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The role of social media during 16th Lok Sabha elections has led to several insights in the manner in which the youth of today is consuming political news. Several social media platforms have played a significant role in voting behaviour. Social media platform acted as a game changer and a catalyst in wooing young voters and influencing their opinion. While Internet users grew 7% in Urban India reaching 315 million users in 2018, digital adoption is now being propelled by rural India, registering a 35% growth in Internet users over the past year. Also, there have come a general perception that television will play a lesser role in this upcoming election and digital media will play a never before seen influence on voters. This research examines the behaviour of youth in India and examines the level of influence by social media in casting their vote in Lok Sabha elections. Whether social media can be a game changer or an influencer. These findings will be carried out by this research work.

Background: An exhaled microRNA-based lung cancer case-control discriminant biomarker strategy is reported.Methods: A microRNA-seq discovery effort compared paired tumor to non-tumor tissue, was reconciled with analogous TCGA and published literature-based tissue-discriminant microRNA data, yielding a candidate panel of 24 microRNAs that are upregulated in either adenocarcinomas and/or squamous cell carcinomas. The technical feasibility of microRNA-PCR assays in exhaled breath condensate (EBC) was tested. The airway origin of exhaled microRNAs was then topographically “fingerprinted”, using paired EBC and bronchoscopic samples. For initial EBC testing, a clinic-based case-control set of 351 individuals (166 NSCLC cases, 185 non-cancer controls) was interrogated with the 24-candidate microRNA panel by qualitative RT-PCR, and curated by melt curve analysis. Data were analyzed by both logistic regression (LR), and by random-forest (RF) models, validated by iterative resampling.Results: Both feasibility of exhaled microRNA detection, and its origins in part from lower airway sources, were confirmed. LR models adjusted for age, sex, smoking status, pack years, quit-years, and underlying lung disease identified exhaled miR-21, 33b, 212 (p.adj,=0.019, 0.018, 0.033, resp.) as case-control discriminant. For the RF analysis, the combined clinical + microRNA models showed modest added discrimination capacity (1.1–2.5%) beyond the clinical models alone: by subgroup, all subjects 1.1% (p = 8.7e-04)); former smokers 2.5% (p = 3.6e-05); early stage 1.2% (p = 9.0e-03). Sensitivity, specificity, positive- and negative-predictive values of the clinical + microRNA models for the entire cohort were 71%-76%.Conclusion: This work suggests that exhaled microRNAs are measurable qualitatively; reflect in part lower airway signatures; and if improved/refined, can potentially help distinguish lung cancer cases from controls.