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Background: Hip prosthetic replacement surgery is the gold standard for patients affected by symptomatic osteoarthritis. The ceramic-on-metal hybrid hard-on-hard bearing was initially launched on the market with the purpose of reducing adhesive and corrosion wear, loss of metal debris and ions and risk of fracture and squeaking. However, this bearing was withdrawn from the market, in the apprehension of local and systemic toxicity. The aim of this study is to evaluate the reliability and safety of ceramic-on-metal bearing at long term follow-up.Methods: From 2 cohorts of patients suffering of hip osteoarthritis who underwent total hip arthroplasty using ceramic-on-metal bearing with two different short stems, 19 of the GROUP A and 25 of the GROUP B were suitable for this study. All patients were compared clinically using the Harris Hip Score (HHS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual analogue scale (VAS), 12-item Short Form Health Survey (SF12P/M), and radiographically. Blood samples were collected in order to evaluate chromium and cobalt ions level. The two groups were compared in terms of metal ions blood levels, and finally all the implanted prostheses were compared with a healthy control group.Results: All the implanted stems were well-positioned and osseointegrated at a mean follow-up of 114 months. Improvements were observed for all clinical scores comparing preoperative and postoperative values in both groups. Radiographic evaluation showed a good ability to restore proper articular geometry. Chromium and cobalt ion analysis revealed values below the safety threshold except for 1 case in GROUP A (cup malposition) and 2 cases in GROUP B (6.1%). No revision occurred.Conclusions: Ceramic-on-metal bearing is safe and reliable at long term follow-up in association to short stems arthroplasty, if the implant is correctly positioned. Chromium and cobalt metal ions blood levels evaluation should be performed annually. [ABSTRACT FROM AUTHOR]

Background: Many tumor-related factors have shown the ability to affect metabolic pathways by paving the way for cancer-specific metabolic features. Here, we investigate the regulation of mTORC1 by MDM4, a p53-inhibitor with oncogenic or anti-survival activities depending on cell growth conditions. Method: MDM4-mTOR relationship was analysed through experiments of overexpression or silencing of endogenous proteins in cell culture and using purified proteins in vitro. Data were further confirmed in vivo using a transgenic mouse model overexpressing MDM4. Additionally, the Cancer Genome Atlas (TCGA) database (N = 356) was adopted to analyze the correlation between MDM4 and mTOR levels and 3D cultures were used to analyse the p53-independent activity of MDM4. Results: Following nutrient deprivation, MDM4 impairs mTORC1 activity by binding and inhibiting the kinase mTOR, and contributing to maintain the cytosolic inactive pool of mTORC1. This function is independent of p53. Inhibition of mTORC1 by MDM4 results in reduced phosphorylation of the mTOR downstream target p70S6K1 both in vitro and in vivo in a MDM4-transgenic mouse. Consistently, MDM4 reduces cell size and proliferation, two features controlled by p70S6K1, and, importantly, inhibits mTORC1-mediated mammosphere formation. Noteworthy, MDM4 transcript levels are significantly reduced in breast tumors characterized by high mTOR levels. Conclusion: Overall, these data identify MDM4 as a nutrient-sensor able to inhibit mTORC1 and highlight its metabolism-related tumor-suppressing function. [ABSTRACT FROM AUTHOR]

Background: Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances., Results: LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples., Conclusion: The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.