In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

[EX Q]: A 68-year old man diagnosed with Middle East Respiratory Syndrome-Coronavirus (MERS-CoV) presented with multiple pneumonic infiltrations on his chest X-ray, and the patient was placed on a mechanical ventilator because of progressive respiratory failure. Urinary protein excretion steadily increased for a microalbumin to creatinine ratio of 538.4 mg/g Cr and a protein to creatinine ratio of 3,025.8 mg/g Cr. The isotope dilution mass spectrometry traceable serum creatinine level increased to 3.0 mg/dL. We performed a kidney biopsy 8 weeks after the onset of symptoms. Acute tubular necrosis was the main finding, and proteinaceous cast formation and acute tubulointerstitial nephritis were found. There were no electron dense deposits observed with electron microscopy. We could not verify the virus itself by in situ hybridization and confocal microscopy (MERS-CoV costained with dipeptidyl peptidase 4). The viremic status, urinary virus excretion, and timely kidney biopsy results should be investigated with thorough precautions to reveal the direct effects of MERS-CoV with respect to renal complications.
[EX A]: A Case Report of a Middle East Respiratory Syndrome Survivor with Kidney Biopsy Results

[EX Q]: Objectives: We aimed to develop a prospective prediction tool on CrimeaneCongo haemorrhagic fever (CCHF) to identify geographic regions at risk. The tool could support public health decision-makers in implementation of an effective control strategy in a timely manner. Methods: We used monthly surveillance data between 2004 and 2015 to predict case counts between 2016 and 2017 prospectively. The Turkish nationwide surveillance data set collected by the Ministry of Health contained 10 411 confirmed CCHF cases. We collected potential explanatory covariates about climate, land use, and animal and human populations at risk to capture spatiotemporal transmission dynamics. We developed a structured Gaussian process algorithm and prospectively tested this tool predicting the future year's cases given past years' cases. Results: We predicted the annual cases in 2016 and 2017 as 438 and 341, whereas the observed cases were 432 and 343, respectively. Pearson's correlation coefficient and normalized root mean squared error values for 2016 and 2017 predictions were (0.83; 0.58) and (0.87; 0.52), respectively. The most important covariates were found to be the number of settlements with fewer than 25 000 inhabitants, latitude, longitude and potential evapotranspiration (evaporation and transpiration). Conclusions: Main driving factors of CCHF dynamics were human population at risk in rural areas, geographical dependency and climate effect on ticks. Our model was able to prospectively predict the numbers of CCHF cases. Our proof-of-concept study also provided insight for understanding possible mechanisms of infectious diseases and found important directions for practice and policy to combat against emerging infectious diseases. Ç. Ak, Clin Microbiol Infect 2020;26:123.e1e123.e7
[EX A]: A prospective prediction tool for understanding CrimeaneCongo haemorrhagic fever dynamics in Turkey

[EX Q]: KEYWORDS Travel health Travel abroad Pretravel Assessment Posttravel Assessment Primary care providers manage the majority of travel medical care. The purpose of the pretravel visit are risk assessment and mitigation. Encourage travelers to enroll in the Smart Traveler Enrollment Program for travel advisories. The Centers for Disease Control and Prevention travel website offers destination-specific, point-of-care resources for clinicians and travelers. Travelers who are visiting friends and relatives are a high-risk group. The most common syndromes in returning travelers are gastrointestinal, febrile, and dermatologic. Prim Care Clin Office Pract 45 (2018) 541-554
[EX A]:
Health Guidelines for Travel Abroad