Assessment of preoperative pressure pain tolerance is significantly correlated with the level of postoperative pain. Pain tolerance assessment after fentanyl was administered and fentanyl sensitivity predicted the dose of analgesics used in the first 24 h after surgery. The algometer is thus a simple, useful tool for predicting postoperative pain and analgesic consumption.

ChIA-PET2 is a versatile and flexible pipeline for analyzing different types of ChIA-PET data from raw sequencing reads to chromatin loops. ChIA-PET2 integrates all steps required for ChIA-PET data analysis, including linker trimming, read alignment, duplicate removal, peak calling and chromatin loop calling. It supports different kinds of ChIA-PET data generated from different ChIA-PET protocols and also provides quality controls for different steps of ChIA-PET analysis. In addition, ChIA-PET2 can use phased genotype data to call allele-specific chromatin interactions. We applied ChIA-PET2 to different ChIA-PET datasets, demonstrating its significantly improved performance as well as its ability to easily process ChIA-PET raw data. ChIA-PET2 is available at https://github.com/GuipengLi/ChIA-PET2.

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Background Eosinophilic inflammation is a major phenotype associated with poorly controlled disease in nasal polyp patients. The difference between systemic and local eosinophilia in relation to disease control is poorly understood. Objective To explore whether blood and polyp tissue eosinophil numbers are independent risk factors for poor disease control in patients with nasal polyp. Methods By using the electronic medical records database and manual evaluation, 183 nasal polyp patients who had undergone endoscopic sinus surgery at least one year prior to the study with complete data of tissue specimens, baseline blood routine test, nasal endoscopy and sinus computed tomography, were identified and recruited to assess disease control based on the criteria of a European position paper on rhinosinusitis and nasal polyps 2012 (EPOS 2012). Multiple logistic regression model was used to determine the association between blood and tissue eosinophil numbers and risk of poor disease control by adjusting for demographics and comorbidities. Results We broke down the cohort into 4 groups according to blood (0.3 ​× ​10 9 /L) and tissue (10%) eosinophils. The patients without eosinophilic inflammation represented the largest group (41.5%). The group with concordant blood and tissue eosinophilia represented the second largest (31.2%), and the patients with isolated tissue (15.3%) or blood (12.0%) eosinophilia were relatively rare. Multiple logistic regression models found blood eosinophil count and tissue eosinophil percentage were independently associated with increased risk for poor disease control after adjustments for covariates related to poor treatment outcome. Furthermore, subjects with concordant blood and tissue eosinophilia had a higher risk for poor disease control than those with isolated blood or tissue eosinophilia. Conclusion Concordant blood and tissue eosinophilia relates to a higher likelihood of poor disease control than isolated blood or tissue eosinophilia after adjustment of potential confounders in nasal polyp patients.