instruction:
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".
question:
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
answer:
True

question:
Paragraph: Despite the wide use of Caenorhabditis elegans as a model organism, the first virus naturally infecting this organism was not discovered until six years ago. The Orsay virus and its related nematode viruses have a positive-sense RNA genome, encoding three proteins: CP, RdRP, and a novel protein that shares no homology with any other proteins. can be expressed either as a free or a CP- fusion protein by ribosomal frameshift, but the structure and function of both and CP- remain unknown. Using a combination of electron microscopy, X-ray crystallography, computational and biophysical analyses, here we show that the Orsay protein forms a~420-A long, pentameric fiber with an N-terminal -helical bundle, a -stranded filament in the middle, and a C-terminal head domain. The pentameric nature of the fiber has been independently confirmed by both mass spectrometry and analytical ultracentrifugation. Recombinant Orsay capsid containing CP- shows protruding long fibers with globular heads at the distal end. Mutant viruses with disrupted CP- fibers were generated by organism-based reverse genetics. These viruses were found to be either non-viable or with poor infectivity according to phenotypic and qRT-PCR analyses. Furthermore, addition of purified proteins to worm culture greatly reduced Orsay infectivity in a sequence-specific manner. Based on the structure resemblance between the Orsay CP- fiber and the fibers from reovirus and adenovirus, we propose that CP- functions as a cell attachment protein to mediate Orsay entry into worm intestine cells. Orsay, the only virus known to naturally infect the nematode Caenorhabditis elegans, expresses a capsid- fusion protein. We have demonstrated that the Orsay fusion protein is incorporated into Orsay capsid and forms a~420-A long fiber protruding from the PLOS Pathogens |
Title: Structure of a pentameric virion-associated fiber with a potential role in Orsay virus entry to host cells
answer:
False

question:
Paragraph: In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) and Machine Learning algorithms to determine the health risk and predict the mortality risk of patients with COVID-19. In this study, we used documented data of 117,000 patients world-wide with laboratory-confirmed COVID-19. This study proposes an AI model to help hospitals and medical facilities decide who needs to get attention first, who has higher priority to be hospitalized, triage patients when the system is overwhelmed by overcrowding, and eliminate delays in providing the necessary care. The results demonstrate 93% overall accuracy in predicting the mortality rate. We used several machine learning algorithms including Support Vector Machine (SVM), Artificial Neural Networks, Random Forest, Decision Tree, Logistic Regression, and K-Nearest Neighbor (KNN) to predict the mortality rate in patients with COVID-19. In this study, the most alarming symptoms and features were also identified. Finally, we used a separate dataset of COVID-19 patients to evaluate our developed model accuracy, and used confusion matrix to make an in-depth analysis of our classifiers and calculate the sensitivity and specificity of our model.
Title: Predicting Mortality Risk in Patients with COVID-19 Using Artificial Intelligence to Help Medical Decision-Making
answer:
False