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15 results on '"Nosirov, Bakhtiyor"'

1. Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Author

Yabo, Yahaya A., Moreno-Sanchez, Pilar M., Pires-Afonso, Yolanda, Kaoma, Tony, Nosirov, Bakhtiyor, Scafidi, Andrea, Ermini, Luca, Lipsa, Anuja, Oudin, Anaïs, Kyriakis, Dimitrios, Grzyb, Kamil, Poovathingal, Suresh K., Poli, Aurélie, Muller, Arnaud, Toth, Reka, Klink, Barbara, Berchem, Guy, Berthold, Christophe, Hertel, Frank, Mittelbronn, Michel, Heiland, Dieter H., Skupin, Alexander, Nazarov, Petr V., Niclou, Simone P., Michelucci, Alessandro, and Golebiewska, Anna

Published
2024
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3. Rel Family Transcription Factor NFAT5 Upregulates COX2 via HIF-1α Activity in Ishikawa and HEC1a Cells

Author

Okumura, Toshiyuki, primary, Raja Xavier, Janet P., additional, Pasternak, Jana, additional, Yang, Zhiqi, additional, Hang, Cao, additional, Nosirov, Bakhtiyor, additional, Singh, Yogesh, additional, Admard, Jakob, additional, Brucker, Sara Y., additional, Kommoss, Stefan, additional, Takeda, Satoru, additional, Staebler, Annette, additional, Lang, Florian, additional, and Salker, Madhuri S., additional

Published
2024
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5. PREDICTION OF STUDENT LEARNING OUTCOMES IN THE COURSE 'PROGRAMMING' BASED ON NEURAL NETWORKS

Author

Abduvalieva Zebinuso, Nosirov Bakhtiyor, Abduvalieva Zebinuso, and Nosirov Bakhtiyor

Abstract

The article describes a hybrid approach in the education process. This approach is based on the introduction of artificial intelligence into the learning process. The results of practical experiments in training such a hybrid network are presented.

Published
2021

6. The 3D genomic landscape of differential response to EGFR/HER2 inhibition in endocrine-resistant breast cancer cells

Author

Yang, Yini, primary, Choppavarapu, Lavanya, additional, Fang, Kun, additional, Naeini, Alireza S., additional, Nosirov, Bakhtiyor, additional, Li, Jingwei, additional, Yang, Ke, additional, He, Zhijing, additional, Zhou, Yufan, additional, Schiff, Rachel, additional, Li, Rong, additional, Hu, Yanfen, additional, Wang, Junbai, additional, and Jin, Victor X., additional

Published
2020
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8. Mapping circulating serum miRNAs to their immune-related target mRNAs

Author

Nosirov,Bakhtiyor, Billaud,Joël, Vandenbon,Alexis, Diez,Diego, Wijaya,Edward, Ishii,Ken J., Teraguchi,Shunsuke, Standley,Daron M., Nosirov,Bakhtiyor, Billaud,Joël, Vandenbon,Alexis, Diez,Diego, Wijaya,Edward, Ishii,Ken J., Teraguchi,Shunsuke, and Standley,Daron M.

Abstract

Bakhtiyor Nosirov,1 Joël Billaud,1 Alexis Vandenbon,2 Diego Diez,3 Edward Wijaya,1 Ken J Ishii,4,5 Shunsuke Teraguchi,3 Daron M Standley1,6 1Systems Immunology Lab, 2Immuno-Genomics Research Unit, 3Quantitative Immunology Research Unit, 4Laboratory of Vaccine Science, WPI Immunology Frontier Research Center, Osaka University, Suita, 5Laboratory of Adjuvant Innovation, National Institute of Biomedical Innovation, Osaka, 6Lab of Integrated Biological Information, Institute for Virus Research Kyoto University, Kyoto, Japan Purpose: Evidence suggests that circulating serum microRNAs (miRNAs) might preferentially target immune-related mRNAs. If this were the case, we hypothesized that immune-related mRNAs would have more predicted serum miRNA binding sites than other mRNAs and, reciprocally, that serum miRNAs would have more immune-related mRNA targets than non-serum miRNAs.Materials and methods: We developed a consensus target predictor using the random forest framework and calculated the number of predicted miRNA–mRNA interactions in various subsets of miRNAs (serum, non-serum) and mRNAs (immune related, nonimmune related).Results: Immune-related mRNAs were predicted to be targeted by serum miRNA more than other mRNAs. Moreover, serum miRNAs were predicted to target many more immune-related mRNA targets than non-serum miRNAs; however, these two biases in immune-related mRNAs and serum miRNAs appear to be completely independent.Conclusion: Immune-related mRNAs have more miRNA binding sites in general, not just for serum miRNAs; likewise, serum miRNAs target many more mRNAs than non-serum miRNAs overall, regardless of whether they are immune related or not. Nevertheless, these two independent phenomena result in a significantly larger number of predicted serum miRNA–immune mRNA interactions than would be expected by chance. Keywords: biomarker, posttranscriptional regulation, random forest, target prediction

Published
2017

9. Mapping circulating serum miRNAs to their immune-related target mRNAs

Author

60570140, Nosirov, Bakhtiyor, Billaud, Joël, Vandenbon, Alexis, Diez, Diego, Wijaya, Edward, Ishii, Ken J., Teraguchi, Shunsuke, Standley, Daron M., 60570140, Nosirov, Bakhtiyor, Billaud, Joël, Vandenbon, Alexis, Diez, Diego, Wijaya, Edward, Ishii, Ken J., Teraguchi, Shunsuke, and Standley, Daron M.

Abstract

Purpose: Evidence suggests that circulating serum microRNAs (miRNAs) might preferentially target immune-related mRNAs. If this were the case, we hypothesized that immune-related mRNAs would have more predicted serum miRNA binding sites than other mRNAs and, reciprocally, that serum miRNAs would have more immune-related mRNA targets than non-serum miRNAs., Materials and Methods: We developed a consensus target predictor using the random forest framework and calculated the number of predicted miRNA–mRNA interactions in various subsets of miRNAs (serum, non-serum) and mRNAs (immune related, nonimmune related)., Results: Immune-related mRNAs were predicted to be targeted by serum miRNA more than other mRNAs. Moreover, serum miRNAs were predicted to target many more immune-related mRNA targets than non-serum miRNAs; however, these two biases in immune-related mRNAs and serum miRNAs appear to be completely independent., Conclusion: Immune-related mRNAs have more miRNA binding sites in general, not just for serum miRNAs; likewise, serum miRNAs target many more mRNAs than non-serum miRNAs overall, regardless of whether they are immune related or not. Nevertheless, these two independent phenomena result in a significantly larger number of predicted serum miRNA–immune mRNA interactions than would be expected by chance.

Published
2017

14. Most accurate mutations in SARS-CoV-2 genomes identified in Uzbek patients show novel amino acid changes.

Author

Ayubov MS, Mirzakhmedov MK, Yusupov AN, Asrorov AM, Nosirov BV, Usmanov DE, Shermatov SE, Ubaydullaeva KA, Abdukarimov A, Buriev ZT, and Abdurakhmonov IY

Abstract

Purpose: The rapid changes in the coronavirus genomes created new strains after the first variation was found in Wuhan in 2019. SARS-CoV-2 genotypes should periodically undergo whole genome sequencing to control it because it has been extremely helpful in combating the virus. Many diagnoses, treatments, and vaccinations have been developed against it based on genome sequencing. With its practical implications, this study aimed to determine changes in the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic by genome sequencing, thereby providing crucial insights for developing effective control strategies that can be directly applied in the field., Design: We meticulously generated 17 high-quality whole-genome sequence data from 48 SARS-CoV-2 genotypes of COVID-19 patients who tested positive by PCR in Tashkent, Uzbekistan. Our rigorous approach, which includes stringent quality control measures and multiple rounds of verification, ensures the accuracy and reliability of our findings., Methods: Our study employed a unique combination of genome sequencing and bioinformatics web tools to analyze amino acid (AA) changes in the virus genomes. This approach allowed us to understand the genetic changes in the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic., Results: Our study revealed significant nucleotide polymorphisms, including non-synonymous (missense) and synonymous mutations in the coding regions of the sequenced sample genomes. These findings, categorized by phylogenetic analysis into the G clade (or GK sub-clade), contribute to our understanding of the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic. A total of 134 mutations were identified, consisting of 65 shared and 69 unique mutations. These nucleotide changes, including one frameshift mutation, one conservative and disruptive insertion-deletion, four upstream region mutations, four downstream region mutations, 39 synonymous mutations, and 84 missense mutations, are crucial in the ongoing battle against the virus., Conclusion: The comprehensive whole-genome sequencing data presented in this study aids in tracing the origins and sources of circulating SARS-CoV-2 variants and analyzing emerging variations within Uzbekistan and globally. The genome sequencing of SARS-CoV-2 from samples collected in Uzbekistan in late 2021, during the peak of the pandemic's second wave nationwide, is detailed here. Following acquiring these sequences, research efforts have focused on developing DNA and plant-based edible vaccines utilizing prevalent SARS-CoV-2 strains in Uzbekistan, which are currently undergoing clinical trials., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ayubov, Mirzakhmedov, Yusupov, Asrorov, Nosirov, Usmanov, Shermatov, Ubaydullaeva, Abdukarimov, Buriev and Abdurakhmonov.)

Published
2024
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15. Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts.

Author

Yabo YA, Moreno-Sanchez PM, Pires-Afonso Y, Kaoma T, Nosirov B, Scafidi A, Ermini L, Lipsa A, Oudin A, Kyriakis D, Grzyb K, Poovathingal SK, Poli A, Muller A, Toth R, Klink B, Berchem G, Berthold C, Hertel F, Mittelbronn M, Heiland DH, Skupin A, Nazarov PV, Niclou SP, Michelucci A, and Golebiewska A

Abstract

Background: A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials., Methods: Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors., Results: We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components., Conclusions: Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment., Competing Interests: Competing interests The authors declare that they have no competing interests.

Published
2023
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