Modeling "Two-Hit" Severe Pneumonia in Mice: Pathological Characteristics and Mechanistic Studies.

Severe pneumonia is one of the most common critical diseases in clinical practice. Existing models for severe pneumonia have limitations, leading to limited clinical translation. In this study, a two-hit severe pneumonia mouse model was established by inducing primary pneumonia through intratracheal instillation of 800 µg lipopolysaccharide (LPS), followed by intraperitoneal injection of 10 mg/kg LPS. The effectiveness of various inflammatory indicators and the lung tissue damage during the time course of this model were confirmed and evaluated. At 3 h post two-hit, the IL-6, TNF-α levels in peripheral blood and bronchoalveolar lavage fluid (BALF), and the white blood cells, neutrophils, and lymphocytes in BALF notably exhibited the most pronounced elevation. At 12 h post two-hit, the white blood cells and neutrophils in peripheral blood significantly increased, accompanied by notable alterations in splenic immune cells and worsened pulmonary histopathological damage. Transcriptomics of lung tissue, microbiota analysis of lung and gut, as well as plasma metabolomics analyses further indicated changes in transcriptional profiles, microbial composition, and metabolites due to the two-hit modeling. These results validate that the two-hit model mimics the clinical presentation of severe pneumonia and serves as a robust experimental tool for studying the pathogenesis of severe pneumonia and developing and assessing treatment strategies.

A glucuronogalactomannan isolated from Tetrastigma hemsleyanum Diels et Gilg: Structure and immunomodulatory activity.

A novel acidic glucuronogalactomannan (STHP-5) was isolated from the aboveground part of Tetrastigma hemsleyanum Diels et Gilg with a molecular weight of 3.225 × 105 kDa. Analysis of chain conformation showed STHP-5 was approximately a random coil chain. STHP-5 was composed mainly of galactose, mannose, and glucuronic acid. Linkages of glycosides were measured via methylation analysis and verified by NMR. In vitro, STHP-5 induced the production of nitric oxide (NO) and secretion of IL-6, MCP-1, and TNF-α in RAW264.7 cells, indicating STHP-5 had stimulatory activity on macrophages. STHP-5 was proven to function as a TLR4 agonist by inducing the secretion of secreted embryonic alkaline phosphatase (SEAP) in HEK-Blue™-hTLR4 cells. The TLR4 activation capacity was quantitatively measured via EC50, and it showed purified polysaccharides had stronger effects (lower EC50) on activating TLR4 compared with crude polysaccharides. In conclusion, our findings suggest STHP-5 may be a novel immunomodulator.

[Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study].

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

Anlotinib in combination with pembrolizumab for low-grade myofibroblastic sarcoma of the pancreas: A case report.

BACKGROUND: Low-grade myofibroblastic sarcoma (LGMS) is a rare spindle cell sarcoma especially in the pancreas, with myofibroblastic differentiation. Hitherto, only a few cases have been reported. CASE SUMMARY: Herein, we report a case involving the discovery of a pancreatic mass detected during a routine physical examination. Subsequent imaging and pathological tests of the patient led to the diagnosis of LGMS of the pancreas. Following surgical intervention, the patient experienced recurrence and metastasis. Conventional treatment is not effective for postoperative recurrent pancreatic LGMS with multiple metastases. After communicating with the patients and their families, informed consent was obtained for the treatment of anlotinib combined with pembrolizumab. Evaluation of imaging and clinical symptoms post-treatment revealed a relatively favorable response to the combination of anlotinib and pembrolizumab. CONCLUSION: Based on the comprehensive literature review, our report aimed to provide evidence for a better understanding of the disease characteristics, diagnostic criteria, imaging findings, and identification of LGMS. And explore novel treatment strategies for this disease.

AKR1C3-dependent lipid droplet formation confers hepatocellular carcinoma cell adaptability to targeted therapy.

Rationale: Increased lipid droplet (LD) formation has been linked to tumor metastasis, stemness, and chemoresistance in various types of cancer. Here, we revealed that LD formation is critical for the adaptation to sorafenib in hepatocellular carcinoma (HCC) cells. We aim to investigate the LD function and its regulatory mechanisms in HCC. Methods: The key proteins responsible for LD formation were screened by both metabolomics and proteomics in sorafenib-resistant HCC cells and further validated by immunoblotting and immunofluorescence staining. Biological function of AKR1C3 was evaluated by CRISPR/Cas9-based gene editing. Isotopic tracing analysis with deuterium3-labeled palmitate or carbon13-labeled glucose was conducted to investigate fatty acid (FA) and glucose carbon flux. Seahorse analysis was performed to assess the glycolytic flux and mitochondrial function. Selective AKR1C3 inhibitors were used to evaluate the effect of AKR1C3 inhibition on HCC tumor growth and induction of autophagy. Results: We found that long-term sorafenib treatment impairs fatty acid oxidation (FAO), leading to LD accumulation in HCC cells. Using multi-omics analysis in cultured HCC cells, we identified that aldo-keto reductase AKR1C3 is responsible for LD accumulation in HCC. Genetic loss of AKR1C3 fully depletes LD contents, navigating FA flux to phospholipids, sphingolipids, and mitochondria. Furthermore, we found that AKR1C3-dependent LD accumulation is required for mitigating sorafenib-induced mitochondrial lipotoxicity and dysfunction. Pharmacologic inhibition of AKR1C3 activity instantly induces autophagy-dependent LD catabolism, resulting in mitochondrial fission and apoptosis in sorafenib-resistant HCC clones. Notably, manipulation of AKR1C3 expression is sufficient to drive the metabolic switch between FAO and glycolysis. Conclusions: Our findings revealed that AKR1C3-dependent LD formation is critical for the adaptation to sorafenib in HCC through regulating lipid and energy homeostasis. AKR1C3-dependent LD accumulation protects HCC cells from sorafenib-induced mitochondrial lipotoxicity by regulating lipophagy. Targeting AKR1C3 might be a promising therapeutic strategy for HCC tumors.

Metabolic Reprogramming and Risk Stratification of Hepatocellular Carcinoma Studied by Using Gas Chromatography-Mass Spectrometry-Based Metabolomics.

Hepatocellular carcinoma (HCC) displays a high degree of metabolic and phenotypic heterogeneity and has dismal prognosis in most patients. Here, a gas chromatography-mass spectrometry (GC-MS)-based nontargeted metabolomics method was applied to analyze the metabolic profiling of 130 pairs of hepatocellular tumor tissues and matched adjacent noncancerous tissues from HCC patients. A total of 81 differential metabolites were identified by paired nonparametric test with false discovery rate correction to compare tumor tissues with adjacent noncancerous tissues. Results demonstrated that the metabolic reprogramming of HCC was mainly characterized by highly active glycolysis, enhanced fatty acid metabolism and inhibited tricarboxylic acid cycle, which satisfied the energy and biomass demands for tumor initiation and progression, meanwhile reducing apoptosis by counteracting oxidative stress. Risk stratification was performed based on the differential metabolites between tumor and adjacent noncancerous tissues by using nonnegative matrix factorization clustering. Three metabolic clusters displaying different characteristics were identified, and the cluster with higher levels of free fatty acids (FFAs) in tumors showed a worse prognosis. Finally, a metabolite classifier composed of six FFAs was further verified in a dependent sample set to have potential to define the patients with poor prognosis. Together, our results offered insights into the molecular pathological characteristics of HCC.

Prognosis prediction of hepatocellular carcinoma after surgical resection based on serum metabolic profiling from gas chromatography-mass spectrometry.

Comprehensive prognostic risk prediction of hepatocellular carcinoma (HCC) after surgical treatment is particularly important for guiding clinical decision-making and improving postoperative survival. Hence, we aimed to build prognostic models based on serum metabolomics data, and assess the prognostic risk of HCC within 5 years after surgical resection. A pseudotargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomics method was applied to analyze serum profiling of 78 HCC patients. Important metabolic features with discriminant ability were identified by a novel network-based metabolic feature selection method based on combinational significance index (N-CSI). Subsequently, phenylalanine and galactose were further identified to be relevant with mortality by the Cox regression analysis, while galactose and tyrosine were associated with recurrence and metastasis. Two models to predict risk of mortality (risk score of overall survival, RSOS) and risk of recurrence and metastasis (risk score of disease-free survival, RSDFS) were generated based on two panels of metabolites, respectively, which present favorable ability to predict prognosis of HCC, especially when combined with clinical staging system. The performance of models was further validated in an external independent cohort from 91 HCC patients. This study demonstrated that metabolomics is a powerful tool for risk screening of HCC prognosis.

Global Metabolic Profiling Identifies a Pivotal Role of Proline and Hydroxyproline Metabolism in Supporting Hypoxic Response in Hepatocellular Carcinoma.

Purpose: Metabolic reprogramming is frequently identified in hepatocellular carcinoma (HCC), which is the most common type of liver malignancy. The reprogrammed cellular metabolisms promote tumor cell survival, proliferation, angiogenesis, and metastasis. However, the mechanisms of this process remain unclear in HCC.Experimental Design: The global nontargeted metabolic study in 69 paired hepatic carcinomas and adjacent tissue specimens was performed using capillary electrophoresis-time of flight mass spectrometry-based approach. Key findings were validated by targeted metabolomic approach. Biological studies were also performed to investigate the role of proline biosynthesis in HCC pathogenesis.Results: Proline metabolism was markedly changed in HCC tumor tissue, characterized with accelerated consumption of proline and accumulation of hydroxyproline, which significantly correlated with α-fetoprotein levels and poor prognosis in HCC. In addition, we found that hydroxyproline promoted hypoxia- and HIF-dependent phenotype in HCC. Moreover, we demonstrated that hypoxia activated proline biosynthesis via upregulation of ALDH18A1, subsequently leading to accumulation of hydroxyproline via attenuated PRODH2 activity. More importantly, we showed that glutamine, proline, and hydroxyproline metabolic axis supported HCC cell survival through modulating HIF1α stability in response to hypoxia. Finally, inhibition of proline biosynthesis significantly enhanced cytotoxicity of sorafenib in vitro and in vivoConclusions: Our results demonstrate that hypoxic microenvironment activates proline metabolism, resulting in accumulation of hydroxyproline that promotes HCC tumor progression and sorafenib resistance through modulating HIF1α. These findings provide the proof of concept for targeting proline metabolism as a potential therapeutic strategy for HCC. Clin Cancer Res; 24(2); 474-85. ©2017 AACR.

Metabolic profiling analysis of Siraitia grosvenorii revealed different characteristics of green fruit and saccharified yellow fruit.

Siraitia grosvenorii is an economic and medicinal plant, its fruit is considered to be good to health for its diverse bioactive ingredients. However, the clarification of chemical composition and their changes after saccharification procedure are not well performed. In present study, a metabolomics method based on ultra-high-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry was developed for metabolic profiling acquisition of Siraitia grosvenorii extract. Furthermore, information dependent analysis (IDA) combined with self-constructed LC-MS/MS identification system for metabolites were employed to identify primary and secondary metabolites in Siraitia grosvenorii. A total of 126 metabolites were identified or tentatively identified. The obvious differences of metabolic profiling between green fruit and saccharified yellow fruit were observed, and metabolites showed their own distribution characteristics in peel, flesh and seed. The majority of the nutrients and effective components were more distributed in flesh and peel, and saccharification was conducive to accumulation of sweet glycosides. This study not only expanded metabolite composition information of Siraitia grosvenorii, but also specified distribution characteristics of identified metabolites.