Cancer is characterized by increased oxidative stress, an imbalance between reactive oxygen species (ROS) and antioxidants. Enhanced ROS accumulation, as a result of metabolic disturbances and signaling aberrations, can promote carcinogenesis and malignant progression by inducing gene mutations and activating pro-oncogenic signaling, providing a possible rationale for targeting oxidative stress in cancer treatment. While numerous antioxidants have demonstrated therapeutic potential, their clinical efficacy in cancer remains unproven. Here, we review the rationale for, and recent advances in, pre-clinical and clinical research on antioxidant therapy in cancer, including targeting ROS with nonenzymatic antioxidants, such as NRF2 activators, vitamins, N-acetylcysteine and GSH esters, or targeting ROS with enzymatic antioxidants, such as NOX inhibitors and SOD mimics. In addition, we will offer insights into prospective therapeutic options for improving the effectiveness of antioxidant therapy, which may expand its applications in clinical cancer treatment.

Major depressive disorder (MDD) is a highly prevalent and disabling disorder. Despite the many hypotheses proposed to understand the molecular pathophysiology of depression, it is still unclear. Current treatments for depression are inadequate for many individuals, because of limited effectiveness, delayed efficacy (usually two weeks), and side effects. Consequently, novel drugs with increased speed of action and effectiveness are required. Ketamine has shown to have rapid, reliable, and long‐lasting antidepressant effects in treatment‐resistant MDD patients and represent a breakthrough therapy for patients with MDD; however, concerns regarding its efficacy, potential misuse, and side effects remain. In this review, we aimed to summarize molecular mechanisms and pharmacological treatments for depression. We focused on the fast antidepressant treatment and clarified the safety, tolerability, and efficacy of ketamine and its metabolites for the MDD treatment, along with a review of the potential pharmacological mechanisms, research challenges, and future clinical prospects.

Alpinia oxyphylla Miq. (i.e., A. oxyphylla), a traditional Chinese medicine, can exert neuroprotective effects in ameliorating mild cognitive impairment and improving the pathological hallmarks of Alzheimer’s disease (AD). Here, 50 active compounds and 164 putative targets were collected and identified with 251 clinically tested AD-associated target proteins using network pharmacology approaches. Based on the Gene Ontology/Kyoto Encyclopedia of Genes and Genomes pathway enrichments, the compound-target-pathway-disease/protein–protein interaction network constructions, and the network topological analysis, we concluded that A. oxyphylla may have neuroprotective effects by regulating neurotransmitter function, as well as brain plasticity in neuronal networks. Moreover, closely-related AD proteins, including the amyloid-beta precursor protein, the estrogen receptor 1, acetylcholinesterase, and nitric oxide synthase 2, were selected as the bottleneck nodes of network for further verification by molecular docking. Our analytical results demonstrated that terpene, as the main compound of A. oxyphylla extract, exerts neuroprotective effects, providing new insights into the development of a natural therapy for the prevention and treatment of AD.

Feature selection for multiple types of data has been widely applied in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) classification research. Combining multi-modal data for classification can better realize the complementarity of valuable information. In order to improve the classification performance of feature selection on multi-modal data, we propose a multi-modal feature selection algorithm using feature correlation and feature structure fusion (FC2FS). First, we construct feature correlation regularization by fusing a similarity matrix between multi-modal feature nodes. Then, based on manifold learning, we employ feature matrix fusion to construct feature structure regularization, and learn the local geometric structure of the feature nodes. Finally, the two regularizations are embedded in a multi-task learning model that introduces low-rank constraint, the multi-modal features are selected, and the final features are linearly fused and input into a support vector machine (SVM) for classification. Different controlled experiments were set to verify the validity of the proposed method, which was applied to MCI and AD classification. The accuracy of normal controls versus Alzheimer’s disease, normal controls versus late mild cognitive impairment, normal controls versus early mild cognitive impairment, and early mild cognitive impairment versus late mild cognitive impairment achieve 91.85 ± 1.42%, 85.33 ± 2.22%, 78.29 ± 2.20%, and 77.67 ± 1.65%, respectively. This method makes up for the shortcomings of the traditional multi-modal feature selection based on subjects and fully considers the relationship between feature nodes and the local geometric structure of feature space. Our study not only enhances the interpretation of feature selection but also improves the classification performance, which has certain reference values for the identification of MCI and AD.

Mitochondria are the primary source of energy production in neurons, supporting the high energy consumption of the nervous system. Inefficient and dysfunctional mitochondria in the central nervous system have been implicated in neurodegenerative diseases. Therefore, targeting mitochondria offers a new therapeutic opportunity for neurodegenerative diseases. Many recent studies have proposed that plant-derived natural products, as pleiotropic, safe, and readily obtainable sources of new drugs, potentially treat neurodegenerative diseases by targeting mitochondria. In this review, we summarize recent advances in targeting mitochondria in neurotherapeutics by employing plant-derived natural products. We discuss the mechanism of plant-derived natural products according to their mechanism of action on mitochondria in terms of regulating biogenesis, fusion, fission, bioenergetics, oxidative stress, calcium homeostasis, membrane potential, and mitochondrial DNA stability, as well as repairing damaged mitochondria. In addition, we discuss the potential perspectives and challenges in developing plant-derived natural products to target mitochondria, highlighting the clinical value of phytochemicals as feasible candidates for future neurotherapeutics.

An imbalance between oxidants and antioxidants in the body can lead to oxidative stress, which is one of the major causes of neurodegenerative diseases. The gut microbiota contains trillions of beneficial bacteria that play an important role in maintaining redox homeostasis. In the last decade, the microbiota–gut–brain axis has emerged as a new field that has revolutionized the study of the pathology, diagnosis, and treatment of neurodegenerative diseases. Indeed, a growing number of studies have found that communication between the brain and the gut microbiota can be accomplished through the endocrine, immune, and nervous systems. Importantly, dysregulation of the gut microbiota has been strongly associated with the development of oxidative stress-mediated neurodegenerative diseases. Therefore, a deeper understanding of the relationship between the gut microbiota and redox homeostasis will help explain the pathogenesis of neurodegenerative diseases from a new perspective and provide a theoretical basis for proposing new therapeutic strategies for neurodegenerative diseases. In this review, we will describe the role of oxidative stress and the gut microbiota in neurodegenerative diseases and the underlying mechanisms by which the gut microbiota affects redox homeostasis in the brain, leading to neurodegenerative diseases. In addition, we will discuss the potential applications of maintaining redox homeostasis by modulating the gut microbiota to treat neurodegenerative diseases, which could open the door for new therapeutic approaches to combat neurodegenerative diseases.