Bone quantity (bone mass) is the clinical indicator for risk of fracture; however, this metric explains less than half of bone fragility fractures. In diseases such as type 2 diabetes mellitus (T2DM), bone mass can be normal, if not slightly elevated, while risk of fracture is higher compared to the risk in a healthy population. This elevated risk of fracture points to the role of bone quality in addition to bone quantity when determining fracture risk. Aspects of bone quality, such as structural changes, mineral content, and fracture paths, can be examined at the microscale using three-dimensional (3D) imaging techniques such as synchrotron radiation micro-computed tomography (SRμCT). In this dissertation, the effects of bone disease on bone quality has been investigated through the lens of in situ SRμCT mechanical testing. Bone biology and imaging were reviewed to highlight changes in bone microstructure that can be measured using SRμCT. Additionally, microstructural features were assessed in several bone fragility diseases, including T2DM, revealing that lacunae and canal density decreased. Unfortunately, standard SRμCT imaging requires high radiation doses that deteriorate the mechanical properties of bone. One solution to mitigate this is to limit radiation exposure; however, this approach sacrifices image quality. To address the issue of low image quality, deep convolutional neural networks (DCNNs) were trained to enhance SRμCT imaging. DCNNs denoised low-quality images, mitigating mechanical damage due to radiation exposure while providing high-resolution SRμCT images. DCNNs combined with in situ SRμCT mechanical testing revealed the role of collagen damage in microscale toughening mechanisms. In situ SRμCT mechanical testing was also developed for self-supervised deep learning, reducing the reliance on high-quality data for denoising SRμCT scans. The self-supervised method Noise2Inverse was used on low-dose SRμCT images where segmentation using traditional thresholding techniques was not possible. By investigating the morphology of microstructural features after applying the networks for each dose, distortions in feature geometry were measured and the feasibility of this technique was assessed for low-dose tomography. Together, the work from this dissertation shows the importance of canals in bone’s microstructure for fracture toughness in diseased bone through innovative in situ SRμCT toughness testing enabled by deep learning.

In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical tests are used to investigate the mechanical properties of bone in relation to its microstructure. Low-dose computed tomography (CT) is used to preserve bone's mechanical properties from radiation damage, though it increases noise. To reduce this noise, the self-supervised deep learning method Noise2Inverse was used on low-dose SRµCT images where segmentation using traditional thresholding techniques was not possible. Simulated-dose datasets were created by sampling projection data at full, one-half, one-third, one-fourth and one-sixth frequencies of an in situ SRµCT mechanical test. After convolutional neural networks were trained, Noise2Inverse performance on all dose simulations was assessed visually and by analyzing bone microstructural features. Visually, high image quality was recovered for each simulated dose. Lacunae volume, lacunae aspect ratio and mineralization distributions shifted slightly in full, one-half and one-third dose network results, but were distorted in one-fourth and one-sixth dose network results. Following this, new models were trained using a larger dataset to determine differences between full dose and one-third dose simulations. Significant changes were found for all parameters of bone microstructure, indicating that a separate validation scan may be necessary to apply this technique for microstructure quantification. Noise present during data acquisition from the testing setup was determined to be the primary source of concern for Noise2Inverse viability. While these limitations exist, incorporating dose calculations and optimal imaging parameters enables self-supervised deep learning methods such as Noise2Inverse to be integrated into existing experiments to decrease radiation dose.

All levels of the unique hierarchical structure of bone, consisting of collagen and hydroxyapatite crystals at the nanoscale to osteon/lamellae structures at the microscale, contribute to its characteristic toughness and material properties. Elements of bone's density and size contribute to bone quantity (or bone mass), whereas elements of bone's material composition, material properties, internal structure, and organization describe bone quality. Bone quantity and quality can be degraded by factors such as aging, disease, treatments, and irradiation, compromising its ability to resist fracture and sustain loading. Accessing the morphology and architecture of bone at the microscale to quantify microstructural features and assess the degree of mineralization and path of crack propagation in bone provides crucial information on how these factors are influencing bone quantity and quality. Synchrotron radiation micro-computed tomography (SRμCT) was first used to assess bone structure at the end of the 1990's. One of the main advantages of the technique is that it enables accurate three-dimensional (3D), non-destructive quantification of structure while traditional histomorphometry on histological sections is inherantly destructive to the sample and two-dimensional (2D). Additionally, SRμCT uses monochromatic, high-flux X-ray beams to provide high-resolution and high-contrast imaging of bone samples. This allows the quantification of small microstructural features (e.g. osteocyte lacunae, canals, trabeculae, microcracks) and direct gray value compositional mapping (e.g. mineral quantification, cement lines) with greater speed and fidelity than lab-based micro-computed tomography. In this article, we review how SRμCT has been applied to bone research to elucidate the mechanisms by which bone aging, disease, and other factors affect bone fragility and resistance to fracture.

Abstract Introduction Platelet-rich plasma (PRP) is a fraction of plasma in which several growth factors are concentrated at high levels. The active soluble releasate isolated following platelet activation of PRP (PRP-releasate) has been demonstrated to stimulate the metabolism of IVD cells in vitro. The in vivo effect of PRP-releasate on degenerated IVD remains unknown. The purpose of this study was to determine the reparative effects of autologous PRP-releasate on degenerated intervertebral discs (IVDs). Methods To induce disc degeneration, New Zealand white rabbits (n = 12) received anular puncture in two noncontiguous discs. Autologous PRP and PPP (platelet-poor plasma) were isolated from fresh blood using two centrifugation techniques. Four weeks after the initial puncture, releasate isolated from clotted PPP or PRP (PPP- or PRP-releasate), or phosphate-buffered saline (PBS; control) was injected into the punctured discs. Disc height, magnetic resonance imaging (MRI) T2-mapping and histology were assessed. Results Anular puncture produced a consistent disc narrowing within four weeks. PRP-releasate induced a statistically significant restoration of disc height (PRP vs. PPP and PBS, P<0.05). In T2-quantification, the mean T2-values of the nucleus pulposus (NP) and anulus fibrosus (AF) of the discs were not significantly different among the three treatment groups. Histologically, the number of chondrocyte-like cells was significantly higher in the discs injected with PRP-releasate compared to that with PBS. Conclusions The administration of active PRP-releasate induced a reparative effect on rabbit degenerated IVDs. The results of this study suggest that the use of autologous PRP-releasate is safe and can lead to a clinical application for IVD degeneration.

Procedures for cryopreserving embryos vary considerably, each having its specific advantages and disadvantages in terms of technical feasibility, embryo survival yield, temperature permissibility and species- or strain-dependent applicability. Here we report a high osmolality vitrification (HOV) method that is advantageous in these respects. Cryopreservation by vitrification is generally very simple, but, unlike slow freezing, embryos should be kept at a supercooling temperature (below -130°C) to avoid cryodamage. We overcame this problem by using an HOV solution containing 42.5% (v/v) ethylene glycol, 17.3% (w/v) Ficoll and 1.0 M sucrose. This solution is more viscous than other cryopreservation solutions, but easy handling of embryos was assured by employing a less viscous equilibration solution before vitrification. Most (>80%) embryos cryopreserved in this solution survived at -80°C for at least 30 days. Normal mice were recovered even after intercontinental transportation in a conventional dry-ice package for 2-3 days, indicating that special containers such as dry shippers with liquid nitrogen vapor are unnecessary. The HOV solution could also be employed for long-term storage in liquid nitrogen, as with other conventional cryoprotectants. Finally, we confirmed that this new vitrification method could be applied successfully to embryos of all six strains of mice we have tested so far. Thus, our HOV method provides an efficient and reliable strategy for the routine cryopreservation of mouse embryos in animal facilities and biomedical laboratories, and for easy and cheap transportation.

Rationale: The lung allocation score (LAS) was revised in 2015 to improve waiting list mortality and rate of transplant for patients with pulmonary arterial hypertension (PAH). Objectives: We sought to determine if the 2015 revision achieved its intended goals. Methods: Using the Standard Transplant Analysis and Research file, we assessed the impact of the 2015 LAS revision by comparing the pre- and postrevision eras. Registrants were divided into the LAS diagnostic categories: group A-chronic obstructive pulmonary disease; group B-pulmonary arterial hypertension; group C-cystic fibrosis; and group D-interstitial lung disease. Competing risk regressions were used to assess the two mutually exclusive competing risks of waiting list death and transplant. Cumulative incidence plots were created to visually inspect risks. Measurements and Main Results: The LAS at organ matching increased by 14.2 points for registrants with PAH after the 2015 LAS revision, the greatest increase among diagnostic categories (other LAS categories: Δ, -0.9 to +2.8 points). Before the revision, registrants with PAH had the highest risk of death and lowest likelihood of transplant. After the 2015 revision, registrants with PAH still had the highest risk of death, now similar to those with interstitial lung disease, and the lowest rate of transplant, now similar to those with chronic obstructive pulmonary disease. Conclusions: Although the 2015 LAS revision improved access to transplant and reduced the risk of waitlist death for patients with PAH, it did not go far enough. Significant differences in waitlist mortality and likelihood of transplant persist.

Mucosal dendritic cells (DCs) in the intestine acquire the unique capacity to produce retinoic acid (RA), a vitamin A metabolite that induces gut tropism and regulates the functional differentiation of the T cells they prime. Here, we identified a stromal cell (SC) population in the intestinal lamina propria (LP), which is capable of inducing RA production in DCs in a RA- and granulocyte-macrophage colony-stimulating factor (GM-CSF)-dependent fashion. Unlike DCs, LP SCs constitutively expressed the enzymatic machinery to produce RA even in the absence of dietary vitamin A, but were not able to do so in germ-free mice implying regulation by microbiota. Interestingly, DCs promoted GM-CSF production by the SCs indicating a two-way cross-talk between both cell types. Furthermore, RA-producing LP SCs and intestinal DCs localized closely in vivo suggesting that the interactions between both cell types might have an important role in the functional education of migratory DCs and therefore in the regulation of immune responses toward oral and commensal antigens.

Plant mitochondria have a fully operational tricarboxylic acid (TCA) cycle that plays a central role in generating ATP and providing carbon skeletons for a range of biosynthetic processes in both heterotrophic and photosynthetic tissues. The cycle enzyme-encoding genes have been well characterized in terms of transcriptional and effector-mediated regulation and have also been subjected to reverse genetic analysis. However, despite this wealth of attention, a central question remains unanswered: "What regulates flux through this pathway in vivo?" Previous proteomic experiments with Arabidopsis discussed below have revealed that a number of mitochondrial enzymes, including members of the TCA cycle and affiliated pathways, harbor thioredoxin (TRX)-binding sites and are potentially redox-regulated. We have followed up on this possibility and found TRX to be a redox-sensitive mediator of TCA cycle flux. In this investigation, we first characterized, at the enzyme and metabolite levels, mutants of the mitochondrial TRX pathway in Arabidopsis: the NADP-TRX reductase a and b double mutant (ntra ntrb) and the mitochondrially located thioredoxin o1 (trxo1) mutant. These studies were followed by a comparative evaluation of the redistribution of isotopes when (13)C-glucose, (13)C-malate, or (13)C-pyruvate was provided as a substrate to leaves of mutant or WT plants. In a complementary approach, we evaluated the in vitro activities of a range of TCA cycle and associated enzymes under varying redox states. The combined dataset suggests that TRX may deactivate both mitochondrial succinate dehydrogenase and fumarase and activate the cytosolic ATP-citrate lyase in vivo, acting as a direct regulator of carbon flow through the TCA cycle and providing a mechanism for the coordination of cellular function.