Biology subjects

Merhof, D.

Publications and source records attributed to Merhof, D..

6 recordsLinked to original sources

bioRxiv2025

Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive Learning

Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into resolving gene expression and clinical diagnosis of cancer. Due to the high cost of data acquisition, large-scale spatial transcriptomics data remain challenging to obtain. In this study, we develop a contrastive learning-based deep learning method to predict spatially resolved gene expression from whole-slide images. Evaluation across six different disease datasets demonstrates that, compared to existing studies, our method improves Pearson Correlation Coefficient (PCC) in the prediction of highly expressed genes, highly variable genes, and marker genes by 6.27%, 6.11%, and 11.26% respectively. Further analysis indicates that our method preserves gene-gene correlations and applies to datasets with limited samples. Additionally, our method exhibits potential in cancer tissue localization based on biomarker expression.

pathology↗

bioRxiv2023

Towards substitution of invasive telemetry: An integrated home cage concept for unobstrusive monitoring of objective physiological parameters in rodents

This study presents a novel concept for a smart cage designed to monitor the physiological parameters of mice and rats in animal-based experiments. The system focuses on monitoring key clinical parameters, including heart rate, respiratory rate, body temperature, activity, and circadian rhythm. To create the smart home cage system, an in-depth analysis of the requirements was performed, including camera positioning, imaging system types, resolution, frame rates, external illumination, video acquisition, data storage, and synchronization. Two different camera perspectives were considered, and specific camera models, including two near-infrared and two thermal cameras, were selected to meet the requirements. During the first testing phase, the system demonstrated the potential of extracting vital parameters such as respiratory and heart rate. This technology has the potential to reduce the need for implantable sensors while providing reliable and accurate physiological data, leading to refinement and improvement in laboratory animal care.

bioengineering↗

bioRxiv2022

Neonatal Peyer's patch cDC activation as a pacemaker of postnatal immune maturation

Marked differences exist between the mucosal immune system of the neonate and adult host. The pronounced influence of the enteric microbiota in adults suggests a causal relationship between postnatal colonization and immune maturation. However, using metagenomic, metaproteomic, and functional immunological analyses we demonstrate an early presence of bacteria and immunogenic microbial antigens preceding immune maturation in the small intestine, the primary inductive site of intestinal immunity. Instead, transcriptomic, flow cytometric and histological analysis indicated neonatal Peyers patch (PP) mononuclear phagocytes (MNP) as rate limiting factor of postnatal immune maturation. Despite the early presence of MNPs, conventional dendritic cells (cDC) of type 1, 2a and 2b exhibited significant age-dependent differences in tissue distribution and cellular composition. Single cell transcriptional profiling and functional assays revealed decreased antimicrobial and antigen processing/presentation capacity, an overall retarded cell maturation and reduced antigen uptake. In cDC2a this resulted in a reduced proportion of CCR7+ migratory cells and a consequent defect in CD4 T cell priming. Interestingly, transcriptional profiling of neonatal DC subsets identified reduced expression of type I interferon (IFN)-stimulated genes (ISG). Type I IFN induction by oral administration of the TLR7 agonist R848 accelerated MNP maturation and enhanced cognate antigen CD4 T cell priming. However, humoral responses to oral vaccination in the presence of R848 were significantly reduced. Together, our results identify PP MNP maturation as pacemaker of postnatal mucosal immune priming, indicate the biological role of delayed maturation and demonstrate that targeted interventional strategies allow manipulation of mucosal responses in early life.

immunology↗

bioRxiv2020

Chemical signatures of human odour generate a unique neural code in the brain of Aedes aegypti mosquitoes

A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient vector of dengue, yellow fever, Zika, and chikungunya viruses. Host-seeking females strongly prefer human odour over the odour of non-human animals, but exactly how they distinguish the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components, making discrimination an interesting sensory coding challenge. Here we show that human and animal odour blends evoke activity in unique combinations of olfactory glomeruli within the Aedes aegypti antennal lobe. Human blends consistently activate a universal glomerulus, which is equally responsive to diverse animal and nectar-related blends, and a more selective human-sensitive glomerulus. This dual signal robustly distinguishes humans from animals across concentrations, individual humans, and diverse animal species. Remarkably, the human-sensitive glomerulus is narrowly tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in (though not specific to) human odour and which likely originate from unique human skin lipids. We propose a model of host-odour coding wherein normalization of activity in the human-sensitive glomerulus by that in the broadly-tuned universal glomerulus generates a robust discriminatory signal of the relative concentration of long-chain aldehydes in a host odour blend. Our work demonstrates how animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals novel targets for the design of next-generation mosquito-control strategies.

neuroscience↗

bioRxiv2020

ATP activation of peritubular cells drives testicular sperm transport

Spermatogenesis, the complex developmental process of male germ cell proliferation, differentiation, and maturation, is the basis of male fertility and reproductive fitness. In the seminiferous tubules of the testes, spermatozoa are constantly generated from spermatogonial stem cells through a stereotyped sequence of mitotic and meiotic divisions. The basic physiological principles, however, that control both maturation and luminal transport of the still immotile spermatozoa within the seminiferous tubules remain poorly, if at all, defined. Here, we show that coordinated contractions of smooth muscle-like testicular peritubular cells provide the propulsive force for luminal sperm transport towards the rete testis and epididymis. Using a mouse model for in vivo imaging, we describe and quantify spontaneous tubular contractions and show a causal relationship between peritubular Ca2+ waves and peristaltic transport. Moreover, we identify P2 receptor-dependent purinergic signaling pathways as physiological triggers of tubular contractions both in vitro and in vivo. When challenged with extracellular ATP, transport of luminal content inside the seminiferous tubules displays stage-dependent directionality. We thus suggest that paracrine purinergic signaling coordinates peristaltic recurrent contractions of the mouse seminiferous tubules to propel immotile spermatozoa to the rete testis. Consequently, our findings could have substantial pharmaceutical implications for both infertility treatment and / or male contraception.

cell biology↗

bioRxiv2019

Breaking Medical Data Sharing Boundaries by EmployingArtificial Radiographs

Artificial intelligence (AI) has the potential to change medicine fundamentally. Here, expert knowledge provided by AI can enhance diagnosis by comprehensive and user independent integration of multiple image features. Unfortunately, existing algorithms often stay behind expectations, as databases used for training are usually too small, incomplete, and heterogeneous in quality. Additionally, data protection constitutes a serious obstacle to data sharing. We propose to use generative models (GM) to produce high-resolution artificial radiographs, which are free of personal identifying information. Blinded analyses by computer vision and radiology experts proved the high similarity of artificial and real radiographs. The combination of multiple GM improves the performance of computer vision algorithms and the integration of artificial data into patient data repositories can compensate for underrepresented disease entities. Furthermore, the low computational effort of our method complies with existing IT infrastructure in hospitals and thus facilitates its dissemination. We envision that our approach could lead to scalable databases of anonymous medical images enabling standardized radiomic analyses at multiple sites.

bioinformatics↗