Ants resort to majority concession to reach democratic consensus in the presence of a persistent minority

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A flexible method to align large numbers of biological sequences

Summary A method for the alignment of two or more biological sequences is described. The method is a direct extension of the method of Taylor (1987) incorporating a consensus sequence approach and allows considerable freedom in the control of the clustering of the sequences. At one extreme this is equivalent to the earlier method (Taylor 1987), whereas at the other, the clustering approaches the binary method of Feng and Doolittle (1987). Such freedom allows the program to be adapted to particular problems, which has the important advantage of resulting in considerable savings in computer time, allowing very large problems to be tackled. Besides a detailed analysis of the alignment of the cytochrome c superfamily, the clustering and alignment of the PIR sequence data bank (3500 sequences approx.) is described.     

A consensus linkage map of barley

A consensus linkage map of the barley genome was constructed. The map is based on six doubled haploid and one F₂ population. The mapping data for three of the doubled haploid populations was obtained via the GrainGenes database. To allow merger of the maps, only RFLP markers that produce a single scorable band were included. Although this reduced the available markers by about half, the resultant map contains a total of 587 markers including 87 of known function. As expected, gene order was highly conserved between maps and all but two discrepancies were found in closely linked markers and are likely to result from the small population sizes used for some maps. The consensus map allows the rapid localisation of markers between published maps and should facilitate the selection of markers for high-density mapping in defined regions.     

Autophosphorylation-dependent protein kinase predominantly phosphorylates Ser115, thein vivo site in brain myelin basic protein

In a previous report [Yanget al., (1987a),J. Biol Chem. 262, 7034–7040], a cyclic-AMP- and calcium-independent brain kinase which requires autophosphorylation for activity was identified as a very potent myelin basic protein (MBP) kinase. In this report, the phosphorylation sites of MBP by this autophosphorylation-dependent protein kinase (autokinase) are further determined by two-dimensional electrophoresis/thin-layer chromatography, phosphoamino acid analysis, high-performance liquid chromatography, tryptic peptide mapping, sequential manual Edman degradation, and direct peptide sequencing. Autokinase phosphorylates MBP on both threonine and serine residues. Three major tryptic phosphopeptide peaks were resolved by C₁₈-reversed phase highper-formance liquid chromatography. Sequential manual Edman degradation together with direct sequence analysis revealed that FS(p)WGAEGQKPGFGYGGR is the phosphorylation site sequence (molar ratio 1.0) for the first major phosphopeptide peak. When mapping with bovine brain MBP sequence, we finally demonstrate Ser¹¹⁵, one of thein vivo phosphorylation sites in MBP, as the major site phosphorylated by autokinase, implicating a physiologically relevant role of autokinase in the regulation of brain myelin function. By using the same approach, we also identified HRDT(p)GILDSLGR (molar ratio 0.9) and TT(p)HYGSLPQK (molar ratio 0.8) as the major phosphorylation site sequences in³²P-MBP phosphorylated by autokinase, further indicating that -Arg-XSer/Thr-(neutral amino acid)₃-(amino acid-containing hydroxyl group such as Ser/Glu/Asp)-(neutral amino acid)₂-may represent a unique consensus sequence motif specifically recognized by this autophosphorylation-dependent multisubstrate/ multifunctional protein kinase in the brain.     

The SKS of the KMSKS signature of class I aminoacyl-tRNA synthetases corresponds to the GKT/S sequence characteristic of the ATP-binding site of many proteins

On the basis of protein modification studies and primary structure comparison, we propose that the SKS sequence within the KMSKS signature of the class 1 aminoacyl-tRNA synthetases corresponds to the GKT(or S) sequence considered as a signature of the nucleotide triphosphate-binding site of many proteins.     

Protocol for Development of American Association of Clinical Endocrinology Clinical Practice Guidelines and Consensus Statements: Summary of Methodology,Process, and Policy – 2023 Update

ObjectiveThis 2023 updated protocol summarizes the American Association of Clinical Endocrinology’s (AACE’s) new framework for the development of clinical practice guidelines and other guidance documents that includes changes to methodology, processes, and policies.MethodsAACE has critically reviewed its development processes for guidance documents over the last several years against the National Academy of Medicine Standards for Developing Trustworthy Clinical Practice Guidelines and the Council of Medical Specialty Societies Principles for Development of Specialty Society Clinical Guidelines to determine areas for improvement.ResultsThe new AACE framework for development of guidance documents incorporates many changes, including a revised conflicts of interest (COI) policy; strengthened commitment to collection of disclosures and management of relevant COI during development; open calls to membership for authors; new requirements for authors; new diversity, equity, and inclusion (DEI) policy; new empanelment process that incorporates consideration of DEI; and adoption of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to increase the quality of evidence assessment and standardize recommendation grades and statements, among other improvements.ConclusionsAACE has revised its policies and adopted a completely new methodology for guideline development in support of the mission to elevate the practice of clinical endocrinology to improve patient care. With the use of an evidence-based medicine framework and by continually assessing and improving its processes for development of guidance, AACE strives to deliver trustworthy, unbiased, and up-to-date information that ensures clinician and patient confidence in AACE content. Further, AACE hopes that these enhancements foster a more collaborative approach to development and increase engagement with the worldwide medical community to improve global health.     

Metropolis Monte Carlo calculations of DNA structure using internal coordinates and NMR distance restraints: An alternative method for generating a high-resolution solution structure

Summary A new method, a restrained Monte Carlo (rMC) calculation, is demonstrated for generating high-resolution structures of DNA oligonucleotides in solution from interproton distance restraints and bounds derived from complete relaxation matrix analysis of two-dimensional nuclear Overhauser effect (NOE) spectral peak intensities. As in the case of restrained molecular dynamics (rMD) refinement of structures, the experimental distance restraints and bounds are incorporated as a pseudo-energy term (or penalty function) into the mathematical expression for the molecular energy. However, the use of generalized helical parameters, rather than Cartesian coordinates, to define DNA conformation increases efficiency by decreasing by an order of magnitude the number of parameters needed to describe a conformation and by simplifying the potential energy profile. The Metropolis Monte Carlo method is employed to simulate an annealing process. The rMC method was applied to experimental 2D NOE data from the octamer duplex d(GTA-TAATG)·d(CATTATAC). Using starting structures from different locations in conformational space (e.g. A-DNA and B-DNA), the rMC calculations readily converged, with a root-mean-square deviation (RMSD) of <0.3 Å between structures generated using different protocols and starting structures. Theoretical 2D NOE peak intensities were calculated for the rMC-generated structures using the complete relaxation matrix program CORMA, enabling a comparison with experimental intensities via residual indices. Simulation of the vicinal proton coupling constants was carried out for the structures generated, enabling a comparison with the experimental deoxyribose ring coupling constants, which were not utilized in the structure determination in the case of the rMC simulations. Agreement with experimental 2D NOE and scalar coupling data was good in all cases. The rMC structures are quite similar to that refined by a traditional restrained MD approach (RMSD<0.5 Å) despite the different force fields used and despite the fact that MD refinement was conducted with additional restraints imposed on the endocyclic torsion angles of deoxyriboses. The computational time required for the rMC and rMD calculations is about the same. A comparison of structural parameters is made and some limitations of both methods are discussed with regard to the average nature of the experimental restraints used in the refinement.Abbreviations MC Monte Carlo - rMC restrained Monte Carlo - MD molecular dynamics - rMD restrained molecular dynamics - DG distance geometry - EM energy minimization - 2D NOE two-dimensional nuclear Overhauser effect - DQF-COSY double-quantum-filtered correlation spectroscopy - RMSD root-mean-square deviation To whom correspondence should be addressed.     

EFFECTIVE POPULATION SIZE IN A CONTINUOUSLY DISTRIBUTED POPULATION

An individual-based simulation model was created to examine genetic variability, time until fixation and spatial genetic structure in a continuously distributed population. Previous mathematical models for continuously distributed populations have the difficulty that the assumption of independent reproduction and independent dispersal of offspring cause clumped spatial distribution and thus violate an assumption of random spatial distribution. In this study, this problem is avoided by considering the dispersal behavior of offspring. The simulation results showed that the inbreeding effective population size estimated by the rate of decrease of heterozygosity during the first 15 generations corresponds to the neighborhood size calculated by the standard deviation of the dispersal distance (σ_T). This inbreeding effective population size does not greatly change with the area of simulation when the densities and σ_T are the same. However, the inbreeding effective population size estimated by heterozygosity using the first 500 generations is larger than the neighborhood size calculated by the dispersal distance and increases with the area of simulation with the same densities. The variance effective population size, estimated by time until fixation of alleles, increases with dispersal distance (σ_T) and with the area of simulation given the same densities. The inbreeding effective population size and variance effective population size were smaller than the actual population size unless σ_T is sufficiently large (2 σ_T > approximate L/2, where L is a side of the simulation square).