3D morphometric analysis of calcified cartilage properties using micro-computed tomography

Objective: Our aim is to establish methods for quantifying morphometric properties of calcified cartilage (CC) from micro-computed tomography (mu CT). Furthermore, we evaluated the feasibility of these methods in investigating relationships between osteoarthritis (OA), tidemark surface morphology and open subchondral channels (OSCCs). Method: Samples (n = 15) used in this study were harvested from human lateral tibial plateau (n = 8). Conventional roughness and parameters assessing local 3-dimensional (3D) surface variations were used to quantify the surface morphology of the CC. Subchondral channel properties (percentage, density, size) were also calculated. As a reference, histological sections were evaluated using Histopathological osteoarthritis grading (OARSI) and thickness of CC and subchondral bone (SCB) was quantified. Results: OARSI grade correlated with a decrease in local 3D variations of the tidemark surface (amount of different surface patterns (r(s) = -0.600, P = 0.018), entropy of patterns (EP) (r(s) = -0.648, P = 0.018), homogeneity index (HI) (r(s) = 0.555, P = 0.032)) and tidemark roughness (TMR) (r(s) = -0.579, P = 0.024). Amount of different patterns (ADP) and EP associated with channel area fraction (CAF) (r(p) = 0.876, P <0.0001; r(p) = 0.665, P = 0.007, respectively) and channel density (CD) (r(p) = 0.680, P = 0.011; r(p) = 0.582, P = 0.023, respectively). TMR was associated with CAF (r(p) = 0.926, P <0.0001) and average channel size (r(p) = 0.574, P = 0.025). CC topography differed statistically significantly in early OA vs healthy samples. Conclusion: We introduced a mu-CT image method to quantify 3D CC topography and perforations through CC. CC topography was associated with OARSI grade and OSCC properties; this suggests that the established methods can detect topographical changes in tidemark and CC perforations associated with OA. (c) 2018 The Authors. Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

3D morphometric analysis of calcified cartilage properties using micro-computed tomography

OBJECTIVE: Our aim is to establish methods for quantifying morphometric properties of calcified cartilage (CC) from micro-computed tomography (muCT). Furthermore, we evaluated the feasibility of these methods in investigating relationships between osteoarthritis (OA), tidemark surface morphology and open subchondral channels (OSCCs). METHOD: Samples (n = 15) used in this study were harvested from human lateral tibial plateau (n = 8). Conventional roughness and parameters assessing local 3-dimensional (3D) surface variations were used to quantify the surface morphology of the CC. Subchondral channel properties (percentage, density, size) were also calculated. As a reference, histological sections were evaluated using Histopathological osteoarthritis grading (OARSI) and thickness of CC and subchondral bone (SCB) was quantified. RESULTS: OARSI grade correlated with a decrease in local 3D variations of the tidemark surface (amount of different surface patterns (rs = -0.600, P = 0.018), entropy of patterns (EP) (rs = -0.648, P = 0.018), homogeneity index (HI) (rs = 0.555, P = 0.032)) and tidemark roughness (TMR) (rs = -0.579, P = 0.024). Amount of different patterns (ADP) and EP associated with channel area fraction (CAF) (rp = 0.876, P < 0.0001; rp = 0.665, P = 0.007, respectively) and channel density (CD) (rp = 0.680, P = 0.011; rp = 0.582, P = 0.023, respectively). TMR was associated with CAF (rp = 0.926, P < 0.0001) and average channel size (rp = 0.574, P = 0.025). CC topography differed statistically significantly in early OA vs healthy samples. CONCLUSION: We introduced a mu-CT image method to quantify 3D CC topography and perforations through CC. CC topography was associated with OARSI grade and OSCC properties; this suggests that the established methods can detect topographical changes in tidemark and CC perforations associated with OA

Total Elbow Arthroplasty

Total elbow arthroplasty has continued to evolve over time. Elbow implants may be linked or unlinked. Unlinked implants are attractive for patients with relatively well preserved bone stock and ligaments, but many favor linked implants, since they prevent instability and allow replacement for a wider spectrum of indications. Inflammatory arthropathies such as rheumatoid arthritis represent the classic indication for elbow arthroplasty. Indications have been expanded to include posttraumatic osteoarthritis, acute distal humerus fractures, distal humerus nonunions and reconstruction after tumor resection. Elbow arthroplasty is very successful in terms of pain relief, motion and function. However, its complication rate remains higher than arthroplasty of other joints. The overall success rate is best for patients with inflammatory arthritis and elderly patients with acute distal humerus fractures, worse for patients with posttraumatic osteoarthritis. The most common complications of elbow arthroplasty include infection, loosening, wear, triceps weakness and ulnar neuropathy. When revision surgery becomes necessary, bone augmentation techniques provide a reasonable outcome

Immunophenotypic predictive profiling of BRCA1-associated breast cancer

The immunophenotypic predictive profile of BRCA1-associated cancers including major predictive markers, i.e., PARP-1, EGFR, c-kit, HER-2, and steroid hormones (ER/PR) that may have therapeutic relevance has not yet been reported in a comprehensive study. Using immunohistochemistry, we examined the expression of these proteins in a large cohort of BRCA1-associated breast cancers. PARP-1 immunoreactivity was found in 81.9%, EGFR in 43.6%, ER/PR in 17.9%, c-kit in 14.7%, and overexpression of HER-2 in 3.6% of cancers. For all markers studied, 8.2% of tumors were negative. Expression of only one predictive marker was found in 29.7% of cancers, and most frequently, it was PARP-1 (20.8%). In 62.1% of tumors, more than one predictive marker was expressed: PARP-1 and EGFR in 30.4%, PARP-1, and hormone receptors in 13.3% and PARP-1 with c-kit in 7.5% of all tumors. Coexpression of two or more other predictive markers was rare. There were significant differences in the median age at diagnosis of BRCA1-associated cancer between patients with ER+ vs. ER− and grades 1–2 vs. grade 3 tumors. These results demonstrate that BRCA1-associated cancers differ with respect to expression of proteins that are regarded as targets for specific therapies and that 92% of patients with BRCA1-associated cancers may benefit from one or several options for specific therapy (in addition to DNA damaging agents, e.g., cisplatin). About 8% of cancers which do not express therapeutic target proteins may not respond to such therapies. Knowledge of the immunophenotypic predictive profile may help with the recruitment of patients for trials of targeted therapies

Frequent high-level expression of the immunotherapeutic target Ep-CAM in colon, stomach, prostate and lung cancers

Epithelial cell adhesion molecule (Ep-CAM; CD326) is used as a target by many immunotherapeutic approaches, but little data are available about Ep-CAM expression in major human malignancies with respect to level, frequency, tumour stage, grade, histologic tumour type and impact on survival. We analysed by immunohistochemical staining tissue microarrays with 4046 primary human carcinoma samples from colon, stomach, prostate and lung cancers for both frequency and intensity of Ep-CAM expression under highly standardised conditions. A total of 3360 samples were analysable. High-level Ep-CAM expression was observed in 97.7% (n=1186) of colon, 90.7% of gastric (n=473), and 87.2% of prostate cancers (n=414), and in 63.9% of lung cancers (n=1287). No detectable Ep-CAM staining was found with only 0.4% of colon, 2.5% of gastric, 1.9% of prostate cancers, and 13.5% of lung cancers. The only significant correlation of Ep-CAM expression with tumour grading was observed in colon cancer where high-level Ep-CAM expression on grade 3 tumours was down to 92.1% (P<0.0001). Adenosquamous and squamous carcinomas of the lung had a lower percentage of high-level Ep-CAM expression compared to adenocarcinomas with 35.4 and 53.6%, respectively, and with 45.5 and 17.3% of tumours being Ep-CAM negative. With the exception of moderately differentiated colon carcinoma, where patients not expressing Ep-CAM on their tumours showed an inferior survival (P=0.0014), correlation of Ep-CAM expression with survival did not reach statistical significance for any of the other cancer indications and subgroups. In conclusion, the data strongly support the notion that Ep-CAM is a prime target for immunotherapies in major human malignancies. This is because the most common human cancers show (i) a low frequency of Ep-CAM-negative tumours, (ii) a high frequency of Ep-CAM expression on cells of a given tumour, and (iii) for most cancers, an insignificant influence of tumour staging, grading and histology on Ep-CAM expression

The impact of transposable element activity on therapeutically relevant human stem cells

Human stem cells harbor significant potential for basic and clinical translational research as well as regenerative medicine. Currently ~ 3000 adult and ~ 30 pluripotent stem cell-based, interventional clinical trials are ongoing worldwide, and numbers are increasing continuously. Although stem cells are promising cell sources to treat a wide range of human diseases, there are also concerns regarding potential risks associated with their clinical use, including genomic instability and tumorigenesis concerns. Thus, a deeper understanding of the factors and molecular mechanisms contributing to stem cell genome stability are a prerequisite to harnessing their therapeutic potential for degenerative diseases. Chemical and physical factors are known to influence the stability of stem cell genomes, together with random mutations and Copy Number Variants (CNVs) that accumulated in cultured human stem cells. Here we review the activity of endogenous transposable elements (TEs) in human multipotent and pluripotent stem cells, and the consequences of their mobility for genomic integrity and host gene expression. We describe transcriptional and post-transcriptional mechanisms antagonizing the spread of TEs in the human genome, and highlight those that are more prevalent in multipotent and pluripotent stem cells. Notably, TEs do not only represent a source of mutations/CNVs in genomes, but are also often harnessed as tools to engineer the stem cell genome; thus, we also describe and discuss the most widely applied transposon-based tools and highlight the most relevant areas of their biomedical applications in stem cells. Taken together, this review will contribute to the assessment of the risk that endogenous TE activity and the application of genetically engineered TEs constitute for the biosafety of stem cells to be used for substitutive and regenerative cell therapiesS.R.H. and P.T.R. are funded by the Government of Spain (MINECO, RYC-2016- 21395 and SAF2015–71589-P [S.R.H.]; PEJ-2014-A-31985 and SAF2015–71589- P [P.T.R.]). GGS is supported by a grant from the Ministry of Health of the Federal Republic of Germany (FKZ2518FSB403)

Heterochromatin and the molecular mechanisms of 'parent-of-origin' effects in animals.

Twenty five years ago it was proposed that conserved components of constitutive heterochromatin assemble heterochromatinlike complexes in euchromatin and this could provide a general mechanism for regulating heritable (cell-to-cell) changes in gene expressibility. As a special case, differences in the assembly of heterochromatin-like complexes on homologous chromosomes might also regulate the parent-of-origin-dependent gene expression observed in placental mammals. Here, the progress made in the intervening period with emphasis on the role of heterochromatin and heterochromatin-like complexes in parent-of-origin effects in animals is reviewed

DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.

Recent technological advances have enabled DNA methylation to be assayed at single-cell resolution. However, current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. We report DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells. We evaluate DeepCpG on single-cell methylation data from five cell types generated using alternative sequencing protocols. DeepCpG yields substantially more accurate predictions than previous methods. Additionally, we show that the model parameters can be interpreted, thereby providing insights into how sequence composition affects methylation variability