Within-group fairness: A guidance for more sound between-group fairness

As they have a vital effect on social decision-making, AI algorithms not only should be accurate and but also should not pose unfairness against certain sensitive groups (e.g., non-white, women). Various specially designed AI algorithms to ensure trained AI models to be fair between sensitive groups have been developed. In this paper, we raise a new issue that between-group fair AI models could treat individuals in a same sensitive group unfairly. We introduce a new concept of fairness so-called within-group fairness which requires that AI models should be fair for those in a same sensitive group as well as those in different sensitive groups. We materialize the concept of within-group fairness by proposing corresponding mathematical definitions and developing learning algorithms to control within-group fairness and between-group fairness simultaneously. Numerical studies show that the proposed learning algorithms improve within-group fairness without sacrificing accuracy as well as between-group fairness

3D Printed Masks and Transfer Stamping Process to Enable the Fabrication of the Hemispherical Organic Photodiodes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138391/1/admt201700090_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138391/2/admt201700090.pd

A lab-on-a-disc platform enables serial monitoring of individual CTCs associated with tumor progression during EGFR-targeted therapy for patients with NSCLC

Rationale: Unlike traditional biopsy, liquid biopsy, which is a largely non-invasive diagnostic and monitoring tool, can be performed more frequently to better track tumors and mutations over time and to validate the efficiency of a cancer treatment. Circulating tumor cells (CTCs) are considered promising liquid biopsy biomarkers; however, their use in clinical settings is limited by high costs and a low throughput of standard platforms for CTC enumeration and analysis. In this study, we used a label-free, high-throughput method for CTC isolation directly from whole blood of patients using a standalone, clinical setting-friendly platform. Methods: A CTC-based liquid biopsy approach was used to examine the efficacy of therapy and emergent drug resistance via longitudinal monitoring of CTC counts, DNA mutations, and single-cell-level gene expression in a prospective cohort of 40 patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Results: The change ratio of the CTC counts was associated with tumor response, detected by CT scan, while the baseline CTC counts did not show association with progression-free survival or overall survival. We achieved a 100% concordance rate for the detection of EGFR mutation, including emergence of T790M, between tumor tissue and CTCs. More importantly, our data revealed the importance of the analysis of the epithelial/mesenchymal signature of individual pretreatment CTCs to predict drug responsiveness in patients. Conclusion: The fluid-assisted separation technology disc platform enables serial monitoring of CTC counts, DNA mutations, as well as unbiased molecular characterization of individual CTCs associated with tumor progression during targeted therapy

Grading system for periodontitis by analyzing levels of periodontal pathogens in saliva

Periodontitis is an infectious disease that is associated with microorganisms that colonize the tooth surface. Clinically, periodontal condition stability reflects dynamic equilibrium between bacterial challenge and host response. Therefore, periodontal pathogen assessment can assist in the early detection of periodontitis. Here we developed a grading system called the periodontal pathogen index (PPI) by analyzing the copy numbers of multiple pathogens both in healthy and chronic periodontitis patients. We collected 170 mouthwash samples (64 periodontally healthy controls and 106 chronic periodontitis patients) and analyzed the salivary 16S rRNA levels of nine pathogens using multiplex, quantitative real-time polymerase chain reaction. Except for Aggregatibacter actinomycetemcomitans, copy numbers of all pathogens were significantly higher in chronic periodontitis patients. We classified the samples based on optimal cut-off values with maximum sensitivity and specificity from receiver operating characteristic curve analyses (AUC = 0.91, 95% CI: 0.87-0.96) into four categories of PPI: Healthy (1-40), Moderate (41-60), At Risk (61-80), and Severe (81-100). PPI scores were significantly higher in all chronic periodontitis patients than in the controls (odds ratio: 31.7, 95% CI: 13.41-61.61) and were associated with age, scaling as well as clinical characteristics including clinical attachment level and plaque index. Our PPI grading system can be clinically useful for the early assessment of pathogenic bacterial burden and follow-up monitoring after periodontitis treatment

Genome-wide data from two early Neolithic East Asian individuals dating to 7700 years ago.

Ancient genomes have revolutionized our understanding of Holocene prehistory and, particularly, the Neolithic transition in western Eurasia. In contrast, East Asia has so far received little attention, despite representing a core region at which the Neolithic transition took place independently ~3 millennia after its onset in the Near East. We report genome-wide data from two hunter-gatherers from Devil's Gate, an early Neolithic cave site (dated to ~7.7 thousand years ago) located in East Asia, on the border between Russia and Korea. Both of these individuals are genetically most similar to geographically close modern populations from the Amur Basin, all speaking Tungusic languages, and, in particular, to the Ulchi. The similarity to nearby modern populations and the low levels of additional genetic material in the Ulchi imply a high level of genetic continuity in this region during the Holocene, a pattern that markedly contrasts with that reported for Europe.V.S. was supported by the Gates Cambridge Trust. R.P. was funded by the European Research Council (ERC) starting grant ADNABIOARC (263441) and the Irish Research Council Advanced Research Project Grant from January 2014 to December 2016. M.H. was supported by ERC Consolidator Grant 310763 “GeneFlow.” This work was supported by the Research Fund (1.140113.01) of Ulsan National Institute of Science and Technology to J.B. This work was also supported by the Research Fund (14-BR-SS-03) of Civil-Military Technology Cooperation Program to J.B. and Y.S.C. M.G.-L. was supported by a Biotechnology and Biological Sciences Research Council Doctoral Training Partnerships studentship. A.M. and A.E. were supported by the ERC Consolidator Grant 647787 “LocalAdaptation.” D.G.B. was funded by ERC Investigator grant 295729-CodeX

Examining the Effects of the Built Environment on Travel Mode Choice across Different Age Groups in Seoul using a Random Forest Method

It is important to analyze factors that influence travel mode choice and to predict individual mode choice because this shapes people’s movement and determines their level of mobility. While there have been studies investigating how built-environment elements are associated with travel mode choice, most efforts have neglected evaluating the heterogeneity of effects that the built environment has on travel mode choice across different age groups. This study aims to examine the effects of the built environment in influencing travel mode choice across age groups in Seoul, South Korea, using a random forest approach. Our random forest model demonstrates what factors are important and how they are associated with the effects on travel mode choice. As a result, the built environment has a greater impact on the subway selection for older adults than other age groups and the random forest approach captures non-linear relationships between certain predictors and travel mode choices. Applying this approach to the travel mode choice analysis, we can examine the heterogeneous effects of the built environment on travel mode choice across different age groups

Fully automated, on-site isolation of cfDNA from whole blood for cancer therapy monitoring

The potential utility of circulating tumour DNA (ctDNA) in patient blood for cancer diagnostics and real-time monitoring of disease progression is highly recognized. However, the lack of automated and efficient methods for cell-free DNA (cfDNA) isolation from peripheral blood has remained a challenge for broader acceptance of liquid biopsy in general clinical settings. Here, we demonstrate a lab-on-a-disc system equipped with newly developed, electromagnetically actuated, and reversible diaphragm valves that allows fully automated and rapid (<30 min) isolation of cfDNA from whole blood (>3 ml) to achieve high detection sensitivity by minimizing the degradation of fragile ctDNA as well as contamination of wild-type DNA from abundant blood cells. As a proof of concept study, we used the lab-on-a-disc to isolate cfDNA from patients with non-small cell lung cancer and successfully detected epidermal growth factor receptor gene mutations (L858R, T790M) during targeted drug therapy. The proposed lab-on-a-disc enables a fully automated, rapid, and point-of-care cfDNA enrichment starting from whole blood to facilitate the wide use of liquid biopsy in routine clinical practice

Quantum mechanical/molecular mechanical approach for the simulation of UV-Vis absorption spectra of pi-conjugated oligomers

It is crucial to understand the light absorption features and electronic structures of conjugated organic materials for their optoelectronic applications. However, neither reliable interpretations of reported ultraviolet-visible (UV-vis) absorption spectra nor correct predictions of new organic materials have been made because of the absence of proper calculation methods. To date, excited-state quantum chemical calculations, such as configuration interaction singles (CIS) and time-dependent density functional theory (TDDFT), have provided such information by overlooking the facts that many conformational isomers of conjugated organic molecules can exist at a given temperature and the resulting distributions of backbone structure can modulate pi-conjugated electronic structures. In this study, we introduced a computational method combining the quantum mechanical/molecular mechanical molecular dynamics simulation (QM/MM MD) and the excited-state electronic structure calculation to include various conformers distributed due to the finite temperature and present a near-perfect simulation of experimentally obtained UV-vis absorption spectra. The simulated UV-vis spectrum of 3,6-bis(5-(benzofuran-2-yl)thiophen-2-yl)-2,5-bis(2-ethylhexyl)pyrrolo[3,4-c]pyrrole-1,4-dione [DPP(TBFu)(2)], a pi-conjugated organic material for organic photovoltaic cells (OPV), shows excellent agreement with its experimental spectrum, and each absorption band is assigned to the different conformers with characteristic excitation energies. We believe that our new method provides an improved interpretation of the electronic structures as well as the conformational variations of pi-conjugated organic materials under ambient environments. (C) 2021 Elsevier B.V. All rights reserved