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Ground-based telescopes often encounter challenges such as stray light and vignetting when capturing space objects, leading to non-uniform image backgrounds. This not only weakens the signal-to-noise ratio for target tracking but also reduces the accuracy of recognition systems. To address this challenge, We have proposed a novel network architecture called CycleMRSNet, which is based on the CycleGAN framework and incorporates a multi-scale attention mechanism to enhance image processing capabilities. Specifically, we have introduced a multi-scale feature extraction module (MSFEM) at the front end of the generator and embedded an efficient multi-scale attention residual block (EMA-residual block) within the Resnet backbone network. This design improves the efficiency of feature extraction and increases the focus on multi-scale information in high-dimensional feature maps, enabling the network to more comprehensively understand and concentrate on key areas within images, thereby capably correcting non-uniform backgrounds. To evaluate the performance of CycleMRSNet, we trained the model using a small-scale dataset and conducted corrections on simulated and real images within the test set. Experimental results showed that our model achieved scores of PSNR 32.7923, SSIM 0.9814, and FID 1.9212 in the test set, outperforming other methods. These metrics suggest that our approach significantly improves the correction of non-uniform backgrounds and enhances the robustness of the system.

Background Cumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that they fail to find the unconfirmed miRNA and disease interactions. Thus, discovering potential miRNA-disease associations will make a contribution to the decrease of the pathogenesis of diseases and benefit disease therapy. Although, existing methods using different computational algorithms have favorable performances to search for the potential miRNA-disease interactions. We still need to do some work to improve experimental results. Results We present a novel combined embedding model to predict MiRNA-disease associations (CEMDA) in this article. The combined embedding information of miRNA and disease is composed of pair embedding and node embedding. Compared with the previous heterogeneous network methods that are merely node-centric to simply compute the similarity of miRNA and disease, our method fuses pair embedding to pay more attention to capturing the features behind the relative information, which models the fine-grained pairwise relationship better than the previous case when each node only has a single embedding. First, we construct the heterogeneous network from supported miRNA-disease pairs, disease semantic similarity and miRNA functional similarity. Given by the above heterogeneous network, we find all the associated context paths of each confirmed miRNA and disease. Meta-paths are linked by nodes and then input to the gate recurrent unit (GRU) to directly learn more accurate similarity measures between miRNA and disease. Here, the multi-head attention mechanism is used to weight the hidden state of each meta-path, and the similarity information transmission mechanism in a meta-path of miRNA and disease is obtained through multiple network layers. Second, pair embedding of miRNA and disease is fed to the multi-layer perceptron (MLP), which focuses on more important segments in pairwise relationship. Finally, we combine meta-path based node embedding and pair embedding with the cost function to learn and predict miRNA-disease association. The source code and data sets that verify the results of our research are shown at https://github.com/liubailong/CEMDA . Conclusions The performance of CEMDA in the leave-one-out cross validation and fivefold cross validation are 93.16% and 92.03%, respectively. It denotes that compared with other methods, CEMDA accomplishes superior performance. Three cases with lung cancers, breast cancers, prostate cancers and pancreatic cancers show that 48,50,50 and 50 out of the top 50 miRNAs, which are confirmed in HDMM V2.0. Thus, this further identifies the feasibility and effectiveness of our method.

Irreproducible wrinkling, characterized by randomly arranged ridges or creases on material surfaces, has significant potential for application in entity identification and anti-counterfeiting. However, active research in this field is hindered because the existing wrinkling methods face challenges in realizing discernible patterns and potential applications of submillimeter-scale wavelength wrinkles are yet to be identified. Herein, we propose a strategy to create unique and irreproducible styrene–ethylene–butylene–styrene (SEBS) wrinkles using “spin evaporation”, a technique that rapidly removes the solvent by spinning. We demonstrate the realization of SEBS wrinkles with wavelengths of hundreds of micrometers with high randomness, irreproducibility, and resistance to external stimuli. Importantly, to demonstrate the potential application of the wrinkle, we suggest and fabricate a human-finger-like fully soft identifiable artificial finger pad electronics and integrate it with a soft bimodal sensing system. The artificial finger pad mimics human finger pad features such as identification, object recognition, and effective grasping. Further integration of this pad into soft robots, cephalopods, and prosthetic skin offers insightful potential for the proposed wrinkling method in various fields. The authors introduce irreproducible soft wrinkles for artificial finger pad electronics, mimicking human finger functions. These structures enable secure authentication, object recognition, improved gripping, and integration into electronic systems.

Low modulus materials that can shape-morph into different three-dimensional (3D) configurations in response to external stimuli have wide-ranging applications in flexible/stretchable electronics, surgical instruments, soft machines and soft robotics. This paper reports a shape-programmable system that exploits liquid metal microfluidic networks embedded in an elastomer matrix, with electromagnetic forms of actuation, to achieve a unique set of properties. Specifically, this materials structure is capable of fast, continuous morphing into a diverse set of continuous, complex 3D surfaces starting from a two-dimensional (2D) planar configuration, with fully reversible operation. Computational, multi-physics modeling methods and advanced 3D imaging techniques enable rapid, real-time transformations between target shapes. The liquid-solid phase transition of the liquid metal allows for shape fixation and reprogramming on demand. An unusual vibration insensitive, dynamic 3D display screen serves as an application example of this type of morphable surface. Low modulus materials that can change shape in response to external stimuli are promising for a wide range of applications. The authors here introduce a shape-reprogrammable construct, based on liquid metal microfluidic networks and electromagnetic actuation, that supports a unique collection of capabilities.

The Insight -Hard X-ray Modulation Telescope ( Insight -HXMT) is a broadband X-ray and γ-ray (1-3000 keV) astronomy satellite. One of its three main telescopes is the High Energy X-ray telescope (HE). The main detector plane of HE comprises 18 NaI(Tl)/CsI(Na) phoswich detectors, where NaI(Tl) is used as the primary detector to measure ~ 20–250 keV photons incident from the field of view (FOV) defined by collimators, and CsI(Na) is used as the active shielding detector to NaI(Tl) by pulse shape discrimination. Additionally, CsI(Na) is used as an omnidirectional γ-ray monitor. The HE collimators have a diverse FOV, i.e. 1.1°×5.7° (15 units), 5.7°×5.7° (2 units), and blocked (1 unit). Therefore, the combined FOV of HE is approximately 5.7°×5.7°. Each HE detector has a diameter of 190 mm resulting in a total geometrical area of approximately 5100 cm 2 , and the energy resolution is ~15% at 60 keV. For each recorded X-ray event by HE, the timing accuracy is less than 10 μs and the dead-time is less than 10 μs. HE is used for observing spectra and temporal variability of X-ray sources in the 20–250 keV band either by pointing observations for known sources or scanning observations to unveil new sources. Additionally, HE is used for monitoring the γ-ray burst in 0.2-3 MeV band. This paper not only presents the design and performance of HE instruments but also reports results of the on-ground calibration experiments.

A black hole X-ray binary produces hard X-ray radiation from its corona and disk when the accreting matter heats up. During an outburst, the disk and corona co-evolves with each other. However, such an evolution is still unclear in both its geometry and dynamics. Here we report the unusual decrease of the reflection fraction in MAXI J1820+070, which is the ratio of the coronal intensity illuminating the disk to the coronal intensity reaching the observer, as the corona is observed to contrast during the decay phase. We postulate a jet-like corona model, in which the corona can be understood as a standing shock where the material flowing through. In this dynamical scenario, the decrease of the reflection fraction is a signature of the corona’s bulk velocity. Our findings suggest that as the corona is observed to get closer to the black hole, the coronal material might be outflowing faster. Evolution of accretion disk and corona during outbursts in black hole binary systems is still unclear. Here, the authors show spectral analysis of MAXI J1820+070 and propose a scenario of a dynamical corona to explain the evolution of the reflection fraction observed by Insight-HXMT.

The gut-brain axis is increasingly recognized as a key regulator of neurological health, with microbial metabolites influencing neurotransmission, synaptic plasticity, and neuroinflammation. Probiotics such as GG and 1714 have been associated with neuroactive effects, yet the molecular mechanisms linking microbial genomic potential to host neuronal responses remain poorly defined. This study aimed to integrate microbial genomics, neurotranscriptomics, and validation to unravel the neuromodulatory effects of GG and 1714. Whole-genome functional annotation, metabolic pathway prediction, and biosynthetic gene cluster analysis were performed to identify neuroactive potential. Neuronal RNA-seq datasets (n = 3 biological replicates per condition) were analyzed using differential expression, WGCNA, and GSEA to capture transcriptomic responses. Multi-omics integration (CCA, DIABLO, SPIEC-EASI) linked microbial pathways with neuronal gene modules. assays using SH-SY5Y and iPSC-derived neurons validated predictions through measurements of cell viability, oxidative stress, neurotransmitter release (ELISA), qPCR of synaptic and inflammatory genes, and extracellular vesicle characterization including EV transcript profiling. Genomic analysis revealed that GG was enriched in γ-aminobutyric acid (GABA) and SCFA pathways, while 1714 carried tryptophan-indole metabolism genes. Transcriptomic profiling demonstrated upregulation of synaptic genes (BDNF, SYN1), showed upregulation of synaptic genes ( , ), serotonergic transporters ( , ), and suppression of inflammatory mediators ( , ). Integration analyses identified two major subnetworks: a \"neurotransmission module\" driven by GG and a \"serotonin-immune module\" driven by 1714. validation confirmed increased GABA (1.7-fold) and serotonin (1.5-fold) release, reduced ROS (-18 to -22%), and EV transcript enrichment for synaptic and anti-inflammatory markers. This multi-omics study demonstrates mechanistic evidence that probiotics exert complementary neuromodulatory effects: GG primarily enhances GABAergic and SCFA-mediated synaptic pathways, whereas 1714 regulates the tryptophan-serotonin-immune axis. Together, these findings support the therapeutic potential of precision probiotics for neurological health and establish a systems-level framework for probing host-microbe interactions.

Pumps are critical life-sustaining components for all animals. At the earliest stages of life, the tubular embryonic heart works as a valveless pump capable of generating unidirectional blood flow. Inspired by this elementary pump, we developed an example of a biohybrid valveless pump-bot powered by engineered skeletal muscle. Our pump-bot consists of a soft hydrogel tube connected at both ends to a stiffer polydimethylsiloxane (PDMS) scaffold, creating an impedance mismatch. A contractile muscle ring wraps around the hydrogel tube at an off-center location, squeezing the tube with or without buckling it locally. Cyclic muscle contractions, spontaneous or electrically stimulated, further squeeze the tube, resulting in elastic waves that propagate along the soft tube and get reflected back at the soft/stiff tube boundaries. Asymmetric placement of muscle ring results in a time delay between the wave arrivals, thus establishing a net unidirectional fluid flow irrespective of whether the tube is buckled or not. Flow rates of up to 22.5 μL/min are achieved by the present pump-bot, which are at least three orders of magnitude higher than those from cardiomyocyte-powered valve pumps of similar size. Owning to its simple geometry, robustness, ease of fabrication, and high pumping performance, our pump-bot is particularly well-suited for a wide range of biomedical applications in microfluidics, drug delivery, biomedical devices, cardiovascular pumping system, and more.

Objective There is no consensus on the optimal treatment for ipsilateral femoral neck and shaft fractures. This meta-analysis aims to assess the effectiveness of reconstruction nails and dual implants in treating ipsilateral femoral neck and shaft fractures to provide a basis for decision-making when selecting the optimal approach. Methods Relevant articles were retrieved from Pubmed, Embase, and Cochrane databases using the keywords \"neck of femur\", \"shaft\" and \"fracture fixation\" from inception until November 17, 2022. The screening process of the studies was conducted independently by two assessors, who assessed each study's eligibility and two assessors assessed the quality. Then compared differences in outcome measures using RevMan 5.3 software. Results A total of ten retrospective cohort studies were included. There were no significant differences in union time, union rate, union-related complications (malunion, nonunion, delayed union) of femoral neck and shaft fractures, osteonecrosis of the femoral head, and functional outcomes (Friedman-Wyman scoring system) ( P  > 0.05). Conclusion Our pooled estimates indicated that reconstruction nails and dual implants for ipsilateral femoral neck and shaft fractures could yield satisfactory surgical results, and that there is no difference between the two treatment methods. Trial registration This meta-analysis was registered on the PROSPERO website (registration number: CRD42022379606).