Cell death, as a final cellular decision which is reached following complex communications, represents a critical process with which to maintain organismic homeostasis. Different classifications and nomenclatures have brought considerable confusion to cell death determination. In the present review article, the hallmarks of different cell death modes are systematically described and are fitted into a simple classification system, where the cell death entities are primarily categorized into programmed cell death (PCD) or non-PCD based on their signal dependency. PCD can be further categorized as apoptotic cell death or non-apoptotic cell death. Programmed apoptosis consists of apoptosis, as well as anoikis. Multiple mechanisms and phenotypes compose programmed non-apoptotic cell death, including vacuole-presenting cell death (autophagy, entosis, methuosis and paraptosis), mitochondrial-dependent cell death (mitoptosis and parthanatos), iron-dependent cell death (ferroptosis), immune-reactive cell death (pyroptosis and NETosis), as well as other types, such as necroptosis. Finally, necrosis represents a form of non-programmed cell death. Contents 1. Introduction 2. Non-programmed cell death 3. Programmed apoptotic cell death 4. Programmed non-apoptotic cell death 5. Implications of cell death in human diseases 6. Conclusions and perspectives

Organoids of human airways to study infectivity and cytopathy of SARS-CoV-2Studies of infectious diseases have been limited by the lack of models that recapitulate normal cellular physiology and pathology. Developments in organotypic models have paved the road towards further studies of viral infections and host-virus interactions. For example, human intestinal organoids were efficiently used to study many viruses, such as rotavirus, norovirus, enterovirus 71, and human adenovirus. 1 Mammalian airway organoids are complex three-dimensional structures characterised by different cellular composition and designed to mimic lung structures. Early research attempted to develop these organoids from different progenitor cells, including basal cells, secretory cells, and alveolar epithelial cells. 2 In the past 5 years, scientists were able to generate mature lung organoids that contain basal, ciliated, and club cells. These organoids were used to study diseases such as cystic fibrosis and lung tumours, and infections. 3 One study 4 used airway organoids to look at viral replication, tissue tropism, and immune response to many human influenza A and avian viruses.Fortunately, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, was isolated and propagated early on in the pandemic using numerous in-vitro models, such as Vero cells, Huh7 cells, and human airway epithelial cells. This isolation was enhanced after SARS-CoV-2 was isolated and propagated in TMPRSS2expressing VeroE6 cells, indicating the vital role of TMPRSS2 serine protease in virus infectivity. 5 Thus, in-vitro models are effective in the study of virus propagation, but they poorly

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A new Plasmodium falciparum histone deacetylase1 (PfHDAC1) homology model was built based on the highest sequence identity available template human histone deacetylase 2 structure. The generated model was carefully evaluated for stereochemical accuracy, folding correctness and overall structure quality. All evaluations were acceptable and consistent. Docking a group of hydroxamic acid histone deacetylase inhibitors and valproic acid has shown binding poses that agree well with inhibitor-bound histone deacetylase-solved structural interactions. Docking affinity dG scores were in agreement with available experimental binding affinities. Further, enzyme-ligand complex stability and reliability were investigated by running 5-nanosecond molecular dynamics simulations. Thorough analysis of the simulation trajectories has shown that enzyme-ligand complexes were stable during the simulation period. Interestingly, the calculated theoretical binding energies of the docked hydroxamic acid inhibitors have shown that the model can discriminate between strong and weaker inhibitors and agrees well with the experimental affinities reported in the literature. The model and the docking methodology can be used in screening virtual libraries for PfHDAC1 inhibitors, since the docking scores have ranked ligands in accordance with experimental binding affinities. Valproic acid calculated theoretical binding energy suggests that it may inhibit PfHDAC1.

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