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author:("Yan, donghu")
1.  Human serum inhibits adhesion and biofilm formation in Candida albicans 
BMC Microbiology  2014;14:80.
Candida albicans can form biofilms on intravenous catheters; this process plays a key role in the pathogenesis of catheter infections. This study evaluated the effect of human serum (HS) on C. albicans biofilm formation and the expression of adhesion-related genes in vitro. A C. albicans laboratory strain (ATCC90028) and three clinical strains were grown for 24 h in RPMI 1640 supplemented with HS or RPMI 1640 alone (as a control). The growth of biofilm cells of four strains was monitored by a Live Cell Movie Analyzer, and by XTT reduction assay. The expression of the adhesion-related genes BCR1, ALS1, ALS3, HWP1 and ECE1 was analyzed by RT-PCR at three time points (60 min, 90 min, and 24 h).
In the adhesion phase, C. albicans cells kept a Brownian movement in RPMI medium containing HS until a large number of germ tubes were formed. In the control group, C. albicans cells quickly adhered to the bottom of the reaction plate. Compared with RPMI 1640, medium supplemented with 3–50% HS caused a significant decrease in biofilm development (all p < 0.001). However, the presence of HS had no significant inhibitory effect on the pre-adhered biofilms (all p > 0.05). Biofilm formation was also inhibited by heat-inactivated and proteinase K pre-treated HS. The presence of 50% HS did not significantly affect the planktonic growth of C. albicans (p > 0.05). At three time points, HS inhibited expression of the ALS1 and ALS3 genes and promoted expression of the HWP1 and ECE1 genes. Significant up-regulation of BCR1 was observed only at the 90-min point.
Human serum reduces biofilm formation by inhibiting the adhesion of C. albicans cells. This response may be associated with the down-regulation of adhesion-related genes ALS1, ALS3 and BCR1. The inhibitory serum component is protease-resistant and heat stable.
PMCID: PMC4101872  PMID: 24673895
Human serum; Biofilm; Adhesion; Candida albicans
2.  Consistent Condom Use Increases the Colonization of Lactobacillus crispatus in the Vagina 
PLoS ONE  2013;8(7):e70716.
Non-hormonal contraception methods have been widely used, but their effects on colonization by vaginal lactobacilli remain unclear.
To determine the association between non-hormonal contraception methods and vaginal lactobacilli on women’s reproductive health.
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.
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).
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).
PMCID: PMC3720897  PMID: 23894682
3.  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 1-3 (3)