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.     

Sequence heterogeneity and anomalous electrophoretic mobility of kinetoplast minicircle DNA from Leishmania tarentolae

Several unit-length minicircles from the kinetoplast DNA of Leishmania tarentolae were cloned into pBR322 and into M13 phage vectors. The complete nucleotide sequences of three different partially homologous minicircles were obtained. The molecules contained a region of approx. 80% sequence homology extending for 160–270 bp and a region unique to each minicircle. A 14-mer was found to be conserved in all kinetoplast minicircle sequences reported to date. The frequency distributions of various minicircle sequence classes in L. tarentolae were obtained by quantitative gel electrophoresis and by examination of the “T ladder” patterns of minicircles randomly cloned into M13 at several sites. By these methods we could assign approx. 50% of the total minicircle DNA into a minimum of five sequence classes. A sequence-dependent polyacrylamide gel migration abnormality was observed with several minicircle fragments both cloned and uncloned. The abnormality was dependent on the presence of a portion of the conserved region of the minicircle.     

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.     

MODY 2: Mutation identification and molecular ancestry in a Brazilian family

Maturity Onset Diabetes of the Young (MODY) is a heterogeneous group of genetic diseases characterized by a primary defect in insulin secretion and hyperglycemia, non-ketotic disease, monogenic autosomal dominant mode of inheritance, age at onset less than 25 years, and lack of auto-antibodies. It accounts for 2–5% of all cases of non-type 1 diabetes. MODY subtype 2 is caused by mutations in the glucokinase (GCK) gene. In this study, we sequenced the GCK gene of two volunteers with clinical diagnosis for MODY2 and we were able to identify four mutations including one for a premature stop codon (c.76C>T). Based on these results, we have developed a specific PCR-RFLP assay to detect this mutation and tested 122 related volunteers from the same family. This mutation in the GCK gene was detected in 21 additional subjects who also had the clinical features of this genetic disease. In conclusion, we identified new GCK gene mutations in a Brazilian family of Italian descendance, with one due to a premature stop codon located in the second exon of the gene. We also developed a specific assay that is fast, cheap and reliable to detect this mutation. Finally, we built a molecular ancestry model based on our results for the migration of individuals carrying this genetic mutation from Northern Italy to Brazil.     

Structure-wise discrimination of adenine and guanine by proteins on the basis of their nonbonded interactions

We have analyzed the nonbonded interactions of the structurally similar moieties, adenine and guanine forming complexes with proteins. The results comprise (a) the amino acid–ligand atom preferences, (b) solvent accessibility of ligand atoms before and after complex formation with proteins, and (c) preferred amino acid residue atoms involved in the interactions. We have observed that the amino acid preferences involved in the hydrogen bonding interactions vary for adenine and guanine. The structural variation between the purine atoms is clearly reflected by their burial tendency in the solvent environment. Correlation of the mean amino acid preference values show the variation that exists between adenine and guanine preferences of all the amino acid residues. All our observations provide evidence for the discriminating nature of the proteins in recognizing adenine and guanine.     

The Mechanism of Supercoiled DNA Recognition by Eukaryotic Type I Topoisomerases: II. A Comparison of the Enzyme Interaction with Specific and Nonspecific Oligonucleotides

Data on the interaction of DNA type I topoisomerases from the murine and human placenta cells with specific and nonspecific oligonucleotides of various structures and lengths are summarized. The relative contributions of various contacts between the enzymes and DNA that have previously been detected by X-ray analysis to the total affinity of the topoisomerases for DNA substrates are estimated. Factors that determine the differences in the enzyme interactions with specific and nonspecific single- and double-stranded DNAs are revealed. The results of the X-ray analysis of human DNA topoisomerase I are interpreted taking into account data on the comprehensive thermodynamic and kinetic analysis of the enzyme interaction with the specific and nonspecific DNAs.     

The role of nutrition on epigenetic modifications and their implications on health

Nutrition plays a key role in many aspects of health and dietary imbalances are major determinants of chronic diseases including cardiovascular disease, obesity, diabetes and cancer. Adequate nutrition is particularly essential during critical periods in early life (both pre- and postnatal). In this regard, there is extensive epidemiologic and experimental data showing that early sub-optimal nutrition can have health consequences several decades later.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

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.