In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

[EX Q]: Paragraph: Quantitative analysis and chromatographic fingerprinting for the quality evaluation of a Chinese herb Scutellaria baicalensis Georgi using capillary electrophoresis (CE) technique was developed. The separation was performed with a 50.0 cm (42.0 cm to the detector window) × 75 m i.d. fused-silica capillary, and the CE fingerprint condition was optimized using the combination of central composite design and multivariate analysis. The optimized buffer system containing 15 mM borate, 40 mM phosphate, 15 mM SDS, 15% (v/v) acetonitrile and 7.5% (v/v) 2-propanol was employed for the method development, and the baseline separation was achieved within 15 min. The determination of the major active components (Baicalin, Baicalein and Wogonin) was carried out using the optimized CE condition. Good linear relationships were provided over the investigated concentration ranges (the values of R 2 : 0.9997 for Baicalin, 0.9992 for Baicalein, and 0.9983 for Wogonin, respectively). The average recoveries of these target components ranged between 96.1-105.6%, 98.6-105.2%, and 96.3-105.0%, respectively. CE fingerprints combined with the quantitative analysis can be used for the quality evaluation of S. baicalensis. 
 Title: Quantitative analysis and chromatographic fingerprinting for the quality evaluation of Scutellaria baicalensis Georgi using capillary electrophoresis
[EX A]: True

[EX Q]: Paragraph: Gram-negative pathogen-induced nosocomial infections and resistance are a most serious menace to global public health. Qingfei Xiaoyan Wan (QF), a traditional Chinese medicine (TCM) formula, has been used clinically in China for the treatment of upper respiratory tract infections, acute or chronic bronchitis and pulmonary infection. In this study, the effects of QF on Pseudomonas aeruginosainduced acute pneumonia in mice were evaluated. The mechanisms by which four typical antiinflammatory ingredients from QF, arctigenin (ATG), cholic acid (CLA), chlorogenic acid (CGA) and sinapic acid (SPA), regulate anti-inflammatory signaling pathways and related targets were investigated using molecular biology and molecular docking techniques. The results showed that pretreatment with QF significantly inhibits the release of cytokines (TNF-α and IL-6) and chemokines (IL-8 and RANTES), reduces leukocytes recruitment into inflamed tissues and ameliorates pulmonary edema and necrosis. In ;6(3):212-221 addition, ATG was identified as the primary anti-inflammatory agent with action on the PI3K/AKT and Ras/MAPK pathways. CLA and CGA enhanced the actions of ATG and exhibited synergistic NF-κB inactivation effects possibly via the Ras/MAPK signaling pathway. Moreover, CLA is speculated to target FGFR and MEK firstly. Overall, QF regulated the PI3K/AKT and Ras/MAPK pathways to inhibit pathogenic bacterial infections effectively. 
 Title: Qingfei Xiaoyan Wan, a traditional Chinese medicine formula, ameliorates Pseudomonas aeruginosa-induced acute lung inflammation by regulation of PI3K/AKT and Ras/MAPK pathways-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
[EX A]: False

[EX Q]: Paragraph: Background: The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud -based open -sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. Conclusions: By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available. 
 Title: Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
[EX A]:
True