Construction and evaluation of cysteine selective electrodes for FIA analysis of pharmaceuticals

A flow injection analysis (FIA) system comprising a cysteine selective electrode as detection system was developed for determination of this amino acid in pharmaceuticals. Several electrodes were constructed for this purpose, having PVC membranes with different ionic exchangers and mediator solvents. Better working characteristics were attained with membranes comprising o-nitrophenyl octyl ether as mediator solvent and a tetraphenylborate based ionic-sensor. Injection of 500 µL standard solutions into an ionic strength adjuster carrier (3x10-3 M) of barium chloride flowing at 2.4mL min-1, showed linearity ranges from 5.0x10-5 to 5.0x10-3 M, with slopes of 76.4±0.6mV decade-1 and R2>0.9935. Slope decreased significantly under the requirement of a pH adjustment, selected at 4.5. Interference of several compounds (sodium, potassium, magnesium, barium, glucose, fructose, and sucrose) was estimated by potentiometric selectivity coefficients and considered negligible. Analysis of real samples were performed and considered accurate, with a relative error to an independent method of +2.7%.

Electroanalytical study of the pesticide ethiofencarb

A detailed study of voltammetric behavior of ethiofencarb (ETF) is reported using glassy carbon electrode (GCE) and hanging mercury drop electrode (HMDE). With GCE, it is possible to verify that the oxidative mechanism is irreversible, independent of pH, and the maximum intensity current was observed at +1.20 V vs. AgCl/Ag at pH 1.9. A linear calibration line was obtained from 1.0x10-4 to 8.0x10-4 mol L-1 with SWV method. To complete the electrochemical knowledge of ETF pesticide, the reduction was also explored with HMDE. A well-defined peak was observed at –1.00V vs. AgCl/Ag in a large range of pH with higher signal at pH 7.0. Linearity was obtained in 4.2x10-6 and 9.4x10-6 mol L-1 ETF concentration range. An immediate alkaline hydrolysis of ETF was executed, producing a phenolic compound (2-ethylthiomethylphenol) (EMP), and the electrochemical activity of the product was examined. It was deduced that it is oxidized on GCE at +0.75V vs. AgCl/Ag with a maximum peak intensity current at pH 3.2, but the compound had no reduction activity on HMDE. Using the decrease of potential peak, a flow injection analysis (FIA) system was developed connected to an amperometric detector, enabling the determination of EMP over concentration range of 1.0x10-7 and 1.0x10-5 mol L-1 at a sampling rate of 60 h-1. The results provided by FIA methodology were performed by comparison with results from high-performance liquid chromatography (HPLC) technique and demonstrated good agreement with relative deviations lower than 4%. Recovery trials were performed and the obtained values were between 98 and 104%.

Molecularly-imprinted materials for potentiometric transduction: application to the antibiotic enrofloxacin

Enrofloxacin (ENR) is an antimicrobial used both in humans and in food producing species. Its control is required in farmed species and their surroundings in order to reduce the prevalence of antibiotic resistant bacteria. Thus, a new biomimetic sensor enrofloxacin is presented. An artificial host was imprinted in specific polymers. These were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. The potentiometric sensors exhibited a near-Nernstian response. Slopes expressing mVΔlog([ENR]/M) varied within 48–63. The detection limits ranged from 0.28 to 1.01 µg mL 1. Sensors were independent from the pH of test solutions within 4–7. Good selectivity was observed toward potassium, calcium, barium, magnesium, glycine, ascorbic acid, creatinine, norfloxacin, ciprofloxacin, and tetracycline. In flowing media, the biomimetic sensors presented good reproducibility (RSD of ±0.7%), fast response, good sensitivity (47 mV/Dlog([ENR]/ M), wide linear range (1.0×10-5–1.0×10-3 M), low detection limit (0.9 µg mL-1), and a stable baseline for a 5×10-2 M acetate buffer (pH 4.7) carrier. The sensors were used to analyze fish samples. The method offered the advantages of simplicity, accuracy, and automation feasibility. The sensing membrane may contribute to the development of small devices allowing in vivo measurements of enrofloxacin or parent-drugs.

Osteoporotic hip fractures: Bisphosphonates sales and observed turning point in trend. A population-based retrospective study

The aim is to examine the temporal trends of hip fracture incidence in Portugal by sex and age groups, and explore the relation with anti-osteoporotic medication. From the National Hospital Discharge Database, we selected from 1st January 2000 to 31st December 2008, 77,083 hospital admissions (77.4% women) caused by osteoporotic hip fractures (low energy, patients over 49 years-age), with diagnosis codes 820.x of ICD 9-CM. The 2001 Portuguese population was used as standard to calculate direct age-standardized incidence rates (ASIR) (100,000 inhabitants). Generalized additive and linear models were used to evaluate and quantify temporal trends of age specific rates (AR), by sex. We identified 2003 as a turning point in the trend of ASIR of hip fractures in women. After 2003, the ASIR in women decreased on average by 10.3 cases/100,000 inhabitants, 95% CI (− 15.7 to − 4.8), per 100,000 anti-osteoporotic medication packages sold. For women aged 65–69 and 75–79 we identified the same turning point. However, for women aged over 80, the year 2004 marked a change in the trend, from an increase to a decrease. Among the population aged 70–74 a linear decrease of incidence rate (95% CI) was observed in both sexes, higher for women: − 28.0% (− 36.2 to − 19.5) change vs − 18.8%, (− 32.6 to − 2.3). The abrupt turning point in the trend of ASIR of hip fractures in women is compatible with an intervention, such as a medication. The trends were different according to gender and age group, but compatible with the pattern of bisphosphonates sales.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.