Myeloperoxidase and oxidative stress in rheumatoid arthritis

Objective. To determine whether MPO contributes to oxidative stress and disease activity in RA and whether it produces hypochlorous acid in SF. Methods. Plasma and where possible SF were collected from 77 RA patients while 120 healthy controls supplied plasma only. MPO and protein carbonyls were measured by ELISAs. 3-Chlorotyrosine in proteins and allantoin in plasma were measured by mass spectrometry. Results. Plasma MPO concentrations were significantly higher in patients with RA compared with healthy controls [10.8?ng/ml, inter-quartile range (IQR): 7.2-14.2; P?3.2) and those with low disease activity (LDA; DAS-28 ≤3.2) (HDA 27.9?ng/ml, 20.2-34.1 vs LDA 22.1?ng/ml, 16.9-34.9; P?>?0.05). There was a significant relationship between plasma MPO and DAS-28 (r?=?0.35; P?=?0.005). Plasma protein carbonyls and allantoin were significantly higher in patients with RA compared with the healthy controls. MPO protein was significantly higher in SF compared with plasma (median 624.0?ng/ml, IQR 258.4-2433.0 vs 30.2?ng/ml, IQR 25.1-50.9; P?相似文献   

Synthesis and anti-inflammatory activity of acyl derivatives of taraxasterol

Acylation of taraxasterol with acid chloranhydrides in the presence of N-dimethylaminopyridine yielded the new compounds 3β-acetoxy-20-methylidenetaraxastane, 3β-trifluoroacetoxy-20-methylidenetaraxastane, and 3β-benzoyl-20-methylidenetaraxastane. The antiphlogistic activities of taraxasterol and its acyl derivatives were studied. All study compounds had anti-inflammatory activity comparable to that of reference agent prednisolone. __________ Translated from Khimiko-Farmatsevticheskii Zhurnal, Vol. 42, No. 6, pp. 12–14, June, 2008.     

Second primary malignancy risk in thyroid cancer survivors: a systematic review and meta-analysis.

OBJECTIVE: To determine the risk of second primary malignancies (SPMs) in thyroid cancer survivors. DESIGN: We performed a systematic review and meta-analysis examining the standardized incidence ratios (SIRs) of SPMs in thyroid cancer survivors (compared to individuals without thyroid cancer). Two independent reviewers screened citations and reviewed all full-text papers deemed potentially relevant. Final consensus was reached on inclusion of papers in the review. Data were pooled using fixed effects models. MAIN OUTCOMES: Thirteen full-text papers were included. The incidence of SPMs in thyroid cancer survivors was increased with an SIR of 1.20 (95% confidence interval 1.17, 1.24) (based on pooled data from six studies of 70,844 thyroid cancer survivors). The SIR of the following SPMs was significantly increased: salivary gland, stomach, colon/colorectal, breast, prostate, kidney, brain/central nervous system, soft tissue sarcoma, non-Hodgkin's lymphoma, multiple myeloma, leukemia, bone/joints, and adrenal. A significantly reduced risk of lung and cervical cancers was observed. CONCLUSIONS: Thyroid cancer survivors are at increased risk of SPMs, which may be related to disease-specific treatments or genetic predisposition.     

Endodontic treatment quality analysis according to the computer tomography data

Endodontic treatment quality of different teeth groups was analysed according to computer tomography data. 1000 dental root canals of 521 teeth of 115 patients of different age groups were studied. The study results testified to low level of endodontic treatment quality. In 71.7% of cases instrumental processing and obturation of dental root canals were fulfilled inadequately. The most often mistake of endodontic treatment was insufficient root canals instrumental processing (62.8%).     

Conservative Exposure Predictions for Rapid Risk Assessment of Phase-Separated Additives in Medical Device Polymers

A novel approach for rapid risk assessment of targeted leachables in medical device polymers is proposed and validated. Risk evaluation involves understanding the potential of these additives to migrate out of the polymer, and comparing their exposure to a toxicological threshold value. In this study, we propose that a simple diffusive transport model can be used to provide conservative exposure estimates for phase separated color additives in device polymers. This model has been illustrated using a representative phthalocyanine color additive (manganese phthalocyanine, MnPC) and polymer (PEBAX 2533) system. Sorption experiments of MnPC into PEBAX were conducted in order to experimentally determine the diffusion coefficient, D = (1.6 ± 0.5) × 10^?11 cm²/s, and matrix solubility limit, C _s = 0.089 wt.%, and model predicted exposure values were validated by extraction experiments. Exposure values for the color additive were compared to a toxicological threshold for a sample risk assessment. Results from this study indicate that a diffusion model-based approach to predict exposure has considerable potential for use as a rapid, screening-level tool to assess the risk of color additives and other small molecule additives in medical device polymers.     

Automated brain extraction of multisequence MRI using artificial neural networks

Brain extraction is a critical preprocessing step in the analysis of neuroimaging studies conducted with magnetic resonance imaging (MRI) and influences the accuracy of downstream analyses. The majority of brain extraction algorithms are, however, optimized for processing healthy brains and thus frequently fail in the presence of pathologically altered brain or when applied to heterogeneous MRI datasets. Here we introduce a new, rigorously validated algorithm (termed HD‐BET) relying on artificial neural networks that aim to overcome these limitations. We demonstrate that HD‐BET outperforms six popular, publicly available brain extraction algorithms in several large‐scale neuroimaging datasets, including one from a prospective multicentric trial in neuro‐oncology, yielding state‐of‐the‐art performance with median improvements of +1.16 to +2.50 points for the Dice coefficient and ?0.66 to ?2.51 mm for the Hausdorff distance. Importantly, the HD‐BET algorithm, which shows robust performance in the presence of pathology or treatment‐induced tissue alterations, is applicable to a broad range of MRI sequence types and is not influenced by variations in MRI hardware and acquisition parameters encountered in both research and clinical practice. For broader accessibility, the HD‐BET prediction algorithm is made freely available ( www.neuroAI-HD.org ) and may become an essential component for robust, automated, high‐throughput processing of MRI neuroimaging data.