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End date: 2023 × Start date: 2023 × Has files: Yes × Subject: Humans × WGL Institute: IPHT ×

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    Orchestrated control of filaggrin-actin scaffolds underpins cornification
    (London [u.a.] : Nature Publishing Group, 2018) Gutowska-Owsiak, Danuta; de La Serna, Jorge Bernardino; Fritzsche, Marco; Naeem, Aishath; Podobas, Ewa I.; Leeming, Michael; Colin-York, Huw; O’Shaughnessy, Ryan; Eggeling, Christian; Ogg, Graham S.
    Epidermal stratification critically depends on keratinocyte differentiation and programmed death by cornification, leading to formation of a protective skin barrier. Cornification is dynamically controlled by the protein filaggrin, rapidly released from keratohyalin granules (KHGs). However, the mechanisms of cornification largely remain elusive, partly due to limitations of the observation techniques employed to study filaggrin organization in keratinocytes. Moreover, while the abundance of keratins within KHGs has been well described, it is not clear whether actin also contributes to their formation or fate. We employed advanced (super-resolution) microscopy to examine filaggrin organization and dynamics in skin and human keratinocytes during differentiation. We found that filaggrin organization depends on the cytoplasmic actin cytoskeleton, including the role for α- and β-actin scaffolds. Filaggrin-containing KHGs displayed high mobility and migrated toward the nucleus during differentiation. Pharmacological disruption targeting actin networks resulted in granule disintegration and accelerated cornification. We identified the role of AKT serine/threonine kinase 1 (AKT1), which controls binding preference and function of heat shock protein B1 (HspB1), facilitating the switch from actin stabilization to filaggrin processing. Our results suggest an extended model of cornification in which filaggrin utilizes actins to effectively control keratinocyte differentiation and death, promoting epidermal stratification and formation of a fully functional skin barrier.
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    Immune mobilising T cell receptors redirect polyclonal CD8+ T cells in chronic HIV infection to form immunological synapses
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2022) Wallace, Zoë; Kopycinski, Jakub; Yang, Hongbing; McCully, Michelle L.; Eggeling, Christian; Chojnacki, Jakub; Dorrell, Lucy
    T cell exhaustion develops in human immunodeficiency virus (HIV) infection due to chronic viral antigenic stimulation. This adaptive response primarily affects virus-specific CD8+ T cells, which may remain dysfunctional despite viral load-reducing antiretroviral therapy; however, abnormalities may also be evident in non-HIV-specific populations. Both could limit the efficacy of cell therapies against viral reservoirs. Here, we show that bulk (polyclonal) CD8+ T cells from people living with HIV (PLWH) express proposed markers of dysfunctional HIV-specific T cells at high levels yet form lytic immunological synapses (IS) and eliminate primary resting infected (HIV Gaglo) CD4+ T cells, when redirected by potent bispecific T cell-retargeting molecules, Immune mobilising monoclonal T cell receptors (TCR) Against Virus (ImmTAV). While PLWH CD8+ T cells are functionally impaired when compared to CD8+ T cells from HIV-naïve donors, ImmTAV redirection enables them to eliminate Gaglo CD4+ T cells that are insensitive to autologous HIV-specific cytolytic T cells. ImmTAV molecules may therefore be able to target HIV reservoirs, which represent a major barrier to a cure.
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    Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Ali, Nairveen; Bolenz, Christian; Todenhöfer, Tilman; Stenzel, Arnulf; Deetmar, Peer; Kriegmair, Martin; Knoll, Thomas; Porubsky, Stefan; Hartmann, Arndt; Popp, Jürgen; Kriegmair, Maximilian C.; Bocklitz, Thomas
    Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates.