Clinical potential of undercarboxylated osteocalcin in metabolic and neurodegenerative diseases: From biomarker to therapeutic target
Peer-Reviewed Publication
Updates every hour. Last Updated: 14-Nov-2025 01:11 ET (14-Nov-2025 06:11 GMT/UTC)
Osteocalcin (OCN), a non-collagenous protein synthesized by osteoblasts, is integral to bone mineralization and demonstrates significant effects on metabolic and neurological functions. Its undercarboxylated form, Glu-OCN, has emerged as a key regulator of glucose metabolism in diabetes, bone density in osteoporosis (OP), and lipid metabolism in conditions such as nonalcoholic fatty liver disease (NAFLD). Additionally, Glu-OCN is implicated in neurodegenerative and cardiovascular diseases through its roles in neurotransmitter synthesis and vascular calcification, respectively. This review examines the essential functions of Glu-OCN in the management of metabolic and neurodegenerative disorders, emphasizing its significance as both a diagnostic biomarker and therapeutic target. While findings to date are promising, most studies remain observational. Advanced detection methodologies and extensive longitudinal studies are urgently needed to elucidate the mechanisms and clinical applications of Glu-OCN. Advancements in this area could facilitate the integration of Glu-OCN into personalized medicine approaches, improving early diagnosis, risk assessment, and treatment monitoring.
α-phase formamidinium lead triiodide (FAPbI3) has demonstrated extraordinary properties for near-infrared perovskite light-emitting diodes (NIR-PeLEDs). The vacuum processing technique has recently received increasing attention from industry and academia due to its solvent-free feature and compatibility with large-scale production. Nevertheless, vacuum-deposited NIR-PeLEDs have been less studied, and their efficiencies lag far behind those of solution-based PeLEDs as it is still challenging to prepare pure α-FAPbI3 by the thermal evaporation. Herein, we report a Cs-containing triple-source co-evaporation approach to develop the perovskite films. The addition of thermally stable Cs cation fills in the perovskite crystal lattice and eliminates the formation of metallic Pb caused by the degradation of FA cation during the evaporation process. The tri-source co-evaporation strategy significantly promotes the phase transition from yellow δ-phase FAPbI3 to black α-phase FACsPbI3, fostering smooth, uniform, and pinhole-free perovskite films with higher crystallinity and fewer defects. On this basis, the resulting NIR-PeLED based on FACsPbI3 yields a maximum EQE of 10.25%, which is around sixfold higher than that of FAPbI3-based PeLEDs. Our work demonstrates a reliable and effective strategy to achieve α-FAPbI3 via thermal evaporation and paves the pathway toward highly efficient perovskite optoelectronic devices for future commercialization.
In the quest for high-efficiency and cost-effective catalysts for the oxygen evolution reaction (OER), a novel biomass-driven strategy is developed to fabricate a unique one-dimensional rod-arrays@two-dimensional interlaced-sheets (C1D@2D) network. A groundbreaking chemical fermentation (CF) pore-generation mechanism, proposed for the first time for creating nanopores within carbon structures, is based on the optimal balance between gasification and solidification. This mechanism not only results in a distinctive C1D@2D multilevel network with nanoscale, intersecting and freely flowing channels but also introduces a novel concept for in situ, extensive and hierarchical pore formation. The unique architecture, combined with the homogeneous dispersion of Ni–Fe nanoparticles, facilitates easy electrolyte penetration and provides abundant active sites for the anchoring and dispersion of reactive molecules or ions. Consequently, the Ni–Fe@C1D@2D porous network demonstrates an exceptional OER electrocatalytic performance, achieving a record-low overpotential of 165 mV at 10 mA cm-2 and maintaining long-term stability for over 90 h. Theoretical calculations reveal that the porous structure markedly strengthens the interaction between alloy nanoparticles and the carbon matrix, thereby significantly boosting their electrocatalytic activity and stability. These findings unequivocally validate the CF pore-generation mechanism as a powerful and innovative strategy for designing highly efficient functional nanostructures.
A research team used flowering data from 169 rice genotypes—each with over 700,000 SNP markers—across multiple environments to develop a robust framework for phenotypic prediction.
A research team has identified a key gene, CsCHLI, that plays a central role in chlorophyll biosynthesis and leaf coloration in tea plants.
HPVTIMER is a comprehensive web-based analysis tool based on the GEO database for HPV-associated cancers. HPVTIMER has four embedded analysis modules: Differential expression analysis module, Correlation analysis module, Immune infiltration analysis module, and Pathway analysis module. HPVTIMER supports users in performing longitudinal systematic analyses and cross-sectional comparisons of data, which can help users explore the tumour immune microenvironment of HPV-associated cancers and search for potential immune regulatory mechanisms and immunotherapeutic targets.
Researchers have systematically elucidated the anti-tumour mechanisms of regulatory T cells (Tregs) for the first time. These immune cells not only suppress pro-tumour inflammation but also enhance anti-tumour immunity, challenging the long-held view that Tregs inevitably promote tumour progression. This discovery provides key insights for developing next-generation immunotherapy strategies.
Drug sensitivity analysis is crucial for precision cancer therapy. We developed CPADS, a web tool integrating transcriptomic data from 29,000+ samples (44 cancers, 288 drugs, 9,000+ gene perturbations). It enables differential expression, pathway, drug, and gene perturbation analyses with interactive visualization. CPADS aids researchers in exploring drug resistance mechanisms at gene/pathway levels. Access: https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.
We are thrilled to announce the publication of our groundbreaking work in PLoS Computational Biology, introducing PESSA (Pathway Enrichment Score-based Survival Analysis) – a robust, user-friendly web platform designed to revolutionize cancer survival data analysis. PESSA uniquely integrates pathway enrichment status as a critical biomarker, offering oncologists and researchers unprecedented insights. Our platform boasts an expansive curated database of over 200 cancer datasets from leading sources (GEO, TCGA, EGA, and published literature), encompassing 51 cancer types, 13 distinct survival outcome measures, and over 13,000 tumor-relevant pathways. PESSA is meticulously designed to accelerate the discovery and validation of novel cancer-related pathway biomarkers. Access PESSA today at: https://smuonco.shinyapps.io/PESSA/ or http://robinl-lab.com/PESSA.