Generalized Log-Normal Chain-Ladder

We propose an asymptotic theory for distribution forecasting from the log normal chain-ladder model. The theory overcomes the difficulty of convoluting log normal variables and takes estimation error into account. The results differ from that of the over-dispersed Poisson model and from the chain-ladder based bootstrap. We embed the log normal chain-ladder model in a class of infinitely divisible distributions called the generalized log normal chain-ladder model. The asymptotic theory uses small $\sigma$ asymptotics where the dimension of the reserving triangle is kept fixed while the standard deviation is assumed to decrease. The resulting asymptotic forecast distributions follow t distributions. The theory is supported by simulations and an empirical application

Functional interaction between Epstein-Barr virus replication protein Zta and host DNA damage response protein 53BP1

Epstein-Barr virus (EBV; human herpesvirus 4) poses major clinical problems worldwide. Following primary infection, EBV enters a form of long-lived latency in B lymphocytes, expressing few viral genes, and it persists for the lifetime of the host with sporadic bursts of viral replication. The switch between latency and replication is governed by the action of a multifunctional viral protein Zta (also called BZLF1, ZEBRA, and Z). Using a global proteomic approach, we identified a host DNA damage repair protein that specifically interacts with Zta: 53BP1. 53BP1 is intimately connected with the ATM signal transduction pathway, which is activated during EBV replication. The interaction of 53BP1 with Zta requires the C-terminal ends of both proteins. A series of Zta mutants that show a wild-type ability to perform basic functions of Zta, such as dimer formation, interaction with DNA, and the transactivation of viral genes, were shown to have lost the ability to induce the viral lytic cycle. Each of these mutants also is compromised in the C-terminal region for interaction with 53BP1. In addition, the knockdown of 53BP1 expression reduced viral replication, suggesting that the association between Zta and 53BP1 is involved in the viral replication cycle

Analysis of the three most prevalent injuries in Australian football demonstrates a season to season association between groin/hip/ osteitis pubis injuries with ACL knee injuries

BACKGROUND: Injuries are common in contact sports like Australian football. The Australian Football League (AFL) has developed an extensive injury surveillance database that can be used for epidemiological studies. OBJECTIVES: The purpose of this study is to identify any association between the three most prevalent injuries in the AFL. PATIENTS AND METHODS: From the AFL injury surveillance data 1997-2012 the injury incidence (new injuries per club per season) and the injury prevalence data (missed games per club per season) were analysed to detect the three most common injuries that would cause a player to miss a match in the AFL. The three most prevalent injuries in the AFL are hamstring strains, groin/hip/osteitis pubis injuries and Anterior Cruciate Ligament (ACL) knee injuries. Following this, further study was undertaken to detect the presence of any statistical relationship between injury incidences of the three most prevalent injuries over this sixteen year study period. RESULTS: Statistical analysis demonstrates for any given year that there was an association between having a groin/hip/osteitis pubis injuriy and having a knee ACL injury (P < 0.05) over the entire sixteen years. In other words if the number of groin/hip/osteitis pubis injuries in any given season were higher than average (alternatively lower) then the number of knee ACL injuries were also higher than average (alternatively lower) for that same season. Hamstring injuries had the highest variance of incidence of the three most prevalent injuries. CONCLUSIONS: Analysis of the AFL injury data demonstrates an association between incidence of groin/hip/osteitis pubis injuries and incidence of knee ACL injuries for any given playing season. This finding is difficult to explain with further research being required.Geoffrey M. Verral, Adrian Esterman, Timothy E. Hewet

Tissues and industrial co-products formed during alginate extraction from <i>Laminaria hyperborea</i> provide different metabolite profiles depending on harvest season

The metabolic profiles of different tissues and industrially relevant co-products of alginate extraction from Laminaria hyperborea samples harvested in different seasons were assessed using Hydrophilic Interaction Liquid Chromatography – Mass Spectrometry (HILIC-MS). Positive and negative mode MS data, predicted exact mass data and matching with database and literature searches, allowed the putative identification of 57 major metabolites. The metabolites ranged from known and abundant components (e.g., iodide, mannitol, and various betaines) to components not previously noted in this species and 11 major components which could not be identified. The levels of these components varied between tissues and co-products with some metabolites seemingly specific to certain samples. The components also varied between winter and summer harvested material, perhaps reflecting seasonality in their biosynthesis and accumulation in the tissues and co-products. The approach applied in this work could assess when components of potential specific commercial interest were maximally accumulated and help plan the most efficient exploitation of the harvested biomass. It could also be used to define variation in components in L. hyperborea from different locations or potential biotopes of this species. This initial work extends our ability to understand the phenotype of seaweeds whilst also identifying new components and new commercial opportunities

Quantitative trait loci mapping of polyphenol metabolites from a 'Latham' x 'Glen Moy' red raspberry (<i>Rubus idaeus L</i>) cross

Objective: The objective of this study was to investigate the genetic control of polyphenol accumulation in red raspberry (Rubus idaeus L).Methods: The levels of total anthocyanins and 37 individual polyphenol metabolites were measured over three years in a raspberry biparental mapping population. Quantitative trait loci (QTLs) for these traits were mapped onto a high-density SNP linkage map.Results: At least one QTL was detected for each trait, with good consistency among the years. On four linkage groups (LG), there were major QTLs affecting several metabolites. On LG1, a QTL had large effects on anthocyanins and flavonols containing a rutinoside or rhamnose group. On LG4, a QTL had large effects on several flavonols and on LG5 and LG6 QTLs had large effects on ellagic acid derivatives. Smaller QTLs were found on LG2 and LG3.Conclusion: The identification of robust QTLs for key polyphenols in raspberry provides great potential for marker-assisted breeding for improved levels of potentially health beneficial components.</p

Distribution of Metals in the Termite Tumulitermes tumuli (Froggatt): Two Types of Malpighian Tubule Concretion Host Zn and Ca Mutually Exclusively

The aim of this study was to determine specific distribution of metals in the termite Tumulitermes tumuli (Froggatt) and identify specific organs within the termite that host elevated metals and therefore play an important role in the regulation and transfer of these back into the environment. Like other insects, termites bio-accumulate essential metals to reinforce cuticular structures and utilize storage detoxification for other metals including Ca, P, Mg and K. Previously, Mn and Zn have been found concentrated in mandible tips and are associated with increased hardness whereas Ca, P, Mg and K are accumulated in Malpighian tubules. Using high resolution Particle Induced X-Ray Emission (PIXE) mapping of whole termites and Scanning Electron Microscope (SEM) Energy Dispersive X-ray (EDX) spot analysis, localised accumulations of metals in the termite T. tumuli were identified. Tumulitermes tumuli was found to have proportionally high Mn concentrations in mandible tips. Malpighian tubules had significant enrichment of Zn (1.6%), Mg (4.9%), P (6.8%), Ca (2.7%) and K (2.4%). Synchrotron scanning X-ray Fluorescence Microprobe (XFM) mapping demonstrated two different concretion types defined by the mutually exclusive presence of Ca and Zn. In-situ SEM EDX realisation of these concretions is problematic due to the excitation volume caused by operating conditions required to detect minor amounts of Zn in the presence of significant amounts of Na. For this reason, previous researchers have not demonstrated this surprising finding

Methylated DNA recognition during the reversal of epigenetic silencing is regulated by cysteine and cerine residues in the Epstein-Barr Virus lytic switch protein

Epstein-Barr virus (EBV) causes infectious mononucleosis and is associated with various malignancies, including Burkitt's lymphoma and nasopharyngeal carcinoma. Like all herpesviruses, the EBV life cycle alternates between latency and lytic replication. During latency, the viral genome is largely silenced by host-driven methylation of CpG motifs and, in the switch to the lytic cycle, this epigenetic silencing is overturned. A key event is the activation of the viral BRLF1 gene by the immediate-early protein Zta. Zta is a bZIP transcription factor that preferentially binds to specific response elements (ZREs) in the BRLF1 promoter (Rp) when these elements are methylated. Zta's ability to trigger lytic cycle activation is severely compromised when a cysteine residue in its bZIP domain is mutated to serine (C189S), but the molecular basis for this effect is unknown. Here we show that the C189S mutant is defective for activating Rp in a Burkitt's lymphoma cell line. The mutant is compromised both in vitro and in vivo for binding two methylated ZREs in Rp (ZRE2 and ZRE3), although the effect is striking only for ZRE3. Molecular modeling of Zta bound to methylated ZRE3, together with biochemical data, indicate that C189 directly contacts one of the two methyl cytosines within a specific CpG motif. The motif's second methyl cytosine (on the complementary DNA strand) is predicted to contact S186, a residue known to regulate methyl-ZRE recognition. Our results suggest that C189 regulates the enhanced interaction of Zta with methylated DNA in overturning the epigenetic control of viral latency. As C189 is conserved in many bZIP proteins, the selectivity of Zta for methylated DNA may be a paradigm for a more general phenomenon

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