Application Value Research Articles

NEMO-Binding Domain/IKKγ Inhibitory Peptide Alleviates Neuronal Pyroptosis in Spinal Cord Injury by Inhibiting ASMase-Induced Lysosome Membrane Permeabilization.

A short peptide termed NEMO-binding domain (NBD) peptide has an inhibitory effect on nuclear factor kappa-B (NF-κB). Despite its efficacy in inhibiting inflammatory responses, the precise neuroprotective mechanisms of NBD peptide in spinal cord injury (SCI) remain unclear. This study aims to determine whether the pyroptosis-related aspects involved in the neuroprotective effects of NBD peptide post-SCI.Using RNA sequencing, the molecular mechanisms of NBD peptide in SCI are explored. The evaluation of functional recovery is performed using the Basso mouse scale, Nissl staining, footprint analysis, Masson's trichrome staining, and HE staining. Western blotting, enzyme-linked immunosorbent assays, and immunofluorescence assays are used to examine pyroptosis, autophagy, lysosomal membrane permeabilization (LMP), acid sphingomyelinase (ASMase), and the NF-κB/p38-MAPK related signaling pathway.NBD peptide mitigated glial scar formation, reduced motor neuron death, and enhanced functional recovery in SCI mice. Additionally, NBD peptide inhibits pyroptosis, ameliorate LMP-induced autophagy flux disorder in neuron post-SCI. Mechanistically, NBD peptide alleviates LMP and subsequently enhances autophagy by inhibiting ASMase through the NF-κB/p38-MAPK/Elk-1/Egr-1 signaling cascade, thereby mitigating neuronal death. NBD peptide contributes to functional restoration by suppressing ASMase-mediated LMP and autophagy depression, and inhibiting pyroptosis in neuron following SCI, which may have potential clinical application value.

Zirconium-based nanoclusters as molecular robots for water decontamination

Water contamination owing to anionic pollutants is a persisting and ubiquitous global threat. The current remediation technologies are mostly low in efficiency, expensive in materials and often associated with complicated processes. Herein, we report a characteristic zirconium-based nanocluster that can work as molecular robots for the efficient remediation of anions-contaminated water with great effectiveness and molecular-level accuracy. It exhibits a stimuli-responsive behavior to facilitate the water treatment process: dissolve in acidic aqueous solutions for molecular-level decontamination and quickly aggregate for post-remediation collection. It can precisely capture the representative anionic pollutants, whilst featuring satisfactory capacities (ca. 175 mg-arsenic/g, 60 mg-chromium/g, 45 mg-fluoride/g, 70 mg-phosphorus/g, respectively), super-fast kinetics (finishing uptake within seconds, which is two to four orders of magnitude faster than typical sorbents), as well as multi-cycle applications without appreciable loss of activity. The coexisting common ions show no effect on the target uptake. The responsible active site investigation shows that four active sites are responsible for the monovalent pollutant removal, and the active sites work in pairs to capture divalent chromate species. Cost analysis shows its economical applicability in practical applications. This work would lead to the development of effective water decontamination with higher effectiveness, more convenience, lower cost and more practical application value.

Ferroptosis-inducing nanomedicine and targeted short peptide for synergistic treatment of hepatocellular carcinoma

The poor prognosis of hepatocellular carcinoma (HCC) is still an urgent challenge to be solved worldwide. Hence, assembling drugs and targeted short peptides together to construct a novel medicine delivery strategy is crucial for targeted and synergy therapy of HCC. Herein, a high-efficiency nanomedicine delivery strategy has been constructed by combining graphdiyne oxide (GDYO) as a drug-loaded platform, specific peptide (SP94-PEG) as a spear to target HCC cells, sorafenib, doxorubicin-Fe2+ (DOX-Fe2+), and siRNA (SLC7A11-i) as weapons to exert a three-path synergistic attack against HCC cells. In this work, SP94-PEG and GDYO form nanosheets with HCC-targeting properties, the chemotherapeutic drug DOX linked to ferrous ions increases the free iron pool in HCC cells and synergizes with sorafenib to induce cell ferroptosis. As a key gene of ferroptosis, interference with the expression of SLC7A11 makes the ferroptosis effect in HCC cells easier, stronger, and more durable. Through gene interference, drug synergy, and short peptide targeting, the toxic side effects of chemotherapy drugs are reduced. The multifunctional nanomedicine GDYO@SP94/DOX-Fe2+/sorafenib/SLC7A11-i (MNMG) possesses the advantages of strong targeting, good stability, the ability to continuously induce tumor cell ferroptosis and has potential clinical application value, which is different from traditional drugs.

Terahertz quasi-optics imaging systems with easy zoom based on beam-shaping devices and a freeform lens.

Terahertz (THz) waves show outstanding application value in the nondestructive detection of hidden targets that are impenetrable to visible light. However, the uncertain location of hidden targets puts a higher demand on the zoom function of the THz quasi-optical systems, especially when the object is immovable. This paper proposes a continuous zoom system working in the THz band consisting of a negative axicon disk, a segmented axicon, and a freeform lens. The negative axicon disk and segmented axicon shape THz waves into annular beams with adjustable diameters, which are respectively focused at different positions by the zone-designed freeform lens. Both simulation and experimental results indicate that the zoom range of the system can reach 82 mm while maintaining an imaging resolution of 6 mm. Notably, continuous zooming is achieved by merely rotating the negative axicon disk, instead of the lens moving. Moreover, all devices in the system can be fabricated by 3D printing or machining. This approach offers the advantages of simple adjustment and low cost, providing, to our knowledge, a novel perspective for the design and application of THz quasi-optical imaging systems.

An Agent-Based Method for Feature Recognition and Path Optimization of Computer Numerical Control Machining Trajectories.

In recent years, artificial intelligence technology has seen increasingly widespread application in the field of intelligent manufacturing, particularly with deep learning offering novel methods for recognizing geometric shapes with specific features. In traditional CNC machining, computer-aided manufacturing (CAM) typically generates G-code for specific machine tools based on existing models. However, the tool paths for most CNC machines consist of a series of collinear motion commands (G01), which often result in discontinuities in the curvature of adjacent tool paths, leading to machining defects. To address these issues, this paper proposes a method for CNC system machining trajectory feature recognition and path optimization based on intelligent agents. This method employs intelligent agents to construct models and analyze the key geometric information in the G-code generated during CNC machining, and it uses the MCRL deep learning model incorporating linear attention mechanisms and multiple neural networks for recognition and classification. Path optimization is then carried out using mean filtering, Bézier curve fitting, and an improved novel adaptive coati optimization algorithm (NACOA) according to the degree of unsmoothness of the path. The effectiveness of the proposed method is validated through the optimization of process files for gear models, pentagram bosses, and maple leaf models. The research results indicate that the CNC system machining trajectory feature recognition and path optimization method based on intelligent agents can significantly enhance the smoothness of CNC machining paths and reduce machining defects, offering substantial application value.

The application value of Rs-fMRI-based machine learning models for differentiating mild cognitive impairment from Alzheimer's disease: a systematic review and meta-analysis.

Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD. PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks). In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD. The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis.

A review of advanced helical fibers: formation mechanism, preparation, properties, and applications.

As a unique structural form, helical structures have a wide range of application prospects. In the field of biology, helical structures are essential for the function of biological macromolecules such as proteins, so the study of helical structures can help to deeply understand life phenomena and develop new biotechnology. In materials science, helical structures can give rise to special physical and chemical properties, such as in the case of spiral nanotubes, helical fibers, etc., which are expected to be used in energy, environment, medical and other fields. The helical structure also has unique charm and application value in the fields of aesthetics and architecture. In addition, helical fibers have attracted a lot of attention because of their tendrils' vascular geometry and indispensable structural properties. In this paper, the development of helical fibers is briefly reviewed from the aspects of mechanism, synthesis process and application. Due to their good chemical and physical properties, helical fibers have a good application prospect in many fields. Potential problems and future opportunities for helical fibers are also presented for future studies.

A single-center retrospective comparison of pT1 substaging methods in bladder cancer.

Substaging of T1 urothelial cancer is associated with tumor progression and its reporting is recommended by international guidelines. However, it has not been integrated in risk stratification tools and there is no agreement on the best method to use for its reporting. We aimed to investigate the applicability, interobserver variability, and prognostic value of histological landmark based and micrometric (aggregate linear length of invasive carcinoma (ALLICA), microscopic vs. extensive system, Rete Oncologica Lombarda (ROL) system) substaging methods. A total of 79 patients with the primary diagnosis of T1 urothelial cancer treated with conventional transurethral resection and adjuvant BCG therapy between 2000 and 2020 at the Medical University of Vienna were included. The anatomical and metrical substaging systems were evaluated using agreement rate, Cohen's kappa, Kendall's tau, and Spearman rank correlation. Prognostic value for high-grade recurrence or T2 progression was evaluated in uni- and multivariable analysis. Applicability and reproducibility were good to moderate and varied between substaging methods. Obstacles are mainly due to fragmentation of samples. Anatomical substaging was associated with progression in univariable and multivariable analysis. In our cohort, we could only identify anatomical landmark-based substaging to be prognostic for T2 progression. A major obstacle for proper pathological assessment is fragmentation of samples due to operational procedure. Avoiding such fragmentation might improve reproducibility and significance of pathological T1 substaging of urothelial cancer.

Long-lasting degradation of long-chain alkanes through activating Bacillus-like microbes after Fenton pre-oxidation in soil

To explore the effects and mechanisms of long-lasting degradation of long-chain alkanes (C25-C30) in petroleum-contaminated soil, a solid iron catalyst prepared by adding different proportions of (5 % and 15 % (w/w)) chitosan (CS) was used for Fenton pre-oxidation experiment. Bioremediation experiments were performed for 100 days after pre-oxidation. The results indicated that the degradation for long-chain alkanes and Total Petroleum Hydrocarbons (TPH) were 76.95 % and 76.89 %, respectively. Furthermore, long-lasting degradation of long-chain alkanes was achieved by activating Bacillus-like microbes. In each biodegradation cycle, the long-chain alkanes degradation in the active control group increased by 77.39 mg/kg, 76.74 mg/kg, 36.88 mg/kg, and 76.51 mg/kg compared to the previous cycle. Besides, the half-life of long-chain alkanes was 131 days shorter in the active control group than in the inactive control group. Higher microbial enzyme activity for degrading long-chain alkanes was observed after Fenton pre-oxidation because the expression of alkane metabolism genes was activated by the high consumption of dissolved organic carbon. Finally, the dominant bacterial genera in the active control group shifted predominantly to Paenibacillus (13.26 %), Acinetobacter (8.02 %), and Microbacterium (17.64 %). Therefore, this study possesses significant engineering application value.

Application of core strength training based on learning control robot technology in Badminton

The implementation of core strength training in badminton has received increasing attention as the game and training theories have matured. A single typical strength training session is not the same as core strength training. Strengthening the trunk’s core muscles can help athletes become more adaptable and physically strong, which will have a significant influence on badminton’s future growth. At present, core strength training has been tried to be applied to the routine training of athletes. However, its application has not been scientifically guided and its role cannot be fully exerted, which has adversely affected the improvement of athletes’ skill levels. Consequently, a thorough analysis of badminton’s features was done in this research. The use of core strength training in badminton was thoroughly investigated based on an exploration of the application value of this technique in conjunction with learning and control robot technology. This article examined three levels of special abilities, physical fitness and balancing ability, and compared it with the standard core strength training technology to demonstrate the application impact of the learning control robot’s core strength training in badminton. According to the experimental findings, learning control robot technology may be achieved through core strength training, the average scores of students’ badminton speed quality and strength quality were about 8.10 and 8.45. There was a clear difference between the scores of 6.69 and 7.54 of the traditional training methods, which proved its feasibility.

A Hybrid Prototype Method Combining Physical Models and Generative Artificial Intelligence to Support Creativity in Conceptual Design

Conceptual design is an essential stage in the design process, and its ultimate success largely depends on designers’ creativity. Both physical and digital prototypes are commonly adopted by designers to support ideation and creativity, providing intuitive perception and rapid iteration, respectively. In recent advancements, large-scale generation models are able to offer data-enabled creativity support by generating high-quality solutions comparable to human designers. This opens up an imaginary space for designers and brings new possibilities for design tools. In this study, we proposed a hybrid prototype method that synergistically combines physical models and generative artificial intelligence (AI) in the conceptual design stage. Correspondingly, we developed a hybrid prototype system to implement the proposed method. We conducted a comparative user study with 45 designers who completed a design task using the physical prototype method, standalone generative AI, and the hybrid prototype method, respectively. Our results verified the effectiveness of the hybrid prototype method and investigated its mechanism in supporting creativity. Finally, we discussed the application value and optimisation space of the hybrid prototype method.

Enhancement of Apple Stress Resistance via Proline Elevation by Sugar Substitutes.

Plants encounter numerous adversities during growth, necessitating the identification of common stress activators to bolster their resistance. However, the current understanding of these activators' mechanisms remains limited. This study identified three anti-stress activators applicable to apple trees, all of which elevate plant proline content to enhance resistance against various adversities. The results showed that the application of these sugar substitutes increased apple proline content by two to three times compared to the untreated group. Even at a lower concentration, these activators triggered plant stress resistance without compromising apple fruit quality. Therefore, these three sugar substitutes can be exogenously sprayed on apple trees to augment proline content and fortify stress resistance. Given their effectiveness and low production cost, these activators possess significant application value. Since they have been widely used in the food industry, they hold potential for broader application in plants, fostering apple industry development.

One-Stage Synthesis of Microporous Carbon Adsorbents from Walnut Shells—Evolution of Porosity and Structure

One-stage synthesis technology for preparing carbon adsorbents with tailored porosity from agricultural waste is worthwhile due to their extensive application value. Thermal gravimetric analysis, low-temperature N2 adsorption, X-ray diffraction (XRD), small-angle X-ray scattering (SAXS), and Raman spectroscopy were used to record the structure transformations of carbon materials, namely pore development, proceeding in the course of the step-wise pyrolysis of renewable and low-cost raw materials such as walnut shells (WNSs), which was carried out within a temperature range of 240–950 °C in a CO2 flow. The minimum threshold carbonization temperature for preparing nanoporous carbon materials from WNSs, determined by the examination of the N2 adsorption data, was 500 °C. The maximum specific micropore volume and BET surface achieved in the process without holding a material at a specified temperature were only 0.19 cm3/g and 440 m2/g, respectively. The pyrolysis at 400–600 °C produced amorphous sp2 carbon. At a temperature as high as 750 °C, an increase in the X-ray reflection intensity indicated the ordering of graphite-like crystallites. At high burn-off degrees, the size of coherently scattering domains becomes smaller, and an increased background in X-ray patterns indicates the destruction of cellulose nanofibrils, the disordering of graphene stacks, and an increase in the amount of disordered carbon. At this stage, pores develop in the crystallites. They are tentatively assigned to crystallites with sizes of 15–20 nm and to micropores. According to the Raman spectra combined with the XRD and SAXS data, the structure of all the pyrolysis products is influenced by the complex structure of the walnut shell precursor, which comprises cellulose nanofibrils embedded in lignin. This structure was preserved in the initial stage of pyrolysis, and the graphitization of cellulose fibrils and lignin proceeds at different rates. Most of the pores accessible for gas molecules in the resulting carbon materials are associated with former cellulose fibrils.

Preliminary discrimination and evaluation of clinical application value of ChatGPT4o in bone tumors

Preliminary discrimination and evaluation of clinical application value of ChatGPT4o in bone tumors

Cross-linking manipulation of waterborne biodegradable polyurethane for constructing mechanically adaptable tissue engineering scaffolds

Abstract Mechanical adaptation of tissue engineering scaffolds is critically important since natural tissue regeneration is highly regulated by mechanical signals. Herein, we report a facile and convenient strategy to tune the modulus of waterborne biodegradable polyurethanes (WBPU) via cross-linking manipulation of phase separation and water infiltration for constructing mechanically adaptable tissue engineering scaffolds. Amorphous aliphatic polycarbonate and trifunctional trimethylolpropane were introduced to polycaprolactone-based WBPUs to interrupt interchain hydrogen bonds in the polymer segments and suppress microphase separation, inhibiting the crystallization process and enhancing covalent cross-linking. Intriguingly, as the crosslinking density of WBPU increases and the extent of microphase separation decreases, the material exhibits a surprisingly soft modulus and enhanced water infiltration. Based on this strategy, we constructed WBPU scaffolds with a tunable modulus to adapt various cells for tissue regeneration and regulate the immune response. As a representative application of brain tissue regeneration model in vivo, it was demonstrated that the mechanically adaptable WBPU scaffolds can guide the migration and differentiation of endogenous neural progenitor cells into mature neurons and neuronal neurites and regulate immunostimulation with low inflammation. Therefore, the proposed strategy of tuning the modulus of WBPU can inspire the development of novel mechanically adaptable biomaterials, which has very broad application value.

Ginsenoside Rh2 suppresses ferroptosis in ulcerative colitis by targeting specific protein 1 by upregulating microRNA-125a-5p

BackgroundWorldwide, ulcerative colitis (UC) is becoming increasingly fast growing. Ginsenoside Rh2 has been reported to alleviate UC. However, the latent biological mechanism of Rh2 in the treatment of UC remains uncertain. In this study, the goal was to determine the therapeutic effect of Rh2 on dextran sulfate sodium (DSS)-induced UC.MethodsA DSS-induced UC mouse model was established and divided into 7 groups for Rh2 gavage and/or miR-125a-5p lentivirus injection (n = 10 per group). Colonic specimens were collected for phenotypic and pathological analysis. miR-125a-5p and specific protein 1 (SP1) expression, inflammation-related factors IL-6 and IL-10, and apoptosis were detected in mice. Human normal colon epithelial cell line NCM460 was treated with H2O2 and ferric chloride hexahydrate to construct an in vitro cell model of colitis and induce ferroptosis. Independent sample t-test was used to compare cell proliferation, cell entry, apoptosis, and oxidative stress between the two groups. One way analysis of variance combined with the least significant difference t test was used for comparison between groups. Multiple time points were compared by repeated measurement analysis of variance.ResultsDSS-induced UC mice had significantly decreased body weight, increased disease activity index, decreased colon length, and decreased miR-125a-5p expression (all P < 0.05). In the DSS-induced mouse model, the expression of miR-125a-5p rebounded and ferroptosis was inhibited after Rh2 treatment (all P < 0.05). Inhibition of miR-125a-5p or upregulation of SP1 expression counteracted the protective effects of Rh2 on UC mice and ferroptosis cell models (all P < 0.05).ConclusionsRh2 mitigated DSS-induced colitis in mice and restrained ferroptosis by targeting miR-125a-5p. Downregulating miR-125a-5p or elevating SP1 could counteract the protective impacts of Rh2 on ferroptotic cells. The findings convey that Rh2 has a latent application value in the treatment of UC.Graphical

Research of the calculation formula for working clearance leakage flow of the hydrogen circulation pump

The hydrogen circulation pump (HCP), a device for recovering unconsumed hydrogen gas in fuel cell systems to improve efficiency, is an important equipment in fuel cell systems. Efficient calculation of the output flow rate of the HCP is crucial for accelerating the product development process, but there is a lack of an effective calculation formula for the working clearance leakage. In this paper, a series of HCP models with different working clearances are established and calculated using an overlapping grid simulation method, verifying that the traditional Roots blower leakage flow formula is feasible for HCP, although the maximum calculation error reaches 10.71%. Further study the pressure distribution law inside the HCP chamber, and revise the traditional calculation formula accordingly, so that the average calculation error of the series models is reduced from 5.75% to 3.82%, and the maximum error is also reduced to 7.73%. Compared with the prototype test data, though the flow values obtained from the two calculation formulas are slightly higher, the calculation error of the correction formula is relatively smaller. The research results indicate that the correction formula can more accurately predict the flow rate of HCP and has important application value.

Effect of silica particle size and coating by natural latex on properties of styrene‐butadiene rubber/carbon black/silica composites

AbstractSilica is a renewable resource that has become the primary filler for the rubber used in eco‐friendly tires. However, silica tends to agglomerate in the rubber matrix, particularly, micro‐ and nano‐scale silica, which limits its application. When ordinary‐particle‐size silica with low cost and high stacking density is modified using appropriate methods, high dispersion in rubber and good performance can be achieved with common processing equipment, which has significant engineering application value. In this study, silica particles with different sizes (nano‐scale, 19 and 45 μm) were treated with a 3‐mercaptopropyltriethoxysilane coupling agent (KH580). Subsequently, the silica with the ordinary particle size of 300 mesh (45 μm) was coated with natural latex (NL), and the mechanical properties of the modified silica‐filled styrene‐butadiene rubber (SBR)/carbon black (CB) compounds were investigated. The results revealed that the mechanical properties of the NL‐coated 45 μm silica‐filled composite improved significantly, particularly, in the area of tear strength and elongation at break, the composite properties were improved by 17.1% and 118.2%, respectively. Excellent performance over composites filled with coupling agent‐treated micron‐ and nanoscale silica. Enhancing the surface modification of silica through latex coating provides a means to improve the efficiency of industrial production and reduce costs.Highlights The low‐fine silica treated with KH580 has good dispersibility. Improved mechanical compatibility of NL‐coated silica with rubber. Improvement in strain performance of composites after NL coated with silica. The effect of silica dispersion on composite properties is greater than the effect of particle size. Industrial silica can be successfully addressed, paving the way for extensive utilization.

Application of Deep Learning Model and Machine Learning Detection Algorithm for Gastric Cancer Patients Undergoing Chemotherapy

This work focused on exploring the application value of machine learning detection (MLD) algorithm and evidence-based nursing (EBN) in the chemotherapy (CHET) for gastric cancer (GC) patients. 100 GC patients who were treated in the Guang’an Traditional Chinese Medicine Hospital and needed postoperative CHET were recruited and randomly assigned to experimental (Exp) and control (Ctrl) groups, each including 50 patients. All participants received adjuvant CHET after gastrectomy. During CHET, participants in the Ctrl group were given routine nursing, while the experimental were given EBN in addition to routine nursing. Differences in self-rating anxiety scale (SAS), self-rating depress scale (SDS), QLQ-C30 life core questionnaire, and adverse reaction (AR) evaluation criteria were compared for participants in different groups after nursing. At the same time, all patients underwent computed tomography (CT) examination and all images were detected by MLD algorithm. After intervention, the SAS and SDS scores of patients in the Exp and Ctrl groups were 26.7±5.3 versus 33.6±6.61 and 30.07±5.58 versus 36.11±8.83, respectively. The total health status (THS) score of patients was 5.59±1.17 in Exp group and 4.53±0.96 in Ctrl group, showing P &lt; 0.05. After intervention, great differences were observed in nausea/vomiting, decreased white blood cells (WBC), decreased haemoglobin (Hb), peripheral nerve paraesthesia (PNP), muscle and joint pain (MJP), hair loss, and other indicators between patients received EBN and routine nursing methods (P &lt; 0.05). The MLD algorithm and EBN were of high application value in the nursing of CHET treatment for GC patients.

Effect of Danhong Injection on Articular Cartilage Degeneration in Rabbits with Knee Osteoarthritis

The aim of this research was to investigate the effect of Danhong injection nanoparticle (DIN) plus warm acupuncture (WA) on articular cartilage degeneration in knee osteoarthritis (KOA) rabbits. First, the KOA model and DIN were made. After success, the rabbits were randomly grouped: according to the treatment methods: controls, DIN, WA, and DIN+WA groups, with 10 rabbits in each group. The controls did not receive any treatment, and the other groups received corresponding treatment intervention, respectively. Through treatment, articular cartilage samples were collected. The bone morphology, LequesneMG score, Mankin score were analyzed. The safranin-fast green, toluidine blue, Terminal Deoxynucleotidyl Transferase Mediated dUTP Nick End Labeling (TUNEL), and immunohistochemical staining were observed. The levels of apoptosis-related factors were determined. The results showed that the KOA rabbit model and DIN were successfully constructed. Compared with other groups, the LequesneMG and Mankin scores of DIN+WA group decreased markedly (P &lt; 0.05). Safranin-fast green and toluidine blue staining showed that the number of chondrocytes in DIN+WA group was markedly increased, which was more as against other groups. TUNEL staining revealed that the number of apoptotic chondrocytes was markedly reduced, and the apoptotic index was markedly lower in DIN+WA group as against other three groups (P &lt; 0.05). Compared with other groups, Bax and Caspase-3 were markedly decreased, and Bcl-2 was markedly raised in DIN+WA group (P &lt; 0.05). According to the review, the combined application of DIN and WA can promote the growth of chondrocytes, inhibit the apoptosis of chondrocytes, and effectively improve the degeneration of knee articular cartilage, which has application value.