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Cardiomyocyte senescence plays a crucial role as a pathological mechanism in heart failure (HF). However, the exact triggering factors and underlying causes of HF onset and progression are still not fully understood. By integrating multi-omics data, this study aimed to determine the genetic associations between cardiomyocyte and HF using cell senescence-related genes (SRGs). The study utilized the CellAge database and the SenMayo dataset, combined with high-resolution single-cell RNA sequencing (scRNA-seq) data, to identify SRG and examine differences in cardiac cell expression. To explore the causal relationship with HF using Mendelian Randomization (MR). Genetic variations influencing gene expression, DNA methylation, and protein expression (cis-eQTL, cis-mQTL, and cis-pQTL) were analyzed using the two-sample MR (TSMR) and summary-data-based MR (SMR). Additionally, Bayesian colocalization analysis, germline genetic variation, and bulk RNA data were employed to strengthen the reliability of the results. The application potential of therapeutic targets is ultimately assessed by evaluating their druggability. The expression of 39 SRGs in cardiomyocytes was identified. In the discovery set revealed that (OR = 1.09, 95% confidence interval (CI) 1.02-1.15, FDR = 0.048) could be causally related to HF, and the results are also replicated in the validation set (OR = 1.20, 95% confidence interval (CI) 1.10-1.30, FDR <0.0001). Based on the SMR method, was confirmed as a candidate pathogenic gene for HF, and its methylation (cg03714916, cg08179530) was associated with HF risk loci. The result is validated by Bayesian colocalization analysis, genetic variations, and bulk RNA data. The druggability analysis identified two potential therapeutic drugs. Based on multi-omics data, this study uncovered the reciprocal regulation of cardiomyocyte senescence through A, providing potential targets for HF drug development.

Background Heart failure (HF) is a prevalent and critical cardiac condition that leads to profound structural and functional changes in the heart. Although traditional treatments have shown partial efficacy, the long-term outcomes remain suboptimal. Emerging research has highlighted the pivotal role of oxidative stress and ferroptosis in HF progression. This study investigates a new therapeutic approach utilizing antioxidant polyphenol nanoparticles loaded with a STAT3 agonist (PN@Col) to target these pathways and improve age-related HF. Results Key cells and genes contributing to HF progression were identified via analysis of the GEO database, with single-cell RNA sequencing (scRNA-seq) and AUCell analysis used to evaluate differential gene expression. The STAT3 gene was highlighted as essential, and its functionality was further validated in vitro through cell experiments, confirming its impact on cardiomyocytes (CMs) in HF. Following the development of PN@Col, in vitro experiments showed that PN@Col effectively reduced oxidative stress and ferroptosis in CMs. In vivo studies in elderly HF mice demonstrated significant improvements in cardiac function following PN@Col treatment. Conclusions PN@Col offers a promising therapeutic approach to age-related HF by mitigating oxidative stress and ferroptosis in cardiomyocytes. These findings provide a solid scientific foundation for PN@Col as a potential novel treatment strategy for HF, supporting further exploration toward clinical application. Graphical Abstract

Accurate and robust navigation is fundamental to Unmanned Aerial Vehicle (UAV) remote sensing operations. However, the susceptibility of UAV navigation sensors to diverse interference and malicious attacks can severely degrade positioning accuracy and compromise mission integrity. Addressing these vulnerabilities, this paper presents an integrated framework combining sensor anomaly detection with a Dynamic Adaptive Extended Kalman Filter (DAEKF) and federated filtering algorithms to bolster navigation resilience and accuracy for UAV remote sensing. Specifically, mathematical models for prevalent UAV sensor attacks were established. The proposed framework employs adaptive thresholding and residual consistency checks for the real-time identification and isolation of anomalous sensor measurements. Based on these detection outcomes, the DAEKF dynamically adjusts its sensor fusion strategies and noise covariance matrices. To further enhance the fault tolerance, a federated filtering architecture was implemented, utilizing adaptively weighted sub-filters based on assessed trustworthiness to effectively isolate faults. The efficacy of this framework was validated through rigorous experiments that involved real-world flight data and software-defined radio (SDR)-based Global Positioning System (GPS) spoofing, alongside simulated attacks. The results demonstrate exceptional performance, where the average anomaly detection accuracy exceeded 99% and the precision surpassed 98%. Notably, when benchmarked against traditional methods, the proposed system reduced navigation errors by a factor of approximately 2-3 under attack scenarios, which substantially enhanced the operational stability of the UAVs in challenging environments.

Intraventricular hemorrhage is one of the most fatal forms of brain injury that is a common complication of premature infants. However, the therapy of this type of hemorrhage is limited, and new strategies are needed to reduce hematoma expansion. Here we show that the meningeal lymphatics is a pathway to remove red blood cells from the brain’s ventricular system of male human, adult and newborn rodents and is a target for non-invasive transcranial near infrared photobiomodulation. Our results uncover the clinical significance of phototherapy of intraventricular hemorrhage in 4-day old male rat pups that have the brain similar to a preterm human brain. The course of phototherapy in newborn rats provides fast recovery after intraventricular hemorrhage due to photo-improvements of lymphatic drainage and clearing functions. These findings shed light on the mechanisms of phototherapy of intraventricular hemorrhage that can be a clinically relevant technology for treatment of neonatal intracerebral bleedings. Intraventricular hemorrhage is one of the most fatal forms of brain injury. It is a common complication in premature infants and has limited treatment options. Here, the authors show that transcranial photostimulation can ameliorate lymphatic removal of blood from the brain of adult and newborn rodents after intraventricular hemorrhage, providing fast recovery and improvement of behavioral outcomes.

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems.

Mammalian reovirus (reovirus) is a multilayered, turreted member of Reoviridae characterized by transcription of dsRNA genome within the innermost capsid shell. Here, we present high-resolution in situ structures of reovirus transcriptase complex in an intact double-layered virion, and in the uncoated single-layered core particles in the unloaded, reloaded, pre-elongation, and elongation states, respectively, obtained by cryo-electron microscopy and sub-particle reconstructions. At the template entry of RNA-dependent RNA polymerase (RdRp), the RNA-loading region gets flexible after uncoating resulting in the unloading of terminal genomic RNA and inactivity of transcription. However, upon adding transcriptional substrates, the RNA-loading region is recovered leading the RNAs loaded again. The priming loop in RdRp was found to play a critical role in regulating transcription, which hinders the elongation of transcript in virion and triggers the rearrangement of RdRp C-terminal domain (CTD) during elongation, resulting in splitting of template-transcript hybrid and opening of transcript exit. With the integration of these structures, a transcriptional model of reovirus with five states is proposed. Our structures illuminate the RdRp activation and regulation of the multilayered turreted reovirus.

Cryo-electron tomography (cryo-ET) is widely used to explore the 3D density of biomacromolecules. However, the heavy noise and missing wedge effect prevent directly visualizing and analyzing the 3D reconstructions. Here, we introduced REST, a deep learning strategy-based method to establish the relationship between low-quality and high-quality density and transfer the knowledge to restore signals in cryo-ET. Test results on the simulated and real cryo-ET datasets show that REST performs well in denoising and compensating the missing wedge information. The application in dynamic nucleosomes, presenting either in the form of individual particles or in the context of cryo-FIB nuclei section, indicates that REST has the capability to reveal different conformations of target macromolecules without subtomogram averaging. Moreover, REST noticeably improves the reliability of particle picking. These advantages enable REST to be a powerful tool for the straightforward interpretation of target macromolecules by visual inspection of the density and of a broad range of other applications in cryo-ET, such as segmentation, particle picking, and subtomogram averaging. Heavy noise and missing wedge effect hamper the efficient visualization and analysis in cryo-ET. Here, authors present a deep learning-based method for directly visualizing and revealing the dynamic states of target molecules.

Minimally invasive testing is essential for early cancer detection, impacting patient survival rates significantly. Our study aimed to establish a pioneering cell-free immune-related miRNAs (cf-IRmiRNAs) signature for early cancer detection. We analyzed circulating miRNA profiles from 15,832 participants, including individuals with 13 types of cancer and control. The data was randomly divided into training, validation, and test sets (7:2:1), with an additional external test set of 684 participants. In the discovery phase, we identified 100 differentially expressed cf-IRmiRNAs between the malignant and non-malignant, retaining 39 using the least absolute shrinkage and selection operator (LASSO) method. Five machine learning algorithms were adopted to construct cf-IRmiRNAs signature, and the diagnostic classifies based on XGBoost algorithm showed the excellent performance for cancer detection in the validation set (AUC: 0.984, CI: 0.980–0.989), determined through 5-fold cross-validation and grid search. Further evaluation in the test and external test sets confirmed the reliability and efficacy of the classifier (AUC: 0.980 to 1.000). The classifier successfully detected early-stage cancers, particularly lung, prostate, and gastric cancers. It also distinguished between benign and malignant tumors. This study represents the largest and most comprehensive pan-cancer analysis on cf-IRmiRNAs, offering a promising non-invasive diagnostic biomarker for early cancer detection and potential impact on clinical practice.

High viscosity of alginate means a relatively low substrate concentration, which limits the efficiency of hydrolysis, resulting in one of the main challenges for the large-scale production of alginate oligosaccharides (AOS). In this study, a pilot-scale degradation product (PSDP) of the recombinant enzyme 102C300C-Vgb was produced for the first time at a substrate concentration of up to 20% sodium alginate. The optimal conditions for SA digestion were: enzyme dosage of 25 U/g, enzymatic temperature of 45 °C, enzymatic pH of 7.0, and enzymatic time of 24 h. Under these conditions, the yield of enzymatic hydrolysis was consistently in the range of 69% to 70%. The average molecular weight (Mw) of PSDP was 1496.36 Da, mainly containing oligosaccharides with degrees of polymerization ranging from 2 to 4. The low-Mw PSDP was subsequently applied in the diet of sea cucumber Stichopus japonicus. The results showed that the body wall weight of S. japonicus increased significantly after 40 days of feeding with a 0.09% PSDP-supplemented diet. Furthermore, PSDP-supplemented diet significantly increased the thickness of the serosal and submucosal layers and the width folds of mucosa of the sea cucumber gut. The abundance of pathogenic bacteria was reduced effectively, and that of beneficial bacteria increased significantly after being fed with PSDP. The results demonstrated that PSDP can serve as a digestive health enhancer for sea cucumbers, promoting their healthy growth.