Opioids such as morphine are mainstay treatments for clinical pain conditions. Itch is a common side effect of opioids, particularly as a result of epidural or intrathecal administration. Recent progress has advanced our understanding of itch circuits in the spinal cord. However, the mechanisms underlying opioid-induced itch are not fully understood, although an interaction between µ-opioid receptor (MOR) and gastrin-releasing peptide receptor (GRPR) in spinal GRPR-expressing neurons has been implicated. In this study we investigated the cellular mechanisms of intrathecal opioid-induced itch by conditional deletion of MOR-encoding Oprm1 in distinct populations of interneurons and sensory neurons. We found that intrathecal injection of the MOR agonists morphine or DAMGO elicited dose-dependent scratching as well as licking and biting, but this pruritus was totally abolished in mice with a specific Oprm1 deletion in Vgat+ neurons [Oprm1-Vgat (Slc32a1)]. Loss of MOR in somatostatin+ interneurons and TRPV1+ sensory neurons did not affect morphine-induced itch but impaired morphine-induced antinociception. In situ hybridization revealed Oprm1 expression in 30% of inhibitory and 20% of excitatory interneurons in the spinal dorsal horn. Whole-cell recordings from spinal cord slices showed that DAMGO induced outward currents in 9 of 19 Vgat+ interneurons examined. Morphine also inhibited action potentials in Vgat+ interneurons. Furthermore, morphine suppressed evoked inhibitory postsynaptic currents in postsynaptic Vgat− excitatory neurons, suggesting a mechanism of disinhibition by MOR agonists. Notably, morphine-elicited itch was suppressed by intrathecal administration of NPY and abolished by spinal ablation of GRPR+ neurons with intrathecal injection of bombesin-saporin, whereas intrathecal GRP-induced itch response remained intact in mice lacking Oprm1-Vgat. Intrathecal bombesin-saporin treatment reduced the number of GRPR+ neurons by 97% in the lumber spinal cord and 91% in the cervical spinal cord, without changing the number of Oprm1+ neurons. Additionally, chronic itch from DNFB-induced allergic contact dermatitis was decreased by Oprm1-Vgat deletion. Finally, naloxone, but not peripherally restricted naloxone methiodide, inhibited chronic itch in the DNFB model and the CTCL model, indicating a contribution of central MOR signalling to chronic itch. Our findings demonstrate that intrathecal morphine elicits itch via acting on MOR on spinal inhibitory interneurons, leading to disinhibition of the spinal itch circuit. Our data also provide mechanistic insights into the current treatment of chronic itch with opioid receptor antagonist such as naloxone.

Endometrial cancer (EC) stem cells (ECSCs) are pivotal in the oncogenesis, metastasis, immune escape, chemoresistance, and recurrence of EC. However, the specific mechanism of stem cell maintenance in EC cells (ECCs) has not been clarified. We found that WTAP and m6A levels decreased in both EC and ECSCs, and that knocking down WTAP promoted ECCs and ECSCs properties, including proliferation, invasion, migration, cisplatin resistance, and self-renewal. The downregulation of WTAP leads to a decrease in the m6A modification of EGR1 mRNA, and it is difficult for IGF2BP3, as an m6A reader, to recognize and bind to EGR1 mRNA that has lost m6A modification, resulting in a decrease in the stability of EGR1 mRNA. A decrease in the EGR1 level led to a decrease of in the expression tumor suppressor gene PTEN, resulting in deregulation and loss of cellular homeostasis and thereby fostering EC stem cell traits. Notably, the enforced overexpression of WTAP, EGR1, and PTEN inhibited the oncogenic effects of ECCs and ECSCs in vivo, and the combined overexpression of WTAP + EGR1 and EGR1 + PTEN further diminished the tumorigenic potential of these cells. Our findings revealed that the WTAP/EGR1/PTEN pathway is important regulator of EC stem cell maintenance, chemotherapeutic resistance, and tumorigenesis, suggesting a novel and promising therapeutic avenue for treating EC.

PDCD4 (programmed cell death 4) is a tumor suppressor that plays a crucial role in multiple cellular functions, such as the control of protein synthesis and transcriptional control of some genes, the inhibition of cancer invasion and metastasis. The expression of this protein is controlled by synthesis, such as via transcription and translation, and degradation by the ubiquitin-proteasome system. The mitogens, known as tumor promotors, EGF (epidermal growth factor) and TPA (12-O-tetradecanoylphorbol-13-acetate) stimulate the degradation of PDCD4 protein. However, the whole picture of PDCD4 degradation mechanisms is still unclear, we therefore investigated the relationship between PDCD4 and autophagy. The proteasome inhibitor MG132 and the autophagy inhibitor bafilomycin A1 were found to upregulate the PDCD4 levels. PDCD4 protein levels increased synergistically in the presence of both inhibitors. Knockdown of p62/SQSTM1 (sequestosome-1), a polyubiquitin binding partner, also upregulated the PDCD4 levels. P62 and LC3 (microtubule-associated protein 1A/1B-light chain 3)-II were co-immunoprecipitated by an anti-PDCD4 antibody. Colocalization particles of PDCD4, p62 and the autophagosome marker LC3 were observed and the colocalization areas increased in the presence of autophagy and/or proteasome inhibitor(s) in Huh7 cells. In ATG (autophagy related) 5-deficient Huh7 cells in which autophagy was impaired, the PDCD4 levels were increased at the basal levels and upregulated in the presence of autophagy inhibitors. Based on the above findings, we concluded that after phosphorylation in the degron and ubiquitination, PDCD4 is degraded by both the proteasome and autophagy systems.

Background: Dyslipidemia has emerged as a significant clinical risk, with its associated complications, including atherosclerosis and ischemic cerebrovascular disease, presenting a grave threat to human well-being. Hence, it holds paramount importance to precisely predict the onset of dyslipidemia. This study aims to use ensemble technology to establish a machine learning model for the prediction of dyslipidemia.Methods: This study included three consecutive years of physical examination data of 2,479 participants, and used the physical examination data of the first two years to predict whether the participants would develop dyslipidemia in the third year. Feature selection was conducted through statistical methods and the analysis of mutual information between features. Five machine learning models, including support vector machine (SVM), logistic regression (LR), random forest (RF), K nearest neighbor (KNN) and extreme gradient boosting (XGBoost), were utilized as base learners to construct the ensemble model. Area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the model.Results: Experimental results show that the ensemble model achieves superior performance across several metrics, achieving an AUC of 0.88 ± 0.01 (P < 0.001), surpassing the base learners by margins of 0.04 to 0.20. Calibration curves and DCA exhibited good predictive performance as well. Furthermore, this study explores the minimal necessary feature set for accurate prediction, finding that just the top 12 features were required for dependable outcomes. Among them, HbA1c and CEA are key indicators for model construction.Conclusions: Our results suggest that the proposed ensemble model has good predictive performance and has the potential to become an effective tool for personal health management.