Genetic epidemiology of childhood brain tumors

A rare familial cancer syndrome involving childhood brain tumors (CBT), breast cancer, sarcomas and an array of other tumors has been described (Li and Fraumeni 1969, 1975, 1982, 1987). A survey of CBT identified through the Connnecticut Tumor Registry in 1984 revealed a high frequency of CBT, leukemia and other childhood cancer in siblings of CBT patients (Farwell and Flannery, 1984). Other syndromes such as neurofibromatosis and nevoid basal cell carcinoma syndrome have also been associated with CBT; however, no systematic family studies have been conducted to determine the extent to which cancer aggregates in family members of CBT patients. This family study was designed to determine the frequency of cancer aggregation overall or at specific sites, to determine the frequency of known or potentially hereditary syndromes in families of CBT patients, and to determine a genetic model to characterize familial cancer syndromes and to identify specific kindreds to which such a model(s) might apply. This study includes 244 confirmed CBT patients referred to the University of Texas M. D. Anderson Cancer Center between the years 1944 and 1983, diagnosed under the age of 15 years and resident in the U.S. or Canada. Family histories were obtained on the proband's first (parents, siblings and offspring) and second degree (proband's aunts, uncles and grandparents) relatives following sequential sampling scheme rules. To determine if cancer aggregates in families, we compared the cancer experience in the population to that expected in the general population using Connecticut Tumor Registry calendar year, age, race and sex-specific rates. The standardized incidence ratio (SIR) for cancer overall was 0.91 (41 observed (O) and 44.94 expected (E); 95% Confidence Interval (CI) = 0.65-1.24). We observed a significant excess of colon cancer among the proband's first degree relatives (O/E = 5/1.64; 95% CI = 1.01-7.65), in particular those under age 45 year. Segregation analysis showed evidence for multifactorial inheritance in the small percentage (N = 5) of the families. ^

Determination of picloram in waters by sequential injection chromatography with UV detection

This paper describes a sequential injection chromatography procedure for determination of picloram in waters exploring the low backpressure of a 2.5 cm long monolithic C18 column. Separation of the analyte from the matrix was achieved in less than 60 s using a mobile phase composed by 20:80 (v v-1) acetonitrile:5.0 mmol L-1 H3PO4 and flow rate of 30 μL s-1. Detection was made at 223 nm with a 40 mm optical path length cell. The limits of detection and quantification were 33 and 137 μg L-1, respectively. The proposed method is sensitive enough to monitor the maximum concentration level for picloram in drinking water (500 μg L-1). The sampling frequency is 60 analyses per hour, consuming only 300 μL of acetonitrile per analysis. The proposed methodology was applied to spiked river water samples and no statistically significant differences were observed in comparison to a conventional HPLC-UV method.

Sequential spectrofluorimetric determination of free and total glycerol in biodiesel in a multicommuted flow system

A new procedure for spectrofluorimetric determination of free and total glycerol in biodiesel samples is presented. It is based on the oxidation of glycerol by periodate, forming formaldehyde, which reacts with acetylacetone, producing the luminescent 3,5-diacetyl-1,4-dihydrolutidine. A flow system with solenoid micro-pumps is proposed for solution handling. Free glycerol was extracted off-line from biodiesel samples with water, and total glycerol was converted to free glycerol by saponification with sodium ethylate under sonication. For free glycerol, a linear response was observed from 5 to 70 mg L(-1) with a detection limit of 0.5 mg L(-1), which corresponds to 2 mg kg(-1) in biodiesel. The coefficient of variation was 0.9% (20 mg L(-1), n = 10). For total glycerol, samples were diluted on-line, and the linear response range was 25 to 300 mg L(-1). The detection limit was 1.4 mg L(-1) (2.8 mg kg(-1) in biodiesel) with a coefficient of variation of 1.4% (200 mg L(-1), n = 10). The sampling rate was ca. 35 samples h(-1) and the procedure was applied to determination of free and total glycerol in biodiesel samples from soybean, cottonseed, and castor beans.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Sequential injection analysis system with spectrophotometric detection for determination of norfloxacin and ciprofloxacin in pharmaceutical formulations

This work proposes a sequential injection analysis (SIA) system for the spectrophotometric determination of norfloxacin (NOR) and ciprofloxacin (CIP) in pharmaceutical formulations. The methodology was based on the reaction of these drugs with p-(dimethylamino)cinnamaldehyde in micellar medium, producing orange colored products (λmax = 495 nm). Beer´s law was obeyed in the concentration range from 2.75x10-5 to 3.44x10-4 mol L-1 and 3.26x10-5 to 3.54x10-4 mol L-1 for NOR and CIP, respectively and sampling rate was 25 h-1. Commercial samples were analyzed and results obtained through the proposed method were in good agreement with those obtained using the reference procedure for a 95% confidence level.

Sequential Optimal Recovery: A Paradigm for Active Learning

In most classical frameworks for learning from examples, it is assumed that examples are randomly drawn and presented to the learner. In this paper, we consider the possibility of a more active learner who is allowed to choose his/her own examples. Our investigations are carried out in a function approximation setting. In particular, using arguments from optimal recovery (Micchelli and Rivlin, 1976), we develop an adaptive sampling strategy (equivalent to adaptive approximation) for arbitrary approximation schemes. We provide a general formulation of the problem and show how it can be regarded as sequential optimal recovery. We demonstrate the application of this general formulation to two special cases of functions on the real line 1) monotonically increasing functions and 2) functions with bounded derivative. An extensive investigation of the sample complexity of approximating these functions is conducted yielding both theoretical and empirical results on test functions. Our theoretical results (stated insPAC-style), along with the simulations demonstrate the superiority of our active scheme over both passive learning as well as classical optimal recovery. The analysis of active function approximation is conducted in a worst-case setting, in contrast with other Bayesian paradigms obtained from optimal design (Mackay, 1992).

Development of a sequential injection-square wave voltammetry method for determination of paraquat in water samples employing the hanging mercury drop electrode

This work describes the development and optimization of a sequential injection method to automate the determination of paraquat by square-wave voltammetry employing a hanging mercury drop electrode. Automation by sequential injection enhanced the sampling throughput, improving the sensitivity and precision of the measurements as a consequence of the highly reproducible and efficient conditions of mass transport of the analyte toward the electrode surface. For instance, 212 analyses can be made per hour if the sample/standard solution is prepared off-line and the sequential injection system is used just to inject the solution towards the flow cell. In-line sample conditioning reduces the sampling frequency to 44 h(-1). Experiments were performed in 0.10 M NaCl, which was the carrier solution, using a frequency of 200 Hz, a pulse height of 25 mV, a potential step of 2 mV, and a flow rate of 100 mu L s(-1). For a concentration range between 0.010 and 0.25 mg L(-1), the current (i(p), mu A) read at the potential corresponding to the peak maximum fitted the following linear equation with the paraquat concentration (mg L(-1)): ip = (-20.5 +/- 0.3) Cparaquat -(0.02 +/- 0.03). The limits of detection and quantification were 2.0 and 7.0 mu g L(-1), respectively. The accuracy of the method was evaluated by recovery studies using spiked water samples that were also analyzed by molecular absorption spectrophotometry after reduction of paraquat with sodium dithionite in an alkaline medium. No evidence of statistically significant differences between the two methods was observed at the 95% confidence level.

Developing a fluorimetric sequential injection methodology to study adsorption/desorption of glyphosate on soil and sediment samples

This paper describes the development of a sequential injection method to automate the fluorimetric determination of glyphosate based on a first step of oxidation to glycine by hypochlorite at 48 degrees C, followed by reaction with the fluorogenic reagent o-phthaldialdehyde in presence of 2-mercaptoethanol in borate buffer (pH > 9) to produce a fluorescent 1-(2`-hydroxyethylthio)-2-N-alkylisoindole. The proposed method has a linear response for glyphosate concentrations between 0.25 and 25.0 mu mol L(-1), with limits of detection and quantification of 0.08 and 0.25 mu mol L(-1), respectively. The sampling rate of the method is 18 samples per hour, consuming only a fraction of reagents consumed by the chromatographic method based on the same chemistry. The method was applied to study adsorption/desorption properties in a soil and in a sediment sample. Adsorption and desorption isotherms were properly fitted by Freundlich and Langmuir equations, leading to adsorption capacities of 1384 +/- 26 and 295 +/- 30 mg kg(-1) for the soil and sediment samples, respectively. These values are consistent with the literature, with the larger adsorption capacity of the soil being explained by its larger content of clay minerals, while the sediment was predominantly sandy. (C) 2011 Elsevier B.V. All rights reserved.

Development of a sequential injection chromatography (SIC) method for determination of simazine, atrazine, and propazine

This paper describes the development of a sequential injection chromatography (SIC) procedure for separation and quantification of the herbicides simazine, atrazine, and propazine exploring the low backpressure of a 2.5 cm long monolithic C(18) column. The separation of the three compounds was achieved in less than 90 s with resolution > 1.5 using a mobile phase composed by ACN/1.25 mmol/L acetate buffer (pH 4.5) at the volumetric ratio of 35:65 and flow rate of 40 mu L/s. Detection was made at 223 nm using a flow cell with 40 mm of optical path length. The LOD was 10 mu g/L for the three triazines and the quantification limits were of 30 mu g/L for simazine and propazine and 40 mu g/L for atrazine. The sampling frequency is 27 samples per hour, consuming 1.1 mL of ACN per analysis. The proposed methodology was applied to spiked water samples and no statistically significant differences were observed in comparison to a conventional HPLC-UV method. The major metabolites of atrazine and other herbicides did not interfere in the analysis, being eluted from the column either together with the unretained peak, or at retention times well-resolved from the studied compounds.

Applying sequential injection analysis (SIA) and response surface methodology for optimization of Fenton-based processes

This work presents the use of sequential injection analysis (SIA) and the response surface methodology as a tool for optimization of Fenton-based processes. Alizarin red S dye (C.I. 58005) was used as a model compound for the anthraquinones family. whose pigments have a large use in coatings industry. The following factors were considered: [H(2)O(2)]:[Alizarin] and [H(2)O(2)]:[FeSO(4)] ratios and pH. The SIA system was designed to add reagents to the reactor and to perform on-line sampling of the reaction medium, sending the samples to a flow-through spectrophotometer for monitoring the color reduction of the dye. The proposed system fed the statistical program with degradation data for fast construction of response surface plots. After optimization, 99.7% of the dye was degraded and the TOC content was reduced to 35% of the original value. Low reagents consumption and high sampling throughput were the remarkable features of the SIA system. (C) 2008 Published by Elsevier B.V.

Square wave adsorptive cathodic stripping voltarnmetry automated by sequential injection analysis - Potentialities and limitations exemplified by the determination of methyl parathion in water samples

This paper describes the development and evaluation of a sequential injection method to automate the determination of methyl parathion by square wave adsorptive cathodic stripping voltammetry exploiting the concept of monosegmented flow analysis to perform in-line sample conditioning and standard addition. Accumulation and stripping steps are made in the sample medium conditioned with 40 mmol L-1 Britton-Robinson buffer (pH 10) in 0.25 mol L-1 NaNO3. The homogenized mixture is injected at a flow rate of 10 mu Ls(-1) toward the flow cell, which is adapted to the capillary of a hanging drop mercury electrode. After a suitable deposition time, the flow is stopped and the potential is scanned from -0.3 to -1.0 V versus Ag/AgCl at frequency of 250 Hz and pulse height of 25 mV The linear dynamic range is observed for methyl parathion concentrations between 0.010 and 0.50 mgL(-1), with detection and quantification limits of 2 and 7 mu gL(-1), respectively. The sampling throughput is 25 h(-1) if the in line standard addition and sample conditioning protocols are followed, but this frequency can be increased up to 61 h(-1) if the sample is conditioned off-line and quantified using an external calibration curve. The method was applied for determination of methyl parathion in spiked water samples and the accuracy was evaluated either by comparison to high performance liquid chromatography with UV detection, or by the recovery percentages. Although no evidences of statistically significant differences were observed between the expected and obtained concentrations, because of the susceptibility of the method to interference by other pesticides (e.g., parathion, dichlorvos) and natural organic matter (e.g., fulvic and humic acids), isolation of the analyte may be required when more complex sample matrices are encountered. (C) 2007 Elsevier B.V. All rights reserved.

Sequential injection analysis system with spectrophotometric detection for determination of norfloxacin and ciprofloxacin in pharmaceutical formulations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Phosphite determination in fertilizers after online sequential sample preparation in a flow injection system

A flow injection spectrophotometric system is proposed for phosphite determination in fertilizers by the molybdenum blue method after the processing of each sample two times on-line without and with an oxidizing step. The flow system was designed to add sulfuric acid or permanganate solutions alternately into the system by simply displacing the injector-commutator from one resting position to another, allowing the determination of phosphate and total phosphate, respectively. The concentration of phosphite is obtained then by difference between the two measurents. The influence of flow rates, sample volume, and dimension of flow line connecting the injector-commutator to the main analytical channel was evaluated. The proposed method was applied to phosphite determination in commercial liquid fertilizers. Results obtained with the proposed FIA system were not statistically different from those obtained by titrimetry at the 95% confidence level. In addition, recoveries within 94 and 100% of spiked fertilizers were found. The relative standard deviation (n = 12) related to the phosphite-converted-phosphate peak alone was <= 3.5% for 800 mg L-1 P (phoshite) solution. Precision due to the differences of total phosphate and phosphate was 1.1% for 10 mg L-1 P (phosphate) + 3000 mg L-1 P (phosphite) solution. The sampling rate was calculated as 15 determinations per hour, and the reagent consumption was about 6.3 mg of KMnO4, 200 mg of (NH4)(6)Mo7O24 center dot 4H(2)O, and 40 mg of ascorbic acid per measurement.

KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging

Several strategies relying on kriging have recently been proposed for adaptively estimating contour lines and excursion sets of functions under severely limited evaluation budget. The recently released R package KrigInv 3 is presented and offers a sound implementation of various sampling criteria for those kinds of inverse problems. KrigInv is based on the DiceKriging package, and thus benefits from a number of options concerning the underlying kriging models. Six implemented sampling criteria are detailed in a tutorial and illustrated with graphical examples. Different functionalities of KrigInv are gradually explained. Additionally, two recently proposed criteria for batch-sequential inversion are presented, enabling advanced users to distribute function evaluations in parallel on clusters or clouds of machines. Finally, auxiliary problems are discussed. These include the fine tuning of numerical integration and optimization procedures used within the computation and the optimization of the considered criteria.

Estimation of a probability in inverse binomial sampling under normalized linear-linear and inverse-linear loss

Sequential estimation of the success probability p in inverse binomial sampling is considered in this paper. For any estimator pˆ , its quality is measured by the risk associated with normalized loss functions of linear-linear or inverse-linear form. These functions are possibly asymmetric, with arbitrary slope parameters a and b for pˆ

p , respectively. Interest in these functions is motivated by their significance and potential uses, which are briefly discussed. Estimators are given for which the risk has an asymptotic value as p→0, and which guarantee that, for any p∈(0,1), the risk is lower than its asymptotic value. This allows selecting the required number of successes, r, to meet a prescribed quality irrespective of the unknown p. In addition, the proposed estimators are shown to be approximately minimax when a/b does not deviate too much from 1, and asymptotically minimax as r→∞ when a=b.