Investigating HMGB1 as a potential serum biomarker for early diabetic nephropathy monitoring by quantitative proteomics.

Current diagnostic methods for diabetic nephropathy (DN) lack precision, especially in early stages and monitoring progression. This study aims to find potential biomarkers for DN progression and evaluate their accuracy. Using serum samples from healthy controls (NC), diabetic patients (DM), early-medium stage DN (DN-EM), and late-stage DN (DN-L), researchers employed quantitative proteomics and Mfuzz clustering analysis revealed 15 proteins showing increased expression during DN progression, hinting at their biomarker potential. Combining Mfuzz clustering with weighted gene co-expression network analysis (WGCNA) highlighted five candidates (HMGB1, CD44, FBLN1, PTPRG, and ADAMTSL4). HMGB1 emerged as a promising biomarker, closely correlated with renal function changes. Experimental validation supported HMGB1's upregulation under high glucose conditions, reinforcing its potential as an early detection biomarker for DN. This research advances DN understanding and identifies five potential biomarkers, notably HMGB1, as a promising early monitoring target. These findings set the stage for future clinical diagnostic applications in DN.

A novel miniature flexible robotic system for endoscopic mucosal dissection: an animal experimental study.

Endoscopic submucosal dissection (ESD) is a standard treatment for early gastrointestinal cancer due to its higher rate of en-bloc resection and lower recurrence rate. However, the technical challenges lead to long learning curve and high risks of adverse events. A gastrointestinal flexible robotic-tool system (GIFTS) was proposed to reduce the difficulty and shorten the learning curve of novices. This is an animal study to evaluate the feasibility of GIFTS in ESD. The GIFTS provides a total of 13 degrees of freedom within 10 mm in diameter and variable stiffness function to achieve endoscopic intervention and submucosal dissection with the cooperation of two flexible robotic instruments. One esophageal and four colorectal ESDs in five porcine models were performed. In all five ESD procedures, the GIFTS was successfully intubated and submucosal dissection was completed without perforation or significant bleeding, and there was no system fault. The mean operative time was 99 min, and the mean size of the specimen was 151 mm2. The fifth experiment showed significantly better results than the first one. In vivo animal experiments confirmed the feasibility of GIFTS in performing ESD. The control of GIFTS is friendly to inexperienced beginners, which will help reduce the technical challenges of ESD and shorten the learning curve of endoscopists.

Flexible instrument with contact-aided structure and force feedback for endoscopic surgery.

BACKGROUND: Robot-assisted surgery can effectively reduce the difficulty and improve the success rate of the surgeries. However, currently available flexible instruments have several limitations, such as large size, few degrees of freedom, and lack of contact force perception. METHODS: This study proposes a master-slave flexible instrument capable of force feedback. The instrument has a maximum outer diameter of 3 mm and an overall length of 1200 mm. With the internal working channel unoccupied, a three-dimensional force sensing unit is designed based on the neural network. The corresponding master-slave control method with proportional force feedback was also designed to effectively control the instrument. RESULTS: To verify the effectiveness of the system, in vitro and in vivo experiments were conducted. The corresponding tasks were successfully completed. CONCLUSIONS: The animal trial conducted in the digestive tract of a live swine proved that the system has the potential for clinical use.

Flexible endoscopic instrument for diagnosis and treatment of early gastric cancer.

Gastric cancer is a common cancer endangering human life and health worldwide. Early detection and diagnosis of gastric cancer that is normally performed by flexible endoscope can significantly improve the survival rate of patients. However, current endoscopic instruments have some problems, such as limitation of degrees of freedom (DOFs) and lack of surgical triangulation. Meanwhile, the lack of an intraoperative technique for the real-time evaluation of early gastric cancer is also a serious problem. To solve these problems, we have developed a dual-bending flexible endoscopic instrument for the diagnosis and treatment of early gastric cancer. This instrument has a compact structure with a maximum outer diameter of 3 mm and an insertion length of 1220 mm. It has 5 DOFs with a dual-bending function, which can form a surgical operation triangulation to easily perform the endoscopic procedure. Apart from the surgical forceps, the end of the instrument can be equipped with different endoscopic devices to meet the needs of diagnosis and treatment, such as endomicroscopic probes, electrosurgical knives, and laser ablation optical fibers. It is verified that the instrument can carry these devices to complete corresponding tasks, demonstrating the great potential of this instrument in clinical applications.

Pharmacological inhibition of SMYD2 protects against cisplatin-induced renal fibrosis and inflammation.

SET and MYND domain protein 2 (SMYD2) can methylate histone H3 at lysine36 (H3K36) and some non-histone substrates to play a role in tumorigenesis. However, It is unclear how SMYD2 contributes to chronic kidney disease (CKD). Here, AZ505 or LLY507, which could inhibit SMYD2, were used in cisplatin-induced CKD to investigate the effects and possible mechanisms by which they might act. We found that high expression of SMYD2 in cisplatin-induced CKD. However, AZ505 or LLY507 can significantly inhibit its expression, improve renal function injury and fibrosis induced by cisplatin, inhibit the transition of epithelial cells to a fibrogenic phenotype and fibrosis-related proteins, inhibit the expression of Inflammatory Cytokines (such as IL-6 and TNF-α), And inhibit the phosphorylation of pro-fibrosis molecule Smad3 and signal transduction and transcription activator-3 (STAT3) and up-regulated the expression of renal protective factor Smad7. In cultured tubular epithelial cells, AZ505 also can inhibit the expression of EMT, fibrosis-related proteins, and inflammatory cytokines in cisplatin-induced tubular epithelial cells. Based on these findings, SMYD2 may be a critical regulator of cisplatin-induced CKD and targeted pharmacological inhibition of SMYD2 may prevent cisplatin-induced CKD through Smad3 or STAT3-related signaling pathways.

Self-supervised monocular depth estimation for gastrointestinal endoscopy.

BACKGROUND AND OBJECTIVE: Gastrointestinal (GI) endoscopy represents a promising tool for GI cancer screening. However, the limited field of view and uneven skills of endoscopists make it remains difficult to accurately identify polyps and follow up on precancerous lesions under endoscopy. Estimating depth from GI endoscopic sequences is essential for a series of AI-assisted surgical techniques. Nonetheless, depth estimation algorithm of GI endoscopy is a challenging task due to the particularity of the environment and the limitation of datasets. In this paper, we propose a self-supervised monocular depth estimation method for GI endoscopy. METHODS: A depth estimation network and a camera ego-motion estimation network are firstly constructed to obtain the depth information and pose information of the sequence respectively, and then the model is enabled to perform self-supervised training by calculating the multi-scale structural similarity with L1 norm (MS-SSIM+L1) loss function between the target frame and the reconstructed image as part of the loss of the training network. The MS-SSIM+L1 loss function is good for reserving high-frequency information and can maintain the invariance of brightness and color. Our model consists of the U-shape convolutional network with the dual-attention mechanism, which is beneficial to capture muti-scale contextual information, and greatly improves the accuracy of depth estimation. We evaluated our method qualitatively and quantitatively with different state-of-the-art methods. RESULTS AND CONCLUSIONS: The experimental results manifest that our method has superior generality, achieving lower error metrics and higher accuracy metrics on both the UCL dataset and the Endoslam dataset. The proposed method has also been validated with clinical GI endoscopy, demonstrating the potential clinical value of the model.

Actuation and design innovations in earthworm-inspired soft robots: A review.

Currently, soft robotics technologies are creating the means of robotic abilities and are required for the development of biomimetic robotics. In recent years, earthworm-inspired soft robot has garnered increasing attention as a major branch of bionic robots. The major studies on earthworm-inspired soft robots focuses on the deformation of the earthworm body segment. Consequently, various actuation methods have been proposed to conduct the expansion and contraction of the robot's segments for locomotion simulation. This review article aims to act as a reference guide for researchers interested in the field of earthworm-inspired soft robot, and to present the current state of research, summarize current design innovations, compare the advantages and disadvantages of different actuation methods with the purpose of inspiring future innovative orientations for researchers. Herein, earthworm-inspired soft robots are classified into single- and multi-segment types, and the characteristics of various actuation methods are introduced and compared according to the number of matching segments. Moreover, various promising application instances of the different actuation methods are detailed along with their main features. Finally, motion performances of the robots are compared by two normalized metrics-speed compared by body length and speed compared by body diameter, and future developments in this research direction are presented.

Query2: Query over queries for improving gastrointestinal stromal tumour detection in an endoscopic ultrasound.

Gastrointestinal stromal tumour (GIST) lesions are mesenchymal neoplasms commonly found in the upper gastrointestinal tract, but non-invasive GIST detection during an endoscopy remains challenging because their ultrasonic images resemble several benign lesions. Techniques for automatic GIST detection and other lesions from endoscopic ultrasound (EUS) images offer great potential to advance the precision and automation of traditional endoscopy and treatment procedures. However, GIST recognition faces several intrinsic challenges, including the input restriction of a single image modality and the mismatch between tasks and models. To address these challenges, we propose a novel Query2 (Query over Queries) framework to identify GISTs from ultrasound images. The proposed Query2 framework applies an anatomical location embedding layer to break the single image modality. A cross-attention module is then applied to query the queries generated from the basic detection head. Moreover, a single-object restricted detection head is applied to infer the lesion categories. Meanwhile, to drive this network, we present GIST514-DB, a GIST dataset that will be made publicly available, which includes the ultrasound images, bounding boxes, categories and anatomical locations from 514 cases. Extensive experiments on the GIST514-DB demonstrate that the proposed Query2 outperforms most of the state-of-the-art methods.

A monocular SLAM system based on SIFT features for gastroscope tracking.

During flexible gastroscopy, physicians have extreme difficulties to self-localize. Camera tracking method such as simultaneous localization and mapping (SLAM) has become a research hotspot in recent years, allowing tracking of the endoscope. However, most of the existing solutions have focused on tasks in which sufficient texture information is available, such as laparoscope tracking, and cannot be applied to gastroscope tracking since gastroscopic images have fewer textures than laparoscopic images. This paper proposes a new monocular SLAM framework based on scale-invariant feature transform (SIFT) and narrow-band imaging (NBI), which extracts SIFT features instead of oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (BRIEF) features from gastroscopic NBI images, and performs feature retention based on the response sorting strategy for achieving more matches. Experimental results show that the root mean squared error of the proposed algorithm can reach a minimum of 2.074 mm, and the pose accuracy can be improved by up to 25.73% compared with oriented FAST and rotated BRIEF (ORB)-SLAM. SIFT features and response sorting strategy can achieve more accurate matching in gastroscopic NBI images than other features and homogenization strategy, and the proposed algorithm can also run successfully on real clinical gastroscopic data. The proposed algorithm has the potential clinical value to assist physicians in locating the gastroscope during gastroscopy.

[Confocal probe localization algorithm based on region growing and endoscope size prior].

Confocal laser endomicroscopy technology can obtain cell-level images in real time and in situ, which can assist doctors in real-time intraoperative diagnosis, but its non-invasiveness makes it difficult to relocate the optical biopsy site. The confocal probe localization algorithm can automatically calculate the coordinates of the probe tip, that is, the coordinates of the optical biopsy site. In this paper, a confocal probe localization algorithm based on region growing and endoscope size prior was proposed. The algorithm detected the probe region by region growing on the probe edge image, then searched for tip points based on a given probe axis, and iteratively optimized it. Finally, based on the single-degree-of-freedom motion characteristics of the probe, the three-dimensional coordinates of the tip of the probe were calculated by using the prior information of the size of the endoscope, which solved the scale uncertainty problem of the monocular camera. The confocal probe localization algorithm was tested on the dataset collected in this paper. The results showed that our algorithm no longer relied on the color information of the probe, avoided the influence of uneven illumination on the gray value of the probe pixels, and had a more robust location accuracy and running speed. Within the length of the probe extending out of the endoscope from 0 to 5 cm, the pixel error could be as low as 11.76 pixels, and the average relative position error could be as low as 1.66 mm, which can achieve the real-time and accurate localization of the confocal probe.

Ranunculus ternatus Thunb extract attenuates renal fibrosis of diabetic nephropathy via inhibiting SMYD2.

CONTEXT: Ranunculus ternatus Thunb (Ranunculaceae), (RTT) is used clinically for the treatment of tuberculosis or as tumour adjuvant therapy, but its potential effect on diabetic nephropathy (DN) has not been studied. OBJECTIVE: To investigate the effect of RTT extract in renal fibrosis of DN. MATERIALS AND METHODS: C57BL/6 mice were randomly divided into four groups (n = 12). Diabetes mellitus (DM) mice were induced by streptozotocin (STZ, 55 mg/kg/day) for five consecutive days and treated by RTT extract (2 g/kg). Afterward, blood glucose, HE and Masson staining were assayed. The expression levels of Vimentin, ɑ-SMA, TNF-ɑ, NF-κB p-p65, NF-κB p65, SMYD2, H3K36me3, H3K4me3 were determined by western blots. Firbronectin was respectively assayed by western blot and immunofluorescent staining. RESULTS: RTT extract significantly ameliorated renal injury and renal fibrosis in the renal tissue of STZ-induced diabetic mice as demonstrated by the decreased expression level of Fibronectin (65%), Vimentin and α-SMA (75% & 53%). In addition, the levels of TNF-α (57%), NF-κB p-p65 and NF-κB p65 (35% & 25%) were elevated in the DN mice. Importantly, these were alleviated after RTT extract treatment. Moreover, we observed that the protein levels of SMYD2 (30%), H3K36me3 and H3K4me3 (53% & 75%) were reduced in DN mice after treatment with RTT extract. DISCUSSION AND CONCLUSIONS: RTT extract mediates antifibrotic effects and anti-inflammatory responses in STZ-induced DN mainly through suppressing SMYD2 activation and H3K36me3 and H3K4me3 protein expression. RTT extract might have therapeutic potential against high glucose-induced nephropathy.

Intensity-based nonrigid endomicroscopic image mosaicking incorporating texture relevance for compensation of tissue deformation.

Image mosaicking has emerged as a universal technique to broaden the field-of-view of the probe-based confocal laser endomicroscopy (pCLE) imaging system. However, due to the influence of probe-tissue contact forces and optical components on imaging quality, existing mosaicking methods remain insufficient to deal with practical challenges. In this paper, we present the texture encoded sum of conditional variance (TESCV) as a novel similarity metric, and effectively incorporate it into a sequential mosaicking scheme to simultaneously correct rigid probe shift and nonrigid tissue deformation. TESCV combines both intensity dependency and texture relevance to quantify the differences between pCLE image frames, where a discriminative binary descriptor named fully cross-detected local derivative pattern (FCLDP) is designed to extract more detailed structural textures. Furthermore, we also analytically derive the closed-form gradient of TESCV with respect to the transformation variables. Experiments on the circular dataset highlighted the advantage of the TESCV metric in improving mosaicking performance compared with the other four recently published metrics. The comparison with the other four state-of-the-art mosaicking methods on the spiral and manual datasets indicated that the proposed TESCV-based method not only worked stably at different contact forces, but was also suitable for both low- and high-resolution imaging systems. With more accurate and delicate mosaics, the proposed method holds promises to meet clinical demands for intraoperative optical biopsy.

Flexible Manipulator with Low-Melting-Point Alloy Actuation and Variable Stiffness.

Flexible manipulators offer significant advantages over traditional rigid manipulators in minimally invasive surgery, because they can flexibly navigate around obstacles and pass cramped or tortuous paths. However, due to the inherent low stiffness, the ability to control/obtain higher stiffness when required remains to be further explored. In this article, we propose a flexible manipulator that exploits the phase transformation property of low-melting-point alloy to hydraulically drive and change the stiffness by heating and cooling. A prototype was fabricated, and experiments were conducted to evaluate the motion characteristics, stiffness performance, and rigid-flexible transition efficiency. The experimental results demonstrate that the proposed manipulator can freely adjust heading direction in the three-dimensional space. The experimental results also indicate that it took 9.2-10.3 s for the manipulator to transform from a rigid state to a flexible state and 15.4 s to transform from a flexible state to a rigid state. The lateral stiffness and flexural stiffness of the manipulator were 95.54 and 372.1 Ncm2 in the rigid state and 7.26 and 0.78 Ncm2 in the flexible state. The gain of the lateral stiffness and flexural stiffness was 13.15 and 477.05, respectively. In the rigid state, the ultimate force without shape deformation was more than 0.98 N in the straight condition (0°) and 1.36 N in the bending condition (90°). By assembling flexible surgical tools, the manipulator can enrich the diagnosis or treatment functions, which demonstrated the potential clinical value of the proposed manipulator.

Miniature Flexible Instrument with Fibre Bragg Grating-Based Triaxial Force Sensing for Intraoperative Gastric Endomicroscopy.

Optical biopsy methods, such as probe-based endomicroscopy, can be used to identify early-stage gastric cancer in vivo. However, it is difficult to scan a large area of the gastric mucosa for mosaicking during endoscopy. In this work, we propose a miniaturised flexible instrument based on contact-aided compliant mechanisms and fibre Bragg grating (FBG) sensing for intraoperative gastric endomicroscopy. The instrument has a compact design with an outer diameter of 2.7 mm, incorporating a central channel with a diameter of 1.9 mm for the endomicroscopic probe to pass through. Experimental results show that the instrument can achieve raster trajectory scanning over a large tissue surface with a positioning accuracy of 0.5 mm. The tip force sensor provides a 4.6 mN resolution for the axial force and 2.8 mN for transverse forces. Validation with random samples shows that the force sensor can provide consistent and accurate three-axis force detection. Endomicroscopic imaging experiments were conducted, and the flexible instrument performed no gap scanning (mosaicking area more than 3 mm2) and contact force monitoring during scanning, demonstrating the potential of the system in clinical applications.

A novel master-slave intraocular surgical robot with force feedback.

BACKGROUND: Intraocular surgery is one of the most challenging microsurgeries. Unintended movements of human hand and lack of force feedback can seriously affect surgical safety. METHODS: We developed a novel master-slave robotic system with force feedback to assist intraocular surgeries. Isomorphism design was adopted to achieve intuitive control of the system. Contact force between instrument tip and tissues was measured with a force sensor developed by our group. Real-time force feedback was provided with one linear voice coil motor and two magnetic particle brakes in the master manipulator. RESULTS: Experiments were carried out to verify the proposed system. In the phantom experiment mimicking realistic surgical operations, the contact force significantly reduced by more than 30% with the force feedback when peeling the egg inner shell membranes. CONCLUSIONS: Experimental results demonstrate the effectiveness of force feedback and indicate the promise of the presented master-slave robotic system for intraocular surgery assistance.

Laparoscopic surgical device with modular end tools for real-time endomicroscopy and therapy.

In recent years, laparoscopic surgery attracts considerable attention for its distinct advantages owing to minimized invasiveness. However, traditional surgical instruments have a single function and lack the ability to provide high-resolution images for real-time tissue assessment. Thus, it remains a challenge to perform complex procedures with the traditional surgical instruments. In this paper, a novel laparoscopic surgical device for real-time endomicroscopy and therapy is proposed. The device is integrated with a visualization unit to provide endoscopic images in a constrained cavity for real-time observation. Moreover, modular end tools can be assembled and switched with the multi-DOF manipulator. The experimental results demonstrate that the surface-scanning tool can perform smooth scanning and obtain a large area mosaic of 6.99 mm2 in 40.2 s for tissue assessment. The spring-loaded forceps can generate an output force of 1.47 N to manipulate tissue. These experimental results demonstrate the potential value of the device for intraoperative endomicroscopy-guided surgery and robot-assisted surgery.

A dual-bending endoscope with shape-lockable hydraulic actuation and water-jet propulsion for gastrointestinal tract screening.

BACKGROUND: Traditional flexible endoscopes are sophisticated medical devices that require frequent and expensive maintenance. Therefore, their implementation within low-income and rural regions is challenging due to their high cost, complex sterilization process and poor portability. AIMS: This paper aims to develop an endoscopic platform that is low-cost, disposable and portable, with the primary goal of reducing gastric cancer-related mortality among low- and middle-income communities through wider access to regular screening programs. MATERIALS AND METHODS: The endoscope employs a custom microvalve to switch between hydraulic actuation of a spatial bending fluidic actuator and water-jet actuation. Three alloy wires with buckle attachments are connected to a pneumatic balloon which facilitates reversible shape-locking of the actuator, and thus supports stable scanning by water-jet actuation. Distal tip of the device has an internal charge-coupled device camera for inspection. RESULTS: Experiments demonstrated a 58% increase in the workspace after introduction of the water-jet and more than three times the load-locking ability variation. Phantom experiment was also conducted for performance comparison with a traditional endoscope. CONCLUSION: By controlling the pressure of supplied water and the inflation of locking balloon, the endoscope achieves a satisfactory workspace and a remarkable shape-locking ability, demonstrating its potential clinical value in improving the prospects for upper gastrointestinal tract disease screening, especially gastric cancer.

Robust Mosaicing of Endomicroscopic Videos via Context-Weighted Correlation Ratio.

Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pathological assessments. However, due to limited field of view, it is difficult for clinicians to get a full understanding of the scanned tissues. In this paper, we develop a novel mosaicing framework to assemble all frame sequences into a full view image. First, a hybrid rigid registration that combines feature matching and template matching is presented to achieve a global alignment of all frames. Then, the parametric free-form deformation (FFD) model with a multiresolution architecture is implemented to accommodate non-rigid tissue distortions. More importantly, we devise a robust similarity metric called context-weighted correlation ratio (CWCR) to promote registration accuracy, where spatial and geometric contexts are incorporated into the estimation of functional intensity dependence. Experiments on both robotic setup and manual manipulation have demonstrated that the proposed scheme significantly precedes some state-of-the-art mosaicing schemes in the presence of intensity fluctuations, insufficient overlap and tissue distortions. Moreover, the comparisons of the proposed CWCR metric and two other metrics have validated the effectiveness of the context-weighted strategy in quantifying the differences between two frames. Benefiting from more rational and delicate mosaics, the proposed scheme is more suitable to instruct diagnosis and treatment during optical biopsies.

Deep learning-based anatomical site classification for upper gastrointestinal endoscopy.

PURPOSE: Upper gastrointestinal (GI) endoscopic image documentation has provided an efficient, low-cost solution to address quality control for endoscopic reporting. The problem is, however, challenging for computer-assisted techniques, because different sites have similar appearances. Additionally, across different patients, site appearance variation may be large and inconsistent. Therefore, according to the British and modified Japanese guidelines, we propose a set of oesophagogastroduodenoscopy (EGD) images to be routinely captured and evaluate its efficiency for deep learning-based classification methods. METHODS: A novel EGD image dataset standardising upper GI endoscopy to several steps is established following landmarks proposed in guidelines and annotated by an expert clinician. To demonstrate the discrimination of proposed landmarks that enable the generation of an automated endoscopic report, we train several deep learning-based classification models utilising the well-annotated images. RESULTS: We report results for a clinical dataset composed of 211 patients (comprising a total of 3704 EGD images) acquired during routine upper GI endoscopic examinations. We find close agreement between predicted labels using our method and the ground truth labelled by human experts. We observe the limitation of current static image classification scheme for EGD image classification. CONCLUSION: Our study presents a framework for developing automated EGD reports using deep learning. We demonstrate that our method is feasible to address EGD image classification and can lead towards improved performance and additionally qualitatively demonstrate its performance on our dataset.