PMhub 1.0: a comprehensive plant metabolome database.

The Plant Metabolome Hub (PMhub), available at https://pmhub.org.cn, is a valuable resource designed to provide scientists with comprehensive information on plant metabolites. It offers extensive details about their reference spectra, genetic foundations, chemical reactions, metabolic pathways and biological functions. The PMhub contains chemical data for 188 837 plant metabolites gathered from various sources, with 1 467 041 standard/in-silico high-resolution tandem mass-spectrometry (HRMS/MS) spectra corresponding to these metabolites. Beyond its extensive literature-derived data, PMhub also boasts a sizable collection of experimental metabolites; it contains 144 366 detected features in 10 typical plant species, with 16 423 successfully annotated by using standard/in-silico HRMS/MS data, this collection is further supplemented with thousands of features gathered from reference metabolites. For each metabolite, the PMhub enables the reconstructed of a simulated network based on structural similarities and existing metabolic pathways. Unlike previous plant-specific metabolome databases, PMhub not only contains a vast amount of metabolic data but also assembles the corresponding genomic and/or transcriptomic information, incorporating multiple methods for the comprehensive genetic analysis of metabolites. To validate the practicality, we verified a synthetic pathway for N-p-coumaroyltyramine by in vitro enzymatic activity experiments. In summary, the robust functionality provided by the PMhub will make it an indispensable tool for studying plant metabolomics.

Discovery of a class of glycosaminoglycan lyases with ultrabroad substrate spectrum and their substrate structure preferences.

Glycosaminoglycan (GAG) lyases are often strictly substrate specific, and it is especially difficult to simultaneously degrade GAGs with different types of glycosidic bonds. Herein, we found a new class of GAG lyases (GAGases) from different bacteria. These GAGases belong to polysaccharide lyase 35 family and share quite low homology with the identified GAG lyases. The most surprising thing is that GAGases can not only degrade three types of GAGs: hyaluronan, chondroitin sulfate, and heparan sulfate but also even one of them can also degrade alginate. Further investigation of structural preferences revealed that GAGases selectively act on GAG domains composed of non/6-O-/N-sulfated hexosamines and d-glucoronic acids as well as on alginate domains composed of d-mannuronic acids. In addition, GAG lyases were once speculated to have evolved from alginate lyases, but no transitional enzymes have been found. The discovery of GAGases not only broadens the category of GAG lyases, provides new enzymatic tools for the structural and functional studies of GAGs with specific structures, but also provides candidates for the evolution of GAG lyases.

Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.

With the improvement of single-cell measurement techniques, there is a growing awareness that individual differences exist among cells, and protein expression distribution can vary across cells in the same tissue or cell line. Pinpointing the protein subcellular locations in single cells is crucial for mapping functional specificity of proteins and studying related diseases. Currently, research about single-cell protein location is still in its infancy, and most studies and databases do not annotate proteins at the cell level. For example, in the human protein atlas database, an immunofluorescence image stained for a particular protein shows multiple cells, but the subcellular location annotation is for the whole image, ignoring intercellular difference. In this study, we used large-scale immunofluorescence images and image-level subcellular locations to develop a deep-learning-based pipeline that could accurately recognize protein localizations in single cells. The pipeline consisted of two deep learning models, i.e. an image-based model and a cell-based model. The former used a multi-instance learning framework to comprehensively model protein distribution in multiple cells in each image, and could give both image-level and cell-level predictions. The latter firstly used clustering and heuristics algorithms to assign pseudo-labels of subcellular locations to the segmented cell images, and then used the pseudo-labels to train a classification model. Finally, the image-based model was fused with the cell-based model at the decision level to obtain the final ensemble model for single-cell prediction. Our experimental results showed that the ensemble model could achieve higher accuracy and robustness on independent test sets than state-of-the-art methods.

Enzymatic comparison of two homologous enzymes reveals N-terminal domain of chondroitinase ABC I regulates substrate selection and product generation.

Chondroitinase ABC-type I (CSase ABC I), which can digest both chondroitin sulfate (CS) and dermatan sulfate (DS) in an endolytic manner, is an essential tool in structural and functional studies of CS/DS. Although a few CSase ABC I have been identified from bacteria, the substrate-degrading pattern and regulatory mechanisms of them have rarely been investigated. Herein, two CSase ABC I, IM3796 and IM1634, were identified from the intestinal metagenome of CS-fed mice. They show high sequence homology (query coverage: 88.00%, percent identity: 90.10%) except for an extra peptide (Met1-His109) at the N-terminus in IM1634, but their enzymatic properties are very different. IM3796 prefers to degrade 6-O-sulfated GalNAc residue-enriched CS into tetra- and disaccharides. In contrast, IM1634 exhibits nearly a thousand times more activity than IM3796 and can completely digest CS/DS with various sulfation patterns to produce disaccharides, unlike most CSase ABC I. Structure modeling showed that IM3796 did not contain an N-terminal domain composed of two ß-sheets, which is found in IM1634 and other CSase ABC I. Furthermore, deletion of the N-terminal domain (Met1-His109) from IM1634 caused the enzymatic properties of the variant IM1634-T109 to be similar to those of IM3796, and conversely, grafting this domain to IM3796 increased the similarity of the variant IM3796-A109 to IM1634. In conclusion, the comparative study of the new CSase ABC I provides two unique tools for CS/DS-related studies and applications and, more importantly, reveals the critical role of the N-terminal domain in regulating the substrate binding and degradation of these enzymes.

Contrastive voxel clustering for multiscale modeling of brain network.

Resting-state functional magnetic resonance imaging (fMRI) provides an efficient way to analyze the functional connectivity between brain regions. A comprehensive understanding of brain functionality requires a unified description of multi-scale layers of neural structure. However, existing brain network modeling methods often simplify this property by averaging Blood oxygen level dependent (BOLD) signals at the brain region level for fMRI-based analysis with the assumption that BOLD signals are homogeneous within each brain region, which ignores the heterogeneity of voxels within each Region of Interest (ROI). This study introduces a novel multi-stage self-supervised learning framework for multiscale brain network analysis, which effectively delineates brain functionality from voxel to ROIs and up to sample level. A Contrastive Voxel Clustering (CVC) module is proposed to simultaneously learn the voxel-level features and clustering assignments, which ensures the retention of informative clustering features at the finest voxel-level and concurrently preserves functional connectivity characteristics. Additionally, based on the extracted features and clustering assignments at the voxel level by CVC, a Brain ROI-based Graph Neural Network (BR-GNN) is built to extract functional connectivity features at the brain ROI-level and used for sample-level prediction, which integrates the functional clustering maps with the pre-established structural ROI maps and creates a more comprehensive and effective analytical tool. Experiments are performed on two datasets, which illustrate the effectiveness and generalization ability of the proposed method by analyzing voxel-level clustering results and brain ROIs-level functional characteristics. The proposed method provides a multiscale modeling framework for brain functional connectivity analysis, which will be further used for other brain disease identification. Code is available at https://github.com/yanliugroup/fmri-cvc.

Controllable and Low-Loss Electrochemiluminescence Waveguide Supported by a Micropipette Electrode.

One-dimensional molecular crystal waveguide (MCW) can transmit self-generated electrochemiluminescence (ECL), but heavy optical loss occurs because of the small difference in the refractive index between the crystal and its surroundings. Herein, we report a micropipette electrode-supported MCW (MPE/MCW) for precisely controlling the far-field transmission of ECL in air with a low optical loss. ECL is generated from one terminal of the MCW positioned inside the MPE, which is transmitted along the MCW to the other terminal in air. In comparison with conventional waveguides on solid substrates or in solutions, the MPE/MCW is propitious to the total internal reflection of light at the MCW/air interface, thus confining the ECL efficiently in MCW and improving the waveguide performance with an extremely low-loss coefficient of 4.49 × 10-3 dB µm-1. Moreover, by regulation of the gas atmosphere, active and passive waveguides can be resolved simultaneously inside MPE and in air. This MPE/MCW offers a unique advantage of spatially controlling and separating ECL signal readout from its generation, thus holding great promise in biosensing without or with less electrical/chemical disturbance.

Evaluating Mixtures of Urinary Phthalate Metabolites and Serum Per-/Polyfluoroalkyl Substances in Relation to Adolescent Hair Cortisol: The HOME Study.

Results of toxicological studies indicate that phthalates and per-/polyfluoroalkyl substances (PFAS), 2 classes of endocrine-disrupting chemicals, may alter the functioning of the hypothalamic-pituitary-adrenocortical (HPA) axis. We evaluated the associations of urinary phthalate metabolites and serum PFAS during gestation and childhood with adolescent hair cortisol concentrations (pg/mg hair) at age 12 years, an integrative marker of HPA axis activity (n = 205 mother-child pairs; Cincinnati, Ohio; enrolled 2003-2006). We used quantile-based g-computation to estimate associations between mixtures of urinary phthalate metabolites or serum PFAS and hair cortisol. We also examined whether associations of individual phthalate metabolites or PFAS with cortisol varied by the timing of exposure. We found that a 1-quartile increase in all childhood phthalate metabolites was associated with 35% higher adolescent hair cortisol (phthalate mixture ψ = 0.13; 95% confidence interval: 0.03, 0.22); these associations were driven by monoethyl phthalate, monoisobutyl phthalate, and monobenzyl phthalate. We did not find evidence that phthalate metabolites during gestation or serum PFAS mixtures were related to adolescent hair cortisol concentrations. We found suggestive evidence that higher childhood concentrations of individual PFAS were related to higher and lower adolescent hair cortisol concentrations. Our results suggest that phthalate exposure during childhood may contribute to higher levels of chronic HPA axis activity.

Estimating effects of longitudinal and cumulative exposure to PFAS mixtures on early adolescent body composition.

Few methods have been used to characterize repeatedly measured biomarkers of chemical mixtures. We applied latent profile analysis (LPA) to serum concentrations of 4 perfluoroalkyl and polyfluoroalkyl substances (PFAS) measured at 4 time points from gestation to age 12 years. We evaluated the relationships between profiles and z scores of height, body mass index, fat mass index, and lean body mass index at age 12 years (n = 218). We compared LPA findings with an alternative approach for cumulative PFAS mixtures using g-computation to estimate the effect of simultaneously increasing the area under the receiver operating characteristic curve (AUC) for all PFAS. We identified 2 profiles: a higher PFAS profile (35% of sample) and a lower PFAS profile (relative to each other), based on their average PFAS concentrations at all time points. The higher PFAS profile had generally lower z scores for all outcomes, with somewhat larger effects for males, though all 95% CIs crossed the null. For example, the higher PFAS profile was associated with a 0.50-unit lower (ß = -0.50; 95% CI, -1.07 to 0.08) BMI z score among males but not among females (ß = 0.04; 95% CI, -0.45 to 0.54). We observed similar patterns with AUCs. We found that a higher childhood PFAS profile and higher cumulative PFAS mixtures may be associated with altered growth in early adolescence. This article is part of a Special Collection on Environmental Epidemiology.

Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks.

Location proteomics seeks to provide automated high-resolution descriptions of protein location patterns within cells. Many efforts have been undertaken in location proteomics over the past decades, thereby producing plenty of automated predictors for protein subcellular localization. However, most of these predictors are trained solely from high-throughput microscopic images or protein amino acid sequences alone. Unifying heterogeneous protein data sources has yet to be exploited. In this paper, we present a pipeline called sequence, image, network-based protein subcellular locator (SIN-Locator) that constructs a multi-view description of proteins by integrating multiple data types including images of protein expression in cells or tissues, amino acid sequences and protein-protein interaction networks, to classify the patterns of protein subcellular locations. Proteins were encoded by both handcrafted features and deep learning features, and multiple combining methods were implemented. Our experimental results indicated that optimal integrations can considerately enhance the classification accuracy, and the utility of SIN-Locator has been demonstrated through applying to new released proteins in the human protein atlas. Furthermore, we also investigate the contribution of different data sources and influence of partial absence of data. This work is anticipated to provide clues for reconciliation and combination of multi-source data for protein location analysis.

A Mixture of Urinary Phthalate Metabolite Concentrations During Pregnancy and Offspring Social Responsiveness Scale Scores.

BACKGROUND: Phthalates are a group of chemicals with ubiquitous exposure worldwide. Exposures to phthalates during pregnancy may play a role in autism spectrum disorder (ASD) etiology by disrupting hormone levels or directly impacting fetal neurodevelopment. However, there is little research quantifying the aggregate effect of phthalates on child ASD-related behaviors. METHODS: We used data from two prospective pregnancy and birth cohorts-the Health Outcomes and Measures of the Environment (HOME) and the Early Autism Risk Longitudinal Investigation (EARLI). HOME is a general population cohort while participants in EARLI were at higher familial risk for ASD. Using quantile g-computation and linear regression models, we assessed the joint and individual associations of a mixture of six phthalate metabolites during pregnancy with child ASD-related traits measured by Social Responsiveness Scale (SRS) scores at ages 3-8 years. RESULTS: Our analyses included 271 participants from HOME and 166 participants from EARLI. There were imprecise associations between the phthalate mixture and SRS total raw scores in HOME (difference in SRS scores per decile increase in every phthalate = 1.3; 95% confidence interval [CI] = -0.2, 2.8) and EARLI (difference in SRS scores per decile increase in every phthalate = -0.9; 95% CI = -3.5, 1.7). CONCLUSIONS: The cohort-specific effect sizes of the pthalates-SRS associations were small and CIs were imprecise. These results suggest that if there are associations between phthalate metabolites during pregnancy and child SRS scores, they may differ across populations with different familial liabilities. Further studies with larger sample sizes are warranted.

Deficiency of INPP4A promotes M2 macrophage polarization in eosinophilic chronic rhinosinusitis with nasal polyps.

OBJECTIVE: The treatment of eosinophilic chronic rhinosinusitis with nasal polyps (E-CRSwNP) remains a challenge due to its complex pathogenesis. Inositol polyphosphate-4-phosphatase type IA (INPP4A), a lipid phosphatase, has been implicated in allergic asthma. However, the expression and function of INPP4A in E-CRSwNP remain unclear. This study aims to investigate the role of INPP4A in macrophages in E-CRSwNP. METHODS: We assessed the expression of INPP4A in human and mouse nasal mucosal tissues via immunofluorescence staining. THP-1 cells were cultured and exposed to various cytokines to investigate the regulation of INPP4A expression and its functional role. Additionally, we established a murine nasal polyp (NP) model and administrated an INPP4A-overexpressing lentivirus evaluate its impact on NP. RESULTS: The percentage of INPP4A + CD68 + macrophages among total macrophages decreased in the E-CRSwNP group compared to the control and the non-eosinophilic CRSwNP (NE-CRSwNP) groups, exhibiting an inverse correlation with an increased percentage of CD206 + CD68 + M2 macrophages among total macrophages. Overexpression of INPP4A led to a reduced percentage of THP-1 cells polarizing towards the M2 phenotype, accompanied by decreased levels of associated chemotactic factors including CCL18, CCL22, CCL24, and CCL26. We also validated the involvement of the PI3K-AKT pathway in the function of INPP4A in vitro. Furthermore, INPP4A overexpression in the murine NP model resulted in the attenuation of eosinophilic inflammation in the nasal mucosa. CONCLUSIONS: INPP4A deficiency promotes macrophage polarization towards the M2 phenotype, leading to the secretion of chemokines that recruit eosinophils and Th2 cells, thereby amplifying eosinophilic inflammation in E-CRSwNP. INPP4A may exert a suppressive role in eosinophilic inflammation and could potentially serve as a novel therapeutic strategy.

Molecularly imprinted polymer-coated hybrid optical waveguides for sub-aM fluorescence sensing.

The sensitivity of fluorescent sensors is crucial for their applications. In this study, we propose a molecularly imprinted polymer (MIP)-coated optical fibre-hybrid waveguide-fibre sensing structure for ultrasensitive fluorescence detection. In such a structure, the MIP coated-hybrid waveguide acts as a sensing probe, and the two co-axially connected optical fibres act as a highly efficient probing light launcher and a fluorescence signal collector, respectively. For the dual-layered waveguide sensing probe, the inner hybrid waveguide core was fabricated using a hollow quartz nanoparticle-hybridized polymer composite with a low refractive index, and the outer MIP coating layer possesses a high refractive index. Simulations showed that this dual-layer configuration can cause light propagation from the waveguide core to the MIP sensing layer with an efficiency of 98%, which is essential for detection. To validate this concept, we adopted a popular fluorescent dye, rhodamine B, to evaluate the sensing characteristics of the proposed system. We achieved an extremely low limit of detection of approximately 1.3 × 10-19 g ml-1 (approximately 0.27 aM).

Development, Validation, and Clinical Application of an Ultra-High-Performance Liquid Chromatography Coupled With Tandem Mass Spectrometry Method for the Determination of 10 Antituberculosis Drugs in Human Serum.

INTRODUCTION: Linezolid, moxifloxacin, rifapentine, rifabutin, cycloserine, clofazimine, bedaquiline, levofloxacin, prothionamide, and ethionamide are commonly used second-line antituberculosis (anti-TB) drugs. To support therapeutic drug monitoring in regular clinical practice, the authors sought to develop a method based on ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) that would allow for the simultaneous quantification of multiple second-line anti-TB drugs in human serum. METHODS: Analytes were extracted from human serum by protein precipitation. UHPLC-MS/MS was performed using a gradient at a flow rate of 0.3 mL/min, and each sample was taken for 7.5 minutes. The mass spectrometry scanning mode used was electrospray ionization with multiple reaction monitoring in the positive mode. RESULTS: Validation showed that endogenous substances in the sample did not interfere with the assay, and the relationship between X and Y was highly linear, with a coefficient of determination (R 2 ) >0.9954 for each curve. The accuracy (85.0%-114.7%) and precision (intraday: 0.27%-9.32%; interday: 0.20%-7.66%) were less than 15.0%, and the internal standard-normalized matrix effects were consistent (coefficient of variation ≤4.40%). The analytes were stable in the final extract and human serum under various storage conditions (recovery: 87.0%-115.0%). The clinical applicability of the method was demonstrated by quantitative determination of analytes in serum samples obtained from patients with TB. Reproducibility of the drug concentrations measured in clinical samples was confirmed by incurred sample reanalysis. CONCLUSIONS: A simple and reliable analytical method was developed and validated for the simultaneous determination of 10 anti-TB drugs in human serum using UHPLC-MS/MS. Quantitation of anti-TB drugs in clinical samples confirmed that the assay is suitable for therapeutic drug monitoring in regular clinical practice.

Homocysteine modulates CXCL10/CXCR3 axis activity to induce endothelial dysfunction.

Elevated homocysteine (Hcy) levels have been linked to the development of cardiovascular diseases, notably endothelial dysfunction, a critical precursor to atherosclerosis. In this extensive investigation, we explore the intricate pathways through which Hcy influences endothelial dysfunction, with particular attention to the CXCL10/CXCR3 axis. Employing a dual approach encompassing both in vitro and in vivo models, we scrutinize the repercussions of Hcy exposure on endothelial functionality. Our results reveal that Hcy significantly impairs crucial endothelial processes, including cell migration, proliferation, and tube formation. Concomitantly, Hcy upregulates the expression of adhesion molecules, exacerbating endothelial dysfunction. In a murine hyperhomocysteinemia (HHcy) model, we observed a parallel increase in plasma Hcy levels and adverse vascular effects. Moreover, our study unraveled a pivotal role of the CXCL10/CXCR3 axis in Hcy-induced endothelial dysfunction. Hcy exposure led to the upregulation of CXCL10 and CXCR3, both in vitro and in HHcy mice. Importantly, the blockade of this axis, achieved through specific antibodies or NBI-74330, mitigated the detrimental effects of Hcy on endothelial function. In conclusion, our findings illuminated the central role of the CXCL10/CXCR3 axis in mediating Hcy-induced endothelial dysfunction, providing valuable insights for potential therapeutic strategies in managing HHcy-related cardiovascular diseases.

Gestational PBDE concentrations, persistent externalizing, and emerging internalizing behaviors in adolescents: The HOME study.

BACKGROUND: Polybrominated diphenyl ethers (PBDEs) are ubiquitous environmental chemicals used as flame retardants in commercial and consumer products. Gestational PBDE concentrations are associated with adverse behaviors in children; however, the persistence of these associations into adolescence remains understudied. OBJECTIVE: We estimated the association of gestational PBDE serum concentrations with early adolescent self- and caregiver-reported behaviors at age 12 years and determined the consistency with previously observed associations in childhood with caregiver-reported behaviors in a prospective pregnancy and birth cohort. METHODS: We measured maternal serum concentrations of five individual PBDE congeners and created a summary exposure variable (∑5BDE: 28, -47, -99, -100 and -153) during pregnancy. At age 12 years, we assessed behaviors for 237 adolescents using self- and caregiver-reports with the Behavioral Assessment System for Children-3 (BASC3). We used multivariable linear regression models to estimate covariate-adjusted associations of lipid standardized, log10-transformed gestational PBDE concentrations with BASC3 scores. We obtained estimates and 95% confidence intervals through a bootstrapping approach. We evaluated potential effect measure modification (EMM) of adolescent sex by examining sex-stratified regression models and estimating the EMM p-values. RESULTS: Gestational PBDE concentrations were positively associated with adolescent-reported BASC3 composite indices for inattention & hyperactivity (BDE-28, -47, -99, -100, ∑5BDE), internalizing problems (BDE-28, -47, -99), functional impairment (BDE-28, ∑5BDE), and emotional symptoms (BDE-28). Gestational PBDE concentrations were positively associated with caregiver-reported BASC3 composite indices for externalizing problems (BDE-28, -47, -99, -100, -153, ∑5BDE) and behavioral symptoms (BDE-99). For caregiver reported behaviors, we observed stronger associations with gestational BDE concentrations among males, especially for executive functioning (BDE-28, -47, -99, -100, ∑5BDE). DISCUSSION: Gestational PBDE serum concentrations were associated with self-reported internalizing and externalizing behavior problems in early adolescence. Caregiver-reported externalizing behaviors recognized during childhood remain associated with gestational PBDE concentrations and persist into early adolescence. Internalizing behaviors were less recognized by caregivers.

Per- and polyfluoroalkyl substances and bone mineral content in early adolescence: Modification by diet and physical activity.

BACKGROUND: Per- and polyfluoroalkyl substance (PFAS) exposures may negatively impact bone mineral accrual, but little is known about potential mitigators of this relation. We assessed whether associations of PFAS and their mixture with bone mineral content (BMC) in adolescence were modified by diet and physical activity. METHODS: We included 197 adolescents enrolled in a prospective pregnancy and birth cohort in Cincinnati, Ohio (2003-2006). At age 12 years, we collected serum for PFAS measurements and used dual-energy x-ray absorptiometry to measure BMC. We calculated dietary calcium intake and Health Eating Index (HEI) scores from repeated 24-h dietary recalls, physical activity scores using the Physical Activity Questionnaire for Older Children (PAQ-C), and average moderate to vigorous physical activity (MVPA) based on accelerometry. We estimated covariate-adjusted differences in BMC z-scores per interquartile range (IQR) increase of individual PFAS concentrations using linear regression and per simultaneous IQR increase in all four PFAS using g-computation. We evaluated effect measure modification (EMM) using interaction terms between each modifier and PFAS. RESULTS: Higher serum perfluorooctanoic acid, perfluorooctanesulfonic acid, and perfluorononanoic acid concentrations and the PFAS mixture were associated with lower BMC z-scores. An IQR increase in all PFAS was associated with a 0.27 (-0.54, 0.01) lower distal radius BMC z-score. Associations with lower BMC were generally stronger among adolescents classified as < median for calcium intake, HEI scores, or MVPA compared to those ≥ median. The difference in distal radius BMC z-score per IQR increase in all PFAS was -0.38 (-0.72, -0.04) for those with

Arginine Methylation of MDH1 by CARM1 Inhibits Glutamine Metabolism and Suppresses Pancreatic Cancer.

Distinctive from their normal counterparts, cancer cells exhibit unique metabolic dependencies on glutamine to fuel anabolic processes. Specifically, pancreatic ductal adenocarcinoma (PDAC) cells rely on an unconventional metabolic pathway catalyzed by aspartate aminotransferase, malate dehydrogenase 1 (MDH1), and malic enzyme 1 to rewire glutamine metabolism and support nicotinamide adenine dinucleotide phosphate (NADPH) production. Here, we report that methylation on arginine 248 (R248) negatively regulates MDH1. Protein arginine methyltransferase 4 (PRMT4/CARM1) methylates and inhibits MDH1 by disrupting its dimerization. Knockdown of MDH1 represses mitochondria respiration and inhibits glutamine metabolism, which sensitizes PDAC cells to oxidative stress and suppresses cell proliferation. Meanwhile, re-expression of wild-type MDH1, but not its methylation-mimetic mutant, protects cells from oxidative injury and restores cell growth and clonogenic activity. Importantly, MDH1 is hypomethylated at R248 in clinical PDAC samples. Our study reveals that arginine methylation of MDH1 by CARM1 regulates cellular redox homeostasis and suppresses glutamine metabolism of pancreatic cancer.

The Role of Breast Cancer Cells in Bone Metastasis: Suitable Seeds for Nourishing Soil.

PURPOSE OF REVIEW: The purpose of this review was to describe the characteristics of breast cancer cells prone to developing bone metastasis and determine how they are regulated by the bone microenvironment. RECENT FINDINGS: The bone is a site of frequent breast cancer metastasis. Bone metastasis accounts for 70% of advanced breast cancer cases and remains incurable. It can lead to skeletal-related events, such as bone fracture and pain, and seriously affect the quality of life of patients. Breast cancer cells escape from the primary lesion and spread to the bone marrow in the early stages. They can then enter the dormant state and restore tumourigenicity after several years to develop overt metastasis. In the last few years, an increasing number of studies have reported on the factors promoting bone metastasis of breast cancer cells, both at the primary and metastatic sites. Identifying factors associated with bone metastasis aids in the early recognition of bone metastasis tendency. How to target these factors and minimize the side effects on the bone remains to be further explored.

Inflammatory microenvironment regulation and osteogenesis promotion by bone-targeting calcium and magnesium repletion nanoplatform for osteoporosis therapy.

Osteoporosis is the most common bone metabolic disease that affects the health of middle-aged and elderly people, which is hallmarked by imbalanced bone remodeling and a deteriorating immune microenvironment. Magnesium and calcium are pivotal matrix components that participate in the bone formation process, especially in the immune microenvironment regulation and bone remodeling stages. Nevertheless, how to potently deliver magnesium and calcium to bone tissue remains a challenge. Here, we have constructed a multifunctional nanoplatform composed of calcium-based upconversion nanoparticles and magnesium organic frameworks (CM-NH2-PAA-Ald, denoted as CMPA), which features bone-targeting and pH-responsive properties, effectively regulating the inflammatory microenvironment and promoting the coordination of osteogenic functions for treating osteoporosis. The nanoplatform can efficaciously target bone tissue and gradually degrade in response to the acidic microenvironment of osteoporosis to release magnesium and calcium ions. This study validates that CMPA possessing favorable biocompatibility can suppress inflammation and facilitate osteogenesis to treat osteoporosis. Importantly, high-throughput sequencing results demonstrate that the nanoplatform exerts a good inflammatory regulation effect through inhibition of the nuclear factor kappa-B signaling pathway, thereby normalizing the osteoporotic microenvironment. This collaborative therapeutic strategy that focuses on improving bone microenvironment and promoting osteogenesis provides new insight for the treatment of metabolic diseases such as osteoporosis.

Alkaline phosphatase-activated prodrug system based on a bifunctional CuO NP tandem nanoenzyme for on-demand bacterial inactivation and wound disinfection.

Nanozymes are promising antimicrobials, as they produce reactive oxygen species (ROS). However, the intrinsic lack of selectivity of ROS in distinguishing normal flora from pathogenic bacteria deprives nanozymes of the necessary selectivities of ideal antimicrobials. Herein, we exploit the physiological conditions of bacteria (high alkaline phosphatase (ALP) expression) using a novel CuO nanoparticle (NP) nanoenzyme system to initiate an ALP-activated ROS prodrug system for use in the on-demand precision killing of bacteria. The prodrug strategy involves using 2-phospho-L-ascorbic acid trisodium salt (AAP) that catalyzes the ALP in pathogenic bacteria to generate ascorbic acid (AA), which is converted by the CuO NPs, with intrinsic ascorbate oxidase- and peroxidase-like activities, to produce ROS. Notably, the prodrug system selectively kills Escherichia coli (pathogenic bacteria), with minimal influence on Staphylococcus hominis (non-pathogenic bacteria) due to their different levels of ALP expression. Compared to the CuO NPs/AA system, which generally depletes ROS during storage, CuO NPs/AAP exhibits a significantly higher stability without affecting its antibacterial activity. Furthermore, a rat model is used to indicate the applicability of the CuO NPs/AAP fibrin gel in wound disinfection in vivo with negligible side effects. This study reveals the therapeutic precision of this bifunctional tandem nanozyme platform against pathogenic bacteria in ALP-activated conditions.