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: Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust "HTR communities" (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.

Output: Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses

Input: Consider Input: Background: Nonadditivity in fitness effects from two or more mutations, termed epistasis, can result in compensation of deleterious mutations or negation of beneficial mutations. Recent evidence shows the importance of epistasis in individual evolutionary pathways. However, an unresolved question in molecular evolution is how often and how significantly fitness effects change in alternative genetic backgrounds. Results: To answer this question, we quantified the effects of all single mutations and double mutations between all positions in the IgG-binding domain of protein G (GB1). By observing the first two steps of all possible evolutionary pathways using this fitness profile, we were able to characterize the extent and magnitude of pairwise epistasis throughout an entire protein molecule. Furthermore, we developed a novel approach to quantitatively determine the effects of single mutations on structural stability (DDG U ). This enabled determination of the importance of stability effects in functional epistasis. Conclusions: Our results illustrate common biophysical mechanisms for occurrences of positive and negative epistasis. Our results show pervasive positive epistasis within a conformationally dynamic network of residues. The stability analysis shows that significant negative epistasis, which is more common than positive epistasis, mostly occurs between combinations of destabilizing mutations. Furthermore, we show that although significant positive epistasis is rare, many deleterious mutations are beneficial in at least one alternative mutational background. The distribution of conditionally beneficial mutations throughout the domain demonstrates that the functional portion of sequence space can be significantly expanded by epistasis.

Output: Article A Comprehensive Biophysical Description of Pairwise Epistasis throughout an Entire Protein Domain

Input: Consider Input: Respiratory virus infections (RVIs) are increasingly recognized as a cause of significant morbidity and mortality in recipients of hematologic stem cell transplant (HCT) and patients with hematologic malignancy (HM). 1,2 With now widespread use of molecular diagnostics, the epidemiology and spectrum of clinical disease of these infections can be better characterized. Apart from influenza, the currently available antivirals are limited in efficacy and/or associated with potential for toxicity, thus emphasizing the importance of prevention strategies. This article provides a review of the epidemiology, clinical characteristics, management, and prevention of RVIs in HCT recipients and HM patients. No disclosures. KEYWORDS Respiratory virus infection Hematopoietic stem cell transplant RSV Influenza Parainfluenza Human metapneumovirus Rhinovirus Coronavirus The morbidity and associated complications of respiratory virus infections are greater in hematopoietic stem cell transplant recipients and patients with hematologic malignancy than in immunocompetent individuals, with severity of illness related to the degree of immunosuppression. Molecular microbiologic testing is the gold standard for diagnosis, allowing differentiation of what are largely overlapping clinical syndromes. Most of the respiratory viruses, apart from influenza and in some circumstances respiratory syncytial virus and adenovirus, are managed supportively. Prevention is key and should focus on vaccination for influenza, avoidance of ill contacts, and compliance with principles of infection control. Infect Dis Clin N Am 33 (2019) 523-544 a Studies are a combination of PCR and traditional laboratory methods (eg, culture, direct fluorescent antibody, and enzyme immunoassay). b PCR-based studies. c Includes all-cause and attributable mortality with variable timeframe to death. d One mortality in a coinfected patient attributed to enterovirus/rhinovirus infection.
Output: Respiratory Virus Infections of the Stem Cell Transplant Recipient and the Hematologic Malignancy Patient