Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part II

This is the part II of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC–MS) and discuss specific issues that arise with MS (and MS–MS) detection in LC (as opposed to the “conventional” detectors). The Part II starts with briefly introducing the main quantitation methods and then addresses the performance related to quantification: linearity of signal, sensitivity, precision, trueness, accuracy, stability and measurement uncertainty. The last section is devoted to practical considerations in validation. With every performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to handle it, specifically in the case of LC–MS methods.     

Resource allocation based on cost efficiency

In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi-objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical examples and an empirical illustration are also provided.     

Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part I

This is the part I of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC–MS) and discuss specific issues that arise with MS (and MS/MS) detection in LC (as opposed to the “conventional” detectors). The Part I briefly introduces the principles of operation of LC–MS (emphasizing the aspects important from the validation point of view, in particular the ionization process and ionization suppression/enhancement); reviews the main validation guideline documents and discusses in detail the following performance parameters: selectivity/specificity/identity, ruggedness/robustness, limit of detection, limit of quantification, decision limit and detection capability. With every method performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to determine it, specifically in the case of LC–MS methods.     

On the Extreme Oxidation States of Iridium

It has recently been suggested that the oxidation states of Ir run from the putative ?III in the synthesized solid Na₃[Ir(CO)₃] to the well‐documented +IX in the species IrO₄⁺. Furthermore, [Ir(CO)₃]^3? was identified as an 18‐electron species. A closer DFT study now finds support for this picture: The orbitals spanned by the 6s,6p,5d orbitals of the iridium are all occupied. Although some have considerable ligand character, the deviations from 18 e leave the orbital symmetries unchanged. The isoelectronic systems from Os^?IV to Au^?I behave similarly, suggesting further possible species. To paraphrase Richard P. Feynmann “there is plenty of room at the bottom”.     

Regularity of the Inverse of a Planar Sobolev Homeomorphism

Let be a domain. Suppose that f ∈ W^1,1_loc(Ω,R²) is a homeomorphism such that Df(x) vanishes almost everywhere in the zero set of J_f. We show that f^-1 ∈ W^1,1_loc(f(Ω),R²) and that Df⁻¹(y) vanishes almost everywhere in the zero set of Sharp conditions to quarantee that f⁻¹ ∈ W^1,q(f(Ω),R²) for some 1<q≤2 are also given.     

Dimension gap under Sobolev mappings

We prove an essentially sharp estimate in terms of generalized Hausdorff measures for the images of boundaries of Hölder domains under continuous Sobolev mappings, satisfying suitable Orlicz–Sobolev conditions. This estimate marks a dimension gap, which was first observed in [2] for conformal mappings.     

Alnumycins A2 and A3: new inverse-epimeric pairs stereoisomeric to alnumycin A1

Two new pairs of stereoisomeric alnumycin As, A2 {(2)-(1R,1′RS,4′SR,5′SR)} and A3 {(2)-(1R,1′RS,4′SR,5′RS)}, are described. Similar to alnumycin A1 {(2)-(1R,1′RS,4′RS,5′SR)}, each of these naturally occurring compounds is also a pair of C-1 inverse epimers. The relative configurations of the dioxane ring sidechains were assigned on the basis of ¹H NMR NOE contacts and molecular modeling using density functional theory (DFT) at the M06-2X/6-31G(d) level of theory. The absolute configurations of C-1 and the determination of inverse epimeric relationships were achieved by experimental electronic circular dichroism (ECD) measurements, with both aspects confirmed by using the chiral derivatizing agent (CDA) Mosher′s acid chloride {α-methoxy-α-trifluorophenylacetyl chloride (MTPACl)} to effect enantiodifferentiation. The absolute configurations of the dioxane ring using the CDA could only be effected in the case of alnumycin A1, the results of which were in agreement with previous assignments. The dioxane ring conformational mobility and the likely interaction between the MTPA groups coupled with the structural novelty of the diols in the dioxane ring with respect to CDA analysis precluded an absolute configuration assignment for alnumycins A2 and A3 based on empirical comparisons or by computational analysis of through-space NMR shieldings (TSNMRS) emanating from the phenyl groups of the MTPA moieties.     

Can a linear value function explain choices? An experimental study

We investigate in a simple bi-criteria experimental study, whether subjects are consistent with a linear value function while making binary choices. Many inconsistencies appeared in our experiment. However, the impact of inconsistencies on the linearity vs. non-linearity of the value function was minor. Moreover, a linear value function seems to predict choices for bi-criteria problems quite well. This ability to predict is independent of whether the value function is diagnosed linear or not. Inconsistencies in responses did not necessarily change the original diagnosis of the form of the value function. Our findings have implications for the design and development of decision support tools for Multiple Criteria Decision Making problems.