Closed midshaft clavicle fractures : an evidence-based triage management algorithm.

AIMS: The management of mid-shaft clavicle fractures (MSCFs) has evolved over the last three decades. Controversy exists over which specific fracture patterns to treat and when. This review aims to synthesize the literature in order to formulate an appropriate management algorithm for these injuries in both adolescents and adults. METHODS: This is a systematic review of clinical studies comparing the outcomes of operative and nonoperative treatments for MSCFs in the past 15 years. The literature was searched using, PubMed, Google scholar, OVID Medline, and Embase. All databases were searched with identical search terms: mid-shaft clavicle fractures (± fixation) (± nonoperative). RESULTS: Using the search criteria identified, 247 studies were deemed eligible. Following initial screening, 220 studies were excluded on the basis that they were duplicates and/or irrelevant to the research question being posed. A total of 27 full-text articles remained and were included in the final review. The majority of the meta-analyses draw the same conclusions, which are that operatively treated fractures have lower nonunion and malunion rates but that, in those fractures which unite (either operative or nonoperative), the functional outcomes are the same at six months. CONCLUSION: With regard to the adolescent population, the existing body of evidence is insufficient to support the use of routine operative management. Regarding adult fractures, the key to identifying patients who benefit from operative management lies in the identification of risk factors for nonunion. We present an algorithm that can be used to guide both the patient and the surgeon in a joint decision-making process, in order to optimize patient satisfaction and outcomes.Cite this article: Bone Jt Open 2022;3(11):850-858.

Phenotypic characterization of chondrosarcoma-derived cell lines.

Gene expression profiling of three chondrosarcoma derived cell lines (AD, SM, 105KC) showed an increased proliferative activity and a reduced expression of chondrocytic-typical matrix products compared to primary chondrocytes. The incapability to maintain an adequate matrix synthesis as well as a notable proliferative activity at the same time is comparable to neoplastic chondrosarcoma cells in vivo which cease largely cartilage matrix formation as soon as their proliferative activity increases. Thus, the investigated cell lines are of limited value as substitute of primary chondrocytes but might have a much higher potential to investigate the behavior of neoplastic chondrocytes, i.e. chondrosarcoma biology.

[cDNA-microarrays in cartilage research - functional genomics of osteoarthritis]. / cDNA-Microarrays in der Knorpelforschung - Funktionale Genomik der Osteoarthrose.

Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. The characterization of the molecular changes of the cartilage cells, the chondrocytes, enables a better understanding of the pathomechanisms of the disease. In particular, the identification and characterization of new target molecules for therapeutic intervention is of interest. Also, potential molecular markers for diagnosis and monitoring of osteoarthritis contribute to a more appropriate patient management. The DNA-microarray technology complements (but does not replace) biochemical and biological research in new disease-relevant genes. Large-scale functional genomics will identify molecular networks such as yet identified players in the anabolic-catabolic balance of articular cartilage as well as disease-relevant intracellular signaling cascades so far rather unknown in articular chondrocytes. However, at the moment it is also important to recognize the limitations of the microarray technology in order to avoid over-interpretation of the results. This might lead to misleading results and prevent to a significant extent a proper use of the potential of this technology in the field of osteoarthritis.

Molecular phenotyping of human chondrocyte cell lines T/C-28a2, T/C-28a4, and C-28/I2.

OBJECTIVE: Because the immortalized chondrocyte cell lines C-28/I2, T/C-28a2, and T/C-28a4 have become a common tool in cartilage research, permitting investigations in a largely unlimited and standardized manner, we investigated the molecular phenotype of these cell lines by gene expression profiling. METHODS: Complementary DNA-array analysis as well as online quantitative polymerase chain reaction were used to identify the gene expression profiles of the 3 cell lines cultured in monolayer and alginate beads, as compared with the expression profiles of cultured human adult primary chondrocytes. RESULTS: A similar, but not identical, gene expression profile was established for all 3 cell lines. SOX9 was expressed at a significant level in all 3 cell lines. Extracellular matrix proteins and matrix-degrading proteases were rarely expressed. In contrast, genes involved in the cell cycle were strongly up-regulated, as compared with the expression levels in physiologic chondrocytes. CONCLUSION: The expression of SOX9, the master gene of chondrocytic cell differentiation, reflects the basically chondrocytic phenotype of these cells. However, the major issue appears to be that these cell lines mainly proliferate and show less expression of genes involved in matrix synthesis and turnover. In this respect, C-28/I2 cells display the highest levels of matrix-anabolic and matrix-catabolic genes and thus are presumably preferable for use in investigating chondrocyte anabolic and catabolic activity and its regulation. None of the 3 cell lines appears to be a direct substitute for primary chondrocytes. A successful approach will have to validate the findings obtained with chondrocyte cell lines by using primary chondrocytes or cartilage-tissue cultures. This would permit the establishment of reproducible in vitro models and subsequently allow investigators to relate the findings to the physiologic situation.

YKL-39 (chitinase 3-like protein 2), but not YKL-40 (chitinase 3-like protein 1), is up regulated in osteoarthritic chondrocytes.

OBJECTIVE: To investigate quantitatively the mRNA expression levels of YKL-40, an established marker of rheumatoid and osteoarthritic cartilage degeneration in synovial fluid and serum, and a closely related molecule YKL-39, in articular chondrocytes. METHODS: cDNA array and online quantitative polymerase chain reaction (PCR) were used to measure mRNA expression levels of YKL-39 and YKL-40 in chondrocytes in normal, early degenerative, and late stage osteoarthritic cartilage samples. RESULTS: Expression analysis showed high levels of both proteins in normal articular chondrocytes, with lower levels of YKL-39 than YKL-40. Whereas YKL-40 was significantly down regulated in late stage osteoarthritic chondrocytes, YKL-39 was significantly up regulated. In vitro both YKLs were down regulated by interleukin 1beta. CONCLUSIONS: The up regulation of YKL-39 in osteoarthritic cartilage suggests that YKL-39 may be a more accurate marker of chondrocyte activation than YKL-40, although it has yet to be established as a suitable marker in synovial fluid and serum. The decreased expression of YKL-40 by osteoarthritic chondrocytes is surprising as increased levels have been reported in rheumatoid and osteoarthritic synovial fluid, where it may derive from activated synovial cells or osteophytic tissue or by increased matrix destruction in the osteoarthritic joint. YKL-39 and YKL-40 are potentially interesting marker molecules for arthritic joint disease because they are abundantly expressed by both normal and osteoarthritic chondrocytes.

Centralization: a new method for the normalization of gene expression data.

Microarrays measure values that are approximately proportional to the numbers of copies of different mRNA molecules in samples. Due to technical difficulties, the constant of proportionality between the measured intensities and the numbers of mRNA copies per cell is unknown and may vary for different arrays. Usually, the data are normalized (i.e., array-wise multiplied by appropriate factors) in order to compensate for this effect and to enable informative comparisons between different experiments. Centralization is a new two-step method for the computation of such normalization factors that is both biologically better motivated and more robust than standard approaches. First, for each pair of arrays the quotient of the constants of proportionality is estimated. Second, from the resulting matrix of pairwise quotients an optimally consistent scaling of the samples is computed.

Anabolic and catabolic gene expression pattern analysis in normal versus osteoarthritic cartilage using complementary DNA-array technology.

OBJECTIVE: To understand changes in gene expression levels that occur during osteoarthritic (OA) cartilage degeneration, using complementary DNA (cDNA)-array technology. METHODS: Nine normal, 6 early degenerated, and 6 late-stage OA cartilage samples of human knee joints were analyzed using the Human Cancer 1.2 cDNA array and TaqMan analysis. RESULTS: In addition to a large variability of expression levels between different patients, significant expression patterns were detectable for many genes. Cartilage types II and VI collagen were strongly expressed in late-stage specimens, reflecting the high matrix-remodeling activity of advanced OA cartilage. The increase in fibronectin expression in early degeneration suggests that fibronectin is a crucial regulator of matrix turnover activity of chondrocytes during early disease development. Of the matrix metalloproteinases (MMPs), MMP-3 appeared to be strongly expressed in normal and early degenerative cartilage and down-regulated in the late stages of disease. This indicates that other degradation pathways might be more important in late stages of cartilage degeneration, involving other enzymes, such as MMP-2 and MMP-11, both of which were up-regulated in late-stage disease. MMP-11 was up-regulated in OA chondrocytes and, interestingly, also in the early-stage samples. Neither MMP-1 nor MMP-8 was detectable, and MMP-13 and MMP-2 were significantly detectable only in late-stage specimens, suggesting that early stages are characterized more by degradation of other matrix components, such as aggrecan and other noncollagenous molecules, than by degradation of type II collagen fibers. CONCLUSION: This investigation allowed us to identify gene expression profiles of the disease process and to get new insights into disease mechanisms, for example, to develop a picture of matrix proteinases that are differentially involved in different phases of the disease process.

A simple iterative approach to parameter optimization.

Various bioinformatics problems require optimizing several different properties simultaneously. For example, in the protein threading problem, a scoring function combines the values for different parameters of possible sequence-to-structure alignments into a single score to allow for unambiguous optimization. In this context, an essential question is how each property should be weighted. As the native structures are known for some sequences, a partial ordering on optimal alignments to other structures, e.g., derived from structural comparisons, may be used to adjust the weights. To resolve the arising interdependence of weights and computed solutions, we propose a heuristic approach: iterating the computation of solutions (here, threading alignments) given the weights and the estimation of optimal weights of the scoring function given these solutions via systematic calibration methods. For our application (i.e., threading), this iterative approach results in structurally meaningful weights that significantly improve performance on both the training and the test data sets. In addition, the optimized parameters show significant improvements on the recognition rate for a grossly enlarged comprehensive benchmark, a modified recognition protocol as well as modified alignment types (local instead of global and profiles instead of single sequences). These results show the general validity of the optimized weights for the given threading program and the associated scoring contributions.

Engineering support vector machine kernels that recognize translation initiation sites.

MOTIVATION: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called translation initiation sites (TIS). RESULTS: The task of finding TIS can be modeled as a classification problem. We demonstrate the applicability of support vector machines for this task, and show how to incorporate prior biological knowledge by engineering an appropriate kernel function. With the described techniques the recognition performance can be improved by 26% over leading existing approaches. We provide evidence that existing related methods (e.g. ESTScan) could profit from advanced TIS recognition.

Analysis of gene expression data with pathway scores.

We present a new approach for the evaluation of gene expression data. The basic idea is to generate biologically possible pathways and to score them with respect to gene expression measurements. We suggest sample scoring functions for different problem specifications. We assess the significance of the scores for the investigated pathways by comparison to a number of scores for random pathways. We show that simple scoring functions can assign statistically significant scores to biologically relevant pathways. This suggests that the combination of appropriate scoring functions with the systematic generation of pathways can be used in order to select the most interesting pathways based on gene expression measurements.

Application of parameter optimization to molecular comparison problems.

Various bioinformatics comparison problems require optimizing several different properties simultaneously. Often linear objective functions combine the values for different properties of solution candidates into a single score to allow for multivariate optimization. In this context, an essential question is how each property should be weighted. Frequently, no apparent measure is available to serve as a model for the score. However, if preferences of certain solution candidates over others in a training set are available, the implied partial ordering may be used to best possibly adjust the weights. We apply different strategies to optimize the parameterization of empirical scoring functions used for two molecular comparison problems, protein threading and small molecule superposition. Using well established evaluation methods, it can be shown that the results of both comparison methods are significantly improved by systematically choosing appropriate weights for the scoring function contributions.