Induction of tolerogenic lung CD4+ T cells by local treatment with a pSTAT-3 and pSTAT-5 inhibitor ameliorated experimental allergic asthma

Signal transducer and activator of transcription (STAT)-3 inhibitors play an important role in regulating immune responses. Galiellalactone (GL) is a fungal secondary metabolite known to interfere with the binding of phosphorylated signal transducer and activator of transcription (pSTAT)-3 as well of pSTAT-6 dimers to their target DNA in vitro. Intra nasal delivery of 50 μg GL into the lung of naive Balb/c mice induced FoxP3 expression locally and IL-10 production and IL-12p40 in RNA expression in the airways in vivo. In a murine model of allergic asthma, GL significantly suppressed the cardinal features of asthma, such as airway hyperresponsiveness, eosinophilia and mucus production, after sensitization and subsequent challenge with ovalbumin (OVA). These changes resulted in induction of IL-12p70 and IL-10 production by lung CD11c+ dendritic cells (DCs) accompanied by an increase of IL-3 receptor α chain and indoleamine-2,3-dioxygenase expression in these cells. Furthermore, GL inhibited IL-4 production in T-bet-deficient CD4+ T cells and down-regulated the suppressor of cytokine signaling-3 (SOCS-3), also in the absence of STAT-3 in T cells, in the lung in a murine model of asthma. In addition, we found reduced amounts of pSTAT-5 in the lung of GL-treated mice that correlated with decreased release of IL-2 by lung OVA-specific CD4+ T cells after treatment with GL in vitro also in the absence of T-bet. Thus, GL treatment in vivo and in vitro emerges as a novel therapeutic approach for allergic asthma by modulating lung DC phenotype and function resulting in a protective response via CD4+FoxP3+ regulatory T cells locall

In vitro evaluation of various bioabsorbable and nonresorbable barrier membranes for guided tissue regeneration

<p>Abstract</p> <p>Background</p> <p>Different types of bioabsorbable and nonresorbable membranes have been widely used for guided tissue regeneration (GTR) with its ultimate goal of regenerating lost periodontal structures. The purpose of the present study was to evaluate the biological effects of various bioabsorbable and nonresorbable membranes in cultures of primary human gingival fibroblasts (HGF), periodontal ligament fibroblasts (PDLF) and human osteoblast-like (HOB) cells <it>in vitro</it>.</p> <p>Methods</p> <p>Three commercially available collagen membranes [TutoDent^®(TD), Resodont^®(RD) and BioGide^®(BG)] as well as three nonresorbable polytetrafluoroethylene (PTFE) membranes [ACE (AC), Cytoplast^®(CT) and TefGen-FD^®(TG)] were tested. Cells plated on culture dishes (CD) served as positive controls. The effect of the barrier membranes on HGF, PDLF as well as HOB cells was assessed by the Alamar Blue fluorometric proliferation assay after 1, 2.5, 4, 24 and 48 h time periods. The structural and morphological properties of the membranes were evaluated by scanning electron microscopy (SEM).</p> <p>Results</p> <p>The results showed that of the six barriers tested, TD and RD demonstrated the highest rate of HGF proliferation at both earlier (1 h) and later (48 h) time periods (<it>P </it>< 0.001) compared to all other tested barriers and CD. Similarly, TD, RD and BG had significantly higher numbers of cells at all time periods when compared with the positive control in PDLF culture (<it>P </it>≤ 0.001). In HOB cell culture, the highest rate of cell proliferation was also calculated for TD at all time periods (<it>P </it>< 0.001). SEM observations demonstrated a microporous structure of all collagen membranes, with a compact top surface and a porous bottom surface, whereas the nonresorbable PTFE membranes demonstrated a homogenous structure with a symmetric dense skin layer.</p> <p>Conclusion</p> <p>Results from the present study suggested that GTR membrane materials, per se, may influence cell proliferation in the process of periodontal tissue/bone regeneration. Among the six membranes examined, the bioabsorbable membranes demonstrated to be more suitable to stimulate cellular proliferation compared to nonresorbable PTFE membranes.</p

Diagnostischer Test: 4-Felder Tafel

&lt;p&gt;Ein diagnostischer Test ein Diagnoseinstrument mit binärem Ausgang bzw Ergebnis: ja/nein, bzw., positiv/negativ. Der Eingangs-Zustand ist ebenfalls binär, z. B. gesund/krank, nicht infiziert/infiziert, nicht geeignet/geeignet usw.&nbsp;&lt;/p&gt;&lt;p&gt;Beide Faktoren, Zustand und Testergebnis, werden in einer 4-Felder-Tafel dargestellt. Als Outcome von Zustand und Test erhält man 4 Zellen (2x2): richtig-positiv und falsch-positiv sowie richtig-negativ und falsch-negativ.&nbsp;&lt;/p&gt;&lt;p&gt;Je nach Lesart – Zeilen oder Spalten – können aus der Tafel sowohl &lt;strong&gt;Sensitivität und Spezifität&nbsp;&lt;/strong&gt;(Pre Test-Wahrscheinlichkeiten)&lt;strong&gt;&nbsp;&lt;/strong&gt;als auch&lt;strong&gt; positiver und negativer Vorhersagewert&nbsp;&lt;/strong&gt;(Post Test-Wahrscheinlichkeiten)&lt;strong&gt;&nbsp;&lt;/strong&gt;abgelesen werden.&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Sensitivität: RP/(RP+FN)&lt;/li&gt;&lt;li&gt;Spezifität:&nbsp; &nbsp; RN/(RN+FP)&lt;/li&gt;&lt;li&gt;Positiver Vorhersagewert: RP/(RP+FP)&lt;/li&gt;&lt;li&gt;Negativer Vorhersagewert: RN/(RN+FN)&lt;/li&gt;&lt;/ul&gt

Procedure of a RCT study

Procedure of a RCT study for two arms or groups (intervention and control group), taking into account random assignment into the groups (randomization). The RCT study is the gold standard for the presentation / proof of efficacy or causality

Three-pillar model of evidence-based medicine (EBM)

The three-pillar model of evidence-based medicine (EBM) is based on integrating individual clinical expertise [professional knowledge, professional experience] with the best available external evidence from systematic research [studies/evidence/knowledge] and the wishes and needs of the patient [citizen/society/region]. The ideas were introduced by David Lawrence Sackett (https://de.wikipedia.org/wiki/David_Sackett, https://ebmlive.org/). EbM has served and continues to serve the better treatment and care of patients based on scientifically verifiable, evident decisions

Diagnostic test: 4-field board

&lt;p&gt;A diagnostic test is a diagnostic instrument with a binary output or result: yes/no or positive/negative. The input state (condition) is also binary, e.g. healthy/diseased, not infected/infected, not suitable/suitable, etc.&lt;/p&gt;&lt;p&gt;Both factors, condition and test result, are shown in a 4-field table. The outcome of the condition and test are 4 cells (2x2): true-positive and false-positive as well as true-negative and false-negative.&lt;/p&gt;&lt;p&gt;Depending on the reading - rows or columns - both &lt;strong&gt;sensitivity and specificity&lt;/strong&gt; (pre-test probabilities) as well as &lt;strong&gt;positive and negative predictive value&lt;/strong&gt; (post-test probabilities) can be read from the table.&lt;/p&gt;&lt;ul&gt;&lt;li&gt;sensitivity: TP/(TP+FN)&lt;/li&gt;&lt;li&gt;specificity: TN/(TN+FP)&lt;/li&gt;&lt;li&gt;positive predictive value: &nbsp;TP/(TP+FP)&lt;/li&gt;&lt;li&gt;negative predictive value: TN/(TN+FN)&lt;/li&gt;&lt;/ul&gt

EFFICIENT FARMING OPTIONS FOR GERMAN APPLE GROWERS BASED ON STOCHASTIC DOMINANCE ANALYSIS

Apple production is afflicted with various risks. As it is a permanent crop, apple producers are less flexible to react upon undesirable events. As a result, for a sustainable economic performance, the determination of efficient farming options, as a combination of the production system and risk management instruments (RMI), is crucial. Our investigation focuses on this choice problem utilizing stochastic dominance criteria, which apply to a wide range of risk preferences. Based on data for 134 apple producers operating in the two main production areas in Germany, we compare and determine efficient production options for the most common regional varieties. Furthermore, appropriate RMIs are identified using stochastic dominance criteria. In this context we investigate internal RMI (frost irrigation and hail nets) as well as external risk protection tools (insurance options). In Germany only a single insurance concept against hail is available, whereas insurance against late frosts is not at the apple growers’ disposal. As frost insurance exists in neighboring countries, we analyze the effect of the latter based on a hypothetic hail-frost insurance policy. Simulated net present values of a one hectare level serve as decision criterion, for which the associated cumulative probability distributions are evaluated according to first and second degree stochastic dominance criteria. In addition, we use SERF (Stochastic Efficiency with Respect to a Function) as it evaluates farming options for defined ranges of relative risk aversion and thus has a higher discriminative power. The results indicate that Red Prince is the most efficient option in the north and subsidized hail insurance with frost irrigation is superior to frost irrigation as single RMI. In the south Braeburn should be chosen under rational aspects, but the tested insurance solutions are not as efficient as the common production practice under hail nets

Verhältnis von Primärstudien und Sekundärstudien

&lt;p&gt;In den Lebenswissenschaften Medizin und Psychologie werden Studien in primäre Studien (individual studies) und sekundäre Studien aufgeteilt.&nbsp;&lt;/p&gt;&lt;p&gt;Zur Sekundärforschung gehören – in aufsteigender Hierarchie – systematische Reviews, Metaanalysen und Umbrella-Reviews. Systematische Reviews geben eine Zusammenfassung bereits existierender Studien, inklusive Bewertung der aktuellen Erkenntnislage. In Metaanalysen werden aus den Effekten der Einzel-Studien ein mittlerer Effekt berechnet.&nbsp;Ein Umbrella-Review fasst mehrere Metaanalysen zusammen.&lt;/p&gt

Procedure of a cohort study

Procedure of a cohort study for two arms/groups: One group is exposed, with a negative-impact risk factor (e.g., smoking, environmental exposure, etc.) or a preventive-impact factor (e.g., exercise, vaccination, diet, support, etc. ). The second group is non-exposed. Prospectively, the frequency with which participants in the two cohorts become ill or do not become ill (outcome) is determined. The risk of disease/non-disease is reported as an absolute frequency for both cohorts