Scatter factor : molecular characteristics and effect on the invasiveness of epithelial cells

The generation of invasiveness in transformed cells represents an essential step of tumor progression. We have previously shown that MDCK epithelial cells, which are deprived of intracellular adhesion by the addition of anti-Arc-1/uvomorulin antibodies, become invasive for collagen gels and embryonal heart tissue (Behrens, J., M. M. Mareel, F. M. Van Roy, and W. Birchmeier. 1989. J. Cell Biol. 108: 2435-2447.). Here we examined whether invasiveness is also induced by scatter factor, which is known to dissociate epithelial cells (Stoker, M., E. Gherardi, M. Perryman, and J. Gray. 1987. Nature (Lond.). 327:239-242.). Scatter factor was purified to homogeneity from conditioned medium of human fibroblasts by heparin-Sepharose chromatography, followed by cation exchange chromatography, gel filtration, or preparative SDS gel electrophoresis. We found that scatter factor represents a 92,000 mol wt glycoprotein which, apparently, is converted by limited proteolysis into disulfide-linked 62,000 and 34/32,000 mol wt subunits. Reversed phase HPLC and sequence analysis of tryptic peptides confirmed the suggested molecular structure, and revealed further that scatter factor exhibits sequence similarities to hepatocyte growth factor and to plasminogen. Purified scatter factor in fact induces the invasiveness into collagen matrices of MDCK epithelial cells, and induces or promotes the invasiveness of a number of human carcinoma cell lines. Apparently, the effect on the human cells depends on their respective degree of differentiation, i.e., cell lines with a less pronounced epithelial phenotype were more susceptible to the factor. Scatter factor does not seem to influence synthesis, steady-state level, and phosphorylation of the cell adhesion molecule Arc-1/uvomorulin. Thus, scatter factor represents a clearly defined molecular species which induces, in vitro, the progression of epithelial cells to a more motile, i.e., invasive phenotype

A quantum probability account of individual differences in causal reasoning

We use quantum probability (QP) theory to investigate individual differences in causal reasoning. By analyzing data sets from Rehder (2014) on comparative judgments, and from Rehder & Waldmann (2016) on absolute judgments, we show that a QP model can both account for individual differences in causal judgments, and why these judgments sometimes violate the properties of causal Bayes nets. We implement this and previously proposed models of causal reasoning (including classical probability models) within the same hierarchical Bayesian inferential framework to provide a detailed comparison between these models, including computing Bayes factors. Analysis of the inferred parameters of the QP model illustrates how these can be interpreted in terms of putative cognitive mechanisms of causal reasoning. Additionally, we implement a latent classification mechanism that identifies subcategories of reasoners based on properties of the inferred cognitive process, rather than post hoc clustering. The QP model also provides a parsimonious explanation for aggregate behavior, which alternatively can only be explained by a mixture of multiple existing models. Investigating individual differences through the lens of a QP model reveals simple but strong alternatives to existing explanations for the dichotomies often observed in how people make causal inferences. These alternative explanations arise from the cognitive interpretation of the parameters and structure of the quantum probability model

Cortico-brainstem mechanisms of biased perceptual decision-making in the context of pain

Perceptual decision-making is commonly studied using stimuli with different physical properties but of comparable affective value. Here, we investigate neural processes underlying human perceptual decisions in the affectively rich domain of pain using a drift-diffusion model in combination with a probabilistic cueing paradigm. This allowed us to characterize a novel role for the dorsolateral prefrontal cortex (DLPFC), whose anticipatory responses reflecting a decision bias were dependent on the affective value of the stimulus. During intense noxious stimulation, these model-based anticipatory DLPFC responses were linked to an engagement of the periaqueductal gray (PAG), a midbrain region implicated in defensive responses including analgesia. Complementing these findings on biased decision-making, the model parameter reflecting sensory processing predicted subcortical responses (in amygdala and PAG) when expectations were violated. Our findings highlight the importance of taking a broader perspective on perceptual decisions and link decisions about pain with subcortical circuitry implicated in endogenous pain modulation

The covalent structure of Acanthamoeba actobindin

Actobindin is a protein from Acanthamoeba castellanii with bivalent affinity for monomeric actin. Because it can bind two molecules of actin, actobindin is a substantially more potent inhibitor of the early phase of actin polymerization than of F-actin elongation. The complete amino acid sequence of 88 residues has been deduced from the determined sequences of overlapping peptides obtained by cleavage with trypsin, Staphylococcus V8 protease, endoproteinase Asp-N, and CNBr. Actobindin contains 2 trimethyllysine residues and an acetylated NH2 terminus. About 76% of the actobindin molecule consists of two nearly identical repeated segments of approximately 33 residues each. This could explain actobindin's bivalent affinity for actin. The circular dichroism spectrum of actobindin is consistent with 15% alpha-helix and 22% beta-sheet structure. A hexapeptide with sequence LKHAET, which occurs at the beginning of each of the repeated segments of actobindin, is very similar to sequences found in tropomyosin, muscle myosin heavy chain, paramyosin, and Dictyostelium alpha-actinin. A longer stretch in each repeated segment is similar to sequences in mammalian and amoeba profilins. Interestingly, the sequences around the trimethyllysine residues in each of the repeats are similar to the sequences flanking the trimethyllysine residue of rabbit reticulocyte elongation factor 1 alpha, but not to the sequences around the trimethyllysine residues in Acanthamoeba actin and Acanthamoeba profilins I and II

Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration

Notch signaling during human T cell development

Notch signaling is critical during multiple stages of T cell development in both mouse and human. Evidence has emerged in recent years that this pathway might regulate T-lineage differentiation differently between both species. Here, we review our current understanding of how Notch signaling is activated and used during human T cell development. First, we set the stage by describing the developmental steps that make up human T cell development before describing the expression profiles of Notch receptors, ligands, and target genes during this process. To delineate stage-specific roles for Notch signaling during human T cell development, we subsequently try to interpret the functional Notch studies that have been performed in light of these expression profiles and compare this to its suggested role in the mouse