Superparamagnetic nanoparticles (SMNPs) with nonlinear magnetic behavior under alternating magnetic fields hold great potential in biomedical applications, including magnetic hyperthermia, biosensing, magnetic separation, magnetic particle imaging, etc. Magnetic hyperthermia therapy, based on the relaxation movement of SMNPs subjected to an alternating magnetic field, is a promising modality for tumor treatment. Herein, we applied the stochastic Langevin equation to study the magnetic hyperthermia performance of SMNPs by taking the coupled Brownian-N & eacute;el rotations into account. The specific absorption rate (SAR) of magnetic fluids is used as a parameter for optimizing the amplitude and frequency of alternating magnetic fields and guiding the design of SMNPs. Specifically, by accounting for the dipole-dipole interactions between SMNPs, it is revealed that these interactions significantly suppress the relaxation behavior of particles, thereby reducing SAR. Furthermore, this study systematically examines the effects of key factors such as particle concentration, particle size, and magnetic anisotropy constant on SAR. The accurate prediction of the rotational and magnetic dynamics of SMNPs under an oscillating magnetic field provides valuable theoretical insights and technical support for the optimized design of external magnetic field systems and the precise fabrication of SMNPs.

Using a recently developed technique to estimate gas temperatures ( T _SF ) in star-forming regions from large photometric surveys, we propose a diagram, analogous to the Hertzsprung–Russell diagram for individual stars, to probe the evolution of individual galaxies. On this T _SF -sSFR (specific star formation rate) diagram, a small fraction of star-forming galaxies appear to be dominated by different feedback mechanisms than typical star-forming galaxies. These galaxies generically have younger stellar populations and lower stellar masses and increase in relative abundance toward higher redshifts, so we argue that these objects are in an earlier stage of galactic star formation. Further, Hubble observations find that these “core-forming” galaxies also exhibit distinct morphology and that tracks on the T _SF -sSFR diagram are also a morphological sequence. Thus, unlike starburst phases which can be triggered environmentally, these earliest core-forming galaxies appear to be a stage that typical galaxies go through early in their star formation history. We therefore argue that most galaxies first go through a core formation stage, then subsequently disk formation, and finally become quiescent.

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.

The stellar initial mass function (IMF) is predicted to depend upon the temperature of gas in star-forming molecular clouds. The introduction of an additional parameter, T_IMF , into photometric template fitting, allows galaxies to be fit with a range of IMFs. Three surprising new features appear: (1) most star-forming galaxies are best fit with a bottom-lighter IMF than the Milky Way; (2) most star-forming galaxies at fixed redshift are fit with a very similar IMF; and (3) the most massive star-forming galaxies at fixed redshift instead exhibit a less bottom-light IMF, similar to that measured in quiescent galaxies. Additionally, since stellar masses and star formation rates both depend on the IMF, these results slightly modify the resulting relationship, while yielding similar qualitative characteristics to previous studies.

The white matter tracts of brain tissue consist of highly-aligned, myelinated fibers; white matter is structurally anisotropic and is expected to exhibit anisotropic mechanical behavior. In vivo mechanical properties of tissue can be imaged using magnetic resonance elastography (MRE). MRE can detect and monitor natural and disease processes that affect tissue structure; however, most MRE inversion algorithms assume locally homogenous properties and/or isotropic behavior, which can cause artifacts in white matter regions. A heterogeneous, model-based transverse isotropic implementation of a subzone-based nonlinear inversion (TI-NLI) is demonstrated. TI-NLI reconstructs accurate maps of the shear modulus, damping ratio, shear anisotropy, and tensile anisotropy of in vivo brain tissue using standard MRE motion measurements and fiber directions estimated from diffusion tensor imaging (DTI). TI-NLI accuracy was investigated with using synthetic data in both controlled and realistic settings: excellent quantitative and spatial accuracy was observed and cross-talk between estimated parameters was minimal. Ten repeated, in vivo, MRE scans acquired from a healthy subject were co-registered to demonstrate repeatability of the technique. Good resolution of anatomical structures and bilateral symmetry were evident in MRE images of all mechanical property types. Repeatability was similar to isotropic MRE methods and well within the limits required for clinical success. TI-NLI MRE is a promising new technique for clinical research into anisotropic tissues such as the brain and muscle.

ALMA observations of the long wavelength dust continuum are used to estimate the gas masses in a sample of 708 star-forming (SF) galaxies at z = 0.3 to 4.5. We determine the dependence of gas masses and star formation efficiencies (SFE=SFR per unit gass mass). We find that 70 percent of the increase in SFRs of the MS is due to the increased gas masses at earlier epochs while 30 percent is due to increased efficiency of SF. For galaxies above the MS this is reversed with 70 percent of the increased SFR relative to the MS being due to elevated SFEs. Thus, the major evolution of star formation activity at early epochs is driven by increased gas masses, while the starburst activity taking galaxies above the MS is due to enhanced triggering of star formation (likely due to galactic merging). The interstellar gas peaks at z = 2 and dominates the stellar mass down to z = 1.2. Accretion rates needed to maintain continuity of the MS evolution exceed 100 Msun per yr at z > 2. The galactic gas contents are likely the driving determinant for both the rise in SF and AGN activity from z = 5 to their peak at z = 2 and subsequent fall to lower z. We suggest that for self-gravitating clouds with supersonic turbulence, cloud collisions and the filamentary structure of the clouds regulate the star formation activity.

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 ng 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.

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

Neuronal nitric oxide synthase (nNOS) generates superoxide, particularly at sub-optimal l-arginine (l-Arg) substrate concentrations. Heat shock protein 90 (Hsp90) was reported to inhibit superoxide generation from nNOS protein. However, commercially available Hsp90 product from bovine brain tissues with unspecified Hsp90α and Hsp90β contents and an undefined Hsp90 protein oligomeric state was utilized. These two Hsp90s can have opposite effect on superoxide production by NOS. Importantly, emerging evidence indicates that nNOS splice variants are involved in different biological functions by functioning distinctly in redox signaling. In the present work, purified recombinant human Hsp90α, in its native dimeric state, was used in electron paramagnetic resonance (EPR) spin trapping experiments to study the effects of Hsp90α on superoxide generation from nNOS splice variants nNOSμ and nNOSα. Human Hsp90α was found to significantly increase superoxide generation from nNOSμ and nNOSα proteins under l-Arg-depleted conditions and Hsp90α influenced superoxide production by nNOSμ and nNOSα at varying degrees. Imidazole suppressed the spin adduct signal, indicating that superoxide was produced at the heme site of nNOS in the presence of Hsp90α, whereas l-Arg repletion diminished superoxide production by the nNOS-Hsp90α. Moreover, NADPH consumption rate values exhibited a similar trend/difference as a function of Hsp90α and l-Arg. Together, these EPR spin trapping and NADPH oxidation kinetics results demonstrated noticeable Hsp90α-induced increases in superoxide production by nNOS and a distinguishable effect of Hsp90α on nNOSμ and nNOSα proteins.

EPR can uniquely measure paramagnetic species. Although commercial EPR was introduced in 1950s, the early studies were mostly restricted to chemicals in solution or cellular experiments using X-band EPR equipment. Due to its limited penetration (< 1 mm), experiments with living animals were almost impossible. To overcome these difficulties, Swartz group, along with several other leaders in field, pioneered the technology of low-frequency EPR (e.g., L-band, 1–2 GHz). The development of low-frequency EPR and the associated probes have dramatically expanded the application of EPR technology into the biomedical research field, providing answers to important scientific questions by measuring specific parameters that are impossible or very difficult to obtain by other approaches. In this review, which is aimed at highlighting the seminal contribution from Swartz group over the last several decades, we will focus on the development of EPR technology that was designed to deal with the potential challenges arising from conducting EPR spectroscopy in living animals. The second half of the review will be concentrated on the application of low-frequency EPR in measuring cerebral tissue pO 2 changes and oxidative stress in various physiological and pathophysiological conditions in the brain of animal disease models.

Hemorrhagic stroke is a leading cause of death. The causes of intracerebral hemorrhage (ICH)-induced brain damage are thought to include lysis of red blood cells, hemin release and iron overload. These mechanisms, however, have not proven very amenable to therapeutic intervention, and so other mechanistic targets are being sought. Here we report that accumulation of endogenously formed zinc protoporphyrin (ZnPP) also critically contributes to ICH-induced brain damage. ICH caused a significant accumulation of ZnPP in brain tissue surrounding hematoma, as evidenced by fluorescence microscopy of ZnPP, and further confirmed by fluorescence spectroscopy and supercritical fluid chromatography-mass spectrometry. ZnPP formation was dependent upon both ICH-induced hypoxia and an increase in free zinc accumulation. Notably, inhibiting ferrochelatase, which catalyzes insertion of zinc into protoporphyrin, greatly decreased ICH-induced endogenous ZnPP generation. Moreover, a significant decrease in brain damage was observed upon ferrochelatase inhibition, suggesting that endogenous ZnPP contributes to the damage in ICH. Our findings reveal a novel mechanism of ICH-induced brain damage through ferrochelatase-mediated formation of ZnPP in ICH tissue. Since ferrochelatase can be readily inhibited by small molecules, such as protein kinase inhibitors, this may provide a promising new and druggable target for ICH therapy.

In patients with substernal goiter, the generally accepted theory is that thyroid uptake measurements with iodine isotopes are underestimated because of attenuation by the chest wall. The extent of this underestimation is not well known. In this study, we calculated the attenuation of 123I emissions using a cadaver chest wall with a thyroid probe to better understand the potential severity of this underestimation. Methods: A 11.1-MBq capsule of 123I was measured using a thyroid probe directly in a standard neck phantom and behind a cadaver chest wall that included the soft tissues and bony structures (sternum). Results: The calculated attenuation of the iodine capsule was 18% for the neck phantom and 35% for the cadaver chest wall. Conclusion: Thyroid uptake in cases of substernal goiter may be underestimated by standard techniques using a neck phantom. The composition of the chest wall can vary greatly, and the substernal extent of the goiter would be difficult to calculate with high accuracy on a routine basis. Comparison between the cadaveric specimen and the phantom does give us a rough estimation of the differences in attenuation. Our findings suggest that attenuation by the chest wall can be substantial. Knowledge of the extent of the substernal component of the thyroid gland may be useful if the uptake measurement is used to calculate doses for treating hyperthyroidism in patients with substernal goiter.

The mechanism of early blood–brain barrier (BBB) disruption after stroke has been intensively studied but still not fully understood. Here, we report that microRNA-30a (miR-30a) could mediate BBB damage using both cellular and animal models of ischemic stroke. In the experiments in vitro, inhibition of miR-30a decreased BBB permeability, prevented the degradation of tight junction proteins, and reduced intracellular free zinc in endothelial cells. We found that the zinc transporter ZnT4 was a direct target of negative regulation by miR-30a, and ZnT4/zinc signaling pathway contributed significantly to miR-30a-mediated BBB damage. Consistent with these in vitro findings, treatment with miR-30a inhibitor reduced zinc accumulation, increased the expression of ZnT4, and prevented the loss of tight junction proteins in microvessels of ischemic animals. Furthermore, inhibition of miR-30a, even at 90 min post onset of middle cerebral artery occlusion, prevented BBB damage, reduced infarct volume, and ameliorated neurological deficits. Together, our findings provide novel insights into the mechanisms of cerebral ischemia-induced BBB disruption and indicate miR-30a as a regulator of BBB function that can be an effective therapeutic target for ischemic stroke.

Anti-inflammatory and proinflammatory responses in macrophages are influenced by cellular metabolism. Macrophages are the primary phagocyte in mucosal environments (i.e., intestinal tract and lungs) acting as first-line defense against microorganisms and environmental pollutants. Given the extensive contamination of our food and water sources with microplastics, we aimed to examine the metabolic response in macrophages to microplastic particles (MPs). Utilizing murine macrophages, we assessed the metabolic response of macrophages after polystyrene MP phagocytosis. The phagocytosis of MP by macrophages induced a metabolic shift toward glycolysis and a reduction in mitochondrial respiration that was associated with an increase of cell surface markers CD80 and CD86 and cytokine gene expression associated with glycolysis. The gastrointestinal consequences of this metabolic switch in the context of an immune response remain uncertain, but the global rise of plastic pollution and MP ingestion potentially poses an unappreciated health risk. Macrophage phagocytosis of microplastics alters cellular metabolism. - Macrophages cannot degrade PS MP. - MP phagocytosis increases glycolysis in murine macrophages. - MP phagocytosis reduces mitochondrial respiration in murine macrophages.

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.

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.

In this study, we describe numerical implementation of a heterogenous, nearly incompressible, transverse isotropic (NITI) finite element (FE) model with key advantages for use in MR elastography of fibrous soft tissue. MR elastography (MRE) estimates heterogenous property distributions from MR-measured harmonic motion fields based on assumed mechanical models of tissue response. Current MRE property estimation methods usually assume isotropic properties, which cause inconsistencies arising from model-data mismatch when anisotropy is present. In this study, we use a NITI model parameterized by a base shear modulus, shear anisotropy, tensile anisotropy, and an isotropic bulk modulus, which describes the mechanical behavior of tissues with aligned fiber structures well. Property and fiber direction heterogeneity are implemented at the level of FE Gauss points, which allows high-resolution diffusion tensor imaging (DTI) data to be incorporated easily into the model. The resulting code was validated against analytical solutions and a commercial FEM package, and is suitable for incorporation into nonlinear inversion MRE algorithms. Simulations of MRE in brain tissue with heterogeneous properties and anisotropic fiber tracts, which produced wavefields similar to experimental MRE, were generated from anatomical, DTI and MRE image data, allowing investigation of MRE inversion performance in a realistic setting where the ground truth and underlying mechanical behavior are known. Two established isotropic inversion algorithms—nonlinear inversion (NLI) and local direct inversion (LDI)—were applied to simulated MRE data. Both algorithms performed well in simple isotropic homogenous cases; however, heterogeneity cased substantial artifacts in LDI arising from violation of local homogeneity assumptions. NLI was able to recover accurate heterogenous displacement fields in the presence of measurement noise. Isotropic NLI inversion of simulated anisotropic data (generated using the NITI model) produced maps of isotropic mechanical properties with undesirable dependence on the wavefield. Local anisotropy also caused wavefield-dependent errors of 7% in nearby isotropic structures, compared to 10% in the anisotropic structures.

We are developing magnetic nanoparticle (NP) methods to characterize inflammation and infectionin 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 inflammationin vivobecause it has the unique ability to monitor phagocytic absorption through relaxation measurements.

Dynamic magnetization of magnetic nanoparticles provides ready access to passive sensing in nanometer scale environments. Here, we use commercially available streptavidin labeled 100 nm magnetic nanoparticles to develop a nanoscale pH sensor. The sensor works based on pH dependent binding of streptavidin to rat tail type-I collagen. The major protein-protein interactions in this case are well rationalized from zeta potential/mobility measurements, which yield a good measure of the relative pIs of the proteins. The pI is the pH at which the protein has zero overall surface charge. Nanoparticle streptavidin has a stable negative charge over the entire range of the measurements from pH 6 to 7.5 (pI similar to 2), whereas collagen has a steadily increasing positive charge as the pH drops below 7.5 (pI 7.8). Interactions between protein1 and NP-protein2 based on an initial pI difference allow sophisticated nanoscale sensors to be constructed that respond to small changes in pH via corresponding systematic changes in protein-protein interactions. More generally, any type of protein-protein interaction can in principle be measured using magnetic nanoparticles.

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 similar to 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-gamma), 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.