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Cytoplasmic STAT3, after activation by growth factors, translocates to different subcellular compartments, including nuclei and mitochondria, where it carries out different biological functions. However, the precise mechanism by which STAT3 undergoes mitochondrial translocation and subsequently regulates the tricarboxylic acid (TCA) cycle-electron transport chain (ETC) remains poorly understood. Here, we clarify this process by visualizing STAT3 acetylation in starved cells after serum reintroduction or insulin stimulation. CBP-acetylated STAT3 undergoes mitochondrial translocation in response to serum introduction or insulin stimulation. In mitochondria, STAT3 associates with the pyruvate dehydrogenase complex E1 (PDC-E1) and subsequently accelerates the conversion of pyruvate to acetyl-CoA, elevates the mitochondrial membrane potential, and promotes ATP synthesis. SIRT5 deacetylates STAT3, thereby inhibiting its function in mitochondrial pyruvate metabolism. In the A549 lung cancer cell line, constitutively acetylated STAT3 localizes to mitochondria, where it maintains the mitochondrial membrane potential and ATP synthesis in an active state.

Cholestatic liver diseases are characterized by excessive bile acid accumulation in the liver. Endothelial cells (ECs) shape the local microenvironment in both normal conditions and liver injury, yet their role in cholestasis is unclear. Through a comparative analysis of single-cell RNA sequencing data from various murine models of liver injury, we identify distinctive Myc activation within ECs during obstructive cholestasis resulting from bile duct ligation (BDL). Myc overexpression in ECs significantly upregulates P-selectin, increasing neutrophil infiltration and worsening cholestatic liver injury. This process occurs through the FXR, activated by chenodeoxycholic acid (CDCA) and its conjugate TCDCA. Inhibiting P-selectin with PSI-697 reduces neutrophil recruitment and alleviates injury. Cholestatic patient liver samples also show elevated Myc and P-selectin in ECs, along with increased neutrophils. The findings identify ECs as key drivers of cholestatic liver injury through a Myc-driven program and suggest that targeting the CDCA/FXR/Myc/P-selectin axis may offer a therapeutic approach. Liver endothelial cells respond differentially to various insults, influencing the liver’s niche and disease outcomes. Here the authors show that in response to bile acid chenodeoxycholic acid during cholestasis, endothelial Myc activation triggers P-selectin expression, promoting neutrophil infiltration and liver damage.

As modern attack methods become more concealed and complex, obtaining many labeled samples in big data streams is difficult. Active learning has long been used to achieve better intrusion detection performance by using only a small number of training samples. Intrusion behaviors can be described by provenance graphs that record the dependency relationships between intrusion processes and the infected files. It is a challenge to develop active learning strategies that consider defining and selecting the most valuable provenance and ensure that the strategy for querying provenance is efficient. We present Angus, an active learning framework for provenance-based intrusion detection. We propose two novel active learning strategies: the most similar graph query strategy and the maximum difference query strategy. They either select samples to update the training set according to similarities of provenance graphs or preferentially select samples with low redundancy and large differences from the current training set. Besides, we also improve the above query strategies by using the parallel query to reduce detection time overheads. The experiments on various real-world applications demonstrate their performance and efficiency.

Spatial heterogeneity and plasticity of the mammalian liver are critical for systemic metabolic homeostasis in response to fluctuating nutritional conditions. Here, a spatially resolved transcriptomic landscape of mouse livers across fed, fasted and refed states using spatial transcriptomics is generated. This approach elucidated dynamic temporal‐spatial gene cascades and how liver zonation—both expression levels and patterns—adapts to shifts in nutritional status. Importantly, the pericentral nuclear receptor Nr1i3 (CAR) as a pivotal regulator of triglyceride metabolism is pinpointed. It is showed that the activation of CAR in the pericentral region is transcriptionally governed by Pparα. During fasting, CAR activation enhances lipolysis by upregulating carboxylesterase 2a, playing a crucial role in maintaining triglyceride homeostasis. These findings lay the foundation for future mechanistic studies of liver metabolic heterogeneity and plasticity in response to nutritional status changes, offering insights into the zonated pathology that emerge during liver disease progression linked to nutritional imbalances. Spatial transcriptomics reveals how mouse liver zonation adapts to nutritional changes, highlighting the pericentral nuclear receptor CAR as a key regulator of triglyceride metabolism. CAR activation, transcriptionally governed by PPARα, enhances lipolysis during fasting by upregulating carboxylesterase 2a, crucial for maintaining triglyceride homeostasis. This study provides insights into the liver's metabolic heterogeneity and plasticity.

The development of shale gas reservoirs often involves the utilization of horizontal well segmental multi-stage fracturing techniques. However, these reservoirs face challenges, such as rapid initial wellhead pressure and production decline, leading to extended periods of low-pressure production. To address these issues and enhance the production during the low-pressure stage, pressurized mining is considered as an effective measure. Determining the appropriate pressurization target and method for the shale gas wells is of great practical significance for ensuring stable production in shale gas fields. This study takes into account the current development status of shale gas fields and proposes a three-stage pressurization process. The process involves primary supercharging at the center station of the block, secondary supercharging at the gas collecting station, and the introduction of a small booster device located behind the platform separator and in front of the outbound valve group. By incorporating a compressor, the wellhead pressure can be reduced to 0.4 MPa, resulting in a daily output of 12,000 to 14,000 cubic meters from the platform. Using a critical liquid-carrying model for shale gas horizontal wells, this study demonstrates that reducing the wellhead pressure decreases the critical flow of liquid, thereby facilitating the discharge of the accumulated fluid from the gas well. Additionally, the formation pressure of shale gas wells is estimated using the mass balance method. This study calculates the cumulative production of different IPR curves based on the formation pressure. It develops a dynamic production decline model for gas outlet wells and establishes a relationship between the pressure depletion of gas reservoirs and the cumulative gas production before and after pressurization of H10 −2 and H10 −3 wells. The final estimated ultimate recovery of two wells is calculated. In conclusion, the implementation of multi-stage pressurization, as proposed in this study, effectively enhances the production of, and holds practical significance for, stable development of shale gas fields.

A type of Fe-Al-Nb-B cored wire was designed and the coating was prepared using a robot-based electric wire arc spraying process. The Fe-Al binary cored wire and coating were also prepared as comparison. The phase composition and structure of the coatings were investigated using X-ray diffraction （XRD）, scanning electron microscopy （SEM） coupled with energy dispersive X-ray spectroscopy （EDS） and transmission electron microscopy （TEM）. The coating tribological properties were evaluated with the micromotion wear tester under different conditions. The results show that, although typical lamellar structure was performed for both the arc sprayed Fe-Al-Nb-B coating and Fe-Al coating, the structure composition, mechanical and wear properties of the former are quite different from those of latter. The Fe-Al-Nb-B coating is a typical composite coating, which is distributed inhomogeneously with α-Fe crystalline, FeAl and Fe3Al intermetallics, amorphous and nanocrystallines as well as locally existed oxide phases. As a result, the mircrohardness and wear resistance of the Fe-Al-Nb-B composite coating increased significantly. Finally the mechanism of the coating wear resistant behavior was discussed based on the experimental results such as friction coefficient, two dimensional and three dimensional worn surface profiles.

Provenance graphs are structured audit logs that describe the history of a system's execution. Recent studies have explored a variety of techniques to analyze provenance graphs for automated host intrusion detection, focusing particularly on advanced persistent threats. Sifting through their design documents, we identify four common dimensions that drive the development of provenance-based intrusion detection systems (PIDSes): scope (can PIDSes detect modern attacks that infiltrate across application boundaries?), attack agnosticity (can PIDSes detect novel attacks without a priori knowledge of attack characteristics?), timeliness (can PIDSes efficiently monitor host systems as they run?), and attack reconstruction (can PIDSes distill attack activity from large provenance graphs so that sysadmins can easily understand and quickly respond to system intrusion?). We present KAIROS, the first PIDS that simultaneously satisfies the desiderata in all four dimensions, whereas existing approaches sacrifice at least one and struggle to achieve comparable detection performance. Kairos leverages a novel graph neural network-based encoder-decoder architecture that learns the temporal evolution of a provenance graph's structural changes to quantify the degree of anomalousness for each system event. Then, based on this fine-grained information, Kairos reconstructs attack footprints, generating compact summary graphs that accurately describe malicious activity over a stream of system audit logs. Using state-of-the-art benchmark datasets, we demonstrate that Kairos outperforms previous approaches.

Security research has concentrated on converting operating system audit logs into suitable graphs, such as provenance graphs, for analysis. However, provenance graphs can grow very large requiring significant computational resources beyond what is necessary for many security tasks and are not feasible for resource constrained environments, such as edge devices. To address this problem, we present the \\textit{resource-interaction graph} that is built directly from the audit log. We show that the resource-interaction graph's storage requirements are significantly lower than provenance graphs using an open-source data set with two container escape attacks captured from an edge device. We use a graph autoencoder and graph clustering technique to evaluate the representation for an anomaly detection task. Both approaches are unsupervised and are thus suitable for detecting zero-day attacks. The approaches can achieve f1 scores typically over 80\\% and in some cases over 90\\% for the selected data set and attacks.

Background Lung ischemia–reperfusion injury (LIRI) is a complex pathophysiological process that can lead to poor patient outcomes. Inflammasome-dependent macrophage pyroptosis contributes to organ damage caused by ischemia/reperfusion injury. Oxidative stress and antioxidant enzymes also play an important role in LIRI. In this study, we conducted experiments to investigate whether and how preconditioning with rHMGB1 could ameliorate LIRI in a mouse model. Methods Adult male BALB/c mice were anesthetized, the left hilus pulmonis was clamped, and reperfusion was performed. rHMGB1 was administered via intraperitoneal injection before anesthesia, and brusatol was given intraperitoneally every other day before surgery. We measured pathohistological lung tissue damage, wet/dry mass ratios of pulmonary tissue, and levels of inflammatory mediators to assess the extent of lung injury. Alveolar macrophage pyroptosis was evaluated by measuring release of lactate dehydrogenase, caspase-1 expression was assessed using flow cytometry, and gasdermin-D expression was analyzed using immunofluorescent staining. Levels of oxidative stress markers and antioxidant enzymes were also analyzed. Results Preconditioning with rHMGB1 significantly ameliorated lung injury induced by ischemia–reperfusion, based on measurements of morphology, wet/dry mass ratios, as well as expression of IL-1β, IL-6, NF-κB, and HMGB1 in lung tissues. It also alleviated alveolar macrophage pyroptosis, reduced oxidative stress and restored the activity of antioxidant enzymes. These beneficial effects were mediated at least in part by the Keap1/Nrf2/HO-1 pathway, since they were reversed by the pathway inhibitor brusatol. Conclusions Preconditioning with rHMGB1 may protect against LIRI by suppressing alveolar macrophage pyroptosis. This appears to involve reduction of oxidative stress and promotion of antioxidant enzyme activity via the Keap1/Nrf2/HO-1 pathway.

Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors’ perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions.