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".

Paragraph: Only a month after the outbreak of pneumonia caused by 2019-nCoV, more than forty-thousand people were infected. This put enormous pressure on the Chinese government, medical healthcare provider, and the general public, but also made the international community deeply nervous. On the 25th day after the outbreak, the Chinese government implemented strict traffic restrictions on the area where the 2019-nCoV had originateddHubei province, whose capital city is Wuhan. Ten days later, the rate of increase of cases in Hubei showed a significant difference (p ¼ 0.0001) compared with the total rate of increase in other provinces of China. These preliminary data suggest the effectiveness of a traffic restriction policy for this pandemic thus far. At the same time, solid financial support and improved research ability, along with network communication technology, also greatly facilitated the application of epidemic prevention measures. These measures were motivated by the need to provide effective treatment of patients, and involved consultation with three major groups in policy formulationdpublic health experts, the government, and the general public. It was also aided by media and information technology, as well as international cooperation. This experience will provide China and other countries with valuable lessons for quickly coordinating and coping with future public health emergencies. 
 Title: Lessons learned from the 2019-nCoV epidemic on prevention of future infectious diseases
False

Paragraph: Background: Although the mini-clinical evaluation (mini-CEX) exercise has been adapted to a broad range of clinical situations, limited studies of the mini-CEX for postgraduate residency training in emergency medicine (EM) have been documented. Aim: The purpose of this study is to analyze the results of implementing the mini-CEX into the one-month postgraduate residency training in EM. Materials and methods: This study is a retrospective review of mini-CEXs completed by ED faculty members from August 2009 to December 2010. All PGY-1 residents enrolled in this study rotated through the one-month EM training. Each PGY-1 resident received one week of trauma training and three weeks of non-trauma training. The clinical competencies of each PGY-1 resident were evaluated with mini-CEXs, rated by a trauma surgeon and three emergency physicians (EPs). We analyzed the validity of weekly mini-CEX and the impact of seniority and specialty training of ED faculties on observation time, feedback time and rating scores. Results: Fifty-seven ED faculty members (42 EPs and 15 trauma surgeons) evaluated 183 PGY-1 residents during the 17 months of EM training. ED faculties with different specialty training provided similar assessment processes. Most competencies were rated significantly higher by trauma surgeons than by EPs. On the computerized mini-CEX rating, no data was missed and junior EPs rated all competencies significantly higher. The evaluators and PGY-1 residents were generally satisfied with the computerized format. As compared to the first assessment, only some competencies of PGY-1 residents were rated significantly higher in subsequent evaluations. Conclusion: The seniority and specialty training of ED faculty affected the mini-CEX ratings. The computer-based mini-CEX facilitated complete data gathering but showed differences for ED faculty with different levels of seniority. Further studies of the reliability and validity of the mini-CEX for PGY-1 EM training are needed. 
 Title: Implementation of the mini-clinical evaluation exercise in postgraduate Year 1 residency training in emergency medicine: Clinical experience at Chang Gung Memorial Hospital ScienceDirect
False

Paragraph: Neuromodulation plays a critical role in brain function in both health and disease. New optical tools, and their validation in biological tissues, are needed that can image neuromodulation with high spatial and temporal resolution, which will add an important new dimension of information to neuroscience research. Here, we demonstrate the use of a catecholamine nanosensor with fluorescent emission in the 1000-1300 nm near-infrared window to measure dopamine transmission in ex vivo brain slices. These near-infrared catecholamine nanosensors (nIRCats) represent a broader class of nanosensors that can be synthesized from non-covalent conjugation of single wall carbon nanotubes (SWNT) with single strand oligonucleotides. We show that nIRCats can be used to detect catecholamine efflux in brain tissue driven by both electrical stimulation or optogenetic stimulation. Spatial analysis of electrically-evoked signals revealed dynamic regions of interest approximately 2 microns in size in which transients scaled with simulation intensity. Optogenetic stimulation of dopaminergic terminals produced similar transients, whereas optogenetic stimulation of glutamatergic terminals showed no effect on nIRCat signal. Bath application of nomifensine prolonged nIRCat fluorescence signal, consistent with reuptake blockade of dopamine. We further show that the chemically synthetic molecular recognition elements of nIRCats permit measurement of dopamine dynamics in the presence of dopamine receptor agonists and antagonists. These nIRCat nanosensors may be advantageous for future use because i) they do not require virus delivery, gene delivery, or protein expression, ii) their near-infrared fluorescence facilitates imaging in optically scattering brain tissue and is compatible for use in conjunction with other optical neuroscience tool sets, iii) the broad availability of unique near-infrared colors have the potential for simultaneous detection of multiple neurochemical signals, and iv) they are compatible with pharmacology. 
 Title: Imaging Striatal Dopamine Release Using a Non-Genetically Encoded Near-Infrared Fluorescent Catecholamine Nanosensor

True