Nighttime Image Stitching Method Based on Image Decomposition Enhancement.

Image stitching technology realizes alignment and fusion of a series of images with common pixel areas taken from different viewpoints of the same scene to produce a wide field of view panoramic image with natural structure. The night environment is one of the important scenes of human life, and the night image stitching technology has more urgent practical significance in the fields of security monitoring and intelligent driving at night. Due to the influence of artificial light sources at night, the brightness of the image is unevenly distributed and there are a large number of dark light areas, but often these dark light areas have rich structural information. The structural features hidden in the darkness are difficult to extract, resulting in ghosting and misalignment when stitching, which makes it difficult to meet the practical application requirements. Therefore, a nighttime image stitching method based on image decomposition enhancement is proposed to address the problem of insufficient line feature extraction in the stitching process of nighttime images. The proposed algorithm performs luminance enhancement on the structural layer, smoothes the nighttime image noise using a denoising algorithm on the texture layer, and finally complements the texture of the fused image by an edge enhancement algorithm. The experimental results show that the proposed algorithm improves the image quality in terms of information entropy, contrast, and noise suppression compared with other algorithms. Moreover, the proposed algorithm extracts the most line features from the processed nighttime images, which is more helpful for the stitching of nighttime images.

Peel learning for pathway-related outcome prediction.

MOTIVATION: Traditional regression models are limited in outcome prediction due to their parametric nature. Current deep learning methods allow for various effects and interactions and have shown improved performance, but they typically need to be trained on a large amount of data to obtain reliable results. Gene expression studies often have small sample sizes but high dimensional correlated predictors so that traditional deep learning methods are not readily applicable. RESULTS: In this article, we proposed peel learning, a novel neural network that incorporates the prior relationship among genes. In each layer of learning, overall structure is peeled into multiple local substructures. Within the substructure, dependency among variables is reduced through linear projections. The overall structure is gradually simplified over layers and weight parameters are optimized through a revised backpropagation. We applied PL to a small lung transplantation study to predict recipients' post-surgery primary graft dysfunction using donors' gene expressions within several immunology pathways, where PL showed improved prediction accuracy compared to conventional penalized regression, classification trees, feed-forward neural network and a neural network assuming prior network structure. Through simulation studies, we also demonstrated the advantage of adding specific structure among predictor variables in neural network, over no or uniform group structure, which is more favorable in smaller studies. The empirical evidence is consistent with our theoretical proof of improved upper bound of PL's complexity over ordinary neural networks. AVAILABILITY AND IMPLEMENTATION: PL algorithm was implemented in Python and the open-source code and instruction will be available at https://github.com/Likelyt/Peel-Learning. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Flexible and stretchable polymer optical fibers for chronic brain and vagus nerve optogenetic stimulations in free-behaving animals.

BACKGROUND: Although electrical stimulation of the peripheral and central nervous systems has attracted much attention owing to its potential therapeutic effects on neuropsychiatric diseases, its non-cell-type-specific activation characteristics may hinder its wide clinical application. Unlike electrical methodologies, optogenetics has more recently been applied as a cell-specific approach for precise modulation of neural functions in vivo, for instance on the vagus nerve. The commonly used implantable optical waveguides are silica optical fibers, which for brain optogenetic stimulation (BOS) are usually fixed on the skull bone. However, due to the huge mismatch of mechanical properties between the stiff optical implants and deformable vagal tissues, vagus nerve optogenetic stimulation (VNOS) in free-behaving animals continues to be a great challenge. RESULTS: To resolve this issue, we developed a simplified method for the fabrication of flexible and stretchable polymer optical fibers (POFs), which show significantly improved characteristics for in vivo optogenetic applications, specifically a low Young's modulus, high stretchability, improved biocompatibility, and long-term stability. We implanted the POFs into the primary motor cortex of C57 mice after the expression of CaMKIIα-ChR2-mCherry detected frequency-dependent neuronal activity and the behavioral changes during light delivery. The viability of POFs as implantable waveguides for VNOS was verified by the increased firing rate of the fast-spiking GABAergic interneurons recorded in the left vagus nerve of VGAT-ChR2 transgenic mice. Furthermore, VNOS was carried out in free-moving rodents via chronically implanted POFs, and an inhibitory influence on the cardiac system and an anxiolytic effect on behaviors was shown. CONCLUSION: Our results demonstrate the feasibility and advantages of the use of POFs in chronic optogenetic modulations in both of the central and peripheral nervous systems, providing new information for the development of novel therapeutic strategies for the treatment of neuropsychiatric disorders.

Nighttime Image Stitching Method Based on Guided Filtering Enhancement.

Image stitching refers to stitching two or more images with overlapping areas through feature points matching to generate a panoramic image, which plays an important role in geological survey, military reconnaissance, and other fields. At present, the existing image stitching technologies mostly adopt images with good lighting conditions, but the lack of feature points in scenes with weak light such as morning or night will affect the image stitching effect, making it difficult to meet the needs of practical applications. When there exist concentrated areas of brightness such as lights and large dark areas in the nighttime image, it will further cause the loss of image details making the feature point matching unavailable. The obtained perspective transformation matrix cannot reflect the mapping relationship of the entire image, resulting in poor splicing effect, and it is difficult to meet the actual application requirements. Therefore, an adaptive image enhancement algorithm is proposed based on guided filtering to preprocess the nighttime image, and use the enhanced image for feature registration. The experimental results show that the image obtained by preprocessing the nighttime image with the proposed enhancement algorithm has better detail performance and color restoration, and greatly improves the image quality. By performing feature registration on the enhanced image, the number of matching logarithms of the image increases, so as to achieve high accuracy for images stitching.

Development and characterization of a mucoadhesive sublingual formulation for pain control: extemporaneous oxycodone films in personalized therapy.

OBJECTIVE: The aim of this work was the development of mucoadhesive sublingual films, prepared using a casting method, for the administration of oxycodone. MATERIALS AND METHODS: A solvent casting method was employed to prepare the mucoadhesive films. A calibrated pipette was used to deposit single aliquots of different polymeric solutions on a polystyrene plate lid. Among the various tested polymers, hydroxypropylcellulose at low and medium molecular weight (HPC) and pectin at two different degrees of esterification (PC) were chosen for preparing solutions with good casting properties, capable of producing films suitable for mucosal application. RESULTS AND DISCUSSION: The obtained films showed excellent drug content uniformity and stability and rapid drug release, which, at 8 min, ranged from 60% to 80%. All films presented satisfactory mucoadhesive and mechanical properties, also confirmed by a test on healthy volunteers, who did not experience irritation or mucosa damages. Pectin films based on pectin at lower degrees of esterification have been further evaluated to study the influence of two different amounts of drug on the physicochemical properties of the formulation. A slight reduction in elasticity has been observed in films containing a higher drug dose; nevertheless, the formulation maintained satisfactory flexibility and resistance to elongation. CONCLUSIONS: HPC and PC sublingual films, obtained by a simple casting method, could be proposed to realize personalized hospital pharmacy preparations on a small scale.

Poly(3,4-Ethylenedioxythiophene)/Functional Gold Nanoparticle films for Improving the Electrode-Neural Interface.

Implantable neural electrodes are indispensable tools for recording neuron activity, playing a crucial role in neuroscience research. However, traditional neural electrodes suffer from limited electrochemical performance, compromised biocompatibility, and tentative stability, posing great challenges for reliable long-term studies in free-moving animals. In this study, a novel approach employing a hybrid film composed of poly(3,4-ethylenedioxythiophene)/functional gold nanoparticles (PEDOT/3-MPA-Au) to improve the electrode-neural interface is presented. The deposited PEDOT/3-MPA-Au demonstrates superior cathodal charge storage capacity, reduced electrochemical impedance, and remarkable electrochemical and mechanical stability. Upon implantation into the cortex of mice for a duration of 12 weeks, the modified electrodes exhibit notably decreased levels of glial fibrillary acidic protein and increased neuronal nuclei immunostaining compared to counterparts utilizing poly(3,4-ethylenedioxythiophene)/poly(styrene sulfonate). Additionally, the PEDOT/3-MPA-Au modified electrodes consistently capture high-quality, stable long-term electrophysiological signals in vivo, enabling continuous recording of target neurons for up to 16 weeks. This innovative modification strategy offers a promising solution for fabricating low-impedance, tissue-friendly, and long-term stable neural interfaces, thereby addressing the shortcomings of conventional neural electrodes. These findings mark a significant advancement toward the development of more reliable and efficacious neural interfaces, with broad implications for both research and clinical applications.

Bioelectrocatalytic reduction by integrating pyrite assisted manganese cobalt-doped carbon nanofiber anode and bacteria for sustainable antimony catalytic removal.

A novel manganese cobalt metal-organic framework based carbon nanofiber electrode (MnCo/CNF) was prepared and used as microbial fuel cell (MFC) anode. Pyrite was introduced into the anode chamber (MnCoPy_MFC). Synergistic function between pyrite and MnCo/CNF facilitated the pollutants removal and energy generation in MnCoPy_MFC. MnCoPy_MFC showed the highest chemical oxygen demand removal efficiency (82 ± 1%) and the highest coulombic efficiency (35 ± 1%). MnCoPy_MFC achieved both efficient electricity generation (maximum voltage: 658 mV; maximum power density: 3.2 W/m3) and total antimony (Sb) removal efficiency (99%). The application of MnCo/CNF significantly enhanced the biocatalytic efficiency of MnCoPy_MFC, attributed to its large surface area and abundant porous structure that provided ample attachment sites for electroactive microorganisms. This study revealed the synergistic interaction between pyrite and MnCo/CNF anode, which provided a new strategy for the application of composite anode MFC in heavy metal removal and energy recovery.

Three-dimensional highly porous hydrogel scaffold for neural circuit dissection and modulation.

Biomimetic brain structures and artificial neural networks have provided a simplified strategy for quantitatively investigating the complex structural and functional characteristics of highly interconnected neural networks. To achieve this, three-dimensional (3D) cell culture approaches have attracted much attention, which can mimic cell-cell interactions at the organism level and help better understand the function of specific neurons and neuronal networks than traditional two-dimensional cell culture methods. However, 3D scaffolds similar to the natural extracellular matrix to support the culturing, recording, and manipulation of neurons have long been an unresolved challenge. To resolve this, 3D hydrogel scaffolds can be fabricated via an innovative thermal treatment followed by an esterification process. A highly porous microstructure was formed within the bulk hydrogel scaffold, which showed a high porosity of 91% and a low Young's modulus of 6.11 kPa. Due to the merits of the fabricated hydrogel scaffolds, we constructed 3D neural networks and detected spontaneous action potentials in vitro. We successfully induced seizure-like waveforms in 3D cultured neurons and suppressed hyperactivated discharges by selectively activating γ-aminobutyric acid-ergic (GABAergic) interneurons. These results prove the advantages of our hydrogel scaffolds and demonstrate their application potential in the accurate dissection of neural circuits, which may help develop effective treatments for various neurological disorders. STATEMENT OF SIGNIFICANCE: While 3D cell culture approaches have attracted much attention and offer more advantages than two-dimensional cell culture methods, 3D scaffolds similar to the natural extracellular matrix to support the culturing, recording, and manipulation of neurons have long been an unresolved challenge. Herein, we developed a simplified and low-cost strategy for fabricating highly porous and cytocompatible hydrogel scaffolds for the construction of three-dimensional (3D) neural networks in vitro. The cultured 3D neural networks can mimic the in vivo connection among different neuron subgroups and help accurately dissect and manipulate the structure and function of specific neural circuits.

Waste lignin-based cationic flocculants treating dyeing wastewater: Fabrication, performance, and mechanism.

Lignin is often considered to be a complex polymeric structural material with excellent scalability. Reduced pressure distillation, a novel effective way, was proposed to recover reusable waste lignin from textile degumming black liquor. The structure of the recovered material was determined by Fourier Transform Infrared Spectroscopy (FT-IR), Gel Permeation Chromatography (GPC) and Klason Component Analysis. Recycled lignin (RL) was used as the basis for the synthesis of a cationic recycled lignin-based polymers (CRLM) through graft polymerizing cationic monomer (DMC). The optimum synthesis conditions were obtained by conducting orthogonal experiments using the cationicity as the studied parameter, while selecting pH, DMC/RL, reaction temperature and time as independent variables. Recovery experiments showed that the maximum recovery concentration of RL in the black liquor was 5 g/L, with a purity of approximately 83 %. Orthogonal experiments showed that a low DMC/RL ratio was crucial for the synthesis of flocculants. When the molar ratio of DMC/RL was 3:1, the cationicity of the prepared CRLM was as high as 11.32 %. Zeta potential and decolorization experiments also confirmed the stable decolorization performance of CRLM in three kinds of anionic dye wastewater. The experimental results showed that charge neutralization, chemical bonding forces and auxiliary effects play great role to remove anionic dyes, resulting in 94 %, 89 % and 94.9 % removal against Reactive Red 195 (RR195), Acid Red 18 (AR18) and Direct 168 (DB168) respectively. Therefore, this study demonstrated the potential of using recycled waste lignin as synthesize lignin-based flocculants in the field of printing and dyeing wastewater by treating waste with waste.

Conducting Polymer-Hydrogel Interpenetrating Networks for Improving the Electrode-Neural Interface.

Implantable neural microelectrodes are recognized as a bridge for information exchange between inner organisms and outer devices. Combined with novel modulation technologies such as optogenetics, it offers a highly precise methodology for the dissection of brain functions. However, achieving chronically effective and stable microelectrodes to explore the electrophysiological characteristics of specific neurons in free-behaving animals continually poses great challenges. To resolve this, poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)/poly(vinyl alcohol) (PEDOT/PSS/PVA) interpenetrating conducting polymer networks (ICPN) are fabricated via a hydrogel scaffold precoating and electrochemical polymerization process to improve the performance of neural microelectrodes. The ICPN films exhibit robust interfacial adhesion, a significantly lower electrochemical impedance, superior mechanical properties, and improved electrochemical stability compared to the pure poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)(PEDOT/PSS) films, which may be attributed to the three-dimensional (3D) porous microstructure of the ICPN. Hippocampal neurons and rat pheochromocytoma cells (PC12 cells) adhesion on ICPN and neurite outgrowth are observed, indicating enhanced biocompatibility. Furthermore, alleviated tissue response at the electrode-neural tissue interface and improved recording signal quality are confirmed by histological and electrophysiological studies, respectively. Owing to these merits, optogenetic modulations and electrophysiological recordings are performed in vivo, and an anxiolytic effect of hippocampal glutamatergic neurons on behavior is shown. This study demonstrates the effectiveness and advantages of ICPN-modified neural implants for in vivo applications.

Iron cobalt-doped carbon nanofibers anode to simultaneously boost bioelectrocatalysis and direct electron transfer in microbial fuel cells: Characterization, performance, and mechanism.

A self-supporting electrode (FeCo-MOF/CNFs) combining iron cobalt bimetallic metal-organic frameworks (FeCo-MOFs) with carbon nanofibers (CNFs) was applied as the anode of a microbial fuel cell (MFC). The introduction of FeCo-MOFs enhanced graphitization degree and electrical conductivity, which endowed FeCo-MOF/CNFs with excellent electrocatalytic performance and good biocompatibility. The hierarchical porous structure of FeCo-MOF/CNFs provided abundant attachment sites for electroactive bacteria (EAB) and facilitated rapid electron transfer. The MFC equipped with FeCo-MOF/CNFs anode (FeCo/CNFs-MFC) exhibited considerable power generation output (maximum power density: 5.3 ± 0.2 W/m2, coulombic efficiency: 54 ± 4 %). In addition, FeCo/CNFs-MFC achieved a direct electron transfer (DET) catalytic current density of 0.63 A/m2. FeCo-MOF/CNFs could simultaneously enhance the bioelectrocatalysis activity and promote the DET process of EAB, which provided an effective way to improve the sluggish extracellular electron transport process of the MFC anode.

Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review.

In August 2022 the Department of Health and Human Services (HHS) issued a notice of proposed rulemaking prohibiting covered entities, which include health care providers and health plans, from discriminating against individuals when using clinical algorithms in decision making. However, HHS did not provide specific guidelines on how covered entities should prevent discrimination. We conducted a scoping review of literature published during the period 2011-22 to identify health care applications, frameworks, reviews and perspectives, and assessment tools that identify and mitigate bias in clinical algorithms, with a specific focus on racial and ethnic bias. Our scoping review encompassed 109 articles comprising 45 empirical health care applications that included tools tested in health care settings, 16 frameworks, and 48 reviews and perspectives. We identified a wide range of technical, operational, and systemwide bias mitigation strategies for clinical algorithms, but there was no consensus in the literature on a single best practice that covered entities could employ to meet the HHS requirements. Future research should identify optimal bias mitigation methods for various scenarios, depending on factors such as patient population, clinical setting, algorithm design, and types of bias to be addressed.

Observability and its impact on differential bias for clinical prediction models.

OBJECTIVE: Electronic health records have incomplete capture of patient outcomes. We consider the case when observability is differential across a predictor. Including such a predictor (sensitive variable) can lead to algorithmic bias, potentially exacerbating health inequities. MATERIALS AND METHODS: We define bias for a clinical prediction model (CPM) as the difference between the true and estimated risk, and differential bias as bias that differs across a sensitive variable. We illustrate the genesis of differential bias via a 2-stage process, where conditional on having the outcome of interest, the outcome is differentially observed. We use simulations and a real-data example to demonstrate the possible impact of including a sensitive variable in a CPM. RESULTS: If there is differential observability based on a sensitive variable, including it in a CPM can induce differential bias. However, if the sensitive variable impacts the outcome but not observability, it is better to include it. When a sensitive variable impacts both observability and the outcome no simple recommendation can be provided. We show that one cannot use observed data to detect differential bias. DISCUSSION: Our study furthers the literature on observability, showing that differential observability can lead to algorithmic bias. This highlights the importance of considering whether to include sensitive variables in CPMs. CONCLUSION: Including a sensitive variable in a CPM depends on whether it truly affects the outcome or just the observability of the outcome. Since this cannot be distinguished with observed data, observability is an implicit assumption of CPMs.

Research progress in external field intensification of forward osmosis process for water treatment: A critical review.

Forward osmosis (FO) is an emerging permeation-driven membrane technology that manifests advantages of low energy consumption, low operating pressure, and uncomplicated engineering compared to conventional membrane processes. The key issues that need to be addressed in FO are membrane fouling, concentration polarization (CP) and reverse solute diffusion (RSD). They can lead to problems about loss of draw solutes and reduced membrane lifetime, which not only affect the water treatment effectiveness of FO membranes, but also increase the economic cost. Current research has focused on FO membrane preparation and modification strategies, as well as on the selection of draw solutions. Unfortunately, these intrinsic solutions had limited success in unraveling these phenomena. In this paper, we provide a brief review of the current state of research on existing external field-assisted FO systems (including electric-, pressure-, magnetic-, ultrasonic-, light- and flow-assisted FO system), analyze their mitigation mechanisms for the above key problems, and explore potential research directions to aid in the further development of FO systems. This review aims to reveal the feasibility of the development of external field-assisted FO technology to achieve a more economical and efficient FO treatment process.

Robotic Roux en Y gastric bypass can be safe and cost-effective in a rural setting: clinical outcomes from a community hospital bariatric program.

Robotic Roux en Y gastric bypass (R-RYGB) is becoming more common due to the shifting trend toward robotic gastrointestinal surgery. The goal of this study is to determine if R-RYGB can be safely implemented at a robotic bariatric surgery program in a community hospital with similar results to laparoscopic RYGB (L-RYGB) in a cost-effective manner. A total of 50 R-RYGB procedures were performed with the Xi and the X da Vinci systems and compared with 50 L-RYGB cases by a single surgeon from October 2018 to January 2020 at an acute-care community hospital in a rural setting with a high-volume MBSAQIP-accredited program. A retrospective chart review was conducted with IRB approval and statistical analysis of 30-day morbidity, mortality, re-interventions, and resolution of co-morbidities, with financial analysis of cost reduction. Both groups were similar in age, gender, ASA class, co-morbidities, and body mass index (BMI). There was no mortality or anastomotic leak. The 30-day morbidity for R-RYGB was 10.0% with a re-operation rate of 4.0%. There were no conversions to open, and the mean hospital length of stay was 2.22 ± 1.19 days. There were no statistically significant differences between R-RYGB and L-RYGB with respect to any measured outcome, including intraoperative time (121.94 vs. 113.52, respectively; p = 0.1495). However, when incidences and percentages were used, R-RYGB had improved performance for most of the outcomes measuring safety. There was an average cost reduction of $816.90 per case (total saving of $40,845.00 for 50 cases) in the R-RYGB by transitioning from a hybrid approach to a totally robotic approach. R-RYGB appears to be as safe as L-RYGB and can be performed in a rural community hospital while maintaining a low complication rate, achieving a high co-morbidity resolution rate, and saving costs with a totally robotic approach.

Dexmedetomidine alleviates LPS-induced apoptosis and inflammation in macrophages by eliminating damaged mitochondria via PINK1 mediated mitophagy.

The macrophage is an innate immune response cell that plays an important role in the development of sepsis. Dexmedetomidine (DEX) is a sedation drug, which have anti-oxidative, anti-inflammatory and anti-apoptosis effects and can be used on sepsis patients in the ICU. However, its mechanisms of action remain poorly understood. PTEN-induced putative kinase 1 (PINK1) is a mitochondrial serine/threonine protein kinase that recognizes damaged mitochondria and leads to mitophagy. This study investigated the effects of DEX on Lipopolysaccharides(LPS)-induced macrophage injury and explained the underlying mechanisms. The results showed that LPS treatment caused mitochondrial damage, mitochondria-dependent apoptosis and PINK1-mediated mitophagy; at the same time, PINK1 has a protective effect on LPS-induced macrophage apoptosis and inflammation by mitophagy that eliminates dysfunctional mitochondria. DEX could promote the clearance of damaged mitochondria characterized by low Mitochondrial membrane potential (MMP) and high reactive oxygen species(ROS), thus exerting a protective effect in LPS treated macrophages, and PINK1 mediated mitophagy is required for this protective effect.

Hydrogen gas inhalation attenuates sepsis-induced liver injury in a FUNDC1-dependent manner.

Sepsis-induced hepatic dysfunction is considered as an independent risk factor of multiple organ dysfunction syndrome (MODS) and death. Mitophagy, a selective form of autophagy, plays a major role in sepsis-induced organ damage. We have demonstrated that hydrogen gas (H2), a selective antioxidant, exerts protective effects in septic mice. Here, we hypothesize that the therapeutic effects of H2 on septic animals with liver damages may be exerted through regulation of the Fun14 domain-containing protein 1 (FUDNC1)-induced mitophagy pathway. Male C57BL/6J mice were subjected to sham or cecal ligation and puncture (CLP) operation and treated with 2% H2 gas inhalation for 3 h starting at 1 h after sham or CLP surgery. To verify the role of FUNDC1, the cell-penetrating peptide P (NH2-GRKKRRQRRRPQDYESDDESYEVLDLTEY-COOH) (1 mg/kg) that functions as a FUNDC1 inhibitor was intraperitoneally injected into mice 24 h before the sham or CLP operation. To evaluate the severity of septic liver injury, the 7-day survival rate, liver histopathologic score, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, respiration control ratio (RCR), and FUDNC1, P-18-FUDNC1, P62, LC3B-II, Tim23, and caspase-1 levels were evaluated after the sham or CLP operation. The results demonstrated that 2% H2 gas inhalation resulted in an increase in the 7-day survival rate, ALT and AST levels, RCR, and P62 and LC3B-II expression but decreased the histological score and FUDNC1, P-18-FUDNC1, Tim23, and caspase-1 levels after sepsis. However, no significant differences were reported between the CLP + peptide P and CLP + H2 + peptide P groups. These observations indicate that 2% H2 gas inhalation for 3 h may serve as an effective therapeutic strategy for sepsis-induced liver injury through the regulation of FUNDC1-dependent mitophagy.

The controlled naringin release from TiO2 nanotubes to regulate osteoblast differentiation.

To design titanium (Ti)-based biomaterials with controlled drug-releasing bioactive property, TiO2 nanotubes with a diameter of approximately 110 nm was fabricated by electrochemical anodization. TiO2 nanotubes were then loaded with naringin by direct dropping and coated with chitosan layers. The surface morphologies, chemical compositions and wettability of different substrates were characterized by field emission scanning electron microscopy, atomic force microscope, X-ray photoelectron spectroscopy and contact angle measurement, respectively. The in vitro release behavior of naringin was evaluated by UV-visible-spectrophotometer. The biological properties of osteoblasts on different substrates were investigated in vitro. Our results indicate that the chitosan-coated naringin-loaded TiO2 nanotubes enhanced osteoblast spreading, proliferation, alkaline phosphatase activity and late-stage osteoblast mineralization. This study provides a platform to help enhance osteointegration between the bone and implant surface in clinical applications.