Abstract Early lung cancer screening is necessary to save lives, and for this reason, this study performed a thorough bioinformatic analysis of the GSE19188 dataset to identify the Bottleneck genes that enable a diagnosis based on breath Volatile Organic Compounds (VOCs). This analysis defined a TRIPOD Survival Signature, that means, the structural driver was COL11A1 (LogFC = 4.692), and the metabolic driver was PSAT1 (LogFC = 3.211) that opposed the canonical Warburg theory (LDHA downregulation, LogFC = −1.2788), favoring biosynthetic anaplerosis (Serine/Glycine). The third is the proliferative driver CDC20 (LogFC = 3.225). We have determined that PSAT1 overactivity provides a molecular connection for the design of an Electronic Nose (e-Nose) for the detection of VOCs produced by PSAT1 metabolites. This technology has potential for use in detection and screening for other types of cancers and metabolic disorders and should be further evaluated for these applications in future wo...

  This paper studies the semantic ambiguity inherent in Ancient Aramaic from polysemy. To fix the loss of nuance in translations, we used a new framework based on Quantum Natural Language Processing (QNLP). It uses Variational Quantum Machine Learning (VQML) with a 10-qubit architecture and 300 optimization cycles. The model found a temporal-hierarchical interpretation for qaddamay with a confidence level of 96.15%. In contrast, Bar had a confidence level of 34.5% due to the scarcity of data in ancient corpora. This work connects quantum algorithms to more transparency in the study of historical manuscripts. Available at  Using Quantum Machine Learning to Resolve Ambiguity in Aramaic | European Journal of Applied Science, Engineering and Technology

  Introduction: Early diagnosis of lung adenocarcinoma is a clinical priority to reduce global mortality, driving the development of various transcriptomic signatures. However, most lack a mechanistic axis connecting gene expression with external diagnostic signals. Objective: To characterize the Extended TRIPOD (E-TRIPOD) model, a five-gene signature (COL11A1, CDC20, PSAT1, LDHA, and UCK2) that integrates structural, proliferative, and metabolic drivers as a biological and theoretical foundation for future e-Nose-based screening. Methods: We analyzed the GSE19188 dataset and performed cross-validation on TCGA real-world data cohorts (n > 500). Kaplan-Meier survival analysis, functional enrichment in g:Profiler, and metabolic mapping via RSEA and KEGG were used to identify potential volatile byproducts. Results: The model showed exceptional prognostic power with a Hazard Ratio of 2.1 (P=8.8×10−16). Unlike standard models, E-TRIPOD reveals a mechanistic axis based on the pyrim...

  Abstract Determined through stylometric analysis is the nature of Saint Faustina Kowalska’s Diary as a dialogue with distinct linguistic traces. Using the Spanish version processed entirely in Python, the study identifies an unaltered conversation despite the translation shift. Validation of the record relies on the simultaneous execution of four independent methodologies. Data curation integrated N-gram Cosine Similarity, Burrows Delta Method, Hapax Legomena density and Principal Component Analysis. Results confirm a global stylistic consistency that rules out external editorial intervention. Scientifically problematic for a single psyche is the detected linguistic pattern with ontological authority and grammatical metrics foreign to Faustina's biographical style. She barely completed basic schooling. Available at  https://ejaset.com/index.php/journal/article/view/486/339