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Cryptotanshinone Suppresses the STAT3/BCL-2 Pathway to Provoke Human Bladder Urothelial Carcinoma Cell Death

Environmental Toxicology 2025年第4期40卷 624-635页

作者： Tung, Min-Che Chang, Ge-Man Dai, Wen-Chyi Hsu, Chen-Hsuan Chang, Hsiang-Chun Yang, Wei-Ting Ho, Yann-Jen Lu, Chien-Hsing Chen, Yi-Hsin Chang, Chia-Che Division of Urology Department of Surgery Tungs' Taichung MetroHarbor Hospital Taichung Taiwan Graduate Institute of Biomedical Sciences National Chung Hsing University Taichung Taiwan Doctoral Program in Biotechnology Industrial Innovation and Management National Chung Hsing University Taichung Taiwan Department of Life Sciences National Chung Hsing University Taichung Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung Taiwan Doctoral Program in Translational Medicine National Chung Hsing University Taichung Taiwan Department of Nephrology Taichung Tzu Chi Hospital Buddhist Tzu chi Medical Foundation Taichung Taiwan School of Medicine Tzu Chi University Hualein Taiwan Department of Artificial Intelligence and Data Science National Chung Hsing University Taichung Taiwan Master Program in Precision Health Rong Hsing Research Center for Translational Medicine The iEGG and Animal Biotechnology Research Center National Chung Hsing University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan

Bladder cancer is one of the most common human malignancies worldwide. Aberrant activation of signal transducer and activator of transcription 3 (STAT3) is crucial to driving malignant progression and predicting poor prognosis of multiple human cancers, including bladder cancer, making STAT3 a promising target of cancer therapeutics. Cryptotanshinone (CTS) is an anticancer ingredient of Danshen (Salvia miltiorrhiza), a top-graded Chinese medicinal herb. However, whether CTS targets STAT3 to exert its cytotoxic effect on human bladder cancer remains unknown. Herein, we demonstrated that CTS is cytotoxic to multiple human urinary bladder transitional cell carcinoma (TCC) cell lines while sparing normal human urothelial cells. CTS provoked apoptosis-dependent bladder TCC cytotoxicity, as apoptosis blockage by z-VAD-fmk markedly rescued the clonogenicity of CTS-treated cells. Besides, CTS was found to suppress constitutive and interleukin 6-inducible activation of STAT3, evidenced by the downregulation of STAT3 tyrosine 705 phosphorylation and BCL2, a recognized STAT3 transcriptional target. Notably, ectopic expression of a dominant-active STAT3 mutant (STAT3-C) or BCL-2 alleviated CTS-induced apoptosis and clonogenicity inhibition, thus confirming STAT3 blockade as a pivotal mechanism of CTS's cytotoxic action on bladder TCC cells. Lastly, immunoblotting revealed that CTS lowered the levels of active JAK2, an upstream kinase that mediates STAT3 tyrosine 705 phosphorylation. Altogether, we conclude that the blockade of the JAK2/STAT3/BCL-2 antiapoptotic signaling axis is a vital mechanism whereby CTS provokes bladder cancer cytotoxicity. The current evidence implicates CTS's potential to be translated into a bladder cancer therapeutic agent. © 2024 Wiley Periodicals LLC.

关键词： Cell death

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Developing Chatbots as Virtual Clients for Empathy Training in Counselor Education: Examining Feasibility from Users’ Perspectives

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Bulletin of Educational Psychology 2025年第3期56卷 539-570页

作者： Hsieh, Lih-Horng Liu, En-Yu Lin, Chi-Min Liu, Chia-Jyi Department of Counseling and Guidance National Changhua University of Education Taiwan School of Medicine College of Medicine Taipei Medical University Taiwan Data Science Degree Program National Taiwan University Taiwan Department of Physics National Changhua University of Education Taiwan

The purpose of this research is to develop chatbots as virtual clients (VCs) for empathy training, and to explore the feasibility assessment of using chatbots to assist in empathy training for students in counseling and guidance-related departments. The virtual clients are developed and tested based on chatbots using domain knowledge of empathy training. Chatbots are powered by natural language processing engines and trained by corpora of dialogues involving various emotions. As such, using chatbots serving as VCs allows the interlocutor to practice empathy skills with diversity and richness. After chatbots are successfully transformed into VCs, 60 volunteers from the Department of Guidance and Counseling are recruited to experience the interaction with VCs, followed by immediately conducting user experience surveys to understand users’ subjective feelings and thoughts for evaluating the ease of use and effectiveness of VC. Chatbots are successfully transformed into VCs by implementing corpora of emotions into “custom brain” of chatbots. The content of corpora includes client scenarios that are consistent with the goals of empathy training for undergraduates in guidance and counseling or psychotherapy. Test results show that the average score from the User Experience Questionnaire of the testers exceeds level 5 (1-7), which is a state of satisfaction. In terms of System Usability Scale, the average score is 4 (1-5), indicating agreement with the system’s usability. Along with qualitative feedback, testers agreed on the usability of the chatbot system, stating that most people can quickly learn to use the system, interact with the virtual client (VC) without stress, feel relaxed, and want to continue the conversation. They believe that VC is suitable for practicing empathy skills, reducing anxiety during practice, and improving empathy response skills through such practice. From the observation of the testers during the test process, the testers showed curious and in

关键词： counselor education empathy empathy training courses smart chatbots virtual clients

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Synergetic effects of multiple junction and surface hydroxyl in Cu/CuO/Cu2O/TiO2 heterostructures towards highly efficient photocatalysts for hydrogen generation

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Materials science for Energy Technologies 2025年 8卷 131-142页

作者： Subagyo, Riki Anindika, Garcelina Rizky Aufkani, Afif Akmal Zhang, Lei Ardhyananta, Hosta Burhan, R.Y. Perry Nugraheni, Zjahra Vianita Akhlus, Syafsir Bahruji, Hasliza Prasetyoko, Didik Wellia, Diana Vanda Ivansyah, Atthar Luqman Arramel Kusumawati, Yuly Department of Chemistry Faculty of Science and Analytic Data Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Center of Excellence Applied Physics and Chemistry Nano Center Indonesia Jl PUSPIPTEK South Tangerang Banten15314 Indonesia Department of Physics National University of Singapore Singapore117551 Singapore Department of Materials and Metallurgical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Centre of Advanced Material and Energy Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Andalas Padang25163 Indonesia Master Program in Computational Science Faculty of Mathematics and Natural Science Institut Teknologi Bandung Jalan Ganesha No. 10 Bandung40132 Indonesia Instrumentation and Computational Physics Research Group Department of Physics Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jalan Ganesha No.10 West Java Bandung40132 Indonesia

The implementation of titanium dioxide (TiO2) as a photocatalyst material in hydrogen (H2) evolution reaction (HER) has embarked renewed interest in the past decade. Rapid electron-hole pairs recombination and wide band gap of a photo-sensitive material of TiO2 are detrimental toward the targeted catalytical reaction. In this study, we present the rational design, fabrication, photocatalytic performance of TiO2-Cu/CuO/Cu2O heterostructures (CuTi) using viable chemical reduction method. The Z-scheme and S-scheme are succesfully generated across the TiO2/CuO/Cu2O interfaces, while the Schottky junction arises on the Cu perimeters. This is evidenced from the blue shifted about 0.3 eV of Cu 2p core level determined by using X-ray photoemission spectroscopy (XPS), in combination with the formation of inverse V-shape of the Mott-Schottky plots. In addition, we find that Cu/CuO/Cu2O facilitates photon absorption range up to the visible region. The multiple heterojunction and the large number of OHsurface enhanced charge carrier transfer are associated to the suppression of photoluminescence (PL) intensity, high surface hydroxyl (OHsurface) density in CuTi probed by XPS, and fast electron transfer based on the electrochemical measurements. The presence of OHsurface inhibits the recombination of electron. A significant H2 photogeneration rate enhancement is achieved when an optimized 5 wt% Cu/CuO/Cu2O concentration is used on TiO2 to achieve 7,157.19 μmol·g−1 (1,789.30 μmol·g−1·h−1). Based on this finding, zero emission energy innitiative could be materialized under multiple heterojunctions in photocatalytic process is beneficial for enhancing the H2 production. © 2025 The Authors

关键词： Titanium dioxide

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SHIFTING ATTENTION TO YOU: PERSONALIZED BRAIN-INSPIRED AI MODELS

arXiv

引用

arXiv 2025年

作者： Zhao, Stephen Chong Hu, Yang Lee, Jason Bender, Andrew Wallace, Mark Tovar, David A. Mazumdar, Trisha Data Science Institute Vanderbilt University Nashville United States Department of Computer Science Vanderbilt University Nashville United States Neurosciences Graduate Program University of California San Diego San Diego United States Department of Psychology Vanderbilt University Nashville United States

The integration of human and artificial intelligence represents a scientific opportunity to advance our understanding of information processing, as each system offers unique computational insights that can enhance and inform the other. The synthesis of human cognitive principles with artificial intelligence has the potential to produce more interpretable and functionally aligned computational models, while simultaneously providing a formal framework for investigating the neural mechanisms underlying perception, learning, and decision-making through systematic model comparisons and representational analyses. In this study, we introduce personalized brain-inspired modeling that integrates human behavioral embeddings and neural data to align with cognitive processes. We took a stepwise approach, fine-tuning the Contrastive Language–Image Pre-training (CLIP) model with large-scale behavioral decisions, group-level neural data, and finally, participant-level neural data within a broader framework that we have named CLIP-Human-Based Analysis (CLIP-HBA). We found that fine-tuning on behavioral data enhances its ability to predict human similarity judgments while indirectly aligning it with dynamic representations captured via magnetoencephalography (MEG). To further gain mechanistic insights into the temporal evolution of cognitive processes, we introduced a model specifically fine-tuned on millisecond-level MEG neural dynamics (CLIP-HBA-MEG). This model resulted in enhanced temporal alignment with human neural processing while still showing improvement on behavioral alignment. Finally, we trained individualized models on participant-specific neural data, effectively capturing individualized neural dynamics and highlighting the potential for personalized AI systems. These personalized systems have far-reaching implications for the fields of medicine, cognitive research, human-computer interfaces, and AI development. © 2025, CC BY-NC-ND.

关键词： Magnetoencephalography

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Unbiased Parameter Estimation for Bayesian Inverse Problems

arXiv

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arXiv 2025年

作者： Chada, Neil K. Jasra, Ajay Maama, Mohamed Tempone, Raul Department of Mathematics City University of Hong Kong China School of Data Science The Chinese University of Hong Kong Shenzhen CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a solution of a differential equation and, even if exact solutions are available, an analytical intractability of the marginal likelihood and its associated gradient, which is used for parameter estimation. The focus of this article is to deliver unbiased estimates of the unknown parameters, that is, stochastic estimators that, in expectation, are equal to the maximizer of the marginal likelihood, and possess no numerical approximation error. Based upon the ideas of [4] we develop a new approach for unbiased parameter estimation for Bayesian inverse problems. We prove unbiasedness and establish numerically that the associated estimation procedure is faster than the current state-of-the-art methodology for this problem. We demonstrate the performance of our methodology on a range of problems which include a PDE and ODE. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

引用

arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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Sampling-Based Estimates of the Weight Enumerators of Reed-Muller Codes

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IEEE Transactions on Communications 2025年

作者： Arvind Rameshwar, V. Jain, Shreyas Kashyap, Navin Indian Institute of Science India Urban Data Exchange Program Unit Bengaluru560012 India IISER Department of Mathematical Sciences Mohali140306 India Indian Institute of Science Department of Electrical Communication Engineering Bengaluru560012 India

This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a sampler that produces codewords according to a suitably defined Gibbs distribution. We apply our method to moderate-blocklength RM RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a sampler that produces codewords according to a suitably defined Gibbs distribution. We apply our method to moderate-blocklength RM codes and derive approximate values of their weight enumerators. We observe that the rates of the weight enumerator estimates returned by our method are close to the true rates when these rates are either known or computable by brute-force search;in other cases, our computations provide provably robust estimates. As a by-product, our sampling algorithm also allows us to put together the weight spectrum, i.e., the weights at which the enumerators are non-zero, of an RM code, by providing witnesses in the form of codewords at each weight in the spectrum. We illustrate our method by providing estimates of the hitherto unknown weight enumerators of the RM(11, 5) code for weights that are multiples of 4 between 512 and 1024. We also obtain the exact weight spectrum of the RM(10, 4) code. © 1972-2012 IEEE.

关键词： Weighing

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Bayesian Inference for Non-Synchronously Observed Diffusions

arXiv

引用

arXiv 2025年

作者： Jasra, Ajay Kamatani, Kengo Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Institute of Statistical Mathematics Tokyo190-0014 Japan Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We consider the problem of Bayesian inference for bi-variate data observed in time but with observation times which occur non-synchronously. In particular, this occurs in a wide variety of applications in finance, such as high-frequency trading or crude oil futures trading. We adopt a diffusion model for the data and formulate a Bayesian model with priors on unknown parameters along with a latent representation for the the so-called missing data. We then consider computational methodology to fit the model using Markov chain Monte Carlo (MCMC). We have to resort to time-discretization methods as the complete data likelihood is intractable and this can cause considerable issues for MCMC when the data are observed in low frequencies. In a high frequency observation frequencies we present a simple particle MCMC method based on an Euler–Maruyama time discretization, which can be enhanced using multilevel Monte Carlo (MLMC). In the low frequency observation regime we introduce a novel bridging representation of the posterior in continuous time to deal with the issues of MCMC in this case. This representation is discretized and fitted using MCMC and MLMC. We apply our methodology to real and simulated data to establish the efficacy of our methodology. © 2025, CC BY.

关键词： Crude oil

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Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations

arXiv

引用

arXiv 2025年

作者： Chen, Yuan Khaliq, Abdul Furati, Khaled M. Computational and Data Science Program Middle Tennessee State University MurfreesboroTN37132 United States Department of Mathematical Science Middle Tennessee State University MurfreesboroTN37132 United States Department of Mathematics King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia

Nonlinear time-dependent partial differential equations are essential in modeling complex phenomena across diverse fields, yet they pose significant challenges due to their computational complexity, especially in higher dimensions. This study explores Quantum Recurrent Neural Networks within an encoder-decoder framework, integrating Variational Quantum Circuits into Gated Recurrent Units and Long Short-Term Memory networks. Using this architecture, the model efficiently compresses high-dimensional spatiotemporal data into a compact latent space, facilitating more efficient temporal evolution. We evaluate the algorithms on the Hamilton-Jacobi-Bellman equation, Burgers’ equation, the Gray-Scott reaction-diffusion system, and the three dimensional Michaelis-Menten reaction-diffusion equation. The results demonstrate the superior performance of the quantum-based algorithms in capturing nonlinear dynamics, handling high-dimensional spaces, and providing stable solutions, highlighting their potential as an innovative tool in solving challenging and complex systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Decoding

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Evaluation of Cuffless Blood Pressure Estimation Accuracy at Each Heartbeat During Exercise 6th

Evaluation of Cuffless Blood Pressure Estimation Accuracy a...

引用

6th International Conference on Biomedical and Health Informatics, ICBHI 2024

作者： Ono, Kouki Maeda, Yuka Yoshimura, Takumi Huang, Ming Tamura, Toshiyo Master’s Program in Intelligent and Mechanical Interaction Systems University of Tsukuba Tsukuba305-8577 Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba305-8577 Japan Medical and Welfare Engineering Tokyo Metropolitan College of Industrial Technology Tokyo116-8523 Japan School of Data Science Nagoya City University Nagoya467-8501 Japan Future Robotics Organization Waseda University Tokyo169-8050 Japan

ISBN: (纸本)9783031863226

Continuous blood pressure monitoring is crucial because of its dynamic nature, influenced by factors such as physical activity and mental stress. Although cuffless blood pressure estimation is a promising technique for continuous monitoring, its accuracy during drastic fluctuations, especially during exercise, remains insufficiently validated. In this study, we evaluated a simple Pulse Arrival Time based blood pressure estimation method and several improved methods for sharp fluctuations induced by exercise. Sixteen subjects in the experiment, with data from 13 valid for analysis. The proposed method achieved an average correlation of 0.527 in systolic blood pressure, suggesting that cuffless blood pressure estimation could be applied to estimate continuous blood pressure variability during exercise. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Blood pressure

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