https://scholar.dgist.ac.kr/handle/20.500.11750/371 2026-08-31T11:56:38Z https://scholar.dgist.ac.kr/handle/20.500.11750/60690 Title: Identification of a robust multitarget protein panel for Parkinson’s disease via absolute quantification and large-scale external replication Author(s): Lee, Ho-Won; Choi, Youngtae; Lee, Shinrye; Kim, Jung-Eun; Jeon, Min-Tae; Jo, Myungjin; Park, Gyuri; Park, Jin-Sung; Kim, Do-Geun; Cheon, Mookyung; Kim, Hyung-Jun Abstract: This study aimed to identify and validate a robust, generalizable panel of plasma protein biomarkers to improve diagnostic precision in Parkinson’s disease. We analysed plasma samples from 12 patients with [18F]-FP-CIT PET-confirmed Parkinson’s disease and 15 healthy controls using the Olink Target 96 Inflammation Panel to identify differentially expressed proteins. Candidate biomarkers were subsequently validated through absolute quantification using Luminex and Olink Flex platforms in an independent cohort of 46 patients with Parkinson’s disease and 33 amyloid-negative and cognitively normal control participants. To assess generalizability, the findings were replicated across multiple heterogeneous populations using large-scale datasets from the UK Biobank and Global eurodegeneration Proteomics Consortium (GNPC) cohorts. Markers of neurodegeneration [neurofilament light chain (NfL)] and Alzheimer’s disease [phosphorylated tau (pTau181), amyloid β [Aβ]42, Aβ40] co-pathology were measured using the single molecule array platform. Our analyses revealed elevated levels of interleukin (IL)-10 and IL-17C and reduced levels of urokinase plasminogen activator (uPA) and neurotrophin-3 (NTF3) in patients with Parkinson’s disease. These findings were confirmed in the validation cohort. Multitarget models demonstrated superior diagnostic performance over individual markers, with the combination of IL-17C and uPA achieving the highest discrimination (area under the curve = 0.780). External validation in the UK Biobank and NPC datasets confirmed consistent directional changes of three candidates (IL-17C, NTF3 and uPA), reinforcing the biological relevance of these markers. Notably, while NfL levels were significantly elevated in Parkinson’s disease, no significant differences were observed for pTau181 levels or Aβ42/Aβ40 ratios. These findings identify a specific plasma protein panel, particularly the combination of IL-17C and uPA, as a robust and generalizable diagnostic signature that captures fundamental pathophysiological aspects of Parkinson’s disease and enhances diagnostic precision alongside established biomarkers. 2025-12-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60688 Title: Cold-injection synthesis of highly emissive perovskite nanocrystals Author(s): Kim S.; Kim S.-A.; Park G.-S.; Kim E.; Kim D.-H.; Lee S.-C.; Woo S.-J.; Jang Y.; Kweon J.J.; Kang S.; Lee M.; Yun H.J.; Park S.; Shim H.-J.; Kim J.S.; Jang K.Y.; Sung M.-J.; Park C.-Y.; Chang S.E.; Park J.; Lee S.K.; Lee T.-W. Abstract: Colloidal perovskite nanocrystal (PeNC) has long been synthesized using the hot-injection method and room-temperature ligand-assisted reprecipitation as the prominent techniques1,2. However, both methods have challenges for industrial-scale production3–5 : the hot-injection method requires high temperatures, an inert gas environment and rapid cooling, which raise safety concerns, whereas ligand-assisted reprecipitation can exhibit limited productivity on scale-up. Here we present a coldinjection method based on pseudo-emulsion, enabling scalable synthesis of PeNCs with near-unity photoluminescence quantum yield (PLQY, ~100%) and enhanced stability by injecting precursor solution below 4 °C. In the cold-injection method, PeNCs grow through the assembly of fully coordinated plumbates out of the pseudoemulsion with the assistance of a demulsifier. We discovered that slow assembly of polybromide plumbates, assisted by cold temperature, is essential for defect suppression, resulting in reproducible, stable and pure-green-emitting PeNCs with near-unity PLQY. Furthermore, this method enables efficient large-scale production, achieving 20-l-scale synthesis with remarkable batch weight while maintaining near-unity PLQY. Our findings represent a substantial advancement in synthesis of high-quality PeNCs, offering potential for broad applications in display and lighting industries. 2026-02-28T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60671 Title: Hyperbolic Prototype-Residual Autoencoder for Interpretable Generative Latent Organization Author(s): Lee, Hyunjong; Kwak, Jeongho Abstract: Interpretable organization of latent spaces remains a central challenge in generative modeling. Most generative models rely on continuous latent variables, but the learned space often lacks an explicit structure that explains how samples are organized or how semantic variation can be controlled. This paper proposes a hyperbolic prototype-residual autoencoder that organizes generative latent representations using a fixed prototype tree embedded in the Poincar & eacute; ball. Each encoded sample is assigned to a prototype by hyperbolic distance, and the decoder reconstructs or generates images from a prototype-residual representation. The prototype serves as a semantic anchor, while the residual captures local instance-level variation around the selected prototype. The framework combines prototype semantic learning, MMD-based latent spreading, and structural regularizers to align encoder-decoder behavior with the predefined hyperbolic hierarchy. Prototype semantic learning encourages fixed prototypes to decode into representative visual anchors, while MMD encourages encoded samples to occupy broad regions of the hyperbolic latent space. Experiments on MNIST and CelebA show interpretable coarse-to-fine behavior through radial decoding and prototype decoding, suggesting that fixed hyperbolic prototype trees provide an effective scaffold for prototype-guided image reconstruction and generation. 2026-07-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60670 Title: LanthanideDoping and Dual-Site Switching on AmorphousHigh-Entropy Metallene Oxides Boost Acidic Water Oxidation Author(s): Li, Yinghao; Sun, Yuntong; Chen, Mengshan; Zhou, Yingtang; Fan, Wenjun; Lee, Jong-Min Abstract: High-entropy oxides (HEOs) are promising electrocatalysts for breaking the Sabatier principle and maximizing their oxygen evolution reaction (OER) efficiency. Herein, the effect of lanthanide doping on RuIr-based HEOs is investigated through theoretical and experimental studies. The optimized amorphous RuIrMnCoGd high-entropy metallene oxides (a-Gd_HEMOs) with moderate intermediate affinity exhibit a small overpotential of 211 mV and an ultralong stability of 700 h at 10 mA cm(-2) in acidic media. Integrated into a proton exchange membrane electrolyzer, they deliver 3.0 A cm(-2) at 1.872 V and maintain stable operation for 300 h at 1.0 A cm(-2). Operando characterizations reveal the changes in electronic configurations and coordination environments of Ru and Ir sites during OER. Theoretical simulations further clarify the adsorbate evolution mechanism and the distinct role of the constituent elements. Specifically, the switching of Ru and activated Ir as primary active sites at low and high potentials, respectively, enhances robustness for oxygen generation. 2026-07-31T15:00:00Z