A Hybrid EEG-Based Stress State Classification Model Using Multi-Domain Transfer Entropy and PCANet.

This paper proposes a new hybrid model for classifying stress states using EEG signals, combining multi-domain transfer entropy (TrEn) with a two-dimensional PCANet (2D-PCANet) approach. The aim is to create an automated system for identifying stress levels, which is crucial for early intervention and mental health management. A major challenge in this field lies in extracting meaningful emotional information from the complex patterns observed in EEG. Our model addresses this by initially applying independent component analysis (ICA) to purify the EEG signals, enhancing the clarity for further analysis. We then leverage the adaptability of the fractional Fourier transform (FrFT) to represent the EEG data in time, frequency, and time-frequency domains. This multi-domain representation allows for a more nuanced understanding of the brain's activity in response to stress. The subsequent stage involves the deployment of a two-layer 2D-PCANet network designed to autonomously distill EEG features associated with stress. These features are then classified by a support vector machine (SVM) to determine the stress state. Moreover, stress induction and data acquisition experiments are designed. We employed two distinct tasks known to trigger stress responses. Other stress-inducing elements that enhance the stress response were included in the experimental design, such as time limits and performance feedback. The EEG data collected from 15 participants were retained. The proposed algorithm achieves an average accuracy of over 92% on this self-collected dataset, enabling stress state detection under different task-induced conditions.

Design of an endoscopic OCT probe based on piezoelectric tube with quartered outside electrodes.

Introduction: Optical coherence tomography (OCT) is a pivotal imaging modality in ophthalmology for real-time, in vivo visualization of retinal structures. To enhance the capability and safety of OCT, this study focuses on the development of a micro intraocular OCT probe. The demand for minimal invasiveness and precise imaging drives the need for advanced probe designs that can access tight and sensitive areas, such as the ocular sclera. Methods: A novel OCT probe was engineered using a piezoelectric tube with quartered electrodes to drive Lissajous scanning movements at the end of a single-mode fiber. This design allows the probe to enter the eyeball through a scleral opening. Structural innovation enables the outer diameter of the endoscopic OCT probe to be adjusted from 13G (2.41 mm) to 25G (0.51 mm), accommodating various imaging field sizes and ensuring compatibility with different scleral incisions. Results: The fabricated micro intraocular OCT probe successfully performed preliminary imaging experiments on in vivo fingers. The Lissajous scanning facilitated comprehensive coverage of the target area, enhancing the imaging capabilities. Discussion: The integration of a piezoelectric tube with quartered outside electrodes into the OCT probe design proved effective for achieving precise control over scanning movements and adaptability to different surgical needs. The design characteristics and practical applications demonstrated the probe's potential in clinical settings.

Interferometric modulation for generating extended light sheet: improving field of view.

Significance: Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful and versatile imaging technique renowned for its remarkable features, including high-speed 3D tomography, minimal photobleaching, and low phototoxicity. The interference light-sheet fluorescence microscope, with its larger field of view (FOV) and more uniform axial resolution, possesses significant potential for a wide range of applications in biology and medicine. Aim: The aim of this study is to investigate the interference behavior among multiple light sheets (LSs) in LSFM and optimize the FOV and resolution of the light-sheet fluorescence microscope. Approach: We conducted a detailed investigation of the interference effects among LSs through theoretical derivation and numerical simulations, aiming to find optimal parameters. Subsequently, we constructed a customized system of multi-LSFM that incorporates both interference light sheets (ILS) and noninterference light-sheet configurations. We performed beam imaging and microsphere imaging tests to evaluate the FOV and axial resolution of these systems. Results: Using our custom-designed light-sheet fluorescence microscope, we captured the intensity distribution profiles of both interference and noninterference light sheets (NILS). Additionally, we conducted imaging tests on microspheres to assess their imaging outcomes. The ILS not only exhibits a larger FOV compared to the NILS but also demonstrates a more uniform axial resolution. Conclusions: By effectively modulating the interference among multiple LSs, it is possible to optimize the intensity distribution of the LSs, expand the FOV, and achieve a more uniform axial resolution.

Mineralocorticoid promotes intestinal inflammation through receptor dependent IL17 production in ILC3s.

Aldosterone is a key mineralocorticoid involved in regulating the concentration of blood electrolytes and physiological volume balance. Activation of mineralocorticoid receptor (MR) has been recently reported to participate in adaptive and innate immune responses under inflammation. Here, we evaluated the role of aldosterone and MR in inflammation bowel diseases (IBD). Aldosterone elevated in the colon of DSS-induced colitis mice. Aldosterone addition induced IL17 production and ROS/RNS level in group 3 innate lymphoid cells (ILC3s) and exacerbated intestinal injury. A selective mineralocorticoid receptor antagonism, eplerenone, inhibited IL17-producing ILC3s and its ROS/RNS production, protected mice from DSS-induced colitis. Mice lacking Nr3c2 (MR coding gene) in ILC3s exhibited decreased IL17 and ROS/RNS production, which alleviated colitis and colitis-associated colorectal cancer (CAC). Further experiments revealed that MR could directly bind to IL17A promoter and facilitate its transcription, which could be enhanced by aldosterone. Thus, our findings demonstrated the critical role of aldosterone-MR-IL17 signaling in ILC3s and gut homeostasis, indicating the therapeutic strategy of eplerenone in IBD clinical trial.

Axial super-resolution optical coherence tomography via complex-valued network.

Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric imaging technique that can provide high-resolution cross-sectional images of biological tissues. OCT's key strength is its depth resolving capability which remains invariant along the imaging depth and is determined by the axial resolution. The axial resolution is inversely proportional to the bandwidth of the OCT light source. Thus, the use of broadband light sources can effectively improve the axial resolution and however leads to an increased cost. In recent years, real-valued deep learning technique has been introduced to obtain super-resolution optical imaging. In this study, we proposed a complex-valued super-resolution network (CVSR-Net) to achieve an axial super-resolution for OCT by fully utilizing the amplitude and phase of OCT signal. The method was evaluated on three OCT datasets. The results show that the CVSR-Net outperforms its real-valued counterpart with a better depth resolving capability. Furthermore, comparisons were made between our network, six prevailing real-valued networks and their complex-valued counterparts. The results demonstrate that the complex-valued network exhibited a better super-resolution performance than its real-valued counterpart and our proposed CVSR-Net achieved the best performance. In addition, the CVSR-Net was tested on out-of-distribution domain datasets and its super-resolution performance was well maintained as compared to that on source domain datasets, indicating a good generalization capability.

Design of a Subretinal Injection Robot Based on the RCM Mechanism.

This study presents an investigation focusing on the advancement of a robot designed for subretinal injections in the context of macular degeneration treatment. The technique of subretinal injection surgery stands as the most efficacious approach for the successful transplantation of stem cells into the retinal pigment epithelium layer. This particular procedure holds immense significance in advancing research and implementing therapeutic strategies involving retinal stem cell transplantation. The execution of artificial subretinal surgery poses considerable challenges which can be effectively addressed through the utilization of subretinal injection surgery robots. The development process involved a comprehensive modeling phase, integrating computer-aided design (CAD) and finite element analysis (FEA) techniques. These simulations facilitated iterative enhancements of the mechanical aspects pertaining to the robotic arm. Furthermore, MATLAB was employed to simulate and visualize the robot's workspace, and independent verification was conducted to ascertain the range of motion for each degree of freedom.

Hydrolysis and condensation of monobutyltin chloride: reaction process analysis with DFT.

As the initial process of preparing transparent conductive oxide materials from monobutyltin chloride (MBTC) to tin oxide, the hydrolysis and condensation of MBTC to form a dimer Sn2 play a critical role. However, the specific mechanism of this process is still unclear. Here we develop a step-by-step searching method based on density functional theory calculation and empirical chemical criteria to determine possible reaction pathways and reveal the most likely reaction mechanism. The wave function analyses of various intermediate species provide more insights into the changes of atomic charge population, chemical bond strength, and coordination situation of central tin in the reaction process. Further investigation on the ring-containing Sn2 reveals the existence of unique three-center four-electron (3c-4e) interactions to stabilize the four-membered Sn2O2 ring structure, which serves as the true driving force for dimerization reaction. These results provide a more detailed understanding of the hydrolysis and condensation process of MBTC and would be helpful for the future optimization of the preparation process of tin oxide films.

Dysambiol, an Anti-inflammatory Secomeroterpenoid from a Dysidea sp. Marine Sponge.

An unusual secomeroterpenoid, dysambiol (1), was isolated from a Dysidea sp. marine sponge collected from the South China Sea. Dysambiol features an unprecedented secomeroterpene scaffold with a rare lactone bridge. The structure of 1 was determined by extensive spectroscopic analysis, Mosher's method, and electronic circular dichroism calculation. Dysambiol displayed potent anti-inflammatory activity in LPS-induced Raw 264.7 macrophages by regulating the NF-κB/MPAK signaling pathway.

Physical compensation method for dispersion of multiple materials in swept source optical coherence tomography.

An ophthalmic swept source-optical coherence tomography (SS-OCT) system based on a high-speed scanning laser at 1060 nm with a scanning rate of 100 KHz is constructed. Since the sample arm of the interferometer is comprised of multiple glass materials, the ensuing dispersion severely degrades imaging quality. In this article, second-order dispersion simulation analysis for various materials was performed first, and dispersion equilibrium was implemented utilizing physical compensation methods. After dispersion compensation, an imaging depth in air of 4.013 mm was achieved in model eye experiments, and signal-to-noise ratio was enhanced by 11.6%, with a value of 53.8 dB. In vivo imaging of the human retina was performed to demonstrate structurally distinguishable retinal images, characterized by an axial resolution improvement of 19.8%, with a value of 7.7 µm close to the theoretical value of 7.5 µm. The proposed physical dispersion compensation method enhances imaging performance in SS-OCT systems, enabling visualization of several low scattering mediums.

Domain Adaptation-Based Automated Detection of Retinal Diseases from Optical Coherence Tomography Images.

PURPOSE: To verify the effectiveness of domain adaptation in generalizing a deep learning-based anomaly detection model to unseen optical coherence tomography (OCT) images. METHODS: Two datasets (source and target, where labelled training data was only available for the source) captured by two different OCT facilities were collected to train the model. We defined the model containing a feature extractor and a classifier as Model One and trained it with only labeled source data. The proposed domain adaptation model was defined as Model Two, which has the same feature extractor and classifier as Model One but has an additional domain critic in the training phase. We trained the Model Two with both the source and target datasets; the feature extractor was trained to extract domain-invariant features while the domain critic learned to capture the domain discrepancy. Finally, a well-trained feature extractor was used to extract domain-invariant features and a classifier was used to detect images with retinal pathologies in the two domains. RESULTS: The target data consisted of 3,058 OCT B-scans captured from 163 participants. Model One achieved an area under the curve (AUC) of 0.912 [95% confidence interval (CI), 0.895-0.962], while Model Two achieved an overall AUC of 0.989 [95% CI, 0.982-0.993] for detecting pathological retinas from healthy samples. Moreover, Model Two achieved an average retinopathies detection accuracy of 94.52%. Heat maps showed that the algorithm focused on the area with pathological changes during processing, similar to manual grading in daily clinical work. CONCLUSIONS: The proposed domain adaptation model showed a strong ability in reducing the domain distance between different OCT datasets.

Dual-slit confocal light-sheet microscopy using birefringent crystals.

We present a method to use a birefringent crystal for generating two illumination beams in a digital scanned laser light-sheet microscopy (DSLM) system. Upon this, a conventional confocal DSLM can be easily upgraded to a dual-slit confocal DSLM with two-fold imaging speed. We have implemented this method to our bidirectional DSLM system, locating two identical calcite crystals on both illumination paths from both sides of the sample. The neurons of in vivo larval zebrafish have been fast imaged with sterling image quality, especially ~2.5 times higher contrast, compared to the conventional DSLM.

Gene Therapy Activates Retinal Pigment Epithelium Cell Proliferation for Age-related Macular Degeneration in a Mouse Model.

OBJECTIVE: Age-related macular degeneration (AMD) is a degenerative retinal disease. The degeneration or death of retinal pigment epithelium (RPE) cells is implicated in the pathogenesis of AMD. This study aimed to activate the proliferation of RPE cells in vivo by using an adeno-associated virus (AAV) vector encoding ß-catenin to treat AMD in a mouse model. METHODS: Mice were intravitreally injected with AAV2/8-Y733F-VMD2-ß-catenin for 2 or 4 weeks, and ß-catenin expression was measured using immunofluorescence staining, real-time quantitative reverse transcription polymerase chain reaction (PCR), and Western blotting. The function of ß-catenin was determined using retinal flat mounts and laser-induced damage models. Finally, the safety of AAV2/8-Y733F-VMD2-ß-catenin was evaluated by multiple intravitreal injections. RESULTS: AAV2/8-Y733F-VMD2-ß-catenin induced the expression of ß-catenin in RPE cells. It activated the proliferation of RPE cells and increased cyclin D1 expression. It was beneficial to the recovery of laser-induced damage by activating the proliferation of RPE cells. Furthermore, it could induce apoptosis of RPE cells by increasing the expression of Trp53, Bax and caspase3 while decreasing the expression of Bcl-2. CONCLUSION: AAV2/8-Y733F-VMD2-ß-catenin increased ß-catenin expression in RPE cells, activated RPE cell proliferation, and helped mice heal from laser-induced eye injury. Furthermore, it could induce the apoptosis of RPE cells. Therefore, it may be a safe approach for AMD treatment.

Targeted delivery of food functional ingredients in precise nutrition: design strategy and application of nutritional intervention.

With the high incidence of chronic diseases, precise nutrition is a safe and efficient nutritional intervention method to improve human health. Food functional ingredients are an important material base for precision nutrition, which have been researched for their application in preventing diseases and improving health. However, their poor solubility, stability, and bad absorption largely limit their effect on nutritional intervention. The establishment of a stable targeted delivery system is helpful to enhance their bioavailability, realize the controlled release of functional ingredients at the targeted action sites in vivo, and provide nutritional intervention approaches and methods for precise nutrition. In this review, we summarized recent studies about the types of targeted delivery systems for the delivery of functional ingredients and their digestion fate in the gastrointestinal tract, including emulsion-based delivery systems and polymer-based delivery systems. The building materials, structure, size and charge of the particles in these delivery systems were manipulated to fabricate targeted carriers. Finally, the targeted delivery systems for food functional ingredients have gained some achievements in nutritional intervention for inflammatory bowel disease (IBD), liver disease, obesity, and cancer. These findings will help in designing fine targeted delivery systems, and achieving precise nutritional intervention for food functional ingredients on human health.

Scleral Suture Intraocular Lens Fixation Under Microscope-Intraoperative Optical Coherence Tomography.

PURPOSE: The aim of this study was to evaluate the accessibility and potential value of intraoperative optical coherence tomography (iOCT) during scleral suture intraocular lens (IOL) fixation. METHODS: This was a prospective cohort study in the Department of Ophthalmology, Eye and ENT Hospital, Fudan University, China. Seven eyes with insufficient capsular support and undergoing two-point scleral suture IOL fixation were included. The potential value of iOCT was evaluated, as well as the safety and efficacy of the surgery. RESULTS: Seven eyes were included. With a tailor-made iOCT, the structure of the anterior segment could be clearly visualized during the surgery. Intraoperatively, iOCT helped locate the proper place for fixation and access the position of the IOL. After an average 4.43-month follow-up, the spherical equivalent changed significantly ( P < 0.001), but the intraocular pressure, best-corrected visual acuity, and endothelial cell density remained unchanged ( P > 0.05). The IOL was well-centered with a horizontal and a vertical tilt of 0.74 ± 0.60° and 1.13 ± 0.65°, and decentration of 0.28 ± 0.12 mm and 0.30 ± 0.13 mm. The estimated IOL-induced astigmatism was -0.11 diopters (D) ± 0.46 D. CONCLUSION: Real-time high-resolution images of the anterior segment acquired by the iOCT helped the surgeon to achieve satisfactory results in scleral suture IOL fixation.

Synthesizing multi-frame high-resolution fluorescein angiography images from retinal fundus images using generative adversarial networks.

BACKGROUND: Fundus fluorescein angiography (FA) can be used to diagnose fundus diseases by observing dynamic fluorescein changes that reflect vascular circulation in the fundus. As FA may pose a risk to patients, generative adversarial networks have been used to convert retinal fundus images into fluorescein angiography images. However, the available methods focus on generating FA images of a single phase, and the resolution of the generated FA images is low, being unsuitable for accurately diagnosing fundus diseases. METHODS: We propose a network that generates multi-frame high-resolution FA images. This network consists of a low-resolution GAN (LrGAN) and a high-resolution GAN (HrGAN), where LrGAN generates low-resolution and full-size FA images with global intensity information, HrGAN takes the FA images generated by LrGAN as input to generate multi-frame high-resolution FA patches. Finally, the FA patches are merged into full-size FA images. RESULTS: Our approach combines supervised and unsupervised learning methods and achieves better quantitative and qualitative results than using either method alone. Structural similarity (SSIM), normalized cross-correlation (NCC) and peak signal-to-noise ratio (PSNR) were used as quantitative metrics to evaluate the performance of the proposed method. The experimental results show that our method achieves better quantitative results with structural similarity of 0.7126, normalized cross-correlation of 0.6799, and peak signal-to-noise ratio of 15.77. In addition, ablation experiments also demonstrate that using a shared encoder and residual channel attention module in HrGAN is helpful for the generation of high-resolution images. CONCLUSIONS: Overall, our method has higher performance for generating retinal vessel details and leaky structures in multiple critical phases, showing a promising clinical diagnostic value.

Combined effects of vitamin C and cold atmospheric plasma-conditioned media against glioblastoma via hydrogen peroxide.

Glioblastoma is the most lethal intracranial malignant tumor, for which the five-year overall survival rate is approximately 5%. Here we explored the therapeutic combination of vitamin C and plasma-conditioned medium on glioblastoma cells in culture and as subcutaneous or intracranial xenografts in mice. The combination treatment reduced cell viability and proliferation while promoting apoptosis, and the effects were significantly stronger than with either treatment on its own. Similar results were obtained in the two xenograft models. Vitamin C appeared to upregulate aquaporin-3 and enhance the uptake of extracellular H2O2, while the combination treatment increased intracellular levels of reactive oxygen species including H2O2 and activated the JNK signaling pathway. The cytotoxic effects of the combination treatment were partially reversed by the specific JNK signaling inhibitor SP600125. Our results suggest that the combination of vitamin C and plasma-conditioned medium has therapeutic potential against glioblastoma, and they provide mechanistic insights that may help investigate this and other potential therapies in greater depth.

Integrating genome-wide association study with RNA-seq revealed DBI as a good candidate gene for intramuscular fat content in Beijing black pigs.

Increasing intramuscular fat (IMF) content can enhance the sensory quality of meat, including tenderness, juiciness, flavor, and color. Genome-wide association study and RNA-sequencing (RNA-seq) analysis were used to identify candidate IMF genes in Beijing Black pigs, a popular species among consumers in northern China. Two and three single nucleotide polymorphisms were significantly associated with IMF in SSC13 and SSC15 respectively. Solute carrier family 4 member 7 (SLC4A7) on SSC13 and insulin induced gene 2 (INSIG2), coiled-coil domain containing 93 (CCDC93), and diazepam binding inhibitor acyl-CoA binding protein (DBI) on SSC15 are good candidate genes in this population. Furthermore, RNA-seq analysis was performed between high and low IMF groups, and 534 differentially expressed genes were identified. In addition, based on differentially expressed genes, Kyoto Encyclopedia of Genes and Genomes analysis revealed that peroxisome proliferator-activated receptors and FoxO signaling pathway pathways might contribute to IMF. Moreover, the DBI gene was identified as a candidate for IMF both by genome-wide association study and RNA-seq analysis, suggesting that it might be a crucial candidate gene for influencing IMF in Beijing Black pigs.

Integrating Genome-Wide Association Study with RNA-Sequencing Reveals HDAC9 as a Candidate GeneInfluencing Loin Muscle Area in Beijing Black Pigs.

Loin muscle area (LMA) is an important meat production trait and plays a key role in determining carcass leanness. Genome-wide association study (GWAS) and RNA sequencing (RNA-seq) analysis were used to identify candidate LMA genes in Beijing Black pigs, a popular breed among consumers in northern China. Ten single nucleotide polymorphisms (SNPs) in sus scrofa chromosome (SSC) 9 were significantly associated with LMA. These SNPs were mapped to a 2.90 Mb (84.94-87.84 Mb) region. A total of 11 annotated genes were mapped on this region, namely MEOX2, CRPPA, SOSTDC1, LRRC72, ANKMY2, BZW2, TSPAN13, AGR2, AHR, SNX13, and HDAC9. In addition, RNA-seq analysis was performed between the high- and low-LMA groups, and 329 differentially expressed genes (DEGs) were identified. Further, Kyoto Encyclopedia of Genes and Genomes analysis based on DEGs revealed that the JAK/STAT signaling pathway and oxytocin signaling pathway may be responsible for LMA. Both GWAS and RNA-seq analysis identified the HDAC9 gene, indicating that it may be an important candidate gene affecting LMA in Beijing Black pigs. The findings provide valuable molecular insights into the mechanisms that influence LMA content in pigs, which can be utilized in targeted approaches to enhance meat quality and commercial profitability.

Rapid Screening of 22 Polycyclic Aromatic Hydrocarbons Residues in Vegetable Oils by Gas Chromatography-Electrostatic Field Orbitrap High Resolution Mass Spectrometry.

A method for simultaneous determination of 22 polycyclic aromatic hydrocarbons (PAHs) residues in vegetable oils by gas chromatography-electrostatic field orbitrap high resolution mass spectrometry (Orbitrap GC-MS) was established. The samples were vortexed with acetonitrile, centrifuged at 8,000 r/min for 5 min, and frozen at -70°C for 10 min. The extracts of upper layer were poured out, dried with nitrogen at 40°C, redissolved in dichloromethane, and measured by Orbitrap GC-MS. The matrix interference in vegetable oil could be effectively removed by determining the accurate mass number of target compounds under the full scan mode. Six typical vegetable oil samples (soybean oil, sesame oil, peanut oil, olive oil, rapeseed oil, sunflower oil) were used for method validation. The calibration curve displayed good linearity in the range of 1-100 ng/mL, with correlation coefficients > 0.9950. The limits of detection (LODs) were in the range of 0.10-0.60 µg/kg, and the limits of quantification (LOQs) were in the range of 0.35-2.00 µg/kg. The average spiked recoveries of 22 PAHs in 6 matrices at 5, 50 and 100 µg/kg levels were 76.4-115.4%, and the average relative standard deviations (RSDs) were 1.8-10.8%. The results showed that 22 PAHs were detected in 6 types of 90 edible vegetable oil samples in the Chinese market by this method. Meanwhile, the abundance of light PAHs (LPAHs) was higher than that of heavy PAHs (HPAHs), and its relative contribution of LPAHs to the total PAHs was higher. All levels of BaP conformed to the Chinese requirement of upper limit, 10 µg/kg. However, 13.3 and 11.1% of the samples exceeded the maximum limits of BaP and PAH4 set by EU, 2 and 10 µg/kg, respectively. The total concentrations of 22 PAHs (defined as PAH22) varies greatly among different oil species, and the average PAH22 contents were listed in descending order as follows: peanut oil > sesame oil > olive oil > rapeseed oil > soybean oil > sunflower seed oil. The established method effectively avoided interference from large amounts of lipids and pigments. Therefore, the method is simple, sensitive and suitable for rapid screening and confirmation of PAHs in vegetable oil.

Centerline extraction by neighborhood-statistics thinning for quantitative analysis of corneal nerve fibers.

Objective.Corneal nerve fiber (CNF) has been found to exhibit morphological changes associated with various diseases, which can therefore be utilized to aid in the early diagnosis of those diseases. CNF is usually visualized under corneal confocal microscopy (CCM) in clinic. To obtain the diagnostic biomarkers from CNF image produced from CCM, image processing and quantitative analysis are needed. Usually, CNF is segmented first and then CNF's centerline is extracted, allowing for measuring geometrical and topological biomarkers of CNF, such as density, tortuosity, and length. Consequently, the accuracy of the segmentation and centerline extraction can make a big impact on the biomarker measurement. Thus, this study is aimed to improve the accuracy and universality of centerline extraction.Approach.We developed a new thinning algorithm based on neighborhood statistics, called neighborhood-statistics thinning (NST), to extract the centerline of CNF. Compared with traditional thinning and skeletonization techniques, NST exhibits a better capability to preserve the fine structure of CNF which can effectively benefit the biomarkers measurement above. Moreover, NST incorporates a fitting process, which can make centerline extraction be less influenced by image segmentation.Main results.This new method is evaluated on three datasets which are segmented with five different deep learning networks. The results show that NST is superior to thinning and skeletonization on all the CNF-segmented datasets with a precision rate above 0.82. Last, NST is attempted to be applied for the diagnosis of keratitis with the quantitative biomarkers measured from the extracted centerlines. Longer length and higher density but lower tortuosity were found on the CNF of keratitis patients as compared to healthy patients.Significance.This demonstrates that NST has a good potential to aid in the diagnostics of eye diseases in clinic.