Systemic lupus erythematosus: one year in review 2023.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with a wide range of clinical manifestations and a relapsing-remitting course. New data regarding pathogenic pathways, biomarkers and clinical manifestations of SLE are emerging, and new drugs and therapeutic protocols have been proposed to improve the control of disease activity. Furthermore, new insights into comorbidities and reproductive health in SLE patients are constantly emerging.This annual review aims to summarise the most relevant data on SLE that was published in 2022.

Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models.

Introduction. The different pathotypes of Escherichia coli can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 consists of stool culture of a diarrhoeal sample on enriched and/or selective media and identification of presumptive colonies and confirmation, which require a certain level of training and are time-consuming and expensive.Hypothesis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a quick and easy way to obtain the protein spectrum of a microorganism, identify the genus and species, and detect potential biomarker peaks of certain characteristics.Aim. To verify the usefulness of MALDI-TOF MS to rapidly identify and differentiate STEC O157 : H7 from other E. coli pathotypes.Methodology. The direct method was employed, and the information obtained using Microflex LT platform-based analysis from 60 clinical isolates (training set) was used to detect differences between the peptide fingerprints of STEC O157 : H7 and other E. coli strains. The protein profiles detected laid the foundations for the development and evaluation of machine learning predictive models in this study.Results. The detection of potential biomarkers in combination with machine learning predictive models in a new set of 142 samples, called 'test set', achieved 99.3 % (141/142) correct classification, allowing us to distinguish between the isolates of STEC O157 : H7 and the other E. coli group. Great similarity was also observed with respect to this last group and the Shigella species when applying the potential biomarkers algorithm, allowing differentiation from STEC O157 : H7Conclusion. Given that STEC O157 : H7 is the main causal agent of haemolytic uremic syndrome, and based on the performance values obtained in the present study (sensitivity=98.5 % and specificity=100.0 %), the implementation of this technique provides a proof of principle for MALDI-TOF MS and machine learning to identify biomarkers to rapidly screen or confirm STEC O157 : H7 versus other diarrhoeagenic E. coli in the future.

Association between triglyceride glucose-related markers and the risk of metabolic-associated fatty liver disease: a cross-sectional study in healthy Chinese participants.

OBJECTIVES: This study aimed to evaluate the performance of the triglyceride glucose (TyG) index and its related markers in predicting metabolic-associated fatty liver disease (MAFLD) in healthy Chinese participants. DESIGN: This was a cross-sectional study. SETTING: The study was conducted at Health Management Department of the Affiliated Hospital of Xuzhou Medical University. PARTICIPANTS: A total of 20 922 asymptomatic Chinese participants (56% men) were enrolled. OUTCOME MEASURES: Hepatic ultrasonography was performed to diagnose MAFLD based on the latest diagnostic criteria. The TyG, TyG-body mass (TyG-BMI) and TyG-waist circumference indices were calculated and analysed. RESULTS: Compared with the lowest quartile of the TyG-BMI, the adjusted ORs and 95% CIs for MAFLD were 20.76 (14.54 to 29.65), 92.33 (64.61 to 131.95) and 380.87 (263.25 to 551.05) in the second, third and fourth quartiles, respectively. According to the subgroup analysis, the TyG-BMI in the female and the lean groups (BMI<23 kg/m2) showed the strongest predictive value, with optimal cut-off values for MAFLD of 162.05 and 156.31, respectively. The areas under the receiver operating characteristic curves in female and lean groups were 0.933 (95% CI 0.927 to 0.938) and 0.928 (95% CI 0.914 to 0.943), respectively, with 90.7% sensitivity and 81.2% specificity in female participants with MAFLD and 87.2% sensitivity and 87.1% specificity in lean participants with MAFLD. The TyG-BMI index demonstrated superior predictive ability for MAFLD compared with other markers. CONCLUSIONS: The TyG-BMI is an effective, simple and promising tool for predicting MAFLD, especially in lean and female participants.

Lymphocyte-C-reactive protein ratio with calf circumference could better predict survival of patients with non-metastatic cancer.

Systemic inflammatory responses caused by tumor cells play an important role in the occurrence and development of tumors. The aim of this study was to identify biomarkers that most accurately predict prognoses in patients with non-metastatic cancer and to evaluate their clinical significance when combined with muscle markers. This study retrospectively evaluated 2,797 cancer patients diagnosed with cancer at TNM stages I, II, and III. Lymphocyte-C-reactive protein ratio (LCR) in conjunction with calf circumference (CC) were used (or chosed) after evaluating the predictive value of 13 inflammatory marker combinations and five anthropometric indicators for patient outcomes using the C-index. The Kaplan-Meier method and Cox's proportional hazards regression modeling were used to analyze the individual and combined effects of these two potential biomarkers on overall survival. This study enrolled 1,604 men (57.3%) and 1,193 women (42.7%) with a mean age of 58.75 years. Among the 13 inflammatory nutritional indicators, the LCR was the most accurate predictor of prognoses in patients with non-metastatic cancer. After multifactorial adjustment, we found that low LCR had an adverse effect on overall survival (hazard ratio [HR]: 2.50; 95% confidence interval [CI]: 2.17, 2.88; P < 0.001). Low LCR combined with low CC was also shown to be an independent risk factor for poor overall survival (HR: 2.26; 95% CI: 1.80, 2.83; P < 0.001). Compared with LCR or CC alone, the combination of the two had greater prognostic value for patients with non-metastatic cancer. The LCR can be implemented as a useful biomarker to predict prognoses in patients with non-metastatic cancer. CC is the best anthropometric indicator of muscle loss in patients with non-metastatic cancer. The combination of LCR and CC can better predict the prognosis of patients with non-metastatic cancer, and can provide important information for clinicians to formulate diagnosis and treatment plans.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Identification of NETs-related biomarkers and molecular clusters in systemic lupus erythematosus.

Neutrophil extracellular traps (NETs) is an important process involved in the pathogenesis of systemic lupus erythematosus (SLE), but the potential mechanisms of NETs contributing to SLE at the genetic level have not been clearly investigated. This investigation aimed to explore the molecular characteristics of NETs-related genes (NRGs) in SLE based on bioinformatics analysis, and identify associated reliable biomarkers and molecular clusters. Dataset GSE45291 was acquired from the Gene Expression Omnibus repository and used as a training set for subsequent analysis. A total of 1006 differentially expressed genes (DEGs) were obtained, most of which were associated with multiple viral infections. The interaction of DEGs with NRGs revealed 8 differentially expressed NRGs (DE-NRGs). The correlation and protein-protein interaction analyses of these DE-NRGs were performed. Among them, HMGB1, ITGB2, and CREB5 were selected as hub genes by random forest, support vector machine, and least absolute shrinkage and selection operator algorithms. The significant diagnostic value for SLE was confirmed in the training set and three validation sets (GSE81622, GSE61635, and GSE122459). Additionally, three NETs-related sub-clusters were identified based on the hub genes' expression profiles analyzed by unsupervised consensus cluster assessment. Functional enrichment was performed among the three NETs subgroups, and the data revealed that cluster 1 highly expressed DEGs were prevalent in innate immune response pathways while that of cluster 3 were enriched in adaptive immune response pathways. Moreover, immune infiltration analysis also revealed that innate immune cells were markedly infiltrated in cluster 1 while the adaptive immune cells were upregulated in cluster 3. As per our knowledge, this investigation is the first to explore the molecular characteristics of NRGs in SLE, identify three potential biomarkers (HMGB1, ITGB2, and CREB5), and three distinct clusters based on these hub biomarkers.

Gut microbiota predicts the diagnosis of celiac disease in Saudi children.

BACKGROUND: Celiac disease (CeD) is a multisystem immune-mediated multifactorial condition strongly associated with the intestinal microbiota. AIM: To evaluate the predictive power of the gut microbiota in the diagnosis of CeD and to search for important taxa that may help to distinguish CeD patients from controls. METHODS: Microbial DNA from bacteria, viruses, and fungi, was isolated from mucosal and fecal samples of 40 children with CeD and 39 controls. All samples were sequenced using the HiSeq platform, the data were analyzed, and abundance and diversities were assessed. For this analysis, the predictive power of the microbiota was evaluated by calculating the area under the curve (AUC) using data for the entire microbiome. The Kruskal-Wallis test was used to evaluate the significance of the difference between AUCs. The Boruta logarithm, a wrapper built around the random forest classification algorithm, was used to identify important bacterial biomarkers for CeD. RESULTS: In fecal samples, AUCs for bacterial, viral, and fungal microbiota were 52%, 58%, and 67.7% respectively, suggesting weak performance in predicting CeD. However, the combination of fecal bacteria and viruses showed a higher AUC of 81.8 %, indicating stronger predictive power in the diagnosis of CeD. In mucosal samples, AUCs for bacterial, viral, and fungal microbiota were 81.2%, 58.6%, and 35%, respectively, indicating that mucosal bacteria alone had the highest predictive power. Two bacteria, Bacteroides intestinalis and Burkholderiales bacterium 1-1-47, in fecal samples and one virus, Human_endogenous _retrovirus_K, in mucosal samples are predicted to be "important" biomarkers, differentiating celiac from nonceliac disease groups. Bacteroides intestinalis is known to degrade complex arabinoxylans and xylan which have a protective role in the intestinal mucosa. Similarly, several Burkholderiales species have been reported to produce peptidases that hydrolyze gluten peptides, with the potential to reduce the gluten content of food. Finally, a role for Human_endogenous _retrovirus_K in immune-mediated disease such as CeD has been reported. CONCLUSION: The excellent predictive power of the combination of the fecal bacterial and viral microbiota with mucosal bacteria alone indicates a potential role in the diagnosis of difficult cases of CeD. Bacteroides intestinalis and Burkholderiales bacterium 1-1-47, which were found to be deficient in CeD, have a potential protective role in the development of prophylactic modalities. Further studies on the role of the microbiota in general and Human_endogenous _retrovirus_K in particular are needed.

Extracellular vesicles from human plasma for biomarkers discovery: Impact of anticoagulants and isolation techniques.

Extracellular vesicles (EVs) isolated from plasma are increasingly recognized as promising circulating biomarkers for disease discovery and progression, as well as for therapeutic drug delivery. The scientific community underlined the necessity of standard operative procedures for the isolation and storage of the EVs to ensure robust results. The understanding of the impact of the pre-analytical variables is still limited and some considerations about plasma anticoagulants and isolation methods are necessary. Therefore, we performed a comparison study between EVs isolated by ultracentrifugation and by affinity substrate separation from plasma EDTA and sodium citrate. The EVs were characterized by Nano Tracking Analysis, Western Blot, cytofluorimetric analysis of surface markers, and lipidomic analysis. While anticoagulants did not significantly alter any of the analyzed parameters, the isolation methods influenced EVs size, purity, surface markers expression and lipidomic profile. Compared to ultracentrifugation, affinity substrate separation yielded bigger particles highly enriched in tetraspanins (CD9, CD63, CD81), fatty acids and glycerolipids, with a predominant LDL- and vLDL-like contamination. Herein, we highlighted that the isolation method should be carefully evaluated prior to study design and the need of standardized operative procedures for EVs isolation and application to biomarkers discovery.

The Associations of Trans-3'-Hydroxy Cotinine, Cotinine, and the Nicotine Metabolite Ratio in Pediatric Patients with Tobacco Smoke Exposure.

(1) Background: Trans-3'-hydroxy cotinine (3HC) and cotinine (COT) are tobacco smoke exposure (TSE) biomarkers and the 3HC/COT ratio is a marker of CYP2A6 activity, an enzyme which metabolizes nicotine. The primary objective was to assess the associations of these TSE biomarkers with sociodemographics and TSE patterns in children who lived with ≥1 smoker. (2) Methods: A convenience sample of 288 children (mean age (SD) = 6.42 (4.8) years) was recruited. Multiple linear regression models were built to assess associations of sociodemographics and TSE patterns with urinary biomarker response variables: (1) 3HC, (2) COT, (3) 3HC+COT sum, and (4) 3HC/COT ratio. (3) Results: All children had detectable 3HC (Geometric Mean [GeoM] = 32.03 ng/mL, 95%CI = 26.97, 38.04) and COT (GeoM = 10.24 ng/mL, 95%CI = 8.82, 11.89). Children with higher cumulative TSE had higher 3HC and COT (ß^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015 and ß^ = 0.03, 95%CI = 0.01, 0.05, p = 0.013, respectively). Highest 3HC+COT sum levels were in children who were Black (ß^ = 0.60, 95%CI = 0.04, 1.17, p = 0.039) and who had higher cumulative TSE (ß^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015). Lowest 3HC/COT ratios were in children who were Black (ß^ = -0.42, 95%CI = -0.78, -0.07, p = 0.021) and female (ß^ = -0.32, 95%CI = -0.62, -0.01, p = 0.044). (4) Conclusion: Results indicate that there are racial and age-related differences in TSE, most likely due to slower nicotine metabolism in non-Hispanic Black children and in younger children.

Patient-derived head and neck cancer organoids allow treatment stratification and serve as a tool for biomarker validation and identification.

BACKGROUND: Organoids are in vitro three-dimensional structures that can be grown from patient tissue. Head and neck cancer (HNC) is a collective term used for multiple tumor types including squamous cell carcinomas and salivary gland adenocarcinomas. METHODS: Organoids were established from HNC patient tumor tissue and characterized using immunohistochemistry and DNA sequencing. Organoids were exposed to chemo- and radiotherapy and a panel of targeted agents. Organoid response was correlated with patient clinical response. CRISPR-Cas9-based gene editing of organoids was applied for biomarker validation. FINDINGS: A HNC biobank consisting of 110 models, including 65 tumor models, was generated. Organoids retained DNA alterations found in HNC. Comparison of organoid and patient response to radiotherapy (primary [n = 6] and adjuvant [n = 15]) indicated potential for guiding treatment options in the adjuvant setting. In organoids, the radio-sensitizing potential of cisplatin and carboplatin could be validated. However, cetuximab conveyed radioprotection in most models. HNC-targeted treatments were tested on 31 models, indicating possible novel treatment options with the potential for treatment stratification in the future. Activating PIK3CA mutations did not predict alpelisib response in organoids. Protein arginine methyltransferase 5 (PRMT5) inhibitors were identified as a potential treatment option for cyclin-dependent kinase inhibitor 2A (CDKN2A) null HNC. CONCLUSIONS: Organoids hold potential as a diagnostic tool in personalized medicine for HNC. In vitro organoid response to radiotherapy (RT) showed a trend that mimics clinical response, indicating the predictive potential of patient-derived organoids. Moreover, organoids could be used for biomarker discovery and validation. FUNDING: This work was funded by Oncode PoC 2018-P0003.

Fatty Acids and Bilirubin as Intrinsic Autofluorescence Serum Biomarkers of Drug Action in a Rat Model of Liver Ischemia and Reperfusion.

The autofluorescence of specific fatty acids, retinoids, and bilirubin in crude serum can reflect changes in liver functional engagement in maintaining systemic metabolic homeostasis. The role of these fluorophores as intrinsic biomarkers of pharmacological actions has been investigated here in rats administered with obeticholic acid (OCA), a Farnesoid-X Receptor (FXR) agonist, proven to counteract the increase of serum bilirubin in hepatic ischemia/reperfusion (I/R) injury. Fluorescence spectroscopy has been applied to an assay serum collected from rats submitted to liver I/R (60/60 min ± OCA administration). The I/R group showed changes in the amplitude and profiles of emission spectra excited at 310 or 366 nm, indicating remarkable alterations in the retinoid and fluorescing fatty acid balance, with a particular increase in arachidonic acid. The I/R group also showed an increase in bilirubin AF, detected in the excitation spectra recorded at 570 nm. OCA greatly reversed the effects observed in the I/R group, confirmed by the biochemical analysis of bilirubin and fatty acids. These results are consistent with a relationship between OCA anti-inflammatory effects and the acknowledged roles of fatty acids as precursors of signaling agents mediating damaging responses to harmful stimuli, supporting serum autofluorescence analysis as a possible direct, real-time, cost-effective tool for pharmacological investigations.

LC/MS-Based Untargeted Metabolomics Analysis in Women with Morbid Obesity and Associated Type 2 Diabetes Mellitus.

Obesity is a chronic and complex disease, with an increasing incidence worldwide that is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM). Thus, it is important to determine the differences between metabolically healthy obese individuals and those with metabolic disorders. The aim of this study was to perform an untargeted metabolomics assay in women with morbid obesity (MO) compared to a normal weight group, and to differentiate the metabolome of these women with MO who present with T2DM. We carried out a liquid chromatography-mass spectrometry-based untargeted metabolomics assay using serum samples of 209 Caucasian women: 73 with normal weight and 136 with MO, of which 71 had T2DM. First, we found increased levels of choline and acylglycerols and lower levels of bile acids, steroids, ceramides, glycosphingolipids, lysophosphatidylcholines, and lysophosphatidylethanolamines in MO women than in the control group. Then, in MO women with T2DM, we found increased levels of glutamate, propionyl-carnitine, bile acids, ceramides, lysophosphatidylcholine 14:0, phosphatidylinositols and phosphoethanolamines, and lower levels of Phe-Ile/Leu. Thus, we found metabolites with opposite trends of concentration in the two metabolomic analyses. These metabolites could be considered possible new factors of study in the pathogenesis of MO and associated T2DM in women.

SMAD4 Expression in Monocytes as a Potential Biomarker for Atherosclerosis Risk in Patients with Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA) patients are at special risk of suffering atherosclerosis, leading to major cardiovascular diseases. Notably, the transforming growth factor (TGF-ß) plays a crucial role in the development and progression of atherosclerosis. In this context, the central regulator of TGF-ß pathway, SMAD4 (small mother against decapentaplegic homolog 4), has been previously reported to be augmented in OSA patients, which levels were even higher in patients with concomitant cardiometabolic diseases. Here, we analyzed soluble and intracellular SMAD4 levels in plasma and monocytes from OSA patients and non-apneic subjects, with or without early subclinical atherosclerosis (eSA). In addition, we used in vitro and ex vivo models to explore the mechanisms underlying SMAD4 upregulation and release. Our study confirmed elevated sSMAD4 levels in OSA patients and identified that its levels were even higher in those OSA patients with eSA. Moreover, we demonstrated that SMAD4 is overexpressed in OSA monocytes and that intermittent hypoxia contributes to SMAD4 upregulation and release in a process mediated by NLRP3. In conclusion, this study highlights the potential role of sSMAD4 as a biomarker for atherosclerosis risk in OSA patients and provides new insights into the mechanisms underlying its upregulation and release to the extracellular space.

Multiplexing Biosensor for the Detection of Extracellular Vesicles as Biomarkers of Tissue Damage and Recovery after Ischemic Stroke.

The inflammatory, reparative and regenerative mechanisms activated in ischemic stroke patients immediately after the event cooperate in the response to injury, in the restoration of functions and in brain remodeling even weeks after the event and can be sustained by the rehabilitation treatment. Nonetheless, patients' response to treatments is difficult to predict because of the lack of specific measurable markers of recovery, which could be complementary to clinical scales in the evaluation of patients. Considering that Extracellular Vesicles (EVs) are carriers of multiple molecules involved in the response to stroke injury, in the present study, we have identified a panel of EV-associated molecules that (i) confirm the crucial involvement of EVs in the processes that follow ischemic stroke, (ii) could possibly profile ischemic stroke patients at the beginning of the rehabilitation program, (iii) could be used in predicting patients' response to treatment. By means of a multiplexing Surface Plasmon Resonance imaging biosensor, subacute ischemic stroke patients were proven to have increased expression of vascular endothelial growth factor receptor 2 (VEGFR2) and translocator protein (TSPO) on the surface of small EVs in blood. Besides, microglia EVs and endothelial EVs were shown to be significantly involved in the intercellular communications that occur more than 10 days after ischemic stroke, thus being potential tools for the profiling of patients in the subacute phase after ischemic stroke and in the prediction of their recovery.

A Scoping Review Investigating the "Gene-Dosage Theory" of Mitochondrial DNA in the Healthy Skeletal Muscle.

This review provides an overview of the evidence regarding mtDNA and valid biomarkers for assessing mitochondrial adaptions. Mitochondria are small organelles that exist in almost all cells throughout the human body. As the only organelle, mitochondria contain their own DNA, mitochondrial DNA (mtDNA). mtDNA-encoded polypeptides are subunits of the enzyme complexes in the electron transport chain (ETC) that are responsible for production of ATP to the cells. mtDNA is frequently used as a biomarker for mitochondrial content, since changes in mitochondrial volume are thought to induce similar changes in mtDNA. However, some exercise studies have challenged this "gene-dosage theory", and have indicated that changes in mitochondrial content can adapt without changes in mtDNA. Thus, the aim of this scoping review was to summarize the studies that used mtDNA as a biomarker for mitochondrial adaptions and address the question as to whether changes in mitochondrial content, induce changes in mtDNA in response to aerobic exercise in the healthy skeletal muscle. The literature was searched in PubMed and Embase. Eligibility criteria included: interventional study design, aerobic exercise, mtDNA measurements reported pre- and postintervention for the healthy skeletal muscle and English language. Overall, 1585 studies were identified. Nine studies were included for analysis. Eight out of the nine studies showed proof of increased oxidative capacity, six found improvements in mitochondrial volume, content and/or improved mitochondrial enzyme activity and seven studies did not find evidence of change in mtDNA copy number. In conclusion, the findings imply that mitochondrial adaptions, as a response to aerobic exercise, can occur without a change in mtDNA copy number.

Recent advances in the roles of exosomal microRNAs (exomiRs) in hematologic neoplasms: pathogenesis, diagnosis, and treatment.

In clinical diagnosis, the capability of exosomes to serve as biomarkers is one of the most important biological functions of exosomes. The superior stability of exosome biomarkers makes them superior to those isolated from traditional samples such as serum and urine. Almost all body fluids contain exosomes, which contain proteins, nucleic acids, and lipids. Several molecular components of exosomes, including exosome proteins and microRNAs (miRNAs), are promising diagnostic biomarkers. These exosomes may carry genetic information by containing messenger RNA (mRNA) and miRNA. The miRNAs are small noncoding RNAs that regulate protein-coding genes by acting as translational repressors. It has been shown that miRNAs are mis-expressed in a range of conditions, including hematologic neoplasms. Additionally, miRNAs found within exosomes have been linked with specific diseases, including hematologic neoplasms. Numerous studies suggest that circulating exosomes contain miRNAs similar to those found in parental cancer cells. Exosomes contain miRNAs that are released by almost all kinds of cells. MiRNAs are packaged into exosomes and delivered to recipient cells, and manipulate its function. It has been recognized that exosomes are new therapeutic targets for immunotherapy and biomedicine of cancers. The current review discusses the current evidence around exosomal miRNAs involved in the pathogenesis, diagnosis, and treatment of hematologic neoplasms. Video Abstract.

Combination of precipitation and size exclusion chromatography as an effective method for exosome like extracellular vesicle isolation from pericardial fluids.

Extracellular vesicles (EVs), such as exosomes, are nanovesicles that have received significant attention due to their ability to contain various molecular cargos. EVs found in biological fluids have been demonstrated to have therapeutic potential, including as biomarkers. Despite being extensively studied, a significant downfall in EV research is the lack of standardised protocol for its isolation from human biological fluids, where EVs usually exist at low densities. In this study, we tested two well-established EV isolation protocols, precipitation, and size exclusion chromatography (SEC), to determine their efficiency in isolating EVs from the pericardial fluid. Precipitation alone resulted in high yields of low-purity exosomes as tested by DLS analysis, transmission electron microscopy, immunogold labelling and western blotting for the exosomal surface proteins. While EVs isolated by SEC were pure, the concentration was low. Interestingly, the combination of precipitation followed by SEC resulted in high EV yields with good purity. Our results suggest that the combination method can be adapted to isolate EVs from body fluids which have low densities of EV.

CD4+CD25+CD127loFOXP3+ cell in food allergy: Does it predict anaphylaxis?

BACKGROUND: Food allergy (FA), hence the incidence of food anaphylaxis, is a public health problem that has increased in recent years. There are still no biomarkers for patients with FA to predict severe allergic reactions such as anaphylaxis. OBJECTIVE: There is limited information on whether regulatory T (Treg) cell levels are a biomarker that predicts clinical severity in cases presenting with FA, and which patients are at a greater risk for anaphylaxis. METHODS: A total of 70 children were included in the study: 25 who had IgE-mediated cow's milk protein allergy (CMPA) and presented with non-anaphylactic symptoms (FA/A-), 16 who had IgE-mediated CMPA and presented with anaphylaxis (FA/A+) (a total of 41 FA cases), and a control group consisting of 29 children without FA. The study was conducted by performing CD4+CD25+CD127loFOXP3+ cell flow cytometric analysis during resting at least 2 weeks after the elimination diet to FA subjects. RESULTS: When the FA group was compared with healthy control subjects, CD4+CD25+CD127loFOXP3+ cell rates were found to be significantly lower in the FA group (p < 0.001). When the FA/A- and FA/A+ groups and the control group were compared in terms of CD4+CD25+CD127loFOXP3+ cell ratios, they were significantly lower in the FA/A- and FA/A+ groups compared to the control group (p < 0.001). CONCLUSIONS: Although there was no significant difference between the FA/A+ group and the FA/A- group in terms of CD4+CD25+CD127loFOXP3+ cells, our study is important, as it is the first pediatric study we know to investigate whether CD4+CD25+CD127loFOXP3+ cells in FA predict anaphylaxis.

Effect of Allium cepa extract on total and differential WBC, TP level, oxidant and antioxidant biomarkers, and lung pathology in ovalbumin-sensitized rats.

BACKGROUND: Previous studies have shown that Allium cepa (A. cepa) has relaxant and anti-inflammatory effects. In this research, A. cepa extract was examined for its prophylactic effect on lung inflammation and oxidative stress in sensitized rats. METHODS: Total and differential white blood cell (WBC) count in the blood, serum levels of oxidant and antioxidant biomarkers, total protein (TP) in bronchoalveolar lavage fluid (BALF), and lung pathology were investigated in control group (C), sensitized group (S), and sensitized groups treated with A. cepa and dexamethasone. RESULTS: Total and most differential WBC count, TP, NO2, NO3, MDA (malondialdehyde), and lung pathological scores were increased while lymphocytes, superoxide dismutase (SOD), catalase (CAT), and thiol were decreased in sensitized animals compared to controls (p < 0.01 to p < 0.001). Treatment with all concentrations of extract significantly improved total WBC, TP, NO2, NO3, interstitial fibrosis, and emphysema compared to the S group (p < 0.05 to p < 0.001). Two higher concentrations of the extract significantly decreased neutrophil and monocyte count, malondialdehyde, bleeding and epithelial damage but increased lymphocyte, CAT, and thiol compared to the S group (p < 0.05 to p < 0.001). Dexamethasone treatment also substantially improved most measured parameters (p < 0.05 to p < 0.001), but it did not change eosinophil percentage. It was proposed that A. cepa extract could affect lung inflammation and oxidative stress in sensitized rats.

Isolation and Identification of Plasma Extracellular Vesicles Protein Biomarkers.

Extracellular vesicles (EVs) have emerged as a valuable source for disease biomarkers and an alternative drug delivery system due to their ability to carry cargo and target specific cells. Proper isolation, identification, and analytical strategy are required for evaluating their potential in diagnostics and therapeutics. Here, a method is detailed to isolate plasma EVs and analyze their proteomic profiling, combining EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and mass spectrometry qualitative and quantitative strategies for EV proteome characterization. The pipeline provides a highly effective EV-based proteome analysis technique that can be applied for EV characterization and evaluation of EV-based diagnosis and therapy.