Publications by authors named "Chenlian Fu"

Article Synopsis
  • Researchers are merging unstructured patient data with structured health records to create the MSK-CHORD dataset, consisting of varied cancer types from nearly 25,000 patients at Memorial Sloan Kettering Cancer Center.
  • This dataset allows for in-depth analysis of cancer outcomes using advanced techniques like natural language processing, revealing new relationships that smaller datasets may not show.
  • Using MSK-CHORD for machine learning models, findings suggest that incorporating features from these unstructured texts can better predict patient survival than relying solely on genomic data or cancer staging.
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Oxygen supplementation is life saving for premature infants and for COVID-19 patients but can induce long-term pulmonary injury by triggering inflammation, with xenobiotic-metabolizing CYP enzymes playing a critical role. Murine studies showed that CYP1B1 enhances, while CYP1A1 and CYP1A2 protect from, hyperoxic lung injury. In this study we tested the hypothesis that Cyp1b1-null mice would revert hyperoxia-induced transcriptomic changes observed in WT mice at the transcript and pathway level.

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Motivation: Computational analysis of large-scale metagenomics sequencing datasets have proven to be both incredibly valuable for extracting isolate-level taxonomic, and functional insights from complex microbial communities. However, due to an ever-expanding ecosystem of metagenomics-specific methods and file-formats, designing studies which implement seamless and scalable end-to-end workflows, and exploring the massive amounts of output data have become studies unto themselves. One-click bioinformatics pipelines have helped to organize these tools into targeted workflows, but they suffer from general compatibility and maintainability issues.

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Background: Comorbid anxiety and depression are common and are associated with greater disease burden than either alone. Our recent efforts have identified an association between gut microbiota dysfunction and severity of anxiety and depression. In this follow-up, we applied Differential Co-Expression Analysis (DiffCoEx) to identify potential gut microbiota biomarker(s) candidates of treatment resistance among psychiatric inpatients.

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Background: Aneurysmal subarachnoid hemorrhage (aSAH) leads to a robust systemic inflammatory response. We hypothesized that an early systemic glycolytic shift occurs after aSAH, resulting in a unique metabolic signature and affecting systemic inflammation.

Methods: Control patients and patients with aSAH were analyzed.

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Background: Respiratory tract microbial dysbiosis can exacerbate inflammation and conversely inflammation may cause dysbiosis. Dysbiotic microbiome metabolites may lead to bronchopulmonary dysplasia (BPD). Hyperoxia and lipopolysaccharide (LPS) interaction alters lung microbiome and metabolome, mediating BPD lung injury sequence.

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