Complex Type Research Articles

How biotic interactions structure species' responses to perturbations.

Predicting how ecological communities will respond to disturbances is notoriously challenging, especially given the variability in species' responses within the same community. Focusing solely on aggregate responses may obscure extinction risks for certain species owing to compensatory effects, emphasizing the need to understand the drivers of the response variability at the species level. Yet, these drivers remain poorly understood. Here, we reveal that despite the typical complexity of biotic interaction networks, species' responses follow a discernible pattern. Specifically, we demonstrate that the species whose population abundances are most reduced by biotic interactions-which are not always the rarest species-are those that exhibit the strongest responses to disturbances. This insight enables us to pinpoint sensitive species within communities without requiring precise information about biotic interactions. Our novel approach introduces avenues for future research aimed at identifying sensitive species and elucidating their impacts on entire communities.

Everyday Dishes from Corn Flour and Groats in the Nutrition of Ukrainians of East Podolian Prydnistrovia in the Late 19th – Early 21st Centuries

The article is devoted to the consideration of an integral component of the traditional daily ration of Ukrainians of East PodolianPrydnistrovia – dishes from corn flour and grits, known as a mandatory food for every day during the late 19th – mid 20th centuries, and some of them (for food variety) are still cooked. The work is based on the analysis of ethnographic works, published sources and the corpus of own field materials (interviews with respondents), recorded during the expeditions to the border settlements of Vinnytsia and the north of Odesa regions in 2013–2016. The author is describing the features of cooking the most common corn products – mamalyha and malai. The gastronomic difficulties of life support under extreme circumstances are considered partially. In particular, attention is focused on the consumption in the region of baderevka and badevka, those are rather modest in terms of nutrition boiled liquid soups with corn flour, and which saved Ukrainians during the difficult times of the post-war famine of 1946–1947. The materials of the conducted research have made it possible to confirm the generalizations of ethnologists-researchers of the Ukrainian-Moldovan borderlands and our preliminary conclusions (based on the study of other components of the life-support system) that in the space of the ethno-contact zone (in particular, in the Transdnistrian territories of Eastern Podillia) a typical ethno-specific food complex partially loses its differentiating function and acquires a special format that combines similar or jointly created ethnocultural practices of both Ukrainians and Moldovans. The analysis of the author’s expedition materials, in addition to the factual disclosure of the subject, also serves as a basis for the spatial characterization of the names and realities of this block of ethnoculture, visualized with the help of a special map scheme introduced into scientific circulation. The concluding remarks outline the prospects for implementing the results for modern cultural preservation practices, primarily in the Vinnytsia and Odesa regions.

Molecular Interactions Governing the Rat Aryl Hydrocarbon Receptor Activities of Polycyclic Aromatic Compounds and Predictive Model Development.

Polycyclic aromatic compounds (PACs) exhibit rat aryl hydrocarbon receptor (rAhR) activities, leading to diverse biological or toxic effects. In this study, the key amino residues and molecular interactions that govern the rAhR activity of PACs were investigated using in silico strategies. The homology model of rAhR was first docked with 90 PACs to yield complexes, and the results of the molecular dynamics simulations of 16 typical complexes showed that the binding energies of the complexes range from -7.37 to -26.39 kcal/mol. The major contribution to the molecular interaction comes from van der Waals forces, and Pro295 and Arg316 become the key residues involved in most complexes. Two QSAR models were further developed to predict the rAhR activity of PACs (in terms of log IEQ for PACs without halogen substitutions and log%-TCDD-max for halogenated PACs). Both models have good predictive ability, robustness, and extrapolation ability. Molecular polarizability, electronegativity, size, and nucleophilicity are identified as the important factors affecting the rAhR activity of PACs. The developed models could be employed to predict the rAhR activity of other reactive PACs. This work provides insight into the mechanisms and interactions of the rAhR activity of PACs and assists in the assessment of their fate and risk in organisms.

Dual stage MRI image restoration based on blind spot denoising and hybrid attention

BackgroundMagnetic Resonance Imaging (MRI) is extensively utilized in clinical diagnostics and medical research, yet the imaging process is often compromised by noise interference. This noise arises from various sources, leading to a reduction in image quality and subsequently hindering the accurate interpretation of image details by clinicians. Traditional denoising methods typically assume that noise follows a Gaussian distribution, thereby neglecting the more complex noise types present in MRI images, such as Rician noise. As a result, denoising remains a challenging and practical task.MethodThe main research work of this paper focuses on modifying mask information based on a global mask mapper. The mask mapper samples all blind spot pixels on the denoised image and maps them to the same channel. By incorporating perceptual loss, it utilizes all available information to improve performance while avoiding identity mapping. During the denoising process, the model may mistakenly remove some useful information as noise, resulting in a loss of detail in the denoised image. To address this issue, we train a generative adversarial network (GAN) with adaptive hybrid attention to restore the detailed information in the denoised MRI images.ResultThe two-stage model NRAE shows an improvement of nearly 1.4 dB in PSNR and approximately 0.1 in SSIM on clinical datasets compared to other classic models. Specifically, compared to the baseline model, PSNR is increased by about 0.6 dB, and SSIM is only 0.015 lower. From a visual perspective, NRAE more effectively restores the details in the images, resulting in richer and clearer representation of image details.ConclusionWe have developed a deep learning-based two-stage model to address noise issues in medical MRI images. This method not only successfully reduces noise signals but also effectively restores anatomical details. The current results indicate that this is a promising approach. In future work, we plan to replace the current denoising network with more advanced models to further enhance performance.

Site-directed mutagenesis leads to the optimized transglycosylation activity of endo-beta-N-acetylglucosaminidase from Trypanosoma brucei.

Endo-β-N-acetylglucosaminidases (ENGases) are pivotal enzymes in the degradation and remodeling of glycoproteins, which catalyze the cleavage or formation of β-1,4-glycosidic bond between two N-acetylglucosamine (GlcNAc) residues in N-linked glycan chains. It was investigated that targeted mutations of amino acids in ENGases active site may modulate their hydrolytic and transglycosylation activities. Endo-Tb, the ENGase derived from Trypanosoma brucei, belongs to the glycoside hydrolase family 85 (GH85). Our group previously demonstrated that Endo-Tb exhibits hydrolytic activity toward high-mannose and complex type N-glycans and preliminarily confirmed its transglycosylation potential. In this study, we further optimized the transglycosylation activity of recombinant Endo-Tb by focusing on the N536A, E538A and Y576F mutants. A comparative analysis of their transglycosylation activity with that of the wild-type enzyme revealed that all mutants exhibited enhanced transglycosylation capacity. The N536A mutant exhibited the most pronounced improvement in transglycosylation activity with a significant reduction in hydrolytic activity. It is suggested that Endo-Tb N536A possesses the potential as a tool for synthesizing a wide array of glycoconjugates bearing high-mannose and complex type N-glycans.

The mechanisms of the copper-carbonate catalyzed oxygen evolution reaction

Copper carbonate/bicarbonate complexes are good catalysts of the oxygen evolution reaction, OER. Previous electro-catalytic studies suggested that at pH 10.8 the active intermediate is a CuIII complex whereas at pH 6.8 the active intermediate is a CuIV complex. Previous pulse-radiolysis studies indicated that CuIII complexes are the active intermediates at both pHs. To solve the source of this discrepancy, the copper carbonate/bicarbonate catalyzed OER using peroxy-mono-sulfate as the oxidant was studied. In this system CuIV complexes are the active intermediates. The result points out that two electron oxidants yield CuIV complexes and one electron oxidants yield CuIII complexes; both types of complexes are water oxidation agents. Electrochemical processes might proceed via both mechanisms as the anode can act as a two-electron acceptor. Thus, pulse-radiolysis does not always yield the same intermediates as electrochemistry.

Socioeconomic impact of livestock production in Gokuleshowor, Baitadi, Nepal

The study was carried out at the Baitadi district's Dilashaini rural municipality. The study area was primarily based on agriculture. Farmers in the studied area adopted a complex type of farming system that includes livestock, crops, fruits, forestry, and vegetable farming. This study was mainly conducted to identify key problems faced by farmers and the socioeconomic importance of livestock farming. Semi-structured questionnaires were used to randomly choose respondents for a key informant interview. 61 households were randomly selected without the replacement method. The results showed that most of the households were headed by men (52 households). The primary occupation was agriculture (72%), followed by business (22%). A benefit-to-cost ratio of 1.65 was discovered. Milk was priced at 48.08 rupees per liter. We found feeding management to be the main problem. Farmers invest a huge amount of their income in managing feed for livestock. Natural breeding was largely prevalent in the study area (96%); artificial insemination was still rare. In the studied area, the dairy sector was profitable, so it emphasized improved breeding programs, improved feeding management, and the establishment of well-managed dairy cooperatives, which helped in the development of the rural economy and the lifestyle of farmers.

Binding Modalities and Phase-Specific Regulation of Cyclin/Cyclin-Dependent Kinase Complexes in the Cell Cycle.

Cyclin-dependent kinases (CDKs) are activated upon cyclin-binding to enable progression through the cell cycle. Dominant CDKs and cyclins in mammalian cells include CDK1, CDK2, CDK4, and CDK6 and corresponding cyclins A, B, D, and E. While only certain, "typical" cyclin/CDK complexes are primarily responsible for cell cycle progression, "atypical" cyclin/CDK complexes can form and sometimes perform the same roles as typical complexes. We asked what structural features of cyclins and CDKs favor the formation of typical complexes, a vital yet not fully explored question. We use computational docking and biophysical analyses to exhaustively evaluate the structure and stability of all CDK and cyclin complexes listed above. We find that binding of the complexes is generally stronger for typical than for atypical complexes, especially when the CDK is in an active conformation. Typical complexes have denser clusters, indicating that they have more defined cyclin-binding sites than atypical complexes. Our results help explain three notable features of cyclin/CDK function in the cell cycle: (i) why CDK4 and cyclin-D have exceptionally high specificity for each other; (ii) why both cyclin-A and cyclin-B strongly activate CDK1, whereas CDK2 is only strongly activated by cyclin-A; and (iii) why cyclin-E normally activates CDK2 but not CDK1. Overall, this work reveals the binding modalities of cyclin/CDK complexes, how the modalities lead to the preference for typical complexes versus atypical complexes, and how binding modalities differ between typical complexes. Our observations suggest targeting CDK catalytic actions through destabilizing their native differential cyclin interfaces.

Lactoferrin-Based Heteroprotein Systems, From Their Formation Mechanism, Properties, To Applications.

Lactoferrin (LF) is an important iron-binding glycoprotein found in milk and mucosal secretions. The alkaline lactoferrin can interact with some acidic proteins to form heteroprotein systems with multifunctional properties and a wide range of applications. Lactoferrin can interact with animal and plant proteins mainly through the electrostatic forces, dipolar attraction, and hydrophobic interactions. In this review, the types of heteroprotein complexes formed by the complex coacervation of lactoferrin with other proteins are introduced, including the preparation, structure, and applications. The factors affecting the formation of heteroprotein complexes are described, such as pH, ionic strength, mixing ratio, total protein concentration, and temperature. The issues and challenges in the formation of heteroprotein complexes are also discussed.

Hydrological modeling using HEC-HMS model, case of Tikur Wuha River Basin, Rift Valley River Basin, Ethiopia

Modeling rainfall-runoff is widely recognized as one of the most complex types of hydrological modeling, primarily because it involves the integration of a diverse array of watershed characteristics. Due to its ability to emulate the hydrological behavior of a watershed, the modeling of rainfall-runoff plays a crucial role in predicting the runoff generated at the watershed's outlet. The present study aimed to simulate runoff by utilizing HECHMS in the Tikur Wuha River watershed situated in the Rift Valley Basin of Ethiopia. To achieve this goal, tools such as HEC-GeoHMS and ArcGIS were employed to establish the necessary input parameters for HECHMS. Various methods were implemented at different stages of the modeling process, including SCS-CN for estimating precipitation loss, SCS-UH for transforming excess rainfall, Muskingum for flood routing, and the monthly constant method for modeling base flow. The process of calibration and validation entailed the use of daily observed flow data from the periods (1990 to 2009) and (2010 to 2015) correspondingly. Nash Sutcliff Efficiency (NSE) and coefficient of determination (R2) were employed as metrics to evaluate the model's performance. The findings showed that the model exhibited high performance in both calibration and validation stages, producing values of (NSE = 0.83, R2 = 0.91) and (NSE = 0.84, R2 = 0.86) respectively. Furthermore, the Percent Bias (PBIAS) values in calibration and validation remained within acceptable ranges, registering at 2.69 % and 4.67 % respectively. After the calibration and validation of the model, the estimated peak flood discharge simulated by the model (206.3m3/s) was compared with the observed stream flow (197.1m3/s), indicating a significant similarity between the model's output and the observed data. Consequently, it can be inferred that the model exhibits a high capability in replicating hydrological parameters effectively for the Tikur Wuha watershed and other watersheds sharing similar hydrological characteristics.

Perceptual Attributes Identification and Importance–Performance Alignment Assessment of Urban Underground Complex: A Case Study in Chengdu Tianfu Square

Background and objectives: The urban underground complex integrates comprehensive architecture and subterranean space, presenting physical and psychological complexities. To mitigate the negative experiences associated with this complexity, we need to explore, in depth, how the built environmental elements of underground complexes affect user perception to design a comfortable, healthy, and biophilic underground space. Methods: We selected Tianfu Square, a typical underground complex in Chengdu, China, as the empirical case. We identified 26 key environmental indicators affecting user perception and designed Kano and satisfaction questionnaires based on these indicators. A total of 476 questionnaires were distributed to collect data on users’ attitudes towards changes in element quality and their satisfaction levels. By integrating the Kano model and IPA method, we defined the perceptual attributes of elements based on their impact on user experiences and assessed the alignment between element attributes and satisfaction. Results: We categorized the elements into five perceptual types: attractive, one-dimensional, indifferent, must-be, and reverse attributes, and assigned corresponding importance levels. We then compared the importance and performance scores of these elements, evaluated their satisfaction alignment, identified elements needing optimization, and proposed improvement strategies. Implications: This research provides valuable guidance for designers on how various built environment elements in underground spaces influence user perceptions, with practical implications for urban underground complex planning and design.

Rare-Earth Metal Complexes Bearing Electrophilic Carbon and Strongly Polarized Metallacyclopropane Moiety: Synthesis and Diverse Reactivity toward Small Molecules.

Metallacyclopropanes are highly strained and very reactive organometallics; the rare-earth metal complexes bearing both highly reactive electrophilic carbon and strongly polarized metallacyclopropanes are extremely rare. This type of rare-earth metal complexes (κ2-L)RE(η2-C2B10H10)·(THF)3 [L = 1-(2-N-C5H10NCH2CH2)-3-(2,6-iPr2C6H3N═CH)-C8H4N, RE = Lu(1a), Yb(1b), Er(1c), Y(1d), Dy(1e)] bearing the indol-2-yl electrophilic carbon and carboryne-based strongly polarized metallacyclopropanes have been synthesized. Structures of complexes 1 are further confirmed by single-crystal X-ray diffraction and DFT theoretical calculations. It is found that complexes 1 have remarkable reactivity toward different polar unsaturated small molecules, elemental sulfur, and selenium to provide different products (2-15) through the selective reactions of the RE-Ccage, and RE-C2-ind bonds with the given small molecules, respectively. The reactivities of these complexes are different from those of the reported rare-earth metallacyclopropenes and d-block metal-carborynes.

Risk analysis of accident-causing evolution in chemical laboratory based on complex network

Chemical laboratories usually have many high risks from various dangerous chemicals, dangerous devices, and experimental operators involved in the laboratory. Once a severe accident occurs, the accident consequence will significantly impact scientific research innovation and social progress. Aiming at laboratory safety problems, an accident evolution model is established to reveal the critical accident-causing factors and the most likely evolutionary path of accidents in the process of accident evolution. Firstly, the 24 model is used to identify the cause factors of laboratory accidents and the causal relationship between factors. Then, the complex network model of laboratory accident evolution is constructed with accident-causing factors as nodes and causal relationships between factors as edges. Secondly, using the TOPSIS method, four typical complex network characteristic indexes, including degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, are constructed into a comprehensive evaluation index to reveal the key influencing factors in the accident evolution process. Finally, the fuzzy number is introduced to quantify the uncertainty of the accident evolution path. The most likely evolutionary path is obtained through the Dijkstra and risk entropy theory. Based on the data of 151 laboratory accidents from 2001 to 2022, the accident evolution analysis of chemical laboratories was carried out. The evolution results show that the maximum probability value is the evolution path of fire accidents, and the minimum probability value is the evolution path of electric shock accidents, which accords with the general statistical law of accidents. When applied to the actual laboratory, the safety management level of the laboratory can be effectively improved by controlling the key influencing factors and cutting off the accident evolution path.

Automated Detection of Hillforts in Remote Sensing Imagery With Deep Multimodal Segmentation

ABSTRACTRecent advancements in remote sensing and artificial intelligence can potentially revolutionize the automated detection of archaeological sites. However, the challenging task of interpreting remote sensing imagery combined with the intricate shapes of archaeological sites can hinder the performance of computer vision systems. This work presents a computer vision system trained for efficient hillfort detection in remote sensing imagery. Equipped with an adapted multimodal semantic segmentation model, the system integrates LiDAR‐derived LRM images and aerial orthoimages for feature fusion, generating a binary mask pinpointing detected hillforts. Post‐processing includes margin and area filters to remove edge inferences and smaller anomalies. The resulting inferences are subjected to hard positive and negative mining, where expert archaeologists classify them to populate the training data with new samples for retraining the segmentation model. As the computer vision system is far more likely to encounter background images during its search, the training data are intentionally biased towards negative examples. This approach aims to reduce the number of false positives, typically seen when applying machine learning solutions to remote sensing imagery. Northwest Iberia experiments witnessed a drastic reduction in false positives, from 5678 to 40 after a single hard positive and negative mining iteration, yielding a 99.3% reduction, with a resulting F1 score of 66%. In England experiments, the system achieved a 59% F1 score when fine‐tuned and deployed countrywide. Its scalability to diverse archaeological sites is demonstrated by successfully detecting hillforts and other types of enclosures despite their typical complex and varied shapes. Future work will explore archaeological predictive modelling to identify regions with higher archaeological potential to focus the search, addressing processing time challenges.

Discrete versus polymeric structures of coordination compounds of copper(II) with (pyridin-2-yl)methylenenicotinohydrazide and a library of dicarboxylic acids

A series of copper(II) discrete and polymeric coordination compounds, namely [{CuL(H2O)}2(fum)] (1), [{CuL(H2O)}2(mes)] (2), [Cu2L2(glu)]n·2n(H2O) (3·2n(H2O)) and [Cu3L2(adi)2]n (4) were fabricated from (pyridin-2-yl)methylenenicotinohydrazide (HL) and a library of dicarboxylic acids, namely fumaric acid (H2fum), mesaconic acid (H2mes), glutaric acid (H2glu) and adipic acid (H2adi), using evaporative crystallization, grinding and slurry synthesis methods. The obtained coordination compounds have been fully characterized by single crystal X-ray diffraction revealing different types of complexes depending on the linker length, viz. from dinuclear complexes for the shorter linkers (fumaric and mesaconic acids) to 1D and 2D coordination polymers for longer glutaric and adipic acids. Thermal stability and spectroscopic features (FTIR and diffuse reflectance) of complexes were also studied. For the nonpolymeric compounds 1 and 2, the supramolecular assemblies driven by a combination of antiparallel π-stacking and hydrogen bonding interactions have been studied and compared using DFT calculations, MEP surface analysis and a combination of QTAIM and NCIplot computational tools.

Dynamic Calculation Approach of the Collision Risk in Complex Navigable Water

It is vital to analyze ship collision risk for preventing collisions and improving safety at sea. This paper takes Ningbo-Zhoushan Port, a typical complex navigable water, as the research object. Firstly, a probabilistic conflict detection method based on an AIS data-driven dynamic ship domain model is proposed to achieve effective ship conflict detection under uncertain environments. Then, a ship group identification method is proposed, which can extract the ship groups with conflict correlation and space compactness. Finally, according to the characteristics of ship traffic in complex navigable waters, the dynamic calculation of ship collision risk is carried out from individual, regional, and local multi-scale perspectives. The experimental results show that the proposed method can detect the collision risk in a timely, reliable, and effective manner under complex dynamic conditions. As such, they provide valuable insights into ship collision risk prediction and the development of risk mitigation measures.

Characterizing the uncertainty of CMORPH products for estimating orographic precipitation over Northern California

Satellite-based precipitation products (SPPs), such as the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), have greatly extended our ability to monitor global precipitation. However, their performance over complex terrain remains highly uncertain. To improve accuracy, CPC has recently upgraded its operational SPP to the second generation CMORPH–CMORPH2. In addition to such efforts, the reliability of SPPs can be further enhanced by developing robust uncertainty estimates. This study employs a censored, shifted gamma distribution (CSGD)-based error modeling framework to develop error models for both CMORPH2 and its predecessor, CMORPH1, at a 6-hourly scale over Northern California—a typical complex terrain region that challenges most SPPs. Using the Stage IV reference precipitation, the relative improvements of CMORPH2 over CMORPH1 are quantified by comparing their CSGD-derived error statistics. The comparison shows that CMORPH2 outperforms CMORPH1 by reducing the overall bias and detection errors, and by better capturing the orographic gradients of precipitation over the Coast Ranges and Sierra Nevada. Validation results show that the trained error models can appropriately represent the bias and random errors; however, the models for both CMORPH2 and CMORPH1 show reduced skills in the high-altitude Sierra Nevada. With high-resolution regional climate simulations, the uncertainty estimates are further improved by incorporating them as covariates. The simulated precipitation shows substantial improvement of the uncertainty estimates over most areas, including the challenging high-altitude Sierra Nevada. Following precipitation, the simulated integrated water vapor transport (IVT) and convective available potential energy (CAPE) also offer modest improvements, mainly along the coast. Independent verification further demonstrates the robustness of the uncertainty estimates during heavy precipitation events. As NOAA is currently reprocessing CMORPH2 to produce an updated global precipitation record from 1991 onward, this error modeling framework holds potential for broader applications in quantifying the uncertainty of CMORPH2 for estimating orographic precipitation over extended periods and locations.

Enhancing Mass-Cytometry Imaging Analysis

Mass cytometry imaging is a technique that utilizes mass spectrometry instead of fluorescent flow cytometry to detect metal-conjugated antibodies binding to single cell antigens. This method generates multi-dimensional images, a complex data type with significant computational and interpretation challenges due to the absence of a standardized analysis workflow. To address this, our project evaluated the quality and efficacy of a previous study’s proposed workflow to advance the interpretability and accuracy of mass cytometry data analysis. The approach evaluated whether the previously proposed workflow could effectively analyze alternative samples classified by previous studies as “mixed” immune structure. The methods included an in-depth examination of cell labeling based on spatial proximity, which emerged as a secondary analytical outcome. This research advances spatial labeling by enhancing the spatial information related to physical connections between interacting cells and incorporating biological interactions, such as protein involvement. By integrating these factors, this research proposes a method for more accurate labeling, contributing to a more robust analysis workflow for this complex data type. Unstructured “mixed” samples remained distinguishable, though less effectively than structured “compartmentalized” samples. Future applications involve exploring additional datasets to further develop means of distinguishing between contact and non-contact interactions among cancer and immune cells.

Risk assessment of bridge construction investigated using random forest algorithm

Bridge construction collapse is one of the most common bridge safety accidents. At present, evaluation results are often affected by the ability and experience of the assessor. Therefore, it is difficult to quickly, accurately and effectively evaluate the risk in the process of bridge construction. Moreover, key factors that can prevent accidents can hardly find from the existing bridge construction safety management and evaluation method. This paper analyzes and classifies the artificial and environmental risk factors that affect the bridge construction stage, and establishes 26 risk factors in 5 categories according to the characteristics of bridge construction and the actual situation of the project. Random forest (RF) algorithm is a non-parametric machine learning method based on decision tree, which does not need to be scored by experts in advance and avoids the influence of subjective factors. Compared with other analysis methods, random forest algorithm has the advantages of accurate and robust risk assessment results. Based on the advantages of random forest algorithm and the characteristics of bridge construction risk, this paper uses random forest algorithm to evaluate the bridge construction risk, and ranks the importance of indicators, and identify the index that has a greater influence on the risk. In order to verify the applicability and feasibility of the proposed method, a typical urban complex pedestrian bridge was taken as an example for actual engineering evaluation and verification. The results obtained are basically consistent with the actual risk assessment results of the pedestrian bridge.

Microliposuction and Radiofrequency Combined With Fat Grating as a New Method for Hybrid-Type Nasolabial Folds.

The hybrid-type nasolabial fold is a special, complex type of nasolabial fold with various causes, making it difficult to obtain an ideal effect with a single treatment. This study aimed to investigate the effect and complications of a comprehensive therapy combining microliposuction, radiofrequency, and fat grafting on hybrid-type nasolabial folds. Twenty-one patients aged 27 to 45 (mean: 34.71±5.41) years, who underwent the therapy for hybrid-type nasolabial folds were retrospectively analyzed. All patients were followed up for 12 months. Two independent observers conducted postoperative follow-ups at 1 week and 12 weeks. One week postoperatively, the hematoma, mass nodule, and skin scald ecchymosis scores were 1.24±0.43, 1.62±0.58, and 1.48±0.59, respectively. At 12 weeks, the scores of mass nodules and skin scald ecchymosis decreased (1.19±0.39 and 1.05±0.21, respectively) without obvious hematoma. The WSRS grade decreased from 4.33±0.47 to 2.19±0.39 (P<0.001), and the hybrid-type nasolabial folds significantly improved. The Face-Q scale score was 20.43±2.63 points (standard score: 85.12±10.95 points). 76.19% of the patients scored more than 80 points in the subjective Face-Q evaluation. Microliposuction and radiofrequency combined with fat grafting effectively treats hybrid-type nasolabial folds, resulting in high patient satisfaction. Most complications can be prevented, and optimal outcomes can be obtained by comprehensive surgical methods and correct procedures, which is thus worthy of clinical promotion.