Syphilis Screening among 27,150 Pregnant Women in South Chinese Rural Areas Using Point-of-Care Tests

Objectives

To determine the prevalence and correlates of syphilis among pregnant women in rural areas of South China.

Methods

Point-of-care syphilis testing was provided at 71 health facilities in less developed, rural areas of Guangdong Province. Positive samples were confirmed at a local referral center by toluidine red unheated serum tests (TRUST) and Treponema pallidum particle agglutination (TPPA) tests.

Results

Altogether 27,150 pregnant women in rural Guangdong were screened for syphilis. 106 (0.39%) syphilis cases were diagnosed, of which 78 (73.6%) received treatment for syphilis. Multivariate analysis revealed that older pregnant women (31–35 years old, aOR 2.7, 95% CI 0.99–7.32; older than 35 years old, aOR 5.9, 95% CI 2.13–16.34) and those with a history of adverse pregnant outcomes (aOR 3.64, 95% CI 2.30–5.76) were more likely to be infected with syphilis.

Conclusions

A high prevalence of syphilis exists among pregnant women living in rural areas of South China. Enhanced integration of syphilis screening with other routine women''s health services (OB GYN, family planning) may be useful for controlling China''s syphilis epidemic.     

A 1.35 Mb DNA fragment is inserted into the DHMN1 locus on chromosome 7q34–q36.2

Distal hereditary motor neuropathies predominantly affect the motor neurons of the peripheral nervous system leading to chronic disability. Using whole genome sequencing (WGS) we have identified a novel structural variation (SV) within the distal hereditary motor neuropathy locus on chromosome 7q34–q36.2 (DHMN1). The SV involves the insertion of a 1.35 Mb DNA fragment into the DHMN1 disease locus. The source of the inserted sequence is 2.3 Mb distal to the disease locus at chromosome 7q36.3. The insertion involves the duplication of five genes (LOC389602, RNF32, LMBR1, NOM1, MNX1) and partial duplication of UBE3C. The genomic structure of genes within the DHMN1 locus are not disrupted by the insertion and no disease causing point mutations within the locus were identified. This suggests the novel SV is the most likely DNA mutation disrupting the DHMN1 locus. Due to the size and position of the DNA insertion, the gene(s) directly affected by the genomic re-arrangement remains elusive. Our finding represents a new genetic cause for hereditary motor neuropathies and highlights the growing importance of interrogating the non-coding genome for SV mutations in families which have been excluded for genome wide coding mutations.     

Fusing Data Mining,Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

Background

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

Methods

The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

Results

After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

Conclusion

The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.     

Root traits of perennial C4 grasses contribute to cultivar variations in soil chemistry and species patterns in particulate and mineral-associated carbon pool formation

Recent studies have indicated that the C₄ perennial bioenergy crops switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii) accumulate significant amounts of soil carbon (C) owing to their extensive root systems. Soil C accumulation is likely driven by inter- and intraspecific variability in plant traits, but the mechanisms that underpin this variability remain unresolved. In this study we evaluated how inter- and intraspecific variation in root traits of cultivars from switchgrass (Cave-in-Rock, Kanlow, Southlow) and big bluestem (Bonanza, Southlow, Suther) affected the associations of soil C accumulation across soil fractions using stable isotope techniques. Our experimental field site was established in June 2008 at Fermilab in Batavia, IL. In 2018, soil cores were collected (30 cm depth) from all cultivars. We measured root biomass, root diameter, specific root length, bulk soil C, C associated with coarse particulate organic matter (CPOM) and fine particulate organic matter plus silt- and clay-sized fractions, and characterized organic matter chemical class composition in soil using high-resolution Fourier-transform ion cyclotron resonance mass spectrometry. C₄ species were established on soils that supported C₃ grassland for 36 years before planting, which allowed us to use differences in the natural abundance of stable C isotopes to quantify C₄ plant-derived C. We found that big bluestem had 36.9% higher C₄ plant-derived C compared to switchgrass in the CPOM fraction in the 0–10 cm depth, while switchgrass had 60.7% higher C₄ plant-derived C compared to big bluestem in the clay fraction in the 10–20 cm depth. Our findings suggest that the large root system in big bluestem helps increase POM-C formation quickly, while switchgrass root structure and chemistry build a mineral-bound clay C pool through time. Thus, both species and cultivar selection can help improve bioenergy management to maximize soil carbon gains and lower CO₂ emissions.     

Impact of Low Dose Prenatal Ethanol Exposure on Glucose Homeostasis in Sprague-Dawley Rats Aged up to Eight Months

Excessive exposure to alcohol prenatally has a myriad of detrimental effects on the health and well-being of the offspring. It is unknown whether chronic low-moderate exposure of alcohol prenatally has similar and lasting effects on the adult offspring’s health. Using our recently developed Sprague-Dawley rat model of 6% chronic prenatal ethanol exposure, this study aimed to determine if this modest level of exposure adversely affects glucose homeostasis in male and female offspring aged up to eight months. Plasma glucose concentrations were measured in late fetal and postnatal life. The pancreas of 30 day old offspring was analysed for β-cell mass. Glucose handling and insulin action was measured at four months using an intraperitoneal glucose tolerance test and insulin challenge, respectively. Body composition and metabolic gene expression were measured at eight months. Despite normoglycaemia in ethanol consuming dams, ethanol-exposed fetuses were hypoglycaemic at embryonic day 20. Ethanol-exposed offspring were normoglycaemic and normoinsulinaemic under basal fasting conditions and had normal pancreatic β-cell mass at postnatal day 30. However, during a glucose tolerance test, male ethanol-exposed offspring were hyperinsulinaemic with increased first phase insulin secretion. Female ethanol-exposed offspring displayed enhanced glucose clearance during an insulin challenge. Body composition and hepatic, muscle and adipose tissue metabolic gene expression levels at eight months were not altered by prenatal ethanol exposure. Low-moderate chronic prenatal ethanol exposure has subtle, sex specific effects on glucose homeostasis in the young adult rat. As aging is associated with glucose dysregulation, further studies will clarify the long lasting effects of prenatal ethanol exposure.