Prediction of 5-year cardiovascular disease risk in people with type 2 diabetes mellitus:derivation in Nanjing, China and external validation in Scotland, UK

BACKGROUND: To use routinely collected data to develop a five-year cardiovascular disease (CVD) risk prediction model for Chinese adults with type 2 diabetes with validation of its performance in a population of European ancestry. METHODS: People with incident type 2 diabetes and no history of CVD at diagnosis of diabetes between 2008 and 2017 were included in derivation and validation cohorts. The derivation cohort was identified from a pseudonymized research extract of data from the First Affiliated Hospital of Nanjing Medical University (NMU). Five-year risk of CVD was estimated using basic and extended Cox proportional hazards regression models including 6 and 11 predictors respectively. The risk prediction models were internally validated and externally validated in a Scottish population–based cohort with CVD events identified from linked hospital records. Discrimination and calibration were assessed using Harrell’s C-statistic and calibration plots, respectively. RESULTS: Mean age of the derivation and validation cohorts were 58.4 and 59.2 years, respectively, with 53.5% and 56.9% men. During a median follow-up time of 4.75 [2.67, 7.42] years, 18,827 (22.25%) of the 84,630 people in the NMU-Diabetes cohort and 8,763 (7.31%) of the Scottish cohort of 119,891 people developed CVD. The extended model had a C-statistic of 0.723 [0.721–0.724] in internal validation and 0.716 [0.713–0.719] in external validation. CONCLUSIONS: It is possible to generate a risk prediction model with moderate discriminative power in internal and external validation derived from routinely collected Chinese hospital data. The proposed risk score could be used to improve CVD prevention in people with diabetes

2,4-Dihydr­oxy-N′-(4-methoxy­benzyl­idene)benzohydrazide

The mol­ecule of the title compound, C15H14N2O4, displays a trans configuration with respect to the hydrazide C=N bond. The dihedral angle between the two benzene rings is 15.0 (2)°. In the crystal structure, mol­ecules are linked through inter­molecular O—H⋯N and O—H⋯O hydrogen bonds, forming layers parallel to the ab plane; an intramolecular N—H⋯O hydrogen bond is also present

Poly(ADP-ribose) Polymerase 1 Is Indispensable for Transforming Growth Factor-β Induced Smad3 Activation in Vascular Smooth Muscle Cell

BACKGROUND: Transforming growth factor type-β (TGF-β)/Smad pathway plays an essential role in vascular fibrosis. Reactive oxygen species (ROS) generation also mediates TGF-β signaling-induced vascular fibrosis, suggesting that some sort of interaction exists between Smad and redox pathways. However, the underlying molecular mechanism is largely unknown. This study aims to investigate the influence of poly(ADP-ribose) polymerase 1 (PARP1), a downstream effector of ROS, on TGF-β signaling transduction through Smad3 pathway in rat vascular smooth muscle cells (VSMCs). METHODS AND RESULTS: TGF-β1 treatment promoted PARP1 activation through induction of ROS generation in rat VSMCs. TGF-β1-induced phosphorylation and nuclear accumulation of Smad3 was prevented by treatment of cells with PARP inhibitor, 3-aminobenzamide (3AB) or N-(6-oxo-5,6-dihydrophenanthridin-2-yl)-2-(N,N-dimethylamino)acetami (PJ34), or PARP1 siRNA. TGF-β1 treatment promoted poly(ADP-ribosy)lation of Smad3 via activation of PARP1 in the nucleus. Poly(ADP-ribosy)lation enhanced Smad-Smad binding element (SBE) complex formation in nuclear extracts and increased DNA binding activity of Smad3. Pretreatment with 3AB, PJ34, or PARP1 siRNA prevented TGF-β1-induced Smad3 transactivation and expression of Smad3 target genes, including collagen Iα1, collagen IIIα1 and tissue inhibitor of metalloproteinase 1, in rat VSMCs. CONCLUSIONS: PARP1 is indispensable for TGF-β1 induced Smad3 activation in rat VSMCs. Targeting PARP1 may be a promising therapeutic approach against vascular diseases induced by dysregulation of TGF-β/Smad3 pathway

(E)-N′-(5-Chloro-2-hydroxy­benzyl­idene)-3,5-dihydroxy­benzohydrazide mono­hydrate

In the title compound, C14H11ClN2O4·H2O, the dihedral angle between the two benzene rings is 8.5 (2)° and an intra­molecular O—H⋯N hydrogen bond is observed in the Schiff base mol­ecule. In the crystal structure, the water mol­ecule accepts an N—H⋯O hydrogen bond and makes O—H⋯O hydrogen bonds to two further Schiff base mol­ecules. Further inter­molecular O—H⋯O hydrogen bonds lead to the formation of layers parallel to the bc plane

A General SIMD-based Approach to Accelerating Compression Algorithms

Compression algorithms are important for data oriented tasks, especially in the era of Big Data. Modern processors equipped with powerful SIMD instruction sets, provide us an opportunity for achieving better compression performance. Previous research has shown that SIMD-based optimizations can multiply decoding speeds. Following these pioneering studies, we propose a general approach to accelerate compression algorithms. By instantiating the approach, we have developed several novel integer compression algorithms, called Group-Simple, Group-Scheme, Group-AFOR, and Group-PFD, and implemented their corresponding vectorized versions. We evaluate the proposed algorithms on two public TREC datasets, a Wikipedia dataset and a Twitter dataset. With competitive compression ratios and encoding speeds, our SIMD-based algorithms outperform state-of-the-art non-vectorized algorithms with respect to decoding speeds