المؤلفون: Lyla Atta, Kalen Clifton, Manjari Anant, Gohta Aihara, Jean Fan

المصدر: Genome Biology, Vol 25, Iss 1, Pp 1-25 (2024)

مصطلحات موضوعية: Normalization, Scaling factor, Spatial transcriptomics, Differential expression, Biology (General), QH301-705.5, Genetics, QH426-470

الوصف: Abstract Background Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals. Results Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue’s component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization. Conclusions We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1474-760XTest

الوصول الحر: https://doaj.org/article/01f2c02da4014bcb949aa202a018ac3eTest

المؤلفون: Kaitlin M. Stouffer, Alain Trouvé, Laurent Younes, Michael Kunst, Lydia Ng, Hongkui Zeng, Manjari Anant, Jean Fan, Yongsoo Kim, Xiaoyin Chen, Mara Rue, Michael I. Miller

المصدر: Nature Communications, Vol 15, Iss 1, Pp 1-22 (2024)

مصطلحات موضوعية: Science

الوصف: Abstract This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2041-1723Test

الوصول الحر: https://doaj.org/article/437796a99edd427faec35dd8a7032d20Test

المؤلفون: Kalen Clifton, Manjari Anant, Gohta Aihara, Lyla Atta, Osagie K. Aimiuwu, Justus M. Kebschull, Michael I. Miller, Daniel Tward, Jean Fan

المصدر: Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)

مصطلحات موضوعية: Science

الوصف: Abstract Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we develop STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. We show that STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over landmark-based affine alignments. Applying STalign to align ST datasets of the mouse brain to the 3D common coordinate framework from the Allen Brain Atlas, we highlight how STalign can be used to lift over brain region annotations and enable the interrogation of compositional heterogeneity across anatomical structures. STalign is available as an open-source Python toolkit at https://github.com/JEFworks-Lab/STalignTest and as Supplementary Software with additional documentation and tutorials available at https://jef.works/STalignTest .

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2041-1723Test

الوصول الحر: https://doaj.org/article/74619ed8e49c4d0184bee33dbf658bc3Test

المؤلفون: Sepideh Gharaie, Kyungho Lee, Kathleen Noller, Emily K. Lo, Brendan Miller, Hyun Jun Jung, Andrea M. Newman-Rivera, Johanna T. Kurzhagen, Nirmish Singla, Paul A. Welling, Jean Fan, Patrick Cahan, Sanjeev Noel, Hamid Rabb

المصدر: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)

مصطلحات موضوعية: Medicine, Science

الوصف: Abstract T cells are important in the pathogenesis of acute kidney injury (AKI), and TCR+CD4-CD8- (double negative-DN) are T cells that have regulatory properties. However, there is limited information on DN T cells compared to traditional CD4+ and CD8+ cells. To elucidate the molecular signature and spatial dynamics of DN T cells during AKI, we performed single-cell RNA sequencing (scRNA-seq) on sorted murine DN, CD4+, and CD8+ cells combined with spatial transcriptomic profiling of normal and post AKI mouse kidneys. scRNA-seq revealed distinct transcriptional profiles for DN, CD4+, and CD8+ T cells of mouse kidneys with enrichment of Kcnq5, Klrb1c, Fcer1g, and Klre1 expression in DN T cells compared to CD4+ and CD8+ T cells in normal kidney tissue. We validated the expression of these four genes in mouse kidney DN, CD4+ and CD8+ T cells using RT-PCR and Kcnq5, Klrb1, and Fcer1g genes with the NIH human kidney precision medicine project (KPMP). Spatial transcriptomics in normal and ischemic mouse kidney tissue showed a localized cluster of T cells in the outer medulla expressing DN T cell genes including Fcer1g. These results provide a template for future studies in DN T as well as CD4+ and CD8+ cells in normal and diseased kidneys.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2045-2322Test

الوصول الحر: https://doaj.org/article/6ca1129e3f5c4b4882e9a4714dae46b0Test

المؤلفون: Jean Fan Yang, Wei Shi, Erica Wen Chen, Ben Nanfeng Luo, Jenny Zejun Zhao, Zhechen Yin, Jiaqi Tao

المصدر: Frontiers in Psychology, Vol 14 (2023)

مصطلحات موضوعية: flexible employment, outsourcing, perceived insider status, job value status, job performance, Psychology, BF1-990

الوصف: IntroductionOutsourcing, one of the nonstandard employment forms, has been increasingly popular with a wide variety of industries and employers. However, much less is known about its consequences at the employee level, especially relative to standard-employed colleagues. Drawing on social categorization theory and the human resource architecture model, the study was to investigate how outsourced (vs. standard) employment form impacts employees’ perceived insider status and then job performance, as well as the moderating role of job value status.MethodsTo examine these effects, we collected two-wave and multi-source questionnaires from a sample of 147 outsourced employees, 279 standard employees, and their immediate supervisors. And interviews with 31 employees, their supervisors, and human resources personnel provided further support for our findings.ResultsThe results showed that relative to standard employees, outsourced employees were lower in perceived insider status and indirectly worse in job performance. Furthermore, both the comparative effects were stronger among core-status than peripheral-status employees.DiscussionOur study contributes to outsourcing and widely nonstandard employment literature, bringing the research focus from employers to outsourced employees’ psychological and behavioral consequences. Also, we extended literature on the human resource architecture, through a deeper investigation on the issue of employment form-job value status (mis)matching as well as its impacts on employees.

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1159022/fullTest; https://doaj.org/toc/1664-1078Test

الوصول الحر: https://doaj.org/article/017f8e7c521b410ebea9e74400499b5fTest

المؤلفون: Wei Shi, Jean Fan Yang, Tianyi Sun, Yizhi Zeng, Zijun Cai

المصدر: Frontiers in Psychology, Vol 14 (2023)

مصطلحات موضوعية: age, proactive work behavior, intrinsic motivation, career aspiration, emotional exhaustion, Psychology, BF1-990

الوصف: Today, there is an increasingly aging workforce. Previous studies have examined whether aged people exhibit more positive attitudes, better health, and better performance. However, the relationship between age and proactive work behavior has seldom been examined, which is unfortunate since organizations need employee proactivity to deal with uncertainty and unpredictability. Based on socioemotional selectivity theory, we propose that age might be positively related to proactive work behavior through intrinsic motivation and emotional exhaustion because older people tend to manage their emotions and obtain intrinsic enjoyment. But age might be negatively related to proactive work behavior through career aspiration because older people focus less on future development. With a sample of 393 people, we revealed intrinsic motivation and career aspiration. The findings could help us better understand how age is related to organizational outcomes and individual differences in proactive work behavior. They could also further reduce age-related discrimination and encourage organizations to manage older people in wise and better ways.

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1154861/fullTest; https://doaj.org/toc/1664-1078Test

الوصول الحر: https://doaj.org/article/33c9c20617ec4942a07573e6daa7a263Test

المؤلفون: Brendan F. Miller, Feiyang Huang, Lyla Atta, Arpan Sahoo, Jean Fan

المصدر: Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)

مصطلحات موضوعية: Science

الوصف: Identifying cell-type-specific spatial patterns in ST data is critical for understanding tissue organization but current methods rely on external references. Here the authors develop a reference-free method to effectively recover cell-type transcriptional profiles and proportions.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2041-1723Test

الوصول الحر: https://doaj.org/article/8169b376adb24eae99a8f90a6c88b8d9Test

المؤلفون: Lyla Atta, Jean Fan

المصدر: Nature Communications, Vol 12, Iss 1, Pp 1-5 (2021)

مصطلحات موضوعية: Science

الوصف: Spatially resolved transcriptomic data demand new computational analysis methods to derive biological insights. Here, we comment on these associated computational challenges as well as highlight the opportunities for standardized benchmarking metrics and data-sharing infrastructure in spurring innovation moving forward.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2041-1723Test

الوصول الحر: https://doaj.org/article/30b39018bedf4a9f9b290b200f3c9857Test

المؤلفون: Jean Fan, Kamil Slowikowski, Fan Zhang

المصدر: Experimental and Molecular Medicine, Vol 52, Iss 9, Pp 1452-1465 (2020)

مصطلحات موضوعية: Medicine, Biochemistry, QD415-436

الوصف: Cancer: analyzing the RNA of single cells By analyzing gene expression patterns in individual tumor cells, researchers can gain patient-specific insights that might inform more effective cancer treatment. Tumors are highly dynamic and heterogeneous collections of cells. Single-cell transcriptomics techniques can offer a valuable window into that complexity but only if the appropriate computational tools are used to analyze the data. Jean Fan of Harvard University, Cambridge, USA, and colleagues have reviewed some of these computational strategies and how they can be employed in cancer research. Single-cell analysis algorithms, for example, can reveal characteristics that distinguish healthy cells from cancerous cells, or indicate how the cells within the tumor may be communicating with each other to promote malignant growth. These are still new technologies, however, and the authors highlight the limitations of the conclusions that can currently be drawn from such analyses.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1226-3613Test; https://doaj.org/toc/2092-6413Test

الوصول الحر: https://doaj.org/article/4fc938ab89fd4687afb48f26f083691cTest

المؤلفون: Cara Haymaker, Aung Naing, Shubham Pant, Minal Barve, Dae Won Kim, Richard Kim, Melissa Johnson, Marya Chaney, Robert Wolff, Jean Fan, Byung Ha Lee, NgocDiep Le, Sara Ferrando-Martinez, Hirva Mamdani

المصدر: Journal for ImmunoTherapy of Cancer, Vol 9, Iss Suppl 2 (2021)

مصطلحات موضوعية: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2051-1426Test

الوصول الحر: https://doaj.org/article/1b86d5d524b24ac796db83a3f7cc63ceTest