instruction:
In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.
question:
Context: Progress in the management of patients with medically intractable epilepsy is impeded because we do not fully understand why pharmacoresistance happens and how it can be predicted. The presence of multiple seizures prior to medical treatment has been suggested as a potential predictor of poor outcome. In the present study, we used an animal model of temporal lobe epilepsy to investigate whether pharmacoresistant rats differ in seizure frequency from pharmacoresponsive animals.', 'Epilepsy with spontaneous recurrent seizures (SRS) was induced by status epilepticus. Frequency of SRS was determined by video/EEG (electroencephalography) monitoring in a total of 33 epileptic rats before onset of treatment with phenobarbital (PB).', 'Thirteen (39%) rats did not respond to treatment with PB. Before treatment with PB, average seizure frequency in PB nonresponders was significantly higher than seizure frequency in responders, which, however, was due to six nonresponders that exhibited > 3 seizures per day. Such high seizure frequency was not observed in responders, demonstrating that high seizure frequency predicts pharmacoresistance in this model, but does not occur in all nonresponders.\Question: Is high seizure frequency prior to antiepileptic treatment a predictor of pharmacoresistant epilepsy in a rat model of temporal lobe epilepsy?
answer:
The data from this study are in line with clinical experience that the frequency of seizures in the early phase of epilepsy is a dominant risk factor that predicts refractoriness. However, resistance to treatment also occurred in rats that did not differ in seizure frequency from responders, indicating that disease severity alone is not sufficient to explain antiepileptic drug (AED) resistance. These data provide further evidence that epilepsy models are useful in the search for predictors and mechanisms of pharmacoresistance.


question:
Context: Chronic inflammation is hypothesized to influence prostate cancer development, although a definitive link has not been established.', 'Prostate cancer cases (N = 191) detected on a for-cause (clinically indicated) or end-of-study (protocol directed) biopsy, and frequency-matched controls (N = 209), defined as negative for cancer on an end-of-study biopsy, were sampled from the placebo arm of the Prostate Cancer Prevention Trial. Inflammation prevalence and extent in benign areas of biopsy cores were visually assessed using digital images of hematoxylin and eosin-stained sections. Logistic regression was used to estimate associations.', 'Of note, 86.2% of cases and 78.2% of controls had at least one biopsy core (of three assessed) with inflammation in benign areas, most of which was chronic. Men who had at least one biopsy core with inflammation had 1.78 [95% confidence interval (CI), 1.04-3.06] times the odds of prostate cancer compared with men who had zero cores with inflammation. The association was stronger for high-grade disease (Gleason sum 7-10, N = 94; OR, 2.24; 95% CI, 1.06-4.71). These patterns were present when restricting to cases and controls in whom intraprostatic inflammation was the least likely to have influenced biopsy recommendation because their prostate-specific antigen (PSA) was low (<2 ng/mL at biopsy).\Question: Is chronic inflammation in benign prostate tissue associated with high-grade prostate cancer in the placebo arm of the prostate cancer prevention trial?
answer:
Inflammation, most of which was chronic, was common in benign prostate tissue, and was positively associated with prostate cancer, especially high grade. The association did not seem to be due to detection bias.


question:
Context: Previously, we found an 11-gene signature could predict pelvic lymph node metastasis (PLNM), and WNT2 is one of the key genes in the signature. This study explored the expression and underlying mechanism of WNT2 in PLNM of cervical cancer.', 'WNT2 expression level in cervical cancer was detected using western blotting, quantitative PCR, and immunohistochemistry. Two WNT2-specific small interfering RNAs (siRNAs) were used to explore the effects of WNT2 on invasive and metastatic ability of cancer cells, and to reveal the possible mechanism of WNT2 affecting epithelial-mesenchymal transition (EMT). The correlation between WNT2 expression and PLNM was further investigated in clinical cervical specimens.', 'Both WNT2 mRNA and protein expression was upregulated in cervical cancer. High WNT2 expression was significantly associated with tumor size, lymphovascular space involvement, positive parametrium, and most importantly, PLNM. PLNM and WNT2 expression were independent prognostic factors for overall survival and disease-free survival. WNT2 knockdown inhibited SiHa cell motility and invasion and reversed EMT by inhibiting the WNT2/β-catenin pathway. WNT2 overexpression in cervical cancer was associated with β-catenin activation and induction of EMT, which further contributed to metastasis in cervical cancer.\Question: Does wNT2 promote Cervical Carcinoma Metastasis and Induction of Epithelial-Mesenchymal Transition?
answer:

WNT2 might be a novel predictor of PLNM and a promising prognostic indicator in cervical cancer.