SPDYC serves as a prognostic biomarker related to lipid metabolism and the immune microenvironment in breast cancer.

Breast cancer remains the most common malignant carcinoma among women globally and is resistant to several therapeutic agents. There is a need for novel targets to improve the prognosis of patients with breast cancer. Bioinformatics analyses were conducted to explore potentially relevant prognostic genes in breast cancer using The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) databases. Gene subtypes were categorized by machine learning algorithms. The machine learning-related breast cancer (MLBC) score was evaluated through principal component analysis (PCA) of clinical patients' pathological statuses and subtypes. Immune cell infiltration was analyzed using the xCell and CIBERSORT algorithms. Kyoto Encyclopedia of Genes and Genomes enrichment analysis elucidated regulatory pathways related to speedy/RINGO cell cycle regulator family member C (SPDYC) in breast cancer. The biological functions and lipid metabolic status of breast cancer cell lines were validated via quantitative real-time polymerase chain reaction (RT‒qPCR) assays, western blotting, CCK-8 assays, PI‒Annexin V fluorescence staining, transwell assays, wound healing assays, and Oil Red O staining. Key differentially expressed genes (DEGs) in breast cancer from the TCGA and GEO databases were screened and utilized to establish the MLBC score. Moreover, the MLBC score we established was negatively correlated with poor prognosis in breast cancer patients. Furthermore, the impacts of SPDYC on the tumor immune microenvironment and lipid metabolism in breast cancer were revealed and validated. SPDYC is closely related to activated dendritic cells and macrophages and is simultaneously correlated with the immune checkpoints CD47, cytotoxic T lymphocyte antigen-4 (CTLA-4), and poliovirus receptor (PVR). SPDYC strongly correlated with C-C motif chemokine ligand 7 (CCL7), a chemokine that influences breast cancer patient prognosis. A significant relationship was discovered between key genes involved in lipid metabolism and SPDYC, such as ELOVL fatty acid elongase 2 (ELOVL2), malic enzyme 1 (ME1), and squalene epoxidase (SQLE). Potent inhibitors targeting SPDYC in breast cancer were also discovered, including JNK inhibitor VIII, AICAR, and JW-7-52-1. Downregulation of SPDYC expression in vitro decreased proliferation, increased the apoptotic rate, decreased migration, and reduced lipid droplets. SPDYC possibly influences the tumor immune microenvironment and regulates lipid metabolism in breast cancer. Hence, this study identified SPDYC as a pivotal biomarker for developing therapeutic strategies for breast cancer.

NSP6 inhibits the production of ACE2-containing exosomes to promote SARS-CoV-2 infectivity.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global pandemic, which severely endangers public health. Our and others' works have shown that the angiotensin-converting enzyme 2 (ACE2)-containing exosomes (ACE2-exos) have superior antiviral efficacies, especially in response to emerging variants. However, the mechanisms of how the virus counteracts the host and regulates ACE2-exos remain unclear. Here, we identified that SARS-CoV-2 nonstructural protein 6 (NSP6) inhibits the production of ACE2-exos by affecting the protein level of ACE2 as well as tetraspanin-CD63 which is a key factor for exosome biogenesis. We further found that the protein stability of CD63 and ACE2 is maintained by the deubiquitination of proteasome 26S subunit, non-ATPase 12 (PSMD12). NSP6 interacts with PSMD12 and counteracts its function, consequently promoting the degradation of CD63 and ACE2. As a result, NSP6 diminishes the antiviral efficacy of ACE2-exos and facilitates the virus to infect healthy bystander cells. Overall, our study provides a valuable target for the discovery of promising drugs for the treatment of coronavirus disease 2019. IMPORTANCE: The outbreak of coronavirus disease 2019 (COVID-19) severely endangers global public health. The efficacy of vaccines and antibodies declined with the rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutants. Angiotensin-converting enzyme 2-containing exosomes (ACE2-exos) therapy exhibits a broad neutralizing activity, which could be used against various viral mutations. Our study here revealed that SARS-CoV-2 nonstructural protein 6 inhibited the production of ACE2-exos, thereby promoting viral infection to the adjacent bystander cells. The identification of a new target for blocking SARS-CoV-2 depends on fully understanding the virus-host interaction networks. Our study sheds light on the mechanism by which the virus resists the host exosome defenses, which would facilitate the study and design of ACE2-exos-based therapeutics for COVID-19.

Identification and validation of anoikis-related lncRNAs for prognostic significance and immune microenvironment characterization in ovarian cancer.

Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and metastasis. However, the potential roles of anoikis-related long non-coding RNAs (arlncRNAs) in the tumor microenvironment are not well understood. In this study, five candidate lncRNAs were screened through least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis based on differentially expressed lncRNAs associated with anoikis-related genes (ARGs) from TCGA and GSE40595 datasets. The prognostic accuracy of the risk model was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) analyses revealed significant differences in immune-related hallmarks and signal transduction pathways between the high-risk and low-risk groups. Additionally, immune infiltrate analysis showed significant differences in the distribution of macrophages M2, follicular T helper cells, plasma cells, and neutrophils between the two risk groups. Lastly, silencing the expression of PRR34_AS1 and SPAG5_AS1 significantly increased anoikis-induced cell death in ovarian cancer cells. In conclusion, our study constructed a risk model that can predict clinicopathological features, tumor microenvironment characteristics, and prognosis of ovarian cancer patients. The immune-related pathways identified in this study may offer new treatment strategies for ovarian cancer.

Hierarchical Reinforcement Learning Framework in Geographic Coordination for Air Combat Tactical Pursuit.

This paper proposes an air combat training framework based on hierarchical reinforcement learning to address the problem of non-convergence in training due to the curse of dimensionality caused by the large state space during air combat tactical pursuit. Using hierarchical reinforcement learning, three-dimensional problems can be transformed into two-dimensional problems, improving training performance compared to other baselines. To further improve the overall learning performance, a meta-learning-based algorithm is established, and the corresponding reward function is designed to further improve the performance of the agent in the air combat tactical chase scenario. The results show that the proposed framework can achieve better performance than the baseline approach.

Effect of oral administration of gabapentin on the minimum alveolar concentration of isoflurane in cats.

Objective: To determine if oral gabapentin decreases the minimum alveolar concentration (MAC) of isoflurane in cats. Study design: Prospective, randomized, blinded, crossover, and experimental study. Animals: A total of six healthy adult cats (three male, three female) aged 18-42 months, weighing 3.31 ± 0.26 kg. Methods: Cats were randomly given oral gabapentin (100 mg cat-1) or placebo 2 h before starting MAC determination, with the crossover treatment given at least 7 days apart. Anesthesia was induced and maintained with isoflurane in oxygen. Isoflurane MAC was determined in duplicate using an iterative bracketing technique and tail clamp method. Hemodynamic and other vital variables were recorded at each stable isoflurane concentration and were compared between gabapentin and placebo treatments at lowest end-tidal isoflurane concentration when cats did not respond to tail clamping. A paired t-test was used to compare normally distributed data, and a Wilcoxon signed-rank test was applied for non-normally distributed data. Significance was set at p < 0.05. Data are mean ± standard deviation. Results: Isoflurane MAC in the gabapentin treatment was 1.02 ± 0.11%, which was significantly lower than that in the placebo treatment (1.49 ± 0.12%; p < 0.001), decreasing by 31.58 ± 6.94%. No significant differences were found in cardiovascular and other vital variables between treatments. Conclusion and clinical relevance: Oral administration of gabapentin 2 h before starting MAC determination had a significant isoflurane MAC-sparing effect in cats with no observed hemodynamic benefit.

DFT Mechanistic Study of the Cyclopropanation of Styrene and Aryldiazodiacetate Catalyzed by Tris(pentafluorophenyl)borane.

Metal-free boron Lewis acids, tris(pentafluorophenyl)borane B(C6F5)3, have the advantages of low toxicity and low cost and are a promising catalyst. A density functional theory (DFT) calculation was used to clarify the mechanism and the origin of the diastereoselective cyclopropanation of aryldiazodiacetate and styrene derivatives catalyzed by B(C6F5)3. Four pathways were calculated: B(C6F5)3-catalyzed N-, C-, and O-bound boron-activated aryldiazodiacetate and without B(C6F5)3 catalysis. By calculating and comparing the energy barriers, the most possible reaction mechanism was proposed, that is, first, B(C6F5)3 catalyzed O-bound boron to activate aryldiazodiacetate, followed by the removal of a N2 molecule, and finally, styrene nucleophilic attack occurred to produce [2+1] cyclopropane products. N2 removal is the rate-limiting step, and this step determines the preference of a given mechanism. The calculated results are in agreement with experimental observations. The origin of diastereoselectivity is further explained on the basis of the favorable mechanism. The steric hindrance interference between the styrene aryl group and the large tri(pentafluorophenyl)borane B(C6F5)3 and the favorable π-π stacking interaction between the benzene rings combined to cause the high diastereoselectivity, which resulted in lower energy of the transition state (TS) corresponding to the reaction mechanism. The calculated results not only provide a more detailed explanation of the mechanism for the experimental study but also have certain reference and guiding significance for other catalytic cyclopropanation reactions.

Mixed YOLOv3-LITE: A Lightweight Real-Time Object Detection Method.

Embedded and mobile smart devices face problems related to limited computing power and excessive power consumption. To address these problems, we propose Mixed YOLOv3-LITE, a lightweight real-time object detection network that can be used with non-graphics processing unit (GPU) and mobile devices. Based on YOLO-LITE as the backbone network, Mixed YOLOv3-LITE supplements residual block (ResBlocks) and parallel high-to-low resolution subnetworks, fully utilizes shallow network characteristics while increasing network depth, and uses a "shallow and narrow" convolution layer to build a detector, thereby achieving an optimal balance between detection precision and speed when used with non-GPU based computers and portable terminal devices. The experimental results obtained in this study reveal that the size of the proposed Mixed YOLOv3-LITE network model is 20.5 MB, which is 91.70%, 38.07%, and 74.25% smaller than YOLOv3, tiny-YOLOv3, and SlimYOLOv3-spp3-50, respectively. The mean average precision (mAP) achieved using the PASCAL VOC 2007 dataset is 48.25%, which is 14.48% higher than that of YOLO-LITE. When the VisDrone 2018-Det dataset is used, the mAP achieved with the Mixed YOLOv3-LITE network model is 28.50%, which is 18.50% and 2.70% higher than tiny-YOLOv3 and SlimYOLOv3-spp3-50, respectively. The results prove that Mixed YOLOv3-LITE can achieve higher efficiency and better performance on mobile terminals and other devices.

Assessment of fibrotic tissue and microvascular architecture by in-line phase-contrast imaging in a mouse model of liver fibrosis.

PURPOSE: To explore the value of in-line phase-contrast imaging with computed tomography (ILPCI-CT) by synchrotron radiation (SR) for liver fibrosis. MATERIALS AND METHODS: Liver fibrosis models were set up in 13 BALB/c mice by peritoneal injections of thioacetamide and evaluated by ILPCI-CT. Histological staging was used to categorize liver fibrosis into normal, mild fibrosis and advanced fibrosis groups. Microvessel density (MVD), the ratio of total vessel length to volume (L/V), the ratio of total number of branching points to liver volume (P/V) and the distribution of vessel diameter were assessed. RESULTS: The CT images showed slightly high-density shadows around the portal tracts in the fibrosis group. Three-dimensional reconstruction can detect vascular and nodular changes on the surface of fibrotic livers. The MVDs between the three groups were significantly different (P = 0.024). L/V was significantly different between the three groups (P = 0.014). There was a positive correlation between MVD and P/V. CONCLUSION: Fibrous material can be detected by ILPCI-CT even in the early stage of fibrosis. MVD, L/V, P/V and the distribution of vessel diameter were consistent with fibrosis-related angiogenesis progress. Three-dimensional reconstruction is a promising method to visualize morphological changes of the fibrotic liver. KEY POINTS: • ILPCI-CT can detect fibrous material even in the early stage of liver fibrosis. • MVD, L/V, P/V, and the distribution of vascular diameter reflect pathological angiogenesis. • 3D reconstruction could be a promising approach for detecting liver fibrosis.

Critical role of CDK11(p58) in human breast cancer growth and angiogenesis.

BACKGROUND: A capillary network is needed in cancer growth and metastasis. Induction of angiogenesis represents one of the major hallmarks of cancer. CDK11(p58), a Ser/Thr kinase that belongs to the Cell Division Cycle 2-like 1 (CDC2L1) subfamily is associated with cell cycle progression, tumorigenesis, sister chromatid cohesion and apoptotic signaling. However, its role in breast cancer proliferation and angiogenesis remains unclear. METHODS: Tumorigenicity assays and blood vessel assessment in athymic mice were used to assess the function of CDK11(p58) in tumor proliferation and angiogenesis. CCK-8 assay was used to detect breast cancer cell growth. Immunohistochemistry was used to detect the expression of vascular endothelial growth factor (VEGF), CD31 and CD34 in CDK11 positive patient breast cancer tissues. Dual-Luciferase array was used to analyze the function of CDK11(p58) in the regulation of VEGF promoter activity. Western blot was used to detect related protein expression levels. RESULTS: CDK11(p58) inhibited breast cancer growth and angiogenesis in breast cancer cells and in nude mice transplanted with tumors. Immunohistochemistry confirmed that CDK11(p58) was negatively associated with angiogenesis-related proteins such as VEGF, CD31 and CD34 in breast cancer patients. Real-time PCR and dual-luciferase assay showed CDK11(p58) inhibited the mRNA levels of VEGF and the promoter activity of VEGF. As CDK11(p58) is a Ser/Thr kinase, the kinase-dead mutant failed to inhibit VEGF mRNA and promoter activity. Western blot analysis showed the same pattern of related protein expression. The data suggested angiogenesis inhibition was dependent on CDK11(p58) kinase activity. CONCLUSION: This study indicates that CDK11(p58) inhibits the growth and angiogenesis of breast cancer dependent on its kinase activity.