Spontaneously immortalised bovine mammary epithelial cells exhibit a distinct gene expression pattern from the breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Spontaneous immortalisation of cultured mammary epithelial cells (MECs) is an extremely rare event, and the molecular mechanism behind spontaneous immortalisation of MECs is unclear. Here, we report the establishment of a spontaneously immortalised bovine mammary epithelial cell line (BME65Cs) and the changes in gene expression associated with BME65Cs cells.</p> <p>Results</p> <p>BME65Cs cells maintain the general characteristics of normal mammary epithelial cells in morphology, karyotype and immunohistochemistry, and are accompanied by the activation of endogenous <it>bTERT </it>(bovine Telomerase Reverse Transcriptase) and stabilisation of the telomere. Currently, BME65Cs cells have been passed for more than 220 generations, and these cells exhibit non-malignant transformation. The expression of multiple genes was investigated in BME65Cs cells, senescent BMECs (bovine MECs) cells, early passage BMECs cells and MCF-7 cells (a human breast cancer cell line). In comparison with early passage BMECs cells, the expression of senescence-relevant apoptosis-related gene were significantly changed in BME65Cs cells. P16^INK4awas downregulated, p53 was low expressed and Bax/Bcl-2 ratio was reversed. Moreover, a slight upregulation of the oncogene <it>c-Myc</it>, along with an undetectable level of breast tumor-related gene <it>Bag-1 </it>and <it>TRPS-1</it>, was observed in BME65Cs cells while these genes are all highly expressed in MCF-7. In addition, <it>DNMT1 </it>is upregulated in BME65Cs. These results suggest that the inhibition of both senescence and mitochondrial apoptosis signalling pathways contribute to the immortality of BME65Cs cells. The expression of <it>p53 </it>and <it>p16</it>^{<it>INK4a </it>}in BME65Cs was altered in the pattern of down-regulation but not "loss", suggesting that this spontaneous immortalization is possibly initiated by other mechanism rather than gene mutation of <it>p53 </it>or <it>p16</it>^{<it>INK4a</it>}.</p> <p>Conclusions</p> <p>Spontaneously immortalised BME65Cs cells maintain many characteristics of normal BMEC cells and exhibit non-malignant transformation. Although this cell line displays altered patterns of gene expression, it is clearly distinct from malignant breast cancer cell line. It showed that co-inhibition of cellular senescence and mitochondrial apoptosis pathways coordinates BME65Cs cells immortalisation. Additionally, mechanisms other than gene mutation are likely to be involved in regulation of cellular functions. This study provides an insight into the relationship between cell senescence and immortalisation. BME65Cs cells will be useful in future studies of cellular senescence and tumorigenesis.</p

Efficient Super-Resolution of Near-Surface Climate Modeling Using the Fourier Neural Operator

Downscaling methods are critical in efficiently generating high-resolution atmospheric data. However, state-of-the-art statistical or dynamical downscaling techniques either suffer from the high computational cost of running a physical model or require high-resolution data to develop a downscaling tool. Here, we demonstrate a recently proposed zero-shot super-resolution method, the Fourier neural operator (FNO), to efficiently perform downscaling without the need for high-resolution data. Because the FNO learns dynamics in Fourier space, FNO is a resolution-invariant emulator; it can be trained at a coarse resolution and produces emulation at any high resolution. We applied FNO to downscale a 4-km resolution Weather Research and Forecasting (WRF) Model simulation of near-surface heat-related variables over the Great Lakes region. The FNO is driven by the atmospheric forcings and topographic features used in the WRF model at the same resolution. We incorporated a physics-constrained loss in FNO by using the Clausius–Clapeyron relation to better constrain the relations among the emulated states. Trained on merely 600 WRF snapshots at 4-km resolution, the FNO shows comparable performance with a widely-used convolutional network, U-Net, achieving averaged modified Kling–Gupta Efficiency of 0.88 and 0.94 on the test data set for temperature and pressure, respectively. We then employed the FNO to produce 1-km emulations to reproduce the fine climate features. Further, by taking the WRF simulation as ground truth, we show consistent performances at the two resolutions, suggesting the reliability of FNO in producing high-resolution dynamics. Our study demonstrates the potential of using FNO for zero-shot super-resolution in generating first-order estimation on atmospheric modeling

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world\u27s largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system

Enhancing Winter Climate Simulations of the Great Lakes: Insights from a New Coupled Lake-Ice-Atmosphere (CLIAv1) Model on the Importance of Integrating 3D Hydrodynamics with a Regional Climate Model

The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States, due to their vast thermal inertia, moisture source potential, and unique heat and moisture flux dynamics. This study presents a newly developed coupled lake-ice-atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulating the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 addresses the limitations of traditional one-dimensional (1D) lake and demonstrates superior performance in reproducing observed LSTs, ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable climate projections. More importantly, this study addresses the crucial question about what are the key processes influencing lake thermal structure and ice cover that are missed by 1D lake models but effectively captured by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes &ndash; ice transport, heat advection, and shear production in turbulence &ndash; that explain the superiority of 3D lake models over 1D lake models, particularly in cold season performance and lake-atmosphere interactions. Properly resolving these processes using 3D hydrodynamic model is crucial for successfully simulating the lake-ice-atmosphere coupled Great Lakes winter system. This research underscores the necessity of incorporating 3D hydrodynamic models in RCMs to improve our predictive understanding of the Great Lakes' response to climate change. The findings advocate for a shift towards high-resolution, physics-based modeling approaches to ensure accurate future climate and limnological projections for large freshwater systems

Blockchain-based power trading system for microgrid

Direct trading between entities in the microgrid is the trend of micro-grid electricity trading. However, the lack of trust and endorsement among multiple entities in micro-grids makes it difficult to complete direct electricity transactions, which limits the green energy efficiency. To solve this problem, firstly, a blockchain-based microgrid power transaction level model and power transaction process management process are proposed. Secondly, an access interface between the microgrid smart terminal and the blockchain is designed to realize the connection between the blockchain and the underlying equipment. The system is implemented in an island microgrid, which realizes the peer-to-peer trading between power suppliers and users. The system builds a bridge among entities in microgrid and makes the power trading open, transparent and traceable

How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming

Multicomponent Solar Cells with High Fill Factors and Efficiencies Based on Non-Fullerene Acceptor Isomers

Multicomponent organic solar cells (OSCs), such as the ternary and quaternary OSCs, not only inherit the simplicity of binary OSCs but further promote light harvesting and power conversion efficiency (PCE). Here, we propose a new type of multicomponent solar cells with non-fullerene acceptor isomers. Specifically, we fabricate OSCs with the polymer donor J71 and a mixture of isomers, ITCF, as the acceptors. In comparison, the ternary OSC devices with J71 and two structurally similar (not isomeric) NFAs (IT-DM and IT-4F) are made as control. The morphology experiments reveal that the isomers-containing blend film demonstrates increased crystallinity, more ideal domain size, and a more favorable packing orientation compared with the IT-DM/IT-4F ternary blend. The favorable orientation is correlated with the balanced charge transport, increased exciton dissociation and decreased bimolecular recombination in the ITCF-isomer-based blend film, which contributes to the high fill factor (FF), and thus the high PCE. Additionally, to evaluate the generality of this method, we examine other acceptor isomers including IT-M, IXIC-2Cl and SY1, which show same trend as the ITCF isomers. These results demonstrate that using isomeric blends as the acceptor can be a promising approach to promote the performance of multicomponent non-fullerene OSCs

Antibiotic use among hospitalized children and neonates in China: results from quarterly point prevalence surveys in 2019

Background: Antimicrobial resistance is a significant clinical problem in pediatric practice in China. Surveillance of antibiotic use is one of the cornerstones to assess the quality of antibiotic use and plan and assess the impact of antibiotic stewardship interventions. Methods: We carried out quarterly point prevalence surveys referring to WHO Methodology of Point Prevalence Survey in 16 Chinese general and children's hospitals in 2019 to assess antibiotic use in pediatric inpatients based on the WHO AWaRe metrics and to detect potential problem areas. Data were retrieved via the hospital information systems on the second Monday of March, June, September and December. Antibiotic prescribing patterns were analyzed across and within diagnostic conditions and ward types according to WHO AWaRe metrics and Anatomical Therapeutic Chemical (ATC) Classification. Results: A total of 22,327 hospitalized children were sampled, of which 14,757 (66.1%) were prescribed ≥1 antibiotic. Among the 3,936 sampled neonates (≤1 month), 59.2% (n = 2,331) were prescribed ≥1 antibiotic. A high percentage of combination antibiotic therapy was observed in PICUs (78.5%), pediatric medical wards (68.1%) and surgical wards (65.2%). For hospitalized children prescribed ≥1 antibiotic, the most common diagnosis on admission were lower respiratory tract infections (43.2%, n = 6,379). WHO Watch group antibiotics accounted for 70.4% of prescriptions (n = 12,915). The most prescribed antibiotic ATC classes were third-generation cephalosporins (41.9%, n = 7,679), followed by penicillins/β-lactamase inhibitors (16.1%, n = 2,962), macrolides (12.1%, n = 2,214) and carbapenems (7.7%, n = 1,331). Conclusion: Based on these data, overuse of broad-spectrum Watch group antibiotics is common in Chinese pediatric inpatients. Specific interventions in the context of the national antimicrobial stewardship framework should aim to reduce the use of Watch antibiotics and routine surveillance of antibiotic use using WHO AWaRe metrics should be implemented.</p