Explore the vast range of titles available.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a prominent extracellular matrix (ECM) deposition and poor prognosis. High levels of ECM proteins derived from tumour cells reduce the efficacy of conventional cancer treatment paradigms and contribute to tumour progression and metastasis. As abundant tumour-promoting cells in the ECM, cancer-associated fibroblasts (CAFs) are promising targets for novel anti-tumour interventions. Nonetheless, related clinical trials are hampered by the lack of specific markers and elusive differences between CAF subtypes. Here, we review the origins and functional diversity of CAFs and show how they create a tumour-promoting milieu, focusing on the crosstalk between CAFs, tumour cells, and immune cells in the tumour microenvironment. Furthermore, relevant clinical advances and potential therapeutic strategies relating to CAFs are discussed.

Oblique detonation waves (ODWs) have been studied widely to facilitate their employment in hypersonic propulsion, but the effects of continuous unsteady inflow have never been addressed so far. Thus, the present study investigates wedge-induced oblique detonations in unsteady flow via numerical simulations based on the reactive Euler equations with a two-step induction–reaction kinetic model. As a first step, the chemical and flow parameters are chosen for the simplest structure such that the ODW initiation occurs under a smooth transition with a curved shock. After a steady ODW with smooth initiation transition is established, the inflow is then subject to a continuous sinusoidal density/temperature disturbance. Cases with single-pulse inflow variation are also simulated to clarify whether the observed phenomena are derived solely from the continuous disturbance. Two aspects are analysed to investigate the features of ODWs in unsteady flow, namely, the formation of triple points on the surface, and the movement of the reactive front position. On the formation of triple points, the continuous disturbance generates at most one pair of triple points, less than or equal to the number of triple points in single-pulse cases. This indicates that the effects of continuous disturbance weaken the ability to generate the triple points, although there appear more triple points convected downstream on the surface at any given instant. On the movement of the reactive front, oscillatory behaviours are induced in either single-pulse or continuous disturbance cases. However, more complicated dynamic displacements and noticeable effects of unsteadiness are observed in the cases of continuous disturbance, and are found to be sensitive to the disturbance wavenumber, $N$ . Increasing $N$ results in three regimes with distinct behaviours, which are quasi-steady, overshooting oscillation and unstable ODW. For the quasi-steady case with low $N$ , the reactive front oscillates coherently with the inflow disturbance with slightly higher amplitude around the initiation region. The overshooting oscillation generates the most significant variation of downstream surface in the case of modest $N$ , reflecting a resonance-like behaviour of unsteady ODW. In the case of high $N$ , the disturbed ODW surface readjusts itself with local unstable features. It becomes more robust and the reactive front of the final unstable ODW structure is less susceptible to flow disturbance.

Wedge-induced oblique detonation waves (ODWs) have been studied widely, but their interactions with complicated geometries have not been fully addressed. In this study, we investigate ODW interaction with a deflected upper corner due to confinement change upstream of the ODW. Numerical simulations are conducted using the reactive Euler equations with a two-step induction–reaction kinetic model. Two ODWs without the upper wall deflection are first simulated to resolve the basic structures with inflow Mach numbers $M_0 = 6$ and 7. Thereafter, we introduce a deflected upper confinement, resulting in a new wave configuration. This wave is characterized by a post-turning, triangular recirculation zone coupled with a gaseous wedge connecting the deflection point and ODW surface. A parametric study is performed to analyse the effects of the deflection location, deflection angle and activation energy of the heat release reaction. The results reveal that the wave configuration is due to the evolution of ODW decoupling in an expanded supersonic flow. We further study the surface stability and structural unsteadiness arising for $M_0 = 6$. Upstream-travelling transverse waves are observed for the first time, and effects of different parameters on the surface instability are analysed via fast Fourier transforms. Two destabilizing mechanisms of ODW structures are proposed, one from the post-surface thermal choking and the other from the enhanced surface instability.

Environmentally adaptive power generation is attractive for the development of next-generation energy sources. Here we develop a heterogeneous moisture-enabled electric generator (HMEG) based on a bilayer of polyelectrolyte films. Through the spontaneous adsorption of water molecules in air and induced diffusion of oppositely charged ions, one single HMEG unit can produce a high voltage of ~0.95 V at low (25%) relative humidity (RH), and even jump to 1.38 V at 85% RH. A sequentially aligned stacking strategy is created for large-scale integration of HMEG units, to offer a voltage of more than 1,000 V under ambient conditions (25% RH, 25 °C). Using origami assembly, a small section of folded HMEGs renders an output of up to 43 V cm −3 . Such integration devices supply sufficient power to illuminate a lamp bulb of 10 W, to drive a dynamic electronic ink screen and to control the gate voltage for a self-powered field effect transistor. A power generator exhibits enhanced output due to a dual-charge-carrier design. The voltage produced is constant yet competitive even under low relative humidity.

Glutathione is the principal intracellular antioxidant buffer against oxidative stress and mainly exists in the forms of reduced glutathione (GSH) and oxidized glutathione (GSSG). The processes of glutathione synthesis, transport, utilization, and metabolism are tightly controlled to maintain intracellular glutathione homeostasis and redox balance. As for cancer cells, they exhibit a greater ROS level than normal cells in order to meet the enhanced metabolism and vicious proliferation; meanwhile, they also have to develop an increased antioxidant defense system to cope with the higher oxidant state. Growing numbers of studies have implicated that altering the glutathione antioxidant system is associated with multiple forms of programmed cell death in cancer cells. In this review, we firstly focus on glutathione homeostasis from the perspectives of glutathione synthesis, distribution, transportation, and metabolism. Then, we discuss the function of glutathione in the antioxidant process. Afterwards, we also summarize the recent advance in the understanding of the mechanism by which glutathione plays a key role in multiple forms of programmed cell death, including apoptosis, necroptosis, ferroptosis, and autophagy. Finally, we highlight the glutathione-targeting therapeutic approaches toward cancers. A comprehensive review on the glutathione homeostasis and the role of glutathione depletion in programmed cell death provide insight into the redox-based research concerning cancer therapeutics.

Accurate prediction of hydraulic support pressure is crucial for ensuring coal mine safety. With increasing mining depths and increasingly complex operating environments, precise prediction faces greater challenges. To address these challenges, this study proposes an LSTM-PatchTST prediction method based on multi-dimensional feature dependency fusion: First, Pearson correlation analysis is used to screen key features, and Gaussian moving average filtering optimizes the data; Subsequently, the preprocessed time series is input to the LSTM network, where the forget gate and input gate capture short-term fluctuations and long-term trends respectively, while residual connections ensure complete preservation of multi-layer temporal features; Then, the dynamic features extracted by LSTM are passed to the PatchTST module, which divides the sequence into local patches, with a multi-layer self-attention encoder simultaneously modeling local details and global dependencies, achieving deep feature fusion. The model’s performance is validated using actual pressure data from Fucun Coal Mine in Zaozhuang, Shandong. Experimental results show that, compared to pure PatchTST and Transformer + LSTM models, the proposed model reduces RMSE by approximately 48.6% and 30.0%, and MAE by approximately 58.7% and 38.8%, respectively. Finally, to further verify the model’s generalization ability, the trained model was transferred to a dataset from Gengcun Coal Mine in Yima, Henan, where compared to pure PatchTST and Transformer + LSTM models, the proposed model reduces RMSE by approximately 34.6% and 31.4%, and MAE by approximately 35.7% and 29.9%, respectively.

The emergence of generative artificial intelligence (AI) technologies is driving transformative changes in physical education, highlighting the critical need for pre-service teachers to develop AI-specific pedagogical knowledge and ethical awareness. This study explores the role of self-regulation in mediating the relationship between basic psychological needs (autonomy, competence, and relatedness) and digital competence, specifically Intelligent-TPACK and ethics, among Physical Education Teacher Education (PETE) students. Data were collected from 548 PETE students at six universities in Wuhan, China. Structural equation modeling (SEM) analysis demonstrated that self-regulation positively predicted both Intelligent-TPACK and ethical awareness, with self-regulation mediating the effects of basic psychological needs on these two dimensions of digital competence. These findings underscore the importance of promoting self-regulation skills to strengthen pre-service teachers’ capacity to integrate AI tools effectively into their educational practices while fostering ethical decision-making. The results offer both theoretical and practical insights implications for teacher education programs seeking to advance AI literacy and ethical responsibility in future physical educators.

The rapid variation of atmospheric water vapor is important for a regional hydrologic cycle and climate change. However, it is rarely investigated in China, due to the lack of a precipitable water vapor (PWV) dataset with high temporal resolution. Therefore, this study focuses on the generation of an hourly PWV dataset using Global Navigation Satellite System (GNSS) observations derived from the Crustal Movement Observation Network of China. The zenith total delay parameters estimated by GAMIT/GLOBK software are used and validated with an average root mean square (RMS) error of 4–5 mm. The pressure (P) and temperature (T) parameters used to calculate the zenith hydrostatic delay (ZHD) and weighted average temperature of atmospheric water vapor (Tm) are derived from the fifth-generation reanalysis dataset of the European Centre for Medium-Range Weather Forecasting (ECMWF ERA5) products. The values of P and T at the GNSS stations are obtained by interpolation in the horizontal and vertical directions using empirical formulas. Tm is calculated at the GNSS stations using the improved global pressure and temperature 2 wet (IGPT2w) model in China with an RMS of 3.32 K. The interpolated P and T are validated by interpolating the grid-based ERA5 data into radiosonde stations. The average RMS and bias of P and T in China are 2.71/−1.11 hPa and 1.88/−0.51 K, respectively. Therefore, the error in PWV with a theoretical RMS of 1.85 mm over the period of 2011–2017 in China can be obtained. Finally, the hourly PWV dataset in China is generated and the practical accuracy of the generated PWV dataset is validated using the corresponding AERONET and radiosonde data at specific stations. Numerical results reveal that the average RMS values of the PWV dataset in the four geographical regions of China are less than 3 mm. A case analysis of the PWV diurnal variations as a response to the EI Niño event of 2015–2016 is performed. Results indicate the capability of the hourly PWV dataset of monitoring the rapid water vapor changes in China.

Monolayer transition metal dichalcogenides (TMDs) have become essential two-dimensional materials for their perspectives in engineering next-generation electronics. For related applications, the controlled growth of large-area uniform monolayer TMDs is crucial, while it remains challenging. Herein, we report the direct synthesis of 6-inch uniform monolayer molybdenum disulfide on the solid soda-lime glass, through a designed face-to-face metal-precursor supply route in a facile chemical vapor deposition process. We find that the highly uniform monolayer film, with the composite domains possessing an edge length larger than 400 µm, can be achieved within a quite short time of 8 min. This highly efficient growth is proven to be facilitated by sodium catalysts that are homogenously distributed in glass, according to our experimental facts and density functional theory calculations. This work provides insights into the batch production of highly uniform TMD films on the functional glass substrate with the advantages of low cost, easily transferrable, and compatible with direct applications. Growth of large-area monolayer transition metal dichalcogenides is critical for their application but remains challenging. Here Yang et al. report rapid chemical vapor deposition of 6-inch monolayer molybdenum disulfide by sufficiently uniformly supplying the precursors and catalysts.

Forest fire is a ubiquitous disaster which has a long-term impact on the local climate as well as the ecological balance and fire products based on remote sensing satellite data have developed rapidly. However, the early forest fire smoke in remote sensing images is small in area and easily confused by clouds and fog, which makes it difficult to be identified. Too many redundant frequency bands and remote sensing index for remote sensing satellite data will have an interference on wildfire smoke detection, resulting in a decline in detection accuracy and detection efficiency for wildfire smoke. To solve these problems, this study analyzed the sensitivity of remote sensing satellite data and remote sensing index used for wildfire detection. First, a high-resolution remote sensing multispectral image dataset of forest fire smoke, containing different years, seasons, regions and land cover, was established. Then Smoke-Unet, a smoke segmentation network model based on an improved Unet combined with the attention mechanism and residual block, was proposed. Furthermore, in order to reduce data redundancy and improve the recognition accuracy of the algorithm, the conclusion was made by experiments that the RGB, SWIR2 and AOD bands are sensitive to smoke recognition in Landsat-8 images. The experimental results show that the smoke pixel accuracy rate using the proposed Smoke-Unet is 3.1% higher than that of Unet, which could effectively segment the smoke pixels in remote sensing images. This proposed method under the RGB, SWIR2 and AOD bands can help to segment smoke by using high-sensitivity band and remote sensing index and makes an early alarm of forest fire smoke.