A social learning model of conflict and cooperation in human societies

Patterns of conflict and cooperation both within and between societies may be related to the degree of cultural similarity within and between the same societies. A simple model of social learning is used to predict patterns of conflict and cooperation in hypothetical societies that differ in the roles of relatives and nonrelatives in the enculturation of children. The model is illustrated by comparing its predictions to known differences in the patterns of conflict between males inpatrilocal and matrilocal societies.     

The role of context, colour and location cues in socially learned novel food source preferences in starlings, Sternus vulgaris

Although the opportunity for errors in social learning is widely recognised, as yet little research has been directed towards understanding specific inaccuracies, biases and limitations in social learning and the mechanisms that give rise to them. In two experiments I ask how starlings, Sternus vulgaris, identify exemplars of novel feeders previously learned about socially. I find that starlings have a stronger response to feeders in the same context as that in which social learning took place, compared to identical and nonidentical feeders in a different context. Within a context that matches where social learning took place, starlings prefer feeders that show the same location and colour as the feeder demonstrated by the demonstrator starling, and show no preference when colour and location cues are dissociated. This suggests that starlings are relatively accurate social learners, since they show strong responses to novel foraging options only if they match the context, colour and location of options learned about socially, and they do so after very few trials. Furthermore, the responses of the subjects were compatible with conditioned learning-like mechanisms, which provide a useful basis for the further investigation of the origins and implications of errors in social learning.     

Free Radicals and Carcinogenesis

The role of free radicals and active states of oxygen in human cancer is as yet unresolved. Various lines of evidence provide strong but inferential evidence that free radical reactions can be of crucial importance in certain carcinogenic mechanisms. A central point in considering free radical reactions in carcinogenesis is that human cancer is really a group of highly diverse diseases for which the initial causation and the progression to clinical disease occur through a wide variety of mechanisms. Furthermore, for many human cancers it appears that there are alternate pathways capable of tumor initiation and tumor progression. While for certain of these pathways free radical reactions appear necessary, it is unlikely that there are human cancers for which free radicals, or any other mechanism, are sufficient for the entire processbeginning with the genetic alteration leading to a somatic mutation and eventually resulting in clinically overt disease. It is crucial that we view free radical reactions as aong a panoply of mechanisms leading to human cancer, and consider research about the role of free radicals in cancer as opportunities to prevent the initiation or progression of human cancer.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.     

Use of a radioimmunoassay technique to measure the titer of anti-cow-zona antibodies in marmoset monkeys

A double antibody radioimmunoassay technique is described for the measurement of anti-zona antibodies in the peripheral plasma of marmosets actively immunized against intact cow zonae pellucidae. The method has been shown to be a reliable, repeatable indicator of antibody titer, enabling direct comparison of the response obtained between marmosets. This is the first report of a procedure describing the active immunization of a primate against zona antigens, and the first time a radioimmunoassay technique has been used to monitor profiles of anti-cow zona antibody production following active immunization. The method should prove to be a useful tool in the evaluation of zona antigens as agents for immunocontraception.     

Limited proteolysis patterns of the B chain of insulin.

The oxidized B chain of insulin was used as a simple model for further consideration of limited proteolysis with low substrate:enzyme ratios. With low B chain:trypsin ratios, the ordinarily slower cleavage rate of the -Lys₂₉-Ala₃₀ bond essentially equaled the cleavage saturation rate of the -Arg₂₂-Gly₂₃ bond. This led to the disappearance of octapeptide which ordinarily forms most rapidly. Heptapeptide and alanine, formed mainly by cleavage of the octapeptide, decreased somewhat at high enzyme relative levels. Trypsin added to B chain formed a single chromatographic peak.     

Preparation of capacitor’s electrode from sunflower seed shell

Series of nanoporous carbons are prepared from sunflower seed shell (SSS) by two different strategies and used as electrode material for electrochemical double-layer capacitor (EDLC). The surface area and pore-structure of the nanoporous carbons are characterized intensively using N₂ adsorption technique. The results show that the pore-structure of the carbons is closely related to activation temperature and dosage of KOH. Electrochemical measurements show that the carbons made by impregnation-activation process have better capacitive behavior and higher capacitance retention ratio at high drain current than the carbons made by carbonization-activation process, which is due to that there are abundant macroscopic pores and less interior micropore surface in the texture of the former. More importantly, the capacitive performances of these carbons are much better than ordered mesoporous carbons and commercial wood-based active carbon, thus highlighting the success of preparing high performance electrode material for EDLC from SSS.     

Dimer–monomer equilibrium of human thymidylate synthase monitored by fluorescence resonance energy transfer

An ad hoc bioconjugation/fluorescence resonance energy transfer (FRET) assay has been designed to spectroscopically monitor the quaternary state of human thymidylate synthase dimeric protein. The approach enables the chemoselective engineering of allosteric residues while preserving the native protein functions through reversible masking of residues within the catalytic site, and is therefore suitable for activity/oligomerization dual assay screenings. It is applied to tag the two subunits of human thymidylate synthase at cysteines 43 and 43′ with an excitation energy donor/acceptor pair. The dimer–monomer equilibrium of the enzyme is then characterized through steady‐state fluorescence determination of the intersubunit resonance energy transfer efficiency.