Gene expression analysis by differential display (DD) is limited by the labor-intensive visual evaluation of the electrophoretic data traces. We describe a flexible method for computer-assisted ranking of expression patterns in data from DD experiments. The method is based on a pairwise alignment and comparison of the quantitative trace data with respect to specific expression patterns defined by the investigator. The observed patterns are ranked according to a score value that identifies the most potential findings to be confirmed visually instead of the vast amount of original results. This two-step approach, enabled by the efficient computer algorithm for gene expression pattern comparison, will increase the percentage of true-positive findings chosen for the tedious downstream processing, while minimizing the cost and labor involved in large scale DD data analysis.
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http://dx.doi.org/10.1385/1-59259-968-0:111 | DOI Listing |
Neurol Neuroimmunol Neuroinflamm
March 2025
MeLis Institute, SynatAc Team, Inserm U1314/ UMR CNRS5284, France.
Background And Objectives: Breast cancers (BCs) of patients with paraneoplastic neurologic syndromes and anti-Yo antibodies (Yo-PNS) overexpress human epidermal growth factor receptor 2 (HER2) and display genetic alterations and overexpression of the Yo-onconeural antigens. They are infiltrated by an unusual proportion of B cells. We investigated whether these features were also observed in patients with PNS and anti-Ri antibodies (Ri-PNS).
View Article and Find Full Text PDFNeurol Neuroimmunol Neuroinflamm
March 2025
Department of Neurology, Mayo Clinic, Rochester, MN.
Background And Objectives: While it is well characterized in adults, little is known about the clinical features of neurofascin 155-IgG4 autoimmune nodopathy (NF155-IgG4 AN) in the pediatric population. In this study, we aimed to describe the clinical features and treatment outcomes in children diagnosed with neurofascin 155-IgG4 autoimmune nodopathy (NF155-IgG4 AN).
Methods: Pediatric and adult patients with NF155-IgG4 AN were identified retrospectively through the Mayo Clinic Neuroimmunology Laboratory database.
Sci Adv
January 2025
Disease Area Oncology, Novartis Institutes for Biomedical Research, CH-4002 Basel, Switzerland.
Cell lines and patient-derived xenografts are essential to cancer research; however, the results derived from such models often lack clinical translatability, as they do not fully recapitulate the complex cancer biology. Identifying preclinical models that sufficiently resemble the biological characteristics of clinical tumors across different cancers is critically important. Here, we developed MOBER, Multi-Origin Batch Effect Remover method, to simultaneously extract biologically meaningful embeddings while removing confounder information.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
State Key Laboratory of Frigid Zone Cardiovascular Diseases, Cardiovascular Research Institute and Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China.
Abdominal aortic aneurysm (AAA) is the most prevalent dilated arterial aneurysm that poses a significant threat to older adults, but the molecular mechanisms linking senescence to AAA progression remain poorly understood. This study aims to identify cellular senescence-related genes (SRGs) implicated in AAA development and assess their potential as therapeutic targets. Four hundred and twenty-nine differentially expressed genes (DEGs) were identified from the GSE57691 training set, and 867 SRGs were obtained.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Cancer Biology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
This study identifies microRNAs (miRNAs) with significant discriminatory power in distinguishing melanoma from nevus, notably hsa-miR-26a and hsa-miR-211, which have exhibited diagnostic potential with accuracy of 81% and 78% respectively. To enhance diagnostic accuracy, we integrated miRNAs into various machine-learning (ML) models. Incorporating miRNAs with AUC scores above 0.
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