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1.
J Chem Phys ; 151(12): 125101, 2019 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-31575173

RESUMO

Gene regulation is one of the most important fundamental biological processes in living cells. It involves multiple protein molecules that locate specific sites on DNA and assemble gene initiation or gene repression multimolecular complexes. While the protein search dynamics for DNA targets has been intensively investigated, the role of intermolecular interactions during the genetic activation or repression remains not well quantified. Here, we present a simple one-dimensional model of target search for two interacting molecules that can reversibly form a dimer molecular complex, which also participates in the search process. In addition, the proteins have finite residence times on specific target sites, and the gene is activated or repressed when both proteins are simultaneously present at the target. The model is analyzed using first-passage analytical calculations and Monte Carlo computer simulations. It is shown that the search dynamics exhibit a complex behavior depending on the strength of intermolecular interactions and on the target residence times. We also found that the search time shows a nonmonotonic behavior as a function of the dissociation rate for the molecular complex. Physical-chemical arguments to explain these observations are presented. Our theoretical approach highlights the importance of molecular interactions in the complex process of gene activation/repression by multiple transcription factor proteins.


Assuntos
DNA/química , Modelos Químicos , Simulação por Computador , DNA/genética , DNA/metabolismo , Proteínas de Ligação a DNA/química , Proteínas de Ligação a DNA/genética , Proteínas de Ligação a DNA/metabolismo , Cinética , Método de Monte Carlo , Proteína Supressora de Tumor p53/química , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo
2.
J Chem Phys ; 151(7): 074109, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438708

RESUMO

It is a challenge to obtain an accurate model of the state-to-state dynamics of a complex biological system from molecular dynamics (MD) simulations. In recent years, Markov state models have gained immense popularity for computing state-to-state dynamics from a pool of short MD simulations. However, the assumption that the underlying dynamics on the reduced space is Markovian induces a systematic bias in the model, especially in biomolecular systems with complicated energy landscapes. To address this problem, we have devised a new approach we call quasistationary distribution kinetic Monte Carlo (QSD-KMC) that gives accurate long time state-to-state evolution while retaining the entire time resolution even when the dynamics is highly non-Markovian. The proposed method is a kinetic Monte Carlo approach that takes advantage of two concepts: (i) the quasistationary distribution, the distribution that results when a trajectory remains in one state for a long time (the dephasing time), such that the next escape is Markovian, and (ii) dynamical corrections theory, which properly accounts for the correlated events that occur as a trajectory passes from state to state before it settles again. In practice, this is achieved by specifying, for each escape, the intermediate states and the final state that has resulted from the escape. Implementation of QSD-KMC imposes stricter requirements on the lengths of the trajectories than in a Markov state model approach as the trajectories must be long enough to dephase. However, the QSD-KMC model produces state-to-state trajectories that are statistically indistinguishable from an MD trajectory mapped onto the discrete set of states for an arbitrary choice of state decomposition. Furthermore, the aforementioned concepts can be used to construct a Monte Carlo approach to optimize the state boundaries regardless of the initial choice of states. We demonstrate the QSD-KMC method on two one-dimensional model systems, one of which is a driven nonequilibrium system, and on two well-characterized biomolecular systems.


Assuntos
Simulação de Dinâmica Molecular , Método de Monte Carlo , Cinética
3.
J Appl Meas ; 20(3): 293-309, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31390604

RESUMO

The purpose of the present paper was twofold: (a) to use 95% confidence intervals of the item and test information functions as a means of visualizing differences between groups on the information provided at the item and test levels, and, (b) to statistically compare item and test information functions as a method for evaluating differential item and differential test functioning. Participants were 2,305 high school students who took a Mathematics National entrance examination in Saudi Arabia. Item and test information functions, conditional standard errors of measurement and reliability were estimated for both males and females. Differences between groups became evident when plotting 95% confidence intervals of the item and test information functions and the visual findings were confirmed using population-based Z-tests of point estimates using a Monte-Carlo simulation. It was concluded that differential group behavior at the item and test levels can be evidenced using information functions and inferential tests of significance can be constructed using the bootstrap distribution. The current procedure involves both item difficulties and discrimination indices and provides increased sensitivity over the traditional methods relying on item difficulties only.


Assuntos
Psicometria , Interpretação Estatística de Dados , Feminino , Humanos , Masculino , Método de Monte Carlo , Reprodutibilidade dos Testes
4.
J Chem Theory Comput ; 15(9): 5116-5134, 2019 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-31386808

RESUMO

Enzymes play a pivotal role in all biological systems. These biomachines are the most effective catalysts known, dramatically enhancing the rate of reactions by more than 10 orders of magnitude relative to the uncatalyzed reactions in solution. Predicting the correct, mechanistically appropriate binding modes for substrate and product, as well as all reaction intermediates and transition states, along a reaction pathway is immensely challenging and remains an unsolved problem. In the present work, we developed an effective methodology for identifying probable binding modes of multiple ligand states along a reaction coordinate in an enzyme active site. The program is called EnzyDock and is a CHARMM-based multistate consensus docking program that includes a series of protocols to predict the chemically relevant orientation of substrate, reaction intermediates, transition states, product, and inhibitors. EnzyDock is based on simulated annealing molecular dynamics and Monte Carlo sampling and allows ligand, as well as enzyme side-chain and backbone flexibility. The program can employ many user-defined constraints and restraints and classical force field potentials, as well as a range of hybrid quantum mechanics-molecular mechanics potentials. Herein, we apply EnzyDock to several different kinds of problems. First, we study two terpene synthase reactions, namely bornyl diphosphate synthase and the bacterial diterpene synthase CotB2. Second, we use EnzyDock to predict reaction coordinate states in a pair of Diels-Alder reactions in the enzymes spirotetronate AbyU and LepI. Third, we study a couple of racemases: the cofactor-dependent serine racemase and the cofactor independent proline racemase. Finally, we study several cases of covalent docking involving the Michael addition reaction. For all systems we predict binding modes that are consistent with available experimental observations, as well as with theoretical modeling studies from the literature. EnzyDock provides a platform for generating mechanistic insight into enzyme reactions, useful and reliable starting points for in-depth multiscale modeling projects, and rational design of noncovalent and covalent enzyme inhibitors.


Assuntos
Racemases e Epimerases/química , Ligantes , Modelos Moleculares , Estrutura Molecular , Método de Monte Carlo , Engenharia de Proteínas , Teoria Quântica , Racemases e Epimerases/metabolismo
5.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 36(4): 633-642, 2019 Aug 25.
Artigo em Chinês | MEDLINE | ID: mdl-31441265

RESUMO

The deoxyribonucleic acid (DNA) molecule damage simulations with an atom level geometric model use the traversal algorithm that has the disadvantages of quite time-consuming, slow convergence and high-performance computer requirement. Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm based on the spatial distributions of energy depositions and hydroxyl radicals (·OH). The algorithm with probability and statistics can quickly get the DNA strand break yields and help to study the variation pattern of the clustered DNA damage. Firstly, we simulated the transportation of protons and secondary particles through the nucleus, as well as the ionization and excitation of water molecules by using Geant4-DNA that is the Monte Carlo simulation toolkit for radiobiology, and got the distributions of energy depositions and hydroxyl radicals. Then we used the damage probability functions to get the spatial distribution dataset of DNA damage points in a simplified geometric model. The DBSCAN clustering algorithm based on damage points density was used to determine the single-strand break (SSB) yield and double-strand break (DSB) yield. Finally, we analyzed the DNA strand break yield variation trend with particle linear energy transfer (LET) and summarized the variation pattern of damage clusters. The simulation results show that the new algorithm has a faster simulation speed than the traversal algorithm and a good precision result. The simulation results have consistency when compared to other experiments and simulations. This work achieves more precise information on clustered DNA damage induced by proton radiation at the molecular level with high speed, so that it provides an essential and powerful research method for the study of radiation biological damage mechanism.


Assuntos
Algoritmos , Dano ao DNA , DNA/efeitos da radiação , Transferência Linear de Energia , Simulação por Computador , Método de Monte Carlo , Prótons
6.
Waste Manag ; 96: 128-135, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31376956

RESUMO

This study aimed at quantification of co-combustion behaviors and kinetic parameters of textile dyeing sludge (TDS) and shaddock peel (SP) in response to blend ratio, heating rate, and temperature. The experimental responses of mass loss (ML) and mass loss rate (MLR) measured using a thermogravimetric analyzer were also estimated using the best-fit multiple non-linear regression (MNLR) models. The independent validations of the models led to high coefficients of determination of 99.8% for ML and 83.8% for MLR. Stochastic uncertainty associated with the model predictors was assessed using Monte Carlo simulations. Our results indicated that the overall cumulative uncertainty was greater in the model predictions of MLR than ML.


Assuntos
Esgotos , Têxteis , Cinética , Método de Monte Carlo , Temperatura Ambiente
7.
Pharm Res ; 36(10): 146, 2019 Aug 08.
Artigo em Inglês | MEDLINE | ID: mdl-31396727

RESUMO

PURPOSE: CTB-001, a recently developed generic version of bivalirudin, an FDA-approved anticoagulant used for prophylaxis and treatment of cardiovascular diseases, has shown good efficacy and safety in clinical trials. We characterized the pharmacokinetics (PK) and pharmacodynamics (PD) of CTB-001 by modeling and simulation analysis. METHODS: PK/PD data were collected from a randomized, double-blind, placebo-controlled, single-dose, dose-escalation phase 1 study conducted in 24 healthy Korean male subjects. PK/PD analysis was conducted sequentially by nonlinear mixed-effects modeling implemented in NONMEM®. Monte-Carlo simulations were conducted for PK, activated partial thromboplastin time (aPTT), prothrombin time (PT), and thrombin time (TT). RESULTS: The CTB-101 PK was best described by a three-compartment linear model with a saturable binding peripheral compartment. All PD endpoints showed dose-response relationship, and their changes over time paralleled those of CTB-101 concentrations. A simple maximum effect model best described the aPTT, PT in INR, PT in seconds, and TT, whereas an inhibitory simple maximum effect model best described PT in percentages. The maximum duration of effect of CTB-001 on aPTT prolongation was 52.1 s. CONCLUSIONS: The modeling and simulation analysis well-characterized the PK and PD of CTB-001 in healthy Koreans, which will be valuable for identifying optimal dosing regimens of CBT-001.


Assuntos
Anticoagulantes/farmacologia , Hirudinas/farmacologia , Modelos Biológicos , Fragmentos de Peptídeos/farmacologia , Adulto , Anticoagulantes/farmacocinética , Simulação por Computador , Relação Dose-Resposta a Droga , Método Duplo-Cego , Medicamentos Genéricos , Hirudinas/farmacocinética , Humanos , Masculino , Método de Monte Carlo , Fragmentos de Peptídeos/farmacocinética , Tempo de Protrombina , Proteínas Recombinantes/farmacocinética , Proteínas Recombinantes/farmacologia , Resultado do Tratamento , Adulto Jovem
8.
BMC Bioinformatics ; 20(1): 411, 2019 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-31362713

RESUMO

BACKGROUND: Linear mixed-effects models (LMM) are a leading method in conducting genome-wide association studies (GWAS) but require residual maximum likelihood (REML) estimation of variance components, which is computationally demanding. Previous work has reduced the computational burden of variance component estimation by replacing direct matrix operations with iterative and stochastic methods and by employing loose tolerances to limit the number of iterations in the REML optimization procedure. Here, we introduce two novel algorithms, stochastic Lanczos derivative-free REML (SLDF_REML) and Lanczos first-order Monte Carlo REML (L_FOMC_REML), that exploit problem structure via the principle of Krylov subspace shift-invariance to speed computation beyond existing methods. Both novel algorithms only require a single round of computation involving iterative matrix operations, after which their respective objectives can be repeatedly evaluated using vector operations. Further, in contrast to existing stochastic methods, SLDF_REML can exploit precomputed genomic relatedness matrices (GRMs), when available, to further speed computation. RESULTS: Results of numerical experiments are congruent with theory and demonstrate that interpreted-language implementations of both algorithms match or exceed existing compiled-language software packages in speed, accuracy, and flexibility. CONCLUSIONS: Both the SLDF_REML and L_FOMC_REML algorithms outperform existing methods for REML estimation of variance components for LMM and are suitable for incorporation into existing GWAS LMM software implementations.


Assuntos
Algoritmos , Genômica , Funções Verossimilhança , Modelos Lineares , Método de Monte Carlo , Software , Processos Estocásticos , Fatores de Tempo
9.
Phys Chem Chem Phys ; 21(32): 17475-17493, 2019 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-31328203

RESUMO

A set of disordered interacting building blocks may form ordered structures by means of a self-assembling process. An external intervention in the system by adding a chemical species or by applying forces leads to different self-assembly scenarios with the appearance of new structures. For instance, the formation of microtubules, gels, virus capsides, cells and living beings among others takes place by self-assembly under nonequilibrium conditions. A general evolution criterion able to account for why nature selects some structures outside equilibrium and not others is lacking. Nevertheless, progress in the understanding of nonequilibrium self-assembly (NESA) mechanisms has been made thanks to the formulation of models that take particular situations into consideration. We review recent efforts devoted to describing self-assembly out of equilibrium and we provide a reference linking several current concepts in order to help in the development of new models and experimental studies. We hope that the knowledge of the intimate mechanisms leading to the formation of structures will make the implementation of re-configurable and bio-inspired materials possible and give a simpler perspective on the understanding of the emergence of life.


Assuntos
Modelos Teóricos , Fenômenos Físicos , Fenômenos Biofísicos , Células/química , Géis/química , Cinética , Método de Monte Carlo , Nanopartículas/química , Polímeros/química , Termodinâmica , Vírus/química
10.
J Chem Theory Comput ; 15(8): 4660-4672, 2019 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-31282669

RESUMO

DNA cyclization is a powerful technique to gain insight into the nature of DNA bending. While the wormlike chain model provides a good description of small to moderate bending fluctuations, it is expected to break down for large bending. Recent cyclization experiments on strongly bent shorter molecules indeed suggest enhanced flexibility over and above that expected from the wormlike chain. Here, we use a coarse-grained model of DNA to investigate the subtle thermodynamics of DNA cyclization for molecules ranging from 30 to 210 base pairs. As the molecules get shorter, we find increasing deviations between our computed equilibrium j-factor and the classic wormlike chain predictions of Shimada and Yamakawa for a torsionally aligned looped molecule. These deviations are due to sharp kinking, first at nicks, and only subsequently in the body of the duplex. At the shortest lengths, substantial fraying at the ends of duplex domains is the dominant method of relaxation. We also estimate the dynamic j-factor measured in recent FRET experiments. We find that the dynamic j-factor is systematically larger than its equilibrium counterpart-with the deviation larger for shorter molecules-because not all the stress present in the fully cyclized state is present in the transition state. These observations are important for the interpretation of recent cyclization experiments, suggesting that measured anomalously high j-factors may not necessarily indicate non-WLC behavior in the body of duplexes.


Assuntos
DNA Circular/química , Pareamento de Bases , Ciclização , Elasticidade , Modelos Moleculares , Método de Monte Carlo , Conformação de Ácido Nucleico , Termodinâmica
11.
J Chem Phys ; 151(1): 014901, 2019 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-31272182

RESUMO

The elasticity of dsDNA molecules is investigated by Monte Carlo simulations based on a coarse-grained model of DNA. The force-displacement (f-r) curves are computed under the constraints of the constant force (Gibbs) or the constant length (Helmholtz) ensemble. Particular attention was paid to the compressional (negative) and weak tensile forces. It was confirmed that simulations using the vector Gibbs ensemble fail to represent the compression behavior of polymers. Simulations using the scalar Gibbs protocol resulted in a qualitatively correct compressional response of DNA provided that the quadratic averages of displacements were employed. Furthermore, a well-known shortcoming of the popular Marko-Siggia relation for DNA elasticity at weak tensile forces is elucidated. Conversely, the function f-r from the simulation at the constant length constraint, as well as the new closed-form expressions, provides a realistic depiction of the DNA elasticity over the wide range of negative and positive forces. Merely a qualitative resemblance of the compression functions f-r predicted by the employed approaches supports the notion that the elastic response of DNA molecules may be greatly affected by the specifics of the experimental setups and the kind of averaging of the measured variable.


Assuntos
DNA/química , Microscopia de Força Atômica , Método de Monte Carlo , Pinças Ópticas
12.
J Chem Phys ; 151(2): 024106, 2019 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-31301707

RESUMO

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. We combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.


Assuntos
Algoritmos , Expressão Gênica , Modelos Genéticos , Método de Monte Carlo , Análise de Célula Única , Teorema de Bayes
13.
J Phys Chem A ; 123(32): 7075-7086, 2019 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-31310526

RESUMO

The nitric oxide synthase (NOS) enzyme consists of multiple domains connected by flexible random coil tethers. In a catalytic cycle, the NOS domains move within the limits determined by the length and flexibility of the interdomain tethers and form docking complexes with each other. This process represents a key component of the electron transport from the flavin adenine dinucleotide/reduced nicotinamide adenine dinucleotide phosphate binding domain to the catalytic heme centers located in the oxygenase domain. Studying the conformational behavior of NOS is therefore imperative for a full understanding of the overall catalytic mechanism. In this work, we have investigated the equilibrium positional distributions of the NOS domains and the bound calmodulin (CaM) by using Monte Carlo calculations of the NOS conformations. As a main experimental reference, we have used the magnetic dipole interaction between a bifunctional spin label attached to T34C/S38C mutant CaM and the NOS heme centers, which was measured by pulsed electron paramagnetic resonance. In general, the calculations of the conformational distributions allow one to determine the range and statistics of positions occupied by the tethered protein domains, assess the crowding effect of the multiple domains on each other, evaluate the accessibility of various potential domain docking sites, and estimate the interaction energies required to achieve target populations of the docked states. In the particular application described here, we have established the specific mechanisms by which the bound CaM facilitates the flavin mononucleotide (FMN)/heme interdomain docking in NOS. We have also shown that the intersubunit FMN/heme domain docking and electron transfer in the homodimeric NOS protein are dictated by the existing structural makeup of the protein. Finally, from comparison of the calculated and experimental docking probabilities, the characteristic stabilization energies for the CaM/heme domain and the FMN domain/heme domain docking complexes have been estimated as -4.5kT and -10.5kT, respectively.


Assuntos
Óxido Nítrico Sintase/química , Espectroscopia de Ressonância de Spin Eletrônica , Modelos Moleculares , Método de Monte Carlo , Óxido Nítrico Sintase/metabolismo , Conformação Proteica
14.
Prev Vet Med ; 169: 104703, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31311629

RESUMO

Pig production in Kenya is hampered by seasonal markets. As an alternative outlet for the finished pigs, several value-added meat-processing firms have been established. Sausage, which is produced using casings derived from intestines of pigs, is one form of processed meats. Kenya imports several kgs of natural casings every year; and a recent concern is Swine vesicular disease virus (SVDV), which has never been reported in Kenya, might be introduced via natural casings imported from Italy. To determine conditions (with associated probabilities) that could lead to the introduction of SVDV, a quantitative risk assessment model was developed. Using Monte Carlo simulations at 10,000 iterations, the probability of introducing SVDV was estimated to be 1.9x10-8. Based on the suggested volume of import and mitigations used in the analysis, contaminated casings derived from an estimated 0.003 (Range = 8.1x10-8 - 0.08) infected pigs will be included in the consignment each year. The critical pathway analysis revealed that rigorous surveillance programs in Italy have a potential to dramatically reduce the risk of introducing SVDV into Kenya by this route.


Assuntos
Microbiologia de Alimentos/métodos , Produtos da Carne/virologia , Doença Vesicular Suína/epidemiologia , Doença Vesicular Suína/prevenção & controle , Matadouros , Animais , Enterovirus Humano B , Itália/epidemiologia , Quênia/epidemiologia , Método de Monte Carlo , Medição de Risco , Suínos
15.
BMC Bioinformatics ; 20(1): 394, 2019 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-31311497

RESUMO

BACKGROUND: High-dimensional data of discrete and skewed nature is commonly encountered in high-throughput sequencing studies. Analyzing the network itself or the interplay between genes in this type of data continues to present many challenges. As data visualization techniques become cumbersome for higher dimensions and unconvincing when there is no clear separation between homogeneous subgroups within the data, cluster analysis provides an intuitive alternative. The aim of applying mixture model-based clustering in this context is to discover groups of co-expressed genes, which can shed light on biological functions and pathways of gene products. RESULTS: A mixture of multivariate Poisson-log normal (MPLN) model is developed for clustering of high-throughput transcriptome sequencing data. Parameter estimation is carried out using a Markov chain Monte Carlo expectation-maximization (MCMC-EM) algorithm, and information criteria are used for model selection. CONCLUSIONS: The mixture of MPLN model is able to fit a wide range of correlation and overdispersion situations, and is suited for modeling multivariate count data from RNA sequencing studies. All scripts used for implementing the method can be found at https://github.com/anjalisilva/MPLNClust .


Assuntos
Algoritmos , RNA/química , Análise por Conglomerados , Sequenciamento de Nucleotídeos em Larga Escala , Cadeias de Markov , Modelos Teóricos , Método de Monte Carlo , RNA/genética , RNA/metabolismo , Análise de Sequência de RNA , Interface Usuário-Computador
16.
Rev Bras Enferm ; 72(3): 617-623, 2019 Jun 27.
Artigo em Inglês, Português | MEDLINE | ID: mdl-31269124

RESUMO

OBJECTIVE: To analyze cost-effectiveness and to calculate incremental cost-effectiveness ratio of the use of infusion pumps with drug library to reduce errors in intravenous drug administration in pediatric and neonatal patients in Intensive Care Units. METHODS: Mathematical modeling for economic analysis of the decision tree type. The base case was composed of reference and alternative settings. The target population was neonates and pediatric patients hospitalized in Pediatric and Neonatal Intensive Care Units, comprising a cohort of 15,034 patients. The cost estimate was based on the bottom-up and top-down approaches. RESULTS: The decision tree, after RollBack, showed that the infusion pump with drug library may be the best strategy to avoid errors in intravenous drugs administration. CONCLUSION: The analysis revealed that the conventional pump, although it has the lowest cost, also has lower effectiveness.


Assuntos
Bombas de Infusão/economia , Bombas de Infusão/normas , Erros de Medicação/prevenção & controle , Administração Intravenosa/métodos , Administração Intravenosa/normas , Brasil , Análise Custo-Benefício , Humanos , Recém-Nascido , Unidades de Terapia Intensiva Neonatal/organização & administração , Unidades de Terapia Intensiva Neonatal/estatística & dados numéricos , Unidades de Terapia Intensiva Pediátrica/organização & administração , Unidades de Terapia Intensiva Pediátrica/estatística & dados numéricos , Erros de Medicação/economia , Erros de Medicação/enfermagem , Método de Monte Carlo , Avaliação da Tecnologia Biomédica/métodos
17.
Chemosphere ; 233: 862-872, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31340412

RESUMO

Groundwater fluoride contamination has long been recognized as a water-related health issue in some parts of Ghana. However, the extent of fluoride contamination and the related human health risk to the communities in the fluoride endemic areas are not adequately studied. In this paper, fluoride concentrations in existing and newly drilled wells were assessed. Probabilistic non carcinogenic human health risk assessment, uncertainty and sensitivity analysis for three age groups (Group A: 0-10 years; Group B: 11-20 years; Group C: 21-72 years) was also carried out using Monte Carlo simulation technique. The results showed that, 27.27% and 15.38% of the existing wells in the Bongo and Kassena Nankana West districts have fluoride values above the guideline value 1.5 mg L-1 respectively. The non-carcinogenic risk of fluoride associated with oral ingestion recorded a mean Hazard Quotient (HQ) > 1 for younger age group (0-10 years) in all the study areas signifying potential health risk to this age group. Additionally, when the upper 95th percentile is used for the HQ, the oral ingestion for all the age categories recorded an HQ > 1. Sensitivity analyses indicated that fluoride concentration in the drinking water and ingestion rate were the most relevant variables in the model to reduce the potential health effect. The study established the basis for a strong advocacy and public awareness on the effect of water quality on human health and proposed some management strategies to guide future groundwater resources management to reduce the potential health risk to the population.


Assuntos
Fluoretos/análise , Água Subterrânea/química , Poluentes Químicos da Água/análise , Qualidade da Água , Poços de Água , Adolescente , Adulto , Idoso , Criança , Pré-Escolar , Gana , Humanos , Lactente , Recém-Nascido , Pessoa de Meia-Idade , Minerais/análise , Método de Monte Carlo , Medição de Risco , Adulto Jovem
18.
BMC Bioinformatics ; 20(1): 295, 2019 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-31146686

RESUMO

BACKGROUND: The real-time quantitative polymerase chain reaction (qPCR) is routinely used for quantification of nucleic acids and is considered the gold standard in the field of relative nucleic acid measurements. The efficiency of the qPCR reaction is one of the most important parameters in data analysis in qPCR experiments. The Minimum Information for publication of Quantitative real-time PCR Experiments (MIQE) guidelines recommends the calibration curve as the method of choice for estimation of qPCR efficiency. The precision of this method has been reported to be between SD = 0.007 (three replicates) and SD = 0.022 (no replicates). RESULTS: In this article, we present a novel approach to the analysis of qPCR data which has been obtained by running a dilution series. Unlike previously developed methods, our method, Pairwise Efficiency, involves a new formula that describes pairwise relationships between data points on separate amplification curves and thus enables extensive statistics. The comparison of Pairwise Efficiency with the calibration curve by Monte Carlo simulation shows the two-folds improvement in the precision of estimations of efficiency and gene expression ratios on the same dataset. CONCLUSIONS: The Pairwise Efficiency nearly doubles the precision in qPCR efficiency determinations compared to standard calibration curve method. This paper demonstrates that applications of combinatorial treatment of data provide the improvement of the determination.


Assuntos
Reação em Cadeia da Polimerase em Tempo Real/métodos , Animais , Calibragem , Linhagem Celular , Análise de Dados , Técnicas de Diluição do Indicador , Camundongos , Método de Monte Carlo
19.
Int J Nanomedicine ; 14: 4157-4165, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31239674

RESUMO

Background: During decades, all improvements and developments in radiation therapy technologies have been focused on its main goal: maximize the dose in the tumor and minimize it in surrounding normal tissues. Recently, scientists have some approaches to nanoparticles, especially gold nanoparticles (GNPs), for dose localization. Purpose: Herein, the effect of GNPs in combination with electron brachytherapy in a model of eye tumor has been investigated. Materials and methods: Monte Carlo simulation was utilized and a complete anatomical model of the eye, a tumor with 5 mm thick, and a type of Ruthenium-106 beta emitter ophthalmic plaque were simulated. Simulation results have been validated by a Plexiglas eye phantom and film dosimetry, experimentally. Results: The results showed using GNPs causes the dose amplification in 2 mm from the plaque surface which the higher concentration has the higher enhancement. At more distances, Dose Enhancement Factors (DEFs) have the negative amounts, so that total delivered dose to the tumor has decreased with increasing of Au concentrations and the dose of organ at risk like sclera has increased. Conclusion: Therefore, using of GNPs along with a 106Ru/106Rh ocular plaque, as an electron emitter source, is a good choice only for superficial lesions, and it is not recommended for deeper tumors due to the parameters of radiation treatment and delivered dose to the tissues.


Assuntos
Braquiterapia , Elétrons , Neoplasias Oculares/radioterapia , Ouro/uso terapêutico , Nanopartículas Metálicas/uso terapêutico , Simulação por Computador , Relação Dose-Resposta à Radiação , Olho/patologia , Olho/efeitos da radiação , Humanos , Método de Monte Carlo , Imagens de Fantasmas , Dosagem Radioterapêutica , Reprodutibilidade dos Testes , Rutênio/química , Prata/uso terapêutico
20.
Environ Monit Assess ; 191(7): 441, 2019 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-31203453

RESUMO

An effective detection algorithm, supervising an online water system, is expected to monitor changes in water quality due to any contamination. However, contemporary event detection methods are often criticized for their high false detection rates as well as for their low true detection rates. This study proposes two new event detection methods for contamination that use multi-objective optimization by investigating the correlation between multiple types of conventional water quality sensors. While the first method incorporates non-dominated sorting genetic algorithm II (NSGA-II) with the Pearson correlation Euclidean distance (PE) method in order to maximize the probability of detection (PD) and to minimize the false alarm rate (FAR), the second method introduces fuzzy logic in order to establish a degree of correlations ranking that replaces the correlation relationship indicator threshold. Optimization is performed by using NSGA-II in the second method. The results of this study show that the incorporation of fuzzy logic with NSGA-II in event detection method have produced better results in event detection. The results also show that both methods detect all true events without producing any false alarm rates. Moreover, an uncertainty analysis on input sensor signals is performed to test the robustness of the fuzzy logic-based event detection method by employing the widely used Monte Carlo simulation (MCS) technique. Four different scenarios of uncertainty are analyzed, in particular, and the findings suggest that the proposed method is very effective in minimizing false alarm rates and maximizing true events detection, and hence, it can be regarded as one of the novel approaches to demonstrate its application in the development of an event detection algorithm.


Assuntos
Monitoramento Ambiental/métodos , Modelos Teóricos , Poluentes Químicos da Água/análise , Qualidade da Água/normas , Abastecimento de Água/normas , Algoritmos , Lógica Fuzzy , Método de Monte Carlo , Probabilidade , Incerteza
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