113 research outputs found
Germline Mutations in NFKB2 Implicate the Noncanonical NF-κB Pathway in the Pathogenesis of Common Variable Immunodeficiency
Common variable immunodeficiency (CVID) is a heterogeneous disorder characterized by antibody deficiency, poor humoral response to antigens, and recurrent infections. To investigate the molecular cause of CVID, we carried out exome sequence analysis of a family diagnosed with CVID and identified a heterozygous frameshift mutation, c.2564delA (p.Lys855Serfs∗7), in NFKB2 affecting the C terminus of NF-κB2 (also known as p100/p52 or p100/p49). Subsequent screening of NFKB2 in 33 unrelated CVID-affected individuals uncovered a second heterozygous nonsense mutation, c.2557C>T (p.Arg853∗), in one simplex case. Affected individuals in both families presented with an unusual combination of childhood-onset hypogammaglobulinemia with recurrent infections, autoimmune features, and adrenal insufficiency. NF-κB2 is the principal protein involved in the noncanonical NF-κB pathway, is evolutionarily conserved, and functions in peripheral lymphoid organ development, B cell development, and antibody production. In addition, Nfkb2 mouse models demonstrate a CVID-like phenotype with hypogammaglobulinemia and poor humoral response to antigens. Immunoblot analysis and immunofluorescence microscopy of transformed B cells from affected individuals show that the NFKB2 mutations affect phosphorylation and proteasomal processing of p100 and, ultimately, p52 nuclear translocation. These findings describe germline mutations in NFKB2 and establish the noncanonical NF-κB signaling pathway as a genetic etiology for this primary immunodeficiency syndrome
The leading digit distribution of the worldwide Illicit Financial Flows
Benford's law states that in data sets from different phenomena leading
digits tend to be distributed logarithmically such that the numbers beginning
with smaller digits occur more often than those with larger ones. Particularly,
the law is known to hold for different types of financial data. The Illicit
Financial Flows (IFFs) exiting the developing countries are frequently
discussed as hidden resources which could have been otherwise properly utilized
for their development. We investigate here the distribution of the leading
digits in the recent data on estimates of IFFs to look for the existence of a
pattern as predicted by Benford's law and establish that the frequency of
occurrence of the leading digits in these estimates does closely follow the
law.Comment: 13 pages, 10 figures, 6 tables, additional data analyi
Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions
The yearly aggregated tax income data of all, more than 8000, Italian
municipalities are analyzed for a period of five years, from 2007 to 2011, to
search for conformity or not with Benford's law, a counter-intuitive phenomenon
observed in large tabulated data where the occurrence of numbers having smaller
initial digits is more favored than those with larger digits. This is done in
anticipation that large deviations from Benford's law will be found in view of
tax evasion supposedly being widespread across Italy. Contrary to expectations,
we show that the overall tax income data for all these years is in excellent
agreement with Benford's law. Furthermore, we also analyze the data of
Calabria, Campania and Sicily, the three Italian regions known for strong
presence of mafia, to see if there are any marked deviations from Benford's
law. Again, we find that all yearly data sets for Calabria and Sicily agree
with Benford's law whereas only the 2007 and 2008 yearly data show departures
from the law for Campania. These results are again surprising in view of
underground and illegal nature of economic activities of mafia which
significantly contribute to tax evasion. Some hypothesis for the found
conformity is presented.Comment: 18 pages, 5 tables, 4 figures, 61 references, To appear in European
Physical Journal
Applying Benford’s law to detect accounting data manipulation in the banking industry
We utilise Benford’s Law to test if balance sheet and income statement data broadly used to assess bank soundness were manipulated prior to and also during the global financial crisis. We find that all banks resort to loan loss provisions to manipulate earnings and income upwards. Distressed institutions that have stronger incentives to conceal their financial difficulties resort additionally to manipulating loan loss allowances and non-performing loans downwards. Moreover, manipulation is magnified during the crisis and expands to encompass regulatory capital
Assessment and validation of a suite of reverse transcription-quantitative PCR reference genes for analyses of density-dependent behavioural plasticity in the Australian plague locust
<p>Abstract</p> <p>Background</p> <p>The Australian plague locust, <it>Chortoicetes terminifera</it>, is among the most promising species to unravel the suites of genes underling the density-dependent shift from shy and cryptic solitarious behaviour to the highly active and aggregating gregarious behaviour that is characteristic of locusts. This is because it lacks many of the major phenotypic changes in colour and morphology that accompany phase change in other locust species. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the most sensitive method available for determining changes in gene expression. However, to accurately monitor the expression of target genes, it is essential to select an appropriate normalization strategy to control for non-specific variation between samples. Here we identify eight potential reference genes and examine their expression stability at different rearing density treatments in neural tissue of the Australian plague locust.</p> <p>Results</p> <p>Taking advantage of the new orthologous DNA sequences available in locusts, we developed primers for genes encoding 18SrRNA, ribosomal protein L32 (RpL32), armadillo (Arm), actin 5C (Actin), succinate dehydrogenase (SDHa), glyceraldehyde-3P-dehydrogenase (GAPDH), elongation factor 1 alpha (EF1a) and annexin IX (AnnIX). The relative transcription levels of these eight genes were then analyzed in three treatment groups differing in rearing density (isolated, short- and long-term crowded), each made up of five pools of four neural tissue samples from 5<sup>th </sup>instar nymphs. SDHa and GAPDH, which are both involved in metabolic pathways, were identified as the least stable in expression levels, challenging their usefulness in normalization. Based on calculations performed with the geNorm and NormFinder programs, the best combination of two genes for normalization of gene expression data following crowding in the Australian plague locust was EF1a and Arm. We applied their use to studying a target gene that encodes a Ca<sup>2+ </sup>binding glycoprotein, <it>SPARC</it>, which was previously found to be up-regulated in brains of gregarious desert locusts, <it>Schistocerca gregaria</it>. Interestingly, expression of this gene did not vary with rearing density in the same way in brains of the two locust species. Unlike <it>S. gregaria</it>, there was no effect of any crowding treatment in the Australian plague locust.</p> <p>Conclusion</p> <p>Arm and EF1a is the most stably expressed combination of two reference genes of the eight examined for reliable normalization of RT-qPCR assays studying density-dependent behavioural change in the Australian plague locust. Such normalization allowed us to show that <it>C. terminifera </it>crowding did not change the neuronal expression of the <it>SPARC </it>gene, a gregarious phase-specific gene identified in brains of the desert locust, <it>S. gregaria</it>. Such comparative results on density-dependent gene regulation provide insights into the evolution of gregarious behaviour and mass migration of locusts. The eight identified genes we evaluated are also candidates as normalization genes for use in experiments involving other Oedipodinae species, but the rank order of gene stability must necessarily be determined on a case-by-case basis.</p
Optimization of the Sybr Green real time PCR for the detection of Human Herpes Virus type 6 (HHV-6)
Analyst information precision and small earnings surprises
This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings
Market competition, earnings management, and persistence in accounting profitability around the world
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