DSpace Community:

DNA-functionalized nanomaterials for optical biosensors: Mechanisms, applications, and design perspectives

2026-03-16T07:17:10Z

Title: DNA-functionalized nanomaterials for optical biosensors: Mechanisms, applications, and design perspectives Authors: Han, Chaewon; Park, Soye; Park, Sehyeon; Lee, Dakyeon; Jo, Hyunda; Seo, Sejeong; Han, Hyunho; Jeong, Sanghwa; Kwon, Woosung Abstract: Background: DNA-functionalized nanomaterials have emerged as a powerful platform for optical biosensing, where DNA's intrinsic molecular recognition imparts high sensitivity and selectivity. However, the integration of DNA with optically active nanomaterials introduces new opportunities and challenges in signal transduction, stability, and application-specific optimization. Despite growing interest in this hybrid field, a unified framework for evaluating and comparing different nanomaterial platforms in the context of DNA-guided sensing is lacking. This review addresses this gap by systematically analyzing the mechanisms and applications of DNAfunctionalized optical biosensors. Results: We provide a comprehensive and critically integrated overview of DNA-functionalized nanomaterials across six major platforms: carbon dots, carbon nanotubes, metal nanoparticles, quantum dots, graphene quantum dots, and silicon-based nanoparticles. Each system is examined in terms of its optical sensing mechanisms, such as fluorescence, FRET, and colorimetric response, and its performance in detecting targets including metal ions, small molecules, nucleic acids, proteins, and pathogens. A direct comparison is presented based on practical criteria such as detection wavelength, detection range, functionalization efficiency, and biocompatibility. We further discuss recent applications in disease diagnostics, point-of-care testing, environmental monitoring, and food safety, along with challenges including signal reproducibility, surface DNA quantification, and stability in complex matrices. Significance: This review establishes a comparative foundation for evaluating DNA-guided optical biosensors and identifies emerging trends and design strategies across material classes. The insights provided are expected to inform the rational development of next-generation biosensors with enhanced precision, accessibility, and real-world applicability.

Association of initial transurethral resection staging on survival in radical cystectomy patients

2026-04-29T08:21:42Z

Title: Association of initial transurethral resection staging on survival in radical cystectomy patients Authors: Choi, Joongwon; Song, Wan; Nam, Jong Kil; Lim, Bumjin; Nam, Wook; Oh, Jong Jin; Jeong, Seung-hwan; Kang, Seok Ho; Kim, Tae-Hwan; Heo, Ji Eun; Ham, Won Sik; Song, Geehyun; Seo, Ho Kyung; Lee, Chung Un; Lee, Yong Seong; Choi, Se Young; Kim, Kyung Hwan; Jeong, Byong Chang Abstract: Purpose: Muscle-invasive bladder cancer (MIBC) is highly aggressive and presents complex treatment challenges. This study aimed to determine if the stage found during the initial transurethral resection of bladder tumor (TURBT) significantly impacts the prognosis of patients undergoing subsequent radical cystectomy (RC). Materials and Methods: We retrospectively analyzed a multi-institutional database of 3,258 RC patients treated between January 2010 and December 2019, with confirmed survival data. The analysis included 68 variables such as baseline characteristics, initial and highest TURBT pathology, and final pathology. Patients were categorized into four groups based on initial T stage: pTa, pT1, pT2, and Tis (carcinoma in situ). Results: The mean follow-up was 46.6 +/- 38.7 months. There were no significant differences in demographic variables between the groups. Overall survival (OS) rates differed significantly across the four groups (p=0.017). Crucially, the Tis group demonstrated the most favorable long-term outcomes, with an OS rate over 60% at 150 months. The initial pTa, pT1, and pT2 groups did not show significant OS differences among themselves. Conclusions: The initial TURBT stage is associated with the prognosis of patients undergoing RC for bladder cancer. Patients with carcinoma in situ (Tis) is associated with more favorable outcomes from earlier cystectomy, leading to markedly improved long-term survival. For patients with more advanced initial stages (pT1, pT2), however, final pathology and lymph node status are more predictive of survival than the initial TURBT findings.

Impact of carcinoma in situ of bladder at transurethral resection and radical cystectomy on survival: Retrospective multicenter study

2026-04-29T08:21:41Z

Title: Impact of carcinoma in situ of bladder at transurethral resection and radical cystectomy on survival: Retrospective multicenter study Authors: Heo, Ji Eun; Kim, Jongchan; Jang, Won Sik; Sung, Hyun Hwan; Lim, Bumjin; Jeong, Seung-hwan; Oh, Jong Jin; Song, Geehyun; Seo, Ho Kyung; Kim, Tae-Hwan; Ha, Yun-Sok; Nam, Wook; Kim, Kyung Hwan; Nam, Jong Kil; Noh, Tae Il; Kang, Seok Ho; Jeong, Byong Chang; Ham, Won Sik Abstract: Purpose: Carcinoma in situ (CIS) of the bladder is a high-grade, non-invasive lesion known to increase the risk of recurrence and progression. However, the prognostic significance of CIS identified at transurethral resection of bladder tumor (TURB) versus radical cystectomy (RC) remains controversial. This study aimed to evaluate the impact of CIS at different treatment stages on recurrence-free survival (RFS) and cancer-specific survival (CSS). Materials and Methods: A retrospective multicenter study was conducted using data from 2,553 patients who underwent TURB followed by RC between 2010 and 2019 across eleven Korean institutions. Kaplan-Meier survival curves and Cox proportional hazards models were used to assess the association of CIS at TURB and RC with RFS and CSS, adjusting for clinicopathological variables. Results: CIS was identified in 731 TURB specimens (28.6%) and 821 RC specimens (32.2%). Patients with CIS at TURB had significantly higher RFS (p<0.001) and CSS (p=0.002) compared to those without. In multivariate analysis, CIS at TURB was independently associated with better RFS (hazard ratio [HR] 0.787, p=0.001) but not CSS (HR 0.989, p=0.905). CIS at RC showed no significant association with either RFS or CSS. Independent predictors of poor survival included advanced stage, lymph node involvement, lymphovascular invasion, and positive surgical margins. Adjuvant therapy was associated with improved CSS. Conclusions: CIS at TURB is associated with a lower recurrence risk following RC, whereas CIS in RC specimens has limited prognostic impact. These findings suggest CIS at TURB may carry different prognostic implications than traditionally assumed, warranting careful clinical interpretation.

A Novel Radiomics-based Interpretable Model for Bladder Cancer Grade Prediction Using White-Light Cystoscopy Images

2026-05-12T08:35:44Z

Title: A Novel Radiomics-based Interpretable Model for Bladder Cancer Grade Prediction Using White-Light Cystoscopy Images Authors: Choi, Yewon; Cho, Sang Wouk; Hong, Junho; Lee, Jongsoo; Kim, Hwiyoung; Lee, Kwang Suk Abstract: Background and objective: White-light cystoscopy (WLC) is the standard diagnostic modality for bladder cancer, but preoperative grading remains inaccurate. We developed a multichannel radiomics model to predict tumour grade (low-grade [LG] vs high-grade [HG]) from WLC and to identify imaging biomarkers. Methods: WLC images were retrospectively collected from 423 patients across two centres. A total of 2624 tumour regions were segmented for training, with 584 and 358 regions for internal and external validation, respectively. Radiomic features were extracted from the greyscale and red-green-blue channels. Feature selection was performed using coefficient thresholding and the least absolute shrinkage and selection operator. Five machine-learning classifiers were trained. Model performance was assessed using discrimination, calibration, and decision curve analysis (DCA). Interpretability was assessed using SHapley Additive exPlanations (SHAP) and feature visualisation. Key findings and limitations: The support vector machine model achieved robust performance, with an area under the receiver operating characteristic curve of 0.87 (95% confidence interval [CI] = 0.84-0.89) for internal validation and 0.79 (95% CI = 0.73-0.85) for external validation. SHAP analysis revealed distinct radiomic patterns differentiating LG from HG tumours. Limitations include retrospective design, manual segmentation, and a small, imbalanced external set, so validation reflects preliminary transportability rather than robustness or generalisability. Although calibration was acceptable and net benefit appeared at thresholds >= 0.30, external data constraints warrant caution. Conclusions and clinical implications: The proposed multichannel radiomics model supports grade prediction from WLC images and identifies a green channel. This approach provides a basis for developing real-time, filter-based tools for intraoperative risk stratification. (c) 2026 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).