Assessment of urine sample collection and processing variables for extracellular vesicle-based proteomics.

Extracellular vesicles (EVs) in urine are a promising source for developing non-invasive biomarkers. However, urine concentration and content are highly variable and dynamic, and actual urine collection and handling often is nonideal. Furthermore, patients such as those with prostate diseases have challenges in sample collection due to difficulties in holding urine at designated time points. Here, we simulated the actual situation of clinical sample collection to examine the stability of EVs in urine under different circumstances, including urine collection time and temporary storage temperature, as well as daily urine sampling under different diet conditions. EVs were isolated using functionalized EVtrap magnetic beads and characterized by nanoparticle tracking analysis (NTA), western blotting, electron microscopy, and mass spectrometry (MS). EVs in urine remained relatively stable during temporary storage for 6 hours at room temperature and for 12 hours at 4 °C, while significant fluctuations were observed in EV amounts from urine samples collected at different time points from the same individuals, especially under certain diets. Sample normalization with creatinine reduced the coefficient of variation (CV) values among EV samples from 17% to approximately 6% and facilitated downstream MS analyses. Finally, based on the results, we applied them to evaluate potential biomarker panels in prostate cancer by data-independent acquisition (DIA) MS, presenting the recommendation that can facilitate biomarker discovery with nonideal handling conditions.

Platelet RNA sequencing reveals profile of caffeic acid affecting hemostasis in mice.

Background: Caffeic acid (CA) is a naturally occurring phenolic compound with diverse pharmacologic properties. CA plays a crucial role in hemostasis by increasing platelet count. However, the mechanism by which CA regulates platelets to promote hemostasis remains unclear. Objectives: We aim to identify the potential target pathways and genes by which CA regulates platelets to promote hemostasis. Methods: We performed RNA sequencing (RNA-seq) analysis of mouse platelet pools in both the CA-gavaged group and phosphate-buffered saline-gavaged group. Results: The 12,934 expressed transcripts had been annotated after platelet RNA-seq. Compared with the phosphate-buffered saline group, 987 differentially expressed genes (DEGs) were identified, of which 466 were downregulated and 521 were upregulated in CA group. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome gene set enrichment analysis demonstrated that upregulated DEGs were enriched in the pathways of hemostasis, platelet activation, signaling, aggregation, and degranulation. Moreover, Kyoto Encyclopedia of Genes and Genomes and Reactome gene set enrichment analysis revealed that 5 of the 25 cosignificantly upregulated DEGs were essential in CA-mediated platelet regulation to promote hemostasis. Conclusion: Our findings of platelet RNA-seq analysis demonstrate that CA regulates the gene expression of hemostasis and platelet activation-related pathways to increase platelet count and promote hemostasis. It will also provide reference molecular resources for future research on the function and mechanism by which CA regulates platelets to promote hemostasis.

Low vitamin D during pregnancy is associated with infantile eczema by up-regulation of PI3K/AKT/mTOR signaling pathway and affecting FOXP3 expression: A bidirectional cohort study.

Vitamin D has received increasing attention because of its association with atopic disease development. Limited studies that have been done on the impact of maternal vitamin D levels during pregnancy on infantile eczema are still debatable. We wanted to discover the effect of maternal vitamin D on infantile eczema and explore whether regulatory T cells (Treg) play a role in this process. 219 pairs of mothers and children were enrolled. Maternal fasting venous blood was collected in pregnancy's second and third trimesters to determine vitamin D levels. Cord blood and placenta samples were collected during childbirth for detecting levels of genes, proteins and cytokines. Pediatricians followed up the prevalence of eczema in infants within 1 year. The reported rate of vitamin D deficiency and insufficiency was 35.6% and 28.3%. Lower maternal 25(OH)D3 levels were related to a higher risk of infantile eczema. Foxp3 gene expression is lower in cord blood of infants with eczema compared to infants without eczema. There was a positive correlation between maternal 25(OH)D3 levels and the expression of FOXP3 gene in cord blood. Compared to vitamin D sufficiency women, vitamin D deficiency women's placental FOXP3 protein expression was decreased and PI3K/AKT/mTOR protein was up-regulated. Our study demonstrates that low prenatal maternal vitamin D levels increased the risk of infantile eczema aged 0-1 year, which might be related to the downregulating of the FOXP3 gene expression in cord blood and decreased placental FOXP3 protein expression. Low placental FOXP3 protein was related with activating PI3K/AKT/mTOR signaling pathway.

Identification of 8 Rare Deleterious Variants in ADAMTS13 by Next-generation Sequencing in a Chinese Population with Thrombotic Thrombocytopenic Purpura.

OBJECTIVE: Thrombotic thrombocytopenic purpura (TTP) is a rare and fatal disease caused by a severe deficiency in the metalloprotease ADAMTS13 and is characterized by thrombotic microangiopathy. The present study aimed to investigate the genes and variants associated with TTP in a Chinese population. METHODS: Target sequencing was performed on 220 genes related to complements, coagulation factors, platelets, fibrinolytic, endothelial, inflammatory, and anticoagulation systems in 207 TTP patients and 574 controls. Subsequently, logistic regression analysis was carried out to identify the TTP-associated genes based on the counts of rare deleterious variants in the region of a certain gene. Moreover, the associations between common variants and TTP were also investigated. RESULTS: ADAMTS13 was the only TTP-associated gene (OR = 3.77; 95% CI: 1.82-7.81; P=3.6×10È¡4) containing rare deleterious variants in TTP patients. Among these 8 variants, 5 novel rare variants that might contribute to TTP were identified, including rs200594025, rs782492477, c.T1928G (p.I643S), c.3336_3361del (p.Q1114Afs*20), and c.3469_3470del (p.A1158Sfs*17). No common variants associated with TTP were identified under the stringent criteria of correction for multiple testing. CONCLUSION: ADAMTS13 is the primary gene related to TTP. The genetic variants associated with the occurrence of TTP were slightly different between the Chinese and European populations.

Genetic Variations of AKT1 are Associated with Risk Screening for Non-Alcoholic Fatty Liver Disease.

Purpose: Protein kinase B (PKB/AKT) has shown a high profile in the research of metabolic diseases. This research sought to determine whether the AKT1 gene's single nucleotide polymorphisms (SNPs) and the risk of developing non-alcoholic fatty liver disease (NAFLD) were related. Patients and Methods: Recruited in this case-control study were 2693 subjects, including 815 with NAFLD and 1878 without NAFLD. Three SNPs of AKT1 (rs2494732, rs2494752 and rs1130233) were genotyped. To examine the correlation between SNPs and NAFLD susceptibility, logistic regression was performed. Results: After adjusting for sex, age, triglyceride and glucose, AKT1 rs2494732-C (all P < 0.05 in co-dominant model, dominant model and additive model) and rs2494752-G (P < 0.05 in co-dominant model) were linked to a lower risk of NAFLD. The combined effect of both SNPs on NAFLD risk was statistically significant, showing a dose dependence (Ptrend = 0.010). Sex, body mass index, hypertension, hyperglycemia, hypertriglyceridemia, high-density lipoprotein-cholesterol, alanine aminotransferase, and beneficial alleles were all significant predictors of NAFLD risk (all P < 0.05). The prediction model achieved good discrimination, with an area under the receiver operating characteristic curve of 0.779. The Hosmer-Lemeshow test suggested an inadequate calibration of the model (χ2 = 21.073, P = 0.007). Conclusion: AKT1 rs2494732 and rs2494752 may be related to Chinese NAFLD susceptibility. The prediction model combining both SNPs with clinical factors displays a strong ability to discriminate NAFLD patients. Both SNPs may be exploited to design new models for early screening of NAFLD high-risk population.

Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis.

High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)2O4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.

Phosphoproteome analysis of cerebrospinal fluid extracellular vesicles in primary central nervous system lymphoma.

Primary central nervous system lymphoma (PCNSL) is a rare but highly aggressive extra-nodal non-Hodgkin's lymphoma, mostly of the diffuse large B-cell lymphoma (DLBCL) type. The present invasive diagnosis and poor prognosis of PCNSL propose an urgent need to develop molecular markers for early detection, real-time monitoring and treatment evaluation. Cerebrospinal fluid (CSF)-derived extracellular vesicles (EVs) are promising biomarker carriers for liquid biopsy of CNS diseases and brain tumors; however, research remains challenging due to the low concentration of EVs in the limited available volume of CSF from each individual patient and the low efficiency of existing methods for EV enrichment. Here, we introduce functionalized magnetic beads called EVTRAP (extracellular vesicles total recovery and purification) for rapid and efficient EV isolation from CSF. By coupling with high-performance mass spectrometry, over 19 000 peptides representing 1841 proteins were identified from just 30 µL of CSF. Furthermore, up to 3000 phosphopeptides representing over 1000 phosphoproteins were identified from about 2 mL of CSF. Finally, we analyzed the EV phosphoproteomics of CSF samples from PCNSL patients and non-PCNSL controls. Among them, multiple phosphoproteins related to PCNSL, including SPP1, MARCKS, NPM1 and VIM, were shown to be up-regulated in the PCNSL group. These results demonstrated the feasibility of the EVTRAP-based analytical strategy in CSF EV phosphoproteomic analysis of PCNSL molecular markers.

Epidemiological characteristics of alcohol-related liver disease in China: a systematic review and meta-analysis.

BACKGROUND: This meta-analysis aimed to explore the epidemiological characteristics of alcohol-related liver disease (ALD) in China. METHODS: Studies published between January 2000 and January 2023 were searched from 3 databases in English and 3 databases in Chinese. DerSimonian-Laird's random-effects model was adopted to calculate the pooled prevalence. RESULTS: A total of 21 studies were included. The pooled prevalence of ALD was 4.8% (95% CI, 3.6%-6.2%) in the general population, 9.3% (95% CI, 4.4%-16.0%) in males, and 2.0% (95% CI, 0.0%-6.7%) in females. The prevalence was the highest in western China (5.0% [95% CI, 3.3%-6.9%]) and the lowest in central China (4.4% [95% CI, 4.0%-4.8%]). The prevalence among people with different drinking histories (less than 5 years, 5 to 10 years, and over 10 years) was 0.9% (95% CI, 0.2%-1.9%), 4.6% (95% CI, 3.0%-6.5%), and 9.9% (95% CI, 6.5%-14.0%), respectively. The prevalence in 1999-2004 was 4.7% (95% CI, 3.0%-6.7%) and then changed from 4.3% (95% CI, 3.5%-5.3%) in 2005-2010 to 6.7% (95% CI, 5.3%-8.3%) in 2011-2016. CONCLUSIONS: The prevalence of ALD in China has increased in recent decades, with population-related variations. Targeted public health strategies are needed, especially in high-risk groups, such as male with long-term alcohol drinking. TRIAL REGISTRATION: The registration number on PROSPERO is CRD42021269365.

Profiling Phosphoproteome Landscape in Circulating Extracellular Vesicles from Microliters of Biofluids through Functionally Tunable Paramagnetic Separation.

Many biological processes are regulated through dynamic protein phosphorylation. Monitoring disease-relevant phosphorylation events in circulating biofluids is highly appealing but also technically challenging. We introduce here a functionally tunable material and a strategy, extracellular vesicles to phosphoproteins (EVTOP), which achieves one-pot extracellular vesicles (EVs) isolation, extraction, and digestion of EV proteins, and enrichment of phosphopeptides, with only a trace amount of starting biofluids. EVs are efficiently isolated by magnetic beads functionalized with TiIV ions and a membrane-penetrating peptide, octa-arginine R8 + , which also provides the hydrophilic surface to retain EV proteins during lysis. Subsequent on-bead digestion concurrently converts EVTOP to TiIV ion-only surface for efficient enrichment of phosphopeptides for phosphoproteomic analyses. The streamlined, ultra-sensitive platform enabled us to quantify 500 unique EV phosphopeptides with only a few µL of plasma and over 1200 phosphopeptides with 100 µL of cerebrospinal fluid (CSF). We explored its clinical application of monitoring the outcome of chemotherapy of primary central nervous system lymphoma (PCNSL) patients with a small volume of CSF, presenting a powerful tool for broad clinical applications.

Combining serum uric acid and fatty liver index to improve prediction quality of nonalcoholic fatty liver disease.

Background: The significant association between serum uric acid (SUA) and nonalcoholic fatty liver disease (NAFLD) is well documented. In this report, we tested the hypothesis that SUA might improve the widely studied fatty liver index (FLI) to predict NAFLD. Methods: A cross-sectional study was performed in a community of Nanjing, China. The population data on sociodemographics, physical examinations, and biochemical tests were collected from July to September 2018. The associations of SUA and FLI with NAFLD were analyzed using linear correlation, multiple linear regressions, binary logistic analyses, and area under receiver-operating characteristic curve (AUROC). Results: A total of 3,499 people were included in this study, of which 36.9% had NAFLD. The prevalence of NAFLD increased with the increase of SUA levels (all P <.05). Logistic regression analyses revealed that SUA was significantly associated with an increased risk of NAFLD (all P <.001). The NAFLD predictive value after combining SUA with FLI was superior to FLI, especially in females (AUROCSUA + FLI = 0.911 vs. AUROCFLI = 0.903, P <.05). The reclassification of NAFLD also significantly improved, based on net reclassification improvement (0.053, 95% confidence interval [CI]: 0.022-0.085, P <.001) and integrated discrimination improvement (0.096, 95% CI: 0.090-0.102, P <.001). A regression formula of this combined algorithm was proposed as: The novel formula = 0.032* waist circumference + 0.303* body mass index + 1.301* natural logarithm of triglyceride + 0.478* natural logarithm of glutamyl transpeptidase + 0.002* SUA- 18.823. At the cutoff value of 13.3, the sensitivity and specificity of this model were 89.2% and 78.4%, respectively. Conclusions: SUA level was positively associated with NAFLD prevalence. A new formula combining SUA with FLI may serve as a better indicator to predict NAFLD compared to FLI, especially in females.

Data-Independent Acquisition Phosphoproteomics of Urinary Extracellular Vesicles Enables Renal Cell Carcinoma Grade Differentiation.

Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated library, direct DIA (library-free), forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease, and healthy control individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2584 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.

Construction of a ternary component chip with enhanced desorption efficiency for laser desorption/ionization mass spectrometry based metabolic fingerprinting.

Introduction: In vitro metabolic fingerprinting encodes diverse diseases for clinical practice, while tedious sample pretreatment in bio-samples has largely hindered its universal application. Designed materials are highly demanded to construct diagnostic tools for high-throughput metabolic information extraction. Results: Herein, a ternary component chip composed of mesoporous silica substrate, plasmonic matrix, and perfluoroalkyl initiator is constructed for direct metabolic fingerprinting of biofluids by laser desorption/ionization mass spectrometry. Method: The performance of the designed chip is optimized in terms of silica pore size, gold sputtering time, and initiator loading parameter. The optimized chip can be coupled with microarrays to realize fast, high-throughput (∼second/sample), and microscaled (∼1 µL) sample analysis in human urine without any enrichment or purification. On-chip urine fingerprints further allow for differentiation between kidney stone patients and healthy controls. Discussion: Given the fast, high throughput, and easy operation, our approach brings a new dimension to designing nano-material-based chips for high-performance metabolic analysis and large-scale diagnostic use.

Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors.

Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC is in high demand to improve prognostic outcome but is still missing. Here, a concave octahedron Mn2 O3 /(Co,Mn)(Co,Mn)2 O4 (MO/CMO) composite with a heterojunction, rough surface, hollow interior, and sharp corners is developed to record metabolic patterns of ovarian tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites with multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, and selective trapping of small molecules. The MO/CMO shows ≈2-5-fold signal enhancement compared to mono- or dual-enhancement counterparts, and ≈10-48-fold compared to the commercialized products. Subsequently, serum metabolic fingerprints of ovarian tumors are revealed by MO/CMO-assisted LDI-MS, achieving high reproducibility of direct serum detection without treatment. Furthermore, machine learning of the metabolic fingerprints distinguishes malignant ovarian tumors from benign controls with the area under the curve value of 0.987. Finally, seven metabolites associated with the progression of ovarian tumors are screened as potential biomarkers. The approach guides the future depiction of the state-of-the-art matrix for intensive MS detection and accelerates the growth of nanomaterials-based platforms toward precision diagnosis scenarios.

Proteomic and phosphoproteomic landscape of salivary extracellular vesicles to assess OSCC therapeutical outcomes.

Circulating extracellular vesicles (EVs) have emerged as an appealing source for surrogates to evaluate the disease status. Herein, we present a novel proteomic strategy to identify proteins and phosphoproteins from salivary EVs to distinguish oral squamous cell carcinoma (OSCC) patients from healthy individuals and explore the feasibility to evaluate therapeutical outcomes. Bi-functionalized magnetic beads (BiMBs) with Ti (IV) ions and a lipid analog, 1,2-Distearoyl-3-sn-glycerophosphoethanolamine (DSPE) are developed to efficiently isolate EVs from small volume of saliva. In the discovery stage, label-free proteomics and phosphoproteomics quantification showed 315 upregulated proteins and 132 upregulated phosphoproteins in OSCC patients among more than 2500 EV proteins and 1000 EV phosphoproteins, respectively. We further applied targeted proteomics by coupling parallel reaction monitoring with parallel accumulation-serial fragmentation (prm-PASEF) to measure panels of proteins and phosphoproteins from salivary EVs collected before and after surgical resection. A panel of three total proteins and three phosphoproteins, most of which have previously been associated with OSCC and other cancer types, show sensitive response to the therapy in individual patients. Our study presents a novel strategy to the discovery of effective biomarkers for non-invasive assessment of OSCC surgical outcomes with small amount of saliva.

Risk factors and protective factors for alcohol-related liver disease: A systematic review and meta-analysis.

BACKGROUND: Although alcohol-related liver disease (ALD) is a global health threat, there are no specific effective treatments for it. Thus, efforts at preventing ALD are important and could be enhanced by using strategies based on validated risk and protective factors for the disease. METHODS: The literature on factors influencing the risk for ALD was systematically searched from PubMed, Embase, and the Cochrane library databases from inception to June 2022. Factors suitable for quantitative analysis were submitted to meta-analysis using fixed-effects and random-effects models to calculate each factor's risk ratio (RR) and 95% confidence interval (CI). RESULTS: Ten cohort studies (covering 1,005,339 subjects) that reported a clear causal relationship were included in the analysis, involving 11 potential risk factors (sex, race, education level, body mass index, alcohol consumption, types of alcoholic beverage, duration of drinking, drinking frequency, smoking, coffee consumption, and tea consumption). Three of these factors (sex, alcohol consumption, and smoking) were subjected to meta-analysis, and the results showed that male sex (RR = 2.84, 95% CI = 1.86-4.36), alcohol consumption ≥280 g/week (RR = 4.96, 95% CI = 2.71-9.07), and smoking (RR = 2.39, 95% CI = 1.97-2.89) were risk factors for ALD. CONCLUSIONS: Many factors are likely to influence the incidence of ALD, and male sex, heavy alcohol consumption, and smoking increase the risk of ALD. The relationship between other factors and ALD risk needs further evaluation.

Association Between Triglyceride-Glucose Index and Risk of Metabolic Dysfunction-Associated Fatty Liver Disease: A Cohort Study.

Objective: Insulin resistance (IR) is a major factor involved in the pathogenesis of metabolic dysfunction-associated fatty liver disease (MAFLD). Triglyceride-glucose (TyG) index, an easily detected surrogate marker of IR, has not been explored sufficiently on its relationship with incident MAFLD risk. This study sought to investigate the association of baseline TyG index with the risk of MAFLD in a Chinese cohort. Methods: This health check-up cohort was constructed with eligible 2056 Chinese from a community. The TyG index was calculated as ln (fasting triglyceride [mg/dL]×fasting glucose [mg/dL]/2). Cox proportion hazard models were used to evaluate the longitudinal association between baseline TyG index and the risk of MAFLD. Results: During an average follow-up of 2.5 ± 0.5 years, about 12.8% of the subjects developed MAFLD, and the incidence of MAFLD trended to increase with the quartile TyG index (P trend < 0.05). After adjusting for all confounders, TyG index was independently correlated with the risk of incident MAFLD (HR = 1.784, 95% CI = 1.383-2.302, P < 0.001), and the risk of MAFLD in the highest quartile of TyG index was two times higher than that in the lowest quartile (95% CI = 1.377-2.992, P = 0.001). The restricted cubic spline analysis showed that the relationship between TyG index and the risk of MAFLD was linear in males (P for total < 0.001; P for non-linearity = 0.746), but nonlinear in females (P for non-linearity = 0.040). Conclusion: A high baseline TyG index was independently associated with a high risk of incident MAFLD, and we might develop the strategy of MAFLD prevention based on the TyG index.

Proteomics, Phosphoproteomics and Mirna Analysis of Circulating Extracellular Vesicles through Automated and High-Throughput Isolation.

Extracellular vesicles (EVs) play an important role in the diagnosis and treatment of diseases because of their rich molecular contents involved in intercellular communication, regulation, and other functions. With increasing efforts to move the field of EVs to clinical applications, the lack of a practical EV isolation method from circulating biofluids with high throughput and good reproducibility has become one of the biggest barriers. Here, we introduce a magnetic bead-based EV enrichment approach (EVrich) for automated and high-throughput processing of urine samples. Parallel enrichments can be performed in 96-well plates for downstream cargo analysis, including EV characterization, miRNA, proteomics, and phosphoproteomics analysis. We applied the instrument to a cohort of clinical urine samples to achieve reproducible identification of an average of 17,000 unique EV peptides and an average of 2800 EV proteins in each 1 mL urine sample. Quantitative phosphoproteomics revealed 186 unique phosphopeptides corresponding to 48 proteins that were significantly elevated in prostate cancer patients. Among them, multiple phosphoproteins were previously reported to associate with prostate cancer. Together, EVrich represents a universal, scalable, and simple platform for EV isolation, enabling downstream EV cargo analyses for a broad range of research and clinical applications.

External validation and comparison of simple tools to screen for nonalcoholic fatty liver disease in Chinese community population.

BACKGROUND: Various noninvasive tools based on anthropometric indicators, blood lipids, and liver enzymes, etc. have been developed to screen for nonalcoholic fatty liver disease (NAFLD), with different diagnostic performance and cutoff values among studies. We aimed to validate and compare eight NAFLD-related models developed by simple indicators and to define their cutoff values in Chinese community population. METHODS: A cross-sectional study was conducted in a health examination cohort of 3259 people. NAFLD was diagnosed by ultrasonography. General, anthropometric and biochemical data were collected. Fatty liver index (FLI), fatty liver disease index (FLD), Zhejiang University index (ZJU), lipid accumulation product (LAP), regression formula of controlled attenuation parameter (CAP), waist-to-height ratio (WHtR), triglyceride and glucose index (TyG), and visceral adiposity index (VAI) were calculated. The accuracy and cutoff points to detect NAFLD were evaluated by area under the receiver operator characteristic curve and the maximum Youden index analysis, respectively. A head-to-head comparison between these models and Decision Curve Analysis (DCA) was conducted. RESULTS: In eight noninvasive diagnostic models of NAFLD, AUCs of FLI and FLD for NAFLD were higher than those of other models in the whole (0.852 and 0.852), male (0.826 and 0.824), and female (0.897 and 0.888) population, respectively. DCA showed that FLI, FLD, and ZJU have higher net benefit to screen for NAFLD compared to other models. CONCLUSIONS: FLI and FLD could be the most accurate and applicable of eight models for the noninvasive diagnosis of NAFLD in both male and female groups.

A combined association of serum uric acid, alanine aminotransferase and waist circumference with non-alcoholic fatty liver disease: a community-based study.

Background: Increasing evidence has supported that serum uric acid (SUA), alanine aminotransferase (ALT) and waist circumference (WC) are associated with the occurrence of non-alcoholic fatty liver disease (NAFLD). However, the combined role of these factors in early screening of NAFLD has not been investigated. We aimed to de lineate this role in a community-based population. Methods: Binary logistic regression was used to explore the correlations of SUA, ALT and WC with NAFLD risk. The goodness of fit and discriminative ability of the model were evaluated by the Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUROC), respectively. Results: Logistic regression analysis indicated that elevated SUA (adjusted odds ratio (OR) = 2.44, 95% confidence interval (CI) [1.76-3.38]), ALT (adjusted OR = 4.98, 95% CI [3.41-7.27]) and WC (adjusted OR = 3.22, 95% CI [2.01-5.16]) were facilitating factors for incident NAFLD after fully adjusted for related confounders. In addition, the risk of NAFLD followed linear trend s with increasing levels of these three indicators (all P trend < 0.001). The risk assessment model consisting of SUA, ALT, WC and demographics showed useful discrimination by AUROC being 0.825 (95% CI [0.811-0.838]) and good performance of calibration (P = 0.561). Conclusions: SUA, ALT and WC were all associated with NAFLD, independent of known risk factors. The simple model composed of these indicators showed good performance in the Chinese population, which may be applicable for appraisal of NAFLD risk in primary healthcare.

Hollow Cobalt Oxide/Carbon Hybrids Aid Metabolic Encoding for Active Systemic Lupus Erythematosus during Pregnancy.

A noninvasive, easy operation, and accurate diagnostic protocol is highly demanded to assess systemic lupus erythematosus (SLE) activity during pregnancy, promising real-time activity monitoring during the whole gestational period to reduce adverse pregnancy outcomes. Here, machine learning of serum metabolic fingerprints (SMFs) is developed to assess the SLE activity for pregnant women. The SMFs are directly extracted through a hollow-cobalt oxide/carbon (Co3 O4 /C)-composite-assisted laser desorption/ionization mass spectrometer (LDI MS) platform. The Co3 O4 /C composite owns enhanced light absorption, size-selective trapping, and better charge-hole separation, enabling improved ionization efficiency and selectivity for LDI MS detection toward small molecules. Metabolic fingerprints are collected from ≈0.1 µL serum within 1 s without enrichment and encoded by the optimized elastic net algorithm. The averaged area under the curve (AUC) value in the differentiation of active SLE from inactive SLE and healthy controls reaches 0.985 and 0.990, respectively. Further, a simplified panel based on four identified metabolites is built to distinguish SLE flares in pregnant women with the highest AUC value of 0.875 for the blind test. This work sets an accurate and practical protocol for SLE activity assessment during pregnancy, promoting precision diagnosis of disease status transitions in clinics.