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 Input:
Paragraph: Background: Viral aetiologies are the most common cause of central nervous system (CNS) infections. Approximately one-half of CNS infections remain of undetermined origin. High-throughput sequencing (HTS) brought new perspectives to CNS infection investigations, allowing investigation of viral aetiologies with an unbiased approach. HTS use is still limited to specific clinical situations. Objectives: The aim of this review was to evaluate the contribution and pitfalls of HTS for the aetiologic identification of viral encephalitis, meningoencephalitis, and meningitis in CNS patient samples. Sources: PubMed was searched from 1 January 2008 to 2 August 2018 to retrieve available studies on the topic. Additional publications were included from a review of full-text sources. Content: Among 366 studies retrieved, 29 used HTS as a diagnostic technique. HTS was performed in cerebrospinal fluid and brain biopsy samples of 307 patients, including immunocompromised, immunocompetent paediatric, and adult cases. HTS was performed retrospectively in 18 studies and prospectively in 11. HTS led to the identification of a potential causal virus in 41 patients, with 11 viruses known and ten not expected to cause CNS infections. Various HTS protocols were used. Implications: The additional value of HTS is difficult to quantify because of various biases. Nevertheless, HTS led to the identification of a viral cause in 13% of encephalitis, meningoencephalitis, and meningitis cases in which various assays failed to identify the cause. HTS should be considered early in clinical management as a complement to routine assays. Standardized strategies and systematic studies are needed for the integration of HTS in clinical management. M.-C. Zanella, Clin Microbiol Infect 2019;25:422
Title: High-throughput sequencing for the aetiologic identification of viral encephalitis, meningoencephalitis, and meningitis. A narrative review and clinical appraisal

Ex Output:
False

Ex Input:
Paragraph: Background: The evaluation of children with purpuric rash and fever (PRF) is controversial. Although many of them have viral infections, on occasion such patients may be infected with Neisseria meningitidis. We described all children aged 0e18 years with PRF in southern Israel during the period 2005 2016 and compared their microbiologic, laboratory, clinical and outcome characteristics in relation to various etiologies of this syndrome. Methods: Data were summarized from electronic patient and microbiology files. Viral diagnoses were made by serology and/or PCR. Results: Sixty-nine children with PRF were admitted; 30 (43.48%), 9 (13.04%) and 30 (43.48%) had a syndrome of bacterial, viral or non-established etiology, respectively. N. meningitidis infection was diagnosed in 16/69 (23.19%) patients and in 16/30 (53.33%) patients with bacterial etiology; 14/30 (46.67%) patients suffered from a non-invasive bacterial disease (9 with Rickettsial disease). Adenovirus and Influenza B (3 and 2 cases, respectively) represented the most frequent etiologic agents among patients with viral etiology. More patients with PRF of bacterial etiology were older, of Bedouin ethnicity, looked ill on admission, had higher Pediatrics and Neonatology (2019) 60, 556e563 rates of meningitis and were treated more frequently with antibiotics compared with patients with non-bacterial PRF. Fatality rates among patients with bacterial, viral and non-established etiology were 5/30 (16.7%), 0% and 2/39 (5.1%). Conclusions: Although PFR was uncommon, high rates of meningococcal infections were recorded in children with PRF, which was associated with high fatality rates. Rickettsial infections were frequent, emphasizing the need for a high index of suspicion for this disease in endemic geographic areas.
Title: Original Article

Ex Output:
True

Ex Input:
Paragraph: Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein-protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.
Title: Generalized lattice graphs for 2D-visualization of biological information

Ex Output:
True