On justifying arguments of species membership

In the debate about the moral status of human beings at the margins of life, arguments of species membership are often considered to be the least plausible ones. Against this backdrop, this article explores two possible ways to formulate feasible arguments of species membership. The first is an (in the broadest sense of the word) Aristotelian or neo-Aristotelian argument; the second is an argument from the intrinsic logic of human rights, which Robert Spaemann refers toas a ‘transcendental-pragmatic’ argument. On these grounds, the article proposes a philosophical justification for an at least moderate speciesism.     

Investigation of the chiral recognition ability of human carboxylesterase 1 using indomethacin esters

Human carboxylesterase 1 (hCES1) is an enzyme that plays an important role in hydrolysis of pharmaceuticals in the human liver. In this study, elucidation of the chiral recognition ability of hCES1 was attempted using indomethacin esters in which various chiral alcohols were introduced. Indomethacin was condensed with various chiral alcohols to synthesize indomethacin esters. The synthesized esters were hydrolyzed with a human liver microsome (HLM) solution and a human intestine microsome (HIM) solution. High hydrolytic rate and high stereoselectivity were confirmed in the hydrolysis reaction in the HLM solution but not in the HIM solution, and these indomethacin esters were thought to be hydrolyzed by hCES1. Next, these indomethacin esters were hydrolyzed in recombinant hCES1 solution and the hydrolysis rates of the esters were calculated. The stereoselectivity confirmed in HLM solution was also confirmed in the hCES1 solution. In the hydrolysis reaction of esters in which a phenyl group is bonded next to the ester, the V_max value of the (R) form was 10 times larger than that of the (S) form.     

Biochemical recognition in seeds: Germination of Rumex obtusifolius is promoted by leaves of facilitative adult conspecifics

Seeds express various germination behaviors in response to competitor plants. However, germination behaviors in response to facilitator plants are not yet well understood. Rumex obtusifolius seedlings usually appear on the ground near adult conspecific plants, and their survival rate under the canopy of adult conspecifics is higher than that outside the canopy, indicating that adult R. obtusifolius plants facilitate their seedling establishments. We hypothesized that emergence of R. obtusifolius seedlings is promoted by cues from adult conspecifics, but emergence of heterospecific seedlings is not. To test this, we investigated emergence responses of seedlings of R. obtusifolius and three other species that grow with R. obtusifolius in the presence of R. obtusifolius leaf phytochemicals. Emergence of R. obtusifolius seedlings was promoted by the presence of R. obtusifolius leaves. In contrast, emergence of other species seedlings was not promoted by R. obtusifolius leaves. We conclude that germination of R. obtusifolius seeds is facilitated in the presence of conspecifics, via water-soluble chemical exposure, and that recognizing these chemicals has adaptive value.     

Substrate binding to Src: A new perspective on tyrosine kinase substrate recognition from NMR and molecular dynamics

Most signal transduction pathways in humans are regulated by protein kinases through phosphorylation of their protein substrates. Typical eukaryotic protein kinases are of two major types: those that phosphorylate‐specific sequences containing tyrosine (~90 kinases) and those that phosphorylate either serine or threonine (~395 kinases). The highly conserved catalytic domain of protein kinases comprises a smaller N lobe and a larger C lobe separated by a cleft region lined by the activation loop. Prior studies find that protein tyrosine kinases recognize peptide substrates by binding the polypeptide chain along the C‐lobe on one side of the activation loop, while serine/threonine kinases bind their substrates in the cleft and on the side of the activation loop opposite to that of the tyrosine kinases. Substrate binding structural studies have been limited to four families of the tyrosine kinase group, and did not include Src tyrosine kinases. We examined peptide‐substrate binding to Src using paramagnetic‐relaxation‐enhancement NMR combined with molecular dynamics simulations. The results suggest Src tyrosine kinase can bind substrate positioning residues C‐terminal to the phosphoacceptor residue in an orientation similar to serine/threonine kinases, and unlike other tyrosine kinases. Mutagenesis corroborates this new perspective on tyrosine kinase substrate recognition. Rather than an evolutionary split between tyrosine and serine/threonine kinases, a change in substrate recognition may have occurred within the TK group of the human kinome. Protein tyrosine kinases have long been therapeutic targets, but many marketed drugs have deleterious off‐target effects. More accurate knowledge of substrate interactions of tyrosine kinases has the potential for improving drug selectivity.     

Positive selection and convergent evolution shape molecular phenotypic traits of innate immunity receptors in tits (Paridae)

Despite widespread variability and redundancy abounding animal immunity, little is currently known about the rate of evolutionary convergence (functionally analogous traits not inherited from a common ancestor) in host molecular adaptations to parasite selective pressures. Toll‐like receptors (TLRs) provide the molecular interface allowing hosts to recognize pathogenic structures and trigger early danger signals initiating an immune response. Using a novel combination of bioinformatic approaches, here we explore genetic variation in ligand‐binding regions of bacteria‐sensing TLR4 and TLR5 in 29 species belonging to the tit family of passerine birds (Aves: Paridae). Three out of the four consensual positively selected sites in TLR4 and six out of 14 positively selected positions in TLR5 were located on the receptor surface near the functionally important sites, and based on the phylogenetic pattern evolved in a convergent (parallel) manner. This type of evolution was also seen at one N‐glycosylation site and two positively selected phosphorylation sites, providing the first evidence of convergence in post‐translational modifications in evolutionary immunology. Finally, the overall mismatch between phylogeny and the clustering of surface charge distribution demonstrates that convergence is common in overall TLR4 and TLR5 molecular phenotypes involved in ligand binding. Our analysis did not reveal any broad ecological traits explaining the convergence observed in electrostatic potentials, suggesting that information on microbial symbionts may be needed to explain TLR evolution. Adopting state‐of‐the‐art predictive structural bionformatics, we have outlined a new broadly applicable methodological approach to estimate the functional significance of positively selected variation and test for the adaptive molecular convergence in protein‐coding polymorphisms.     

Insects and incest: Sib‐mating tolerance in natural populations of a parasitoid wasp

Sib‐mating avoidance is a pervasive behaviour that is expected to evolve in species subject to inbreeding depression. Although laboratory studies provide elegant demonstrations, small‐scaled bioassays minimize the costs of mate finding and choice, and thus may produce spurious findings. We therefore combined laboratory experiments with field observations to examine the existence of inbreeding avoidance using the parasitoid wasp Venturia canescens. In the laboratory, our approach consisted of mate‐choice experiments to assess kin discrimination in population cages with competitive interactions. A higher mating probability after sib rejections suggested that females could discriminate their sibs; however, in contrast to previous findings, sib‐mating avoidance was not observed. To compare our laboratory results to field data, we captured 241 individuals from two populations. Females laid eggs in the lab, and 226 daughters were obtained. All individuals were genotyped at 18 microsatellite loci, which allowed inference of the genotype of each female's mate and subsequently the relatedness within each mating pair. We found that the observed rate of sib‐mating did not differ from the probability that sibs encountered one another at random in the field, which is consistent with an absence of sib‐mating avoidance. In addition, we detected a weak but significant male‐biased dispersal, which could reduce encounters between sibs. We also found weak fitness costs associated with sib‐mating. As such, the sex‐biased dispersal that we found is probably sufficient to mitigate these costs. These results imply that kin discrimination has probably evolved for purposes other than mate choice, such as superparasitism avoidance.     

Limited dispersal and an unexpected aggression pattern in a native supercolonial ant

Understanding how social groups function requires studies on how individuals move across the landscape and interact with each other. Ant supercolonies are extreme cooperative units that may consist of thousands of interconnected nests, and their individuals cooperate over large spatial scales. However, the inner structure of suggested supercolonial (or unicolonial) societies has rarely been extensively studied using both genetic and behavioral analyses. We describe a dense supercolony‐like aggregation of more than 1,300 nests of the ant Formica (Coptoformica) pressilabris. We performed aggression assays and found that, while aggression levels were generally low, there was some aggression within the assumed supercolony. The occurrence of aggression increased with distance from the focal nest, in accordance with the genetically viscous population structure we observe by using 10 DNA microsatellite markers. However, the aggressive interactions do not follow any clear pattern that would allow specifying colony borders within the area. The genetic data indicate limited gene flow within and away from the supercolony. Our results show that a Formica supercolony is not necessarily a single unit but can be a more fluid mosaic of aggressive and amicable interactions instead, highlighting the need to study internest interactions in detail when describing supercolonies.     

Optimized Two-Stage Ensemble Model for Mammography Mass Recognition

ObjectivesMammography mass recognition is considered as a very challenge pattern recognition problem due to the high similarity between normal and abnormal masses. Therefore, the main objective of this study is to develop an efficient and optimized two-stage recognition model to tackle this recognition task.Material and methodsBasically, the developed recognition model combines an ensemble of linear Support Vector Machine (SVM) classifiers with a Reinforcement Learning-based Memetic Particle Swarm Optimizer (RLMPSO) as RLMPSO-SVM recognition model. RLMPSO is used to construct a two-stage of an ensemble of linear SVM classifiers by performing simultaneous SVM parameters tuning, features selection, and training instances selection. The first stage of RLMPSO-SVM recognition model is responsible about recognizing the input ROI mammography masses as normal or abnormal mass pattern. Meanwhile, the second stage of RLMPSO-SVM model used to perform further recognition for abnormal ROIs as malignant or benign masses. In order to evaluate the effectiveness of RLMPSO-SVM, a total of 1187 normal ROIs, 111 malignant ROIs, and 135 benign ROIs were randomly selected from DDSM database images.ResultsReported results indicated that RLMPSO-SVM model was able to achieve performances of 97.57% sensitivity rate with 97.86% specificity rate for normal vs. abnormal recognition cases. For malignant vs. benign recognition performance it was reported of 97.81% sensitivity rate with 96.92% specificity rate.ConclusionReported results indicated that RLMPSO-SVM recognition model is an effective tool that could assist the radiologist during the diagnosis of the presented abnormalities in mammography images. The outcomes indicated that RLMPSO-SVM significantly outperformed various SVM-based models as well as other variants of computational intelligence models including multi-layer perceptron, naive Bayes classifier, and k-nearest neighbor.