Publications by authors named "Y Q Cheng"

Converting natural vegetation to croplands alters the local land surface energy budget. Here, we use two decades of satellite data and a physics-based framework to analyse the biophysical mechanisms by which croplands influence daily mean land surface temperature (LST). Globally, 60% of croplands exhibit an annual warming effect, while 40% have a cooling effect compared to their surrounding natural ecosystems.

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Somatic variants play a crucial role in the occurrence and progression of cancer. However, in the absence of matched normal controls, distinguishing between germline and somatic variants becomes challenging in tumor samples. The existing tumor-only genomic analysis methods either suffer from limited performance or insufficient interpretability due to an excess of features.

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Objective: Epithelial-mesenchymal transition (EMT) and metastasis are the primary causes of mortality in non-small-cell lung cancer (NSCLC). 5'-3' exoribonuclease 2 (XRN2) plays an important role in the process of tumor EMT. Thus, this investigation mainly aimed to clarify the precise molecular pathways through which XRN2 contributes to EMT and metastasis in NSCLC.

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Objective: Gestational diabetes mellitus (GDM) is a common complication during pregnancy and increases the risk of metabolic diseases in offspring. We hypothesize that the poor intrauterine environment in pregnant women with GDM may lead to chromosomal DNA damage and telomere damage in umbilical cord blood cells, providing evidence of an association between intrauterine programming and increased long-term metabolic disease risk in offspring.

Methods: We measured telomere length (TL), serum telomerase (TE) activity, and oxidative stress markers in umbilical cord blood mononuclear cells (CBMCs) from pregnant women with GDM (N=200) and healthy controls (Ctrls) (N=200) and analysed the associations of TL with demographic characteristics, biochemical indicators, and blood glucose levels.

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Background: Risk prediction models can identify individuals at high risk of chronic liver disease (CLD), but there is limited evidence on the performance of various models in diverse populations. We aimed to systematically review CLD prediction models, meta-analyze their performance, and externally validate them in 0.5 million Chinese adults in the China Kadoorie Biobank (CKB).

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