Alkylphenol polyethoxylates are one of the most importantclasses of nonionic surfactants. They are widely used in the household detergents and dyeing industry. Indeed, alkylphenols have been estimated that they are persistence organic pollutions which are not easily biodegraded by microorganisms and demonstrated as endocrine disruptors. Therefore alkylphenols regard as environmental hormones. The purpose in this research is developing the method which can be used for detection and quantification of alkylphenols and alkylphenol polyethoxylates in waters and sediments. LC-MS/MS was used as the analytical instrument which can analyze alkylphenols combined with long ethoxylate chain with improved sensitivity and selectivity. The extraction is liquid-liquid extraction. The mobile phase consisting of acetonitrile, water and methanol(43/14/43%, v/v/v) with 20mM ammonium acetate added was used for HPLC separation. The recoveries of alkylphenols and alkylphenol polyethoxylates from water and sediments were 83.0~95.1% and 84.8~94.6%. Decision limit(CC£\) and detection capability(CC£]) of water were 0.10~1.65 ng/L and 0.13~2.03 ng/L. CC£\ and CC£] of sediments were 0.05~0.95 ng/g and 0.06~1.18 ng/g.

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In this study, a LC/MS/MS method for the determination of ampicillin antibiotic in fish muscle tissue was developed and accredited according to Commission Decision 2002/657/EC. The metabolism of ampicillin in tilapia was them studied in serum, liver and muscle. The homogenized fish tissue was first extracted with MeOH-H2O(4:1), C18 sorbent was added to remove lipids and impurities, the extract was then evaporated to dryness with a steam of nitrogen gas at 38 ¢XC. The residue was redissolved with H2O, filtered and analyzed by LC/MS/MS equipped with an Agilient HC-C18(5£gm, 150mm ¡Ñ4.6mm), the mobile phase A was 10mM ammonium acetate containing 0.1% formic acid, while the mobile phase B was methanol. The determination of ampicillin was performed with electrospray ionization-tandem mass spectrometry in positive mode using multiple reation monitoring(MRM) for detection. Average recoveries were 81¡V86%, the limit of detection was 6.00 £gg kg-1¡Adecision limit(CC£\) of ampicillin in fish muscle sample was 63.65 ¡Ó 7.99 £gg kg-1. In the metabolism study, the oral administered dose to talipia was 20 mg/kg¡DBW. The maximum concentration of ampicillin in each tissues was obserned at 0.5 hour after oral administration, the maximum concentration in serum, liver and muscle was 27.53 mg L-1, 66.75 mg kg-1 and 1.33 mg kg-1, respectively. The concentration of ampicillin in muscle was 0.04 mg kg-1 24 hours after oral administration, which is lower than the 0.05 mg kg-1 MRL value of European Union resolutions. No residual ampicillin was detected in tilapia 48 hours after oral treatment, which conformed to the drug regulations for aquaculture ainmals in Taiwan.

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The purpose of this research is that investigate the effects of time and concentration of exposure for the accumulation and depletion of malachite green and leucomalachite green in tilapia by pharmacokinetics. LC-MS/MS was used as the analytical instrument in this research, and the detection limit of malachite green and leucomalachite green is 0.51 ppb and 0.48 ppb. The results show that malachite green is unstable at high temperature. Addition of TMPD into the standard can stabilize malachite green. The malachite green in exposure water is easy to adhere to the fiberglass tub and cause the decreases of concentration of malachite green in water. The concentrations of malachite green and leucomalachite green in tilapia are positive related to the time and concentration of exposure. In experiments of exposure of malachite green, the highest concentration of malachite green occurs in liver, accumulation rate constant is 21.62 h-1. Liver is also the major organ for transforming malachite green into leucomalachite green, the net leucomalachite green accumulation rate constant is 213.67 h-1. In the period of water bath, Gill is the fastest organ for eliminating malachite green and leucomalachite green, the elimination rate constant is 0.7799 h-1 and 0.4658 h-1; the leucomalachite green concentration in fat is still increase until 6h of water bath.

The study felld into three sections. The first section that a liquid chromatography method with fluorescence detection was developed for simultaneous determination of 11 quinolones (QNs; marbofloxacin, norfloxacin, ciprofloxacin, lomefloxacin, danofloxacin, enrofloxacin, sarafloxacin, difloxacin, oxolinic acid, nalidixic acid and flumequine) in chicken, pork, fish and shrimp. The analytes were extracted with 0.3% metaphosphoric acid: acetonitrile (1:1, v/v), followed by a HLB cartridge clean-up procedure. The HPLC separation was carried out on a symmetry column C18 (250 mm x 4.5 mm i.d., 5 £gm) with linear gradient elution of 0.1% formic acid: acetonitrile as mobile phase and programmable fluorescence detection. The method was validated by spiking blank animals tissues at three different levels (25, 50 and 250 ng/g; except 6.25, 12.5 and 62.5 ng/g for DAN) and linearity, detection limit, quantification limit, precision and accuracy were checked. Mean recoveries of 11 QNs from edible animal tissues were 71.7-105.3%. The limits of quantification in different muscle tissues ranged from 5.0 to 28.0 ng/g. The results showed it was simple, rapid, sensitive and suitable for routine test. The second section that a LC-ESI-MS/MS method was developed for determining 18 (fluoro)quinolone (QNs) residues in milk, chicken, pork, fish and shrimp. This method is capable of screening and confirming the presence of 12 amphoteric QNs (marbofloxacin, norfloxacin, enrofloxacin, ciprofloxacin, desethylene ciprofloxacin, lomefloxacin, danofloxacin, sarfloxacin, difloxacin, ofloxacin, orbifloxacin and enoxacin) and 6 acidic QNs (oxolinic acid, nalidixic acid, flumequine, cinoxacin, piromidic acid and pipemidic acid). The drugs were extracted from matrix using acetonitrile with 1% formic acid, diluted in 10% acetonitrile and defatted by extraction with hexane. The LC separation was conducted on a XDB C8 (150 x 4.6 mm, 5£gm) column with gradient elution of 20 mM ammonium formate with 0.1% formic acid¡Vacetonitrile as the mobile phase. Mass spectral acquisition was completed in the positive ion mode by applying multiple reaction mode (MRM). The decision limit (CC£\) and detection capability (CC£]) stated in the Decision No. 2002/657/EC and the ISO standard No.11843, has been calculated in the case of the nonauthorized substance. The values of CC£\ ranged from 0.18 to 0.68 ng/g and CC£] ranged from 0.24 to 0.96 ng/g under specified conditions. The third section that the pharmacokinetics of ENR and its active metabolite (CIP and des-CIP) were estimated in tilapia after intravenous (i.v.) and oral (p.o.) administration of a single dose of 2.5 and 10 mg/kg body weigh, respectively. At prefixed time points, from 0.25 h to 7 days after administration, whole blood and main tissue (liver, kidney, bile and muscle) from 4 individuals in each were collected. The concentration of ENR and its active metabolites in the main tissue were simultaneously detected by LC/MS/MS method. Limited of quantitation (LOQ) of this method were 0.01£gg/g. Pharmacokinetic parameters from both routes were described to have a two- compartment open model with first-order elimination. After i.v. administration, the area under the drug concentration-time (AUC), elimination half-life (t1/2£]), maximum plasma concentration (Cmax ), total body clearance (Cltot) and apparent volume of distribution at steady-state (Vss) of ENR were 109.6 ¡Ó 31.33 £gg.h/mL, 55.17 ¡Ó 22.84 h, 4.70 ¡Ó 0.36 £gg/mL, 14.82 ¡Ó 4.24 L/h/kg, 1105 ¡Ó 223.40 L/kg ,respectively. After oral administration, the AUC , t1/2£], Tmax , Cmax of ENR were 599.42 ¡Ó 76.19£gg.h/mL , 75.95 ¡Ó 12.94 h, 0.601¡Ó0.06h, 9.75 ¡Ó 0.46£gg/mL, respectively. After p.o. administration, CIP could be detected in liver, kidney and bile. Regarding des-CIP, the main active metabolite of CIP, could be detected in 120¡ã168 h bile among tissue. ENR and CIP had significance enterohepatic cycle in Tilapia and easily accumulated in bile. It seems reasonable to explain the phenomenon of ENR and CIP maintenance of high concentration in blood and muscle during the test time.

The use of breath odours in medical diagnosis dates back to classical times, though in its modern form the technique is only a few decades old. There are several breath tests in common clinical use, though all of them involve administration of a known or labelled exogenous compound. More recently, over the last twenty years, interest has focussed on analysis of endogenous metabolites in breath, but despite a large number of published studies reporting a number of disease markers, there has been little or no impact on clinical practice. Nonetheless, breath analysis offers a number of potential advantages over current biochemical methods. One major advantage of breath analysis is its non-invasive nature, which has led to significant interest in its use at point-of care for monitoring chronic diseases such as diabetes and the chronic infections ubiquitous in cystic fibrosis. However, breath analysis classically involves the use of expensive laboratory based analytical equipment which requires extensively-trained personnel and which cannot readily be miniaturised. Systems based on simple gas sensors might offer a way of overcoming these limitations. In recent years, Cranfield University has developed an instrument called the single metal oxide sensor gas analyser (SMOS-GA, more commonly referred to as the “Breathotron”) as a proof of concept for sensor-based breath analysis. In this project the Breathotron has been used in conjunction with selected ion flow tube mass spectrometry (SIFT-MS) and thermal desorption gas chromatography mass spectrometry (TD-GC-MS) to determine the changes in the concentrations of volatile organic compounds (VOCs) in breath in a number of experimental situations which a relevant to the diagnostic monitoring of diabetes mellitus. Studies conducted on clinically healthy volunteers were: an oral glucose tolerance test (OGTT); a six minute treadmill walking test; and a bicycle ergometer test. Additionally Breathotron and analytical data were also obtained during a hypoglycaemic clamp study carried out on hypoglycaemia-unaware Type I diabetics. The principle breath volatiles determined analytically were: acetone, acetaldehyde, ammonia isoprene though data on a number of others was also available. In general, it proved difficult to establish any reproducible relationship between the concentration of any compound measured and blood glucose concentration any of the experimental interventions. It was notable, though, that statistically significant associations were observed occasionally in data from individual volunteers, but even these were not reproduced in those trials which involved repeated measurements. This remained true even where spirometry data were used to derive VOC clearance rates. This may explain previous reports from smaller studies of an association between glucose and breath acetone concentration. It seems probable that any experimentally-induced changes in breath VOC concentration or clearance were of much smaller magnitude than background variability and was consequently not detectable. These observations were mirrored in the sensor-derived results. Multivariate analysis across all trials where Breathotron data were obtained suggested clustering by individual volunteer rather than glycaemic status. This suggests that that there exists a “background” breath volatile composition, dependent perhaps on such factors as long-term diet, which is independent of our experimental intervention. The Breathotron was also used as a platform to assess the performance of three different types of mixed metal oxide sensor in vitro. Calibration curves were generated for acetone, ammonia and propanol covering the physiological range of concentrations and with a similar water content to breath. Close correlations were obtained between concentration and the amplitude of the sensor response. Sensor response reproducibility was also determined using acetone at a concentration of 10ppm with dry and humidified test gas. There were significant differences between sensor types in overall reproducibility and in response to humidity. These results suggest that had there been substantial changes in breath VOC composition as a result of our experimental interventions, any of the types of sensor used would have been capable of responding to them. In summary, these results do not support the efficacy of breath VOC analysis as a means of non-invasive diagnostic monitoring.

Introduction 61Cu (T1/2 = 3.33 hr, Eβ= 1.22 MeV, 61.4 %) is an attractive isotope for positron emission tomography (PET) radiopharmaceutical agents such as ATSM and PTSM. Various separation processes have been reported for the production of 61Cu on a medium cyclotron using 13–22 MeV protons on natural and enriched 64Zn target materials [1,2]. This work, investigates production of 61Cu using both natural and enriched 64Zn targets and its separation. Three types of resins were used to assess for their efficiency and speed to separate the desired 61Cu from the 66,67,68Ga and 64Zn and for the recycling of 64Zn target material. The effective specific activity of purified 61Cu, was determined by ICP-MS and its titration with various polyaza and polycarboxylate complexing ligands. Material and Methods 1. Production and Separation Targets were irradiated by proton beam of IBA cyclotron 18/18MeV via the 64Zn(p,α) 61Cu and natZn(p,x) 61Cu reactions using an enriched 64Zn foil(15×15×0.05mm, ~50 mg) and natural foil (diameter 25 mm, 0.05 mm,~ 60 mg). Thirty minute irradiations were conducted with incident proton energies between 11.7–12.0 MeV and beam currents of 20 and 40 µA. Irradiated Zn targets were dissolved in 8M HCl at 150 oC then evaporated to dryness. Trace water to the resultant residue (twice) and resultant solutions evaporated to dryness. The residue was re-dissolved in 2ml of 0.01M HCl before loading onto a Cu-resin column (FIG. 1) Zn and Ga isotopes were collectively eluted using 30 ml of 0.01M HCl. The Cu was then removed using 1.5 ml of 8M HCl and passed directly onto a cation exchange followed by an anion exchange column. An additional 3 ml of 8M HCl was used to rinse the cation exchange column and ensure quantitatively removal of Cu (II) ions. The Cu was finally eluted from the anion exchange column using 3 ml of 2M HCl. The Cu solution was heated up at 150 oC until evaporated to dryness and 61Cu final product dissolved in 400–800 μL of 0.01M HCl. 2. Specific activity of 61Cu The specific activity (GBq/µmol) of the purified 61Cu was determined by ICP-MS and compared with that determined using dota, nota and di-amsar complexing ligands. For each 61Cu production run aliquot of final solution (100 µL) was left to decay before dilut-ing to 10 mL with 10% HNO3. Decayed samples were sent to ChemCentre (Curtin University) for ICP-MS analysis. Each sample was analysed for Cu, Al, Ca, Co, Fe, Ga, Ni, Si, and Zn, which are known to compete with Cu2+ for ligand complexation. Effective specific activity of the 61Cu was deter-mined by titrating various known concentration of ligands with 61Cu solution. The method is detailed in the literature [3]. Briefly, varying concentrations of each ligand was prepared in 0.1M sodium acetate buffer pH 6.5 to a total volume 20 µL. Fixed concentration of diluted 61Cu (0.01M HCl) in 10 µL was added to each ligand solution. The mixtures were vortexed then left to incubate at the room temperature for 30 mins. Two uL aliquots were withdrawn (in triplicate) from each reaction mixture and spot-ted on ITLC –SA. [Mobile phase: 0.1M NaCl: 0.1M EDTA (9:1) for Cu2+ and diamsar mixtures: Rf <0.2 Cu-diamsar; Rf > 0.8 free Cu2+ and 0.1M sodium acetate pH 4.5: H2O: MeOH: ammonium hydroxide (20:18:2:1 v/v) for Cu2+ dota and nota mixtures: Rf >0.8 Cu-dota and Cu-nota Rf < 0.2 free Cu2+]. Complexation of the 61Cu with each ligand was complete within 30 mins at room temperature. Concentration of Cu2+ was deter-mined from the 50% labelling efficiency. Results and Conclusion 1. Production and Separation The radioisotopes production from natZn target must be minimized by the optimum proton energy to reduce a radiation dose in the final product. The excitation functions of 66,67,68Ga ,65Zn and 61Cu are shown in FIG. 2. Proton beam energy of 11.7 MeV was used for both Zn targets to minimise the production of Ga isotopes and prevent formation of 65Zn. For the enriched 64Zn target (99.30%) higher proton energy could be used for the production of 61Cu allowing for increased yields and reduce radio contaminants. Previously, we used anion and cation exchange resin as described in the literature to separate the 61Cu [1]. Unfortunately the literature method was too long (up to 3 hours) and requiring high concentration of HCl and long evaporation times compromising achievable yields [4]. Thieme S. et al., 2013 [2] reported the successful use of Cu-resin for the separation of Cu radioisotopes and it was of interest to the current work to test this material for the separation of 61Cu in our hands. A cation, anion exchange and Cu-resin were combined into closed system to separate the 61Cu within 30 mins (FIG. 1). The system is designed to contain the transfer of solutions be-tween each column using simple plunger to force solution through and between each column. This system afforded an easy, reliable and fast separation of 61Cu that could be completed within 30 min. 2. Specific activity The specific activity of 61Cu was determined using ICP-MS and by titration with three ligands is summarized in TABLE 1. The ICP-MS data show values ranging from 9.2 to 32.4 GBq/μmol for 8 production runs. Specific activity determine using nota and dota were in all cases lower than the ICP MS data indicating some interference from the other metal ion contaminates such as Fe(ii/Iii), Ni (II), Ca (II), Zn (II), Ga (III). The specific activity determine using diamsar, which is known to be highly selective for Cu(II) (and Zn(II) and Fe(III)) in the presence of alkali and alkaline earth ions gave values significantly higher effective specific activity than that obtained using ICP MS. Variations in values can be explained by presence of contaminating metal ions.