Search for a Dark-Matter-Induced Cosmic Axion Background with ADMX.

We report the first result of a direct search for a cosmic axion background (CaB)-a relativistic background of axions that is not dark matter-performed with the axion haloscope, the Axion Dark Matter eXperiment (ADMX). Conventional haloscope analyses search for a signal with a narrow bandwidth, as predicted for dark matter, whereas the CaB will be broad. We introduce a novel analysis strategy, which searches for a CaB induced daily modulation in the power measured by the haloscope. Using this, we repurpose data collected to search for dark matter to set a limit on the axion photon coupling of a CaB originating from dark matter cascade decay via a mediator in the 800-995 MHz frequency range. We find that the present sensitivity is limited by fluctuations in the cavity readout as the instrument scans across dark matter masses. Nevertheless, we suggest that these challenges can be surmounted using superconducting qubits as single photon counters, and allow ADMX to operate as a telescope searching for axions emerging from the decay of dark matter. The daily modulation analysis technique we introduce can be deployed for various broadband rf signals, such as other forms of a CaB or even high-frequency gravitational waves.

Evaluating the role of sarcopenia and [18F]FDG PET/CT parameters in prognosis of pancreatic ductal adenocarcinoma.

This study investigates the relationship between 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters, clinicopathological characteristics, and sarcopenia in patients with pancreatic ductal adenocarcinoma (PDAC) and evaluates their prognostic roles. MATERIAL AND METHODS: The primary tumor's maximum standard uptake (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) values, as well as clinicopathological factors, were evaluated retrospectively. Computed tomography (CT) was used to assess the skeletal muscle index (SMI). Sarcopenia was defined based on SMI calculated at the third lumbar vertebra (L3). SMI cut-off values ​​for sarcopenia were accepted as 44.77 cm2/m2 for men and 32.50 cm2/m2 for women. The primary endpoint was the overall survival (OS). OS data were analyzed by the Kaplan-Meier method and compared using the log-rank test. To identify predictive factors for sarcopenia, multivariable logistic regression was used following univariable logistic regression. Cox proportional hazards regression analyses were used to find predictors of OS. RESULTS: Of the 86 patients included in the study, 37 (43%) were diagnosed with sarcopenia. Compared with non-sarcopenic patients, sarcopenia was observed in older patients (P=0,028) and patients with lower body mass index (BMI) (p=0,001). Age and BMI independently predicted sarcopenia. Univariate analysis identified sarcopenia, advanced stage, and higher primary tumor TLG as significant predictors of overall survival. Multivariate Cox regression analysis revealed that the advanced tumor stage (p=0.017) and higher TLG (p=0,042) independently predicted OS. The median OS was 9.4 months in non-sarcopenic patients and 5.0 months in sarcopenic patients (p=0,021). CONCLUSION: In this study cohort, advanced-stage disease and higher primary tumor TLG were identified as independent predictors of OS in patients with PDAC. Additionally, we emphasize the importance of incorporating [18F]FDG PET/CT-derived sarcopenia assessments into the prognostic evaluation and clinical management of PDAC patients. While sarcopenia was associated with shorter OS in univariate analysis, it was not an independent predictor in multivariate analysis.

Dark matter axion search using a Josephson Traveling wave parametric amplifier.

We describe the first implementation of a Josephson Traveling Wave Parametric Amplifier (JTWPA) in an axion dark matter search. The operation of the JTWPA for a period of about two weeks achieved sensitivity to axion-like particle dark matter with axion-photon couplings above 10-13 Ge V-1 over a narrow range of axion masses centered around 19.84 µeV by tuning the resonant frequency of the cavity over the frequency range of 4796.7-4799.5 MHz. The JTWPA was operated in the insert of the axion dark matter experiment as part of an independent receiver chain that was attached to a 0.56-l cavity. The ability of the JTWPA to deliver high gain over a wide (3 GHz) bandwidth has engendered interest from those aiming to perform broadband axion searches, a longstanding goal in this field.

Improved tests of local position invariance using 87Rb and 133Cs fountains.

We report tests of local position invariance based on measurements of the ratio of the ground state hyperfine frequencies of 133Cs and 87Rb in laser-cooled atomic fountain clocks. Measurements extending over 14 years set a stringent limit to a possible variation with time of this ratio: d ln(ν(Rb)/ν(Cs))/dt=(-1.39±0.91)×10(-16) yr(-1). This improves by a factor of 7.7 over our previous report [H. Marion et al., Phys. Rev. Lett. 90, 150801 (2003)]. Our measurements also set the first limit to a fractional variation of the Rb/Cs frequency ratio with gravitational potential at the level of c(2)d ln(ν(Rb)/ν(Cs))/dU=(0.11±1.04)×10(-6), providing a new stringent differential redshift test. The above limits equivalently apply to the fractional variation of the quantity α(-0.49)(g(Rb)/g(Cs)), which involves the fine-structure constant α and the ratio of the nuclear g-factors of the two alkalis. The link with variations of the light quark mass is also presented together with a global analysis combining other available highly accurate clock comparisons.

Predicting Alzheimer's conversion in mild cognitive impairment patients using longitudinal neuroimaging and clinical markers.

Patients with mild cognitive impairment (MCI) have a high risk for conversion to Alzheimer's disease (AD). Early diagnose of AD in MCI subjects could help to slow or halt the disease progression. Selecting a set of relevant markers from multimodal data to predict conversion from MCI to probable AD has become a challenging task. The aim of this paper is to quantify the impact of longitudinal predictive models with single- or multisource data for predicting MCI-to-AD conversion and identifying a very small subset of features that are highly predictive of conversion. We developed predictive models of MCI-to-AD progression that combine magnetic resonance imaging (MRI)-based markers (cortical thickness and volume of subcortical structures) with neuropsychological tests. These models were built with longitudinal data and validated using baseline values. By using a linear mixed effects approach, we modeled the longitudinal trajectories of the markers. A set of longitudinal features potentially discriminating between MCI subjects who convert to dementia and those who remain stable over a period of 3 years was obtained. Classifier were trained using the marginal longitudinal trajectory residues from the selected features. Our best models predicted conversion with 77% accuracy at baseline (AUC = 0.855, 84% sensitivity, 70% specificity). As more visits were available, longitudinal predictive models improved their predictions with 84% accuracy (AUC = 0.912, 83% sensitivity, 84% specificity). The proposed approach was developed, trained and evaluated using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with a total of 2491 visits from 610 subjects.

Longitudinal survival analysis and two-group comparison for predicting the progression of mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Longitudinal studies using structural magnetic resonance imaging (MRI) and neuropsychological measurements (NMs) allow a noninvasive means of following the subtle anatomical changes occurring during the evolution of AD. NEW METHOD: This paper compared two approaches for the construction of longitudinal predictive models: a) two-group comparison between converter and nonconverter MCI subjects and b) longitudinal survival analysis. Predictive models combined MRI-based markers with NMs and included demographic and clinical information as covariates. Both approaches employed linear mixed effects modeling to capture the longitudinal trajectories of the markers. The two-group comparison approaches used linear discriminant analysis and the survival analysis used risk ratios obtained from the extended Cox model and logistic regression. RESULTS: The proposed approaches were developed and evaluated using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with a total of 1330 visits from 321 subjects. With both approaches, a very small number of features were selected. These markers are easily interpretable, generating robust, verifiable and reliable predictive models. Our best models predicted conversion with 78% accuracy at baseline (AUC = 0.860, 79% sensitivity, 76% specificity). As more visits were made, longitudinal predictive models improved their predictions with 85% accuracy (AUC = 0.944, 86% sensitivity, 85% specificity). COMPARISON WITH EXISTING METHOD: Unlike the recently published models, there was also an improvement in the prediction accuracy of the conversion to AD when considering the longitudinal trajectory of the patients. CONCLUSIONS: The survival-based predictive models showed a better balance between sensitivity and specificity with respect to the models based on the two-group comparison approach.

Divergent molecular and growth responses of young "Cabernet Sauvignon" (Vitis vinifera) plants to simple and mixed infections with Grapevine rupestris stem pitting-associated virus.

Grapevine rupestris stem pitting associated virus (GRSPaV) is one of the most widely distributed viruses; even so, little is known about its effect on Vitis vinifera. To provide new insights, the effects of single and mixed GRSPaV infections on the V. vinifera cultivar "Cabernet Sauvignon" were studied by evaluating growth parameters, such as measurements of the total plant length, the number and distance of internodes and the number of leaves per shoot. In addition, parameters relating to gas exchange, i.e., the stomatal conductance, net photosynthetic rate, internal CO2 concentration and leaf transpiration, were also assessed. All the measurements were performed in one- and two-year-old plants with a single GRSPaV infection or mixed infections of GRSPaV and Grapevine fanleaf virus (GFLV). The results show that the plant phytosanitary status did not significantly alter the growth and gas exchange parameters in one-year-old plants. However, in two-year-old plants, single GRSPaV infections increased shoot elongation, which was accompanied by the overexpression of genes associated with the gibberellic acid response pathway. The gas exchange parameters of these plants were negatively affected, despite exhibiting higher LHCII gene expression. Plants with mixed infections did not have modified growth parameters, although they presented a greater reduction in the primary photosynthetic parameters evaluated with no change in LHCII expression. The results presented here confirm the co-evolution hypothesis for V. vinifera and GRSPaV during the early stages of plant development, and they provide new evidence about the effects of GRSPaV and GFLV co-infections on the "Cabernet Sauvignon" cultivar.

Longitudinal Neuroimaging Hippocampal Markers for Diagnosing Alzheimer's Disease.

Hippocampal atrophy measures from magnetic resonance imaging (MRI) are powerful tools for monitoring Alzheimer's disease (AD) progression. In this paper, we introduce a longitudinal image analysis framework based on robust registration and simultaneous hippocampal segmentation and longitudinal marker classification of brain MRI of an arbitrary number of time points. The framework comprises two innovative parts: a longitudinal segmentation and a longitudinal classification step. The results show that both steps of the longitudinal pipeline improved the reliability and the accuracy of the discrimination between clinical groups. We introduce a novel approach to the joint segmentation of the hippocampus across multiple time points; this approach is based on graph cuts of longitudinal MRI scans with constraints on hippocampal atrophy and supported by atlases. Furthermore, we use linear mixed effect (LME) modeling for differential diagnosis between clinical groups. The classifiers are trained from the average residue between the longitudinal marker of the subjects and the LME model. In our experiments, we analyzed MRI-derived longitudinal hippocampal markers from two publicly available datasets (Alzheimer's Disease Neuroimaging Initiative, ADNI and Minimal Interval Resonance Imaging in Alzheimer's Disease, MIRIAD). In test/retest reliability experiments, the proposed method yielded lower volume errors and significantly higher dice overlaps than the cross-sectional approach (volume errors: 1.55% vs 0.8%; dice overlaps: 0.945 vs 0.975). To diagnose AD, the discrimination ability of our proposal gave an area under the receiver operating characteristic (ROC) curve (AUC) [Formula: see text] 0.947 for the control vs AD, AUC [Formula: see text] 0.720 for mild cognitive impairment (MCI) vs AD, and AUC [Formula: see text] 0.805 for the control vs MCI.

Invited article: design techniques and noise properties of ultrastable cryogenically cooled sapphire-dielectric resonator oscillators.

We review the techniques used in the design and construction of cryogenic sapphire oscillators at the University of Western Australia over the 18 year history of the project. We describe the project from its beginnings when sapphire oscillators were first developed as low-noise transducers for gravitational wave detection. Specifically, we describe the techniques that were applied to the construction of an interrogation oscillator for the PHARAO Cs atomic clock in CNES, in Toulouse France, and to the 2006 construction of four high performance oscillators for use at NMIJ and NICT, in Japan, as well as a permanent secondary frequency standard for the laboratory at UWA. Fractional-frequency fluctuations below 6 x 10(-16) at integration times between 10 and 200 s have been repeatedly achieved.

Rigorous ESR spectroscopy of Fe3+ impurity ion with oxygen vacancy in ferroelectric SrTiO3 crystal at 20 mK.

Impurity Fe3+ ion electron spin resonance (ESR) spectroscopy using multiple dielectric modes in a SrTiO3 dielectric resonator has been performed with a tunable DC magnetic field of up to 1.6 T. The Ti[Formula: see text] ion is substituted by Fe3+ ion forming FeO6 octahedral complex with an iron-oxygen-vacancy (Fe[Formula: see text]). In such a metal-ligand complex, a giant g-factor of [Formula: see text] was observed in the ferroelectric phase at 20 mK. The change of Fe3+ ion center-symmetry in the FeO6 complex as a soft-mode characteristics of ferroelectric phase transition and the influences of iron-oxygen-vacancy (Fe[Formula: see text]), are interactively sensitive to asymmetry in the octahedral rotational parameter Φ in SrTiO3.

Aggregate frequency width, nuclear hyperfine coupling and Jahn-Teller effect of Cu2+ impurity ion ESR in SrLaAlO4 dielectric resonator at 20 millikelvin.

The impurity paramagnetic ion, [Formula: see text] substitutes Al in the [Formula: see text] single crystal lattice, this results in a [Formula: see text] elongated octahedron, and the resulting measured g-factors satisfy four-fold axes variation condition. The aggregate frequency width of the electron spin resonance with the required minimum level of impurity concentration has been evaluated in this single crystal [Formula: see text] at 20 millikelvin. Measured parallel hyperfine constants, [Formula: see text], were determined to be [Formula: see text] and [Formula: see text] at [Formula: see text] for the nuclear magnetic quantum number [Formula: see text], and [Formula: see text] respectively. The anisotropy of the hyperfine structure reveals the characteristics of the static Jahn-Teller effect. The second-order-anisotropy term, [Formula: see text], is significant and cannot be disregarded, with the local strain dominating over the observed Zeeman-anisotropy-energy difference. The Bohr electron magneton, [Formula: see text], (within [Formula: see text] so-called experimental error) has been found using the measured spin-Hamiltonian parameters. Measured nuclear dipolar hyperfine structure parameter [Formula: see text] shows that the mean inverse third power of the electron distance from the nucleus is [Formula: see text] a.u. for [Formula: see text] ion in the substituted [Formula: see text] ion site assuming nuclear electric quadruple moment [Formula: see text] barn.

Combining a Patch-based Approach with a Non-rigid Registration-based Label Fusion Method for the Hippocampal Segmentation in Alzheimer's Disease.

We provide and evaluate an open-source software solution for automatically hippocampal segmentation from T1-weighted (T1w) magnetic resonance imaging (MRI). The method is applied for measuring the hippocampal volume, which allows discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls (NC). The method is based on a fast patch-based label fusion method, whose selected patches and their weights are calculated from a combination of similarity measures between patches using intensity-based distances and labeling-based distances. These combined similarity measures produces better selection of the patches, and their weights are more robust. The algorithm is trained with the Harmonized Hippocampal Protocol (HarP). The proposal is compared with FreeSurfer and other label fusion methods. To evaluate the performance and the robustness of the proposed label fusion method, we employ two databases of T1w MRI of human brains. For AD vs NC, we obtain a high degree of accuracy, approximately 90 %. For MCI vs NC, we obtain accuracies around 75 %. The average time for the hippocampal segmentation from a T1w MRI is less than 17 minutes.

Whispering Gallery mode ESR spectroscopy and parameters measurement in single crystal SrLaAlO4 at millikelvin temperature.

A cylindrical single crystal SrLaAlO4 Whispering Gallery mode dielectric resonator was cooled to millikelvin temperature using a dilution refrigerator. By controlling a DC-magnetic field, impurity ions' spins were coupled to a variety of modes allowing the measurement of hybrid spin-photon systems. This Electron Spin Resonance mapping technique allowed us to detect Cu2+,Fe3+ and Mn4+ impurity ions (at the level of parts per million (ppm) to parts per billion (ppb)), verified by the measurement of the spin parameters along with their site symmetry. Whispering Gallery modes exhibited Q-factors ⩾105 at a temperature less than 20mK, allowing sensitive spectroscopy with high precision. Measured hyperfine line constants of the Cu2+ ion shows different parallel g-factors, g‖Cu, of 2.526,2.375,2.246 and 2.142. The spin-orbit coupling constant of the Cu2+ ion was determined to be λ≃-635cm-1. The low-spin state Fe3+ ion's measured parallel g-factor, g‖Fe, of 2.028 reveals tetragonal anisotropy. The Mn4+ ion is identified in the lattice, producing hyperfine structure with high-valued g-factors,g‖Mn, of 7.789,7.745,7.688,7.613,7.5304 and 7.446. The hyperfine structures of the Cu2+ and Mn4+ ions show broadening of about 79G between 9.072GHz and 10.631GHz, and 24.5G broadening between 9.072GHz and 14.871GHz, respectively.

Experiments match simulations in a multiple post reentrant cavity.

Microwave reentrant cavities are used for many applications in science and engineering. The potential for both high mechanical tunability and high electric quality factors make them important tools in many areas. They are usually resonant cylindrical cavities with a central post, which makes a small gap spacing with the cavity wall. By adding an arbitrary number of extra posts, they are generalized to a type of multiple post reentrant cavity. This new approach has been theoretically studied but no experimental results have been presented. The main purpose of this work was to compare experimental modes with simulated ones from a reentrant cavity made of forty nine cylindrical posts. Each post could be moved using a screw in order to make tunable gap spacing between the post top and the cavity cover. Eight different gap setups were made making it possible to investigate thirty six different reentrant modes at room temperature. The lowest frequency percentage agreement between experiment and simulation was 91.31%, and the best one was 99.92%. Taking into account all the modes, 94.44% of them agreed above 96%. Thus, we have determined an experimental procedure suitable to investigate the reentrant modes from multiple post cavities. There is a wide range of potential applications for such cavities due to their unique features compared to conventional ones.

Optical frequency synthesis from a cryogenic microwave sapphire oscillator.

We demonstrate an optical frequency comb with fractional frequency instability of

A fast approach for hippocampal segmentation from T1-MRI for predicting progression in Alzheimer's disease from elderly controls.

BACKGROUND: We provide and evaluate an open-source software solution for automatically measuring hippocampal volume and hippocampal surface roughness based on T1-weighted MRI, which allows for discriminating between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls (NC) using only one scan. NEW METHOD: This solution is based on a fast multiple-atlas segmentation technique, which combines a patch-based labeling method with an atlas-warping using non-rigid registrations. RESULTS: The classifications are comparable to the best classifications in a large clinical dataset. For AD vs control, we obtain a high degree of accuracy, approximately 90%. For MCI vs control, we obtain accuracies ranging from 70% to 78%. The average time for the hippocampal segmentation from a T1-MRI is less than 17min. COMPARISON WITH EXISTING METHOD: In this study, we investigate a combination of our method with annotations using the Harmonized Hippocampal Protocol (HarP). We compare its capabilities with the FreeSurfer method and verify its impact on segmentation and diagnostic group separation capabilities. Our approach is developed and validated using 134 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database with annotations from HarP. Then, this method, tuned with the best parameters, is applied to 162 subjects from a private image database. CONCLUSIONS: Our approach with HarP annotations has a high level of accuracy for segmentation of the hippocampus and is robust to multi-site data. The bio-markers extracted from our proposed method have discriminative power based on a scalar feature, showing robustness in generalization and avoid overfitting. The computational time in our hippocampal segmentation algorithm has decreased considerably compared to other available analysis.

Piezoelectric tunable microwave superconducting cavity.

In the context of engineered quantum systems, there is a demand for superconducting tunable devices, able to operate with high-quality factors at power levels equivalent to only a few photons. In this work, we developed a 3D microwave re-entrant cavity with such characteristics ready to provide a very fine-tuning of a high-Q resonant mode over a large dynamic range. This system has an electronic tuning mechanism based on a mechanically amplified piezoelectric actuator, which controls the resonator dominant mode frequency by changing the cavity narrow gap by very small displacements. Experiments were conducted at room and dilution refrigerator temperatures showing a large dynamic range up to 4 GHz and 1 GHz, respectively, and were compared to a finite element method model simulated data. At elevated microwave power input, nonlinear thermal effects were observed to destroy the superconductivity of the cavity due to the large electric fields generated in the small gap of the re-entrant cavity.

A label fusion method using conditional random fields with higher-order potentials: Application to hippocampal segmentation.

OBJECTIVE: The objective of this study is to develop a probabilistic modeling framework for segmenting structures of interest from a collection of atlases. We present a label fusion method that is based on minimizing an energy function using graph-cut techniques. METHODS AND MATERIALS: We use a conditional random field (CRF) model that allows us to efficiently incorporate shape, appearance and context information. This model is characterized by a pseudo-Boolean function defined on unary, pairwise and higher-order potentials. Given a subset of registered atlases in the target image for a particular region of interest (ROI), we first derive an appearance-shape model from these registered atlases. The unary potentials combine an appearance model based on multiple features with a label prior using a weighted voting method. The pairwise terms are defined from a Finsler metric that minimizes the surface of separation between voxels whose labels are different. The higher-order potentials used in our framework are based on the robust P(n) model proposed by Kohli et al. The higher-order potentials enforce label consistency in cliques; hence, the proposed method can be viewed as an approach to integrate high-level information with images based on low-level features. To evaluate the performance and the robustness of the proposed label fusion method, we employ two available databases of T1-weighted (T1W) magnetic resonance (MR) images of human brains. We compare our approach with other label fusion methods in the automatic hippocampal segmentation from T1W-MR images. RESULTS: Our label fusion method yields mean Dice coefficients of 0.829 and 0.790 for the two databases used with mean times of approximately 80 and 160s, respectively. CONCLUSIONS: We introduce a new label fusion method based on a CRF model and on ROIs. The CRF model is characterized by a pseudo-Boolean function defined on unary, pairwise and higher-order potentials. The proposed Boolean function is representable by graphs. A globally optimal binary labeling is found using a st-mincut algorithm in each ROI. We show that the proposed approach is very competitive with respect to recently reported methods.

A qualitative study of participants' experiences with dietary assessment.

OBJECTIVE: This article reports on the use of focus groups and an experimental participatory activity to investigate factors influencing participants' decisions about what to eat and what to report on food records and food frequency questionnaires. DESIGN: Four focus groups examined participants' experience with diet records and 3 focus groups explored the topic of food portions using a group consensus activity. Twenty-two women participated in the diet record focus groups, and 15 participated in portion estimation groups. SUBJECTS: Focus group participants were equally distributed by age and body mass index values. Each woman completed a 10-day doubly labeled water protocol to measure total energy expenditure, 7 days of diet records (before and during total energy expenditure), and a food frequency questionnaire after the total energy expenditure. ANALYSIS: Transcripts of the focus groups were coded to index categories of responses and to identify themes within and across those responses. Themes discussed in this article are those that were discussed most often and at greatest length by all groups. RESULTS: The diet record focus groups revealed that 2 major factors influenced reporting on diet records: honesty vs social acceptability, and simplifying food intake. The portion estimation focus groups revealed 5 factors that influenced perceptions of portion size: the role of food in the meal, the type of food, personal preferences, product serving sizes, and comparison of personal servings with those of others. APPLICATIONS: The validity and reliability of self-reported food consumption is greatly influenced by the ways people interpret and respond to dietary assessment instruments. These findings indicate that dietetics professionals need to take extra steps to address issues of accurately recording "bad" foods when training patients to complete diet records. Extra probing is needed when dietary records do not include snacks and include simple meals and a large amount of prepared and packaged food because this may indicate that changes in normal dietary patterns were made in order to more easily complete a dietary record.

Validation of the Arizona Activity Frequency Questionnaire using doubly labeled water.

PURPOSE: Physical activity questionnaires (PAQs) are considered the most cost-efficient method to estimate total energy expenditure (TEE) in epidemiological studies. However, relatively few PAQs have been validated using doubly labeled water (DLW) in women or in samples with diverse ethnic backgrounds. This study was conducted to validate the Arizona Activity Frequency Questionnaire (AAFQ) for estimation of TEE and physical activity energy expenditure (PAEE) over 1 month using DLW as a reference method. METHODS: Thirty-five relatively sedentary women completed the AAFQ before participating in an 8-d DLW protocol to measure TEE. TEE and PAEE were estimated from the AAFQ by calculating resting metabolic rate (RMR) using the equation of Mifflin et al. (AAFQmif), by measuring RMR using indirect calorimetry (AAFQic), and using MET conversion (AAFQmet). A predictive equation for TEE was generated. RESULTS: The mean +/- SD for TEE and PAEE from DLW were 9847 +/- 2555 kJ x d(-1) and 5578 +/- 2084 kJ x d(-1), respectively. Formulas using RMR to calculate the TEE and PAEE from the AAFQ tended to underestimate TEE and PAEE, whereas those that included only weight tended to overestimate TEE and PAEE. On the basis of the Mifflin et al. equation, the AAFQ tends to underestimate PAEE by 13%. This underestimation may be explained by the low lean body mass of the sample population and by effectiveness of the METs/RMR ratio in the obese. The following predictive equation was calculated: TEE (kJ x d(-1)) = (86.0 * average total daily METs) + (2.23 * RMRmif) - 6726. When the predictive equation is used, TEE calculated from the AAFQ is highly correlated with DLW TEE (adjusted r(2) = 0.70, P < 0.001). CONCLUSION: The AAFQ is an effective tool for the prediction of TEE and PAEE in epidemiological studies.