Antenatal dexamethasone for early preterm birth in low-resource countries

BACKGROUND: The safety and efficacy of antenatal glucocorticoids in women in low-resource countries who are at risk for preterm birth are uncertain. METHODS: We conducted a multicountry, randomized trial involving pregnant women between 26 weeks 0 days and 33 weeks 6 days of gestation who were at risk for preterm birth. The participants were assigned to intramuscular dexamethasone or identical placebo. The primary outcomes were neonatal death alone, stillbirth or neonatal death, and possible maternal bacterial infection; neonatal death alone and stillbirth or neonatal death were evaluated with superiority analyses, and possible maternal bacterial infection was evaluated with a noninferiority analysis with the use of a prespecified margin of 1.25 on the relative scale. RESULTS: A total of 2852 women (and their 3070 fetuses) from 29 secondary- and tertiary-level hospitals across Bangladesh, India, Kenya, Nigeria, and Pakistan underwent randomization. The trial was stopped for benefit at the second interim analysis. Neonatal death occurred in 278 of 1417 infants (19.6%) in the dexamethasone group and in 331 of 1406 infants (23.5%) in the placebo group (relative risk, 0.84; 95% confidence interval [CI], 0.72 to 0.97; P=0.03). Stillbirth or neonatal death occurred in 393 of 1532 fetuses and infants (25.7%) and in 444 of 1519 fetuses and infants (29.2%), respectively (relative risk, 0.88; 95% CI, 0.78 to 0.99; P=0.04); the incidence of possible maternal bacterial infection was 4.8% and 6.3%, respectively (relative risk, 0.76; 95% CI, 0.56 to 1.03). There was no significant between-group difference in the incidence of adverse events. CONCLUSIONS: Among women in low-resource countries who were at risk for early preterm birth, the use of dexamethasone resulted in significantly lower risks of neonatal death alone and stillbirth or neonatal death than the use of placebo, without an increase in the incidence of possible maternal bacterial infection.Fil: Oladapo, Olufemi T.. Organizacion Mundial de la Salud; ArgentinaFil: Vogel, Joshua P.. Organizacion Mundial de la Salud; ArgentinaFil: Piaggio, Gilda. Organizacion Mundial de la Salud; ArgentinaFil: Nguyen, My-Huong. Organizacion Mundial de la Salud; ArgentinaFil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Metin Gülmezoglu, A.. Organizacion Mundial de la Salud; ArgentinaFil: Bahl, Rajiv. Organizacion Mundial de la Salud; ArgentinaFil: Rao, Suman P.N.. Organizacion Mundial de la Salud; ArgentinaFil: de Costa, Ayesha. Organizacion Mundial de la Salud; ArgentinaFil: Gupta, Shuchita. Organizacion Mundial de la Salud; ArgentinaFil: Shahidullah, Mohammod. No especifíca;Fil: Chowdhury, Saleha B.. No especifíca;Fil: Ara, Gulshan. No especifíca;Fil: Akter, Shaheen. No especifíca;Fil: Akhter, Nasreen. No especifíca;Fil: Dey, Probhat R.. No especifíca;Fil: Abdus Sabur, M.. No especifíca;Fil: Azad, Mohammad T.. No especifíca;Fil: Choudhury, Shahana F.. No especifíca;Fil: Matin, M.A.. No especifíca;Fil: Goudar, Shivaprasad S.. No especifíca;Fil: Dhaded, Sangappa M.. No especifíca;Fil: Metgud, Mrityunjay C.. No especifíca;Fil: Pujar, Yeshita V.. No especifíca;Fil: Somannavar, Manjunath S.. No especifíca;Fil: Vernekar, Sunil S.. No especifíca;Fil: Herekar, Veena R.. No especifíca;Fil: Bidri, Shailaja R.. No especifíca;Fil: Mathapati, Sangamesh S.. No especifíca;Fil: Patil, Preeti G.. No especifíca;Fil: Patil, Mallanagouda M.. No especifíca;Fil: Gudadinni, Muttappa R.. No especifíca;Fil: Bijapure, Hidaytullah R.. No especifíca;Fil: Mallapur, Ashalata A.. No especifíca;Fil: Katageri, Geetanjali M.. No especifíca;Fil: Chikkamath, Sumangala B.. No especifíca;Fil: Yelamali, Bhuvaneshwari C.. No especifíca;Fil: Pol, Ramesh R.. No especifíca;Fil: Misra, Sujata S.. No especifíca;Fil: Das, Leena. No especifíca

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

ngVLA Key Science Goal 5 Understanding the Formation and Evolution of Black Holes in the Era of Multi-Messenger Astronomy

The next-generation Very Large Array (ngVLA) will be a powerful telescope for finding and studying black holes across the entire mass range. High-resolution imaging abilities will allow the separation of low-luminosity black holes in the local Universe from background sources, thereby providing critical constraints on the mass function, formation, and growth of black holes. Its combination of sensitivity and angular resolution will provide new constraints on the physics of black hole accretion and jet formation. Combined with facilities across the spectrum and gravitational wave observatories, the ngVLA will provide crucial constraints on the interaction of black holes with their environments, with specific implications for the relationship between evolution of galaxies and the emission of gravitational waves from in-spiraling supermassive black holes and potential implications for stellar mass and intermediate mass black holes. The ngVLA will identify the radio counterparts to transient sources discovered by electromagnetic, gravitational wave, and neutrino observatories, and its high-resolution, fast-mapping capabilities will make it the preferred instrument to pinpoint electromagnetic counterparts to events such as supermassive black hole mergers. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration

Application of stacking ensemble technique in agriculture for prediction of crop yield

In comparison to other methodologies, Machine Learning has proven to be an effective tool for making reasonable predictions. Initially, a single machine learning model is used on data to make predictions; however, instead of using a single machine learning model, a collection of ML models is employed instead. Models can reduce prediction variance, bias, or both. The result provided will be more appealing and correct if appropriate features affecting the prediction values are supplied. This study presents a framework for selecting feature subsets using the L2 regularization feature selection technique. The study took into account 11 crops and 15 characteristics from 300 districts across India. For predicting yield, basic learners' models such as Linear Regression, LASSO Regression, Decision Trees, Random Forests, Extreme Gradient Boosting (XGBoost), and Support Vector Machines are initially trained and tested. Base learners are used to create the stacking ensemble and the proposed optimum stacking ensemble. In terms of the performance measures employed, the proposed Optimized stacking ensemble shows approximately (MSE =6408, Accuracy=85%) outperforms the Normal stacking ensemble (MSE=8315, Accuracy=83%)