Deep learning for predicting circular retinal nerve fiber layer thickness from fundus photographs and diagnosing glaucoma.

Purpose: This study aimed to propose a new deep learning (DL) approach to automatically predict the retinal nerve fiber layer thickness (RNFLT) around optic disc regions in fundus photography trained by optical coherence tomography (OCT) and diagnose glaucoma based on the predicted comprehensive information about RNFLT.

Methods: A total of 1403 pairs of fundus photographs and OCT RNFLT scans from 1403 eyes of 1196 participants were included. A residual deep neural network was trained to predict the RNFLT for each local image in a fundus photograph, and then a RNFLT report was generated based on the local images.

A Dual-Modal Fusion Network Using Optical Coherence Tomography and Fundus Images in Detection of Glaucomatous Optic Neuropathy.

Purpose: We designed a dual-modal fusion network to detect glaucomatous optic neuropathy, which utilized both retinal nerve fiber layer thickness from optical coherence tomography reports and fundus images.

Methods: A total of 327 healthy subjects (410 eyes) and 87 glaucomatous optic neuropathy patients (113 eyes) were included. The retinal nerve fiber layer thickness from optical coherence tomography reports and fundus images were used as predictors in the dual-modal fusion network to diagnose glaucoma.

Learning Rates of Deep Nets for Geometrically Strongly Mixing Sequence.

The great success of deep learning poses an urgent challenge to establish the theoretical basis for its working mechanism. Recently, research on the convergence of deep neural networks (DNNs) has made great progress. However, the existing studies are based on the assumption that the samples are independent, which is too strong to be applied to many real-world scenarios.

Nano-NdO reduced soil bacterial community function by altering the relative abundance of rare and sensitive taxa.

Nanoparticulate-NdO (nano-NdO) has been excessively utilized in agriculture, industry, and medicine. Hence, nano-NdO can have environmental implications. However, the impact of nano-NdO on alpha diversity, composition, and function of soil bacterial communities has not been thoroughly evaluated.

Clinical, histological and molecular characteristics of Alport syndrome in Chinese children.

Background: Alport syndrome is caused by COL4A3, COL4A4, or COL4A5 gene mutations. The present study aims to compare the clinicopathological features, gene mutations, and outcome of Chinese children with different forms of Alport syndrome.

Methods: One hundred twenty-eight children from 126 families diagnosed with Alport syndrome through pathological and genetic examination between 2003 and 2021 were included in this single-center retrospective study.

Integrated bioinformatics and approaches reveal the biological targets and molecular mechanisms of 1,25-dihydroxyvitamin D against COVID-19 and diabetes mellitus.

Coronavirus disease 2019 (COVID-19) and diabetes mellitus (DM) are two major diseases threatening human health. The susceptibility of DM patients to COVID-19 and their worse outcomes have forced us to explore efficient routes to combat COVID-19/DM. As the most active form of Vitamin D, 1,25-dihydroxyvitamin D (1,25(OH)D) has been shown a beneficial effect in the treatment of COVID-19/DM.

Outcomes of Microcatheter-Assisted Trabeculotomy for Glaucoma Associated With Sturge-Weber Syndrome and Phakomatosis Pigmentovascularis.

Purpose: To evaluate mid-term efficacy and safety of ab externo Microcatheter-assisted trabeculotomy (MAT) for early-onset glaucoma associated with Sturge-Weber syndrome (SWS) and phakomatosis pigmentovascularis (PPV).

Design: Retrospective, non-comparative, interventional case series.

Methods: Medical records of consecutive SWS- or PPV-associated glaucoma patients who had undergone ab externo MAT between August 2017 and April 2020 at Beijing Children's Hospital were reviewed.

Practical Application of Artificial Intelligence Technology in Glaucoma Diagnosis.

Purpose: By comparing the performance of different models between artificial intelligence (AI) and doctors, we aim to evaluate and identify the optimal model for future usage of AI.

Methods: A total of 500 fundus images of glaucoma and 500 fundus images of normal eyes were collected and randomly divided into five groups, with each group corresponding to one round. The AI system provided diagnostic suggestions for each image.

The Hematopoietic Function of Medicinal Wine Maoji Jiu Revealed in Blood Deficiency Model Rats.

Maoji Jiu (MJ), a medicinal wine, has been used commonly by the Chinese to enrich and nourish the blood. In this study, the aim is to examine the hematopoietic function of MJ and investigate its hematopoietic regulation mechanism. Thirty-six female Sprague-Dawley rats (200 ± 20 g) were randomly divided into six groups with six rats in each group.

Compared With Girls, Boys' Psychological Symptoms Are More Likely to Be Influenced by Lifestyle in Chinese Middle School Students.

Purpose: To explore the relationship between Chinese middle school students' lifestyles and psychological symptoms and compare the differences between genders.

Method: Using the method of stratified cluster sampling, 14,356 students aged 13-18 years from 8 cities in China were selected as participants. The Multidimensional Sub-health Questionnaire of Adolescents was used to estimate psychological symptoms.

Metabonomics Study of the Hematopoietic Effect of Medicinal Wine Maoji Jiu on a Blood Deficiency Rat Model by Ultra-High-Performance Liquid Chromatography Coupled to Quadrupole Time-of-Flight Mass Spectrometry and a Pattern Recognition Approach.

Maoji Jiu (MJ) is a kind of medicinal wine that has been widely used by Chinese people for many years to nourish and promote blood circulation. The purpose of this study was to investigate the hematopoietic effect of MJ on the metabolism of blood deficient rats and to explore the underlying hematopoietic regulation mechanisms. Blood deficiency model rats were induced by subcutaneous injection of N-acetylphenylhydrazine (APH) and intraperitoneal injection of cyclophosphamide (CTX).

Preparation, Characterization, and Performance Evaluation of Petroleum Asphalt Modified with Bio-Asphalt Containing Furfural Residue and Waste Cooking Oil.

The study aims to analyze the feasibility of proposing waste cooking oil and industrial waste furfural residue as raw materials to prepare bio-asphalt as partial substitutes for petroleum asphalt, so as to reduce the cost of pavement construction and decrease the consumption of non-renewable resources. In this study, 90# petroleum asphalt was partially substituted with the bio-asphalt in different proportions to prepare biomass-modified petroleum asphalt, the performance of which was first evaluated based on three indices: penetration, softening point, and ductility. Comparison of the crystal structures of the bio-asphalt and furfural residue were enabled by X-ray diffraction, and the blending mechanism and microscopic morphologies of the biomass-substituted asphalt mixtures were characterized by Fourier transform infrared spectroscopy and scanning electron microscopy.

Clinical and Renal Histology Findings and Different Responses to Induction Treatment Affecting the Long-Term Renal Outcomes of Children With ANCA-Associated Vasculitis: a Single-Center Cohort Analysis.

Introduction: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is relatively rare in children. This article aimed to analyze clinical and renal histology findings and different responses to induction treatment associated with the long-term renal outcomes in children with AAV in a single center.

Methods: All pediatric patients with AAV admitted to Tongji Hospital from January 2002 to January 2021 were included in the study.

SMRT sequencing of the full-length transcriptome of Gekko gecko.

Tokay Gecko (Gekko gecko) is a rare and endangered medicinal animal in China. Its dry body has been used as an anti-asthmatic agent for two thousand years. To date, the genome and transcriptome of this species remain poorly understood.

A hierarchical deep learning approach with transparency and interpretability based on small samples for glaucoma diagnosis.

The application of deep learning algorithms for medical diagnosis in the real world faces challenges with transparency and interpretability. The labeling of large-scale samples leads to costly investment in developing deep learning algorithms. The application of human prior knowledge is an effective way to solve these problems.

REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs.

Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders. However, its application to glaucoma has been limited to the computation of a few related biomarkers such as the vertical cup-to-disc ratio.

Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples.

Glaucoma is a serious eye disease that can cause permanent blindness and is difficult to diagnose early. Optic disc (OD) and optic cup (OC) play a pivotal role in the screening of glaucoma. Therefore, accurate segmentation of OD and OC from fundus images is a key task in the automatic screening of glaucoma.

Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

Importance: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.

Objective: To establish a DLS for detection of GON using retinal fundus images and glaucoma diagnosis with convoluted neural networks (GD-CNN) that has the ability to be generalized across populations.

Design, Setting, And Participants: In this cross-sectional study, a DLS for the classification of GON was developed for automated classification of GON using retinal fundus images obtained from the Chinese Glaucoma Study Alliance, the Handan Eye Study, and online databases.

Anti-Diabetic Effect of a Shihunine-Rich Extract of on 3T3-L1 Cells and db/db Mice by Up-Regulating AMPK-GLUT4-PPARα.

The stems of , a Chinese herb, are often used to treat diabetes and its polar extract is rich in shihunine, a water-soluble alkaloid, but little is known about the anti-diabetes effects and mechanism of shihunine. This study investigated the anti-diabetic effect of a shihunine-rich extract of (DLS) based on 3T3-L1 cells and db/db mice. The underlying mechanisms were primarily explored using Western blot analysis and immunohistochemical staining.

Microcatheter-assisted Trabeculotomy for Primary Congenital Glaucoma After Failed Glaucoma Surgeries.

Purpose: To evaluate the effectiveness of microcatheter-assisted trabeculotomy (MAT) to treat primary congenital glaucoma after failed previous glaucoma surgeries.

Materials And Methods: Retrospective, noncomparative, interventional case series conducted at Beijing Tongren Eye Center, China. Outcome measures were compared between 3 groups: successful and complete (≥330 degrees) MAT; successful and partial (<330 degrees) MAT; or cases converted to traditional trabeculotomy when the Schlemm's canal could not be catheterized >180 degrees.

Learning Rates of Regularized Regression With Multiple Gaussian Kernels for Multi-Task Learning.

This paper considers a least square regularized regression algorithm for multi-task learning in a union of reproducing kernel Hilbert spaces (RKHSs) with Gaussian kernels. It is assumed that the optimal prediction function of the target task and those of related tasks are in an RKHS with the same but with unknown Gaussian kernel width. The samples for related tasks are used to select the Gaussian kernel width, and the sample for the target task is used to obtain the prediction function in the RKHS with this selected width.

Geographic variation in body size and its relationship with environmental gradients in the Oriental Garden Lizard, .

Patterns of geographic variation in body size are predicted to evolve as adaptations to local environmental gradients. However, many of these clinal patterns in body size, such as Bergmann's rule, are controversial and require further investigation into ectotherms such as reptiles on a regional scale. To examine the environmental variables (temperature, precipitation, topography and primary productivity) that shaped patterns of geographic variation in body size in the reptile , we sampled 180 adult specimens (91 males and 89 females) at 40 locations across the species range in China.