The efficacy of PPV-23 vaccine on outcomes of pneumococcal disease in adults still remains controversial due mainly to the lack of consistency between the results obtained from observational studies(OSs) and those obtained from randomized controlled trials(RCTs). As a consequence, the complexity in the structure of evidence available, in turn, generates a challenge for combining disparate pieces of evidence quantitatively. In this regard, we used a hierarchical Bayesian inference-based evidence synthesis of RCTs and observational data using a two-stage approach (in addition to a traditional random-effects meta-analysis) to examine the effectiveness of PPV-23 in adults. To this end, 21 studies were included involving 826109 adult participants. By a two-stage Bayesian meta-analysis, which was directly used for combining studies of different designs, the overall log OR (95% credible interval) for IPDs was −0.1048 (−0.3920,−0.0250), indicating a significant protective effect of the vaccination against IPDs. No significant effect of PPV-23 was found on all-cause pneumonia, pneumococcal pneumonia, and death from pneumonia, which confirmed the results obtained by a traditional method followed by stratified and sensitivity analyses. The estimated overall log OR (95% credible interval) was −0.0002 (−0.0241,0.0142), −0.0002 (−0.0110,0.0122), and −6.3912 × 10−5 (−0.0219,0.0131), respectively. The PPV-23 vaccine might be effective in preventing the most severe invasive forms of pneumococcal diseases, but not effective in preventing other clinical outcomes, in the adult population of 18 years and older.

Genetic variants within oncogenic long non-coding RNAs HOTAIR and HOTTIP may affect their gene expression levels, thereby modifying genetic susceptibility to gastric cancer (GC). In a hospital-based study in Ardabil—a very high-risk area in North-West Iran, 600 blood samples from 300 GC patients and 300 healthy controls were recruited for genotyping. Seven HOTAIR (i.e., rs17720428, rs7958904, rs1899663, and rs4759314) and HOTTIP (i.e., rs3807598, rs17501292, and rs1859168) ‘tag’ single nucleotide polymorphisms (SNPs) were genotyped by the Infinium HTS platform. The rs17720428, rs7958904, and rs1899663 tagSNPs significantly increased GC risk under dominant models by 1.5-, 1.57-, and 1.5-fold, respectively. The G-C-T-A haplotype of HOTAIR tagSNPs increased the risk of GC by 1.31-fold. No significant association was found between HOTTIP SNPs and the risk of GC. HOTAIR and HOTTIP variants were also not associated with any clinicopathologic characteristics. The SNP-SNP interaction of HOTAIR rs17720428/rs7958904 with HOTTIP rs1859168 was associated with an increased risk of GC (rs17720428 TG-rs1859168 CC, OR = 1.76; rs7958904 GC-rs1859168 CC, OR = 1.85; rs7958904 CC-rs1859168 CC, OR = 1.86). Interestingly, the SNP-SNP interaction of HOTAIR rs1899663 with HOTTIP rs1859168 strongly increased the risk of GC (rs1899663 GT-rs1859168 CC, OR = 4.3; rs1899663 TT-rs1859168 CC, OR = 9.37; rs1899663 TT-rs1859168 CA, OR = 6.59). We showed that the HOTAIR rs17720428, rs7958904, and rs1899663 tagSNPs and their interactions with the HOTTIP rs1859168 polymorphism significantly increased the risk of GC. Specifically, novel SNP-SNP interactions between HOTAIR and HOTTIP tagSNPs have a larger impact than individual SNP effects on GC risk, thereby providing us with valuable information to reveal potential biological mechanisms for developing GC.

In the present paper, we study functional varying coefficient model in which both the response and the predictor are functions. We give estimates of the intercept and the slope functions in the case that the observations are sparse and noise-contaminated longitudinal data by using least squares representation of the model parameters. To estimate the parameter functions involved in the representation, we use a regularization method in some reproducing kernel Hilbert spaces. As we will see, our procedure is easy to implement. Also, we obtain the convergence rates of the estimators in the 2 -sense. These convergence rates establish that the procedure performs well, especially, when sampling frequency or sample size increases.

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