ObjectiveDimethyl fumarate (DMF), a therapy for relapsing‐remitting multiple sclerosis (RRMS), is implicated as acting on inflammatory and antioxidant responses within both systemic immune and/or central nervous system (CNS) compartments. Orally administered DMF is rapidly metabolized to monomethyl fumarate (MMF). Our aim was to analyze the impact of fumarates on antiinflammatory and antioxidant profiles of human myeloid cells found in the systemic compartment (monocytes) and in the inflamed CNS (blood‐derived macrophages and brain‐derived microglia).MethodsWe analyzed cytokine and antioxidant expression in monocytes from untreated or DMF‐treated RRMS patients and controls, and in monocyte‐derived macrophages (MDMs) and microglia isolated from adult and fetal human brain tissue.ResultsMonocytes from multiple sclerosis (MS) patients receiving DMF had reduced expression of the proinflammatory micro‐RNA miR‐155 and of antioxidant genes HMOX1 and OSGIN1 compared to untreated MS patients; similar changes were observed in patients receiving FTY720 and/or natalizumab. In vitro addition of DMF but not MMF to MDMs and microglia inhibited lipopolysaccharide‐induced production of inflammatory cytokines and increased expression of the antioxidant gene HMOX1 in the absence of significant cytotoxicity.InterpretationOur in vivo‐based observations that effects of DMF therapy on systemic myeloid cell gene expression are also observed with FTY720 and natalizumab therapy suggests that the effect may be indirect, reflecting reduced overall disease activity. Our in vitro results demonstrate significant effects of DMF but not MMF on inflammation and antioxidant responses by MDMs and microglia, questioning the mechanisms whereby DMF therapy would modulate myeloid cell properties within the CNS.
One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details in bony areas and the brain soft-tissue. For example, the results show the ventricles and some brain folds become visible in SDIR reconstructed images and the contrast of the visible lesions is effectively improved. The line-pair resolution was improved from 12 line-pair/cm in FBP to 14 line-pair/cm in SDIR. Adjusting the parameters of the ASD-POCS to achieve 14 line-pair/cm caused the noise variance to be higher than the SDIR. Using these parameters for ASD-POCS, the MTF of FBP and ASD-POCS were very close and equal to 0.7 mm which was increased to 1.2 mm by SDIR, at half maximum.
Neuromodulation approaches to treating lower urinary tract dysfunction could be substantially improved by a sensor able to detect when the bladder is full. A number of approaches to this problem have been proposed, but none has been found entirely satisfactory. Electrical plethysmography approaches attempt to relate the electrical impedance of the bladder to its volume, but have previously focused only on the amplitudes of the measured signals. We investigated whether the phase relationships between sinusoidal currents applied through a pair of stimulating electrodes and measured through a pair of recording electrodes could provide information about bladder volume. Acute experiments in a rabbit model were used to investigate how phase-to-volume or amplitude-to-volume regression models could be used to predict bladder volumes in future recordings, with and without changes to the saline conductivity. Volume prediction errors were found to be 6.63 ± 1.12 mL using the phase information and 8.32 ± 3.88 mL using the amplitude information (p = 0.44 when comparing the phase and amplitude results, n = 6), where the volume of the filled bladder was about 25 mL. When a full/empty binary decision rule was applied based on the regression model, the difference between the actual threshold that would result from this rule and the desired threshold was found to be 4.24 ± 0.65 mL using the phase information and 106.92 ± 189.82 mL using the amplitude information (p = 0.03, n = 6). Our results suggest that phase information can form the basis for more effective and robust electrical plethysmography approaches to bladder volume measurement.
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