ABSTRACT
Constructing nanoreactors with multiple active sites in well-defined crystalline mesoporous frameworks is an effective strategy for tailoring photocatalysts to address the challenging of CO2 reduction. Herein, one-dimensional (1-D) mesoporous single-crystal TiO2 nanorod (MS-TiO2-NRs, ≈110 nm in length, high surface area of 117 m2 g-1, and uniform mesopores of ≈7.0 nm) based nanoreactors are prepared via a droplet interface directed-assembly strategy under mild condition. By regulating the interfacial energy, the 1-D mesoporous single-crystal TiO2 can be further tuned to polycrystalline fan- and flower-like morphologies with different oxygen vacancies (Ov). The integration of single-crystal nature and mesopores with exposed oxygen vacancies make the rod-like TiO2 nanoreactors exhibit a high-photocatalytic CO2 reduction selectivity to CO (95.1%). Furthermore, photocatalytic cascade nanoreactors by in situ incorporation of CuW6O24 (W-Cu) clusters onto MS-TiO2-NRs via Ov are designed and synthesized, which improved the CO2 adsorption capacity and achieved two-step CO2-CO-CH4 photoreduction. The second step CO-to-CH4 reaction induced by W-Cu sites ensures a high generation rate of CH4 (420.4 µmol g-1 h-1), along with an enhanced CH4 selectivity (≈94.3% electron selectivity). This research provides a platform for the design of mesoporous single-crystal materials, which potentially extends to a range of functional ceramics and semiconductors for various applications.
ABSTRACT
In pursuit of accessing clean water, the phosphate removal is of great importance for preventing eutrophication toward sustainable ecology. However, effective adsorbents with high capacity, selectivity, and long-term stability for treating phosphate in water still remain desired, which requires further development. Herein, a type of porous La-based adsorbents, which are composed of highly dispersed La(OH)3 on amino-functionalized Caragana korshinskii (CK) nanowires, are designed and fabricated through simple amination and decoration of lemon bars. Specifically, the adsorption to phosphate can be quickly completed within 50 min, and an ultrahigh adsorption capacity of 173.3 mg of P g-1 is realized. Moreover, these composite adsorbents display excellent selectivity and anti-interference ability to phosphate in the presence of common anions (CO3 2-, NO3-, Cl-, and SO4 2-). After four regenerations, there is still a removal rate of 85%. This study underscores an integrated material model for designing advanced structures toward efficient wastewater treatment.
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Mesoporous materials endowed with a hollow structure offer ample opportunities due to their integrated functionalities; however, current approaches mainly rely on the recruitment of solid rigid templates, and feasible strategies with better simplicity and tunability remain infertile. Here, we report a novel emulsion-driven coassembly method for constructing a highly tailored hollow architecture in mesoporous carbon, which can be completely processed on oil-water liquid interfaces instead of a solid rigid template. Such a facile and flexible methodology relies on the subtle employment of a 1,3,5-trimethylbenzene (TMB) additive, which acts as both an emulsion template and a swelling agent, leading to a compatible integration of oil droplets and composite micelles. The solution-based assembly process also shows high controllability, endowing the hollow carbon mesostructure with a uniform morphology of hundreds of nanometers and tunable cavities from 0 to 130 nm in diameter and porosities (mesopore sizes 2.5-7.7 nm; surface area 179-355 m2 g-1). Because of the unique features in permeability, diffusion, and surface access, the hollow mesoporous carbon nanospheres exhibit excellent high rate and cycling performances for sodium-ion storage. Our study reveals a cooperative assembly on the liquid interface, which could provide an alternative toolbox for constructing delicate mesostructures and complex hierarchies toward advanced technologies.
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Highly crystalline ZSM-23 zeolite, exhibiting a distinctive dumbbell morphology, was synthesized via a hydrothermal method. Bifunctional catalysts, comprising single metals (Pt or Au) and bimetals (Pt-Au), were successfully prepared by using a positional precipitation method. The hydroisomerization of hexadecane served as a model reaction to assess the catalytic performance arising from the synergistic effects of bimetallic active sites. In comparison to single-metal catalysts, 0.3Au0.7Pt/ZSM-23 demonstrated increased n-C16 conversion, while 0.5Au0.5Pt/ZSM-23 exhibited enhanced i-C16 selectivity, achieving the highest i-C16 yield. The bimetallic catalyst not only finely tuned the metal site activity through bimetallic synergy but also achieved a superior balance between metal and acid catalysis, resulting in improved catalytic performance in the n-C16 hydroisomerization. The Pt-Au bimetallic catalyst approached the ideal requirements for a hydroisomerization catalyst, achieving a harmonious balance of metal and acid catalysis.
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The development of acute lung injury (ALI), a common respiratory condition with multiple causes, is significantly influenced by the pro-inflammatory environment of signal transducer and activator of transcription 3 (STAT3) in macrophages. Our study aimed to evaluate the anti-inflammatory effects of B9 (N-(4-hydroxyphenyl)-9, 10-dioxo-9, 10-dihydroanthracene-2-sulfonamide), a novel inhibitor targeting the STAT3 SH2 domain, in macrophages and to assess its therapeutic potential for ALI using a mouse model of lipopolysaccharide (LPS)-induced ALI. We found that B9 (30 mg/kg) significantly reduced lung pathological damage and neutrophil infiltration caused by the intratracheal administration of LPS. Additionally, the high expression of pro-inflammatory cytokines (TNF-α, IL-1ß, and IL-6) in alveolar lavage fluid was also inhibited by B9 treatment. The decreased expression of CD86 and increased CD206 in lung tissue demonstrated the anti-inflammatory effect of B9, which was due to its inhibition of the STAT3 signaling pathway in macrophages of ALI mice. Furthermore, B9 suppressed the activation of RAW264.7 cells induced by LPS, characterized by its ability to inhibit the activation of iNOS and STAT3 in a dose-dependent manner, as well as reduce the secretion of IL-6 and IL-1ß. The in vivo preliminary safety evaluation indicated that B9 had a favorable safety profile at the administered doses. These results suggest that B9 exerts a therapeutic effect on LPS-induced ALI, potentially by preventing the phosphorylation of STAT3 Y705 and S727 without affecting the STAT3 protein level. Taken together, these findings provide a foundation for developing B9 as a novel anti-inflammatory agent for ameliorating LPS-induced ALI.
Subject(s)
Acute Lung Injury , Anti-Inflammatory Agents , Cytokines , Lipopolysaccharides , Macrophages , STAT3 Transcription Factor , Animals , Acute Lung Injury/drug therapy , Acute Lung Injury/chemically induced , Acute Lung Injury/immunology , Acute Lung Injury/pathology , STAT3 Transcription Factor/metabolism , STAT3 Transcription Factor/antagonists & inhibitors , Mice , Anti-Inflammatory Agents/therapeutic use , Anti-Inflammatory Agents/pharmacology , RAW 264.7 Cells , Male , Macrophages/drug effects , Macrophages/immunology , Cytokines/metabolism , Lung/pathology , Lung/drug effects , Lung/immunology , Sulfonamides/pharmacology , Sulfonamides/therapeutic use , Mice, Inbred C57BL , Signal Transduction/drug effects , Disease Models, AnimalABSTRACT
The humidity has often been measured through a single point sensor. Where, the humidity could be varied at different locations as well as depending on environmental conditions. The present paper developed the dual point humidity measuring sensor by using a polymer optical fiber (POF) based on a single illuminating fiber. The sensor's basic structure is to twist two fibers and bend them at a certain radius. However, the dual point sensor is developed through the cascading of twisted micro bend (TMB-1 and TMB-2). The twisting of fibers couples the light from one fiber to another fiber through the side coupling method. An increase in the humidity level leads to a change in the reflective index, which helps to get variation in coupled light intensity. To measure the humidity, the dual point sensors are placed into the control humidity chamber at two random positions. The power reading variation is significantly linear when the humidity level increases from 30 to 80%. The sensor has a fast response of about 1 s and a recovery time of about 4 s. Furthermore, the chemical coating is applied to improve the sensor's sensitivity. Between 30 and 80% range of humidity, the both sensors of dual point TMB-1 and TMB-2 have appropriate sensitivity and detection limits, which is about 680.8 nW/% and 763.9 nW/% and 1.37% and 1.98%, respectively. To measure the humidity at variable positions, the present dual points humidity sensor is well-stable, easy, and straightforward, which uses a less expensive method.
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Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species.
Subject(s)
Greenhouse Gases , Quercus , Climate Change , China , Taiwan , EcosystemABSTRACT
The encapsulation of functional colloidal nanoparticles (100â nm) into single-crystalline ZSM-5 zeolites, aiming to create uniform core-shell structures, is a highly sought-after yet formidable objective due to significant lattice mismatch and distinct crystallization properties. In this study, we demonstrate the fabrication of a core-shell structured single-crystal zeolite encompassing an Fe3O4 colloidal core via a novel confinement stepwise crystallization methodology. By engineering a confined nanocavity, anchoring nucleation sites, and executing stepwise crystallization, we have successfully encapsulated colloidal nanoparticles (CN) within single-crystal zeolites. These grafted sites, alongside the controlled crystallization process, compel the zeolite seed to nucleate and expand along the Fe3O4 colloidal nanoparticle surface, within a meticulously defined volume (1.5×107≤V≤1.3×108â nm3). Our strategy exhibits versatility and adaptability to an array of zeolites, including but not restricted to ZSM-5, NaA, ZSM-11, and TS-1 with polycrystalline zeolite shell. We highlight the uniformly structured magnetic-nucleus single-crystalline zeolite, which displays pronounced superparamagnetism (14â emu/g) and robust acidity (~0.83â mmol/g). This innovative material has been effectively utilized in a magnetically stabilized bed (MSB) reactor for the dehydration of ethanol, delivering an exceptional conversion rate (98 %), supreme ethylene selectivity (98 %), and superior catalytic endurance (in excess of 100â hours).
ABSTRACT
Jaw cysts are mainly caused by abnormal tooth development, chronic oral inflammation, or jaw damage, which may lead to facial swelling, deformity, tooth loss, and other symptoms. Due to the diversity and complexity of cyst images, deep-learning algorithms still face many difficulties and challenges. In response to these problems, we present a horizontal-vertical interaction and multiple side-outputs network for cyst segmentation in jaw images. First, the horizontal-vertical interaction mechanism facilitates complex communication paths in the vertical and horizontal dimensions, and it has the ability to capture a wide range of context dependencies. Second, the feature-fused unit is introduced to adjust the network's receptive field, which enhances the ability of acquiring multi-scale context information. Third, the multiple side-outputs strategy intelligently combines feature maps to generate more accurate and detailed change maps. Finally, experiments were carried out on the self-established jaw cyst dataset and compared with different specialist physicians to evaluate its clinical usability. The research results indicate that the Matthews correlation coefficient (Mcc), Dice, and Jaccard of HIMS-Net were 93.61, 93.66 and 88.10% respectively, which may contribute to rapid and accurate diagnosis in clinical practice.
Subject(s)
Cysts , Humans , Cysts/diagnostic imaging , Algorithms , Communication , Inflammation , Image Processing, Computer-AssistedABSTRACT
The sustained loss of HBsAg is considered a pivotal indicator for achieving functional cure of HBV. Dihydroquinolizinone derivatives (DHQs) have demonstrated remarkable inhibitory activity against HBsAg both in vitro and in vivo. However, the reported neurotoxicity associated with RG7834 has raised concerns regarding the development of DHQs. In this study, we designed and synthesized a series of DHQs incorporating nitrogen heterocycle moieties. Almost all of these compounds exhibited potent inhibition activity against HBsAg, with IC50 values at the nanomolar level. Impressively, the compound (S)-2a (10 µM) demonstrated a comparatively reduced impact on the neurite outgrowth of HT22 cells and isolated mouse DRG neurons in comparison to RG7834, thereby indicating a decrease in neurotoxicity. Furthermore, (S)-2a exhibited higher drug exposures than RG7834. The potent anti-HBV activity, reduced neurotoxicity, and favorable pharmacokinetic profiles underscore its promising potential as a lead compound for future anti-HBV drug discovery.
Subject(s)
Hepatitis B Surface Antigens , Hepatitis B virus , Animals , Mice , Antiviral Agents/pharmacology , ZidovudineABSTRACT
Ordered mesoporous crystalline frameworks (MCFs), which possess both functional frameworks and well-defined porosity, receive considerable attention because of their unique properties including high surface areas, large pore sizes, tailored porous structures, and compositions. Construction of novel crystalline mesoporous architectures that allows for rich accessible active sites and efficient mass transfer is envisaged to offer ample opportunities for potential energy-related applications. In this review, the rational synthesis, unique structures, and energy applications of MCFs are the main focus. After summarizing the synthetic approaches, an emphasis is placed on the delicate control of crystallites, mesophases, and nano-architectures by concluding basic principles and showing representative examples. Afterward, the currently fabricated components of MCFs such as metals, metal oxides, metal sulfides, and metal-organic frameworks are described in sequence. Further, typical applications of MCFs in rechargeable batteries, supercapacitors, electrocatalysis, and photocatalysis are highlighted. This review ends with the possible development and synthetic challenges of MCFs as well as a future prospect for high-efficiency energy applications, which underscores a pathway for developing advanced materials.
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The high-current-density Zn-air battery shows big prospects in next-generation energy technologies, while sluggish O2 reaction and diffusion kinetics barricade the applications. Herein, the sequential assembly is innovatively demonstrated for hierarchically mesoporous molybdenum carbides/carbon microspheres with a tunable thickness of mesoporous carbon layers (Meso-Mo2C/C-x, where x represents the thickness). The optimum Meso-Mo2C/C-14 composites (≈2 µm in diameter) are composed of mesoporous nanosheets (≈38 nm in thickness), which possess bilateral mesoporous carbon layers (≈14 nm in thickness), inner Mo2C/C layers (≈8 nm in thickness) with orthorhombic Mo2C nanoparticles (≈2 nm in diameter), a high surface area of ≈426 m2 g-1, and open mesopores (≈6.9 nm in size). Experiments and calculations corroborate the hierarchically mesoporous Mo2C/C can enhance hydrophilicity for supplying sufficient O2, accelerate oxygen reduction kinetics by highly-active Mo2C and N-doped carbon sites, and facilitate O2 diffusion kinetics over hierarchically mesopores. Therefore, Meso-Mo2C/C-14 outputs a high half-wave potential (0.88 V vs RHE) with a low Tafel slope (51 mV dec-1) for oxygen reduction. More significantly, the Zn-air battery delivers an ultrahigh power density (272 mW cm-2), and an unprecedented 100 h stability at a high-current-density condition (100 mA cm-2), which is one of the best performances.
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Mesoporous materials with crystalline frameworks have been widely explored in many fields due to their unique structure and crystalline feature, but accurate manipulations over crystalline scaffolds, mainly composed of uncontrolled polymorphs, are still lacking. Herein, we explored a controlled crystallization-driven monomicelle assembly approach to construct a type of uniform mesoporous TiO2 particles with atomically aligned single-crystal frameworks. The resultant mesoporous TiO2 single-crystal particles possess an angular shape â¼80 nm in diameter, good mesoporosity (a high surface area of 112 m2 g-1 and a mean pore size at 8.3 nm), and highly oriented anatase frameworks. By adjusting the evaporation rate during assembly, such a facile solution-processed strategy further enables the regulation of the particle size and mesopore size without the destruction of the oriented crystallites. Such a combination of ordered mesoporosity and crystalline orientation provides both effective mass and charge transportation, leading to a significant increase in the hydrogen generation rate. A maximum hydrogen evolution rate of 12.5 mmol g-1 h-1 can be realized, along with great stability under solar light. Our study is envisaged to extend the possibility of mesoporous single crystal growth to a range of functional ceramics and semiconductors toward advanced applications.
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As an encouraging photocatalyst, crystalline carbon nitride (CCN) exhibits unsatisfactory photocatalytic activity and stability due to its rapid recombination of photo-generative carriers. Herein, high-crystalline g-C3N4 was prepared, including CCN obtained in KCl (K-CCN), LiCl-KCl mixture (Li/K-CCN), and LiCl-NaCl-KCl mixture (Li/Na/K-CCN), via the molten salt strategy using pre-prepared bulk carbon nitride (BCN) as a precursor. The obtained BCN sample was formed by heptazine-based units, which convert into triazine-based units for K-CCN. Heptazine and triazine are two isotypes that co-exist in the Li/K-CCN and Li/Na/K-CCN samples. Compared with BCN and other CCN samples, the as-prepared Li/Na/K-CCN sample exhibited the optimal photocatalytic hydrogen evolution rates (3.38 mmol·g-1·h-1 under simulated sunlight and 2.25 mmol·g-1·h-1 under visible light) and the highest apparent quantum yield (10.97%). The improved photocatalytic performance of the Li/Na/K-CCN sample is mainly attributed to the construction of type-II heterojunction and the institution of the built-in electric field between triazine-based CCN and heptazine-based BCN. This work provides a new strategy for the structural optimization and heterostructure construction of crystalline carbon nitride photocatalysts.
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Accurate segmentation of skin lesions in dermoscopic images plays an important role in improving the survival rate of patients. However, due to the blurred boundaries of pigment regions, the diversity of lesion features, and the mutations and metastases of diseased cells, the effectiveness and robustness of skin image segmentation algorithms are still a challenging subject. For this reason, we proposed a bi-directional feedback dense connection network framework (called BiDFDC-Net), which can perform skin lesions accurately. Firstly, under the framework of U-Net, we integrated the edge modules into each layer of the encoder which can solve the problem of gradient vanishing and network information loss caused by network deepening. Then, each layer of our model takes input from the previous layer and passes its feature map to the densely connected network of subsequent layers to achieve information interaction and enhance feature propagation and reuse. Finally, in the decoder stage, a two-branch module was used to feed the dense feedback branch and the ordinary feedback branch back to the same layer of coding, to realize the fusion of multi-scale features and multi-level context information. By testing on the two datasets of ISIC-2018 and PH2, the accuracy on the two datasets was given by 93.51% and 94.58%, respectively.
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As a principal category in the promising field of medical image processing, medical image enhancement has a powerful influence on the intermedia features and final results of the computer aided diagnosis (CAD) system by increasing the capacity to transfer the image information in the optimal form. The enhanced region of interest (ROI) would contribute to the early diagnosis and the survival rate of patients. Meanwhile, the enhancement schema can be treated as the optimization approach of image grayscale values, and metaheuristics are adopted popularly as the mainstream technologies for medical image enhancement. In this study, we propose an innovative metaheuristic algorithm named group theoretic particle swarm optimization (GT-PSO) to tackle the optimization problem of image enhancement. Based on the mathematical foundation of symmetric group theory, GT-PSO comprises particle encoding, solution landscape, neighborhood movement and swarm topology. The corresponding search paradigm takes place simultaneously under the guidance of hierarchical operations and random components, and it could optimize the hybrid fitness function of multiple measurements of medical images and improve the contrast of intensity distribution. The numerical results generated from the comparative experiments show that the proposed GT-PSO has outperformed most other methods on the real-world dataset. The implication also indicates that it would balance both global and local intensity transformations during the enhancement process.
Subject(s)
Image Enhancement , Image Processing, Computer-Assisted , Humans , Image Enhancement/methods , Image Processing, Computer-Assisted/methods , Algorithms , Diagnosis, Computer-Assisted , MovementABSTRACT
Mesoporous materials with crystalline frameworks have been acknowledged as very attractive materials in various applications. Nevertheless, due to the cracking issue during crystallization and incompatible hydrolysis and assembly, the precise control for crystalline mesoscale membranes is quite infertile. Herein, we presented an ingenious stepwise monomicelle assembly route for the syntheses of highly ordered mesoporous crystalline TiO2 membranes with delicately controlled mesophase, mesoporosity, and thickness. Such a process involves the preparation of monomicelle hydrogels and follows self-assembly by stepwise solvent evaporation, which enables the sensitive hydrolysis of TiO2 oligomers and dilatory micelle assembly to be united. In consequence, the fabricated mesoporous TiO2 membranes exhibit a broad flexibility, including tunable ordered mesophases (worm-like, hexagonal p6mm to body-centered cubic Im3Ì m), controlled mesopore sizes (3.0-8.0 nm), and anatase grain sizes (2.3-8.4 nm). Besides, such mesostructured crystalline TiO2 membranes can be extended to diverse substrates (Ti, Ag, Si, FTO) with tailored thickness. The great mesoporosity of the in situ fabricated mesoscopic membranes also affords excellent pseudocapacitive behavior for sodium ion storage. This study underscores a novel pathway for balancing the interaction of precursors and micelles, which could have implications for synthesizing crystalline mesostructures in higher controllability.
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Acupuncture has been shown as an effective traditional Chinese medicine treatment method, especially for pain relief. Recently, laser acupuncture is becoming increasingly popular, thanks to its noninvasive and painless nature and effectiveness in treating diseases, proven by many studies (for example, some previous studies showed that low-power laser stimulation is able to increase the power of alpha rhythms and theta waves). In our prior work, we developed a novel laser acupuncture model that emulates lifting-and-thrusting operation commonly used in traditional needle acupuncture and showed its benefit in improving cardiac output and peripheral circulation. By extending our previous studies, in this work, we perform extensive experiments to understand the effect of such a system on electrodermal activity (EDA) of acupoints, pulse characteristics, and brainwave, to further verify its efficacy. In particular, we found that laser stimulation could cause significant changes in EDA of acupoints, pulse amplitude, pulse-rate-variability (PRV), and acupoint conductance, as a function of laser power and stimulation time. In addition, laser acupuncture with the lifting-and-thrusting operation has more significant effect on increasing the power of alpha and theta frequency bands as compared to laser acupuncture without the lifting-and-thrusting operation. Finally, given sufficient stimulation time (e.g., > 20 min), the performance of a low-powered laser acupuncture with the lifting-and-thrusting operation could be comparable to that of traditional needle acupuncture.
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Background: Image segmentation is an important step during the processing of medical images. For example, for the computer aid diagnostic systems for lung cancer image analysis, the segmented regions of tumors would help doctors in early diagnosis to determine timely and appropriate treatment possibilities and thereby improve the survival rate of the patients. However, general clinical routines of manual segmentation for large number of medical images are very difficult and time consuming, which is the challenge we aim to tackle using our proposed method. Methods: A novel image segmentation method with evolutionary learning technique named Group Theoretic Particle Swarm Optimization is proposed. It can tackle multi-level thresholding optimization problem during the segmentation process and rebuild the search paradigm according to the solid mathematical foundation of symmetric group from four designable aspects, which are particle encoding, solution landscape, neighborhood movement and swarm topology, respectively. The Kapur's entropy of multi-level thresholds is assessed as the objective function. Results: In contrast to those conventional metaheuristics methods for lung cancer image segmentation, this newly presented method generates the best performance result among them. Experimental results show that its Kapur's entropy has the value of 9.07, which is 16% higher than the worst case. Computational time is acceptable at the cost of 173.730 seconds, average level of evaluation metrics [Kappa, Precision, Recall, F1-measure, intersection over union (IoU) and receiver operating characteristic (ROC)] is over 90%, and search process of multi-level threshold combination would finally converge in the later phase of iterations after 700. The ablation study indicates that all components are significant to the contributions of our proposed method. Conclusions: Group Theoretic Particle Swarm Optimization for multi-level threshold segmentation is an efficient way to split a medical image into distinct regions and extract tumor tissues regions from the background. It maintains the balanced relationship between diversification and intensification during the search process and helps clinicians to make the diagnosis more accurately. Our proposed method processes potential medical value and clinical meanings.