Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.
Background A comprehensive evaluation of the independent and combined associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality is required for assessment of the impact of kidney function on risk in the general population, with implications for improving the definition and staging of chronic kidney disease (CKD). Methods A collaborative meta-analysis of general population cohorts was undertaken to pool standardized data for all-cause and cardiovascular mortality. The two kidney measures and potential confounders from 14 studies (105,872 participants; 730,577 person-years) with urine albumin-to-creatinine ratio (ACR) measurements and seven studies (1,128,310 participants; 4,732,110 person-years) with urine protein dipstick measurements were modeled. Findings In ACR studies, mortality risk was unrelated to eGFR between 75-105 ml/min/1·73 m2 and increased at lower eGFR. Adjusted hazard ratios (HRs) for all-cause mortality at eGFR 60, 45, and 15 (versus 95) ml/min/1·73 m2 were 1·18 (95% CI: 1·05-1·32), 1·57 (1·39-1·78), and 3·14 (2·39-4·13), respectively. ACR was associated with mortality risk linearly on the log-log scale without threshold effects. Adjusted HRs for all-cause mortality at ACR 10, 30, and 300 (versus 5) mg/g were 1·20 (1·15-1·26), 1·63 (1·50-1·77), and 2·22 (1·97-2·51). eGFR and ACR were multiplicatively associated with mortality without evidence of interaction. Similar findings were observed for cardiovascular mortality and in dipstick studies. Interpretation Lower eGFR (<60 ml/min/1·73 m2) and higher albuminuria (ACR ≥10 mg/g) were independent predictors of mortality risk in the general population. This study provides quantitative data for using both kidney measures for risk evaluation and CKD definition and staging.
The recent discovery of mutations in metabolic enzymes has rekindled interest in harnessing the altered metabolism of cancer cells for cancer therapy. One potential drug target is isocitrate dehydrogenase 1 (IDH1), which is mutated in multiple human cancers. Here, we examine the role of mutant IDH1 in fully transformed cells with endogenous IDH1 mutations. A selective R132H-IDH1 inhibitor (AGI-5198) identified through a high-throughput screen blocked, in a dose-dependent manner, the ability of the mutant enzyme (mIDH1) to produce R-2-hydroxyglutarate (R-2HG). Under conditions of near-complete R-2HG inhibition, the mIDH1 inhibitor induced demethylation of histone H3K9me3 and expression of genes associated with gliogenic differentiation. Blockade of mIDH1 impaired the growth of IDH1-mutant—but not IDH1–wild-type—glioma cells without appreciable changes in genome-wide DNA methylation. These data suggest that mIDH1 may promote glioma growth through mechanisms beyond its well-characterized epigenetic effects.
Language model pre-training, such as BERT, has significantly improved the performances of many natural language processing tasks. However, pre-trained language models are usually computationally expensive, so it is difficult to efficiently execute them on resourcerestricted devices. To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer-based models. By leveraging this new KD method, the plenty of knowledge encoded in a large "teacher" BERT can be effectively transferred to a small "student" Tiny-BERT. Then, we introduce a new two-stage learning framework for TinyBERT, which performs Transformer distillation at both the pretraining and task-specific learning stages. This framework ensures that TinyBERT can capture the general-domain as well as the task-specific knowledge in BERT. TinyBERT 41 with 4 layers is empirically effective and achieves more than 96.8% the performance of its teacher BERT BASE on GLUE benchmark, while being 7.5x smaller and 9.4x faster on inference. TinyBERT 4 is also significantly better than 4-layer state-of-the-art baselines on BERT distillation, with only ∼28% parameters and ∼31% inference time of them. Moreover, TinyBERT 6 with 6 layers performs on-par with its teacher BERT BASE .
Chemical ReviewsREVIEW resorcinol and phthalic anhydride via FriedelÀCrafts acylation/ cyclodehydration. 25 Some of the advantageous features of the fluorescein fluorophores are good water solubility, visible excitation and emission (an absorption maximum at 494 nm and emission maximum of 521 nm in water), and maximum brightness at physiological pH. 26 Similarly, fluorescein derivates are nonfluorescent when they exist in the lactone form, and the ringopened form can induce color changes and fluorescence enhancements (Figure 1). Spirocyclic derivatives of rhodamine and fluorescein dyes are useful sensing platforms because the ring-opening process leads to a turn-on fluorescence change. Since the first rhodamine-based fluorescent chemosensor for Cu(II) was reported by Anthony W. Czarnik in 1997, a large number of papers involving fluorescent chemosensors based on spiroring-opening processes have been published. The analytic objects have included various metal ions
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