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Blunting the tumor's stress-sensing ability is an effective strategy for controlling tumor adaptive survival and metastasis. Here, we have designed a cyclically amplified nano-energy interference device based on lipid nanoparticles (LNP), focused on altering cellular energy metabolism. This innovative nano device efficiently targets and monitors the tumor's status while simultaneously inhibiting mitochondrial respiration, biogenesis and ribosome production. To this end, we first identified azelaic acid (AA), a binary acid capable of disrupting the mitochondrial respiratory chain. Upon encapsulation in LNP and linkage to mitochondrial-targeting molecules, this disruptive effect is further augmented. Consequently, tumors exhibit a substantial upregulation of the glycolytic pathway, intensifying their glucose demand and worsening the tumor's energy-deprived microenvironment. Then, the glucose analog, 2-Deoxy-D-glucose (2-DG), linked to the LNP, efficiently targets tumors and competitively inhibits the tumor's normal glucose uptake. The synergetic results of combining AA with 2-DG induce comprehensive energy deficiency within tumors, blocking the generation of energy-sensitive ribosomes. Ultimately, the disruption of both mitochondria and ribosomes depletes energy supply and new protein-generating capacity, weakening tumor's ability to adapt to environmental stress and thereby inhibiting growth and metastasis. Comprehensively, this nano-energy interference device, by controlling the tumor's stress-sensing ability, provides a novel therapeutic strategy for refractory tumors.

Identification of reservoir types in deep carbonates has always been a great challenge due to complex logging responses caused by the heterogeneous scale and distribution of storage spaces. Traditional cross-plot analysis and empirical formula methods for identifying reservoir types using geophysical logging data have high uncertainty and low efficiency, which cannot accurately reflect the nonlinear relationship between reservoir types and logging data. Recently, the kernel Fisher discriminant analysis (KFD), a kernel-based machine learning technique, attracts attention in many fields because of its strong nonlinear processing ability. However, the overall performance of KFD model may be limited as a single kernel function cannot simultaneously extrapolate and interpolate well, especially for highly complex data cases. To address this issue, in this study, a mixed kernel Fisher discriminant analysis (MKFD) model was established and applied to identify reservoir types of the deep Sinian carbonates in central Sichuan Basin, China. The MKFD model was trained and tested with 453 datasets from 7 coring wells, utilizing GR, CAL, DEN, AC, CNL and RT logs as input variables. The particle swarm optimization (PSO) was adopted for hyper-parameter optimization of MKFD model. To evaluate the model performance, prediction results of MKFD were compared with those of basic-kernel based KFD, RF and SVM models. Subsequently, the built MKFD model was applied in a blind well test, and a variable importance analysis was conducted. The comparison and blind test results demonstrated that MKFD outperformed traditional KFD, RF and SVM in the identification of reservoir types, which provided higher accuracy and stronger generalization. The MKFD can therefore be a reliable method for identifying reservoir types of deep carbonates. [ABSTRACT FROM AUTHOR]

The risk for suffering immune checkpoint inhibitors (ICIs)-associated myocarditis increases in patients with pre-existing conditions and the mechanisms remain to be clarified. Spatial transcriptomics, single-cell RNA sequencing, and flow cytometry are used to decipher how anti-cytotoxic T lymphocyte antigen-4 m2a antibody (anti-CTLA-4 m2a antibody) aggravated cardiac injury in experimental autoimmune myocarditis (EAM) mice. It is found that anti-CTLA-4 m2a antibody increases cardiac fibroblast-derived C-X-C motif chemokine ligand 1 (Cxcl1), which promots neutrophil infiltration to the myocarditic zones (MZs) of EAM mice via enhanced Cxcl1-Cxcr2 chemotaxis. It is identified that the C-C motif chemokine ligand 5 (Ccl5)-neutrophil subpopulation is responsible for high activity of cytokine production, adaptive immune response, NF-κB signaling, and cellular response to interferon-gamma and that the Ccl5-neutrophil subpopulation and its-associated proinflammatory cytokines/chemokines promoted macrophage (Mφ) polarization to M1 Mφ. These altered infiltrating landscape and phenotypic switch of immune cells, and proinflammatory factors synergistically aggravated anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. Neutralizing neutrophils, Cxcl1, and applying Cxcr2 antagonist dramatically alleviates anti-CTLA-4 m2a antibody-induced leukocyte infiltration, cardiac fibrosis, and dysfunction. It is suggested that Ccl5-neutrophil subpopulation plays a critical role in aggravating anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. This data may provide a strategic rational for preventing/curing ICIs-associated myocarditis., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)