Nanjing University

About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.

Cancer associated fibroblasts: An essential role in the tumor microenvironment (Review)

Abstract: Fibroblasts in the tumor stroma are well recognized as having an indispensable role in carcinogenesis, including in the initiation of epithelial tumor formation. The association between cancer cells and fibroblasts has been highlighted in several previous studies. Regulation factors released from cancer-associated fibroblasts (CAFs) into the tumor microenvironment have essential roles, including the support of tumor growth, angiogenesis, metastasis and therapy resistance. A mutual interaction between tumor-induced fibroblast activation, and fibroblast-induced tumor proliferation and metastasis occurs, thus CAFs act as tumor supporters. Previous studies have reported that by developing fibroblast-targeting drugs, it may be possible to interrupt the interaction between fibroblasts and the tumor, thus resulting in the suppression of tumor growth, and metastasis. The present review focused on the reciprocal feedback loop between fibroblasts and cancer cells, and evaluated the potential application of anti-CAF agents in the treatment of cancer.

The Long Noncoding RNA HOTAIR Contributes to Cisplatin Resistance of Human Lung Adenocarcinoma Cells via downregualtion of p21WAF1/CIP1 Expression

Abstract: HOTAIR, a long intervening non-coding RNA (lincRNA), associates with the Polycomb Repressive Complex 2 (PRC2) and is reported to reprogram chromatin organization and promote tumor progression. However, little is known about the roles of this gene in the development of chemoresistance phenotype of lung adenocarcinoma (LAD). Thus, we investigated the involvement of HOTAIR in the resistance of LAD cells to cisplatin. In this study, we show that HOTAIR expression was significantly upregulated in cisplatin-resistant A549/DDP cells compared with in parental A549 cells. Knockdown of HOTAIR by RNA interference could resensitize the responses of A549/DDP cells to cisplatin both in vitro and in vivo. In contrast, overexpression of HOTAIR could decrease the sensitivity of A549 and SPC-A1 cells to cisplatin. We also found that the siRNA/HOTAIR1-mediated chemosensivity enhancement was associated with inhibition of cell proliferation, induction of G0/G1 cell-cycle arrest and apoptosis enhancement through regulation of p21WAF1/CIP1 (p21) expression. Also, pcDNA/p21or siRNA/p21 could mimic the effects of siRNA/HOTAIR1 or pcDNA/HOTAIR on the sensitivity of LAD cells to cisplatin. Importantly, siRNA/p21 or pcDNA/p21 could partially rescue the effects of siRNA/HOTAIR1 or pcDNA/HOTAIR on both p21 expression and cisplatin sensitivity in LAD cells. Further, HOTAIR was observed to be significantly downregulated in cisplatin-responding LAD tissues, and its expression was inversely correlated with p21 mRNA expression. Taken together, our findings suggest that upregulation of HOTAIR contributes to the cisplatin resistance of LAD cells, at least in part, through the regulation of p21 expression.

Dual signal amplification of glucose oxidase-functionalized nanocomposites as a trace label for ultrasensitive simultaneous multiplexed electrochemical detection of tumor markers.

Abstract: A novel tracer, glucose oxidase-functionalized nanocomposite, was designed to label the signal antibodies for ultrasensitive multiplexed measurement of tumor markers using a disposable immunosensor...

Flatbands and Emergent Ferromagnetic Ordering in Fe 3 Sn 2 Kagome Lattices

Abstract: A flatband representing a highly degenerate and dispersionless manifold state of electrons may offer unique opportunities for the emergence of exotic quantum phases To date, definitive experimental demonstrations of flatbands remain to be accomplished in realistic materials Here, we present the first experimental observation of a striking flatband near the Fermi level in the layered Fe_{3}Sn_{2} crystal consisting of two Fe kagome lattices separated by a Sn spacing layer The band flatness is attributed to the local destructive interferences of Bloch wave functions within the kagome lattices, as confirmed through theoretical calculations and modelings We also establish high-temperature ferromagnetic ordering in the system and interpret the observed collective phenomenon as a consequence of the synergetic effect of electron correlation and the peculiar lattice geometry Specifically, local spin moments formed by intramolecular exchange interaction are ferromagnetically coupled through a unique network of the hexagonal units in the kagome lattice Our findings have important implications to exploit emergent flat-band physics in special lattice geometries

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

Abstract: One-stage detector basically formulates object detection as dense classification and localization. The classification is usually optimized by Focal Loss and the box location is commonly learned under Dirac delta distribution. A recent trend for one-stage detectors is to introduce an individual prediction branch to estimate the quality of localization, where the predicted quality facilitates the classification to improve detection performance. This paper delves into the representations of the above three fundamental elements: quality estimation, classification and localization. Two problems are discovered in existing practices, including (1) the inconsistent usage of the quality estimation and classification between training and inference and (2) the inflexible Dirac delta distribution for localization when there is ambiguity and uncertainty in complex scenes. To address the problems, we design new representations for these elements. Specifically, we merge the quality estimation into the class prediction vector to form a joint representation of localization quality and classification, and use a vector to represent arbitrary distribution of box locations. The improved representations eliminate the inconsistency risk and accurately depict the flexible distribution in real data, but contain continuous labels, which is beyond the scope of Focal Loss. We then propose Generalized Focal Loss (GFL) that generalizes Focal Loss from its discrete form to the continuous version for successful optimization. On COCO test-dev, GFL achieves 45.0\% AP using ResNet-101 backbone, surpassing state-of-the-art SAPD (43.5\%) and ATSS (43.6\%) with higher or comparable inference speed, under the same backbone and training settings. Notably, our best model can achieve a single-model single-scale AP of 48.2\%, at 10 FPS on a single 2080Ti GPU. Code and models are available at this https URL.