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The Tigris–Euphrates dryland river basin has experienced a declining trend in terrestrial water storage (TWS) from April 2002 to June 2017. Using satellite observations and a process-based land surface model, we find that climate variations and direct human interventions explain ∼61% (−0.57 mm month−1) and ∼39% (−0.36 mm month−1) of the negative trend, respectively. We further disaggregate the effects of climate variations and find that interannual climate variability contributes substantially (−0.27 mm month−1) to the negative TWS trend, slightly greater than the decadal climate change (−0.25 mm month−1). Interannual climate variability affects TWS mainly through the nonlinear relationship between monthly TWS dynamics and aridity. Slow recovery of TWS during short wetting periods does not compensate for rapid depletion of TWS through transpiration during prolonged drying periods. Despite enhanced water stress, the dryland ecosystems show slightly enhanced resilience to water stress through greater partitioning of evapotranspiration into transpiration and weak surface “greening” effects. However, the dryland ecosystems are vulnerable to drought impacts. The basin shows straining ecosystem functioning after experiencing a severe drought event. In addition, after the onset of the drought, the dryland ecosystem becomes more sensitive to variations in climate conditions. Significance Statement The purpose of the research is to better understand climate impacts on terrestrial water storage over dryland regions with declining water storage. In our study, we disaggregate three components of climate impacts, namely, decadal climate change, interannual variability, and intra-annual variability. We then use observational datasets and a process-based model to quantify their individual effects on water storage. We find that interannual variability is the most significant climatic contributor to the declining water storage, mainly caused by prolonged drought periods and corresponding quick drying rates due to plant transpiration. We also find that the dryland ecosystem is sensitive and vulnerable to severe drought events. This study is important because 1) it provides a framework to investigate climate impacts on water fluxes and storages, 2) it highlights the importance of vegetation dynamics on dryland hydrology, and 3) it emphasizes the negative impacts of extreme hydroclimatological events on ecosystem functioning.

Anemia of inflammation (AI) is associated with inflammatory diseases, and inflammation-induced iron metabolism disorder is the major pathogenic factor. Earlier studies have reported a tendency of AI in periodontitis patients, but the explicit relationship and possible pathological mechanisms remain unclear. Here, the analyses of both periodontitis patients and a mouse model of ligature-induced experimental periodontitis showed that periodontitis was associated with lower levels of hemoglobin and hematocrit with evidence of systemic inflammation (increased white blood cell levels) and evidence of iron restriction (low serum iron along with a high serum hepcidin and ferritin levels), in accordance with the current diagnosis criteria for AI. Moreover, periodontal therapy improved the anemia status and iron metabolism disorders. Furthermore, the increased level of hepcidin and significant correlation between hepcidin and key indicators of iron metabolism emphasized the pivotal role of hepcidin in the pathogenesis of periodontitis-related AI. Administration of the signal transducer and activator of transcription 3 (STAT3) inhibitors Stattic suggested that the IL-6–STAT3–hepcidin signaling pathway participated in this regulatory process. Together, these findings demonstrated that periodontitis should be considered an inflammatory disease that contributes to the development of AI; furthermore, IL-6–STAT3–hepcidin signaling pathway plays a key regulatory role in the pathogenesis of periodontitis-related AI. Our study will provide new insights into the systemic effects of periodontitis, while meaningfully expanding the spectrum of inflammatory diseases that contribute to AI.

Utilizing mycoremediation is an important direction for managing heavy metal pollution. Zn2+ pollution has gradually become apparent, but there are few reports about its pollution remediation. Here, the Zn2+ remediation potential of Paraisaria dubia, an anamorph of the entomopathogenic fungus Ophiocordyceps gracilis, was explored. There was 60% Zn2+ removed by Paraisaria dubia mycelia from a Zn2+-contaminated medium. To reveal the Zn2+ tolerance mechanism of Paraisaria dubia, transcriptomic and metabolomic were executed. Results showed that Zn2+ caused a series of stress responses, such as energy metabolism inhibition, oxidative stress, antioxidant defense system disruption, autophagy obstruction, and DNA damage. Moreover, metabolomic analyses showed that the biosynthesis of some metabolites was affected against Zn2+ stress. In order to improve the tolerance to Zn2+ stress, the metabolic mechanism of metal ion transport, extracellular polysaccharides (EPS) synthesis, and microcycle conidiation were activated in P. dubia. Remarkably, the formation of microcycle conidiation may be triggered by reactive oxygen species (ROS) and mitogen-activated protein kinase (MAPK) signaling pathways. This study supplemented the gap of the Zn2+ resistance mechanism of Paraisaria dubia and provided a reference for the application of Paraisaria dubia in the bioremediation of heavy metals pollution.

Transfer learning can be applied in deep reinforcement learning to accelerate the training of a policy in a target task by transferring knowledge from a policy learned in a related source task. This is commonly achieved by copying pretrained weights from the source policy to the target policy prior to training, under the constraint that they use the same model architecture. However, not only does this require a robust representation learned over a wide distribution of states -- often failing to transfer between specialist models trained over single tasks -- but it is largely uninterpretable and provides little indication of what knowledge is transferred. In this work, we propose an alternative approach to transfer learning between tasks based on action advising, in which a teacher trained in a source task actively guides a student's exploration in a target task. Through introspection, the teacher is capable of identifying when advice is beneficial to the student and should be given, and when it is not. Our approach allows knowledge transfer between policies agnostic of the underlying representations, and we empirically show that this leads to improved convergence rates in Gridworld and Atari environments while providing insight into what knowledge is transferred., Accepted to CoLLAs 2023

Oil and gas (O&G) companies, as key players in the contemporary global energy landscape, have evolved within the context of a dynamic interaction between states and markets. However, their role is being transformed radically by two successive “global shifts”: economic globalization—driving energy demand growth patterns—and climate change—driving energy system transformation and decarbonization, both of which require them to reconsider their business strategies. Using an interdisciplinary lens that draws on human geography, strategy and international business, and international political economy, we propose an integrated conceptual framework for two periods—the 1990s–early 2010s and the post-Paris Agreement era—to explore the nature of strategic responses by O&G companies to these global economic and environmental shifts. We illustrate the linkage of O&G companies' two strategies of (re-)globalization and decarbonization by the aspects of production, finance, and knowledge as internal structures. Energy security is one of the priorities in the macro external environment. It is becoming increasingly difficult for O&G companies to deal with current dilemmas: climate goals require a significant reduction in fossil fuel production and consumption, and pressures from governments, nongovernmental organizations, and investors threaten the long-term survival of O&G companies, while fossil fuel demand will remain high in the short to medium term. At the same time, the post-pandemic recovery and Russia's war in Ukraine are resulting in a re-assessment of the benefits of unfettered globalization. Therefore, global O&G companies face dual challenges in the new era of (re-)globalization and decarbonization and need to make changes to ensure their future viability.

Additional file 1: Sup. Table 1. Experimental materials and reagents. Sup. Figure 1. Differences between MEF50 function groups in microbiome composition at species level. Sup. Figure 2. Taxonomy tree and LDA scores of the groups. (A) Taxonomy tree and LDA scores between MEF50predicted%-low and MEF50predicted%-high groups. (B) Taxonomy tree and LDA scores between the MEF50predicted%-low group and the healthy control group. Circles from within to outward indicate the classification from the phylum to the genus, respectively. Each small circle represents a taxon with its diameter proportional to the relative abundance. Dots with different colors denote the core species of each group. Histogram showing the LDA scores of the biomarkers with statistical differences. Sup. Figure 3. Volcano plot of fold change (≥ 1.2-fold, adjusted p < 0.05) between the MEF50predicted%-low and MEF50predicted%-high groups in subjects with asthma.

Additional file 1: Fig. S1–S9. Additional figures, Table S1. siRNA sequences for knockdown assays, and Table S2. primers for qPCR.

While there has been significant development of models for Plain Language Summarization (PLS), evaluation remains a challenge. This is in part because PLS involves multiple, interrelated language transformations (e.g., adding background explanations, removing specialized terminology). No metrics are explicitly engineered for PLS, and the suitability of other text generation evaluation metrics remains unclear. To address these concerns, our study presents a granular meta-evaluation testbed, APPLS, designed to evaluate existing metrics for PLS. Drawing on insights from previous research, we define controlled perturbations for our testbed along four criteria that a metric of plain language should capture: informativeness, simplification, coherence, and faithfulness. Our analysis of metrics using this testbed reveals that current metrics fail to capture simplification, signaling a crucial gap. In response, we introduce POMME, a novel metric designed to assess text simplification in PLS. We demonstrate its correlation with simplification perturbations and validate across a variety of datasets. Our research contributes the first meta-evaluation testbed for PLS and a comprehensive evaluation of existing metrics, offering insights with relevance to other text generation tasks.

The aim is to establish a model of nonalcoholic fatty liver disease (NAFLD) caused by feeding with high-fat, high-fructose, and high-cholesterol diet (HFFCD) in golden hamsters, and to investigate the characteristics of the NAFLD model and metabolite changes of liver tissue. Golden hamsters were fed HFFCD or control diets for six weeks. Body weight, abdominal fat index, and liver index was assessed, serum parameters, hepatic histology, and liver metabolites were examined. The results showed that body weight, abdominal fat, and liver index of hamsters were significantly increased in the model group, the level of serum total cholesterol (TC), triglyceride (TG), and low density lipoprotein-cholesterol (LDL-C) were significantly increased in model group as well, and high density lipoprotein-cholesterol (HDL-C) was significantly decreased. In addition, lipid deposition in liver tissue formed fat vacuoles of different sizes. Metabonomics analysis of the liver showed that the metabolic pathways of sphingolipid, glycerophospholipids, and arginine biosynthesis were disordered in the NAFLD model. The modeling method is simple, short time, and uniform. It can simulate the early fatty liver caused by common dietary factors, and provides an ideal model for the study of the initial pathogenesis and therapeutic drugs for NAFLD.

Angiogenesis inhibitors targeting the VEGF signaling pathway are developed into drugs for the treatment of vaious diseases, such as cancer, rheumatoid arthritis, and age-related macular degeneration. Recent studies have revealed that oleanolic acid (OA), a natural pentacyclic triterpenoid, inhibited the VEGF/VEGFR2 signaling pathway and angiogenesis in HUVECs, which may represent an attractive VEGF inhibitor. In this paper, rational structural modification towards OA was performed in order to improve its inhibitory effects aganist VEGF and anti-angiogenesis potential. As a result, a series of novel OA derivatives, possessing α,β-unsaturated ketone system in ring A and amide functional group at C-28, were prepared and evaluated for cytotoxicity and their ability to inhibit VEGF-induced abnormal proliferation of HUVECs. The results showed that two promising derivatives, OA-1 and OA-16, exhibited no in vitro cytotoxicity against HUVECs but showed more potent inhibitory activity against VEGF-induced proliferation and angiogenesis in HUVECs, compared with OA. The results of Western blot indicated that OA-1 and OA-16 inhibited VEGF-induced VEGFR2 activation. Furthermore, small interfering RNA experiments were performed to confirm that both compounds inhibited VEGF-induced angiogenesis via VEGFR2. Thus, the present study resulted in the discovery of new promising OA-inspired VEGF inhibitors, which can serve as potential lead compounds for the treatment of angiogenesis-related diseases.

Ex-vivo normothermic machine perfusion (NMP) preserves the liver metabolism at 37°C and has rapidly developed as a promising approach for assessing the viability and improving the performance of organs from expanded criteria donors, including fatty liver grafts. NMP is an effective method for defatting fatty livers when combined with pharmaceutical therapies. Pharmacological agents have been shown to facilitate liver defatting by NMP.This systematic review summarizes available pharmacological therapies for liver defatting, with a particular emphasis on defatting agents that can be employed clinically as defatting components during liver NMP as an ex vivo translational paradigm.NMP provides an opportunity for organ treatment and can be used as a defatting platform in the future with defatting agents. Nagrath's cocktail is the most commonly used defatting cocktail in NMP; however, its carcinogenic components may limit its clinical application. Thus, the combination of a defatting cocktail with a new clinically applicable component, for example, a polyphenolic natural compound, may be a novel pharmacological option.

This paper aims to explore the activity of Codonopsis canescens extract against rheumatoid arthritis(RA) based on the Toll-like receptors(TLRs)/mitogen-activated protein kinases(MAPKs)/nuclear factor kappa B(NF-κB) signaling pathways and its mechanism. The ultra-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry(UPLC-Q-TOF-MS) was used to identify the components of C. canescens extract. Forty-eight male SD rats were randomly divided into six groups, namely the normal group, the model group, the methotrexate(MTX) tablet group, and the low, medium, and high-dose C. canescens extract(ZDS-L, ZDS-M, and ZDS-H) groups, with 8 rats in each group. The model of collagen-induced arthritis in rats was induced by injection of bovine type Ⅱ collagen emulsion. MTX(2.5 mg·kg~(-1)), ZDS-L, ZDS-M, and ZDS-H(0.3 g·kg~(-1), 0.6 g·kg~(-1), and 1.2 g·kg~(-1)) were administrated by gavage. Rats in the normal group and the model group received distilled water. MTX was given once every three days for 28 days, and the rest medicines were given once daily for 28 days. Body weight, degree of foot swelling, arthritis index, immune organ index, synovial histopathological changes, and serum levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), and interleukin-6(IL-6) were observed. Protein expressions of TLR2, TLR4, NF-κB p65, p38 MAPK, and p-p38 MAPK in rats were determined by Western blot. Thirty-four main components were identified by UPLC-Q-TOF-MS, including 15 flavonoids, 7 phenylpropanoids, 4 terpenoids, 4 organic acids, 2 esters, and 2 polyalkynes. As compared with the normal group, the body weight of the model group was significantly decreased(Plt;0.01), and foot swelling(Plt;0.05, Plt;0.01), arthritis index(Plt;0.01), and the immune organ index(Plt;0.01) were significantly increased. The synovial histopathological injury was obviously observed in the model group. The serum levels of inflammatory factors TNF-α, IL-1β, and IL-6 were significantly increased(Plt;0.01), and the protein expression levels of TLR2, TLR4, NF-κB p65, p-p38 MAPK/p38 MAPK in the synovial tissue were significantly increased(Plt;0.01) in the model group. As compared with the model group, the body weights of the ZDS dose groups were increased(Plt;0.01), and the degree of foot swelling(Plt;0.01) and the arthritis index were decreased(Plt;0.05, Plt;0.01). The immune organ index was decreased(Plt;0.01) in the ZDS dose groups, and the synovial tissue hyperplasia and inflammatory cell infiltration were alleviated. The serum levels of TNF-α, IL-1β, and IL-6 were significantly decreased(Plt;0.05, Plt;0.01), and the protein expression levels of TLR2, TLR4, NF-κB p65, p-p38 MAPK/p38 MAPK were decreased(Plt;0.05, Plt;0.01) in the ZDS dose groups. C. canescens extract containing apigenin, tricin, chlorogenic acid, aesculin, ferulic acid, caffeic acid, and oleanolic acid has a good anti-RA effect, and the mechanism may be related to the inhibition of TLRs/MAPKs/NF-κB signaling pathways.

Meta-learning of numerical algorithms for a given task consists of the data-driven identification and adaptation of an algorithmic structure and the associated hyperparameters. To limit the complexity of the meta-learning problem, neural architectures with a certain inductive bias towards favorable algorithmic structures can, and should, be used. We generalize our previously introduced Runge-Kutta neural network to a recursively recurrent neural network (R2N2) superstructure for the design of customized iterative algorithms. In contrast to off-the-shelf deep learning approaches, it features a distinct division into modules for generation of information and for the subsequent assembly of this information towards a solution. Local information in the form of a subspace is generated by subordinate, inner, iterations of recurrent function evaluations starting at the current outer iterate. The update to the next outer iterate is computed as a linear combination of these evaluations, reducing the residual in this space, and constitutes the output of the network. We demonstrate that regular training of the weight parameters inside the proposed superstructure on input/output data of various computational problem classes yields iterations similar to Krylov solvers for linear equation systems, Newton-Krylov solvers for nonlinear equation systems, and Runge-Kutta integrators for ordinary differential equations. Due to its modularity, the superstructure can be readily extended with functionalities needed to represent more general classes of iterative algorithms traditionally based on Taylor series expansions., manuscript (22 pages, 9 figures), supporting information (11 pages, 9 figures)

Action advising is a knowledge transfer technique for reinforcement learning based on the teacher-student paradigm. An expert teacher provides advice to a student during training in order to improve the student's sample efficiency and policy performance. Such advice is commonly given in the form of state-action pairs. However, it makes it difficult for the student to reason with and apply to novel states. We introduce Explainable Action Advising, in which the teacher provides action advice as well as associated explanations indicating why the action was chosen. This allows the student to self-reflect on what it has learned, enabling advice generalization and leading to improved sample efficiency and learning performance - even in environments where the teacher is sub-optimal. We empirically show that our framework is effective in both single-agent and multi-agent scenarios, yielding improved policy returns and convergence rates when compared to state-of-the-art methods, This work has been published by ICRA 2023(979-8-3503-2365-8/23/$31.00 copyright 2023 IEEE)

Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility. However, the applicability of these models is constrained by the limited size and topical breadth of available corpora. We introduce CELLS, the largest (63k pairs) and broadest-ranging (12 journals) parallel corpus for lay language generation. The abstract and the corresponding lay language summary are written by domain experts, assuring the quality of our dataset. Furthermore, qualitative evaluation of expert-authored plain language summaries has revealed background explanation as a key strategy to increase accessibility. Such explanation is challenging for neural models to generate because it goes beyond simplification by adding content absent from the source. We derive two specialized paired corpora from CELLS to address key challenges in lay language generation: generating background explanations and simplifying the original abstract. We adopt retrieval-augmented models as an intuitive fit for the task of background explanation generation, and show improvements in summary quality and simplicity while maintaining factual correctness. Taken together, this work presents the first comprehensive study of background explanation for lay language generation, paving the path for disseminating scientific knowledge to a broader audience. CELLS is publicly available at: https://github.com/LinguisticAnomalies/pls_retrieval.

Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature., This work was primarily supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI [Grant Number 19K19461]. Y.C. was supported by a Senior Research grant [2019R1A2C1086194] from the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies). V.H. received support from the Spanish Ministry of Economy, Industry and Competitiveness [Grant ID: PCIN-2017-046]. J.K. and A.U. were supported by the Czech Science Foundation [project 18-22125S]. A.S. acknowledged funding from European Union’s Horizon 2020 research and innovation programme under grant agreement No 820655 (EXHAUSTION). A.G. was supported by the Medical Research Council-UK [Grant ID: MR/R013349/1], the Natural Environment Research Council UK [Grant ID: NE/R009384/1] and the European Union’s Horizon 2020 Project Exhaustion [Grant ID: 820655]. M.H. was supported by the Japan Science and Technology Agency (JST) as part of SICORP [Grant Number JPMJSC20E4].

The use of silicon-containing steel in the manufacture of transformer cores can save raw materials and greatly reduce the volume and energy consumption of the transformer. A forsterite film of stoichiometry Mg2SiO4 formed on the steel surface provides a certain degree of insulation and forms by reaction between the oxides in internal oxidized zone and a deposited MgO coating during high-temperature annealing. In this work, the morphology evolution of internal oxidized zone and the forsterite film on the steel surface are studied when the arrangement methods for silicon steel and annealing atmosphere are different, then the relationship of morphology between internal oxidized zone and forsterite film is explored. Results showed that the morphology of forsterite film on the steel surface is closely related to the morphology of internal oxidized zone. Metallic iron particles exist in the forsterite film when an iron layer exists in the surface of internal oxidized zone.

Background: The PITX gene family, comprising PITX1, PITX2, and PITX3, is critical in organogenesis and has been evolutionary conserved in animals. PITX genes are associated with the advanced progression and poor prognosis of multiple cancers. However, the relationship between the PITX genes and head and neck squamous cell carcinoma (HNSC) has not been reported.Methods: We used data from The Cancer Genome Atlas (TCGA) to analyze the association between PITX mRNA expression and clinicopathological parameters of patients with HNSC. The prognostic value of PITX genes was evaluated using the Kaplan-Meier plotter. Multivariate Cox analysis was used to screen out prognosis-associated genes to identify better prognostic indicators. The potential roles of PITX1 and PITX2 in HNSC prognosis were investigated using the protein-protein interaction (PPI) network, Gene Ontology (GO) analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The correlation between PITX1 and PITX2 expression or methylation and immune cell infiltration was evaluated using the tumor-immune system interaction database (TISIDB). MethSurv was used to identify DNA methylation and its effect on HNSC prognosis.Results:PITX genes expression was correlated with different cancers. PITX1 and PITX2 expression was lower in the patients with HNSC. In HNSC, PITX1 expression was significantly related to the clinical stage, histologic grade, and N stage, while PITX2 expression was only significantly related to the histologic grade. The high expression of PITX3 was significantly related to the histologic grade, T stage, and N stage. Survival analysis revealed that PITX genes had prognostic value in HNSC, which was supported by multivariate Cox analysis. PPI network and enrichment analysis showed that the genes interacting with PITX1 and PITX2 belonged predominantly to signaling pathways associated with DNA binding and transcription. Of the CpG DNA methylation sites in PITX1 and PITX2, 28 and 22 were related to the prognosis of HNSC, respectively. Additionally, PITX1 and PITX2 expression and methylation was associated with tumor-infiltrating lymphocytes (TILs).Conclusion: The PITX genes were differentially expressed in patients with HNSC, highlighting their essential role in DNA methylation and tumor-infiltrating immune cell regulation, as well as overall prognostic value in HNSC.

High-molecular-weight glutenin subunits (HMW-GSs) are the most critical grain storage proteins that determine the unique processing quality of wheat. Although it is part of the superior HMW-GS pair (Dx5+Dy10), the contribution of the Dy10 subunit to wheat processing quality remains unclear. In this study, we elucidated the effect of Dy10 on wheat processing quality by generating and analyzing a deletion mutant (with the Dy10-null allele) and by elucidating the changes to wheat flour following the incorporation of purified Dy10. The Dy10-null allele was transcribed normally, but there was a lack of the Dy10 subunit. These findings implied that the Dy10-null allele decreased the glutenin:gliadin ratio and negatively affected dough strength (i.e., Zeleny sedimentation value, gluten index, and dough development and stability times) and the bread-making quality; however, it positively affected the biscuit-making quality. The incorporation of various amounts of purified Dy10 into wheat flour had a detrimental effect on biscuit-making quality. The results of this study demonstrate that the Dy10 subunit is essential for maintaining wheat dough strength. Furthermore, the Dy10-null allele may be exploited by soft wheat breeding programs.

Aims The vertical distribution of plant roots is a comprehensive result of plant adaptation to the environment. Limited knowledge on fine vertical root distributions and complex interactions between roots and environmental variables hinders our ability to reliably predict climatic impacts on vegetation dynamics. This study attempts to understand the drought adaptability of plants in arid areas from the perspective of the relationship between vertical root distribution and surroundings. Methods By analyzing root profiles compiled from published studies, the root vertical profiles of two typical phreatophytes, Tamarix ramosissima and Populus euphratica, and their relationships with environmental factors were investigated. A conceptual model was adopted to link the parameter distribution frequency with plant drought adaptability. Important Findings The strong hydrotropism (groundwater-dependent) and flexible water-use strategy of T. ramosissima and P. euphratica help both species survive in hyperarid climates. The differences in the developmental environments between T. ramosissima and P. euphratica can be explained well by the different distribution characteristics of root profiles. That is, higher root plasticity helps T. ramosissima develop a more efficient water-use strategy and therefore survive in more diverse climatic and soil conditions than P. euphratica. We conclude that the higher variation in root profile characteristics of phreatophytes can have greater root adaptability to the surroundings and thus wider hydrological niches and stronger ecological resilience. The inadequacy of models in describing root plasticity limits the accuracy of predicting the future response of vegetation to climate change, which calls for developing process-based dynamic root schemes in Earth system models.

Marine mollusks are a prolific source of secondary metabolites with complex/diverse structures and various aspects of biological activities. For the above-mentioned reason, these animals have been extensively explored and have become the hotspot of the research subject in recent years. It is well documented that mollusks can escape from predation by utilizing bioactive metabolites as defensive chemicals. In the last decade, the possible diet relationship between the South China Sea mollusks and their related potential prey organisms, including sponges, corals, algae, etc. has been systematically investigated. A series of interesting results have been obtained concerning the chemistry, chemoecology, and pharmacological profiles of the studied marine organisms. The present review focuses on recent developments dealing with chemistry, chemoecology, and bioactivity of the South China Sea mollusks and their dietary organisms.

Health literacy has emerged as a crucial factor in making appropriate health decisions and ensuring treatment outcomes. However, medical jargon and the complex structure of professional language in this domain make health information especially hard to interpret. Thus, there is an urgent unmet need for automated methods to enhance the accessibility of the biomedical literature to the general population. This problem can be framed as a type of translation problem between the language of healthcare professionals, and that of the general public. In this paper, we introduce the novel task of automated generation of lay language summaries of biomedical scientific reviews, and construct a dataset to support the development and evaluation of automated methods through which to enhance the accessibility of the biomedical literature. We conduct analyses of the various challenges in solving this task, including not only summarization of the key points but also explanation of background knowledge and simplification of professional language. We experiment with state-of-the-art summarization models as well as several data augmentation techniques, and evaluate their performance using both automated metrics and human assessment. Results indicate that automatically generated summaries produced using contemporary neural architectures can achieve promising quality and readability as compared with reference summaries developed for the lay public by experts (best ROUGE-L of 50.24 and Flesch-Kincaid readability score of 13.30). We also discuss the limitations of the current attempt, providing insights and directions for future work., Yue Guo and Wei Qiu contribute equally to this work. This paper is accepted by AAAI 2021

Groundwater-based irrigation has dramatically expanded over the past decades. It has important implications for terrestrial water, energy fluxes, and food production, as well as local to regional climates. However, irrigation water use is hard to monitor at large scales due to various constraints, including the high cost of metering equipment installation and maintenance, privacy issues, and the presence of illegal or unregistered wells. This study estimates irrigation water amounts using machine learning to integrate in situ pumping records, remote sensing products, and climate data in the Kansas High Plains. We use a random forest regression to estimate the annual irrigation water amount at a reprojected spatial resolution of 6 km based on various data, including remotely sensed vegetation indices and evapotranspiration (ET), land cover, near-surface meteorological forcing, and a satellite-derived irrigation map. In addition, we assess the value of ECOSTRESS ET products for irrigation water use estimation and compare with the baseline results by using MODIS ET. The random forest regression model can capture the temporal and spatial variability of irrigation amounts with a satisfactory accuracy (R2 = 0.82). It performs reasonably well when it is calibrated on the western portion of the study area and tested on the eastern portion that receives more rain than the western one, suggesting its potential transferability to other regions. ECSOTRESS ET and MODIS ET yield a similar irrigation estimation accuracy.

In orthotopic liver transplantation (OLT) recipients, median arcuate ligament syndrome (MALS) is considered a risk factor for hepatic arterial thrombosis (HAT), which is dreadful for OLT recipients. Different alternative surgical procedures have been proposed to overcome the impact of MALS on transplantation, but clinical evidence is still scarce.To evaluate the feasible surgical management of MALS to reduce complications in OLT patients.Data for 288 consecutive patients who underwent OLT at The First Hospital of Jilin University between January 2017 and July 2020 were retrospectively reviewed. The surgical management of median arcuate ligament (MAL) and modifications to the arterial anastomosis were recorded. The perioperative and long-term prognosis of MALS recipients were noted. Detailed preoperative and postoperative data of patients were analyzed in a descriptive manner.Eight patients with MALS were included in this study. The first patient with MALS received no intervention during the primary surgery and developed postoperative HAT. Salvage liver transplantation with MAL division was successfully performed. Gastroduodenal artery (GDA) preservation with splenic artery ligation was performed on three patients, only GDA preservation was performed on two patients, and no intervention was performed on two patients. No patient developed HAT after surgery and postoperative recovery was satisfactory.The preservation of collateral circulation between the superior mesenteric artery and celiac trunk

Funding Information: This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). YW was supported by the China Scholarship Council (number 202006010044). SL was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number APP2009866). QZ was supported by the Program of Qilu Young Scholars of Shandong University, Jinan, China. BW was supported by the China Scholarship Council (number 202006010043). JK and AU were supported by the Czech Science Foundation (project number 20–28560S). NS was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776). S-CP and YLG were supported by the Ministry of Science and Technology (Taiwan; MOST 109–2621-M-002–021). YH was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency. MdSZSC and PHNS were supported by the São Paulo Research Foundation (FAPESP). ST was supported by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600). HO and EI were supported by the Estonian Ministry of Education and Research (IUT34–17). JM was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016). AG and FS were supported by the Medical Research Council UK (grant ID MR/R013349/1), the Natural Environment Research Council UK (grant ID NE/R009384/1), and the EU's Horizon 2020 project, Exhaustion (grant ID 820655). AS, SR, and FdD were supported by the EU's Horizon 2020 project, Exhaustion (grant ID 820655). VH was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046). AT was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). YG was supported by the Career Development Fellowship (number APP1163693) and Leader Fellowship (number APP2008813) of the Australian National Health and Medical Research Council. Statistics South Africa kindly provided the mortality data, but had no other role in the study. This Article is published in memory of Simona Fratianni, who helped to contribute the data for Romania. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council. publishersversion published

Background: Pyrethrum tatsienense (Bureau & Franch.) Ling ex C. Shih (PTLCS) belongs to the family Compositae, which is a perennial medicinal plant mainly distributed in the Qinghai-Tibet Plateau of China. This review provides a comprehensive summary of the ethnopharmacology, phytochemistry, and pharmacology of PTLCS. This review offers valuable references and guidance for researching PTLCS in depth. Methods: The related references of PTLCS were retrieved from an online database, such as Web of Science, Google Scholar, SciFinder, PubMed, SpringLink, Elsevier, Willy, CNKI, and so on. Results: PTLCS is widely reported for treating headaches, head injuries, traumatic injuries, anabrosis, impetigo, hepatitis, and other diseases in the medical field. Phytochemical research revealed that this plant contained flavonoid aglycones, flavonoid glycosides, xanthones, triterpenoids, coumarins, polyacetylenes, volatile oils, and other compounds. Meanwhile, PTLCS exhibited extensive pharmacological activities including anti-cardiac ischemia, anti-hypoxia, hepatoprotective, anti- inflammatory and analgesic, and antioxidant activities. Conclusions: PTLCS is widely used as a Tibetan medicine, which has a variety of chemicals with diverse bioactivities. Therefore, further studies are necessary to perform on the PTLCS to assay biological activities, discover their bioactive constituents, and reveal pharmacological mechanisms. This review may supply an important theoretical basis and valuable reference for in-depth research and exploitations of PTLCS.

Background The introduction of fracture reduction robot can solve the problem of large reduction forces during fracture reduction surgeries and the need to collect multiple medical images. However, because its safety has not been certified, there are few academic achievements on this type of robot. To calculate the safety factor during its operation, a musculoskeletal model needs to be established to study the constraints of muscles on the robot. The existing academic achievements of musculoskeletal modelling are mainly for application such as rehabilitation treatment and collision in car accidents. Methods A musculoskeletal model applied to the fracture reduction robot is proposed in this paper. First, by comparing the characteristics of mainstream muscle models and combining the biological characteristics of the anesthetised muscles, the Hill model was selected as the muscle model for this study. Second, based on the motion composition of six spatial degrees of freedom, five basic fractural malposition situations are proposed. Then, a 170-cm tall male musculoskeletal model was built in Opensim. Based on this model, the muscle force curves of the above malposition situations are calculated. Finally, a similar musculoskeletal model was established in Adams, and the accuracy of its muscle force data was tested. The study is approved by the ethics committee of the Rehabilitation Hospital, National Research Center for Rehabilitation Technical Aids, Beijing, China. Results The muscle force curve of Opensim and Adams model under situations of five basic malposition are compared. Most of the correlation coefficients are in the range of 0.98-0.99. The overall correlation coefficient is greater than 0.95. Conclusions The simulation results prove that this model can be used for the safety assessment of the fracture reduction robots. This model will be served as an environmental constraint to study the control of fracture reduction robot.

Dinuclear Pt(II) complexes have the potential to achieve high electroluminescence (EL) performance because of the enhanced phosphorescence emission induced by the extra metal center. However, to date, organic light-emitting devices (OLEDs) utilizing dinuclear Pt(II) complexes as emitters usually show low EL performance with external quantum efficiencies (EQE) less than 10%. In this work, with the triphenylphosphine oxide group as the scaffold core and different N-heterocycles (pyridine, thiazole, and quinoline) as the end-groups, dinuclear Pt(II) complexes PyPODPt, ThPODPt, and QuPODPt are synthesized to show bright emissions peaking at 500, 543, and 586 nm in solutions. The photoluminescence quantum yields are measured to be up to 0.96. More importantly, the solution-processed orange-red device based on QuPODPt exhibits outstanding EL performance with the EQE reaching 11.2%, which is among the highest EQEs reported for OLEDs employing dinuclear Pt(II) complexes. The superior device performance demonstrates the promising potential of triphenylphosphine oxide-based dinuclear Pt(II) complexes for OLED applications.

The power grid load shows a trend of diversified development. With the continuous increase of the power grid construction scale, it is very important to optimize the power supply of the distribution network and improve the utilization of assets and equipment by using the peak valley complementary characteristics of multiple loads. In this paper, the peak-valley fluctuation characteristics of load are classified and analyzed. Cluster analysis is used to study the load classification with stable peak-valley characteristics in the complex load composition. Based on the peak-peak superposition and peak-valley complementary characteristics of the classified load, and considering the load space dimension, the multi-load optimization combination method for the whole period and time segment is proposed, and verified by simulation.

Herein, we describe a facile method to control the size and dispersion of CuO nanoparticles (NPs) in SBA-15 by the supercritical antisolvent (SAS) method during the depressurization process of supercritical fluid deposition (SCFD), describing the mass transfer between supercritical carbon dioxide (scCO₂) and a cosolvent. On reducing the concentration of the cupric nitrate precursor, the size of CuO NPs was decreased from 3.5 ± 1.0 to 1.0 ± 0.4 nm (Cu loading 14.2–12.1 wt %) under the depressurized rate of ∼20 MPa/min. Based on the size distribution and nucleation theory, the nucleation rate of the precursor could reach 10²⁵ cm–³·s–¹, and the calculated interface energy of cupric nitrate was less than 0.1 J/m², indicating that scCO₂ as an antisolvent caused the heterogeneous nucleation of the precursor on the surface of SBA-15 channels. Hence, the nucleation rate and growth of cupric nitrate were regulated under a given scCO₂ depressurized rate, and then the CuO NPs’ size distribution and Cu loading were controlled subsequent to calcination.

Direct arylation methods have been used to polymerize thienylmethylene oxindoles (TEIs) and 3,3-bis[[(2-ethylhexyl)oxy]methyl]-3,4-dihydro-2H-thieno-[3,4-b][1,4]dioxepin (ProDOT) for new donor-acceptor conjugated polymers. The polymers exhibited blue hues in neutral-state with distinct color-to-transmissive reversible electrochromic switching under applied potentials from 0 V to +1.5 V, and showed high coloration efficiencies (436–438 cm2·C−1) in near-infrared regions with high switching speeds around 1–2 s under ambient conditions.