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Article ; Online: AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerization.

Fang, Yuan / Bansal, Kushagra / Mostafavi, Sara / Benoist, Christophe / Mathis, Diane

2024 Volume 628, Issue 8007, Page(s) 400–407

Abstract: AIRE is an unconventional transcription factor that enhances the expression of thousands of genes in medullary thymic epithelial cells and promotes clonal deletion or phenotypic diversion of self-reactive T ... ...

Abstract	AIRE is an unconventional transcription factor that enhances the expression of thousands of genes in medullary thymic epithelial cells and promotes clonal deletion or phenotypic diversion of self-reactive T cells
MeSH term(s)	Animals ; Mice ; AIRE Protein/metabolism ; Chromatin/genetics ; Chromatin/metabolism ; DNA Breaks, Double-Stranded ; DNA, Z-Form/chemistry ; DNA, Z-Form/genetics ; DNA, Z-Form/metabolism ; Epithelial Cells/metabolism ; Genetic Variation ; Immune Tolerance ; Neural Networks, Computer ; NF-E2-Related Factor 2/metabolism ; Promoter Regions, Genetic ; T-Lymphocytes/cytology ; T-Lymphocytes/immunology ; Thymus Gland/cytology ; Transcription, Genetic ; Female
Chemical Substances	AIRE Protein ; Aire protein, mouse ; Chromatin ; DNA, Z-Form ; NF-E2-Related Factor 2 ; Nfe2l2 protein, mouse
Language	English
Publishing date	2024-03-13
Publishing country	England
Document type	Journal Article
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-024-07169-7
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Zs.A 26: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article: Recurrent cannabis-induced catatonia: a case report and comprehensive systematic literature review.

Moshfeghinia, Reza / Hosseinzadeh, Mehrnaz / Mostafavi, Sara / Jabbarinejad, Roxana / Malekpour, Mahdi / Chohedri, Elnaz / Ahmadi, Jamshid

Frontiers in psychiatry

2024 Volume 15, Page(s) 1332310

Abstract: Background: Catatonia presents itself as a complex neuropsychiatric syndrome, giving rise to various motor, speech, and behavioral challenges. It is noteworthy that approximately 10% of psychiatric hospital admissions can be attributed to this condition. ...

Abstract	Background: Catatonia presents itself as a complex neuropsychiatric syndrome, giving rise to various motor, speech, and behavioral challenges. It is noteworthy that approximately 10% of psychiatric hospital admissions can be attributed to this condition. It is imperative to note that cannabis-induced catatonia, while infrequent, has been linked to the use of marijuana. This connection has the potential to disrupt neurotransmitter systems, necessitating further research for a comprehensive understanding and effective treatment, particularly given the evolving trends in cannabis use. In this context, we shall delve into a unique case of recurrent cannabis-induced catatonia. Case presentation: A 23-year-old gentleman, who has previously struggled with substance use disorder, experienced the emergence of mutism, social isolation, and a fixed gaze subsequent to his use of cannabis. Remarkably, despite the absence of hallucinations, he exhibited recurrent episodes of catatonia. These episodes were effectively addressed through a combination of electroconvulsive therapy (ECT) and lorazepam administration. Notably, when the lorazepam dosage was gradually reduced to below 2 mg per day, the catatonic symptoms resurfaced; however, they promptly abated upon reinstating the medication. The diagnosis of cannabis-induced catatonia was established, and its management primarily involved a therapeutic approach encompassing ECT and lorazepam. It is pertinent to underscore that this catatonic condition can be directly linked to the individual's cannabis usage. Conclusion: The connection between cannabis and catatonia is intricate and not entirely comprehended. Although cannabis possesses therapeutic advantages, it can paradoxically trigger catatonia in certain individuals. Multiple factors, such as genetics, cannabinoids, and neurotransmitter systems, contribute to this intricacy, underscoring the necessity for additional research.
Language	English
Publishing date	2024-01-18
Publishing country	Switzerland
Document type	Case Reports
ZDB-ID	2564218-2
ISSN	1664-0640
ISSN	1664-0640
DOI	10.3389/fpsyt.2024.1332310
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Article ; Online: Gemini: memory-efficient integration of hundreds of gene networks with high-order pooling.

Woicik, Addie / Zhang, Mingxin / Xu, Hanwen / Mostafavi, Sara / Wang, Sheng

Bioinformatics (Oxford, England)

2023 Volume 39, Issue 39 Suppl 1, Page(s) i504–i512

Abstract: Motivation: The exponential growth of genomic sequencing data has created ever-expanding repositories of gene networks. Unsupervised network integration methods are critical to learn informative representations for each gene, which are later used as ... ...

Abstract	Motivation: The exponential growth of genomic sequencing data has created ever-expanding repositories of gene networks. Unsupervised network integration methods are critical to learn informative representations for each gene, which are later used as features for downstream applications. However, these network integration methods must be scalable to account for the increasing number of networks and robust to an uneven distribution of network types within hundreds of gene networks. Results: To address these needs, we present Gemini, a novel network integration method that uses memory-efficient high-order pooling to represent and weight each network according to its uniqueness. Gemini then mitigates the uneven network distribution through mixing up existing networks to create many new networks. We find that Gemini leads to more than a 10% improvement in F1 score, 15% improvement in micro-AUPRC, and 63% improvement in macro-AUPRC for human protein function prediction by integrating hundreds of networks from BioGRID, and that Gemini's performance significantly improves when more networks are added to the input network collection, while Mashup and BIONIC embeddings' performance deteriorates. Gemini thereby enables memory-efficient and informative network integration for large gene networks and can be used to massively integrate and analyze networks in other domains. Availability and implementation: Gemini can be accessed at: https://github.com/MinxZ/Gemini.
MeSH term(s)	Humans ; Gene Regulatory Networks ; Chromosome Mapping ; Genomics
Language	English
Publishing date	2023-06-30
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btad247
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Article: Quantitative serum determination of CD3, CD4, CD8, CD16, and CD56 in women with primary infertility: The role of cell-mediated immunity.

Shakerian, Behzad / Irvani, Sahar / Mostafavi, Sara / Moghtaderi, Mozhgan

Turkish journal of obstetrics and gynecology

2022 Volume 19, Issue 3, Page(s) 242–245

Abstract: Objective: Cellular adaptive immunity plays an essential role in the etiology of primary infertility. This study aimed to measure the T-lymphocyte subpopulations and natural killer (NK) cells in infertile women compared with healthy ones.: Materials ... ...

Abstract	Objective: Cellular adaptive immunity plays an essential role in the etiology of primary infertility. This study aimed to measure the T-lymphocyte subpopulations and natural killer (NK) cells in infertile women compared with healthy ones. Materials and methods: From January to September 2021, we conducted this cross-sectional study among women with primary infertility, and healthy women were referred to Isfahan Fertility and Infertility Center affiliated with Najafabad University of medical sciences in Isfahan, Iran for immunological investigations. For each person, we determined quantitative serum measurements of CD3, CD4, CD8, CD4/CD8, CD16, CD56, and CD56+16. Results: This study included one hundred and fifty-one infertile women with a mean age of 31.4±4.7 years and 46 healthy women with a mean age of 31.5±3.4 years. Compared to the controls, immunophenotyping findings in infertile patients revealed a significant drop in CD8 T cells [p=0.01, 95% confidence interval (CI) 0.53 to 4.57] and the percentage of CD 56 NK cells (p=0.005, 95% CI 0.74 to 4.03) in infertile patients. Conclusion: Despite having a normal quantity of CD3 T cells, infertile women had lower CD8 T cells and CD56 NK cells than the controls. More studies are needed to confirm the role of cell-mediated assessments as a screening test in patients with primary infertility.
Language	English
Publishing date	2022-09-23
Publishing country	Turkey
Document type	Journal Article
ISSN	2149-9322
ISSN	2149-9322
DOI	10.4274/tjod.galenos.2022.47527
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Article ; Online: A practical guide to applying machine learning to infant EEG data.

Ng, Bernard / Reh, Rebecca K / Mostafavi, Sara

Developmental cognitive neuroscience

2022 Volume 54, Page(s) 101096

Abstract: Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challenging ... ...

Abstract	Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challenging due to the low number of trials, low signal-to-noise ratio, high inter-subject variability, and high inter-trial variability. Here, we provide a step-by-step tutorial on how to apply ML to classify cognitive states in infants. We describe the type of brain attributes that are widely used for EEG classification and also introduce a Riemannian geometry based approach for deriving connectivity estimates that account for inter-trial and inter-subject variability. We present pipelines for learning classifiers using trials from a single infant and from multiple infants, and demonstrate the application of these pipelines on a standard infant EEG dataset of forty 12-month-old infants collected under an auditory oddball paradigm. While we classify perceptual states induced by frequent versus rare stimuli, the presented pipelines can be easily adapted for other experimental designs and stimuli using the associated code that we have made publicly available.
MeSH term(s)	Adult ; Algorithms ; Brain ; Electroencephalography ; Humans ; Infant ; Machine Learning
Language	English
Publishing date	2022-03-14
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2572271-2
ISSN	1878-9307 ; 1878-9307
ISSN (online)	1878-9307
ISSN	1878-9307
DOI	10.1016/j.dcn.2022.101096
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Article ; Online: ExplaiNN: interpretable and transparent neural networks for genomics.

Novakovsky, Gherman / Fornes, Oriol / Saraswat, Manu / Mostafavi, Sara / Wasserman, Wyeth W

Genome biology

2023 Volume 24, Issue 1, Page(s) 154

Abstract: Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with the interpretability of linear models. ExplaiNN can predict TF ... ...

Abstract	Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with the interpretability of linear models. ExplaiNN can predict TF binding, chromatin accessibility, and de novo motifs, achieving performance comparable to state-of-the-art methods. Its predictions are transparent, providing global (cell state level) as well as local (individual sequence level) biological insights into the data. ExplaiNN can serve as a plug-and-play platform for pretrained models and annotated position weight matrices. ExplaiNN aims to accelerate the adoption of deep learning in genomic sequence analysis by domain experts.
MeSH term(s)	Neural Networks, Computer ; Genomics/methods ; Chromatin/genetics ; Protein Binding
Chemical Substances	Chromatin
Language	English
Publishing date	2023-06-27
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/s13059-023-02985-y
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Article: Epidemiology of Asthma in Patients with COVID-19: Investigation of Respiratory Allergy as a Risk Factor for COVID-19 Severity.

Moghtaderi, Mozhgan / Mostafavi, Sara / Hosseini Teshnizi, Saeed / Mostafavi, Ali / Ashraf, Mohammad Ali

Tanaffos

2023 Volume 21, Issue 2, Page(s) 186–192

Abstract: Background: The outcome of coronavirus disease 2019 (COVID-19) is complicated by various comorbidities; asthma, a common chronic disease, may be considered one of these conditions. This study aimed to investigate the effect of asthma as a potential ... ...

Abstract	Background: The outcome of coronavirus disease 2019 (COVID-19) is complicated by various comorbidities; asthma, a common chronic disease, may be considered one of these conditions. This study aimed to investigate the effect of asthma as a potential comorbid condition on the COVID-19 prognosis. Materials and methods: This retrospective study included all RT-PCR confirmed COVID-19 cases recorded on the Shiraz health department's electronic database from January to May 2020. A questionnaire was designed to collect information about patients' demographics, their history of asthma and other comorbidities, and the severity of COVID-19 by contacting them by phone. Results: Of 3163 COVID-19 patients, 109 (3.4%) had self-reported asthma with a mean age of 42.7 ± 19.1 years. Most patients (98%) had mild-to-moderate asthma, while 2% had severe disease. Among asthmatic patients, fourteen (12.8%) were admitted to the hospital, and five (4.6%) died. Univariate logistic regression results showed that asthma had no significant effect on hospitalization (OR 0.95, 95% CI: 0.54-1.63) and mortality (OR 1.18, 95% CI: 0.48-2.94) in patients with COVID-19. Compared living and deceased patients with COVID-19, the pooled OR was 18.2 (95% CI: 7.3-40.1) for cancer, 13.5 (95% CI: 8.2-22.5) for age 40-70 years, 3.1 (95% CI: 2-4.8) for hypertension, 3.1 (95% CI: 1.8-5.3) for cardiac disease and 2.1 (95% CI: 1.3-3.5) for diabetes mellitus. Conclusion: This study showed that asthma is not associated with an increased risk of hospitalization and mortality in patients with COVID-19. Further studies are needed to investigate the risk of different asthma phenotypes on the severity of COVID-19 disease.
Language	English
Publishing date	2023-01-18
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2233372-1
ISSN	1735-0344
ISSN	1735-0344
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Article ; Online: Mosaic loss of Chromosome Y in aged human microglia.

Vermeulen, Michael C / Pearse, Richard / Young-Pearse, Tracy / Mostafavi, Sara

Genome research

2022 Volume 32, Issue 10, Page(s) 1795–1807

Abstract: Mosaic loss of Chromosome Y (LOY) is a common acquired structural mutation in the leukocytes of aging men that is correlated with several age-related diseases, including Alzheimer's disease (AD). The molecular basis of LOY in brain cells has not been ... ...

Abstract	Mosaic loss of Chromosome Y (LOY) is a common acquired structural mutation in the leukocytes of aging men that is correlated with several age-related diseases, including Alzheimer's disease (AD). The molecular basis of LOY in brain cells has not been systematically investigated. Here, we present a large-scale analysis of single-cell and single-nuclei RNA brain data sets, yielding 851,674 cells, to investigate the cell type-specific burden of LOY. LOY frequencies differed widely between donors and CNS cell types. Among five well-represented neural cell types, LOY was enriched in microglia and rare in neurons, astrocytes, and oligodendrocytes. In microglia, LOY was significantly enriched in AD subjects. Differential gene expression (DE) analysis in microglia found 172 autosomal genes, three X-linked genes, and 10 pseudoautosomal genes associated with LOY. To our knowledge, we provide the first evidence of LOY in the microglia and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.
MeSH term(s)	Humans ; Male ; Aged ; Chromosomes, Human, Y/genetics ; Mosaicism ; Microglia ; Alzheimer Disease/genetics ; Aging/genetics
Language	English
Publishing date	2022-08-30
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	1284872-4
ISSN	1549-5469 ; 1088-9051 ; 1054-9803
ISSN (online)	1549-5469
ISSN	1088-9051 ; 1054-9803
DOI	10.1101/gr.276409.121
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Article ; Online: Impact on splicing in

Perchlik, Molly / Sasse, Alexander / Mostafavi, Sara / Fields, Stanley / Cuperus, Josh T

RNA (New York, N.Y.)

2023 Volume 30, Issue 1, Page(s) 52–67

Abstract: Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing-5' and 3' splice sites and a branchpoint-are especially well-characterized ... ...

Abstract	Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing-5' and 3' splice sites and a branchpoint-are especially well-characterized in
MeSH term(s)	Introns/genetics ; Saccharomyces cerevisiae/genetics ; Saccharomyces cerevisiae/metabolism ; RNA Precursors/metabolism ; Base Sequence ; RNA Splicing/genetics ; RNA Splice Sites/genetics
Chemical Substances	RNA Precursors ; RNA Splice Sites
Language	English
Publishing date	2023-12-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	1241540-6
ISSN	1469-9001 ; 1355-8382
ISSN (online)	1469-9001
ISSN	1355-8382
DOI	10.1261/rna.079752.123
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Zs.A 4777: Show issues

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Article: Deep learning decodes the principles of differential gene expression.

Tasaki, Shinya / Gaiteri, Chris / Mostafavi, Sara / Wang, Yanling

Nature machine intelligence

2020 Volume 2, Issue 7, Page(s) 376–386

Abstract: Identifying the molecular mechanisms that control differential gene expression (DE) is a major goal of basic and disease biology. We develop a systems biology model to predict DE, and mine the biological basis of the factors that influence predicted gene ...

Abstract	Identifying the molecular mechanisms that control differential gene expression (DE) is a major goal of basic and disease biology. We develop a systems biology model to predict DE, and mine the biological basis of the factors that influence predicted gene expression, in order to understand how it may be generated. This model, called
Language	English
Publishing date	2020-07-06
Publishing country	England
Document type	Journal Article
ISSN	2522-5839
ISSN	2522-5839
DOI	10.1038/s42256-020-0201-6
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