How often is genital yeast infection sexually transmitted?

We analysed data from a computer-based bank of clinical records of patients seen in a clinic for sexually transmitted diseases over a three-year period to investigate the association between genital yeast infections and sexually transmitted diseases (STDs). We classified STDs as primary and secondary syphilis; gonorrhoea; lymphogranuloma venereum; trichomoniasis; scabies; pediculosis; genital herpes; warts; and molluscum contagiosum. Of a total of 2984 disease episodes among women, 1054 (35-3%) included yeast infections, whereas only 382 (6-9%) of 5501 episodes in heterosexual men were associated with yeast infections, We found a significant association between yeast infection and STD and non-specific genital infection (non-specific urethritis (NSU) and procitis in men, and female contacts of men with NSU), which suggested that yeast infection was sexually acquired in 414 out of 1054 disease episodes in women (39%) and 110 out of 382 episodes in heterosexual men (29%). We conclude that sexually active patients with genital yeast infections should be screened for other STDs particularly non-specific genital infection.     

A cross-cancer metastasis signature in the microRNA–mRNA axis of paired tissue samples

In the progression of cancer, cells acquire genetic mutations that cause uncontrolled growth. Over time, the primary tumour may undergo additional mutations that allow for the cancerous cells to spread throughout the body as metastases. Since metastatic development typically results in markedly worse patient outcomes, research into the identity and function of metastasis-associated biomarkers could eventually translate into clinical diagnostics or novel therapeutics. Although the general processes underpinning metastatic progression are understood, no clear cross-cancer biomarker profile has emerged. However, the literature suggests that some microRNAs (miRNAs) may play an important role in the metastatic progression of several cancer types. Using a subset of The Cancer Genome Atlas (TCGA) data, we performed an integrated analysis of mRNA and miRNA expression with paired metastatic and primary tumour samples to interrogate how the miRNA–mRNA regulatory axis influences metastatic progression. From this, we successfully built mRNA- and miRNA-specific classifiers that can discriminate pairs of metastatic and primary samples across 11 cancer types. In addition, we identified a number of miRNAs whose metastasis-associated dysregulation could predict mRNA metastasis-associated dysregulation. Among the most predictive miRNAs, we found several previously implicated in cancer progression, including miR-301b, miR-1296, and miR-423. Taken together, our results suggest that metastatic samples have a common cross-cancer signature when compared with their primary tumour pair, and that these miRNA biomarkers can be used to predict metastatic status as well as mRNA expression.

     

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.     

Response of Barley Genotypes to Fusarium Head Blight under Natural Infection and Artificial Inoculation Conditions

Forty-eight spring barley genotypes were evaluated for deoxynivalenol (DON) concentration under natural infection across 5 years at Harrington, Prince Edward Island. These genotypes were also evaluated for Fusarium head blight (FHB) severity and DON concentration under field nurseries with artificial inoculation of Fusarium graminearum by the grain spawn method across 2 years at Ottawa, Ontario, and one year at Hangzhou, China. Additionally, these genotypes were also evaluated for FHB severity under greenhouse conditions with artificial inoculation of F. graminearum by conidial suspension spray method across 3 years at Ottawa, Ontario. The objective of the study was to investigate if reactions of barley genotypes to artificial FHB inoculation correlate with reactions to natural FHB infection. DON concentration under natural infection was positively correlated with DON concentration (r = 0.47, P < 0.01) and FHB incidence (r = 0.56, P < 0.01) in the artificially inoculated nursery with grain spawn method. Therefore, the grain spawn method can be used to effectively screen for low DON. FHB severity, generated from greenhouse spray, however, was not correlated with DON concentration (r = 0.12, P > 0.05) under natural infection and it was not correlated with DON concentration (r = −0.23, P > 0.05) and FHB incidence (r = 0.19, P > 0.05) in the artificially inoculated nursery with grain spawn method. FHB severity, DON concentration, and yield were affected by year, genotype, and the genotype × year interaction. The effectiveness of greenhouse spray inoculation for indirect selection for low DON concentration requires further studies. Nine of the 48 genotypes were found to contain low DON under natural infection. Island barley had low DON and also had high yield.     

Sequence diversity in the amino-terminal region of the malaria-vaccine candidate serine repeat antigen in natural Plasmodium falciparum populations

The amino-terminal region of the serine repeat antigen (SERA) of Plasmodium falciparum is a major malaria-vaccine candidate. Variation in this molecule is essentially dimorphic and alleles may be grouped into the types FCR3, K1 and Honduras1. The Honduras1-type is thought to be the product of homologous recombination between FCR3 and K1 alleles. Here we have examined patterns of sequence diversity in exon II of SERA gene, which encodes most of the amino-terminal region of the antigen, in wild P. falciparum isolates from Indonesia (n=60), Myanmar (n=10) and Thailand (n=14). Among the Indonesian isolates the FCR-3 type predominated (56/60), twenty of which we characterized as novel alleles. A new K1-type allele was also found. In Myanmar, however, all isolates displayed K1-type SERA sequences, which included one new allele. The Honduras1-type was not detected in both countries. In contrast, the 14 isolates from Thailand displayed all three allelic types, with one new Honduras1-type and three new K1-type alleles. On examining the global distribution of SERA alleles by combining previously published sequence data with our results, the FCR3-type alleles predominated in Indonesia, Brazil, and Solomon Islands, but were not found in wild isolates from Myanmar and Africa. Brazil was the only area where K1-type alleles were not found. The distribution of Honduras1-type alleles seems to be mostly restricted to parasite populations from Vietnam, Thailand and Africa. In the allelic families FCR3 and K1, most diversity resulted from variation in sequence and number of octamer repeat units and of allotypes encoding the stretch of serine residues. Sequence analysis indicated that both insertions and deletions of repetitive motifs (creating variation within dimorphic allelic families) and homologous recombination between alleles belonging to different allelic families (creating Honduras1-type alleles) play a role in generating new SERA alleles. Since repeat motifs in the amino-terminal region of SERA contain epitopes recognized by parasite-inhibitory antibodies, sequence variation in exon II may represent one of the parasite's immune-evasion strategies.