PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-2 (2)
 

Clipboard (0)
None

Select a Filter Below

Journals
Authors
more »
Year of Publication
Document Types
author:("Yan, donggui")
1.  Consistent Condom Use Increases the Colonization of Lactobacillus crispatus in the Vagina 
PLoS ONE  2013;8(7):e70716.
Background
Non-hormonal contraception methods have been widely used, but their effects on colonization by vaginal lactobacilli remain unclear.
Objective
To determine the association between non-hormonal contraception methods and vaginal lactobacilli on women’s reproductive health.
Methods
The cross-sectional study included 164 healthy women between 18–45 years of age. The subjects were divided into different groups on the basis of the different non-hormonal contraception methods used by them. At the postmenstrual visit (day 21 or 22 of the menstrual cycle), vaginal swabs were collected for determination of Nugent score, quantitative culture and real-time polymerase chain reaction (PCR) of vaginal lactobacilli. The prevalence, colony counts and 16S rRNA gene expression of the Lactobacillus strains were compared between the different groups by Chi-square and ANOVA statistical analysis methods.
Results
A Nugent score of 0–3 was more common in the condom group (93.1%) than in the group that used an interuterine device(IUD) (75.4%), (p = 0.005). The prevalence of H2O2-producing Lactobacillus was significantly higher in the condom group (82.3%) than in the IUD group (68.2%), (p = 0.016). There was a significant difference in colony count (mean ± standard error (SE), log10colony forming unit (CFU)/ml) of H2O2-producing Lactobacillus between condom users (7.81±0.14) and IUD users (6.54±0.14), (p = 0.000). The 16S rRNA gene expression (mean ± SE, log10copies/ml) of Lactobacillus crispatus was significantly higher in the condom group (8.09±0.16) than in the IUD group (6.03±0.18), (p = 0.000).
Conclusion
Consistent condom use increases the colonization of Lactobacillus crispatus in the vagina and may protect against both bacterial vaginosis (BV) and human immunodeficiency virus (HIV).
doi:10.1371/journal.pone.0070716
PMCID: PMC3720897  PMID: 23894682
2.  Statistical Methods for Tissue Array Images – Algorithmic Scoring and Co-training 
The annals of applied statistics  2012;6(3):1280-1305.
Recent advances in tissue microarray technology have allowed immunohistochemistry to become a powerful medium-to-high throughput analysis tool, particularly for the validation of diagnostic and prognostic biomarkers. However, as study size grows, the manual evaluation of these assays becomes a prohibitive limitation; it vastly reduces throughput and greatly increases variability and expense. We propose an algorithm—Tissue Array Co-Occurrence Matrix Analysis (TACOMA)—for quantifying cellular phenotypes based on textural regularity summarized by local inter-pixel relationships. The algorithm can be easily trained for any staining pattern, is absent of sensitive tuning parameters and has the ability to report salient pixels in an image that contribute to its score. Pathologists’ input via informative training patches is an important aspect of the algorithm that allows the training for any specific marker or cell type. With co-training, the error rate of TACOMA can be reduced substantially for a very small training sample (e.g., with size 30). We give theoretical insights into the success of co-training via thinning of the feature set in a high dimensional setting when there is “sufficient” redundancy among the features. TACOMA is flexible, transparent and provides a scoring process that can be evaluated with clarity and confidence. In a study based on an estrogen receptor (ER) marker, we show that TACOMA is comparable to, or outperforms, pathologists’ performance in terms of accuracy and repeatability.
PMCID: PMC3441061  PMID: 22984376

Results 1-2 (2)