SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains.

Modern multiomic technologies can generate deep multiscale profiles. However, differences in data modalities, multicollinearity of the data, and large numbers of irrelevant features make analyses and integration of high-dimensional omic datasets challenging. Here we present Significant Latent Factor Interaction Discovery and Exploration (SLIDE), a first-in-class interpretable machine learning technique for identifying significant interacting latent factors underlying outcomes of interest from high-dimensional omic datasets. SLIDE makes no assumptions regarding data-generating mechanisms, comes with theoretical guarantees regarding identifiability of the latent factors/corresponding inference, and has rigorous false discovery rate control. Using SLIDE on single-cell and spatial omic datasets, we uncovered significant interacting latent factors underlying a range of molecular, cellular and organismal phenotypes. SLIDE outperforms/performs at least as well as a wide range of state-of-the-art approaches, including other latent factor approaches. More importantly, it provides biological inference beyond prediction that other methods do not afford. Thus, SLIDE is a versatile engine for biological discovery from modern multiomic datasets.

Regulatory T Cell Insufficiency in Autoimmune Diabetes Is Driven by Selective Loss of Neuropilin-1 on Intraislet Regulatory T Cells.

Approaches to reverse or limit regulatory T cell (Treg) insufficiency are of great interest for development of immunotherapeutic treatments for autoimmune patients, including type 1 diabetes. Treg insufficiency is heavily implicated in the progression of autoimmune diabetes in the NOD mouse model and is characterized by defects in Treg numbers, development, and/or function. Utilizing a Treg-centric screen, we show that intraislet Tregs have a uniquely dysfunctional phenotype, hallmarked by an almost complete lack of neuropilin-1 (Nrp1), a cell surface receptor required to maintain Treg stability. Intraislet Nrp1- Tregs exhibit hallmark features of fragility, including reduced suppressive capacity, decreased CD73 and Helios, and increased Rorγt and Tbet. Intraislet Nrp1- Tregs also exhibit decreased Foxp3 expression on a per cell basis, suggesting that Nrp1 may also be required for long-term Treg stability. Mechanistically, Treg-restricted augmentation of Nrp1 expression limited the onset of autoimmune diabetes in NOD mice suggesting that Nrp1 critically impacts intraislet Treg function. Transcriptional analysis showed that Nrp1 restoration led to an increase in markers and pathways of TCR signaling, survival, and suppression, and when Nrp1 protein expression is examined by cellular indexing of transcriptomes and epitopes by sequencing, significant differences were observed between Nrp1+ and Nrp1- Tregs in all tissues, particularly in markers of Treg fragility. This translated into substantive differences between Nrp1+ and Nrp1- Tregs that afforded the former with a competitive advantage in the islets. Taken together, these data suggest that maintenance of Nrp1 expression and signaling on Tregs limits diabetes onset and may serve as a strategy to combat Treg insufficiency in autoimmune disease.

CircPHKB decreases the sensitivity of liver cancer cells to sorafenib via miR-1234-3p/CYP2W1 axis.

Sorafenib is currently the first-line treatment for patients with advanced liver cancer, but its therapeutic efficacy declines significantly after a few months of treatment. Therefore, it is of great importance to investigate the regulatory mechanisms of sorafenib sensitivity in liver cancer cells. In this study, we provided initial evidence demonstrating that circPHKB, a novel circRNA markedly overexpressed in sorafenib-treated liver cancer cells, attenuated the sensitivity of liver cancer cells to sorafenib. Mechanically, circPHKB sequestered miR-1234-3p, resulting in the up-regulation of cytochrome P450 family 2 subfamily W member 1 (CYP2W1), thereby reducing the killing effect of sorafenib on liver cancer cells. Moreover, knockdown of circPHKB sensitized liver cancer cells to sorafenib in vivo. The findings reveal a novel circPHKB/miR-1234-3p/CYP2W1 pathway that decreases the sensitivity of liver cancer cells to sorafenib, suggesting that circPHKB and the axis may serve as promising targets to improve the therapeutic efficacy of sorafenib against liver cancer.

Washing antimony and arsenic from agricultural soil with eco-friendly organic acids and the relevant bioavailability assessment.

Antimony (Sb) and arsenic (As) contamination in agricultural soil poses human health risks through agricultural products. Soil washing with degradable low molecular weight organic acids (LMWOAs) is an eco-friendly strategy to remediate agricultural soils. In this study, three eco-friendly LMWOAs, oxalic acid (OA), tartaric acid (TA), and citric acid (CA), were used to treat Sb and As co-contaminated agricultural soil from Xikuangshan mine area. The OA, TA, and CA washed out 18.4, 16.8, and 26.6% of Sb and 15.3, 19.9, and 23.8% of As from the agricultural soil, with CA being the most efficient reagent for the soil washing. These organic acids also led to pH decline and macronutrients losses. Fraction analysis using a sequential extraction procedure showed that the three organic acids targeted and decreased the specifically sorbed (F2) (by 19.3-37.6% and 2.41-23.5%), amorphous iron oxide associated (F3) (by 49.1-61.2% and 51.2-70.2%), and crystallized iron oxide associated (F4) (by 12.3-26.0% and 26.1-29.1%) Sb and As. The leachability of Sb and As, as well as their concentrations and bioconcentration factor (BCF) in vegetables reduced due to the soil washing. It demonstrated that the bioavailability of both the elements was decreased by the organic acids washing. The concentrations of Sb and As in typical vegetable species cultivated in CA washed soil were less than the threshold value for consumption safety, while those in OA and TA washed soils were still higher than the value, suggesting that only CA is a potential washing reagent in soil washing for Sb- and As-contaminated agricultural soil.

Platelet Concentrates Preconditioning of Mesenchymal Stem Cells and Combined Therapies: Integrating Regenerative Strategies for Enhanced Clinical Applications.

This article presents a comprehensive review of the factors influencing the efficacy of mesenchymal stem cells (MSCs) transplantation and its association with platelet concentrates (PCs). It focuses on investigating the impact of PCs' composition, the age and health status of platelet donors, application methods, and environmental factors on the outcomes of relevant treatments. In addition, it delves into the strategies and mechanisms for optimizing MSCs transplantation with PCs, encompassing preconditioning and combined therapies. Furthermore, it provides an in-depth exploration of the signaling pathways and proteomic characteristics associated with preconditioning and emphasizes the efficacy and specific effects of combined therapy. The article also introduces the latest advancements in the application of biomaterials for optimizing regenerative medical strategies, stimulating scholarly discourse on this subject. Through this comprehensive review, the primary goal is to facilitate a more profound comprehension of the factors influencing treatment outcomes, as well as the strategies and mechanisms for optimizing MSCs transplantation and the application of biomaterials in regenerative medicine, offering theoretical guidance and practical references for related research and clinical practice.

Inhibitors of APE1 redox and ATM synergistically sensitize osteosarcoma cells to ionizing radiation by inducing ferroptosis.

The resistance of osteosarcoma (OS) to ionizing radiation (IR) is an obstacle for effective patient treatment. Apurinic/apyrimidinic endonuclease-reduction/oxidation factor 1 (APE1/Ref-1) is a multifunctional protein with DNA repair and reduction/oxidation (redox) activities. We previously revealed the role of APE1 in OS radioresistance; however, whether the redox activity of APE1 is involved in OS radioresistance is unclear. APE1 regulates the activation of ataxia-telangiectasia mutated (ATM), an initiator of DNA damage response that mediates radioresistance in other cancers. The role of APE1 redox activity and ATM activation in OS radioresistance is unknown. Our study revealed that IR increased APE1 expression and ATM activation in OS cells, and APE1 directly regulated ATM activation by its redox activity. The combined use of an APE1 redox inhibitor and ATM inhibitor effectively sensitized OS cells to IR in vitro and in vivo. Mechanistically, the increased radiosensitization of OS cells by the combined use of the two inhibitors was mediated by increased ferroptosis. Co-treatment with the two inhibitors significantly decreased expression of the common targeted transcription factor P53 compared with single inhibitor treatment. Collectively, APE1 redox activity, ATM activation and their crosstalk play important roles in the resistance of OS to irradiation. Synergetic inhibition of APE1 redox activity and ATM activation sensitized OS cells to IR by inducing ferroptosis, which provides a promising strategy for OS radiotherapy.

From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches.

A significant surge in research endeavors leverages the vast potential of high-throughput omic technology platforms for broad profiling of biological responses to vaccines and cutting-edge immunotherapies and stem-cell therapies under development. These profiles capture different aspects of core regulatory and functional processes at different scales of resolution from molecular and cellular to organismal. Systems approaches capture the complex and intricate interplay between these layers and scales. Here, we summarize experimental data modalities, for characterizing the genome, epigenome, transcriptome, proteome, metabolome, and antibody-ome, that enable us to generate large-scale immune profiles. We also discuss machine learning and network approaches that are commonly used to analyze and integrate these modalities, to gain insights into correlates and mechanisms of natural and vaccine-mediated immunity as well as therapy-induced immunomodulation.