Analytisches Laboratorium

Abstract Actively avoiding threatening stimuli or situations is an adaptive defensive strategy that minimizes the risk of potential harm. Despite the prominent role avoidance plays in our daily lives, the mechanisms that reinforce avoidance behavior remain incompletely understood. Accumulating evidence implicates the mesolimbic dopamine reward system in the acquisition of avoidance, suggesting that the omission of an aversive event may acquire rewarding properties and function as a positive reinforcer of avoidance behavior. In a series of six experiments (N = 246 male Wistar rats), we examined whether safety signals that coincide with successful avoidance responses in a two-way active avoidance (2WAA) task facilitate avoidance acquisition and acquire reward-like properties, by assessing whether they elicit approach behavior and support the acquisition of a novel instrumental response. Although the presentation of a safety signal accelerated avoidance learning in some experiments, the effect was not consistent. Furthermore, the safety signal neither elicited approach behavior nor supported the acquisition of a novel instrumental response. Together, these findings question whether safety signals in avoidance learning acquire rewarding properties detectable through behavioral measures.

Jungian psychotherapy (JP) is an established treatment modality in modern healthcare systems, yet empirical validation remains a key requirement for its continued recognition and insurance coverage. This study aimed to assess the effectiveness of JP by evaluating pre- and post-treatment changes in psychological symptoms, personality structure, and quality of life among 104 participants undergoing supervised therapy at a German training institute. Using a pre-post design, participants completed standardized psychometric assessments, including the International Classification of Diseases – 10th Revision (ICD-10) Symptom Rating (ISR), the Fragebogen zur Lebenszufriedenheit (FLZ; Life Satisfaction Questionnaire), and the Operationalized Psychodynamic Diagnosis - Structure Questionnaire (OPD-SQ), before and after therapy. Results from paired samples t-tests and Wilcoxon signed-rank tests indicated significant improvements across multiple domains. Participants experienced notable reductions in symptom burden, particularly in depression, anxiety, and obsessive-compulsive symptoms, with effect sizes ranging from moderate to large (d=0.555 to d=1.174). Improvements were also observed in self-perception, interpersonal contact, and relational experiences. However, eating disorder symptoms did not show significant improvement (p=.275), likely due to the need for specialized interventions. Future research should employ randomized controlled trials (RCTs) and long-term follow-ups to establish the durability of treatment effects.

Abstract Background Histopathology remains a cornerstone of diagnosis and prognostication in pediatric brain tumors. However, in-depth characterization of the tumor microenvironmental (TME) elucidated by spatial proteomics offers therapy-relevant insight. We present a digital pathology AI framework offering spatial proteomic insight from hematoxylin and eosin (H&E) stained pathology slides. Method We analyzed over 800 independent tissue cores originating from 79 post-mortem patients representing various pediatric brain tumor indications, with a focus on diffuse midline glioma (DMG). In a systematic benchmark of six state-of-the-art digital pathology feature extractors, we predict spatial profiles for 22 protein markers from virtual H&E images. These markers characterize the tumor microenvironment for key brain cell type (e.g. MBP) immune (e.g. CD3, CD8, CD68, CD163, PD1), stemness (e.g. Nestin), and treatment-relevant (e.g. B7H3) expression profiles. We combined the extracted features with a light gradient-boosted machine classifier, trained exclusively on one cohort (403 specimens) enabling predictions on an independently processed, previously unseen test data cohort of 405 tissue specimens. Results We established a novel AI platform for the detection of 22 antigens in H&E-stained tissue. We observed a performance advantage for feature extractors building on vision transformers with the top pipeline achieving competitive performance for most markers (test-set ROCAUC 0.57-0.90). The detection of H3K27M+ DMG cells (ROCAUCH3K27M=0.88+\-0.01) and NESTIN+ neural stem/progenitor cells (ROCAUCNESTIN=0.86+/- 0.01) and MBP (ROCAUCMBP=0.90+/- 0.01) was highly robust. Similarly, immune suppressive signals such as PD1 and CD163 showed moderate performance (ROCAUC3PD1=0.71+/-0.01, ROCAUCCD163=0.75+/-0.01). Conclusions Our AI platform demonstrates the feasibility of extracting in-depth tissue characteristics and gaining molecular insight into the TME from H&E images through digital pathology in the absence of staining, as well as enabling the spatial prediction of key molecular markers (e.g. H3K27M) for DMG identification.

Abstract Background Early clinical promises have led to the recent FDA approval of GD2 chimeric antigen receptor (CAR) T-cell therapy for DMG. However, the response is transitory (extended survival of 2 years) indicating the need to further explore DMG immune microenvironment to better understand tumor microenvironment (TME). Method Whole brains (49 DMGs, 20 non-DMG, 10 non-malignant) from 79 pediatric patients were used to establish a tissue microarray (918 cores) representing primary, metastatic, and adjacent healthy sites. We multiplexed probing for 33 immune and cell type markers (CellDIVE MxIF) followed by signal quantification (QuPath). Bulk RNA sequencing was (n = 62 patients) performed to define additional immune signatures. Immune signature was correlated to patient clinical management. Findings were validated using patient plasma and DMG PDX models. Results Multiplex immunofluorescent probing for 33 antigens revealed enrichment of M1-activated microglia in primary versus adjacent healthy tissue. PD1 positive cells were significantly (p < 0.01) higher in primary and metastatic sites compared to adjacent controls. mRNA profiling validated upregulation of immune markers in primary versus metastatic DMG sites further indicating two distinct groups with top 35 significant (p < 0.05) genes revealing synaptic signature in metastatic cohort. We stratified the patient cohort by treatment [immunotherapy (n = 9), imipridone, a known immune activator drug (n = 5), immuno/imipridone combination (n = 7) and immuno/imipridone naïve (n = 17)]. Imipridone cohort was void of progenitor (Nestin+, Vimentin+, and SOX2+) cells as well as increased macrophages/microglia infiltration. Increased T and B cells was validated in patient plasma following imipridone therapy. Combination therapy cohort exhibited increased myeloid (Iba1, CD68, CD163) and lymphoid (CD3, CD8) cells. Enhanced immune engagement was validated in DMG PDX models. Conclusion DMG tumors maintain a cold immune microenvironment, which is nevertheless dynamic and responsive to therapy. Our observation that DMG TME responds to imipridone, and immunotherapy indicated the need to explore combination therapies that will enhance clinical response in this patient population.

Experimental studies on the influence of structural systems of railway bridges on their dynamic behavior are not widely available in the literature. This paper presents unique results of a vast full-scale measurement campaign of dynamic responses of six structurally different single-span railway bridges excited by multiple passes of a rail vehicle at various predetermined driving speeds not exceeding 100 km/h. Structural variants of the examined bridges included twin steel I-shaped beam or truss girders, steel or reinforced concrete or no deck slab, and nonballasted or ballasted single-track systems. The results of driving and free-vibration tests were analyzed, and a database of the most critical parameters representing the dynamic behavior of the bridges was provided. The collected data were compared in terms of the driving speed of the rail vehicle, the structural system and the span length of the tested bridges. The basic dynamic characteristics of the bridges were related to the threshold values given in the Eurocode EN 1991-2 standard. It was found that the tested bridges without a reinforced concrete deck experienced 1.3–3.7 times greater total deflections and 1.8–5.7 greater dynamic deflections compared with those with a reinforced concrete deck. Moreover, the studied bridges with a ballast layer were associated with a damping ratio of 2.00%–3.97%, whereas in the case of beam bridges without ballast, this ratio was below 2.0%. It was shown that the differences in the dynamic features of all tested bridges resulted more from the different structural typologies than from the length of their spans. The presented case study provides an experimental dataset that can constitute the basis for further profound studies and can also help verify the theoretical model and predict the dynamic behavior of railway bridges with similar structural systems.

Injury prevention in sports remains a perpetual challenge, frequently hindered by linear approaches that fail to account for the complexity of real-world scenarios. We propose a paradigm shift in this perspective, framing injury prevention as a 'wicked problem' characterised by evolving, context-dependent factors and competing priorities. We suggest that while eliminating injuries entirely may not be feasible, their impact can be effectively reduced through tailored, adaptable solutions. We illustrate the practical application of this framework through a case study of Cirque du Soleil. By adopting a revised 'Sense-Think-Act' paradigm, interventions were collaboratively developed with performers, medical personnel and organisational leaders. This resulted in a 15% reduction in injuries and substantial decreases in missed performances and overuse injuries over 4 years. The success of this approach can be attributed to context-sensitive strategies that effectively balance injury risk mitigation with performance objectives. Our proposed view challenges traditional definitions of success in injury prevention, that is, developing 'optimal solutions' instead of 'ultimate solutions'. By rethinking injury prevention as a wicked problem, we nudge sports professionals to adopt flexible, sustainable practices that address the dynamic realities of their environments. Such a shift enhances injury prevention outcomes and aligns these efforts with the broader priorities of athletic communities.

Background. Despite its clinical promise in non-solid tumor, immunotherapy is yet to show significant clinical efficacy for brain tumors including pediatric diffuse midline glioma (DMG). This indicated the need to fully explore DMG immune tumor microenvironment (TME). Method. Whole brains (49 DMGs, 20 non-DMG, 10 non-malignant) from 79 pediatric patients were used to establish a tissue microarray (918 cores) representing primary, metastatic, and adjacent healthy sites. CellDIVE MxIF multiplex assay was used to probe for 33 immune and cell type markers. RNA sequencing (n=62 patients) defined additional immune signatures. Findings were validated using patient plasma and DMG PDX models. Our annotated single-cell atlas was used to train a spatial AI model to predict antigens from H&E staining. Findings. We found enrichment of M1-activated microglia in primary versus adjacent healthy tissue. PD1 positive cells were significantly (p<0.01) higher in tumor compared to adjacent controls. This was validated by mRNA profiling, further indicating two distinct groups with top 35 significant (p<0.05) genes revealing synaptic signature in the metastatic cohort. We stratified the patient cohort by treatment. Imipridone cohort (n=5) showed decreased progenitor (Nestin+, Vimentin+, and SOX2+) and increased macrophages/microglia infiltration. Increased T and B cells was validated in patient plasma following imipridone therapy. Combination therapy of imipridone and immunotherapy (n=7) resulted in increased myeloid (Iba1, CD68, CD163) and lymphoid (CD3, CD8) cells. Enhanced immune engagement was validated in DMG PDX models. Machine learning resulted in a spatial AI model capable of predicting 22 antigens using H&E slides. Interpretations. DMG tumors maintain a cold immune microenvironment, which is nevertheless dynamic and responsive to therapy, indicating the need to explore combination therapies. AI-assisted antigen detection is suitable for rapid interpretation of clinical biospecimens.

This bioequivalence research aims to evaluate the relative bioavailability and pharmacokinetic characteristics of ethinyl estradiol and drospirenone in the test preparation in comparison to the reference preparation during fasting conditions. A liquid chromatography method with tandem mass spectrometry was used to determine the concentrations of drospirenone and ethinyl estradiol in plasma. The pharmacokinetic parameters that were analyzed were the maximum plasma concentration (Cmax), time to achieve Cmax (tmax), elimination half life, and area under the concentration time curve of plasma (AUC0-t, AUC0-∞ for ethinyl estradiol, and AUC0-72h for drospirenone). Both the AUC and Cmax parameters were determined to be between 80.00% and 125.00% (90% confidence intervals), which is the acceptable range. Based on the study findings, it was concluded that the test formulation, which includes 3 mg of drospirenone and 0.03 mg of ethinyl estradiol, demonstrated bioequivalence when compared to the reference formulation.