Analyst Underreaction to Past Information About Earnings: reporting, processing or plain old misspecification bias?

We revisit the debate concerning the interpretation given to prior year’s earnings changes in predicting future earnings as discussed by Abarbanell & Bernard (1992), Francis & Philbrick (1993) and Easterwood and Nutt (1999). We advance a new specification of this relationship which distinguishes between earnings reversion and momentum. On a large UK dataset, we find there is substantial underreaction, particularly in situations of earnings momentum, approximately six times as large as that identified by Abarbanell & Bernard. This suggests that analysts behaviour is still a candidate to explain post earnings announcement drift. We also show that our model performs well relative to a specification recently proposed by Easterwood and Nutt (1999)

Differences in genotype and virulence among four multidrug-resistant <i>Streptococcus pneumoniae</i> isolates belonging to the PMEN1 clone

We report on the comparative genomics and characterization of the virulence phenotypes of four &lt;i&gt;S. pneumoniae&lt;/i&gt; strains that belong to the multidrug resistant clone PMEN1 (Spain&lt;sup&gt;23F&lt;/sup&gt; ST81). Strains SV35-T23 and SV36-T3 were recovered in 1996 from the nasopharynx of patients at an AIDS hospice in New York. Strain SV36-T3 expressed capsule type 3 which is unusual for this clone and represents the product of an in vivo capsular switch event. A third PMEN1 isolate - PN4595-T23 - was recovered in 1996 from the nasopharynx of a child attending day care in Portugal, and a fourth strain - ATCC700669 - was originally isolated from a patient with pneumococcal disease in Spain in 1984. We compared the genomes among four PMEN1 strains and 47 previously sequenced pneumococcal isolates for gene possession differences and allelic variations within core genes. In contrast to the 47 strains - representing a variety of clonal types - the four PMEN1 strains grouped closely together, demonstrating high genomic conservation within this lineage relative to the rest of the species. In the four PMEN1 strains allelic and gene possession differences were clustered into 18 genomic regions including the capsule, the blp bacteriocins, erythromycin resistance, the MM1-2008 prophage and multiple cell wall anchored proteins. In spite of their genomic similarity, the high resolution chinchilla model was able to detect variations in virulence properties of the PMEN1 strains highlighting how small genic or allelic variation can lead to significant changes in pathogenicity and making this set of strains ideal for the identification of novel virulence determinant

Patients with schizophrenia show deficits of working memory maintenance components in circuit-specific tasks

Working memory (WM) deficits are a neuropsychological core finding in patients with schizophrenia and also supposed to be a potential endophenotype of schizophrenia. Yet, there is a large heterogeneity between different WM tasks which is partly due to the lack of process specificity of the tasks applied. Therefore, we investigated WM functioning in patients with schizophrenia using process- and circuit-specific tasks. Thirty-one patients with schizophrenia and 47 controls were tested with respect to different aspects of verbal and visuospatial working memory using modified Sternberg paradigms in a computer-based behavioural experiment. Total group analysis revealed significant impairment of patients with schizophrenia in each of the tested WM components. Furthermore, we were able to identify subgroups of patients showing different patterns of selective deficits. Patients with schizophrenia exhibit specific and, in part, selective WM deficits with indirect but conclusive evidence of dysfunctions of the underlying neural networks. These deficits are present in tasks requiring only maintenance of verbal or visuospatial information. In contrast to a seemingly global working memory deficit, individual analysis revealed differential patterns of working memory impairments in patients with schizophrenia

Energy expenditure during overfeeding

The large inter-individual variation in weight gain during standardized overfeeding together with a weight gain that is often less than theoretically calculated from the energy excess suggest that there are differences between persons in the capacity to regulate energy expenditure and hence metabolic efficiency. Adaptive thermogenesis is defined as the regulated production of heat in response to environmental changes in temperature and diet, resulting in metabolic inefficiency. The question is whether adaptive thermogenesis can be identified in overfeeding experiments. From the numerous human overfeeding experiments we selected those studies that applied suitable protocols and measurement techniques. Five studies claimed to have found evidence for adaptive thermogenesis based on weight gains smaller than expected or unaccounted increases in thermogenesis above obligatory costs. Results from the other 11 studies suggest there is no adaptive thermogenesis as weight gains were proportional to the amount of overfeeding and the increased thermogenesis was associated with theoretical costs of an increased body size and a larger food intake. These results show that in humans, evidence for adaptive thermogenesis is still inconsistent. However, they do not rule out the existence, but emphasize that if present, adaptive changes in energy expenditure may be too small to measure considering measurement errors, errors in assumptions made and small (day-to-day) differences in physical activity. In addition, it is not clear in which component or components of total energy expenditure adaptive changes can occur and whether components can overlap due to measurement limitations

Statistical method on nonrandom clustering with application to somatic mutations in cancer

<p>Abstract</p> <p>Background</p> <p>Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention.</p> <p>Results</p> <p>We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC) database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and <it>β</it>-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors.</p> <p>Conclusions</p> <p>Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.</p

Variation analysis and gene annotation of eight MHC haplotypes: The MHC Haplotype Project

The human major histocompatibility complex (MHC) is contained within about 4 Mb on the short arm of chromosome 6 and is recognised as the most variable region in the human genome. The primary aim of the MHC Haplotype Project was to provide a comprehensively annotated reference sequence of a single, human leukocyte antigen-homozygous MHC haplotype and to use it as a basis against which variations could be assessed from seven other similarly homozygous cell lines, representative of the most common MHC haplotypes in the European population. Comparison of the haplotype sequences, including four haplotypes not previously analysed, resulted in the identification of >44,000 variations, both substitutions and indels (insertions and deletions), which have been submitted to the dbSNP database. The gene annotation uncovered haplotype-specific differences and confirmed the presence of more than 300 loci, including over 160 protein-coding genes. Combined analysis of the variation and annotation datasets revealed 122 gene loci with coding substitutions of which 97 were non-synonymous. The haplotype (A3-B7-DR15; PGF cell line) designated as the new MHC reference sequence, has been incorporated into the human genome assembly (NCBI35 and subsequent builds), and constitutes the largest single-haplotype sequence of the human genome to date. The extensive variation and annotation data derived from the analysis of seven further haplotypes have been made publicly available and provide a framework and resource for future association studies of all MHC-associated diseases and transplant medicine

Development of Functional and Molecular Correlates of Vaccine-Induced Protection for a Model Intracellular Pathogen, F. tularensis LVS

In contrast with common human infections for which vaccine efficacy can be evaluated directly in field studies, alternative strategies are needed to evaluate efficacy for slowly developing or sporadic diseases like tularemia. For diseases such as these caused by intracellular bacteria, serological measures of antibodies are generally not predictive. Here, we used vaccines varying in efficacy to explore development of clinically useful correlates of protection for intracellular bacteria, using Francisella tularensis as an experimental model. F. tularensis is an intracellular bacterium classified as Category A bioterrorism agent which causes tularemia. The primary vaccine candidate in the U.S., called Live Vaccine Strain (LVS), has been the subject of ongoing clinical studies; however, safety and efficacy are not well established, and LVS is not licensed by the U.S. FDA. Using a mouse model, we compared the in vivo efficacy of a panel of qualitatively different Francisella vaccine candidates, the in vitro functional activity of immune lymphocytes derived from vaccinated mice, and relative gene expression in immune lymphocytes. Integrated analyses showed that the hierarchy of protection in vivo engendered by qualitatively different vaccines was reflected by the degree of lymphocytes' in vitro activity in controlling the intramacrophage growth of Francisella. Thus, this assay may be a functional correlate. Further, the strength of protection was significantly related to the degree of up-regulation of expression of a panel of genes in cells recovered from the assay. These included IFN-γ, IL-6, IL-12Rβ2, T-bet, SOCS-1, and IL-18bp. Taken together, the results indicate that an in vitro assay that detects control of bacterial growth, and/or a selected panel of mediators, may ultimately be developed to predict the outcome of vaccine efficacy and to complement clinical trials. The overall approach may be applicable to intracellular pathogens in general

Variation in Size and Growth of the Great Scallop Pecten maximus along a Latitudinal Gradient

Understanding the relationship between growth and temperature will aid in the evaluation of thermal stress and threats to ectotherms in the context of anticipated climate changes. Most Pecten maximus scallops living at high latitudes in the northern hemisphere have a larger maximum body size than individuals further south, a common pattern among many ectotherms. We investigated differences in daily shell growth among scallop populations along the Northeast Atlantic coast from Spain to Norway. This study design allowed us to address precisely whether the asymptotic size observed along a latitudinal gradient, mainly defined by a temperature gradient, results from differences in annual or daily growth rates, or a difference in the length of the growing season. We found that low annual growth rates in northern populations are not due to low daily growth values, but to the smaller number of days available each year to achieve growth compared to the south. We documented a decrease in the annual number of growth days with age regardless of latitude. However, despite initially lower annual growth performances in terms of growing season length and growth rate, differences in asymptotic size as a function of latitude resulted from persistent annual growth performances in the north and sharp declines in the south. Our measurements of daily growth rates throughout life in a long-lived ectothermic species provide new insight into spatio-temporal variations in growth dynamics and growing season length that cannot be accounted for by classical growth models that only address asymptotic size and annual growth rate

Raman Spectroscopy and Regenerative Medicine: A Review

The field of regenerative medicine spans a wide area of the biomedical landscape—from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool