Brain metastasis (BM) is a major cause of mortality in small-cell lung cancer (SCLC) patients; however, the molecular pathway of SCLC BM remains largely unknown because of a lack of investigation. Here we screen the levels of some candidate-soluble factors in the serum of SCLC patients and find that SCLC patients with high levels of placental growth factor (PLGF) are prone to BM. Using in vitro blood-brain barrier model, we show that PLGF derived from SCLC cells triggers vascular endothelial growth factor receptor-1-Rho-extracellular regulated protein kinase 1/2 signaling axis activation, results in disassembly of tight junction in brain endothelial cells and promotes SCLC cell transendothelial migration. Furthermore, the downregulation of PLGF suppresses SCLC cell metastasis to the brain in an experimental BM model. These data suggest that PLGF is a potential signature of SCLC BM and a prospective therapeutic target for SCLC BM.

Background and purpose: Stimulation of astrocytes by the a 2 -adrenoceptor agonist dexmedetomidine, a neuroprotective drug, transactivates epidermal growth factor (EGF) receptors. The present study investigates signal pathways leading to release of an EGF receptor ligand and those activated during EGF receptor stimulation, and the response of neurons to dexmedetomidine and to astrocyte-conditioned medium. Experimental approach: Phosphorylation of ERK 1/2 was determined by western blotting and immunocytochemistry, and phosphorylation of EGF receptors by immunoprecipitation and western blotting. mRNA expression of fos family was measured by RT-PCR. Key results: Pertussis toxin (0.2 mg ml À1 ) an inhibitor of bg subunit dissociation from Ga i protein, and GF 109203X (500 nM), a protein kinase C inhibitor, abolished ERK 1/2 phosphorylation. PP1 (10 mM), inhibiting Src kinase and GM 6001 (10 mM), an inhibitor of Zn-dependent metalloproteinase, abolished ERK 1/2 phosphorylation by dexmedetomidine (50 nM), but not that by EGF (10 ng ml À1 ), showing Src kinase and metalloproteinase activation during the first stage only; AG 1478 (1 mM), an inhibitor of the EGF receptor tyrosine kinase, abolished ERK 1/2 phosphorylation. Dexmedetomidine-induced EGF receptor phosphorylation was prevented by AG 1478, GM 6001, PP1 and GF 109203X and its induction of cfos and fosB by AG 1478 and by U0126 (10 mM), an inhibitor of ERK phosphorylation, indicating downstream effects of ERK 1/2 phosphorylation. EGF and conditioned medium from dexmedetomidine-treated astrocytes, but not dexmedetomidine itself, induced ERK phosphorylation in primary cultures of cerebellar neurons. Conclusions and implications: Dexmedetomidine-induced transactivation pathways were delineated. Its paracrine effect on neurons may account for its neuroprotective effects.

Mercury (Hg) represents a ubiquitous environmental heavy metal that could lead to severe toxic effects in a variety of organs usually at a low level. The present study focused on the liver oxidative stress, one of the most important roles playing in Hg hepatotoxicity, by evaluation of different concentrations of mercuric chloride (HgCl2) administration. Moreover, the protective potential of curcumin against Hg hepatotoxic effects was also investigated. Eighty-four rats were randomly divided into six groups for a three-days experiment: control, dimethyl sulfoxide control, HgCl2 treatment (0.6, 1.2, and 2.4 mg kg−1 day−1), and curcumin pretreatment (100 mg kg−1 day−1) groups. Exposure of HgCl2 resulted in acute dose-dependent hepatotoxic effects. Administration of 2.4 mg kg−1 HgCl2 significantly elevated total Hg, nonprotein sulfhydryl, reactive oxygen species formation, malondialdehyde, apoptosis levels, serum lactate dehydrogenase, and alanine transaminase activities, with an impairment of superoxide dismutase and glutathione peroxidase in the liver. Moreover, HgCl2 treatment activated nuclear factor-E2-related factor 2-antioxidant response element (Nrf2-ARE) signaling pathway in further investigation, with a significant upregulation of Nrf2, heme oxygenase-1, and γ-glutamylcysteine synthetase heavy subunit expression, relative to control. Pretreatment with curcumin obviously prevented HgCl2-induced liver oxidative stress, which may be due to its free radical scavenging or Nrf2-ARE pathway-inducing properties. Taking together these data suggest that curcumin counteracts HgCl2 hepatotoxicity through antagonizing liver oxidative stress.

Background Early prediction of intravenous corticosteroid (IVCS) resistance in Acute severe ulcerative colitis (ASUC) patients could reduce costs and delay in rescue therapy. However, most prediction models for ASUC were at high risk of bias with a lack of external validation. This study aims to construct and validate a model that accurately predicts IVCS resistance using various statistical methods. Methods A retrospective cohort of patients who were diagnosed with ASUC and had undergone IVCS treatment between March 2012 to January 2020 was established. Predictors evaluated included age, gender, race, medications before admission, infections, and laboratory data at baseline and during IVCS treatment, and endoscopic outcomes relied on blinded centralized endoscopy reading. The LASSO regression was used in feature selection for multivariate logistic regression model. Models based on machine learning methods (decision tree and random forest [RF]) were also constructed. Internal validity was confirmed and model performances were compared. External validation was conducted using data using an independent cohort from a tertiary referral centre. Results A total of 129 patients were included in the derivation cohort. During index hospitalization, 102 (79.1%) responded to IVCS, and 27 (20.9%) failed; 16 patients underwent colectomy, 6 received cyclosporin, and 5 succeeded with IFX as rescue therapy. Ulcerative Colitis Endoscopic Index of Severity (UCEIS; odds ratio [OR] 5.39, 95% confidence interval [CI] 2.52–14.0, p<0.001) and C-reactive protein (CRP) level on the third day (OR 1.05, 95% CI 1.03–1.08, p<0.001) were selected by LASSO regression and identified as the only two independent predictors of IVCS resistance in logistic regression. The decision tree model identified a UCEIS higher than 6.5 points and CRP level at day 3 higher than 33.57 mg/dL as the proxy for IVCS resistance. UCEIS and CRP level at day 3 were also the most important predictors in the RF model. Areas under the curve receiver operating characteristic (AUC) of logistic model, decision tree model, and RF model were 0.64 (95% CI 0.49–0.80), 0.81 (95% CI 0.71–0.90), and 0.88 (95% CI 0.82–0.95), respectively. A validation cohort of 65 ASUC patients were established, and the AUC of the models in external validation were 0.57 (95% CI 0.45–0.70), 0.70 (95% CI 0.61–0.80), and 0.71 (95% CI 0.48–0.94), respectively. Conclusion In patients with ASUC, UCEIS and CRP level at day 3 of IVCS treatment appeared to allow the prompt prediction of likely IVCS nonresponders. Machine learning-based models outperformed the traditional statistical model in the prediction. The models may aid therapeutic decision-making in ASUC patients.