Perception and the potential of traditional chinese medicine.

This project examines people's perception of traditional chinese medicine in relation to the recent developments within the chinese medicine industry

Probably Approximate Shapley Fairness with Applications in Machine Learning

The Shapley value (SV) is adopted in various scenarios in machine learning (ML), including data valuation, agent valuation, and feature attribution, as it satisfies their fairness requirements. However, as exact SVs are infeasible to compute in practice, SV estimates are approximated instead. This approximation step raises an important question: do the SV estimates preserve the fairness guarantees of exact SVs? We observe that the fairness guarantees of exact SVs are too restrictive for SV estimates. Thus, we generalise Shapley fairness to probably approximate Shapley fairness and propose fidelity score, a metric to measure the variation of SV estimates, that determines how probable the fairness guarantees hold. Our last theoretical contribution is a novel greedy active estimation (GAE) algorithm that will maximise the lowest fidelity score and achieve a better fairness guarantee than the de facto Monte-Carlo estimation. We empirically verify GAE outperforms several existing methods in guaranteeing fairness while remaining competitive in estimation accuracy in various ML scenarios using real-world datasets

Trans-interaction of risk loci 6p24.1 and 10q11.21 is associated with endothelial damage in coronary artery disease

Background and aims: Single nucleotide polymorphism rs6903956 has been identified as one of the genetic risk factors for coronary artery disease (CAD). However, rs6903956 lies in a non-coding locus on chromosome 6p24.1. We aim to interrogate the molecular basis of 6p24.1 containing rs6903956 risk alleles in endothelial disease biology. Methods and Results: We generated induced pluripotent stem cells (iPSCs) from CAD patients (AA risk genotype at rs6903956) and non-CAD subjects (GG non-risk genotype at rs6903956). CRISPR-Cas9-based deletions (Δ63- 89bp) on 6p24.1, including both rs6903956 and a short tandem repeat variant rs140361069 in linkage disequilibrium, were performed to generate isogenic iPSC-derived endothelial cells. Edited CAD endothelial cells, with removal of ‘A’ risk alleles, exhibited a global transcriptional downregulation of pathways relating to abnormal vascular physiology and activated endothelial processes. A CXC chemokine ligand on chromosome 10q11.21, CXCL12, was uncovered as a potential effector gene in CAD endothelial cells. Underlying this effect was the preferential inter-chromosomal interaction of 6p24.1 risk locus to a weak promoter of CXCL12, confirmed by chromatin conformation capture assays on our iPSC-derived endothelial cells. Functionally, risk genotypes AA/AG at rs6903956 were associated significantly with elevated levels of circulating damaged endothelial cells in CAD patients. Circulating endothelial cells isolated from patients with risk genotypes AA/AG were also found to have 10 folds higher CXCL12 transcript copies/cell than those with non-risk genotype GG. Conclusions: Our study reveals the trans-acting impact of 6p24.1 with another CAD locus on 10q11.21 and is associated with intensified endothelial injury.Ministry of Education (MOE)Nanyang Technological UniversityNational Research Foundation (NRF)Published versionThe National Research Foundation, Singapore (Project Number 370062002) funded the Singapore Coronary Artery Disease Genetics Study (SCADGENS) and genotyping of the participants. The team from Nanyang Technological University Singapore was funded by an Academic Research Fund Tier 1 grant (2018-T1-001-030) from the Ministry of Education, Singapore, Human Frontier Science Program Research Grant (RGY0069/2019), and the Nanyang Assistant Professorship. K.Y. T. is supported by NTU Research Scholarship. H.H.L. is supported by the Institute of Molecular and Cell Biology (IMCB) Scientific Staff Development Award (SSDA) for her part-time Ph.D. A.K.K.T. is supported by IMCB, A*STAR, Precision Medicine and Personalised Therapeutics Joint Research Grant 2019, the 2nd A*STAR-AMED Joint Grant Call 192B9002 and NUHSRO/2021/035/NUSMed/04/NUS-IMCB Joint Lab/LOA

Prioritization of Post-Myocardial Infarction Heart Failure Targets Using Large-Scale Plasma Proteomics and Genome-Wide Single-Cardiac Cell Transcriptomics

Scientific Sessions of the American-Heart-Association14

Phenotyping Diabetes Mellitus on Aggregated Electronic Health Records from Disparate Health Systems

Background: Identifying patients with diabetes mellitus (DM) is often performed in epidemiological studies using electronic health records (EHR), but currently available algorithms have features that limit their generalizability. Methods: We developed a rule-based algorithm to determine DM status using the nationally aggregated EHR database. The algorithm was validated on two chart-reviewed samples (n = 2813) of (a) patients with atrial fibrillation (AF, n = 1194) and (b) randomly sampled hospitalized patients (n = 1619). Results: DM diagnosis codes alone resulted in a sensitivity of 77.0% and 83.4% in the AF and random hospitalized samples, respectively. The proposed algorithm combines blood glucose values and DM medication usage with diagnostic codes and exhibits sensitivities between 96.9% and 98.0%, while positive predictive values (PPV) ranged between 61.1% and 75.6%. Performances were comparable across sexes, but a lower specificity was observed in younger patients (below 65 versus 65 and above) in both validation samples (75.8% vs. 90.8% and 60.6% vs. 88.8%). The algorithm was robust for missing laboratory data but not for missing medication data. Conclusions: In this nationwide EHR database analysis, an algorithm for identifying patients with DM has been developed and validated. The algorithm supports quantitative bias analyses in future studies involving EHR-based DM studies

Prioritizing Candidates of Post-Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics

10.1161/CIRCULATIONAHA.119.045158CIRCULATION142151408-142

Maritime Interdiction Operations in Logistically Barren Environments

Includes supplementary materialThis report contains analysis that shows that existing technology exists to improve Maritime Interdiction Operations (MIO) by approximately 30%. Furthermore, analysis contained herein will aid MIO planning for future operations. Since MIOs are an inherently dangerous, but necessary activity with far reaching implications to theater political and economic dynamics, this improvement is of great interest. MIO is a Naval solution to the problems of smuggling weapons, explosives, people and narcotics. MIO, when employed correctly has the potential to save lives and limit economic/political damage.N