Evolutionary Patterns Research Articles

Genomic Analysis of the Caleosin Family in Theaceae Reveals Lineagespecific Evolutionary Patterns.

Caleosins are recognized as the key proteins found in Lipid Droplets (LDs) and are crucial for the creation, maintenance, and breakdown of LDs. Nevertheless, our understanding of caleosins remains limited within Theaceae, a prominent botanical family encompassing economically significant tea and oil tea species. In this research, we conducted a comprehensive genome-wide exploration and examination of the caleosin family in Theaceae species with sequenced genomes. The gene number of caleosin was similar among Theaceae species. Segmental duplication was the main form of caleosin expansion in Shuchazao (SCZ), Huangdan (HD), Biyun (BY), Tieguanyin (TGY), Longjing (LJ), C. lanceoleosa (Cla) and C. chekiangoleosa (CCH). Synteny analysis revealed one-to-more and more-to-one collinear relationships of caleosin genes among Theaceae species. Caleosins in Theaceae are categorized into either the H-family or the L-family, each exhibiting distinct motif structures and physicochemical properties. Expression analysis revealed an apparent flower-predominant expression pattern of caleosin genes in Theaceae species. In addition, most paralogous pairs displayed expression divergence. This research enhanced our understanding of the lineage-specific evolution of caleosin genes in Theaceae, and is valuable for future functional analysis of this gene family in tea and oil-tea species.

Detecting Driving Factors from Spatial Spectrums Perspective: A Multilevel Analysis of Homestay Industry in Heterogeneous Heritage Destinations

ABSTRACT Homestay represents a tourism product constrained by space and dependent on regional context. While academic attention has grown toward studying homestay distribution patterns in urban areas, heritage destinations have received limited focus. This study establishes a two-scale analytical framework to explore the spatial evolution patterns and formation mechanism of the homestay industry in diverse heritage destinations, identifying the main factors influencing spatial heterogeneity through geographic detectors. Our findings elucidate several key insights: (a) a consistent annual growth trend, alongside a distinct clustering and spatial autocorrelation in the distribution of homestays across the three types of heritage destinations – natural, cultural, and mixed World Heritage sites; (b) the predominant influence of topography, tourism development levels, and transportation infrastructure in shaping the spatial differentiation of homestays; and (c) socioeconomic and tourism development factors emerging as the primary drivers of this differentiation, while the transportation factor, particularly road mileage, exhibits a heightened significance in natural heritage sites. This study offers insights for planning, marketing, and managing tourism heritage destinations.

Fifty years marshland changes in a large floodplain lake: Natural driving or human impact?

Study region: Poyang Lake, the largest freshwater floodplain lake in China. Study focus: Marshlands in a floodplain, as the typical natural wetland offering vital habitats for various organisms, are sensitive to environmental changes. The spatiotemporal changes of marshlands were investigated and their driving forces from both natural factors and human activities were discussed. The remote sensing image data from 1973 to 2022 was adopted to explore the long-term changes of marshlands exposed in dry season. New hydrological insights for the region: Over the past fifty years, the total area of marshlands in Poyang Lake is around 2540–2718 km2 and has undergone substantial changes. It follows the bell-shaped curve pattern with continuous rise since 1970s and reach the maximum at the end of 20 century and then fluctuating decline. Different evolutionary patterns were identified in different lake regions owing to the combination of human activities and natural processes. The expanding marshlands mainly concentrate in the central lake, while the significant losses of marshlands are observed in the northern lake（By sand mining and dyke constructions）. In the southern lake, sediment input from inflow rivers deposited naturally in the river mouth elevated the lake bed and lead to delta expansion（A 3.1 km expansion has been observed）. The complex geomorphological processes and fishery activities also create the dish-shaped internal sub-lakes in marshlands.

A new gansuid bird (Avialae, Euornithes) from the Lower Cretaceous (Aptian) Jiufotang Formation of Jianchang, western Liaoning, China

The study of the Cretaceous birds closest to the living euornithine species has mainly focused on the evolutionary patterns leading to the modern group. Yet, the morphological and ecological diversity of the euornithine branches not directly ancestral to the crown-group is probably underestimated. A new euornithine bird, Shuilingornis angelai gen. et sp. nov., is erected based on a nearly complete skeletal material from the Early Cretaceous (Aptian) Jehol Biota in western Liaoning, China. The new taxon is similar to the penecontemporary gansuids, yet it differs in the smaller body size and in the retention of plesiomorphic features widespread among non-gansuid euornithines. The osteohistological analysis indicates that Shuilingornis gen. nov. represents an early adult stage at the time of death. The phylogenetic analysis robustly supports the referral of Shuilingornis gen. nov. to Gansuidae. Except for the controversial Hollanda, the gansuids have been uncovered from four Aptian basins deposited under similar paleoclimatic conditions. Gansuid success in the middle part of the Cretaceous demonstrates that the exploration of semi-aquatic ecologies was a consistent euornithine pattern which preceded the later ornithurine radiation.

Carbon emission measurement and regional decomposition analysis of China’s beef cattle farming industry

IntroductionWarming caused by greenhouse gas (GHG) emissions has become a global environmental issue of widespread concern, and China, as a responsible power, has the pressing task of reducing carbon emissions. China is one of the world’s major beef producers and consumers, and at the same time, beef cattle, as a large livestock, is the largest source of GHG emissions in the livestock industry.MethodsThis study considered the panel data of 31 provinces in China from 2008 to 2022. The kernel density estimation and Dagum Gini coefficient were used to analyze the spatiotemporal dynamic evolution patterns and influencing factors of carbon emissions from China’s beef cattle farming industry.Results(1) The carbon emission trajectory of beef cattle production follows a distinctive “ascend-descend-ascend” three-phase pattern. By 2022, the sector’s cumulative carbon emissions had burgeoned by 37.62% relative to 2008, reflecting an average annual escalation of 2.31%. Despite the overall upward trend in carbon emissions, significant regional differences were observed. The Central Plains region has witnessed a consistent decline, in stark contrast to the Southwest and Northeast regions, which have emerged as hotspots for heightened carbon emissions and intensified emission densities within China’s beef cattle production landscape, underscoring the intensifying significance of carbon mitigation measures. (2) The kernel density curve shows an overall rightward shift with a specific gradient effect on carbon emissions. In addition, the range of the right drag of the curve in 2022 was significantly reduced, which laterally reflects the narrowing of the difference between the provinces with the highest and lowest carbon emissions from beef cattle farming. The principal source of variance in the overall carbon emissions from beef cattle production is the disparities between regions, which accounts for an average annual contribution rate of 52.52%. Conversely, the within-region contribution rates have remained relatively stable, while those for the intensity of transvariation have witnessed a substantial rise, with annual averages of 18.31 and 28.96%, respectively. (3) Regarding the factors influencing carbon emissions reduction, environmental regulations and production efficiency significantly drive carbon emissions reduction in beef cattle farming.DiscussionRelevant government departments should actively guide farmers toward green production, establish perfect policies and regulations for low-carbon beef cattle farming, and promote low-carbon beef cattle farming models based on local conditions.

Evolution Patterns and Anisotropic Connectivity Characteristics of Pores and Fissures in Oil Shale After Steam Heating at Different Temperatures

Evolution Patterns and Anisotropic Connectivity Characteristics of Pores and Fissures in Oil Shale After Steam Heating at Different Temperatures

Memory effects in a sequence of measurements of noncommuting observables

We use continuous, stochastic quantum trajectories within a framework of quantum state diffusion (QSD) to describe alternating measurements of two noncommuting observables. Projective measurement of an observable completely destroys memory of the outcome of a previous measurement of the conjugate observable. In contrast, measurement under QSD is not projective and it is possible to vary the rate at which information about previous measurement outcomes is lost by changing the strength of measurement. We apply our methods to a spin 1/2 system and a spin 1 system undergoing alternating measurements of the Sz and Sx spin observables. Performing strong Sz measurements and weak Sx measurements on the spin 1 system, we demonstrate return to the same eigenstate of Sz to a degree beyond that expected from projective measurements and the Born rule. Such a memory effect appears to be greater for return to the ±1 eigenstates than the 0 eigenstate. Furthermore, the spin 1 system follows a measurement cascade process where an initial superposition of the three eigenstates of the observable evolves into a superposition of just two, before finally collapsing into a single eigenstate, giving rise to a distinctive pattern of evolution of the spin components. Published by the American Physical Society 2024

Cancerous time estimation for interpreting the evolution of lung adenocarcinoma.

The evolution of lung adenocarcinoma is accompanied by a multitude of gene mutations and dysfunctions, rendering its phenotypic state and evolutionary direction highly complex. To interpret the evolution of lung adenocarcinoma, various methods have been developed to elucidate the molecular pathogenesis and functional evolution processes. However, most of these methods are constrained by the absence of cancerous temporal information, and the challenges of heterogeneous characteristics. To handle these problems, in this study, a patient quasi-potential landscape method was proposed to estimate the cancerous time of phenotypic states' emergence during the evolutionary process. Subsequently, a total of 39 different oncogenetic paths were identified based on cancerous time and mutations, reflecting the molecular pathogenesis of the evolutionary process of lung adenocarcinoma. To interpret the evolution patterns of lung adenocarcinoma, three oncogenetic graphs were obtained as the common evolutionary patterns by merging the oncogenetic paths. Moreover, patients were evenly re-divided into early, middle, and late evolutionary stages according to cancerous time, and a feasible framework was developed to construct the functional evolution network of lung adenocarcinoma. A total of six significant functional evolution processes were identified from the functional evolution network based on the pathway enrichment analysis, which plays critical roles in understanding the development of lung adenocarcinoma.

The Spatial–Temporal Evolution and Driving Factors of the Coastal Tourism Economy in China

Tourism has emerged as a pivotal element of China’s economic development, particularly within its coastal cities. This paper presents a comprehensive analysis of China’s coastal city tourism economic development, focusing on 53 coastal cities. Through a meticulous combination of literature analysis and data crawling, a robust database is constructed, encompassing tourism resources and revenues. This study delineates the spatial–temporal evolution pattern of China’s coastal city tourism development and employs geo-detector methods to quantitatively analyze the impact factors driving this evolution. Key findings reveal distinct trends in the coastal tourism economy of China from 2009 to 2019, characterized by spatial stability, similar trends in adjacent spatial units, and localized spatial structures. Notably, factors such as actual foreign investment, the presence of star-rated guesthouses, tourism industry employment, airport activity, and import–export trade volume exert significant influence on the domestic tourism economy. Similarly, tourism employment, airport activity, availability of star-rated hotels, import–export trade, and utilization of foreign capital emerge as influential factors shaping inbound tourism. Policy recommendations emphasize the need for government intervention to optimize tourism development strategies for coastal cities. This entails balancing resource exploitation with environmental protection and enhancing the quality of tourism services, fostering sustainable growth and long-term prosperity.

Fine-scale phylogeography of Tripneustes gratilla revealed a core-periphery pattern in the South China sea

The Core-Periphery Hypothesis (CPH) is a theoretical framework in phylogeography used to examine the spatial distribution of genetic diversity. The tropical Indian-Western Pacific (IWP), serving as a prominent marine biodiversity hotspot, constantly exports species and evolutionary novelties to peripheral habitats. Many species display genetic patterns consistent with CPH predictions from the IWP to periphery regions. However, the presence of CPH’s genetic signals in intermediate distribution zones remains underexplored. Here, we collected four sea urchin populations of Tripneustes gratilla in the South China Sea and analysed their population structure and evolutionary patterns using 13 morphological parameters, one mitochondrial 16S rRNA gene and nine polymorphic microsatellites. The results revealed substantial genetic homogeneity among the populations, implying a single origin from a glacial refugium. Nonetheless, morphological and microsatellite data distinctly differentiate the northernmost Fengjiawan population from the others, which could be attributed to increased environmental selection pressures such as temperature. Analysis of genetic diversity variation along latitudinal gradients and the relationship between geographic and genetic distances align with CPH expectations for both 16S and microsatellites, albeit to varying degrees of significance. This study enhances our understanding of tropical marine invertebrate evolution and supports the applicability of the CPH model at a fine-scale level.

Clonal dynamics and somatic evolution of haematopoiesis in mouse.

Haematopoietic stem cells maintain blood production throughout life. While extensively characterised using the laboratory mouse, little is known about how the population is sustained and evolves with age. We isolated stem cells and progenitors from young and old mice, identifying 221,890 somatic mutations genome-wide in 1845 single cell-derived colonies, and used phylogenetic analysis to infer the ontogeny and population dynamics of the stem cell pool. Mouse stem cells and progenitors accrue ~45 somatic mutations per year, a rate only about 2-fold greater than human progenitors despite the vastly different organismal sizes and lifespans. Phylogenetic patterns reveal that stem and multipotent progenitor cell pools are both established during embryogenesis, after which they independently self-renew in parallel over life. The stem cell pool grows steadily over the mouse lifespan to approximately 70,000 cells, self-renewing about every six weeks. Aged mice did not display the profound loss of stem cell clonal diversity characteristic of human haematopoietic ageing. However, targeted sequencing revealed small, expanded clones in the context of murine ageing, which were larger and more numerous following haematological perturbations and exhibited a selection landscape similar to humans. Our data illustrate both conserved features of population dynamics of blood and distinct patterns of age-associated somatic evolution in the short-lived mouse.

Exploring the dynamics of sports records evolution through the gembris prediction model and network relevance analysis

Background Sports records hold valuable insights into human physiological limits. However, presently, there is a lack of integration and evolutionary patterns in the recorded information across various sports. Methods We selected sports records from 1992 to 2018, covering 24 events in men’s track, field, and swimming. The Gembris prediction model calculated performance randomness, and Pearson correlation analysis assessed network relevance between projects. Quantitative study of model parameters revealed the impact of various world records’ change range, predicted value, and network correlation on evolutionary patterns. Results 1) The evolution range indicates that swimming events generally have a larger annual world record variation than track and field events; 2) Gembris’s predictions show that sprint, marathon, and swimming records outperform their predicted values annually; 3) Network relevance analysis reveals highly significant correlations between all swimming events and sprints, as well as significant correlations between marathon and all swimming events. Conclusion Sports record evolution is closely linked not only to specific sports technology but also to energy expenditure. Strengthening basic physical training is recommended to enhance sports performance.

Whole genome sequences of 135 “Candidatus Liberibacter asiaticus” strains from China

“Candidatus Liberibacter asiaticus” (CLas) is a phloem-limited alpha-proteobacteria causing Citrus Huanglongbing, the destructive disease currently threatening global citrus industry. Genomic analyses of CLas provide insights into its evolution and biology. Here, we sequenced and assembled whole genomes of 135 CLas strains originally from 20 citrus cultivars collected at ten citrus-growing provinces in China. The resulting dataset comprised 135 CLas genomes ranging from 1,221,309 bp to 1,308,521 bp, with an average coverage of 675X. Prophage typing showed that 44 strains contained Type 1 prophage, 89 strains contained Type 2 prophage, 44 strains contained Type 3 prophage, and 34 of them contained more than one type of prophage/phage. The SNP calling identified a total of 5,090 SNPs. Genome-based phylogenetic analysis revealed two major clades among CLas strains, with Clade I dominated by CLas strains containing Type 1 prophage (79/95) and Clade II dominated by CLas strains containing Type 1 or Type 3 prophage (80/95). This CLas genome dataset provides valuable resources for studying genetic diversity and evolutionary pattern of CLas strains.

SiGNN: A spike-induced graph neural network for dynamic graph representation learning

In the domain of dynamic graph representation learning (DGRL), capturing the temporal evolution within real-world networks is of paramount importance. Spiking Neural Networks (SNNs), renowned for their temporal dynamics and low-power characteristics, provide an efficient solution for temporal processing in DGRL tasks. However, due to the spike-based information encoding mechanism of SNNs, existing DGRL methods that employ SNNs face significant limitations in their representational capacity. To address this issue, we propose an innovative framework named Spike-induced Graph Neural Network (SiGNN) for learning enhanced spatiotemporal representations on dynamic graphs. Specifically, we achieve a harmonious integration of SNNs and GNNs through a novel Temporal Activation (TA) mechanism. This mechanism enables SiGNN to effectively harness the temporal dynamics of SNNs while circumventing the representational constraints imposed by the binary nature of spikes. Furthermore, leveraging the inherent adaptability of SNNs, SiGNN incorporates an in-depth analysis of evolutionary patterns within graphs across multiple time granularities, thereby facilitating the acquisition of multiscale temporal node representations. Extensive experiments on various real-world dynamic graph datasets demonstrate the superior performance of SiGNN in the node classification task. Our code is publicly available at https://github.com/CharliedoD/SiGNN.

Spatiotemporal evolution and driving factors of agricultural land transfer in China.

This paper systematically analyzes the spatiotemporal evolution trends and macroeconomic driving factors of farmland transfer at the provincial level in China since 2005, aiming to offer a new perspective for understanding the dynamic mechanisms of China's farmland transfer. Through the integrated use of kernel density estimation, the Markov model, and panel quantile regression methods, this study finds the following: (1) Farmland transfer rates across Chinese provinces show an overall upward trend, but regional differences exhibit a "U-shaped" evolution characterized by initially narrowing and then widening; (2) although provinces have relatively stable farmland transfer levels, there is potential for dynamic transitions; (3) factors such as per capita arable land, farmers' disposable income, the social security level, the urban‒rural income gap, the urbanization rate, government intervention, and the marketization level significantly promote farmland transfer, while inclusive finance inhibits transfer, and agricultural mechanization level and population aging have heterogeneous impacts. Therefore, to achieve convergence of low farmland transfer regions to medium levels while promoting medium-level regions to higher levels, it is recommended that the government increase support for agricultural mechanization, increase farmers' income and social security levels, and optimize marketization processes and government intervention strategies. The main contributions of this paper are (1) systematically revealing the spatiotemporal evolution patterns of China's farmland transfer and (2) employing panel quantile regression methods to explore the heterogeneous impacts of driving factors, providing more precise and detailed empirical support for the government's formulation of farmland transfer policies.

A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset

Recently, intelligent analysis of lung nodules with the assistant of computer aided diagnosis (CAD) techniques can improve the accuracy rate of lung cancer diagnosis. However, existing CAD systems and pulmonary datasets mainly focus on Computed Tomography (CT) images from one single period, while ignoring the cross spatio-temporal features associated with the progression of nodules contained in imaging data from various captured periods of lung cancer. If the evolution patterns of nodules across various periods in the patients’ CT sequences can be explored, it will play a crucial role in guiding the precise screening identification of lung cancer. Therefore, a cross spatio-temporal lung nodule dataset with pathological information for nodule identification and diagnosis is constructed, which contains 317 CT sequences and 2,295 annotated nodules from 109 patients. This comprehensive database is intended to drive research in the field of CAD towards more practical and robust methods, and also contribute to the further exploration of precision medicine related field. To ensure patient confidentiality, we have removed sensitive information from the dataset.

Investigation on the Instability Mechanism of Expansive Soil Slope With Weak Interlayer Based on Strain Softening

ABSTRACTExpansive soils are widespread in the world and coincide with areas of high human activity. The main cause of deep instability of expansive soil slopes is due to their softening caused by excavation and seepage. By developing a comprehensive numerical model based on the theory of unsaturated soil, this study examines the characteristics of stress and displacement distribution of expansive soil slopes through hydraulic‐mechanical coupled numerical simulation. This study analyzes the evolution patterns of slopes with excavation unloading and seepage of water storage to reveal the mechanisms of deep‐seated instability of expansive soil slopes. The findings demonstrate that: The instability of expansive soil slopes begins at the foot of the slope and propagates along the interlayer, affecting the entire slope. Excavation leads to the softening of the expansive soil interlayer and the transfer of shear stress. During water storage, the weakening of the soil strength results in slope instability along the weak interlayer slip. Softening of the expansive soil interlayer facilitates the redistribution of shear forces in the slope and alters the distribution law of the plastic zone in the deep layer. Overly slowing down the slope leads to significant excavation unloading, which is detrimental to the slope's stability.

Dynamics of tumor evolution after Gammaknife radiosurgery for sporadic vestibular schwannoma: defining volumetric patterns characterizing individual trajectory.

Definition of tumor control and treatment failure after Gammaknife radiosurgery (GKRS) for vestibular schwannoma (VS) is still debated. The lack of knowledge on the dynamics of tumor evolution can lead to misinterpretation and subsequent inappropriate second treatment. The aim of this study was to evaluate the post-GKRS dynamics of evolution of tumor volume, and characterize volumetric patterns. We included patients with sporadic VS treated by GKRS with an MRI follow-up of minimum 3 years. A clustering in 2 steps was performed: definition of the patterns of evolution based on a subset of patients with the most comprehensive follow-up, then assignment of the remaining patients on a best fit basis. The minimum length of follow-up was assessed by measuring the consistency of the clusters over time (Adjusted Rand Index and Normalized Mutual Information). An analysis of the discriminant variables was finally performed. 1,607 patients were included (median follow-up: 67 months). Five patterns were defined with one pattern gathering almost all cases of treatment failure. The clustering at 5 years afforded the highest consistency with long-term follow-up. Discriminant variables for clusters were: sex, initial symptoms, delay of diagnosis, Koos grading, fundus invasion, and number of isocenters. The definition of these robust distinct patterns is likely to help tremendously the physicians to distinguish tumor control from potential failure. We advocate for no retreatment decision before 5 years post-GKRS. Further investigations are required to decide if the dynamics of evolution can be predicted at GKRS on an individual basis.

Elucidating the Hydrolysis and Polymerization Reactions of Al3+‐Solvated Molecules by Reactive Molecular Dynamics Simulation

ABSTRACTUtilizing the reactive molecular dynamics (ReaxFF MD) simulation, we conducted a comprehensive study on the impact of basicity (OH−/Al3+ ratio), concentration, and temperature on the hydrolysis and polymerization reactions of Al3+‐solvated molecules. Through simulations, we analyzed the structural changes, energy fluctuations of the system, and the evolution patterns of reaction products under different parameters, which were subsequently validated by experimental data. The research results indicate that hydroxide ions in the solution directly influence the breakage of OH bonds in the coordinating water molecules of solvated aluminum ions. This, in turn, affects the number of H2O and OH− ions coordinated with Al3+, leading to changes in hydrolysis products. Additionally, the number of OH− ions surrounding Al3+ affects the electrostatic repulsion, making it easier for polymerization reactions to occur as the system approaches the point of zero charge. On the other hand, an increase in concentration and temperature enhances the frequency of cluster collisions, thus contributing to an increase in polymerization degree. The experimental results align closely with our simulated predictions. As the pH value increases, the particle size exhibits a trend of first increasing and then decreasing, reaching a maximum at the point of zero charge. Simultaneously, an increase in concentration also prompts an increase in particle size. The combination of these empirical results with simulations enhances the credibility and reliability of our model's predictive capabilities. This study not only expands our understanding of the relevant chemical reaction processes but also provides important theoretical support for practical applications in related fields.

Desert-oasis evolutionary process in the Tarim Basin since ∼ 2.2 ka B.P. during the late Holocene and their environmental implications

Oases, serving as ideal locations for human settlements in arid regions, exhibit extreme sensitivity to regional climatic fluctuations. Consequently, the oasis deposition sediments play a pivotal role in the study of regional paleoenvironmental changes and the exploration of prehistoric human-environment interactions. The YSD and STM sections, both typical aeolian-lacustrine sections located at the edge of the Tarim Basin, were investigated in this study. By analyzing optically stimulated luminescence (OSL) dating results and grain-size proxy indicators, the environmental evolution patterns in the Tarim Basin since approximately 2.2 ka BP were reconstructed. Additionally, the parametric end-member analysis on the grain-size data was conducted to explore the environmental significance revealed by each end-member. The research findings indicate that: (1) ∼ 2.2–1.8 ka B.P., sediment morphology and grain-size parameters indicate that the climate in the Tarim Basin recorded by the STM section was relatively dry, with rivers gradually receding and frequent sand-drift activities. During the development of the YSD section (∼1.67–1.5 ka B.P.), the environmental conditions in the Tarim Basin transitioned to a relatively humid phase, with the Yarkand River experienced multiple episodes of natural diluvial deposition. The grain-size data of two sections both comprise five sedimentary dynamic components, serving as sensitive indicators of regional humidity conditions and winter monsoon intensity. (2) The oasis development in the Tarim Basin during the late Holocene (particularly refers to between ∼ 2.2 ka B.P. and ∼ 1.4 ka B.P.) exhibits a significant positive correlation with temperature records. (3) Environmental changes and human activities jointly regulate the spatial and temporal distribution and number of archeological sites during the development of both sections. However, the dominance of the two factors varied across different historical periods.