Biology subjects

Hoppe, J.

Publications and source records attributed to Hoppe, J..

6 recordsLinked to original sources

bioRxiv2025

Photoacoustics-guided Real-Time Closed-loop Control of Magnetic Microrobots through Deep Learning

Medical microrobots promise to increase the efficacy and reduce the invasiveness of certain medical procedures in the future. Real-time tracking of the microrobot, actuation, and closed-loop control of its position under in vivo conditions is crucial to fulfill the task at hand. We present a system for closed-loop control of magnetic microrobots using dual-mode ultrasound and photoacoustic imaging. It employs GPU-accelerated beamforming and tracking to achieve real-time operation with a closed-loop cycle time of 100 ms. Artifacts from simultaneous imaging and magnetic actuation are suppressed through time-multiplexing. To address the challenge of detecting microrobots in low-contrast, strong-background images, we implemented real-time Deep Learning-based tracking. A custom dataset of various types of microrobots is curated from long-duration closed-loop control measurements and employed to fine-tune a pre-trained detection model. We introduce a platform for real-time closed-loop control of microrobots and demonstrate its performance with a 300 m spiral-shaped microrobot following a figure-of-8 shape under photoacoustic imaging guidance. The localization error is evaluated against an optical reference measurement. Our results show that photoacoustic-based tracking significantly outperforms ultrasound tracking, with the deep learning approach further reducing missed detections. This demonstrates the algorithms ability to generalize to a previously unseen type of microrobot. We envision this platform to advance medical microrobotics research by providing real-time closed-loop control of untethered microrobots under deep tissue.

bioengineering↗

bioRxiv2025

Influence of hyperparameters on the performance of deep learning-based microrobotic localization under phantom tissue

For the effective operation of medical microrobots within living organisms and precise targeting, it is imperative to employ imaging techniques closely integrated with real-time deep-tissue tracking methods. However, due to a typically low Signal-to-Noise ratio images with strong background, it is hard for traditional tracking methods to achieve sufficient accuracy. This challenge can be addressed by deep learning-based tracking with a real-time detection model. However, a multitude of design choices and Hyperparameters influence the performance. In this study we compared the influence of the hyperparameters and model architecture versions of the "you only look once" (YOLO) network. We use experimental data from a magnetic microrobot imaged with Photoacoustics through 5 mm phantom tissue to evaluate the tracking in comparison with an optical reference. The deep-learning based methods consistently achieved lower missing-detection ratios. Regarding the Root Mean Square localization error, we observed that increasing the weight of the box loss function and utilizing the distribution focal loss can enhance the performance by 10%. Furthermore, it can be seen that YOLOv9 consistently outperformed its predecessor YOLOv8. This study quantifies the robustness of deep-learning based tracking of medical microrobots under tissues.

bioengineering↗

bioRxiv2024

TNF Superfamily Member 14 Drives Post-Influenza Depletion of Alveolar Macrophages Enabling Secondary Pneumococcal Pneumonia

Secondary bacterial infection, often caused by Streptococcus pneumoniae (Spn), is one of the most frequent and severe complications of influenza A virus (IAV)-induced pneumonia. Phenotyping of the pulmonary innate immune landscape after IAV infection revealed a significant depletion of the tissue-resident alveolar macrophage (TR-AM) population at day 7, which was associated with increased susceptibility to Spn outgrowth. To elucidate the molecular mechanisms underlying TR-AM depletion, and to define putative targets for treatment, we combined single-cell transcriptomics and cell-specific PCR profiling in an unbiased manner, using in vivo models of IAV infection and IAV/Spn co-infection. The TNF superfamily 14 (TNFSF14) ligand-receptor axis was revealed as the driving force behind post-influenza TR-AM death during the early infection phase, enabling the transition to pneumococcal pneumonia, while intrapulmonary transfer of genetically modified TR-AMs and antibody-mediated neutralization of specific pathway components alleviated disease severity. With a mainly neutrophilic expression and a high abundance in the bronchoalveolar fluid (BALF) of patients with severe virus-induced ARDS, TNFSF14 emerged as a novel determinant of virus-driven lung injury. Targeting the TNFSF14-mediated intercellular communication network in the virus-infected lung can, therefore, improve host defense, minimizing the risk of subsequent bacterial pneumonia, and ameliorating disease outcome.

molecular biology↗

bioRxiv2022

Tissue protective role of Ganetespib in SARS-CoV-2-infected Syrian golden hamsters

The emergence of new SARS-CoV-2 variants, capable of escaping the humoral immunity acquired by the available vaccines, together with waning immunity and vaccine hesitancy, challenges the efficacy of the vaccination strategy in fighting COVID-19. Improved therapeutic strategies are therefore urgently needed to better intervene particularly in severe cases of the disease. They should aim at controlling the hyper-inflammatory state generated upon infection, at reducing lung tissue pathology and endothelial damages, along with viral replication. Previous research has pointed a possible role for the chaperone HSP90 in SARS-CoV-2 replication and COVID-19 pathogenesis. Pharmacological intervention through HSP90 inhibitors was shown to be beneficial in the treatment of inflammatory diseases, infections and reducing replication of diverse viruses. In this study, we analyzed the effects of the potent HSP90 inhibitor Ganetespib in vitro on alveolar epithelial cells and alveolar macrophages to characterize its effects on cell activation and viral replication. Additionally, to evaluate its efficacy in controlling systemic inflammation and the viral burden after infection in vivo, a Syrian hamster model was used. In vitro, Ganetespib reduced viral replication on AECs in a dose-dependent manner and lowered significantly the expression of pro-inflammatory genes, in both AECs and alveolar macrophages. In vivo, administration of Ganetespib led to an overall improvement of the clinical condition of infected animals, with decreased systemic inflammation, reduced edema formation and lung tissue pathology. Altogether, we show that Ganetespib could be a potential medicine to treat moderate and severe cases of COVID-19.

microbiology↗

bioRxiv2021

Single cell RNA-seq uncovers the nuclear decoy lincRNA PIRAT as a regulator of systemic monocyte immunity during COVID-19

The systemic immune response to viral infection is shaped by master transcription factors such as NF{kappa}B or PU.1. Although long non-coding RNAs (lncRNAs) have been suggested as important regulators of transcription factor activity, their contributions to the systemic immunopathologies observed during SARS-CoV-2 infection have remained unknown. Here, we employed a targeted single-cell RNA-seq approach to reveal lncRNAs differentially expressed in blood leukocytes during severe COVID-19. Our results uncover the lncRNA PIRAT as a major PU.1 feedback-regulator in monocytes, governing the production of the alarmins S100A8/A9 - key drivers of COVID-19 pathogenesis. Knockout and transgene expression, combined with chromatin-occupancy profiling characterized PIRAT as a nuclear decoy RNA, diverting the PU.1 transcription factor from alarmin promoters to dead-end pseudogenes in naive monocytes. NF{kappa}B-dependent PIRAT down-regulation during COVID-19 consequently releases a transcriptional brake, fueling alarmin production. Our results suggest a major role of nuclear noncoding RNA circuits in systemic antiviral responses to SARS-CoV-2 in humans.

immunology↗

bioRxiv2020

Tau in the brain interstitial fluid is fragmented and seeding-competent

In Alzheimer disease, Tau pathology is thought to propagate from cell to cell throughout interconnected brain areas. However, the forms of Tau released into the brain interstitial fluid (ISF) in vivo during the development of Tauopathy and their pathological relevance remain unclear. Combining in vivo microdialysis and biochemical analysis, we find that in Tau transgenic mice, human Tau (hTau) present in brain ISF is truncated and comprises at least 10 distinct fragments spanning the entire Tau protein. The fragmentation pattern is similar across different Tau transgenic models, pathological stages and brain areas. ISF hTau concentration decreases during Tauopathy progression, while its phosphorylation increases. ISF from mice with established Tauopathy induces Tau aggregation in HEK293-Tau biosensor cells. Notably, immunodepletion of ISF phosphorylated Tau, but not Tau fragments, significantly reduces its ability to seed Tau aggregation and only a fraction of Tau, separated by ultracentrifugation, is seeding competent. These results indicate that ISF seeding competence is driven by a small subset of Tau, which potentially contribute to the propagation of Tau pathology. HighlightsO_LIIn interstitial fluid (ISF) of transgenic mice, Tau comprises >10 distinct fragments C_LIO_LIISF Tau decreases with Tauopathy progression, while its phosphorylation increases C_LIO_LIOnly ISF from mice with established Tauopathy is seeding competent in vitro C_LIO_LIRemoval of phospho-Tau reduces ISF seeding competence C_LIO_LIISF seeding competence is driven by less soluble, aggregated and phosphorylated Tau C_LI Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

neuroscience↗