Oral Frailty and Its Relationship with Physical Frailty in Older Adults: A Longitudinal Study Using the Oral Frailty Five-Item Checklist.

Background/objectives: Oral frailty, first identified in Japan in 2014, refers to a state between healthy oral function and severe decline, marked by minor issues, such as tooth loss and chewing difficulties. The oral frailty five-item checklist (OF-5) enables non-dental professionals to evaluate oral frailty using five key indicators: remaining teeth count, chewing difficulties, swallowing difficulties, dry mouth, and articulatory oral skills. Limited studies exist.

tomoseqr: A Bioconductor package for spatial reconstruction and visualization of 3D gene expression patterns based on RNA tomography.

RNA tomography computationally reconstructs 3D spatial gene expression patterns genome-widely from 1D tomo-seq data, generated by RNA sequencing of cryosection samples along three orthogonal axes. We developed tomoseqr, an R package designed for RNA tomography analysis of tomo-seq data, to reconstruct and visualize 3D gene expression patterns through user-friendly graphical interfaces. We show the effectiveness of tomoseqr using simulated and real tomo-seq data, validating its utility for researchers.

Association between frailty and subjective and objective sleep indicators in Japanese community-dwelling older adults.

Studies have linked frailty to sleep duration and/or quality using questionnaire-based subjective sleep assessments. This study clarified the relationship between frailty status and subjective and objective sleep indicators among community-dwelling older adults in a rural Japanese area. This cross-sectional cohort study analyzed the data of older adult participants in the FESTA Study, assessing subjective and objective sleep indicators using the Pittsburgh Sleep Quality Index (PSQI) and an actigraph, respectively.

Artificial intelligence-based personalized survival prediction using clinical and radiomics features in patients with advanced non-small cell lung cancer.

Background: Multiple first-line treatment options have been developed for advanced non-small cell lung cancer (NSCLC) in each subgroup determined by predictive biomarkers, specifically driver oncogene and programmed cell death ligand-1 (PD-L1) status. However, the methodology for optimal treatment selection in individual patients is not established. This study aimed to develop artificial intelligence (AI)-based personalized survival prediction model according to treatment selection.

Long-Term Response of Lorlatinib to Leptomeningeal Metastasis in Patients with Anaplastic Lymphoma Kinase Fusion Positive Non-Small Lung Cancer: A Case Report.

Introduction: Patients with anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) are at increased risk of central nervous system (CNS) metastasis at initial diagnosis and throughout treatment. In a phase 3 trial, lorlatinib, a third-generation ALK tyrosine kinase inhibitor, significantly improved progression-free survival. In further analysis, lorlatinib revealed superior intracranial efficacy and prolonged time to intracranial progression compared with crizotinib.