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High-fat diet (HFD) decreases insulin sensitivity. How high-fat diet causes insulin resistance is largely unknown. Here, we show that lean mice become insulin resistant after being administered exosomes isolated from the feces of obese mice fed a HFD or from patients with type II diabetes. HFD altered the lipid composition of exosomes from predominantly phosphatidylethanolamine (PE) in exosomes from lean animals (L-Exo) to phosphatidylcholine (PC) in exosomes from obese animals (H-Exo). Mechanistically, we show that intestinal H-Exo is taken up by macrophages and hepatocytes, leading to inhibition of the insulin signaling pathway. Moreover, exosome-derived PC binds to and activates AhR, leading to inhibition of the expression of genes essential for activation of the insulin signaling pathway, including IRS-2, and its downstream genes PI3K and Akt. Together, our results reveal HFD-induced exosomes as potential contributors to the development of insulin resistance. Intestinal exosomes thus have potential as broad therapeutic targets. High-fat diet plays a role in development of insulin resistance. Here, the authors report a mechanism that underlies the development of diet induced insulin resistance through the activation of an aryl hydrocarbon receptor mediated signalling pathway in the liver by faecal exosomes derived from intestinal cells.

Diet has emerged as a key impact factor for gut microbiota function. However, the complexity of dietary components makes it difficult to predict specific outcomes. Here we investigate the impact of plant-derived nanoparticles (PNP) on gut microbiota and metabolites in context of cancer immunotherapy with the humanized gnotobiotic mouse model. Specifically, we show that ginger-derived exosome-like nanoparticle (GELN) preferentially taken up by Lachnospiraceae and Lactobacillaceae mediated by digalactosyldiacylglycerol (DGDG) and glycine, respectively. We further demonstrate that GELN aly-miR159a-3p enhances anti-PD-L1 therapy in melanoma by inhibiting the expression of recipient bacterial phospholipase C (PLC) and increases the accumulation of docosahexaenoic acid (DHA). An increased level of circulating DHA inhibits PD-L1 expression in tumor cells by binding the PD-L1 promoter and subsequently prevents c-myc-initiated transcription of PD-L1. Colonization of germ-free male mice with gut bacteria from anti-PD-L1 non-responding patients supplemented with DHA enhances the efficacy of anti-PD-L1 therapy compared to controls. Our findings reveal a previously unknown mechanistic impact of PNP on human tumor immunotherapy by modulating gut bacterial metabolic pathways. The impact of diet on gut microbiota and metabolites in context of cancer immunotherapy remains elusive. Here the authors reveal ginger-derived exosome-like nanoparticle (GELN) aly-miR159a-3p enhances anti-PD-L1 therapy by increasing microbiota-dependent docosahexaenoic acid (DHA) level thus limiting tumor cell PD-L1 expression.

Obesity is becoming a global epidemic and reversing the pathological processes underlying obesity and metabolic co-morbidities is challenging. Obesity induced chronic inflammation including brain inflammation is a hallmark of obesity via the gut-brain axis. The objective of this study was to develop garlic exosome-like nanoparticles (GaELNs) that inhibit systemic as well as brain inflammatory activity and reverse a HFD induced obesity in mice. GELNs were isolated and administrated orally into HFD fed mice. GaELNs were fluorescent labeled for monitoring their trafficking route after oral administration and quantified the number particles in several tissues. The brain inflammation was determined by measuring inflammatory cytokines by ELISA and real-time PCR. Mitochondrial membrane permeability of microglial cells was determined using JC-10 fluorescence dye. The apoptotic cell death was quantified by TUNEL assay. The brain metabolites were identified and quantified by LC-MS analysis. Memory function of the mice was determined by several memory functional analysis. The effect of GaELNs on glucose and insulin response of the mice was determined by glucose and insulin tolerance tests. c-Myc localization and interaction with BASP1 and calmodulin was determined by confocal microscopy. Our results show that GaELNs is preferentially taken up microglial cells and inhibits the brain inflammation in HFD mice. GaELN phosphatidic acid (PA) (36:4) is required for the uptake of GaELNs via interaction with microglial BASP1. Formation of the GaELNs/BASP1 complex is required for inhibition of c-Myc mediated expression of STING. GaELN PA binds to BASP1, leading to inhibition of c-Myc expression and activity through competitively binding to CaM with c-Myc transcription factor. Inhibition of STING activity leads to reducing the expression of an array of inflammatory cytokines including IFN-γ and TNF-α. IFN-γ induces the expression of IDO1, which in turn the metabolites generated as IDO1 dependent manner activate the AHR pathway that contributes to developing obesity. The metabolites derived from the GaELNs treated microglial cells promote neuronal differentiation and inhibit mitochondrial mediated neuronal cell death. GaELNs treated HFD mice showed improved memory function and increased glucose tolerance and insulin sensitivity in these mice. : Collectively, these results demonstrate how nanoparticles from a healthy diet can inhibit unhealthy high-fat diet induced brain inflammation and reveal a link between brain microglia/diet to brain inflammatory disease outcomes via diet-derived exosome-like nanoparticles.

Background The aim of this study was to validate the generalisability of the ECOG-ACRIN A6702 multicenter trial identified mean apparent diffusion coefficient (ADC) cutoff (1.53 × 10 − 3 mm 2 /s) and compare its biopsy reduction efficacy against a data-derived ADC minimum (ADC min ) cutoff. Methods This dual-cohort retrospective analysis included 453 patients with 494 BI-RADS 4/5 lesions (derivation cohort: 288 patients/311 lesions; validation: 165 patients/183 lesions). ADC min and mean ADC (ADC mean ) were measured, the data-derived ADC min cutoff was optimised via an ROC analysis (negative likelihood ratio ≤ 0.1) .Performance metrics included biopsy reduction rates, sensitivity, and false-negative rates, stratified by lesion type, size, BI-RADS category, and field strength. Results In the derivation cohort, the data-derived ADC min cutoff (1.39 × 10 − 3 mm 2 /s) showed comparable performance to the A6702 ADC mean (ADC ACRIN ) cutoff in overall (24.7% vs. 24.1%), benign (47.9% vs. 45.1%) biopsy reduction and sensitivity (95.2% vs. 95.2%, all P  > 0.05), with its robustness confirmed by the validation cohort (26.2% overall, 57.9% benign reduction, 96.3% sensitivity). Both cutoffs exhibited field strength dependency, with higher biopsy reduction at 1.5T vs. 3.0T (derivation: 30.1% vs. 17.8% for ADC min , P  = 0.01; validation: 28.7% vs.17.5% for ADC min ). Conclusions The data-derived ADC min cutoff (1.39 × 10 − 3 mm 2 /s) demonstrated non-inferiority to the ADC ACRIN cutoff in biopsy reduction while preserving sensitivity. Observed performance variations between 1.5T and 3.0T suggest that field strength and other technical factors may influence cutoff efficacy. Prospective multicenter studies with standardized protocols are needed to validate its generalisability and clarify the role of field strength.

China has suffered a significant urban sprawl in a rapidly urbanizing process. The trial urban growth boundary (UGB) delineation can help control urban sprawl, and these changes in urban growth have deep effects on land carrying capacity (LCC). This study characterizes the effects of trial UGB delineation on LCC in China. LCC which was subdivided into three components: economic carrying capacity, social carrying capacity, and ecological carrying capacity of land was assessed. Then the difference-in-difference model was further employed to quantify the associations between trial UGB delineation and LCC. The results showed trial UGB delineation has a significant negative impact on the economic carrying capacity of land (coefficients of DID are −0.057 and −0.059). Trial UGB delineation has significant positive impacts on the social carrying capacity (coefficients of DID are 0.051 and 0.031) and ecological carrying capacity of land (coefficients of DID are 0.030 and 0.027). Meanwhile, the effects of trial UGB delineation on the three components of LCC are heterogeneous in the eastern, central, and western regions. Besides, the heterogeneous effects of UGB delineation on the three components of LCC have existed adding dummy variables of urban hierarchy. Based on the findings, targeted policy recommendations include adopting regionally differentiated UGB adjustment mechanisms, integrating dynamic resource-carrying capacity evaluation into UGB delineation, and establishing full-cycle UGB management.

Background Although 15-hydroxyprostaglandin dehydrogenase (HPGD) is known to regulate the metabolism of prostaglandins and lipoxin A4, and its dysregulation has been implicated in various cancers, its role in esophageal squamous cell carcinoma (ESCC) has not been determined. This study is the first to comprehensively characterize HPGD expression in ESCC and establish its clinical relevance in predicting patient outcomes. Furthermore, we elucidated the previously unrecognized molecular mechanisms through which HPGD suppresses ESCC progression and its potential as a novel therapeutic target. Methods Transcriptome sequencing was performed on paired tumor and adjacent normal tissues from deceased patients with ESCC to identify differentially expressed genes. The differential expression of the HPGD gene was subsequently validated in two independent, large-scale ESCC patient cohorts, and its prognostic significance was evaluated. To evaluate the functional role of HPGD in ESCC, the enzyme was overexpressed in ESCC cell lines, and a series of in vitro assays were conducted to assess its effects on proliferation, apoptosis, invasion, and migration. To elucidate the molecular mechanisms underlying the effects of HPGD, we performed transcriptomic sequencing to profile gene expression changes in ESCC cells. Through multiple analyses, including measurements of lipid peroxidation, intracellular ferrous ion and reactive oxygen species (ROS) levels, dual-fluorescence flow cytometry for autophagy, phosphoprotein microarrays, biotin pull-down assays, and chromatin immunoprecipitation (ChIP), we demonstrated that HPGD regulates the malignant phenotype of ESCC cells primarily by inducing ferroptosis and autophagy. Finally, the impact of HPGD on ESCC tumor growth was validated in vivo using a subcutaneous xenograft model in nude mice. Results HPGD expression was significantly lower in ESCC tissues than in normal tissues and was negatively correlated with tumor cell differentiation and patient outcomes. HPGD overexpression inhibited ESCC cell proliferation, invasion, and migration in vitro and in xenograft tumor growth in vivo. In vitro experiments demonstrated that HPGD suppresses ERK1/2 activation by facilitating lipoxin A4 (LXA4) degradation. This inhibition facilitates binding of the RNA-binding protein U2AF2 to the promoter region of the transferrin receptor (TFRC), thereby increasing TFRC expression. Consequently, these alterations lead to intracellular iron accumulation and initiate ferroptosis. Excessive generation of ROS during ferroptosis results in hyperactivation of autophagy via the AMPK/mTOR signaling pathway. Mitigating the HPGD-induced upregulation of TFRC or reducing ROS production effectively reverses ferroptosis, prevents excessive autophagy, and ameliorates malignant cell phenotypes. Conclusions HPGD exerts its antitumor effects by promoting ferroptosis through the LXA4-ERK1/2-U2AF2 signaling axis, which in turn induces autophagy hyperactivation via the AMPK-mTOR pathway. These findings suggest that HPGD is a promising therapeutic target for esophageal squamous cell carcinoma (ESCC) and reveal the nonclassic role of the RNA-binding protein U2AF2 in regulating the expression of TFRC by acting like a transcription factor.

Oral squamous cell carcinoma (OSCC) is a highly aggressive head and neck malignancy with a poor prognosis associated with its complex tumor microenvironment. Cancer-associated fibroblasts (CAFs) contribute to tumor progression by secreting various signaling molecules. This study investigates the molecular mechanism through which Z-DNA-binding protein 1 (ZBP1) promotes OSCC development through CAF regulation. To this end, orthotopic MOC1 transplantation and 4NQO-induced carcinogenesis OSCC models were established with Zbp1 −/− mice. Single-cell RNA sequencing (scRNA-seq) analyzed cellular heterogeneity and signaling network alterations in the tumor microenvironment. An in vitro CAF induction model combined with a Transwell co-culture system clarified the molecular mechanism of ZBP1. Finally, the role of the ZBP1–CCL7/CCR1 signaling axis in promoting OSCC progression was evaluated via in vivo recombinant CCL7 protein rescue and CCR1 antagonist (BX471) intervention. ZBP1 is highly expressed in OSCC tissues, while its deficiency inhibits tumor growth and proliferation. Proliferation-related pathways (e.g., E2F targets, MYC targets, cell cycle) are downregulated while immune activation signatures (e.g., interferon response, p53 pathway, TNF-α/NF-κB signaling) are upregulated in Zbp1 −/− tumor cells. Cellular interaction analysis and ligand–receptor network profiling demonstrated significant attenuation of the CCL7–CCR1 signaling axis between CAFs and tumor cells. ZBP1 deficiency reduces CCL7 expression in CAFs, diminishing their ability to promote tumor cell proliferation, migration, and invasion via the CCL7/CCR1 axis. Exogenous CCL7 supplementation partially restores tumor growth in Zbp1 −/− mice, indicating that ZBP1 bridges CAF–tumor cell communication through the CCL7–CCR1 axis. This study highlights ZBP1 as crucial for OSCC progression by regulating CCL7 expression in CAFs to activate CCR1 signaling in tumor cells. This provides insights into the regulatory mechanisms within the OSCC microenvironment, offering a potential therapeutic strategy for targeted interventions.

Organic solvent nanofiltration (OSN) technology is advantageous for separating mixtures of organic solutions owing to its low energy consumption and environmental friendliness. Covalent organic frameworks (COFs) are good candidates for enhancing the efficiency of solvent transport and ensuring precise molecular sieving of OSN membranes. In this study, p-phenylenediamine (Pa) and 1,3,5-trimethoxybenzene (Tp) are used to construct, in situ, a TpPa COF skin layer via interfacial polymerization (IP) on a polyimide substrate surface. After subsequent crosslinking and activation steps, a kind of TpPa/polyimide (PI) OSN membrane is obtained. Under optimized fabrications, this OSN membrane exhibits an ethanol permeance of 58.0 LMH/MPa, a fast green FCF (FGF) rejection of 96.2%, as well as a pure n-hexane permeance of 102.0 LMH/MPa. Furthermore, the TpPa/PI OSN membrane exhibits good solvent resistance, which makes it suitable for the separation, purification, and concentration of organic solvents.

Purpose Accurate classification of pulmonary pure ground-glass nodules (pGGNs) is essential for distinguishing invasive adenocarcinoma (IVA) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), which significantly influences treatment decisions. This study aims to develop a high-precision integrated strategy by combining radiomics-based feature extraction, Quantum Machine Learning (QML) models, and SHapley Additive exPlanations (SHAP) analysis to improve diagnostic accuracy and interpretability in pGGN classification. Methods A total of 322 pGGNs from 275 patients were retrospectively analyzed. The CT images was randomly divided into training and testing cohorts (80:20), with radiomic features extracted from the training cohort. Three QML models-Quantum Support Vector Classifier (QSVC), Pegasos QSVC, and Quantum Neural Network (QNN)-were developed and compared with a classical Support Vector Machine (SVM). SHAP analysis was applied to interpret the contribution of radiomic features to the models’ predictions. Results All three QML models outperformed the classical SVM, with the QNN model achieving the highest improvements ( ) in classification metrics, including accuracy (89.23 , 95 CI: 81.54 − 95.38 ), sensitivity (96.55 , 95 CI: 89.66 − 100.00 ), specificity (83.33 , 95 CI: 69.44 − 94.44 ), and area under the curve (AUC) (0.937, 95 CI: 0.871 - 0.983), respectively. SHAP analysis identified Low Gray Level Run Emphasis (LGLRE), Gray Level Non-uniformity (GLN), and Size Zone Non-uniformity (SZN) as the most critical features influencing classification. Conclusion This study demonstrates that the proposed integrated strategy, combining radiomics, QML models, and SHAP analysis, significantly enhances the accuracy and interpretability of pGGN classification, particularly in small-sample datasets. It offers a promising tool for early, non-invasive lung cancer diagnosis and helps clinicians make more informed treatment decisions. Clinical trial number Not applicable.