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Long non-coding RNAs (lncRNAs) play critical functions in various cancers. Firre intergenic repeating RNA element (FIRRE), a lncRNA located in the nucleus, was overexpressed in colorectal cancer (CRC). However, the detailed mechanism of FIRRE in CRC remains elusive. Results of RNA sequence and qPCR illustrated overexpression of FIRRE in CRC cell lines and tissues. The aberrant expression of FIRRE was correlated with the migration, invasion, and proliferation in cell lines. In accordance, it was also associated with lymphatic metastasis and distant metastasis in patients with CRC. FIRRE was identified to physically interact with Polypyrimidine tract-binding protein (PTBP1) by RNA pull-down and RNA immunoprecipitation (RIP). Overexpression of FIRRE induced the translocation of PTBP1 from nucleus to cytoplasm, which was displayed by immunofluorescence and western blot. In turn, delocalization of FIRRE from nucleus to cytoplasm is observed after the loss of PTBP1. The RNA-protein complex in the cytoplasm directly bound to BECN1 mRNA, and the binding site was at the 3' end of the mRNA. Cells with FIRRE and PTBP1 depletion alone or in combination were treated by Actinomycin D (ACD). Results of qPCR showed FIRRE stabilized BECN1 mRNA in a PTBP1-medieated manner. In addition, FIRRE contributed to autophagy activity. These findings indicate FIRRE acts as an oncogenic factor in CRC, which induces tumor development through stabilizing BECN1 mRNA and facilitating autophagy in a PTBP1-mediated manner.

Magnetic soft robots have recently become a promising technology that has been applied to minimally invasive cardiovascular surgery. This paper presents the analytical modeling of a novel multi-section magnetic soft robot (MS-MSR) with multi-curvature bending, which is maneuvered by an associated collaborative multirobot navigation system (CMNS) with magnetic actuation and ultrasound guidance targeted for intravascular intervention. The kinematic and dynamic analysis of the MS-MSR’s telescopic motion is performed using the optimized Cosserat rod model by considering the effect of an external heterogeneous magnetic field, which is generated by a mobile magnetic actuation manipulator to adapt to complex steering scenarios. Meanwhile, an extracorporeal mobile ultrasound navigation manipulator is exploited to track the magnetic soft robot’s distal tip motion to realize a closed-loop control. We also conduct a quadratic programming-based optimization scheme to synchronize the multi-objective task-space motion of CMNS with null-space projection. It allows the formulation of a comprehensive controller with motion priority for multirobot collaboration. Experimental results demonstrate that the proposed magnetic soft robot can be successfully navigated within the multi-bifurcation intravascular environment with a shape modeling error 3.62 ± 1.28 ∘ and a tip error of 1.08 ± 0.45 mm under the actuation of a CMNS through in vitro ultrasound-guided vasculature interventional tests.

Ground-based detection of spaceborne dynamic objects, such as near-Earth asteroids and space debris, is essential for ensuring the safety of space operations. This paper presents YOLO-Dynamic, a novel detection algorithm aimed at addressing the limitations of existing models, particularly in complex environments and small-object detection. The proposed algorithm introduces two newly designed modules: the SC_Block_C2f and the LASF_Neck. SC_Block_C2f, developed in this study, integrates StarNet and Convolutional Gated Linear Unit (CGLU) operations, improving small-object recognition and feature extraction. Meanwhile, LASF_Neck employs a lightweight multi-scale architecture for optimized feature fusion and faster detection. The YOLO-Dynamic algorithm’s performance was validated on real-world images captured at Antarctic observatory sites. Compared to the baseline YOLOv8s model, YOLO-Dynamic achieved a 7% increase in mAP@0.5 and a 10.3% improvement in mAP@0.5:0.95. Additionally, the number of parameters was reduced by 1.48 M, and floating-point operations decreased by 3.8 G. These results confirm that YOLO-Dynamic not only delivers superior detection accuracy but also maintains computational efficiency, making it well suited for real-world applications requiring reliable and efficient spaceborne object detection.

Precipitation's temporal and spatial patterns under climate change significantly impact global terrestrial ecology and human social activities. Climate models are essential tools for assessing the impacts of climate change and formulating policies to address climate change. The evaluation results of historical climate model simulations can represent the reliability of their future simulations. This study evaluated the simulation capabilities of 41 historical All‐Forcing monthly precipitation simulations and three integrated models over global land in the Coupled Model Comparison Project Phase 6 (CMIP6). The results show that the simulation capability of global climate models (GCMs) in CMIP6 is highly variable overland around the world. This variability is manifested in two aspects: the spatial variability of the comprehensive simulation ability of each model in different geographical regions and climatic zones of the world and the significant difference in the simulation ability of different models in each region. These GCMs generally overestimate global monthly precipitation over land, with the exception of southeast Asia and tropical rainforest climate (Af), where all models underestimate monthly precipitation. Some GCMS can perform well regionally but poorly on the global scale. One example shows that EC‐Earth3's best capability at Cwc climatic zone, surpassing the integrated model, but failed to rank in the top 10 in 22 of the 29 climate zones. Our results highlight the need to select appropriate models for integration when conducting climate change studies at global and regional scales as a critical factor in studying climate change predictions. Plain Language Summary This study evaluated 41 monthly precipitation models in Coupled Model Comparison Project Phase 6 from geographic regionalization and global climate classification at the global land scale. Quantile integration was used to get three integration models to participate in the evaluation. Indicators used include correlation coefficient, Taylor skill score, Wasserstein distance, and common indicators of deviation analysis. Conclusions mainly include the performance of integrated models is generally better than that of single models on the global scale. The variation deviations of most indices have similar patterns to the corresponding mean deviations. In different geographic regions and climate types around the world, global climate models that perform better are different. In addition, this research also gives the suitable models in each region of the world and the upper limit of the simulation capability of all models in each area of the world. Key Points The comprehensive simulation capability of each global climate model (GCM) has spatial variability in different geographical regions and climate zones There is no single model can achieve good performance on a global scale Multiple model ensembles (quantile integration in this study) can significantly improve GCM's applicability on the large scale

Recent studies have shown that crustal body wave phases, such as PmP or SmS, can be effectively retrieved from ambient noise cross‐correlations. However, few studies have used these phases to constrain crustal structures. In this study, we successfully retrieve SmS signals from ambient noise data and observe SmS splitting caused by crustal radial anisotropy. Furthermore, through simulations of synthetic tests and application to field data, we demonstrate that these SmS signals can be used to constrain crustal radial anisotropy structures through joint inversion with surface waves. Our findings suggest that SmS signals obtained from noise data can significantly enhance the understanding of fine crustal radial anisotropic structures. Plain Language Summary By cross‐correlating ambient noise data, seismologists can extract the empirical Green's function between a pair of stations. Theoretically, both body and surface waves can be retrieved from these cross‐correlations. However, in practice, retrieving body wave signals from field data remains challenging. In this study, we successfully observe SmS signals, and their splitting caused by crustal radial anisotropy. By combining these SmS phases with surface wave dispersions, we can constrain the fine radial anisotropic structure of the crust. Using these body‐wave signals will enhance our understanding of the structure of the lower crust. Key Points SmS phases extracted from ambient noise show splitting due to radial anisotropy of the crust SmS signals can be used to constrain the radial anisotropy of the lower crust Joint inversion of SmS signals and surface waves provides an advantage in constructing the radial anisotropy of the crust

This study conducted a comprehensive investigation of the prognostic significance and immunological features associated with mitophagy-related gene signatures in clear cell renal cell carcinoma (KIRC). Our primary aim was to establish an optimized predictive model for precise prognosis stratification and treatment response prediction in KIRC patients. Through LASSO Cox regression analysis, we systematically identified mitophagy-related genes (MRGs) and implemented them to develop a prognostic risk stratification model. The model’s reliability was rigorously validated using both internal cohorts and independent external datasets. We subsequently constructed a clinically applicable nomogram by integrating the risk score with established prognostic indicators and relevant clinical parameters, thereby enabling multidimensional risk evaluation. Notably, tumor microenvironment characterization revealed enhanced immunotherapeutic responsiveness in high-risk patients, highlighting potential clinical utility for treatment selection. Complementary in vitro functional assays demonstrated that METTL24 overexpression significantly suppressed KIRC cell proliferation and migration capacity. Collectively, our mitophagy-related gene signature represents a novel prognostic biomarker with substantial clinical relevance, offering valuable insights for personalized therapeutic strategies in KIRC management. These findings not only advance our understanding of KIRC pathogenesis but also provide a framework for developing precision medicine approaches to optimize clinical outcomes.

Crickets use the pulse pattern of the species-specific calling song as a primary cue for mate recognition. Here we combined transcriptome profiling of brain regions with network-based analyses in Gryllus bimaculatus exposed to silence or pulse trains known to elicit strong or weak phonotactic attraction. Acoustic stimulation triggered specific transcriptional changes in the brain, with the anterior protocerebrum showing the most pronounced and selective responses to the calling song pattern, characterized by enrichment in neuromodulatory and neurotransmitter-related pathways. Weighted gene co-expression analysis identified a specific cluster of highly co-expressed genes in the anterior brain (termed the calling song-responsive module) that responded selectively only to the calling song stimulus. Genetic network topology analysis revealed six highly connected key hub genes within the calling song-responsive module—GbOrb2, Gbgl, Gbpum, GbDnm, GbCadN, and GbNCadN. These genes showed extensive interactions with many other genes in the network, suggesting their central regulatory role in response to calling song in female crickets. These findings support the anterior brain as a central integrator of cricket auditory mate recognition cues and point to a core molecular network that likely underpins this behavior.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) stands as a cornerstone in the treatment of hematological malignancies, recognized for its remarkable efficacy. However, the persistent challenge of graft-versus-host disease (GVHD) continues to represent a significant barrier, often being the leading cause of nonrelapse mortality after allo-HSCT. To address this limitation, hematopoietic stem cell microtransplantation (MST) has emerged as a novel therapeutic strategy that synergistically combines chemotherapy, allo-HSCT, and cellular immunotherapy. This innovative approach is designed to retain the patient’s immune function, promote the establishment of microchimerism, and achieve a potent graft-versus-tumor (GVT) response, all while significantly minimizing the risk of GVHD. MST has primarily been applied in the treatment of hematological malignancies, where it has demonstrated promising outcomes, including marked improvements in complete remission rates, overall survival rates, and progression-free survival rates. Moreover, MST facilitates hematopoietic recovery, decreases the likelihood of infections, and reduces the incidence of GVHD, thus contributing to an improved quality of life for patients. A deeper and more comprehensive understanding of MST’s mechanisms could enhance its clinical utility and integration into standard treatment protocols. This review aims to explore the underlying mechanisms, current clinical applications, and challenges of MST, shedding light on its potential role in advancing the management of hematological malignancies. Graphical Abstract ALL, acute lymphocytic leukemia; AML, acute myeloid leukemia; GVT, graft-versus-tumor effect; HLH, hemophagocytic lymphohistiocytosis; MDS, myelodysplastic syndrome; MM, multiple myeloma; MSC, mesenchymal stem cell; NK cells, natural killer cells; RVT, recipient-versus-tumor effect.

This study simulates future runoff in the Yalong River Basin by first identifying optimal NEX-GDDP-CMIP6 climate model data through Taylor diagrams and skill scores. Basin-specific meteorological datasets were derived for hydrological modeling. Using DEM, vegetation, and soil data, we parameterized and constructed a Variable Infiltration Capacity (VIC) model specifically calibrated for the basin. Daily and monthly runoff observations from Luning Station demonstrated model robustness during calibration and validation, yielding Nash-Sutcliffe Efficiency coefficients exceeding 0.8 and relative errors below 15%. The selected FGOALS-g3 historical climate data further validated the framework, achieving NSE > 0.75 and relative error < 15%. Coupling FGOALS-g3 with VIC yielded monthly runoff projections for 2025–2100. Analysis indicates a significant growth trend under both SSP245 and SSP585 emission scenarios, with intensification accelerating after 2069 under SSP585. Runoff remains seasonally concentrated (June–October ≈ 75%; winter ≈ 8%), consistent with historical patterns. Spectral analysis reveals distinct multidecadal periodicities: SSP245 shows 11 (5–10a), 17 (10–20a), and 7 (30–40a) wet-dry cycles; SSP585 exhibits 24 (5–10a) and 6 (40–50a) cycles. Primary oscillation modes occur at 5a, 13a, and 29a (SSP245) versus 5a, 20a, and 48a (SSP585). These findings provide critical insights for future hydrological planning and water resource management in the basin.

To address challenges in locating high-impedance grounding faults (HIGFs) and isolating fault areas in resonant grounding systems, this paper proposes a novel fault identification method based on coordinating a Peterson coil and a resistance grounding system. This method ensures power supply reliability by extinguishing the fault arc during transient faults with the Peterson coil. When a fault is determined to be permanent, the neutral point switches to a resistance grounding mode, ensuring regular distribution of zero-sequence currents in the network, thereby addressing the challenges of HIGF localization and fault area isolation. Fault calibration and nature determination rely on recognizing neutral point displacement voltage waveforms and dynamic characteristics, eliminating interference from asymmetric phase voltage variations. Fault area identification involves assessing the polarity of zero-sequence current waveforms attenuation during grounding mode switching, preventing misjudgments in grounding protection due to random initial fault angles and Peterson coil compensation states. Field experiments validate the feasibility of this fault location method and its control strategy.