Saliva diagnostics have become increasingly popular due to their non-invasive nature and patient-friendly collection process. Various collection methods are available, yet these are not always well standardized for either quantitative or qualitative analysis. In line, the objective of this study was to evaluate if measured levels of various biomarkers in the saliva of healthy individuals were affected by three distinct saliva collection methods: 1) unstimulated saliva, 2) chew stimulated saliva, and 3) oral rinse. Saliva samples from 30 healthy individuals were obtained by the three collection methods. Then, the levels of various salivary biomarkers such as proteins and ions were determined. It was found that levels of various biomarkers obtained from unstimulated saliva were comparable to those in chew stimulated saliva. The levels of potassium, sodium, and amylase activity differed significantly among the three collection methods. Levels of all biomarkers measured using the oral rinse method significantly differed from those obtained from unstimulated and chew-stimulated saliva. In conclusion, both unstimulated and chew-stimulated saliva provided comparable levels for a diverse group of biomarkers. However, the results obtained from the oral rinse method significantly differed from those of unstimulated and chew-stimulated saliva, due to the diluted nature of the saliva extract.
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Aim: To investigate the effects of exercise on salivary concentrations of inflammatory markers by analyzing a panel of 25 inflammatory markers in subjects who had participated in bicycle ergometer tests varying in workload and hydration status. Methods: Fifteen healthy young men (20-35 years) had performed 4 different exercise protocols of 1 hour duration in a randomly assigned cross-over design, preceded by a rest protocol. Individual workloads depended on participant's pre-assessed individual maximum workload (Wmax): rest (protocol 1), 70% Wmax in hydrated (protocol 2) and dehydrated (protocol 3) state, 50% Wmax (protocol 4) and intermittent 85%/55% Wmax in 2 min blocks (protocol 5). Saliva samples were collected before (T0) and immediately after exercise (T1), and at several time points after exercise (2 hours (T3), 3 hours (T4), 6 hours (T5) and 24 hours (T6)). Secretory Leukocyte Protease Inhibitor (SLPI), Matrix Metallopeptidase-9 (MMP-9) and lactoferrin was analyzed using a commercial ELISA kit, a panel of 22 cytokines and chemokines were analyzed using a commercial multiplex immunoassay. Data was analyzed using a multilevel mixed linear model, with multiple test correction. Results: Among a panel of 25 inflammatory markers, SLPI concentrations were significantly elevated immediately after exercise in all protocols compared to rest and higher concentrations reflected the intensity of exercise and hydration status. MMP-9 showed a significant increase in the 70% Wmax dehydrated, 50% Wmax and intermittent protocols. Conclusions: Salivary concentrations of SLPI and MMP-9 seem associated with exercise intensity and hydration status and may offer non-invasive biomarkers to study (local) inflammatory responses to different exercise intensities in human studies. sa
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Purpose: Exercise therapy with a focus on muscle strengthening has proven to be effective for the management of knee osteoarthritis (OA). Yet it is not known whether high-intensity resistance training (RT) is more effective in improving upper leg muscle strength and physical performance than low-intensity RT. Still, there is some controversy regarding the effectiveness of high-intensity RT and whether or not it is harmful, for instance by accelerating cartilage degeneration, osteophyte formation, or increasing synovitis. Any catabolic or anabolic response of musculoskeletal tissue to RT might first be visible on a biochemical level before changes in clinical symptoms are measurable. Serum biomarkers can objectively measure early biochemical changes and assess whether RT leads to a more anabolic or catabolic response. The aim of this study is to assess (i) whether high-intensity RT elicits a different response (e.g. catabolic) on systemic inflammation and musculoskeletal tissues in and surrounding the joint, including bone, cartilage, muscle, and synovial tissue compared to low-intensity RT; and (ii) whether there is an association between changes in serum levels of inflammatory and musculoskeletal tissue-derived biomarkers and improvements in clinical outcomes (performance-based tests and self-reported outcomes on pain and activity limitations).Methods: In a randomized controlled trial, 177 participants with knee OA conducted a high-intensity (70%-80% of the Repetition Maximum (1RM)) or low-intensity (40%-50% 1RM) RT program 3 times a week for 12 weeks. Measures of clinical outcomes and serum samples were collected at the start of RT (pre-intervention), after 3 months at the end of RT (post-intervention), and 6 months after RT (follow-up). As a reflection of systemic inflammation (CRP), synovitis (CRPM, C3M), bone turnover (OC, CTX-I), cartilage turnover (PRO-C2, C2M, huARGS), muscle turnover (PRO-C3, PRO-C6), and cell behaviour (col10neo) a total of eleven serum biomarkers were analysed. With the exception of CRP, which was determined with an immunoturbidimetric assay, ELISA assays were used to quantify serum levels of the other 10 serum biomarkers. The primary outcome measures are the changes in serum biomarker levels. Other outcome measures include upper leg muscle strength, performance-based tests, and self-reported outcomes on pain and activity limitations.Results: High-intensity RT resulted in greater improvements in muscle strength compared to low-intensity RT when measured by the estimated 1RM. No significant differences between groups were found for upper leg muscle strength (Nm/kg) when measured with an isokinetic dynamometer. Both groups showed similar improvements in pain and physical functioning. Although there is no difference between groups in clinical outcomes, except for the estimated 1RM, we expect that participants in the high-intensity RT group are more likely to have enhanced serum levels of catabolic biomarkers than participants in the low-intensity RT group. Since both the high-intensity RT group and low-intensity RT group improved over time, we expect that changes in serum biomarker levels are associated with overall improvements in clinical outcomes. Almost all participants had normal CRP values (<10 mg/L) at baseline. No significant differences between the intensity RT groups in CRP levels at baseline, at 3 months, and 6 months were found. In both groups, there was no evidence that RT influenced CRP serum levels.Conclusions: The work to date on CRP serum levels suggests that RT did not influence CRP levels. This result may be explained by the high percentage of participants with normal CRP levels (<10 mg/L). We are currently in the process of analyzing the remaining 10 neo-epitope biomarkers. We expect that our remaining 10 assays have the potential to measure changes in serum biomarker levels in response to RT. This will be the first study to investigate the effects of high-intensity versus low-intensity RT on musculoskeletal tissue turnover in individuals with knee OA. With this, we aim to determine whether high-intensity RT can improve upper leg muscle strength and physical performance without worsening systemic inflammation or causing adverse effects on musculoskeletal knee OA-related tissues.
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tIn this study we aimed to identify genes that are responsive to pertussis toxin (PTx) and might eventu-ally be used as biological markers in a testing strategy to detect residual PTx in vaccines. By microarrayanalysis we screened six human cell types (bronchial epithelial cell line BEAS-2B, fetal lung fibroblastcell line MRC-5, primary cardiac microvascular endothelial cells, primary pulmonary artery smooth mus-cle cells, hybrid cell line EA.Hy926 of umbilical vein endothelial cells and epithelial cell line A549 andimmature monocyte-derived dendritic cells) for differential gene expression induced by PTx. Imma-ture monocyte-derived dendritic cells (iMoDCs) were the only cells in which PTx induced significantdifferential expression of genes. Results were confirmed using different donors and further extendedby showing specificity for PTx in comparison to Escherichia coli lipopolysaccharide (LPS) and Bordetellapertussis lipo-oligosaccharide (LOS). Statistical analysis indicated 6 genes, namely IFNG, IL2, XCL1, CD69,CSF2 and CXCL10, as significantly upregulated by PTx which was also demonstrated at the protein levelfor genes encoding secreted proteins. IL-2 and IFN- gave the strongest response. The minimal PTx con-centrations that induced production of IL-2 and IFN- in iMoDCs were 12.5 and 25 IU/ml, respectively.High concentrations of LPS slightly induced IFN- but not IL-2, while LOS and detoxified pertussis toxindid not induce production of either cytokine. In conclusion, using microarray analysis we evaluated sixhuman cell lines/types for their responsiveness to PTx and found 6 PTx-responsive genes in iMoDCs ofwhich IL2 is the most promising candidate to be used as a biomarker for the detection of residual PTx.
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Objectives: Pulmonary hypertension is one of the leading causes of death in systemic sclerosis. Early detection and treatment of pulmonary hypertension in systemic sclerosis is crucial. Nailfold capillaroscopy microscopy, vascular autoantibodies AT1R and ETAR, and several candidate-biomarkers have the potential to serve as noninvasive tools to identify systemic sclerosis patients at risk for developing pulmonary hypertension. Here, we explore the classifying potential of nailfold capillaroscopy microscopy characteristics and serum levels of selected candidate-biomarkers in a sample of systemic sclerosis patients with and without different forms of pulmonary hypertension.Methods: A total of 81 consecutive systemic sclerosis patients were included, 40 with systemic sclerosis pulmonary hypertension and 41 with no pulmonary hypertension. In each group, quantitative and qualitative nailfold capillaroscopy microscopy characteristics, vascular autoantibodies AT1R and ETAR, and serum levels of 24 soluble serum factors were determined. For evaluation of the nailfold capillaroscopy microscopy characteristics, linear regression analysis accounting for age, sex, and diffusing capacity of the lungs for carbon monoxide percentage predicted was used. Autoantibodies and soluble serum factor levels were compared using two-sample t test with equal variances.Results: No statistically significant differences were observed in quantitative or qualitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibody ETAR and AT1R titer between systemic sclerosis-pulmonary hypertension and systemic sclerosis-no pulmonary hypertension. In contrast, several serum levels of soluble factors differed between groups: Endostatin, sVCAM, and VEGFD were increased, and CXCL4, sVEGFR2, and PDGF-AB/BB were decreased in systemic sclerosis-pulmonary hypertension. Random forest classification identified Endostatin and CXCL4 as the most predictive classifiers to distinguish systemic sclerosispulmonary hypertension from systemic sclerosis-no pulmonary hypertension.Conclusion: This study shows the potential for several soluble serum factors to distinguish systemic sclerosis-pulmonary hypertension from systemic sclerosis-no pulmonary hypertension. We found no classifying potential for qualitative or quantitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibodies.
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Background: Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of metabolic side-effects, e.g. insulin resistance, glucose intolerance and diabetes. To gain more insight into the mechanisms behind glucocorticoid induced insulin resistance, it is important to understand which genes play a role in the development of insulin resistance and which genes are affected by glucocorticoids. Medline abstracts contain many studies about insulin resistance and the molecular effects of glucocorticoids and thus are a good resource to study these effects. Results: We developed CoPubGene a method to automatically identify gene-disease associations in Medline abstracts. We used this method to create a literature network of genes related to insulin resistance and to evaluate the importance of the genes in this network for glucocorticoid induced metabolic side effects and anti-inflammatory processes. With this approach we found several genes that already are considered markers of GC induced IR, such as phosphoenolpyruvate carboxykinase (PCK) and glucose-6-phosphatase, catalytic subunit (G6PC). In addition, we found genes involved in steroid synthesis that have not yet been recognized as mediators of GC induced IR. Conclusions: With this approach we are able to construct a robust informative literature network of insulin resistance related genes that gave new insights to better understand the mechanisms behind GC induced IR. The method has been set up in a generic way so it can be applied to a wide variety of disease networks. © 2013 Fleuren et al.; licensee BioMed Central Ltd.
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ObjectivesTo investigate cartilage tissue turnover in response to a supervised 12-week exercise-related joint loading training program followed by a 6-month period of unsupervised training in patients with knee osteoarthritis (OA). To study the difference in cartilage tissue turnover between high- and low-resistance training.MethodPatients with knee OA were randomized into either high-intensity or low-intensity resistance supervised training (two sessions per week) for 3 months and unsupervised training for 6 months. Blood samples were collected before and after the supervised training period and after the follow-up period. Biomarkers huARGS, C2M, and PRO-C2, quantifying cartilage tissue turnover, were measured by ELISA. Changes in biomarker levels over time within and between groups were analyzed using linear mixed models with baseline values as covariates.ResultshuARGS and C2M levels increased after training and at follow-up in both low- and high-intensity exercise groups. No changes were found in PRO-C2. The huARGS level in the high-intensity resistance training group increased significantly compared to the low-intensity resistance training group after resistance training (p = 0.029) and at follow-up (p = 0.003).ConclusionCartilage tissue turnover and cartilage degradation appear to increase in response to a 3-month exercise-related joint loading training program and at 6-month follow-up, with no evident difference in type II collagen formation. Aggrecan remodeling increased more with high-intensity resistance training than with low-intensity exercise.These exploratory biomarker results, indicating more cartilage degeneration in the high-intensity group, in combination with no clinical outcome differences of the VIDEX study, may argue against high-intensity training.
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Introduction: Strenuous physical stress induces a range of physiological responses, the extent depending, among others, on the nature and severity of the exercise, a person’s training level and overall physical resilience. This principle can also be used in an experimental set-up by measuring time-dependent changes in biomarkers for physiological processes. In a previous report, we described the effects of workload delivered on a bicycle ergometer on intestinal functionality. As a follow-up, we here describe an analysis of the kinetics of various other biomarkers. Aim: To analyse the time-dependent changes of 34 markers for different metabolic and immunological processes, comparing four different exercise protocols and a rest protocol. Methods: After determining individual maximum workloads, 15 healthy male participants (20–35 years) started with a rest protocol and subsequently performed (in a cross-over design with 1-week wash-out) four exercise protocols of 1-h duration at different intensities: 70% Wmax in a hydrated and a mildly dehydrated state, 50% Wmax and intermittent 85/55% Wmax in blocks of 2 min. Perceived exertion was monitored using the Borg’ Rating of Perceived Exertion scale. Blood samples were collected both before and during exercise, and at various timepoints up to 24 h afterward. Data was analyzed using a multilevel mixed linear model with multiple test correction. Results: Kinetic changes of various biomarkers were exercise-intensity-dependent. Biomarkers included parameters indicative of metabolic activity (e.g., creatinine, bicarbonate), immunological and hematological functionality (e.g., leukocytes, hemoglobin) and intestinal physiology (citrulline, intestinal fatty acid-binding protein, and zonulin). In general, responses to high intensity exercise of 70% Wmax and intermittent exercise i.e., 55/85% Wmax were more pronounced compared to exercise at 50% Wmax. Conclusion: High (70 and 55/85% Wmax) and moderate (50% Wmax) intensity exercise in a bicycle ergometer test produce different time-dependent changes in a broad range of parameters indicative of metabolic activity, immunological and hematological functionality and intestinal physiology. These parameters may be considered biomarkers of homeostatic resilience. Mild dehydration intensifies these time-related changes. Moderate intensity exercise of 50% Wmax shows sufficient physiological and immunological responses and can be employed to test the health condition of less fit individuals.
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Background and aims: Observational data indicate that diets rich in fruits and vegetables have a positive effect on inflammatory status, improve metabolic resilience and may protect against the development of non-communicable diseases. Nevertheless, experimental evidence demonstrating a causal relationship between nutrient intake (especially whole foods) and changes in metabolic health is scarce. This study investigated the pleiotropic effects of sulforaphane from broccoli sprouts, compared to pea sprouts, on biomarkers of endothelial function, inflammation and metabolic stress in healthy participants subjected to a standardized caloric challenge.Methods: In this double-blind, crossover, randomized, placebo-controlled trial 12 healthy participants were administered 16 g broccoli sprouts, or pea sprouts (placebo) followed by the standardized high-caloric drink PhenFlex given to disturb healthy homeostasis. Levels of inflammatory biomarkers and metabolic parameters were measured in plasma before and 2 h after the caloric overload.Results: Administration of broccoli sprouts promoted an increase in levels of CCL-2 induced by caloric load (p = 0.017). Other biomarkers (sICAM-1, sVCAM-1, hs-CRP, and IL-10) individually showed insignificant tendencies toward increase with administration of sulforaphane. Combining all studied biomarkers into the systemic low-grade inflammation score further confirmed upregulation of the inflammatory activity (p = 0.087) after sulforaphane. No significant effects on biomarkers of metabolic stress were detected.Conclusion: This study has demonstrated that sulforaphane facilitated development of a mild pro-inflammatory state during the caloric challenge, which could be suggestive of the onset of the hormetic response induced by this phytonutrient. The use of integrative outcomes measures such as the systemic low-grade inflammation score can be viewed as a more robust approach to study the subtle and pleiotropic effects of phytonutrients.Clinical trial registration:www.clinicaltrials.gov, identifier NCT05146804.Keywords: biomarkers; diet; glucoraphanin; hormesis; inflammation; nutrients; phenotypic flexibility; sulforaphane.
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By applying Axiomatic Design, a Smart Medical Cast was developed to provide patients, who are suffering from forearm fractures, with a personalized healing process. The device monitors the overall healing status and three complications, which are: Muscle Atrophy, Compartment Syndrome, and Deep Vein Thrombosis. In the conceptual phase, desk research has been performed to find biomarkers that correlate with the monitored processes. Per biomarker, a measuring principle has been designed and these combined formed the design of the smart medical cast. Following the design phase, two tests were performed on healthy individuals to measure the robustness in a real application. The first test focused on correctly measuring the biomarkers and further specifying the sensor specifications. For the second test, a new prototype was used to determine correlations between the measured data and the monitored process and the impact of application during the casting process. The test results show that the measuring system can measure the biomarkers within the expected range, except for bone density. No significant impact on the casting process was measured. The Smart Medical Cast has only been evaluated in situations without a fracture, the next step will be to test the measurables in an environment with a fracture
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