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Plasticity, the ability of cancer cells to transition between differentiation states without genomic alterations, has been recognized as a major source of intratumoral heterogeneity. It has a crucial role in cancer metastasis and treatment resistance. Thus, targeting plasticity holds tremendous promise. However, the molecular mechanisms of plasticity in cancer cells remain poorly understood. Several studies found that mRNA, which acts as a bridge linking the genetic information of DNA and protein, has an important role in translating genotypes into phenotypes. The present review provided an overview of the regulation of cancer cell plasticity occurring via changes in the transcription and editing of mRNAs. The role of the transcriptional regulation of mRNA in cancer cell plasticity was discussed, including DNA-binding transcriptional factors, DNA methylation, histone modifications and enhancers. Furthermore, the role of mRNA editing in cancer cell plasticity was debated, including mRNA splicing and mRNA modification. In addition, the role of non-coding (nc)RNAs in cancer plasticity was expounded, including microRNAs, long intergenic ncRNAs and circular RNAs. Finally, different strategies for targeting cancer cell plasticity to overcome metastasis and therapeutic resistance in cancer were discussed.

This field-based study examined whether bounce-referenced preparation timing during tennis forehand groundstrokes was associated with incoming-ball speed and skill level, and whether this timing descriptor related to local ball–racquet dominance around bounce. Thirty male university players (15 high-skill, 15 low-skill) performed continuous baseline forehand topspin rallies. Analyses included trials with valid incoming-ball speed within a common-support range of 60–110 km/h and ball landings within a predefined central target zone. Preparation timing was quantified using an Index of Preparation (IdP), defined as the signed offset between racquet set completion and ball bounce within normalized stroke progress. Trial-level IdP and bounce-window ball-dominant occupancy (BDO), derived from coupling angle mapping, were analyzed using participant-clustered models; Gaussian mixture summaries were retained as secondary descriptive analyses. In low-skill players, higher incoming-ball speed was associated with lower IdP, whereas this decrease was attenuated in high-skill players. Lower IdP was also associated with higher BDO, suggesting that delayed preparation was accompanied by greater local ball-dominant organization around bounce. These findings support IdP as a field-based performance analysis descriptor, while BDO-derived measures should be interpreted as exploratory descriptors requiring further validation against simpler coaching indicators and direct performance outcomes.

Aqueous zinc-ion batteries offer inherent safety and low cost, yet performance is limited by unstable zinc metal negative electrodes and dissolution-prone positive electrodes, causing dendrite growth, sluggish ion transport, and rapid capacity decay. Replacing both electrodes with intercalation hosts provides a solution, but progress is slowed by the lack of a universal principle for selecting kinetically compatible pairs. Most existing efforts optimize single components rather than addressing the electrodes’ kinetic mismatch governing full-cell stability. Here we show a machine-learning-assisted kinetic-matching framework that quantitatively evaluates ion-transport compatibility in intercalation-type zinc-ion batteries electrodes. By correlating interlayer spacing with Zn 2+ diffusion behavior, the model introduces two descriptors predicting synchronized ion flux for rational electrode pairing. Using this framework, an optimized Zn 3 V 3 O 8  | |NH 4 V 4 O 10 system achieves a specific capacity of 310 mAh g -1 and retains over 12,000 cycles at 5 A g -1 . The strategy further extends to deformable formats through conductive hydrogel architectures, enabling omnidirectionally stretchable, all-hydrogel zinc-ion batteries with an areal capacity of 1.2 mAh cm -2 and an energy density of 1070 μWh cm -2 . These results provide a quantitative design route for next-generation zinc-ion batteries. Aqueous zinc-ion batteries are safe and affordable but limited by incompatible electrode kinetics. Here, authors present a machine learning framework that resolves this mismatch, enabling the rational design of durable and stretchable zinc-ion batteries.

Background Smart healthcare systems are expected to have a positive impact on addressing challenges in healthcare. However, the real-world adoption and widespread integration of Smart healthcare systems still face many barriers, and their clinical utility lacks empirical research with large sample sizes, particularly in rural areas. The aim of this study is to evaluate the impact of a new smart healthcare system, the Health All-in-One Machines (HAMs), on improving the health services in rural areas of China. Methods The data included health services information from 1,866 village clinics in Hainan, China, covering the period November 30, 2020, to April 30, 2023. The impact of Health All-in-One Machines on access to healthcare was measured using four outcome indicators: the number of patient visits, medical revenue, pharmaceutical revenue, and medical expense per patient. We conducted a three-phase interrupted time series study to explore the effects of the Health All-in-One Machines intervention on these indicators across two distinct periods: the second phase (26 weeks, adaptation period) and the third phase (74 weeks, full-scale implementation period). Results The interrupted time-series analysis revealed that the Health All-in-One Machines intervention had no significant impact on outcome indicators comparing the pre-intervention period to the adaptation period. However, from the adaptation period to full implementation, significant impacts were observed. Specifically, notable level changes were observed: the number of patient visits increased by 37.85% ( p  < 0.01), medical revenue increased by 54.03% ( p  < 0.001), pharmaceutical revenue increased by 32.84% ( p  < 0.05), and medical expense per patient increased by 2.368 CNY ( p  < 0.001). Additionally, a significant trend change was observed in medical expense per patient, with a decrease of 0.15 CNY per week ( p  < 0.05). Conclusions This study provides empirical evidence of some positive changes in the Health All-in-One Machines intervention on the outcome indicators regarding the access to healthcare. Moreover, our analysis indicates that the Health All-in-One Machines intervention would at least take longer to take effect when implemented in large-scale rural healthcare institutions. The findings from this study provide insights for future delivery and policy making of Smart healthcare systems in rural areas.

Purpose Human activities drive the input of various pollutants into urban river ecosystems, which in turn induce ecotoxicity that alters the community structure and diversity of environmental microorganisms; however, the ecotoxicological effects of human activities on microorganisms in the environmental media of urban rivers ecosystems remain inadequately investigated, and systematic understanding of bacterial resistance distribution and community assembly pattern differences in urban rivers is still lacking. Methods PacBio third-generation sequencing technology was used to sequence the full-length 16 S rRNA genes of microorganisms extracted from water and riparian soil samples, to analyze the spatial distribution and characteristics of microbial community structure and diversity in urban rivers ecosystems, and to identify the potential microbial sources of microbes using SourceTracker. Results The dominant phyla in water samples were Proteobacteria and Bacteroidota, whereas those in soil samples were Proteobacteria, Acidobacteriota, Bacteroidota and Actinobacteriota. Soil microbial communities exhibited no significant geographical differences, while water microbial communities showed distinct geographical distribution patterns among groups (upstream, midstream, and downstream of the Minxin River, and the City Ring Water System) with up to 51 inter-group biomarkers. SourceTracker was used to identify potential microbial sources for downstream water samples (with upstream water, midstream water, and outfalls as candidate sources). Results showed that microorganisms in downstream Minxin River water primarily originated from outfalls (54.11%) and midstream water (32.27%), demonstrating the significant impact of outfalls on river microbial community structure. Conclusions Thus, human activities (e.g., wastewater discharge) and associated pollutant inputs have significantly altered the microbial community structure of urban rivers, providing valuable insights for the ecological management and restoration of urban river ecosystems under human disturbance.

Hydrogel actuators have shown great promise in underwater robotic applications as they can generate controllable shape transformations upon stimulation due to their ability to absorb and release water reversibly. Herein, a photoresponsive anisotropic hydrogel actuator is developed from poly(N‐isopropylacrylamide) (PNIPAM) and gold‐decorated carbon nitride (Au/g‐C3N4) nanoparticles. Carbon nitride nanoparticles endow hydrogel actuators with photocatalytic properties, while their reorientation and mobility driven by the electrical field provide anisotropic properties to the surrounding network. A variety of light‐fueled soft robotic functionalities including controllable and programmable shape‐change, gripping, and locomotion is elicited. A responsive flower‐like photocatalytic reactor is also fabricated, for water splitting, which maximizes its energy‐harvesting efficiency, that is, hydrogen generation rate of 1061.82 µmol g−1 h−1, and the apparent quantum yield of 8.55% at 400 nm, by facing its light‐receiving area adaptively towards the light. The synergy between photoactive and photocatalytic properties of this hydrogel portrays a new perspective for the design of underwater robotic and photocatalytic devices. Hydrogel actuators with anisotropic microstructure, photothermal shape‐change, and photocatalytic activity are prepared from composites of poly(N‐isopropylacrylamide) and Au/g‐C3N4 nanoparticles. A variety of light‐fueled controllable shape‐change is elicited, applicable to soft robotics. The photothermal deformation of hydrogel constructs is utilized to maximize their energy harvesting capability and photocatalytic hydrogen generation.

This study introduces a novel method for predicting solar radiation by focusing on the sun's position and cloud conditions in the sky. The proposed approach utilizes sun position feature maps and spatial attention mechanisms to improve the accuracy of solar irradiance prediction. Key contributions include the development of sun position feature maps to precisely locate the sun in all-sky images and the integration of spatial attention mechanisms with convolutional neural networks to enhance predictive modeling. Comparative analysis with three other models demonstrates the effectiveness of the proposed approach, particularly in overcast conditions. These innovative techniques significantly enhance the accuracy of solar radiation prediction and offer valuable insights for the design and operation of renewable energy systems.

Background Atherosclerosis is characterized by complex pathological processes, including endothelial dysfunction and inflammation. The underlying pathogenic mechanisms have been well elucidated; however, effective treatments are yet to be validated. Our study explored the novel application of a recognized antiviral agent, remdesivir, focusing on its impact on endothelial activation and atherosclerosis. Methods Pharmacological treatment with remdesivir significantly reduced atherosclerotic lesions in the total aorta and decreased VCAM-1 expression in aortic roots of ApoE−/− mice. Remdesivir notably attenuated ox-LDL-induced endothelial cell (EC) activation, monocyte adhesion, and ROS production. In HUVECs, TAL1 interference via siRNA significantly increased TRAF6 protein levels, which was reversed by remdesivir. Remdesivir also reduced both total and K63-linked ubiquitination of TRAF6 in HUVECs. Immunoprecipitation assays revealed diminished co-localization of the two proteins under ox-LDL treatment, but this effect was reversed by remdesivir. Importantly, ectopic adeno-associated virus (AAV)-mediated overexpression of TAL1 reduced atherosclerotic lesions and VCAM-1 expression in the aorta of ApoE−/− mice. Results In ApoE –/– mice fed with a Western diet, remdesivir greatly attenuated atherosclerosis progression. At the cellular level, remdesivir suppressed oxidative stress, THP-1 adhesion, vascular cell adhesion molecule 1, and intercellular adhesion molecule 1 via oxidized low-density lipoprotein in human umbilical vein endothelial cells. T-cell acute lymphoblastic leukemia 1 (TAL1) functions by interacting with the ubiquitin E3 ligase TNF receptor-associated factor 6 (TRAF6) to ubiquitinate TRAF6, inhibiting nuclear factor kappa B activation. Remdesivir also restored the TAL1-TRAF6 interaction and decreased endothelial activation. Endothelial-specific TAL1 over-expression in ApoE –/– mice significantly reduced aortic plaque formation. Conclusions Remdesivir impedes atherosclerosis progression by re-establishing the interaction between TAL1 and TRAF6, diminishing endothelial activation. These findings offer an innovative therapeutic approach for atherosclerosis.

The substantial computational demands associated with Deep Neural Network (DNN)-based camera relocalization during the reasoning process impede their integration into autonomous vehicles. Cost and energy efficiency considerations may dissuade automotive manufacturers from employing high-computing equipment, limiting the adoption of advanced models. In response to this challenge, we present an innovative edge cloud collaborative framework designed for camera relocalization in autonomous vehicles. Specifically, we strategically offload certain modules of the neural network to the server and evaluate the inference time of data frames under different network segmentation schemes to guide our offloading decisions. Our findings highlight the vital role of server-side offloading in DNN-based camera relocation for autonomous vehicles, and we also discuss the results of data fusion. Finally, we validate the effectiveness of our proposed framework through experimental evaluation.

The integration of electrochromic devices and energy storage systems in wearable electronics is highly desirable yet challenging, because self‐powered electrochromic devices often require an open system design for continuous replenishment of the strong oxidants to enable the coloring/bleaching processes. A self‐powered electrochromic device has been developed with a close configuration by integrating a Zn/MnO2 ionic battery into the Prussian blue (PB)‐based electrochromic system. Zn and MnO2 electrodes, as dual shared electrodes, the former one can reduce the PB electrode to the Prussian white (PW) electrode and serves as the anode in the battery; the latter electrode can oxidize the PW electrode to its initial state and acts as the cathode in the battery. The bleaching/coloring processes are driven by the gradient potential between Zn/PB and PW/MnO2 electrodes. The as‐prepared Zn||PB||MnO2 system demonstrates superior electrochromic performance, including excellent optical contrast (80.6%), fast self‐bleaching/coloring speed (2.0/3.2 s for bleaching/coloring), and long‐term self‐powered electrochromic cycles. An air‐working Zn||PB||MnO2 device is also developed with a 70.3% optical contrast, fast switching speed (2.2/4.8 s for bleaching/coloring), and over 80 self‐bleaching/coloring cycles. Furthermore, the closed nature enables the fabrication of various flexible electrochromic devices, exhibiting great potentials for the next‐generation wearable electrochromic devices. A self‐powered Zn||PB||MnO2 electrochromic device based on a shared electrode design and featuring a closed configuration, has been developed, which consists of a Prussian blue (PB) based electrochromic system and a zinc‐ion battery (ZIB). Both the bleaching and coloring processes are driven by the gradient potentials between Zn/PB and PW/MnO2 electrodes instead of external power supply. Owning to the closed nature of Zn||PB||MnO2 electrochromic system, a range of integrated flexible electrochromic devices are successfully fabricated, including electrochromic glasses, labels, and wristbands, exhibiting great potentials for the next‐generation wearable electrochromic devices.