p21WAF1 modulates drug-induced apoptosis and cell cycle arrest in B-cell precursor acute lymphoblastic leukemia

p21^WAF1 is a well-characterized mediator of cell cycle arrest and may also modulate chemotherapy-induced cell death. The role of p21^WAF1 in drug-induced cell cycle arrest and apoptosis of acute lymphoblastic leukemia (ALL) cells was investigated using p53-functional patient-derived xenografts (PDXs), in which p21^WAF1 was epigenetically silenced in T-cell ALL (T-ALL), but not in B-cell precursor (BCP)-ALL PDXs. Upon exposure to diverse cytotoxic drugs, T-ALL PDX cells exhibited markedly increased caspase-3/7 activity and phosphatidylserine (PS) externalization on the plasma membrane compared with BCP-ALL cells. Despite dramatic differences in apoptotic characteristics between T-ALL and BCP-ALL PDXs, both ALL subtypes exhibited similar cell death kinetics and were equally sensitive to p53-inducing drugs in vitro, although T-ALL PDXs were significantly more sensitive to the histone deacetylase inhibitor vorinostat. Transient siRNA suppression of p21^WAF1 in the BCP-ALL 697 cell line resulted in a moderate depletion of the cell fraction in G1 phase and marked increase in PS externalization following exposure to etoposide. Furthermore, stable lentiviral p21^WAF1 silencing in the BCP-ALL Nalm-6 cell line accelerated PS externalization and cell death following exposure to etoposide and vorinostat, supporting previous findings. Finally, the Sp1 inhibitor, terameprocol, inhibited p21^WAF1 expression in Nalm-6 cells exposed to vorinostat and also partially augmented vorinostat-induced cell death. Taken together, these findings demonstrate that p21^WAF1 regulates the early stages of drug-induced apoptosis in ALL cells and significantly modulates their sensitivity to vorinostat.     

How do antiporters exchange substrates across the cell membrane? An atomic-level description of the complete exchange cycle in NarK

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Trafficking mechanisms of extracellular matrix macromolecules: Insights from vertebrate development and human diseases

Cellular life depends on protein transport and membrane traffic. In multicellular organisms, membrane traffic is required for extracellular matrix deposition, cell adhesion, growth factor release, and receptor signaling, which are collectively required to integrate the development and physiology of tissues and organs. Understanding the regulatory mechanisms that govern cargo and membrane flow presents a prime challenge in cell biology. Extracellular matrix (ECM) secretion remains poorly understood, although given its essential roles in the regulation of cell migration, differentiation, and survival, ECM secretion mechanisms are likely to be tightly controlled.Recent studies in vertebrate model systems, from fishes to mammals and in human patients, have revealed complex and diverse loss-of-function phenotypes associated with mutations in components of the secretory machinery. A broad spectrum of diseases from skeletal and cardiovascular to neurological deficits have been linked to ECM trafficking. These discoveries have directly challenged the prevailing view of secretion as an essential but monolithic process. Here, we will discuss the latest findings on mechanisms of ECM trafficking in vertebrates.     

Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process

We model the vague-to-crisp dynamics of forming percepts in the brain by combining two methodologies: dynamic logic (DL) and operant learning process. Forming percepts upon the presentation of visual inputs is likened to model selection based on sampled evidence. Our framework utilizes the DL in selecting the correct “percept” among competing ones, but uses an intrinsic reward mechanism to allow stochastic online update in lieu of performing the optimization step of the DL framework. We discuss the connection of our framework with cognitive processing and the intentional neurodynamic cycle.     

Evolutionary dynamics of giant viruses and their virophages

Giant viruses contain large genomes, encode many proteins atypical for viruses, replicate in large viral factories, and tend to infect protists. The giant virus replication factories can in turn be infected by so called virophages, which are smaller viruses that negatively impact giant virus replication. An example is Mimiviruses that infect the protist Acanthamoeba and that are themselves infected by the virophage Sputnik. This study examines the evolutionary dynamics of this system, using mathematical models. While the models suggest that the virophage population will evolve to increasing degrees of giant virus inhibition, it further suggests that this renders the virophage population prone to extinction due to dynamic instabilities over wide parameter ranges. Implications and conditions required to avoid extinction are discussed. Another interesting result is that virophage presence can fundamentally alter the evolutionary course of the giant virus. While the giant virus is predicted to evolve toward increasing its basic reproductive ratio in the absence of the virophage, the opposite is true in its presence. Therefore, virophages can not only benefit the host population directly by inhibiting the giant viruses but also indirectly by causing giant viruses to evolve toward weaker phenotypes. Experimental tests for this model are suggested.     

An overview of mechanistic modeling of liquid chromatography

Abstract

Liquid chromatography is considered to be the bottleneck for purification of therapeutic proteins. Development and optimization of chromatography process is a cumbersome activity due to the increasing complexities in the types and content of impurities present in the high product titer cell culture harvest obtained from the upstream processing. Further, regulatory expectations are continuously rising with the recent initiatives of quality by design and process analytical technology expecting the manufacturer to have a deeper understanding of the process and the product. Mechanistic modeling is one approach to gain this deeper understanding of a process step. It involves modeling of the underlying physicochemical processes. A well calibrated model with acceptable predictability can be very effective in both process optimization and process characterization activities. In this paper we provide an overview of mechanistic modeling of liquid chromatography. We discuss the various components that such a model entails and also presents the status quo of this area.