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Articles by Yichen Pan
MSTO1 modulates RAD51 activity to safeguard mitochondrial DNA integrity and control immune responses
Abstract Pathogenic MSTO1 mutations cause cerebellar ataxia and congenital myopathy, yet their molecular mechanisms remain poorly understood. This study identifies MSTO1 as a crucial regulator of mitochondrial genome integrity through direct interaction with RAD51. MSTO1 deficiency enhances RAD51 binding to mitochondrial DNA (mtDNA), disrupting mtDNA replication and causing mtDNA damage.
Pd-Catalyzed Decarboxylative Negishi Coupling of Zinc Aryl Carboxylates with Arylthianthrenium Salts
DDX39A resolves replication fork-associated RNA-DNA hybrids to balance fork protection and cleavage for genomic stability maintenance
Keywords genomic stability replication stress DNA damage fork restart chemoresistance DDX39A DNA2 Rad51 Get full text access Log in, subscribe or purchase for full access. References 1. Gómez-González, B. ∙ Aguilera, A. Transcription-mediated replication hindrance: a major driver of genome instability Genes Dev. 2019; 33:1008-1026 2. Hamperl, S. ∙ Cimprich, K.A. Conflict Resolution in the Genome: How Transcription and Replication Make It Work Cell. 2016; 167:1455-1467 3. Dutta, D. ∙ Shatalin, K.
Review of Predicting Synergistic Drug Combinations
4. Methods in Drug Combination Prediction Over the course of the last many years, computational techniques have been broadly used to predict drug combinations, including traditional machine learning methods, deep learning methods, mathematical methods, systems biology methods, and search algorithms. A brief description of each method reviewed is listed in Table 2. Traditional machine learning applies to various feature types for high prediction accuracy in different scale databases.
Inkjet-printed alloy-like cross-linked hole-transport layer for high-performance solution-processed green phosphorescent OLEDs
Inkjet-printed alloy-like cross-linked hole-transport layer for high-performance solution-processed green phosphorescent OLEDs† Yichen Pan,ab Hongli Liu,*ab Shirong Wang, ab Xinjun Han ab and Xianggao Li *ab Author affiliations * Corresponding authors a School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China E-mail: liuhongli@tju.edu.cn, lixianggao@tju.edu.cn b Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, China...
Accuracy and reliability of maxillary digital model (MDM) superimposition in evaluating teeth movement in adults compared with CBCT maxillary superimposition
Abstract Superimposition of 3D maxillary digital dental models of different time points based on palatal vault region has been used to evaluate tooth movement during orthodontic treatment. This study evaluated the accuracy and reliability of 3D maxillary digital model (MDM) superimposition in adults by comparing it with CBCT maxillary superimposition.
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