Genome-wide comparative analysis of the codon usage patterns in plants

Codon usage analysis has been a classical area of study for decades and is important for evolution, mRNA translation, and new gene discovery. Recently, genome sequencing has made it possible to perform studies of the entire genome in plant kingdoms. The base composition of the coding sequence, codon usage pattern, codon pairs, and related indicators of relative synonymous codon usage (RSCU), including the Fop, Nc, RSCU, CAI and GC contents, were analyzed. We found that the GC content of single-celled algae is the highest, whereas dicotyledons are the lowest. Moreover, the base composition of plants is similar within the same family. In addition, the GC content of the second base of the codon is lower than the first and third base. In conclusion, the codon usage characteristics are opposite in Gramineae, single-celled algae, fern and dicotyledon, moss, and Pinaceae. Furthermore, the degree of codon usage bias is decreasing with evolution. Therefore, we hypothesize that the lower the plants, the more that they must optimize codons and that higher plants no longer need to optimize codons.     

Tim-3 Is Upregulated in NK Cells during Early Pregnancy and Inhibits NK Cytotoxicity toward Trophoblast in Galectin-9 Dependent Pathway

NK cells accumulate at the maternal-fetal interface (MFI) and play essential roles in maintaining immune tolerance during pregnancy. The mechanisms that facilitate NK cells tolerance to fetal tissue are largely unknown. T cell Ig and mucin domain-containing protein 3 (Tim-3) is a newly defined molecule with essential immunological function in many physiological and pathological processes. Recent study showed that Tim-3 was involved in the regulation of immune tolerance at MFI. However, whether Tim-3 regulates NK cells cytotoxicity toward trophoblasts is unclear. Here, we showed Tim-3 was mainly expressed by decidual NK cells (dNK) and Tim-3 level in dNK was higher than peripheral NK cells (pNK). Tim-3⁺ dNK expressed more levels of mature markers CD94 and CD69 than Tim-3^- dNK cells and blocking Tim-3 significantly inhibited dNK IFN-γ and TNF-α secretion. Furthermore, we found TGF-β1 may contribute to such up-regulation of Tim-3 in NK cells. Interestingly, blocking Tim-3 enhanced NK cytotoxicity toward trophoblast cell line HTR-8 but not K562. We found HTR-8 expressed Tim-3 ligand Galectin-9, in contrast K562 did not. Small interfering RNA-mediated silencing of Galectin-9 expression enhanced NK cytotoxicity toward HTR-8. We further showed Tim-3/Galecin-9 inhibited NK cytotoxicity toward trophoblast partially via impairing the degranulation process. In addition, clinical data showed that abnormal Tim-3 level on pNK might be associated with recurrent spontaneous abortion (RSA). Thus, our data demonstrate Tim-3/Galectin-9 pathway maintains local tolerance by suppressing NK cytotoxicity toward trophoblasts which may represent a new immunologic tolerance mechanism at MFI.     

Monocyte Trafficking,Engraftment, and Delivery of Nanoparticles and an Exogenous Gene into the Acutely Inflamed Brain Tissue – Evaluations on Monocyte-Based Delivery System for the Central Nervous System

The ability of monocytes and monocyte-derived macrophages (MDM) to travel towards chemotactic gradient, traverse tissue barriers, and accumulate precisely at diseased sites makes them attractive candidates as drug carriers and therapeutic gene delivery vehicles targeting the brain, where treatments are often hampered by the blockade of the blood brain barrier (BBB). This study was designed to fully establish an optimized cell-based delivery system using monocytes and MDM, by evaluating their homing efficiency, engraftment potential, as well as carriage and delivery ability to transport nano-scaled particles and exogenous genes into the brain, following the non-invasive intravenous (IV) cell adoptive transfer in an acute neuroinflammation mouse model induced by intracranial injection of Escherichia coli lipopolysaccharides. We demonstrated that freshly isolated monocytes had superior inflamed-brain homing ability over MDM cultured in the presence of macrophage colony stimulating factor. In addition, brain trafficking of IV infused monocytes was positively correlated with the number of adoptive transferred cells, and could be further enhanced by transient disruption of the BBB with IV administration of Mannitol, Bradykinin or Serotonin right before cell infusion. A small portion of transmigrated cells was detected to differentiate into IBA-1 positive cells with microglia morphology in the brain. Finally, with the use of superparamagnetic iron oxide nanoparticles SHP30, the ability of nanoscale agent-carriage monocytes to enter the inflamed brain region was validated. In addition, lentiviral vector DHIV-101 was used to introduce green fluorescent protein (GFP) gene into monocytes, and the exogenous GFP gene was detected in the brain at 48 hours following IV infusion of the transduced monocytes. All together, our study has set up the optimized conditions for the more-in-depth tests and development of monocyte-mediated delivery, and our data supported the notion to use monocytes as a non-invasive cell-based delivery system for the brain.     

Turing learning: a metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for ‘tricking’ the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product—the classifiers—that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.     

Rapid method for protein quantitation by Bradford assay after elimination of the interference of polysorbate 80

Bradford assay is one of the most common methods for measuring protein concentrations. However, some pharmaceutical excipients, such as detergents, interfere with Bradford assay even at low concentrations. Protein precipitation can be used to overcome sample incompatibility with protein quantitation. But the rate of protein recovery caused by acetone precipitation is only about 70%. In this study, we found that sucrose not only could increase the rate of protein recovery after 1 h acetone precipitation, but also did not interfere with Bradford assay. So we developed a method for rapid protein quantitation in protein drugs even if they contained interfering substances.     

Graphene quantum dots as additives in capillary electrophoresis for separation cinnamic acid and its derivatives

A facile capillary electrophoresis (CE) method for the separation of cinnamic acid and its derivatives (3,4-dimethoxycinnamic acid, 4-methoxycinnamic acid, isoferulic acid, sinapic acid, cinnamic acid, ferulic acid, and trans-4-hydroxycinnamic acid) using graphene quantum dots (GQDs) as additives with direct ultraviolet (UV) detection is reported. GQDs were synthesized by chemical oxidization and further purified by a macroporous resin column to remove salts (Na₂SO₄ and NaNO₃) and other impurities. Transmission electron microscopy (TEM) indicated that GQDs have a relatively uniform particle size (2.3 nm). Taking into account the structural features of GQDs, cinnamic acid and its derivatives were adopted as model compounds to investigate whether GQDs can be used to improve CE separations. The separation performance of GQDs used as additives in CE was studied through variations of pH, concentration of the background electrolyte (BGE), and contents of GQDs. The results indicated that excellent separation can be achieved in less than 18 min, which is mainly attributed to the interaction between the analytes and GQDs, especially isoferulic acid, sinapic acid, and cinnamic acid.