Natural Evolution Research Articles

Predator morphology affects prey consumption: evidence from an anuran population in subtropical wetlands

Morphology and diet are key factors in the ecology of organisms, determining aspects of the natural history and evolution of the species. In this work, we evaluated the diet-morphology relationship in an anuran population, measuring the influence of morphological traits on the variation in the diet of individuals of Leptodactylus luctator. For this purpose, we collected individuals from a natural grassland habitat in southern Brazil. We analysed the stomach content of individuals and classified the consumed food items up to the classification level of order. We also measured four morphological traits per individual of L. luctator: distance between eyes, relative limb length, relative mouth width (gape) and snout-vent length. We applied Linear Mixed Effect Models to evaluate the relationship of anuran morphological traits, number of prey taxa and volume of consumed prey. We tested the hypothesis that the configuration of predator morphological traits determines variations in prey consumption patterns. Our results indicate that the body size of L. luctator was not directly related to the diet composition but the individuals’ gape is directly and positively related to the number of consumed taxa. This suggests that gape limitation could be a limiting factor in prey selection. The capacity to consume a wide variety of prey taxa could be an advantage in unpredictable environments, especially those with great daily thermal amplitudes such as the subtropical Brazilian grasslands. Keywords: Leptodactylus luctator, diet, amphibian, ecomorphology, functional ecology

Clinical Characterization of New-Onset Chronic Musculoskeletal Pain in Long COVID: A Cross-Sectional Study.

New-onset chronic musculoskeletal (MSK) pain is one of the common persistent symptoms in Long COVID (LC). This study investigated its clinical characteristics, underlying mechanisms, and impact on function, psychological health, and quality of life. Thirty adults (19 female, 11 male) with LC and new-onset chronic MSK pain underwent clinical examination, Quantitative Sensory Testing (QST), and blood tests for inflammatory markers and completed the following outcome measures: Timed Up and Go test (TUG), handgrip strength test, COVID-19 Yorkshire Rehabilitation Scale (C19-YRS), Brief Pain Inventory (BPI), Pain Self-Efficacy Questionnaire (PSEQ), Pain Catastrophizing Scale (PCS), International Physical Activity Questionnaire-short form (IPAQ-sf), Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), and EuroQol Five Dimensions health-related quality of life (EQ-5D-5L). New-onset chronic MSK pain was widespread and continuous in nature, and worse in the joints. When compared to normative values reported in the literature: a) QST revealed mechanical hyperalgesia, heightened temporal summation of pain, and hypoesthesia to vibration stimuli, which is strongly suggestive of central sensitization; b) Plasma cytokine assays indicated distinct pro-inflammatory profiles; c) TUG time indicated reduced balance and mobility; d) handgrip strength revealed general weakness; e) physical activity was lower; and f) there were moderate levels of depression and anxiety with lower self-efficacy scores and lower levels of pain catastrophizing. LC symptoms were of moderate severity (44.8/100), moderate functional disability (22.8/50) and severely compromised overall health (2.6/10) when compared to pre-COVID scores. New-onset chronic MSK pain in LC tends to be widespread, constant, and associated with weakness, reduced function, depression, anxiety, and reduced quality of life. There is associated central sensitization and proinflammatory state in the condition. Further research is essential to explore the longitudinal progression and natural evolution of the new-onset chronic MSK pain in LC.

Longitudinal Follow Up of Patients Colonized with Clostridioides difficile: a Retrospective Cohort Study

Background: Patients colonized with Clostridioides difficile are at risk of transmitting C. difficile to other patients, and of developing C. difficile infection (CDI). Known risk factors for carriage include previous hospitalization, gastric acid suppression and previous CDI. Data regarding duration of carriage and its predictors are lacking but could be useful to better understand the natural evolution of carriage and better estimate the likelihood of transmission or progression to CDI. Methods: We performed a retrospective cohort study of C. difficile colonized patients with > = 1 admission to a tertiary academic institution between November 2013 and January 2017. Colonization status was determined upon hospital admission by detection of TcdB gene by polymerase chain reaction on a rectal screening swab, as part of a systematic screening program. Overall duration of carriage and predictors of prolonged carriage were explored using Kaplan-Meier methods and Cox regression. Results: There were 134 patients, who after having a positive initial screening test (and therefore identified as colonized with C. difficile), had subsequent testing. The median age was 77 years (IQR, 66 to 85), and 53.6% of the patients were female. After hospital discharge, 26 (19.4%) colonized patients progressed to CDI. Mean duration of follow up was 269 days, with a median of 179 days. Median duration of carriage was 211 days, (95% confidence interval (CI) [157, 264]). Predictors associated with decreased duration of C. difficile colonization included younger age (HR per unit decrease (year), 1.013; 95% CI, 1.025 to 1.001; p=0.03), and receipt of antibiotics in the 3 months prior to first admission (mean days to clearance of patients with and without recent antibiotic use, 252 days vs 372 days, respectively; HR, 1.55; 95% CI, 1.01 to 2.36; p < 0 .04). By contrast, the presence of comorbidities (e.g. heart failure, diabetes, cancer, and chronic kidney disease), the use of proton-pump inhibitors (PPIs), the receipt of antibiotics during the first admission, and the duration of first hospitalization were not associated with significant differences in duration of carriage. Conclusion: This study is the largest cohort of C. difficile carriers with longitudinal follow up of their colonization status. It highlights the extended duration of carrier status especially in older patients and identifies predictors of prolonged carriage. Further studies are needed to understand the underlying relationship with the predictors identified in this study.

Evolutionary nature of puffed-up stripped star binaries and their occurrence in stellar populations

The majority of massive stars are formed in multiple systems, and at some point during their life, they interact with their companions via mass transfer. This interaction typically leads to the primary shedding its outer envelope, resulting in the formation of a “stripped star”. Classically, stripped stars are expected to quickly contract to become hot and UV-bright helium stars. Surprisingly, recent optical spectroscopic surveys have unveiled many stripped stars that are much larger and cooler, appearing “puffed up” and overlapping with the Main Sequence (MS) in the Hertzsprung–Russell diagram. Here, we study the evolutionary nature of puffed-up stripped (PS) stars and the duration of this enigmatic phase using the stellar-evolution code MESA. We computed grids of binary models at four metallicities: Solar (Z⊙ = 0.017), Large Magellanic Cloud (LMC, Z = 0.0068), Small Magellanic Cloud (SMC, Z = 0.0034), and Z = 0.1 Z⊙. Contrary to previous assumptions, we find that stripped stars regain thermal equilibrium shortly after the end of mass transfer and maintain it during most of the PS phase. Their further contraction towards hot and compact He stars is determined by the rate at which the residual H-rich envelope is depleted, with the main agents being H-shell burning (dominant for M ≲ 50 M⊙) and mass-loss in winds. The duration of the PS star phase is approximately 10% of the core-He burning lifetime (1% total lifetime) and up to 100 times more than the thermal timescale. It decreases with increasing mass and luminosity and increases with metallicity. We explored several factors influencing PS star lifetimes: orbital period, mass ratio, winds, and semiconvection. We further carried out a simple binary population synthesis estimation, finding that ∼0.5–0.7% of all the stars with log (L/L⊙) > 3.7 may, in fact, be PS stars. Our results indicate that tens to hundreds of PS stars in post-interaction binaries may be hiding in the MS population, disguised as ‘normal’ stars: ∼100 (∼280) in the SMC (LMC) and ∼1500 in the Milky Way. Their true nature may be revealed by spectroscopically measured low surface gravities, high N enrichment, and likely slow rotation rates.

Non-Gaussian Ensemble Optimization

Ensemble-based optimization (EnOpt), commonly used in reservoir management, can be seen as a special case of a natural evolution algorithm. Stein’s lemma gives a new interpretation of EnOpt. This interpretation enables us to study EnOpt in the context of general mutation distributions. In this paper, a non-Gaussian generalization of EnOpt (GenOpt) is proposed, where the control gradient is estimated using Stein’s lemma, and the mutation distribution is updated separately via natural evolution. For the multivariate case, a Gaussian copula is used to represent dependencies between the marginals. The correlation matrix is also iteratively optimized. It is shown that using beta distributions as marginals in the GenOpt algorithm addresses the truncation problem that sometimes arises when applying EnOpt on bounded optimization problems. The performance of the proposed optimization algorithm is evaluated on several test cases. The experiments indicate that GenOpt is less dependent on the chosen hyperparameters, and it is able to converge more quickly than EnOpt on a reservoir management test case.

Genetic Algorithm-Based Optimization of Clustering Algorithms for the Healthy Aging Dataset

Clustering is a crucial and, at the same time, challenging task in several application domains. It is important to incorporate the optimum feature finding into our clustering algorithms for better exploration of features and to draw meaningful conclusions, but this is difficult when there is no or little information about the importance or relevance of features. To tackle this task in an efficient manner, we employ the natural evolution process inherent in genetic algorithms (GAs) to find the optimum features for clustering the healthy aging dataset. To empirically verify the findings, genetic algorithms were combined with a number of clustering algorithms, including partitional, density-based, and agglomerative clustering algorithms. A variant of the popular KMeans algorithm, named KMeans++, gave the best performance on all performance metrics when combined with GAs.

Reactive transport modelling as a toolbox to compare remediation strategies for aquifers impacted by uranium in situ recovery

More than 60% of worldwide uranium production is based on the In Situ Recovery mining technique. This exploitation method directly falls within the scope of the applications of reactive transport modelling to optimize uranium production and limit its associated environmental impact. We propose a modelling approach which is able to represent the natural evolution of an aquifer impacted by an ISR test performed using sulfuric acid. The model is calibrated on a 12 year-long data series obtained from 12 monitoring wells surrounding an ISR pilot cell. Through this process-based approach, we simulate the impact of several remediation strategies that can be considered in these contexts. In particular, we model the impact of Pump & Treat combined with reverse osmosis, as well as the circulation of non-impacted fluids through the reservoir with different operating strategies. Our approach allows to compare the effectiveness of these strategies. For this small-scale ISR pilot, monitored natural attenuation constitutes an interesting approach due to its faster pH recovery time with respect to Pump & Treat (5–10 years to pH ∼ 6), whose efficiency can be improved by the addition of exchangeable cations. Circulation of unimpacted fluids can reduce pH recovery times if performed for periods longer than the ISR exploitation and/or deployed with a delay. Combined with an economic evaluation of their deployment, this modelling approach can help the mining operator select and design optimal remediation strategies from an environmental and economical standpoint.

The territorial nature and power of human capital in urban development processes from the perspective of the path dependence concept

Knowledge and human capital are gaining importance as determinants of urban and regional development on a global scale. We can observe a simultaneous increase in the mobility of human capital, the availability of knowledge, and an increase in the importance of location. This phenomenon is sometimes referred to as glocalisation. Mobile and highly valuable human capital are being territorialised. From the city’s point of view, is this an opportunity or a threat? The question can be asked whether the territorialisation of human capital has an impact on the durability of urban development. It is not obvious whether it helps to develop competitive potential and competitive advantages of an area only temporarily or in the long term. An analysis using elements of the path dependency theory can provide answers to these questions. It considers both the complexity of the research subject and the evolutionary nature of development processes. Therefore, the fundamental question of this article is whether the territorialisation of human capital affects the durability of urban development. The main findings of the study show that both the size of a city and the rate of demographic growth affect the choice of the type of development path. Cities with high demographic growth rates and complex development strategies enter reactive paths. This type of path guarantees the durability of development processes.

Antimicrobial resistance among clinically significant bacteria in wildlife: An overlooked one health concern

Antimicrobial resistance (AMR) has emerged as a critical global health challenge. However, the significance of AMR is not limited to humans and domestic animals but extends to wildlife and the environment. Based on the analysis of > 200 peer-reviewed papers, this review provides comprehensive and current insights into the detection of clinically significant antimicrobial resistant bacteria and resistance genes in wild mammals, birds and reptiles worldwide. The review also examines the overlooked roles of wildlife in AMR emergence and transmission. In wildlife, AMR is potentially driven by anthropogenic activity, agricultural and environmental factors, and natural evolution. This review highlights the significance of AMR surveillance in wildlife, identifies species and geographical foci and gaps, and demonstrates the value of multifaceted One Health strategies if further escalation of AMR globally is to be curtailed.

PBP-A, a cyanobacterial dd-peptidase with high specificity for amidated muropeptides, exhibits pH-dependent promiscuous activity harmful to Escherichia coli

Penicillin binding proteins (PBPs) are involved in biosynthesis, remodeling and recycling of peptidoglycan (PG) in bacteria. PBP-A from Thermosynechococcus elongatus belongs to a cyanobacterial family of enzymes sharing close structural and phylogenetic proximity to class A β-lactamases. With the long-term aim of converting PBP-A into a β-lactamase by directed evolution, we simulated what may happen when an organism like Escherichia coli acquires such a new PBP and observed growth defect associated with the enzyme activity. To further explore the molecular origins of this harmful effect, we decided to characterize deeper the activity of PBP-A both in vitro and in vivo. We found that PBP-A is an enzyme endowed with dd-carboxypeptidase and dd-endopeptidase activities, featuring high specificity towards muropeptides amidated on the d-iso-glutamyl residue. We also show that a low promiscuous activity on non-amidated peptidoglycan deteriorates E. coli’s envelope, which is much higher under acidic conditions where substrate discrimination is mitigated. Besides expanding our knowledge of the biochemical activity of PBP-A, this work also highlights that promiscuity may depend on environmental conditions and how it may hinder rather than promote enzyme evolution in nature or in the laboratory.

Insight into the Dynamic Nature of the Pt-CeO2 Interface in Dry Reforming of Methane.

Single-atom catalysts (SACs) are attractive in one-carbon (C1) chemistry because of their high atom efficiency. However, it is a great challenge for understanding the dynamic roles of SACs under operating conditions. Here, isolated Pt atoms trapped on defective CeO2 surface are investigated by experiments, especially operando techniques, which offers basic understanding of the nature and dynamic evolution of the Pt-CeO2 interface in dry reforming of methane (DRM). The Pt-Olattice configuration is highly active for CH4 dissociation at the expense of the Olattice atoms, which in turn promotes the H-assisted dissociation of CO2. The transformation of Pt atoms between positive and metallic states is driven by the DRM reaction, which is essential for rendering highly efficient catalysis. The dynamic evolution of Pt atoms favors to eliminate the reactive intermediates, such as carbonates and formates. The dynamic nature of the Pt-CeO2 interface in the DRM reaction shows a similar picture to the Yin and Yang transformation in ancient Chinese Tai Ji wisdom.

Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus.

Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance development and elucidate underlying genetic changes against three antiviral substances. Our analyzes reveal no principle difference in the evolutionary behavior of both viruses, adaptive processes are overall similar, however significantly accelerated for the hypermutator. We conclude that hypermutator viruses are useful for modeling adaptation to antiviral therapy. They offer the benefit of expedited adaptation without introducing apparent bias and can therefore serve as an accelerator to predict natural evolution.

Latarjet Classics: An Analysis of The 50 Most-Cited Articles on The Latarjet Procedure

Purpose: The Latarjet procedure was initially described by Michel Latarjet in 1954 as a treatment for recurrent dislocations of the shoulder. Over the last decade, an arthroscopic approach has emerged as the natural evolution of the open procedure. The purpose of this study was to identify and analyze the fifty most-cited articles related to the Latarjet, analyze the associated characteristics of each article, and to evaluate whether surgeons are currently influenced by primarily higher versus lower-level studies. Methods: Various Boolean queries were searched on the Clarivate Analytics Web of Science, which yielded final search terms of topics on “latarjet OR latarjet-bristow OR bristow-latarjet OR latarjet-patte or patte-latarjet”. Information collected included: author demographics, study type, level of evidence, journal name, number of citations, and publication year. Results: The top fifty Latarjet articles had 5,319 citations and consisted of 0 level I, 3 level II, 8 level III, 25 level IV and 14 level V studies (date range: 1983 – 2017, median 2012). The most cited article received 454 citations. Authors from France (n = 14, 27%) contributed the most to included papers, followed by the United States (n = 8, 16%). Conclusions: The most-cited articles on the Latarjet procedure tend to be case series, cohort studies, and expert opinions published primarily by French and American authors between 2000 and 2016. With the recent technical innovation surrounding the Latarjet procedure and glenoid bone-block reconstruction in general, these articles may form the foundation that future higher level-of-evidence studies will build upon in their research.

Chemical nature evolution of solid supports used in electromembrane extraction procedures: A comparative analysis based on metric tools

BackgroundIn recent decades, green chemistry has been focusing on the adaptation of different chemical methods towards environmental friendliness. Sample preparation procedures, which constitute a fundamental step in analytical methodology, have also been modified and implemented in this direction. In particular, electromembrane extraction (EME) procedures, which have traditionally used plastic supports, have been optimized towards greener approaches through the emergence of alternative materials. In this regard, biopolymer-based membranes (such as agarose or chitosan) have become versatile and very promising substitutes to perform these processes. ResultsDifferent green metric tools (Analytical Eco-Scale, ComplexGAPI and AGREEprep have been applied to study the evolution of solid supports used in EME from nanostructured tissues and polymer inclusion membranes to agar films and chitosan flat membranes. The main goal is to evaluate the usage of these new biomaterials in the analytical procedure to quantify their environmental impact in the frame of Green Analytical Chemistry (GAC). In addition, both RGB model and BAGI metrics have been employed to study the sustainability of the whole procedure, including not only greenness, but also analytical performance and feasibility aspects. Results obtained after the performance of the mentioned metrics have demonstrated that the most efficient and environmentally friendly analytical methods are based on the use of chitosan supports. This improvement is mainly due to the chemical nature of this biopolymer as well as to the removal of organic solvents. SignificanceThis work highlights the advantages of biodegradable materials employment in EME procedures to achieve green analytical methodologies. These materials also contribute to raise the figure of merits regarding to the quantification parameters in a wide range of applications compared to classical supports employed in EME, thus enhancing sustainability of procedures.

Elucidating the Enzymatic Mechanism of Dihydrocoumarin Degradation: Insight into the Functional Evolution of Methyl-Parathion Hydrolase from QM/MM and MM MD Simulations.

Methyl-parathion hydrolase (MPH), which evolved from dihydrocoumarin hydrolase, offers one of the most efficient enzymes for the hydrolysis of methyl-parathion. Interestingly, the substrate preference of MPH shifts from the methyl-parathion to the lactone dihydrocoumarin (DHC) after its mutation of five specific residues (R72L, L273F, L258H, T271I, and S193Δ, m5-MPH). Here, extensive QM/MM calculations and MM MD simulations have been used to delve into the structure-function relationship of MPH enzymes and plausible mechanisms for the chemical and nonchemical steps, including the transportation and binding of the substrate DHC to the active site, the hydrolysis reaction, and the product release. The results reveal that the five mutations remodel the active pocket and reposition DHC within the active site, leading to stronger enzyme-substrate interactions. The MM/GBSA-estimated binding free energies are about -20.7 kcal/mol for m5-MPH and -17.1 kcal/mol for wild-type MPH. Furthermore, this conformational adjustment of the protein may facilitate the chemical step of DHC hydrolysis and the product release, although there is a certain influence on the substrate transport. The hydrolytic reaction begins with the nucleophilic attack of the bridging OH- with the energy barriers of 22.0 and 18.0 kcal/mol for the wild-type and m5-MPH enzymes, respectively, which is rate-determining for the entire process. Unraveling these mechanistic intricacies may help in the understanding of the natural evolution of enzymes for diverse substrates and establish the enzyme structure-function relationship.

ENHANCING FASHION FORECASTING ACCURACY THROUGH CONSUMER DATA ANALYTICS: INSIGHTS FROM CURRENT LITERATURE

The fashion industry is characterized by its fast-paced nature and constant evolution of consumer preferences, making accurate fashion forecasting essential for brands to remain competitive. Traditional forecasting methods, which rely heavily on historical sales data and expert intuition, are increasingly being complemented or replaced by advanced consumer data analytics. This article explores the integration of consumer data analytics into fashion forecasting, drawing insights from recent literature. By examining methodologies such as machine learning, big data analytics, and AI, as well as utilizing diverse data sources including social media, online shopping behaviors, and mobile data, this study highlights the significant improvements in trend prediction accuracy and operational efficiency. Key findings indicate that data-driven approaches provide more precise and real-time insights into consumer preferences, enabling brands to better anticipate market demands and optimize inventory management. The discussion underscores the transformative potential of consumer data analytics in enhancing the overall effectiveness of fashion forecasting.

Dent's Disease: A Cause of Monogenic Kidney Stones and Nephrocalcinosis.

Kidney stones are becoming increasingly common, affecting up to 10% of adults. A small percentage are of monogenic origin, such as Dent's disease (DD). DD is a syndrome that causes low-molecular-weight proteinuria, hypercalciuria, nephrolithiasis, and nephrocalcinosis. It is X-linked, and most patients have mutations in the CLCN5 gene. We performed a review of the literature and evaluated the case series (n = 6) of a single center in Spain, reviewing the natural evolution of kidney stones, clinical implications, laboratory analyses, radiological development, and treatment. All patients had a genetically confirmed diagnosis, with the CLCN5 mutation being the most frequent (66%). All patients had proteinuria and albuminuria, while only two and three presented hypercalciuria and phosphate abnormalities, respectively. Only one patient did not develop lithiasis, with most (60%) requiring extracorporeal shock wave lithotripsy or surgery during follow-up. Most of the patients are under nephrological follow-up, and two have either received a renal transplant or are awaiting one. The management of these patients is similar to that with lithiasis of non-monogenic origin, with the difference that early genetic diagnosis can help avoid unnecessary treatments, genetic counseling can be provided, and some monogenic kidney stones may benefit from targeted treatments.

Leveraging the histidine kinase-phosphatase duality to sculpt two-component signaling

Bacteria must constantly probe their environment for rapid adaptation, a crucial need most frequently served by two-component systems (TCS). As one component, sensor histidine kinases (SHK) control the phosphorylation of the second component, the response regulator (RR). Downstream responses hinge on RR phosphorylation and can be highly stringent, acute, and sensitive because SHKs commonly exert both kinase and phosphatase activity. With a bacteriophytochrome TCS as a paradigm, we here interrogate how this catalytic duality underlies signal responses. Derivative systems exhibit tenfold higher red-light sensitivity, owing to an altered kinase-phosphatase balance. Modifications of the linker intervening the SHK sensor and catalytic entities likewise tilt this balance and provide TCSs with inverted output that increases under red light. These TCSs expand synthetic biology and showcase how deliberate perturbations of the kinase-phosphatase duality unlock altered signal-response regimes. Arguably, these aspects equally pertain to the engineering and the natural evolution of TCSs.

Weather-Based Prediction of Power Consumption in District Heating Network: Case Study in Finland

Accurate prediction of energy consumption in district heating systems plays an important role in supporting effective and clean energy production and distribution in dense urban areas. Predictive models are needed for flexible and cost-effective operation of energy production and usage, e.g., using peak shaving or load shifting to compensate for heat losses in the pipeline. This helps to avoid exceedance of power plant capacity. The purpose of this study is to automate the process of building machine learning (ML) models to solve a short-term power demand prediction problem. The dataset contains a district heating network’s measured hourly power consumption and ambient temperature for 415 days. In this paper, we propose a hybrid evolutionary-based algorithm, named GA-SHADE, for the simultaneous optimization of ML models and feature selection. The GA-SHADE algorithm is a hybrid algorithm consisting of a Genetic Algorithm (GA) and success-history-based parameter adaptation for differential evolution (SHADE). The results of the numerical experiments show that the proposed GA-SHADE algorithm allows the identification of simplified ML models with good prediction performance in terms of the optimized feature subset and model hyperparameters. The main contributions of the study are (1) using the proposed GA-SHADE, ML models with varying numbers of features and performance are obtained. (2) The proposed GA-SHADE algorithm self-adapts during operation and has only one control parameter. There is no fine-tuning required before execution. (3) Due to the evolutionary nature of the algorithm, it is not sensitive to the number of features and hyperparameters to be optimized in ML models. In conclusion, this study confirms that each optimized ML model uses a unique set and number of features. Out of the six ML models considered, SVR and NN are better candidates and have demonstrated the best performance across several metrics. All numerical experiments were compared against the measurements and proven by the standard statistical tests.

Bamboo-inspired lightweight, mechanically-stable and vibration-damping structural members for engineering applications

After millions of years of natural evolution, bamboo stems have formed exquisite variable cross-section hollow multi-node structures that are lightweight, tough, and stable. Bamboo is difficult to break and damage from the roots under dynamic loads, providing an important reference for te biomimetic design of lightweight components. This paper investigates the structural characteristics and variation patterns of bamboo stems and subsequently proposes an imitation bamboo stem structure design strategy for engineering structural members, namely, imitation bamboo double-jointed columns (IDJC). We establish a macro scale finite element model to predict the mechanical properties and failure modes of the IDJC under cyclic bending loads, and validate the model using experimental and analytical methods. The simulation and experimental results show that compared with traditional double-jointed columns (DJC), the weight of the IDJC is reduced by 41.7 %. Under bending load, the compressive stress of each section is approximately equal, reducing stress concentration, and increasing bending resistance. The strength to weight ratio of IDJC is 1.96 times that of DJC, indicating lightweight and high-strength characteristics. The stiffness degradation, energy dissipation, and damping and vibration reduction performance of the IDJC were also evaluated. The results showed that compared with the DJC, the stiffness degradation rate of the IDJC decreased by 6.87 times, the energy dissipation rate increased by 1.07 times, and the damping and vibration reduction performance improved by 48.40 %, reflecting a high stability and robust vibration reduction performance. The results demonstrate the potential application of biomimetic structures for the development and design of resource-rich, low-carbon, and sustainable bamboo for bamboo engineering members with excellent performance and functionality. Biomimetic structures have great potential in replacing nonrenewable structural materials in the fields of civil engineering and transportation.