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Tumor cells reprogram their metabolism to produce specialized metabolites that both fuel their own growth and license tumor immune evasion. However, the relationships between these functions remain poorly understood. Here, we report CRISPR screens in a mouse model of colo-rectal cancer (CRC) that implicates the dual specificity phosphatase 18 (DUSP18) in the establishment of tumor-directed immune evasion. Dusp18 inhibition reduces CRC growth rates, which correlate with high levels of CD8 + T cell activation. Mechanistically, DUSP18 dephosphorylates and stabilizes the USF1 bHLH-ZIP transcription factor. In turn, USF1 induces the SREBF2 gene, which allows cells to accumulate the cholesterol biosynthesis intermediate lanosterol and release it into the tumor microenvironment (TME). There, lanosterol uptake by CD8 + T cells suppresses the mevalonate pathway and reduces KRAS protein prenylation and function, which in turn inhibits their activation and establishes a molecular basis for tumor cell immune escape. Finally, the combination of an anti-PD-1 antibody and Lumacaftor, an FDA-approved small molecule inhibitor of DUSP18, inhibits CRC growth in mice and synergistically enhances anti-tumor immunity. Collectively, our findings support the idea that a combination of immune checkpoint and metabolic blockade represents a rationally-designed, mechanistically-based and potential therapy for CRC. Dual-specificity phosphatases regulate several processes associated with carcinogenesis. Here the authors show that inhibition of the dual-specificity phosphatase DUSP18 improves the activity of tumor-infiltrating CD8 T cells, enhancing response to immune checkpoint blockade in preclinical models of colorectal cancer.

To address yttrium (Y) contamination from ion adsorption mining, this study developed a combined microbial phytoremediation strategy for dual objectives: ensuring crop safety in and enhancing Y recovery by . Two specific microbial consortia were constructed from rare earth tailings isolates: inoculant I (bacterial: sp., sp., sp.) applied to , and inoculant II (fungal: sp., sp., sp.) applied to . Inoculant I increased biomass by 26% while reducing Y content in roots and rhizosphere soil solution by 47% and 56%, respectively, potentially through down-regulation of amino acid metabolites. Inoculant II increased Y content in the rhizosphere soil solution by 89%, linked to up-regulation of organic acids and coumarin derivatives. Both consortia reduced plant stress markers and enhanced soil enzyme activities. These findings demonstrate that specialized microbial consortia can differentially regulate Y behavior in the rhizosphere-immobilizing it in a crop for food safety, while enhancing its bioavailability for a hyperaccumulator-offering a targeted strategy for managing rare earth element-contaminated agricultural soils.

The metabolic pathways through which p53 functions as a potent tumor suppressor are incompletely understood. Here we report that, by associating with the Vitamin D receptor (VDR), p53 induces numerous genes encoding enzymes for peroxisomal fatty acid β-oxidation (FAO). This leads to increased cytosolic acetyl-CoA levels and acetylation of the enzyme 5-Aminoimidazole-4-Carboxamide Ribonucleotide Formyltransferase/IMP Cyclohydrolase (ATIC), which catalyzes the last two steps in the purine biosynthetic pathway. This acetylation step, mediated by lysine acetyltransferase 2B (KAT2B), occurs at ATIC Lys 266, dramatically inhibits ATIC activity, and inversely correlates with colorectal cancer (CRC) tumor growth in vitro and in vivo, and acetylation of ATIC is downregulated in human CRC samples. p53-deficient CRCs with high levels of ATIC is more susceptible to ATIC inhibition. Collectively, these findings link p53 to peroxisomal FAO, purine biosynthesis, and CRC pathogenesis in a manner that is regulated by the levels of ATIC acetylation.

Permanent highway support in deep coal mines now depends on the anchor drilling robot’s drill arm. The drilling arm’s trajectory planning using the conventional RRT (rapid-expanding random tree) algorithm is inefficient and has crooked, rough paths. To improve the accuracy of path planning, we propose an improved RRT algorithm. Firstly, the kinematic model of the drill arm of the drill and anchor robot was established, and the improved DH solution parameters and the positive solution of the drill arm kinematics were solved. The end effector’s attainable working space was calculated using the Monte Carlo approach. Additionally, to address the problem of the slow running speed of the RRT algorithm, an artificial potential field factor was introduced to construct virtual force fields at obstacle and target points and calculate the potential field map for the entire reachable workspace to improve the speed of the sampling points close to the target point. At the same time, the greedy approach and the three-time B-sample curve-fitting method were used simultaneously to remove unnecessary points and carry out smooth path processing in order to improve the quality of the drill arm trajectory. This was carried out in order to solve the issue of rough pathways generated by the RRT algorithm. Finally, 50 time-sampling comparison experiments were conducted on 2D and 3D maps. The experimental results showed that the improved RRT algorithm improved the average sampling speed by 20% and reduced the average path length by 14% compared with the RRT algorithm, which verified the feasibility and effectiveness of this improved RRT algorithm. The improved RRT algorithm generates more efficient and smoother paths, which can improve the intelligence of the support process by integrating and automating drilling and anchoring and providing reliable support for coal mine intelligence.

β‐catenin signaling is abnormally activated in cancer. Here, this work screens the mevalonate metabolic pathway enzyme PMVK to stabilize β‐catenin signaling using a human genome‐wide library. On the one hand, PMVK‐produced MVA‐5PP competitively binds to CKIα to prevent β‐catenin Ser45 phosphorylation and degradation. On the other hand, PMVK functions as a protein kinase to directly phosphorylate β‐catenin Ser184 to increase its protein nuclear localization. This synergistic effect of PMVK and MVA‐5PP together promotes β‐catenin signaling. In addition, PMVK deletion impairs mouse embryonic development and causes embryonic lethal. PMVK deficiency in liver tissue alleviates DEN/CCl4‐induced hepatocarcinogenesis. Finally, the small molecule inhibitor of PMVK, PMVKi5, is developed and PMVKi5 inhibits carcinogenesis of liver and colorectal tissues. These findings reveal a non‐canonical function of a key metabolic enzyme PMVK and a novel link between the mevalonate pathway and β‐catenin signaling in carcinogenesis providing a new target for clinical cancer therapy. The mevalonate pathway kinase PMVK stabilizes β‐catenin via the PMVK‐generated intermediate MVA‐5PP. MVA‐5PP blocks β‐catenin phosphorylation at Ser45 by inhibiting the CKIα kinase. This stabilizes β‐catenin by preventing its cytoplasmic sequestration and proteolysis. Concurrently, PMVK also phosphorylates β‐catenin at Ser184, which facilitates its nuclear translocation. PMVK thus represents a novel therapeutic target in cancers that rely on aberrant β‐catenin signaling.

Highlights A novel anisotropic sensor with oriented piezoelectric filaments was prepared, capable of detecting both the magnitude and direction of micro-deformations. Due to the efficient load transfer of continuous fibers and the formation of porous ferroelectrets, an ultra-low strain detection limit of 0.06% was achieved in the sensor. Given the sensor's ultra-low detection limit and deformation direction sensing capability, we developed the sensor for detecting micron-scale deformations in thin-film structures and for robotic tactile sensing applications. Monitoring minuscule mechanical signals, both in magnitude and direction, is imperative in many application scenarios, e.g., structural health monitoring and robotic sensing systems. However, the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix, and achieving sensitivity for detecting micrometer-scale deformations is also challenging. Herein, we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement, capable of detecting minute anisotropic deformations. The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%, thereby enabling its utility in accurately discerning the 5 μm-height wrinkles in thin films and in monitoring human pulse waves. The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase. Additionally, when integrated with machine learning techniques, the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100% accuracy. The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli, offering a novel perspective for enhancing recognition accuracy.

Superlubricity of graphite and graphene has aroused increasing interest in recent years. Yet how to obtain a long-lasting superlubricity between graphene layers, under high applied normal load in ambient atmosphere still remains a challenge but is highly desirable. Here, we report a direct measurement of sliding friction between graphene and graphene, and graphene and hexagonal boron nitride (h-BN) under high contact pressures by employing graphene-coated microsphere (GMS) probe prepared by metal-catalyst-free chemical vapour deposition. The exceptionally low and robust friction coefficient of 0.003 is accomplished under local asperity contact pressure up to 1 GPa, at arbitrary relative surface rotation angles, which is insensitive to relative humidity up to 51% RH. This ultralow friction is attributed to the sustainable overall incommensurability due to the multi-asperity contact covered with randomly oriented graphene nanograins. This realization of microscale superlubricity can be extended to the sliding between a variety of two-dimensional (2D) layers. Superlubricity can be unstable in graphene systems, especially under high applied loads. Here the authors use microspheres uniformly coated by graphene to measure friction between 2D materials and show that superlow friction is preserved for long periods of time under high loads and various atmospheres.

Deep learning-based impact load identification technology for the next generation of large aircraft structures has garnered significant attention and has become one of the focal points in aircraft structural health monitoring. However, this technology relies on a large number of training samples and exhibits poor scalability. One of the current challenges in system-level multi-structure monitoring is how to construct deep learning models with a small number or even zero impact training samples, and improve the models’ ability to migrate between different structures. To address this challenge, a novel method for impact load identification using only a small number of samples, based on a supervised scene adaptive model, is proposed. The performance of the model is validated on real aircraft structures. For large and complex structures, the model can be applied to other similar structural areas or different structural areas by using samples from the baseline area for training. Then, a very small number of calibration samples from the migrated area can be used for calibration. The results demonstrate that the proposed model, calibrated with just a single sample, achieves 97.22% accuracy in impact location identification and 99.44% accuracy in energy identification under similar regional structural conditions. Under different structural region conditions, the location identification accuracy of the proposed model is 87.65%, while the energy identification accuracy remains at 98.85%. The position identification accuracy of the model is 91.98% under different impact energy level conditions, and the identification accuracy remains at 87.04% even under varying impact energy levels and structural region conditions.

In this paper, BiOBr/BiOCl heterostructure microspheres are prepared successfully via a simple solvothermal way. Research shows that BiOBr/BiOCl microspheres exhibit significantly much higher photocatalytic performance than pure BiOBr or BiOCl. The optimum photodegradation rate of BiOBr/BiOCl for rhodamine B (RhB) is 0.0290 min −1 , which is approximately 4.5 times as high as pure BiOBr ( k  = 0.0065 min −1 ) and 8.8 times as high as pure BiOCl ( k  = 0.0033 min −1 ) under visible light. For this new photocatalyst, the enhanced photoactivity is presumably attributed to the formation of heterojunction which improves the separation of photoinduced electrons and holes to a great extent. Mechanism investigation reveals that O 2 .− plays significant roles during the photocatalysis process.

Background Recent evidence suggests that the box H/ACA small nucleolar RNA (snoRNA)-ended long noncoding RNA (lncRNA), SLERT, plays a critical role in gene regulation. However, its role in cancer remains undetermined. Herein, we explored its implication in human endometrial cancer (EC). Methods EC plasma and tissue samples were collected for the detection of SLERT expression using qRT-PCR method. The functional investigation was tested by CCK-8 and transwell assays. Luciferase reporter, RNA pull-down, and immunoprecipitation (RIP) assays were used to determine the regulatory network involved in SLERT. The in vivo effect of SLERT was tested by caudal vein lung metastasis model. Results Stable knockdown of SLERT significantly inhibited EC cell (KLE and AN3CA) migration and invasion, while it did not affect cell viability. SLERT induced epithelial-mesenchymal transition (EMT) via elevating N-cadherin and Vimentin and downregulating E-cadherin. Further investigation showed that SLERT directly binds to METTL3, increasing the m 6 A levels of BDNF mRNA; then, the m 6 A sites were read by IGF2BP1, enhancing BDNF mRNA stability, followed by the activation of BDNF/TRKB signaling, an inducer of EMT. The animal model showed that overexpression of SLERT increased EC cell lung metastasis, and this effect was effectively blocked by BDNF silencing or treatment with TRKB inhibitor k252a. Clinically, EC patients have high levels of SLERT both in tissue or plasma, which might be used as a biomarker of diagnosis and prognosis. Conclusion Our findings, for the first time, uncover the metastasis-promoting effect of SLERT in EC via in vitro and in vivo evidence, providing a potential therapeutic target for metastatic EC treatment.