SynONIM: A Comprehensive Database of Synthetic Oligonucleotide Modifications and Impurities to Aid in Their Characterization by Mass Spectrometry.

Given the resurgence of oligonucleotides in the biotherapeutic space, there is a profound focus on their characterization by mass spectrometry. These therapeutic moieties commonly employ synthetic modifications to aid in increasing efficacy and stability; however, these modifications can also increase the complexity of mass spectrometry data analysis. Additionally, various stress conditions can affect both the observed level and type of impurities stemming from the variety of utilized modifications. Within the oligonucleotide analytical development community, a clear desire exists for a unified database of synthetic oligonucleotide modifications and impurities where information regarding structure, mass, and shorthand nomenclature can be contained. To address this, the authors have prepared an online database and webtool of synthetic oligonucleotide impurities and modifications, SynONIM, to centrally locate information key to the mass spectrometry community. SynONIM can be queried by elemental composition lost or gained, mass shift, shorthand notation, nucleotide location, and species origin.

Lipid Based Formulations in Hard Gelatin and HPMC Capsules: a Physical Compatibility Study.

PURPOSE: To investigate the compatibility between hard gelatin and HPMC capsules with a range of different isotropic lipid based formulations containing multiple excipients. METHODS: The miscibility was investigated for 350 systems applying five different oils (Labrafac ™ lipophile WL1349, Maisine® CC, Captex 300 EP/NF, olive oil, and Capmul MCM EP/NF), five different surfactans (Labrasol ® ALF, Labrafil M 2125 CS, Kolliphor ® ELP, Kolliphor ® HS 15, Tween 80) and three different cosolvents (propylene glycol, polyethylene glycol 400, and Transcutol ® HP). For the isotropic systems capsule compatibility was investigated in both gelatin and HPMC capsules at 25°C at 40% and 60% relative humidity by examining physical damages to the capsules and weight changes after storage. RESULTS: The miscibility of lipid based vehicles was best when the formulation contained monoglycerides and surfactants with a hydrophilic-lipophilic balance value <12. Gelatin capsules in general resulted in a better compatibility when compared to HPMC capsules for the evaluated formulations. Addition of water to the formulation improved the capsule compatibility for both capsule types. The expected capsule mass change could partly be predicted in binary systems using the provided data of the single excipients weighted for its formulation proportion. CONCLUSIONS: The capsule compatibility was driven by the components incorporated into the formulations, where more was compatible with gelatin than HPMC capsules. Prediction of the mass change from individual excipient contributions can provide a good first estimate if a vehicle is compatible with a capsule, however, this needs to be proved experimentally.

The successive projection algorithm as an initialization method for brain tumor segmentation using non-negative matrix factorization.

Non-negative matrix factorization (NMF) has become a widely used tool for additive parts-based analysis in a wide range of applications. As NMF is a non-convex problem, the quality of the solution will depend on the initialization of the factor matrices. In this study, the successive projection algorithm (SPA) is proposed as an initialization method for NMF. SPA builds on convex geometry and allocates endmembers based on successive orthogonal subspace projections of the input data. SPA is a fast and reproducible method, and it aligns well with the assumptions made in near-separable NMF analyses. SPA was applied to multi-parametric magnetic resonance imaging (MRI) datasets for brain tumor segmentation using different NMF algorithms. Comparison with common initialization methods shows that SPA achieves similar segmentation quality and it is competitive in terms of convergence rate. Whereas SPA was previously applied as a direct endmember extraction tool, we have shown improved segmentation results when using SPA as an initialization method, as it allows further enhancement of the sources during the NMF iterative procedure.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

BACKGROUND: Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. METHODS: We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. RESULTS: Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. CONCLUSIONS: Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

Hierarchical non-negative matrix factorization to characterize brain tumor heterogeneity using multi-parametric MRI.

Tissue characterization in brain tumors and, in particular, in high-grade gliomas is challenging as a result of the co-existence of several intra-tumoral tissue types within the same region and the high spatial heterogeneity. This study presents a method for the detection of the relevant tumor substructures (i.e. viable tumor, necrosis and edema), which could be of added value for the diagnosis, treatment planning and follow-up of individual patients. Twenty-four patients with glioma [10 low-grade gliomas (LGGs), 14 high-grade gliomas (HGGs)] underwent a multi-parametric MRI (MP-MRI) scheme, including conventional MRI (cMRI), perfusion-weighted imaging (PWI), diffusion kurtosis imaging (DKI) and short-TE (1)H MRSI. MP-MRI parameters were derived: T2, T1 + contrast, fluid-attenuated inversion recovery (FLAIR), relative cerebral blood volume (rCBV), mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and the principal metabolites lipids (Lip), lactate (Lac), N-acetyl-aspartate (NAA), total choline (Cho), etc. Hierarchical non-negative matrix factorization (hNMF) was applied to the MP-MRI parameters, providing tissue characterization on a patient-by-patient and voxel-by-voxel basis. Tissue-specific patterns were obtained and the spatial distribution of each tissue type was visualized by means of abundance maps. Dice scores were calculated by comparing tissue segmentation derived from hNMF with the manual segmentation by a radiologist. Correlation coefficients were calculated between each pathologic tissue source and the average feature vector within the corresponding tissue region. For the patients with HGG, mean Dice scores of 78%, 85% and 83% were obtained for viable tumor, the tumor core and the complete tumor region. The mean correlation coefficients were 0.91 for tumor, 0.97 for necrosis and 0.96 for edema. For the patients with LGG, a mean Dice score of 85% and mean correlation coefficient of 0.95 were found for the tumor region. hNMF was also applied to reduced MRI datasets, showing the added value of individual MRI modalities.

Relation between subject-specific hip joint loading, stress distribution in the proximal femur and bone mineral density changes after total hip replacement.

In the prediction of bone remodelling processes after total hip replacement (THR), modelling of the subject-specific geometry is now state-of-the-art. In this study, we demonstrate that inclusion of subject-specific loading conditions drastically influences the calculated stress distribution, and hence influences the correlation between calculated stress distributions and changes in bone mineral density (BMD) after THR. For two patients who received cementless THR, personalized finite element (FE) models of the proximal femur were generated representing the pre- and post-operative geometry. FE analyses were performed by imposing subject-specific three-dimensional hip joint contact forces as well as muscle forces calculated based on gait analysis data. Average values of the von Mises stress were calculated for relevant zones of the proximal femur. Subsequently, the load cases were interchanged and the effect on the stress distribution was evaluated. Finally, the subject-specific stress distribution was correlated to the changes in BMD at 3 and 6 months after THR. We found subject-specific differences in the stress distribution induced by specific loading conditions, as interchanging of the loading also interchanged the patterns of the stress distribution. The correlation between the calculated stress distribution and the changes in BMD were affected by the two-dimensional nature of the BMD measurement. Our results confirm the hypothesis that inclusion of subject-specific hip contact forces and muscle forces drastically influences the stress distribution in the proximal femur. In addition to patient-specific geometry, inclusion of patient-specific loading is, therefore, essential to obtain accurate input for the analysis of stress distribution after THR.

Assessment of the primary rotational stability of uncemented hip stems using an analytical model: comparison with finite element analyses.

BACKGROUND: Sufficient primary stability is a prerequisite for the clinical success of cementless implants. Therefore, it is important to have an estimation of the primary stability that can be achieved with new stem designs in a pre-clinical trial. Fast assessment of the primary stability is also useful in the preoperative planning of total hip replacements, and to an even larger extent in intraoperatively custom-made prosthesis systems, which result in a wide variety of stem geometries. METHODS: An analytical model is proposed to numerically predict the relative primary stability of cementless hip stems. This analytical approach is based upon the principle of virtual work and a straightforward mechanical model. For five custom-made implant designs, the resistance against axial rotation was assessed through the analytical model as well as through finite element modelling (FEM). RESULTS: The analytical approach can be considered as a first attempt to theoretically evaluate the primary stability of hip stems without using FEM, which makes it fast and inexpensive compared to other methods. A reasonable agreement was found in the stability ranking of the stems obtained with both methods. However, due to the simplifying assumptions underlying the analytical model it predicts very rigid stability behaviour: estimated stem rotation was two to three orders of magnitude smaller, compared with the FEM results. CONCLUSION: Based on the results of this study, the analytical model might be useful as a comparative tool for the assessment of the primary stability of cementless hip stems.