A cross-sectional analysis of the relationship between daily alcohol consumption and serum adiponectin levels among adults aged 40 years or more in a rural area of Korea

BACKGROUND/OBJECTIVES

Light-to-moderate alcohol consumption has been proposed to raise serum adiponectin levels, but this view is controversial. There is little information on the effect of heavy drinking. The aim of this study was to examine the relationship between alcohol consumption and serum adiponectin levels in healthy Koreans.

SUBJECTS/METHODS

The design of the study was cross-sectional, using data from the Korean Multi-Rural Communities Cohort Study (MRCohort), which is a part of the Korean Genome Epidemiology Study (KoGES). The subjects were 1542 individuals (635 men and 907 women) aged ≥ 40 years who were recruited in Yangpyeong-Gun, Kyunggi province, South Korea, in 2005 and 2006. Daily alcohol consumption was calculated from average frequency of alcohol consumption and the amount of alcohol consumed per occasion using a structured questionnaire and serum adiponectin levels were measured.

RESULTS

Although adiponectin levels appeared to be higher in those consuming moderate levels of alcohol than in nondrinkers, the difference was not statistically significant. Heavy drinking (≥ 90.0 g/day) was significantly related to reduced serum adiponectin levels (P=0.003), although the significance of the relationship was reduced after adjusting for potential confounders (P=0.061) such as age, waist/hip ratio, blood pressure, fasting blood glucose, current smoker, higher education, protein intake, vitamin C intake and vitamin E intake in men. The relation seemed to be stronger in individuals consuming alcohol in the form of takju (Korean rice wine; P=0.022).

CONCLUSIONS

Heavy alcohol drinking (≥ 90.0 g/day) may be related to lower serum adiponectin levels in Korean men.

TOPAS: an innovative proton Monte Carlo platform for research and clinical applications

PURPOSE

While Monte Carlo particle transport has proven useful in many areas (treatment head design, dose calculation, shielding design, and imaging studies) and has been particularly important for proton therapy (due to the conformal dose distributions and a finite beam range in the patient), the available general purpose Monte Carlo codes in proton therapy have been overly complex for most clinical medical physicists. The learning process has large costs not only in time but also in reliability. To address this issue, we developed an innovative proton Monte Carlo platform and tested the tool in a variety of proton therapy applications.

METHODS

Our approach was to take one of the already-established general purpose Monte Carlo codes and wrap and extend it to create a specialized user-friendly tool for proton therapy. The resulting tool, TOol for PArticle Simulation (TOPAS), should make Monte Carlo simulation more readily available for research and clinical physicists. TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on computed tomography (CT) images, score dose, fluence, etc., save and restart a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. A custom-designed TOPAS parameter control system was placed at the heart of the code to meet requirements for ease of use, reliability, and repeatability without sacrificing flexibility.

RESULTS

We built and tested the TOPAS code. We have shown that the TOPAS parameter system provides easy yet flexible control over all key simulation areas such as geometry setup, particle source setup, scoring setup, etc. Through design consistency, we have insured that user experience gained in configuring one component, scorer or filter applies equally well to configuring any other component, scorer or filter. We have incorporated key lessons from safety management, proactively removing possible sources of user error such as line-ordering mistakes. We have modeled proton therapy treatment examples including the UCSF eye treatment head, the MGH stereotactic alignment in radiosurgery treatment head and the MGH gantry treatment heads in passive scattering and scanning modes, and we have demonstrated dose calculation based on patient-specific CT data. Initial validation results show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D.

CONCLUSIONS

We have demonstrated TOPAS accuracy and usability in a variety of proton therapy setups. As we are preparing to make this tool freely available for researchers in medical physics, we anticipate widespread use of this tool in the growing proton therapy community.

The fate of Treponema denticola within human gingival epithelial cells

Treponema denticola is one of the major pathogens associated with chronic periodontitis. Bacterial invasion into gingival tissues is a critical process in the pathogenesis of periodontal disease. We recently reported that T. denticola can invade gingival epithelial cells. The aim of this study is to determine the fate of internalized T. denticola in gingival epithelial cells. Immortalized human gingival epithelial HOK-16B cells were infected with 5- (and 6-) carboxy-fluorescein diacetate succinimidyl ester (CFSE)-labeled live or heat-killed T. denticola for 24 h, and the presence of bacteria inside the cells was confirmed by confocal microscopy. Live T. denticola, but not heat-killed bacteria, invaded HOK-16B cells. Confocal microscopy also revealed that internalized T. denticola rarely colocalized with either endosomes or lysosomes. Transmission electron microscopy of infected cells showed that intracellular T. denticola was localized inside endosome-like structures. Although a culture-based antibiotics protection assay could not detect viable intracellular T. denticola 12 h after infection, a substantial number of bacteria were observed by confocal microscopy and weak expression of bacterial 16S ribosomal RNA was detected 48 h after infection. In addition, flow cytometric analysis of HOK-16B cells infected with CFSE-labeled T. denticola showed no loss of fluorescence over 48 h. Collectively, T. denticola invades gingival epithelial cells and remains within the host cells for many hours by resisting endolysosomal degradation. These findings may provide new insight into the role of T. denticola in the pathogenesis of periodontitis.

SU-E-T-500: Pencil-Beam versus Monte Carlo Based Dose Calculation for Proton Therapy Patients with Complex Geometries. Clinical Use of the TOPAS Monte Carlo System

PURPOSE

To investigate the necessity of the verification of dose distributions using Monte Carlo (MC) simulations for proton therapy of head and neck patients and other complex patient geometries.

METHODS

TOPAS, a TOol for PArticle Simulations that makes MC simulations easy-to-use for research and clinical use and is layered on top of Geant4, has been used to simulate the treatments of head and neck patients at the Massachusetts General Hospital (MGH). The resulting dose distributions have been compared to pencil beam calculations based on the XiO treatment planning system. Dose difference distributions were used to highlight areas where the two algorithms did not agree. Dose volume histograms are utilized to investigate the overall agreement of the planned doses in target structures.

RESULTS

21 head and neck patients, both nasopharynx and spinal cord, were investigated. The field complexity ranges from a single field up to 13 fields. For all patients, the dose in the clinical target volume agrees well. Nevertheless, differences in critical structures around the targets have been observed mostly due to range differences between the two algorithms.

CONCLUSIONS

Pencil beam algorithms provide an accurate description of dose in the target volume. However, we conclude that the differences between MC simulations and pencil beam algorithms in regions outside the target for complex geometries, such as present in head and neck patients, support the necessity of routine use of MC simulations for treatment verifications before treatment. TOPAS is aiming to make such routine simulations available to all researchers and clinics. An automated interface utilizing TOPAS to enable such simulations has been developed at MGH and should become routinely used in the near future for patients with complex geometries. NIH/NCI R01 CA140735.

SU-E-T-234: LET Measurement Using Nuclear Emulsion and Monte Carlo Simulation for Proton Beam

PURPOSE

The significant issue of particle therapy such as proton and carbon ion biological effect on tumors and normal tissue. This effect closely connected with linear-energy-transfer (LET). This work presents a Monte Carlo study using GEANT4 and the verification using Nuclear Emulsion to show LET for proton beam.

METHODS

National Cancer Center (NCC) has IBA Beam Nozzle and cyclotron for proton therapy. We use proton beam bragg peak range 14cm. Also, we already developed the simulation using GEANT4 and finished validation for scattering proton beam. In our simulation, we make same condition with experimental setup.Nuclear emulsion films interleaved with tissue equivalent absorbers can be fruitfully used to reconstruct proton tracks with very high precision. This Nuclear emulsion film has been supported from Nagoya University, analyzed in Pusan University, was irradiated with a therapeutic proton beam at NCC. The Emulsion packs was located at entrance and bragg peak region of proton. This position means low and high LET region. The scanning of the emulsions has been performed at Nagoya University, where a fully automated microscopic scanning technology has been developed for the OPERA experiment on neutrino oscillations.

RESULTS

We could see the reconstructed track of proton scanning emulsion. From film scanning, we got the LET distribution at low and high LET region for several proton tracks. Simulation results was similar distribution within standard deviation in acceptance level. Also we got the RBE distribution using LET measurement for proton beam.

CONCLUSIONS

We measured LET at entrance and bragg peak region using Monte Carlo study and Nuclear Emulsion film, for NCC proton beam. This results means the good observation of LET using the nuclear emulsion. And this method can be used successfully in medical field.

The effect of fractional carbon dioxide lasers on idiopathic guttate hypomelanosis: a preliminary study

BACKGROUND

Idiopathic guttate hypomelanosis (IGH) is a commonly acquired leucoderma that is characterized by discrete, round or oval porcelain-white macules ∼2-5 mm in diameter that increases in number with age. A variety of therapies with variable success rates, including cryotherapy, superficial abrasion and topical retinoids are currently being used.

OBJECTIVES

The effects of fractional CO(2) laser therapy on IGH were investigated in this pilot study.

PATIENTS AND METHODS

A total of 40 patients with IGH were enrolled. The hypopigmented lesions were treated using a 10 600-nm carbon dioxide fractional laser (CO(2) FL). Two months after a single treatment, physicians' clinical assessments were performed and the patients' overall satisfaction was evaluated.

RESULTS

The mean age of enrolled patients was 57.5 ± 10.9 years and the gender ratio was 7 : 33. The face was the most commonly treated area, although the extremities are epidemiologically the most frequently affected areas. Two months after treatment, objective assessments performed by two independent dermatologists indicated more than 50% improvement in 36 patients (90%), compared with baseline. In addition, 33 patients (82.5%) were very satisfied or satisfied with just one session of CO(2) FL treatment. Although a few patients complained of long-standing erythema and postinflammatory hyperpigmentation, these problems spontaneously resolved within 2 months after the assessments. No other noticeable side effects were observed.

CONCLUSION

CO(2) FL might be a very convenient and effective modality for treating IGH without significant side effects.

A modular method to handle multiple time-dependent quantities in Monte Carlo simulations

A general method for handling time-dependent quantities in Monte Carlo simulations was developed to make such simulations more accessible to the medical community for a wide range of applications in radiotherapy, including fluence and dose calculation. To describe time-dependent changes in the most general way, we developed a grammar of functions that we call 'Time Features'. When a simulation quantity, such as the position of a geometrical object, an angle, a magnetic field, a current, etc, takes its value from a Time Feature, that quantity varies over time. The operation of time-dependent simulation was separated into distinct parts: the Sequence samples time values either sequentially at equal increments or randomly from a uniform distribution (allowing quantities to vary continuously in time), and then each time-dependent quantity is calculated according to its Time Feature. Due to this modular structure, time-dependent simulations, even in the presence of multiple time-dependent quantities, can be efficiently performed in a single simulation with any given time resolution. This approach has been implemented in TOPAS (TOol for PArticle Simulation), designed to make Monte Carlo simulations with Geant4 more accessible to both clinical and research physicists. To demonstrate the method, three clinical situations were simulated: a variable water column used to verify constancy of the Bragg peak of the Crocker Lab eye treatment facility of the University of California, the double-scattering treatment mode of the passive beam scattering system at Massachusetts General Hospital (MGH), where a spinning range modulator wheel accompanied by beam current modulation produces a spread-out Bragg peak, and the scanning mode at MGH, where time-dependent pulse shape, energy distribution and magnetic fields control Bragg peak positions. Results confirm the clinical applicability of the method.

Efficient voxel navigation for proton therapy dose calculation in TOPAS and Geant4

A key task within all Monte Carlo particle transport codes is 'navigation', the calculation to determine at each particle step what volume the particle may be leaving and what volume the particle may be entering. Navigation should be optimized to the specific geometry at hand. For patient dose calculation, this geometry generally involves voxelized computed tomography (CT) data. We investigated the efficiency of navigation algorithms on currently available voxel geometry parameterizations in the Monte Carlo simulation package Geant4: G4VPVParameterisation, G4VNestedParameterisation and G4PhantomParameterisation, the last with and without boundary skipping, a method where neighboring voxels with the same Hounsfield unit are combined into one larger voxel. A fourth parameterization approach (MGHParameterization), developed in-house before the latter two parameterizations became available in Geant4, was also included in this study. All simulations were performed using TOPAS, a tool for particle simulations layered on top of Geant4. Runtime comparisons were made on three distinct patient CT data sets: a head and neck, a liver and a prostate patient. We included an additional version of these three patients where all voxels, including the air voxels outside of the patient, were uniformly set to water in the runtime study. The G4VPVParameterisation offers two optimization options. One option has a 60-150 times slower simulation speed. The other is compatible in speed but requires 15-19 times more memory compared to the other parameterizations. We found the average CPU time used for the simulation relative to G4VNestedParameterisation to be 1.014 for G4PhantomParameterisation without boundary skipping and 1.015 for MGHParameterization. The average runtime ratio for G4PhantomParameterisation with and without boundary skipping for our heterogeneous data was equal to 0.97: 1. The calculated dose distributions agreed with the reference distribution for all but the G4PhantomParameterisation with boundary skipping for the head and neck patient. The maximum memory usage ranged from 0.8 to 1.8 GB depending on the CT volume independent of parameterizations, except for the 15-19 times greater memory usage with the G4VPVParameterisation when using the option with a higher simulation speed. The G4VNestedParameterisation was selected as the preferred choice for the patient geometries and treatment plans studied.