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: Mannheimia haemolytica is the most important bacterial agent associated with the bovine respiratory disease complex (BRDC), which causes worldwide economic losses to the cattle industry. M. haemolytica cells initially colonize the tonsillar crypts in the upper respiratory tract of cattle, from where they can subsequently descend into the lungs to cause disease. Many bacteria exist as biofilms inside their hosts. We hypothesize that M. haemolytica colonization of cattle during its commensal state may include biofilm formation. To begin to assess this possibility, we developed an in vitro system to study biofilm formation directly on bovine respiratory epithelial cells. Using fixed primary bovine bronchial epithelial cells, we observed M. haemolytica biofilm formation after a 48 h incubation period at 37 C. Addition of mucin, the main component of mucus present in the upper respiratory tract, decreased M. haemolytica biofilm formation on bovine epithelial cells. We investigated the effects of prior viral infection of the epithelial cells on subsequent biofilm formation by M. haemolytica and found negligible effects. Utilization of this model system will provide new insights into the potential role of biofilm formation by M. haemolytica in the pathogenesis of BRDC.

Output: Mannheimia haemolytica biofilm formation on bovine respiratory epithelial cells


Input: Consider Input: Interferon-inducible transmembrane proteins 1, 2, and 3 (IFITM1, 2, and 3) are recently identified viral restriction factors that inhibit infection mediated by the influenza A virus (IAV) hemagglutinin (HA) protein. Here we show that IFITM proteins restricted infection mediated by the entry glycoproteins (GP 1,2 ) of Marburg and Ebola filoviruses (MARV, EBOV). Consistent with these observations, interferon-b specifically restricted filovirus and IAV entry processes. IFITM proteins also inhibited replication of infectious MARV and EBOV. We observed distinct patterns of IFITM-mediated restriction: compared with IAV, the entry processes of MARV and EBOV were less restricted by IFITM3, but more restricted by IFITM1. Moreover, murine Ifitm5 and 6 did not restrict IAV, but efficiently inhibited filovirus entry. We further demonstrate that replication of infectious SARS coronavirus (SARS-CoV) and entry mediated by the SARS-CoV spike (S) protein are restricted by IFITM proteins. The profile of IFITM-mediated restriction of SARS-CoV was more similar to that of filoviruses than to IAV. Trypsin treatment of receptor-associated SARS-CoV pseudovirions, which bypasses their dependence on lysosomal cathepsin L, also bypassed IFITM-mediated restriction. However, IFITM proteins did not reduce cellular cathepsin activity or limit access of virions to acidic intracellular compartments. Our data indicate that IFITM-mediated restriction is localized to a late stage in the endocytic pathway. They further show that IFITM proteins differentially restrict the entry of a broad range of enveloped viruses, and modulate cellular tropism independently of viral receptor expression. This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

Output: Distinct Patterns of IFITM-Mediated Restriction of Filoviruses, SARS Coronavirus, and Influenza A Virus


Input: Consider Input: This paper discusses the issue of selecting the design solution that best accords with an articulated preference of multiple criteria with an acceptable performance band. The application of a newly developed multi-criteria decision-making tool called RR-PARETO2 is presented. An example of HVAC design is used to illustrate how solutions could be selected within a multi-criteria optimization framework. In this example, five criteria have been selected, namely, power consumption, thermal comfort, risk of airborne infection of influenza and tuberculosis and effective differential temperature ( t eq ) of body parts. The goal is to select the optimal air exchange rate that makes reasonable trade-offs among all the objectives. Two scenarios have been studied. In the first scenario, there is an influenza outbreak and the important objective is to prevent the spread of infection. In the second scenario, energy prices are high and the primary objective is to reduce energy. In both scenarios, RR-PARETO2 algorithm selects solutions that make reasonable trade-offs among conflicting objectives. The example illustrates how objectives such as reduction of airborne disease transmission and maximizing thermal comfort can be incorporated in the design of a practical, full-scale HVAC system.


Output: A preference driven multi-criteria optimization tool for HVAC design and operation