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The number and size of granulomas in Dox-treated animals was higher than untreated and Pzq-treated mice. Dox treatment inhibited the increase in MMP-1 and MMP-2 activity but upregulated myeloperoxidase and N-acetylglucosaminidase activity compared to untreated and Pzq-treated animals. Dox and Pzq exerted no effect on elastin depletion and upregulation of elastase activity. Together, our findings indicated that Dox aggravated granulomatous inflammation, accelerating lung microstructural remodeling by downregulating MMP-1 and MMP-2 activity without impair neutrophils and macrophages recruitment or elastase activity. Thus, Dox potentiates inflammatory damage associated with lung fibrosis, elastin depletion and massive alveolar collapse, profoundly subverting lung structure in S. mansoni-infected mice.Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distributions of diffusion tensors. It models each sub-voxel fascicle separately, resolving crossing white-matter pathways and allowing for a fascicle-element (fixel) based analysis of microstructural features. Alternatively, specific features of the intra-voxel diffusion tensor distribution can be selectively measured using tensor-valued diffusion-weighted acquisition schemes. However, the impact of such schemes on estimating brain microstructural features has only been studied in a handful of parametric single-fascicle models. In this work, we derive a general Laplace transform for the non-central matrix-variate Gamma distribution, which enables the extension of DIAMOND to tensor-valued encoded data. We then evaluate this "Magic DIAMOND" model in silico and in vivo on various combinations of tensor-valued encoded data. Assessing uncertainty on parameter estimation via stratified bootstrap, we investigate both voxel-based and fixel-based metrics by carrying out multi-peak tractography. We demonstrate using in silico evaluations that tensor-valued diffusion encoding significantly improves Magic DIAMOND's accuracy. Most importantly, we show in vivo that our estimated metrics can be robustly mapped along tracks across regions of fiber crossing, which opens new perspectives for tractometry and microstructure mapping along specific white-matter tracts.

Surgical tool detection, segmentation, and 3D pose estimation are crucial components in Computer-Assisted Laparoscopy (CAL). The existing frameworks have two main limitations. First, they do not integrate all three components. Integration is critical; for instance, one should not attempt computing pose if detection is negative. Second, they have highly specific requirements, such as the availability of a CAD model. We propose an integrated and generic framework whose sole requirement for the 3D pose is that the tool shaft is cylindrical. Our framework makes the most of deep learning and geometric 3D vision by combining a proposed Convolutional Neural Network (CNN) with algebraic geometry. We show two applications of our framework in CAL tool-aware rendering in Augmented Reality (AR) and tool-based 3D measurement.

We name our CNN as ART-Net (Augmented Reality Tool Network). It has a Single Input Multiple Output (SIMO) architecture with one encoder and multiple decoders to achieve detection, segmentation, aonditions of laparoscopy. The source code of our framework and our annotated dataset will be made publicly available at https//github.com/kamruleee51/ART-Net.

The proposed framework outperforms existing ones in detection and segmentation. Compared to separate networks, integrating the tasks in a single network preserves accuracy in detection and segmentation but substantially improves accuracy in geometric primitive extraction. Overall, our framework has similar or better accuracy in 3D pose estimation while largely improving robustness against the very challenging imaging conditions of laparoscopy. The source code of our framework and our annotated dataset will be made publicly available at https//github.com/kamruleee51/ART-Net.The midfoot joint complex (MFJC) is related to the mechanics and efficiency of the walking propulsive phase and low midfoot passive stiffness may require compensatory foot and ankle joint moments to avoid excessive pronation and inefficient propulsion. This study aimed to investigate the kinematics and kinetics of the MFJC and ankle during the propulsive phase of walking in subjects with larger and smaller midfoot passive stiffness. MFJC passive stiffness of 20 healthy adult participants, and the kinematics and kinetics of the MFJC (forefoot-rearfoot) and ankle (rearfoot-shank) during the stance phase of walking were measured. The participants were divided equally into two groups according to the MFJC passive stiffness. Ranges of motion (ROM) and mean joint moments were computed for the late stance. Independent t-tests (α = 0.05) revealed that subjects with lower midfoot passive stiffness showed an increased MFJC sagittal ROM (flattened longitudinal arch) (p = 0.002), increased ankle frontal ROM (more everted positions) (p = 0.002), increased MFJC frontal ROM (more inverted positions) (p = 0.019), as well as a tendency for larger ankle sagittal ROM (p = 0.056). They also showed increased MFJC (p = 0.021) and ankle (p = 0.018) moments in the sagittal plane, increased MFJC moment in the frontal plane (p = 0.047) and a tendency for a predominant ankle moment in the frontal (p = 0.058). Foot and ankle joint moments are possible strategies to reduce pronation and improve propulsion, but not sufficient to prevent the altered kinematics related to low midfoot stiffness. Therefore, midfoot passive stiffness is critical for foot and ankle kinematics and kinetics during walking propulsive phase and is a potential target of interventions.

This study aimed to investigate the energy response of a radiophotoluminescent glass dosimeter (RGD) for diagnostic kilovoltage x-ray beams by Monte Carlo (MC) calculations and measurements.

The uniformity and reproducibility of GD-352M (with Sn filter) and GD-302M (no filter) were tested with 45 RGDs in free air. Subsequently, the RGD response was obtained as a function of an Al-HVL using the parameter, quality index (QI), which is defined as the ratio of the effective energy (keV) to the maximum energy (keV) of the photons. Tocilizumab ic50 The x-ray fluence spectra with QI of 0.4, 0.5, and 0.6 were set for tube voltages of 50~137.6 kVp. The RGD response was calculated in free air using the MC method and verified by the air kerma, K

, measured using an ionization chamber.

The uniformity and reproducibility of the 45 RGDs were±2.3% and±2.7% for GD-352M and±0.7% and±1.6% for GD-302M at the one standard deviation level, respectively. The calculated RGD response was 0.965 to 1.062 at Al-HVL 2.73mm or more for GD-352M and varied from 3.