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117 citation(s) found for "Xu, Duan".

A phase 1/1b study of the theranostic pair RYZ811 (diagnostic) and RYZ801 (therapeutic) in patients with glypican-3-positive (GPC3+) previously treated unresectable hepatocellular carcinoma.
Mancini, Brandon Robert, Osman, Medhat, Fonkoua, Lionel Aurelien Kankeu, Meyer, Jeffrey , Mehr, Samuel H., Wang, Hui , Gong, Lucy, Harding, James J., Reilley, Matthew J. , Fonkoua, Lionel Aurelien Kankeu , Majeed, Umair , McConathy, Jonathan , Iravani, Amir , Duan, Heying , Harding, James J.

Journal of Clinical Oncology | January 12, 2026 | Volume: 44 | Issue: 2_suppl | Pages: No page available

10.1200/jco.2026.44.2_suppl.tps611 Get It

TPS611 Background: GPC3 is an oncofetal protein expressed in up to 75% of hepatocellular carcinomas (HCCs) and associated with poor prognosis. Its selective expression in tumor and not in normal tissue makes it a promising target for radiopharmaceutical imaging and therapy (theranostics). The GPC3-selective diagnostic RYZ811 ([ 68 Ga]Ga-RAYZ-8009) and therapeutic α particle-emitting RYZ801 ([ 225 Ac]Ac-RAYZ-8009) are a theranostic pair. Previous studies show high uptake of RYZ811 in intrahepatic and extrahepatic HCCs, with low normal liver background uptake. In GPC3+ HCC mouse models, single administrations of RYZ801 significantly inhibited tumor growth. Methods: RYZ801-101 is a single-arm, open-label, phase 1/1b study of RYZ811 and RYZ801 in previously treated patients with GPC3+ unresectable HCC. The study has two parts: dose escalation (part 1) and dose expansion (part 2). Each part consists of two stages: RYZ811 imaging and RYZ801 treatment. The aim of imaging is to determine if RYZ811 safely and adequately identifies patients with GPC3+ tumors. The aim of treatment is to determine the safety, pharmacokinetics (PK), recommended phase 2 dose (RP2D; part 1), and preliminary antitumor activity (part 2) of RYZ801. Key eligibility criteria are: confirmed HCC; Barcelona Clinic Liver Cancer stage B or C; Child-Pugh A; ≥1 RECIST v1.1-measurable lesion (treatment stage); and disease progression after ≥1 systemic therapy in part 1 and 1 prior line in part 2. In part 1, approximately 60 patients will receive RYZ811 (185 MBq) in the imaging stage; up to 30 of these will receive escalating doses of RYZ801 (2.6–5.5 MBq × 4 doses) in the treatment stage. In part 2, approximately 80 patients will receive RYZ811 (185 MBq) in the imaging stage; up to 40 of these will receive RYZ801 at the RP2D in the treatment stage. Primary RYZ811 objectives are to assess the safety/tolerability and biodistribution of RYZ811. Secondary objectives are to determine absorbed doses (ADs) to organs and tissues and any association between RYZ811 uptake and RYZ801 efficacy. Primary RYZ801 objectives are to identify the RP2D and safety/tolerability of RYZ801. Secondary objectives are to assess PK, ADs to critical organs and tumors, and preliminary antitumor activity. Enrollment for Part 1 is ongoing in the USA. Clinical trial information: NCT06726161 .
Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults
Jeon, Dae-Seong , Zhu, Lijing , Li, Haifang , Li, Pengze , Feng, Jingna , Duan, Tiehang , Song, Houbing , Tao, Cui , Niu, Shuteng , Jeon, Dong Hyun , Song, Houbing Herbert , Tao, Cui , Niu, Shuteng , Zhu, Lijing

Proceedings of the 34th ACM International Conference on Information and Knowledge Management | November 7, 2025 | Volume: No volume available | Issue: No issue available | Pages: 1035-1045

10.1145/3746252.3761282 | PMID 41940015 Get It

Bridging the Computational-Experimental Gap: Leveraging Large Language Model to Prioritize Alzheimer’s Therapeutics Based on Comparison of Learning Models
Li, Manqi , Li, Jianfu , Hu, Xinyue , Atık, Merve, Wang, Leiwei, Taner, Nilüfer, Xu, Yifeng, Niu, Shuteng , Xu, Yifeng, Liu, Duan , Xu, Xiaolei , Wang, Leiwei, Tao, Cui

No container title available | November 7, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-7811754/v1 | PMID 41282120 Get It

Abstract Alzheimer’s Disease (AD) 1 is a progressive neurodegenerative disorder with limited therapeutic options, driving interest in drug repurposing to accelerate treatment discovery. Drug repurposing has emerged as a promising strategy to accelerate therapeutic discovery by repositioning existing drugs for new clinical indications. Recent computational repurposing approaches, including knowledge graph reasoning, transcriptomic signature analysis, and integrative literature mining, have demonstrated strong predictive capabilities 2 . However, these methods often yield divergent drug rankings, which makes it difficult to decide which candidates to advance for experimental follow-up and results in substantial gaps between computational predictions and feasible in vivo validation 2 .To bridge this computational-experimental gap, we proposed an advanced prioritization framework leveraging large language models (LLMs). Our method systematically evaluated three state-of-the-art (SOTA) and representative computational methods (TxGNN 3 , Composition-based Graph Convolutional Network (CompGCN) 4 , and a regularized logistic regression (RLR) 5 , to analyze both their predictive performance and pharmaceutical class distributions. By integrating the strengths and divergences of these models, we generated a unified, streamlined list of 90 candidate drugs for further prioritization. We then utilized an LLM-based agent to perform evidence synthesis from biomedical literature abstracts for each candidate. This process mimics expert manual curation but significantly reduces human effort and time by efficiently distilling vast textual data into actionable insights. Applying consistent and transparent selection criteria, we obtained a refined and prioritized list of drug candidates suitable for subsequent in vivo experimental validation. The robustness and clinical relevance of our framework were validated using real-world data from Alzheimer’s patient cohorts, clinical trial registries, and expert pharmacological reviews. This comprehensive validation confirmed that our LLM-driven approach enhances efficiency, consistency, scalability, and generalizability. By integrating computational predictions with scalable evidence synthesis and multifaceted validation, our framework facilitated rapid and informed prioritization of repurposed drugs. Our framework can potentially accelerate the translational pathway toward viable AD therapeutics. Moreover, the versatility of our framework can also be applied to drug repurposing efforts for other diseases beyond AD.
Abstract 4367359: Understanding the association between patient empowerment level and patient-prioritized education topics in adult congenital patient population: A descriptive cross-sectional study
Banala, Keerthana Reddy , Valente, J. , Rivera, Andrea Carolina Godínez , Duan, Rong, Alano, Lindsay, Parang, Kim , Jaimes, Katia Bravo, Moons, Philip , Okumura, Megumi J. , Gurvitz, Michelle , Agarwal, Anushree , Valente, Joseph, Alano, Lindsay, Norris, Mark, Reardon, Leigh Christopher

Circulation | November 3, 2025 | Volume: 152 | Issue: Suppl_3 | Pages: No page available

10.1161/circ.152.suppl_3.4367359 Get It

Background: Adults with congenital heart disease (CHD) face ongoing physical, emotional, and psychosocial challenges that impact long-term outcomes. Research is limited on how their health topic interests vary by levels of empowerment. The 15-item Gothenburg Empowerment Scale (GES) assesses CHD patient empowerment across five domains. Objective: Examine the association between patient empowerment levels and patient-prioritized health education topics among adults with CHD. Methods: This cross-sectional study included adults (≥18) with self-reported CHD enrolled in the Empower My Congenital Heart digital study. Participants completed the GES survey and responded to open-ended questions regarding information of interest to them in managing their healthcare. GES scores were divided into tertiles, and responses were grouped into patient-prioritized topics. Descriptive analysis examined associations between empowerment levels and topic preferences. Results: Of 292 eligible patients, mean age was 45.6 ± 14.7 years, 91.4% were Caucasian, and 66.4% were female. The median (25th, 75th) GES score was 62 (57, 68). The most frequently observed patient prioritized topic was CHD health knowledge (73%), followed by interest in building CHD community (52.7%), lifestyle management (23.6%), health care navigation (7.2%), research and representation (5.1%). Participants in the lower and middle GES tertiles more frequently expressed interest in foundational sub-topics such as understanding CHD and surgical history, finding ACHD specialists, exercise and nutrition. In contrast, participants in the highest GES tertile prioritized sub-topics related to aging with CHD, managing menopause, CHD research and legislative activities. Peer support was a common topic across all groups (Figure 1). Patient quotes were stratified by tertile and patient prioritized health topics and subtopics as summarized in table 1. Conclusion: Adults with CHD prioritized varied health education topics depending on their baseline empowerment levels. Those with lower GES scores prioritized foundational information and guidance, while those with higher scores prioritized community-oriented and research-related topics. These findings could help tailor CHD patient-centered education strategies based on individual empowerment profiles.
Abstract 4371654: Acceptability and Feasibility Of A Digital Health Intervention For Adults with Congenital Heart Disease
Valente, J. , Banala, Keerthana, Buenrostro, Karina , Alano, Lindsay, Duan, Rong, Parang, Kim , Manyan, Karina, Jaimes, Katia Bravo, Moons, Philip , Okumura, Megumi J. , Gurvitz, Michelle , Agarwal, Anushree , Valente, Joseph, Alano, Lindsay, Norris, Mark, Reardon, Leigh Christopher

Circulation | November 3, 2025 | Volume: 152 | Issue: Suppl_3 | Pages: No page available

10.1161/circ.152.suppl_3.4371654 Get It

Background: Digital health offers a potential solution to support adults with congenital heart disease (CHD), filling the critical gap to help maintain recommended lifelong care with adult CHD specialists. However, its design and implementation require a rigorous scientific approach to make it scalable and usable for the target population. Objective: To pilot test the acceptability and feasibility of a digital health intervention to support lifelong healthcare for adults with CHD. Methods: Using a community-based participatory research and a behavioral theory-based approach, we developed and piloted a digital tool, Empower My Congenital Heart (EmpowerMyCH), within the web—and mobile-based Eureka Digital Research platform at UCSF. Intervention components within EmpowerMyCH include exhibits (expert and peer-developed learning modules on CHD-related topics such as finding specialists or navigating visits, tests, procedures, etc.), peer support, and a digital medical passport (Figure 1). Participants receive an exhibit with study measure surveys every two months, with a two-month completion window. Participant satisfaction with the digital tool is measured at six months using the Client Satisfaction Questionnaire-8 (CSQ-8), a validated survey with scores ranging from 8 to 32; higher scores indicate higher satisfaction with the digital tool. Results: Of the 519 participants recruited, 495 were eligible adults with CHD, 445 consented, and 6 withdrew. The median age was 43 (ranging from 20 to 85) years, and 30.1% were males. Survey completion rate was the highest at 88.7% during the first two months after enrollment and 53.5% at 8 months. Of the five exhibits delivered so far, over 87% of participants rated the exhibits to be helpful (Figure 2). Participants found the exhibits readable, easily accessible, motivational, useful, and educational (Figure 3). The median (25th, 75th) CSQ-8 score was 21 (18, 25) among 144 participants who completed the survey. Conclusions: EmpowerMyCH, the digital health tool, appears to be acceptable to most adults with CHD to support and educate them in navigating their healthcare. The tool and its contents are accessible, user-friendly, and responsive to the needs of the CHD community, resulting in high satisfaction rates. The feasibility rates and satisfaction scores are similar to or higher for EmpowerMyCH than those of prior digital health studies. Future hybrid intervention trials can demonstrate EmpowerMyCH‘s effectiveness.
Abstract 4368828: CUB domain-containing protein 1 Regulates Extracellular Matrix Remodeling and Src Kinase-Mediated Signaling in Human Cardiac Fibroblasts
Srinivas, Akshatha Narayanrao, Liu, Duan , Choi, Kyoung Moo , Weinshilboum, Richard, Tschumperlin, Daniel J. , Pereira, Naveen L. , Srinivas, Akshatha Narayanrao, Ghazal, Rachad

Circulation | November 3, 2025 | Volume: 152 | Issue: Suppl_3 | Pages: No page available

10.1161/circ.152.suppl_3.4368828 Get It

Background: Cardiac fibrosis is a critical and independent driver of heart failure (HF), characterized by excessive extracellular matrix (ECM) deposition. Decreased CDCP1 (CUB domain-containing protein 1) expression has been associated with myocardial recovery in human genome wide association studies by attenuating PDGF-BB driven cardiac fibroblast proliferation with no effect on canonical TGF-beta mediated transdifferentiation in-vitro. In-vivo, Cdcp1 deletion significantly reduced cardiac fibrosis and dysfunction in an angiotensin II/phenylephrine-induced pressure overload mouse model. However, its upstream regulators and its downstream effects on molecular signaling pathways that modulate ECM remodeling are unknown. Hypothesis: CDCP1 promotes human cardiac fibroblast mediated ECM remodeling in the HF microenvironment. Methods: Human ventricular fibroblasts (HVF) were treated with PDGF-BB (20 ng/ml), TGF-β (10 ng/ml), or Angiotensin II (100 ng/ml) for 48 hours. CDCP1 knockdown (KD) was achieved through siRNA transfection. Gene expression analysis was performed using qRT-PCR and protein quantification by Western blot. Both intact HVF and decellularized ECM were immunostained for collagen 1 to evaluate for ECM compositional changes. Results: Individual and combination treatments with fibrotic stimuli significantly increased CDCP1 expression (Figure 1A-1B). CDCP1 KD resulted in reduction of key ECM markers COL1A1, CTGF, and LOX (Figure 1C) across all fibrotic stimuli . Immunostaining of HVF after treatment with fibrotic stimuli showed reduced collagen 1 production with CDCP1 KD (Figure 1D). Western blot analysis showed increased phosphorylation of Src (tyr416) with 6h of treatment with fibrotic stimuli which was nullified by silencing of CDCP1 (Figure 1E). Conclusion: Our findings demonstrate that CDCP1 is necessary for ECM synthesis and Src signaling across multiple profibrotic pathways. Selective targeting of CDCP1 to modulate Src signaling pathways could provide novel therapeutic avenues for HF and fibrosis treatment.
Abstract 4366386: The Impact of Race/Ethnicity, Education, and Income on Patient Engagement in Adult Congenital Heart Disease Care
Rivera, Andrea Sandoval, Valente, J. , Banala, Keerthana Reddy , Duan, Rong, Alano, Lindsay, Parang, Kim , Jaimes, Katia Bravo, Moons, Philip , Okumura, Megumi J. , Gurvitz, Michelle , Agarwal, Anushree , Rivera, Andrea Sandoval, Valente, Joseph, Norris, Mark, Reardon, Leigh Christopher

Circulation | November 3, 2025 | Volume: 152 | Issue: Suppl_3 | Pages: No page available

10.1161/circ.152.suppl_3.4366386 Get It

Background: It is currently unknown whether patient engagement in adult congenital heart disease (CHD) care is influenced by social determinants of health (SDOH) such as race/ethnicity, education, and income. Adapting from the chronic care model, patient engagement, defined as the knowledge, skills, ability, and willingness to manage one’s health, can minimize lapses in care and improve CHD care outcomes. Methods: This cross-sectional study analyzes data from patients aged 18 and older with a self-reported diagnosis of CHD enrolled in a digital health research study called Empower My Congenital Heart. Patient engagement was measured using the Gothenburg Empowerment Scale (GES). We compared mean GES scores across demographic categories (race/ethnicity, education, and income), using independent samples t-tests or one-way ANOVA as appropriate. Additionally, we conducted a multivariate linear regression analysis to evaluate the impact of race/ethnicity, education, and income on GES scores, adjusting for age, gender, marital status, parental status, and employment status. Results: Of 323 adult CHD patients, the mean age was 45.6 ±15 years, 32.5% were males, 89.9% were non-Hispanic White, 29.7% had less than a Bachelor's degree, and 43.5% had less than $100,000 annual household income. The mean GES score was 61.8 ± 8, with significantly higher scores observed for non-Hispanic White identifying individuals (p=0.006) and those with a Bachelor's or higher level of education (p=0.005), while no difference across income levels (p = 0.394) (Figure 1). Linear regression analysis demonstrated that race and ethnicity remained significantly associated with GES scores (Table 1). Conclusions: Race/ethnicity and education level (in the bivariate analysis only), but not income, are the SDOH variables significantly associated with how empowered a CHD patient is in managing their health care. Future interventions that target enhancing patient engagement and self-management skills should take into consideration the influence of these demographic and social factors.
Abstract Thu133: Discovery of a Novel Compound Targeting CDCP1 to Modulate Human Cardiac Fibrosis
Srinivas, Akshatha Narayanrao, Wang, Min , Zhang, Heyu , Weber, Caleb, Islam, Naeyma N., Fuller, Jessica , Lambert, Laura , Weinshilboum, Richard M. , Pereira, Naveen L. , Ghazal, Rachad , Srinivas, Akshatha Narayanrao, Selvaraj, Manikandan , Marín-Goñi, Irene , Coban, Matt , Weber, Caleb, Fuller, Jessica, Liu, Duan , Lambert, Laura, Weinshilboum, Richard M. , Caulfield, Thomas R.

Circulation Research | October 8, 2025 | Volume: 137 | Issue: Suppl_1 | Pages: No page available

10.1161/res.137.suppl_1.thu133 Get It

Background: Cardiac fibrosis is a central pathological process that leads to worse outcomes in various cardiomyopathies. Recent evidence shows that CDCP1 (CUB domain-containing protein 1) modulates myocardial recovery by attenuating human cardiac fibroblast (HCF) proliferation. This study investigates the hypothesis that selective targeting of the CDCP1 cleavage domain can mitigate fibroblast proliferation, thereby offering a novel therapeutic approach to reducing cardiac fibrosis. Methods: A high-throughput in silico screening was performed using the Enamine compound library, focusing on structural regions that include the cleavage and adjacent sites of CDCP1 . A total of 147 candidate compounds were prioritized based on docking scores and binding stability profiles. Selected compounds were subsequently evaluated in vitro using HCF cultures seeded at 3,000 cells/well in 96-well plates. Each compound was administered at 10 μM concentration, and cell proliferation and viability were assessed by time-lapse imaging in the Incucyte® system at 24 and 96 hours. All experiments were done in triplicate with appropriate DMSO vehicle controls. Results: Compound C3 significantly reduced HCF proliferation (Fig B) to 27.3±2.4% relative to DMSO controls (99.9±0.5%, P <0.001) at 96 hours. Detailed structural modeling indicated that C3 binds to the CDCP1 cleavage site (Fig C) with a favorable Glide XP docking score of -7.66 kcal/mol. The interaction is stabilized by hydrogen bonds with Lys365 and Cys374 (Fig D), and supplementary hydrophobic interactions between aromatic rings and aliphatic groups, which contribute to a strong inhibitory effect. Conclusion: Targeting the CDCP1 cleavage domain with compound C3 effectively diminishes HCF proliferation in vitro. Therefore, these results substantiate the therapeutic potential of CDCP1 inhibition in cardiac fibrosis. Ongoing in vivo studies will explore the translational relevance of these findings.
Teleportation: Defense Against Stealing Attacks of Data-Driven Healthcare APIs
Wang, Zhenyi , Shen, Li , Luan, Siyu , Li, Fang , Doretto, Gianfranco , Adjeroh, Donald , Niu, Shuteng , Li, Jianfu , Tao, Cui , Tao, Cui , Niu, Shuteng , Li, Jianfu , Li, Fang , Duan, Tiehang , Shen, Li , Luan, Siyu

IEEE Transactions on Artificial Intelligence | July 29, 2025 | Volume: 7 | Issue: 3 | Pages: 1273-1289

10.1109/tai.2025.3593470 Get It