4,601 research outputs found

    Choice between alternative routes to go public: backdoor listing versus IPO

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    Going public is the dream of many private companies. It represents a major milestone in the development of a firm. The listing status brings a lot of advantages to a firm. Some of these advantages include (1) access to capital markets and lower cost of capital; (2) enhanced company reputation and profile; (3) providing liquidity for owners to cash out; and (4) use of stock to pay for acquisitions, among others. However, going public is also a costly process. The out-of-pocket costs for an IPO typically involve fees paid for investment banks, accountants, auditors, lawyers, other experts, underwriters and brokers. The IPO firm will also have to pay for the printing of a prospectus and listing fees and other compliance costs. Other hidden costs entail underpricing, more stringent disclosure and regulatory requirements and the time spent by senior management in preparing the company for public listing

    FXN promoter silencing in the humanized mouse model of Friedreich Ataxia

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    Background - Friedreich ataxia is caused by an expanded GAA triplet-repeat sequence in intron 1 of the FXN gene that results in epigenetic silencing of the FXN promoter. This silencing mechanism is seen in patient-derived lymphoblastoid cells but it remains unknown if it is a widespread phenomenon affecting multiple cell types and tissues. Methodology / Principal Findings - The humanized mouse model of Friedreich ataxia (YG8sR), which carries a single transgenic insert of the human FXN gene with an expanded GAA triplet-repeat in intron 1, is deficient for FXN transcript when compared to an isogenic transgenic mouse lacking the expanded repeat (Y47R). We found that in YG8sR the deficiency of FXN transcript extended both upstream and downstream of the expanded GAA triplet-repeat, suggestive of deficient transcriptional initiation. This pattern of deficiency was seen in all tissues tested, irrespective of whether they are known to be affected or spared in disease pathogenesis, in both neuronal and non-neuronal tissues, and in cultured primary fibroblasts. FXN promoter function was directly measured via metabolic labeling of newly synthesized transcripts in fibroblasts, which revealed that the YG8sR mouse was significantly deficient in transcriptional initiation compared to the Y47R mouse. Conclusions / Significance- Deficient transcriptional initiation accounts for FXN transcriptional deficiency in the humanized mouse model of Friedreich ataxia, similar to patient-derived cells, and the mechanism underlying promoter silencing in Friedreich ataxia is widespread across multiple cell types and tissues.This research was supported by grants from the National Institutes of Health (R01 NS072418), and the Muscular Dystrophy Association to S.I.B. Y.K.C. is supported by a postdoctoral research fellowship from the Million Dollar Bike Ride Grant Program of the Orphan Disease Center at University of Pennsylvania. T.T.H. was supported by the American College of Medical Genetics Foundation. A.C.P. and M.G.M. were supported by the SURE and OSCTR programs at OUHSC, respectively

    Methods for estimating the case fatality ratio for a novel, emerging infectious disease.

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    During the course of an epidemic of a potentially fatal disease, it is important that the case fatality ratio be well estimated. The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital

    3D multi-agent models for protein release from PLGA spherical particles with complex inner morphologies

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    In order to better understand and predict the release of proteins from bioerodible micro- or nanospheres, it is important to know the influences of different initial factors on the release mechanisms. Often though it is difficult to assess what exactly is at the origin of a certain dissolution profile. We propose here a new class of fine-grained multi-agent models built to incorporate increasing complexity, permitting the exploration of the role of different parameters, especially that of the internal morphology of the spheres, in the exhibited release profile. This approach, based on Monte-Carlo (MC) and Cellular Automata (CA) techniques, has permitted the testing of various assumptions and hypotheses about several experimental systems of nanospheres encapsulating proteins. Results have confirmed that this modelling approach has increased the resolution over the complexity involved, opening promising perspectives for future developments, especially complementing in vitro experimentation

    Occurrence of testicular microlithiasis in androgen insensitive hypogonadal mice

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    <b>Background</b>: Testicular microliths are calcifications found within the seminiferous tubules. In humans, testicular microlithiasis (TM) has an unknown etiology but may be significantly associated with testicular germ cell tumors. Factors inducing microlith development may also, therefore, act as susceptibility factors for malignant testicular conditions. Studies to identify the mechanisms of microlith development have been hampered by the lack of suitable animal models for TM.<BR/> <b>Methods</b>: This was an observational study of the testicular phenotype of different mouse models. The mouse models were: cryptorchid mice, mice lacking androgen receptors (ARs) on the Sertoli cells (SCARKO), mice with a ubiquitous loss of androgen ARs (ARKO), hypogonadal (hpg) mice which lack circulating gonadotrophins, and hpg mice crossed with SCARKO (hpg.SCARKO) and ARKO (hpg.ARKO) mice.<BR/> <b>Results</b>: Microscopic TM was seen in 94% of hpg.ARKO mice (n=16) and the mean number of microliths per testis was 81 +/- 54. Occasional small microliths were seen in 36% (n=11) of hpg testes (mean 2 +/- 0.5 per testis) and 30% (n=10) of hpg.SCARKO testes (mean 8 +/- 6 per testis). No microliths were seen in cryptorchid, ARKO or SCARKO mice. There was no significant effect of FSH or androgen on TM in hpg.ARKO mice.<BR/> <b>Conclusions</b>: We have identified a mouse model of TM and show that lack of endocrine stimulation is a cause of TM. Importantly, this model will provide a means with which to identify the mechanisms of TM development and the underlying changes in protein and gene expression

    Backdoor Listings in Australia

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    We study a large sample of Australian backdoor listings (BDLs) over the period from 1994 to 2014. BDLs account for roughly 13 per cent of all firms going public on the Australian Securities Exchange and are popular among hi-tech firms and those with foreign-domiciled assets. We find that the BDL market is likely influenced by the sentiment in the initial public offering (IPO) market, with the number of BDLs announced in a year being negatively (positively) correlated with the number of IPOs lodged (the percentage of IPOs withdrawn) in the prior year. Contrary to common belief, BDL transactions take longer to complete than IPOs, since they typically combine both a reverse takeover and the public listing process. Roughly three quarters of our sample raised equity capital as part of the BDL process

    Symptoms associated with victimization in patients with schizophrenia and related disorders

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    Background: Patients with psychoses have an increased risk of becoming victims of violence. Previous studies have suggested that higher symptom levels are associated with a raised risk of becoming a victim of physical violence. There has been, however, no evidence on the type of symptoms that are linked with an increased risk of recent victimization. Methods: Data was taken from two studies on involuntarily admitted patients, one national study in England and an international one in six other European countries. In the week following admission, trained interviewers asked patients whether they had been victims of physical violence in the year prior to admission, and assessed symptoms on the Brief Psychiatric Rating Scale (BPRS). Only patients with a diagnosis of schizophrenia or related disorders (ICD-10 F20–29) were included in the analysis which was conducted separately for the two samples. Symptom levels assessed on the BPRS subscales were tested as predictors of victimization. Univariable and multivariable logistic regression models were fitted to estimate adjusted odds ratios. Results: Data from 383 patients in the English sample and 543 patients in the European sample was analysed. Rates of victimization were 37.8% and 28.0% respectively. In multivariable models, the BPRS manic subscale was significantly associated with victimization in both samples. Conclusions: Higher levels of manic symptoms indicate a raised risk of being a victim of violence in involuntary patients with schizophrenia and related disorders. This might be explained by higher activity levels, impaired judgement or poorer self-control in patients with manic symptoms. Such symptoms should be specifically considered in risk assessments

    The identification of informative genes from multiple datasets with increasing complexity

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    Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

    Coevolved mutations reveal distinct architectures for two core proteins in the bacterial flagellar motor

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    Switching of bacterial flagellar rotation is caused by large domain movements of the FliG protein triggered by binding of the signal protein CheY to FliM. FliG and FliM form adjacent multi-subunit arrays within the basal body C-ring. The movements alter the interaction of the FliG C-terminal (FliGC) "torque" helix with the stator complexes. Atomic models based on the Salmonella entrovar C-ring electron microscopy reconstruction have implications for switching, but lack consensus on the relative locations of the FliG armadillo (ARM) domains (amino-terminal (FliGN), middle (FliGM) and FliGC) as well as changes during chemotaxis. The generality of the Salmonella model is challenged by the variation in motor morphology and response between species. We studied coevolved residue mutations to determine the unifying elements of switch architecture. Residue interactions, measured by their coevolution, were formalized as a network, guided by structural data. Our measurements reveal a common design with dedicated switch and motor modules. The FliM middle domain (FliMM) has extensive connectivity most simply explained by conserved intra and inter-subunit contacts. In contrast, FliG has patchy, complex architecture. Conserved structural motifs form interacting nodes in the coevolution network that wire FliMM to the FliGC C-terminal, four-helix motor module (C3-6). FliG C3-6 coevolution is organized around the torque helix, differently from other ARM domains. The nodes form separated, surface-proximal patches that are targeted by deleterious mutations as in other allosteric systems. The dominant node is formed by the EHPQ motif at the FliMMFliGM contact interface and adjacent helix residues at a central location within FliGM. The node interacts with nodes in the N-terminal FliGc α-helix triad (ARM-C) and FliGN. ARM-C, separated from C3-6 by the MFVF motif, has poor intra-network connectivity consistent with its variable orientation revealed by structural data. ARM-C could be the convertor element that provides mechanistic and species diversity.JK was supported by Medical Research Council grant U117581331. SK was supported by seed funds from Lahore University of Managment Sciences (LUMS) and the Molecular Biology Consortium
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