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  • 1
    In: Neuroscience Informatics, Elsevier BV, Vol. 3, No. 2 ( 2023-06), p. 100131-
    Type of Medium: Online Resource
    ISSN: 2772-5286
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 3102713-1
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  • 2
    Online Resource
    Online Resource
    The American Association of Immunologists ; 2016
    In:  The Journal of Immunology Vol. 196, No. 1_Supplement ( 2016-05-01), p. 127.5-127.5
    In: The Journal of Immunology, The American Association of Immunologists, Vol. 196, No. 1_Supplement ( 2016-05-01), p. 127.5-127.5
    Abstract: MicroRNAs (miRNAs) are tightly regulated in the immune system as aberrant expression of miRNAs often results in hematopoietic malignancies and autoimmune diseases. Previously, elevated levels of miR-27 in T cells isolated from multiple sclerosis patients has been suggested to facilitate disease progression through inhibiting Th2 immunity and promoting pathogenic Th1 responses. Here we show while mice with T cell-specific overexpression of miR-27 harbor dysregulated Th1 responses and develop autoimmune pathology, these disease phenotypes are not driven by miR-27 in effector T cells in a cell autonomous manner but rather resulted from a perturbed regulatory T (Treg) cell compartment. Excessive miR-27 expression in T cells severely impairs thymic Treg cell development and TGFb-mediated conversion of peripheral Treg cells from conventional T (Tconv) cells. Moreover, Treg cells with exaggerated miR-27-mediated gene regulation exhibit diminished homeostatic potential and suppressor function in vivo. Mechanistically, miR-27 represses a subset of genes that play critical roles in controlling multiple aspects of Treg cell biology. Collectively, our data show miR-27 functions as a key regulator in Treg cell development and function and suggest that proper regulation of miR-27 is pivotal to safeguard Treg cell-mediated immunological tolerance.
    Type of Medium: Online Resource
    ISSN: 0022-1767 , 1550-6606
    RVK:
    RVK:
    Language: English
    Publisher: The American Association of Immunologists
    Publication Date: 2016
    detail.hit.zdb_id: 1475085-5
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  • 3
    Online Resource
    Online Resource
    American Society for Clinical Investigation ; 2017
    In:  Journal of Clinical Investigation Vol. 127, No. 2 ( 2017-1-9), p. 530-542
    In: Journal of Clinical Investigation, American Society for Clinical Investigation, Vol. 127, No. 2 ( 2017-1-9), p. 530-542
    Type of Medium: Online Resource
    ISSN: 0021-9738 , 1558-8238
    Language: English
    Publisher: American Society for Clinical Investigation
    Publication Date: 2017
    detail.hit.zdb_id: 2018375-6
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  • 4
    In: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, Wiley, Vol. 15, No. 2 ( 2023-04)
    Abstract: Speech and language changes occur in Alzheimer's disease (AD), but few studies have characterized their longitudinal course. We analyzed open‐ended speech samples from a prodromal‐to‐mild AD cohort to develop a novel composite score to characterize progressive speech changes. Participant speech from the Clinical Dementia Rating (CDR) interview was analyzed to compute metrics reflecting speech and language characteristics. We determined the aspects of speech and language that exhibited significant longitudinal change over 18 months. Nine acoustic and linguistic measures were combined to create a novel composite score. The speech composite exhibited significant correlations with primary and secondary clinical endpoints and a similar effect size for detecting longitudinal change. Our results demonstrate the feasibility of using automated speech processing to characterize longitudinal change in early AD. Speech‐based composite scores could be used to monitor change and detect response to treatment in future research. HIGHLIGHTS Longitudinal speech samples were analyzed to characterize speech changes in early AD. Acoustic and linguistic measures showed significant change over 18 months. A novel speech composite score was computed to characterize longitudinal change. The speech composite correlated with primary and secondary trial endpoints. Automated speech analysis could facilitate remote, high frequency monitoring in AD.
    Type of Medium: Online Resource
    ISSN: 2352-8729 , 2352-8729
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2832898-X
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  • 5
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2016
    In:  Bioinformatics Vol. 32, No. 17 ( 2016-09-01), p. i658-i664
    In: Bioinformatics, Oxford University Press (OUP), Vol. 32, No. 17 ( 2016-09-01), p. i658-i664
    Abstract: As an increasing amount of protein–protein interaction (PPI) data becomes available, their computational interpretation has become an important problem in bioinformatics. The alignment of PPI networks from different species provides valuable information about conserved subnetworks, evolutionary pathways and functional orthologs. Although several methods have been proposed for global network alignment, there is a pressing need for methods that produce more accurate alignments in terms of both topological and functional consistency. Results In this work, we present a novel global network alignment algorithm, named ModuleAlign, which makes use of local topology information to define a module-based homology score. Based on a hierarchical clustering of functionally coherent proteins involved in the same module, ModuleAlign employs a novel iterative scheme to find the alignment between two networks. Evaluated on a diverse set of benchmarks, ModuleAlign outperforms state-of-the-art methods in producing functionally consistent alignments. By aligning Pathogen–Human PPI networks, ModuleAlign also detects a novel set of conserved human genes that pathogens preferentially target to cause pathogenesis. Availability http://ttic.uchicago.edu/∼hashemifar/ModuleAlign.html Contact canzar@ttic.edu or j3xu.ttic.edu Supplementary information Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4803 , 1367-4811
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 6
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 44, No. D1 ( 2016-01-04), p. D882-D887
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 7
    In: European Journal of Human Genetics, Springer Science and Business Media LLC, Vol. 29, No. 1 ( 2021-01), p. 122-130
    Type of Medium: Online Resource
    ISSN: 1018-4813 , 1476-5438
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2005160-8
    SSG: 12
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  • 8
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S5 ( 2022-12)
    Abstract: Novel automated tools for analyzing speech and language may provide new insights into Alzheimer’s disease (AD). Although speech and language changes occur in AD and other neurodegenerative diseases, current clinical assessments to monitor these symptoms can be burdensome and may have limited sensitivity. Through analyses of open‐ended naturalistic speech collected from a standardized clinical interview, we developed a novel measure to characterize progressive speech changes in AD. Methods We analyzed Clinical Dementia Rating (CDR) recordings from a subset of 101 participants (58F, 43M, mean age=69 years, SD=7) from the Tauriel trial of semorinemab in prodromal‐to‐mild AD. CDR recordings were collected at the baseline, 6‐month, 12‐month and 18‐month timepoints. Recordings were processed using the Winterlight speech analysis platform which generates 〉 500 acoustic and linguistic features. After controlling for age, sex and level of education, we identified multiple features that had significant linear effects of time (indicating progressive longitudinal change). These speech features were combined into an unweighted composite speech score, which was compared with other clinical endpoints. Results The novel speech composite score included six linguistic features (related to word duration, word frequency, syntactic depth, use of nouns, pronouns and particles) and three acoustic features (related to the power spectrum of the vocal recordings). When compared with clinical endpoints, the speech composite had a similar effect size for detecting longitudinal change (β=0.29) compared to the CDR‐Sum of Boxes (CDR‐SB; β=0.30) and Alzheimer’s Disease Assessment Scale‐Cognitive Subscale (ADAS‐Cog; β=0.22). Notably, it had a significantly greater longitudinal effect size compared to the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS; β=‐0.15, p 〈 0.01) and the language subscales of the ADAS‐Cog measuring word finding difficulty (β=0.12, p 〈 0.01) and spoken language ability (β=0.09, p 〈 0.01). Conclusions Progressive speech changes are detectable in early AD and measurable via automated language processing tools. Speech composite scores have the potential to be more sensitive measures of disease progression and/or treatment response for speech‐related symptoms in AD that do not contribute to additional patient burden. Further validation is needed to replicate these findings and confirm the clinical and neuropathological relevance of this novel measure.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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  • 9
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2014
    In:  Bioinformatics Vol. 30, No. 17 ( 2014-09-01), p. i438-i444
    In: Bioinformatics, Oxford University Press (OUP), Vol. 30, No. 17 ( 2014-09-01), p. i438-i444
    Abstract: Motivation: High-throughput experimental techniques have produced a large amount of protein–protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. Results: This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. Availability: HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip Contact:  jinboxu@gmail.com Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2014
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 10
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2013
    In:  Bioinformatics Vol. 29, No. 13 ( 2013-07-01), p. 1654-1662
    In: Bioinformatics, Oxford University Press (OUP), Vol. 29, No. 13 ( 2013-07-01), p. 1654-1662
    Abstract: Motivation: The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. Results: We present a novel algorithm for the global alignment of protein–protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein–protein interaction networks. Availability: Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. Contact:  sh.arab@modares.ac.ir Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4803 , 1367-4811
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2013
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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