231 research outputs found

    Trial protocol OPPTIMUM : does progesterone prophylaxis for the prevention of preterm labour improve outcome?

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    Background Preterm birth is a global problem, with a prevalence of 8 to 12% depending on location. Several large trials and systematic reviews have shown progestogens to be effective in preventing or delaying preterm birth in selected high risk women with a singleton pregnancy (including those with a short cervix or previous preterm birth). Although an improvement in short term neonatal outcomes has been shown in some trials these have not consistently been confirmed in meta-analyses. Additionally data on longer term outcomes is limited to a single trial where no difference in outcomes was demonstrated at four years of age of the child, despite those in the “progesterone” group having a lower incidence of preterm birth. Methods/Design The OPPTIMUM study is a double blind randomized placebo controlled trial to determine whether progesterone prophylaxis to prevent preterm birth has long term neonatal or infant benefit. Specifically it will study whether, in women with singleton pregnancy and at high risk of preterm labour, prophylactic vaginal natural progesterone, 200 mg daily from 22 – 34 weeks gestation, compared to placebo, improves obstetric outcome by lengthening pregnancy thus reducing the incidence of preterm delivery (before 34 weeks), improves neonatal outcome by reducing a composite of death and major morbidity, and leads to improved childhood cognitive and neurosensory outcomes at two years of age. Recruitment began in 2009 and is scheduled to close in Spring 2013. As of May 2012, over 800 women had been randomized in 60 sites. Discussion OPPTIMUM will provide further evidence on the effectiveness of vaginal progesterone for prevention of preterm birth and improvement of neonatal outcomes in selected groups of women with singleton pregnancy at high risk of preterm birth. Additionally it will determine whether any reduction in the incidence of preterm birth is accompanied by improved childhood outcome

    Description of a PCR-based technique for DNA splicing and mutagenesis by producing 5' overhangs with run through stop DNA synthesis utilizing Ara-C

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    BACKGROUND: Splicing of DNA molecules is an important task in molecular biology that facilitates cloning, mutagenesis and creation of chimeric genes. Mutagenesis and DNA splicing techniques exist, some requiring restriction enzymes, and others utilize staggered reannealing approaches. RESULTS: A method for DNA splicing and mutagenesis without restriction enzymes is described. The method is based on mild template-dependent polymerization arrest with two molecules of cytosine arabinose (Ara-C) incorporated into PCR primers. Two rounds of PCR are employed: the first PCR produces 5' overhangs that are utilized for DNA splicing. The second PCR is based on polymerization running through the Ara-C molecules to produce the desired final product. To illustrate application of the run through stop mutagenesis and DNA splicing technique, we have carried out splicing of two segments of the human cofilin 1 gene and introduced a mutational deletion into the product. CONCLUSION: We have demonstrated the utility of a new PCR-based method for carrying out DNA splicing and mutagenesis by incorporating Ara-C into the PCR primers

    Metabolic phenotypes in a Lyz2Cre recombinase mouse model

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    The Cre-Lox system is essential in biomedical research for precise gene deletion in specific cell types, crucial for understanding genetic roles in disease. Although generally considered non-detrimental, Cre recombinase expression has been associated with potential adverse effects, including Cre toxicity, ectopic expression, and disruption of endogenous genes. We investigated the role of macrophage nucleotide-binding oligomerization domain (Nod1) in obesity-associated diabetes using myeloid-specific Nod1-knockout mice (Nod1 floxed crossed with Lyz2Cre). Our study examined Lyz2Cre as well as floxed control mice separately, unlike most research. Results indicated that Lyz2Cre expression alone impacts glucose metabolism, challenging the notion that Cre expression is harmless. This finding highlights the critical importance of including Cre-only controls in studies using floxed alleles to generate conditional knockout mouse models in order to ensure robust and accurate conclusions in molecular research

    Inter-Rater Reliability of the CASCADE Criteria: Challenges in Classifying Arteriopathies.

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    Background and purposeThere are limited data about the reliability of subtype classification in childhood arterial ischemic stroke, an issue that prompted the IPSS (International Pediatric Stroke Study) to develop the CASCADE criteria (Childhood AIS Standardized Classification and Diagnostic Evaluation). Our purpose was to determine the CASCADE criteria's reliability in a population of children with stroke.MethodsEight raters from the IPSS reviewed neuroimaging and clinical records of 64 cases (16 cases each) randomly selected from a prospectively collected cohort of 113 children with arterial ischemic stroke and classified them using the CASCADE criteria. Clinical data abstracted included history of present illness, risk factors, and acute imaging. Agreement among raters was measured by unweighted κ statistic.ResultsThe CASCADE criteria demonstrated a moderate inter-rater reliability, with an overall κ statistic of 0.53 (95% confidence interval [CI]=0.39-0.67). Cardioembolic and bilateral cerebral arteriopathy subtypes had much higher agreement (κ=0.84; 95% CI=0.70-0.99; and κ=0.90; 95% CI=0.71-1.00, respectively) than cases of aortic/cervical arteriopathy (κ=0.36; 95% CI=0.01-0.71), unilateral focal cerebral arteriopathy of childhood (FCA; κ=0.49; 95% CI=0.23-0.76), and small vessel arteriopathy of childhood (κ=-0.012; 95% CI=-0.04 to 0.01).ConclusionsThe CASCADE criteria have moderate reliability when used by trained and experienced raters, which suggests that it can be used for classification in multicenter pediatric stroke studies. However, the moderate reliability of the arteriopathic subtypes suggests that further refinement is needed for defining subtypes. Such revisions may reduce the variability in the literature describing risk factors, recurrence, and outcomes associated with childhood arteriopathy

    Towards a consensus-based classification of childhood arterial ischemic stroke.

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    Background and purposeThe implementation of uniform nomenclature and classification in adult arterial ischemic stroke (AIS) has been critical for defining outcomes and recurrence risks according to etiology and in developing risk-stratified treatments. In contrast, current classification and nomenclature in childhood AIS are often overlapping or contradictory. Our purpose was to develop a comprehensive consensus-based classification system for childhood AIS.MethodsUsing a modified-Delphi method, members of the International Pediatric Stroke Study (IPSS) developed the Childhood AIS Standardized Classification And Diagnostic Evaluation (CASCADE) criteria. Two groups of pediatric stroke specialists from the IPSS classified 7 test cases using 2 methods each: (1) classification typical of the individual clinician's current clinical practice; and (2) classification based on the CASCADE criteria. Group 1 underwent in-person training in the utilization of the CASCADE criteria. Group 2 classified the same cases via an online survey, including definitions but without training. Inter-rater reliability (IRR) was assessed via multi-rater unweighted κ-statistic.ResultsIn Group 1 (with training), IRR was improved using CASCADE criteria (κ=0.78, 95% CI=[0.49, 0.94]), compared with typical clinical practice (κ=0.40, 95% CI=[0.11, 0.60]). In Group 2 (without training), IRR was lower than among trained raters (κ=0.61, 95% CI=[0.29, 0.77]), but higher than current practice (κ=0.23, 95% CI=[0.03, 0.36]).ConclusionsA new, consensus-based classification system for childhood AIS, the CASCADE criteria, can be used to classify cases with good IRR. These preliminary findings suggest that the CASCADE criteria may be particularity useful in the setting of prospective multicenter studies in childhood-onset AIS, where standardized training of investigators is feasible

    Glycine inhibits NINJ1 membrane clustering to suppress plasma membrane rupture in cell death

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    First recognized more than 30 years ago, glycine protects cells against rupture from diverse types of injury. This robust and widely observed effect has been speculated to target a late downstream process common to multiple modes of tissue injury. The molecular target of glycine that mediates cytoprotection, however, remains elusive. Here, we show that glycine works at the level of NINJ1, a newly identified executioner of plasma membrane rupture in pyroptosis, necrosis, and post-apoptosis lysis. NINJ1 is thought to cluster within the plasma membrane to cause cell rupture. We demonstrate that the execution of pyroptotic cell rupture is similar for human and mouse NINJ1 and that NINJ1 knockout functionally and morphologically phenocopies glycine cytoprotection in macrophages undergoing lytic cell death. Next, we show that glycine prevents NINJ1 clustering by either direct or indirect mechanisms. In pyroptosis, glycine preserves cellular integrity but does not affect upstream inflammasome activities or accompanying energetic cell death. By positioning NINJ1 clustering as a glycine target, our data resolve a long-standing mechanism for glycine-mediated cytoprotection. This new understanding will inform the development of cell preservation strategies to counter pathologic lytic cell death.publishedVersio

    Rapid detection of pandemic influenza in the presence of seasonal influenza

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    Background: Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland. Methods: We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data. Results: We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland. Conclusions: While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical
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