FOXO1 reshapes neutrophils to aggravate acute brain damage and promote late depression after traumatic brain injury.

BACKGROUND: Neutrophils are traditionally viewed as first responders but have a short onset of action in response to traumatic brain injury (TBI). However, the heterogeneity, multifunctionality, and time-dependent modulation of brain damage and outcome mediated by neutrophils after TBI remain poorly understood. METHODS: Using the combined single-cell transcriptomics, metabolomics, and proteomics analysis from TBI patients and the TBI mouse model, we investigate a novel neutrophil phenotype and its associated effects on TBI outcome by neurological deficit scoring and behavioral tests. We also characterized the underlying mechanisms both in vitro and in vivo through molecular simulations, signaling detections, gene expression regulation assessments [including dual-luciferase reporter and chromatin immunoprecipitation (ChIP) assays], primary cultures or co-cultures of neutrophils and oligodendrocytes, intracellular iron, and lipid hydroperoxide concentration measurements, as well as forkhead box protein O1 (FOXO1) conditional knockout mice. RESULTS: We identified that high expression of the FOXO1 protein was induced in neutrophils after TBI both in TBI patients and the TBI mouse model. Infiltration of these FOXO1high neutrophils in the brain was detected not only in the acute phase but also in the chronic phase post-TBI, aggravating acute brain inflammatory damage and promoting late TBI-induced depression. In the acute stage, FOXO1 upregulated cytoplasmic Versican (VCAN) to interact with the apoptosis regulator B-cell lymphoma-2 (BCL-2)-associated X protein (BAX), suppressing the mitochondrial translocation of BAX, which mediated the antiapoptotic effect companied with enhancing interleukin-6 (IL-6) production of FOXO1high neutrophils. In the chronic stage, the "FOXO1-transferrin receptor (TFRC)" mechanism contributes to FOXO1high neutrophil ferroptosis, disturbing the iron homeostasis of oligodendrocytes and inducing a reduction in myelin basic protein, which contributes to the progression of late depression after TBI. CONCLUSIONS: FOXO1high neutrophils represent a novel neutrophil phenotype that emerges in response to acute and chronic TBI, which provides insight into the heterogeneity, reprogramming activity, and versatility of neutrophils in TBI.

Multimodal data fusion for supervised learning-based identification of USP7 inhibitors: a systematic comparison.

Ubiquitin-specific-processing protease 7 (USP7) is a promising target protein for cancer therapy, and great attention has been given to the identification of USP7 inhibitors. Traditional virtual screening methods have now been successfully applied to discover USP7 inhibitors aiming at reducing costs and speeding up time in several studies. However, due to their unsatisfactory accuracy, it is still a difficult task to develop USP7 inhibitors. In this study, multiple supervised learning classifiers were built to distinguish active USP7 inhibitors from inactive ligands. Physicochemical descriptors, MACCS keys, ECFP4 fingerprints and SMILES were first calculated to represent the compounds in our in-house dataset. Two deep learning (DL) models and nine classical machine learning (ML) models were then constructed based on different combinations of the above molecular representations under three activity cutoff values, and a total of 15 groups of experiments (75 experiments) were implemented. The performance of the models in these experiments was evaluated, compared and discussed using a variety of metrics. The optimal models are ensemble learning models when the dataset is balanced or severely imbalanced, and SMILES-based DL performs the best when the dataset is slightly imbalanced. Meanwhile, multimodal data fusion in some cases can improve the performance of ML and DL models. In addition, SMOTE, unbiased decoy selection and SMILES enumeration can improve the performance of ML and DL models when the dataset is severely imbalanced, and SMOTE works the best. Our study established highly accurate supervised learning classification models, which would accelerate the development of USP7 inhibitors. Some guidance was also provided for drug researchers in selecting supervised models and molecular representations as well as handling imbalanced datasets.

MXRA5 Is a Novel Immune-Related Biomarker That Predicts Poor Prognosis in Glioma.

BACKGROUND: Glioma is the most common primary intracranial tumor and is associated with poor prognosis. Identifying effective biomarkers for glioma is particularly important. MXRA5, a secreted glycoprotein, is involved in cell adhesion and extracellular matrix remodeling and has been reported to be expressed in many cancers. However, the role and mechanism of action of MXRA5 in gliomas remain unclear. This study was aimed at investigating the role of MXRA5 at the transcriptome level and its clinical prognostic value. METHODS: In this study, RNA microarray data of 301 glioma patients from the Chinese Glioma Genome Atlas (CGGA) were collected as a training cohort and RNA-seq data of 702 glioma samples from The Cancer Genome Atlas (TCGA) were used for validation. We analyzed the clinical and molecular characteristics as well as the prognostic value of MXRA5 in glioma. In addition, the expression level of MXRA was evaluated in 28 glioma tissue samples. RESULTS: We found that MXRA5 expression was significantly upregulated in high-grade gliomas and IDH wild-type gliomas compared to controls. Receiver operating characteristic (ROC) analysis showed that MXRA5 is a potential marker of the mesenchymal subtype of glioblastoma multiforme (GBM). We found that MXRA5 expression is highly correlated with immune checkpoint molecule expression levels and tumor-associated macrophage infiltration. High MXRA5 expression could be used as an independent indicator of poor prognosis in glioma patients. CONCLUSION: Our study suggests that MXRA5 expression is associated with the clinicopathologic features and poor prognosis of gliomas. MXRA5 may play an important role in the immunosuppressive microenvironment of glioma. As a secreted glycoprotein, MXRA5 is a potential circulating biomarker for glioma, deserving further investigation.

Fabrication and adhesion of a bio-inspired microarray: capillarity-induced casting using porous silicon mold.

Inspired by the setal microstructure found on the gecko's toe-pads, a highly dense array of high-aspect-ratio (HAR) artificial setae has been developed with a novel mold-casting technique using a porous silicon (PSi) template. To overcome the high fluid resistance in the HAR capillary pores, the PSi template surface is modified with a monolayer coating of dimethylsilane. The coating exhibits similar chemical composition and surface energy to the precursor of the poly(dimethylsiloxane) (PDMS) replica. The compatibility between the template and the replica addresses the major challenge of molding HAR microstructures, resulting in high-resolution replicas of artificial PDMS microsetae with complicated geometry resembling a real gecko's setae. The artificial setae are characterized by a mean radius of 1.3 µm, an aspect ratio of 35.1, and a density of ~4.7 × 105 per mm2. Results from adhesion characterizations reveal that with increasing preload, the shear adhesion of micro-setae continually increases while the normal adhesion decreases. The unique adhesion performance is caused by both van der Waals forces and the elastic resistance of PDMS setae. With further structural optimizations and the addition of an actuation mechanism, artificial setal arrays might eventually demonstrate the fascinating adhesion performances of the gecko for mimetic devices such as wall-climbing devices.