Quitting smoking and mortality: risk of all-cause mortality decreased sharply in 5-9 years after quitting smoking among Chinese

e-PosterLi Ka Shing Faculty of Medicine Frontiers SeriesConference Theme: MOOCs in Postmodern Asia (Oct 27, 2014) and Big Data and Precision Medicine (Oct 28, 2014)postprin

Level 5. Previously in 1996, the Boeing

the median time to move from Capabilit

Integration of Phytochrome and Cryptochrome Signals Determines Plant Growth during Competition for Light.

Plants in dense vegetation perceive their neighbors primarily through changes in light quality. Initially, the ratio between red (R) and far-red (FR) light decreases due to reflection of FR by plant tissue well before shading occurs. Perception of low R:FR by the phytochrome photoreceptors induces the shade avoidance response [1], of which accelerated elongation growth of leaf-bearing organs is an important feature. Low R:FR-induced phytochrome inactivation leads to the accumulation and activation of the transcription factors PHYTOCHROME-INTERACTING FACTORs (PIFs) 4, 5, and 7 and subsequent expression of their growth-mediating targets [2, 3]. When true shading occurs, transmitted light is especially depleted in red and blue (B) wavelengths, due to absorption by chlorophyll [4]. Although the reduction of blue wavelengths alone does not occur in nature, long-term exposure to low B light induces a shade avoidance-like response that is dependent on the cryptochrome photoreceptors and the transcription factors PIF4 and PIF5 [5-7]. We show in Arabidopsis thaliana that low B in combination with low R:FR enhances petiole elongation similar to vegetation shade, providing functional context for a low B response in plant competition. Low B potentiates the low R:FR response through PIF4, PIF5, and PIF7, and it involves increased PIF5 abundance and transcriptional changes. Low B attenuates a low R:FR-induced negative feedback loop through reduced gene expression of negative regulators and reduced HFR1 levels. The enhanced response to combined phytochrome and cryptochrome inactivation shows how multiple light cues can be integrated to fine-tune the plant's response to a changing environment

[Ge₂]⁴⁻Dumbbells with Very Short Ge−Ge Distances in the Zintl Phase Li₃NaGe₂: A Solid-State Equivalent to Molecular O₂

The novel ternary Zintl phase Li3NaGe2 comprises alkali-metal cations and [Ge2]4− dumbbells. The diatomic [Ge2]4− unit is characterized by the shortest Ge−Ge distance (2.390(1) Å) ever observed in a Zintl phase and thus represents the first Ge=Ge double bond under such conditions, as also suggested by the (8−N) rule. Raman measurements support these findings. The multiple-bond character is confirmed by electronic-structure calculations, and an upfield 6Li NMR shift of −10.0 ppm, which was assigned to the Li cations surrounded by the π systems of three Ge dumbbells, further underlines this interpretation. For the unperturbed, ligand-free dumbbell in Li3NaGe2, the π- bonding py and pz orbitals are degenerate as in molecular oxygen, which has singly occupied orbitals. The partially filled π-type bands of the neat solid Li3NaGe2 cross the Fermi level, resulting in metallic properties. Li3NaGe2 was synthesized from the elements as well as from binary reactants and subsequently characterized crystallographically.O.P. acknowledges support from a Marie Skłodowska-Curie Individual Fellowship. L.M.S. is further grateful to the Fonds der Chemischen Industrie and the Studienstiftung des deutschen Volkes for her fellowships. A.J.K. gratefully acknowledges funding from the Alfred Kordelin Foundation and computational resources from CSC – the Finnish IT Center for Science.This is the accepted manuscript. The final version is available at http://onlinelibrary.wiley.com/wol1/doi/10.1002/ange.201508044/abstract

Smoking and nasopharyngeal carcinoma mortality: a cohort study of 101823 adults in Guangzhou, China

published_or_final_versio

A molecular insight into algal-oomycete warfare : cDNA analysis of Ectocarpus siliculosus infected with the basal oomycete Eurychasma dicksonii

Peer reviewedPublisher PD

Hybrid Ensemble Stacking Techniques for Coronary Artery Disease Prediction Using Machine Learning Algorithms

Throughout history, humanity has been plagued by several outbreaks that have claimed numerous lives. Since coronary artery disease is among the most fatal illnesses that humanity has faced in the modern era, it has been recognized in our time. It links several Coronary Artery Disease (CAD) risk factors to the critical requirement for precise, reliable, and workable methods for early identification and management. In light of this, we suggest a technique called Hybrid Ensemble Stacking that combines Naive Bayes (NB), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Ada Boosting for the prediction of CAD illnesses. To combine the forecasts of the basis models, a meta-logistic regression model is utilized. According to a quantitative study, the ensemble model and brute force feature selection method together produce a classification accuracy for heart disease of up to 92.66%. The suggested stacking model has demonstrated its effectiveness and outperforms current methods in the categorization of cardiac disorders. Several classification issues have been solved successfully using ensemble techniques. The suggested method was constructed using the Sani dataset, which contains 303 nearly completed records. Using Min-Max Normalization, the data are pre-processed to making it suitable for a Machine Learning (ML) model. SMOTE and SelectKBest technique were applied to   increases the accuracy and efficiency of a model. Using the metrics such as accuracy, precision, recall, F1, ROC and log-loss, the outcomes produced by the suggested model had the greatest performance