Branch Research Articles

NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model.

Copy number aberrations (CNAs) are ubiquitous in many types of cancer. Inferring CNAs from cancer genomic data could help shed light on the initiation, progression, and potential treatment of cancer. While such data have traditionally been available via "bulk sequencing," the more recently introduced techniques for single-cell DNA sequencing (scDNAseq) provide the type of data that makes CNA inference possible at the single-cell resolution. We introduce a new birth-death evolutionary model of CNAs and a Bayesian method, NestedBD, for the inference of evolutionary trees (topologies and branch lengths with relative mutation rates) from single-cell data. We evaluated NestedBD's performance using simulated data sets, benchmarking its accuracy against traditional phylogenetic tools as well as state-of-the-art methods. The results show that NestedBD infers more accurate topologies and branch lengths, and that the birth-death model can improve the accuracy of copy number estimation. And when applied to biological data sets, NestedBD infers plausible evolutionary histories of two colorectal cancer samples. NestedBD is available at https://github.com/Androstane/NestedBD .

Modeling branch attributes and biomass for Catalpa bungei plantations under various fertilization regimes

The development and morphology of branches, a crucial step in producing high-quality large-diameter lumber, may be influenced by fertilization. The response of branch attributes to different fertilization regimes, however, is still poorly understood. The Catalpa bungei plantations, which had been growing for 6 years in northern China, were chosen to study how various fertilization measures affected branch attributes. The two fertilization techniques used were hole fertilization (HF) and water and fertilizer integration (WF), with no fertilization (CK) as a control. The quantity, density, morphology (e.g., diameter, length, and angle), and position (e.g., height and orientation) of branches, and organ biomass of 18 standard trees (total of 516 branches) were investigated. The results demonstrated a considerable increase in tree height, diameter at breast height (DBH), canopy ratio, branch quantity, and organ biomass following the addition of fertilizer. Both the maximum branch diameter and the number of branches rose with fertilization. Following fertilization, the number of branches rose by 16% (HF) and 28% (WF) compared to non-fertilized trees, while the maximum branch diameter increased by 3.5% (HF) and 17.3% (WF), respectively. WF led to an increase in the number of branches and largest branch diameter in comparison to CK and HF. The length, angle, and diameter of branches, however, were not affected significantly by different fertilization treatments. There were roughly equal amounts of branches in four orientations. The mixed-model analysis revealed that the number of branches was positively correlated with branch density and tree height. The branch diameter increased with the increase of branch length and angle. The branch length was negatively correlated with branch height and angle. The branch angle showed a larger angle at the bottom of the canopy. Tree height plus diameter at breast height combined, or just the diameter at breast height indicator alone, can both reliably predict the total biomass of trees. The branch models created in this research may offer some theoretical backing for understanding the crown dynamics of valuable tree species in northern China.

An image segmentation and point cloud registration combined scheme for sensing of obscured tree branches

Automated robots are emerging as a solution for labor-intensive fruit orchard management. Three-dimensional (3D) reconstruction of tree branches is a fundamental requirement for robots to perform tasks like pruning and fruit harvesting. Current branch sensing methods often rely on planar segmentation with limited 3D information or computationally expensive point cloud segmentation, which may not be suitable for natural orchards with obscured tree branches. This study proposes a novel scheme that reconstructs occluded branches from RGB-D (Red-Green-Blue-Depth) images by integrating the point clouds converted from planar segmentation masks and depth images. The proposed approach extends the existing 2D branch sensing techniques to 3D, leveraging multi-view information. The deep learning models DeeplabV3+ and Pix2pix are employed to generate the segmentation masks, separately. And the Fast Global Registration (FGR) is used to register the multi-view point clouds. The results demonstrate that the output point clouds have at least a 24 % increase in the number of corresponding points after FGR. Furthermore, the time cost per hundred corresponding points is reduced by 85 % and 69 % when using the DeepLabV3 + and Pix2pix-based schemes, respectively, compared to the PointNet++ approach. These findings indicate that the proposed scheme significantly improves the sensing of occluded branches in terms of output richness and computational efficiency, making it applicable to natural orchard working spaces.

Properties of Forest Tree Branches as an Energy Feedstock in North-Eastern Poland

Tree branches from forest tree harvesting for the timber industry are an important energy feedstock. Solid biofuel in the form of wood chips, produced from branches, is an excellent renewable energy source for generating heat and electricity. However, the properties of wood chips as a solid biofuel produced from forest tree branches can vary greatly depending on the species from which they have been produced. Therefore, this study aimed to assess the thermophysical properties and elemental composition of fresh branches harvested from nine tree species (pedunculate oak, silver birch, European ash, common aspen, grey alder, Norway maple, Scots pine, European larch and Norway spruce) over three consecutive years (2020–2022). The branches of the tree species most commonly found in Polish forests (Scots pine) were characterized by the highest heating value (an average of 20.74 GJ Mg−1 DM), the highest carbon content (an average of 55.03% DM), the lowest ash (an average of 0.60% DM) and nitrogen contents (an average of 0.32% DM), and low sulfur (an average of 0.017% DM) and chlorine contents (an average of 0.014% DM). A cluster analysis showed that the branches of all three coniferous tree species (Scots pine, Norway spruce and European larch) formed one common cluster, indicating similar properties. The branches of the European ash were characterized by the lowest wood moisture content (an average of 37.19% DM) and thus the highest lower heating value (an average of 10.50 GJ Mg−1). During the three years of the study, the chlorine and ash contents of the branches of the tree species under study exhibited the highest variability.

Analysis of the characteristics and causes of city gas explosion accidents based on DT-AR algorithm

In order to effectively prevent and control accidents, it is essential to trace back the causes of gas explosions in cities. The DT-AR(decision tree-association rule) algorithm is proposed as a quantitative analysis of gas accident features and causality. First, 210 gas explosion accident investigation reports were taken as samples. The gas accident causation system is divided into three aspects, including environmental factors, management factors and physical factors. Management factors were sorted into organizational-level and individual-level factors from the investigation reports. Second, the CART decision tree model was used to compare location features, organizational causality features, and individual causality features of the piped and bottled gas accidents, and a decision tree model with the gas system fault site as the root node was built to filter the key feature variables. In order to reveal factor correlations and deep-level causation, the Apriori algorithm is used to mine accident association rules. The combinations on the branches of the decision tree are used as constraints to filter the critical causality rule, which improves the efficiency of association rule screening and enhances prediction accuracy. The results demonstrate that the DT-AR algorithm can evaluate the importance of variables, quickly locate effective combinations of factors, and mine the complete causal chain. The association rule is screened based on the constraint of the key element combination of the decision tree, which compensates for the low efficiency of the Apriori algorithm for association rule mining. In addition, the accident-caused excavation results provide an effective path for gas companies, outsourced service companies and administrative departments to implement gas safety chain supervision, which can address the problem of gas accident safety management failures and provide decision support for accident prevention.

A novel jujube tree trunk and branch salient object detection method for catch-and-shake robotic visual perception

Visual perception has become a prerequisite for automated jujube harvesting robot operations under complex orchard conditions. Catch-and-Shake harvesting, as the most efficient and common harvesting method, has widely been applied on various manually operated harvesters to complete large-area jujube fruit harvesting. However, the main factors restricting the development of existing harvesters are labor shortage, high labor cost, and low operating efficiency. To address the issues, we designed a catch-and-shake harvesting robot for jujube tree trunks and branches visual perception that can provide a barrier-free catch-and-shake operation area and guide the manipulator to reach the area to complete the harvesting operation. Meanwhile, a visual perception system including tree trunks and branches detection, skeleton extraction, catch-and-shake area confirmation was presented to guide robot intelligent operations. In the visual perception system, a novel salientobjectdetectionmodel called feature intersection and fusion Transformer (FIT-Transformer) network was proposed to split branches and background to provide reference for determining safe catch-and-shake areas. Moreover, we designed a diverse feature aggregation (DFA) and an attention feature fusion module (AFFM) to strengthen feature learning capabilities and obtain robust perception models. Comparative experimental results showed that our proposed FIT-Transformer model outperformed 12 state-of-the-art (SOTA) algorithms including C2FNet, RAS, BASNet, U2Net, SCRNet, PiCANet, EDRNet, EGNet, ICONR, VST, TransSOD and ABiU_Net. Specifically, the segmentation accuracy of jujube tree trunks and branches using our method showed the satisfactory result on five evaluation indexes under natural environment (the EM, SM, WF, FM and MAE reached 0.9713, 0.8991, 0.8854, 0.8905, and 0.0302, respectively). Field experiments also proved that our method could meet the requirements of operational accuracy and real-time operations.

Seasonal patterns of nonstructural carbohydrate storage and mobilization in two tree species with distinct life-history traits.

Nonstructural carbohydrates (NSC) are essential for tree growth and adaptation, yet our understanding of the seasonal storage and mobilization dynamics of whole-tree NSC is still limited, especially when tree functional types are involved. Here, Quercus acutissima Carruth. and Pinus massoniana Lamb, with distinct life-history traits (i.e. a deciduous broadleaf species vs an evergreen coniferous species), were studied to assess the size and seasonal fluctuations of organ and whole-tree NSC pools with a focus on comparing differences in carbon resource mobilization patterns between the two species. We sampled the organs (leaf, branch, stem and root) of the target trees repeatedly over four seasons of the year. Then, NSC concentrations in each organ were paired with biomass estimates from the allometric model to generate whole-tree NSC pools. The seasonal dynamics of the whole-tree NSC of Q. acutissima and P. massoniana reached the peak in autumn and summer, respectively. The starch pools of the two species were supplemented in the growing season while the soluble sugar pools were the largest in the dormant season. Seasonal dynamics of organ-level NSC concentrations and pools were affected by organ type and tree species, with above-ground organs generally increasing during the growing season and P. massoniana roots decreasing during the growing season. In addition, the whole-tree NSC pools of P. massoniana were larger but Q. acutissima showed larger seasonal fluctuations, indicating that larger storage was not associated with more pronounced seasonal fluctuations. We also found that the branch and root were the most dynamic organs of Q. acutissima and P. massoniana, respectively, and were the major suppliers of NSC to support tree growth activities. These results provide fundamental insights into the dynamics and mobilization patterns of NSC at the whole-tree level, and have important implications for investigating environmental adaptions of different tree functional types.

Morphological estimation of primary branch length of individual apple trees during the deciduous period in modern orchard based on PointNet++

Primary branch length is an important morphological trait of individual apple tree phenotypes. This study presents a novel method for estimating the primary branch lengths of individual apple trees during the deciduous period by distinguishing their instances, i.e., merging those belonging to the same primary branch based on part segmentation outputs of PointNet++. Firstly, colored and colorless 3D-datasets were prepared for training PointNet++ models. The model with higher overall accuracy (OA), class average accuracy (CAA), and mean intersection-over-union (mIoU) was employed to segment the point cloud of a tree into primary branches (PB), trunk (TK), and end-points of primary branches (EPB) of individual apple trees. Skeletonization was applied to the outputs of the three parts of individual apple trees. Subsequently, each primary branch instance was distinguished by determining its corresponding path and retaining the longest path of the same primary branch only. Finally, the primary branch length was estimated by calculating the sum of Euclidean distances between adjacent points on the corresponding path. Results indicated that adding color to point clouds did not improve segmentation accuracy of PointNet++ on segmenting PB, TK, and EPB with similar color features. The PointNet++ model that was trained without color achieved an OA, CAA, and mIoU of 0.84, 0.83, and 0.70, respectively. The proportion of estimated and ground-truth values of the number of primary branches was 93.64 %. The mean absolute percentage error of estimating primary branch lengths was 12.00 %. These findings demonstrate that the proposed method is promising for high-throughput phenotyping of apple trees.

Using Reinforcement Learning to Select an Optimal Feature Set

Feature Selection (FS) is an essential research topic in the area of machine learning. FS, which is the process of identifying the relevant features and removing the irrelevant and redundant ones, is meant to deal with the high dimensionality problem for the sake of selecting the best performing feature subset. In the literature, many feature selection techniques approach the task as a research problem, where each state in the search space is a possible feature subset. In this paper, we introduce a new feature selection method based on reinforcement learning. First, decision tree branches are used to traverse the search space. Second, a transition similarity measure is proposed so as to ensure exploit‐explore trade‐off. Finally, the informative features are the most involved ones in constructing the best branches. The performance of the proposed approaches is evaluated on nine standard benchmark datasets. The results using the AUC score show the effectiveness of the proposed system.

Generating lymphoma ultrasound image description with transformer model

Lymphoma, the most prevalent hematologic tumor originating from the lymphatic hematopoietic system, can be accurately diagnosed using high-resolution ultrasound. Microscopic ultrasound performance enables clinicians to identify suspected tumors and subsequently obtain a definitive pathological diagnosis through puncture biopsy. However, the complex and diverse ultrasonographic manifestations of lymphoma pose challenges for accurate characterization by sonographers. To address these issues, this study proposes a Transformer-based model for generating descriptive ultrasound images of lymphoma, aiming to provide auxiliary guidance for ultrasound doctors during screening procedures. Specifically, deep stable learning is integrated into the model to eliminate feature dependencies by training sample weights. Additionally, a memory module is incorporated into the model decoder to enhance semantic information modeling in descriptions and utilize learned semantic tree branch structures for more detailed image depiction. Experimental results on an ultrasonic diagnosis dataset from Shanghai Ruijin Hospital demonstrate that our proposed model outperforms relevant methods in terms of prediction performance.

Surgical interpretation of the WHO subclassification of intrahepatic cholangiocarcinoma: a narrative review.

Intrahepatic cholangiocarcinoma (iCCA) has been subclassified by its gross morphology into the mass-forming (MF), periductal-infiltrating (PI), and intraductal growth (IG) types and their combinations. This classification correlates well with clinical features; for example, MF-iCCA has less lymph-node metastasis and a better prognosis than PI-iCCA. According to the recently accumulated evidence from histological investigations, the WHO classification endorsed a subclassification scheme in which iCCA cases are classified into small- and large-duct types. Small-duct iCCA is considered to originate from septal or smaller bile ducts and is characterized by less frequent lymph-node metastasis, a favorable prognosis, and an MF appearance. Large-duct iCCA arises around the second branch of the biliary tree and has more aggressive biology and distinct genetic abnormalities. According to the practice guidelines for iCCA from the Liver Cancer Study Group of Japan and the National Comprehensive Cancer Network, upfront surgery is recommended for iCCA without distant metastasis regardless of the morphological subtype, based on clinical experience. In consideration of the biological heterogeneity of iCCA, the treatment strategy for iCCA needs to be reconsidered based on the WHO subtypes.

Synchronized Expansion and Contraction of Olfactory, Vomeronasal, and Taste Receptor Gene Families in Hystricomorph Rodents.

Chemical senses, including olfaction, pheromones, and taste, are crucial for the survival of most animals. There has long been a debate about whether different types of senses might influence each other. For instance, primates with a strong sense of vision are thought to have weakened olfactory abilities, although the oversimplified trade-off theory is now being questioned. It is uncertain whether such interactions between different chemical senses occur during evolution. To address this question, we examined four receptor gene families related to olfaction, pheromones, and taste: olfactory receptor (OR), vomeronasal receptor type 1 and type 2 (V1R and V2R), and bitter taste receptor (T2R) genes in Hystricomorpha, which is morphologically and ecologically the most diverse group of rodents. We also sequenced and assembled the genome of the grasscutter, Thryonomys swinderianus. By examining 16 available genome assemblies alongside the grasscutter genome, we identified orthologous gene groups among hystricomorph rodents for these gene families to separate the gene gain and loss events in each phylogenetic branch of the Hystricomorpha evolutionary tree. Our analysis revealed that the expansion or contraction of the four gene families occurred synchronously, indicating that when one chemical sense develops or deteriorates, the others follow suit. The results also showed that V1R/V2R genes underwent the fastest evolution, followed by OR genes, and T2R genes were the most evolutionarily stable. This variation likely reflects the difference in ligands of V1R/V2Rs, ORs, and T2Rs: species-specific pheromones, environment-based scents, and toxic substances common to many animals, respectively.

Design and Testing of the Double-Symmetric Eccentric Exciter for Fruit Tree Vibration Harvest

The amplitude of excitation force from exciters used in fruit tree vibration harvesting remains constant at a given frequency, leading to poor fruit detachment ratio and tree damage. A solution has been proposed through the development of a Double-Symmetric Eccentric Exciter (DSEE). This new exciter allows for the adjustment of excitation force amplitude while maintaining a constant frequency by varying the phase angle of the DSEE. To validate the effectiveness of the DSEE, vibration tests were conducted on fruit trees using different parameter exciting forces. Acceleration sensors were employed to measure the vibration accelerations of the tree branches. The experimental results revealed that when a fixed frequency excitation force with a constant phase angle was applied to the trunk, the vibration acceleration of branches exhibited inconsistent variations due to differences in the vibration differential equation parameters of each branch. Furthermore, it was observed that increasing the phase angle of the DSEE at a fixed frequency led to larger vibration accelerations in every branch. This signifies that adjusting the phase angle of the DSEE can effectively increase the amplitude of the exciting force. Consequently, the ability to control both the amplitude and frequency of the excitation force independently can mitigate issues such as low fruit harvest rates and minimize damage to fruit trees.

Traumatic flap dehiscence 15 years after LASIK: case report and review of the literature

Introduction: Corneal flap trauma rarely occurs years after laser in situ keratomileusis (LASIK), and management is not standardized. The authors report a case of LASIK flap dehiscence 15 years postoperatively with a review of the literature describing clinical characteristics, management, and outcomes of similar cases occurring at least 6 years postoperatively. Patient and Clinical Findings: A 55-year-old man with a history of LASIK surgery 15 years prior presented with flap dehiscence after trauma with a tree branch. His right eye uncorrected distance visual acuity (UDVA) at presentation was counting fingers. On slitlamp examination, the medial flap edge was folded underneath the temporal aspect. Diagnosis, Intervention, and Outcomes: The flap was unfolded, irrigated, repositioned, and instilled with topical antibiotics. The patient was started on prednisolone acetate 1% and moxifloxacin. On postoperative day 1, his UDVA improved to 20/50 and the flap remained centered and clear. His vision stabilized at 20/30 after 7 months. Peripheral epithelial ingrowth was noted without visual axis obscuration. Conclusions: This case, along with 20 reported instances of late traumatic flap dehiscence, highlights that early recognition with prompt intervention can optimize visual outcomes. Comparison of injury mechanisms, treatments, and complications may guide surgeons in patient counseling and care.

Comparative study of imaging and pathology of primary mucinous adenocarcinoma with different imaging manifestations.

Pulmonary mucinous adenocarcinoma is a special type of lung cancer. Its imaging manifestations are diverse, which brings challenges to clinical diagnosis. However, its formation mechanism is unclear. The objective of this study is to analyse the relevant mechanisms of the formation of pulmonary mucinous adenocarcinoma by observing its different imaging and pathological manifestations. Retrospective analysis was conducted on imaging manifestations and pathological data of 103 patients with pulmonary mucinous adenocarcinoma confirmed intraoperatively or pathologically. Forty-three patients had pulmonary mucinous adenocarcinoma with a solitary nodule/mass, 41 patients with localized pneumonia and 19 patients with diffuse pneumonia. Their CT manifestations included 'falling snowflake sign', ground-glass opacity close to the heart, vacuous signs/honeycombing and withered tree branches. Under the microscope, all the three types of pulmonary mucinous adenocarcinoma had visibly formed mucus lakes but were made of tumour cells with totally different shapes, which included the goblet-like shape (tall column-like shape) and quasi-circular shape. Tall column-shaped tumour cells were negative or weakly positive for thyroid transcription factor-1 (TTF-1) and strongly positive for ALK mutation, whereas quasi-circular tumour cells were positive for TTF-1 and less positive for ALK mutation. The different imaging manifestations of mucinous adenocarcinoma are possibly due to the different amounts or viscosity of mucus produced, and the mechanisms of its formation may include (1) tumour cells in different shapes have different abilities to produce mucus; (2) tumours in different stages produce different amounts or viscosity of mucus; and (3) the TTF-1 and ALK genes affect the production of mucus.

辊式枝条捡拾机构运动学仿真与试验分析

Apple tree branches have the physical characteristics of high cellulose content and high elasticity, and the use of traditional soft straw pickers will miss a large number of branches. It is necessary to design a picking mechanism that adapts to the physical characteristics of fruit tree branches. In the treatment of branches in modern orchards, the picking mechanism is an important part of the picking device. The success rate of picking directly affects the processing performance of the whole machine. To improve the picking rate, the roller branch picking mechanism is studied. The trajectory of the roller picking and the stress state of the branches are analyzed, and five main factors affecting the picking effect are obtained, i.e. the position relationship between the rotation center of the picking roller and the feeding roller, inclination angle of the steel teeth, the effective working length, the speed and the forward speed of the machine. A mathematical model is established to obtain the static and dynamic motion trajectories of the roller picking mechanism are obtained by using Matlab. Taking the analysis results of influencing factors as the optimization goal, the picking trajectory of the mechanism is simulated to obtain a set of non-inferior solutions. A roller branch picker is manufactured according to the parameter values and tested in the field, and the picking rate can reach 91%.

Applications of machine learning in phylogenetics

Machine learning has increasingly been applied to a wide range of questions in phylogenetic inference. Supervised machine learning approaches that rely on simulated training data have been used to infer tree topologies and branch lengths, to select substitution models, and to perform downstream inferences of introgression and diversification. Here, we review how researchers have used several promising machine learning approaches to make phylogenetic inferences. Despite the promise of these methods, several barriers prevent supervised machine learning from reaching its full potential in phylogenetics. We discuss these barriers and potential paths forward. In the future, we expect that the application of careful network designs and data encodings will allow supervised machine learning to accommodate the complex processes that continue to confound traditional phylogenetic methods.

The updated genome of the Hungarian population of Aedes koreicus

Vector-borne diseases pose a potential risk to human and animal welfare, and understanding their spread requires genomic resources. The mosquito Aedes koreicus is an emerging vector that has been introduced into Europe more than 15 years ago but only a low quality, fragmented genome was available. In this study, we carried out additional sequencing and assembled and characterized the genome of the species to provide a background for understanding its evolution and biology. The updated genome was 1.1 Gbp long and consisted of 6099 contigs with an N50 value of 329,610 bp and a BUSCO score of 84%. We identified 22,580 genes that could be functionally annotated and paid particular attention to the identification of potential insecticide resistance genes. The assessment of the orthology of the genes indicates a high turnover at the terminal branches of the species tree of mosquitoes with complete genomes, which could contribute to the adaptation and evolutionary success of the species. These results could form the basis for numerous downstream analyzes to develop targets for the control of mosquito populations.

Phylogeny of Transferable Oxazolidinone Resistance Genes and Homologs.

Oxazolidinone resistance, especially transmissible resistance, is a major public health concern, and the origin of this resistance mechanism is not yet resolved. This study aims to delve into the phylogenetic origin of the transmissible oxazolidinone resistance mechanisms conferring cross-resistance to other drugs of human and veterinary importance. The amino acid sequences of the five cfr ribosomal methylases and optrA and poxtA were used as queries in searches against 219,549 bacterial proteomes in the NCBI RefSeq database. Hits with >40% amino acid identity and >80% query coverage were aligned, and phylogenetic trees were reconstructed. All five cfr genes yielded highly similar trees, with rlmN housekeeping ribosomal methylases located basal to the sister groups of S-adenosyl-methionine-dependent methyltransferases from various Deltaproteobacteria and Actinomycetia, including antibiotic-producing Streptomyces species, and the monophyletic group of cfr genes. The basal branches of the latter contained paenibacilli and other soil bacteria; they then could be split into the clades [cfr(C):cfr(E)] and [[cfr:cfr(B)]:cfr(D)], always with different Bacillaceae in their stems. Lachnospiraceae were encountered in the basal branches of both optrA and poxtA trees. The ultimate origin of the cfr genes is the rlmN housekeeping ribosomal methylases, which evolved into a suicide-avoiding methylase in antibiotic producers; a soil organism (Lachnospiraceae, Paenibacilli) probably acted as a transfer organism into pathogenic bacteria. In the case of optrA, the porcine pathogenic Streptococcus suis was present in all branches, while the proteins closest to poxtA originated from Clostridia.

Dendritic boron and nitrogen doped high-entropy alloy porous carbon fibers for high-efficiency hydrogen evolution reaction

Among various electrocatalysts, high-entropy alloys (HEAs) have gained significant attention for their unique properties and excellent catalytic activity in the hydrogen evolution reaction (HER). However, the precise synthesis of HEA catalysts in small sizes remains challenging, which limits further improvement in their catalytic performance. In this study, boron- and nitrogen-doped HEA porous carbon nanofibers (HE-BN/PCNF) with an in situ-grown dendritic structure were successfully prepared, inspired by the germination and growth of tree branches. Furthermore, the dendritic fibers constrained the growth of HEA particles, leading to the synthesis of quantum dot-sized (1.67nm) HEA particles, which also provide a pathway for designing HEA quantum dots in the future. This work provides design ideas and guiding suggestions for the preparation of borated HEA fibers with different elemental combinations and for the application of dendritic nanofibers in various fields.