Evolutionary Trajectories Research Articles

A bi-population cooperative scatter search algorithm for distributed hybrid flow shop scheduling with machine breakdown

The occurrence of machine breakdowns is a frequent and dynamic phenomenon in the production process. The implementation of effective preventive measures can mitigate such events and result in reduced production costs. This paper investigates the distributed hybrid flow shop scheduling problem with machine breakdown (DHFSSPB) considering short maintenance time. The bi-population cooperative scatter search (BCSS) algorithm is proposed to address the DHFSSPB, wherein the search for the optimal scheduling sequence is transformed into genetic evolution aiming to obtain a gene chain with both minimum lower bound and minimum cost attributes. Firstly, the DHFSSPB problem is modeled through a combination of predictive maintenance strategy and right-shift rescheduling rule. Subsequently, a diversification approach is developed to facilitate attribute inheritance, enhance the efficiency of job allocation, and establish a reference set. The reference set is partitioned into two subpopulations based on lower bound attributes and cost attributes, respectively. The corresponding hybrid search strategies are designed to enhance the efficiency of job sorting and machine selection for subpopulations with distinct attributes. The cooperative evolution between subpopulations occurs through the competitive interaction and fusion of individuals. An enhanced reinforcement learning approach is proposed to expedite the acceleration of individual attribute evolution by leveraging evolutionary knowledge acquired from populations, thereby effectively guiding the evolutionary trajectories of individuals. Additionally, a method for evaluating the population during the learning process is developed based on problem characteristics to enhance learning efficiency. Experimental results demonstrate that BCSS outperforms the comparative algorithm in solving the DHFSSPB.

Early Genetic Divergence of High-Grade Carcinomas Originating from Low-Grade Serous Ovarian Neoplasms

The current paradigm implicates a fallopian tube precursor as the origin of most ovarian high-grade serous carcinomas (HGSCs). However, a rare subset of HGSCs develop via a distinct pathway from low-grade serous ovarian neoplasms (namely, serous borderline tumors and low-grade serous carcinoma). This alternate pathway for the development of HGSC and other poorly differentiated carcinomas of the ovary is not well understood. To elucidate the molecular pathogenesis and evolutionary trajectory of histologic transformation of low-grade serous neoplasms, we performed whole exome sequencing on microdissected low-grade and higher-grade components from 7 cases of serous borderline tumor or low-grade serous carcinoma associated with a synchronous or metachronous indeterminate/high-grade carcinoma. In most cases, there were relatively few somatic mutations shared between matched low-grade and higher-grade tumors compared with private mutations specific to each component (ie, phylogenetic trees with short trunks and long branches). Truncal mutations, present across all tumor samples from a given patient, included known drivers of low-grade serous neoplasms: KRAS (G12D, n = 4), BRAF (G469A, n = 1), NF2 (n = 1), and USP9X (n = 1). Transformation to HGSC was associated with a TP53 mutation with bi-allelic inactivation in 3 cases, all with severe nuclear atypia, and associated with genome-wide copy number alterations and allelic imbalances. TP53-wildtype tumors comprised a morphologic spectrum, which included indeterminate-grade serous carcinomas with moderate nuclear atypia and high mitotic activity, although lacking extensive chromosomal instability (n = 2) and poorly differentiated carcinomas (n = 2, including a high-grade Mullerian carcinoma and an undifferentiated carcinoma with sarcomatoid features). In summary, synchronous and metachronous low-grade serous neoplasms and higher-grade carcinomas are clonally related. Early genetic divergence, most evident in cases with TP53 mutations, suggests that high-grade transformation may be a relatively early molecular event.

Analysis of genetic evolutionary differences among four Tibetan pig populations in China

Tibetan pigs are a locally bred domestic pig breed originating from the Tibetan Plateau in China. They can be categorized into four distinct groups based on their geographical locations: Sichuan Tibetan pigs, Tibetan pigs from Tibet, Yunnan Tibetan pigs, and Gansu Tibetan pigs. This study aimed to explore population diversity, genetic structure and selection signals among Tibetan pigs in four Chinese national nature reserves. The results show that there is different observed heterozygosity among Tibetan pig populations (0.1957–0.1978). Ratio of runs of homozygosity (Froh) calculation of four Tibetan pig populations by runs of homozygosity (ROH) revealed the presence of inbreeding within the population (0.0336–0.0378). Analysis of the genetic structure demonstrated distinct population stratification among the four Tibetan pig populations, with each showing relatively independent evolutionary directions. Furthermore, Five methods (FST, Piratio, ROD, Tajima's D, XP-CLR) were used to artificially select evolutionary trajectories. The results mainly involved processes such as DNA repair, immune regulation, muscle fat deposition and adaptation to hypoxia. In conclusion, this study enhances our understanding of the genetic characteristics of Tibetan pig populations and provides a theoretical reference for the conservation of resources across different populations of Tibetan pigs.

Genetic diversity and evolution of porcine hemagglutinating encephalomyelitis virus in Guangxi province of China during 2021-2024.

Porcine hemagglutinating encephalomyelitis virus (PHEV) is the only known porcine neurotropic coronavirus, which is prevalent worldwide at present. It is of great significance to understand the genetic and evolutionary characteristics of PHEV in order to perform effective measures for prevention and control of this disease. In this study, a total of 6,986 tissue samples and nasopharyngeal swabs were collected from different regions of Guangxi province in southern China during 2021-2024, and were tested for PHEV using a quadruplex RT-qPCR. The positivity rate of PHEV was 2.81% (196/6,986), of which tissue samples and nasopharyngeal swabs had 2.05% (87/4,246) and 3.98% (109/2,740) positivity rates, respectively. Fifty PHEV positive samples were selected for PCR amplification and gene sequencing. Sequence analysis revealed that the nucleotide homology and amino acid similarities of S, M, and N genes were 94.3%-99.3% and 92.3%-99.2%, 95.0%-99.7% and 94.7%-100.0%, 94.0%-99.5% and 93.5%-99.3%, respectively, indicating M and N genes were more conservative than S gene. Phylogenetic trees based on these three genes revealed that PHEV strains from different countries could be divided into two groups G1 and G2, and the PHEV strains from Guangxi province obtained in this study distributed in subgroups G1c and G2b. Bayesian analysis revealed that the population size of PHEV has been in a relatively stable state since its discovery until it expanded sharply around 2015, and still on the slow rise thereafter. S gene sequences analysis indicated that PHEV strains existed variation of mutation, and recombination. The results indicated that the prevalent PHEV strains in Guangxi province had complex evolutionary trajectories and high genetic diversity. To the best of our knowledge, this is the first report on the genetic and evolutionary characteristics of PHEV in southern China.

Ethical artificial intelligence (AI): principles and practices

Purpose This study aims to delve into the ethical challenges in artificial intelligence (AI) technologies to underscore the necessity of establishing principles for ethical AI utilization in hospitality and tourism. Design/methodology/approach A narrative review of research on ethical AI across diverse realms was conducted to reflect current research progress and examine whether sufficient measures have been taken to address issues pertinent to AI utilization in hospitality and tourism. Findings Ethical issues including privacy concerns, detrimental stereotypes, manipulation and brutalization pertinent to AI utilization are elaborated. How AI should be properly used and managed ethically, responsibly and sustainably is suggested. Research limitations/implications Five fine-tuned principles for regulating AI use in hospitality and tourism are proposed. Practical implications A resilient mindset, enhancement of AI context adaptability, equilibrium between development and regulation and collaborative effort of multiple stakeholders are paramount. Originality/value Through applying the AI evolution trajectory model, this study contributes to the current discourse of managing AI by proposing a framework that addresses the specific characteristics of hospitality and tourism.

Evolution of AI in Smart Home Systems: A Comprehensive Review

The evolution of Artificial Intelligence (AI) has significantly transformed the landscape of smart home systems into a new era of convenience, efficiency, and personalized experiences. This paper provides an insightful exploration into the historical progression and contemporary developments of AI within smart home environments. Beginning with an overview of early automation technologies, we trace the evolutionary trajectory of AI's integration into smart homes, highlighting key milestones, breakthroughs, and paradigm shifts. Moreover, this paper also highlights the applications of AI in smart home ecosystems, including home automation, energy management, security surveillance, healthcare monitoring, and personalized assistance. Through advanced sensor technologies, ubiquitous connectivity, and cloud-based computing, AI-enabled smart home platforms offer seamless integration, interoperability, and scalability, paving the way for a more interconnected and intelligent living environment. Furthermore, we discuss the emerging trends and future directions shaping the evolution of AI in smart home systems. We also address the associated challenges and considerations, including privacy concerns, data security risks, ethical implications, and regulatory frameworks, which warrant careful attention and mitigation strategies.

Deciphering the multi- partite mitochondrial genome of Crataegus pinnatifida: insights into the evolution and genetics of cultivated Hawthorn

Flowering plant (angiosperm) mitochondrial genomes are remarkably dynamic in their structures. We present the complete mitochondrial genome of hawthorn (Crataegus pinnatifida Bunge), a shrub that bears fruit and is celebrated for its extensive medicinal history. We successfully assembled the hawthorn mitogenome utilizing the PacBio long-read sequencing technique, which yielded 799,862 reads, and the Illumina novaseq6000 sequencing platform, which producing 6.6 million raw paired reads. The C. pinnatifida mitochondria sequences encompassed a total length of 440,295 bp with a GC content of 45.42%. The genome annotates 54 genes, including 34 that encode proteins, 17 that encode tRNA, and three genes for rRNA. A fascinating interplay was observed between the chloroplast and mitochondrial genomes, which share 17 homologous sequences sequences that rotal 1,933 bp. A total of 134 SSRs, 22 tandem repeats and 42 dispersed repeats were identified in the mitogenome. Four conformations of C. pinnatifida mitochondria sequences recombination were verified through PCR experiments and Sanger sequencing, and C. pinnatifida mitogenome is more likely to be assembled into three circular-mapping chromosomes. All the RNA editing sites that were identified C-U edits, which predominantly occurred at the first and second positions of the codons. Phylogenetic and collinearity analyses identified the evolutionary trajectory of C. pinnatifida, which reinforced the genetic identity of the hawthorn section. This unveiling of the unique multi-partite structure of the hawthorn mitogenome offers a foundational reference for future study into the evolution and genetics of C. pinnatifida.

Comparative genomics unravels a rich set of biosynthetic gene clusters with distinct evolutionary trajectories across fungal species (Termitomyces) farmed by termites

The use of compounds produced by hosts or symbionts for defence against antagonists has been identified in many organisms, including in fungus-farming termites (Macrotermitinae). The obligate mutualistic fungus Termitomyces plays a pivotal role in plant biomass decomposition and as the primary food source for these termites. Despite the isolation of various specialized metabolites from different Termitomyces species, our grasp of their natural product repertoire remains incomplete. To address this knowledge gap, we conducted a comprehensive analysis of 39 Termitomyces genomes, representing 21 species associated with members of five termite host genera. We identified 754 biosynthetic gene clusters (BGCs) coding for specialized metabolites and categorized 660 BGCs into 61 biosynthetic gene cluster families (GCFs) spanning five compound classes. Seven GCFs were shared by all 21 Termitomyces species and 21 GCFs were present in all genomes of subsets of species. Evolutionary constraint analyses on the 25 most abundant GCFs revealed distinctive evolutionary histories, signifying that millions of years of termite-fungus symbiosis have influenced diverse biosynthetic pathways. This study unveils a wealth of non-random and largely undiscovered chemical potential within Termitomyces and contributes to our understanding of the intricate evolutionary trajectories of biosynthetic gene clusters in the context of long-standing symbiosis.

Differentiation of the Anammox core microbiome: Unraveling the evolutionary impetus of scalable gene flow

Anaerobic ammonium oxidation bacteria (AAOB), distinguished by their unique autotrophic nitrogen metabolism, hold pivotal positions in the global nitrogen cycle and environmental biotechnologies. However, the ecophysiology and evolution of AAOB remain poorly understood, attributed to the absence of monocultures. Hence, a comprehensive elucidation of the AAOB-dominated core microbiome, anammox core, is imperative to further completing the theory of engineered nitrogen removal and ecological roles of anammox. Performing taxonomic and phylogenetic analyses on collected genome repertoires, we show here that Candidatus Brocadia and Candidatus Kuenenia possesses a more compact core than Candidatus Jettenia, which partly explains why the latter has a less common ecological presence. Evidence of gene flow is particularly striking in functions related to biosynthesis and oxygen detoxification, underscoring the evolutionary forces driving lineage and core differentiation. Furthermore, CRISPR spacer traceback of the AAOB metagenome-assembled genomes (MAGs) reveals a series of genetic traces for the concealed phages. By reconceptualizing the functional divergence of AAOB with the historical role of phages, we ultimately propose a coevolutionary framework to understand the evolutionary trajectory of anammox microecology. The discoveries provided in this study offer new insights into understanding the evolution of AAOB and the ecology of anammox.

7942 Evolution of Insulin, Insulin-like Growth Factor and Their Cognate Receptors in Vertebrates, Invertebrates and Viruses

Abstract Disclosure: M. Chrudinova: None. Y.D. Dogru: None. R. Huang: None. R. Reiners: None. P. De Meyts: None. J. DaCosta: None. E. Altindis: None. The insulin/insulin-like growth factor (IGF) signaling system is an evolutionarily conserved system and controls central processes including metabolism, cellular growth, proliferation, and differentiation in vertebrates. On the other hand, invertebrate insulin-like peptides (ILPs) regulate growth, stress responses, longevity and sex-related functions. In addition, we recently showed that six viruses possess viral insulin-like peptides (VILPs) that can bind to the receptors and stimulate post-receptor signaling. The evolution of these hormones and the origin of VILPs are not completely understood. Here, we collected vertebrate and invertebrate insulin, IGF and their cognate receptor sequences to analyze their evolutionary relations. We analyzed 177 vertebrate insulins, 119 vertebrate IGF-1s, 127 vertebrate IGF-2s, 197 invertebrate ILPs and 6 viral insulin/IGF-1 like peptides. We also analyzed 214 insulin receptor (IR), 160 IGF receptor (IGF1R) and 39 invertebrate receptor sequences to identify conservation and the evolutionary trajectory to reveal conserved motifs. Through phylogenetic analyses, we observed a separate branching of invertebrate ILPs and vertebrate insulins, IGF-1s and IGF-2s with notable exceptions including VILPs. IGF-1 and IGF-2 ligands were evolutionally better conserved compared to insulin ligands. Insulin C-peptide which is processed and cleaved was not well conserved compared to the functional A- and B-chain residues. In contrast, C-peptide of IGF-1 that plays an important role in receptor binding was very well conserved. IGF-1 C-domain showed higher variability in IGF1R binding residues compared to the A and B-domains, while residues important for binding of IGF-2 to IGF1R were well conserved. Insulin residues interacting with IR binding Site 1 were more conserved than those interacting with IR binding Site 2, while residues important for insulin dimerization and hexamerization residues are well conserved across species. We also showed that VILPs contain 14 amino acids that are conserved in insulin and IGFs, indicating their functional importance. Phylogenetic relationships of the receptor sequences suggest vertebrate IRs and IGF1Rs evolved from a common ancestor during early vertebrate evolution. Interestingly, receptor subunits revealed a closer relation of amphibian IR α-subunits to Mammalia IR α-subunits than Aves and Reptilians. The conservation rate of receptor residues essential for ligand-receptor interaction revealed that these residues are best conserved in the L1 domain for IR and IGF1R, with a higher rate of variation in other domains for both receptors. Taken together, our study provides a comprehensive analysis of insulin, IGFs, VILPs and their cognate receptors’ evolution, and opens new avenues to better understand the evolution, function, and structure relations of this complex signaling system. Presentation: 6/3/2024

Genomic evidence of Escherichia coli gut population diversity translocation in leukemia patients.

Escherichia coli, a commensal species of the human gut, is an opportunistic pathogen that can reach extra-intestinal compartments, including the bloodstream and the bladder, among others. In non-immunosuppressed patients, purifying or neutral evolution of E. coli populations has been reported in the gut. Conversely, it has been suggested that when migrating to extra-intestinal compartments, E. coli genomes undergo diversifying selection as supported by strong evidence for adaptation. The level of genomic polymorphism and the size of the populations translocating from gut to extra-intestinal compartments is largely unknown. To gain insights into the pathophysiology of these translocations, we investigated the level of polymorphism and the evolutionary forces acting on the genomes of 77 E. coli isolated from various compartments in three immunosuppressed patients. Each patient had a unique strain, which was a mutator in one case. In all instances, we observed that translocation encompasses much of the genomic diversity present in the gut. The same signature of selection, whether purifying or diversifying, and as anticipated, neutral for mutator isolates, was observed in both the gut and bloodstream. Additionally, we found a limited number of non-specific mutations among compartments for non-mutator isolates. In all cases, urine isolates were dominated by neutral selection. These findings indicate that substantial proportions of populations are undergoing translocation and that they present a complex compartment-specific pattern of selection at the patient level.IMPORTANCEIt has been suggested that intra and extra-intestinal compartments differentially constrain the evolution of E. coli strains. Whether host particular conditions, such as immunosuppression, could affect the strain evolutionary trajectories remains understudied. We found that, in immunosuppressed patients, large fractions of E. coli gut populations are translocating with variable modifications of the signature of selection for commensal and pathogenic isolates according to the compartment and/or the patient. Such multiple site sampling should be performed in large cohorts of patients to gain a better understanding of E. coli extra-intestinal diseases.

Tracing the technological trajectories of smart logistics domain based on citation analysis and topic modelling

ABSTRACT The emergence and development of intelligent technology are triggering major changes in the logistics industry, and relevant scientific and technological research on smart logistics (SL) is emerging endlessly. However, there is no research that systematically explores SL from the technological perspective. Therefore, this article selects 47,253 documents retrieved from the Derwent Innovation Index for systematic analysis and provides a comprehensive understanding of the SL domain. We combine main path analysis (MPA) and LDA topic modelling approaches to identify technological evolution trajectories. Through three main paths, the key technologies and technological evolution directions in the SL domain are revealed. Through topic identification and topic correlation calculation, global topic popularity trends and local topic evolution paths are identified. Finally, this study summarises our findings, contributions, and limitations. This is the first attempt to detect key technologies in the SL domain through MPA and topic analysis, thereby guiding relevant researchers and enterprises.

Examining the evolution trajectory of construction and demolition waste in China: An empirical analysis based on spatial metrology and the environmental Kuznets curve

Curbing the increasing construction and demolition waste (C&DW) is critical for achieving China's goals of cleaner production and environmental sustainability. This paper based on the Environmental Kuznets Curve (EKC) and combining spatial econometrics with the GM (1,1) model, predicts key time points that will change the growth trend of C&DW and explores measures to reduce production. The results indicate that: (1)As of 2022, more than 87% of China's regional C&DW is unevenly distributed and agglomeration exists. More than 50% of the regions exhibit “high-high” agglomeration, which can lead to an inevitable inter-regional transfer of C&DW, but the central region has formed a “segregation zone”. (2) The evolution trajectory of C&DW shows a “growth-decline-regrowth” pattern, with points of change for regrowth occurring when GDP per capita reaches 142,914.24. Construction enterprises and consumption levels contribute significantly to C&DW, while the opposite is true for education, market competition, and transportation. (3) More than 95% of regions will experience C&DW regrowth during 2036–2040. Economic development is no longer considered to play a leading role in C&DW reduction measures. Even if the economic growth rate is increased by 10%, 30%, or even 50%, C&DW will enter the era of full-scale regrowth only three years earlier on average. This paper aims to shift the current focus of C&DW forecasting from solely on model innovation to accurately calculating the timing of future C&DW regrowth by verifying the EKC hypothesis application. This approach fills the gap in the quantitative analysis of long-term C&DW forecasting and provides new empirical cases for the theory of environmental economics. Furthermore, it addresses potential obstacles for decision-makers in achieving “zero waste cities”, thereby promoting global cleaner production and environmental sustainability.

Multiscale morphological trajectories to support management of free-flowing rivers: the Vjosa in South-East Europe

Free-flowing rivers (FFRs) are fundamental references for river management, providing the opportunity to investigate river functioning under minimal anthropic disturbance. However, large free-flowing rivers are rare in Europe and worldwide, and knowledge of their dynamics is often scarce due to a lack of data and baseline studies. So far, their characterization is mainly grounded in the longitudinal connectivity assessment, with scarce integration of further hydro-morphological aspects, particularly concerning the processes and drivers of changes in their morphology over time scales of management relevance. This work aims to broaden the characterization of FFRs by reconstructing their catchment-scale morphological evolutionary trajectories and understanding their driving causes, to support their management better. This is achieved by integrating freely available global data including Landsat imagery and climatic reanalysis with the few locally available quantitative and qualitative information. The analysis of possible drivers of change at the catchment and reach scale assesses hydrological variability, flow regulation, land use change, sediment mining and bank protection works. We applied this approach to the Vjosa River (Albania), a model ecosystem of European significance and one of the few FFRs in Europe. The Vjosa was recently declared a Wild River National Park. We investigated its catchment-scale morphological changes over 50 years, considering four reaches of the Vjosa and four reaches of its main tributaries. Satellite imagery was analyzed taking advantage of Google Earth Engine cloud computing platform. The analysis reveals a catchment-scale response to climatic fluctuations, especially in the most natural reaches, with a significant narrowing of the active river corridor, following a flood-intense period in the early 1960s. The narrowing rate gradually decreased, from 35% before 1985 to 24% between 1985 and 2000, reaching a new equilibrium from 2000 to 2020. However, the recent trajectories of the lowland reaches have been impacted by human pressures, particularly sediment mining, which intensified after the 1990s, suggesting that these reaches may instead be far from equilibrium and adjusting to such persistent stressor. Identifying the key drivers of change and building catchment-scale knowledge of geomorphic change can inform the management of riverine protected areas, and the proposed integrated approach is a promising tool to help overcome the data scarcity typical of the limited remaining large FFRs.

Comparative Analysis of the Codon Usage Pattern in the Chloroplast Genomes of Gnetales Species

Codon usage bias refers to the preferential use of synonymous codons, a widespread phenomenon found in bacteria, plants, and animals. Codon bias varies among species, families, and groups within kingdoms and between genes within an organism. Codon usage bias (CUB) analysis sheds light on the evolutionary dynamics of various species and optimizes targeted gene expression in heterologous host plants. As a significant order of gymnosperms, species within Gnetales possess extremely high ecological and pharmaceutical values. However, comprehensive analyses of CUB within the chloroplast genomes of Gnetales species remain unexplored. A systematic analysis was conducted to elucidate the codon usage patterns in 13 diverse Gnetales species based on the chloroplast genomes. Our results revealed that chloroplast coding sequences (cp CDSs) in 13 Gnetales species display a marked preference for AT bases and A/T-ending codons. A total of 20 predominantly high-frequency codons and between 2 and 7 optimal codons were identified across these species. The findings from the ENC-plot, PR2-plot, and neutrality analyses suggested that both mutation pressure and natural selection exert influence on the codon bias in these 13 Gnetales species, with natural selection emerging as the predominant influence. Correspondence analysis (COA) demonstrated variation in the codon usage patterns among the Gnetales species and indicated mutation pressure is another factor that could impact CUB. Additionally, our research identified a positive correlation between the measure of idiosyncratic codon usage level of conservatism (MILC) and synonymous codon usage order (SCUO) values, indicative of CUB’s potential influence on gene expression. The comparative analysis concerning codon usage frequencies among the 13 Gnetales species and 4 model organisms revealed that Saccharomyces cerevisiae and Nicotiana tabacum were the optimal exogenous expression hosts. Furthermore, the cluster and phylogenetic analyses illustrated distinct patterns of differentiation, implying that codons, even with weak or neutral preferences, could affect the evolutionary trajectories of these species. Our results reveal the characteristics of codon usage patterns and contribute to an enhanced comprehension of evolutionary mechanisms in Gnetales species.

Adaptive evolution and functional significance of the PPARGC1A gene across diverse animal species.

Codon-based analyses of the PPARGC1A gene across 38 vertebrate species were deployed to elucidate patterns of evolutionary change. Employing maximum likelihood assessments through MEGA, we scrutinized 447 codon positions addressing the entire coding region, excluding positions mired by gaps or missing data. Distinct codons manifested variance in selection pressures, particularly codons 4, 11, 66, and 123, which exhibited positive dN-dS values suggestive of positive selection. Codon 137 displayed the most pronounced dN-dS value, signifying intensified selective advantage. Meanwhile, codons 30 and 90 portrayed near-neutral scores, indicative of purifying selection. Complementary computational methods (IFEL, REL, FUBAR, and SLAC) confirmed positive selection at specific codon sites, with varying degrees of corroboration. The integration of mixed-effect modeling (MEME) identified episodic diversifying selection, pinpointing codons that underwent selection episodes in certain lineages. Refined codon model selection lent insight into substitution rates, revealing nuanced degrees of evolutionary conservation among different codons. Supporting these genetic insights, the phylogenetic analysis highlighted relationships among the PPARGC1A sequences and domain analysis confirmed conserved features across species, while protein-protein interaction networks suggested a complex web of functional interdependencies. These findings advance our understanding of the PPARGC1A gene's evolutionary trajectory and underscore the gene's potential adaptive significance within diverse vertebrate lineages.

Unlocking the Synergy: Increasing productivity through Human-AI collaboration in the industry 5.0 Era

The prevailing trajectory of technological evolution emphasizes the sustainable development of human-AI collaboration. In this study, we employ the coupling coordination degree model to evaluate the dynamics of human-AI collaboration in China and match it with listed companies. Through panel models, the study not only quantifies the contribution of such collaboration to enhancing company input–output efficiency but also explores how it serves as a catalyst for technological catch-up. Our findings indicate that the integration of human capital with AI emerges as a potent driver of company efficiency, with the extent of the impact also tied to organizational characteristics. Furthermore, the scale of investment and organizational size play a crucial role in the effectiveness of HIC, underscoring the adaptability of human-AI collaboration strategies to various organizational contexts and the importance of tailored implementation. Our research highlights the inherent collaborative potential of AI within the Industry 5.0 framework, advocating for the fusion of human creativity with AI precision to foster a development paradigm that is resource-efficient, cost-effective, and human-centric.

Ecological shifts underlie parallels between ontogenetic and evolutionary allometries in parrotfishes.

During ontogeny, animals often undergo significant shape and size changes, coinciding with ecological shifts. This is evident in parrotfishes (Eupercaria: Labridae), which experience notable ecological shifts during development, transitioning from carnivorous diets as larvae and juveniles to herbivorous and omnivorous diets as adults, using robust beaks and skulls for feeding on coral skeletons and other hard substrates. These ontogenetic shifts mirror their evolutionary history, as parrotfishes are known to have evolved from carnivorous wrasse ancestors. Parallel shifts at ontogenetic and phylogenetic levels may have resulted in similar evolutionary and ontogenetic allometric trajectories within parrotfishes. To test this hypothesis, using micro-computed tomography (μCT) scanning and three-dimensional geometric morphometrics, we analyse the effects of size on the skull shape of the striped parrotfish Scarus iseri and compare its ontogenetic allometry to the evolutionary allometries of 57 parrotfishes and 162 non-parrotfish wrasses. The young S. iseri have skull shapes resembling non-parrotfish wrasses and grow towards typical adult parrotfish forms as they mature. There was a significant relationship between size and skull shapes and strong evidence for parallel ontogenetic and evolutionary slopes in parrotfishes. Our findings suggest that morphological changes associated with the ecological shift characterizing interspecific parrotfish evolution are conserved in their intraspecific ontogenies.

Variation in season length and development time is sufficient to drive the emergence and coexistence of social and solitary behavioural strategies.

Season length and its associated variables can influence the expression of social behaviours, including the occurrence of eusociality in insects. Eusociality can vary widely across environmental gradients, both within and between different species. Numerous theoretical models have been developed to examine the life history traits that underlie the emergence and maintenance of eusociality, yet the impact of seasonality on this process is largely uncharacterized. Here, we present a theoretical model that incorporates season length and offspring development time into a single, individual-focused model to examine how these factors can shape the costs and benefits of social living. We find that longer season lengths and faster brood development times are sufficient to favour the emergence and maintenance of a social strategy, while shorter seasons favour a solitary one. We also identify a range of season lengths where social and solitary strategies can coexist. Moreover, our theoretical predictions are well matched to the natural history and behaviour of two flexibly eusocial bee species, suggesting that our model can make realistic predictions about the evolution of different social strategies. Broadly, this work reveals the crucial role that environmental conditions can have in shaping social behaviour and its evolution and it underscores the need for further models that explicitly incorporate such variation to study the evolutionary trajectories of eusociality.

Distinct evolutionary trajectories following loss of RNA interference in Cryptococcus neoformans.

While increased mutation rates typically have negative consequences in multicellular organisms, hypermutation can be advantageous for microbes adapting to the environment. Previously, we identified two hypermutator Cryptococcus neoformans clinical isolates that rapidly develop drug resistance due to transposition of a retrotransposon, Cnl1. Cnl1-mediated hypermutation is caused by a nonsense mutation in the gene encoding a novel RNAi component, Znf3, combined with a tremendous transposon burden. To elucidate adaptative mechanisms following RNAi loss, two bioinformatic pipelines were developed to identify RNAi loss-of-function mutations in a collection of 387 sequenced C. neoformans isolates. Remarkably, several RNAi-loss isolates were identified that are not hypermutators and have not accumulated transposons. To test if these RNAi loss-of-function mutations can cause hypermutation, the mutations were introduced into a non-hypermutator strain with a high transposon burden, which resulted in a hypermutator phenotype. To further investigate if RNAi-loss isolates can become hypermutators, in vitro passaging was performed. Although no hypermutators were found in two C. neoformans RNAi-loss strains after short-term passage, hypermutation was observed in a passaged C. deneoformans strain with increased transposon burden. Consistent with a two-step evolution, when an RNAi-loss isolate was crossed with an isolate containing a high Cnl1 burden, F1 hypermutator progeny inheriting a high transposon burden were identified. In addition to Cnl1 transpositions, insertions of a novel gigantic DNA transposon KDZ1 (~11 kb), contributed to hypermutation in the progeny. Our results suggest that RNAi loss is relatively common (7/387, ~1.8%) and enables distinct evolutionary trajectories: hypermutation following transposon accumulation or survival without hypermutation.