The integration of sensing and communication can achieve ubiquitous sensing while enabling ubiquitous communication. Within the gradually improving global communication, the integrated sensing and communication system based on optical fibers can accomplish various functionalities, such as urban structure imaging, seismic wave detection, and pipeline safety monitoring. With the development of quantum communication, quantum networks based on optical fiber are gradually being established. In this paper, we propose an integrated sensing and quantum network (ISAQN) scheme, which can achieve secure key distribution among multiple nodes and distributed sensing under the standard quantum limit. The continuous variables quantum key distribution protocol and the round-trip multiband structure are adopted to achieve the multinode secure key distribution. Meanwhile, the spectrum phase monitoring protocol is proposed to realize distributed sensing. It determines which node is vibrating by monitoring the frequency spectrum and restores the vibration waveform by monitoring the phase change. The scheme is experimentally demonstrated by simulating the vibration in a star structure network. Experimental results indicate that this multiuser quantum network can achieve a secret key rate of approximately 0.7 Mbits/s for each user under 10-km standard fiber transmission, and its network capacity is 8. In terms of distributed sensing, it can achieve a vibration response bandwidth ranging from 1 Hz to 2 kHz, a strain resolution of 0.50 \mathrm{n}\epsilon /\sqrt{\mathrm{Hz}}, and a spatial resolution of 0.20 m under shot-noise-limited detection. The proposed ISAQN scheme enables simultaneous quantum communication and distributed sensing in a multipoint network, laying a foundation for future large-scale quantum networks and high-precision sensing networks.

Removing trace amounts of acetylene (C₂H₂) from ethylene (C₂H₄)-rich gas mixtures is vital for the supply of high-purity C₂H₄ to the chemical industry and plastics sector. However, selective removal of C₂H₂ is challenging due to the similar physical and chemical properties of C₂H₂ and C₂H₄. Here, we report a “single-molecule trap” strategy that utilizes electrostatic interactions between the one-dimensional (1D) channel of a covalent organic framework (denoted as COF-1) and C₂H₂ molecules to massively enhance the adsorption selectivity toward C₂H₂ over C₂H₄. C₂H₂ molecules are immobilized via interactions with the O atom of C=O groups, the N atom of C≡N groups, and the H atom of phenyl groups in 1D channels of COF-1. Due to its exceptionally high affinity for C₂H₂, COF-1 delivered a remarkable C₂H₂ uptake of 7.97 cm³/g at 298 K and 0.01 bar, surpassing all reported COFs and many other state-of-the-art adsorbents under similar conditions. Further, COF-1 demonstrated outstanding performance for the separation of C₂H₂ and C₂H₄ in breakthrough experiments under dynamic conditions. COF-1 adsorbed C₂H₂ at a capacity of 0.17 cm³/g at 2,000 s/g when exposed to 0.5 ml/min C₂H₄-rich gas mixture (99% C₂H₄) at 298 K, directly producing high-purity C₂H₄ gas at a rate of 3.95 cm³/g. Computational simulations showed that the strong affinity between C₂H₂ and the single-molecule traps of COF-1 were responsible for the excellent separation performance. COF-1 is also robust, providing a promising new strategy for the efficient removal of trace amounts of C₂H₂ in practical C₂H₄ purification.

Problem: Chest radiography is a crucial tool for diagnosing thoracic disorders, but interpretation errors and a lack of qualified practitioners can cause delays in treatment. Aim: This study aimed to develop a reliable multi-classification artificial intelligence (AI) tool to improve the accuracy and efficiency of chest radiograph diagnosis. Methods: We developed a convolutional neural network (CNN) capable of distinguishing among 26 thoracic diagnoses. The model was trained and externally validated using 795,055 chest radiographs from 13 datasets across 4 countries. Results: The CNN model achieved an average area under the curve (AUC) of 0.961 across all 26 diagnoses in the testing set. COVID-19 detection achieved perfect accuracy (AUC 1.000, [95% confidence interval {CI}, 1.000 to 1.000]), while effusion or pleural effusion detection showed the lowest accuracy (AUC 0.8453, [95% CI, 0.8417 to 0.8489]). In external validation, the model demonstrated strong reproducibility and generalizability within the local dataset, achieving an AUC of 0.9634 for lung opacity detection (95% CI, 0.9423 to 0.9702). The CNN outperformed both radiologists and nonradiological physicians, particularly in trans-device image recognition. Even for diseases not specifically trained on, such as aortic dissection, the AI model showed considerable scalability and enhanced diagnostic accuracy for physicians of varying experience levels (all P < 0.05). Additionally, our model exhibited no gender bias (P > 0.05). Conclusion: The developed AI algorithm, now available as professional web-based software, substantively improves chest radiograph interpretation. This research advances medical imaging and offers substantial diagnostic support in clinical settings.

Radiotherapy (RT) serves as the primary treatment for solid tumors. Its potential to incite an immune response against tumors both locally and distally profoundly impacts clinical outcomes. However, RT may also promote the accumulation of immunosuppressive cytokines and immunosuppressive cells, greatly impeding the activation of antitumor immune responses and substantially limiting the effectiveness of RT. Therefore, regulating post-RT immunosuppression to steer the immune milieu toward heightened activation potentially enhances RT's therapeutic potential. Cytokines, potent orchestrators of diverse cellular responses, play a pivotal role in regulating this immunosuppressive response. Identifying and promptly neutralizing early released immunosuppressive cytokines are a crucial development in augmenting RT's immunomodulatory effects. To this end, we conducted a screen of immunosuppressive cytokines following RT and identified macrophage colony-stimulating factor (MCSF) as an early up-regulated and persistent immune suppressor. Single-cell sequencing revealed that the main source of up-regulated MCSF derived from tumor cells. Mechanistic exploration revealed that irradiation-dependent phosphorylation of the p65 protein facilitated its binding to the MCSF gene promoter, enhancing transcription. Knockdown and chemical inhibitor experiments conclusively demonstrated that suppressing tumor cell-derived MCSF amplifies RT's immune-activating effects, with optimal results achieved by early MCSF blockade after irradiation. Additionally, we validated that MCSF acted on macrophages, inducing the secretion of a large number of inhibitory cytokines. In summary, we propose a novel approach to enhance the immune activation effects of RT by blocking the MCSF-CSF1R signaling pathway early after irradiation.

The identification of aging- and longevity-associated genes is important for promoting healthy aging. By analyzing a large cohort of Chinese centenarians, we previously found that single-nucleotide polymorphisms (SNPs) in the SLC39A11 gene (also known as ZIP11) are associated with longevity in males. However, the function of the SLC39A11 protein remains unclear. Here, we found that SLC39A11 expression is significantly reduced in patients with Hutchinson–Gilford progeria syndrome (HGPS). In addition, we found that zebrafish with a mutation in slc39a11 that significantly reduces its expression have an accelerated aging phenotype, including a shortened average lifespan, muscle atrophy and reduced swimming, impaired muscle regeneration, gut damage, and abnormal morphology in the reproductive system. Interestingly, these signs of premature aging were more pronounced in male zebrafish than in females. RNA-sequencing analysis revealed that cellular senescence may serve as a potential mechanism for driving this slc39a11 deficiency-induced phenotype in mutant zebrafish. Moreover, immunofluorescence showed significantly increased DNA damage and reactive oxygen species signaling in slc39a11 mutant zebrafish. Using inductively coupled plasma mass spectrometry (ICP-MS), we found that manganese significantly accumulates in slc39a11 mutant zebrafish, as well as in the serum of both global Slc39a11 knockout and hepatocyte-specific Slc39a11 knockout mice, suggesting that this metal transporter regulates systemic manganese levels. Finally, using cultured human fibroblasts, we found that both knocking down SLC39A11 and exposure to high extracellular manganese increased cellular senescence. These findings provide compelling evidence that SLC39A11 serves to protect against the aging process, at least in part by regulating cellular manganese homeostasis.

The emergence of multi-petawatt laser facilities is expected to push forward the maximum energy gain that can be achieved in a single stage of a laser wakefield acceleration (LWFA) to tens of giga-electron volts, which begs the question—is it likely to impact particle physics by providing a truly compact particle collider? Colliders have very stringent requirements on beam energy, acceleration efficiency, and beam quality. In this article, we propose an LWFA scheme that can for the first time simultaneously achieve hitherto unrealized acceleration efficiency from the laser to the electron beam of >20% and a sub-1% energy spread using a stepwise plasma structure and a nonlinearly chirped laser pulse. Three-dimensional high-fidelity simulations show that the nonlinear chirp can effectively mitigate the laser waveform distortion and lengthen the acceleration distance. This, combined with an interstage rephasing process in the stepwise plasma, can triple the beam energy gain compared to that in a uniform plasma for a fixed laser energy, thereby dramatically increasing the efficiency. A dynamic beam loading effect can almost perfectly cancel the energy chirp that arises during the acceleration, leading to the sub-percent energy spread. This scheme is highly scalable and can be applied to petawatt LWFA scenarios. Scaling laws are obtained, which suggest that electron beams with parameters relevant for a Higgs factory could be reached with the proposed high-efficiency, low-energy-spread scheme.

Metal-organic frameworks (MOFs) have been widely considered as ideal platforms for the preparation of biomimetic catalysts, but it remains challenging to fabricate MOF-based enzyme-like catalysts with optimal activity. Here, we leverage the inherent flexibility of MOFs and propose a novel trans-functionalization strategy to construct a carbonic anhydrase (CA) mimic by the structural transformation from ZIF-L to ZIF-8. Theoretical and experimental results reveal that during the structural transformation, the hydroxyl group will preferentially coordinate with the interlayer Zn clusters to form the CA-like active center Zn-N₃-OH. Therefore, more accessible active centers are generated on the as-prepared ZIF-8-OH, resulting in substantially enhanced catalytic activity in the hydrolysis of para-nitrophenyl acetate.

Vibration is a common strategy for aquatic organisms to achieve their life activities, especially at the air–water interface. For the locomotion of small creatures, the organs with plate features are often used on water surfaces, which inspires relevant studies about using thin plates for robot propulsions. However, the influence of the general deformations of thin plates on the generated flow fields has not been considered. Here, a comprehensive investigation is conducted about the flow fields that arose by vibrations of thin plates and the potential as locomotion strategies are explored. It is discovered that as thin plates are subjected to vibration excitations on the water surface, the produced flow fields are mainly determined by the vibration shapes, and the influence rules of plate deformations on the flow fields are identified. The main factors producing asymmetric flow fields are analyzed to realize the morphology control of the flow fields. Then, to determine effective locomotion strategies on the water surface, the flow fields stimulated by integrated vibration exciters are explored, and 2 water surface robots are developed consequentially, which exhibit superior motion performance. This work reveals the basic rules of the vibration-induced-flow mechanism by thin plates and establishes new locomotion strategies for aquatic robots.

Due to the absence of definitive diagnostic criteria, there remains a lack of consensus regarding the risk assessment of central lymph node metastasis (CLNM) and the necessity for prophylactic lymph node surgery in ultrasound-diagnosed thyroid cancer. The localization of thyroid nodules is a recognized predictor of CLNM; however, quantifying this relationship is challenging due to variable measurements. In this study, we developed a differential isomorphism-based alignment method combined with a graph transformer to accurately extract localization and morphological information of thyroid nodules, thereby predicting CLNM. We collected 88,796 ultrasound images from 48,969 patients who underwent central lymph node (CLN) surgery and utilized these images to train our predictive model, ACE-Net. Furthermore, we employed an interpretable methodology to explore the factors influencing CLNM and generated a risk heatmap to visually represent the distribution of CLNM risk across different thyroid regions. ACE-Net demonstrated superior performance in 6 external multicenter tests (AUC = 0.826), surpassing the predictive accuracy of human experts (accuracy = 0.561). The risk heatmap enabled the identification of high-risk areas for CLNM, likely correlating with lymphatic metastatic pathways. Additionally, it was observed that the likelihood of metastasis exceeded 80% when the nodal margin's minimum distance from the thyroid capsule was less than 1.25 mm. ACE-Net's capacity to effectively predict CLNM and provide interpretable disease-related insights can importantly reduce unnecessary lymph node dissections by 37.9%, without missing positive cases, thus offering a valuable tool for clinical decision-making.

Metal wear particles generated by the movement of joint prostheses inevitably lead to aseptic osteolytic damage and ultimately prosthesis loosening, which are aggravated by various types of regulated cell death of bone. Nevertheless, the exact cellular nature and regulatory network underlying osteoferroptosis are poorly understood. Here, we report that titanium particles (TP) induced severe peri-implant osteolysis and ferroptotic changes with concomitant transcriptional repression of a key anti-ferroptosis factor, GPX4, in a mouse model of calvarial osteolysis. GPX4 repression was accompanied by an increase in DNA methyltransferases (DNMTs) 1/3a/3b and hypermethylation of the Gpx4 promoter, which were partly mediated by the transcriptional regulator/co-repressor KLF5 and NCoR. Conversely, treatment with SGI-1027, a DNMT-specific inhibitor, resulted in marked reversal of Gpx4 promoter hypermethylation and GPX4 repression, as well as improvement in ferroptotic osteolysis to a similar extent as with a ferroptosis inhibitor, liproxstatin-1. This suggests that epigenetic GPX4 repression and ferroptosis caused by the increase of DNMT1/3a/3b have a causal influence on TP-induced osteolysis. In cultured primary osteoblasts and osteoclasts, GPX4 repression and ferroptotic changes were observed primarily in osteoblasts that were alleviated by SGI-1027 in a GPX4 inactivation-sensitive manner. Furthermore, we developed a mouse strain with Gpx4 haplodeficiency in osteoblasts (Gpx4^Ob+/−) that exhibited worsened ferroptotic osteolysis in control and TP-treated calvaria and largely abolished the anti-ferroptosis and osteoprotective effects of SGI-1027. Taken together, our results demonstrate that DNMT1/3a/3b elevation, resulting GPX4 repression, and osteoblastic ferroptosis form a critical epigenetic pathway that significantly contributes to TP-induced osteolysis, and that targeting DNMT aberration and the associated osteoferroptosis could be a potential strategy to prevent or slow down prosthesis-related osteolytic complications.