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  • 1
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    A new calibration method for charm jet identification validated with proton-proton collision events at √s = 13 TeV
    IOP Publishing ; 2022
    In:  Journal of Instrumentation Vol. 17, No. 03 ( 2022-03-01), p. P03014-
    Details
    In: Journal of Instrumentation, IOP Publishing, Vol. 17, No. 03 ( 2022-03-01), p. P03014-
    Abstract: Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.
    Type of Medium: Online Resource
    ISSN: 1748-0221
    URL: Article
    DOI: 10.1088/1748-0221/17/03/P03014
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2235672-1
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  • 2
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    Image1.JPEG
    Frontiers Media SA ; 2023
    In:  Frontiers in Cell and Developmental Biology Vol. 11 ( 2023-4-20)
    Details
    In: Frontiers in Cell and Developmental Biology, Frontiers Media SA, Vol. 11 ( 2023-4-20)
    Abstract: Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group ( p & lt; 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro . Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.
    Type of Medium: Online Resource
    ISSN: 2296-634X
    URL: Article
    URL: Article
    DOI: 10.3389/fcell.2023.1159355
    DOI: 10.3389/fcell.2023.1159355.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2737824-X
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  • 3
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    DataSheet1.docx
    Frontiers Media SA ; 2023
    In:  Frontiers in Pharmacology Vol. 14 ( 2023-8-7)
    Details
    In: Frontiers in Pharmacology, Frontiers Media SA, Vol. 14 ( 2023-8-7)
    Abstract: Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM). Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR). Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease’s prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG’s significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR. Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.
    Type of Medium: Online Resource
    ISSN: 1663-9812
    URL: Article
    URL: Article
    DOI: 10.3389/fphar.2023.1203125
    DOI: 10.3389/fphar.2023.1203125.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2587355-6
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  • 4
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    Table1.XLSX
    Frontiers Media SA ; 2023
    In:  Frontiers in Cell and Developmental Biology Vol. 11 ( 2023-6-2)
    Details
    In: Frontiers in Cell and Developmental Biology, Frontiers Media SA, Vol. 11 ( 2023-6-2)
    Abstract: Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult. Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes. Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study. Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients.
    Type of Medium: Online Resource
    ISSN: 2296-634X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fcell.2023.1198949
    DOI: 10.3389/fcell.2023.1198949.s001
    DOI: 10.3389/fcell.2023.1198949.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2737824-X
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  • 5
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    Table_4.docx
    Frontiers Media SA ; 2024
    In:  Frontiers in Oncology Vol. 14 ( 2024-3-18)
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    In: Frontiers in Oncology, Frontiers Media SA, Vol. 14 ( 2024-3-18)
    Abstract: To assess the prognostic significance of β2-microglobulin decline index (β2M DI) in multiple myeloma (MM). Methods 150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing β2M DI was built up based on the data in training cohort. The validation group was used to verify the model. Results β2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p & lt;0.05). Conclusion β2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with β2M DI showed a better correlation with OS.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2024.1322680
    DOI: 10.3389/fonc.2024.1322680.s001
    DOI: 10.3389/fonc.2024.1322680.s002
    DOI: 10.3389/fonc.2024.1322680.s003
    DOI: 10.3389/fonc.2024.1322680.s004
    DOI: 10.3389/fonc.2024.1322680.s005
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2649216-7
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  • 6
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    Effect of a modified regimen on drug-sensitive retreated pulmonary tuberculosis: A multicenter study in China
    Frontiers Media SA ; 2023
    In:  Frontiers in Public Health Vol. 11 ( 2023-1-26)
    Details
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 11 ( 2023-1-26)
    Abstract: Retreatment pulmonary tuberculosis (PTB) still accounts for a large proportion of tuberculosis, and the treatment outcome is unfavorable. The recurrence of retreatment PTB based on long-term follow-up has not been well demonstrated. This study aimed to evaluate effect of a modified regimen on drug-sensitive retreated pulmonary tuberculosis. Methods This multicenter cohort study was conducted in 29 hospitals from 23 regions of China from July 1, 2009, to December 31, 2020. Patients were divided into two treatment regimen groups including experimental group [modified regimen (4H-Rt2-E-Z-S(Lfx)/4H-Rt2-E)]and control group [standard regimen (2H-R-E-Z-S/6H-R-E or 3H-R-E-Z/6H-R-E)] . The patients enrolled were followed up of 56 months after successful treatment. We compared the treatment success rate, treatment failure rate, adverse reaction rate, and recurrence rate between two regimens. Multivariate Cox regression model was used to identify the potential risk factors for recurrence after successful treatment with proportional hazards assumptions tested for all variables. Results A total of 381 patients with retreatment PTB were enrolled, including 244 (64.0%) in the experimental group and 137 (36.0%) in the control group. Overall, the treatment success rate was significant higher in the experimental group than control group (84.0 vs. 74.5%, P = 0.024); no difference was observed in adverse reactions between the two groups (25.8 vs. 21.2%, P & gt; 0.05). A total of 307 patients completed the 56 months of follow-up, including 205 with the modified regimen and 102 with the standard regimen. Among these, 10 cases (3.3%) relapsed, including 3 in the experimental group and 7 in the control group (1.5% vs 6.9%, P = 0.035). Reduced risks of recurrence were observed in patients treated with the modified regimen compared with the standard regimen, and the adjusted hazard ratio was 0.19 (0.04–0.77). Conclusion The modified retreatment regimen had more favorable treatment effects, including higher treatment success rate and lower recurrence rate in patients with retreated drug-sensitive PTB.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    DOI: 10.3389/fpubh.2023.1039399
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2711781-9
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  • 7
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    Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution
    Association for the Advancement of Artificial Intelligence (AAAI) ; 2021
    In:  Proceedings of the AAAI Conference on Artificial Intelligence Vol. 35, No. 4 ( 2021-05-18), p. 2738-2745
    Details
    In: Proceedings of the AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), Vol. 35, No. 4 ( 2021-05-18), p. 2738-2745
    Abstract: Visual Information Extraction (VIE) has attracted considerable attention recently owing to its various advanced applications such as document understanding, automatic marking and intelligent education. Most existing works decoupled this problem into several independent sub-tasks of text spotting (text detection and recognition) and information extraction, which completely ignored the high correlation among them during optimization. In this paper, we propose a robust Visual Information Extraction System (VIES) towards real-world scenarios, which is an unified end-to-end trainable framework for simultaneous text detection, recognition and information extraction by taking a single document image as input and outputting the structured information. Specifically, the information extraction branch collects abundant visual and semantic representations from text spotting for multimodal feature fusion and conversely, provides higher-level semantic clues to contribute to the optimization of text spotting. Moreover, regarding the shortage of public benchmarks, we construct a fully-annotated dataset called EPHOIE (https://github.com/HCIILAB/EPHOIE), which is the first Chinese benchmark for both text spotting and visual information extraction. EPHOIE consists of 1,494 images of examination paper head with complex layouts and background, including a total of 15,771 Chinese handwritten or printed text instances. Compared with the state-of-the-art methods, our VIES shows significant superior performance on the EPHOIE dataset and achieves a 9.01% F-score gain on the widely used SROIE dataset under the end-to-end scenario.
    Type of Medium: Online Resource
    ISSN: 2374-3468 , 2159-5399
    URL: Article
    DOI: 10.1609/aaai.v35i4.16378
    Language: Unknown
    Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
    Publication Date: 2021
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  • 8
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    Optimal Regimens and Cutoff Evaluation of Tildipirosin Against Pasteurella multocida
    Frontiers Media SA ; 2018
    In:  Frontiers in Pharmacology Vol. 9 ( 2018-7-26)
    Details
    In: Frontiers in Pharmacology, Frontiers Media SA, Vol. 9 ( 2018-7-26)
    Type of Medium: Online Resource
    ISSN: 1663-9812
    URL: Article
    DOI: 10.3389/fphar.2018.00765
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2018
    detail.hit.zdb_id: 2587355-6
    SSG: 15,3
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  • 9
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    Alignment Relation is What You Need for Diagram Parsing
    Institute of Electrical and Electronics Engineers (IEEE) ; 2024
    In:  IEEE Transactions on Image Processing Vol. 33 ( 2024), p. 2131-2144
    Details
    In: IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 33 ( 2024), p. 2131-2144
    Type of Medium: Online Resource
    ISSN: 1057-7149 , 1941-0042
    URL: Article
    DOI: 10.1109/TIP.2024.3374511
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2024
    detail.hit.zdb_id: 2034319-X
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  • 10
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    Table_1.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Plant Science Vol. 14 ( 2023-5-15)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 14 ( 2023-5-15)
    Abstract: ATP-dependent SWI/SNF chromatin remodeling complexes (CRCs) are evolutionarily conserved multi-component machines that regulate transcription, replication, and genome stability in eukaryotes. SWI/SNF components play pivotal roles in development and various stress responses in plants. However, the compositions and biological functions of SWI/SNF complex subunits remain poorly understood in soybean. In this study, we used bioinformatics to identify 39 genes encoding SWI/SNF subunit distributed on the 19 chromosomes of soybean. The promoter regions of the genes were enriched with several cis -regulatory elements that are responsive to various hormones and stresses. Digital expression profiling and qRT-PCR revealed that most of the SWI/SNF subunit genes were expressed in multiple tissues of soybean and were sensitive to drought stress. Phenotypical, physiological, and molecular genetic analyses revealed that GmLFR1 ( Leaf and Flower-Related1 ) plays a negative role in drought tolerance in soybean and Arabidopsis thaliana . Together, our findings characterize putative components of soybean SWI/SNF complex and indicate possible roles for GmLFR1 in plants under drought stress. This study offers a foundation for comprehensive analyses of soybean SWI/SNF subunit and provides mechanistic insight into the epigenetic regulation of drought tolerance in soybean.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2023.1176376
    DOI: 10.3389/fpls.2023.1176376.s001
    DOI: 10.3389/fpls.2023.1176376.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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