Biology subjects

Schulze, K.

Publications and source records attributed to Schulze, K..

7 recordsLinked to original sources

bioRxiv2025

A potential role of altered SIgA-targeting of gut microbiota in long-term dysbiosis in pediatric solid organ transplant recipients

BackgroundComposition of gut microbiota (GM) is altered in solid organ transplantation (SOT) patients, where the degree of dysbiosis is associated with long-term survival. Factors governing dysbiosis are poorly understood with immunosuppression therapy believed to be involved in altering GM composition in those patients, either directly or via the immune system. At the interface stands secretory (S)IgA, however, little is known on its role governing dysbiosis in the context of SOT. In this study, we performed quantitative metagenomic analyses of GM accompanied by SIgA sequencing in 48 pediatric SOT recipients (age = 10.6 {+/-} 4.7 years) receiving either a heart (HTR, n=10), a kidney (KTR, n=11) or a liver (LTR, n=27) and compared results to healthy controls (HC, n=16). ResultsWe confirmed compositional and functional dysbiosis in SOT patients that broadly clustered into two groups, where cluster 1 (n=23) comprised most LTR patients and was closer to HC compared with cluster 2 (n=24) that exhibited stronger dysbiosis and included most HTR and KTR patients. The degree of dysbiosis was associated with Tacrolimus (TAC) levels. Overall, patients exhibited higher SIgA levels than HC, along with an increased percentage of bacteria targeted and altered target spectra. Furthermore, altered SIgA responses were associated with the degree of dysbiosis and were especially increased in cluster 2, in particular in HTR patients. A mechanistic model connecting immunosuppression, GM composition and SIgA targeting is proposed. ConclusionOur study suggests that altered SIgA responses play an important role for GM alterations observed in SOT patients. It opens new therapeutic angles to combat GM dysbiosis and associated long-erm complications.

microbiology↗

bioRxiv2024

Accessing the specific capacity of TIL-derived CD8 T-cells to suppress tumor recurrence in resectable HBV-HCC patients

BackgroundHepatocellular carcinoma represents a significant global health challenge, affecting over a million patients annually, arising mainly from chronic liver diseases, with a majority being related to viral infections. However, despite the groundbreaking clinical results of immune checkpoint blockades and adoptive cell therapies, we still face non-responders accompanied by high rebound rates after resection. Considering that the main concern is to overcome a highly specialized immunosuppressive tumor microenvironment of the individual patient, the characterization of the particular tumor microenvironment and the source of the immune cells used in ACT is of immense importance. Approved ACT therapies mainly use modified peripheral blood cells from individuals. At the same time, tumor-infiltrating lymphocytes are underrepresented even if they have garnered interest due to their potential to target tumor-specific antigens more effectively. MethodsIn this study, we employed allogenic and autologous immune cell sources for expansion and stimulation, resulting in adoptive T-cell transfer experiments determining the effector cell differentiation and the related anti-tumor effects by the possible implementation of re-stimulation. ResultsWe determined a high success rate in expanding and stimulating tumor-infiltrating lymphocytes with consistent CD8 T-cell fractions from HCC patients. To showcase the effectiveness of stimulated T-cells from different sources, we generated cell lines derived from the margin and center of an HBV-induced HCC with a highly immune-suppressive TME. We found effective immune responses supported by cell death induction, ferroptosis, proptosis and apoptosis triggered by all sources of T-cells depending on the area of derived tumor cells. ConclusionEffector T-cell fractions derived from tumor-infiltrating lymphocytes present a viable source for cell-based immune therapy combined with immune checkpoint inhibitors in HCC patients, especially after resection, to suppress rebound strategies of the parental tumor on an individual level.

immunology↗

bioRxiv2024

Patient-derived HCC cells recapitulating the transcriptomic landscape of primary HCV-related liver cancer

BackgroundThe hepatocellular carcinoma is one of the leading causes of cancer-related mortality and is characterized by high heterogeneity and subsequently adaptation by developing resistance to current treatments. In this scenario the application of individualized models is crucial to understand the potential of approved therapies. Recently, we established a series of individual cell lines derived from patients who developed HCC on different entities, serving as a platform for individual approaches. In this study, we classified the LC4 cells derived from the center region of a HCC with underlying HIV-HCV co-infection, by using deep analysis on the pathway regulation level. MethodsWe employed DEG analysis, followed by pathway analysis to characterize the preservation level of the LC4 cells and the level of adoption. Next, we classify the model, by employing healthy donor samples, commonly used HCC cell lines and global RNAseq data sets. ResultsWe showed that the LC4 cells reflect significant characteristics of the parental region, including the replication of the immuno-suppressive and the proliferative milieu. The LC4 cells exhibit a metabolic reprogramming characterized by the downregulation of drug-metabolizing CYP enzymes compared to healthy individuals, indicating a transition to alternate metabolic pathways. Moreover, we identified common Biomarkers in the parental tissue, global datasets and the LC4 cells. ConclusionWe showed that the LC4 cell line is applicable as an individual model for pre-clinical testing of treatment regimens in HCC driven research.

cancer biology↗

bioRxiv2024

Ex-vivo expansion of patient-derived PBMCs preferentially results in effector memory T-cell proliferation with restored autologous efficiency in HBV-HCC

BackgroundT-cell-based therapies achieved milestones in targeting solid tumors, such as hepatocellular carcinoma, by leveraging the cytotoxic potential of effector memory T-cells. However, a key challenge lies in the ex-vivo expansion of functional memory T-cells while simultaneously preventing over-differentiation into senescent TEMRA cells. MethodsPBMC derived from 10 HCC patients and two healthy donors were used for expansion in small bioreactors equipped with a permeable membrane for 2 weeks. During expansion, surface marker composition, cytokine and chemokine production were observed. Enriched T-cell subsets from three patients with chronic HBV infection were analysed in detail. We extracted the enriched complement of one chronically infected patient to elucidate the therapeutic potential. ResultsWe successfully expanded the effector T-cell subsets for all investigated samples and consistently enriched the cell amount over time. Subsequently, we showed that the expanded patient-derived T-cells showed functionality against autologous liver cancer-derived cells by inducing receptor and protein-mediated cell death. ConclusionWe showed the consistent ex-vivo expansion of T-cell subsets of initial patient-derived PBMCs. The enriched subsets exhibit cytotoxic functionality and shift to cytolytic TEMRA cells in an immune evasion setting in the context of chronic HBV-infected patient-derived liver cancer cells.

immunology↗

bioRxiv2022

Chimeric U-Net - Modifying the standard U-Net towards Explainability

Healthcare guided by semantic segmentation has the potential to improve our quality of life through early and accurate disease detection. Convolutional Neural Networks, especially the U-Net-based architectures, are currently the state-of-the-art learningbased segmentation methods and have given unprecedented performances. However, their decision-making processes are still an active field of research. In order to reliably utilize such methods in healthcare, explainability of how the segmentation was performed is mandated. To date, explainability is studied and applied heavily in classification tasks. In this work, we propose the Chimeric U-Net, a U-Net architecture with an invertible decoder unit, that inherently brings explainability into semantic segmentation tasks. We find that having the restriction of an invertible decoder does not hinder the performance of the segmentation task. However, the invertible decoder helps to disentangle the class information in the latent space embedding and to construct meaningful saliency maps. Furthermore, we found that with a simple k-Nearest-Neighbours classifier, we could predict the Intersection over Union scores of unseen data, demonstrating that the latent space, constructed by the Chimeric U-Net, encodes an interpretable representation of the segmentation quality. Explainability is an emerging field, and in this work, we propose an alternative approach, that is, rather than building tools for explaining a generic architecture, we propose constraints on the architecture which induce explainability. With this approach, we could peer into the architecture to reveal its class correlations and local contextual dependencies, taking an insightful step towards trustworthy and reliable A.I. Code to build and utilize the Chimeric U-Net is made available under: https://github.com/kenrickschulze/Chimeric-UNet---Half-invertible-UNet-in-Pytorch

bioinformatics↗

bioRxiv2019

Mice tune out not in: Violation of prediction drives auditory saliency

Successful navigation in complex acoustic scenes requires focusing on relevant sounds while ignoring irrelevant distractors. It has been argued that the ability to track stimulus statistics and generate predictions supports the choice what to attend and what to ignore. However, the role of these predictions about future auditory events in drafting decisions remains elusive. While most psychophysical studies in humans indicate that expected stimuli serve as implicit cues attracting attention, most work studying physiological auditory processing in animals highlights the detection of unexpected, surprising stimuli. Here, we tested whether in the mouse, target probability is used as an implicit cue attracting attention or whether detection is biased towards low-probability deviants using an auditory detection task. We implemented a probabilistic choice model to investigate whether a possible dependence on stimulus statistics arises from short term serial correlations or from integration over longer periods. Our results demonstrate that target detectability in mice decreases with increasing probability, contrary to humans. We suggest that mice indeed track probability over a time scale of at least several minutes but do not use this information in the same way as humans do: instead of maximizing reward by focusing on high-probability targets, the saliency of a target is determined by surprise.

animal behavior and cognition↗

bioRxiv2019

Early migration of precursor neurons initiates cellular and functional regeneration after spinal cord injury in zebrafish.

Zebrafish have a remarkable capacity to regenerate following spinal cord (SC) injury but the responsible cellular events are not well understood. We used in vivo imaging and genetics to pin-point specific cellular processes controlling SC regeneration in zebrafish. We identified two temporally and mechanistically distinct phases of cellular regeneration in the SC. The initial phase relies on migration of precursor neurons to the injury, enabling rapid functional recovery, and activation of quiescent neural progenitor cells (NPCs). A second phase of regenerative neurogenesis compensates for both the lost tissue and cells depleted due to precursor neuron migration. We propose a critical role of precursor neurons recruitment in initiating neuronal circuit recovery and buying sufficient time for regenerative neurogenesis to take place. Taken together, our data suggests an unanticipated role of precursor cell recruitment in driving neural repair and functional recovery during the regenerative response. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/539940v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@12c5be9org.highwire.dtl.DTLVardef@1461e99org.highwire.dtl.DTLVardef@82d28aorg.highwire.dtl.DTLVardef@cc6870_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗