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.

Input: Consider Input: To investigate a cluster of Middle East respiratory syndrome (MERS) cases in a women-only dormitory in Riyadh, Saudi Arabia, in October 2015, we collected epidemiologic information, nasopharyngeal/oropharyngeal swab samples, and blood samples from 828 residents during November 2015 and December 2015-January 2016. We found confirmed infection for 19 (8 by reverse transcription PCR and 11 by serologic testing). Infection attack rates varied (2.7%-32.3%) by dormitory building. No deaths occurred. Independent risk factors for infection were direct contact with a confirmed case-patient and sharing a room with a confirmed case-patient; a protective factor was having an air conditioner in the bedroom. For 9 women from whom a second serum sample was collected, antibodies remained detectable at titers >1:20 by pseudoparticle neutralization tests (n = 8) and 90% plaque-reduction neutralization tests (n = 2). In closed high-contact settings, MERS coronavirus was highly infectious and pathogenicity was relatively low.

Output: EID podcast Tuberculosis Surveillance and Control in Puerto Rico


Input: Consider Input: We report a hereditary leukodystrophy in Standard Schnauzer puppies. Clinical signs occurred shortly after birth or started at an age of under 4 weeks and included apathy, dysphoric vocalization, hypermetric ataxia, intension tremor, head tilt, circling, proprioceptive deficits, seizures and ventral strabismus consistent with a diffuse intracranial lesion. Magnetic resonance imaging revealed a diffuse white matter disease without mass effect. Macroscopically, the cerebral white matter showed a gelatinous texture in the centrum semiovale. A mild hydrocephalus internus was noted. Histopathologically, a severe multifocal reduction of myelin formation and moderate diffuse edema without inflammation was detected leading to the diagnosis of leukodystrophy. Combined linkage analysis and homozygosity mapping in two related families delineated critical intervals of approximately 29 Mb. The comparison of whole genome sequence data of one affected Standard Schnauzer to 221 control genomes revealed a single private homozygous protein changing variant in the critical intervals, TSEN54:c.371G>A or p.(Gly124Asp). TSEN54 encodes the tRNA splicing endonuclease subunit 54. In humans, several variants in TSEN54 were reported to cause different types of pontocerebellar hypoplasia. The genotypes at the c.371G>A variant were perfectly associated with the leukodystrophy phenotype in 12 affected Standard Schnauzers and almost 1000 control dogs from different breeds. These results suggest that TSEN54:c.371G>A causes the leukodystrophy. The identification of a candidate causative variant enables genetic testing so that the unintentional breeding of affected Standard Schnauzers can be avoided in the future. Our findings extend the known genotype-phenotype correlation for TSEN54 variants. Various hereditary diseases of the cerebral white matter occur in humans and dogs. We describe a new leukodystrophy in Standard Schnauzers. Genetic mapping and whole genome sequence analysis identified a likely candidate causative variant in the TSEN54 gene encoding tRNA splicing endonuclease 54. These results provide new information about the role of TSEN54 in cell metabolism and the development of the central nervous system in the late gestational and early post-natal period. The affected dogs potentially represent a translational large animal model for similar leukoencephalopathies in human medicine. The clinical phenotype in Schnauzers included multifocal central nervous system signs. A holistic pathogenically driven understanding of disease initiation and perpetuation requires a solid analysis of the underlying genetics and characterization of the disease phenotype at the clinical and cellular as well as sub-cellular level. In contrast to the canine phenotype with a predominant manifestation in the cerebrum white matter, other TSEN54 variants in humans have been reported to result in a different pathological phenotype characterized by pontocerebellar hypoplasia. The differences between humans and dogs underscore the need for comparative analysis at the clinical, pathological and molecular level to understand species-specific protein mediated pathways, interactions and outcomes.

Output: TSEN54 missense variant in Standard Schnauzers with leukodystrophy Author summary


Input: Consider Input: There exists significant interest in developing statistical and computational tools for inferring 'who infected whom' in an infectious disease outbreak from densely sampled case data, with most recent studies focusing on the analysis of whole genome sequence data. However, genomic data can be poorly informative of transmission events if mutations accumulate too slowly to resolve individual transmission pairs or if there exist multiple pathogens lineages within-host, and there has been little focus on incorporating other types of outbreak data. We present here a methodology that uses contact data for the inference of transmission trees in a statistically rigorous manner, alongside genomic data and temporal data. Contact data is frequently collected in outbreaks of pathogens spread by close contact, including Ebola virus (EBOV), severe acute respiratory syndrome coronavirus (SARS-CoV) and Mycobacterium tuberculosis (TB), and routinely used to reconstruct transmission chains. As an improvement over previous, ad-hoc approaches, we developed a probabilistic model that relates a set of contact data to an underlying transmission tree and integrated this in the outbreaker2 inference framework. By analyzing simulated outbreaks under various contact tracing scenarios, we demonstrate that contact data significantly improves our ability to reconstruct transmission trees, even under realistic limitations on the coverage of the contact tracing effort and the amount of non-infectious mixing between cases. Indeed, contact data is equally or more informative than fully sampled whole genome sequence data in certain scenarios. We then use our method to analyze the early stages of the 2003 SARS outbreak in Singapore and describe the range of transmission scenarios consistent with contact data and genetic sequence in a probabilistic manner for the first time. This simple yet flexible model can easily be incorporated into existing tools for outbreak reconstruction and should permit a better integration of genomic and epidemiological data for inferring transmission chains. PLOS Computational Biology | https://doi.


Output: Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data