Yiguanjian cataplasm attenuates opioid dependence in a mouse model of naloxone-induced opioid withdrawal syndrome

AbstractObjectiveTo investigate the effect of Yiguanjian (YGJ) cataplasm on the development of opioid dependence in a mouse model of naloxone-induced opioid withdrawal syndrome.MethodsOne hundred Swiss albino mice, of equal male to female ratio, were randomly and equally divided into 10 groups. A portion (3 cm2) of the backside hair of the mice was removed 1 day prior to the experiment. Morphine (5 mg/kg) was intraperitoneally administered twice daily for 5 days. YGJ cataplasm was prepared and pasted on the bare region of the mice immediately before morphine administration on day 3 and subsequently removed at the end day 5. On day 6, naloxone (8 mg/kg) was intraperitoneally injected to precipitate opioid withdrawal syndrome. Behavioral observation was performed in two 30-min phases immediately after naloxone injection.ResultsThe YGJ cataplasm significantly and dose-dependently attenuated morphine-naloxone-induced experimental opioid withdrawal, in terms of withdrawal severity score and the frequencies of jumping, rearing, forepaw licking, and circling behaviors. However, YGJ cataplasm treatment did not alter the acute analgesic effect of morphine.ConclusionYGJ cataplasm could attenuate opioid dependence and its associated withdrawal symptoms. Therefore, YGJ cataplasm could serve as a potential therapy for opioid addiction in the future

Development and validation of a predictive nomogram for lower extremity deep vein thrombosis dislodgement in orthopedic patients

ObjectiveTo analyze the risk factors of lower extremity deep venous thrombosis (DVT) detachment in orthopedic patients, and to establish a risk nomogram prediction model.MethodsThe clinical data of 334 patients with orthopedic DVT admitted to the Third Hospital of Hebei Medical University from January 2020 to July 2021 were retrospectively analyzed. General statistics included gender, age, BMI, thrombus detachment, inferior vena cava filter window type, filter implantation time, medical history, trauma history, operation, use of tourniquet, thrombectomy, anesthesia mode, anesthesia grade, operative position, blood loss during operation, blood transfusion, immobilization, use of anticoagulants, thrombus side, thrombus range, D-dimer content before filter implantation and during removal of inferior vena cava filter. Logistic regression was used to perform univariate and multivariate analysis on the possible factors of thrombosis detachment, screen out independent risk factors, establish a risk nomogram prediction model by variables, and internally verify the predictability and accuracy of the model.ResultsBinary logistic regression analysis showed that Short time window filter (OR = 5.401, 95% CI = 2.338–12.478), lower extremity operation (OR = 3.565, 95% CI = 1.553–8.184), use of tourniquet (OR = 3.871, 95% CI = 1.733–8.651), non-strict immobilization (OR = 3.207, 95% CI = 1.387–7.413), non-standardized anticoagulation (OR = 4.406, 95% CI = 1.868–10.390), distal deep vein thrombosis (OR = 2.212, 95% CI = 1.047–4.671) were independent risk factors for lower extremity DVT detachment in orthopedic patients (P < 0.05). Based on these six factors, a prediction model for the risk of lower extremity DVT detachment in orthopedic patients was established, and the risk prediction ability of the model was verified. The C-index of the nomogram model was 0.870 (95% CI: 0.822–0.919). The results indicate that the risk nomogram model has good accuracy in predicting the loss of deep venous thrombosis in orthopedic patients.ConclusionThe nomogram risk prediction model based on six clinical factors, including filter window type, operation condition, tourniquet use, braking condition, anticoagulation condition, and thrombosis range, has good predictive performance

MicroRNA-140 mediates RB tumor suppressor function to control stem cell-like activity through interleukin-6

We established an in vitro cell culture system to determine novel activities of the retinoblastoma (Rb) protein during tumor progression. Rb depletion in p53-null mouse-derived soft tissue sarcoma cells induced a spherogenic phenotype. Cells retrieved from Rb-depleted spheres exhibited slower proliferation and less efficient BrdU incorporation, however, much higher spherogenic activity and aggressive behavior. We discovered six miRNAs, including mmu-miR-18a, -25, -29b, -140, -337, and -1839, whose expression levels correlated tightly with the Rb status and spherogenic activity. Among these, mmu-miR-140 appeared to be positively controlled by Rb and to antagonize the effect of Rb depletion on spherogenesis and tumorigenesis. Furthermore, among genes potentially targeted by mmu-miR-140, Il-6 was upregulated by Rb depletion and downregulated by mmu-mir-140 overexpression. Altogether, we demonstrate the possibility that mmu-mir-140 mediates the Rb function to downregulate Il-6 by targeting its 3\u27-untranslated region. Finally, we detected the same relationship among RB, hsa-miR-140 and IL-6 in a human breast cancer cell line MCF-7. Because IL-6 is a critical modulator of malignant features of cancer cells and the RB pathway is impaired in the majority of cancers, hsa-miR-140 might be a promising therapeutic tool that disrupts linkage between tumor suppressor inactivation and pro-inflammatory cytokine response.Supplementary Table1 and Supplementary Table2: We offer the table data with an Excel fil

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

「がん抑制遺伝子RB1の不活性化はCCL2を介してがんを促進する微小環境を構築する」

第18回　高安賞最優秀論文賞受賞　Cancer Res. 2019 Aug 1; 79 (15): 3903-3915. 令和元年8月掲載 Fengkai Li, Shunsuke Kitajima, Susumu Kohno, Akiyo Yoshida, Shoichiro Tange, Soichiro Sasaki, Nobuhiro Okada, Yuuki Nishimoto, Hayato Muranaka, Naoko Nagatani, Misa Suzuki, Sayuri Masuda, Tran C. Thai, Takumi Nishiuchi, Tomoaki Tanaka, David A. Barbie, Naofumi Mukaida, and Chiaki Takahash

Cancer Stem Cells and Neovascularization

Cancer stem cells (CSCs) refer to a subpopulation of cancer cells responsible for tumorigenesis, metastasis, and drug resistance. Increasing evidence suggests that CSC-associated tumor neovascularization partially contributes to the failure of cancer treatment. In this review, we discuss the roles of CSCs on tumor-associated angiogenesis via trans-differentiation or forming the capillary-like vasculogenic mimicry, as well as the roles of CSCs on facilitating endothelial cell-involved angiogenesis to support tumor progression and metastasis. Furthermore, we discuss the underlying regulation mechanisms, including the intrinsic signals of CSCs and the extrinsic signals such as cytokines from the tumor microenvironment. Further research is required to identify and verify some novel targets to develop efficient therapeutic approaches for more efficient cancer treatment through interfering CSC-mediated neovascularization

Tumor Milieu Controlled by RB Tumor Suppressor

The RB gene is one of the most frequently mutated genes in human cancers. Canonically, RB exerts its tumor suppressive activity through the regulation of the G1/S transition during cell cycle progression by modulating the activity of E2F transcription factors. However, aberration of the RB gene is most commonly detected in tumors when they gain more aggressive phenotypes, including metastatic activity or drug resistance, rather than accelerated proliferation. This implicates RB controls’ malignant progression to a considerable extent in a cell cycle-independent manner. In this review, we highlight the multifaceted functions of the RB protein in controlling tumor lineage plasticity, metabolism, and the tumor microenvironment (TME), with a focus on the mechanism whereby RB controls the TME. In brief, RB inactivation in several types of cancer cells enhances production of pro-inflammatory cytokines, including CCL2, through upregulation of mitochondrial reactive oxygen species (ROS) production. These factors not only accelerate the growth of cancer cells in a cell-autonomous manner, but also stimulate non-malignant cells in the TME to generate a pro-tumorigenic niche in a non-cell-autonomous manner. Here, we discuss the biological and pathological significance of the non-cell-autonomous functions of RB and attempt to predict their potential clinical relevance to cancer immunotherapy