instruction:
In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
question:
Paragraph: microRNAs (miRNAs) represent a newly identified class of nonprotein-coding *22 nt small RNA that plays important roles in multiple biological processes by degrading targeted mRNA or repressing mRNA translation. This study observed the morphology of swine testicular tissue at different developmental stages (including 1-day old, 1-7 month old) by Hematoxylin-eosin staining. We also examined the expression of miR-499 and its target genes (CYLC1, DMRT1, QKI, XRN2, ZNF313) in samples of tissue slices using quantitative reversetranscription polymerase chain reaction, which showed that miR-499 had a significant negative correlation with QKI gene. Then, the proteins of QKI gene expression were determined by western blot, which were consistent with results of quantitative polymerase chain reaction (qPCR) detection. Therefore, the luciferase reporter gene system was used to verify correlation between miR-499 and QKI gene. Activity of luciferase was significantly lower in miR-499 co-transfected with pmiR-RB-REPORT-QKI-WT group than the miR-499 co-transfected with pmiR-RB-REPORT-QKI-mut/si groups, indicating that target sequence of miR-499 existed in 3¢UTR of QKI gene. Furthermore, the expressions of miR-499 and QKI were detected in testicular cells that were transfected with miR-499, miR-499 negative control and untreated. The results showed that the diameter of convoluted seminiferous tubule growth increased with age. Significantly different expressions of miR-499 and its target genes were found in swine testicular tissue at different developmental stages ( p < 0.05), overexpressing miR-499 analysis, suggesting that miR-499 was negatively correlated to the expression of QKI ( p < 0.05). In conclusion, QKI is a target gene of miR-499. 
 Title: Differential Expression of miR-499 and Validation of Predicted Target Genes in the Testicular Tissue of Swine at Different Developmental Stages
answer:
False


question:
Paragraph: To circumvent limitations of poor antigen presentation and immunogenicity of DNA vaccines that target induction of CD8 + T cell immunity, we have generated single chain MHC I trimers (MHC I SCTs) composed of a single polypeptide chain with a linear composition of antigenic peptide, β2microglobulin, and heavy chain of a MHC class I molecule connected by flexible linkers. Because of its pre-assembled nature, the SCT presents enhanced expression and presentation of the antigenic peptide/MHC complexes at the cell surface. Furthermore, DNA vaccination with a plasmid DNA encoding an SCT incorporating an immunodominant viral epitope elicited protective CD8 + T cell responses against lethal virus infection. To extend these findings, here we tested the efficacy of SCT DNA vaccines against bacterial infections. In a mouse infection model of Listeria monocytogenes, the SCT DNA vaccine encoding H-2K d and the immunodominant peptide LLO 91-99 generated functional primary and memory peptide-specific CD8 + T cells that confer partial protection against L. monocytogenes infection. DNA immunization of K d /LLO 91-99 SCTs generated functional memory CD8 + T cells independently of CD4 + T cells, although the expression of cognate or non-cognate CD4 + helper T cell epitopes further enhanced the protective efficacy of SCTs. Our study further demonstrates that the SCT serves as a potent platform for DNA vaccines against various infectious diseases. 
 Title: Single Chain MHC I trimer-based DNA vaccines for protection against Listeria monocytogenes infection
answer:
True


question:
Paragraph: Sensors and biosensors have been increasingly used for clinical analysis due to their miniaturization and portability, allowing the construction of diagnostic devices for point-of-care testing. This paper presents an up-to-date overview and comparison of the analytical performance of sensors and biosensors recently used in clinical analysis. This includes cancer and cardiac biomarkers, hormones, biomolecules, neurotransmitters, bacteria, virus and cancer cells, along with related significant advances since 2011. Some methods of enhancing the analytical performance of sensors and biosensors through their figures of merit are also discussed. 
 Title: Critical overview on the application of sensors and biosensors for clinical analysis
answer:

True