Quadrupolar XMCD at the Fe K -edge in Fe phthalocyanine film on Au: Insight into the magnetic ground state

Under the terms of the Creative Commons Attribution license.-- et al.The observation of an anomalous quadrupolar signal in x-ray magnetic circular dichroism (XMCD) at the Fe K-edge of iron phthalocyanine (FePc) films is reported. All ground states previously suggested for FePc are incompatible with the experimental data. Based on ab initio molecular orbital multiplet calculations of the isolated FePc molecule, we propose a model for the magnetic ground state of the FePc film that explains the XMCD data and reproduces the observed values of the orbital moments in the perpendicular and planar directions.The financial support of the Spanish financial agency MINECO MAT2011-23791 and MAT2014-53921-R, Aragonese DGA-IMANA E34 (co-funded by Fondo Social Europeo), and European Union FEDER funds is acknowledged. The research at UCSD was supported by the Office of Basic Energy Science, US Department of Energy, BES-DMS, funded by the Department of Energy Office of Basic Energy Science, DMR, under Grant No. DE FG03 87ER-45332.Peer Reviewe

Validity of Daily Physical Activity Measurements of Fitbit Charge 2

Physical activity monitors collect continuous data to provide a summary of daily activity. The Fitbit Charge 2 monitors heart rate as well as steps, calories, and active minutes throughout the day. There is currently no research validating the Fitbit Charge 2 at measuring daily physical activity levels in a real life setting. PURPOSE: To compare measures of daily steps and active minutes of Fitbit Charge 2 with a research-grade accelerometer. METHODS: Sixteen active college students (Mean±SD; 23±4.9yrs; 16.43±10.19%fat; 9 male) consented to be part of the study. Participants wore an ActiGraph GT3X accelerometer and Fitbit Charge 2 concurrently for seven consecutive days. Both devices were programed with each participant’s information and the participants were instructed to perform their daily activities wearing both devices and only remove them to shower and to sleep. Data were considered valid when participants wore both devices for at least 10 hours on 4 or more days of the week. Steps and active minutes (moderate-vigorous physical activity) were recorded by each device. Mean bias was calculated by subtracting ActiGraph steps and active minutes from those obtained from the Fitbit Charge 2 for each day and an average daily mean bias was calculated using values from all seven days. Absolute percentage error was also calculated [100(|Fitbit Charge 2 - ActiGraph|)/ActiGraph] to indicate the overall 7-day difference between the Fitbit Charge 2 and ActiGraph. Pearson correlations and paired sample t-test were performed to compare Fitbit Charge 2 measurements with the corresponding ActiGraph measurements with significance considered at p\u3c0.05. RESULTS: The Fitbit Charge 2 overestimated steps by 2,451.3±2085.4 compared to the ActiGraph using the daily average steps over the seven days. This was 32.2±40.7% above the ActiGraph measurement. Average mean bias for daily active minutes was -52.1±58.9 with the Fitbit Charge 2 underestimating compared to the ActiGraph. Active minutes for the Fitbit Charge 2 were an average of 69±26.1% away from the ActiGraph. Steps for the Fitbit Charge 2 were significantly correlated to ActiGraph steps (r=0.575, p=0.02) while active minutes were not significantly correlated (r= -0.255, p=0.34). Paired sample t-test results showed a significant difference between the Fitbit Charge 2 steps and active minutes compared with the ActiGraph (p\u3c0.01 for both). CONCLUSION: The Fitbit Charge 2 may be useful for measuring steps in a free-living environment, however active minutes are significantly underestimated

Accuracy of Fitbit Charge 2 at Estimating VO2max, Calories, and Steps on a Treadmill

Current fitness activity trackers can account for steps, calories burned, heart rate, and distance traveled. A new feature has recently been introduced on the Fitbit Charge 2, “Cardio Fitness Level,” which is comparable to a VO2max score in that it allows consumers to be aware of their aerobic fitness level. PURPOSE: To assess the accuracy of the Fitbit Charge 2 at estimating VO2 score (“Cardio Fitness Level”), calories, and steps when compared to indirect calorimetry and video analyzed steps, respectively. METHODS: Twenty-two healthy adults (Mean±SD; 24.1±4.2yrs; 16.9±9.0%fat; 15 male) completed two separate visits. On the first visit, anthropometric measurements were taken followed by a 10-minute outdoor run. Participants ran for 10 minutes at their own pace on flat terrain as recommended by Fitbit to generate a Cardio Fitness score. On the second visit, participants came fasted, at least 8 hours, and completed a standardized VO2max protocol (Arizona State protocol) using a PARVO TrueOne2400 metabolic cart. The treadmill was set at 3mph for the first 3 minutes with 0% grade. Following the first stage, the speed was raised to the participant’s pre-selected speed (between 5-8mph) with 0% grade. After stage 2 the grade increased every minute by 1.5% and speed was kept constant until fatigue was reached. Calories and step counts from the Fitbits were correlated with the metabolic cart and tally counter respectively, using 2-tailed Pearson correlations. Significance was set at pRESULTS: Participants completed the VO2max test in an average of 11:05. Eight of the 22 estimated VO2max ranges given by Fitbit included the value given by the metabolic cart. Fitbit ranges for seven participants were below the metabolic cart values and the Fitbit ranges for the remaining seven participants were above the metabolic cart values. Calories were correlated between the Fitbit and metabolic cart (r = 0.874, pCONCLUSION: VO2 scores given by the Fitbit Charge 2 did not always match values given by the metabolic cart but may serve as a rough estimate of fitness level. Fitbit Charge 2 may also be useful in tracking calories and steps in a controlled setting, but results may differ in real world conditions

Accuracy of Fitbit Activity Trackers During Walking in a Controlled Setting

Activity trackers are widely used to measure daily physical activity. Many devices have been shown to measure steps more accurately at higher intensities, however, it is also important to determine the accuracy of these new devices at measuring steps while walking at a pace similar to that used during most daily activities. PURPOSE: To assess the accuracy of 6 popular activity trackers at measuring steps while walking on a treadmill. METHODS: Twenty-six college students (Mean±SD; 22.1±3.7yrs; 25.1±4.0kg/m2; 13 male) walked 500 steps at 3mph on a treadmill while wearing 6 different activity trackers (Pedometer, Fitbit Blaze, Charge HR, Alta, Flex, Zip, One). The Charge HR was placed two fingers above the right wrist while the Flex was next to the wrist bone. The Blaze was placed two fingers above the left wrist while the Alta was next to the wrist bone. The Fitbit Zip and the One were aligned with the hipbone on the left and right waistband respectively. Steps were counted by a trained researcher using a hand tally counter. Missing values were replaced with the mean value for that device. Step counts were correlated between Fitbit devices and the pedometer and tally counter using Pearson correlations. Significance was set at p\u3c0.05. Mean bias scores were calculated between the step counts for each device and the tally counter. Mean Absolute Percent Error (MAPE) values were also calculated for each device relative to the tally counter. RESULTS: Fitbit Zip and One were significantly correlated with the tally counter (r=0.50, p\u3c0.05; r=0.68, p\u3c0.01, respectively) while the other devices were not significantly correlated. Mean bias and MAPE values were as follows: Device (Mean Bias/MAPE) Pedometer (-0.2±39.2/3.8±6.8), Blaze (34.5±67.1/9.9±11.3), Charge HR (-12.6±61.5/7.0±10.3), Alta (-85.0±70.8/17.1±14.1), Flex (49.5±242.4/19.7±45.3), Zip (1.8±3.4/0.4±0.6), One (0.2±2.1/0.3±0.3). Fitbit Zip and One were within one half percent of actual steps while wrist-worn Fitbits ranged from 7.0-19.7% from actual step counts. CONCLUSION: Consistent with previous research, activity trackers worn at the waist provide the most accurate step counts compared to wrist-worn models. Differences found in wrist-worn models may result in significant over- or underestimation of activity levels when worn for long periods of time

Comparison of Smartphone Pedometer Apps on a Treadmill versus Outdoors

Previous research has focused on the accuracy of smartphone pedometer apps in laboratory settings, however less information is available in outdoor (free living) environments. PURPOSE: Determine the accuracy of 5 smartphone apps at recording steps at a walking speed in a laboratory versus an outdoor setting. METHODS: Twenty-three healthy college students consented (Mean±SD; 22±3.8yrs; BMI 24.9±4.13kg/m2) to participate in 2 separate visits. During the first visit participants walked 500 steps at 3mph on a treadmill while wearing a pedometer and a smartphone placed in the pocket using 5 pedometer apps concurrently (Moves, Google Fit (G-Fit), Runtastic, Accupedo, S-Health). During the second visit, participants walked 400 meters at 3mph on a sidewalk outside. Actual steps for each visit were recorded using a hand tally counter device. Zero and negative values were replaced with the mean value for that trial. Statistical analyses were performed using IBM SPSS 23.0. Mean bias scores were calculated between the step count for each app and the respective tally count for each trial. Mean bias scores were correlated between trials for each app using Pearson correlations and significance was set at p\u3c0.05. Mean Absolute Percent Error (MAPE) values were also calculated for each app for both trials. RESULTS: G-Fit recorded 2 zero values and 2 negative values and Moves recorded 1 zero value. Mean bias scores were significantly correlated between the indoor and outdoor protocols for the pedometer (r=0.67, p\u3c0.01) and S-Health (r=0.46, p\u3c0.5). The remaining apps were not correlated between protocols. The outdoor protocol producing a greater mean bias for the outdoor protocol for G-Fit, Runtastic, and Accupedo (mean bias ± SD indoor, outdoor; -4.3±53.1, -19.3±120.0; -10.7±63.3, -33.4±118.7; 16.0±143.6, 79.0±75.0; respectively) and a greater mean bias for the indoor protocol for the pedometer, Moves, and S-Health (mean bias indoor, outdoor; -1.4±41.5, 0.0±34.1; -117.4±196.7, -42.2±209.6; 11.3±28.4, 0.0±58.7; respectively). MAPE was below 5% for the pedometer and S-Health for both trials. CONCLUSION: Apps with the lowest error in a controlled setting may be less affected when used in other settings, while apps with greater variation in a controlled setting may be affected when used in a different environment

Effects of ultrasound versus pasteurization on whey–oat beverage processing: quality and antioxidative properties

The consumption of functional beverages is rapidly increasing. The improvement in the functional properties of whey after the application of ultrasound is due to the release of bioactive peptides that have antioxidant properties, among others. Bioactive peptides with antioxidant activity have also been found in oats, stimulating the study of whey beverages formulated with oats to obtain functional products. The aim of this study was to determine the influence of ultrasound (24 kHz) at 20 °C for 15 min at 23 W and 154 W on the quality and functional properties of whey–oat (50:50 v/v) beverages and compare it with pasteurization at 65 °C for 30 min (LTLT). Non-significant effect (p > 0.05) of ultrasound intensity (23 W and 154 W) was observed on the physicochemical characteristics and the proximal composition of the whey–oat beverages. The sonicated beverages showed a greater tendency to green and yellow color (p < 0.05), higher fat content (p < 0.05), and less ash and carbohydrates (p < 0.05) than the pasteurized beverage. The antioxidant activity of the mM Trolox equivalent/mL of the sonicated beverages was higher (p < 0.05) (4.24 and 4.27 for 23W and 54 W, respectively) compared to that of the pasteurized beverage (4.12). It is concluded that ultrasound is superior to pasteurization in improving the antioxidant activity of whey–oat beverages without having a detrimental impact on the proximal composition and physicochemical quality. Future studies should evaluate more functional parameters and determine the shelf life of sonicated whey–oat beverages

2-Hydroxyglutarate Production, but Not Dominant Negative Function, Is Conferred by Glioma-Derived NADP+-Dependent Isocitrate Dehydrogenase Mutations

Gliomas frequently contain mutations in the cytoplasmic NADP(+)-dependent isocitrate dehydrogenase (IDH1) or the mitochondrial NADP(+)-dependent isocitrate dehydrogenase (IDH2). Several different amino acid substitutions recur at either IDH1 R132 or IDH2 R172 in glioma patients. Genetic evidence indicates that these mutations share a common gain of function, but it is unclear whether the shared function is dominant negative activity, neomorphic production of (R)-2-hydroxyglutarate (2HG), or both.We show by coprecipitation that five cancer-derived IDH1 R132 mutants bind IDH1-WT but that three cancer-derived IDH2 R172 mutants exert minimal binding to IDH2-WT. None of the mutants dominant-negatively lower isocitrate dehydrogenase activity at physiological (40 µM) isocitrate concentrations in mammalian cell lysates. In contrast to this, all of these mutants confer 10- to 100-fold higher 2HG production to cells, and glioma tissues containing IDH1 R132 or IDH2 R172 mutations contain high levels of 2HG compared to glioma tissues without IDH mutations (54.4 vs. 0.1 mg 2HG/g protein).Binding to, or dominant inhibition of, WT IDH1 or IDH2 is not a shared feature of the IDH1 and IDH2 mutations, and thus is not likely to be important in cancer. The fact that the gain of the enzymatic activity to produce 2HG is a shared feature of the IDH1 and IDH2 mutations suggests that this is an important function for these mutants in driving cancer pathogenesis

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Supporting Spartina: Interdisciplinary perspective shows Spartina as a distinct solid genus

In 2014 a DNA-based phylogenetic study confirming the paraphyly of the grass subtribe Sporobolinae proposed the creation of a large monophyletic genus Sporobolus, including (among others) species previously included in the genera Spartina, Calamovilfa, and Sporobolus. Spartina species have contributed substantially (and continue contributing) to our knowledge in multiple disciplines, including ecology, evolutionary biology, molecular biology, biogeography, experimental ecology, environmental management, restoration ecology, history, economics, and sociology. There is no rationale so compelling to subsume the name Spartina as a subgenus that could rival the striking, global iconic history and use of the name Spartina for over 200 years. We do not agree with the arguments underlying the proposal to change Spartina to Sporobolus. We understand the importance of taxonomy and of formalized nomenclature and hope that by opening this debate we will encourage positive feedback that will strengthen taxonomic decisions with an interdisciplinary perspective. We consider the strongly distinct, monophyletic clade Spartina should simply and efficiently be treated as the genus Spartina