The Role of Hippo Pathway in Mitosis and Cancer

The Hippo signaling pathway has been recently elucidated as a tumor suppressor pathway controlling cell proliferation and apoptosis. The core of this pathway is a kinase cascade which contains MST1/2 (Mammalian sterile 20-like kinase 1/2), LATS1/2 (large tumor suppressor 1/2) and downstream effector named Yes-associated protein (YAP). MST1/2 transduce their kinase activity mainly through directly phosphorylating LATS1/2. Once phosphorylated and activated, LATS1/2 subsequently phosphorylate and inhibit YAP from translocating to nucleus. Current studies involving the Hippo pathway focus on determining its oncogenic role in various organs/tissues. While those studies provide important insight into the tumor suppressor properties of this pathway, the underlying molecular mechanisms through which the Hippo components exert their oncogenic/suppressing function are poorly understood. Our study found that the adaptor protein Ajuba (recent found as a positive regulator of YAP oncogenic activity) and MST2 (the core kinase in the Hippo pathway), are phosphorylated by CDK1 in mitosis via novel sites. We further characterized the phospho-regulation of Ajuba and MST2 in mitosis and examined the functional significance of the phosphorylation. Mutation of those phosphorylation sites impact cell proliferation in vitro and tumorigenesis in vivo. Our group has recently shown that the downstream effector of the Hippo pathway, YAP, is phosphorylated during mitosis and activated in a CDK1-dependent manner. In this study, we generated, for the first time, a doxycycline-inducible mouse model in which active YAP was specifically expressed in the pancreas. Interestingly, this mouse model develops pancreatic acinar-to-ductal metaplasia (ADM) in two weeks. Moreover, significant body weight loss and food intake decrease were observed after YAP induction in the pancreas, which are characteristics of cachexia. Cachexia is a wasting syndrome associated with typical types of cancer, particularly the gastrointestinal tract cancer and lung cancer. Among those cancer types, pancreatic ductal adenocarcinoma (PDAC) has the highest incidence of cancer cachexia. Therefore, our study suggests a potential role of YAP in pancreatic cancer-associated cachexia (CAC)

Explicit solutions for a class of nonlinear backward stochastic differential equations and their nodal sets

In this paper, we investigate a class of nonlinear backward stochastic differential equations (BSDEs) arising from financial economics, and give specific information about the nodal sets of the related solutions. As applications, we are able to obtain the explicit solutions to an interesting class of nonlinear BSDEs including the k-ignorance BSDE arising from the modeling of ambiguity of asset pricing

Large Language Models at Work in China's Labor Market

This paper explores the potential impacts of large language models (LLMs) on the Chinese labor market. We analyze occupational exposure to LLM capabilities by incorporating human expertise and LLM classifications, following Eloundou et al. (2023)'s methodology. We then aggregate occupation exposure to the industry level to obtain industry exposure scores. The results indicate a positive correlation between occupation exposure and wage levels/experience premiums, suggesting higher-paying and experience-intensive jobs may face greater displacement risks from LLM-powered software. The industry exposure scores align with expert assessments and economic intuitions. We also develop an economic growth model incorporating industry exposure to quantify the productivity-employment trade-off from AI adoption. Overall, this study provides an analytical basis for understanding the labor market impacts of increasingly capable AI systems in China. Key innovations include the occupation-level exposure analysis, industry aggregation approach, and economic modeling incorporating AI adoption and labor market effects. The findings will inform policymakers and businesses on strategies for maximizing the benefits of AI while mitigating adverse disruption risks

Optimizing Video Object Detection via a Scale-Time Lattice

High-performance object detection relies on expensive convolutional networks to compute features, often leading to significant challenges in applications, e.g. those that require detecting objects from video streams in real time. The key to this problem is to trade accuracy for efficiency in an effective way, i.e. reducing the computing cost while maintaining competitive performance. To seek a good balance, previous efforts usually focus on optimizing the model architectures. This paper explores an alternative approach, that is, to reallocate the computation over a scale-time space. The basic idea is to perform expensive detection sparsely and propagate the results across both scales and time with substantially cheaper networks, by exploiting the strong correlations among them. Specifically, we present a unified framework that integrates detection, temporal propagation, and across-scale refinement on a Scale-Time Lattice. On this framework, one can explore various strategies to balance performance and cost. Taking advantage of this flexibility, we further develop an adaptive scheme with the detector invoked on demand and thus obtain improved tradeoff. On ImageNet VID dataset, the proposed method can achieve a competitive mAP 79.6% at 20 fps, or 79.0% at 62 fps as a performance/speed tradeoff.Comment: Accepted to CVPR 2018. Project page: http://mmlab.ie.cuhk.edu.hk/projects/ST-Lattice

Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment

Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission and processing power. Encoding the image information in quantum-mechanical systems instead of classical ones and replacing classical with quantum information processing may alleviate some of these challenges. By encoding and processing the image information in quantum-mechanical systems, we here demonstrate the framework of quantum image processing, where a pure quantum state encodes the image information: we encode the pixel values in the probability amplitudes and the pixel positions in the computational basis states. Our quantum image representation reduces the required number of qubits compared to existing implementations, and we present image processing algorithms that provide exponential speed-up over their classical counterparts. For the commonly used task of detecting the edge of an image, we propose and implement a quantum algorithm that completes the task with only one single-qubit operation, independent of the size of the image. This demonstrates the potential of quantum image processing for highly efficient image and video processing in the big data era.Comment: 13 pages, including 9 figures and 5 appendixe

Palaeosedimentary Environment and Formation Mechanism of High-Quality Xujiahe Source Rocks, Sichuan Basin, South China

AbstractTriassic Xujiahe source rocks, the main gas source of shallow tight gas, are the most typical continental coal-bearing source rocks in the Sichuan Basin, South China. However, the organic matter enrichment section cannot be identified easily, leading to limited progress in the exploration of coal-bearing tight gas. This paper reveals the main controlling factors of the organic matter enrichment, reconstructs the evolution process of the Xujiahe palaeosedimentary environment, proposes a dynamic enrichment mechanism of the organic matter, and determines the organic matter enrichment section of the high-quality coal-bearing source rocks by geochemical characteristics of the source rocks, major elements, and trace elements. The results show that the Xujiahe sedimentary environment can be divided into a fluctuating stage of transitional sedimentation, stable stage of transitional sedimentation, fluctuating stage of continental sedimentation, and stable stage of continental sedimentation. The Xujiahe source rocks were featured with high-quality coal-bearing source rocks with high total organic carbon and maturity and good parent material in the stable stage of transitional sedimentation and fluctuating stage of continental sedimentation, in which the water was connected with the Palaeo-Tethys Ocean with abundant terrestrial organisms. The water was shallow in the fluctuating stage of transitional sedimentation with a low sedimentation rate, leading to poor organic matter enrichment. The Palaeo-Tethys Ocean withdrew westward from the Yangtze plate in the late period of the fluctuating stage of continental sedimentation, leading to the absence of algae and dinosteranes and a decrease in biological productivity in the stable stage of continental sedimentation. Therefore, high terrestrial inputs and biological productivity and high sedimentation rate were conducive to the organic matter preservation in the coal-bearing source rocks

Active YAP promotes pancreatic cancer cell motility, invasion and tumorigenesis in a mitotic phosphorylation-dependent manner through LPAR3.

The transcriptional co-activator Yes-associated protein, YAP, is a main effector in the Hippo tumor suppressor pathway. We recently defined a mechanism for positive regulation of YAP through CDK1-mediated mitotic phosphorylation. Here, we show that active YAP promotes pancreatic cancer cell migration, invasion and anchorage-independent growth in a mitotic phosphorylation-dependent manner. Mitotic phosphorylation is essential for YAP-driven tumorigenesis in animals. YAP reduction significantly impairs cell migration and invasion. Immunohistochemistry shows significant upregulation and nuclear localization of YAP in metastases when compared with primary tumors and normal tissue in human. Mitotic phosphorylation of YAP controls a unique transcriptional program in pancreatic cells. Expression profiles reveal LPAR3 (lysophosphatidic acid receptor 3) as a mediator for mitotic phosphorylation-driven pancreatic cell motility and invasion. Together, this work identifies YAP as a novel regulator of pancreatic cancer cell motility, invasion and metastasis, and as a potential therapeutic target for invasive pancreatic cancer