Metabolomics with gut microbiota analysis of podophyllotoxin-mediated cardiotoxicity in mice based on the toxicological evidence chain (TEC) concept.

Podophyllotoxin (PPT) is a lignan isolated from the traditional Chinese medicine Dysosma Versipellis, with significant anti-tumor activity. However, its cardiotoxicity restricts its clinical application. This study aims to investigate the cardiotoxicity of PPT in mice and its underlying mechanisms based on the concept of toxicological evidence chain (TEC).

On-site burn severity assessment using smartphone-captured color burn wound images.

Accurate assessment of burn severity is crucial for the management of burn injuries. Currently, clinicians mainly rely on visual inspection to assess burns, characterized by notable inter-observer discrepancies. In this study, we introduce an innovative analysis platform using color burn wound images for automatic burn severity assessment.

CellVisioner: A Generalizable Cell Virtual Staining Toolbox based on Few-Shot Transfer Learning for Mechanobiological Analysis.

Visualizing cellular structures especially the cytoskeleton and the nucleus is crucial for understanding mechanobiology, but traditional fluorescence staining has inherent limitations such as phototoxicity and photobleaching. Virtual staining techniques provide an alternative approach to addressing these issues but often require substantial amount of user training data. In this study, we develop a generalizable cell virtual staining toolbox (termed CellVisioner) based on few-shot transfer learning that requires substantially reduced user training data.

Non-invasive medical imaging technology for the diagnosis of burn depth.

Currently, the clinical diagnosis of burn depth primarily relies on physicians' judgements based on patients' symptoms and physical signs, particularly the morphological characteristics of the wound. This method highly depends on individual doctors' clinical experience, proving challenging for less experienced or primary care physicians, with results often varying from one practitioner to another. Therefore, scholars have been exploring an objective and quantitative auxiliary examination technique to enhance the accuracy and consistency of burn depth diagnosis.

Comprehensive retinal vascular measurements: time in range is associated with peripheral retinal venular calibers in type 2 diabetes in China.

Aim: Retinal vascular parameters are biomarkers of diabetic microangiopathy. We aimed to investigate the relationship between time in range (TIR) assessed by continuous glucose monitoring (CGM) and retinal vascular parameters in patients with type 2 diabetes in China.

Methods: The TIR assessed by CGM and retinal photographs were obtained at the same time from adults with type 2 diabetes who were recruited.

Joint conditional generative adversarial networks for eyelash artifact removal in ultra-wide-field fundus images.

Ultra-Wide-Field (UWF) fundus imaging is an essential diagnostic tool for identifying ophthalmologic diseases, as it captures detailed retinal structures within a wider field of view (FOV). However, the presence of eyelashes along the edge of the eyelids can cast shadows and obscure the view of fundus imaging, which hinders reliable interpretation and subsequent screening of fundus diseases. Despite its limitations, there are currently no effective methods or datasets available for removing eyelash artifacts from UWF fundus images.

AV-casNet: Fully Automatic Arteriole-Venule Segmentation and Differentiation in OCT Angiography.

Automatic segmentation and differentiation of retinal arteriole and venule (AV), defined as small blood vessels directly before and after the capillary plexus, are of great importance for the diagnosis of various eye diseases and systemic diseases, such as diabetic retinopathy, hypertension, and cardiovascular diseases. Optical coherence tomography angiography (OCTA) is a recent imaging modality that provides capillary-level blood flow information. However, OCTA does not have the colorimetric and geometric differences between AV as the fundus photography does.

Similar color analysis based on deep learning (SCAD) for multiplex digital PCR a single fluorescent channel.

Digital PCR (dPCR) has recently attracted great interest due to its high sensitivity and accuracy. However, the existing dPCR depends on multicolor fluorescent dyes and multiple fluorescent channels to achieve multiplex detection, resulting in increased detection cost and limited detection throughput. Here, we developed a deep learning-based similar color analysis method, namely SCAD, to achieve multiplex dPCR in a single fluorescent channel.

Anomaly segmentation in retinal images with poisson-blending data augmentation.

Diabetic retinopathy (DR) is one of the most important complications of diabetes. Accurate segmentation of DR lesions is of great importance for the early diagnosis of DR. However, simultaneous segmentation of multi-type DR lesions is technically challenging because of 1) the lack of pixel-level annotations and 2) the large diversity between different types of DR lesions.

Multi-Scale Pathological Fluid Segmentation in OCT With a Novel Curvature Loss in Convolutional Neural Network.

The segmentation of pathological fluid lesions in optical coherence tomography (OCT), including intraretinal fluid, subretinal fluid, and pigment epithelial detachment, is of great importance for the diagnosis and treatment of various eye diseases such as neovascular age-related macular degeneration and diabetic macular edema. Although significant progress has been achieved with the rapid development of fully convolutional neural networks (FCN) in recent years, some important issues remain unsolved. First, pathological fluid lesions in OCT show large variations in location, size, and shape, imposing challenges on the design of FCN architecture.

Deep level set method for optic disc and cup segmentation on fundus images.

Glaucoma is a leading cause of blindness. The measurement of vertical cup-to-disc ratio combined with other clinical features is one of the methods used to screen glaucoma. In this paper, we propose a deep level set method to implement the segmentation of optic cup (OC) and optic disc (OD).

Correlation between retinal vascular parameters and cystatin C in patients with type 2 diabetes.

Aims: To investigate the relationship between retinal vascular parameters and cystatin C in patients with type 2 diabetes in northwestern China.

Methods: This was a cross-sectional study of 1689 patients with type 2 diabetes. A validated fully automated computer program was used to extract retinal vascular parameters from the entire vascular tree.

Dilated retinal large vessels and capillaries associated with diabetic macular edema and photoreceptor loss respectively.

Purpose: Previously, we measured retinal large vessels and capillaries separately on optical coherence tomography angiography (OCTA). In the present study, we aim to evaluate the role of these parameters in association to diabetic macular edema (DME) and ellipsoid zone disruption (EZD).

Methods: In this cross-sectional study, 54 eyes from 31 patients (10 females, 31 Asians) with severe non-proliferative diabetic retinopathy (25 eyes) or proliferative diabetic retinopathy (PDR, 29 eyes) were enrolled.

MiR-16-5p suppresses myofibroblast activation in systemic sclerosis by inhibiting NOTCH signaling.

Systemic sclerosis (SSc) is a prototypic fibrotic disease characterized by localized or diffuse skin thickening and fibrosis. Tissue fibrosis is driven by myofibroblasts, and factors affecting myofibroblast activation may also be involved in the development of SSc. In this study, we examined molecular mechanisms underlying SSc by focusing on myofibroblast activation processes.

Resveratrol Ameliorates Systemic Sclerosis via Suppression of Fibrosis and Inflammation Through Activation of SIRT1/mTOR Signaling.

Purpose: Resveratrol (Res) is a natural polyphenolic compound found in several plants and reported as a promising biological molecule with effective anti-fibrosis and anti-inflammatory activities. However, the underlying mechanism of Res on systemic sclerosis (SSc) remains unclear. In the study, we identified the key cellular signaling pathways involved in the Res regulatory process on SSc.

Retinal image measurements and their association with chronic kidney disease in Chinese patients with type 2 diabetes: the NCD study.

Aims: Retinal and renal microcirculations are known to share similar physiological changes during early diabetes because of abnormal glucose metabolism and other processes. The retinal vasculature therefore may serve as potential biomarker for the early identification of those at high risk of chronic kidney disease (CKD) in diabetes.

Methods: Data from 1925 patients (aged 49.

Comprehensive retinal vascular measurements: a novel association with renal function in type 2 diabetic patients in China.

To examine the association between various retinal vascular measurements and microalbuminuria in patients with type 2 diabetes in a northwestern China study. Data from 911 patients with type 2 diabetes were analyzed. Novel retinal vascular measurements from the whole vascular tree were extracted using a validated fully automatic computer program.

Graph convolutional network based optic disc and cup segmentation on fundus images.

Calculating the cup-to-disc ratio is one of the methods for glaucoma screening with other clinical features. In this paper, we propose a graph convolutional network (GCN) based method to implement the optic disc (OD) and optic cup (OC) segmentation task. We first present a multi-scale convolutional neural network (CNN) as the feature map extractor to generate feature map.

Automated quantification of superficial retinal capillaries and large vessels for diabetic retinopathy on optical coherence tomographic angiography.

Optical coherence tomography angiography (OCTA) is a relatively new technique with capillary-level resolution, which has shown great potential for the diagnosis of diabetic retinopathy (DR). A fully automatic algorithm for the quantitative measurement of microcirculatory changes in sight-threatening DR is presented. The foveal avascular zone (FAZ) segmentation was improved with a graph-theoretic method and the large vessels and capillaries were separately identified and analyzed.

Influence of Axial Length on Parafoveal and Peripapillary Metrics from Swept Source Optical Coherence Tomography Angiography.

To assess the effect of axial length (AL) on the quantification of superficial vessel density of both macular and disc region using swept source optical coherence tomography angiography (SSOCTA). This is a cross-sectional clinical study. Seventy-five eyes from 75 Chinese healthy participants (56 females) with a mean age of 26.

A smartphone-based on-site nucleic acid testing platform at point-of-care settings.

We developed a smartphone-based on-site nucleic acid testing (NAT) platform that can image and analyze lateral flow nucleic acid assays at point-of-care settings. An inexpensive add-on was devised to run lateral flow assays while providing homogeneous ambient light for imaging. In addition, an Android app with a user-friendly interface was developed for the result analysis and management.

Eriodictyol inhibits high glucose-induced oxidative stress and inflammation in retinal ganglial cells.

Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes mellitus and is considered as a leading cause of blindness. Oxidative stress and inflammation are significant drivers for the development of DR. Eriodictyol, a flavonoid compound, was proved to possess anti-inflammatory, antioxidative, and antidiabetic activities.

Simultaneous arteriole and venule segmentation with domain-specific loss function on a new public database.

The segmentation and classification of retinal arterioles and venules play an important role in the diagnosis of various eye diseases and systemic diseases. The major challenges include complicated vessel structure, inhomogeneous illumination, and large background variation across subjects. In this study, we employ a fully convolutional network to simultaneously segment arterioles and venules directly from the retinal image, rather than using a vessel segmentation-arteriovenous classification strategy as reported in most literature.