3-Hy­droxy-N′-[(E)-3-pyridyl­methyl­idene]-2-naphtho­hydrazide

The title compound, C17H13N3O2, displays an E configuration about the C=N bond. The mean planes of the pyridine and benzene rings make a dihedral angle of 31.2 (2)°. An intra­molecular O—H⋯O hydrogen bond is observed. In the crystal, inter­molecular N—H⋯N hydrogen bonding links the mol­ecules into a chain along [101]

Regulation of neural progenitor cell state by ephrin-B

Maintaining a balance between self-renewal and differentiation in neural progenitor cells during development is important to ensure that correct numbers of neural cells are generated. We report that the ephrin-B–PDZ-RGS3 signaling pathway functions to regulate this balance in the developing mammalian cerebral cortex. During cortical neurogenesis, expression of ephrin-B1 and PDZ-RGS3 is specifically seen in progenitor cells and is turned off at the onset of neuronal differentiation. Persistent expression of ephrin-B1 and PDZ-RGS3 prevents differentiation of neural progenitor cells. Blocking RGS-mediated ephrin-B1 signaling in progenitor cells through RNA interference or expression of dominant-negative mutants results in differentiation. Genetic knockout of ephrin-B1 causes early cell cycle exit and leads to a concomitant loss of neural progenitor cells. Our results indicate that ephrin-B function is critical for the maintenance of the neural progenitor cell state and that this role of ephrin-B is mediated by PDZ-RGS3, likely via interacting with the noncanonical G protein signaling pathway, which is essential in neural progenitor asymmetrical cell division

Study of prevalence and risk factors of chemotherapy-induced mucositis in gastrointestinal cancer using machine learning models

ObjectiveChemotherapy-induced mucositis (CIM) significantly impacts clinical outcomes and diminishes the quality of life in patients with gastrointestinal cancer. This study aims to prospectively determine the incidence, severity, and underlying risk factors associated with CIM in this patient population.MethodsTo achieve this objective, we introduce a novel Machine Learning-based Toxicity Prediction Model (ML-TPM) designed to analyze the risk factors contributing to CIM development in gastrointestinal cancer patients. Within the winter season spanning from December 15th, 2018 to January 14th, 2019, we conducted in-person interviews with patients undergoing chemotherapy for gastrointestinal cancer. These interviews encompassed comprehensive questionnaires pertaining to patient demographics, CIM incidence, severity, and any supplementary prophylactic measures employed.ResultsThe study encompassed a cohort of 447 participating patients who provided complete questionnaire responses (100%). Of these, 328 patients (73.4%) reported experiencing CIM during the course of their treatment. Notably, CIM-induced complications led to treatment discontinuation in 14 patients (3%). The most frequently encountered CIM symptoms were diarrhea (41.6%), followed by nausea (37.8%), vomiting (25.1%), abdominal pain (21%), gastritis (10.5%), and oral pain (10.3%). Supplementary prophylaxis was administered to approximately 62% of the patients. The analysis revealed significant correlations between the overall incidence of CIM and gender (p=0.015), number of chemotherapy cycles exceeding one (p=0.039), utilization of platinum-based regimens (p=0.039), and administration of irinotecan (p=0.003). Specifically, the incidence of diarrhea exhibited positive correlations with prior surgical history (p=0.037), irinotecan treatment (p=0.021), and probiotics usage (p=0.035). Conversely, diarrhea incidence demonstrated an adverse correlation with platinum-based treatment (p=0.026).ConclusionIn conclusion, this study demonstrates the successful implementation of the ML-TPM model for automating toxicity prediction with accuracy comparable to conventional physical analyses. Our findings provide valuable insights into the identification of CIM risk factors among gastrointestinal cancer patients undergoing chemotherapy. Furthermore, the results underscore the potential of machine learning in enhancing our understanding of chemotherapy-induced mucositis and advancing personalized patient care strategies

The MBD7 complex promotes expression of methylated transgenes without significantly altering their methylation status.

DNA methylation is associated with gene silencing in eukaryotic organisms. Although pathways controlling the establishment, maintenance and removal of DNA methylation are known, relatively little is understood about how DNA methylation influences gene expression. Here we identified a METHYL-CpG-BINDING DOMAIN 7 (MBD7) complex in Arabidopsis thaliana that suppresses the transcriptional silencing of two LUCIFERASE (LUC) reporters via a mechanism that is largely downstream of DNA methylation. Although mutations in components of the MBD7 complex resulted in modest increases in DNA methylation concomitant with decreased LUC expression, we found that these hyper-methylation and gene expression phenotypes can be genetically uncoupled. This finding, along with genome-wide profiling experiments showing minimal changes in DNA methylation upon disruption of the MBD7 complex, places the MBD7 complex amongst a small number of factors acting downstream of DNA methylation. This complex, however, is unique as it functions to suppress, rather than enforce, DNA methylation-mediated gene silencing

Identification and characterization of bone/cartilage-associated signatures in common fibrotic skin diseases

Background: Fibrotic skin diseases are characterized by excessive accumulation of the extracellular matrix (ECM) and activation of fibroblasts, leading to a global healthcare burden. However, effective treatments of fibrotic skin diseases remain limited, and their pathological mechanisms require further investigation. This study aims to investigate the common biomarkers and therapeutic targets in two major fibrotic skin diseases, namely, keloid and systemic sclerosis (SSc), by bioinformatics analysis.Methods: The keloid (GSE92566) and SSc (GSE95065) datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We then constructed a protein–protein interaction (PPI) network for the identification of hub genes. We explored the possibility of further functional enrichment analysis of hub genes on the Metascape, GeneMANIA, and TissueNexus platforms. Transcription factor (TF)–hub gene and miRNA–hub gene networks were established using NetworkAnalyst. We fixed GSE90051 and GSE76855 as the external validation datasets. Student’s t-test and receiver operating characteristic (ROC) curve were used for candidate hub gene validation. Hub gene expression was assessed in vitro by quantitative real-time PCR.Results: A total of 157 overlapping DEGs (ODEGs) were retrieved from the GSE92566 and GSE95065 datasets, and five hub genes (COL11A1, COL5A2, ASPN, COL10A1, and COMP) were identified and validated. Functional studies revealed that hub genes were predominantly enriched in bone/cartilage-related and collagen-related processes. FOXC1 and miR-335-5p were predicted to be master regulators at both transcriptional and post‐transcriptional levels.Conclusion: COL11A1, COL5A2, ASPN, COL10A1, and COMP may help understand the pathological mechanism of the major fibrotic skin diseases; moreover, FOXC1 and miR-355-5p could build a regulatory network in keloid and SSc

Evolutionary history of two evergreen Rhododendron species as revealed by chromosome-level genome assembly

BackgroundThe genus Rhododendron (Ericaceae), a species-rich and widely distributed genus of woody plants, is distinguished for the beautiful and diverse flowers. Rhododendron delavayi Franch. and Rhododendron irroratum Franch., are highly attractive species widely distributed in south-west China and abundant new varieties have been selected from their genetic resources.MethodsWe constructed chromosome-scale genome assemblies for Rhododendron delavayi and Rhododendron irroratum. Phylogenetic and whole-genome duplication analyses were performed to elucidate the evolutionary history of Rhododendron. Further, different types of gene duplications were identified and their contributions to gene family expansion were investigated. Finally, comprehensive characterization and evolutionary analysis of R2R3-MYB and NBS-encoding genes were conducted to explore their evolutionary patterns.ResultsThe phylogenetic analysis classified Rhododendron species into two sister clades, ‘rhododendrons’ and ‘azaleas’. Whole-genome duplication (WGD) analysis unveiled only one WGD event that occurred in Rhododendron after the ancestral γ triplication. Gene duplication and gene family expansion analyses suggested that the younger tandem and proximal duplications contributed greatly to the expansion of gene families involved in secondary metabolite biosynthesis and stress response. The candidate R2R3-MYB genes likely regulating anthocyanin biosynthesis and stress tolerance in Rhododendron will facilitate the breeding for ornamental use. NBS-encoding genes had undergone significant expansion and experienced species-specific gain and loss events in Rhododendron plants.ConclusionsThe reference genomes presented here will provide important genetic resources for molecular breeding and genetic improvement of plants in this economically important Rhododendron genus

Genomic mosaicism due to homoeologous exchange generates extensive phenotypic diversity in nascent allopolyploids

Allopolyploidy is an important process in plant speciation, yet newly formed allopolyploid species typically suffer from extreme genetic bottlenecks. One escape from this impasse might be homoeologous meiotic pairing, during which homoeologous exchanges (HEs) generate phenotypically variable progeny. However, the immediate genome-wide patterns and resulting phenotypic diversity generated by HEs remain largely unknown. Here, we analyzed the genome composition of 202 phenotyped euploid segmental allopolyploid individuals from the 4th selfed generation following chromosomal doubling of reciprocal F1 hybrids of crosses between rice subspecies, using whole genome sequencing. We describe rampant occurrence of HEs that, by overcoming incompatibility or conferring superiority of hetero-cytonuclear interactions, generate extensive and individualized genomic mosaicism across the analyzed tetraploids. We show that the resulting homoeolog copy number alteration in tetraploids affects known-function genes and their complex genetic interactions, in the process creating extraordinary phenotypic diversity at the population level following a single initial hybridization. Our results illuminate the immediate genomic landscapes possible in a tetraploid genomic environment, and underscore HE as an important mechanism that fuels rapid phenotypic diversification accompanying the initial stages of allopolyploid evolution

Motion processing across spatial and temporal scales for human perception and eye movements

We live in a dynamic visual environment, which requires perceiving moving objects around us and acting accordingly. However, we do not yet fully understand how visual information informs perception and motor actions. This dissertation examines the perception-action link by testing how motion and expectation signals are processed for perception and for eye movements as an example of human motor action. I focus on two types of human eye movements triggered by distinct brain mechanisms: ocular torsion, the eyes’ rotation about the line of sight triggered by rotational motion, and smooth pursuit, the eyes’ continuous tracking of translational motion. Torsion is mostly controlled by subcortical brain areas, but might share early-stage cortical processing of sensory signals with perception. In contrast, smooth pursuit is controlled by subcortical and cortical areas and might therefore be more closely linked to perception, sharing both motion and expectation signal processing with perception. To test the torsion-perception link, I utilized a perceptual illusion induced by visual rotational motion. Results show that torsional velocity correlates with the perceptual illusion, potentially suggesting shared motion processing (Chapter 2.1). However, anticipatory torsion can only be elicited by trial repetition, but not by cognitive cues that induce expectation (Chapter 2.2). These results show that similar visual motion signals might drive reflexive torsion and perception. Expectation signals appear to be less effective in driving torsion. Probing the pursuit-perception link, I found dissociations between how each system processes motion and expectation signals. When integrating diverse motion signals across space, pursuit was biased to the average motion direction, whereas perception showed no consistent bias (Chapter 3). When investigating the role of expectation, I found that anticipatory pursuit followed the expected direction, whereas perception was biased in the opposite direction (Chapter 4). Overall, this dissertation reveals that perception and eye movements likely share early-stage motion processing, even for reflexive eye movements such as torsion. But perception and eye movements differ in how they utilize higher-level motion or expectation signals. The dissociations might indicate how each system optimally meets different functional demands: Perception relies on object segregation, whereas eye movements rely on signal integration.Medicine, Faculty ofGraduat