Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data.

OBJECTIVE: Breast cancer, a global concern predominantly impacting women, poses a significant threat when not identified early. While survival rates for breast cancer patients are typically favorable, the emergence of regional metastases markedly diminishes survival prospects. Detecting metastases and comprehending their molecular underpinnings are crucial for tailoring effective treatments and improving patient survival outcomes. METHODS: Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. Finally, the selected features were considered, and the SHAP algorithm was utilized to identify the most significant features for enhancing the decoding of dominant molecular mechanisms in lymph node metastases. RESULTS: In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. The RF classifier utilized the candidate mRNAs to differentiate between negative and positive categories with an accuracy of 61% and an AUC of 0.6. During the SHAP process, intriguing relationships between the selected mRNAs and positive/negative lymph node status were discovered. The results indicate that GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2 are among the top five most impactful mRNAs based on their SHAP values. CONCLUSION: The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.

Harnessing the power of machine learning for crop improvement and sustainable production.

Crop improvement and production domains encounter large amounts of expanding data with multi-layer complexity that forces researchers to use machine-learning approaches to establish predictive and informative models to understand the sophisticated mechanisms underlying these processes. All machine-learning approaches aim to fit models to target data; nevertheless, it should be noted that a wide range of specialized methods might initially appear confusing. The principal objective of this study is to offer researchers an explicit introduction to some of the essential machine-learning approaches and their applications, comprising the most modern and utilized methods that have gained widespread adoption in crop improvement or similar domains. This article explicitly explains how different machine-learning methods could be applied for given agricultural data, highlights newly emerging techniques for machine-learning users, and lays out technical strategies for agri/crop research practitioners and researchers.

Novel treatment options in rituximab-resistant membranous nephropathy patients.

The conventional treatment options (including alkylating agents, steroids, calcinurine inhibitors) have been largely replaced by anti-CD20 antibodies to achieve remission of nephrotic proteinuria in primary membranous nephropathy (PMN) patients. Two-third of rituximab-receiving PMN patients develop remission of proteinuria, and the results of MENTOR trial turned this drug into the first-line therapeutic agent in non-severe cases. However, in 20-40% of patients, remission is not achieved. Therefore, rituximab-resistant membranous nephropathy cases are increasingly reported. Different molecular mechanisms have been implicated in this context resulting in the introduction of new biologic agents. Second-generation anti-CD20 antibodies and other options such as plasma cell depleting agents and proteasome inhibition might lead to a novel treatment paradigm for patients with PMN.

Targeting Mitochondrial Biogenesis with Polyphenol Compounds.

Appropriate mitochondrial physiology is an essential for health and survival. Cells have developed unique mechanisms to adapt to stress circumstances and changes in metabolic demands, by meditating mitochondrial function and number. In this context, sufficient mitochondrial biogenesis is necessary for efficient cell function and haemostasis, which is dependent on the regulation of ATP generation and maintenance of mitochondrial DNA (mtDNA). These procedures play a primary role in the processes of inflammation, aging, cancer, metabolic diseases, and neurodegeneration. Polyphenols have been considered as the main components of plants, fruits, and natural extracts with proven therapeutic effects during the time. These components regulate the intracellular pathways of mitochondrial biogenesis. Therefore, the current review is aimed at representing an updated review which determines the effects of different natural polyphenol compounds from various plant kingdoms on modulating signaling pathways of mitochondrial biogenesis that could be a promising alternative for the treatment of several disorders.

Phytochemicals impact on osteogenic differentiation of mesenchymal stem cells.

Medicinal plants have always been utilized for the prevention and treatment of the spread of different diseases all around the world. To name some traditional medicine that has been used over centuries, we can refer to phytochemicals such as naringin, icariin, genistein, and resveratrol gained from plants. Osteogenic differentiation and mineralization of stem cells can be the result of specific bioactive compounds from plants. One of the most appealing choices for therapy can be mesenchymal stem cells (MSCs) because it has a great capability of self-renewal and differentiation into three descendants, namely, endoderm, mesoderm, and ectoderm. Stem cell gives us the glad tidings of great advances in tissue regeneration and transplantation field for treatment of diseases. Using plant bioactive phytochemicals also holds tremendous promises in treating diseases such as osteoporosis. The purpose of the present review article thus is to investigate what are the roles and consequences of phytochemicals on osteogenic differentiation of MSCs.