FOXO1 (Forkhead box O1)

Review on FOXO1 (Forkhead box O1), with data on DNA, on the protein encoded, and where the gene is implicated

Aligning the Global Delta Risk Index with SDG and SFDRR Global frameworks to assess risk to socio-ecological systems in river deltas

River deltas globally are highly exposed and vulnerable to natural hazards and are often over-exploited landforms. The Global Delta Risk Index (GDRI) was developed to assess multi-hazard risk in river deltas and support decision-making in risk reduction interventions in delta regions. Disasters have significant impacts on the progress towards the Sustainable Development Goals (SDGs). However, despite the strong interlinkage between disaster risk reduction and sustainable development, global frameworks are still developed in isolation and actions to address them are delegated to different institutions. Greater alignment between frameworks would both simplify monitoring progress towards disaster risk reduction and sustainable development and increase capacity to address data gaps in relation to indicator-based assessments for both processes. This research aims at aligning the GDRI indicators with the SDGs and the Sendai Framework for Disaster and Risk Reduction (SFDRR). While the GDRI has a modular indicator library, the most relevant indicators for this research were selected through a delta-specific impact chain designed in consultation with experts, communities and stakeholders in three delta regions: the Red River and Mekong deltas in Vietnam and the Ganges–Brahmaputra–Meghna (GBM) delta in Bangladesh and India. We analyse how effectively the 143 indicators for the GDRI match (or not) the SDG and SFDRR global frameworks. We demonstrate the interconnections of the different drivers of risk to better inform risk management and in turn support delta-level interventions towards improved sustainability and resilience of these Asian mega-deltas

Optimality of mutation and selection in germinal centers

The population dynamics theory of B cells in a typical germinal center could play an important role in revealing how affinity maturation is achieved. However, the existing models encountered some conflicts with experiments. To resolve these conflicts, we present a coarse-grained model to calculate the B cell population development in affinity maturation, which allows a comprehensive analysis of its parameter space to look for optimal values of mutation rate, selection strength, and initial antibody-antigen binding level that maximize the affinity improvement. With these optimized parameters, the model is compatible with the experimental observations such as the ~100-fold affinity improvements, the number of mutations, the hypermutation rate, and the "all or none" phenomenon. Moreover, we study the reasons behind the optimal parameters. The optimal mutation rate, in agreement with the hypermutation rate in vivo, results from a tradeoff between accumulating enough beneficial mutations and avoiding too many deleterious or lethal mutations. The optimal selection strength evolves as a balance between the need for affinity improvement and the requirement to pass the population bottleneck. These findings point to the conclusion that germinal centers have been optimized by evolution to generate strong affinity antibodies effectively and rapidly. In addition, we study the enhancement of affinity improvement due to B cell migration between germinal centers. These results could enhance our understandings to the functions of germinal centers.Comment: 5 figures in main text, and 4 figures in Supplementary Informatio

Optimal functional outcome measures for assessing treatment for Dupuytren's disease: A systematic review and recommendations for future practice

This article is available through the Brunel Open Access Publishing Fund. Copyright © 2013 Ball et al.; licensee BioMed Central Ltd.Background: Dupuytren's disease of the hand is a common condition affecting the palmar fascia, resulting in progressive flexion deformities of the digits and hence limitation of hand function. The optimal treatment remains unclear as outcomes studies have used a variety of measures for assessment. Methods: A literature search was performed for all publications describing surgical treatment, percutaneous needle aponeurotomy or collagenase injection for primary or recurrent Dupuytren’s disease where outcomes had been monitored using functional measures. Results: Ninety-one studies met the inclusion criteria. Twenty-two studies reported outcomes using patient reported outcome measures (PROMs) ranging from validated questionnaires to self-reported measures for return to work and self-rated disability. The Disability of Arm, Shoulder and Hand (DASH) score was the most utilised patient-reported function measure (n=11). Patient satisfaction was reported by eighteen studies but no single method was used consistently. Range of movement was the most frequent physical measure and was reported in all 91 studies. However, the methods of measurement and reporting varied, with seventeen different techniques being used. Other physical measures included grip and pinch strength and sensibility, again with variations in measurement protocols. The mean follow-up time ranged from 2 weeks to 17 years. Conclusions: There is little consistency in the reporting of outcomes for interventions in patients with Dupuytren’s disease, making it impossible to compare the efficacy of different treatment modalities. Although there are limitations to the existing generic patient reported outcomes measures, a combination of these together with a disease-specific questionnaire, and physical measures of active and passive individual joint Range of movement (ROM), grip and sensibility using standardised protocols should be used for future outcomes studies. As Dupuytren’s disease tends to recur following treatment as well as extend to involve other areas of the hand, follow-up times should be standardised and designed to capture both short and long term outcomes

Expression of cytoplasmic and nuclear Survivin in primary and secondary human glioblastoma

Clinically, human glioblastoma (GBM) may develop de novo or from a low-grade glioma (secondary GBM), and molecular alterations in the two pathways may differ. This study examined the status of Survivin expression and apoptosis in 30 primary and 26 secondary GBMs. Our results show that cytoplasmic Survivin positivity was significantly (P<0.001) more frequent in primary GBMs (83%) than that in secondary GBMs (46%). In addition, an inverse correlation of cytoplasmc Survivin positivity with GBM apoptotic index, and a positive association between cytoplasmic Survivin and size of the tumours were observed. These results suggest that cytoplasmic Survivin, via its antiapoptotic function, may be involved in the tumorigenesis of many primary GBMs, but only in a small fraction of secondary GBMs. Furthermore, the overall progression times from low-grade precursor lesions to secondary GBMs were significantly shorter (P<0.05) in cytoplasmic Survivin-positive cases (mean, 15.6 months) than those in Survivin-negative cases (mean, 23.8 moths), and the positive expression level of Survivin in cytoplasm was upregulated in most secondary GBMs when compared to matched pre-existing low-graded lesions. These results suggest that the increased accumulation of Survivin in the cytoplasm of more malignant glioma cells may prove to be a selective advantage, thus accelerating progression to a more aggressive phenotype

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Selective Serotonin Reuptake Inhibitor Use Is Associated with Right Ventricular Structure and Function: The MESA-Right Ventricle Study

PURPOSE:Serotonin and the serotonin transporter have been implicated in the development of pulmonary hypertension (PH). Selective serotonin reuptake inhibitors (SSRIs) may have a role in PH treatment, but the effects of SSRI use on right ventricular (RV) structure and function are unknown. We hypothesized that SSRI use would be associated with RV morphology in a large cohort without cardiovascular disease (N = 4114). METHODS:SSRI use was determined by medication inventory during the Multi-Ethnic Study of Atherosclerosis baseline examination. RV measures were assessed via cardiac magnetic resonance imaging. The cross-sectional relationship between SSRI use and each RV measure was assessed using multivariable linear regression; analyses for RV mass and end-diastolic volume (RVEDV) were stratified by sex. RESULTS:After adjustment for multiple covariates including depression and left ventricular measures, SSRI use was associated with larger RV stroke volume (RVSV) (2.75 mL, 95% confidence interval [CI] 0.48-5.02 mL, p = 0.02). Among men only, SSRI use was associated with greater RV mass (1.08 g, 95% CI 0.19-1.97 g, p = 0.02) and larger RVEDV (7.71 mL, 95% 3.02-12.40 mL, p = 0.001). SSRI use may have been associated with larger RVEDV among women and larger RV end-systolic volume in both sexes. CONCLUSIONS:SSRI use was associated with higher RVSV in cardiovascular disease-free individuals and, among men, greater RV mass and larger RVEDV. The effects of SSRI use in patients with (or at risk for) RV dysfunction and the role of sex in modifying this relationship warrant further study

Mechanisms Underlying Insulin Deficiency-Induced Acceleration of β-Amyloidosis in a Mouse Model of Alzheimer's Disease

Although evidence is accumulating that diabetes mellitus is an important risk factor for sporadic Alzheimer's disease (AD), the mechanisms by which defects in insulin signaling may lead to the acceleration of AD progression remain unclear. In this study, we applied streptozotocin (STZ) to induce experimental diabetes in AD transgenic mice (5XFAD model) and investigated how insulin deficiency affects the β-amyloidogenic processing of amyloid precursor protein (APP). Two and half months after 5XFAD mice were treated with STZ (90 mg/kg, i.p., once daily for two consecutive days), they showed significant reductions in brain insulin levels without changes in insulin receptor expression. Concentrations of cerebral amyloid-β peptides (Aβ40 and Aβ42) were significantly increased in STZ-treated 5XFAD mice as compared with vehicle-treated 5XFAD controls. Importantly, STZ-induced insulin deficiency upregulated levels of both β-site APP cleaving enzyme 1 (BACE1) and full-length APP in 5XFAD mouse brains, which was accompanied by dramatic elevations in the β-cleaved C-terminal fragment (C99). Interestingly, BACE1 mRNA levels were not affected, whereas phosphorylation of the translation initiation factor eIF2α, a mechanism proposed to mediate the post-transcriptional upregulation of BACE1, was significantly elevated in STZ-treated 5XFAD mice. Meanwhile, levels of GGA3, an adapter protein responsible for sorting BACE1 to lysosomal degradation, are indistinguishable between STZ- and vehicle-treated 5XFAD mice. Moreover, STZ treatments did not affect levels of Aβ-degrading enzymes such as neprilysin and insulin-degrading enzyme (IDE) in 5XFAD brains. Taken together, our findings provide a mechanistic foundation for a link between diabetes and AD by demonstrating that insulin deficiency may change APP processing to favor β-amyloidogenesis via the translational upregulation of BACE1 in combination with elevations in its substrate, APP

Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution