Estimation of Mortalities

If a linear regression is fit to log-transformed mortalities and the estimate is back-transformed according to the formula Ee^Y = e^{\mu + \sigma^2/2} a systematic bias occurs unless the error distribution is normal and the scale estimate is gauged to normal variance. This result is a consequence of the uniqueness theorem for the Laplace transform. We determine the systematic bias of minimum-L_2 and minimum-L_1 estimation with sample variance and interquartile range of the residuals as scale estimates under a uniform and four contaminated normal error distributions. Already under innocent looking contaminations the true mortalities may be underestimated by 50% in the long run. Moreover, the logarithmic transformation introduces an instability into the model that results in a large discrepancy between rg_Huber estimates as the tuning constant regulating the degree of robustness varies. Contrary to the logarithm the square root stabilizes variance, diminishes the influence of outliers, automatically copes with observed zeros, allows the `nonparametric' back-transformation formula E Y^2 = \mue^2 + \sigma^2, and in the homoskedastic case avoids a systematic bias of minimum-L_2 estimation with sample variance. For the company-specific table 3 of [Loeb94], in the age range of 20-65 years, we fit a parabola to root mortalities by minimum-L_2 , minimum-L_1, and robust rg_Huber regression estimates, and a cubic and exponential by least squares. The fits thus obtained in the original model are excellent and practically indistinguishable by a \chi^2 goodness-of-fit test. Finally , dispensing with the transformation of observations, we employ a Poisson generalized linear model and fit an exponential and a cubic by maximum likelihood

A study of the production of pullulan by Aureobasidium pullulans

Nanotechnology is proving to play a major role in the future of biomedical applications such as drug delivery, gene therapy and cell imaging/tracking, in particular the use of nanoparticles is regularly highlighted. However with regards to nanoparticles, direct intracellular and intranuclear delivery has, until recently, been difficult to achieve due to the impermeable nature of the plasma and nuclear membranes. The advent of cell penetrating peptides being employed as delivery vectors has opened up many avenues with respect to targeted delivery systems. In this paper, quantum dots were synthesised and functionalised with the HIV-1 tat peptide, and uptake into human bone marrow derived cell populations was assessed. Results demonstrated an increase in uptake for tat modified quantum dots, possibly via a different mechanism to non-modified dots

Protein and metal cluster structure of the wheat metallothionein domain gamma-Ec-1: the second part of the puzzle

Metallothioneins (MTs) are small cysteine-rich proteins coordinating various transition metal ions, including ZnII, CdII, and CuI. MTs are ubiquitously present in all phyla, indicating a successful molecular concept for metal ion binding in all organisms. The plant MT Ec-1 from Triticum aestivum, common bread wheat, is a ZnII- binding protein that comprises two domains and binds up to six metal ions. The structure of the C-terminal four metal ion binding beta-E domain was recently described. Here we present the structure of the N-terminal second domain, gama-Ec-1, determined by NMR spectroscopy. The gamma-Ec-1 domain enfolds an MIICys cluster and was characterized as part of the full-length Zn6Ec-1 protein as well as in the form of the separately expressed domain, both in the ZnII-containing isoform and the CdII-containing isoform. Extended X-ray absorption fine structure analysis of Zn2g- Ec-1 clearly shows the presence of a ZnS4 coordination sphere with average Zn–S distances of 2.33 A ̊. 113Cd NMR experiments were used to identify the MII-Cys connectivity pattern, and revealed two putative metal cluster conformations. In addition, the general metal ion coordination abilities of g-Ec-1 were probed with CdII binding experiments as well as by pH titrations of the ZnII and CdII forms, the latter suggesting an interaction of the c domain and the bE domain within the full-length protein

Structural features specific to plant metallothioneins

The metallothionein (MT) superfamily combines a large variety of small cysteine-rich proteins from nearly all phyla of life that have the ability to coordinate various transition metal ions, including Zn(II), Cd(II), and Cu(I). The members of the plant MT family are characterized by great sequence diversity, requiring further subdivision into four subfamilies. Very peculiar and not well understood is the presence of rather long cysteine-free amino acid linkers between the cysteine-rich regions. In light of the distinct differences in sequence to MTs from other families, it seems obvious to assume that these differences will also be manifested on the structural level. This was already impressively demonstrated with the elucidation of the three-dimensional structure of the wheat E(c)-1 MT, which revealed two metal cluster arrangements previously unprecedented for any MT. However, as this structure is so far the only one available for the plant MT family, other sources of information are in high demand. In this review the focus is thus set on any structural features known, deduced, or assumed for the plant MT proteins. This includes the determination of secondary structural elements by circular dichroism, IR, and Raman spectroscopy, the analysis of the influence of the long linker regions, and the evaluation of the spatial arrangement of the sequence separated cysteine-rich regions with the aid of, e.g., limited proteolytic digestion. In addition, special attention is paid to the contents of divalent metal ions as the metal ion to cysteine ratios are important for predicting and understanding possible metal-thiolate cluster structures