Serum Early Prostate Cancer Antigen (EPCA) Level and Its Association with Disease Progression in Prostate Cancer in a Chinese Population

BACKGROUND: Early prostate cancer antigen (EPCA) has been shown a prostate cancer (PCa)-associated nuclear matrix protein, however, its serum status and prognostic power in PCa are unknown. The goals of this study are to measure serum EPCA levels in a cohort of patients with PCa prior to the treatment, and to evaluate the clinical value of serum EPCA. METHODS: Pretreatment serum EPCA levels were determined with an ELISA in 77 patients with clinically localized PCa who underwent radical prostatectomy and 51 patients with locally advanced or metastatic disease who received primary androgen deprivation therapy, and were correlated with clinicopathological variables and disease progression. Serum EPCA levels were also examined in 40 healthy controls. RESULTS: Pretreatment mean serum EPCA levels were significantly higher in PCa patients than in controls (16.84 ± 7.60 ng/ml vs. 4.12 ± 2.05 ng/ml, P<0.001). Patients with locally advanced and metastatic PCa had significantly higher serum EPCA level than those with clinically localized PCa (22.93 ± 5.28 ng/ml and 29.41 ± 8.47 ng/ml vs. 15.17 ± 6.03 ng/ml, P = 0.014 and P<0.001, respectively). Significantly elevated EPCA level was also found in metastatic PCa compared with locally advanced disease (P < 0.001). Increased serum EPCA levels were significantly and positively correlated with Gleason score and clinical stage, but not with PSA levels and age. On multivariate analysis, pretreatment serum EPCA level held the most significantly predictive value for the biochemical recurrence and androgen-independent progression among pretreatment variables (HR = 4.860, P<0.001 and HR = 5.418, P<0.001, respectively). CONCLUSIONS: Serum EPCA level is markedly elevated in PCa. Pretreatment serum EPCA level correlates significantly with the poor prognosis, showing prediction potential for PCa progression

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

A nonlinear dynamic model of magnetorheological elastomers in magnetic fields based on fractional viscoelasticity

As smart materials, magnetorheological elastomers (MREs) have been broadly applied in the field of intelligent structures and devices. In order to mathematically represent the dynamic behavior in a wide range of strain amplitude, excitation frequency and magnetic field; a nonlinear model with a fractional element was developed for MREs in a linear viscoelastic regime. The identification of model parameters was realized through fitting experimental data of dynamic moduli measured in shear mode, and the identified parameters exhibited good repeatability and consistency to reflect the rationality of this nonlinear dynamic model. Considering material elasticity and viscosity, the dependence of model parameters on strain amplitudes and magnetic fields was analyzed to interpret the dynamics of MREs. The fitted results displayed an excellent agreement with the experimental results on the dependence of dynamic moduli on strain amplitudes and magnetic fields. Using the predictor-corrector approach, predicted results on the stress-strain hysteresis loop were calculated based on identified parameters to further validate the proposed model by comparing with experimental results and predicted results of the revised Bouc-Wen model. This proposed model is expected to facilitate the dynamic analysis and simulation of MRE based vibration systems with a high precision accuracy.</p

Pharmacokinetic and toxicological evaluation of multi-functional thiol-6-fluoro-6-deoxy-d-glucose gold nanoparticles in vivo

We synthesized a novel, multi-functional, radiosensitizing agent by covalently linking 6-fluoro-6-deoxy-d-glucose (6-FDG) to gold nanoparticles (6-FDG-GNPs) via a thiol functional group. We then assessed the bio-distribution and pharmacokinetic properties of 6-FDG-GNPs in vivo using a murine model. At 2h, following intravenous injection of 6-FDG-GNPs into the murine model, approximately 30% of the 6-FDG-GNPs were distributed to three major organs: the liver, the spleen and the kidney. PEGylation of the 6-FDG-GNPs was found to significantly improve the bio-distribution of 6-FDG-GNPs by avoiding unintentional uptake into these organs, while simultaneously doubling the cellular uptake of GNPs in implanted breast MCF-7 adenocarcinoma. When combined with radiation, PEG-6-FDG-GNPs were found to increase the apoptosis of the MCF-7 breast adenocarinoma cells by radiation both in vitro and in vivo. Pharmacokinetic data indicate that GNPs reach their maximal concentrations at a time window of two to four hours post-injection, during which optimal radiation efficiency can be achieved. PEG-6-FDG-GNPs are thus novel nanoparticles that preferentially accumulate in targeted cancer cells where they act as potent radiosensitizing agents. Future research will aim to substitute the 18F atom into the 6-FDG molecule so that the PEG-6-FDG-GNPs can also function as radiotracers for use in positron emission tomography scanning to aid cancer diagnosis and image guided radiation therapy planning.Peer reviewed: YesNRC publication: Ye