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.

Example Input: The lengthy duration of multidrug therapy needed to cure tuberculosis (TB) poses significant challenges for global control of the disease. Moreover, chronic inflammation associated with TB leads to pulmonary damage that can remain even after successful cure. Thus, there is a great need for the development of effective shorter drug regimens to improve clinical outcome and strengthen TB control. Host-directed therapy (HDT) is emerging as a novel adjunctive strategy to enhance the efficacy and shorten the duration of TB treatment. Previously, we showed that the administration of CC-3052, a phosphodiesterase-4 inhibitor (PDE4i), reduced the host inflammatory response during Mycobacterium tuberculosis (Mtb) infection and improved the antimicrobial efficacy of isoniazid (INH) in both the mouse and rabbit models. In the present study, we evaluated the pharmacokinetics and explored the mechanism underlying the efficacy of a more potent PDE4i, CC-11050, as adjunct to INH treatment in a mouse model of pulmonary Mtb infection. Genome-wide lung transcriptome analysis confirmed the dampening of inflammation and associated network genes that we previously reported with CC-3052. Consistent with the reduction in inflammation, a significant improvement in Mtb control and pathology was observed in the lungs of mice treated with CC-11050 plus INH, compared to INH alone. This important confirmatory study will be used to help design upcoming human clinical trials with CC-11050 as an HDT for TB treatment.
Example Output: Pharmacologic inhibition of host Phosphodiesterase-4 improves isoniazid-Mediated clearance of Mycobacterium tuberculosis

Example Input: Background: Houttuynia cordata Thunb. is an important traditional medical herb in China and other Asian countries, with high medicinal and economic value. However, a lack of available genomic information has become a limitation for research on this species. Thus, we carried out high-throughput transcriptomic sequencing of H. cordata to generate an enormous transcriptome sequence dataset for gene discovery and molecular marker development. Principal Findings: Illumina paired-end sequencing technology produced over 56 million sequencing reads from H. cordata mRNA. Subsequent de novo assembly yielded 63,954 unigenes, 39,982 (62.52%) and 26,122 (40.84%) of which had significant similarity to proteins in the NCBI nonredundant protein and Swiss-Prot databases (E-value ,10 25 ), respectively. Of these annotated unigenes, 30,131 and 15,363 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. In addition, 24,434 (38.21%) unigenes were mapped onto 128 pathways using the KEGG pathway database and 17,964 (44.93%) unigenes showed homology to Vitis vinifera (Vitaceae) genes in BLASTx analysis. Furthermore, 4,800 cDNA SSRs were identified as potential molecular markers. Fifty primer pairs were randomly selected to detect polymorphism among 30 samples of H. cordata; 43 (86%) produced fragments of expected size, suggesting that the unigenes were suitable for specific primer design and of high quality, and the SSR marker could be widely used in markerassisted selection and molecular breeding of H. cordata in the future. Conclusions: This is the first application of Illumina paired-end sequencing technology to investigate the whole transcriptome of H. cordata and to assemble RNA-seq reads without a reference genome. These data should help researchers investigating the evolution and biological processes of this species. The SSR markers developed can be used for construction of high-resolution genetic linkage maps and for gene-based association analyses in H. cordata. This work will enable future functional genomic research and research into the distinctive active constituents of this genus.
Example Output: Transcriptome Analysis of Houttuynia cordata Thunb. by Illumina Paired-End RNA Sequencing and SSR Marker Discovery

Example Input: Purpose: To examine the feasibility of using a computer tool for stratifying the severity of Coronavirus Disease 2019 (COVID-19) based on computed tomography (CT) images. Materials and methods: We retrospectively examined 44 confirmed COVID-19 cases. All cases were evaluated separately by radiologists (visually) and through an in-house computer software. The degree of lesions was visually scored by the radiologist, as follows, for each of the 5 lung lobes: 0, no lesion present; 1, <1/3 involvement; 2, >1/3 and < 2/3 involvement; and 3, >2/3 involvement. Lesion density was assessed based on the proportion of ground-glass opacity (GGO), consolidation and fibrosis of the lesions. The parameters obtained using the computer tool included lung volume (mL), lesion volume (mL), lesion percentage (%), and mean lesion density (HU) of the whole lung, right lung, left lung, and each lobe. The scores obtained by the radiologists and quantitative results generated by the computer software were tested for correlation. A Chi-square test was used to test the consistency of radiologist-and computerderived lesion percentage in the right/left lung, upper/lower lobe, and each of the 5 lobes. The results showed a strong to moderate correlation between lesion percentage scores obtained by radiologists and the computer software (r ranged from 0.7679 to 0.8373, P < 0.05), and a moderate correlation between the proportion of GGO and mean lesion density (r ¼ À0.5894, P < 0.05), and proportion of consolidation and mean lesion density (r ¼ 0.6282, P < 0.05). Computer-aided quantification showed a statistical significant higher lesion percentage for lower lobes than that assessed by the radiologists (c 2 ¼ 8.160, P ¼ 0.004). Conclusions: Our experiments demonstrated that the computer tool could reliably and accurately assess the severity and distribution of pneumonia on CT scans.
Example Output:
Quantitative computed tomography analysis for stratifying the severity of Coronavirus Disease 2019-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)