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  1. Background Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. HPV can cause genital warts and multiple types of cancers in females. HPV vaccination is recommended to youth age 11 or 12 years before sexual initiation to prevent onset of HPV-related diseases. For females who have not been vaccinated previously, catch-up vaccines are recommended through age 26. The extent to which catch-up vaccines are beneficial in terms of disease prevention and cost-effectiveness is questionable given that some women may have been exposed to HPV before receiving the catch-up vaccination. This study aims to examine whethermore »the cutoff age of catch-up vaccination should be determined based on an individual woman’s risk characteristic instead of a one-size-fits-all age 26. Methods We developed a microsimulation model to evaluate multiple clinical outcomes of HPV vaccination for different women based on a number of personal attributes. We modeled the impact of HPV vaccination at different ages on every woman and tracked her course of life to estimate the clinical outcomes that resulted from receiving vaccines. As the simulation model is risk stratified, we used extreme gradient boosting to build an HPV risk model estimating every woman’s dynamic HPV risk over time for the lifetime simulation model. Results Our study shows that catch-up vaccines still benefit all women after age 26 from the perspective of clinical outcomes. Women facing high risk of HPV infection are expected to gain more health benefits compared with women with low HPV risk. Conclusions From a cancer prevention perspective, this study suggests that the catch-up vaccine after age 26 should be deliberately considered.« less
    Free, publicly-accessible full text available May 1, 2023
  2. Free, publicly-accessible full text available January 1, 2023
  3. Free, publicly-accessible full text available August 27, 2022
  4. Free, publicly-accessible full text available November 1, 2022
  5. Summary In recent biomedical research, genome-wide association studies (GWAS) have demonstrated great success in investigating the genetic architecture of human diseases. For many complex diseases, multiple correlated traits have been collected. However, most of the existing GWAS are still limited because they analyze each trait separately without considering their correlations and suffer from a lack of sufficient information. Moreover, the high dimensionality of single nucleotide polymorphism (SNP) data still poses tremendous challenges to statistical methods, in both theoretical and practical aspects. In this article, we innovatively propose an integrative functional linear model for GWAS with multiple traits. This study ismore »the first to approximate SNPs as functional objects in a joint model of multiple traits with penalization techniques. It effectively accommodates the high dimensionality of SNPs and correlations among multiple traits to facilitate information borrowing. Our extensive simulation studies demonstrate the satisfactory performance of the proposed method in the identification and estimation of disease-associated genetic variants, compared to four alternatives. The analysis of type 2 diabetes data leads to biologically meaningful findings with good prediction accuracy and selection stability.« less
  6. Abstract Multi-time-scale variabilities of the Indian Ocean (IO) temperature over 0–700 m are revisited from the perspective of vertical structure. Analysis of historical data for 1955–2018 identifies two dominant types of vertical structures that account for respectively 70.5% and 21.2% of the total variance on interannual-to-interdecadal time scales with the linear trend and seasonal cycle removed. The leading type manifests as vertically coherent warming/cooling with the maximal amplitude at ~100 m and exhibits evident interdecadal variations. The second type shows a vertical dipole structure between the surface (0–60 m) and subsurface (60–400 m) layers and interannual-to-decadal fluctuations. Ocean model experimentsmore »were performed to gain insights into underlying processes. The vertically coherent, basinwide warming/cooling of the IO on an interdecadal time scale is caused by changes of the Indonesian Throughflow (ITF) controlled by Pacific climate and anomalous surface heat fluxes partly originating from external forcing. Enhanced changes in the subtropical southern IO arise from positive air–sea feedback among sea surface temperature, winds, turbulent heat flux, cloud cover, and shortwave radiation. Regarding dipole-type variability, the basinwide surface warming is induced by surface heat flux forcing, and the subsurface cooling occurs only in the eastern IO. The cooling in the southeast IO is generated by the weakened ITF, whereas that in the northeast IO is caused by equatorial easterly winds through upwelling oceanic waves. Both El Niño–Southern Oscillation (ENSO) and IO dipole (IOD) events are favorable for the generation of such vertical dipole anomalies.« less