Coastal flooding catastrophes have affected human societies on coastal 15 plains around the world on several occasions in the past, and are threatening 21 th 16 century societies under global warming and sea-level rise. However, the role of 17 coastal flooding in the interruption of the Neolithic Liangzhu culture in the lower 18 Yangtze valley, East China coast has been long contested. In this study, we used a 19 well-dated Neolithic site (the Yushan site) close to the present coastline to 20 demonstrate a marine drowning event at the terminal stage of the Liangzhu culture 21 and discuss its linkage to relative sea-level rise. We analysed sedimentology, 22 chronology, organic elemental composition, diatoms and dinoflagellate cysts for 2 23 several typical profiles at the Yushan site. The field and sedimentary data provided 24 clear evidence of a palaeo-typhoon event that overwhelmed the Yushan site at ~2560 25 BCE, which heralded a period of marine inundation and ecological deterioration at 26 the site. We also infer an acceleration in sea-level rise at 2560-2440 BCE from the 27 sedimentary records at Yushan, which explains the widespread signatures of coastal 28 flooding across the south Yangtze coastal plain at that time. The timing of this mid-29 Holocene coastal flooding coincided with the sudden disappearance of the advanced 30 and widespread Liangzhu culture along the lower Yangtze valley. We infer that 31 extreme events and flooding accompanying accelerated sea-level rise were major 32 causes of vulnerability for prehistoric coastal societies.33 34 35 39 (Woodruff et al., 2013). The vulnerability of low-lying coastal plains and deltas 40 across the world is further exacerbated due to human-induced sediment starvation and 41 land sinking (Syvitski et al., 2009; Giosan et al., 2014). The west Pacific Ocean coast 42 is one of the most vulnerable regions in the world because it is characterized by active 43 tropical cyclones (Woodruff et al., 2013) and, in recent decades, its rate of relative 44sea-level rise is three times higher than the global mean (Nicholls and Cazenave, 3 45 2010). In the densely-populated Yangtze delta, East China (Fig. 1), models under 46 future climate scenarios predict an increase in flood risk from extreme events and 47 relative sea-level rise by 150% to 400% in the next 50 years (Tessler et al., 2015). In 48 fact, Typhoon Fitow (the strongest October typhoon making landfall in China for over 49 60 years) in 2013 caused flooding to a depth >0.5 m across most of the Yaojiang 50Plain, south east of the Hangzhou Bay (Fig. 1C). There is thus clearly an urgent need 51 for integrated research on sea-level rise, extreme events, coastal flooding and human 52 response. 53Coastal flooding is not a new threat. The fact that the south Yangtze coastal 54 plains (Fig. 1B) hold relative thick and rich archaeological records, preserved in 55 marine and deltaic flood basin sediments (Zong et al., 2007;Zheng et al., 2012), is 56 direct witness of past flooding of these areas during human occupation. N...

Our data indicate that miR-448 functions as a tumor suppressor in ovarian cancer, which exerts its activity by suppressing the expression of CXCL12.

Background Despite the clinical success of androgen receptor (AR)‐targeted therapies, prostate cancer (PCa) inevitably progresses to castration‐resistant prostate cancer (CRPC). Transcription factor 6 α (ATF6α), an effector of the unfolded protein response (UPR) that modulates the cellular response to endoplasmic reticulum (ER) stress, has been linked to tumor development, metastasis, and relapse. However, the role of ATF6α in CRPC remains unclear. Methods The effect of ATF6α on the CRPC‐like phenotype in PCa cells was evaluated by 3‐(4,5‐dimethylthiazol‐2‐yl)−5‐(3‐carb‐Oxymethoxyphenyl)−2‐(4‐sulfophenyl)−2H‐tetrazolium inner salt (MTS), 5‐Bromo‐2‐deoxyUridine (BrdU) incorporation analysis, and cell death assay. Mechanistically, bioinformatic analysis was utilized to evaluate the potential of PLA2G4A as the target of ATF6α. Moreover, Western blot analysis, real‐time polymerase chain reaction, chromatin immunoprecipitation, arachidonic acid (AA), and prostaglandin E2 (PGE2) assays were performed to identify the regulatory effect of ATF6α on PLA2G4A. Results In this study, we found that the increase of ATF6α expression in response to androgen deprivation generates PCa cells with a CRPC‐like phenotype. PCa cells with high levels of ATF6α expression are resistant to ferroptosis, and genetic and pharmacological inhibition of ATF6α could, therefore, promote the ferroptotic death of tumor cells and delay PCa progression. Molecular analyses linked ATF6α regulation of ferroptosis to the PLA2G4A‐mediated release of AA and the resulting increase in PGE2 production, the latter of which acts as an antiferroptotic factor. Conclusions This study defines ATF6α as a novel antiferroptotic regulator that exacerbates PCa progression. In addition, our data establish ATF6α‐PLA2G4A signaling as an important pathological pathway in PCa, and targeting this pathway may be a novel treatment strategy.

Spectator or actor? Density functional theory calculations were performed to examine the role of the base in the nickel‐catalyzed cross‐coupling of aryl phosphates with arylboronic acids. Potassium phosphate was found to not act as a spectator base but was involved in the transmetalation step, as shown by a lower barrier than that of a base‐free process, owing to the activation of the carbonboron bond by the base. Further experimental observations support the theoretical findings.

Semantic image segmentation has recently witnessed considerable progress by training deep convolutional neural networks (CNNs). The core issue of this technique is the limited capacity of CNNs to depict visual objects. Existing approaches tend to utilize approximate inference in a discrete domain or additional aides and do not have a global optimum guarantee. We propose the use of the multi-label manifold ranking (MR) method in solving the linear objective energy function in a continuous domain to delineate visual objects and solve these problems. We present a novel embedded single stream optimization method based on the MR model to avoid approximations without sacrificing expressive power. In addition, we propose a novel network, which we refer to as dual multi-scale manifold ranking (DMSMR) network, that combines the dilated, multi-scale strategies with the single stream MR optimization method in the deep learning architecture to further improve the performance. Experiments on high resolution images, including close-range and remote sensing datasets, demonstrate that the proposed approach can achieve competitive accuracy without additional aides in an end-to-end manner.