Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis

Advances of New Extracellular Vesicle Isolation and Detection Technologies in Cancer Diagnosis

Cancer is a global health issue threatening people's lives. Currently, cancer detection methods still have a lot of room for improvement in both efficiency and accuracy. The development and application of new technologies are urgently required for early cancer diagnosis and prognosis. Extracellular vesicles (EVs) are a type of phospholipid bilayer vesicle secreted by cells and play an important role in cancer development and metastasis. These small vesicles participate in cancer information transmission, antigen presentation, angiogenesis, immune response, tumor invasion, and mediate signaling pathways in the tumor microenvironment. Liquid biopsy of EV cargo contents is a fast-developing research area, holding promise for early cancer diagnosis and monitoring cancer progression in real-time. However, current EV detection technologies for clinical translation are still facing many challenges. Recent advancements in developing techniques for EV isolation and detection have made significant progress and are paving the way toward clinical application. Here, the advantages and limitations of traditional EV detection and isolation technologies in cancer diagnosis and prognosis are reviewed. The review also focuses on emerging EV detection and isolation technologies in cancer, discusses the challenges faced by current methods, and explores the perspective of new EV detection techniques for future cancer diagnosis.

Multi-omics joint analysis reveals that the Miao medicine Yindanxinnaotong formula attenuates non-alcoholic fatty liver disease

BACKGROUD

Non-alcoholic fatty liver disease (NAFLD) is a growing chronic liver disease worldwide, and no effective agent is approved yet for this condition. Traditional Chinese Medicine (TCM), which has been practiced for thousands of years in China and other Asian countries, is considered an important source for identifying novel medicines for various diseases. Miao medicine Yindanxinnaotong formula (YDX) is a classical TCM for the treatment of hyperlipidemia disease by reducing blood lipid content, while the role of YDX have not been clarified in NAFLD.

PURPOSE

To investigate the protective effect of YDX on NAFLD in mice induced by high fat diet (HFD) and clarify the potential mechanism.

METHODS

NAFLD mice model was constructed by receiving HFD for 10-week period with or without YDX administration. Lipid profiles, biochemical indicators, and histopathological staining were performed to evaluate the extent of hepatic lipid accumulation and hepatic steatosis. 16S rRNA sequencing was used to determine the gut microbial composition. Serum metabolomics was further used to investigate the changes in plasma biomarkers for NAFLD-associated by UPLC-Q-TOF/MS analysis. Subsequently, liver transcriptomics was employed to identify differentially expressed genes and explore regulatory pathways. Then, lipid metabolism-related proteins and inflammation factors were examined by Western blot and ELISA.

RESULTS

YDX reduced body weight gain, liver index and inflammatory cytokines levels, along with improved hepatic steatosis, serum lipid profile, sensitivity to insulin and also tolerance to glucose, and enhanced oxidative defense system in HFD-induced mice. Also, YDX remarkedly affected gut microbiota diversity and community richness and decreased the ratio of Firmicutes/Bacteroidetes. Meanwhile, YDX also reduced the production of harmful lipid metabolites in the sera of NAFLD mice, such as LPC(18:0), LPC(18:1) and carnitine. Notably, consistent with liver transcriptomics results, YDX downregulated the expression of proteins implicated in de novo lipid synthesis (Srebp-1c, Acaca, Fasn, Scd-1, and Cd36) and pro-inflammatory cytokines (IL-6 and TNF-α), and increased the expression of proteins-related fatty acid β-oxidation (Ampkα, Ppar-α, and Cpt-1) in the liver by activating Ampk pathway.

CONCLUSION

YDX is promisingly an effective therapy for preventing NAFLD by modulating the Ampk pathway, inhibiting gut microbiota disorder, and reducing the production of harmful lipid metabolites.

Identification of the serum metabolomic profile for acute ischemic preconditioning in athletes

Purpose

In recent years, ischemic preconditioning (IPC) has emerged as an effective strategy to increase tissue resistance against long-term ischemic damage and has been increasingly integrated into exercise regimens. However, further research is needed to explore the impact of IPC-mediated metabolic alterations from an exercise standpoint to conduct a comprehensive exploration of metabolic alterations and their exercise-related mechanisms during acute IPC.

Methods

Nontarget metabolomics was performed on blood samples obtained from 8 male athletes both before and after IPC. The studies included the identification of differentially abundant metabolites, analysis of receiver operating characteristic (ROC) curves, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for differentially abundant metabolites, and metabolite set enrichment analysis (MSEA).

Results

Nineteen differentially abundant metabolites were identified, with increasing levels of five metabolites, such as O-desmethyltramadol and D-gluconate, whereas 14 metabolites, including 9-hydroxy-10e, 12z-octadecadienoic acid (9-HODE), tetradione, 2-hexenal, (2,4-dichlorophenoxy)acetic acid (2,4-D), and phosphatidylserine (PS), decreased. ROC curve analysis revealed an AUC of 0.9375 for D-gluconate. Both KEGG enrichment analysis and MSEA revealed enrichment in the pentose phosphate pathway (PPP).

Conclusion

This study revealed that PPP, D-gluconate, O-desmethyltramadol, and D-2-aminobutyric acid could be upregulated within 5 min after acute IPC, whereas 2,4-D, PS, 9-HODE, 2-hexenal, and tetradinone could be downregulated. These identified metabolites show promise for improving physical functional status and could be harnessed to enhance athletic performance.

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.

Nanoformulations for the diagnosis and treatment of metabolic dysfunction-associated steatohepatitis

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive phase of metabolic dysfunction-associated steatotic liver disease (MASLD) that develops into irreversible liver cirrhosis and hepatocellular carcinoma, ultimately necessitating liver transplantation as the sole life-saving option. However, given the drawbacks of liver transplantation, including invasiveness, chronic immunosuppression, and a lack of donor livers, prompt diagnosis and effective treatment are indispensable. Due to the limitations of liver biopsy and conventional imaging modalities in diagnosing MASH, as well as the potential hazards associated with liver-protecting medicines, numerous nanoformulations have been created for MASH theranostics. Particularly, there has been significant study interest in artificial nanoparticles, natural biomaterials, and bionic nanoparticles that exhibit exceptional biocompatibility and bioavailability. In this review, we summarized extracellular vesicles (EVs)-based omics analysis and Fe3O4-based functional magnetic nanoparticles as magnetic resonance imaging (MRI) contrast agents for MASH diagnosis. Additionally, artificial nanoparticles such as organic and inorganic nanoparticles, as well as natural biomaterials such as cells and cell-derived EVs and bionic nanoparticles including cell membrane-coated nanoparticles, have also been reported for MASH treatment owing to their specific targeting and superior therapeutic effect. This review has the potential to stimulate advancements in nanoformulation fabrication techniques. By exploring their compatibility with cell biology, it could lead to the creation of innovative material systems for efficient theragnostic uses for MASH. STATEMENT OF SIGNIFICANCE: People with metabolic dysfunction-associated steatohepatitis (MASH) will progress to fibrosis, cirrhosis, or even liver cancer. It is imperative to establish effective theragnostic techniques to stop MASH from progressing into a lethal condition. In our review, we summarize the advancement of artificial, natural, and bionic nanoparticles applied in MASH theragnosis. Furthermore, the issues that need to be resolved for these cutting-edge techniques are summarized to realize a more significant clinical impact. We forecast the key fields that will advance further as nanotechnology and MASH research progress. Generally, our discovery has significant implications for the advancement of nanoformulation fabrication techniques, and their potential to be compatible with cell biology could lead to the creation of innovative materials systems for effective MASH theragnostic.

Current Methods for Analysing Mesenchymal Stem Cell-Derived Extracellular Vesicles

The use of extracellular vesicles (EVs) generated by mesenchymal stem cells (MSCs) holds great promise as a novel therapeutic approach. Although their immunomodulatory and regeneration potential has been reported to be similar to that of MSCs, the use of MSC-derived EVs in clinical settings will require several problems to be resolved. It is necessary to develop a standardised and widely accepted isolation technology and to improve methods such as the quantification and characterisation of MSC-derived EVs. In this way, EV studies can be compared, the acquired knowledge can be safely transferred to clinical platforms and the clinical results can be evaluated appropriately. There are many procedures for the collection and analysis of vesicles derived from different cells; however, this review provides an overview of methods for the determination of the total protein amount, specific proteins, particle number, non-protein markers like lipids and RNA, microscopy and other methods focusing on MSC-derived EVs.

Metabolic profiling in tissues and urine of patients with prostatic lesions and the diagnostic value of urine extracellular vesicles metabolites in prostate cancer

BACKGROUND

Prostate cancer (PCa) lacks convenient and highly specific diagnostic markers. Although the value of extracellular vesicles (EV) in oncology is widely recognized, the diagnostic value of EV metabolites requires further exploration. This study aimed to explore the diagnostic value of urine EV (u-EV) metabolomics in PCa.

METHODS

We first detected metabolites in paired tissues cells (cells), tissue EV (t-EVs), u-EVs, and urine samples in cohort 1 (8 PCa vs. 5 benign prostatic hypertrophy, BPH) to prob the feasibility of EV metabolites as diagnostic markers. We then analyzed the value of u-EVs as markers for PCa diagnosis and typing in the expanded sample cohort (60 PCa vs. 40 BPH).

RESULTS

U-EV metabolites were more consistent with those in tissue-derived samples (cells and t-EVs) than those in urine, and more differential metabolites between BPH and PCa were identified in u-EV. Subsequently, we used a random forest model to construct a panel of six metabolites for PCa, which showed an area under the curve (AUC) of 0.833 in training cohort and 0.844 in validation cohort. We also found significantly differentially expressed metabolites between PCa subtypes (Gleason ≤ 7 vs. Gleason > 7 and localized vs. metastasis), demonstrating the value of EV metabolites in PCa typing and prognostic assessment.

CONCLUSION

Metabolomic analysis of u-EVs is a promising source of noninvasive markers for PCa diagnosis.

Extracellular Vesicles: A New Star for Gene Drug Delivery

Recently, gene therapy has become a subject of considerable research and has been widely evaluated in various disease models. Though it is considered as a stand-alone agent for COVID-19 vaccination, gene therapy is still suffering from the following drawbacks during its translation from the bench to the bedside: the high sensitivity of exogenous nucleic acids to enzymatic degradation; the severe side effects induced either by exogenous nucleic acids or components in the formulation; and the difficulty to cross the barriers before reaching the therapeutic target. Therefore, for the successful application of gene therapy, a safe and reliable transport vector is urgently needed. Extracellular vesicles (EVs) are the ideal candidate for the delivery of gene drugs owing to their low immunogenicity, good biocompatibility and low toxicity. To better understand the properties of EVs and their advantages as gene drug delivery vehicles, this review covers from the origin of EVs to the methods of EVs generation, as well as the common methods of isolation and purification in research, with their pros and cons discussed. Meanwhile, the engineering of EVs for gene drugs is also highlighted. In addition, this paper also presents the progress in the EVs-mediated delivery of microRNAs, small interfering RNAs, messenger RNAs, plasmids, and antisense oligonucleotides. We believe this review will provide a theoretical basis for the development of gene drugs.

Efficient preparation of high-purity and intact mesenchymal stem cell-derived extracellular vesicles

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have shown great promise for regeneration and immunomodulation. However, efficient and scalable methods for their preparation are still lacking. In this study, we present the adoption of a label-free technique known as "EXODUS" to isolate and purify MSC-EVs from the conditioned medium. Our findings indicate that EXODUS can rapidly isolate EVs from 10 mL of conditioned medium with a 5-fold higher yield compared to conventional approaches, including ultracentrifugation (UC) and polyethylene glycol precipitation (PEG) methods. Additionally, pre-storing the conditioned medium at 4°C for 1 week resulted in a ~2-fold higher yield of MSC-EVs compared to the freshly prepared medium. However, storing the purified EV particles at 4°C for 1 month led to a 2-fold reduction in particle concentration. Furthermore, we found that MSC-EVs isolated using EXODUS exhibit higher expression levels of EV markers such as Alix, Flotillin1, CD81, and TSG101 in comparison to PEG and UC methods. We also discovered that MSC-EVs isolated using EXODUS are enriched in response to cytokine, collagen-containing extracellular matrix, and calcium ion binding compared to PEG method and enriched in extracellular structure organization, extracellular matrix, and extracellular matrix structure constituents compared to UC. Finally, we demonstrated that MSC-EVs isolated using EXODUS exhibit greater potential in animal organ development, tissue development, and anatomical structure morphogenesis compared to the UC. These findings suggest that EXODUS is a suitable method for the large-scale preparation of high-quality MSC-EVs for various clinical applications.

Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning

Metabolic dysfunction-associated fatty liver disease (MAFLD) has reached epidemic proportions worldwide and is the most frequent cause of chronic liver disease in developed countries. Within the spectrum of liver disease in MAFLD, steatohepatitis is a progressive form of liver disease and hepatocyte ballooning (HB) is a cardinal pathological feature of steatohepatitis. The accurate and reproducible diagnosis of HB is therefore critical for the early detection and treatment of steatohepatitis. Currently, a diagnosis of HB relies on pathological examination by expert pathologists, which may be a time-consuming and subjective process. Hence, there has been interest in developing automated methods for diagnosing HB. This narrative review briefly discusses the development of artificial intelligence (AI) technology for diagnosing fatty liver disease pathology over the last 30 years and provides an overview of the current research status of AI algorithms for the identification of HB, including published articles on traditional machine learning algorithms and deep learning algorithms. This narrative review also provides a summary of object detection algorithms, including the principles, historical developments, and applications in the medical image analysis. The potential benefits of object detection algorithms for HB diagnosis (specifically those combined with a transformer architecture) are discussed, along with the future directions of object detection algorithms in HB diagnosis and the potential applications of generative AI on transformer architecture in this field. In conclusion, object detection algorithms have huge potential for the identification of HB and could make the diagnosis of MAFLD more accurate and efficient in the near future.

Multi-omics reveals goose fatty liver formation from metabolic reprogramming

To comprehensively provide insight into goose fatty liver formation, we performed an integrative analysis of the liver transcriptome, lipidome, and amino acid metabolome, as well as peripheral adipose tissue transcriptome analysis using samples collected from the overfed geese and normally fed geese. Transcriptome analysis showed that liver metabolism pathways were mainly enriched in glucolipid metabolism, amino acid metabolism, inflammation response, and cell cycle; peripheral adipose tissue and the liver cooperatively regulated liver lipid accumulation during overfeeding. Liver lipidome patterns obviously changed after overfeeding, and 157 different lipids were yielded. In the liver amino acid metabolome, the level of Lys increased after overfeeding. In summary, this is the first study describing goose fatty liver formation from an integrative analysis of transcriptome, lipidome, and amino acid metabolome, which will provide a whole new dimension to understanding the mechanism of goose fatty liver formation.

Engineering of Cell Derived-Nanovesicle as an Alternative to Exosome Therapy

BACKGROUND

Exosomes, nano-sized vesicles ranging between 30 and 150 nm secreted by human cells, play a pivotal role in long-range intercellular communication and have attracted significant attention in the field of regenerative medicine. Nevertheless, their limited productivity and cost-effectiveness pose challenges for clinical applications. These issues have recently been addressed by cell-derived nanovesicles (CDNs), which are physically synthesized exosome-mimetic nanovesicles from parent cells, as a promising alternative to exosomes. CDNs exhibit structural, physical, and biological properties similar to exosomes, containing intracellular protein and genetic components encapsulated by the cell plasma membrane. These characteristics allow CDNs to be used as regenerative medicine and therapeutics on their own, or as a drug delivery system.

METHODS

The paper reviews diverse methods for CDN synthesis, current analysis techniques, and presents engineering strategies to improve lesion targeting efficiency and/or therapeutic efficacy.

RESULTS

CDNs, with their properties similar to those of exosomes, offer a cost-effective and highly productive alternative due to their non-living biomaterial nature, nano-size, and readiness for use, allowing them to overcome several limitations of conventional cell therapy methods.

CONCLUSION

Ongoing research and enhancement of CDNs engineering, along with comprehensive safety assessments and stability analysis, exhibit vast potential to advance regenerative medicine by enabling the development of efficient therapeutic interventions.

Identification of stable reference genes for relative quantification of long RNA expression in urinary extracellular vesicles

Urinary extracellular vesicles (uEVs) are rich in valuable biomolecule information which are increasingly recognized as potential biomarkers for various diseases. uEV long RNAs are among the critical cargos capable of providing unique transcriptome information of the source cells. However, consensus regarding ideal reference genes for relative long RNAs quantification in uEVs is not available as of date. Here we explored stable reference genes through profiling the long RNA expression by RNA-seq following unsupervised analysis and validation studies. Candidate reference genes were identified using four algorithms: NormFinder, GeNorm, BestKeeper and the Delta Ct method, followed by validation. RNA profile showed uEVs contained abundant long RNAs information and the core transcriptome was related to cellular structures, especially ribosome which functions mainly as translation, protein and RNA binding molecules. Analysis of RNA-seq data identified RPL18A, RPL11, RPL27, RACK1, RPSA, RPL41, H1-2, RPL4, GAPDH, RPS27A as candidate reference genes. RT-qPCR validation revealed that RPL41, RPSA and RPL18A were reliable reference genes for long RNA quantification in uEVs from patients with diabetes mellitus (DM), diabetic nephropathy (DN), IgA nephropathy (IgAN) and prostate cancer (PCA). Interestingly, RPL41 also outperformed traditional reference genes in renal tissues of DN and IgAN, as well as in plasma EVs of several types of cancers. The stable reference genes identified in this study may facilitate development of uEVs as novel biomarkers and increase the accuracy and comparability of biomarker studies.

Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles-From Pre-Analytical Obstacles to Biomarker Research

Urinary extracellular vesicles (uEV) hold non-invasive RNA biomarkers for genitourinary tract diseases. However, missing knowledge about reference genes and effects of preanalytical choices hinder biomarker studies. We aimed to assess how preanalytical variables (urine storage temperature, isolation workflow) affect diabetic kidney disease (DKD)-linked miRNAs or kidney-linked miRNAs and mRNAs (kidney-RNAs) in uEV isolates and to discover stable reference mRNAs across diverse uEV datasets. We studied nine raw and normalized sequencing datasets including healthy controls and individuals with prostate cancer or type 1 diabetes with or without albuminuria. We focused on kidney-RNAs reviewing literature for DKD-linked miRNAs from kidney tissue, cell culture and uEV/urine experiments. RNAs were analyzed by expression heatmaps, hierarchical clustering and selecting stable mRNAs with normalized counts (>200) and minimal coefficient of variation. Kidney-RNAs were decreased after urine storage at -20 °C vs. -80 °C. Isolation workflows captured kidney-RNAs with different efficiencies. Ultracentrifugation captured DKD -linked miRNAs that separated healthy and diabetic macroalbuminuria groups. Eleven mRNAs were stably expressed across the datasets. Hence, pre-analytical choices had variable effects on kidney-RNAs-analyzing kidney-RNAs complemented global correlation, which could fade differences in some relevant RNAs. Replicating prior DKD-marker results and discovery of candidate reference mRNAs encourages further uEV biomarker studies.

Lipidomics in pathogenesis, progression and treatment of nonalcoholic steatohepatitis (NASH): Recent advances

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease affecting up to 30% of the general adult population. NAFLD encompasses a histological spectrum ranging from pure steatosis to non-alcoholic steatohepatitis (NASH). NASH can progress to cirrhosis and is becoming the most common indication for liver transplantation, as a result of increasing disease prevalence and of the absence of approved treatments. Lipidomic readouts of liver blood and urine samples from experimental models and from NASH patients disclosed an abnormal lipid composition and metabolism. Collectively, these changes impair organelle function and promote cell damage, necro-inflammation and fibrosis, a condition termed lipotoxicity. We will discuss the lipid species and metabolic pathways leading to NASH development and progression to cirrhosis, as well as and those species that can contribute to inflammation resolution and fibrosis regression. We will also focus on emerging lipid-based therapeutic opportunities, including specialized proresolving lipid molecules and macrovesicles contributing to cell-to-cell communication and NASH pathophysiology.

Proteomic Research of Extracellular Vesicles in Clinical Biofluid

Extracellular vesicles (EVs), the lipid bilayer membranous structures of particles, are produced and released from almost all cells, including eukaryotes and prokaryotes. The versatility of EVs has been investigated in various pathologies, including development, coagulation, inflammation, immune response modulation, and cell-cell communication. Proteomics technologies have revolutionized EV studies by enabling high-throughput analysis of their biomolecules to deliver comprehensive identification and quantification with rich structural information (PTMs, proteoforms). Extensive research has highlighted variations in EV cargo depending on vesicle size, origin, disease, and other features. This fact has sparked activities to use EVs for diagnosis and treatment to ultimately achieve clinical translation with recent endeavors summarized and critically reviewed in this publication. Notably, successful application and translation require a constant improvement of methods for sample preparation and analysis and their standardization, both of which are areas of active research. This review summarizes the characteristics, isolation, and identification approaches for EVs and the recent advances in EVs for clinical biofluid analysis to gain novel knowledge by employing proteomics. In addition, the current and predicted future challenges and technical barriers are also reviewed and discussed.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Diabetes with kidney injury may change the abundance and cargo of urinary extracellular vesicles

BACKGROUND

Urinary extracellular vesicles (uEVs) are derived from epithelia facing the renal tubule lumen in the kidney and urogenital tract; they may carry protein biomarkers of renal dysfunction and structural injury. However, there are scarce studies focusing on uEVs in diabetes with kidney injury.

MATERIALS AND METHODS

A community-based epidemiological survey was performed, and the participants were randomly selected for our study. uEVs were enriched by dehydrated dialysis method, quantified by Coomassie Bradford protein assay, and adjusted by urinary creatinine (UCr). Then, they identified by transmission electron microscopy (TEM), nanoparticle track analysis (NTA), and western blot of tumor susceptibility gene 101.

RESULTS

Decent uEVs with a homogeneous distribution were finally obtained, presenting a membrane-encapsulated structure like cup-shaped or roundish under TEM, having active Brownian motion, and presenting the main peak between 55 and 110 nm under NTA. The Bradford protein assay showed that the protein concentrations of uEVs were 0.02 ± 0.02, 0.04 ± 0.05, 0.05 ± 0.04, 0.07 ± 0.08, and 0.11 ± 0.15 μg/mg UCr, respectively, in normal controls and in prediabetes, diabetes with normal proteinuria, diabetes with microalbuminuria, and diabetes with macroproteinuria groups after adjusting the protein concentration with UCr by calculating the vesicles-to-creatinine ratio.

CONCLUSION

The protein concentration of uEVs in diabetes with kidney injury increased significantly than the normal controls before and after adjusting the UCr. Therefore, diabetes with kidney injury may change the abundance and cargo of uEVs, which may be involved in the physiological and pathological changes of diabetes.

Lipidomics analysis reveals new insights into the goose fatty liver formation

Our previous study described the mechanism of goose fatty liver formation from cell culture and transcriptome. However, how lipidome of goose liver response to overfeeding is unclear. In this study, we used the same batch of geese (control group and corn flour overfeeding group) to explore the lipidome changes and underlying metabolic mechanisms of goose fatty liver formation. Liquid chromatography-mass spectrometry (LC-MS) was provided to lipidome detection. Liver lipidomics profiles analysis was performed by principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA), different lipids were identified and annotated, and the enriched metabolic pathways were showed. The results of PCA, PLS-DA, and OPLS-DA displayed a clear separation and discrimination between control group and corn flour overfeeding group. Two hundred and fifty-one different lipids were yielded, which were involved in triglyceride (TG), diglyceride (DG), phosphatidic acids (PA), phosphatidylinositols (PI), phosphatidylethanolamines (PE), phosphatidylcholines (PC), lyso-phosphatidylcholines (LPC), monogalactosylmonoacylglycerol (MGMG), sphingolipids (SM), ceramides (Cer), and hexaglycosylceramides (Hex1Cer). Different lipids were enriched in glycerophospholipid metabolism, glycerolipid metabolism, phosphatidylinositol signaling system, inositol phosphate metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis and sphingolipid metabolism. In conclusion, this is the first report describing the goose fatty liver formation from lipidomics, this study might provide some insights into the underlying glucolipid metabolism disorders in the process of fatty liver formation.