Osseointegration and biocompatibility of different metal implants-a comparative experimental investigation in sheep

Background In the present study, 4 different metallic implant materials, either partly coated or polished, were tested for their osseointegration and biocompatibility in a pelvic implantation model in sheep. Methods Materials to be evaluated were: Cobalt-Chrome (CC), Cobalt-Chrome/Titanium coating (CCTC), Cobalt-Chrome/Zirconium/Titanium coating (CCZTC), Pure Titanium Standard (PTST), Steel, TAN Standard (TANST) and TAN new finish (TANNEW). Surgery was performed on 7 sheep, with 18 implants per sheep, for a total of 63 implants. After 8 weeks, the specimens were harvested and evaluated macroscopically, radiologically, biomechanically (removal torque), histomorphometrically and histologically. Results Cobalt-Chrome screws showed significantly (p = 0.031) lower removal torque values than pure titanium screws and also a tendency towards lower values compared to the other materials, except for steel. Steel screws showed no significant differences, in comparison to cobalt-chrome and TANST, however also a trend towards lower torque values than the remaining materials. The results of the fluorescence sections agreed with those of the biomechanical test. Histomorphometrically, there were no significant differences of bone area between the groups. The BIC (bone-to-implant-contact), used for the assessment of the osseointegration, was significantly lower for cobalt-chrome, compared to steel (p = 0.001). Steel again showed a lower ratio (p = 0.0001) compared to the other materials. Conclusion This study demonstrated that cobalt-chrome and steel show less osseointegration than the other metals and metal-alloys. However, osseointegration of cobalt-chrome was improved by zirconium and/or titanium based coatings (CCTC, TANST, TAN, TANNEW) being similar as pure titanium in their osseointegrative behavior.

Complications related to cement leakage in sacroplasty

Data concerning the safety of sacroplasty in terms of cement leakage is scarce. Frequency, distribution patterns and clinical consequences of cement leakage were assessed in 33 patients (28 female, mean age: 74 +/- 10 yrs; bilateral SIF: n = 30, 63 sacroplasties) treated with sacroplasty between 06/2003 and 11/2010 in a retrospective study using patients' records, operative notes and postoperative radiographs. Cement leakage was noted within the fracture gap (27%), into veins (6%), neuroforamina (3%) or in the intervertebral disc space L5/S1 (2%). In one patient, cement leakage into the fracture gap led to unilateral radiculopathy of the 5th lumbar nerve root. Leakage into the fracture gap is at high risk of affecting the 5th lumbar nerve root due to the special course of its ventral branch over the sacral promontory. The risks of cement leakage with neurological impairment should be explained to patients.

Impact of permanent pacemaker implantation on clinical outcome among patients undergoing transcatheter aortic valve implantation

This study sought to assess the impact of permanent pacemaker (PPM) implantation on clinical outcomes among patients undergoing transfemoral transcatheter aortic valve implantation (TAVI).

High HSP27 and HSP70 expression levels are independent adverse prognostic factors in primary resected colon cancer

The expression of Heat Shock Proteins (HSPs) is increased in various cancers and has been shown to correlate with biological tumor behaviour. This study aimed to investigate the impact of HSP70, HSP60 and HSP27 expression in colon cancer.

Tissue-based proteomics reveals FXYD3, S100A11 and GSTM3 as novel markers for regional lymph node metastasis in colon cancer

Regional lymph node metastasis negatively affects prognosis in colon cancer patients. The molecular processes leading to regional lymph node metastasis are only partially understood and proteomic markers for metastasis are still scarce. Therefore, a tissue-based proteomic approach was undertaken for identifying proteins associated with regional lymph node metastasis. Two complementary tissue-based proteomic methods have been employed. MALDI imaging was used for identifying small proteins (≤25 kDa) in situ and label-free quantitative proteomics was used for identifying larger proteins. A tissue cohort comprising primary colon tumours without metastasis (UICC II, pN0, n = 21) and with lymph node metastasis (UICC III, pN2, n = 33) was analysed. Subsequent validation of identified proteins was done by immunohistochemical staining on an independent tissue cohort consisting of primary colon tumour specimens (n = 168). MALDI imaging yielded ten discriminating m/z species, and label-free quantitative proteomics 28 proteins. Two MALDI imaging-derived candidate proteins (FXYD3 and S100A11) and one from the label-free quantitative proteomics (GSTM3) were validated on the independent tissue cohort. All three markers correlated significantly with regional lymph node metastasis: FXYD3 (p = 0.0110), S100A11 (p = 0.0071), and GSTM3 (p = 0.0173). FXYD3 and S100A11 were more highly expressed in UICC II patient tumour tissues. GSTM3 was more highly expressed in UICC III patient tumour tissues. By our tissue-based proteomic approach, we could identify a large panel of proteins which are associated with regional lymph node metastasis and which have not been described so far. Here we show that novel markers for regional lymph metastasis can be identified by MALDI imaging or label-free quantitative proteomics and subsequently validated on an independent tissue cohort. Copyright © 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.