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Molecular dynamics (MD) simulations are frequently carried out for proteins to investigate the role of electrostatics in their biological function. The choice of force field (FF) can significantly alter the MD results, as the simulated local electrostatic interactions lack benchmarking in the absence of appropriate experimental methods. We recently reported that the transition dipole moment (TDM) of the popular nitrile vibrational probe varies linearly with the environmental electric field, overcoming well-known hydrogen bonding (H-bonding) issues for the nitrile frequency and, thus, enabling the unambiguous measurement of electric fields in proteins ( J. Am. Chem. Soc. 2022 , 144 (17), 7562-7567). Herein, we utilize this new strategy to enable comparisons of experimental and simulated electric fields in protein environments. Specifically, previously determined TDM electric fields exerted onto nitrile-containing o -cyanophenylalanine residues in photoactive yellow protein are compared with MD electric fields from the fixed-charge AMBER FF and the polarizable AMOEBA FF. We observe that the electric field distributions for H-bonding nitriles are substantially affected by the choice of FF. As such, AMBER underestimates electric fields for nitriles experiencing moderate field strengths; in contrast, AMOEBA robustly recapitulates the TDM electric fields. The FF dependence of the electric fields can be partly explained by the presence of additional negative charge density along the nitrile bond axis in AMOEBA, which is due to the inclusion of higher-order multipole parameters; this, in turn, begets more head-on nitrile H-bonds. We conclude by discussing the implications of the FF dependence for the simulation of nitriles and proteins in general.

Magnetic particle spectroscopy (MPS) in the Brownian relaxation regime, also termed magnetic spectroscopy of Brownian motion (MSB), can detect and quantitate very low, sub-nanomolar concentrations of molecular biomarkers. MPS/MSB uses the harmonics of the magnetization induced by a small, low-frequency oscillating magnetic field to provide quantitative information about the magnetic nanoparticles' (mNPs') microenvironment. A key application uses antibody-coated mNPs to produce biomarker-mediated aggregation that can be detected using MPS/MSB. However, relaxation changes can also be caused by viscosity changes. To address this challenge, we propose a metric that can distinguish between aggregation and viscosity. Viscosity changes scale the MPS/MSB harmonic ratios with a constant multiplier across all applied field frequencies. The change in viscosity is exactly equal to the multiplier with generality, avoiding the need to understand the signal explicitly. This simple scaling relationship is violated when particles aggregate. Instead, a separate multiplier must be used for each frequency. The standard deviation of the multipliers over frequency defines a metric isolating viscosity (zero standard deviation) from aggregation (non-zero standard deviation). It increases monotonically with biomarker concentration. We modeled aggregation and simulated the MPS/MSB signal changes resulting from aggregation and viscosity changes. MPS/MSB signal changes were also measured experimentally using 100 nm iron-oxide mNPs in solutions with different viscosities (modulated by glycerol concentration) and with different levels of aggregation (modulated by concanavalin A linker concentrations). Experimental and simulation results confirmed that viscosity changes produced small changes in the standard deviation and aggregation produced larger values of standard deviation. This work overcomes a key barrier to using MPS/MSB to detect biomarkers in vivo with variable tissue viscosity.

Estimating statistical significance of the difference between two spectra or series is a fundamental statistical problem. Multivariate significance tests exist but the limitations preclude their use in many common cases; e.g., one-sided testing, unequal variance and when few repetitions are acquired all of which are required in magnetic spectroscopy of nanoparticle Brownian motion (MSB). We introduce a test, termed the T-S test, that is powerful and exact (exact type I error). It is flexible enough to be one- or two-sided and the one-sided version can specify arbitrary regions where each spectrum should be larger. The T-S test takes the-one or two-sided p-value at each frequency and combines them using Stouffer's method. We evaluated it using simulated spectra and measured MSB spectra. For the single-sided version, mean of the spectrum, A-T, was used as a reference; the T-S test is as powerful when the variance at each frequency is uniform and outperforms when the noise power is not uniform. For the two-sided version, the Hotelling T2 two-sided multivariate test was used as a reference; the two-sided T-S test is only slightly less powerful for large numbers of repetitions and outperforms rather dramatically for small numbers of repetitions. The T-S test was used to estimate the sensitivity of our current MSB spectrometer showing 1 nanogram sensitivity. Using eight repetitions the T-S test allowed 15 pM concentrations of mouse IL-6 to be identified while the mean of the spectra only identified 76 pM.

Nitriles are widely used vibrational probes; however, the interpretation of their IR frequencies is complicated by hydrogen bonding (H-bonding) in protic environments. We report a new vibrational Stark effect (VSE) that correlates the electric field projected on the -C≡N bond to the transition dipole moment and, by extension, the nitrile peak area or integrated intensity. This linear VSE applies to both H-bonding and non-H-bonding interactions. It can therefore be generally applied to determine electric fields in all environments. Additionally, it allows for semiempirical extraction of the H-bonding contribution to the blueshift of the nitrile frequency. Nitriles were incorporated at H-bonding and non-H-bonding protein sites using amber suppression, and each nitrile variant was structurally characterized at high resolution. We exploited the combined information available from variations in frequency and integrated intensity and demonstrate that nitriles are a generally useful probe for electric fields.

Photosynthetic reaction centers (RCs) from Rhodobacter sphaeroides were engineered to vary the electronic properties of a key tyrosine (M210) close to an essential electron transfer component via its replacement with site-specific, genetically encoded noncanonical amino acid tyrosine analogs. High fidelity of noncanonical amino acid incorporation was verified with mass spectrometry and X-ray crystallography and demonstrated that RC variants exhibit no significant structural alterations relative to wild type (WT). Ultrafast transient absorption spectroscopy indicates the excited primary electron donor, P*, decays via a ∼4-ps and a ∼20-ps population to produce the charge-separated state P + H A - in all variants. Global analysis indicates that in the ∼4-ps population, P + H A - forms through a two-step process, P*→ P + B A - → P + H A - , while in the ∼20-ps population, it forms via a one-step P* → P + H A - superexchange mechanism. The percentage of the P* population that decays via the superexchange route varies from ∼25 to ∼45% among variants, while in WT, this percentage is ∼15%. Increases in the P* population that decays via superexchange correlate with increases in the free energy of the P + B A - intermediate caused by a given M210 tyrosine analog. This was experimentally estimated through resonance Stark spectroscopy, redox titrations, and near-infrared absorption measurements. As the most energetically perturbative variant, 3-nitrotyrosine at M210 creates an ∼110-meV increase in the free energy of P + B A - along with a dramatic diminution of the 1,030-nm transient absorption band indicative of P + B A - formation. Collectively, this work indicates the tyrosine at M210 tunes the mechanism of primary electron transfer in the RC., Competing Interests: The authors declare no competing interest.

Rationale and Objectives: Hydrocephalus (HC) is caused by accumulating cerebrospinal fluid resulting in enlarged ventricles and neurological symptoms. HC can be treated via a shunt in a subset of patients; identifying which individuals will respond through noninvasive imaging would avoid complications from unsuccessful treatments. This preliminary work is a longitudinal study applying MR Elastography (MRE) to HC patients with a focus on normal pressure hydrocephalus (NPH)., Materials and Methods: Twenty-two ventriculomegaly patients were imaged and subsequently received a lumbar drain placement for cerebrospinal fluid (CSF) drainage. NPH lumbar drain responders and NPH syndrome nonresponders were categorized by clinical presentation. Displacement images were acquired using intrinsic activation (IA) MRE and poroelastic inversion recovered shear stiffness and hydraulic conductivity values. A stable IA-MRE inversion protocol was developed to produce unique solutions for both recovered properties, independent of initial estimates., Results: Property images showed significantly increased shear modulus (p = 0.003 in periventricular region, p = 0.005 in remaining cerebral tissue) and hydraulic conductivity (p = 0.04 in periventricular region) in ventriculomegaly patients compared to healthy volunteers. Baseline MRE imaging did not detect significant differences between NPH lumbar drain responders and NPH syndrome nonresponders; however, MRE time series analysis demonstrated consistent trends in average poroelastic shear modulus values over the course of the lumbar drain process in responders (initial increase, followed by a later decrease) which did not occur in nonresponders., Conclusion: These findings are indicative of acute mechanical changes in the brain resulting from CSF drainage in NPH patients., (Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Magnetic Resonance Elastography allows noninvasive visualization of tissue mechanical properties by measuring the displacements resulting from applied stresses, and fitting a mechanical model. Poroelasticity naturally lends itself to describing tissue - a biphasic medium, consisting of both solid and fluid components. This article reviews the theory of poroelasticity, and shows that the spatial distribution of hydraulic permeability, the ease with which the solid matrix permits the flow of fluid under a pressure gradient, can be faithfully reconstructed without spatial priors in simulated environments. The paper describes an in-house MRE computational platform - a multi-mesh, finite element poroelastic solver coupled to an artificial epistemic agent capable of running Bayesian inference to reconstruct inhomogenous model mechanical property images from measured displacement fields. Building on prior work, the domain of convergence for inference is explored, showing that hydraulic permeabilities over several orders of magnitude can be reconstructed given very little prior knowledge of the true spatial distribution., Competing Interests: Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Under physiological conditions biomarker concentrations tend to rise and fall over time e.g. for inflammation. Ex vivo measurements provide a snapshot in time of biomarker concentrations, which is useful, but limited. Approaching real time monitoring of biomarker concentration(s) using a wearable, implantable or injectable in vivo sensor is therefore an appealing target. As an early step towards developing an in vivo biomarker sensor, antibody (AB) tagged magnetic nanoparticles (NPs) are used here to demonstrate the in vitro measurement of ~5 distinct biomarkers with high specificity and sensitivity. In previous work, aptamers were used to target a given biomarker in vitro and generate magnetic clusters that exhibit a characteristic rotational signature quite different from free NPs. Here the method is expanded to detect a much wider range of biomarkers using polyclonal ABs attached to the surface of the NPs. Commercial ABs exist for a wide range of targets allowing accurate and specific concentration measurements for most significant biomarkers. We show sufficient detection sensitivity, using an in-house spectrometer to measure the rotational signatures of the NPs, to assess physiological concentrations of hormones, cytokines and other signaling molecules. Detection limits for biomarkers drawn mainly from pain and inflammation targets were: 10 pM for mouse Granzyme B (mGZM-B), 40 pM for mouse interferon-gamma (mIFN- γ ), 7 pM for mouse interleukin-6 (mIL-6), 40 pM for rat interleukin-6 (rIL-6), 40 pM for mouse vascular endothelial growth factor (mVEGF) and 250 pM for rat calcitonin gene related peptide (rCGRP). Much lower detection limits are certainly possible using improved spectrometers and nanoparticles.

We are developing magnetic nanoparticle (NP) methods to characterize inflammation and infection in vivo. Peritoneal infection in C57BL/6 mice was used as a biological model. An intraperitoneal NP injection was followed by measurement of magnetic nanoparticle spectroscopy of Brownian rotation (MSB) spectra taken over time. MSB measures the magnetization of NPs in a low frequency alternating magnetic field. Two groups of three mice were studied; each group had two infected mice and one control with no infection. The raw MSB signal was compared with two derived metrics: the NP relaxation time and number of NPs present in the sensitive volume of the receive coil. A four compartment dynamic model was used to relate those physical properties to the relevant biological processes including phagocytic activity and migration. The relaxation time increased over time for all of the mice as the NPs were absorbed. The NP number decreased over time as the NPs were cleared from the sensitive volume of the receive coil. The composite p-values for all three rate constants were significant: raw signal, 0.0002, relaxation, <10 -16 and local NP clearance, <10 -16 . However, not all the individual mice had significant changes: Only half the infected mice had significantly different rate constants for raw signal reduction. All infected mice had significantly smaller relaxation time constants. All but one of the infected mice had significantly lower rate constants for local clearance. Relaxation is affected by both phagocytic activity, edema and temperature changes and it should be possible to better isolate those effects to more completely characterize inflammation using more advanced MSB methods. The MSB NP signal can be used to identify inflammation in vivo because it has the unique ability to monitor phagocytic absorption through relaxation measurements.

Magnetic resonance elastography (MRE) has been developed to noninvasively reconstruct mechanical properties for tissue and tissue-like materials over a frequency range of 10 ~200 Hz. In this work, low frequency (1~1.5 Hz) MRE activations were employed to estimate mechanical property distributions of simulated data and experimental phantoms. Nonlinear inversion (NLI) MRE algorithms based on viscoelastic and poroelastic material models were used to solve the inverse problems and recover images of the shear modulus and hydraulic conductivity. Data from a simulated phantom containing an inclusion with property contrast was carried out to study the feasibility of our low frequency actuated approach. To verify the stability of NLI algorithms for low frequency actuation, different levels of synthetic noise were added to the displacement data. Spatial distributions and property values were recovered well for noise level less than 5%. For the presented experimental phantom reconstructions with regularizations, the computed storage moduli from viscoelastic and poroelastic MRE gave similar results. Contrast was detected between inclusions and background in recovered hydraulic conductivity images. Results and findings confirm the feasibility of future in vivo neuroimaging examinations using natural cerebrovascular pulsations at cardiac frequencies, which can eliminate specialized equipment for high frequency actuation.

The quantification of magnetic nanoparticles is important for many applications, especially for in vivo biosensing. The magnetization harmonics used in spectroscopy of magnetic nanoparticles can be used to estimate nanoparticle number or weight. However, other effects such as temperature or relaxation time change can also influence the nanoparticle magnetization. Therefore, it is necessary to compensate for these factors when estimating the amount of magnetic nanoparticles. This paper shows through simulation that a two-dimensional scaling method can be used to improve the accuracy of nanoparticle quantification, especially when multiple effects are present which can influence the nanoparticle magnetization. Finally, an experiment was performed on a Magnetic Spectroscopy of Brownian motion (MSB) apparatus to demonstrate this method, and nanoparticle weight was determined with a mean error of 1.3 ng (1.81%).

Purpose: The harmonic spectrum of the magnetization of magnetic nanoparticles (MNPs) in the presence of an applied magnetic field can be used to characterize the properties of the microenvironment of the MNPs. The change in temperature and relaxation time has been measured by varying the magnetic field amplitudes or frequency to obtain the harmonic spectrum. However, scaling estimates of temperature or relaxation time are poor if both change simultaneously. In this work, we show that scaling over both the amplitude and frequency of the applied magnetic field allows both the temperature and relaxation to be estimated simultaneously., Methods: The scaling methods previously used to measure temperature and relaxation times individually have been expanded to two dimensions allowing both parameters to be estimated simultaneously. Samples with different temperature and relaxation times were measured using a magnetic nanoparticle spectrometer to verify this two-dimensional scaling method. Simulations were also carried out for a range of nanoparticle sizes, and the best particle sizes were estimated for this two-dimensional method., Results: The two-dimensional scaling method achieved a mean error of 0.83% for relaxation time by considering the temperature variation as well as relaxation time changes. The temperature and viscosity of the MNPs were measured simultaneously with the mean error of 1.03°C and 0.011 mPas. For monodisperse particles with Brownian relaxation, simulation showed that core radius of 16 nm and hydrodynamic radius of 23 nm had best accuracy for the scaling method., Conclusions: The two-dimensional scaling method allows both temperature and relaxation time to be estimated simultaneously. The measurement accuracy can be improved by combining information in ratios and phases of the magnetic harmonics of the magnetization and by choosing the optimal particle sizes., (© 2019 American Association of Physicists in Medicine.)

Intrinsic activation MR elastography (IA-MRE) is a novel technique which seeks to estimate brain mechanical properties non-invasively and without external mechanical drivers. The method eliminates actuation hardware and patient discomfort while capitalizing on the brain's intrinsic low frequency motion. This study explores low frequency actuation (1 Hz) MR elastography in phantoms and analyzes performance of non-linear inversion (NLI) of viscoelastic and poroelastic mechanical models as a framework for assessing clinical results from IA-MRE. We present results from four gelatin phantoms and report stiffness resolution of 6 mm (two measurement voxels) with a stiffness contrast ratio of 4.21 relative to the background and 9 mm (three measurement voxels) with a lower stiffness contrast ratio of near 1.77. Stiffness edge resolution was also evaluated using edge spread and line spread functions and yielded a stiffness edge response distance of 9 mm. The intraclass correlation coefficient was high (0.93) between mechanical testing and poroelastic estimates, although quantitative agreement was affected by model-data mismatch. Viscoelastic MRE at low frequencies has issues with non-uniqueness due to small inertial forces, and performed worse than poroelastic MRE in terms of inclusion detection and consistency with mechanical testing. These results present the first evaluation of MR elastography using displacement measurements from an actuation frequency less than 5 Hz and support the validity of brain IA-MRE to recover spatially resolved stiffness changes. They provide a baseline of performance in terms of standard metrics for future animal and human brain stiffness studies and analyses based on intrinsic motion.

Magnetic Resonance Elastography (MRE) detects induced periodic motions in biological tissues allowing maps of tissue mechanical properties to be derived. In-vivo MRE is commonly performed at frequencies of 30-100 Hz using external actuation, however, using cerebro-vascular pulsation at 1 Hz as a form of intrinsic actuation (IA-MRE) eliminates the need for external motion sources and simplifies data acquisition. In this study a hydraulic actuation system was developed to drive 1 Hz motions in gelatin as a tool for investigating the performance limits of IA-MRE image reconstruction under controlled conditions. Quantitative flow (QFLOW) MR techniques were used to phase encode 1 Hz motions as a function of gradient direction using 3D or 4D acquisition; 4D acquisition was twice as fast and yielded comparable motion field and concomitant image reconstruction results provided the motion signal was sufficiently strong. Per voxel motion noise floor corresponded to a displacement amplitude of about 20-30 μm. Signal to noise ratio (SNR) was 94 ± 17 for 3D and dropped to 69 ± 10 for the faster 4D acquisition, but yielded octahedral shear stress and shear modulus maps of high quality that differed by only about 20% on average. QFLOW measurements in gel phantoms were improved significantly by adding Mn(II) to mimic relaxation rates found in brain. Overall, the hydraulic 1 Hz actuation system when coupled with 4D sequence acquisition produced a fast reliable approach for future IA-MRE phantom evaluation and contrast detail studies needed to benchmark imaging performance., (Copyright © 2018 Elsevier Inc. All rights reserved.)

This study evaluated non-linear inversion MRE (NLI-MRE) based on viscoelastic governing equations to determine its sensitivity to small, low contrast inclusions and interface changes in shear storage modulus and damping ratio. Reconstruction parameters identical to those used in recent in vivo MRE studies of mechanical property variations in small brain structures were applied. NLI-MRE was evaluated on four phantoms with contrast in stiffness and damping ratio. Image contrast to noise ratio was assessed as a function of inclusion diameter and property contrast, and edge and line spread functions were calculated as measures of imaging resolution. Phantoms were constructed from silicone, agar, and tofu materials. Reconstructed property estimates were compared with independent mechanical testing using dynamic mechanical analysis (DMA). The NLI-MRE technique detected inclusions as small as 8 mm with a stiffness contrast as low as 14%. Storage modulus images also showed an interface edge response distance of 11 mm. Damping ratio images distinguished inclusions with a diameter as small as 8 mm, and yielded an interface edge response distance of 10 mm. Property differences relative to DMA tests were in the 15%-20% range in most cases. In this study, NLI-MRE storage modulus estimates resolved the smallest inclusion with the lowest stiffness contrast, and spatial resolution of attenuation parameter images was quantified for the first time. These experiments and image quality metrics establish quantitative guidelines for the accuracy expected in vivo for MRE images of small brain structures, and provide a baseline for evaluating future improvements to the NLI-MRE pipeline.

Purpose: To evaluate the thrombus maturity noninvasively providing the promise of much earlier and more accurate diagnosis of diseases ranging from stroke to myocardial infarction to deep vein thrombosis., Methods: Magnetic spectroscopy of nanoparticle Brownian rotation (MSB), a form of magnetic particle spectroscopy sensitive to Brownian rotation of magnetic nanoparticles, was used for the detection and characterization of blood clots. The nanoparticles' relaxation time was quantified by scaling the MSB spectra in frequency to match the spectra from nanoparticles in a reference state. The nanoparticles' relaxation time, in the bound state, was used to characterize the nanoparticle binding to thrombin on the blood clot. The number of nanoparticles bound to the clot was also estimated. Both the relaxation time and the weight of bound nanoparticles were obtained for clots of several ages, reflecting different stages of development and organization. The impact of clot development was explored using functionalized nanoparticles present during clot formation., Results: The relaxation time of the bound nanoparticles decreases for more mature, organized clots. The number of nanoparticles able to bind the clot diminishes quantitatively with clot age. On mature clots, the nanoparticles bind the thrombin on the surface while for developing clots the nanoparticles bind several thrombin molecules or become trapped in the clot matrix during formation., Conclusions: By estimating the magnetic nanoparticles' relaxation time the clot age and organization can be predicted. The purposed methods are quick and minimally invasive for in vivo applications., (© 2018 American Association of Physicists in Medicine.)

Photosynthetic reaction centers (RCs) are the membrane proteins responsible for the initial charge separation steps central to photosynthesis. As a complex and spectroscopically complicated membrane protein, the RC (and other associated photosynthetic proteins) would benefit greatly from the insight offered by site-specifically encoded noncanonical amino acids in the form of probes and an increased chemical range in key amino acid analogues. Toward that goal, we developed a method to transfer amber codon suppression machinery developed for E. coli into the model bacterium needed to produce RCs, Rhodobacter sphaeroides. Plasmids were developed and optimized to incorporate 3-chlorotyrosine, 3-bromotyrosine, and 3-iodotyrosine into RCs. Multiple challenges involving yield and orthogonality were overcome to implement amber suppression in R. sphaeroides, providing insights into the hurdles that can be involved in host transfer of amber suppression systems from E. coli. In the process of verifying noncanonical amino acid incorporation, characterization of this membrane protein via mass spectrometry (which has been difficult previously) was substantially improved. Importantly, the ability to incorporate noncanonical amino acids in R. sphaeroides expands research capabilities in the photosynthetic field.

A series of techniques have been developed to use magnetic nanoparticles as biosensors to characterize their local microenvironment. Two approaches have been used to obtain quantitative information: model based approaches and scaling based approaches. We have favored scaling based approaches, because approximations made in models can lead to limitations in the accuracy. Currently all the scaling approaches use harmonic ratios to retrieve physical parameters like temperature, viscosity and relaxation time. In this work, we showed that the phase angle of the signal at a single harmonic frequency is an alternative to the ratio. The phase angle is nanoparticle density-independent, and can be used to improve sensitivity, enabling us to measure smaller biomedical effects. With the phase angle as an example, we showed that scaling methods are general and do not depend on specific approximations. We showed that the same scaling techniques can be used with both the phase angle and harmonic ratio because they both depend on the same combinations of physical parameters. Using the phase angle improves the precision and using the combination of phase angles and harmonic ratio provides the best precision.

The noninvasive imaging technique of magnetic resonance elastography (MRE) was used to estimate the power law behavior of the viscoelastic properties of the human brain in vivo. The mechanical properties for four volunteers are investigated using shear waves induced over a frequency range of 10-50Hz to produce a displacement field measured by magnetic resonance motion-encoding gradients. The average storage modulus (μ R ) reconstructed with non-linear inversion (NLI) increased from approximately 0.95 to 2.58kPa over the 10-50Hz span; the average loss modulus (μ I ) also increased from 0.29 to 1.25kPa over the range. These increases were modeled by independent power law (PL) relations for μ R and μ I returning whole brain, group mean exponent values of 0.88 and 1.07 respectively. Investigation of these exponents also showed distinctly different behavior in the region of the cerebral falx compared to other brain structures., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed.

Deep vein thrombosis, the development of blood clots in the peripheral veins, is a very serious, life threatening condition that is prevalent in the elderly. To deliver proper treatment that enhances the survival rate, it is very important to detect thrombi early and at the point of care. We explored the ability of magnetic particle spectroscopy (MSB) to detect thrombus via specific binding of aptamer functionalized magnetic nanoparticles with the blood clot. MSB uses the harmonics produced by nanoparticles in an alternating magnetic field to measure the rotational freedom and, therefore, the bound state of the nanoparticles. The nanoparticles' relaxation time for Brownian rotation increases when bound [A.M. Rauwerdink and J. B. Weaver, Appl. Phys. Lett. 96 , 1 (2010)]. The relaxation time can therefore be used to characterize the nanoparticle binding to thrombin in the blood clot. For longer relaxation times, the approach to saturation is more gradual reducing the higher harmonics and the harmonic ratio. The harmonic ratios of nanoparticles conjugated with anti-thrombin aptamers (ATP) decrease significantly over time with blood clot present in the sample medium, compared with nanoparticles without ATP. Moreover, the blood clot removed from the sample medium produced a significant MSB signal, indicating the nanoparticles are immobilized on the clot. Our results show that MSB could be a very useful non-invasive, quick tool to detect blood clots at the point of care so proper treatment can be used to reduce the risks inherent in deep vein thrombosis.

Design: Case report., Setting: Operating room., Patient: 25YF, ASA IV E who underwent an emergent decompressive craniectomy for refractory intracranial hypertension secondary to acute intracranial hemorhage., Interventions: A 25Y caucasian female presented with acute intracranial hemorrhage with intraventricular extension secondary to Moya Moya disease. Post admisison, she underwent an emergent decompressive craniectomy for medically refractory intracranial hypertension. Introperatively (post dural closure and bone flap removal) the patient developed acutely worsening peak and plateau pressures followed by pulseless electrical activity necessitating CPR with epinephrine and Vasopressin before return of circulation before return of circulation. Intraoperative TEE done during return of circulation, was essentially non diagnostic, the patient had normal breath sounds throughout, and non-contributory bronchoscopy findings., Measurements: EKG, arterial blood pressure, heart rate, resp. rate, introperative tranesophageal echocardiogram (TEE), Pulse oximetry, serial arterial blood gases, introperative bronchoscopy, ventilatory peak pressures., Main Results: A post operative chest CT revealed extensive pneumomediastinum with subcutaneous emphysema. The focussed introperative echocardiogram showed preserved left ventricular function and no evidence of tamponade physiology., Conclusions: Tension pneumomediastinum was the likely etiologic factor for the acute hemodynamic collapse and should be considered in the differential diagnosis of intraoperative circulatory arrest., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The extremely high sensitivity that has been suggested for magnetic particle imaging has its roots in the unique signal produced by the nanoparticles at the frequencies of the harmonics of the drive field. That sensitivity should be translatable to other methods that utilize magnetic nanoparticle probes, specifically towards magnetic nanoparticle spectroscopy that is used to measure molecular biomarker concentrations for an " in vivo ELISA" assay approach. In this paper, we translate the predicted sensitivity of magnetic particle imaging into a projected sensitivity limit for in vivo ELISA. The simplifying assumptions adopted are: 1) the limiting noise in the detection system is equivalent to the minimum detectable mass of nanoparticles; 2) the nanoparticle's signal arising from Brownian relaxation is completely eliminated by the molecular binding event, which can be accomplished by binding the nanoparticle to something so massive that it can no longer physically rotate and is large enough that Neel relaxation is minimal. Given these assumptions, the equation for the minimum concentration of molecular biomarker we should be able to detect is obtained and the in vivo sensitivity is estimated to be in the attomolar to zeptomolar range. Spectrometer design and nonspecific binding are the technical limitations that need to be overcome to achieve the theoretical limit presented.

We describe an efficient gradient computation for solving inverse problems arising in magnetic resonance elastography (MRE). The algorithm can be considered as a generalized 'adjoint method' based on a Lagrangian formulation. One requirement for the classic adjoint method is assurance of the self-adjoint property of the stiffness matrix in the elasticity problem. In this paper, we show this property is no longer a necessary condition in our algorithm, but the computational performance can be as efficient as the classic method, which involves only two forward solutions and is independent of the number of parameters to be estimated. The algorithm is developed and implemented in material property reconstructions using poroelastic and viscoelastic modeling. Various gradient- and Hessian-based optimization techniques have been tested on simulation, phantom and in vivo brain data. The numerical results show the feasibility and the efficiency of the proposed scheme for gradient calculation.

Understanding the dynamics of magnetic particles can help to advance several biomedical nanotechnologies. Previously, scaling relationships have been used in magnetic spectroscopy of nanoparticle Brownian motion (MSB) to measure biologically relevant properties (e.g., temperature, viscosity, bound state) surrounding nanoparticles in vivo. Those scaling relationships can be generalized with the introduction of a master variable found from non-dimensionalizing the dynamical Langevin equation. The variable encapsulates the dynamical variables of the surroundings and additionally includes the particles' size distribution and moment and the applied field's amplitude and frequency. From an applied perspective, the master variable allows tuning to an optimal MSB biosensing sensitivity range by manipulating both frequency and field amplitude. Calculation of magnetization harmonics in an oscillating applied field is also possible with an approximate closed-form solution in terms of the master variable and a single free parameter.

Magnetic nanoparticles have been studied intensely because of their possible uses in biomedical applications. Biosensing using the rotational freedom of particles has been used to detect biomarkers for cancer, hyperthermia therapy has been used to treat tumors, and magnetic particle imaging is a promising new imaging modality that can spatially resolve the concentration of nanoparticles. There are two mechanisms by which the magnetization of a nanoparticle can rotate, a fact that poses a challenge for applications that rely on precisely one mechanism. The challenge is exacerbated by the high sensitivity of the dominant mechanism to applied fields. Here, we demonstrate stochastic Langevin equation simulations for the combined rotation in magnetic nanoparticles exposed to oscillating applied fields typical to these applications to both highlight the existing relevant theory and quantify which mechanism should occur in various parameter ranges.

Magnetic nanoparticles are promising tools for a host of therapeutic and diagnostic medical applications. The dynamics of rotating magnetic nanoparticles in applied magnetic fields depend strongly on the type and strength of the field applied. There are two possible rotation mechanisms and the decision for the dominant mechanism is often made by comparing the equilibrium relaxation times. This is a problem when particles are driven with high-amplitude fields because they are not necessarily at equilibrium at all. Instead, it is more appropriate to consider the "characteristic timescales" that arise in various applied fields. Approximate forms for the characteristic time of Brownian particle rotations do exist and we show agreement between several analytical and phenomenological-fit models to simulated data from a stochastic Langevin equation approach. We also compare several approximate models with solutions of the Fokker-Planck equation to determine their range of validity for general fields and relaxation times. The effective field model is an excellent approximation, while the linear response solution is only useful for very low fields and frequencies for realistic Brownian particle rotations.

Dynamic mechanical analysis (DMA) is a common way to measure the mechanical properties of materials as functions of frequency. Traditionally, a viscoelastic mechanical model is applied and current DMA techniques fit an analytical approximation to measured dynamic motion data by neglecting inertial forces and adding empirical correction factors to account for transverse boundary displacements. Here, a finite-element (FE) approach to processing DMA data was developed to estimate poroelastic material properties. Frequency-dependent inertial forces, which are significant in soft media and often neglected in DMA, were included in the FE model. The technique applies a constitutive relation to the DMA measurements and exploits a nonlinear inversion to estimate the material properties in the model that best fit the model response to the DMA data. A viscoelastic version of this approach was developed to validate the approach by comparing complex modulus estimates to the direct DMA results. Both analytical and FE poroelastic models were also developed to explore their behavior in the DMA testing environment. All of the models were applied to tofu as a representative soft poroelastic material that is a common phantom in elastography imaging studies. Five samples of three different stiffnesses were tested from 1-14 Hz with rough platens placed on the top and bottom surfaces of the material specimen under test to restrict transverse displacements and promote fluid-solid interaction. The viscoelastic models were identical in the static case, and nearly the same at frequency with inertial forces accounting for some of the discrepancy. The poroelastic analytical method was not sufficient when the relevant physical boundary constraints were applied, whereas the poroelastic FE approach produced high quality estimates of shear modulus and hydraulic conductivity. These results illustrated appropriate shear modulus contrast between tofu samples and yielded a consistent contrast in hydraulic conductivity as well.

Purpose: Descriptions of the structure of brain tissue as a porous cellular matrix support application of a poroelastic (PE) mechanical model which includes both solid and fluid phases. However, the majority of brain magnetic resonance elastography (MRE) studies use a single phase viscoelastic (VE) model to describe brain tissue behavior, in part due to availability of relatively simple direct inversion strategies for mechanical property estimation. A notable exception is low frequency intrinsic actuation MRE, where PE mechanical properties are imaged with a nonlinear inversion algorithm., Methods: This paper investigates the effect of model choice at each end of the spectrum of in vivo human brain actuation frequencies. Repeat MRE examinations of the brains of healthy volunteers were used to compare image quality and repeatability for each inversion model for both 50 Hz externally produced motion and ≈1 Hz intrinsic motions. Additionally, realistic simulated MRE data were generated with both VE and PE finite element solvers to investigate the effect of inappropriate model choice for ideal VE and PE materials., Results: In vivo, MRE data revealed that VE inversions appear more representative of anatomical structure and quantitatively repeatable for 50 Hz induced motions, whereas PE inversion produces better results at 1 Hz. Reasonable VE approximations of PE materials can be derived by equating the equivalent wave velocities for the two models, provided that the timescale of fluid equilibration is not similar to the period of actuation. An approximation of the equilibration time for human brain reveals that this condition is violated at 1 Hz but not at 50 Hz. Additionally, simulation experiments when using the "wrong" model for the inversion demonstrated reasonable shear modulus reconstructions at 50 Hz, whereas cross-model inversions at 1 Hz were poor quality. Attenuation parameters were sensitive to changes in the forward model at both frequencies, however, no spatial information was recovered because the mechanisms of VE and PE attenuation are different., Conclusions: VE inversions are simpler with fewer unknown properties and may be sufficient to capture the mechanical behavior of PE brain tissue at higher actuation frequencies. However, accurate modeling of the fluid phase is required to produce useful mechanical property images at the lower frequencies of intrinsic brain motions.

We know a great deal about the biochemistry of cells because they can be isolated and studied. The biochemistry of the much more complex in vivo environment is more difficult to study because the only ways to quantitate concentrations is to sacrifice the animal or biopsy the tissue. Either method disrupts the environment profoundly and neither method allows longitudinal studies on the same individual. Methods of measuring chemical concentrations in vivo are very valuable alternatives to sacrificing groups of animals. We are developing microscopic magnetic nanoparticle (mNP) probes to measure the concentration of a selected molecule in vivo . The mNPs are targeted to bind the selected molecule and the resulting reduction in rotational freedom can be quantified remotely using magnetic spectroscopy. The mNPs must be contained in micrometer sized porous shells to keep them from migrating and to protect them from clearance by the immune system. There are two key issues in the development of the probes. First, we demonstrate the ability to measure concentrations in the porous walled alginate probes both in phosphate buffered saline and in blood, which is an excellent surrogate for the complex and challenging in vivo environment. Second, sensitivity is critical because it allows microscopic probes to measure very small concentrations very far away. We report sensitivity measurements on recently introduced technology that has allowed us to improve the sensitivity by two orders of magnitude, a factor of 200 so far.

Superparamagnetic iron oxide nanoparticles with highly nonlinear magnetic behavior are attractive for biomedical applications like magnetic particle imaging and magnetic fluid hyperthermia. Such particles display interesting magnetic properties in alternating magnetic fields and here we document experiments that show differences between the magnetization dynamics of certain particles in frozen and melted states. This effect goes beyond the small temperature difference (Δ T ~ 20 °C) and we show the dynamics to be a mixture of Brownian alignment of the particles and Néel rotation of their moments occurring in liquid particle suspensions. These phenomena can be modeled in a stochastic differential equation approach by postulating log-normal distributions and partial Brownian alignment of an effective anisotropy axis. We emphasize that precise particle-specific characterization through experiments and nonlinear simulations is necessary to predict dynamics in solution and optimize their behavior for emerging biomedical applications including magnetic particle imaging.