Amphiphilic cationic peptides mediate cell adhesion to plastic surfaces

Four amphiphilic peptides, each with net charges of +2 or more at neutrality and molecular weights under 4 kilodaltons, were found to mediate the adhesion of normal rat kidney fibroblasts to polystyrene surfaces. Two of these peptides, a model for calcitonin (peptide 1, MCT) and melittin (peptide 2, MEL), form amphiphilic alpha-helical structures at aqueous/nonpolar interfaces. The other two, a luteinizing hormone-releasing hormone model (peptide 3, LHM) and a platelet factor model (peptide 4, MPF) form beta-strand structures in amphiphilic environments. Although it contains only 10 residues, LHM mediated adhesion to surfaces coated with solutions containing as little as 10 pmoles/ml of peptide. All four of these peptides were capable of forming monolayers at air-buffer interfaces with collapse pressures greater than 20 dynes/cm. None of these four peptides contains the tetrapeptide sequence Arg-Gly-Asp-Ser, which has been associated with fibronectin-mediated cell adhesion. Ten polypeptides that also lacked the sequence Arg-Gly-Asp-Ser but were nonamphiphilic and/or had net charges less than +2 at neutrality were all incapable of mediating cell adhesion (Pierschbacher and Ruoslahti, 1984). The morphologies of NRK cells spread on polystyrene coated with peptide LHM resemble the morphologies on fibronectin-coated surfaces, whereas cells spread on surfaces coated with MCT or MEL exhibit strikingly different morphologies. The adhesiveness of MCT, MEL, LHM, and MPF implies that many amphiphilic cationic peptides could prove useful as well defined adhesive substrata for cell culture and for studies of the mechanism of cell adhesion.     

Cytosolic HMGB1 Mediates Autophagy Activation in an Emulsified Isoflurane Anesthesia Cell Model

Neurochemical Research - Inhalation anesthetic isoflurane may cause an increased risk of cognitive impairment. Previous studies have indicated that this cognitive decline is associated with...     

Growth-related expression of a double-stranded RNA-dependent protein kinase in 3T3 cells

Cultured mouse 3T3-F442A and 3T3-C2 fibroblasts exhibit a transient double-stranded RNA (dsRNA)-dependent phosphorylation of a 67,000-dalton protein (67K) without prior treatment with interferon (IFN). This phosphoprotein is similar but not identical to the dsRNA-dependent eukaryotic initiation factor-2 (eIF-2) alpha protein kinase (dsI), which regulates protein synthesis in rabbit reticulocytes. We have studied the relationship between cell growth and phosphorylation of the 67K protein (designated 3T3-dsRNA-dependent eIF-2 alpha kinase). A low level of dsRNA-dependent phosphorylation of 3T3-dsI was detectable in extracts prepared from cells not treated with IFN and grown at a low cell density. The phosphorylation of dsI and the phosphorylation of a 38K protein identified as the alpha-subunit (38K) of 3T3-eIF-2 (eIF-2 alpha) occurred concomitantly; the levels of these phosphorylations confluent and thereafter decreased markedly. Treatment of cells with IFN at all stages of growth resulted in an increase in phosphorylation of dsI. 3T3-F442A and 3T3-C2 fibroblasts were found to produce and secrete IFN at levels sufficient to induce an elevated dsI activity.     

A cross-talk between epithelium and endothelium mediates human alveolar–capillary injury during SARS-CoV-2 infection

COVID-19, caused by SARS-CoV-2, is an acute and rapidly developing pandemic, which leads to a global health crisis. SARS-CoV-2 primarily attacks human alveoli and causes severe lung infection and damage. To better understand the molecular basis of this disease, we sought to characterize the responses of alveolar epithelium and its adjacent microvascular endothelium to viral infection under a co-culture system. SARS-CoV-2 infection caused massive virus replication and dramatic organelles remodeling in alveolar epithelial cells, alone. While, viral infection affected endothelial cells in an indirect manner, which was mediated by infected alveolar epithelium. Proteomics analysis and TEM examinations showed viral infection caused global proteomic modulations and marked ultrastructural changes in both epithelial cells and endothelial cells under the co-culture system. In particular, viral infection elicited global protein changes and structural reorganizations across many sub-cellular compartments in epithelial cells. Among the affected organelles, mitochondrion seems to be a primary target organelle. Besides, according to EM and proteomic results, we identified Daurisoline, a potent autophagy inhibitor, could inhibit virus replication effectively in host cells. Collectively, our study revealed an unrecognized cross-talk between epithelium and endothelium, which contributed to alveolar–capillary injury during SARS-CoV-2 infection. These new findings will expand our understanding of COVID-19 and may also be helpful for targeted drug development.Subject terms: Mechanisms of disease, Viral infection     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Incorporation of biological information in cancer risk assessment: Example — Vinyl chloride

Vinyl chloride (VC) is used as an example to demonstrate how biological information can be incorporated into quantitative risk assessment. The information included is the pharmacokinetics of VC in animals and humans and the data-generated hypothesis that VC primarily affects the initiation stage of the multistage carcinogenesis. The emphasis in this paper is on the improvement of risk assessment methodology rather than the risk assessment of VC per se.Sufficient data are available to construct physiologically-based pharmacokinetic models for both animals and humans. These models are used to calculate the metabolized dose corresponding to exposure scenarios in animals and in humans.On the basis of the data on liver angiosarcomas and carcinomas in rats, the cancer risk per unit of metabolized dose is comparable, irrespective of routes (oral or inhalation) of exposure. The tumor response from an intermittent/partial lifetime exposure is shown to be consistent with that from a lifetime exposure when VC is assumed to affect the first (initiation) stage of the multistage carcinogenic process. Furthermore, the risk estimates calculated on the basis of animal data are shown to be consistent with the human experience.     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

The development of anoxia following occlusion

Following arteriolar occlusion, tissue oxygen concentration decreases and anoxic tissue eventually develops. Although anoxia first appears in the region most distal to the capillary at the venous end, it eventually spreads throughout the entire region of supply. In this paper the changing oxygen concentration, from the time of occlusion until the tissue is entirely anoxic, is examined mathematically. The equations governing oxygen transport to tissue are solved by iterating a nonlinear integral equation. This solution is valid until anoxia first appears. After anoxia develops it is necessary to solve a moving boundary problem. This is done using the method of matched asymptotic expansions, and accurate solutions are obtained for a wide range of physiological conditions.