Multiple Biofluids Research Articles

Reusable Cyclodextrin-Mediated Electrochemical Sensor in Automated Flow Cell for Cortisol Detection

Our focus is on using beta cyclodextrin (βCD) to electrochemically detect cortisol; cortisol is a hydrophobic molecule that is a vital hormone, and cortisol is involved in the immune system, metabolism, heart health, and overall body balance. Cyclodextrins, characterized by a hydrophobic inner cavity and a hydrophilic outer surface, emerge as promising molecular receptors for detecting hydrophobic molecules. Notably, βCD and cortisol can form host/guest inclusion complexes. Building on our success in detecting cortisol with βCD in previous static cell experiments [1], herein we introduce innovations to further improve our methodology by employing an automated flow cell system. The transition to automation offers advantages such as repeated runs for obtaining more reproducible data and the elimination of human interactions and considerations, leading to an increased number of experiments. Our efforts, including the utilization of a ten-way multi-position valve and a pump for solution transfer, were crucial for enhancing the accuracy, stability, and reproducibility of cyclodextrin-mediated biosensors in automated flow cell systems. The automation process did encounter challenges, particularly with pump control, necessitating manual pauses before electrochemical measurements. Additionally, issues related to bubbles arose, prompting the search for the optimal flow rate and the utilization of a degasser. The ultimate goal is to optimize sensor stability, sensitivity, and reproducibility, contributing to the advancement of cortisol detection with the automated cyclodextrin-mediated biosensors.Research supported by New Hampshire- INBRE through an Institutional Development Award (IDeA), P20GM103506, from the National Institute of General Medical Sciences of the NIH. Support was also provided by a National Science Foundation EPSCoR award (#2119237), BIO-SENS.[1] Z. Panahi, T. Ren, and J. M. Halpern, “Nanostructured Cyclodextrin-Mediated Surface for Capacitive Determination of Cortisol in Multiple Biofluids,” ACS Appl. Mater. Interfaces, vol. 14, no. 37, pp. 42374–42387, Sep. 2022, doi: 10.1021/acsami.2c07701.

Patterns of perinatal polyunsaturated fatty acid status and associated dietary or candidate-genetic factors

Perinatal exposure to omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) can be characterized through biomarkers in maternal or cord blood or breast milk. Objectives were to describe perinatal PUFA status combining multiple biofluids and to investigate how it was influenced by dietary intake during pregnancy and maternal FADS and ELOVL gene polymorphisms. This study involved 1,901 mother–child pairs from the EDEN cohort, with PUFA levels measured in maternal and cord erythrocytes, and colostrum. Maternal dietary PUFA intake during the last trimester was derived from a food frequency questionnaire. Twelve single-nucleotide polymorphisms in FADS and ELOVL genes were genotyped from maternal DNA. Principal component analysis incorporating PUFA levels from the three biofluids identified patterns of perinatal PUFA status. Spearman’s correlations explored associations between patterns and PUFA dietary intake, and linear regression models examined pattern associations with FADS or ELOVL haplotypes. Five patterns were retained: “High omega-3 LC-PUFAs, low omega-6 LC-PUFAs”; “Omega-6 LC-PUFAs”; “Colostrum LC-PUFAs”; “Omega-6 precursor (LA) and DGLA”; “Omega-6 precursor and colostrum ALA”. Maternal omega-3 LC-PUFA intakes were correlated with “High omega-3 LC-PUFAs, low omega-6 LC-PUFAs” (r(DHA) = 0.33) and “Omega-6 LC-PUFAs” (r(DHA) = −0.19) patterns. Strong associations were found between FADS haplotypes and PUFA patterns except for “High omega-3 LC-PUFAs, low omega-6 LC-PUFAs”. Lack of genetic association with the “High omega-3 LC-PUFAs, low omega-6 LC-PUFAs” pattern, highly correlated with maternal omega-3 LC-PUFA intake, emphasizes the importance of adequate omega-3 LC-PUFA intake during pregnancy and lactation. This study offers a more comprehensive assessment of perinatal PUFA status and its determinants.

Abstract P497: Saliva, Plasma, and Multi-Fluid Metabolomic Profiles of Excess Adiposity and Their Associations With Diabetes Progression Among Puerto Ricans

Introduction: Plasma metabolomic profiles of BMI are associated with type 2 diabetes (T2D) risk but none have examined saliva or combined information from multiple biofluids. Our aim was to identify plasma, saliva, and plasma-saliva multi-fluid metabolomic profiles of BMI and waist circumference (WC) and examine their associations with diabetes progression. Methods: We included 911 participants from the San Juan Overweight Adult Longitudinal Study, a 3-year prospective cohort of overweight Puerto Ricans. At baseline, using LC-MS, we quantified metabolites from saliva (n=635) and plasma (n=1,051). We used elastic net regression with 10-fold cross-validation to identify metabolomic profiles from plasma, saliva, and plasma and saliva (multi-fluid) that were predictive of BMI and WC. We used Cox-proportional hazard models to evaluate associations between metabolomic profiles and diabetes progression adjusting for age, sex, socioeconomic factors, lifestyle, and medication use. Results: For BMI metabolomic profiles, we identified 207 metabolites in plasma, 118 metabolites in saliva, and 225 in the multi-fluid profile. For WC, we identified 157, 89, and 210 metabolites for plasma, saliva, and multi-fluid profiles, respectively. Highly positively weighted metabolites across all BMI and WC metabolomic profiles included those in pathways of alanine and aspartate metabolism, purine metabolism, and sphingomyelins. BMI and WC metabolomic profiles were highly correlated (r=0.80-0.88). Each SD increase in saliva, but not plasma or multi-fluid, metabolic profile of BMI was significantly associated with diabetes progression (Table). Saliva, but not plasma or multi-fluid, metabolomic profile of WC was significantly associated with progression from pre-diabetes to T2D. All associations became stronger after further adjustment for anthropometric measures of BMI and WC. Conclusion: Saliva is an underexplored and easily accessible biofluid to measure metabolites that associate with diabetes progression.

Exosome-Mediated Antigen Delivery: Unveiling Novel Strategies in Viral Infection Control and Vaccine Design.

Exosomes are small subtypes of extracellular vesicles (EVs) naturally released by different types of cells into their environment. Their physiological roles appear to be multiple, yet many aspects of their biological activities remain to be understood. These vesicles can transport and deliver a variety of cargoes and may serve as unconventional secretory vesicles. Thus, they play a crucial role as important vectors for intercellular communication and the maintenance of homeostasis. Exosome production and content can vary under several stresses or modifications in the cell microenvironment, influencing cellular responses and stimulating immunity. During infectious processes, exosomes are described as double-edged swords, displaying both beneficial and detrimental effects. Owing to their tractability, the analysis of EVs from multiple biofluids has become a booming tool for monitoring various pathologies, from infectious to cancerous origins. In this review, we present an overview of exosome features and discuss their particular and ambiguous functions in infectious contexts. We then focus on their properties as diagnostic or therapeutic tools. In this regard, we explore the capacity of exosomes to vectorize immunogenic viral antigens and their function in mounting adaptive immune responses. As exosomes provide interesting platforms for antigen presentation, we further review the available data on exosome engineering, which enables peptides of interest to be exposed at their surface. In the light of all these data, exosomes are emerging as promising avenues for vaccine strategies.

Potential Metabolite Biomarkers of Multiple Sclerosis from Multiple Biofluids.

Multiple sclerosis (MS) is a chronic and progressive neurological disorder without a cure, but early intervention can slow disease progression and improve the quality of life for MS patients. Obtaining an accurate diagnosis for MS is an arduous and error-prone task that requires a combination of a detailed medical history, a comprehensive neurological exam, clinical tests such as magnetic resonance imaging, and the exclusion of other possible diseases. A simple and definitive biofluid test for MS does not exist, but is highly desirable. To address this need, we employed NMR-based metabolomics to identify potentially unique metabolite biomarkers of MS from a cohort of age and sex-matched samples of cerebrospinal fluid (CSF), serum, and urine from 206 progressive MS (PMS) patients, 46 relapsing-remitting MS (RRMS) patients, and 99 healthy volunteers without a MS diagnosis. We identified 32 metabolites in CSF that varied between the control and PMS patients. Utilizing patient-matched serum samples, we were able to further identify 31 serum metabolites that may serve as biomarkers for PMS patients. Lastly, we identified 14 urine metabolites associated with PMS. All potential biomarkers are associated with metabolic processes linked to the pathology of MS, such as demyelination and neuronal damage. Four metabolites with identical profiles across all three biofluids were discovered, which demonstrate their potential value as cross-biofluid markers of PMS. We further present a case for using metabolic profiles from PMS patients to delineate biomarkers of RRMS. Specifically, three metabolites exhibited a variation from healthy volunteers without MS through RRMS and PMS patients. The consistency of metabolite changes across multiple biofluids, combined with the reliability of a receiver operating characteristic classification, may provide a rapid diagnostic test for MS.

Expanding Our Cyclodextrin-Based Sensors with Automation and New Surfaces

We have had significant success in building cyclodextrin mediated sensors. We initially started with a gold surface, being able to detect analyte up to three times post modification [1]. Afterwards, we improved the stability and reusability by moving to a phenyl-modified carbon electrode via diazonium salt chemistry [2]. With his new surface, we were able to detect cortisol up to 10 different times with high accuracy, repeatability, and sensitivity in buffer, urine, and artificial saliva. We were limited by manually manipulating the electrode; therefore, we were not able to test the electrode for greater than 10 measurements. Within this poster, we intend to present our ideas and progress towards developing an automated detection system that can be preprogrammed to clean, reset, and test the cyclodextrin-mediated surface with target analytes. Further, we will share our various target analytes and our strategy to expand our sensor surface to include multiple cyclodextrin derivatives.Research supported by New Hampshire- INBRE through an Institutional Development Award (IDeA), P20GM103506, from the National Institute of General Medical Sciences of the NIH.[1] Z. Panahi, M. A. Merrill, and J. M. Halpern, “Reusable Cyclodextrin-Based Electrochemical Platform for Detection of trans -Resveratrol,” ACS Appl. Polym. Mater., vol. 2, no. 11, pp. 5086–5093, Nov. 2020.[2] Z. Panahi, T. Ren, and J. M. Halpern, “Nanostructured Cyclodextrin-Mediated Surface for Capacitive Determination of Cortisol in Multiple Biofluids,” ACS Appl. Mater. Interfaces, Aug. 2022.

Identification of Candidate Salivary, Urinary and Serum Metabolic Biomarkers for High Litter Size Potential in Sows (Sus scrofa).

The selection of sows that are reproductively fit and produce large litters of piglets is imperative for success in the pork industry. Currently, low heritability of reproductive and litter-related traits and unfavourable genetic correlations are slowing the improvement of pig selection efficiency. The integration of biomarkers as a supplement or alternative to the use of genetic markers may permit the optimization and increase of selection protocol efficiency. Metabolite biomarkers are an advantageous class of biomarkers that can facilitate the identification of cellular processes implicated in reproductive condition. Metabolism and metabolic biomarkers have been previously implicated in studies of female mammalian fertility, however a systematic analysis across multiple biofluids in infertile and high reproductive potential phenotypes has not been explored. In the current study, the serum, urinary and salivary metabolomes of infertile (INF) sows and high reproductive potential (HRP) sows with a live litter size ≥ 13 piglets were examined using LC-MS/MS techniques, and a data pipeline was used to highlight possible metabolite reproductive biomarkers discriminating the reproductive groups. The metabolomes of HRP and INF sows were distinct, including significant alterations in amino acid, fatty acid, membrane lipid and steroid hormone metabolism. Carnitines and fatty acid related metabolites were most discriminatory in separating and classifying the HRP and INF sows based on their biofluid metabolome. It appears that urine is a superior biofluid than saliva and serum for potentially predicting the reproductive potential level of a given female pig based on the performance of the resultant biomarker models. This study lays the groundwork for improving gilt and sow selection protocols using metabolomics as a tool for the prediction of reproductive potential.

Nanostructured Cyclodextrin-Mediated Surface for Capacitive Determination of Cortisol in Multiple Biofluids.

The aim of this work is to develop a reusable polypropylene glycol (PPG):β-cyclodextrin (βCD) biosensor for cortisol detection. To achieve the most stable support for βCD, we developed two PPG surfaces. The first surface is based on a gold surface modified with SAM of 3-mercaptopropionic acid (3MPA), and the second surface is based on a glassy carbon surface grafted with 4-carboxyphenyl diazonium salt. We characterized both surfaces by EIS, XPS, and ATR-FTIR and evaluated the stability and reusability of each surface. We found the GC-carboxyphenyl-PPG:βCD is stable for at least 1 month. We have also demonstrated the reusability of the surface up to 10 times. In detecting cortisol, we used a nonfaradaic electrochemical impedance capacitive model to interpret the surface confirmation changes. We achieved sensitive detection of cortisol in PBS buffer, urine, and saliva with limit of detection of 2.13, 1.29, and 1.33 nM, respectively.

Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults

High-throughput quantification of the composition of all chemical elements (elementome) in biological samples is essential for understanding their diverse functions in large cohort studies. We, here, established an ICP-MS method to simultaneously quantify 70 elements in 50 μL biofluids within 5 min. This validated method had excellent quantification linearity (R2 > 0.998), sensitivity (with LOD as low as 1.0 ng/L), precision (CV<15%), accuracy (|RE|<20% except Hg), recovery (80–120%), throughput and coverage with minute samples. The method also showed good applicability to multiple biofluids including human serum, plasma, urine and goat serum samples. By using this method, we furture measured 70 elements in blood plasma samples from 758 Chinese adult participants and established the first reference intervals for the concentration of these elements from 127 healthy adults in this population. This offers a high-throughput quantitative elementomics method to define population elementomic phenotypes and for investigating the diverse biological functions of many elements in multiple biological matrices.

Dynamic behavior of cell-free mitochondrial DNA in human saliva

Mitochondria contain their own genome that can be released in multiple biofluids such as blood and cerebrospinal fluid, as cell-free mitochondrial DNA (cf-mtDNA). In clinical studies, blood cf-mtDNA predicts mortality and higher cf-mtDNA levels are associated with mental and physical stress. However, the dynamics of cf-mtDNA has not been defined, and whether it can be measured non-invasively like other neuroendocrine markers in saliva has not been examined. Here we report cf-mtDNA in human saliva and establish its natural within-person dynamic behavior across multiple weeks. In a small proof-of-principle cohort of healthy adults, we first develop an approach to rapidly quantify salivary cf-mtDNA without DNA isolation, and demonstrate the existence of salivary cf-mtDNA. We then deploy this approach to perform an intensive repeated-measures analysis of two healthy men studied at 4 daily timepoints over 53–60 consecutive days (n = 212–220 observations each) with parallel measures of steroid hormones, self-reported daily mood, and health-related behaviors. Salivary cf-mtDNA exhibited a robust awakening response reaching up to two orders of magnitude 30–45 min after awakening, varied from day-to-day, and moderately correlated with the cortisol awakening response. In exploratory analyses, no consistent association with self-reported daily mood/health-related behaviors were found, although this requires further examination in future studies. Dynamic variation in cf-mtDNA was inversely related with salivary interleukin 6 (IL-6), inconsistent with a pro-inflammatory effect of salivary cf-mtDNA. The highly dynamic behavior of salivary cf-mtDNA opens the door to non-invasive studies examining the relevance of mtDNA signaling in relation to human health.

Metabolomics Analysis Across Multiple Biofluids Reveals the Metabolic Responses of Lactating Holstein Dairy Cows to Fermented Soybean Meal Replacement.

This experiment was performed to reveal the metabolic responses of dairy cows to the replacement of soybean meal (SBM) with fermented soybean meal (FSBM). Twenty-four lactating Chinese Holstein dairy cattle were assigned to either the SBM group [the basal total mixed ration (TMR) diet containing 5.77% SBM] or the FSBM group (the experimental TMR diet containing 5.55% FSBM), in a completely randomized design. The entire period of this trial consisted of 14 days for the adjustment and 40 days for data and sample collection, and sampling for rumen liquid, blood, milk, and urine was conducted on the 34th and 54th day, respectively. When SBM was completely replaced by FSBM, the levels of several medium-chain FA in milk (i.e., C13:0, C14:1, and C16:0) rose significantly (p < 0.05), while the concentrations of a few milk long-chain FA (i.e., C17:0, C18:0, C18:1n9c, and C20:0) declined significantly (p < 0.05). Besides, the densities of urea nitrogen and lactic acid were significantly (p < 0.05) higher, while the glucose concentration was significantly (p < 0.05) lower in the blood of the FSBM-fed cows than in the SBM-fed cows. Based on the metabolomics analysis simultaneously targeting the rumen liquid, plasma, milk, and urine, it was noticed that substituting FSBM for SBM altered the metabolic profiles of all the four biofluids. According to the identified significantly different metabolites, 3 and 2 amino acid-relevant metabolic pathways were identified as the significantly different pathways between the two treatments in the rumen fluid and urine, respectively. Furthermore, glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and cysteine and methionine metabolism were the three key integrated different pathways identified in this study. Results mainly implied that the FSBM replacement could enhance nitrogen utilization and possibly influence the inflammatory reactions and antioxidative functions of dairy cattle. The differential metabolites and relevant pathways discovered in this experiment could serve as biomarkers for the alterations in protein feed and nitrogen utilization efficiency of dairy cows, and further investigations are needed to elucidate the definite roles and correlations of the differential metabolites and pathways.

A Systematic Review of Metabolic Alterations Underlying IgE-Mediated Food Allergy in Children.

Immunoglobulin E-mediated food allergies (IgE-FA) are characterized by an ever-increasing prevalence, currently reaching up to 10.4% of children in the European Union. Metabolomics has the potential to provide a deeper understanding of the pathogenic mechanisms behind IgE-FA. In this work, literature is systematically searched using Web of Science, PubMed, Scopus, and Embase, from January 2010 until May 2021, including human and animal metabolomic studies on multiple biofluids (urine, blood, feces). In total, 15 studies on IgE-FA are retained and a dataset of 277 potential biomarkers is compiled for in-depth pathway mapping. Decreased indoleamine 2,3-dioxygenase-1 (IDO- 1) activity is hypothesized due to altered plasma levels of tryptophan and its metabolites in IgE-FA children. In feces of children prior to IgE-FA, aberrant metabolization of sphingolipids and histidine is noted. Decreased fecal levels of (branched) short chain fatty acids ((B)SCFAs) compel a shift towards aerobic glycolysis and suggest dysbiosis, associated with an immune system shift towards T-helper 2 (Th2) responses. During animal anaphylaxis, a similar switch towards glycolysis is observed, combined with increased ketogenic pathways. Additionally, altered histidine, purine, pyrimidine, and lipid pathways are observed. To conclude, this work confirms the unprecedented opportunities of metabolomics and supports the in-depth pathophysiological qualification in the quest towards improved diagnostic and prognostic biomarkers for IgE-FA.

The polysaccharide chitosan facilitates the isolation of small extracellular vesicles from multiple biofluids.

Several studies have demonstrated the potential uses of extracellular vesicles (EVs) for liquid biopsy‐based diagnostic tests and therapeutic applications; however, clinical use of EVs presents a challenge as many currently‐available EV isolation methods have limitations related to efficiency, purity, and complexity of the methods. Moreover, many EV isolation methods do not perform efficiently in all biofluids due to their differential physicochemical properties. Thus, there continues to be a need for novel EV isolation methods that are simple, robust, non‐toxic, and/or clinically‐amenable. Here we demonstrate a rapid and efficient method for small extracellular vesicle (sEV) isolation that uses chitosan, a linear cationic polyelectrolyte polysaccharide that exhibits biocompatibility, non‐immunogenicity, biodegradability, and low toxicity. Chitosan‐precipitated material was characterized using Western blotting, nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), and relevant proteomic‐based gene ontology analyses. We find that chitosan facilitates the isolation of sEVs from multiple biofluids, including cell culture‐conditioned media, human urine, plasma and saliva. Overall, our data support the potential for chitosan to isolate a population of sEVs from a variety of biofluids and may have the potential to be a clinically amenable sEV isolation method.

Author Response: In Vivo Distribution of α-Synuclein in Multiple Tissues and Biofluids in Parkinson Disease.

Regarding the sensitivity of IHC aSyn methods in participants with idiopathic REM sleep behavioral disorder (RBD), we agree that these are encouraging for the early detection of α-synucleinopathies but point out that not all participants with PD or dementia with Lew bodies (DLB) have RBD and those who do tend to have more widespread and severe aSyn brain histopathology as compared with those without RBD.6 This may also be true for prodromal participants with and without RBD.

A multiparametric extraction method for Vn96-isolated plasma extracellular vesicles and cell-free DNA that enables multi-omic profiling

Extracellular vesicles (EVs) have been recognized as a rich material for the analysis of DNA, RNA, and protein biomarkers. A remaining challenge for the deployment of EV-based diagnostic and prognostic assays in liquid biopsy testing is the development of an EV isolation method that is amenable to a clinical diagnostic lab setting and is compatible with multiple types of biomarker analyses. We have previously designed a synthetic peptide, known as Vn96 (ME kit), which efficiently isolates EVs from multiple biofluids in a short timeframe without the use of specialized lab equipment. Moreover, it has recently been shown that Vn96 also facilitates the co-isolation of cell-free DNA (cfDNA) along with EVs. Herein we describe an optimized method for Vn96 affinity-based EV and cfDNA isolation from plasma samples and have developed a multiparametric extraction protocol for the sequential isolation of DNA, RNA, and protein from the same plasma EV and cfDNA sample. We are able to isolate sufficient material by the multiparametric extraction protocol for use in downstream analyses, including ddPCR (DNA) and ‘omic profiling by both small RNA sequencing (RNA) and mass spectrometry (protein), from a minimum volume (4 mL) of plasma. This multiparametric extraction protocol should improve the ability to analyse multiple biomarker materials (DNA, RNA and protein) from the same limited starting material, which may improve the sensitivity and specificity of liquid biopsy tests that exploit EV-based and cfDNA biomarkers for disease detection and monitoring.

Metabolic Homeostasis in Chronic Helminth Infection Is Sustained by Organ-Specific Metabolic Rewiring.

Opisthorchiasis, is a hepatobiliary disease caused by flukes of the trematode family Opisthorchiidae. A chronic form of the disease implies a prolonged coexistence of a host and the parasite. The pathological changes inflicted by the worm to the host’s hepatobiliary system are well documented. Yet, the response to the infection also triggers a deep remodeling of the host systemic metabolism reaching a new homeostasis and affecting the organs beyond the worm location. Understanding the metabolic alternation in chronic opisthorchiasis, could help us to pinpoint pathways that underlie infection opening possibilities for the development of more selective treatment strategies. Here, with this report we apply an integrative, multicompartment metabolomics analysis, using multiple biofluids, stool samples and tissue extracts to describe metabolic changes in Opisthorchis felineus infected animals at the chronic stage. We show that the shift in lipid metabolism in the serum, a depletion of the amino acids pool, an alteration of the ketogenic pathways in the jejunum and a suppressed metabolic activity of the spleen are the key features of the metabolic host adaptation at the chronic stage of O. felineus infection. We describe this combination of the metabolic changes as a “metabolically mediated immunosuppressive status of organism” which develops during a chronic infection. This status in combination with other factors (e.g., parasite-derived immunomodulators) might increase risk of infection-related malignancy.

Isolation and characterization of human amniotic fluid-derived exosomes.

Extracellular vesicles (EVs), specifically exosomes of 50-150nm, have emerged as important communication channels between cells and tissues and can be isolated from multiple biofluids including blood, urine and amniotic fluid. No standardized approach for exosome isolation from these biofluids has been established. This chapter outlines an optimized approach for isolating exosomes from human amniotic fluid samples. Like plasma, amniotic fluid contains many protein and cellular contaminants that requires multiple steps for cleanup. Therefore, to ensure samples contain minimal contaminants, including larger EVs, we also outline multiple methods for characterization of isolated exosomes for size, morphology and protein markers.

ExRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study bydeconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of theexRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Biological System Responses of Dairy Cows to Aflatoxin B1 Exposure Revealed with Metabolomic Changes in Multiple Biofluids.

Research on mycotoxins now requires a systematic study of post-exposure organisms. In this study, the effects of aflatoxin B1 (AFB1) on biofluids biomarkers were examined with metabolomics and biochemical tests. The results showed that milk concentration of aflatoxin M1 changed with the addition or removal of AFB1. AFB1 significantly affected serum concentrations of superoxide dismutase (SOD) and malon dialdehyde (MDA), SOD/MDA, and the total antioxidant capacity. Significant differences of volatile fatty acids and NH3-N were detected in the rumen fluid. Eighteen rumen fluid metabolites, 11 plasma metabolites, and 9 milk metabolites were significantly affected by the AFB1. These metabolites are mainly involved in the pathway of amino acids metabolism. Our results suggest that not only is the study of macro-indicators (milk composition and production) important, but that more attention should be paid to micro-indicators (biomarkers) when assessing the risks posed by mycotoxins to dairy cows.

A Review of MicroRNA Biomarkers in Traumatic Brain Injury.

There is growing public concern surrounding traumatic brain injury (TBI). TBI can cause significant morbidity, and the long-term sequelae are poorly understood. TBI diagnosis and management rely on patient-reported symptoms and subjective clinical assessment. There are no biologic tools to detect mild TBI or to track brain recovery. Emerging evidence suggests that microRNAs (miRNAs) may provide information about the injured brain. These tiny epigenetic molecules are expressed throughout the body. However, they are particularly important in neurons, can cross the blood-brain barrier, and are securely transported from cell to cell, where they regulate gene expression. miRNA levels may identify patients with TBI and predict symptom duration. This review synthesizes miRNA findings from 14 human studies. We distill more than 291 miRNAs to 17 biomarker candidates that overlap across multiple studies and multiple biofluids. The goal of this review is to establish a collective understanding of miRNA biology in TBI and identify clinical priorities for future investigations of this promising biomarker.