Potential morphological responses of an artificial beach to a flood in extreme events: field observation and numerical modelling

Conch Island is a typical artificial island at the Tanghe Estuary in Bohai Sea,China.To improve natural environment and boost local tourism,beach nourishment will be applied to its north-western shore.The projected beach is landward and opposite to the Jinmeng Bay Beach.Nowadays,with climate changes,frequent heavy rainfalls in Hebei Province rise flood hazards at the Tanghe Estuary.Under this circumstance,potential influences on the projected beach of a flood are investigated for sustainable managements.A multi-coupled model is established and based on the data from field observations,where wave model,flow model and multifraction sediment transport model are included.In addition,the impacts on the projected beach of different components in extreme events are discussed,including the spring tides,storm winds,storm waves,and sediment inputs.The numerical results indicate the following result.(1)Artificial islands protect the coasts from erosion by obstructing landward waves,but rise the deposition risks along the target shore.(2)Flood brings massive sediment inputs and leads to scours at the estuary,but the currents with high sediment concentration contribute to the accretions along the target shore.(3)The projected beach mitigates flood actions and reduces the maximum mean sediment concentration along the target shore by 20%.(4)The storm winds restrict the flood and decrease the maximum mean sediment concentration by 21%.With the combined actions of storm winds and waves,the maximum value further declines by 38%.(5)A quadratic polynomial relationship between the deposition depths and the maximum sediment inputs with flood is established for estimations on the potential morphological changes after the flood process in extreme events.For the uncertainty of estuarine floods,continuous monitoring on local hydrodynamic variations and sediment characteristics at Tanghe Estuary is necessary.

Do nocturnal birds use acoustic and visual cues to avoid predation by bats?

Anti-predation strategies are critical to animal survival and are fundamental to deciphering predator–prey interactions.As an important defense strategy,sensory predator detection(such as through acoustic and visual cues)enables animals to assess predation risk and execute predator-avoidance behavior;however,there are limited studies on the anti-predation behavior of nocturnal animals.The prey of bats provides an excellent representative system for examining the anti-predation behavior of nocturnal animals.Here,we broadcasted different types of echolocation calls of the bird-eating bat Ia io to two wild passerine birds,namely,Zosterops japonicus and Sinosuthora webbiana,that are preyed upon by I.io,and presented the birds with individual bats under different light intensities.The results showed that both bird species were able to perceive the low-frequency audible portion of the bats’echolocation calls;however,they did not exhibit escape responses to the acoustic stimuli.In the dark and under moonlit conditions,both bird species were unable to respond to active bats at close range and the birds only exhibited evasive flight behavior when bats approached or touched them.These results suggest that nocturnal passerine birds may not be able to use acoustic or visual cues to detect bats and adopt evasive maneuvers to avoid predation.This work suggests that bat predation pressure may not elicit primary predator-avoidance responses in nocturnal passerine birds.The results provide new insights into the anti-predation behavior of nocturnal animals.

Exosome miRNAs profiling in serum and prognostic evaluation in patients with multiple myeloma

MicroRNAs(MiRNAs)carried by exosomes play pivotal roles in the crosstalk between cell components in the tumor microenvironment.Our study aimed at identifying the expression profile of exosomal miRNAs(exo-miRNAs)in the serum of multiple myeloma(MM)patients and investigating the regulation networks and their potential functions by integrated bioinformatics analysis.Exosomes in serum from 19 newly diagnosed MM patients and 9 healthy donors were isolated and the miRNA profile was investigated by small RNA sequencing.Differential expression of exo-miRNAs was calculated and target genes of miRNAs were predicted.CytoHubba was applied to identify the hub miRNAs and core target genes.The LASSO Cox regression model was used to develop the prognostic model,and the ESTIMATE immune score was calculated to investigate the correlation between the model and immune status in MM patients.The top six hub differentially expressed serum exo-miRNAs were identified.513 target genes of the six hub exo-miRNAs were confirmed to be differentially expressed in MM cells in the Zhan Myeloma microarray dataset.Functional enrichment analysis indicated that these target genes were mainly involved in mRNA splicing,cellular response to stress,and deubiquitination.13 core exo-miRNA target genes were applied to create a novel prognostic signature to provide risk stratification for MM patients,which is associated with the immune microenvironment of MM patients.Our study comprehensively investigated the exo-miRNA profiles in MM patients.A novel prognostic signature was constructed to facilitate the risk stratification of MM patients with distinct outcomes.

Artificial intelligence in gastric cancer:applications and challenges

Gastric cancer(GC)is one of the most common malignant tumors with high mortality.Accurate diagnosis and treatment decisions for GC rely heavily on human experts’careful judgments on medical images.However,the improvement of the accuracy is hindered by imaging conditions,limited experience,objective criteria,and inter-observer discrepancies.Recently,the developments of machine learning,especially deep-learning algorithms,have been facilitating computers to extract more information from data automatically.Researchers are exploring the far-reaching applications of artificial intelligence(AI)in various clinical practices,including GC.Herein,we aim to provide a broad framework to summarize current research on AI in GC.In the screening of GC,AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological confirmation.In the diagnosis of GC,AI can support tumor-node-metastasis(TNM)staging and subtype classification.For treatment decisions,AI can help with surgical margin determination and prognosis prediction.Meanwhile,current approaches are challenged by data scarcity and poor interpretability.To tackle these problems,more regulated data,unified processing procedures,and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.

RXRα agonist bexarotene attenuates radiation-induced skin injury by relieving oxidative stress

Objective: To investigate the protective effect of bexarotene in radiation-induced skin injury and elucidate underlying mechanism.Methods: Irradiated cellular and animal models were established using an X-ray linear accelerator. Cell viabilityand apoptosis were evaluated by CCK8 and flow cytometry. In vivo protective effect of bexarotene was measuredin irradiated SD rats. The antioxidant capacity of bexarotene was validated by DCF-DA method. The signalingpathways involved in bexarotene-mediated skin repair were enriched by RNA sequencing.Results: Bexarotene could significantly restore the proliferation and inhibit the apoptosis of WS1 cells with radiation damage (P < 0.05). Moreover, bexarotene could effectively shorten the process of skin damage andpromote skin repair in a rat model of radiation-induced skin injury (P < 0.05). Mechanistically, bexaroteneeffectively reduced the expression of RXRα (P < 0.05), thus leading to an early decrease in reactive oxygen species(ROS) after radiation exposure. Furthermore, a transcriptome analysis indicated that bexarotene-mediated recovery of radiation damage involves redox signaling, immune regulation, lipid metabolism and autophagy.Conclusion: Bexarotene is a promising therapeutic agent in the treatment of radiation-induced skin injury.