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Novel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers. However, current generative design algorithms focus on diagrammatic or spatial concepts that are either too abstract to understand or too detailed for early phase design exploration. This paper explores the uses of generative pre-trained transformers (GPT) for natural language design concept generation. Our experiments involve the use of GPT-2 and GPT-3 for different creative reasonings in design tasks. Both show reasonably good performance for verbal design concept generation.

Background: MicroRNAs (miRNAs) are involved in gastric cancer development and progression. However, the expression and role of miRNAs in gastric cancer stromal cells are still unclear. Methods: The miRNAs differentially expressed in gastric cancer tissue-derived mesenchymal stem cells (GC-MSCs) relative to adjacent non-cancerous tissue-derived MSCs (GCN-MSCs) and in cancer tissues relative to adjacent non-cancerous tissues were screened using miRNA microarray and validated by quantitative RT–PCR. The impact of GC-MSCs on HGC-27 cells was observed in vitro using colony formation and transwell assays, and these cells were subcutaneously co-injected into mice to assess tumour growth in vivo . Exogenous downregulation of miR-221 expression in cells was achieved using an miRNA inhibitor. Results: miR-214, miR-221 and miR-222 were found to be commonly upregulated in GC-MSCs and cancer tissues. Their levels were tightly associated with lymph node metastasis, venous invasion and the TNM stage. Gastric cancer tissue-derived mesenchymal stem cells significantly promoted HGC-27 growth and migration and increased the expression of miR-221 via paracrine secretion, and the targeted inhibition of miR-221 in GC-MSCs could block its tumour-supporting role. GC-MSC-derived exosomes were found to deliver miR-221 to HGC-27 cells and promoted their proliferation and migration. Conclusions: Gastric cancer tissue-derived mesenchymal stem cells favour gastric cancer progression by transferring exosomal miRNAs to gastric cancer cells, thus providing a novel mechanism for the role of GC-MSCs and new biomarkers for gastric cancer.

While major progress has been made in the research of inertial confinement fusion, significant challenges remain in the pursuit of ignition. To tackle the challenges, we propose a double-cone ignition (DCI) scheme, in which two head-on gold cones are used to confine deuterium–tritium (DT) shells imploded by high-power laser pulses. The scheme is composed of four progressive controllable processes: quasi-isentropic compression, acceleration, head-on collision and fast heating of the compressed fuel. The quasi-isentropic compression is performed inside two head-on cones. At the later stage of the compression, the DT shells in the cones are accelerated to forward velocities of hundreds of km s –1 . The head-on collision of the compressed and accelerated fuels from the cone tips transfer the forward kinetic energy to the thermal energy of the colliding fuel with an increased density. The preheated high-density fuel can keep its status for a period of approximately 200 ps. Within this period, MeV electrons generated by ps heating laser pulses, guided by a ns laser-produced strong magnetic field further heat the fuel efficiently. Our simulations show that the implosion inside the head-on cones can greatly mitigate the energy requirement for compression; the collision can preheat the compressed fuel of approximately 300 g cm −3 to a temperature above keV. The fuel can then reach an ignition temperature of greater than 5 keV with magnetically assisted heating of MeV electrons generated by the heating laser pulses. Experimental campaigns to demonstrate the scheme have already begun. This article is part of a discussion meeting issue ‘Prospects for high gain inertial fusion energy (part 1)’.

Long noncoding RNAs (lncRNAs) are emerging as key factors in various fundamental cellular biological processes, and many of them are likely to have functional roles in tumorigenesis. Maternally expressed gene 3 ( MEG3 ) is an imprinted gene located at 14q32 that encodes a lncRNA, and the decreased MEG3 expression has been reported in multiple cancer tissues. However, nothing is known about the alteration and role of MEG3 in environmental carcinogen-induced lung tumorigenesis. Our present study, for the first time to the best of our knowledge, discovered that environmental carcinogen nickel exposure led to MEG3 downregulation, consequently initiating c-Jun-mediated PHLPP1 transcriptional inhibition and hypoxia-inducible factor-1α (HIF-1α) protein translation upregulation, in turn resulting in malignant transformation of human bronchial epithelial cells. Mechanistically, MEG3 downregulation was attributed to nickel-induced promoter hypermethylation via elevating DNMT3b expression, whereas PHLPP1 transcriptional inhibition was due to the decreasing interaction of MEG3 with its inhibitory transcription factor c-Jun. Moreover, HIF-1α protein translation was upregulated via activating the Akt/p70S6K/S6 axis resultant from PHLPP1 inhibition in nickel responses. Collectively, we uncover that nickel exposure results in DNMT3b induction and MEG3 promoter hypermethylation and expression inhibition, further reduces its binding to c-Jun and in turn increasing c-Jun inhibition of PHLPP1 transcription, leading to the Akt/p70S6K/S6 axis activation, and HIF-1α protein translation, as well as malignant transformation of human bronchial epithelial cells. Our studies provide a significant insight into understanding the alteration and role of MEG3 in nickel-induced lung tumorigenesis.

The entorhinal cortex (EC) is one of the most vulnerable brain regions that is attacked during the early stage of Alzheimer's disease (AD). Here, we report that the synaptic terminals of pyramidal neurons in the EC layer II (ECIIPN ) directly innervate CA1 parvalbumin (PV) neurons (CA1PV ) and are selectively degenerated in AD mice, which exhibit amyloid-β plaques similar to those observed in AD patients. A loss of ECIIPN -CA1PV synapses disables the excitatory and inhibitory balance in the CA1 circuit and impairs spatial learning and memory. Optogenetic activation of ECIIPN using a theta burst paradigm rescues ECIIPN -CA1PV synaptic defects and intercepts the decline in spatial learning and memory. These data reveal a novel mechanism of memory loss in AD mice via the selective degeneration of the ECIIPN -CA1PV pathway.

Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH4+, NO3− and POx; representing the sum of PO43−, HPO42− and H2PO4−) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N2O emissions, free phosphorus, sorbed phosphorus and NH4+ pools at a tropical forest site (Tapajos). The overall model uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer–substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results also imply that under strong nutrient limitation, relative competitiveness depends strongly on the competitor functional traits (affinity and nutrient carrier enzyme abundance). We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.

Terrestrial carbon–climate feedbacks depend on two large and opposing fluxes—soil organic matter decomposition and photosynthesis—that are tightly regulated by nutrients1,2. Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 represented nutrient dynamics poorly1,3, rendering predictions of twenty-first century carbon–climate feedbacks highly uncertain. Here, we use a new land model to quantify the effects of observed plant nutrient uptake mechanisms missing in most other ESMs. In particular, we estimate the global role of root nutrient competition with microbes and abiotic processes during periods without photosynthesis. Nitrogen and phosphorus uptake during these periods account for 45 and 43%, respectively, of annual uptake, with large latitudinal variation. Globally, night-time nutrient uptake dominates this signal. Simulations show that ignoring this plant uptake, as is done when applying an instantaneous relative demand approach, leads to large positive biases in annual nitrogen leaching (96%) and N2O emissions (44%). This N2O emission bias has a GWP equivalent of ~2.4 PgCO2 yr−1, which is substantial compared to the current terrestrial CO2 sink. Such large biases will lead to predictions of overly open terrestrial nutrient cycles and lower carbon sequestration capacity. Both factors imply over-prediction of positive terrestrial feedbacks with climate in current ESMs.

Rural household energy use for cooking and heating is an important source of air pollutants in China, as it affects both human health and climate change. However, the magnitude of rural household energy use, especially during the recent rapid socioeconomic transition period, has not been well quantified. Here, we present first-hand nationwide data from a 34,489-household energy-mix survey and a 1,670-household fuel-weighing campaign. We found that the consumption of wood and crop residues in rural China decreased by 63% and 51%, respectively, from 1992 to 2012, and these decreases were much greater than the 15% and 8%, respectively, reported by the International Energy Agency and Food and Agriculture Organization. The rapid residential energy transition over these two decades was primarily driven by the rapid socioeconomic development. One important implication of this transition is the significant reduction in the emissions of major air pollutants, especially incomplete combustion products leading to significant impacts on health and climate. Use of wood and crop residue for cooking and heating in rural China is a significant source of carbon emissions and air pollution. Using a survey of more than 34,000 households, researchers show that between 1992 and 2012 usage of these fuels decreased by much more than previous estimates, due primarily to rising incomes.

Cold‐season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold‐season CH4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH4 yr−1. While summer CH4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade−1. Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH4) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH4 emissions from wetlands need to be improved. Key Points Cold‐season methane (CH4) emissions simulated by 16 Global Carbon Project‐CH4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty

Background The aim of this study was to assess the role of lipolysis of epicardial adipose tissue (EAT) in cardiac function after myocardial infarction (MI). Methods We used a rat model of MI with or without EAT removal to study the effects of EAT lipolysis on cardiovascular function. Echocardiography and cardiac catheterization were used to determine cardiac function, and infarct size and histopathology specimens were analyzed in postmortem sections. Inflammatory responses were evaluated via flow cytometry and Elisa analyses. Results We found that the lipolysis of EAT increased significantly after MI. Removal of the EAT after MI (MI-EAT) improved cardiac function by nearly 10% and decreased the infarct area by 6% when compared with rats retaining EAT after MI (MI+EAT). Furthermore, the removal of EAT reduced the number of CD45-positive leukocytes (50 vs. 34.8%) and increased the ratio of macrophage/leukocytes (56 vs. 75%) in the infarcted heart. Compared with the MI+EAT group, the concentration of tumor necrosis factor-alpha and interleukin 1‑beta were reduced in the MI-EAT group. Conclusion Lipolysis of EAT increased significantly after MI. Removal of EAT improved cardiac function, in part, by weakening the inflammatory response.