Use of Deep-Learning Assisted Assessment of Cardiac Parameters in Zebrafish to Discover Cyanidin Chloride as a Novel Keap1 Inhibitor Against Doxorubicin-Induced Cardiotoxicity

Digital intelligence technology: new quality productivity for precision traditional Chinese medicine

Traditional Chinese medicine is a complex medical system characterized by multiple metabolites, targets, and pathways, known for its low drug resistance and significant efficacy. However, challenges persist within Traditional Chinese medicine, including difficulties in assessing the quality of Botanical drugs, reliance on experiential knowledge for disease diagnosis and treatment, and a lack of clarity regarding the pharmacological mechanisms of Traditional Chinese medicine. The advancement of digital intelligence technology is driving a shift towards precision medicine within the Traditional Chinese medicine model. This transition propels Traditional Chinese medicine into an era of precision, intelligence, and digitalization. This paper introduces standard digital intelligence technologies and explores the application of digital intelligence technologies in quality control and evaluation of Traditional Chinese medicine, studies the research status of digital intelligence technologies in assisting diagnosis, treatment and prevention of diseases, and further promotes the application and development of digital intelligence technologies in the field of Traditional Chinese medicine.

Bee Pollen Potential to Modulate Ferroptosis: Phytochemical Insights for Age-Related Diseases

Bee pollen (BP) is one of the richest known natural resources of micronutrients and bioactive phytochemicals. Some captivating bioactivities of BP compounds, although being largely investigated for the latter as individual molecules, remain very scarcely investigated or completely uninvestigated in bee pollen as a whole product. Among the most intriguing of these bioactivities, we identified ferroptosis as a major one. Ferroptosis, a recently discovered form of cell death (connecting oxidative stress and inflammation), is a complex pathophysiological process and one of the most crucial and perplexing events in current challenging human diseases such as cancer, neurodegeneration, and general aging diseases. Many BP compounds were found to intricately modulate ferroptosis depending on the cellular context by inducing this cell death mechanism in malignant cells and preventing it in non-malignant cells. Since research in both fields, i.e., BP and ferroptosis, is still recent, we deemed it necessary to undertake this review to figure out the extent of BP potential in modulating ferroptosis mechanisms. Our research proved that a wide range of BP compounds (polyphenols, phenolamides, carotenoids, vitamins, minerals, and others) substantially modulate diverse ferroptosis mechanisms. Accordingly, these phytochemicals and nutrients showed interesting potential in preclinical studies to lead to ferroptosis-mediated outcomes in important pathophysiological processes, including many aging-related disorders. One of the most paramount challenges that remain to be resolved is to determine how different BP compounds act on ferroptosis in different biological and pathophysiological contexts, either through synergistic or antagonistic behaviors. We hope that our current work constitutes a valuable incentive for future investigations in this promising and very relevant research avenue.

Ferroptosis-related oxaliplatin resistance in multiple cancers: Potential roles and therapeutic Implications

Oxaliplatin (OXA)-based therapy is effective in the treatment of multiple cancers. However, primary or acquired OXA resistance remains an emerging challenge for its clinical application. Ferroptosis is an iron-dependent mode of cell death that has been demonstrated to play an essential role in the chemoresistance of many drugs, including OXA. In particular, dysregulation of SLC7A11-GPX4, one of the major antioxidant systems of ferroptosis, was found in the OXA resistance of colorectal cancer (CRC) and hepatocellular carcinoma (HCC). In addition, Nrf2, the upstream regulator of GPX4 and many other antioxidant factors, is also involved in the OXA resistance of CRC and HCC. Inhibition of SLC7A11-GPX4 or Nrf2 by genetic deletion of pharmaceutical inhibition could significantly reverse OXA resistance. Long noncoding RNA (lncRNA) also participates in chemoresistance and ferroptosis of cancer cells. Specifically, LINC01134 promotes the recruitment of Nrf2 to the promoter of GPX4, thereby exerting transcriptional regulation of GPX4, which eventually increases the OXA sensitivity of HCC through upregulation of ferroptosis. On the other hand, a novel lncRNA DACT3-AS1 sensitizes gastric cancer cells to OXA through miR-181a-5p/sirtuin 1(SIRT1)-mediated ferroptosis. Therapies based on ferroptosis or a combination of OXA and ferroptosis enhancers could provide new therapeutic insights to overcome OXA resistance. In the present review, we present the current understanding of ferroptosis-related OXA resistance, highlight ferroptosis pathogenesis in OXA chemoresistance, and summarize available therapies that target OXA resistance by enhancing ferroptosis.

Two-Dimensional Deep Learning Frameworks for Drug-Induced Cardiotoxicity Detection

The identification of drug-induced cardiotoxicity remains a pressing challenge with far-reaching clinical and economic ramifications, often leading to patient harm and resource-intensive drug recalls. Current methodologies, including in vivo and in vitro models, have severe limitations in accurate identification of cardiotoxic substances. Pioneering a paradigm shift from these conventional techniques, our study presents two deep learning-based frameworks, STFT-CNN and SST-CNN, to assess cardiotoxicity with markedly improved accuracy and reliability. Leveraging the power of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) as a more human-relevant cell model, we record mechanical beating signals through impedance measurements. These temporal signals were converted into enriched two-dimensional representations through advanced transformation techniques, specifically short-time Fourier transform (STFT) and synchro-squeezing transform (SST). These transformed data are fed into the proposed frameworks for comprehensive analysis, including drug type classification, concentration classification, cardiotoxicity classification, and new drug identification. Compared to traditional models like recurrent neural network (RNN) and 1-dimensional convolutional neural network (1D-CNN), SST-CNN delivered an impressive test accuracy of 98.55% in drug type classification and 99% in distinguishing cardiotoxic and noncardiotoxic drugs. Its feasibility is further highlighted with a stellar 98.5% average accuracy for classification of various concentrations, and the superiority of our proposed frameworks underscores their promise in revolutionizing drug safety assessments. With a potential for scalability, they represent a major leap in drug safety assessments, offering a pathway to more robust, efficient, and human-relevant cardiotoxicity evaluations.

Targeting ferroptosis unveils a new era for traditional Chinese medicine: a scientific metrology study

In the past 11 years, there has been a surge in studies exploring the regulatory effect of Traditional Chinese Medicine (TCM) on ferroptosis. However, a significant gap persists in comprehensive scientometric analysis and scientific mapping research, especially in tracking the evolution, primary contributors, and emerging research focal points. This study aims to comprehensively update the advancements in targeting ferroptosis with various TCMs during the previous 11 years. The data, covering the period from 1 January 2012, to 30 November 2023, were retrieved from the Web of Science database. For in-depth scientometric and visualized analyses, a series of advanced analytical instruments were employed. The findings highlight China's predominant role, accounting for 71.99% of total publications and significantly shaping research in this domain. Noteworthy productivity was observed at various institutions, including Guangzhou University of Chinese Medicine, Chengdu University of Traditional Chinese Medicine, and Zhejiang University. Thomas Efferth emerged as the foremost author within this field, while Frontiers in Pharmacology boasted the highest publication count. This study pinpointed hepatocellular carcinoma, chemical and drug-induced liver injury, mitochondrial diseases, acute kidney injury, and liver failure as the most critical disorders addressed in this research realm. The research offers a comprehensive bibliometric evaluation, enhancing our understanding of the present status of TCM therapy in managing ferroptosis-related diseases. Consequently, it aids both seasoned researchers and newcomers by accelerating access to vital information and fostering innovative concept extraction within this specialized field.