Combining formal methods and Bayesian approach for inferring discrete-state stochastic models from steady-state data.

Stochastic population models are widely used to model phenomena in different areas such as cyber-physical systems, chemical kinetics, collective animal behaviour, and beyond. Quantitative analysis of stochastic population models easily becomes challenging due to the combinatorial number of possible states of the population. Moreover, while the modeller easily hypothesises the mechanistic aspects of the model, the quantitative parameters associated to these mechanistic transitions are difficult or impossible to measure directly. In this paper, we investigate how formal verification methods can aid parameter inference for population discrete-time Markov chains in a scenario where only a limited sample of population-level data measurements-sample distributions among terminal states-are available. We first discuss the parameter identifiability and uncertainty quantification in this setup, as well as how the existing techniques of formal parameter synthesis and Bayesian inference apply. Then, we propose and implement four different methods, three of which incorporate formal parameter synthesis as a pre-computation step. We empirically evaluate the performance of the proposed methods over four representative case studies. We find that our proposed methods incorporating formal parameter synthesis as a pre-computation step allow us to significantly enhance the accuracy, precision, and scalability of inference. Specifically, in the case of unidentifiable parameters, we accurately capture the subspace of parameters which is data-compliant at a desired confidence level.

Network Pharmacology and Molecular Docking Study on the Multi-Target Mechanisms of Aloe vera for Non-Alcoholic Steatohepatitis Treatment.

Non-alcoholic steatohepatitis (NASH) is a leading cause of chronic liver disease with limited treatment options. The widely distributed plant Aloe vera has shown protective effects against NASH in animals, yet the precise mechanism remains unknown. In this study, we investigated the potential mechanisms underlying the anti-NASH effects of Aloe vera using a network pharmacology and molecular docking approach. By searching online databases and analyzing the Gene Expression Omnibus dataset, we obtained 260 Aloe vera-NASH common targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the common targets were strongly associated with the key pathological processes implicated in NASH, including lipid and glucose metabolism, inflammation, apoptosis, oxidative stress, and liver fibrosis. Four core proteins, AKT serine/threonine kinase 1 (AKT1), tumor necrosis factor alpha (TNFα), transcription factor c-Jun, and tumor suppressor protein p53, were identified from compound-target-pathway and protein-protein interaction networks. Molecular docking analysis verified that the active ingredients of Aloe vera were able to interact with the core proteins, especially AKT1 and TNFα. The results demonstrate the multi-compound, multi-target, and multi-pathway mechanisms of Aloe vera against NASH. Our study has shown the scientific basis for further experiments in terms of the mechanism to develop Aloe vera-based natural products as complementary treatments for NASH. Furthermore, it identifies novel drug candidates based on the structures of Aloe vera's active compounds.

Loss of EMP2 Inhibits Melanogenesis of MNT1 Melanoma Cells via Regulation of TRP-2

Melanogenesis is the production of melanin from tyrosine by a series of enzyme-catalyzed reactions, in which tyrosinase and DOPA oxidase play key roles. The melanin content in the skin determines skin pigmentation. Abnormalities in skin pigmentation lead to various skin pigmentation disorders. Recent research has shown that the expression of EMP2 is much lower in melanoma than in normal melanocytes, but its role in melanogenesis has not yet been elucidated. Therefore, we investigated the role of EMP2 in the melanogenesis of MNT1 human melanoma cells. We examined TRP-1, TRP-2, and TYR expression levels during melanogenesis in MNT1 melanoma cells by gene silencing of EMP2. Western blot and RT-PCR results confirmed that the expression levels of TYR and TRP-2 were decreased when EMP2 expression was knocked down by EMP2 siRNA in MNT1 cells, and these changes were reversed when EMP2 was overexpressed. We verified the EMP2 gene was knocked out of the cell line (EMP2 CRISPR/Cas9) by using a CRISPR/Cas9 system and found that the expression levels of TRP-2 and TYR were significantly lower in the EMP2 CRISPR/Cas9 cell lines. Loss of EMP2 also reduced migration and invasion of MNT1 melanoma cells. In addition, the melanosome transfer from the melanocytes to keratinocytes in the EMP2 KO cells cocultured with keratinocytes was reduced compared to the cells in the control coculture group. In conclusion, these results suggest that EMP2 is involved in melanogenesis via the regulation of TRP-2 expression.

PRR16/Largen Induces Epithelial-Mesenchymal Transition through the Interaction with ABI2 Leading to the Activation of ABL1 Kinase

Advanced or metastatic breast cancer affects multiple organs and is a leading cause of cancer-related death. Cancer metastasis is associated with epithelial-mesenchymal metastasis (EMT). However, the specific signals that induce and regulate EMT in carcinoma cells remain unclear. PRR16/Largen is a cell size regulator that is independent of mTOR and Hippo signalling pathways. However, little is known about the role PRR16 plays in the EMT process. We found that the expression of PRR16 was increased in mesenchymal breast cancer cell lines. PRR16 overexpression induced EMT in MCF7 breast cancer cells and enhances migration and invasion. To determine how PRR16 induces EMT, the binding proteins for PRR16 were screened, revealing that PRR16 binds to Abl interactor 2 (ABI2). We then investigated whether ABI2 is involved in EMT. Gene silencing of ABI2 induces EMT, leading to enhanced migration and invasion. ABI2 is a gene that codes for a protein that interacts with ABL proto-oncogene 1 (ABL1) kinase. Therefore, we investigated whether the change in ABI2 expression affected the activation of ABL1 kinase. The knockdown of ABI2 and PRR16 overexpression increased the phosphorylation of Y412 in ABL1 kinase. Our results suggest that PRR16 may be involved in EMT by binding to ABI2 and interfering with its inhibition of ABL1 kinase. This indicates that ABL1 kinase inhibitors may be potential therapeutic agents for the treatment of PRR16-related breast cancer.

Gonadotropin-releasing hormone agonist trigger in oocyte donors co-treated with a gonadotropin-releasing hormone antagonist: a dose-finding study.

OBJECTIVE: To determine the optimal GnRH agonist dose for triggering of oocyte maturation in oocyte donors. DESIGN: Single-center, randomized, parallel, investigator-blinded trial. SETTING: IVFMD, My Duc Hospital, Ho Chi Minh City, Vietnam. PATIENT(S): One hundred sixty-five oocyte donors (aged 18-35 years, body mass index [BMI] <28 kg/m(2), antimüllerian hormone level >1.25 ng/mL, and antral follicle count ≥6). INTERVENTION(S): Ovulation trigger with 0.2, 0.3, or 0.4 mg triptorelin in a GnRH antagonist cycle. MAIN OUTCOME MEASURE(S): The primary end point was number of metaphase II oocytes. Secondary end points were fertilization and cleavage rates, number of embryos and top-quality embryos, steroid levels, ovarian volume, and ongoing pregnancy rate (PR) in recipients. RESULT(S): There were no significant differences between the triptorelin 0.2, 0.3, and 0.4 mg trigger groups with respect to number of metaphase II oocytes (16.0 ± 8.5, 15.9 ± 7.8, and 14.7 ± 8.4, respectively), embryos (13.2 ± 7.8, 11.7 ± 6.9, 11.8 ± 7.0), and number of top-quality embryos (3.8 ± 2.9, 3.6 ± 3.0, 4.1 ± 3.0). Luteinizing hormone levels at 24 hours and 36 hours after trigger was significantly higher with triptorelin 0.4 mg versus 0.2 mg and 0.3 mg (9.8 ± 7.1 IU/L vs. 7.3 ± 4.1 IU/L and 7.2 ± 3.7 IU/L, respectively; 4.6 ± 3.2 IU/L vs. 3.2 ± 2.3 IU/L and 3.3 ± 2.1 IU/L, respectively. Progesterone level at oocyte pick-up +6 days was significantly higher in the 0.4-mg group (2.2 ± 3.7 ng/ml) versus 0.2 mg (1.1 ± 1.0 ng/ml) and 0.3 mg (1.2 ± 1.6 ng/ml). One patient developed early-onset severe ovarian hyperstimulation syndrome (OHSS). CONCLUSION(S): No significant differences between triptorelin doses of 0.2, 0.3, and 0.4 mg used for ovulation trigger in oocyte donors were seen with regard to the number of mature oocytes and top-quality embryos. CLINICAL TRIAL REGISTRATION NUMBER: NCT02208986.

Impact of GnRH agonist triggering and intensive luteal steroid support on live-birth rates and ovarian hyperstimulation syndrome: a retrospective cohort study.

BACKGROUND: Conventional luteal support packages are inadequate to facilitate a fresh transfer after GnRH agonist (GnRHa) trigger in patients at high risk of developing ovarian hyperstimulation syndrome (OHSS). By providing intensive luteal-phase support with oestradiol and progesterone satisfactory implantation rates can be sustained. The objective of this study was to assess the live-birth rate and incidence of OHSS after GnRHa trigger and intensive luteal steroid support compared to traditional hCG trigger and conventional luteal support in OHSS high risk Asian patients. METHODS: We conducted a retrospective cohort study of 363 women exposed to GnRHa triggering with intensive luteal support compared with 257 women exposed to conventional hCG triggering. Women at risk of OHSS were defined by ovarian response ≥15 follicles ≥12 mm on the day of the trigger. RESULTS: Live-birth rates were similar in both groups GnRHa vs hCG; 29.8% vs 29.2% (p = 0.69). One late onset severe OHSS case was observed in the GnRHa trigger group (0.3%) compared to 18 cases (7%) after hCG trigger. CONCLUSIONS: GnRHa trigger combined with intensive luteal steroid support in this group of OHSS high risk Asian patients can facilitate fresh embryo transfer, however, in contrast to previous reports the occurrence of late onset OHSS was not completely eliminated.