There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Coronavirus disease 2019 (COVID-19) is a novel, viral-induced respiratory disease that in ∼10-15% of patients progresses to acute respiratory distress syndrome (ARDS) triggered by a cytokine storm. In this Perspective, autopsy results and literature are presented supporting the hypothesis that a little known yet powerful function of neutrophils-the ability to form neutrophil extracellular traps (NETs)-may contribute to organ damage and mortality in COVID-19. We show lung infiltration of neutrophils in an autopsy specimen from a patient who succumbed to COVID-19. We discuss prior reports linking aberrant NET formation to pulmonary diseases, thrombosis, mucous secretions in the airways, and cytokine production. If our hypothesis is correct, targeting NETs directly and/or indirectly with existing drugs may reduce the clinical severity of COVID-19.

https://rupress.org/jem/article-pdf/217/6/e20200652/1414639/jem_20200652.pdf

Targeting potential drivers of COVID-19: Neutrophil extracellular traps.

Biofilm formation is a key virulence factor for a wide range of microorganisms that cause chronic infections. The multifactorial nature of biofilm development and drug tolerance imposes great challenges for the use of conventional antimicrobials and indicates the need for multi-targeted or combinatorial therapies. In this Review, we focus on current therapeutic strategies and those under development that target vital structural and functional traits of microbial biofilms and drug tolerance mechanisms, including the extracellular matrix and dormant cells. We emphasize strategies that are supported by in vivo or ex vivo studies, highlight emerging biofilm-targeting technologies and provide a rationale for multi-targeted therapies aimed at disrupting the complex biofilm microenvironment.

/pdf/targeting-microbial-biofilms-current-and-prospective-2br9buvtyz.pdf

Targeting microbial biofilms: current and prospective therapeutic strategies.

Neutrophils play an important role in innate immunity by defending the host organism against invading microorganisms. Antimicrobial activity of neutrophils is mediated by release of antimicrobial peptides, phagocytosis as well as formation of neutrophil extracellular traps (NET). These structures are composed of DNA, histones and granular proteins such as neutrophil elastase and myeloperoxidase. This study focused on the influence of NET on the host cell functions, particularly on human alveolar epithelial cells as the major cells responsible for gas exchange in the lung. Upon direct interaction with epithelial and endothelial cells, NET induced cytotoxic effects in a dose-dependent manner, and digestion of DNA in NET did not change NET-mediated cytotoxicity. Pre-incubation of NET with antibodies against histones, with polysialic acid or with myeloperoxidase inhibitor but not with elastase inhibitor reduced NET-mediated cytotoxicity, suggesting that histones and myeloperoxidase are responsible for NET-mediated cytotoxicity. Although activated protein C (APC) did decrease the histone-induced cytotoxicity in a purified system, it did not change NET-induced cytotoxicity, indicating that histone-dependent cytotoxicity of NET is protected against APC degradation. Moreover, in LPS-induced acute lung injury mouse model, NET formation was documented in the lung tissue as well as in the bronchoalveolar lavage fluid. These data reveal the important role of protein components in NET, particularly histones, which may lead to host cell cytotoxicity and may be involved in lung tissue destruction.

/pdf/neutrophil-extracellular-traps-directly-induce-epithelial-1iumh4331b.pdf

Neutrophil Extracellular Traps Directly Induce Epithelial and Endothelial Cell Death: A Predominant Role of Histones

(R)-Roscovitine, a pharmacological inhibitor of kinases, is currently in phase II clinical trial as a drug candidate for the treatment of cancers, Cushing's disease and rheumatoid arthritis. We here review the data that support the investigation of (R)-roscovitine as a potential therapeutic agent for the treatment of cystic fibrosis (CF). (R)-Roscovitine displays four independent properties that may favorably combine against CF: (1) it partially protects F508del-CFTR from proteolytic degradation and favors its trafficking to the plasma membrane; (2) by increasing membrane targeting of the TRPC6 ion channel, it rescues acidification in phagolysosomes of CF alveolar macrophages (which show abnormally high pH) and consequently restores their bactericidal activity; (3) its effects on neutrophils (induction of apoptosis), eosinophils (inhibition of degranulation/induction of apoptosis) and lymphocytes (modification of the Th17/Treg balance in favor of the differentiation of anti-inflammatory lymphocytes and reduced production of various interleukins, notably IL-17A) contribute to the resolution of inflammation and restoration of innate immunity, and (4) roscovitine displays analgesic properties in animal pain models. The fact that (R)-roscovitine has undergone extensive preclinical safety/pharmacology studies, and phase I and II clinical trials in cancer patients, encourages its repurposing as a CF drug candidate.

/pdf/modulating-innate-and-adaptive-immunity-by-r-roscovitine-4p801w2q1i.pdf

Modulating Innate and Adaptive Immunity by (R)-Roscovitine: Potential Therapeutic Opportunity in Cystic Fibrosis

https://www.cysticfibrosisjournal.com/article/S1569-1993(11)00170-6/pdf

Ultrastructural characterization of cystic fibrosis sputum using atomic force and scanning electron microscopy.

Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in the technical histopathological procedures like staining protocols, and finally the individual experience of the diagnosing pathologist. Thus, to raise astrocytoma grading to a more objective standard, this paper proposes a methodology based on atomic force microscopy (AFM) derived images made from histopathological samples in combination with data mining techniques. By comparing AFM images with corresponding light microscopy images of the same area, the progressive formation of cavities due to cell necrosis was identified as a typical morphological marker for a computer-assisted analysis. Using genetic programming as a tool for feature analysis, a best model was created that achieved 94.74% classification accuracy in distinguishing grade II tumors from grade IV ones. While utilizing modern image analysis techniques, AFM may become an important tool in astrocytic tumor diagnosis. By this way patients suffering from grade II tumors are identified unambiguously, having a less risk for malignant transformation. They would benefit from early adjuvant therapies.

/pdf/brain-tumor-classification-using-afm-in-combination-with-12nyy37p2n.pdf

Brain Tumor Classification Using AFM in Combination with Data Mining Techniques

The present paper deals with the application of atomic force microscopy (AFM) as a tool for morphological characterization of histological brain tumor samples. Data mining techniques will be applied for automatic identification of brain tumor tissues based on AFM images by means of classifying grade II and IV tumors. The rapid advancement of AFM in recent years turned it into a valuable and useful tool to determine the topography of surface nanoscale structures with high precision. Therefore, it is used in a variety of applications in life science, materials science, electrochemistry, polymer science, biophysics, nanotechnology, and biotechnology. Minkowski functionals are used (in particular the Euler- Poincare characteristic) as a feature descriptor to characterize global geometric structures in images related to the topology of the AFM image. In order to improve classification accuracy on the one hand, but to infer interpretable information from AFM images for domain experts on the other hand, feature analysis and reduction will be applied. From a data mining point of view, Genetic Programming will be introduced as a sophisticated method for both feature analysis and reduction as well as for producing highly accurate and interpretable models. Support Vector Machines will be used for comparison reasons when talking about reachable model accuracy.

Marlene Huml

Papers

Ultrastructural characterization of cystic fibrosis sputum using atomic force and scanning electron microscopy.

Brain Tumor Classification Using AFM in Combination with Data Mining Techniques

Data mining techniques for AFM- based tumor classification