Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

A new histology scoring system for the assessment of the quality of human cartilage repair: ICRS II

A reliable and reproducible method is needed to assess cartilage repair.

Adsorption of Components of the Plasma Kinin-forming System on the Surface of Porphyromonas gingivalis Involves Gingipains as the Major Docking Platforms

Enhanced production of proinflammatory bradykinin-related peptides, the kinins, has been suggested to contribute to the pathogenesis of periodontitis, a common inflammatory disease of human gingival tissues. In this report, we describe a plausible mechanism of activation of the kinin-generating system, also known as the contact system or kininogen-kallikrein-kinin system, by the adsorption of its plasma-derived components such as high-molecular-mass kininogen (HK), prekallikrein (PK), and Hageman factor (FXII) to the cell surface of periodontal pathogen Porphyromonas gingivalis. The adsorption characteristics of mutant strains deficient in selected proteins of the cell envelope suggested that the surface-associated cysteine proteinases, gingipains, bearing hemagglutinin/adhesin domains (RgpA and Kgp) serve as the major platforms for HK and FXII adhesion. These interactions were confirmed by direct binding tests using microplate-immobilized gingipains and biotinylated contact factors. Other bacterial cell surface components such as fimbriae and lipopolysaccharide were also found to contribute to the binding of contact factors, particularly PK. Analysis of kinin release in plasma upon contact with P. gingivalis showed that the bacterial surface-dependent mechanism is complementary to the previously described kinin generation system dependent on HK and PK proteolytic activation by the gingipains. We also found that several P. gingivalis clinical isolates differed in the relative significance of these two mechanisms of kinin production. Taken together, these data show the importance of this specific type of bacterial surface-host homeostatic system interaction in periodontal infections.

In pediatric lymphoblastic leukemia of B-cell origin, a small population of primitive blast cells is noncycling, suggesting them to be leukemia stem cell candidates

Kinetic investigations in pediatric acute lymphoblastic leukemia (ALL) are based on all blast cells and, therefore, reflect the proliferative characteristics of the predominant immunophenotype of leukemic cells. Nothing is known about proliferation of immunologically defined rare subpopulations of leukemic cells. In this study, mononuclear cells from the bone marrow of 15 children with untreated CD19 B-cell precursor ALL were examined for proliferative features according to the immunophenotype. After exclusion of highly proliferating residual normal hematopoietic cells, ∼ 3% of blast cells were CD19 and showed a low percentage of cells in S-phase assessed by the bromodeoxyuridine labeling index (BrdU-LI): median BrdU-LI, 0.19% [interquartile range (IQR), 0.15-0.40%]. In contrast, a median BrdU-LI of 7.2% (IQR, 5.7-8.8%) was found for the major CD19 blast cell compartment. Staining smears of sorted CD19 cells for CD10 or CD34 revealed a small fraction of CD19CD10 or CD19CD34 blast cells. These cells were almost nonproliferating with a median BrdU-LI of <0.1% (IQR, 0-0.2%). This proliferative behavior is suggestive of a stem/progenitor cell function and, in addition, the low proliferative activity might render them more resistant to an antiproliferation-based chemotherapy. However, xenotransplantation experiments will be necessary to demonstrate a possible stem cell function.

Prediction of psychosis in clinical high-risk patients by the Schizotypal Personality Questionnaire. Results of the EPOS project

OBJECTIVE: Schizotypal features indicate proneness to psychosis in the general population. It is also possible that they increase transition to psychosis (TTP) among clinical high-risk patients (CHR). Our aim was to investigate whether schizotypal features predict TTP in CHR patients. METHODS: In the EPOS (European Prediction of Psychosis Study) project, 245 young help-seeking CHR patients were prospectively followed for 18 months and their TTP was identified. At baseline, subjects were assessed with the Schizotypal Personality Questionnaire (SPQ). Associations between SPQ items and its subscales with the TTP were analysed in Cox regression analysis. RESULTS: The SPQ subscales and items describing ideas of reference and lack of close interpersonal relationships were found to correlate significantly with TTP. The co-occurrence of these features doubled the risk of TTP. CONCLUSIONS: Presence of ideas of reference and lack of close interpersonal relations increase the risk of full-blown psychosis among CHR patients. This co-occurrence makes the risk of psychosis very high.