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Wang, Yanyu

Publications and source records attributed to Wang, Yanyu.

Nitrogen management during decarbonization

Decarbonization is crucial to combat climate change. However, some decarbonization strategies could profoundly impact the nitrogen cycle. Here, in this Review, we explore the nitrogen requirements of five major decarbonization strategies to reveal the complex interconnections between the carbon and nitrogen cycles and identify opportunities to enhance their mutually sustainable management. Some decarbonization strategies require substantial new nitrogen production, potentially leading to increased nutrient pollution and exacerbation of eutrophication in aquatic systems. For example, the strategy of substituting 44% of fossil fuels used in marine shipping with ammonia-based fuels could reduce CO 2 emissions by up to 0.38 Gt CO 2 -eq yr -1 but would require a corresponding increase in new nitrogen synthesis of 212 Tg N yr -1 . Similarly, using biofuels to achieve 0.7 ± 0.3 Gt CO 2 -eq yr -1 mitigation would require new nitrogen inputs to croplands of 21–42 Tg N yr -1 . To avoid increasing nitrogen losses and exacerbating eutrophication, decarbonization efforts should be designed to provide carbon–nitrogen co-benefits. Reducing the use of carbon-intensive synthetic nitrogen fertilizer is one example that can simultaneously reduce both nitrogen inputs by 14 Tg N yr -1 and CO 2 emissions by 0.04 (0.03–0.06) Gt CO 2 -eq yr -1 . Future research should guide decarbonization efforts to mitigate eutrophication and enhance nitrogen use efficiency in agriculture, food and energy systems.

54 ENVIRONMENTAL SCIENCES↗

Crowdsourced reliable labeling of safety-rule violations on images of complex construction scenes for advanced vision-based workplace safety

Construction workplace hazard detection requires engineers to analyze scenes manually against many safety rules, which is time-consuming, labor-intensive, and error-prone. Computer vision algorithms are yet to achieve reliable discrimination of anomalous and benign object relations underpinning safety violation detections. Recently developed deep learning-based computer vision algorithms need tens of thousands of images, including labels of the safety rules violated, in order to train deep-learning networks for acquiring spatiotemporal reasoning capacity in complex workplaces. Such training processes need human experts to label images and indicate whether the relationship between the worker, resource, and equipment in the scenes violate spatiotemporal arrangement rules for safe and productive operations. False alarms in those manual labels (labeling no-violation images as having violations) can significantly mislead the machine learning process and result in computer vision models that produce inaccurate hazard detections. Compared with false alarms, another type of mislabels, false negatives (labeling images having violations as “no violations”), seem to have fewer impacts on the reliability of the trained computer vision models.

97 MATHEMATICS AND COMPUTING↗

LncRNA PRAL is closely related to clinical prognosis of multiple myeloma and the bortezomib sensitivity

Chromosome 17p deletions (del(17p)) are present in about 11% of newly diagnosed multiple myeloma (MM) patients and related to inferior prognosis. Bortezomib (BTZ), the first proteasome inhibitor anticancer drug, has a good therapeutic effect for newly diagnosed, relapsed or refractory MM, but is unable to improve the outcome of MM patients with del(17p). Long noncoding RNA (lncRNA) PRAL is located on chromosome 17p, and is associated with the progression and prognosis of different types of cancers. However, little is known about its role in MM. Here, we found that PRAL was downregulated in primary MM cells and cell lines, especially in MM cells with del(17p), and was associated with ISS (international staging system) stage and Durie-Salmon stage in MM patients. Survival curves showed that MM patients with low PRAL expression had a significantly shorter disease-free survival (DFS) and overall survival (OS) than the patients with high PRAL expression. Multivariate Cox regression analysis showed that PRAL expression was an independent predictor for DFS and OS. Then cell proliferation, viability, Ki67 expression, and caspase-3 activity detection showed that PRAL promoted MM cell growth inhibition and apoptosis, and potentiated the anti-MM effect of BTZ in vitro. We further identified and confirmed that miR-210 was the target of PRAL, and miR-210 overexpression overturned the potentiation effect of PRAL on BTZ efficacy. Subsequently, bone morphogenetic protein 2 (BMP2) was confirmed to be the target of miR-210, and PRAL positively regulated the derepression of BMP2 by sponging miR-210. Overexpression of BMP2 potentiated the anti-MM effect of BTZ in vitro. In addition, animal experiments further confirmed that PRAL potentiated BTZ efficacy in vivo. Collectively, our study first revealed a critical role of PRAL-miR-210-BMP2 axis in MM progression, prognosis and treatment with BTZ, and PRAL could become a novel diagnostic, prognostic and therapeutic candidate for MM patients especially for the MM patients harboring del(17p) in the future.

60 APPLIED LIFE SCIENCES↗