Hui-Wen Ho

Bio: Hui-Wen Ho is an academic researcher from Memorial Hospital of South Bend. The author has contributed to research in topics: Pattern recognition (psychology) & Artificial intelligence. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

The Evolving Role of Ferroptosis in Breast Cancer: Translational Implications Present and Future.

Abstract: Breast cancer (BC) is the most common malignancy among women worldwide. The discovery of regulated cell death processes has enabled advances in the treatment of BC. In the past decade, ferroptosis, a new form of iron-dependent regulated cell death caused by excessive lipid peroxidation has been implicated in the development and therapeutic responses of BC. Intriguingly, the induction of ferroptosis acts to suppress conventional therapy-resistant cells, and to potentiate the effects of immunotherapy. As such, pharmacological or genetic modulation targeting ferroptosis holds great potential for the treatment of drug-resistant cancers. In this review, we present a critical analysis of the current understanding of the molecular mechanisms and regulatory networks involved in ferroptosis, the potential physiological functions of ferroptosis in tumor suppression, its potential in therapeutic targeting, and explore recent advances in the development of therapeutic strategies for BC.

Breast Lesions Screening of Mammographic Images with 2D Spatial and 1D Convolutional Neural Network-Based Classifier

Abstract: Mammography is a first-line imaging examination that employs low-dose X-rays to rapidly screen breast tumors, cysts, and calcifications. This study proposes a two-dimensional (2D) spatial and one-dimensional (1D) convolutional neural network (CNN) to early detect possible breast lesions (tumors) to reduce patients’ mortality rates and to develop a classifier for use in mammographic images on regions of interest where breast lesions (tumors) may likely occur. The 2D spatial fractional-order convolutional processes are used to strengthen and sharpen the lesions’ features, denoise, and improve the feature extraction processes. Then, an automatic extraction task is performed using a specific bounding box to sequentially pick out feature patterns from each mammographic image. The multi-round 1D kernel convolutional processes can also strengthen and denoise 1D feature signals and assist in the identification of the differentiation levels of normality and abnormality signals. In the classification layer, a gray relational analysis-based classifier is used to screen the possible lesions, including normal (Nor), benign (B), and malignant (M) classes. The classifier development for clinical applications can reduce classifier’s training time, computational complexity level, computational time, and achieve a more accurate rate for meeting clinical/medical purpose. Mammographic images were selected from the mammographic image analysis society image database for experimental tests on breast lesions screening and K-fold cross-validations were performed. The experimental results showed promising performance in quantifying the classifier’s outcome for medical purpose evaluation in terms of recall (%), precision (%), accuracy (%), and F1 score.

After Total Knee Arthroplasty, Monitored Active Ankle Pumping Improves Lower Leg Circulation More Than Unmonitored Pumping: A Pilot Study

Abstract: (1) Background: deep venous thrombosis (DVT) has long been recognized as the most devastating complication after total knee replacement (TKR). To prevent DVT, intermittent pneumatic compression to improve venous return in the lower leg has been advocated by surgeons. Physical activities such as active ankle pumping and early mobilization have been recommended as auxiliary measures to increase venous return in the lower leg and help in ambulation after TKR. In this study, in order to remind patients to exercise their ankle actively and efficiently after TKR, a foot band with motion sensor and reminder alarm was used. (2) Methods: The patients were randomly allocated into three groups according to the therapeutic protocols. The patients in group 1 conducted active ankle pumping without any reminders, those in group 2 underwent intermittent pneumatic compression, and those in group 3 conducted active ankle pumping with ankle motion sensor/reminder. The parameters of blood flow, namely, peak flow velocity and flow volume, in the bilateral common femoral vein and popliteal vein on the 1st, 3rd, and 14th days after surgery were measured using the echo technique, an index to evaluate the effect on promotion of venous return, among the three groups. (3) Results: The peak flow velocity and flow volume of the operative limb in group 3 (with motion sensor/reminder) were significantly higher than those in other groups. The peak flow velocity and flow volume in the popliteal vein in group 3 increased by 112% and 93.8%, respectively, compared to group 1 on the 14th day. No significant difference in peak flow velocity or flow volume was found in the nonoperative limb between the groups. (4) Conclusions: According to the results, a motion sensor/reminder with vibration alarms can improve the performance of active ankle pumping exercises in improving lower leg circulation, and hence may reduce the risk of DVT.

Number of Convolution Layers and Convolution Kernel Determination and Validation for Multilayer Convolutional Neural Network: Case Study in Breast Lesion Screening of Mammographic Images

Abstract: Mammography is a low-dose X-ray imaging technique that can detect breast tumors, cysts, and calcifications, which can aid in detecting potential breast cancer in the early stage and reduce the mortality rate. This study employed a multilayer convolutional neural network (MCNN) to screen breast lesions with mammographic images. Within the region of interest, a specific bounding box is used to extract feature maps before automatic image segmentation and feature classification are conducted. These include three classes, namely, normal, benign tumor, and malignant tumor. Multiconvolution processes with kernel convolution operations have noise removal and sharpening effects that are better than other image processing methods, which can strengthen the features of the desired object and contour and increase the classifier’s classification accuracy. However, excessive convolution layers and kernel convolution operations will increase the computational complexity, computational time, and training time for training the classifier. Thus, this study aimed to determine a suitable number of convolution layers and kernels to achieve a classifier with high learning performance and classification accuracy, with a case study in the breast lesion screening of mammographic images. The Mammographic Image Analysis Society Digital Mammogram Database (United Kingdom National Breast Screening Program) was used for experimental tests to determine the number of convolution layers and kernels. The optimal classifier’s performance is evaluated using accuracy (%), precision (%), recall (%), and F1 score to test and validate the most suitable MCNN model architecture.

Ferroptosis as a Major Factor and Therapeutic Target for Neuroinflammation in Parkinson's Disease

Abstract: Mounting evidence suggests that ferroptosis is not just a consequence but also a fundamental contributor to the development and progression of Parkinson's disease (PD). Ferroptosis is characterized as iron-dependent regulated cell death caused by excessive lipid peroxidation, leading to plasma membrane rupture, release of damage-associated molecular patterns, and neuroinflammation. Due to the crucial role of intracellular iron in mediating the production of reactive oxygen species and the formation of lipid peroxides, ferroptosis is intimately controlled by regulators involved in many aspects of iron metabolism, including iron uptake, storage and export, and by pathways constituting the antioxidant systems. Translational and transcriptional regulation of iron homeostasis and redox status provide an integrated network to determine the sensitivity of ferroptosis. We herein review recent advances related to ferroptosis, ranging from fundamental mechanistic discoveries and cutting-edge preclinical animal studies, to clinical trials in PD and the regulation of neuroinflammation via ferroptosis pathways. Elucidating the roles of ferroptosis in the survival of dopaminergic neurons and microglial activity can enhance our understanding of the pathogenesis of PD and provide opportunities for the development of novel prevention and treatment strategies.

Inhibition of cannabinoid receptor type 1 sensitizes triple-negative breast cancer cells to ferroptosis via regulating fatty acid metabolism

Abstract: Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancer that displays highly aggressive with poor prognosis. Owing to the limited targets and drugs for TNBC clinical therapy, it is necessary to investigate the factors regulating cancer progression and develop novel therapies for cancer treatment. Ferroptosis, a nonapoptotic form of programmed cell death characterized by accumulation of iron-dependent peroxidation of phospholipids, is regulated by cellular metabolism, redox homeostasis, and various cancer-related signaling pathways. Recently, considerable progress has been made in demonstrating the critical role of lipid metabolism in regulating ferroptosis, indicating potential combinational therapeutic strategies for cancer treatment. In this study, by drug combination screen of lipid metabolism compounds with ferroptosis inducers in decreasing TNBC cell viability, we found potent synergy of the CB1 antagonist rimonabant with erastin/(1 S, 3 R)-RSL3 (RSL3) in inhibiting TNBC cell growth both in vitro and in vivo via promoting the levels of lipid peroxides, malondialdehyde (MDA), 4-hydroxynonenal (4-HNE) and cytosolic reactive oxygen species (ROS) production, enhancing intracellular glutathione (GSH) depletion and inducing G1 cell cycle arrest. We identified that inhibition of CB1 promoted the effect of erastin/RSL3 on inducing ferroptosis and enhanced their inhibitory effect on tumor growth. Using RNA-Seq, fatty acid analyses and functional assays, we found that CB1 regulated stearoyl-CoA desaturase 1 (SCD1)- and fatty acyl desaturase 2 (FADS2)-dependent fatty acid metabolism via phosphatidylinositol 3 kinase (PI3K)-AKT and mitogen-activated protein kinase (MAPK) signaling pathways to modulate ferroptosis sensitivity in TNBC cells. These data demonstrate that dual targeting of CB1 and ferroptosis could be a promising therapeutic strategy for TNBC.

Inducing ferroptosis has the potential to overcome therapy resistance in breast cancer

Abstract: Breast cancer is the most common type of malignancy among women. Due to the iron-dependent character of breast cancer cells, they are more sensitive to ferroptosis compared to normal cells. It is possible to reverse tumor resistance by inducing ferroptosis in breast cancer cells, thereby improving tumor treatment outcomes. Ferroptosis is highly dependent on the balance of oxidative and antioxidant status. When ferroptosis occurs, intracellular iron levels are significantly increased, leading to increased membrane lipid peroxidation and ultimately triggering ferroptosis. Ferroptotic death is a form of autophagy-associated cell death. Synergistic use of nanoparticle-loaded ferroptosis-inducer with radiotherapy and chemotherapy achieves more significant tumor suppression and inhibits the growth of breast cancer by targeting cancer tissues, enhancing the sensitivity of cells to drugs, reducing the drug resistance of cancer cells and the toxicity of drugs. In this review, we present the current status of breast cancer and the mechanisms of ferroptosis. It is hopeful for us to realize effective treatment of breast cancer through targeted ferroptosis.