Publications by authors named "Yike Shen"

Article Synopsis
  • - The study investigates the impact of metal/element exposures on the gut microbiome in children aged 8 to 12, exploring the relationships between 19 different stool metal concentrations and microbiome profiles within a cohort of 116 participants from the GESTE study.
  • - Significant associations were found, such as positive correlations between zinc (Zn) and certain microbiome species, while cadmium (Cd) was linked to declines in specific gut bacteria, indicating that metal exposure could affect the composition of the gut microbiome.
  • - The research also identified 490 functional pathways related to microbiome activities, suggesting that these metal exposures could influence crucial processes like amino acid synthesis and carbohydrate degradation, highlighting the need for further research on their implications
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  • Coronary heart disease (CHD) is a major health issue in the U.S., and improved prediction models could help in early detection and intervention.
  • Researchers developed a deep learning autoencoder survival analysis model (AESurv) that analyzes DNA methylation and clinical data to predict CHD events more accurately.
  • The AESurv model outperformed traditional survival analysis models in two studies, showing strong potential for improving early CHD prediction and aiding healthcare professionals in managing patient care.
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  • The study investigates how high-altitude hypoxia affects the pharmacokinetics (how the body processes) of metformin, a common diabetes medication, in patients with Type 2 diabetes (T2DM).
  • 85 patients were divided into two groups based on altitude: one at 1,500 meters and another at 3,800 meters, with blood samples collected to analyze metformin levels using advanced chromatography techniques.
  • Results showed significant differences in pharmacokinetic parameters between the two groups, indicating that altitude and age influence metformin's distribution and clearance, while the drug's efficacy in controlling blood sugar levels remained comparable.
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  • Contemporary environmental health sciences utilize extensive studies to assess how environmental factors and behaviors impact disease risk over time with various cohorts.
  • The proposed Cohort Network employs a multilayer knowledge graph to organize and visualize connections between exposures and health outcomes, making it easier to analyze large volumes of data from multiple publications.
  • By applying this network to studies from the VA Normative Aging Study, researchers were able to identify significant connections, such as those between air pollution and lung function, which could help generate new research hypotheses and enhance knowledge sharing in the field.
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Understanding how bacterial community assembly and antibiotic resistance genes (ARGs) respond to antibiotic exposure is essential to deciphering the ecological risk of anthropogenic antibiotic pollution in soils. In this study, three loam soils with different land management (unmanured golf course, dairy-manured pasture, and swine-manured cornfield) were spiked with a mixture of 11 antibiotics at the initial concentration of 100 and 1000 μg kg for each antibiotic and incubated over 132 days, mimicking a scenario of pulse disturbance and recovery in soils, with unspiked soil samples as the control treatment. The Infer Community Assembly Mechanisms by Phylogenetic-bin-based null model (iCAMP) analysis demonstrated that drift and dispersal limitation contributed to 57%-65% and 16%-25%, and homogeneous selection 12%-16% of soil bacterial community assembly.

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  • - This study investigates the impact of air pollutants, specifically particulate matter (PM) and nitrogen oxides (NO), on bone mineral density (BMD) in postmenopausal women, utilizing data from the Women's Health Initiative Study.
  • - Using advanced statistical methods, researchers found that increased exposure to these pollutants over 1 to 5 years was linked to a significant decrease in BMD, particularly in the lumbar spine region.
  • - The results emphasize that higher levels of air pollution, particularly from nitrogen oxides, contribute to bone loss in postmenopausal women, indicating a need for further research and public health strategies.
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The explosion of microbiome research over the past decade has shed light on the various ways that external factors interact with the human microbiome to drive health and disease. Each individual is exposed to more than 300 environmental chemicals every day. Accumulating evidence indicates that the microbiome is involved in the early response to environmental toxicants and biologically mediates their adverse effects on human health.

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Background: In the Checkmate9ER trial, first-line treatment with nivolumab combined with cabozantinib (NI + CA) has shown efficacy for advanced renal cell carcinoma. This study aims to evaluate the impact of the health and economic outcomes of NI + CA in China.

Methods: Clinical efficacy data were derived from pivotal phase III CheckMate 9ER trial.

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Pregnant individuals are exposed to acetaminophen and caffeine, but it is unknown how these exposures interact with the developing gut microbiome. We aimed to determine whether acetaminophen and/or caffeine relate to the childhood gut microbiome and whether features of the gut microbiome alter the relationship between acetaminophen/caffeine and neurodevelopment. Forty-nine and 85 participants provided meconium and stool samples at 6-7, respectively, for exposure and microbiome assessment.

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Pesticide dissipation half-life in plants is an important factor to assessing environmental fate of pesticides and establishing pre-harvest intervals critical to good agriculture practices. However, empirically measured pesticide dissipation half-lives are highly variable and the accurate prediction with models is challenging. This study utilized a dataset of pesticide dissipation half-lives containing 1363 datapoints, 311 pesticides, 10 plant types, and 4 plant component classes.

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In silico prediction of chemical ecotoxicity (HC) represents an important complement to improve in vivo and in vitro toxicological assessment of manufactured chemicals. Recent application of machine learning models to predict chemical HC yields variable prediction performance that depends on effectively learning chemical representations from high-dimension data. To improve HC prediction performance, we developed an autoencoder model by learning latent space chemical embeddings.

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Background: The gut microbiome is important in modulating health in childhood. Metal exposures affect multiple health outcomes, but their ability to modify bacterial communities in children is poorly understood.

Objectives: We assessed the associations of childhood and perinatal blood metal levels with childhood gut microbiome diversity, structure, species, gene family-inferred species, and potential pathway alterations.

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Root concentration factor (RCF) is an important characterization parameter to describe accumulation of organic contaminants in plants from soils in life cycle impact assessment (LCIA) and phytoremediation potential assessment. However, building robust predictive models remains challenging due to the complex interactions among chemical-soil-plant root systems. Here we developed end-to-end machine learning models to devolve the complex molecular structure relationship with RCF by training on a unified RCF data set with 341 data points covering 72 chemicals.

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Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain. However, traditional empirical or mechanistic models frequently show variable performance due to complex interactions among contaminants, soils, and plants. Thus, in this study different machine learning algorithms were compared and applied to predict root concentration factors (RCFs) based on a dataset comprising 57 chemicals and 11 crops, followed by comparison with a traditional linear regression model as the benchmark.

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Abstract: Food labeling is one approach to encourage safe, healthy, and sustainable dietary practices. Consumer buy and pay preferences for specially labeled food products (e.g.

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Bacteria and antibiotic resistance genes (ARGs) in vegetables may influence human gut microbiome and ultimately human health. However, little is known about how vegetable microbiomes and ARGs respond to exposure of anthropogenic antibiotics from crop irrigation water. This study investigated bacterial community assembly and ARG profiles in lettuce (Lactuca sativa) shoots and roots, rhizosphere soil, and bulk soil irrigated with antibiotics-containing water, using 16S rRNA amplicon sequencing and high throughput real-time qPCR, respectively.

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Plant uptake of antibiotics raises serious food safety concerns. Measurements and predictions of antibiotic uptake by plants are often based on root concentration factors (RCF) determined using antibiotic concentrations in bulk soil (RCF) rather than in rhizosphere soil (RCF) where root uptake actually occurs. This study investigated the fate and transport of nine antibiotics in the continuum of bulk soil, rhizosphere soil, roots and shoots of lettuce (Lactuca sativa) under soil-surface irrigation.

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New classes of emerging contaminants such as pharmaceuticals, antibiotic resistant bacteria (ARB), and antibiotic resistance genes (ARGs) have received increasing attention due to rapid increases of their abundance in agroecosystems. As food consumption is a direct exposure pathway of pharmaceuticals, ARB, and ARGs to humans, it is important to understand changes of bacterial communities and ARG profiles in food crops produced with contaminated soils and waters. This study examined the level and type of ARGs and bacterial community composition in soil, and lettuce shoots and roots under soil-surface or overhead irrigation with pharmaceuticals-contaminated water, using high throughput qPCR and 16S rRNA amplicon sequencing techniques, respectively.

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Background: Hickory (Carya cathayensis), a woody plant with high nutritional and economic value, is widely planted in China. Due to its long juvenile phase, grafting is a useful technique for large-scale cultivation of hickory. To reveal the molecular mechanism during the graft process, we sequenced the transcriptomes of graft union in hickory.

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