Dynamics of metabolic characteristics in dairy cows and their impact on disease-free survival time.

Dairy cows are at a greater risk of disease due to increased energy demand during the transition period. Blood biomarkers including beta-hydroxybutyrate (BHBA)1 and non-esterified fatty acids (NEFA)2 are routinely used to identify animals in a state of negative energy balance (NEB)3. Recent research demonstrates cattle have varied response to NEB, that requires multiple blood biomarkers to characterize. This research identified five subcategories (cowtypes) of metabolic responses in transition dairy cows: Healthy, Athlete, Clever, Hyperketonemia, and Poor Metabolic Adaptation Syndrome (PMAS)4. The data set used in this study was collected in Germany by VIT - Vereinigte Informationssysteme Tierhaltung w.V. from 2016 to 2020. Health issues with time of diagnostic were included in the dataset. Using previously reported prediction models for blood BHB and blood NEFA and milk Fourier-transform infrared spectroscopy (FTIR)5 data, the cowtypes in our dataset were predicted. The objective of this study is to evaluate the association of the cowtypes with the disease-free survival time in dairy cows during early post calving using an accelerated failure time regression model. Additionally, transition probabilities of the population dynamics between cowtypes are studied by means of a Markov chain model. Using Healthy cowtype as reference level, Athlete, Clever, and PMAS cowtypes were found to be significant for the disease-free survival probability (P < 0.01). Conversely, Hyperketonemia cowtype was not significant (P = 0.182). Compared to the Healthy cowtype, all other cowtypes had a negative effect on the survival probabilities, which was higher for PMAS cows. Furthermore, after computing the estimated population transition probabilities among cowtypes, the stationary distribution of the Markov chain, along with bootstrap confidence intervals were computed. The results showed 0.091 (95% CI:0.089,0.092), 0.077 (95 % CI:0.074,0.078), 0.684 (95 % CI:0.067,0.069), 0.138 (95 % CI:0.136,0.139), and 0.009 (95% CI:0.008,0.010) of probability of being in Healthy, Athlete, Clever, Hyperketonemia, and PMAS cowtype, respectively. These estimates represent the proportion of cows belonging to the different cowtypes in a herd; information which may prove useful for herd management. The application of blood biomarker predictions using milk FTIR allows us to investigate differences between predicted cowtype and movements between these states and the association with time to disease. Further research will improve our understanding of the dynamic nature of the transition period.

Novel prediction models for hyperketonemia using bovine milk Fourier-transform infrared spectroscopy.

Metabolic diseases driven by negative energy balance in dairy cattle contribute to reduced milk production, increased disease incidence, culling, and death. Cow side tests for negative energy balance markers are available but are labor-intensive. Milk sample analysis using Fourier transform infrared spectroscopy (FTIR) allows for sampling numerous cows simultaneously. FTIR prediction models have moderate accuracy for hyperketonemia diagnosis (beta-hydroxybutyrate (BHB) ≥ 1.2 mmol/L). Most research using FTIR has focused on homogenous datasets and conventional prediction models, including partial least squares, linear discriminant analysis, and ElasticNet. Our objective was to evaluate more diverse modeling options, such as deep learning, gradient boosting machine models, and model ensembles for hyperketonemia classification. We compiled a sizable, heterogeneous dataset including milk FTIR and concurrent blood samples. Blood samples were tested for blood BHB, and wavenumber data was obtained from milk FTIR analysis. Using this dataset, we trained conventional prediction models and other options listed above. We demonstrate prediction model performance is similar for convolutional neural networks and ensemble models to simpler algorithm options. Results obtained from this study indicate that deep learning and model ensembles are potential algorithm options for predicting hyperketonemia in dairy cattle. Additionally, our results indicate hyperketonemia prediction models can be developed using heterogeneous datasets.

The reliability and accuracy of two methods for proximal caries detection and depth on directly visible proximal surfaces: an in vitro study.

This study aimed to determine the reliability and accuracy of the ICDAS and radiographs in detecting and estimating the depth of proximal lesions on extracted teeth. The lesions were visible to the naked eye. Three trained examiners scored a total of 132 sound/carious proximal surfaces from 106 primary teeth and 160 sound/carious proximal surfaces from 140 permanent teeth. The selected surfaces were first scored visually, using the 7 classes in the ICDAS. They were then assessed on radiographs using a 5-point classification system. Reexaminations were conducted with both scoring systems. Teeth were then sectioned and the selected surfaces histologically classified using a stereomicroscope (×5). Intrareproducibility values (weighted kappa statistics) for the ICDAS for both primary and permanent teeth were >0.9, and for the radiographs between 0.6 and 0.8. Interreproducibility values for the ICDAS were >0.85, for the radiographs >0.6. For both primary and permanent teeth, the accuracy of each examiner (Spearman's correlation coefficient) for the ICDAS was ≥0.85, and for the radiographs ≥0.45. Corresponding data were achieved when using pooled data from the 3 examiners for both the ICDAS and the radiographs. The associations between the 2 detection methods were measured to be moderate. In particular, the ICDAS was accurate in predicting lesion depth (histologically) confined to the enamel/outer third of the dentine versus deeper lesions. This study shows that when proximal lesions are open for inspection, the ICDAS is a more reliable and accurate method than the radiograph for detecting and estimating the depth of the lesion in both primary and permanent teeth.

Developing a predictive model for beta-hydroxybutyrate and non-esterified fatty acids using milk fourier-transform infrared spectroscopy in dairy cows.

Negative energy balance following parturition predisposes dairy cattle to numerous metabolic disorders. Current diagnostics are limited by their labor requirements and inability to measure multiple metabolic markers simultaneously. Fourier-transform Infrared spectroscopy (FTIR) data, measured from milk samples, could improve the detection of metabolic disorders using routine milk samples from dairy farms. The objective of this study was to develop a predictive model for numeric values of blood beta-hydroxybutyrate (BHB) and blood non-esterified fatty acids (NEFA). The study utilized a dataset comprised of 622 observations with known blood BHB and blood NEFA values measured concurrently with the milk FTIR data. Using ElasticNet regression on milk FTIR data and production information, we built regression models for numeric blood BHB and blood NEFA prediction and classification models for blood BHB values greater than 1.2 mmol/L and blood NEFA values greater than 0.7 mmol/L. The R2 of the best fitting model was 0.56 and 0.51 for log-transformed BHB and log-transformed NEFA, respectively. The BHB classification model had a 90 % sensitivity and 83 % specificity and the NEFA classification model achieved a sensitivity of 73 % and specificity of 74 %. We applied our numeric prediction models to an external dataset (n = 9660) with known blood metabolites to validate the prediction accuracy of log-transformed blood BHB and log-transformed blood NEFA models. Log-transformed BHB root mean square error (RMSE) was 0.4018 and log-transformed NEFA RMSE was 0.4043. The second objective of this study was to develop a categorization for cows as either metabolically disordered or healthy. Responses to negative energy balance in transition cows are related to blood levels of BHB and NEFA. Cows suffering from metabolic disorders without elevated blood BHB values remain unidentified when detection is focused on blood BHB alone. To account for this differentiated metabolic response, we categorized cows as either 'metabolically healthy' or suffering a 'metabolic disorder' by using a combination of blood BHB, blood NEFA, and milk fat to protein quotient. We obtained a balanced accuracy of 94 % for the prediction of cow metabolic status. Direct prediction of metabolic status can be used to identify hyperketonemic cows in addition to cows exhibiting metabolic response patterns not detected by elevated blood BHB alone.

Full model selection using regression trees for numeric predictions of biomarkers for metabolic challenges in dairy cows.

Dairy cows suffer poor metabolic adaptation syndrome (PMAS)1 during early post-calving periods caused by negative energy balance. Measurement of blood beta-hydroxy butyric acid (BHBA)2 and blood non-esterified fatty acids (NEFA)3 allow early and accurate detection of negative energy balance. Machine learning prediction of blood BHBA and blood NEFA using milk testing samples represents an opportunity to identify at-risk animals, using less labor than direct blood testing methods. Routine milk testing on modern dairies and computer record keeping provide an immense amount of data which can then be used in machine learning models. Previous research for predicting blood metabolites using Fourier-transform infrared spectroscopy (FTIR)4 milk data has focused mainly on individual models rather than a comparison among the models. Full model selection is the process of comparing different combinations of pre-processing methods, variable selection, and statistical learning algorithms to determine which model results in the lowest prediction error for a given dataset. For this project we used a full model selection approach with regression trees (rtFMS)5 . rtFMS uses the cross-validated performance of different model configurations to feed a regression tree for selecting a final model. A total of 384 possible model configurations (algorithms, predictors and data preprocessing options) for each outcome (blood BHBA and blood NEFA) were considered in the rtFMS technique. rtFMS allows direct comparison of multiple modeling approaches reducing bias due to empirical knowledge, modeling habits, or preferences, identifying the model with minimal root mean squared prediction error (RMSE)6 . An elastic net regression model was selected as the best performing model for both biomarkers. The input data for blood BHBA predictions were FTIR milk spectra, with a second derivative pre-processing, and a filter with 212 wave numbers, obtaining RMSE = 0.354 (0.328-0.392). The best performing model for blood NEFA had input data of FTIR milk spectra, with a second derivative pre-processing, and a filter with 212 wave numbers filter along with the time of milking, obtaining RMSE = 0.601 (0.564-0.654). The comparison of multiple modeling strategies, conducted by rtFMS, present an option for improved FTIR prediction models of blood BHBA and blood NEFA by reducing error due to human bias. The implementation of rtFMS to design future prediction models can guide model inputs and features. Our prediction models have the potential to increase early detection of metabolic disorders in dairy cows during the transition period.

The role of timeliness in the cost-effectiveness of older adult vaccination: A case study of pneumococcal conjugate vaccine in Australia.

While the impact of the timeliness of vaccine administration has been well-studied for childhood vaccinations, there has been little detailed quantitative analysis on the potential impact of the timeliness of vaccinations in older adults. The aim of this study was to explore the impact of implementing more realistic observed uptake distributions, taking into the account reduced vaccine efficacy but higher pneumococcal disease burden with increasing age beyond 65 years. A multi-cohort Markov model was constructed to evaluate the cost-effectiveness of a pneumococcal (PCV13) immunisation program in Australia, assuming two different uptake modelling approaches. The approach using an estimate of observed uptake was compared with a scenario in which the total cumulative uptake was delivered at the recommended age of vaccination. We found these two approaches produced different results both in terms of cases prevented and cost-effectiveness. The impact of the non-timely uptake in adult programs may sometimes have positive and other times negative effects, depending on several factors including the age-specific disease rates and the duration of vaccine protection. Our study highlights the importance of using realistic assumptions around uptake (including non-timely vaccination) when estimating the impact of vaccination in adults.

Fast separation liquid chromatography-tandem mass spectrometry for the confirmation and quantitative analysis of avermectin residues in food.

A new residue analytical method for the confirmation and quantification of avermectin residues in food is described in this article. This method allows a fast analysis for the determination of avermectin residues, abamectin (ABM), ivermectin (IVM), emamectin benzoate (EMA) and doramectin (DOR) by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Separation was performed using a short column of 1.8 microm particle size. The hybrid quadrupole/linear ion trap (QqQ(LIT)) system via the linearly accelerating (LINAC) high-pressure collision cell, allows the MS detection in multiple reaction monitoring (MRM) mode operating in fast scan acquisition times. The effect of reduced dwell times on mass spectral quality and sensitivity is evaluated in this study. For quantitative purposes, the influence of dwell time on S/N ratio and peak area was observed. ABM, IVM, EMA and DOR show an increased trend of peak area and S/N ratio, when dwell times are of 50 ms against 10-20 ms, suited when the number of compounds to be analyzed is higher. The sensitivity achieved by using the LC-MS/MS system is enough for the confirmation of avermectin residues in the selected commodities (salmon muscle and pepper) at trace concentration levels (sub-microg/kg and microg/kg) and therefore a sample pre-concentration step was not necessary. The instrumental limits of quantification (ILQ) are in the range of 0.15-5 ppb. Samples were extracted by solid-liquid extraction (SLE) procedure using acetonitrile, and cleaned-up using alumina. The average recoveries obtained were acceptable (80-95%). The calibration curves were linear over the working range from ILQs to 500 microg/kg. For the quantitative analysis, matrix-matched calibration and dilution of SLE extracts was proven as reliable alternative to compensate matrix-effects and for its feasible application in routine analysis.

Cost-effectiveness of 13-valent pneumococcal conjugate vaccine (PCV13) in older Australians.

BACKGROUND: The 23-valent pneumococcal polysaccharide vaccine (PPV23) has been funded under the Australia National Immunisation Program (NIP) since January 2005 for those aged >65years and other risk groups. In 2016, PCV13 was accepted by the Pharmaceutical Benefits Advisory Committee (PBAC) as a replacement for a single dose of PPV23 in older Australian adults. METHODS: A single-cohort deterministic multi-compartment (Markov) model was developed describing the transition of the population between different invasive and non-invasive pneumococcal disease related health states. We applied a healthcare system perspective with costs (Australian dollars, A$) and health effects (measured in quality adjusted life-years, QALYs) attached to model states and discounted at 5% annually. We explored replacement of PPV23 with PCV13 at 65years as well as other age based vaccination strategies. Parameter uncertainty was explored using deterministic and probabilistic sensitivity analysis. RESULTS: In a single cohort, we estimated PCV13 vaccination at the age of 65years to cost ∼A$11,120,000 and prevent 39 hospitalisations and 6 deaths from invasive pneumococcal disease and 180 hospitalisations and 10 deaths from community acquired pneumonia. The PCV13 program had an incremental cost-effectiveness ratio of ∼A$88,100 per QALY gained when compared to a no-vaccination, whereas PPV23 was ∼A$297,200 per QALY gained. To fall under a cost-effectiveness threshold of A$60,000 per QALY, PCV13 would have to be priced below ∼A$46 per dose. The cost-effectiveness of PCV13 in comparison to PPV23 was ∼A$35,300 per QALY gained. CONCLUSION: In comparison to no-vaccination, we found PCV13 use in those aged 65years was unlikely to be cost-effective unless the vaccine price was below A$46 or a longer duration of protection can be established. However, we found that in comparison to the PPV23, vaccination with PCV13 was cost-effective. This partly reflects the poor value for money estimated for PPV23 use in Australia.

Beyond expectations: Post-implementation data shows rotavirus vaccination is likely cost-saving in Australia.

BACKGROUND: Universal vaccination against rotavirus was included in the funded Australian National Immunisation Program in July 2007. Predictive cost-effectiveness models assessed the program before introduction. METHODS: We conducted a retrospective economic evaluation of the Australian rotavirus program using national level post-implementation data on vaccine uptake, before-after measures of program impact and published estimates of excess intussusception cases. These data were used as inputs into a multi-cohort compartmental model which assigned cost and quality of life estimates to relevant health states, adopting a healthcare payer perspective. The primary outcome was discounted cost per quality adjusted life year gained, including or excluding unspecified acute gastroenteritis (AGE) hospitalisations. RESULTS: Relative to the baseline period (1997-2006), over the 6years (2007-2012) after implementation of the rotavirus program, we estimated that ∼77,000 hospitalisations (17,000 coded rotavirus and 60,000 unspecified AGE) and ∼3 deaths were prevented, compared with an estimated excess of 78 cases of intussusception. Approximately 90% of hospitalisations prevented were in children <5years, with evidence of herd protection in older age groups. The program was cost-saving when observed changes (declines) in both hospitalisations coded as rotavirus and as unspecified AGE were attributed to the rotavirus vaccine program. The adverse impact of estimated excess cases of intussusception was far outweighed by the benefits of the program. CONCLUSION: The inclusion of herd impact and declines in unspecified AGE hospitalisations resulted in the value for money achieved by the Australian rotavirus immunisation program being substantially greater than predicted bypre-implementation models, despite the potential increased cases of intussusception. This Australian experience is likely to be relevant to high-income countries yet to implement rotavirus vaccination programs.

Retrospective economic evaluation of childhood 7-valent pneumococcal conjugate vaccination in Australia: Uncertain herd impact on pneumonia critical.

BACKGROUND: Retrospective cost-effectiveness analyses of vaccination programs using routinely collected post-implementation data are sparse by comparison with pre-program analyses. We performed a retrospective economic evaluation of the childhood 7-valent pneumococcal conjugate vaccine (PCV7) program in Australia. METHODS: We developed a deterministic multi-compartment model that describes health states related to invasive and non-invasive pneumococcal disease. Costs (Australian dollars, A$) and health effects (quality-adjusted life years, QALYs) were attached to model states. The perspective for costs was that of the healthcare system and government. Where possible, we used observed changes in the disease rates from national surveillance and healthcare databases to estimate the impact of the PCV7 program (2005-2010). We stratified our cost-effectiveness results into alternative scenarios which differed by the outcome states included. Parameter uncertainty was explored using probabilistic sensitivity analysis. RESULTS: The PCV7 program was estimated to have prevented ∼5900 hospitalisations and ∼160 deaths from invasive pneumococcal disease (IPD). Approximately half of these were prevented in adults via herd protection. The incremental cost-effectiveness ratio was ∼A$161,000 per QALY gained when including only IPD-related outcomes. The cost-effectiveness of PCV7 remained in the range A$88,000-$122,000 when changes in various non-invasive disease states were included. The inclusion of observed changes in adult non-invasive pneumonia deaths substantially improved cost-effectiveness (∼A$9000 per QALY gained). CONCLUSION: Using the initial vaccine price negotiated for Australia, the PCV7 program was unlikely to have been cost-effective (at conventional thresholds) unless observed reductions in non-invasive pneumonia deaths in the elderly are attributed to it. Further analyses are required to explore this finding, which has significant implications for the incremental benefit achievable by adult PCV programs.

Analytical, toxicological and kinetic investigation of decomposition of the drug diclofenac in waters and wastes using gamma radiation.

The radiolytic decomposition of the drug diclofenac (DCF), and in limited extent, also two other widely used drugs, ibuprofen and carbamazepine, was examined using liquid chromatography (LC) methods. The efficiency of DCF decomposition was examined in function of the absorbed dose of gamma radiation, and also in the presence of selected scavengers of radicals, which are commonly present in natural waters and wastes. Three different tests were employed for the monitoring of toxicity changes in the irradiated DCF solutions. The LC/mass spectrometry (MS) was used for the determination of products of DCF radiolysis. Using pulse-radiolysis method with the spectrophotometric detection, the rate constant values were determined for reactions of DCF with the main products of water radiolysis: hydroxyl radicals (1.24 ± 0.02) × 10(10) M(-1) s(-1) and hydrated electrons (3.1 ± 0.2) × 10(9) M(-1) s(-1). Their values indicate that both oxidative and reductive processes in radiolytic decomposition of DCF can take place in irradiated diluted aqueous solutions of DCF. The possibility of decomposition of all examined analytes was investigated in samples of river water and hospital waste. Compared to the previous studies, the conducted measurements in real samples were carried out at the concentration levels, which are close to those reported earlier in environmental samples. Graphical abstract ᅟ.

Economic evaluations of implemented vaccination programmes: key methodological challenges in retrospective analyses.

Post-implementation evaluation should play an important role in assessing the success of public health programmes; however, the value for money achieved by vaccine programmes after introduction has received relatively little attention to date. In this article we explore the methodological challenges in these analyses and offer direction for future evaluations in the area. We identify alternative approaches to addressing these challenges, which include the estimation of disease changes attributable to vaccination efforts, the hypothetical no vaccination comparator scenario and the full benefit achieved by implemented vaccination programmes. We also outline other important considerations such as the evolution of prices over time. Further work needs to be done to explore these issues and to determine how the application of different approaches may impact on the results of evaluations in various circumstances. As retrospective analyses are likely to become more frequent and influential, it is important that both the benefits and the limitations of post-implementation evaluations are recognised and understood. We argue that it would be useful to establish a methodological framework to provide standards and guidance on how to undertake such analyses in the future.

Determination of pesticides in milk-based infant formulas by pressurized liquid extraction followed by gas chromatography tandem mass spectrometry.

An efficient and selective automated analytical method for the determination and quantification of a selected group of 12 organochlorine and organophosphorous pesticides in milk-based infant formulas has been developed. The samples were extracted by pressurized liquid extraction (PLE) and analysed using GC-MS/MS. The use of alumina as the fat retainer in the PLE extraction cell, together with the application of an injector temperature program during the GC injection process, avoided typical matrix interferences without the application of additional cleanup steps. Mean recoveries of between 70 and 110% were achieved for most of the compounds, except for chlorpyrifos methyl (50%), vinclozoline (48%), fenitrothion (56%) and procymidone (53%), with relative standard deviations ranging from 9 to 17%. Low limits of quantification were obtained for the studied compounds, from 0.01 to 2.6 microg kg(-1), thus guaranteeing their accurate determination within the rigorous requirements established for baby food. The validated method was applied to a pilot monitoring study in Spain. Twenty five samples of different brands of powdered infant formulas were obtained from supermarkets. Positive findings of endosulfan I, endosulfan II, fenitrothion, chlorpyrifos ethyl and bifenthrin were detected at concentrations ranging from 0.03 to 5.03 microg kg(-1).

Application of high-performance liquid chromatography-tandem mass spectrometry with a quadrupole/linear ion trap instrument for the analysis of pesticide residues in olive oil.

This article describes the development of an enhanced liquid chromatography-mass spectrometry (LC-MS) method for the analysis of pesticides in olive oil. One hundred pesticides belonging to different classes and that are currently used in agriculture have been included in this method. The LC-MS method was developed using a hybrid quadrupole/linear ion trap (QqQ(LIT)) analyzer. Key features of this technique are the rapid scan acquisition times, high specificity and high sensitivity it enables when the multiple reaction monitoring (MRM) mode or the linear ion-trap operational mode is employed. The application of 5 ms dwell times using a linearly accelerating (LINAC) high-pressure collision cell enabled the analysis of a high number of pesticides, with enough data points acquired for optimal peak definition in MRM operation mode and for satisfactory quantitative determinations to be made. The method quantifies over a linear dynamic range of LOQs (0.03-10 microg kg(-1)) up to 500 microg kg(-1). Matrix effects were evaluated by comparing the slopes of matrix-matched and solvent-based calibration curves. Weak suppression or enhancement of signals was observed (<15% for most-80-of the pesticides). A study to assess the identification criteria based on the MRM ratio was carried out by comparing the variations observed in standard vs matrix (in terms of coefficient of variation, CV%) and within the linear range of concentrations studied. The CV was lower than 15% when the response observed in solvent was compared to that in olive oil. The limit of detection was < or =10 microg kg(-1) for five of the selected pesticides, < or =5 microg kg(-1) for 14, and < or =1 microg kg(-1) for 81 pesticides. For pesticides where additional structural information was necessary for confirmatory purposes-in particular at low concentrations, since the second transition could not be detected-survey scans for enhanced product ion (EPI) and MS3 were developed.

Development of a solid surface fluorescence-based sensing system for aluminium monitoring in drinking water.

A novel, single and robust solid surface fluorescence-based sensing device assembled in a continuous flow system has been developed for the determination of trace amounts of aluminium in water samples. The proposed method is based on the transient immobilization of the target species on an appropriate active solid sensing zone (C(18) silica gel). The target species was the fluorogenic chelate, formed as a result of the on-line complexation of Al(III) with chromotropic acid (CA) at pH 4.1. The fluorescence of the complex is continuously monitored at an emission wavelength of 390nm upon excitation at 361nm. The instrumental, chemical and flow-injection variables affecting the fluorescence signal were carefully investigated and optimized. After selecting the most suitable conditions, the sensing system was calibrated in the range 10-500mugl(-1), obtaining a detection limit of 2.6mugl(-1), and a R.S.D. of 2.2%, with a sampling frequency of 24h(-1). In addition, the selectivity of the proposed methodology was evaluated by performing interference studies with different cations and anions which could affect the analytical response. Finally, the proposed method, which meets the EU regulations regarding the aluminium content in drinking waters, was satisfactorily applied to different water samples, with recoveries between 97 and 105%. The simplicity, low cost and easy operation are the main advantages of the present procedure.

Solid-phase ultraviolet sensing system for determination of methylxanthines.

In this study the use of a single continuous-flow solid-phase UV spectrophotometric sensing system for determination of methylxanthines was evaluated. Two methods were developed to determine caffeine (CF) and theophylline (TP) in pharmaceuticals and CF and theobromine (TB) in food and beverages. The sensor is based on transient and sequential retention of the analytes on a hydrophobic sensing solid zone (octadecyl silane C18 gel) and detection of their intrinsic UV absorbance. Temporary sequencing of the arrival of the analytes at the sensing zone is achieved by on-line separation of one of the analytes using a pre-column of the same particulate material, placed just before the flow cell. After TB or TP had been carried toward the sensing zone (by the appropriate carrier solution), produced its transitory signal, and been eluted by the carrier, an appropriate eluting solution (25% MeOH) was used to elute CF, which was strongly retained on the minicolumn, so that its transient signal could be recorded. The sensing zone was completely regenerated with this eluting solution, and so was ready for analysis of another sample. After selecting the most suitable conditions, the sensing system was calibrated in the range 1-16 and 1-12 mg L(-1) for CF and TP-TB, respectively, giving detection limits below 0.1 mg L(-1) with RSD values less than 3%. The usefulness of this approach has been evaluated by applying it to the determination of caffeine, theobromine, and theophylline in different samples of food, beverages, and pharmaceutical formulations. The results were in satisfactory agreement with those obtained by use of an HPLC reference method.

Multiwavelength fluorescence based optosensor for simultaneous determination of fuberidazole, carbaryl and benomyl.

In the present work, a novel approach is proposed for the simultaneous determination of three widely used pesticides (namely, fuberidazole (FBZ), carbaryl (CBL) and benomyl (BNM)). The proposed method is based on a single continuous-flow solid surface fluorimetric multi-optosensor implemented with the use of a minicolumn placed just before the flow-through cell and filled with C(18) silica gel. The three pesticides are determined from an only injection (simultaneous determination): the minicolumn strongly retains two of them while the third develops a transitory signal when passing through the sensing solid microzone. Then, two alternate eluting solutions appropriately selected perform the sequential elution of the two pesticides from the minicolumn, achieving the detection zone and developing their transitory signals. The proposed optosensor works under optimal sensitivity conditions for all the three analytes because of the use of multi-wavelength fluorescence detection mode, so recording three different signals corresponding at three pairs of optima excitation/emission wavelengths. Using a sample volume of 2100mul, the system was calibrated in the range 0.5-15, 40-800 and 50-1000mugl(-1) with detection limits of 0.09, 6 and 9mugl(-1) for FBZ, CBL and BNM, respectively. The R.S.D values (n=10) were lower than 2% in all cases. The proposed methodology was applied satisfactorily to water samples. Recovery percentages ranging from 97.8 to 101.1%, 97.9 to 103% and from 97 to 105% for FBZ, CBL and BNM, respectively, were obtained.

Continuous-flow separation and pre-concentration coupled on-line to solid-surface fluorescence spectroscopy for the simultaneous determination of o-phenylphenol and thiabendazole.

A novel and single flow-injection system combined with solid-surface fluorescence detection is proposed in this work for the resolution of a mixture of two widely used pesticides (o-phenylphenol and thiabendazole). The continuous-flow methodology is based on the implementation of on-line pre-concentration and separation of both analytes on the surface of C18 silica gel beads placed just inside the flow cell, implemented with gel-phase fluorimetric multi-wavelength detection (using 305/358 and 250/345 nm as excitation/emission wavelengths for thiabendazole and o-phenylphenol, respectively). The separation of the pesticides was possible owing to the different retention/desorption kinetics of their interactions with the solid support in the zone where the stream impinges on the solid material. No previous separation of the analytes before they reach the flow cell is needed thereby simplifying substantially both the procedure and the manifold. By using a sample volume of 2,600 microL, the system was calibrated in the range 0.5-16 and 5-120 ng mL(-1) with detection limits of 0.09 and 0.60 ng mL(-1) for thiabendazole and o-phenylphenol, respectively. The RSD values (n=10) were about 1% for both analytes. The proposed methodology was applied to environmental water samples and also to various commercial pesticide formulations containing both analytes. Recovery percentages were 97-103% and 98-102% for thiabendazole and o-phenylphenol, respectively.