Measurement of blood oxygen saturation (O2 saturation) is of great importance for evaluation of patients with many cardiovascular diseases, but currently there are no established non-invasive methods to measure blood O2 saturation in the heart. While T2-based CMR oximetry methods have been previously described, these approaches rely on technique-specific calibration factors that may not generalize across patient populations and are impractical to obtain in individual patients. We present a solution that utilizes multiple T2 measurements made using different inter-echo pulse spacings. These data are jointly processed to estimate all unknown parameters, including O2 saturation, in the Luz-Meiboom (L-M) model. We evaluated the accuracy of the proposed method against invasive catheterization in a porcine hypoxemia model.τ180 . Venous and arterial blood T2 values from these maps, together with hematocrit and arterial O2 saturation, were jointly processed to derive estimates for venous O2 saturation and other nuisance parameters in the L-M model. The technique was validated by a progressive graded hypoxemia experiment in seven pigs. CMR estimates of O2 saturation in the right ventricle were compared against a reference O2 saturation obtained by invasive catheterization from the right atrium in each pig, at each hypoxemia stage. O2 saturation derived from the proposed technique was also compared against the previously described method of applying a global calibration factor (K) to the simplified L-M model.Sufficient data diversity to estimate the various unknown parameters of the L-M model, including O2 saturation, was achieved by acquiring four T2 maps, each at a different 2 = 0.89) with invasive blood gas analysis when compared to O2 saturation estimated by a global calibration method .Venous O2 saturation results obtained using the proposed CMR oximetry method exhibited better agreement (y = 0.84× + 12.29, RWe have demonstrated a novel, non-invasive method to estimate O2 saturation using quantitative T2 mapping. This technique may provide a valuable addition to the diagnostic utility of CMR in patients with congenital heart disease, heart failure, and pulmonary hypertension. Blood oxygen saturation (O2 saturation) is a relevant biomarker in many cardiovascular diseases; O2 saturation is used to determine the presence and severity of intra- and extra-cardiac shunts in congenital heart disease, and to provide an index of systemic oxygen delivery and consumption in heart failure and pulmonary artery hypertension , 2. InvaBased on the magnetic properties of oxygenated (diamagnetic) and deoxygenated (paramagnetic) hemoglobin in blood, non-invasive magnetic resonance (MR) techniques have been previously described to estimate blood O2 saturation, myocardial and skeletal tissue oxygenation, and brain oxygen extraction fraction –8. TheseThe transverse relaxivity (R2 or 1/T2) of blood may be influenced by a number of physiological, dynamic, and pulse sequence dependent factors. The Luz-Meiboom (L-M) chemical exchange model  has beenTb2 is the T2 relaxation time of blood , TO2 is the T2 of fully oxygenated blood, Pa is the fraction of protons at one of the two sites undergoing chemical exchange, τex is the water proton exchange time between erythrocytes and plasma, α is a dimensionless parameter that is dependent on the susceptibility difference of deoxy- and oxyhemoglobin and the geometry of the red blood cells, ω0 is the proton resonance frequency (fixed for a given static field strength), %SbO2 is the oxygen saturation , and τ180 is the inter-echo spacing of the 180° refocusing pulses in the CPMG echo train or the T2 preparation module. The term Pa has been described as 0.9 times or equal to hematocrit (Hct) [Pa to be equal to Hct in our implementation of the L-M model.Efforts to accurately characterize this relationship between T2 and O2 saturation of whole blood have led to experimental and theoretical parameterization of the L-M model with varying degrees of model complexity, including segregating the contributions from individual paramagnetic and diamagnetic blood components , 12, 13.it (Hct) , the volIn this model, there are several unknown biophysical parameters besides O2 saturation that are experimentally difficult to determine. In vitro studies have been performed using static or flowing human or animal blood in order to determine these unknown parameters; however, the accuracy of estimation is prone to variability in experimental conditions . It is aTb2 is the measured T2 value of blood; TO2 is the T2 value of fully oxygenated blood, which is either assumed or measured in vitro; K is a calibration factor derived from in vitro experiments and incorporates parameters such as Hct, τex, α, and τ180; and %SbO2 is the parameter of interest, i.e. the blood O2 saturation. While the use of a simplified model with a fixed calibration factor may offer greater computational ease, it comes at the cost of reduced accuracy and precision. As an example, due to the dependence of K on hematocrit, the calibrated factor from an in vitro calibration process performed over a normal range of hematocrit may not be accurate in anemic or polycythemic patients [These parameters are typically calibrated for specific imaging conditions, such as for a particular inter-echo spacing or field strength. A commonly used simplified model, initially proposed by Wright et al.  is shownpatients .To overcome the inaccuracies of a globally calibrated model, patient-specific calibration has also been proposed . HoweverTherefore, for successful clinical application in the evaluation of cardiovascular disease, T2-based cardiovascular MR (CMR) oximetry must (i) reliably and accurately estimate blood T2 across various cardiac and vascular locations, (ii) provide a patient-specific estimate of O2 saturation by accounting for inter-individual variability of the other biophysical parameters in the L-M model, and (iii) utilize a clinically practical procedure that entails efficient data acquisition and analysis. Taking these factors into consideration, we propose a framework for patient-specific, T2-based CMR oximetry. We hypothesize that a more accurate estimation of O2 saturation is obtained by solving the L-M model using multiple T2 maps. The estimation of O2 saturation and other nuisance parameters in the L-M model is posed as a non-linear least squares (NLLS) problem, with constraints enforced on the nuisance parameters. We validated this technique against invasive blood gas analysis in a porcine model of graded hypoxemia.Tb2 can be measured using CMR, and Hct (Pa) can be measured from a small blood sample. The parameters ω0 and τ180 can be controlled based on the choice of magnetic field strength and T2-preparation pulse design, respectively. This leaves the desired blood oxygen saturation, %SbO2, and three other nuisance parameters  as unknowns.In the model described in Eq. 1, τ180 is a controllable parameter, acquiring multiple T2 measurements, each at a different τ180, provides the diversity of data that is needed to characterize the patient-specific relationship between blood T2 and O2 saturation. Once a sufficient number of T2 values have been acquired, each using a different τ180, the four unknown model parameters  can be estimated using a NLLS curve fit. Under high signal-to-noise (SNR) conditions, the solution remains viable when the nuisance parameters are unknown a priori. However, in order to discourage convergence to local minima and to combat loss of estimation sensitivity in the presence of noise, we opted to constrain the nuisance parameters. This approach provides a framework for patient-specific T2 oximetry  phase cycled composite 1800 (900–1800–900) refocusing RF pulses, ending with a composite 900 (2700–3600) tip-up RF pulse. The T2 preparation is immediately followed by a balanced steady-state free precession (bSSFP) readout, with linear traversal across k-space data. The T2 mapping sequence also employs a non-rigid registration motion correction algorithm to correct for motion occurring between the different T2-prepared images. The signal in each of the motion corrected T2 prepared images are fit pixel-wise to a mono-exponential decay curve as a function of T2p, resulting in a quantitative T2 map of the region being imaged.Our lab has previously developed a technique to perform rapid, quantitative characterization of the myocardial T2 to identify inflammation and edema , 28. Theτ180 was adjusted among a fixed number of refocusing pulses in the T2 preparation train in order to vary the echo times, T2p, which is defined as T2p = number of refocusing pulses x τ180. For the estimation of blood O2 saturation, we extend T2p by increasing the number of refocusing pulses based on a segmented Malcolm Levitt phase cycling pattern  [τ180 values of 12, 15, 20, and 25 ms. The T2p times corresponding to each T2 map used in the study were therefore 0, 24, 48, 96, and 144 ms (for τ180 = 12 ms); 0, 30, 60, 90, and 180 ms (for τ180 = 15 ms); 0, 40, 80, and 160 ms (for τ180 = 20 ms); and 0, 50, 100, and 200 ms (for τ180 = 25 ms), respectively. The number of T2p images used to generate each map was chosen such that the latest T2p for each T2 map remained within a close range, around the expected T2 values of arterial and venous blood. An illustration of the T2 mapping scheme is shown in Fig. In this technique, which was primarily designed for myocardial T2 measurement,  pulses) . Thus, wAs the CMR imaging planes of the heart usually include both arterial and venous blood pools, each T2 map can provide a T2 measurement of both arterial and venous blood. It is also possible to measure the O2 saturation of arterial blood by non-invasive pulse oximetry. Therefore, joint processing of venous and arterial blood T2 measurements, together with a known value of arterial O2 saturation, can provide additional information that aids in accurate parameter estimation.τ180, and (ii) utilize a NLLS fitting approach to jointly estimate venous O2 saturation along with the remaining unknown nuisance parameters of the L-M model.In summary, to derive an estimate of blood O2 saturation from its corresponding T2, we acquired four T2 maps resulting in eight equations: four for the venous blood of interest and four for a reference arterial blood pool. We propose that these T2 measurements, together with the hematocrit and non-invasive arterial O2 saturation, collectively support a reliable fit of the L-M model. As shown in Fig. The study was conducted with the approval of the Institutional Animal Care and Use Committee. Seven pigs were anesthetized with isoflurane and mechanically ventilated on 100% oxygen. Balloon catheters were inserted into the right atrium and proximal aorta for sampling venous and arterial blood, respectively. After placement in the CMR scanner, the animals were subjected to controlled graded hypoxemia by varying the ratio of oxygen to nitrogen gas inhaled . We sougEach inspired gas mixture was maintained for at least 10 min to allow O2 saturation levels to stabilize before blood sampling and imaging. Arterial and venous blood samples (roughly 0.1 mL) were drawn from aortic and right atrial catheters before and after imaging at each hypoxemic stage; the samples were immediately analyzed with a Vetscan I-stat 1 handheld blood gas analyzer . The arterial and venous O2 saturation for each hypoxemic stage was determined by averaging the saturation levels measured before and after imaging (approximately ten minutes apart). The hematocrit was measured in each blood sample and averaged across all measurements to determine the value for each animal.After stepping through stages from highest to lowest level of inspired oxygen, the animal was allowed to recover for approximately 15–20 min by breathing 100% oxygen. The animal was then euthanized after a second set of measurements was made at 100% arterial O2 saturation. The two sets of baseline blood gas measurements obtained from each animal before and after CMR imaging were tested to evaluate the reproducibility of O2 saturation measurements by catheterization and blood gas analysis.τ180, in a single short axis view including both right and left ventricles. At each stage of hypoxemia, four T2 maps, each with τ180 of 12, 15, 20, and 25 ms, were acquired in a randomized order to avoid any bias that may be caused by the drifting of the O2 saturation levels. The images were cardiac triggered and acquired free breathing in late systole to avoid rapid, disrupted flow during diastolic filling. The imaging parameters were: TR (time between T2 prepared image acquisitions) 4000 to 5000 ms , two signal averages (NEX), where each NEX is a single shot measurement, flip angle = 700, parallel acceleration = 2, bandwidth = 1182 Hz/pixel, field of view = 400 × 368 mm, matrix size = 128 × 118, spatial resolution = 3.1 × 3.1 × 10 mm. The TE of the SSFP readout was 0.89 ms while TR was 2.2 ms. Parallel acceleration was used in combination with multiple NEX to keep the shot time short while preserving SNR. The acquisition time of each map was approximately 40 to 50 s. Cardiac output was measured at the aortic outflow using a real-time velocity sequence [All imaging was performed on a 1.5 T magnet  with a maximum gradient amplitude of 45 mT/m and slew rate of 200 mT/m/ms. A flexible six-element phased array body coil was placed on the thorax over the heart and combined with elements of a spine array coil for signal reception. CMR at each stage of hypoxemia included the acquisition of four T2 maps, each using a different sequence  at each Image analysis was performed on a Leonardo workstation . Prior to performing the animal study, the four T2 maps were evaluated on static phantoms prepared to approximate T2 value of arterial and venous blood. The T2 values of the phantoms were measured by placing a region of interest in each of the four maps. These values were compared against a reference T2, measured by a multi-echo turbo spin echo (MESE) sequence. The reference T2 values were calculated by mono-exponential fitting of the signal to the echo times in the MESE sequence. For the animal experiment, the T2 values of arterial and venous blood were measured by manually drawing contours around the lumen of the right ventricular (venous) and left ventricular  blood pools in each of the four T2 maps acquired at each hypoxemia stage.ω0 (4 × 108 rad/s at 1.5 T) and τ180  were known. The eight measurements of blood T2 , along with the measured hematocrit and reference arterial O2 saturation at each stage were processed jointly to estimate the O2 saturation in the right ventricular cavity.For the proposed method, parameter estimation of the L-M model (Eq. 1) was performed using a NLLS curve fit based on an interior point algorithm in Matlab R2016a . Blood T2, hematocrit, and arterial O2 saturation  were all measured, and τ180 = 12 ms) and a previously defined value of K (25 s−1). There are two unknown parameters, TO2 and %SbO2, in this simplified model. As previously proposed by Wright et al., TO2 was first calculated for each hypoxemia stage using the reference measurement of arterial O2 saturation (measured in samples drawn by invasive catheterization) for arterial blood T2. The calculated TO2, predetermined K, and measured venous blood T2 were then used in Eq. τ180 value. Approach 3: This approach was similar to Approach 2 with the exception that the values of TO2, τex, and α were learned from a training dataset. Approach 4 (our proposed approach described above): This approach was similar to Approach 2 with the exception that estimation of nuisance parameters was subjected to constraints (bounds) that were learned from a training dataset.For the animal experiment, we tested and compared results from four different approaches. Approach 1: Estimate O2 saturation from the simplified L-M model in Eq. http://www.medcalc.org; 2017). The coefficient of variation was calculated to determine the reproducibility of blood gas measurements. Linear regression was performed to compare the relationship between the venous O2 saturation estimated using CMR against the reference venous O2 saturation measured by blood gas analysis. The systematic bias and limits of agreement between the two methods were evaluated by the Bland Altman method. A regression analysis was also performed on the differences of the two methods in the Bland Altman plots to determine any proportional bias [P < 0.05.All variables are reported in mean ± standard deviation. Statistical analysis was performed in MedCalc Statistical Software version 17.8  and 184 ms (Phantom 2), respectively. The quantitative T2 values measured in the four T2 maps were similar for both phantoms. The T2 values corresponding to The average baseline characteristics for all animals are listed in Table τ180. The T2 maps acquired at four different stages of hypoxemia in one animal are shown in Fig. The heart rate and cardiac output increased with progressive hypoxemia in all animals. Arterial and venous blood T2 values decreased with lower levels of inspired oxygen. T2 of arterial and venous blood generally decreased with increasing Thirty-three paired measurements of arterial and venous blood at different oxygen saturation levels were obtained from the seven animals. Two of the animals died during the experiment, prior to 100% O2 recovery; however, data from three O2 saturation levels could be used in one of these animals, and from one O2 saturation level in the other. Six data sets, where the venous O2 saturation fell below 40% were excluded from the analysis because rapid breathing, along with high and variable heart rates at these severe hypoxemia stages, significantly degraded image quality. Therefore, the data used in the final analysis included 27 measurements - from one hypoxemia stage in one animal, three hypoxemia stages in two animals, and five hypoxemia stages in the other four animals.Out of these 27 measurements, two animals were randomly chosen to be used as a training set. These animals had five and three usable data sets respectively, leading to a total of eight data sets available for training. Using exhaustive search, a single optimal value, as well as a set of bounds that minimized average absolute error in estimated venous O2 saturation was chosen for each of the three nuisance parameters. These values or bounds limit the solution space and thus avoid local minima or physiologically improbable values. The remaining 19 data sets were then used for comparing the four solutions described in the methods above. The fixed or initial values and bounds applied in the NLLS curve fitting of the L-M model are listed in Table For the training set, the venous O2 saturation levels measured by catheter sampling ranged from 45% to 81%; for the testing set, the venous O2 saturation ranged from 47% to 87%. To determine the reproducibility of blood gas measurements, 14 data sets  were evaluated. The coefficient of variation was found to be 2.6%.K, the O2 saturation values estimated by CMR ranged from 57% to 88% and had an RMSE value of 8.8. O2 saturation could not be determined for one of the 19 data sets  since the T2 value for venous blood measured slightly higher than the arterial blood T2 (283.9 ms and 274.1 ms). For the unconstrained solution to the L-M model, the O2 saturation values estimated by CMR ranged from 6% to 99% and had an RMSE value of 26.6. The mean, standard deviation, and range of the three nuisance parameters were: 6.8×109 ± 2.6×1010 ms (165 to 1.1× 1011 ms) for TO2; 2.2×104 ± 3.9×104 ms (1.5 to 1.0× 105 ms) for τex; and 11.37 ± 17.29 ppm (0.23 to 71.69 ppm) for α. For the solution with fixed, learned values for the nuisance parameters, the O2 saturation values estimated by CMR ranged from 50% to 81% and had an RMSE value of 4.5. For the proposed constrained solution, the O2 saturation values estimated by CMR ranged from 49% to 90% and had an RMSE value of 4.1. The mean, standard deviation, and range of the three nuisance parameters were: 225 ± 27 ms (200–279 ms) for TO2; 5.0 ± 1.1 ms (3.1–6 ms) for τex; and 0.56 ± 0.01 ppm (0.52–0.57 ppm) for α.For the pre-calibrated solution using the simplified L-M model and a previously defined single calibration factor P = 0.49). Therefore, considering the small sample size, the different data points were treated independently in the regression analysis.Linear regression and Bland Altman plots comparing the different solutions for CMR estimations of O2 saturation against catheter based venous O2 saturation measurements are shown in Figs. 2 = 0.73, P < 0.0001), the fixed parameter solution , and the constrained solution . The unconstrained solution did not exhibit a significant linear relationship . The coefficient of determination, R2, was the highest for the solution with the fixed nuisance parameters while the solution with the constrained parameters demonstrated the lowest offset and slope closest to 1.0.The linear relationship between blood gas and CMR based solutions to the L-M models was significant for the pre-calibrated method  for the solution using the pre-calibrated method. The limits of agreement ranged from −18.1% to 4.4%. The bias was the highest but non-significant for the unconstrained solution ; the limits of agreement were the widest from −58.8% to 43.7%. The bias was considerably lower and non-significant for the fixed parameter solution  as well as the constrained solution . The limits of agreement for the fixed parameter solution were −7.2% to 10.1% and for the constrained solution were −9.2% to 6.5%. In addition, the regression of the differences in the Bland Altman plot showed a significant slope for the unconstrained and fixed parameter solutions, indicating a significant proportional bias in O2 saturation estimated with these methods.The Bland Altman plot showed a significant systematic bias  for TO2, eleven sets for α, and nine data sets for τex during the NLLS curve fit.With regard to the nuisance parameters, previously reported values of o 372 ms , 35, 37,to 12 ms , 37–39,  1.4 ppm , 38. In 0.69 ppm , 35, 40.It may also be advantageous to replace the bounds with Gaussian priors for the nuisance parameters. The mean and variance of such priors could be learned via training. In contrast to bounds, Gaussian priors can accommodate extended ranges for the nuisance parameters and provide a softer mechanism to discourage divergent values due to lack of estimation sensitivity.Besides providing non-invasive access to virtually any location in the cardiovascular system, this CMR-based method also offers the ability to assess average O2 saturation over large regions of interest. Catheter-based blood sampling in chambers where sufficient mixing has not occurred may result in inaccurate O2 saturation measurements as the catheter provides only a small, localized sample. Non-invasive measurement of O2 saturation by CMR, on the other hand, allows the spatial averaging of O2 saturation within a large region of interest within cardiac chambers or blood vessels. This provides effective “mixing” of the blood within the image plane and thus may overcome one limitation of diagnostic invasive catheterization. In the future, three-dimensional imaging techniques may be developed to provide full spatial coverage of cardiac chambers and large vessels.In the absence of noise or any model mismatch, an unconstrained approach described in this paper should work reliably. In the presence of measurement noise, however, the sensitivity to estimate each of the unknown parameters is limited, which results in parameter estimation with large variance. For such cases, enforcing bounds on parameters acts as a safeguard against assigning unrealistic values to some of the nuisance parameters while still providing some room for the parameters to adapt to the data. Reliance on bounds, however, is one of the limitations of this approach because the results are partially influenced by the selection of the bounds and not entirely by the data. For the in vivo data presented, one or more nuisance parameter bounds became active . Despite this limitation, our preliminary results indicate that the proposed method can outperform existing methods that use a single predetermined calibration constant.For the hypoxemia experiment, CMR was performed in the left and right ventricles. However, we obtained venous blood samples from the right atrium to avoid any artifacts that may be caused by the catheter being positioned in the imaging plane. The right atrium is known to exhibit greater regional variability of O2 saturation within the blood pool due to blood draining from the superior and inferior vena cavae and the coronary sinus. As the blood from these vessels have different levels of oxygenation, sampling of blood from the right atrium as was done in this experiment could cause greater variability in the catheter based O2 saturation measurement; this may have degraded the correlation with the CMR-based measurement that was made in the right ventricle. In addition, the arterial and venous O2 saturation levels by blood gas analysis varied from the start to the end of imaging at some hypoxemia stages despite waiting for ten minutes for the animal to achieve a steady state. We tried to alleviate any systematic bias in the measurement of T2 by acquiring the T2 maps in a randomized order, and by taking an average O2 saturation of the blood samples obtained at the beginning and end of imaging at each hypoxemia stage as the reference standard. Despite these measures, the resulting variability could account for the small inaccuracy seen between the reference and estimated venous O2 saturation in our study.Hyperoxia or breathing 100% oxygen can increase the amount of oxygen dissolved in plasma, which is known to increase the relaxation rates. However, a recent study by Ma et al.  has showAlthough the T2 preparation is non-selective, it is possible that high blood flow rates may result in partial inflow of blood from distal regions that have not experienced the magnetization preparation. Another possibility is that the proximity of the lungs and trachea to the vena cavae may have some influence on the uniformity of T2 preparation of blood. These conditions may have contributed to some of the regional T2 variations in the ventricles, and account for the larger variation in O2 saturation seen in some hypoxemia stages.Because the non-invasive pulse oximeter readings obtained from the lips of the animals were found to be unreliable, invasive arterial O2 saturation was used as the reference value. With the goal of measuring O2 saturation non-invasively in patients, an invasive arterial O2 saturation measurement would not normally be available; however, in patients a finger pulse oximeter is expected to provide a reasonable reference value for arterial O2 saturation that will support the accurate estimation of venous O2 saturation.τ180 [K = 25 s−1 applied to a venous blood sample having a T2 of 150 ms and TO2 of 300 ms would result in an estimated O2 saturation of 64%, assuming the calibration is performed for the normal hematocrit range. However, if the patient had anemia and the actual Hct was 0.25 instead of a normal value of 0.45, the true O2 saturation would be 58% if one accounted for the contribution of Hct to the L-M model in Eq. 1. We believe that our concept would be universally applicable for any mathematical representation of the exchange/diffusion model that describes the dependence of blood T2 to its corresponding O2 saturation as a function of the inter-echo spacing (τ180). The data could therefore, potentially be acquired with any imaging sequence that achieves T2 weighting with a train of refocusing pulses. By allowing the nuisance parameters to be estimated on a patient-specific basis, we do not have to account for the individual effects of age, gender, etc., on the hemodynamic properties of blood. With regard to applicability at a higher field strength of 3 T, where the effects of B0 and B1 inhomogeneities are greater, our preliminary experiments in a cohort of healthy volunteers [CMR oximetry techniques have been previously described to estimate blood O2 saturation in pediatric and adult populations , 23, 26.τ180 , 13, 35,lunteers  indicateHct(1 − Hct) in the L-M model, a solution from T2 relaxation alone is difficult due to the possibility of multiple values being estimated. Recent studies have demonstrated the potential to estimate hematocrit and oxygen saturation from T1 measurements [Non-invasive estimation of hematocrit would render the oximetry technique truly non-invasive. As hematocrit factors in as urements , and havurements . IncorpoThe clinical application of this technique would be especially valuable in heart failure, pulmonary hypertension, and congenital heart disease patients, who may present under different hemodynamic and metabolic states, and altered blood magnetic properties than the normal population. The present study focused on an animal hypoxemia model with normal cardiovascular anatomy. Animal models of intra- and extra-cardiac shunts could also be useful to help establish the performance of the technique under conditions that may be found in a congenital heart disease population.A novel CMR method for patient-specific, non-invasive estimation of blood O2 saturation in the heart was implemented and validated across a range of physiological and pathological O2 saturation levels. In this preliminary evaluation that primarily sought to establish proof of concept, effective T2 measurements of arterial and venous blood using T2-prepared bSSFP T2 maps were acquired at distinct inter-echo spacings and fit to the L-M model to non-invasively estimate O2 saturation along with three nuisance parameters. The estimation of venous O2 saturation from these effective T2 measurements of the blood pool was in good agreement with the reference measurement obtained by invasive catheterization.


Previous research has been inconsistent on whether violent video games exert positive and/or negative effects on cognition. In particular, attentional bias in facial affect processing after violent video game exposure continues to be controversial. The aim of the present study was to investigate attentional bias in facial recognition after short term exposure to violent video games and to characterize the neural correlates of this effect. In order to accomplish this, participants were exposed to either neutral or violent video games for 25 min and then event-related potentials (ERPs) were recorded during two emotional search tasks. The first search task assessed attentional facilitation, in which participants were required to identify an emotional face from a crowd of neutral faces. In contrast, the second task measured disengagement, in which participants were required to identify a neutral face from a crowd of emotional faces. Our results found a significant presence of the ERP component, N2pc, during the facilitation task; however, no differences were observed between the two video game groups. This finding does not support a link between attentional facilitation and violent video game exposure. Comparatively, during the disengagement task, N2pc responses were not observed when participants viewed happy faces following violent video game exposure; however, a weak N2pc response was observed after neutral video game exposure. These results provided only inconsistent support for the disengagement hypothesis, suggesting that participants found it difficult to separate a neutral face from a crowd of emotional faces. Research has remained inconsistent regarding the effect of violent video game exposure on cognition. For example, cross-correlational, experimental, and longitudinal studies have indicated a close association between exposure to violent video games and aggression, see two meta-analysis ,2. HowevIn recent years, the General Aggression Model (GAM) has been used by researchers to explain the association between violent video game exposure and aggressive behavior . The GAMA number of studies have identified negative effects  associated with individual exposure to violent video games –8. SpeciHowever, some researchers argue that the GAM does not effectively explain the link between violent video games and aggression . A commoAttentional bias is a key issue in studies investigating the effects of violent video games, as early attentional processes exert crucial influence on later cognitive decisions. More specifically, two opposing mechanisms have been described with regard to the effects of violent video games on affect processing  . AttentiHowever, it is difficult for individuals to discard information related to negative affect, a process known as attentional disengagement failure . InteresGiven the inconsistency in results regarding attentional regulation after exposure to violent video games, the present study aimed to investigate two differing mechanisms of attentional bias after short-term exposure to violent video games, and to characterize their neural correlates using ERP analysis. N2pc is an ERP component that is closely associated with attentional bias during visual information processing –24. AnalTwo potential mechanisms exist to explain the role of N2pc in the visual search process, including the facilitation of target stimuli and ignoring task-irrelevant stimuli to promote target-specific processing . When stIn the present study, two tasks were designed to explore the role of N2pc in emotional face processing following short-term violent video game exposure. In the facilitation task, participants were required to identify an emotional face in a group of neutral faces as quickly as possible (task A), while in the disengagement task, participants were required to rapidly separate a neutral face from angry and/or happy faces (task B). According to previous studies, the effects of violent video game exposure can be visualized by a reduction in the happy face advantage ,8 and deApproval of the study was granted by the Human Research Ethics Committee of the Southwest University of China (SWUC). In compliance with the principles of the Declaration of Helsinki, all participants provided written informed consent prior to the start of experimentation. Further, the individuals in this manuscript have given written informed consent to publish these case details.Forty-five right-handed student volunteers were recruited from SWUC  for the present study. Upon completion of the study, participants were paid RMB 40. All participants had normal or corrected-to-normal vision, and none had recently taken medication or suffered from neurological deficits .The sample size in the violent video game group was set to 23 . The neutral group  originally featured an identical sample size of n = 23; however, one participant quit the test prior to formal experimentation. This sample size (23 per group) was determined prior to recruiting participants and was based on previous ERP studies, which usually feature groups of 20 participants.Avoid Tetris, Mega World Smash, and Babel Running) and three corresponding violent video games  were included. Following completion of the games, participants were required to complete the Game Evaluation Questionnaire (GEQ) [Six video games were selected for use in preliminary studies. In accordance with previous violent video game research , 38, 39,Preliminary game evaluations included 57 participants  who were not part of the formal experiment. Each participant was required to complete two randomly selected video game evaluations . Participants played one game for 3 min in a practice round to ensure that they understood the rules. Participants then played the game for 20 min, at which point the experimenter stopped the game and asked them to complete the GEQ. After a 3-min break, participants followed the same procedure to evaluate another game.Avoid Tetris and Left 4 Dead were best matched to the neutral and violent video game categories, respectively (Left 4 Dead) than the neutral video game (Avoid Tetris)  = 12.66, and F = 12.62, respectively, p < .01). However, no other features had significant effects . Therefore, these two games were used in the formal experiment.Subsequent results indicated that ectively . With reTwo hundred and forty affective facial images were selected from the Chinese Facial Affective Picture System (CFAPS) , 41. UsiF = 515.24, p < .01) and pleasure  = 732.54, p < .01).Happy faces with scores in pleasure and arousal lower than 5, angry faces with pleasure scores higher than 2 and arousal scores lower than 3, and neutral faces with scores in pleasure and arousal lower than 3 were removed from the selection according to previous studies . Thirty Fig 1A).Emotional search task A was used to explore attentional facilitation. Participants were required to identify an emotional face among three other faces as quickly as possible. Three types of images were used for this task: a happy face with three neutral faces, an angry face with three neutral faces, and four neutral faces .Emotional search task B was used to examine attentional disengagement. In this task, participants were required to identify neutral faces among other facial stimuli as quickly as possible. Four types of images were used for this task, including a neutral face and three happy faces, a neutral face with three angry faces, four happy faces, or four angry faces  and accuracy were assessed for both tasks A and B.Continuous EEG recordings were obtained using 64 Ag-AgCl unipolar leads on a 64-lead connection, which was consistent with the extended 10–20 system, and digitized at a sampling rate of 500 Hz (Brain Products GmbH). The impedance for all electrodes was maintained below 5 kΩ. The prefrontal electrode, at the midpoint between FPz and Fz , was connected to the ground using the frontal vertex  as the online reference. Participants were asked to refrain from blinking, to remain as still as possible, and to relax their facial muscles. Participants were then required to direct their gaze towards a fixation point presented on the screen. To control for eye movement artifacts, horizontal and vertical electrooculograms were recorded from electrodes positioned above and at the outer canthus of the right eye, respectively.Offline analysis of EEG data was performed using Analyzer 2.0 software (Brain Products GmbH), with recordings re-referenced to the “infinity” reference provided by the reference electrode standardization technique (REST) . RegressFig 2) and task B . For RT and accuracy in task A, a repeated-measures ANOVA was conducted for two game types  × three target faces . For RT and ACC in task B, a repeated-measures ANOVA was conducted for two game types  × two target faces (angry and happy) × two types of consistency (conformity and unconformity). For N2pc average amplitudes, a repeated-measures ANOVA was conducted for two game types  × two target faces (angry and happy). N2pc was computed from contralateral minus ipsilateral ERP waveforms in response to angry and happy target faces. To confirm that N2pc components were reliably elicited in response to angry or happy faces, N2pc effects were compared with zero in two-tailed single-sample t tests. To measure effect sizes, Cohen’s d and partial eta-squared (η2p) values [t or F tests comparing behavioral data and N2pc amplitudes.N2pc components were quantified based on ERP waveforms measured at the lateral posterior electrodes PO7 and PO8 ,27. An e) values  were comBF1,0, which has been suggested to support the alternative hypothesis, is comprised of the following conventional cut-offs: A Bayes factor > 3 or < 1/3 represents substantial evidence; conversely, anything between 1/3 and 3 represents only weak or anecdotal evidence [For getting more reliable results in N2pc, game types and target faces were also analyzed using a Bayesian version of the repeated-measures ANOVA . Bayes fevidence .F < 2.50, p >.10). However, a significant main effect was detected for emotion  = 39.69, p < .01, η2p = .49, BF1,0 = 9.54×109) on RT, with shorter RTs in response to emotional faces  relative to neutral faces . No difference in RT was observed between angry and happy faces (p > .05). In addition, no main effect was detected for game type and no interaction was identified between game type × emotion with regard to RT .For task A, data was only available for 44 of the 45 participants, as one participant exhibited low accuracy (less than .50). F = 79.66, p < .01, η2p = .65, BF1,0 = 9.69×1036; F = 38.90, p < .01, η2p = .57, BF1,0 = 6.58×1020, respectively). Higher accuracy was identified in conditions of conformity vs. unconformity , and higher accuracy was identified when participants were presented with happy faces over neutral faces . No main effect was found for game type . However, an interaction of emotion × consistency was identified  = 9.49, p < .01, η2p = .18, BF1,0 = 7.65). Simple effect tests indicated higher accuracy in unconformity than conformity for angry faces compared with happy faces. No other two- three-way interactions were detected for accuracy .For task B, data was available for 44 participants, due to low accuracy in one participant (less than .50); this was not the same subject that exhibited low accuracy in task A. F = 27.39, p < .01, η2p = .40, BF1,0 = 2322.06; F = 49.22, p < .01, η2p = .54, BF1,0 = 2.05×109, respectively). Shorter RTs were identified in conditions of unconformity over conformity , and following exposure to happy faces compared to neutral faces . No main effect was found for game type . However, an interaction between game type × consistency × target face was identified  = 4.72, p = .035, η2p = .10, BF1,0 = 3.06). A simple effect test was performed. For conformity conditions, slower search activity was observed for angry faces compared to happy faces in the violent video game group  = 16.21, p < .01, η2p = .28); however, no difference was observed in the neutral video game group  = 3.72, p = .06 η2p = .08. For the unconformity condition, a slower RT was observed for angry faces over happy faces in both groups . No additional two-way interactions were identified for RT .For RT, significant main effects were identified for consistency and target face  and target face (angry vs. happy).F = 2.15, p = .15,η2p = .051, BF1,0 = 1.56. In addition, no main effect of game type was found, F = .21, p = .649, η2p = .001, BF1,0 = 2.94x10-25. There was no two-way interaction for game type and target face, F = .03, p = .876 η2p = .001, BF1,0 = 2.94x10-121.For task A, 42 participants were included the data analysis, as two participants demonstrated large artifacts (over 50% trail amplitudes exceeding ±100 μV). Our results indicated no main effect of target face, t(20) = -4.36, p < .01, d = .97) and happy (t(20) = -4.86, p < .01, d = 1.18) faces . An N2pc component was also observed in the neutral video game group in response to both angry (t(20) = -2.81, p = .011, d = .78) and happy (t(20) = -4.40, p < .01, d = 1.14) faces.In order to detect the N2pc component in the two gaming groups, we compared the component measures with zero, and observed significant N2pc activity in the violent video game group in response to both angry  = .66, p = .421,η2p = .017, BF1,0 = .892. In addition, no main effect of game type was found, F = .94, p = .339, η2p = .025, BF1,0 = .295. There was a weak two-way interaction of game type and target face, F = 4.22, p = .046 η2p = .097, BF1,0 = 2.56.Data from 41 participants were used for task B, since three participants demonstrated large artifacts (over 50% trail amplitudes exceeding ±100 μV). Our results indicated no main effect of target face, t(19) = -.01, p = .99, d = .01) or angry (t(19) = -1.79, p = .09, d = .40) faces . Despite this, N2pc activity was detected in the neutral video game group (t(20) = -5.71, p < .01, d = 1.02), but not in response to angry faces (t(20) = -.23, p = .82, d = .06). This therefore provides weak evidence for attentional capture having occurred in response to happy but not angry faces for the neutral video game group. In addition, regardless of the target face, the violent video game group exhibited difficulty in disengaging for task B.In order to detect the N2pc component in the two gaming groups, we compared the component measures with zero, and observed no N2pc activity in the violent video game group in response to either happy  than what we employed in the present study . This difference is crucial since violent games such as House of the Dead 2 are more dread-based, while the game we employed was a shooting game, which was extremely bloody. However, despite inconsistencies with previous research, attentional facilitation was identified in response to both violent and neutral video games, and this finding is not consistent with the GAM theory that violent video games increase aggressive cognition .The present study identified no effects of violent video game exposure on attentional facilitation, which did not support our predictions. Specifically, the N2pc results observed during task A suggested that attentional facilitation did not solely result from violent video game exposure, since both violent and neutral video games had the same effect on attentional bias in response to happy and angry faces, indicating that attention was focused on array switching. As previously mentioned, N2pc reflects the attentional selection process ; thus, oN2pc responses during the attentional disengagement task reflect the top-down regulatory nature of attentional selection processes. A significant N2pc component was identified in response to happy faces following participant exposure to neutral but not violent video games. On the other hand, individuals exposed to violent video games experienced difficulty in disengagement when searching for happy faces; specifically, these participants took longer to distinguish happy faces from neutral faces. N2pc has been linked to attentional ability , 27, wheIt is worth noting that no significant N2pc component was identified in response to angry faces in both the violent and neutral video game groups, which suggests that difficulty in disengagement was not unique to violent video game exposure. This finding was inconsistent with our predictions. Although research has been inconsistent, and marked by some significant flaws, there is some evidence that may indicate some action oriented games may influence social cue processing and attentional bias to threatening faces , 20, howThe present findings are not consistent with previous action video game studies, which have reported that game exposure might improve cognitive shifting and attention . HoweverDespite encouraging findings, the present study was subject to several limitations. First, while effort was made to control for difficulty, enjoyment, and other video game attributes, various aspects, such as competitiveness and arousal, were not matched. Indeed, a higher level of arousal was observed in almost all subjects following violent video game exposure when compared to those exposed to neutral video games. Therefore, future research must control for the abovementioned key variables as much as possible in order to help resolve debates regarding the effects of violent video games. Second, two typical types of emotional faces were employed in this study. Other studies have considered a wider range emotions, including disgust or sadness, which might produce different attention bias after exposure to violent video games. In particular, it remains unclear whether difficulties in disengagement from negative stimuli were due to desensitization resulting from violent video game exposure or difficulties in disengagement from negative stimuli. Future research should investigate this. Third, our participants were predominantly male. Although the majority of violent video game players are male, a balance of genders might be more suitable and could provide further insight on the effects of exposure to violent video games. In addition, individual variables, such as personality traits, were not considered in the present study. Previous research suggests that individuals with increased neuroticism, one of the “Big Five” personality traits, prefer to play violent video games and demonstrate attentional bias to negative stimuli , 50. FurWith regard to debates into the effects of violent video games, the present study suffered from the above limitations, and was unable to provide direct evidence of the effects of violent video games on aggression. It might be that difficulties in disengagement result from violent video game exposure. However, caution should be exercised in the interpretation of our results, especially, with regard to this critical issue. Specifically, whether there exists a close association between violent video game exposure and aggressive behavior requires further research.While future investigation is needed, the present study identified the neural correlates of media violence on attentional and emotional face processing. To clarify the involvement of attentional component facilitation vs. difficulty in disengagement, we conducted two emotional search tasks after video game exposure . Our results did not support the facilitation mechanism of violent video game exposure, indicating no significant difference in N2pc activity between the two game groups. However, reduced attentional capture was observed following violent video game exposure, supporting difficulty in disengagement as a potential attentional mechanism that might underlie the effects of violent video game exposure on affect processing. No N2pc component was observed in response to happy faces in individuals exposed to violent video games, but weak N2pc activity in response to happy faces was observed in individuals exposed to neutral video games. This provided only inconsistent support for the disengagement hypothesis, as we postulated that participants would exhibit difficulty disengaging only after violent video game exposure.S1 File(XLS)Click here for additional data file.S2 File(XLS)Click here for additional data file.


The colorimetric response of the AuNPs toward Mg2+ was noticed with naked eyes, and spectral changes were monitored by using UV-Vis spectrophotometer. The detection response was rapid (less than 1 min), with a detection limit (LOD) about 0.2 µmol L−1. The proposed nanoprobe shows characteristic red-shift of the AuNPs at 620 nm and high selectivity for Mg2+ due to the binding affinity of the tryptophan with Mg2+. The real-time response of the UV-Vis spectrum was monitored at three different concentrations of Mg2+ . The AuNPs probe was suitable to provide a molecular platform for selective coordination with Mg2+ over Ca2+ ions, thus it could be facile to establish a practically viable sensing system. Furthermore, experimental results were confirmed to exhibit excellent linear curve for urine and serum samples spiked with Mg2+. Thus, this nanosensor is practically useful for the detection of Mg2+, without using expensive instruments, enzymes and/or DNA molecules.The functional nanoparticles with specific molecular probe appear to be a promising approach for developing colorimetric nanosensor. In this work, we have synthesized tryptophan capped gold nanoparticles (AuNPs) and used to establish colorimetric detection of magnesium (Mg Mg2+ acts as a cofactor for more than 300 enzymes, and also play an important role in controlling ion transport, structural stabilization of the proteins, enzymes, and nucleic acids1. Mg2+ ion remains chelated in chlorophyll via carboxyl groups of the photosynthetic apparatus, thus play a central role in chlorophyll structure and functions2. Magnesium deficiency can result in a variety of disorders including, hypocalcemia, hypokalemia, and neurological disorders3. Water hardness caused by Ca2+ and Mg2+ is a great concern in both domestic and industrial wastewater management since it involves in cerebrovascular disease and cardiovascular risk4. The measurement of Mg2+ have been accomplished using traditional methods, such as atomic absorption spectroscopy (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS). However, involving expensive instrumentation and complex detection procedures, the previously reported methods demands upgradations6.Magnesium .Tryptophan and HAuCl4. The AuNPs synthesis reaction was allowed to run for 48 hours at 95 °C. Centrifugation of the AuNPs solution was carried out at 10,000 rpm for 15 min to remove unbound tryptophan molecules and NaOH used in the synthesis. UV-Vis spectrophotometer (Optizen-2120) was used to record UV-Vis spectrum of the AuNPs in the wavelength range from 400 to 900 nm, with a resolution of 5 nm. Transmission electron microscope (TEM) images of the AuNPs were obtained from a Hitachi HF-3300. TEM samples were prepared by adding 100 μL of the AuNPs solution onto the 200-mesh Formvar-coated copper grid. X-ray diffraction (XRD) spectrum of the of the AuNPs thin film was measured by using Rigaku Ultima-IV System by operating at voltage 40 kV and current of 30 mA using Cu K radiation. FT-IR spectra of the centrifuged AuNPs was collected by using an infrared spectrometer (Thermo Electron Nicolet-6700).A typical growth solution of the AuNPs was prepared as follows: 3-mL of the aqueous solutions tryptophan (6.25 mM) was added in different glass bottles containing diluted NaOH (5 mM). This solution was brought to 95 °C and the synthesis of the AuNPs was initiated by adding 1.0 mL of 20 mM HAuCl2+ was carried out as follows: 300 μL of AuNPs stocking solution was added in water  aqueous solution. The absorbance spectra of the AuNPs suspensions having different concentrations of Mg2+  were measured respectively after 20 min of the incubation. Subsequently, concentration vs absorbance intensity at 620 nm was plotted to test the linear fit.The measurement of the AuNPs sensitivity toward Mg2+ by using different concertations of the diluted NaOH . Typically, 300 μL of AuNPs was treated with 0.05 mM NaOH and total volume (1-mL) was adjusted by distilled water. The absorbance spectra of the AuNPs suspensions having different concentrations of Mg2+  were measured after 20 min of the incubation. The same protocol was followed for quantification of Mg2+ in the range  at 0.1 mM NaOH. Furthermore, quantification of Mg2+ in a broad concentration range  was established at 0.2 mM NaOH.This report investigates the possibility of tuning the sensitivity of the AuNPs toward Mg2+. Typically, 300 μL of the AuNPs solution was suspended in water . The UV-Vis spectrum of the AuNPs was acquired before exposure to Mg2+. Subsequently, AuNPs suspensions were treated with three different concertations of Mg2+ . The red-shift of the longitudinal and SPR band were observed for a long period of the time (20 to 360 min).UV-Vis spectral response of the AuNPs was detected at different time intervals after reaction with Mg−1 stock Mg2+ solution was added to the respective NaOH-AuNPs suspensions. These suspensions were again placed inside the UV-Vis spectrophotometer for another 10 min and the absorbance was measured at 530 nm. The same protocol was followed to test the effect of NaCl , and CaCl2  in identical conditions.The effect of pH values on the AuNPs was studied as follows: 400 μL of the AuNPs stocking solution was suspended in water  at different concertations of NaOH and HCl . These suspensions were placed inside the UV-Vis spectrophotometer for 10 min and the absorbance was measured at 530 nm. Then, 50 µL of 10 µmol L2+ over other metal ions was investigated. The selectivity assay was conducted in water for Mg2+, Hg3+, Co3+, As+, Li+, Cr3+, Ca2+, K+, Mn3+, Zn3+, Cd2+, and Pb3+ at 200 ppb. The absorbance spectra of the AuNPs suspension were measured respective samples. These suspensions were placed inside the UV-Vis spectrophotometer for 20 min and the absorbance spectra of the suspensions were measured.In addition, the selectivity of the AuNPs toward Mg2+. At first, a mixture of the metal ions  was mixed with 600 µL of the AuNPs solution. Then the UV-Vis spectrum of the AuNPs was acquired in the presence of these metal ions. The UV-Vis spectrum was measured after adding 50 µL of 10 µmol L−1 Mg2+ to demonstrate the selectivity of the AuNPs.After testing the selectivity of the AuNPs toward Mg2+ ions. Typically, 300 μL of the AuNPs solution was treated with 0.5 mL urine and artificial serum samples. Finally, total volume about 1-mL was adjusted by adding distilled water. The UV-Vis spectrum of the AuNPs suspensions was acquired after 20 min of the incubation. Subsequently, concentration vs absorbance intensity at 620 nm was plotted. Unknown samples were monitored using standard graph prepared for urine and serum samples.UV-Vis spectral response of the AuNPs was collected after reacting urine and artificial serum samples containing Mg2+. The UV-Vis spectrum, size, shape, and structure of the AuNPs were examined by different techniques. Figure 15. The FT-IR spectrum of the centrifuged AuNPs was shown in Fig. −1 corresponds to the stretching vibrations of the C = O bond of the amide Fig. −1 from the OH stretching vibrations. The adsorptive interaction of the amino acid was reported with silica particles16. The AuNPs having spherical shape and narrow size-distribution with average size about 15 nm was observed by TEM. It can be seen that AuNPs were dispersed with few aggregates formed from the two or three nanoparticles in the Fig. The tryptophan capped AuNPs were used for characterization and application as a sensitive probe for Mg2+ . It was easy to demonstrate the assay for visual detection of Mg2+ based on the color change from purple to dark blue as shown in the inset of the Fig. 2+ from 0.35 to 0.45 µmol L−1 was prominent and stable at 620 nm. The red-shift of the longitudinal band and the characteristic spectral response attributes to the coupled plasmon absorbance of the AuNPs in close proximity. Furthermore, there was a linear relation between the relative absorbance intensity at 620 nm and the concentration of Mg2+ varying from 0.1 to 0.45 μmol L−1 with a detection limit of 0.2 µmol L−1  was examined using Cys- DTT-AuNPs suspensions at room temperature5.Sensing experiments were carried out by using centrifuged AuNPs having SPR band at 530 nm. As shown in Fig. L−1 Fig. . It is s2+. The intensity of the absorbance was highly responsive toward Mg2+. Tryptophan capped AuNPs showed enhanced stability in diluted NaOH concentrations (0.05 to 0.2 mM). Thus, the absorbance enhancement was adjusted at different concentrations of NaOH . The AuNPs were made suitable for detecting and quantification of Mg2+ due to their pH sensitivity. A linear response for Mg2+ ions from 0.4 to 1.0 µmol L−1 was established by adding of 0.05 mM NaOH to the detection system  at 0.2 mM NaOH  within the time frame of 20 to 360 min  even after incubation for 360 min indicates excellent stability of the AuNP aggregates   Fig. . The abs2+ sensing ability at different sensing conditions were investigated by measuring decrease in absorbance at 530 nm. The result shown in Fig. 2+ was decreased in the presence of diluted NaOH. The result observed with diluted HCl (0.05 to 0.5 mM) shows that the AuNPs were responsive to the acidic pH conditions. The absorbance intensity at 530 nm was significantly decreased in acidic conditions in the presence and the absence of Mg2+ ions  under identical conditions. The results showed that most of the other metal ions do not cause the colorimetric response of the AuNPs. However, the Mg2+ could increase the absorbance intensity of the AuNPs at 620 nm. According to the previous reports, tryptophan ligands may coordinate with metal ions21.High selectivity is significantly important to establish excellent colorimetric sensor. Thus, the selectivity of the AuNPs was examined by screening its response to individual metal ions  was significantly important. Figure 2+ and results a broad red-shift of the longitudinal band located at 660 nm. However, ability of the probe to recognize Mg2+ in the presence of other competitive metal ions could be demonstrated.It was important to note that both Ca25. A facile, rapid, and cost-effective methods are desired to diagnose impaired absorption in the intestines and excessive excretion of Mg2+ by the kidneys. This sensor was tested to reveal its applications in detecting renal function deterioration by measuring Mg2+ concentrations in urine and artificial serum samples. The similar linear curve was observed when the titrations were carried out in the presence of urine, suggesting that presence numerous metabolites in urine are not preventive for the detection of Mg2+ 26. Cerebral spinal fluid samples contain both Ca2+ and Mg2+ in mM level, thus proposed sensor is an excellent alternative for the detection of Mg2+, without the interference from the Ca2+ ions5. To our knowledge, no other small-molecular receptors were reported for Mg2+ in urine and serum samples. Selective detection of Mg2+ is appropriate to identify the significance of the Mg2+ in many physiological functions and pathological conditions27. Thus, results demonstrated reliability of the tryptophan capped AuNPs for detecting Mg2+ contents in real samples.Renal magnesium wasting has been recognized in numerous conditions, including congenital defects, endocrine disorders , and exposure to the drugs g2+ Fig. . The devrum Fig. . And it 2+. Functional AuNPs could be prepared easily and environmental friendly by mixing HAuCl4 to the tryptophan solution. Hence, this is the first report which explores sensing based on the tryptophan capped AuNPs for the analysis of Mg2+ content in a wide concentration range of Mg2+. The color change from purple to dark blue and well-defined red-shift appears within the fraction of a minute indicates coordination complex forms rapidly. The proposed design of a colorimetric assay where AuNPs acts as an indicator–receptor coupled with tryptophan ligands. The decrease in absorbance intensity of the AuNPs was significantly dependent on the concentration of Mg2+, thus the potential opportunity to prepare stable and unstable AuNP aggregates. This probe allows the detection of Mg2+ with high sensitivity and selectivity, without the interference from the competitive metal ions. Biologically relevant ions Ca2+ and K+ do not compete with AuNPs when it bounds with Mg2+. Furthermore, the proposed probe is suitable to detect Mg2+ content in water, urine, and serum samples.In summary, a facile detection method based on absorbance probe AuNPs has been established, which allows highly sensitive determination of Mg


Medical education is a rapidly evolving field that has been using new technology to improve how medical students learn. One of the recent implementations in medical education is the recording of lectures for the purpose of playback at various speeds. Though previous studies done via surveys have shown a subjective increase in the rate of knowledge acquisition when learning from sped-up lectures, no quantitative studies have measured information retention. The purpose of this study was to compare mean test scores on written assessments to objectively determine if watching a video of a recorded lecture at 1.5× speed was significantly different than 1.0× speed for the immediate retention of novel material.Fifty-four University of Kentucky medical students volunteered to participate in this study. The subjects were divided into two separate groups: Group A and Group B. Each group watched two separate videos, the first at 1.5× speed and the second at 1.0× speed, then completed assessments following each. The topics of the two videos were ultrasonography artifacts and transducers. Group A watched the artifacts video first at 1.5× speed followed by the transducers video at 1.0× speed. Group B watched the transducers video first at 1.5× speed followed by the artifacts video at 1.0× speed. The percentage correct on the written assessment were calculated for each subject at each video speed. The mean and standard deviation were also calculated using a t-test to determine if there was a significant difference in assessment scores between 1.5× and 1.0× speeds.There was a significant (p=0.0188) detriment in performance on the artifacts quiz at 1.5× speed  compared to the control group at normal speed . On the transducers assessment, there was not a significant (p=0.1365) difference in performance in the 1.5× speed group  compared to the control group .These findings suggest that, unlike previously published studies that showed subjective improvement in performance with sped-up video-recorded lectures compared to normal speed, objective performance may be worse. Medical education is a rapidly evolving field that has been using new forms of media and technology to enhance the learning of medical students across the U.S. One of the more prevalent and extensively used advancements is the use of video recording systems. In previous studies, medical students have reported greater subjective benefit from video-recorded lectures than from live lectures.1The advantages to using video-recorded lectures include the ability to rewind, pause and return to finish a lecture later, and watch lectures at faster speeds. In a medical school setting where knowledge of minutiae and comprehension of concepts is paramount to success, the added flexibility that video-recorded lectures provide could be extremely important. As medical education demands countless hours of studying, the biggest advantage may be the ability to watch lectures at faster speeds. As an example, for every hour of material in the traditional classroom setting played at 1.5× speed, a student could save 20 minutes. Therefore, in a typical four-hour morning lecture scenario, a student could save 80 minutes by watching the video at 1.5× speed.Though the benefits may seem numerous and prior survey studies have shown subjective benefits with lectures played at faster speeds, no quantitative studies to date have measured information retention. The objective of this pilot study was to determine if watching video-recorded lectures at faster speeds compared to the original recording had any effect on the immediate retention of novel learning material.This was a prospective, single-center, randomized controlled trial, pilot study that presented a novel curriculum to medical students and tested information retention with a short examination. Material presentation and assessments were all done in a single day. The study was approved by the university institutional review board (IRB), as well as by the administration of the medical school involved.The two new educational subjects chosen were transducers and artifacts. The presented videos were recorded by a nationally recognized emergency ultrasound educator. These two specific videos were chosen because these topics are not covered in the medical school curriculum and, therefore, we believed that the material presented was novel. Subjects were also asked if they had exposure to the material; if they had, they were excluded from the study. Additionally, these videos were similar in length  and “factoid heavy,” or in other words, had a wealth of material that could be used to assess student learning.What do we already know about this issue?Previous survey studies have shown a subjective increase in the rate of knowledge acquisition from sped-up lectures. However, no quantitative studies have measured objective retention.What was the research question?Would students’ mean test scores differ significantly after watching video lectures at 1.5× speed compared to 1.0× speed?What was the major finding of the study?We found that watching a lecture at a faster speed may have a detrimental or no significant effect on learning novel material.How does this improve population health?This data is important to modern learners as it challenges the assumption that faster podcast speeds lead to potential time savings for learners.We created a 23-question multiple-choice assessment for the transducers video, and a 20-question assessment for the artifacts video. Given the pilot nature of the study, the assessments were tested by the two medical students involved in the study as well as by the video creator and content experts to ensure that the two tests were of comparable difficulty levels. To avoid different interpretations of a correct answer, the tests asked about definable facts explicitly stated in the video. The investigators created an answer key for both assessments, which were subsequently reviewed and proofread before submission to the IRB.We conducted the experiment in August, at the beginning of the school year, when first-year (M1), second-year (M2) and third-year (M3) medical students had limited exposures to emergency medicine (EM). Subject recruitment was conducted by first sending an email to all four medical school classes. This was then followed by live announcements to each class. All students were told that results on the assessments would have no effect on medical school evaluations or grades and that participation was voluntary. Students who participated were given a $5 Starbucks gift card as a token of appreciation.Inclusion criteria for subjects included being a medical student and being over the age of 18. The primary exclusion criterion was having been exposed to the presented material before, since prior knowledge of the subjects could skew the results. Additionally, medical students with prior ultrasound experience and students rotating in EM were excluded from the study.To enforce the exclusion criteria, each participant was asked to enroll via Google Docs and sign an informed consent prior to the study. Each student was asked to answer “yes” or “no” to having previously seen either the transducers video or the artifacts video. Those who answered “yes” received the $5 Starbucks gift card and the opportunity to sit in on the study, but they were excluded from examination and data analysis. To protect the privacy of student performance, each student was identified by his/her student ID number. Demographic data including ethnicity, gender, and year in medical school were also collected. Assessment performance was not shared with the medical school.Of the 81 students who signed up for the study, 63 showed up on the day of the experiment. Two were excluded from the examination for having prior knowledge of the material, and seven were excluded from assessment for arriving late. As a result, 54 medical students were included in the final data analysis. Participants were randomized into group A or B by converting the Google docs sign-up document to a Microsoft Excel spreadsheet, and then using the “randomize” function to assign participants into either group A or B. On the date of the experiment, participants could see their group assignment at the check-in desk.Group A watched the artifacts video at 1.5× speed first and then took the artifacts assessment immediately after the video. Following this, Group A watched the transducers video at normal speed and immediately took the transducers assessment. Group A served as the experimental group for the artifacts video and the control group for the transducers video. Group B watched the transducers video at 1.5× speed first and took the corresponding assessment immediately following the video. Group B then watched the artifacts video at normal speed and took the assessment. Group B served as the experimental group for the transducers video and the control group for the artifacts video.Since the two assessments had an unequal number of questions, the scores were converted into a percent correct score. Then the means and standard deviations (SD) of the variable of interest and percentage score were calculated for each assessments . Group A Artifacts at 1.5× speed was compared to Group B Artifacts at normal speed using a t-test. Similarly, Group B Transducers at 1.5× speed was compared to Group A Transducers at normal speed using a t-test. To compare the demographic information, such as year in medical school, gender, and ethnicity, the Fisher’s exact test was used. The p-values were used to determine if there was a significant difference in performance for both videos. Statistical significance was set at p < 0.05. All analyses were completed in R version 3.4.1 .A total of 54 students participated in the study. Of these, 21 were M1s, 27 were M2s, two were M3s, and four were M4s. Thirty participants were female and 24 were male. Finally, seven participants self-identified as Asian American, one as African American, 45 as Caucasian, and one participant chose not to provide ethnicity .There was a similar distribution of M1, M2, M3, and M4 in each group. Among the 21 M1s, 11 were in Group A and 10 in Group B. Among the 27 M2s, 14 were in Group B and 13 in Group B. Each Group A and B had three M3 and M4 participants.The average performance of Group A on the assessment for Artifacts at 1.5× speed ± SD was 61.4 ± 19.3% . On the Transducers assessment at normal speed, Group A’s mean performance was 73.8 ± 15.6%  .The average performance of Group B on the assessment for transducers at 1.5× speed was 66.9 ± 17.6% . For artifacts at normal speed, Group B averaged 72.7 ± 14.6% .For both videos, the performance of the control and experimental groups were compared using the t-test, and estimated the effect sizes using Cohen’s d. For the artifacts video, there was a significant difference between the performance at 1.5× speed compared to 1.0× speed (p= 0.0188), along with a moderate effect size (Cohen’s d = 0.654). For the transducers video, a statistically non-significant (p= 0.1365) difference was found in the performance between the two groups along with a small effect size (Cohen’s d = 0.414).We compared the performance of the control groups of artifacts and transducers videos using the t-test and found no significant difference (p= 0.7965), suggesting that the tests did not differ in difficulty.We chose to conduct a quantitative analysis of students’ information retention after viewing a sped-up video compared to retention at normal speed because there was a lack of literature regarding the topic. To assess retention, novel education material was presented to the test subjects one at normal speed and another at 1.5× speed and assessed comprehension after each video. Participants overall performed worse on assessments after learning from 1.5× speed compared to 1.0× speed. For the artifacts video, the average test score was 72.7 at 1.0× speed compared to 61.4 at 1.5× speed. For the transducers video, the average test score was 73.8 at 1.0× speed compared to 66.9 at 1.5× speed. Our findings were contrary to previous studies that reported subjective, accelerated learning when learning from videos at faster speeds.The difference in performance on the artifacts quiz at 1.5× speed compared to the control group was significant. Although the difference in performance of the 1.5× group compared to the control group was not significant for the transducers video, the difference was equivalent to a letter-grade difference.The discrepancy in relative performance between control and experimental groups for each of the videos may be explained by confounding factors. The main confounding error that may have led to the difference in results was that the artifacts video and assessment may have been more inherently complex in nature compared to the transducers video and assessment. Although the video selection was done deliberately to ensure videos were similar in length and in the amount of fact content covered, retrospectively we realized that for a novice learner, a few of the questions on the artifacts video may have been more conceptual compared to the transducers questions.For example, many students answered correctly to the question asking about the A line on the artifacts video, much in the same way they answered correctly about the linear transducer having a higher frequency. However, with no prior knowledge of how ultrasound works, many students answered incorrectly on posterior acoustic shadowing vs. enhancement. As one participant later remarked, as a new learner she focused all her cognitive energy learning to associate that stones cause sound waves to reflect back, which made her associate stones with the word “enhancement.” However, someone with a basic concept of ultrasound would have easily picked up that because of this reflection of sound waves off the stone, there would be shadowing of the structures lying posterior to it. We theorize that when learning multiple-step processes such as these, playback speed plays a more significant role than when learning a rote memorization fact.This data is important to modern learners as it challenges the assumption that faster podcast speeds lead to potential time savings for learners. This time savings is only realized if the retention of the material is comparable.Among this study’s limitations was the small sample size of 54 students that limited the power of this study. Also, even though students with prior exposure to subject material were excluded from the study, it was impossible to ensure that the entire study population was naïve to the material. Another limitation was the inability to establish that the two novel subject matters presented were equivalent in complexity, as discussed above. Final noteworthy point was our decision to play the 1.5× speed video before the 1.0× speed. This may have affected performance and impacted the study results.This study was designed to examine the immediate recall of information after watching a video at 1.5× speed vs. at normal speed. However, to emulate the full utility of video-recorded lectures, students must be given the ability to rewind parts of the lecture they did not understand or re-watch a lecture a second time. A potential study design to examine this could involve giving both the experimental and control groups the same allotted time to learn a lecture while using 1.0× speed or 1.5× speed and comparing their performance. Long-term information retention is another variable that should be assessed. This study only tested immediate recall.Our study suggests that watching a video lecture at a faster speed may have detrimental or no significant effect on learning novel material. Contrary to previous studies showing subjective improvement in performance with sped-up, video-recorded lectures compared to normal speed, our data showed that immediate retention of novel material at 1.5× speed was worse compared to normal speed.


I would like for you to join me in a thought exercise to explore how and why our current generation of students are compelled to shoulder up to $100,000 in graduate school debt to enter our profession. Not only are the debt levels onerous, these loans typically bear interest rates of up to 7%. In contrast, it is easy to get a car loan for around 4%. What is the meaning of this for our newly minted generation of professional colleagues?http://www.slate.com/blogs/browbeat/2014/10/10/germany_college_is_free_there_even_for_foreign_students_why.html).I remember a time when tuition was affordable and it was relatively easy to complete a master's or doctorate in medical physics without any debt at all. That was only a generation ago. What changed and why? If we look across the pond, nations of the European Union seem to be working to eliminate university tuition. Germany did this in 2014 (http://trends.collegeboard.org/college‐pricing/figures‐tables/tuition‐fees‐room‐board‐time‐1974‐75‐2014‐15‐selected‐years)?Yes, I believe a good education is worth paying for, and maybe free tuition is an unreasonable goal in the United States. However many US universities seem to be swimming in gifts, grants, endowments, and other resources. Why are some graduate medical physics program tuitions so high, and why have we been so willing and unconcerned to see these tuitions rise so dramatically? Why have tuitions increased at double‐digit rates beyond inflation? Is it because the universities were able to do so because students had access to virtually unlimited amounts of funds in the form of loans guaranteed by the Federal Government :wage garnishment without a court ordersuspension of state professional licensesgarnishment of social security/disability incomewithholding IRS tax refundsHarsh collection methods are reserved for student loans. Miss a few payments and you may experience . Does it, therefore, make sense for our system to penalize the youngest and most vulnerable of our colleagues trying to make it in a difficult economy?So why are things the way they are? Who benefits from this situation? One reality is that the US Federal Government profits from about $50 billion per year from student loan debt (http://www.forbes.com/sites/jeffreydorfman/2014/04/19/student‐loan‐profits‐show‐government‐should‐get‐out‐of‐student‐loan‐business/).I do not expect anything to happen respecting student debt relief. Why? Because America's higher learning system itself is dependent on perpetuating the status quo. Because if loans are harder to come by, college tuitions would be subject to downward pressure and the business model of the modern university would be threatened. Even if it makes little sense for the Federal Government to profit at the expense of graduate student debt, the Universities need the revenue from these artificially high tuitions . Work hard, get your Board Certification, and pay off your loans as soon as you possibly can. Live frugally and save. And consider your salary could be about the same as a starting general practice physician, many of whom have up to $200,000 and more in student loans to pay off. Medical physics can still be a smart career choice, if you do it right.My counsel to anyone considering medical physics as a career is to identify a graduate program that has low tuition and a good record for placing its students in residency programs. Make every effort to qualify for in‐state tuition. Embrace the reality that some program graduates will not successfully match to enter a residency program (Michael D. Mills, PhDEditor‐in‐Chief