the best balance between processing time, voltage profiles and reduction of power losses.

In recent years, human activity recognition has become a hot topic inside the scientific community. The reason to be under the spotlight is its direct application in multiple domains, like healthcare or fitness. Additionally, the current worldwide use of smartphones makes it particularly easy to get this kind of data from people in a non-intrusive and cheaper way, without the need for other wearables. In this paper, we introduce our orientation-independent, placement-independent and subject-independent human activity recognition dataset. The information in this dataset is the measurements from the accelerometer, gyroscope, magnetometer, and GPS of the smartphone. Additionally, each measure is associated with one of the four possible registered activities: inactive, active, walking and driving. This work also proposes asupport vector machine (SVM) model to perform some preliminary experiments on the dataset. Considering that this dataset was taken from smartphones in their actual use, unlike other datasets, the development of a good model on such data is an open problem and a challenge for researchers. By doing so, we would be able to close the gap between the model and a real-life application.