Search Results (324)

Background: Codon usage bias (CUB), which is shaped by mutation pressure, natural selection, and genetic drift, provides valuable insights into phylogenetic relationships and molecular evolution. This study investigated the patterns and determinants of mitochondrial genome codon usage in two Enicurus species (Enicurus scouleri and Enicurus schistaceus) and provided a foundation for understanding codon optimisation mechanisms and genetic relationships within this avian genus. Methods: Complete mitochondrial genome sequences were retrieved from GenBank, and ten protein-coding sequences were selected for CUB analysis. Evolutionary relationships across the studied species were investigated using phylogenetic trees and relative synonymous codon usage (RSCU) clustering diagrams. Results: GC1, GC2, and GC3 contents were below 50% in both species, with the third-position nucleotides exhibiting A3s > C3s > T3s > G3s composition. The average effective number of codons (ENC) value was >35, indicating a weak bias for codon usage. CUB reflects the combined effects of natural selection and mutational pressure, with the former exerting a stronger influence. Four shared optimal codons were identified with a strong bias towards A/C-ending triplets. Subsequent phylogenetic analysis validated the close kinship of the two Enicurus species, although RSCU-based clustering yielded results that diverged from the phylogenetic relationships. Conclusions: Comprehensive mechanistic analysis revealed natural selection as the dominant force shaping mitochondrial CUB in Enicurus species. The findings offered valuable insights for future research on the reproductive biology, environmental adaptation, and conservation of Enicurus birds while providing new perspectives on the molecular evolution and systematic development of Muscicapidae. Full article

Position-independent geometric errors crucially impact the accuracy of five-axis machine tools, yet their identification remains challenging due to computational complexities, inadequate measurement pose selection, and disturbances arising from thermal drift and residual uncompensated errors. Existing methods typically rely on linearized kinematic models, heuristic sampling of measurement poses, or computationally expensive global optimization procedures, which collectively limit their effectiveness in industrial environments. This study presents a unified identification framework that overcomes these limitations; it incorporates 3D offset parameters to enhance the decoupling of true geometric errors from non-PIGEs, an observability-driven measurement pose selection strategy to maximize the parameter sensitivity, and an ANN-surrogate model to accelerate high-dimensional global optimization. A genetic algorithm is used to optimize the measurement points based on the observability index of the machine tool. The ANN-surrogate model enhances the identification accuracy of error parameters (11 PIGEs + 3 offsets) through precise kinematic models, global exploration, and final refinement. Experimental validation on a five-axis machine tool demonstrates a volumetric error reduction of 88.615% after compensation, with RMSE decreasing to 0.4337 μm. Sensitivity analysis reveals that PIGEs contribute up to 75.26% of the total inaccuracy, while offset parameters capture 24.74% of the error from thermal and non-PIGE sources. The results confirm the method’s superiority over other techniques in terms of identification accuracy, efficiency, and robustness, providing a practical solution for high-precision applications in the manufacturing industries. Full article

Amphibians are threatened globally by habitat loss and emerging diseases, yet information on their diversity and distribution remains scarce in many regions. Ethiopia is renowned for its rich anuran diversity, but little is known about the diversity and abundance of anurans in Chebera Churchura National Park (CCNP). We conducted surveys from June 2022 to April 2024 along transects in various habitats during both dry and wet seasons. Methods included visual encounter surveys, acoustic monitoring, opportunistic observations, and pitfall traps with drift fences. Species identification was primarily based on morphology and subsequently validated through genetic barcoding using mitochondrial 16S rRNA sequence analysis for five species. A total of 2175 individuals were recorded, representing 16 species from 8 families. The families Bufonidae and Ptychadenidae were the most dominant. Riverine forest habitats exhibited the highest anuran diversity, followed by montane forest, woodland, and savannah grassland. These findings underscore the importance of CCNP as a refuge for Ethiopian anuran species and the need for further research into the park’s unexplored areas. Full article

Balancing structural safety and economic efficiency in super-tall building design remains a formidable challenge. To address this issue, this study proposes a genetic-algorithm-based multi-variable, multi-objective optimization method. The design variables include the member sizes and vertical layout positions of outrigger and belt trusses, as well as the cross-sectional dimensions of mega-columns. Total structural weight and maximum inter-story drift ratio are adopted as objective functions, while code-specified constraints, such as shear-weight ratio, stiffness-weight ratio, and axial compression ratio, are incorporated to formulate the fitness evaluation for optimization. Taking a 300 m baseline structure designed for 6-degree seismic intensity and equipped with two outrigger trusses and three belt trusses as an example, single-variable sensitivity analyses are first performed. The results show that optimizing any single parameter can yield certain local improvements, yet it cannot overcome the weight–deformation trade-off induced by strong variable coupling. By selecting representative feasible solutions from the multi-variable solution set that match the “optimal” values identified by single-variable optimization as benchmarks, the multi-variable optimum reduces the total structural weight by approximately 6.5–18.4% relative to these representative designs. Moreover, optimal layout strategies of outrigger and belt trusses are investigated for two typical building heights (200 m and 300 m) and two seismic intensity levels associated with design ground motions having a 10% exceedance probability in 50 years, namely 6-degree (0.05 g) and 8-degree (0.20 g). Finally, the proposed method is validated through a case study of a super-tall financial center in Chongqing, where the total structural weight is reduced by 12.3% after optimization while the inter-story drift ratio still satisfies relevant code requirements. The results demonstrate that the proposed framework can generate competitive feasible solutions and provide a systematic means to achieve a balanced trade-off between structural safety and economic efficiency for outrigger–belt-truss super-tall buildings. Full article

Codon usage bias (CUB) in mitochondrial genomes reflects evolutionary forces such as mutation, selection, and genetic drift, yet its dynamics in early-diverging fungal lineages like Conidiobolus (Zoopagomycota) remain unclear. This study systematically analyzed mitochondrial core protein-coding genes (PCGs) from eight Conidiobolus species to elucidate the drivers of CUB and phylogenomic patterns. Nucleotide composition revealed pronounced AT richness (73.32% ± 3.38%) and low GC3 (13.40% ± 5.11%), indicating a preference for A/T-ending codons. Neutrality and ENC-GC3s plots demonstrated that natural selection, rather than mutation pressure, predominantly shaped codon bias, supported by weak GC12-GC3 correlations (slopes: 0.037–0.335) and significant ENC deviations from mutation-driven expectations. PR2-bias analysis further highlighted a strong bias toward A over T and C over G. Correspondence analysis linked major codon usage variations to GC3s, CAI, and FOP indices. Phylogenetic reconstructions based on relative synonymous codon usage (RSCU) and concatenated mitochondrial sequences revealed discordant topologies, particularly in the placement of C. polytocus and C. polyspermus, suggesting divergent evolutionary trajectories. Optimal codon analysis identified species-specific preferences dominated by A/T termini. These findings underscore natural selection as the primary force driving AT-biased mitochondrial CUB in Conidiobolus, while phylogenomic discordance highlights complex evolutionary pressures in this ecologically diverse fungal genus. This study provides foundational insights into mitochondrial genome evolution and codon adaptation mechanisms in early-diverging fungi. Full article

Background: The H1N1 influenza A virus evades host immunity through continuous antigenic drift, posing a significant challenge to broad-spectrum neutralizing antibody therapies. This study aims to systematically evaluate the neutralizing capacity of the broad-spectrum antibody C12H5 against H1N1 strains from different eras and identify key immune escape mutation sites. Methods: Three representative H1N1 virus strains from 2009, 2018, and 2023 were selected. An antigen–antibody binding prediction model based on the ESM-2 large language model was constructed by integrating 48,762 GISAID sequence data and deep mutation scanning data from the Bloom laboratory. Candidate escape sites were screened using SHAP (SHapley Additive exPlanations) value analysis. Mutant viruses were constructed via reverse genetics, and their neutralizing capacity and replication fitness were validated through hemagglutination inhibition assays, microneutralization assays, and viral growth kinetics analysis. Results: Machine learning scoring identified five potential escape sites, with K147 exhibiting the highest overall score (0.92). SHAP analysis revealed that the K147 site within the HA protein’s 130-loop region received the highest importance score (0.28), significantly surpassing other candidate sites. Experimental validation revealed that the K147N mutation reduced neutralizing potency against C12H5 by 8-fold (from 1:1024 to 1:128) and approximately 6-fold in microneutralization assays (from 8.3 log₂ to 5.7 log₂), while exhibiting a replication advantage in MDCK cells. Microneutralization assays further confirmed an approximately 6-fold reduction in neutralization sensitivity. Structural analysis indicated that K147 is located at the periphery of the HA receptor-binding domain, immediately adjacent to the receptor-binding site. Conclusions: K147N is identified as the critical mutation mediating C12H5 immune escape, and this mutation has emerged in 2023 circulating strains. This study provides important molecular targets and early warning mechanisms for broad-spectrum antibody optimization and influenza vaccine updates. Full article

Swine influenza virus (SIV) continues to evolve and possesses notable zoonotic potential, making it an important respiratory pathogen of concern for both the global swine industry and public health. Owing to antigenic drift, genetic reassortment, and regional lineage diversity, vaccine efficacy against SIV shows marked variability across different epidemiological contexts. Therefore, establishing appropriate animal models to dissect its pathogenic mechanisms, transmission characteristics, and immune response patterns is of critical importance. This review systematically summarises the animal models commonly used in SIV research, including mice, ferrets, guinea pigs, pigs, and non-human primates, and provides an integrated analysis across three core dimensions: pathological manifestations, viral replication kinetics, and immune architecture. The evidence indicates that substantial inter-model differences exist in pulmonary lesion distribution, transmission efficiency, mucosal immune development, and cellular immune complexity, which in turn define their functional roles in mechanistic studies, transmission research, and vaccine evaluation. Building on this framework, this review further emphasises the value of a tiered, multi-model strategy in SIV research. In vitro systems and mouse models are well suited for early mechanistic exploration and preliminary vaccine screening; ferret and guinea pig models facilitate the evaluation of transmission dynamics; and the pig model, as the natural host system, remains the critical platform for confirming protective efficacy, identifying potential immunopathological risks, and assessing translational relevance. Importantly, the potential occurrence of vaccine-associated enhanced respiratory disease under antigen-mismatched conditions highlights the need to evaluate both protective performance and immunological safety during vaccine development. Overall, rational integration of evidence across multiple models, anchored to the natural host, will improve the predictability and translational reliability of SIV vaccine research. Full article

Quasi-Static Electromagnetic Forming (QSEF) technology utilizes stable magnetic fields generated by long-pulse flat-top currents to achieve non-contact, high-precision forming of large-scale integral aerospace components. To meet the immense energy demands of large-scale component forming, the drive system requires instantaneous power output capabilities at the Gigawatt level. Consequently, the precise regulation of ultra-high flat-top current waveforms becomes a critical challenge for ensuring forming quality. However, traditional meta-heuristic methods, such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO), exhibit limited adaptability and robustness when addressing strong geometric nonlinearities induced by workpiece deformation and the performance degradation of pulsed power modules. To address engineering challenges such as capacitor degradation, inductance drift, and module failures, this paper proposes a Staged Deep Reinforcement Learning (Staged-DQN) adaptive current control framework. This framework decouples the discharge scheduling into “heuristic rapid rise” and “DQN fine compensation” stages, adaptively optimizing triggering timing to suppress plateau oscillations and compensate for energy deficits caused by faults. Simulation results demonstrate that under typical high-energy operating conditions, the proposed method achieves superior tracking accuracy compared to traditional PSO in fault-free scenarios. In extreme scenarios involving 25 faulty modules, the Mean Absolute Percentage Error (MAPE) is maintained between 1.13% and 1.80%, significantly lower than the 2.65–3.52% of the baseline DQN. This study validates the effectiveness of the proposed method in enhancing waveform quality and system fault tolerance, offering a reliable intelligent control solution for large-scale electromagnetic manufacturing equipment. Full article

The adoption of Internet of Things (IoT) technologies has significantly enhanced precision farming by enabling continuous environmental monitoring and data-driven agricultural management. However, the increasing reliance on distributed sensor networks introduces critical challenges, including sensor faults, data anomalies, and cyber-physical security threats, which can undermine system reliability and decision accuracy. This study proposes an IoT-driven anomaly detection framework for smart agriculture that integrates a Convolutional Neural Network (CNN) optimized using a hybrid Particle Swarm Optimization and Genetic Algorithm (PSO–GA). The CNN learns complex spatio-temporal patterns from multivariate sensor data, while the PSO–GA strategy automatically tunes CNN hyperparameters to improve detection accuracy and model stability. To enhance adaptability under dynamic agricultural conditions, the proposed framework incorporates an online learning mechanism that incrementally updates the CNN model using newly arriving sensor data, enabling continuous adaptation to environmental changes and concept drift without full model retraining. Experiments conducted on a publicly available smart agriculture dataset demonstrate that the proposed CNN–PSO–GA framework achieves an accuracy of 74%, precision of 74%, recall of 100%, and an F1-score of 85%, outperforming baseline methods such as One-Class Support Vector Machine and Isolation Forest, particularly in reducing missed anomaly events. The results confirm the robustness, adaptability, and reliability of the proposed approach. Overall, the framework provides a practical and scalable solution for enhancing security, resilience, and operational effectiveness in precision farming systems. Full article

Polygenic adaptation in response to natural selection on a quantitative trait has become an important topic in population genetics and evolution. We modeled a scenario in which a population was assumed to be in equilibrium between mutation, selection and genetic drift, when a sudden shift in the fitness optimum occurred. It is well known that after an environmental shift the trait mean may approach the new optimum very quickly at a rate proportional to the equilibrium genetic variance. Here, we analyze the dynamics of the allele frequencies at individual loci, using diffusion theory. We show that genetic drift slows down the speed of polygenic adaptation. We also found that, while the frequencies of rare and very common alleles decrease during the adaptive phase, alleles starting at intermediate equilibrium frequencies at the time of the optimum shift change most quickly and thus may substantially modify the shape of the allele frequency distribution. Finally, we explain how these properties of the allele frequency spectrum may be utilized in statistical tests of polygenic selection. Full article

Despite the persistent global threat of seasonal influenza viruses such as A(H1N1)pdm09 and A/H3N2, their epidemiological and genetic characteristics in China following the implementation of COVID-19 non-pharmaceutical interventions (NPIs) remain poorly characterized. Between September 2020 and December 2023, we conducted an integrated epidemiological and genomic analysis of influenza A viruses in children in Wuhan. The overall positivity rate for influenza A virus was markedly low at 3.43% (109/3171), reflecting a profound suppression of circulation during the pandemic. Among genotyped positives, H1N1pdm09 was predominant (52.3%), followed by H3N2 (16.5%) and untypeable strains (32.1%). Preschool children showed the highest susceptibility. Phylogenetic analysis revealed that the circulating H1N1 strains (90%) belonged to clade 6B.1A.5a.2, clustering with viruses from Hong Kong and Pakistan. In contrast, H3N2 strains (76.92%) primarily fell into clade 3C.2a1b.2a.2b, closely related to contemporary strains from Europe and North America. Notably, we identified key hemagglutinin mutations associated with antigenic drift (e.g., R240Q in H1N1; E78G, R158G in H3N2) and neuraminidase mutations potentially conferring antiviral resistance (e.g., S247N in H1N1; S245N, a putative novel glycosylation site, in H3N2). Evidence of reassortment events was also detected, underscoring the continued genomic evolution of these viruses despite their low prevalence. Our findings demonstrate that genetically diverse and antigenically drifted influenza A viruses continued to circulate and evolve in Wuhan during the COVID-19 pandemic, albeit at dramatically reduced levels. This highlights the critical need for sustained genomic surveillance and timely updates of vaccine compositions to pre-empt the resurgence of influenza in the post-pandemic era. Full article

Background/Objectives: The Bedouins (nomads) and the Fellahin (farmers) of Jordan represent two distinct subpopulations, characterized by unique lifestyles, settlement patterns, and linguistic features. This study aims to estimate the frequency of 27 Y-STRs in these two Jordanian subpopulations, along with various forensic parameters and paternal lineage comparisons with neighboring populations. Methods: Twenty-seven Y-STRs were typed in two major Jordanian subpopulations: Bedouin nomads (n = 101) and Fellahin farmers (n = 98). The forensic and paternal genetic lineage parameters and Y-haplogroup predictions were estimated. In addition, we conducted multidimensional scaling (MDS) and centroid analyses based on the Fst distance matrix to compare the sampled communities with neighboring populations from the MENA region, East Africa, Southeast Europe, and South Asia. Results: The Y-haplogroup predictions revealed differences in the predicted lineage composition based on the Y-STR profiles. The predicted J1a2a1a2 haplogroup predominated among the Bedouins (74.3%), whereas the Fellahin displayed a more heterogeneous profile, with notable frequencies of J1 (40%) and J2 (17.3%). Furthermore, the Fellahin exhibited remarkable genetic diversity and significant gene flow, providing plausible evidence of kinship with neighboring Levantine and Arabian groups. In contrast, the Bedouins showed consistently lower diversity across multiple loci, indicating long-term tribal isolation and, therefore, the potential effects of genetic drift. The MDS and centroid analyses positioned the Fellahin among the genetically interconnected Middle Eastern populations, while the Bedouins were clustered with the Arabian Peninsula populations. Conclusions: Overall, the contrasting genetic signatures of the two Jordanian subpopulations reflect their settlement patterns and sociocultural practices. In addition, the Y-STR dataset generated in this study enhances the Jordanian forensic database and to extends our understanding of paternal lineage structures in the West Asian/Levantine region. Full article

Rhizoctonia solani anastomosis group (AG)-2-2IIIB and AG-4HGI are the main pathogens causing sugar beet seedling damping-off and crown and root rot disease. In this study, 1232 loci of simple sequence repeats (SSRs) were obtained via transcriptome sequencing, with 592 from AG-2-2IIIB and 640 from AG-4HGI. Fourteen and twenty loci of SSRs were selected for studying the genetic structure of the AG-2-2IIIB and AG-4HGI populations, respectively. A population of 134 strains of AG-2-2IIIB and 145 strains of AG-4HGI, sampled from three geographic regions in China, indicated that both AG-2-2IIIB and AG-4HGI had a high level of genetic diversity, and that the selected SSR markers could reliably capture the genetic variation. Genetic analysis indicated that the individual strains of AG-2-2IIIB and AG-4HGI randomly mated within their respective population, and that a considerable degree of inbreeding was present among the populations. High to moderate gene flow and low to moderate population subdivision were detected among the populations of AG-2-2IIIB and AG-4HGI, which indicated that weak differentiation existed in these two subgroups. In addition, a founder effect (genetic drift) or a bottleneck effect was inferred to have occurred in the AG-4HGI population. This study provides the first analysis of the population genetic structure of AG-2-2IIIB and AG-4HGI associated with sugar beet seedling damping-off and crown and root rot disease, and the present results offer useful guidance for developing effective integrated disease management. Full article

Cetaceans are artiodactyls adapted to live in the marine environment, and this group includes whales, dolphins, and porpoises. Although mitochondrial nucleotide diversity has been reported separately for many cetacean groups, the proportion of deleterious mutations in these populations is unknown. Furthermore, a comparison of mitogenomic diversities across all cetaceans is also lacking. To investigate this, we conducted a comparative genomic analysis of 2244 mitochondrial genomes from 65 populations across 32 cetacean species. We observed a 78-fold variation in mitogenomic diversity among cetacean populations, suggesting a large difference in genetic diversity. We used the ratio of nonsynonymous-to-synonymous diversities (dN/dS) to measure the proportion of deleterious mutations in the mitochondrial exomes. The dN/dS ratio showed a 22-fold difference between the cetacean population. Based on genetic theories, the large differences observed in the two measures could be attributed to differences in the effective sizes of the cetacean populations. Typically, small populations have low heterozygosity and a high dN/dS ratio, and the reverse is true for large populations. This was further confirmed by the negative correlation observed between heterozygosity and dN/dS ratios of cetacean populations. While our analysis revealed similarities in mitogenomic diversity between the endangered and least-concern cetacean species, the dN/dS ratio of the former was found to be higher than that of the latter. The findings of this study are useful for identifying the relative magnitude of reductions in the population sizes of different cetacean species. This will help conservation management efforts prioritise the use of limited resources, time, and effort to protect the cetacean populations that need immediate attention. Full article

Five rare variants in BRIP1/FANCJ, initially identified in ovarian cancer (OC) or breast cancer (BC) cases by the adult hereditary cancer clinics, were investigated for their candidacy as clinically relevant variants. These variants were investigated genetically in a population exhibiting genetic drift and molecularly assayed for biological impact. Using in silico tools, population-based genetic databases and other resources, three of the five reported BRIP1 variants were likely to be damaging: c.797C>T; p.Thr266Met, c.2087C>T; p.Pro696Leu and c.2990_2993delCAAA; p.Thr997ArgfsTer61. The carrier frequencies ranged from 0 to 0.7% in ancestry-defined cancer groups comprising 47 OC families, 49 hereditary breast and ovarian cancer syndrome families, 142 hereditary breast cancer syndrome families, 435 sporadic OC cases and 563 sporadic BC cases and 0–0.2% in 1025 population-matched controls. Multiple carriers of the these variants were identified in additional population-matched cancer cases. Of the five reported BRIP1 variants, p.Thr266Met, p.Pro696Leu and c.2990_2993delCAAA; p.Thr997ArgfsTer61, which were predicted to be damaging, conferred cellular sensitivity to mitomycin C and cisplatin unlike p.Ser139Ala and p.Ala406Ser. Collectively, our investigation implicates BRIP1 c.797C>T; p.Thr266Met, c.2087C>T; p.Pro696Leu and c.2990_2993delCAAA; p.Thr997ArgfsTer61 as deleterious variants in OC and BC. Full article