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This Author published in this journals
All Journal Journal of Multidisciplinary Sustainability Asean International Journal of Language and Ubiquitous Learning
Esther Allen
United Methodist University
Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Other

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A Bioinformatics Analysis Of Circulating Microrna Signatures As Novel Biomarkers For Predicting Chemotherapy Response T. Amirul Muttaqin; Esther Allen; Beatriz Salazar
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2663

Abstract

Background. Chemotherapy response is highly variable, leading to ineffective treatment and toxicity. Reliable, non-invasive biomarkers to predict response a priori are urgently needed. Circulating microRNAs (miRNAs) are stable liquid biopsy candidates, but previous studies often lack robust validation. Purpose. This study aimed to identify and validate a novel, non-invasive circulating miRNA signature to accurately predict chemotherapy response using a large-scale bioinformatic approach. Method. A comprehensive in silico study was conducted. We aggregated and harmonized 948 patient samples from five public datasets (GEO, TCGA). A machine learning pipeline (LASSO + Random Forest) was applied to a Training Set (n=664) to discover a predictive signature. The signature was then validated in an Internal Testing Set (n=284) and a separate External Validation Cohort (n=120). Results. We aggregated and harmonized 948 patient samples from five public datasets (GEO, TCGA). A machine learning pipeline (LASSO + Random Forest) was applied to a Training Set (n=664) to discover a predictive signature. The signature was then validated in an Internal Testing Set (n=284) and a separate External Validation Cohort (n=120). We identified and validated a 7-miRNA circulating signature (c-miRSig). The model demonstrated high accuracy in both the internal (AUC 0.89) and external (AUC 0.86) validation sets. Conclusion. The signature was also a powerful prognostic tool, significantly stratifying patients for progression-free survival (p < 0.001). Functional analysis linked the signature to key chemoresistance pathways (PI3K-Akt, ABC transporters). The c-miRSig is a robust, non-invasive biomarker with dual predictive and prognostic power. This computationally validated signature provides a strong foundation for a clinically viable test to personalize chemotherapy, sparing non-responders from toxic, ineffective treatment.
Ubiquitous Learning Environments and Language Mastery: Designing Adaptive Platforms for 21st-Century Language Learners Nur Hakim; Samuel Tuan; Esther Allen
International Journal of Language and Ubiquitous Learning Vol. 4 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijlul.v4i3.3861

Abstract

Background. Ubiquitous learning environments (ULEs) have become a cornerstone in modern education, driven by the increasing use of digital technologies and mobile devices. These environments allow for continuous learning, enabling students to engage with educational content anytime and anywhere. In the context of language learning, ULEs present unique opportunities to enhance language mastery by providing adaptive, context-aware platforms that cater to the dynamic needs of 21st-century learners. However, the design and implementation of such platforms remain underexplored, particularly in how they can be optimized for language acquisition. Purpose. This study aims to design and evaluate adaptive language learning platforms within ubiquitous learning environments that support the development of language mastery. The research focuses on creating a dynamic platform that adjusts to learners’ needs, context, and progress, thereby fostering an engaging and personalized learning experience. Method. The study uses a mixed-methods approach, combining the design of a prototype adaptive language learning platform with empirical data collection from language learners using the platform. Participants’ language proficiency, engagement, and learning outcomes were assessed through pre- and post-tests, usage analytics, and surveys. Results. omes were assessed through pre- and post-tests, usage analytics, and surveys. The findings indicate that learners using the adaptive platform demonstrated significant improvements in language proficiency, particularly in speaking and listening skills. Additionally, learners reported higher engagement and satisfaction levels compared to traditional language learning methods. Conclusion. Adaptive platforms in ubiquitous learning environments can significantly enhance language learning outcomes by providing personalized and flexible learning experiences. Future research should focus on further optimizing these platforms for diverse learner populations.
Co-Authors Beatriz Salazar Nur Hakim Samuel Tuan T. Amirul Muttaqin