Immunosorbents: A new tool for pesticide sample handling in environmental analysis

 Immunoaffinity techniques have been widely used for the determination of different analytes in the medical field. However the use of antibodies immobilized in an appropriate support material to preconcentrate pesticides from environmental samples is only recent. The production of antibodies, election of supports, antibody immobilization procedures, elution of analytes from immunosorbents and the more recent applications in the field of pesticide analysis are reviewed. The present review concludes that immunosorbents have great potential and discusses the present limitations and expected future trends. Received: 29 July 1996 / Accepted: 14 August 1996     

Features of the decomposition of the neutral nitrosyl iron complexes with aryl-containing thiolate ligands in various solvents. Reaction with glutathione

The decomposition of two neutral binuclear nitrosyl iron complexes (NICs) of the µ-S structural type and general composition [Fe₂(SR)₂(NO)₄]⁰ was studied in comparison. The exchange reaction of the thiophenol or 2-aminothiophenol thiolate ligand by glutathione (GSH) in neutral NICs was studied. The reaction system was analyzed by spectrophotometry to prove the presence of a new NICs with the GS^– ligand in it. It was found that, unlike the earlier studied binuclear cationic NICs of the µ-S type and general composition [Fe₂(µ-SR)₂(NO)₄]²⁺SO₄?nH₂O with cysteamine and penicillamine ligands in which both thiolate ligands exchange by GS^–, in these neutral complexes both thiolate ligands are de-tached by only one GSH ligand is attached. A water molecule is inserted into the second free site. It is assumed that the antitumor activity of the neutral NICs can be determined not only by their NO-donor activity but also by their ability to exchange the thiolate ligand by GS^–, i.e., "to remove" GSH from the medium as in the case of cationic NICs. The discovered reaction can prevent, most likely, the S-glutathionylation of important metabolites in the presence of GSH and is very significant for metabolism of NICs.     

Quantum chemical modeling of possible reactions of mononuclear iron nitrosyl complex [Fe(SC(NH<Subscript>2</Subscript>)<Subscript>2</Subscript>)<Subscript>2</Subscript>(NO)<Subscript>2</Subscript>]Cl•H<Subscript>2</Subscript>O in an aqueous solution

Possible reactions of the mononuclear iron nitrosyl complex [Fe(SC(NH₂)₂)₂(NO)₂]Сl?H₂O in an aqueous solution were studied using quantum chemical modeling. The electronic structures of the possible intermediates were examined by the NBO and AIM methods. The substitution of the thio ligand in the iron—sulfur nitrosyl complex by a water molecule and the formation of dimeric intermediate complexes were found to facilitate the NO-donation process.     

Online large volume sample staking preconcentration and separation of enantiomeric GHRH analogs by capillary electrophoresis

A capillary electrophoresis method is proposed to analyze the four most well-known growth hormone–releasing hormone (GHRH) analogs that are misused by athletes. Dimethyl-β-cyclodextrin used as a chiral selector allowed, for the first time, the separation of those basic peptide analogs, including enantiopeptides (sermorelin and CJC-1293) that differ by the chirality of only one amino acid. To increase the method sensitivity, electrokinetic preconcentration methods have been investigated. The large volume sample stacking with polarity switching (PS-LVSS) method with an injected sample volume corresponding to 80% of the capillary one was found superior to the sweeping in terms of signal enhancement factor (SEF). Acid and organic solvent addition to the sample (0.1 mM phosphoric acid with 30% methanol) led to a twofold signal improvement, when compared to water as a matrix. We increased capillary dimensions to provide a signal enhancement through the injection of a larger sample volume. Finally, using a combination of the optimized PS-LVSS preconcentration with the chiral capillary zone electrophoresis (CZE), the GHRH analogs were separated and limits of detection between 75 and 200 ng/mL were reached. This method was successfully applied to urine after a desalting step. An optimized C18 SPE was used for that purpose in order to provide low sample conductivity (<130 µS/cm) and preserve the efficiency of LVSS preconcentration. SEF of 640 was obtained with desalted urine spiked with sermorelin by comparison to the CZE (without preconcentration) method.     

On Perturbed Discrete Boundary Value Problems

In this paper, we study nonlinear discrete boundary value problems of the form x ( t +1)= A ( t ) x ( t )+ h ( t )+ k f ( t , x ( t ), k ) subject to Bx (0)+ Dx ( J )= u + k g ( x (0), x ( J ), k ) where k is a "small" parameter. Our main concern is the case of resonance, that is, the situation where the associated linear homogeneous boundary value problem x ( t +1)= A ( t ) x ( t ), Bx (0)+ Dx ( J )=0 admits nontrivial solutions. We establish conditions for the solvability of the nonlinear boundary value problem when k is "small". We also establish qualitative properties of these solutions.     

Principe de densité pour les groupes rèuctifs

The main goal of this Letter is to give a new proof of a result conjectured by D. De George and N. Wallach and proved by P. Deborne and to extend it to the S-arithmetic setting. The proof is based on a density principle.     

New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.     

Protecting the data-driven newsvendor against rare events: a correction-term approach

We propose an approach to the data-driven newsvendor problem that incorporates a correction factor to account for rare events, when the decision-maker has few historical data points at his disposal but knows the range of the demand. This mitigates a weakness of pure data-driven methodologies, specifically, the fact that they under-protect the system against tail events, which are in general under-observed in the empirical demand distribution. We test the approach in extensive computational experiments and provide a summary table of the numerical experiments to help the decision maker gain further insights.     

Limit Theorems for the Maximum Terms of a Sequence of Random Variables with Marginal Geometric Distributions

Let X _n1 ^* , ... X _nn ^* be a sequence of n independent random variables which have a geometric distribution with the parameter p _n = 1/n, and M _n ^* = \max\{X _n1 ^* , ... X _nn ^* }. Let Z ₁, Z₂, Z₃, ... be a sequence of independent random variables with the uniform distribution over the set N _n = {1, 2, ... n}. For each j N _n let us denote X _nj = min{k : Z_k = j}, M _n = max{X_n1, ... X_nn}, and let S _n be the 2nd largest among X _n1, X_n2, ... X_nn. Using the methodology of verifying D(u_n) and D'(u_n) mixing conditions we prove herein that the maximum M _n has the same type I limiting distribution as the maximum M _n ^* and estimate the rate of convergence. The limiting bivariate distribution of (S_n, M_n) is also obtained. Let _n, _n N_n, , and T _n = min{M(A_n), M(B_n)}. We determine herein the limiting distribution of random variable T _n in the case _n , _n/_n > 0, as n .