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".

Input: Consider Input: Paragraph: Sprague-Dawley rats were injected intraperitoneally with a suspension of Trypanosoma brucei brucei. An early induction of major histocompatibility complex (MHC) class I antigens as well as an infiltration of macrophage-like cells and cytotoxic T-cells was detected with immunohistochemical techniques in circumventricular organs, such as the median eminence, neurohypophysis, subfornical organ, pineal gland and area postrema. These areas, which lack a blood-brain barrier, correspond to those showing early invasion of trypanosomes. In addition, there was a marked induction of MHC class I in neurons in two hypothalamic nuclei, the paraventricular and supraoptic nuclei. Neurons in these two nuclei are located behind the blood-brain barrier, but project to the neurohypophysis and to the median eminence, thereby exposing their axon terminals to factors circulating in the blood or released locally from invading trypanosomes or from macrophages or cytotoxic T-cells. It is suggested that the alteration in the nerve cell bodies in the hypothalamic nuclei is caused by retrograde axonal signals from these target areas. 
 Title: Early major histocompatibility complex (MHC) class I antigen induction in hypothalamic supraoptic and paraventricular nuclei in trypanosome-infected rats

Output: True


Input: Consider Input: Paragraph: Despite the significant role of seasonal influenza vaccination in preventing and minimizing the serious complications of influenza infection in type 2 diabetes mellitus (T2DM) patients, unsatisfactory compliance still exists for vaccination. Study objectives were to explore the vaccination status and determinants in T2DM patients in southwestern Saudi Arabia. A cross-sectional study on a representative sample of T2DM patients in Abha city, southwestern Saudi Arabia, was conducted. Data for sociodemographic characteristics, clinical criteria, vaccination status, vaccination motivators and barriers and seasonal influenza knowledge were collected. Out of 353 T2DM patients included in the study, seasonal influenza vaccination coverage was 61% in year 2017. A significant factors associated with non-vaccination were; poor influenza and its vaccine knowledge (OR = 4.31, 95% CI: 2.73-6.80), illiteracy (OR = 1.93, 95% CI: 1.11-3.37), and more than 10 years disease duration (OR = 2.07, 95% CI: 1.11-3.87). Presence of family history of DM and ischemic heart comorbidity minimized the possibility of non-vaccination (OR = 0.54 and 0.28 respectively). Healthcare givers' advice was the most reported vaccination motivator (84.7%) while; fear of vaccine side effects was the most stated barrier (73%). In conclusion, influenza vaccination rate among T2DM in the present study is less than the recommended level. Continuous primary health care center-based educational programs should be implemented to aware and encourage influenza vaccination among T2DM patients. 
 Title: Influenza Vaccination in Type 2 Diabetes Patients: Coverage Status and Its Determinants in Southwestern Saudi Arabia

Output: True


Input: Consider Input: Paragraph: Coronavirus disease broke out in Wuhan, Hubei province, China, in December 2019 and soon after Chinese health authorities took unprecedented prevention and control measures to curb the spreading of the novel coronavirus-related pneumonia. We develop a mathematical model based on daily updates of reported cases to study the evolution of the epidemic. With the model, on 95% confidence level, we estimate the basic reproduction number, R 0 = 2.82 ± 0.11, time between March 19 and March 21 when the effective reproduction number becoming less than one, the epidemic ending after April 2 and the total number of confirmed cases approaching 14408 ± 429 on the Chinese mainland excluding Hubei province. 
 Title: A deterministic epidemic model for the emergence of COVID-19 in China


Output: True