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1.
Medicina (B Aires) ; 80(1): 31-38, 2020.
Artículo en Español | MEDLINE | ID: mdl-32044739

RESUMEN

A stochastic simulation model allows to study and represents in a simplified manner the behavior of complex variables in terms of probability. In this context, the objective of this work is to present, through the use of information and communication technology tools, the applicability of simulation models and methods, in studies of indicators within the health sector. Through the development of a case study, this work demonstrates the potential of the @Risk and Excel technological tools in the construction of stochastic models that allow health professionals to predict, monitor and support decision making in the treatment and monitoring of indicators and indices of a population.


Asunto(s)
Comunicación en Salud , Sistemas de Información en Salud/estadística & datos numéricos , Tecnología de la Información/estadística & datos numéricos , Probabilidad , Procesos Estocásticos , Factores de Edad , Índice de Masa Corporal , Preescolar , Ecuador/epidemiología , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Método de Montecarlo , Obesidad/epidemiología , Reproducibilidad de los Resultados , Factores Sexuales
2.
Br J Radiol ; 93(1107): 20190919, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-32003576

RESUMEN

OBJECTIVE: Monte Carlo (MC) simulations substantially improve the accuracy of predicted doses. This study aims to determine and quantify the uncertainties of setting up such a MC system. METHODS: Doses simulated with two Geant4-based MC calculation codes, but independently tuned to the same beam data, have been compared. Different methods of MC modelling of a pre-absorber have been employed, either modifying the beam source parameters (descriptive) or adding the pre-absorber as a physical component (physical). RESULTS: After the independent beam modelling of both systems in water (resulting in excellent range agreement) range differences of up to 3.6/4.8 mm (1.5% of total range) in bone/brain-like tissues were found, which resulted from the use of different mean water ionisation potentials during the energy tuning process. When repeating using a common definition of water, ranges in bone/brain agreed within 0.1 mm and gamma-analysis (global 1%,1mm) showed excellent agreement (>93%) for all patient fields. However, due to a lack of modelling of proton fluence loss in the descriptive pre-absorber, differences of 7% in absolute dose between the pre-absorber definitions were found. CONCLUSION: This study quantifies the influence of using different water ionisation potentials during the MC beam modelling process. Furthermore, when using a descriptive pre-absorber model, additional Faraday cup or ionisation chamber measurements with pre-absorber are necessary. ADVANCES IN KNOWLEDGE: This is the first study quantifying the uncertainties caused by the MC beam modelling process for proton pencil beam scanning, and a more detailed beam modelling process for MC simulations is proposed to minimise the influence of critical parameters.


Asunto(s)
Método de Montecarlo , Terapia de Protones/métodos , Incertidumbre , Absorción de Radiación , Aire , Huesos/efectos de la radiación , Encéfalo/efectos de la radiación , Humanos , Hipofraccionamiento de la Dosis de Radiación , Dosificación Radioterapéutica , Reproducibilidad de los Resultados , Agua
3.
Lancet ; 395(10225): 689-697, 2020 02 29.
Artículo en Inglés | MEDLINE | ID: mdl-32014114

RESUMEN

BACKGROUND: Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions. METHODS: We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23-24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI). FINDINGS: In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47-2·86) and that 75 815 individuals (95% CrI 37 304-130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8-7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227-805), 113 (57-193), 98 (49-168), 111 (56-191), and 80 (40-139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1-2 weeks. INTERPRETATION: Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally. FUNDING: Health and Medical Research Fund (Hong Kong, China).


Asunto(s)
Simulación por Computador , Infecciones por Coronavirus/epidemiología , Epidemias , China/epidemiología , Infecciones por Coronavirus/transmisión , Predicción , Hospitalización/estadística & datos numéricos , Humanos , Periodo de Incubación de Enfermedades Infecciosas , Internacionalidad , Cadenas de Markov , Método de Montecarlo , Prevalencia
4.
Environ Monit Assess ; 192(2): 100, 2020 Jan 08.
Artículo en Inglés | MEDLINE | ID: mdl-31912242

RESUMEN

Water temperature is a key characteristic defining chemical, physical, and biologic conditions in riverine systems. Models of riverine water quality require many inputs, which are commonly beset by uncertainty. This study presents an uncertainty analysis of inputs to the stream-temperature simulation model HFLUX. This paper's assessment relies on a Markov chain Monte Carlo (MCMC) analysis with the DREAM algorithm, which has fast convergence rate and good accuracy. The inputs herein considered are the river width and depth, percent shade, view to sky, streamflow, and the minimum and maximum values of inputs required for uncertainty analysis. The results are presented as histograms for each input specifying the input's uncertainty. A comparison of the observational data with the DREAM algorithm estimates yielded a maximum error equal to 7.5%, which indicates excellent performance of the DREAM algorithm in ascertaining the effect of uncertainty in riverine water quality assessment.


Asunto(s)
Monitoreo del Ambiente/métodos , Hidrodinámica , Ríos , Algoritmos , Teorema de Bayes , Cadenas de Markov , Método de Montecarlo , Temperatura Ambiental , Incertidumbre , Agua/química , Calidad del Agua
5.
J Chem Phys ; 152(2): 025101, 2020 Jan 14.
Artículo en Inglés | MEDLINE | ID: mdl-31941320

RESUMEN

Many fundamental biological processes are regulated by protein-DNA complexes called synaptosomes, which possess multiple interaction sites. Despite the critical importance of synaptosomes, the mechanisms of their formation are not well understood. Because of the multisite nature of participating proteins, it is widely believed that their search for specific sites on DNA involves the formation and breaking of DNA loops and sliding in the looped configurations. In reality, DNA in live cells is densely covered by other biological molecules that might interfere with the formation of synaptosomes. In this work, we developed a theoretical approach to evaluate the role of obstacles in the target search of multisite proteins when the formation of DNA loops and the sliding in looped configurations are possible. Our theoretical method is based on analysis of a discrete-state stochastic model that uses a master equations approach and extensive computer simulations. It is found that the obstacle slows down the search dynamics in the system when DNA loops are long-lived, but the effect is minimal for short-lived DNA loops. In addition, the relative positions of the target and the obstacle strongly influence the target search kinetics. Furthermore, the presence of the obstacle might increase the noise in the system. These observations are discussed using physical-chemical arguments. Our theoretical approach clarifies the molecular mechanisms of formation of protein-DNA complexes with multiple interactions sites.


Asunto(s)
ADN/química , Simulación de Dinámica Molecular , Proteínas/química , Método de Montecarlo
6.
J Chem Theory Comput ; 16(2): 1349-1358, 2020 Feb 11.
Artículo en Inglés | MEDLINE | ID: mdl-31909999

RESUMEN

High-speed (HS) atomic force microscopy (AFM) is a prominent imaging technology that observes large-scale structural dynamics of biomolecules near the physiological condition, but the AFM data are limited to the surface shape of specimens. Rigid-body fitting methods were developed to obtain molecular structures that fit to an AFM image, without accounting for conformational changes. Here, we developed a method to fit flexibly a three-dimensional (3D) biomolecular structure into an AFM image. First, we describe a method to produce a pseudo-AFM image from a given 3D structure in a differentiable form. Then, using a correlation function between the experimental AFM image and the computational pseudo-AFM image, we developed a flexible fitting molecular dynamics (MD) simulation method by which we obtain protein structures that well fit to the given AFM image. We first test it with a twin experiment; using an AFM image produced from a protein structure different from its native conformation as a reference, we performed the flexible fitting MD simulations to sample conformations that fit well the reference AFM image, and the method was confirmed to work well. Then, parameter dependence in the protocol was discussed. Finally, we applied the method to a real experimental HS-AFM image for a flagellar protein FlhA, demonstrating its applicability. We also test the rigid-body fitting of a molecular structure to an AFM image. Our method will be a general tool for dynamic structure modeling based on HS-AFM images and is publicly available through the CafeMol software.


Asunto(s)
Microscopía de Fuerza Atómica , Modelos Químicos , Simulación de Dinámica Molecular , Proteínas/química , Método de Montecarlo , Conformación Proteica
7.
BMC Infect Dis ; 20(1): 74, 2020 Jan 23.
Artículo en Inglés | MEDLINE | ID: mdl-31973753

RESUMEN

BACKGROUND: Staphylococcus aureus is one of the major causes of bloodstream infections (BSI) worldwide, representing a major challenge for public health due to its resistance profile. Higher vancomycin minimum inhibitory concentrations (MIC) in S. aureus are associated with treatment failure and defining optimal empiric options for BSIs in settings where these isolates are prevalent is rather challenging. In silico pharmacodynamic models based on stochastic simulations (Monte Carlo) are important tools to estimate best antimicrobial regimens in different scenarios. We aimed to compare the pharmacodynamic profiles of different antimicrobials regimens for the treatment of S. aureus BSI in an environment with high vancomycin MIC. METHODS: Steady-state drug area under the curve ratio to MIC (AUC/MIC) or the percent time above MIC (fT > MIC) were modeled using a 5000-patient Monte Carlo simulation to achieve pharmacodynamic exposures against 110 consecutive S. aureus isolates associated with BSI. RESULTS: Cumulative fractions of response (CFRs) against all S. aureus isolates were 98% for ceftaroline; 79% and 92% for daptomycin 6 mg/kg q24h and for the high dose of 10 mg/kg q24h, respectively; 77% for linezolid 600 mg q12h when MIC was read according to CLSI M100-S26 instructions, and 64% when MIC was considered at the total growth inhibition; 65% and 86% for teicoplanin, three loading doses of 400 mg q12 h followed by 400 mg q24 h and for teicoplanin 400 mg q12 h, respectively; 61% and 76% for vancomycin 1000 mg q12 h and q8 h, respectively. CONCLUSIONS: Based on this model, ceftaroline and high-dose daptomycin regimens delivered best pharmacodynamic exposures against S. aureus BSIs. Teicoplanin higher dose regimen achieved the best CFR (86%) among glycopeptides, although optimal threshold was not achieved, and vancomycin performance was critically affected by the S. aureus vancomycin MIC ≥2 mg/L. Linezolid effectiveness (CFR of 73%) is also affected by high prevalence of isolates with linezolid MIC ≥2 mg/L. These data show the need to continually evaluate the pharmacodynamic profiles of antimicrobials for empiric treatment of these infections.


Asunto(s)
Antibacterianos/farmacología , Bacteriemia/tratamiento farmacológico , Infecciones Estafilocócicas/tratamiento farmacológico , Staphylococcus aureus/efectos de los fármacos , Vancomicina/farmacología , Antibacterianos/farmacocinética , Bacteriemia/microbiología , Brasil , Cefalosporinas/farmacocinética , Cefalosporinas/farmacología , Daptomicina/farmacocinética , Daptomicina/farmacología , Humanos , Staphylococcus aureus Resistente a Meticilina/efectos de los fármacos , Pruebas de Sensibilidad Microbiana , Método de Montecarlo , Estudios Retrospectivos , Infecciones Estafilocócicas/microbiología , Vancomicina/farmacocinética
8.
Br J Radiol ; 93(1107): 20190332, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31944824

RESUMEN

Proton minibeam therapy (PMBT) is a form of spatially fractionated radiotherapy wherein broad beam radiation is replaced with segmented minibeams-either parallel, planar minibeam arrays generated by a multislit collimator or scanned pencil beams that converge laterally at depth to create a uniform dose layer at the tumor. By doing so, the spatial pattern of entrance dose is considerably modified while still maintaining tumor dose and efficacy. Recent studies using computational modeling, phantom experiments, in vitro and in vivo preclinical models, and early clinical feasibility assessments suggest that unique physical and biological attributes of PMBT can be exploited for future clinical benefit. We outline some of the guiding principle of PMBT in this concise overview of this emerging area of preclinical and clinical research inquiry.


Asunto(s)
Creatividad , Neoplasias/radioterapia , Terapia de Protones/métodos , Absorción de Radiación , Algoritmos , Fraccionamiento de la Dosis de Radiación , Estudios de Factibilidad , Humanos , Método de Montecarlo , Tratamientos Conservadores del Órgano , Órganos en Riesgo , Radiobiología , Radiometría
9.
Top Curr Chem (Cham) ; 378(1): 14, 2020 Jan 13.
Artículo en Inglés | MEDLINE | ID: mdl-31933069

RESUMEN

Classical molecular simulations can provide significant insights into the gas adsorption mechanisms and binding sites in various metal-organic frameworks (MOFs). These simulations involve assessing the interactions between the MOF and an adsorbate molecule by calculating the potential energy of the MOF-adsorbate system using a functional form that generally includes nonbonded interaction terms, such as the repulsion/dispersion and permanent electrostatic energies. Grand canonical Monte Carlo (GCMC) is the most widely used classical method that is carried out to simulate gas adsorption and separation in MOFs and identify the favorable adsorbate binding sites. In this review, we provide an overview of the GCMC methods that are normally utilized to perform these simulations. We also describe how a typical force field is developed for the MOF, which is required to compute the classical potential energy of the system. Furthermore, we highlight some of the common analysis techniques that have been used to determine the locations of the preferential binding sites in these materials. We also review some of the early classical molecular simulation studies that have contributed to our working understanding of the gas adsorption mechanisms in MOFs. Finally, we show that the implementation of classical polarization for simulations in MOFs can be necessary for the accurate modeling of an adsorbate in these materials, particularly those that contain open-metal sites. In general, molecular simulations can provide a great complement to experimental studies by helping to rationalize the favorable MOF-adsorbate interactions and the mechanism of gas adsorption.


Asunto(s)
Gases/aislamiento & purificación , Estructuras Metalorgánicas/química , Adsorción , Dióxido de Carbono/aislamiento & purificación , Simulación por Computador , Hidrógeno/aislamiento & purificación , Modelos Químicos , Modelos Moleculares , Método de Montecarlo , Electricidad Estática , Termodinámica
10.
Adv Exp Med Biol ; 1232: 307-313, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31893425

RESUMEN

Near infrared optical tomography (NIROT) is a non-invasive imaging technique to provide physiological information e.g. the oxygenation of tissue. For image reconstruction in clinical and preclinical scenarios, models to accurately describe light propagation are needed. This work aims to assess the accuracy and efficiency of different models, which paves the way for an optimal design of model-based image reconstruction algorithms in NIROT for realistic tissue geometries and heterogeneities. Two popular simulators were evaluated: the Monte Carlo (MC) method based MCX and the finite element method (FEM) based Toast++. We compared simulated results with experimental data measured on a homogeneous silicone phantom with well-calibrated parameters. The laser light was focused on the center of the phantom surface and images were captured by a CCD camera in both reflection and transmission modes. For transmittance measurements, the two models showed good agreement. Both achieve a cosine similarity of ~99%. In contrast, for reflectance measurements, FEM results deviated more from the measured values than MC, yielding similarity values of 86% and 94%, respectively. This study recommends the use of MC for NIROT in reflection mode and both MC and FEM yield excellent results for transmission mode.


Asunto(s)
Análisis de Elementos Finitos , Modelos Teóricos , Método de Montecarlo , Tomografía Óptica , Algoritmos , Simulación por Computador , Análisis de Elementos Finitos/normas , Luz , Fantasmas de Imagen
11.
Br J Radiol ; 93(1107): 20190583, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31696729

RESUMEN

OBJECTIVE: To identify a subgroup of lung cancer plans where the analytical dose calculation (ADC) algorithm may be clinically acceptable compared to Monte Carlo (MC) dose calculation in intensity modulated proton therapy (IMPT). METHODS: Robust-optimised IMPT plans were generated for 20 patients to a dose of 70 Gy (relative biological effectiveness) in 35 fractions in Raystation. For each case, four plans were generated: three with ADC optimisation using the pencil beam (PB) algorithm followed by a final dose calculation with the following algorithms: PB (PB-PB), MC (PB-MC) and MC normalised to prescription dose (PB-MC scaled). A fourth plan was generated where MC optimisation and final dose calculation was performed (MC-MC). Dose comparison and γ analysis (PB-PB vs PB-MC) at two dose thresholds were performed: 20% (D20) and 99% (D99) with PB-PB plans as reference. RESULTS: Overestimation of the dose to 99% and mean dose of the clinical target volume was observed in all PB-MC compared to PB-PB plans (median: 3.7 Gy(RBE) (5%) (range: 2.3 to 6.9 Gy(RBE)) and 1.8 Gy(RBE) (3%) (0.5 to 4.6 Gy(RBE))). PB-MC scaled plans resulted in significantly higher CTVD2 compared to PB-PB (median difference: -4 Gy(RBE) (-6%) (-5.3 to -2.4 Gy(RBE)), p ≤ .001). The overall median γ pass rates (3%-3 mm) at D20 and D99 were 93.2% (range:62.2-97.5%) and 71.3 (15.4-92.0%). On multivariate analysis, presence of mediastinal disease and absence of range shifters were significantly associated with high γ pass rates. Median D20 and D99 pass rates with these predictors were 96.0% (95.3-97.5%) and 85.4% (75.1-92.0%). MC-MC achieved similar target coverage and doses to OAR compared to PB-PB plans. CONCLUSION: In the presence of mediastinal involvement and absence of range shifters Raystation ADC may be clinically acceptable in lung IMPT. Otherwise, MC algorithm would be recommended to ensure accuracy of treatment plans. ADVANCES IN KNOWLEDGE: Although MC algorithm is more accurate compared to ADC in lung IMPT, ADC may be clinically acceptable where there is mediastinal involvement and absence of range shifters.


Asunto(s)
Algoritmos , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Neoplasias Pulmonares/radioterapia , Método de Montecarlo , Terapia de Protones/métodos , Planificación de la Radioterapia Asistida por Computador/métodos , Radioterapia de Intensidad Modulada/métodos , Análisis de Varianza , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/patología , Fraccionamiento de la Dosis de Radiación , Tomografía Computarizada Cuatridimensional , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Neoplasias del Mediastino/radioterapia , Análisis Multivariante , Órganos en Riesgo/efectos de la radiación , Efectividad Biológica Relativa , Incertidumbre
12.
Int J Clin Pharmacol Ther ; 58(1): 50-56, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31670654

RESUMEN

OBJECTIVE: Patients with cerebral hemorrhage are often prone to intracranial infection, and meropenem is recommended for treatment. But whether the widely used dosing regimen (1 g, 2-hour infusion, every 12 hours) is suitable for antibiotic therapy is still unclear. The purpose of this study was to perform pharmacokinetic/pharmacodynamic (PK/PD) analyses of meropenem in both plasma and cerebrospinal fluid (CSF) in these patients. MATERIALS AND METHODS: Ten patients were enrolled in the present study. The blood samples and CSF samples were taken at predetermined time points and determined by our previously developed HPLC method. Pharmacokinetic parameters were then calculated, and the probability of target attainment (PTA) was calculated by the time that drug concentrations were above the minimum inhibitory concentration (%T>MIC). RESULTS: The peak meropenem concentration (Cmax) of 17.79 ± 3.38 µg/mL in plasma was reached at 2 hours, and the area under the curve (AUC) was 46.95 ± 4.37 h×µg/mL. The Cmax of 6.51 ± 1.11 µg/mL in CSF was reached at 3.50 ± 0.53 hours, and the AUC was 24.53 ± 4.28 h×µg/mL. The average penetration rate of meropenem in these patients was 52.25%. In the case where the MIC value was ≤ 1 µg/mL and using 40%T>MIC as a PK/PD index, the PTA of meropenem in both plasma and CSF were able to provide good coverage with MIC ≤ 1 µg/mL. CONCLUSION: In conclusion, this is the first study on the PK/PD analysis of meropenem in both plasma and CSF in patients with cerebral hemorrhage. The results will assist in selecting appropriate dosing regimens of meropenem in these patients.


Asunto(s)
Antibacterianos/farmacocinética , Hemorragia Cerebral , Drenaje , Meropenem/farmacocinética , Antibacterianos/sangre , Antibacterianos/líquido cefalorraquídeo , Humanos , Meropenem/sangre , Meropenem/líquido cefalorraquídeo , Pruebas de Sensibilidad Microbiana , Método de Montecarlo
13.
Br J Radiol ; 93(1107): 20190334, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31738081

RESUMEN

Dose in proton radiotherapy is generally prescribed by scaling the physical proton dose by a constant value of 1.1. Relative biological effectiveness (RBE) is defined as the ratio of doses required by two radiation modalities to cause the same level of biological effect. The adoption of an RBE of 1.1. assumes that the biological efficacy of protons is similar to photons, allowing decades of clinical dose prescriptions from photon treatments and protocols to be utilized in proton therapy. There is, however, emerging experimental evidence that indicates that proton RBE varies based on technical, tissue and patient factors. The notion that a single scaling factor may be used to equate the effects of photons and protons across all biological endpoints and doses is too simplistic and raises concern for treatment planning decisions. Here, we review the models that have been developed to better predict RBE variations in tissue based on experimental data as well as using a mechanistic approach.


Asunto(s)
Modelos Teóricos , Neoplasias/radioterapia , Terapia de Protones/métodos , Traumatismos por Radiación , Efectividad Biológica Relativa , Algoritmos , Animales , Línea Celular Tumoral , ADN/efectos de la radiación , Reparación del ADN , Humanos , Modelos Biológicos , Método de Montecarlo , Órganos en Riesgo/efectos de la radiación , Fotones/uso terapéutico , Planificación de la Radioterapia Asistida por Computador
14.
J Chem Theory Comput ; 16(1): 553-563, 2020 Jan 14.
Artículo en Inglés | MEDLINE | ID: mdl-31738552

RESUMEN

Proteins are exposed to various mechanical loads that can lead to covalent bond scissions even before macroscopic failure occurs. Knowledge of these molecular breakages is important to understand mechanical properties of the protein. In regular molecular dynamics (MD) simulations, covalent bonds are predefined, and reactions cannot occur. Furthermore, such events rarely take place on MD time scales. Existing approaches that tackle this limitation either rely on computationally expensive quantum calculations (e.g., QM/MM) or complex bond order formalisms in force fields (e.g., ReaxFF). To circumvent these limitations, we present a new reactive kinetic Monte Carlo/molecular dynamics (KIMMDY) scheme. Here, bond rupture rates are calculated based on the interatomic distances in the MD simulation and then serve as an input for a kinetic Monte Carlo step. This easily scalable hybrid approach drastically increases the accessible time scales. Using this new technique, we investigate bond ruptures in a multimillion atom system of tensed collagen, a structural protein found in skin, bones, and tendons. Our findings show a clear concentration of bond scissions near chemical cross-links in collagen. We also examine subsequent dynamic relaxation steps. Our method exhibits only a minor slowdown compared to classical MD and is straightforwardly applicable to other complex (bio)materials under load and related chemistries.


Asunto(s)
Proteínas/química , Animales , Colágeno/química , Dipéptidos/química , Humanos , Cinética , Simulación de Dinámica Molecular , Método de Montecarlo , Conformación Proteica , Teoría Cuántica , Estrés Mecánico
15.
Br J Radiol ; 93(1107): 20190669, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31799859

RESUMEN

OBJECTIVE: This study is part of ongoing efforts aiming to transit from measurement-based to combined patient-specific quality assurance (PSQA) in intensity-modulated proton therapy (IMPT). A Monte Carlo (MC) dose-calculation algorithm is used to improve the independent dose calculation and to reveal the beam modeling deficiency of the analytical pencil beam (PB) algorithm. METHODS: A set of representative clinical IMPT plans with suboptimal PSQA results were reviewed. Verification plans were recalculated using an MC algorithm developed in-house. Agreements of PB and MC calculations with measurements that quantified by the γ passing rate were compared. RESULTS: The percentage of dose planes that met the clinical criteria for PSQA (>90% γ passing rate using 3%/3 mm criteria) increased from 71.40% in the original PB calculation to 95.14% in the MC recalculation. For fields without beam modifiers, nearly 100% of the dose planes exceeded the 95% γ passing rate threshold using the MC algorithm. The model deficiencies of the PB algorithm were found in the proximal and distal regions of the SOBP, where MC recalculation improved the γ passing rate by 11.27% (p < 0.001) and 16.80% (p < 0.001), respectively. CONCLUSIONS: The MC algorithm substantially improved the γ passing rate for IMPT PSQA. Improved modeling of beam modifiers would enable the use of the MC algorithm for independent dose calculation, completely replacing additional depth measurements in IMPT PSQA program. For current users of the PB algorithm, further improving the long-tail modeling or using MC simulation to generate the dose correction factor is necessary. ADVANCES IN KNOWLEDGE: We justified a change in clinical practice to achieve efficient combined PSQA in IMPT by using the MC algorithm that was experimentally validated in almost all the clinical scenarios in our center. Deficiencies in beam modeling of the current PB algorithm were identified and solutions to improve its dose-calculation accuracy were provided.


Asunto(s)
Algoritmos , Método de Montecarlo , Terapia de Protones/normas , Garantía de la Calidad de Atención de Salud , Radioterapia de Intensidad Modulada/normas , Análisis de Datos , Humanos , Terapia de Protones/instrumentación , Terapia de Protones/métodos , Control de Calidad , Dosificación Radioterapéutica , Planificación de la Radioterapia Asistida por Computador/métodos , Planificación de la Radioterapia Asistida por Computador/normas , Planificación de la Radioterapia Asistida por Computador/estadística & datos numéricos , Radioterapia de Intensidad Modulada/instrumentación , Radioterapia de Intensidad Modulada/métodos , Reproducibilidad de los Resultados , Sincrotrones
16.
Br J Radiol ; 93(1107): 20190304, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31356107

RESUMEN

Treatment planning is the process where the prescription of the radiation oncologist is translated into a deliverable treatment. With the complexity of contemporary radiotherapy, treatment planning cannot be performed without a computerized treatment planning system. Proton therapy (PT) enables highly conformal treatment plans with a minimum of dose to tissues outside the target volume, but to obtain the most optimal plan for the treatment, there are a multitude of parameters that need to be addressed. In this review areas of ongoing improvements and research in the field of PT treatment planning are identified and discussed. The main focus is on issues of immediate clinical and practical relevance to the PT community highlighting the needs for the near future but also in a longer perspective. We anticipate that the manual tasks performed by treatment planners in the future will involve a high degree of computational thinking, as many issues can be solved much better by e.g. scripting. More accurate and faster dose calculation algorithms are needed, automation for contouring and planning is required and practical tools to handle the variable biological efficiency in PT is urgently demanded just to mention a few of the expected improvements over the coming 10 years.


Asunto(s)
Algoritmos , Predicción , Terapia de Protones/métodos , Planificación de la Radioterapia Asistida por Computador/métodos , Radioterapia Conformacional/métodos , Automatización , Exactitud de los Datos , Humanos , Método de Montecarlo , Evaluación de Necesidades , Órganos en Riesgo/diagnóstico por imagen , Terapia de Protones/tendencias , Planificación de la Radioterapia Asistida por Computador/tendencias , Radioterapia Conformacional/tendencias , Efectividad Biológica Relativa , Factores de Tiempo
17.
J Chem Theory Comput ; 16(1): 765-772, 2020 Jan 14.
Artículo en Inglés | MEDLINE | ID: mdl-31756296

RESUMEN

The folding and stability of proteins is a fundamental problem in several research fields. In the present paper, we have used different computational approaches to study the effects caused by changes in pH and for charged mutations in cold shock proteins from Bacillus subtilis (Bs-CspB). First, we have investigated the contribution of each ionizable residue for these proteins to their thermal stability using the TKSA-MC, a Web server for rational mutation via optimizing the protein charge interactions. Based on these results, we have proposed a new mutation in an already optimized Bs-CspB variant. We have evaluated the effects of this new mutation in the folding energy landscape using structure-based models in Monte Carlo simulation at constant pH, SBM-CpHMC. Our results using this approach have indicated that the charge rearrangements already in the unfolded state are critical to the thermal stability of Bs-CspB. Furthermore, the conjunction of these simplified methods was able not only to predict stabilizing mutations in different pHs but also to provide essential information about their effects in each stage of protein folding.


Asunto(s)
Bacillus subtilis/química , Proteínas Bacterianas/química , Proteínas y Péptidos de Choque por Frío/química , Secuencia de Aminoácidos , Bacillus subtilis/genética , Proteínas Bacterianas/genética , Proteínas y Péptidos de Choque por Frío/genética , Concentración de Iones de Hidrógeno , Modelos Moleculares , Método de Montecarlo , Mutación , Pliegue de Proteína , Estabilidad Proteica , Desplegamiento Proteico , Electricidad Estática
18.
Int J Sports Med ; 41(1): 44-53, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31747700

RESUMEN

The indirect identification of doping in sports can be performed by assessing athletes' hematological perturbations from the analysis of blood collected on different occasions. Because prosecution for doping based on this information requires expensive and time-consuming interpretation of blood analysis results by various expert hematologists, mathematical data screening is performed to decide which cases should be forwarded to hematologists. The current Bayesian and univariate screening of data does not process the multivariate trends of blood parameters or take the time interval between samplings into account. This work presents a computational tool that overcomes these limitations by calculating a single score, the hematological perturbation index (HPIx), for which a threshold is defined above which hematologists should be asked to assess the athlete's biological passport. The doping detection from this index, normalized for days difference between samplings based on 3, 4 or 5 consecutive samplings, is associated with true positive result rates (TP) not below 98% and false positive result rates (FP) less than 0.9%. Therefore, this tool can be useful as an early warning system of hematological perturbations to decide which athletes should be more closely monitored and which biological passports should be forwarded to hematologists for medical interpretation of data.


Asunto(s)
Doping en los Deportes , Pruebas Hematológicas , Detección de Abuso de Sustancias/métodos , Reacciones Falso Positivas , Humanos , Método de Montecarlo , Análisis Multivariante , Incertidumbre
19.
J Chem Theory Comput ; 16(2): 1284-1299, 2020 Feb 11.
Artículo en Inglés | MEDLINE | ID: mdl-31877249

RESUMEN

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes such as ligand binding or mutation can alter the function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understand the evasion by human immunodeficiency virus type-1 (HIV-1) protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight into the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among the sequence, structure, and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in the protein structure, hydrogen bonding, and protein-ligand contacts.


Asunto(s)
Farmacorresistencia Viral , Proteasa del VIH/metabolismo , VIH-1/enzimología , Ligandos , Aprendizaje Automático , Proteasa del VIH/química , Proteasa del VIH/genética , Inhibidores de la Proteasa del VIH/química , Inhibidores de la Proteasa del VIH/metabolismo , Humanos , Enlaces de Hidrógeno , Simulación de Dinámica Molecular , Método de Montecarlo , Mutación , Unión Proteica , Electricidad Estática
20.
Accid Anal Prev ; 134: 105235, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31561839

RESUMEN

To improve the road safety, policy makers relay on data analysis to enact new traffic policies. Accordingly, statistical modeling has been linked in various studies of road crash counts with excess zeros. On top of this excess zero problem, missing data are also likely to occur in the road traffic accident data. Unless the missing data are resulted randomly, the popular naive estimation may not provide reliable results for policy making. In contrast, the implementation of the Horvitz method, which inversely weights the observed data by a weight that are obtained parametrically or nonparametrically, results in reliable estimators. We received satisfactory results on the performance of our approach handling the missing data problems in both a Monte Carlo simulation and a real traffic accident data exploration.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Exactitud de los Datos , Humanos , Modelos Estadísticos , Método de Montecarlo , Distribución de Poisson
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