A quadratic isothermal amplification fluorescent biosensor without intermediate purification for ultrasensitive detection of circulating tumor DNA.

Circulating tumor DNA (ctDNA) is an auspicious tumor biomarker released into the bloodstream by tumor cells, offering abundant information concerning cancer genes. It plays a crucial role in the early diagnosis of cancer. However, due to extremely low levels in body fluids, achieving a simple, sensitive, and highly specific detection of ctDNA remains challenging. Here, we constructed a purification-free fluorescence biosensor based on quadratic amplification of ctDNA by combining nicking enzyme mediated amplification (NEMA) and catalytic hairpin assembly (CHA) reactions. After double isothermal amplification, this biosensor achieved an impressive signal amplification of nearly 107-fold, enabling it to detect ctDNA with ultra-sensitivity. And the detection limit of this biosensor is as low as 2 aM. In addition, we explored the influence of human serum on the performance of the biosensor and found that it showed favorable sensitivity in the presence of serum. This biosensor eliminates the need for an intermediate purification step, resulting in enhanced sensitivity and convenience. Thus, our purification-free fluorescent biosensor exhibits ultra-high sensitivity when compared to other biosensors and has the potential to serve as an effective diagnostic tool for early detection of cancer.

In-situ synthesis Fe3C@C/rGO as matrix for high performance lithium-sulfur batteries at room and low temperatures.

People have been focusing on how to improve the specific capacity and cycling stability of lithium-sulfur batteries at room temperature, however, on some special occasions such as cold cities and aerospace fields, the operating temperature is low, which dramatically hinders the performance of batteries. Here, we report an iron carbide (Fe3C)/rGO composite as electrode host, the Fe3C nanoparticles in the composite have strong adsorption and high catalytic ability for polysulfide. The rGO makes the distribution of Fe3C nanoparticles more disperse, and this specific structure makes the deposition of Li2S more uniform. Therefore, it realizes the rapid transformation and high performance of lithium-sulfur batteries at both room and low temperatures. At room temperature, after 100 cycles at 1C current density, the reversible specific capacity of the battery can be stabilized at 889 ± 7.1 mAh/g. Even at -40 °C, in the first cycle battery still emits 542.9 ± 3.7 mAh/g specific capacity. This broadens the operating temperature for lithium-sulfur batteries and also provides a new idea for the selection of host materials for sulfur in low-temperature lithium-sulfur batteries.

A label-free colorimetric biosensor utilizing natural material for highly sensitive exosome detection.

Exosomes, extracellular vesicles secreted by cells, play a crucial role in intercellular communication by transferring information from source cells to recipient cells. These vesicles carry important biomarkers, including nucleic acids and proteins, which provide valuable insights into the parent cells' status. As a result, exosomes have emerged as noninvasive indicators for the early diagnosis of cancer. Colorimetric biosensors have garnered significant attention due to their cost-effectiveness, simplicity, rapid response, and reproducibility. In this study, we employ sporopollenin microcapsules (SP), a natural biopolymer material derived from pollen, as a substrate for gold nanoparticles (AuNPs). By modifying the SP-Au complex with CD63 aptamers, we develop a label-free colorimetric biosensor for exosome detection. In the absence of exosomes, the SP-Au complex catalyzes the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), resulting in a color change from colorless to blue. However, the addition of exosomes inhibits the catalytic activity of the SP-Au complex due to coverage of exosomes on AuNPs. This colorimetric biosensor exhibits high sensitivity and selectivity for exosome detection, with a detection limit of 10 particles/µL and a wide linear range of 10 - 108 particles/µL. Additionally, the SP-Au biosensor demonstrates remarkable resistance to serum protein adsorption and excellent catalytic stability even in harsh environments, making it highly suitable for clinical diagnostics.

Transient Temperature at Tool-Chip Interface during Initial Period of Chip Formation in Orthogonal Cutting of Inconel 718.

Machining nickel-based super alloys such as Inconel 718 generates a high thermal load induced via friction and plastic deformation, causing these alloys to be among most difficult-to-cut materials. Localized heat generation occurring in machining induces high temperature gradients. Experimental techniques for determining cutting tool temperature are challenging due to the small dimensions of the heat source and the chips produced, making it difficult to observe the tool-chip interface. Therefore, theoretical analysis of cutting temperatures is crucial for understanding heat generation and temperature distribution during cutting operations. Periodic heating and cooling occurring during cutting and interruption, respectively, are modeled using a hybrid analytical and finite element (FE) transient thermal model. In addition to identifying a transition distance associated with initial period of chip formation (IPCF) from apparent coefficient of friction results using a sigmoid function, the transition temperature is also identified using the thermal model. The model is validated experimentally by measuring the tool-chip interface temperature using a two-color pyrometer at a specific cutting distance. Due to the cyclic behavior in interrupted cutting, where a steady-state condition may or may not be achieved, transient thermal modeling is required in this case. Input parameters required to identify the heat flux for the transient thermal model are obtained experimentally and the definitions of heat-flux-reducing factors along the cutting path are associated with interruptions and the repeating IPCF. The thermal model consists of two main parts: one is related to identifying the heat flux, and the other part involves the determination of the temperature field within the tool using a partial differential equation (PDE) solved numerically via a 2D finite element method.

Multi-Stage Network With Geometric Semantic Attention for Two-View Correspondence Learning.

The removal of outliers is crucial for establishing correspondence between two images. However, when the proportion of outliers reaches nearly 90%, the task becomes highly challenging. Existing methods face limitations in effectively utilizing geometric transformation consistency (GTC) information and incorporating geometric semantic neighboring information. To address these challenges, we propose a Multi-Stage Geometric Semantic Attention (MSGSA) network. The MSGSA network consists of three key modules: the multi-branch (MB) module, the GTC module, and the geometric semantic attention (GSA) module. The MB module, structured with a multi-branch design, facilitates diverse and robust spatial transformations. The GTC module captures transformation consistency information from the preceding stage. The GSA module categorizes input based on the prior stage's output, enabling efficient extraction of geometric semantic information through a graph-based representation and inter-category information interaction using Transformer. Extensive experiments on the YFCC100M and SUN3D datasets demonstrate that MSGSA outperforms current state-of-the-art methods in outlier removal and camera pose estimation, particularly in scenarios with a high prevalence of outliers. Source code is available at https://github.com/shuyuanlin.

Empagliflozin and liraglutide ameliorate HFpEF in mice via augmenting the Erbb4 signaling pathway.

Heart failure with preserved ejection fraction (HFpEF) is closely associated with metabolic derangement. Sodium glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) exert anti-HFpEF effects, but the underlying mechanisms remain unclear. In this study, we explored the anti-HFpEF effects of empagliflozin and liraglutide and the underlying molecular mechanisms in a mouse model of HFpEF. This model was established by high-fat diet (HFD) feeding plus Nω-nitro-L-arginine methyl ester (L-NAME) treatment. The mice were treated with empagliflozin (20 mg·kg-1·d-1, i.g.) or liraglutide (0.3 mg·kg-1·d-1, i.p.) or their combination for 4 weeks. At the end of the experimental protocol, cardiac function was measured using ultrasound, then mice were euthanized and heart, liver, and kidney tissues were collected. Nuclei were isolated from frozen mouse ventricular tissue for single-nucleus RNA-sequencing (snRNA-seq). We showed that administration of empagliflozin or liraglutide alone or in combination significantly improved diastolic function, ameliorated cardiomyocyte hypertrophy and cardiac fibrosis, as well as exercise tolerance but no synergism was observed in the combination group. Furthermore, empagliflozin and/or liraglutide lowered body weight, improved glucose metabolism, lowered blood pressure, and improved liver and kidney function. After the withdrawal of empagliflozin or liraglutide for 1 week, these beneficial effects tended to diminish. The snRNA-seq analysis revealed a subcluster of myocytes, in which Erbb4 expression was down-regulated under HFpEF conditions, and restored by empagliflozin or liraglutide. Pseudo-time trajectory analysis and cell-to-cell communication studies confirmed that the Erbb4 pathway was a prominent pathway essential for both drug actions. In the HFpEF mouse model, both empagliflozin and liraglutide reversed Erbb4 down-regulation. In rat h9c2 cells, we showed that palmitic acid- or high glucose-induced changes in PKCα and/or ERK1/2 phosphorylation at least in part through Erbb4. Collectively, the single-cell atlas reveals the anti-HFpEF mechanism of empagliflozin and liraglutide, suggesting that Erbb4 pathway represents a new therapeutic target for HFpEF. Effects and mechanisms of action of empagliflozin and liraglutide in HFpEF mice. HFpEF was induced with a high-fat diet and L-NAME for 15 weeks, and treatment with empagliflozin and liraglutide improved the HFpEF phenotype. Single nucleus RNA sequencing (snRNA-seq) was used to reveal the underlying mechanism of action of empagliflozin and liraglutide.

Exploring the Application of Graphene Oxide-Based Nanomaterials in the Repair of Osteoporotic Fractures.

Osteoporotic fractures are induced by osteoporosis, which may lead to the degradation of bone tissues and microstructures and impair their healing ability. Conventional internal fixation therapies are ineffective in the treatment of osteoporotic fractures. Hence, developing tissue engineering materials is crucial for repairing osteoporotic fractures. It has been demonstrated that nanomaterials, particularly graphene oxide (GO), possess unique advantages in tissue engineering due to their excellent biocompatibility, mechanical properties, and osteoinductive abilities. Based on that, GO-nanocomposites have garnered significant attention and hold promising prospects for bone repair applications. This paper provides a comprehensive insight into the properties of GO, preparation methods for nanocomposites, advantages of these materials, and relevant mechanisms for osteoporotic fracture applications.

A novel mouse model of familial combined hyperlipidemia and atherosclerosis.

Within the context of residual cardiovascular risk in post-statin era, emerging evidence from epidemiologic and human genetic studies have demonstrated that triglyceride (TG)-rich lipoproteins and their remnants are causally related to cardiovascular risk. While, carriers of loss-of-function mutations of ApoC3 have low TG levels and are protected from cardiovascular disease (CVD). Of translational significance, siRNAs/antisense oligonucleotide (ASO) targeting ApoC3 is beneficial for patients with atherosclerotic CVD. Therefore, animal models of atherosclerosis with both hypercholesterolemia and hypertriglyceridemia are important for the discovery of novel therapeutic strategies targeting TG-lowering on top of traditional cholesterol-lowering. In this study, we constructed a novel mouse model of familial combined hyperlipidemia through inserting a human ApoC3 transgene (hApoC3-Tg) into C57BL/6 J mice and injecting a gain-of-function variant of adeno-associated virus-proprotein convertase subtilisin/kexin type 9 (AAV-PCSK9)-D377Y concurrently with high cholesterol diet (HCD) feeding for 16 weeks. In the last 10 weeks, hApoC3-Tg mice were orally treated with a combination of atorvastatin (10 mg·kg-1·d-1) and fenofibrate (100 mg·kg-1·d-1). HCD-treated hApoC3-Tg mice demonstrated elevated levels of serum TG, total cholesterol (TC) and low density lipoprotein-cholesterol (LDL-C). Oral administration of atorvastatin and fenofibrate significantly decreased the plaque sizes of en face aorta, aortic sinus and innominate artery accompanied by improved lipid profile and distribution. In summary, this novel mouse model is of considerable clinical relevance for evaluation of anti-atherosclerotic drugs by targeting both hypercholesterolemia and hypertriglyceridemia.

Score-based Counterfactual Generation for Interpretable Medical Image Classification and Lesion Localization.

Deep neural networks (DNNs) have immense potential for precise clinical decision-making in the field of biomedical imaging. However, accessing high-quality data is crucial for ensuring the high-performance of DNNs. Obtaining medical imaging data is often challenging in terms of both quantity and quality. To address these issues, we propose a score-based counterfactual generation (SCG) framework to create counterfactual images from latent space, to compensate for scarcity and imbalance of data. In addition, some uncertainties in external physical factors may introduce unnatural features and further affect the estimation of the true data distribution. Therefore, we integrated a learnable FuzzyBlock into the classifier of the proposed framework to manage these uncertainties. The proposed SCG framework can be applied to both classification and lesion localization tasks. The experimental results revealed a remarkable performance boost in classification tasks, achieving an average performance enhancement of 3-5% compared to previous state-of-the-art (SOTA) methods in interpretable lesion localization.

A Statistical Physics Perspective: Understanding the Causality Behind Convolutional Neural Network Adversarial Vulnerability.

The adversarial vulnerability of convolutional neural networks (CNNs) refers to the performance degradation of CNNs under adversarial attacks, leading to incorrect decisions. However, the causes of adversarial vulnerability in CNNs remain unknown. To address this issue, we propose a unique cross-scale analytical approach from a statistical physics perspective. It reveals that the huge amount of nonlinear effects inherent in CNNs is the fundamental cause for the formation and evolution of system vulnerability. Vulnerability is spontaneously formed on the macroscopic level after the symmetry of the system is broken through the nonlinear interaction between microscopic state order parameters. We develop a cascade failure algorithm, visualizing how micro perturbations on neurons' activation can cascade and influence macro decision paths. Our empirical results demonstrate the interplay between microlevel activation maps and macrolevel decision-making and provide a statistical physics perspective to understand the causality behind CNN vulnerability. Our work will help subsequent research to improve the adversarial robustness of CNNs.

Combination of stem cells and nerve guide conduit for the treatment of peripheral nerve injury: A meta-analysis.

INTRODUCTION/AIMS: Many small-sized, single-center preclinical studies have investigated the benefits of introducing stem cells into the interior of nerve conduit. The aims of this meta-analysis are to review and contrast the effects of various types of stem cells in in vivo models used to reconstruct peripheral nerve injuries (PNIs) and to assess the reliability and stability of the available evidence. METHODS: A systematic search was conducted using Cochrane Library, Embase, PubMed, and Web of Science to identify studies conducted from January 1, 2000, to September 21, 2022, and investigate stem cell therapy in peripheral nerve reconstruction animal models. Studies that met the relevant criteria were deemed eligible for this meta-analysis. RESULTS: Fifty-five preclinical studies with a total of 1234 animals were incorporated. Stem cells demonstrated a positive impact on peripheral nerve regeneration at different follow-up times in the forest plots of five outcome indicators: compound muscle action potential (CMAP) amplitude, latency, muscle mass ratio, nerve conduction velocity, and sciatic functional index (SFI). In most comparisons, stem cell groups showed substantial differences compared with the control groups. The superior performance of adipose-derived stem cells (ADSCs) in terms of SFI, CMAP amplitude, and latency (p < .001) was identified. DISCUSSION: The findings consistently demonstrated a favorable outcome in the reconstruction process when utilizing different groups of stem cells, as opposed to control groups where stem cells were not employed.

Explanatory Object Part Aggregation for Zero-Shot Learning.

Zero-shot learning (ZSL) aims to recognize objects from unseen classes only based on labeled images from seen classes. Most existing ZSL methods focus on optimizing feature spaces or generating visual features of unseen classes, both in conventional ZSL and generalized zero-shot learning (GZSL). However, since the learned feature spaces are suboptimal, there exists many virtual connections where visual features and semantic attributes are not corresponding to each other. To reduce virtual connections, in this paper, we propose to discover comprehensive and fine-grained object parts by building explanatory graphs based on convolutional feature maps, then aggregate object parts to train a part-net to obtain prediction results. Since the aggregated object parts contain comprehensive visual features for activating semantic attributes, the virtual connections can be reduced by a large extent. Since part-net aims to extract local fine-grained visual features, some attributes related to global structures are ignored. To take advantage of both local and global visual features, we design a feature distiller to distill local features into a master-net which aims to extract global features. The experimental results on AWA2, CUB, FLO, and SUN dataset demonstrate that our proposed method obviously outperforms the state-of-the-arts in both conventional ZSL and GZSL tasks.

Sporopollenin exine capsules modulate the function of microglial cells.

Immune cells are the housekeepers of the human body. They protect the body from pathogens, cellular damage, and foreign matter. Proper activation of immune cells is of great significance to diseases such as infection, inflammation, and neurodegeneration. However, excessive activation of cells can be detrimental. An ideal biomaterial could enhance the cellular immune function without proinflammation. In this work, we used sporopollenin exine capsules (SEC) from pollen to promote functions of primary microglia, a typical resident immune cell of the brain. We found that microglia aggregated around SEC and did not undergo any proinflammation. SEC improved the viability, migration, phagocytosis, and anti-inflammatory ability of microglia. By exploring the underlying mechanism of microglial activation without the production of cytotoxic pro-inflammatory cytokines, we found that SEC protects microglia against inflammation induced by lipopolysaccharide (LPS), an immunostimulatory factor, through the toll-like receptor 4 (TLR4) signaling pathway in a myeloid differentiation factor 88-dependent manner. These findings might shed light on the potential application of SEC in microglia transplantation for treatment of microglia-associated degenerative central nervous system diseases.

Synthesis of Low-Cost and High-Performance Dual-Atom Doped Carbon-Based Materials with a Simple Green Route as Anodes for Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) are promising alternatives to replace lithium-ion batteries as future energy storage batteries because of their abundant sodium resources, low cost, and high charging efficiency. In order to match the high energy capacity and density, designing an atomically doped carbonous material as the anode is presently one of the important strategies to commercialize SIBs. In this work, we report the preparation of high-performance dual-atom-doped carbon (C) materials using low-cost corn starch and thiourea (CH4N2S) as the precursors. The electronegativity and radii of the doped atoms and C are different, which can vary the embedding properties of sodium ions (Na+) into/on C. As sulfur (S) can effectively expand the layer spacing, it provides more channels for embedding and de-embedding Na+. The synergistic effect of N and S co-doping can remarkably boost the performance of SIBs. The capacity is preserved at 400 mAh g -1 after 200 cycles at 500 mA g-1; more notably, the initial Coulombic efficiency is 81%. Even at a high rate of high current of 10 A g-1, the cell capacity can still reach 170 mAh g-1. More importantly, after 3000 cycles at 1 A g-1, the capacity decay is less than 0.003% per cycle, which demonstrates its excellent electrochemical performance. These results indicate that high-performance carbon materials can be prepared using low-cost corn starch and thiourea.

Design, Synthesis, Insecticidal Activity, and SAR of Aryl Isoxazoline Derivatives Containing Pyrazole-5-carboxamide Motif.

It is important to develop new insecticides with a new mode of action because of increasing pesticide resistance. In this study, a series of novel aryl isoxazoline derivatives containing the pyrazole-5-carboxamide motif were designed and synthesized. Their structures were confirmed by 1H NMR, 13C NMR, and HRMS. Bioassays indicated that the 24 compounds synthesized possessed excellent insecticidal activity against Mythimna separate and no activity against Aphis craccivora and Tetranychus cinnabarinus. Among these aryl isoxazoline derivatives, 3-(5-(3,5-dichlorophenyl)-5-(trifluoromethyl)-4,5-dihydrozol-3-yl)-N-(4-fluorophenyl)-1-methyl-1H-pyrazole-5-carboxamide (IA-8) had the best insecticidal activity against M. separate, which is comparable with the positive control fluralaner. The molecular docking results of compound IA-8 and fluralaner with the GABA model demonstrated the same docking mode between compound IA-8 and positive control fluralaner in the active site of GABA. Molecular structure comparisons and ADMET analysis can potentially be used to design more active compounds. The structure-activity relationships are also discussed. This work provided an excellent insecticide for further optimization.

Osteoarthritis: Role of Peroxisome Proliferator-Activated Receptors.

Osteoarthritis (OA) represents the foremost degenerative joint disease observed in a clinical context. The escalating issue of population aging significantly exacerbates the prevalence of OA, thereby imposing an immense annual economic burden on societies worldwide. The current therapeutic landscape falls short in offering reliable pharmaceutical interventions and efficient treatment methodologies to tackle this growing problem. However, the scientific community continues to dedicate significant efforts towards advancing OA treatment research. Contemporary studies have discovered that the progression of OA may be slowed through the strategic influence on peroxisome proliferator-activated receptors (PPARs). PPARs are ligand-activated receptors within the nuclear hormone receptor family. The three distinctive subtypes-PPARα, PPARß/δ, and PPARγ-find expression across a broad range of cellular terminals, thus managing a multitude of intracellular metabolic operations. The activation of PPARγ and PPARα has been shown to efficaciously modulate the NF-κB signaling pathway, AP-1, and other oxidative stress-responsive signaling conduits, leading to the inhibition of inflammatory responses. Furthermore, the activation of PPARγ and PPARα may confer protection to chondrocytes by exerting control over its autophagic behavior. In summation, both PPARγ and PPARα have emerged as promising potential targets for the development of effective OA treatments.

Secure Outsourced SIFT: Accurate and Efficient Privacy-Preserving Image SIFT Feature Extraction.

Cloud computing has become an important IT infrastructure in the big data era; more and more users are motivated to outsource the storage and computation tasks to the cloud server for convenient services. However, privacy has become the biggest concern, and tasks are expected to be processed in a privacy-preserving manner. This paper proposes a secure SIFT feature extraction scheme with better integrity, accuracy and efficiency than the existing methods. SIFT includes lots of complex steps, including the construction of DoG scale space, extremum detection, extremum location adjustment, rejecting of extremum point with low contrast, eliminating of the edge response, orientation assignment, and descriptor generation. These complex steps need to be disassembled into elementary operations such as addition, multiplication, comparison for secure implementation. We adopt a serial of secret-sharing protocols for better accuracy and efficiency. In addition, we design a secure absolute value comparison protocol to support absolute value comparison operations in the secure SIFT feature extraction. The SIFT feature extraction steps are completely implemented in the ciphertext domain. And the communications between the clouds are appropriately packed to reduce the communication rounds. We carefully analyzed the accuracy and efficiency of our scheme. The experimental results show that our scheme outperforms the existing state-of-the-art.

Crosstalk between ferroptosis and chondrocytes in osteoarthritis: a systematic review of in vivo and in vitro studies.

Purpose: Recent scientific reports have revealed a close association between ferroptosis and the occurrence and development of osteoarthritis (OA). Nevertheless, the precise mechanisms by which ferroptosis influences OA and how to hobble OA progression by inhibiting chondrocyte ferroptosis have not yet been fully elucidated. This study aims to conduct a comprehensive systematic review (SR) to address these gaps. Methods: Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, we conducted a comprehensive search of the Embase, Ovid, ProQuest, PubMed, Scopus, the Cochrane Library, and Web of Science databases to identify relevant studies that investigate the association between ferroptosis and chondrocytes in OA. Our search included studies published from the inception of these databases until January 31st, 2023. Only studies that met the predetermined quality criteria were included in this SR. Results: In this comprehensive SR, a total of 21 studies that met the specified criteria were considered suitable and included in the current updated synthesis. The mechanisms underlying chondrocyte ferroptosis and its association with OA progression involve various biological phenomena, including mitochondrial dysfunction, dysregulated iron metabolism, oxidative stress, and crucial signaling pathways. Conclusion: Ferroptosis in chondrocytes has opened an entirely new chapter for the investigation of OA, and targeted regulation of it is springing up as an attractive and promising therapeutic tactic for OA. Systematic review registration: https://inplasy.com/inplasy-2023-3-0044/, identifier INPLASY202330044.

Tibial plateau fracture and RNA sequencing with osteogenesis imperfecta: a case report.

Osteogenesis imperfecta (OI) is a hereditary skeletal dysplasia with an incidence of approximately 1:15,000 to 20,000. OI is usually caused by the mutation of COL1A1 and COL1A2, which would encode the α-chain of type I collagen. OI is clinically characterized by decreased bone mass, increased risk of bone fragility, blue sclerae, and dentinogenesis. Case presentation: A 29-year-old male patient was diagnosed with right tibial plateau fracture caused by slight violence. Physical examination revealed the following: height, 140 cm; weight, 70 kg; body mass index (BMI), 35.71 kg/m2; blue sclera and barrel chest were observed. X-ray examination showed left convex deformity of the thoracic vertebrae with reduced thoracic volume. Laboratory examinations revealed a decrease in both vitamin D and blood calcium levels. Bone mineral density (BMD) was lower than the normal range. After the preoperative preparation was completed, the open reduction and internal fixation of the right tibial plateau fracture were performed. Meanwhile, whole blood samples of this OI patient and the normal control were collected for RNA transcriptome sequencing. The RNA sequence analysis revealed that there were 513 differentially expressed genes (DEGs) between this OI patient and the normal control. KEGG-enriched signaling pathways were significantly enriched in extracellular matrix (ECM)-receptor interactions. Conclusion: In this case, DEGs between this OI patient and the normal control were identified by RNA transcriptome sequencing. Moreover, the possible pathogenesis of OI was also explored, which may provide new evidence for the treatment of OI.