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To address the conflict between the "fitness" and "feasibility" of body-fitted stents, this paper investigates the impact of various smoothing design strategies on the mechanical behaviour and apposition performance of stent. Based on the three-dimensional projection method, the projection region was fitted with the least squares method (fitting orders 1-6 corresponded to models 1-6, respectively) to achieve the effect of smoothing the body-fitted stent. The simulation included the crimping and expansion process of six groups of stents in stenotic vessels with different degrees of plaque calcification. Various metrics were analyzed, including bending stiffness, stent ruggedness, area residual stenosis rate, contact area fraction, and contact volume fraction. The study findings showed that the bending stiffness, stent ruggedness, area residual stenosis rate, contact area fraction and contact volume fraction increased with the fitting order's increase. Model 1 had the smallest contact area fraction and contact volume fraction, 77.63% and 83.49% respectively, in the incompletely calcified plaque environment. In the completely calcified plaque environment, these values were 72.86% and 82.21%, respectively. Additionally, it had the worst "fitness". Models 5 and 6 had similar values for stent ruggedness, with 32.15% and 32.38%, respectively, which indicated the worst "feasibility" for fabrication and implantation. Models 2, 3, and 4 had similar area residual stenosis rates in both plaque environments. In conclusion, it is more reasonable to obtain the body-fitted stent by using 2nd to 4th order fitting with the least squares method to the projected region. Among them, the body-fitted stent obtained by the 2nd order fitting performs better in the completely calcified environment.

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A key strategy for increasing drug mass (DM) while maintaining good safety is to improve the drug release profile (RP). We designed a dual layer coating drug-eluting stent (DES) that exhibited smaller concentration gradients between the coating and the artery wall and significantly impacted the drug RP. However, a detailed understanding of the effects of the DES designed by our team on safety and efficacy is still lacking. The objective of this study was to provide a comprehensive multiscale computational framework that would allow us to probe the safety and efficacy of the DES we designed. This framework consisted of four coupled modules, namely (1) a mechanical stimuli module, simulating mechanical stimuli caused by percutaneous coronary intervention through a finite element analysis, (2) an inflammation module, simulating inflammation of vascular smooth muscle cells (VSMCs) induced by mechanical stimuli through an agent-based model (ABM), (3) a drug transport module, simulating drug transport through a continuum-based approach, and (4) a mitosis module, simulating VSMC mitosis through an ABM. Our results indicated that when the DM increased to two times the initial DM value, the DES we designed had higher safety and lower efficacy values than a conventional DES. When the DM increased to five times the initial DM value, the DES we designed had higher safety than a conventional DES, and negligible differences in efficacy compared with a conventional DES. In summary, the DES we designed exhibited a significant advantage in safety, but a slightly reduced efficacy compared with that of a conventional DES.

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Background: Pneumonia and lung cancer have a mutually reinforcing relationship. Lung cancer patients are prone to contracting COVID-19, with poorer prognoses. Additionally, COVID-19 infection can impact anticancer treatments for lung cancer patients. Developing an early diagnostic system for COVID-19 pneumonia can help improve the prognosis of lung cancer patients with COVID-19 infection. Method: This study proposes a neural network for COVID-19 diagnosis based on non-enhanced CT scans, consisting of two 3D convolutional neural networks (CNN) connected in series to form two diagnostic modules. The first diagnostic module classifies COVID-19 pneumonia patients from other pneumonia patients, while the second diagnostic module distinguishes severe COVID-19 patients from ordinary COVID-19 patients. We also analyzed the correlation between the deep learning features of the two diagnostic modules and various laboratory parameters, including KL-6. Result: The first diagnostic module achieved an accuracy of 0.9669 on the training set and 0.8884 on the test set, while the second diagnostic module achieved an accuracy of 0.9722 on the training set and 0.9184 on the test set. Strong correlation was observed between the deep learning parameters of the second diagnostic module and KL-6. Conclusion: Our neural network can differentiate between COVID-19 pneumonia and other pneumonias on CT images, while also distinguishing between ordinary COVID-19 patients and those with white lung. Patients with white lung in COVID-19 have greater alveolar damage compared to ordinary COVID-19 patients, and our deep learning features can serve as an imaging biomarker.

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Tyrannosaurids were the most derived group of Tyrannosauroidea and are characterized by having two body plans: gracile, long-snouted and robust, deep-snouted skulls. Both groups lived sympatrically in central Asia. Here, we report a new deep-snouted tyrannosaurid, Asiatyrannus xui gen. et sp. nov., from the Upper Cretaceous of Ganzhou City, southeastern China, which has produced the large-bodied and long-snouted Qianzhousaurus. Based on histological analysis, the holotype of Asiatyrannus xui is not a somatically mature adult, but it already passed through the most rapid growth stages. Asiatyrannus is a small to medium-sized tyrannosaurine, with a skull length of 47.5 cm and an estimated total body length of 3.5-4 m; or around half the size of Qianzhousaurus and other large-bodied tyrannosaurines in similar growth stages. Asiatyrannus and Qianzhousaurus are sympatric tyrannosaurid genera in the Maastrichtian of southeastern China. Asiatyrannus differs from Qianzhousaurus in that it has a proportionally deeper snout, longer premaxilla, deeper maxilla, and deeper dentary, and the cornual process of the lacrimal is inflated without developing a discrete horn. The different skull proportions and body sizes suggest that Asiatyrannus and Qianzhousaurus likely had different feeding strategies and occupied different ecological niches.

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BACKGROUND: The purpose of this study is to determine the variations in the prevalence of self-reported asthma among the adult population in the United States of America (USA), analyzing demographic characteristics, physical indicators, living habits, and sarcopenia. METHODS: 10,566 participants from the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) of the USA who were 20 years of age or older and not pregnant were included in the study. RESULTS: The prevalence of patients with asthma varies by age, gender, and race. The weighted prevalence is 15.5%, estimated to represent 19.36 million people in the USA (95% CI, 14.5% to 16.6%). The prevalence of self-reported asthma decreases with age, with the highest prevalence among young adults aged 20-25 for both males and females. Females were also more susceptible to asthma compared to males. The increase in asthma prevalence attributed to smoking was most pronounced among African American and Caucasian participants (p < 0.05), while its effect on Mexican American and Asian participants was relatively minor. Notably, the prevalence of asthma was significantly higher in African American and Caucasian participants with sarcopenia compared to those without sarcopenia. CONCLUSIONS: The prevalence of asthma is associated to varying degrees with factors such as age, gender, smoking, and the presence of sarcopenia. The elevated prevalence of asthma among young people and females warrants attention. Intensifying efforts toward smoking cessation and the scientific management of sarcopenia could be instrumental in reducing the incidence of asthma.

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This article comprehensively elucidates the discovery of Krebs von den Lungen-6 (KL-6), its structural features, functional mechanisms, and the current research status in various respiratory system diseases. Discovered in 1985, KL-6 was initially considered a tumor marker, but its elevated levels in interstitial lung disease (ILD) led to its recognition as a relevant serum marker for ILD. KL-6 is primarily produced by type 2 alveolar epithelial cell regeneration. Over the past 30 years since the discovery of KL-6, the number of related research papers has steadily increased annually. Following the coronavirus disease 2019 (COVID-19) pandemic, there has been a sudden surge in relevant literature. Despite KL-6's potential as a biomarker, its value in the diagnosis, treatment, and prognosis varies across different respiratory diseases, including ILD, idiopathic pulmonary fibrosis (IPF), COVID-19, and lung cancer. Therefore, as an important serum biomarker in respiratory system diseases, the value of KL-6 still requires further investigation.

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BACKGROUND AND OBJECTIVE: The metabolic syndrome induced by obesity is closely associated with cardiovascular disease, and the prevalence is increasing globally, year by year. Obesity is a risk marker for detecting this disease. However, current research on computer-aided detection of adipose distribution is hampered by the lack of open-source large abdominal adipose datasets. METHODS: In this study, a benchmark Abdominal Adipose Tissue CT Image Dataset (AATCT-IDS) containing 300 subjects is prepared and published. AATCT-IDS publics 13,732 raw CT slices, and the researchers individually annotate the subcutaneous and visceral adipose tissue regions of 3213 of those slices that have the same slice distance to validate denoising methods, train semantic segmentation models, and study radiomics. For different tasks, this paper compares and analyzes the performance of various methods on AATCT-IDS by combining the visualization results and evaluation data. Thus, verify the research potential of this data set in the above three types of tasks. RESULTS: In the comparative study of image denoising, algorithms using a smoothing strategy suppress mixed noise at the expense of image details and obtain better evaluation data. Methods such as BM3D preserve the original image structure better, although the evaluation data are slightly lower. The results show significant differences among them. In the comparative study of semantic segmentation of abdominal adipose tissue, the segmentation results of adipose tissue by each model show different structural characteristics. Among them, BiSeNet obtains segmentation results only slightly inferior to U-Net with the shortest training time and effectively separates small and isolated adipose tissue. In addition, the radiomics study based on AATCT-IDS reveals three adipose distributions in the subject population. CONCLUSION: AATCT-IDS contains the ground truth of adipose tissue regions in abdominal CT slices. This open-source dataset can attract researchers to explore the multi-dimensional characteristics of abdominal adipose tissue and thus help physicians and patients in clinical practice. AATCT-IDS is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/AATTCT-IDS/23807256.

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BACKGROUND AND OBJECTIVE: Intracerebral hemorrhage is one of the diseases with the highest mortality and poorest prognosis worldwide. Spontaneous intracerebral hemorrhage (SICH) typically presents acutely, prompt and expedited radiological examination is crucial for diagnosis, localization, and quantification of the hemorrhage. Early detection and accurate segmentation of perihematomal edema (PHE) play a critical role in guiding appropriate clinical intervention and enhancing patient prognosis. However, the progress and assessment of computer-aided diagnostic methods for PHE segmentation and detection face challenges due to the scarcity of publicly accessible brain CT image datasets. METHODS: This study establishes a publicly available CT dataset named PHE-SICH-CT-IDS for perihematomal edema in spontaneous intracerebral hemorrhage. The dataset comprises 120 brain CT scans and 7,022 CT images, along with corresponding medical information of the patients. To demonstrate its effectiveness, classical algorithms for semantic segmentation, object detection, and radiomic feature extraction are evaluated. The experimental results confirm the suitability of PHE-SICH-CT-IDS for assessing the performance of segmentation, detection and radiomic feature extraction methods. RESULTS: This study conducts numerous experiments using classical machine learning and deep learning methods, demonstrating the differences in various segmentation and detection methods on the PHE-SICH-CT-IDS. The highest precision achieved in semantic segmentation is 76.31%, while object detection attains a maximum precision of 97.62%. The experimental results on radiomic feature extraction and analysis prove the suitability of PHE-SICH-CT-IDS for evaluating image features and highlight the predictive value of these features for the prognosis of SICH patients. CONCLUSION: To the best of our knowledge, this is the first publicly available dataset for PHE in SICH, comprising various data formats suitable for applications across diverse medical scenarios. We believe that PHE-SICH-CT-IDS will allure researchers to explore novel algorithms, providing valuable support for clinicians and patients in the clinical setting. PHE-SICH-CT-IDS is freely published for non-commercial purpose at https://figshare.com/articles/dataset/PHE-SICH-CT-IDS/23957937.

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Biodegradable stents can support vessels for an extended period, maintain vascular patency, and progressively degrade once vascular remodeling is completed, thereby reducing the constraints of traditional metal stents. An ideal degradable stent must have good mechanical properties, degradation behavior, and biocompatibility. Zinc has become a new type of biodegradable metal after magnesium and iron, owing to its suitable degradation rate and good biocompatibility. However, zinc's poor strength and ductility make it unsuitable as a vascular stent material. Therefore, this paper reviewed the primary methods for improving the overall properties of zinc. By discussing the mechanical properties, degradation behavior, and biocompatibility of various improvement strategies, we found that alloying is the most common, simple, and effective method to improve mechanical properties. Deformation processing can further improve the mechanical properties by changing the microstructures of zinc alloys. Surface modification is an important means to improve the biological activity, blood compatibility and corrosion resistance of zinc alloys. Meanwhile, structural design can not only improve the mechanical properties of the vascular stents, but also endow the stents with special properties such as negative Poisson 's ratio. Manufacturing zinc alloys with excellent degradation properties, improved mechanical properties and strong biocompatibility and exploring their mechanism of interaction with the human body remain areas for future research.

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Current research on the fatigue properties of degradable zinc alloy stents has not yet considered the issue of the fatigue life changing with material properties during the dynamic degradation process. Therefore, in this paper, we established a fatigue damage algorithm to study the fatigue problem affected by the changing of material properties during the dynamic degradation process of the stent under the action of pulsating cyclic loading. Three models: the dynamic degradation model, the dynamic degradation model under pulsating cyclic loading, and the coupled model of fatigue damage and dynamic degradation, were developed to verify the effect of fatigue damage on stent life. The results show that fatigue damage leads to a deeper degree of inhomogeneous degradation of the stent, which affects the service life of the stent. Fatigue damage is a factor that cannot be ignored. Therefore, when studying the mechanical properties and lifetime of degradable stents, incorporating fatigue damage into the study can help more accurately assess the lifetime of the stents.

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Colorectal Cancer (CRC) is currently one of the most common and deadly cancers. CRC is the third most common malignancy and the fourth leading cause of cancer death worldwide. It ranks as the second most frequent cause of cancer-related deaths in the United States and other developed countries. Histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of CRC. In order to improve the objectivity and diagnostic efficiency for image analysis of intestinal histopathology, Computer-aided Diagnosis (CAD) methods based on machine learning (ML) are widely applied in image analysis of intestinal histopathology. In this investigation, we conduct a comprehensive study on recent ML-based methods for image analysis of intestinal histopathology. First, we discuss commonly used datasets from basic research studies with knowledge of intestinal histopathology relevant to medicine. Second, we introduce traditional ML methods commonly used in intestinal histopathology, as well as deep learning (DL) methods. Then, we provide a comprehensive review of the recent developments in ML methods for segmentation, classification, detection, and recognition, among others, for histopathological images of the intestine. Finally, the existing methods have been studied, and the application prospects of these methods in this field are given.

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The Special Issue entitled "Biomechanical Study and Analysis for Cardiovascular/Skeletal Materials and Devices" addresses biological functional materials and devices relevant to cardiovascular diseases and orthopedic conditions [...].

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Dynamization, that is, increasing interfragmentary movement (IFM) by reducing fixation stiffness from a rigid to a more flexible state, has been successfully used in clinical practice to promote fracture healing. However, it remains unclear how dynamization timing and degree affect bone healing of different fracture types. Finite element models of tibial fractures based on the OTA/AO classification (Simple: A1-Spiral, A2-Oblique, A3-Transverse; Wedge: B2-Spiral, B3-Fragmented; Complex: C2-Segment, C3-Irregular), in combination with fuzzy logic-based mechano-regulatory tissue differentiation algorithms, were used to simulate the healing process when dynamization of varied degrees (dynamization coefficient or DC = 0-0.9; 0.9 represents 90% reduction in the fixation stiffness relative to a rigid fixation) were applied at different time points after fracture. The fuzzy logic-based algorithms have been validated with a preclinical animal model. The results showed that the healing responses of type A fractures were more sensitive to the changes in dynamization degree and timing comparing with type B or C fractures. Additionally, the optimal dynamization regime for each fracture type was different. For type A fractures, a moderate dynamization degree (e.g., DC = 0.5) applied after Week 1 promoted the recovery of biomechanical integrity. For type B and C fractures, the effective dynamization included a greater dynamization degree (DC = 0.7) applied after Week 2. Our results further demonstrated that the fracture morphology affected interfragmentary strain environments within the callus, leading to varied healing results for different fracture types. These results suggest that the effects of dynamization are highly dependent of the fracture types. Therefore, specific dynamization strategies should be chosen for different fracture types to achieve optimal healing outcomes.

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Bone has a special structure that is both stiff and elastic, and the composition of bone confers it with an exceptional mechanical property. However, bone substitute materials that are made of the same hydroxyapatite (HA) and collagen do not offer the same mechanical properties. It is important for bionic bone preparation to understand the structure of bone and the mineralization process and factors. In this paper, the research on the mineralization of collagen is reviewed in terms of the mechanical properties in recent years. Firstly, the structure and mechanical properties of bone are analyzed, and the differences of bone in different parts are described. Then, different scaffolds for bone repair are suggested considering bone repair sites. Mineralized collagen seems to be a better option for new composite scaffolds. Last, the paper introduces the most common method to prepare mineralized collagen and summarizes the factors influencing collagen mineralization and methods to analyze its mechanical properties. In conclusion, mineralized collagen is thought to be an ideal bone substitute material because it promotes faster development. Among the factors that promote collagen mineralization, more attention should be given to the mechanical loading factors of bone.

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In cyanobacteria and algae (but not plants), flavodoxin (Fld) replaces ferredoxin (Fd) under stress conditions to transfer electrons from photosystem I (PSI) to ferredoxin-NADP+ reductase (FNR) during photosynthesis. Fld constitutes a small electron carrier noncovalently bound to flavin mononucleotide (FMN), and also an ideal model for revealing the protein/flavin-binding mechanism because of its relative simplicity compared to other flavoproteins. Here, we report two crystal structures of apo-Fld from Synechococcus sp. PCC 7942, one dimeric structure of 2.09 Å and one monomeric structure of 1.84 Å resolution. Analytical ultracentrifugation showed that in solution, apo-Fld exists both as monomers and dimers. Our dimer structure contains two ligand-binding pockets separated by a distance of 45 Å, much longer than the previous structures of FMN-bound dimers. These results suggested a potential dimer-monomer transition mechanism of cyanobacterial apo-Fld. We further propose that the dimer represents the "standby" state to stabilize itself, while the monomer constitutes the "ready" state to bind FMN. Furthermore, we generated a new docking model of cyanobacterial Fld-FNR complex based on the recently reported cryo-EM structures, and mapped the special interactions between Fld and FNR in detail.

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Percutaneous coronary intervention with stent implantation is one of the most commonly used approaches to treat coronary artery stenosis. Stent malapposition (SM) can increase the incidence of stent thrombosis, but the quantitative association between SM distance and stent thrombosis is poorly clarified. The objective of this study is to determine the biomechanical reaction mechanisms underlying stent thrombosis induced by SM and to quantify the effect of different SM severity grades on thrombosis. The thrombus simulation was performed in a continuous model based on the diffusion-convection response of blood substance transport. Simulated models included well-apposed stents and malapposed stents with various severities where the detachment distances ranged from 0 to 400 µm. The abnormal shear stress induced by SM was considered a critical contributor affecting stent thrombosis, which was dependent on changing SM distances in the simulation. The results illustrate that the proportion of thrombus volume was 1.88% at a SM distance of 75 µm (mild), 3.46% at 150 µm, and 3.93% at 400 µm (severe), but that a slight drop (3.18%) appeared at the detachment distance of 225 µm (intermediate). The results indicate that when the SM distance was less than 150 µm, the thrombus rose notably as the gap distance increased, whereas the progression of thrombogenicity weakened when it exceeded 150 µm. Therefore, more attention should be paid when SM is present at a gap distance of 150 µm. Moreover, when the SM length of stents are the same, thrombus tends to accumulate downstream towards the distal end of the stent as the SM distance increases.

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To explore the effects and safety of low dose of esketamine combined with propofol in elderly patients undergoing fibronchoscopy. Eighty elderly patients who underwent painless fibronchoscopy in our hospital from June 2021 to September 2021 were recruited,and randomly divided into experimental group (esketamine 0.15mg/ kg + propofol 1mg/ kg) and control group (sufentanil 0.1 µg/ kg + propofol 1mg/ kg), with 40 cases in each group. There were significant differences in MAP, HR and SpO2 of T2, T3 and T4 between the experimental and control groups (P < .05). Besides, there were significantly differences on the trend of change between the 2 groups, with a small and relatively stable fluctuation in the experimental group (P < .05). Compared with the control group, the total dosage of propofol in the experimental group was significantly lower, and the number of vasoactive drugs, the incidence of respiratory depression and bronchospasm were significantly lower (P < .05). There was no significant difference in microscopic examination time, wake-up time, visual analogue score, and agitation, mental symptoms, increased secretion, nausea and vomiting, choking cough and laryngeal spasm during awakening period between the 2 groups. The incidence of total adverse reactions in the experimental group were strongly lower than those in control group. (P < .05). Low dose of esketamine combined with propofol can be safely used for fibronchoscopy in elderly patients, with good effects, more stable respiration and circulation, and low incidence of adverse reactions.

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BACKGROUND AND OBJECTIVE: Distraction osteogenesis (DO), a bone lengthening technique, is widely employed to treat congenital and acquired limb length discrepancies and large segmental bone defects. However, a major issue of DO is the prolonged consolidation phase (10-36 months) during which patients must wear a cumbersome external fixator. Attempts have been made to accelerate the healing process of DO by an alternating distraction and compression mode (so-called "accordion" technique or AT). However, it remains unclear how varied AT parameters affect DO outcomes and what the most effective AT mode is. METHODS: Based on an experimentally-verified mechanobiological model, we performed a parametric analysis via in silico simulation of the bone regeneration process of DO under different AT modes, including combinations of varied application times (AT began at week 1-8 of the consolidation phase), durations (AT was used continuously for 1 week, 2 weeks or 4 weeks) and rates (distraction or compression at 0.25, 0.5, 0.75, and 1 mm/12 h). The control group had no AT applied during the consolidation phase. RESULTS: Compared with the control group (no AT), AT applied at an early consolidation stage (e.g. week 1 of the consolidation phase) significantly enhanced bone formation and reduced the overall healing time. However, the effect of AT on bone healing was dependent on its duration and rate. Specifically, a moderate rate of AT (e.g. 0.5 mm/12 h) lasting for two weeks promoted blood perfusion recovery and bone regeneration, ultimately shortening the healing time. Conversely, over-high rates (e.g. 1 mm/12 h) and longer durations (e.g. 4 weeks) of AT adversely affected bone regeneration and blood perfusion recovery, thereby delaying bone bridging. CONCLUSIONS: These results suggest that the therapeutic effects of AT on DO are highly dependent of the AT parameters of choice. Under appropriate durations and rates, the AT applied at an early consolidation phase is beneficial for blood recovery and bone regeneration. These results may provide a basis for selecting effective AT modes to accelerate consolidation and reduce the overall treatment period of DO.

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Traditional inert materials used in internal fixation have caused many complications and generally require removal with secondary surgeries. Biodegradable materials, such as magnesium (Mg)-, iron (Fe)- and zinc (Zn)-based alloys, open up a new pathway to address those issues. During the last decades, Mg-based alloys have attracted much attention by researchers. However, the issues with an over-fast degradation rate and release of hydrogen still need to be overcome. Zn alloys have comparable mechanical properties with traditional metal materials, e.g., titanium (Ti), and have a moderate degradation rate, potentially serving as a good candidate for internal fixation materials, especially at load-bearing sites of the skeleton. Emerging Zn-based alloys and composites have been developed in recent years and in vitro and in vivo studies have been performed to explore their biodegradability, mechanical property, and biocompatibility in order to move towards the ultimate goal of clinical application in fracture fixation. This article seeks to offer a review of related research progress on Zn-based biodegradable materials, which may provide a useful reference for future studies on Zn-based biodegradable materials targeting applications in orthopedic internal fixation.

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Most of the studies on the finite element analysis (FEA) of biodegradable vascular stents (BVSs) during the degradation process have limited the accuracy of the simulation results due to the application of the uniform degradation model. This paper aims to establish an FEA model for the non-uniform degradation of BVSs by considering factors such as the dynamic changes of the corrosion properties and material properties of the element, as well as the pitting corrosion and stress corrosion. The results revealed that adjusting the corrosion rate according to the number of exposed surfaces of the element and reducing the stress threshold according to the corrosion status accelerates the degradation time of BVSs by 26% and 25%, respectively, compared with the uniform degradation model. The addition of the pitting model reduces the service life of the BVSs by up to 12%. The effective support of the stent to the vessel could reach at least 60% of the treatment effect before the vessel collapsed. These data indicate that the proposed non-uniform degradation model of BVSs with multiple factors produces different phenomena compared with the commonly used models and make the numerical simulation results more consistent with the real degradation scenario.