The Forel-Ule scale revisited spectrally: preparation protocol, transmission measurements and chromaticity

Within the EC-funded project CITLOPS (Citizens' Observatory for Coast and Ocean Optical Monitoring), with its main goal to empower endusers, willing to employ community-based environmental monitoring, our aim is to digitalize the colours of the Forel-Ule scale to establish the colour of natural waters through smartphone imaging. The objective of this study was to reproduce the Forel-Ule scale following the original recipes, measure the transmission of the solutions and calculate the chromaticity coordinates of the scale as Wernand and Van der Woerd did in 2010, for the future development of a smartphone application. Some difficulties were encountered when producing the scale, so a protocol for its consistent reproduction was developed and is described in this study. Recalculated chromaticity coordinates are presented and compared to measurements conducted by former scientists. An error analysis of the spectral and colourimetric information shows negligible experimental errors

Genetically modified lactococcus lactis for delivery of human interleukin-10 to dendritic cells

Interleukin-10 (IL-10) plays an indispensable role in mucosal tolerance by programming dendritic cells (DCs) to induce suppressor Th-cells. We have tested the modulating effect of L. lactis secreting human IL-10 (L.lacti s IL-10) on DC function in vitro. Monocyte-derived DC incubated with L.lacti s IL-10 induced effector Th-cells that markedly suppressed the proliferation of allogenic Th-cells as compared to L. lactis. This suppressive effect was only seen when DC showed increased CD83 and CD86 expression. Furthermore, enhanced production of IL-10 was measured in both L.lacti s IL-10 -derived DC and Th-cells compared to L. lactis-derived DC and Th-cells. Neutralizing IL-10 during DC-Th-cell interaction and coculturing L.lacti s IL-10 -derived suppressor Th-cells with allogenic Th-cells in a transwell system prevented the induction of suppressor Th-cells. Only 130pg/mL of bacterial-derived IL-10 and 40 times more exogenously added recombinant human IL-10 were needed during DC priming for the generation of suppressor Th-cells. The spatially restricted delivery of IL-10 by food-grade bacteria is a promising strategy to induce suppressor Th-cells in vivo and to treat inflammatory diseases

Predicting the likelihood of successful medical treatment of early pregnancy loss:development and internal validation of a clinical prediction model

STUDY QUESTION: What are clinical predictors for successful medical treatment in case of early pregnancy loss (EPL)? SUMMARY ANSWER: Use of mifepristone, BMI, number of previous uterine aspirations and the presence of minor clinical symptoms (slight vaginal bleeding or some abdominal cramps) at treatment start are predictors for successful medical treatment in case of EPL. WHAT IS KNOWN ALREADY: Success rates of medical treatment for EPL vary strongly, between but also within different treatment regimens. Up until now, although some predictors have been identified, no clinical prediction model has been developed yet. STUDY DESIGN, SIZE, DURATION: Secondary analysis of a multicentre randomized controlled trial in 17 Dutch hospitals, executed between 28 June 2018 and 8 January 2020. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women with a non-viable pregnancy between 6 and 14 weeks of gestational age, who opted for medical treatment after a minimum of 1 week of unsuccessful expectant management. Potential predictors for successful medical treatment of EPL were chosen based on literature and expert opinions. We internally validated the prediction model using bootstrapping techniques. MAIN RESULTS AND THE ROLE OF CHANCE: 237 out of 344 women had a successful medical EPL treatment (68.9%). The model includes the following variables: use of mifepristone, BMI, number of previous uterine aspirations and the presence of minor clinical symptoms (slight vaginal bleeding or some abdominal cramps) at treatment start. The model shows a moderate capacity to discriminate between success and failure of treatment, with an AUC of 67.6% (95% CI = 64.9-70.3%). The model had a good fit comparing predicted to observed probabilities of success but might underestimate treatment success in women with a predicted probability of success of ∼70%. LIMITATIONS, REASONS FOR CAUTION: The vast majority (90.4%) of women were Caucasian, potentially leading to less optimal model performance in a non-Caucasian population. Limitations of our model are that we have not yet been able to externally validate its performance and clinical impact, and the moderate accuracy of the prediction model of 0.67. WIDER IMPLICATIONS OF THE FINDINGS: We developed a prediction model, aimed to improve and personalize counselling for medical treatment of EPL by providing a woman with her individual chance of complete evacuation. STUDY FUNDING/COMPETING INTEREST(S): The Triple M Trial, upon which this secondary analysis was performed, was funded by the Healthcare Insurers Innovation Foundation (project number 3080 B15-191). TRIAL REGISTRATION NUMBER: Clinicaltrials.gov: NCT03212352

Leukocyte Counts, Myeloperoxidase, and Pregnancy-Associated Plasma Protein A as Biomarkers for Cardiovascular Disease: Towards a Multi-Biomarker Approach

We evaluated leukocyte counts and levels of CRP, fibrinogen, MPO, and PAPP-A in patients with stable and unstable angina pectoris, acute myocardial infarction, and healthy controls. All biomarkers were analyzed again after 6 months. Leukocyte counts and concentrations of fibrinogen, CRP, MPO, and PAPP-A were significantly increased in patients with acute myocardial infarction. Leukocyte counts and concentrations of MPO were significantly increased in patients with unstable angina pectoris compared with controls. After 6 months, leukocyte counts and MPO concentrations were still increased in patients with acute myocardial infarction when compared to controls. Discriminant analysis showed that leukocyte counts, MPO, and PAPP-A concentrations classified study group designation for acute coronary events correctly in 83% of the cases. In conclusion, combined assessment of leukocyte counts, MPO, and PAPP-A was able to correctly classify acute coronary events, suggesting that this could be a promising panel for a multibiomarker approach to assess cardiovascular risk

Joint modeling of liver transplant candidates outperforms the model for end-stage liver disease: the effect of disease development over time on patient outcome

Liver function is measured regularly in liver transplantation (LT) candidates. Currently, these previous disease development data are not used for survival prediction. By constructing and validating joint models (JMs), we aimed to predict the outcome based on all available data, using both disease severity and its rate of change over time. Adult LT candidates listed in Eurotransplant between 2007 and 2018 (n = 16 283) and UNOS between 2016 and 2019 (n = 30 533) were included. Patients with acute liver failure, exception points, or priority status were excluded. Longitudinal MELD(-Na) data were modeled using spline-based mixed effects. Waiting list survival was modeled with Cox proportional hazards models. The JMs combined the longitudinal and survival analysis. JM 90-day mortality prediction performance was compared to MELD(-Na) in the validation cohorts. MELD(-Na) score and its rate of change over time significantly influenced patient survival. The JMs significantly outperformed the MELD(-Na) score at baseline and during follow-up. At baseline, MELD-JM AUC and MELD AUC were 0.94 (0.92-0.95) and 0.87 (0.85-0.89), respectively. MELDNa-JM AUC was 0.91 (0.89-0.93) and MELD-Na AUC was 0.84 (0.81-0.87). The JMs were significantly (p < .001) more accurate than MELD(-Na). After 90 days, we ranked patients for LT based on their MELD-Na and MELDNa-JM survival rates, showing that MELDNa-JM-prioritized patients had three times higher waiting list mortality.Transplant surger

Development and validation of a dynamic survival prediction model for patients with acute-on-chronic liver failure

Background & aims: Acute-on-chronic liver failure (ACLF) is usually associated with a precipitating event and results in the failure of other organ systems and high short-term mortality. Current prediction models fail to adequately estimate prognosis and need for liver transplantation (LT) in ACLF. This study develops and validates a dynamic prediction model for patients with ACLF that uses both longitudinal and survival data.Methods: Adult patients on the UNOS waitlist for LT between 11.01.2016-31.12.2019 were included. Repeated model for end-stage liver disease-sodium (MELD-Na) measurements were jointly modelled with Cox survival analysis to develop the ACLF joint model (ACLF-JM). Model validation was carried out using separate testing data with area under curve (AUC) and prediction errors. An online ACLF-JM tool was created for clinical application.Results: In total, 30,533 patients were included. ACLF grade 1 to 3 was present in 16.4%, 10.4% and 6.2% of patients, respectively. The ACLF-JM predicted survival significantly (p <0.001) better than the MELD-Na score, both at baseline and during follow-up. For 28- and 90-day predictions, ACLF-JM AUCs ranged between 0.840-0.871 and 0.833-875, respectively. Compared to MELD-Na, AUCs and prediction errors were improved by 23.1%-62.0% and 5%-37.6% respectively. Also, the ACLF-JM could have prioritized patients with relatively low MELD-Na scores but with a 4-fold higher rate of waiting list mortality.Conclusions: The ACLF-JM dynamically predicts outcome based on current and past disease severity. Prediction performance is excellent over time, even in patients with ACLF-3. Therefore, the ACLF-JM could be used as a clinical tool in the evaluation of prognosis and treatment in patients with ACLF.Lay summary: Acute-on-chronic liver failure (ACLF) progresses rapidly and often leads to death. Liver transplantation is used as a treatment and the sickest patients are treated first. In this study, we develop a model that predicts survival in ACLF and we show that the newly developed model performs better than the currently used model for ranking patients on the liver transplant waiting list. (C) 2021 The Author(s). Published by Elsevier B.V.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Supernatant from Bifidobacterium Differentially Modulates Transduction Signaling Pathways for Biological Functions of Human Dendritic Cells

International audienceBACKGROUND:Probiotic bacteria have been shown to modulate immune responses and could have therapeutic effects in allergic and inflammatory disorders. However, the signaling pathways engaged by probiotics are poorly understood. We have previously reported that a fermentation product from Bifidobacterium breve C50 (BbC50sn) could induce maturation, high IL-10 production and prolonged survival of DCs via a TLR2 pathway. We therefore studied the roles of mitogen-activated protein kinases (MAPK), glycogen synthase kinase-3 (GSK3) and phosphatidylinositol 3-kinase (PI3K) pathways on biological functions of human monocyte-derived DCs treated with BbC50sn.METHODOLOGY/PRINCIPAL FINDINGS:DCs were differentiated from human monocytes with IL-4 and GM-CSF for 5 days and cultured with BbC50sn, lipopolysaccharide (LPS) or Zymosan, with or without specific inhibitors of p38MAPK (SB203580), ERK (PD98059), PI3K (LY294002) and GSK3 (SB216763). We found that 1) the PI3K pathway was positively involved in the prolonged DC survival induced by BbC50sn, LPS and Zymosan in contrast to p38MAPK and GSK3 which negatively regulated DC survival; 2) p38MAPK and PI3K were positively involved in DC maturation, in contrast to ERK and GSK3 which negatively regulated DC maturation; 3) ERK and PI3K were positively involved in DC-IL-10 production, in contrast to GSK3 that was positively involved in DC-IL-12 production whereas p38MAPK was positively involved in both; 4) BbC50sn induced a PI3K/Akt phosphorylation similar to Zymosan and a p38MAPK phosphorylation similar to LPS.CONCLUSION/SIGNIFICANCE:We report for the first time that a fermentation product of a bifidobacteria can differentially activate MAPK, GSK3 and PI3K in order to modulate DC biological functions. These results give new insights on the fine-tuned balance between the maintenance of normal mucosal homeostasis to commensal and probiotic bacteria and the specific inflammatory immune responses to pathogen bacteria