Search Results
Scanning electron microscopy preparation of the cellular actin cortex: A quantitative comparison between critical point drying and hexamethyldisilazane drying
2021, Schu, Moritz, Terriac, Emmanuel, Koch, Marcus, Paschke, Stephan, Lautenschläger, Franziska, Flormann, Daniel A.D.
The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.
Cost-effective mitigation of nitrogen pollution from global croplands
2023, Gu, Baojing, Zhang, Xiuming, Lam, Shu Kee, Yu, Yingliang, van Grinsven, Hans J. M., Zhang, Shaohui, Wang, Xiaoxi, Bodirsky, Benjamin Leon, Wang, Sitong, Duan, Jiakun, Ren, Chenchen, Bouwman, Lex, de Vries, Wim, Xu, Jianming, Sutton, Mark A., Chen, Deli
Cropland is a main source of global nitrogen pollution1,2. Mitigating nitrogen pollution from global croplands is a grand challenge because of the nature of non-point-source pollution from millions of farms and the constraints to implementing pollution-reduction measures, such as lack of financial resources and limited nitrogen-management knowledge of farmers3. Here we synthesize 1,521 field observations worldwide and identify 11 key measures that can reduce nitrogen losses from croplands to air and water by 30–70%, while increasing crop yield and nitrogen use efficiency (NUE) by 10–30% and 10–80%, respectively. Overall, adoption of this package of measures on global croplands would allow the production of 17 ± 3 Tg (1012 g) more crop nitrogen (20% increase) with 22 ± 4 Tg less nitrogen fertilizer used (21% reduction) and 26 ± 5 Tg less nitrogen pollution (32% reduction) to the environment for the considered base year of 2015. These changes could gain a global societal benefit of 476 ± 123 billion US dollars (USD) for food supply, human health, ecosystems and climate, with net mitigation costs of only 19 ± 5 billion USD, of which 15 ± 4 billion USD fertilizer saving offsets 44% of the gross mitigation cost. To mitigate nitrogen pollution from croplands in the future, innovative policies such as a nitrogen credit system (NCS) could be implemented to select, incentivize and, where necessary, subsidize the adoption of these measures.
Immune mobilising T cell receptors redirect polyclonal CD8+ T cells in chronic HIV infection to form immunological synapses
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.
Evolutionary design of explainable algorithms for biomedical image segmentation
2023, Cortacero, Kévin, McKenzie, Brienne, Müller, Sabina, Khazen, Roxana, Lafouresse, Fanny, Corsaut, Gaëlle, Van Acker, Nathalie, Frenois, François-Xavier, Lamant, Laurence, Meyer, Nicolas, Vergier, Béatrice, Wilson, Dennis G., Luga, Hervé, Staufer, Oskar, Dustin, Michael L., Valitutti, Salvatore, Cussat-Blanc, Sylvain
An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
Non-thermal plasma modulates cellular markers associated with immunogenicity in a model of latent HIV-1 infection
2021, Mohamed, Hager, Clemen, Ramona, Freund, Eric, Lackmann, Jan-Wilm, Wende, Kristian, Connors, Jennifer, Haddad, Elias K., Dampier, Will, Wigdahl, Brian, Miller, Vandana, Bekeschus, Sander, Krebs, Fred C., Kashanchi, Fatah
Effective control of infection by human immunodeficiency virus type 1 (HIV-1), the causative agent of the acquired immunodeficiency syndrome (AIDS), requires continuous and life-long use of anti-retroviral therapy (ART) by people living with HIV-1 (PLWH). In the absence of ART, HIV-1 reemergence from latently infected cells is ineffectively suppressed due to suboptimal innate and cytotoxic T lymphocyte responses. However, ART-free control of HIV-1 infection may be possible if the inherent immunological deficiencies can be reversed or restored. Herein we present a novel approach for modulating the immune response to HIV-1 that involves the use of non-thermal plasma (NTP), which is an ionized gas containing various reactive oxygen and nitrogen species (RONS). J-Lat cells were used as a model of latent HIV-1 infection to assess the effects of NTP application on viral latency and the expression of pro-phagocytic and pro-chemotactic damage-associated molecular patterns (DAMPs). Exposure of J-Lat cells to NTP resulted in stimulation of HIV-1 gene expression, indicating a role in latency reversal, a necessary first step in inducing adaptive immune responses to viral antigens. This was accompanied by the release of pro-inflammatory cytokines and chemokines including interleukin-1β (IL-1β) and interferon-γ (IFN-γ); the display of pro-phagocytic markers calreticulin (CRT), heat shock proteins (HSP) 70 and 90; and a correlated increase in macrophage phagocytosis of NTP-exposed J-Lat cells. In addition, modulation of surface molecules that promote or inhibit antigen presentation was also observed, along with an altered array of displayed peptides on MHC I, further suggesting methods by which NTP may modify recognition and targeting of cells in latent HIV-1 infection. These studies represent early progress toward an effective NTP-based ex vivo immunotherapy to resolve the dysfunctions of the immune system that enable HIV-1 persistence in PLWH.
Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors
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.
Computational design and optimization of electro-physiological sensors
2021, Nittala, Aditya Shekhar, Karrenbauer, Andreas, Khan, Arshad, Kraus, Tobias, Steimle, Jürgen
Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.
Tumor cytotoxicity and immunogenicity of a novel V-jet neon plasma source compared to the kINPen
2021, Miebach, Lea, Freund, Eric, Horn, Stefan, Niessner, Felix, Sagwal, Sanjeev Kumar, von Woedtke, Thomas, Emmert, Steffen, Weltmann, Klaus-Dieter, Clemen, Ramona, Schmidt, Anke, Gerling, Torsten, Bekeschus, Sander
Recent research indicated the potential of cold physical plasma in cancer therapy. The plethora of plasma-derived reactive oxygen and nitrogen species (ROS/RNS) mediate diverse antitumor effects after eliciting oxidative stress in cancer cells. We aimed at exploiting this principle using a newly designed dual-jet neon plasma source (Vjet) to treat colorectal cancer cells. A treatment time-dependent ROS/RNS generation induced oxidation, growth retardation, and cell death within 3D tumor spheroids were found. In TUM-CAM, a semi in vivo model, the Vjet markedly reduced vascularized tumors' growth, but an increase of tumor cell immunogenicity or uptake by dendritic cells was not observed. By comparison, the argon-driven single jet kINPen, known to mediate anticancer effects in vitro, in vivo, and in patients, generated less ROS/RNS and terminal cell death in spheroids. In the TUM-CAM model, however, the kINPen was equivalently effective and induced a stronger expression of immunogenic cancer cell death (ICD) markers, leading to increased phagocytosis of kINPen but not Vjet plasma-treated tumor cells by dendritic cells. Moreover, the Vjet was characterized according to the requirements of the DIN-SPEC 91315. Our results highlight the plasma device-specific action on cancer cells for evaluating optimal discharges for plasma cancer treatment.