42 research outputs found
A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier
While the accuracy-fairness trade-off has been frequently observed in the
literature of fair machine learning, rigorous theoretical analyses have been
scarce. To demystify this long-standing challenge, this work seeks to develop a
theoretical framework by characterizing the shape of the accuracy-fairness
trade-off Pareto frontier (FairFrontier), determined by a set of all optimal
Pareto classifiers that no other classifiers can dominate. Specifically, we
first demonstrate the existence of the trade-off in real-world scenarios and
then propose four potential categories to characterize the important properties
of the accuracy-fairness Pareto frontier. For each category, we identify the
necessary conditions that lead to corresponding trade-offs. Experimental
results on synthetic data suggest insightful findings of the proposed
framework: (1) When sensitive attributes can be fully interpreted by
non-sensitive attributes, FairFrontier is mostly continuous. (2) Accuracy can
suffer a \textit{sharp} decline when over-pursuing fairness. (3) Eliminate the
trade-off via a two-step streamlined approach. The proposed research enables an
in-depth understanding of the accuracy-fairness trade-off, pushing current fair
machine-learning research to a new frontier
Integrated Sensing and Communication based Outdoor Multi-Target Detection, Tracking and Localization in Practical 5G Networks
The 6th generation (6G) wireless networks will likely to support a variety of
capabilities beyond communication, such as sensing and localization, through
the use of communication networks empowered by advanced technologies.
Integrated sensing and communication (ISAC) has been recognized as a critical
technology as well as an usage scenario for 6G, as widely agreed by leading
global standardization bodies. ISAC utilizes communication infrastructure and
devices to provide the capability of sensing the environment with high
resolution, as well as tracking and localizing moving objects nearby. Meeting
both the requirements for communication and sensing simultaneously, ISAC based
approaches celebrate the advantages of higher spectral and energy efficiency
compared to two separate systems to serve two purposes, and potentially lower
costs and easy deployment. A key step towards the standardization and
commercialization of ISAC is to carry out comprehensive field trials in
practical networks, such as the 5th generation (5G) network, to demonstrate its
true capacities in practical scenarios. In this paper, an ISAC based outdoor
multi-target detection, tracking and localization approach is proposed and
validated in 5G networks. The proposed system comprises of 5G base stations
(BSs) which serve nearby mobile users normally, while accomplishing the task of
detecting, tracking and localizing drones, vehicles and pedestrians
simultaneously. Comprehensive trial results demonstrate the relatively high
accuracy of the proposed method in practical outdoor environment when tracking
and localizing single targets and multiple targets.Comment: Accepted by an open access journal (appearing on IEEEXplore soon
Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning
Background: Non-alcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver pathologies. However, no medical treatment has been approved for the treatment of NAFLD. In our previous study, we found that PKLR could be a potential target for treatment of NALFD. Here, we investigated the effect of PKLR in in vivo model and performed drug repositioning to identify a drug candidate for treatment of NAFLD. Methods: Tissue samples from liver, muscle, white adipose and heart were obtained from control and PKLR knockout mice fed with chow and high sucrose diets. Lipidomics as well as transcriptomics analyses were conducted using these tissue samples. In addition, a computational drug repositioning analysis was performed and drug candidates were identified. The drug candidates were both tested in in vitro and in vivo models to evaluate their toxicity and efficacy. Findings: The Pklr KO reversed the increased hepatic triglyceride level in mice fed with high sucrose diet and partly recovered the transcriptomic changes in the liver as well as in other three tissues. Both liver and white adipose tissues exhibited dysregulated circadian transcriptomic profiles, and these dysregulations were reversed by hepatic knockout of Pklr. In addition, 10 small molecule drug candidates were identified as potential inhibitor of PKLR using our drug repositioning pipeline, and two of them significantly inhibited both the PKLR expression and triglyceride level in in vitro model. Finally, the two selected small molecule drugs were evaluated in in vivo rat models and we found that these drugs attenuate the hepatic steatosis without side effect on other tissues. Interpretation: In conclusion, our study provided biological insights about the critical role of PKLR in NAFLD progression and proposed a treatment strategy for NAFLD patients, which has been validated in preclinical studies. Funding: ScandiEdge Therapeutics and Knut and Alice Wallenberg Foundation
Reactivity of Hydrogen-Helium and Hydrogen-Nitrogen Mixtures at High Pressures
Through a series of Raman spectroscopy studies, we investigate the behaviour
of hydrogen-helium and hydrogen-nitrogen mixtures at high pressure across wide
ranging concentrations. We find that there is no evidence of chemical
association, miscibility, nor any demixing of hydrogen and helium in the solid
state up to pressures of 250 GPa at 300 K. In contrast, we observe the
formation of concentration-dependent N-H van der Waals solids, which
react to form N-H bonded compounds above 50 GPa. Through this combined study,
we can demonstrate that the recently claimed chemical association of H-He
can be attributed to significant N contamination and subsequent formation
of N-H compounds.Comment: 16 pages, 8 figures including Supplementary Materia
Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity
Heterogeneity in gene expression and epigenetic states exists across individual cells. Here, the authors develop scCAT-seq, a technique for simultaneously performing ATAC-seq and RNA-seq within the same single cell
AKR1C3 in carcinomas: from multifaceted roles to therapeutic strategies
Aldo-Keto Reductase Family 1 Member C3 (AKR1C3), also known as type 5 17ÎČ-hydroxysteroid dehydrogenase (17ÎČ-HSD5) or prostaglandin F (PGF) synthase, functions as a pivotal enzyme in androgen biosynthesis. It catalyzes the conversion of weak androgens, estrone (a weak estrogen), and PGD2 into potent androgens (testosterone and 5α-dihydrotestosterone), 17ÎČ-estradiol (a potent estrogen), and 11ÎČ-PGF2α, respectively. Elevated levels of AKR1C3 activate androgen receptor (AR) signaling pathway, contributing to tumor recurrence and imparting resistance to cancer therapies. The overexpression of AKR1C3 serves as an oncogenic factor, promoting carcinoma cell proliferation, invasion, and metastasis, and is correlated with unfavorable prognosis and overall survival in carcinoma patients. Inhibiting AKR1C3 has demonstrated potent efficacy in suppressing tumor progression and overcoming treatment resistance. As a result, the development and design of AKR1C3 inhibitors have garnered increasing interest among researchers, with significant progress witnessed in recent years. Novel AKR1C3 inhibitors, including natural products and analogues of existing drugs designed based on their structures and frameworks, continue to be discovered and developed in laboratories worldwide. The AKR1C3 enzyme has emerged as a key player in carcinoma progression and therapeutic resistance, posing challenges in cancer treatment. This review aims to provide a comprehensive analysis of AKR1C3âs role in carcinoma development, its implications in therapeutic resistance, and recent advancements in the development of AKR1C3 inhibitors for tumor therapies
Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.
Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ââSpatioTemporal Omics Consortiumââ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would
like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen,
China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center
for Excellence in Brain Science and Intelligence Technology, Chinese Academy
of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute,
Boston, USA) for their help. This work was supported by the grant of Top Ten
Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory
of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu
was supported by the National Natural Science Foundation of China
(31900466) and Miguel A. Estebanâs laboratory at the Guangzhou Institutes of
Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research
Foundation (2021B1515120075).S
Cell transcriptomic atlas of the non-human primate Macaca fascicularis.
Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M.âfascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding
Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland
Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for
technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene
expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi
from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing
reagents. This work was supported by the Shenzhen Basic Research Project for Excellent
Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics
(ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In
addition, L.L. was supported by the National Natural Science Foundation of China (31900466),
Y. Hou was supported by the Natural Science Foundation of Guangdong Province
(2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award
(419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences
(XDA16030502), a Chinese Academy of SciencesâJapan Society for the Promotion of Science
joint research project (GJHZ2093), the National Natural Science Foundation of China
(92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation
(2021B1515120075). M.L. was supported by the National Key Research and Development
Program of China (2021YFC2600200).S