Patterns Of Selection Research Articles

Climate change reduces the tension of conflicting selection pressures on breeding date in a passerine bird.

Unpredictably fluctuating environments create complex selective landscapes that shape the distribution of key life history traits. Identifying the mechanisms behind dynamic patterns of selection is difficult, yet essential for predicting responses to climate change. We combine long-term measures with field manipulation of natural selection on breeding date in a wild bird to investigate whether highly variable spring cold snaps drive fluctuating selection. We show that variation in cold snap intensity leads to fluctuating selection on breeding date-in weak cold snap years, selection was consistently negative; however, in strong cold snap years, its direction reversed. These patterns were mirrored in a field experiment; nests that were food supplemented during cold snaps avoided cold snap mortality leading earlier breeders to have higher fitness. In contrast, in the non-supplemented group earlier breeders had higher cold snap nest mortality and selection was positive. Using nearly a century of climate data, we show that cold snaps are becoming less frequent and paradoxically occurring later which should allow earlier breeders to avoid them, potentially releasing conflicting selection pressures and facilitating a rapid phenological shift. Thus, rather than constraining a species' ability to adapt, climate change can enable a rapid shift to a new phenotypic optimum.

Preamble Design and Detection Based on Sequence Selection Pattern for Random Access in Non-Terrestrial Networks

Preamble Design and Detection Based on Sequence Selection Pattern for Random Access in Non-Terrestrial Networks

Seasonal and anthropogenic effects on niche overlap and habitat selection by sympatric bears (Ursus arctos marsicanus) and wolves (Canis lupus) in a human-dominated landscape.

Interspecific interactions among species of the same guild play a critical role in shaping their realized niches, and their understanding may disclose mechanisms of coexistence. Investigating interactions among apex predators is of ecological and management interest, especially in human-dominated landscapes where type and intensity of their interspecific competition may be affected by human interference. During 2005-2010, we investigated, by means of GPS-telemetry, interactions between brown bears (n = 19) and wolves (n = 7) in a long-established national park in the central Apennines, Italy, where bears and wolves have always coexisted close to humans. Based on a K-select analysis and a randomization approach, we assessed the extent of overlap between the species' niches on a seasonal basis. Bears and wolves clearly segregated in fall but not during summer when overlap between their realized niches suggests a convergent adaptation to a seasonal peak of anthropogenic pressure. However, using multi-species resource selection functions (RSFs) at the home range level (i.e., third-order selection), we revealed that habitat selection by bears and wolves was reciprocally affected also when their niches overlapped, possibly disclosing mechanisms of fine-scale resource partitioning. In early summer, bears selected areas with a high probability of resource selection by wolves, but in late summer avoided areas positively selected by wolves. On the contrary, wolves avoided areas where the probability of resource selection by bears was high, both in late summer and fall. These results indicate that bears and wolves do interact in our study area and, although the actual behavioral mechanisms are unknown, they reciprocally and asymmetrically affect their realized niche and habitat selection patterns. Further research is needed to better understand how anthropogenic factors impact intraguild interactions and what are the effects at the population and community levels.

Trends in enrolment and academic performance of scheduled tribe students at the undergraduate level in Assam: A decadal analysis

This research work examines the enrolment and performance pattern of the Scheduled Tribe (ST) students at the undergraduate level in Assam for the period of 2012-2022. Based on the enrolment data collected from various ST students, the study examines the gender pattern and course selection of students in different disciplines such as B.A., B.Com., and B.Sc. The study reveals major trends in enrolment increase, gender distribution, and course choices for the decade. Using chi-square tests and comparative performance measures, the study reveals factors that affect academic performance and enrolment. Furthermore, bar graphs and line charts are used to present these trends and to give further analysis. The conclusion of this study provides significant implications for the policymakers and educators who are interested in improving the educational access and opportunities for ST students in the higher education in Assam.

How does urbanization affect natural selection?

Abstract Urbanization is one of the most significant contributors to the Anthropocene, and urban evolutionary ecology has become an important field of research. While it is commonly assumed that cities impose new and stronger selection, the contradictory assertion that selection may be relaxed in cities is also frequently mentioned, and overall, our understanding of the effects of urbanization on natural selection is incomplete. In this review, we first conduct a literature search to find evidence for patterns of natural selection on phenotypic traits including morphology, physiology, behaviour and life history, in urban and non‐urban populations of animals and plants. This search reveals that coefficients of natural selection in the context of urbanization are scarce (n = 8 studies providing selection gradients/differentials that include a total of n = 200 coefficients) and a lack of standardized methods hinders quantitative comparisons across studies (e.g. with meta‐analysis). These studies, however, provide interesting insight on the agents shaping natural selection in cities and improve our mechanistic understanding of selection processes at different spatial scales. We then perform a second literature search to review genomic studies assessing selection intensity in cities, on the genome of non‐human natural populations. While this search returns 383 articles, only 34 of these truly investigate footprints of selection associated with urbanization, and only one study provides urban genetic selection coefficients. Here again, we find highly heterogeneous approaches, yet some studies provide strong evidence of genomic footprints of urban adaptation. In neither the phenotypic nor genomic literature review were we able to quantitatively assess natural selection across urban versus non‐urban habitats. Thus, we propose a roadmap of how future studies should provide standardized metrics to facilitate mega‐ or meta‐analyses and explore generalized effects of urbanization on selection. Read the free Plain Language Summary for this article on the Journal blog.

Estimation of Cotton SPAD Based on Multi-Source Feature Fusion and Voting Regression Ensemble Learning in Intercropping Pattern of Cotton and Soybean

The accurate estimation of soil plant analytical development (SPAD) values in cotton under various intercropping patterns with soybean is crucial for monitoring cotton growth and determining a suitable intercropping pattern. In this study, we utilized an unmanned aerial vehicle (UAV) to capture visible (RGB) and multispectral (MS) data of cotton at the bud stage, early flowering stage, and full flowering stage in a cotton–soybean intercropping pattern in the Yellow River Delta region of China, and we used SPAD502 Plus and tapeline to collect SPAD and cotton plant height (CH) data of the cotton canopy, respectively. We analyzed the differences in cotton SPAD and CH under different intercropping ratio patterns. It was conducted using Pearson correlation analysis between the RGB features, MS features, and cotton SPAD, then the recursive feature elimination (RFE) method was employed to select image features. Seven feature sets including MS features (five vegetation indices + five texture features), RGB features (five vegetation indices + cotton cover), and CH, as well as combinations of these three types of features with each other, were established. Voting regression (VR) ensemble learning was proposed for estimating cotton SPAD and compared with the performances of three models: random forest regression (RFR), gradient boosting regression (GBR), and support vector regression (SVR). The optimal model was then used to estimate and visualize cotton SPAD under different intercropping patterns. The results were as follows: (1) There was little difference in the mean value of SPAD or CH under different intercropping patterns; a significant positive correlation existed between CH and SPAD throughout the entire growth period. (2) All VR models were optimal when each of the seven feature sets were used as input. When the features set was MS + RGB, the determination coefficient (R2) of the validation set of the VR model was 0.902, the root mean square error (RMSE) was 1.599, and the relative prediction deviation (RPD) was 3.24. (3) When the features set was CH + MS + RGB, the accuracy of the VR model was further improved, compared with the feature set MS + RGB, the R2 and RPD were increased by 1.55% and 8.95%, respectively, and the RMSE was decreased by 7.38%. (4) In the intercropping of cotton and soybean, cotton growing under 4:6 planting patterns was better. The results can provide a reference for the selection of intercropping patterns and the estimation of cotton SPAD.

Adaptive QP algorithm for depth range prediction and encoding output in virtual reality video encoding process.

In order to reduce the encoding complexity and stream size, improve the encoding performance and further improve the compression performance, the depth prediction partition encoding is studied in this paper. In terms of pattern selection strategy, optimization analysis is carried out based on fast strategic decision-making methods to ensure the comprehensiveness of data processing. In the design of adaptive strategies, different adaptive quantization parameter adjustment strategies are adopted for the equatorial and polar regions by considering the different levels of user attention in 360 degree virtual reality videos. The purpose is to achieve the optimal balance between distortion and stream size, thereby managing the output stream size while maintaining video quality. The results showed that this strategy achieved a maximum reduction of 2.92% in bit rate and an average reduction of 1.76%. The average coding time could be saved by 39.28%, and the average reconstruction quality was 0.043, with almost no quality loss detected by the audience. At the same time, the model demonstrated excellent performance in sequences of 4K, 6K, and 8K. The proposed deep partitioning adaptive strategy has significant improvements in video encoding quality and efficiency, which can improve encoding efficiency while ensuring video quality.

Naivety dies with the calf: calf loss to human hunters imposes behavioral change in a long-lived but heavily harvested ungulate

BackgroundIn prey, patterns of individual habitat selection and movement can be a consequence of an individuals’ anti-predator behavior. Adjustments of anti-predator behavior are important for prey to increase their survival. Hunters may alter the anti-predator behavior of prey. In long-lived animals, experience may cause behavioral changes during individuals’ lifetime, which may result in altered habitat selection and movement. Our knowledge of which specific events related to hunting activity induce behavioral changes in solitary living species is still limited.MethodsWe used offspring loss in a solitary and long-lived ungulate species, moose (Alces alces), as our model system. We investigated whether offspring loss to hunters induces behavioral changes in a species subjected to heavy human harvest but free from natural predation. To test for behavioral change in relation to two proxies for experience (calf fate and age), we combined movement data from 51 adult female moose with data on their offspring survival and female age. We tested for adjustments in females’ habitat selection and movement following calf harvest using Hidden Markov Models and integrated Step Selection Analysis to obtain behavioral state specific habitat selection coefficients.ResultsWe found that females with a harvested calf modified habitat selection and movement during the following hunting season. Female moose selected for shorter distance to roads during the night, selected for shorter distance to forests and greater distance to human settlements following calf harvest than females who had not lost a calf. The survival of twins in a given hunting season was related to female age. Older females we more likely to have twins survive the hunting season.ConclusionsOur findings suggest that losing offspring to human harvest imposes behavioral changes in a long-lived ungulate species, leading to adjustments in females' habitat selection and movement behavior, which may lower the risk of encountering hunters. In our study, female moose that experienced calf loss selected for lower distance to forest and selected for greater distance to human settlements during periods of high hunting pressure compared to females without the experience of calf loss during the previous hunting season. We interpret this as potential learning effects.

Data Envelopment Analysis-based Scenario Selection for Sequencing Pattern in a Simulated Robotic Cell

In this study, the performance of suggested scenarios for part input sequences in a 3-machine robotic cell producing different parts is determined through the application of data envelopment analysis (DEA) and the Banker–Charnes–Cooper model. A single gripper robot supports the manufacturing process by loading and unloading products and moving them inside the system. This study addresses random machine failures and repairs to minimize cycle time based on two robot move cycles in a three-machine robotic cell and overall production costs. Here, simulation assists in the modeling of uncertainty and a simulation-based optimization approach is applied to find the best scenarios for sequencing patterns in the cell through several numerical examples using DEA. The results displayed that, efficient scenarios satisfying minimum time and cost, are those, in which the percentages of operations assigned to the machines are close to each other. This enables decision-makers in manufacturing systems to make precise selections of the optimal part sequencing pattern with the lowest production cost and cycle time for robotic cells.

Pattern dynamics in a predator–prey model with Smith growth function and prey refuge in predator poisoned environment

In this article, we investigate temporal as well as spatiotemporal dynamics of a predator–prey system where prey grows according to Smith growth function and prey refuges in predator poisoned environment. Self as well as cross diffusion are taken into consideration to describe spatial moment of the species which make the system more realistic. This study aims to investigate the role of prey refuge, toxin-carrying carcass and the impact of cross-diffusion on the spatial distribution of species densities and associated patterns. The existence of equilibria and their stability conditions for non-spatial system are derived. We discuss the occurrence of Hopf bifurcation and detect the stability of limit cycle by computing first Lyapunov number. Temporal dynamics of the system is studied by varying the significant parameters. Study reveals that both prey refuge and fatality rate of predator due to toxin-carrying carcass, initially makes the system stable for low refuge and fatality rate but predator population goes to extinction as those effects increase. Turing instability conditions are listed and different instability regions so formed are discussed. In Turing region, pattern selection with the help of amplitude equation via weakly nonlinear analysis are performed which also numerically supported. Intensity of refuge and fatality rate due to toxin carrying carcass result paradox with real ecological world due to the presence of cross diffusion. Various kind of patterns such as mixture of stripe and spot, spot, irregular chaotic patterns emerge due to Hopf and Turing instability. Particularly, spatiotemporal chaos is a controversial topic because of its significant consequences for population dynamics. The results of this work are expected to contribute to a better understanding the level of prey refuge, use of toxin-carrying carcass considering movement in population and effect of cross-diffusion.

Linking divergence in phenotypic selection on floral traits to divergence in local pollinator assemblages in a pollination-generalized plant.

Divergent patterns of phenotypic selection on floral traits can arise in response to interactions with functionally distinct pollinators. However, there are a limited number of studies that relate patterns of phenotypic selection on floral traits to variation in local pollinator assemblages in pollination-generalized plant species. We studied phenotypic selection on floral traits of Viscaria vulgaris, a plant that interacts with a broad range of diurnal and nocturnal pollinators, and related divergence in phenotypic selection on floral traits to the expected level of divergence in local pollinator assemblages. We detected phenotypic selection on floral traits involved in the attraction of pollinators and the mechanics of pollen removal and deposition, and demonstrated that floral traits are subject to spatiotemporal variation in the strength and direction of phenotypic selection. We revealed that diurnal and nocturnal pollinators, when considered in isolation, mediated divergent patterns of phenotypic selection on floral traits. Consistent with the Grant-Stebbins model, we observed that divergence in phenotypic selection on floral traits increased with the expected level of divergence in local pollinator assemblages. Thus, generalized plant-pollinator interactions can mediate phenotypic selection on floral traits and distinct local pollinator assemblages can generate a geographic mosaic of divergent patterns of phenotypic selection. We underscore that these outcomes are not exclusive to specialized plant-pollinator interactions and can emerge at a local geographic scale.

Seeking a multi‐dimensional approach to understand agricultural commodity expansion in Asian tropics

AbstractAgricultural commodity expansion into natural and semi‐natural ecosystems in Asia is a multi‐dimensional sustainability challenge posing a threat to natural and human capital. At the symposium pertaining to agricultural commodity landscapes organized at the 59th meeting of the Association for Tropical Biology and Conservation, we aimed to identify key aspects that require further attention to address the negative impacts of commodity‐driven agricultural expansion in the Asian tropics. Using a combination of insights obtained both from participants' research and those that developed organically in the symposium, we identified five key themes: (1) Robust land use suitability assessments to determine the viability of agricultural expansion or other competing demands on productive land in given landscapes; (2) the need for plot‐level studies of soil biodiversity and ecological functions for commodity crops; (3) Irrigation for commodity crops with blue and green water and evaluating co‐dependent drivers and outcomes; (4) an improved understanding of local producer motivations and supply chains and (5) the analysis of co‐benefits, trade‐offs and synergies in agro‐commodity systems. These themes include the various steps involved in agricultural commodity expansion, right from land selection and crop patterns to aspects pertaining to the post‐harvest value chain. These themes are inter‐connected and span across multiple local and regional spatial scales in tropical Asia but hold relevance to agricultural landscapes elsewhere too. Immediate and sustained attention on these themes would secure multiple goals of sustainable land use, biodiversity conservation, climate change mitigation and human well‐being.

Sensitive Coatings Based on Molecular-Imprinted Polymers for Triazine Pesticides' Detection.

Triazine pesticide (atrazine and its derivatives) detection sensors have been developed to thoroughly check for the presence of these chemicals and ultimately prevent their exposure to humans. Sensitive coatings were designed by utilizing molecular imprinting technology, which aims to create artificial receptors for the detection of chlorotriazine pesticides with gravimetric transducers. Initially, imprinted polymers were developed, using acrylate and methacrylate monomers containing hydrophilic and hydrophobic side chains, specifically for atrazine, which shares a basic heterocyclic triazine structure with its structural analogs. By adjusting the ratio of the acid to the cross-linker and introducing acrylate ester as a copolymer, optimal non-covalent interactions were achieved with the hydrophobic core of triazine molecules and their amino groups. A maximum sensor response of 546 Hz (frequency shift/layer height equal to 87.36) was observed for a sensitive coating composed of 46% methacrylic acid and 54% ethylene glycol dimethacrylate, with a demonstrated layer height of 250 nm (6.25 kHz). The molecularly imprinted copolymer demonstrated fully reversible sensor responses, not only for atrazine but also for its metabolites, like des-ethyl atrazine, and structural analogs, such as propazine and terbuthylazine. The efficiency of modified molecularly imprinted polymers for targeted analytes was tested by combining them with a universally applicable quartz crystal microbalance transducer. The stable selectivity pattern of the developed sensor provides an excellent basis for a pattern recognition procedure.

Geometrical incompatibility regulated pattern selection and morphological evolution in growing spherical soft tissues

Surface morphological patterns are widely observed in natural systems, which are closely correlated to vital biological functions and inspire surface morphology designs in soft matter systems. Geometrical incompatibility widely exists in biological tissues across different length scales and plays an important role in growth-induced pattern selection and morphological evolution of soft tissues. However, the underlying physical mechanism of growth-induced pattern formation and post-buckling evolution in geometrically incompatible spherical soft tissues remain elusive. Here, the effect of geometrical incompatibility on the growth-induced pattern selection and post-buckling evolution are investigated through swelling experiment, theoretical analysis and numerical simulation. The results show that not only the instability pattern but also the instability threshold can be regulated by manipulating geometric incompatibility. Notably, when the geometrical incompatibility parameter exceeds a critical value, spontaneous instability is observed before growth. With continuous growth, the core–shell soft sphere buckles into a periodic buckyball pattern and evolves toward a bean-shaped pattern, and then undergoes a wrinkle-to-fold transition into a labyrinth topography. Our results demonstrate, both experimentally and theoretically, that geometrical incompatibility can guide the growth-induced pattern formation and morphological evolution effectively. This study not only enhances our understanding of the growth-induced pattern selection and morphological evolution in spherical soft tissues, but also provides an inspiring insight for the fabrication of morphological patterns on curved surfaces.

Positive Selection Drives the Evolution of the Structural Maintenance of Chromosomes (SMC) Complexes.

Structural Maintenance of Chromosomes (SMC) complexes are an evolutionary conserved protein family. In most eukaryotes, three SMC complexes have been characterized, as follows: cohesin, condensin, and SMC5/6 complexes. These complexes are involved in a plethora of functions, and defects in SMC genes can lead to an increased risk of chromosomal abnormalities, infertility, and cancer. To investigate the evolution of SMC complex genes in mammals, we analyzed their selective patterns in an extended phylogeny. Signals of positive selection were identified for condensin NCAPG, for two SMC5/6 complex genes (SMC5 and NSMCE4A), and for all cohesin genes with almost exclusive meiotic expression (RAD21L1, REC8, SMC1B, and STAG3). For the latter, evolutionary rates correlate with expression during female meiosis, and most positively selected sites fall in intrinsically disordered regions (IDRs). Our results support growing evidence that IDRs are fast evolving, and that they most likely contribute to adaptation through modulation of phase separation. We suggest that the natural selection signals identified in SMC complexes may be the result of different selective pressures: a host-pathogen arms race in the condensin and SMC5/6 complexes, and an intragenomic conflict for meiotic cohesin genes that is similar to that described for centromeres and telomeres.

Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from decade-spanning reciprocal transplants.

Sympatric species are often locally adapted to distinct microhabitats. However, temporal variation may cause local maladaptation and species boundary breakdown, especially during extreme climatic events leading to episodic selection. Repeated reciprocal transplants can reveal the interplay between short and long-term patterns of natural selection. To examine evolutionary trajectories of sympatric Monkeyflowers adapted to different niches, Mimulus guttatus and M. laciniatus, we performed three replicated transplants and combined them with previous experiments to leverage a dataset of five transplants spanning 10 years. We performed phenotypic selection analyses on parents and hybrids in parental habitats in Yosemite NP, CA during years of drastically differing snowpack. If there is ecological isolation, then we predicted divergent phenotypic selection between habitats in line with species' differences and local adaptation. We found interannual fluctuations in phenotypic selection, often in unpredicted directions. However, a combined-year analysis detected longer-term divergent selection on flowering time, a key temporally isolating and adaptative trait, suggesting that selection may reinforce species boundaries despite short-term fluctuations. Finally, we found temporal variation in local adaptation with M. laciniatus locally adapted in low snowpack years, while an extremely high snowpack year contributed to average local maladaptation of M. guttatus.

Management of retinal diseases, therapeutic association between ophthalmology and endocrinology in the treatment of diabetic retinopathy

Introduction: Effective management of retinal diseases, especially diabetic retinopathy, is crucial for preventing severe visual complications. Collaboration between ophthalmologists and endocrinologists plays a fundamental role in the effective treatment of this condition, aiming to preserve vision and improve patients' quality of life. Methods: A bibliographic review was conducted to understand the management of retinal diseases and the therapeutic association between ophthalmology and endocrinology in the treatment of diabetic retinopathy. We used databases such as MEDLINE, PubMed, and Scielo to identify relevant articles published in the last 20 years. Inclusion and exclusion criteria were defined to ensure the selection of pertinent studies. Results: After the search and selection of articles, patterns and trends in the management of diabetic retinopathy were identified. A variety of treatment options were located, including laser photocoagulation, intravitreal injections of medications, and vitreoretinal surgery. The importance of metabolic control of diabetes to prevent retinal damage was noted. The analysis of the studies also highlighted that the interaction between these specialties ensures better clinical outcomes. Conclusion: The importance of collaboration between ophthalmologists and endocrinologists in the management of diabetic retinopathy is reinforced. An integrated approach that considers both ophthalmological and endocrinological aspects of the disease is essential to provide effective care to patients. This cooperation can result in better visual outcomes and quality of life for those affected by diabetic retinopathy.

Evolutionary selection and morphological integration in the hand of modern humans.

To enhance our understanding of the evolutionary dynamics of the modern human hand by analyzing the degree of integration and ability to respond to selection pressures of each phalanx and metacarpal bone. The sample comprised 96 adult individuals, both female and male, from Euro-American, Afro-American, and European populations. We collected 10 linear measurements from the 19 metacarpals and proximal, middle, and distal phalanges that constitute the five digits of the hand. Using these data, we constructed variance/covariance matrices to quantify the degree of integration and assess the hand ability to respond to selective pressures. Distal phalanges are the most evolvable and flexible elements, while being the least integrated and constrained. The thumb is similarly integrated as the second and third rays, while medial rays (fourth and fifth digits) are more integrated. However, the thumb presents different integration and response to selection patterns. No significant relationship was found between functionality and the indices of selection and integration. Finally, the correlation between hand and foot indices yielded significant results for conditional evolvability and flexibility. The findings suggest different evolutionary trajectories for the metacarpal and distal phalanx in the modern human thumb, likely reflecting varying functional and developmental pressures. The first metacarpal, characterized by high flexibility and low evolvability, appears to have reached a stable, optimal morphology, under stabilizing selection. In contrast, the distal phalanx seems to have undergone directional evolution, suggesting specialization for a specific function. Comparisons between hands and feet suggest that these structures evolve differently under directional selection but similarly under stabilizing selection.

Fracture strain improving via structural austenitic stainless steel-coated 22MnB5 plates

A total of 316 austenitic stainless steel (ASS) coatings were deposited on 22MnB5 press-hardening steel plates by varying the substrate bias voltages using a magnetron sputtering technique and quenched in a flat mold with cooling water. The substrate bias current and ion-bombardment energy densities increased up to 0.5 mA/mm2 and 50 J/mm2 at a high voltage of −100 V, and, therefore, the variations in the coatings’ morphologies were owing to the increases in the ion bombardment. The porous bulk pattern appeared in the quenched ASS coating at −100 V, clearly different from the porous columnar structure of the others at −50 and −75 V. The γ-Fe and α-Fe phases were observed from the diffraction peaks, presented the ASS coating and 22MnB5 substrate, respectively. There was no intermetallic compound (IMC) peak detected. In addition, the diffusion layer of the quenched ASS-coated plate was observed, in which its morphology was different from the quenched martensite (M) plate, and proved to be the α-Fe microstructure by the very low α-Fe peak at the standard (110) position. The bright image of TEM and the select area electron diffraction pattern indicated the nanostructure of the quenched ASS coating. The nanohardness of the ASS coating, diffusion layer, and M plate (7.36, 3.60, and 6.25 GPa, respectively) was detected, indirectly proving an α-Fe structure of the diffusion layer. The fracture angles of the 316-coated plates significantly improved from 51.82° at −50 V, 53.77° at −75 V to 57.38° at −100 V, as the ASS structure changed to be porous bulk pattern. The clearance of IMC, coating’s porous bulk pattern, and the low hardness α-Fe diffusion layer benefited for the fracture strain by lengthening the pathway of the crack’s development and blocking the further crack’s propagation, respectively.

Mitochondrial genomes of Macropsini (Hemiptera: Cicadellidae: Eurymelinae): Structural features, codon usage patterns, and phylogenetic implications.

Macropsini is a tribe of Eurymelinae in the family Cicadellidae that is widely distributed worldwide. Still, its taxonomic status has been unstable, and the classification of certain clades at the genus level has been controversial. The aim of this study is to address the patterns and processes that explain the structure and the evolution of the mitogenomes of Macropsini, while contributing to the resolution of systematic issues involving five of their genera. To this task, the mitogenomes of 26 species of the tribe were sequenced and characterized, and their phylogenetic relationships were reconstructed. The results revealed that the nucleotide composition of mitochondrial genes in these 26 species was significantly skewed toward A and T. Codons ending with T or A in relative synonymous codon usage were significantly more prevalent than those ending with C or G. The parity plot, neutrality plot, and correspondence analysis revealed that mutation and selective pressure affect codon usage patterns. In the phylogenetic relationships of the Macropsini, the monophyly of Pedionis and Macropsis was well-supported. Meanwhile, Oncopsis revealed paraphyletic regarding Pediopsoides. In conclusion, this research not only contributes the valuable data to the understanding of the mitogenome of the Macropsini but also provides a reference for future investigations on codon usage patterns, potential adaptive evolution, and the phylogeny of the mitogenome within the subfamily Eurymelinae.