Dynamic changes of choroidal vasculature and its association with myopia control efficacy in children during 1-year orthokeratology treatment.

PURPOSE: To investigate the dynamic changes of choroidal vasculature and its association in mediating ocular elongation over 1 year of orthokeratology (ortho-k) treatment. METHODS: This observational study included 8-14 year old myopic children who were willing to receive ortho-k treatment or wear single vision spectacle lenses (SVL). Axial length (AL) and choroidal characteristics, including submacular luminal area (LA), stromal area (SA), total choroidal area (TCA), choroidal vascularity index (CVI), subfoveal choroidal thickness (SFCT) and choriocapillaris flow deficits (CcFD) from OCT/OCTA images, were evaluated at baseline, 3, 6 and 12 months. RESULTS: After 1 year, AL elongation was significantly less in 25 children treated with ortho-k than in 29 children wearing SVL (0.17 ± 0.14 v.s. 0.28 ± 0.16 mm, P<0.01). In the ortho-k group, LA, SA, TCA and SFCT were significantly increased by 0.033 ± 0.059 mm2, 0.024 ± 0.035 mm2, 0.058 ± 0.087 mm2, 8.9 ± 17.4 µm, respectively, at 3 months (all P<0.05). These parameters returned to near baseline levels over the following 9 months. Meanwhile, CcFD decreased by 0.83 ± 1.09 % over 12 months, but CVI remained steady during this period. No significant changes in these choroidal parameters (except for CcFD, decreased by -0.56 ± 1.23 %) were observed in the SVL group over 12 months. Increases in SFCT, LA, SA and TCA over 12 months were significantly greater in the ortho-k group than in the SVL group. Mediation analyses showed that 44.8 % of effect on inhibiting AL elongation through ortho-k was mediated via TCA (in particular LA). CONCLUSIONS: The decelerated ocular elongation during ortho-k treatment is accompanied by increases in content of choroidal vascular lumen and stromal component. Dynamic changes of choroidal vasculature provide a possible mechanism underlying myopia control efficacy via ortho-k.

Prediction of Human Microbe-Drug Association based on Layer Attention Graph Convolutional Network.

Human microbes are closely associated with a variety of complex diseases and have emerged as drug targets. Identification of microbe-related drugs is becoming a key issue in drug development and precision medicine. It can also provide guidance for solving the increasingly serious problem of drug resistance enhancement in viruses. METHODS: In this paper, we have proposed a novel model of layer attention graph convolutional network for microbe-drug association prediction. First, multiple biological data have been integrated into a heterogeneous network. Then, the heterogeneous network has been incorporated into a graph convolutional network to determine the embedded microbe and drug. Finally, the microbe-drug association scores have been obtained by decoding the embedding of microbe and drug based on the layer attention mechanism. RESULTS: To evaluate the performance of our proposed model, leave-one-out crossvalidation (LOOCV) and 5-fold cross-validation have been implemented on the two datasets of aBiofilm and MDAD. As a result, based on the aBiofilm dataset, our proposed model has attained areas under the curve (AUC) of 0.9178 and 0.9022 on global LOOCV and local LOOCV, respectively. Based on aBiofilm dataset, the proposed model has attained an AUC value of 0.9018 and 0.8902 on global LOOCV and local LOOCV, respectively. In addition, the average AUC and standard deviation of the proposed model for 5- fold cross-validation on the aBiofilm and MDAD datasets were 0.9141±6.8556e-04 and 0.8982±7.5868e-04, respectively. Also, two kinds of case studies have been further conducted to evaluate the proposed models. CONCLUSION: Traditional methods for microbe-drug association prediction are timeconsuming and laborious. Therefore, the computational model proposed was used to predict new microbe-drug associations. Several evaluation results have shown the proposed model to achieve satisfactory results and that it can play a role in drug development and precision medicine.

Short-term choroidal changes as early indicators for future myopic shift in primary school children: results of a 2-year cohort study.

BACKGROUND: To assess predictive value of short-term choroidal changes for future myopic shift in children. METHODS: 577 eyes of 289 primary school children were prospectively followed for 2 years. Cycloplegic refractions at baseline, 1 year and 2 years, and choroidal measurements by optical coherence tomography at baseline and 3 months, were used for analyses. Myopic shift was defined as refraction change of at least -0.50 dioptre/year, at 2 years compared with baseline. RESULTS: 228 participants (455 eyes) completed 2-year follow-up. Approximately 37.6% of 311 initially non-myopic eyes and 73.6% of 144 initially myopic eyes developed a myopic shift. Notably, at 3 months greater reductions were found in initially myopic eyes with myopic shift, than in those without myopic shift-in choroidal thickness (ChT), luminal area (LA), stromal area (SA) and total choroidal area (TCA), but no significant differences in any choroidal parameters were observed between non-myopic eyes, with and without myopic shift. Multivariable analyses showed that in myopic eyes, each percentage increase in ChT, LA, SA and TCA was associated with reduced odds of myopic shift (all p<0.001). Similar associations were observed in non-myopic eyes, with smaller effects than in myopic eyes. Adding a 3-month percentage change of each choroidal parameter to a basic model including age, gender, parental myopia and baseline refraction significantly improved the predictive performance in myopic eyes (area under the receiver operating characteristic curves increasing from 0.650 to approximately 0.800, all p<0.05), but not in non-myopic eyes. CONCLUSION: Short-term choroidal changes could act as early indicators for future myopic shift in children.

Causal Relationships Between Retinal Diseases and Psychiatric Disorders Have Implications for Precision Psychiatry.

Observational studies and clinical trials have reported potential associations between retinal diseases and psychiatric disorders. However, the causal associations between them have remained elusive. In this study, we used bi-directional two-sample Mendelian randomization (MR) analysis to explore unconfounded causal relationships between retinal diseases and psychiatric disorders using large-scale genome-wide association study (GWAS) summary statistics of over 500,000 participants of European ancestry from the FinnGen project, the Psychiatric Genomics Consortium, the European Bioinformatics Institute, and the UK Biobank. Our MR analysis revealed significant causal relationships between major retinal diseases and specific psychiatric disorders. Specifically, susceptibility to dry age-related macular degeneration was associated with a reduced risk of anorexia nervosa (OR = 0.970; 95% CI = 0.930 ~ 0.994; P = 0.025). Furthermore, we found some evidence that exposure to diabetic retinopathy was associated with an increased risk of schizophrenia (OR = 1.021; 95% CI 1.012 ~ 1.049; P = 0.001), and exposure to retinal detachments and breaks was associated with an increased risk of attention deficit hyperactivity disorder (OR = 1.190; 95% CI 1.063 ~ 1.333; P = 0.003). These causal relationships were not confounded by biases of pleiotropy and reverse causation. Our study highlights the importance of preventing and managing retinal disease as a potential avenue for improving the prevention, management and treatment of major psychiatric disorders.

Identification of Shaker Potassium Channel Family Members and Functional Characterization of SsKAT1.1 in Stenotaphrum secundatum Suggest That SsKAT1.1 Contributes to Cold Resistance.

Stenotaphrum secundatum is an excellent shade-tolerant warm-season turfgrass. Its poor cold resistance severely limits its promotion and application in temperate regions. Mining cold resistance genes is highly important for the cultivation of cold-resistant Stenotaphrum secundatum. Although there have been many reports on the role of the Shaker potassium channel family under abiotic stress, such as drought and salt stress, there is still a lack of research on their role in cold resistance. In this study, the transcriptome database of Stenotaphrum secundatum was aligned with the whole genome of Setaria italica, and eight members of the Shaker potassium channel family in Stenotaphrum secundatum were identified and named SsKAT1.1, SsKAT1.2, SsKAT2.1, SsKAT2.2, SsAKT1.1, SsAKT2.1, SsAKT2.2, and SsKOR1. The KAT3-like gene, KOR2 homologous gene, and part of the AKT-type weakly inwardly rectifying channel have not been identified in the Stenotaphrum secundatum transcriptome database. A bioinformatics analysis revealed that the potassium channels of Stenotaphrum secundatum are highly conserved in terms of protein structure but have more homologous members in the same group than those of other species. Among the three species of Oryza sativa, Arabidopsis thaliana, and Setaria italica, the potassium channel of Stenotaphrum secundatum is more closely related to the potassium channel of Setaria italica, which is consistent with the taxonomic results of these species belonging to Paniceae. Subcellular location experiments demonstrate that SsKAT1.1 is a plasma membrane protein. The expression of SsKAT1.1 reversed the growth defect of the potassium absorption-deficient yeast strain R5421 under a low potassium supply, indicating that SsKAT1.1 is a functional potassium channel. The transformation of SsKAT1.1 into the cold-sensitive yeast strain INVSC1 increased the cold resistance of the yeast, indicating that SsKAT1.1 confers cold resistance. The transformation of SsKAT1.1 into the salt-sensitive yeast strain G19 increased the resistance of yeast to salt, indicating that SsKAT1.1 is involved in salt tolerance. These results suggest that the manipulation of SsKAT1.1 will improve the cold and salt stress resistance of Stenotaphrum secundatum.

Concepts and applications of digital twins in healthcare and medicine.

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.

40 Hz light flickering facilitates the glymphatic flow via adenosine signaling in mice.

The glymphatic-lymphatic system is increasingly recognized as fundamental for the homeostasis of the brain milieu since it defines cerebral spinal fluid flow in the brain parenchyma and eliminates metabolic waste. Animal and human studies have uncovered several important physiological factors regulating the glymphatic system including sleep, aquaporin-4, and hemodynamic factors. Yet, our understanding of the modulation of the glymphatic system is limited, which has hindered the development of glymphatic-based treatment for aging and neurodegenerative disorders. Here, we present the evidence from fluorescence tracing, two-photon recording, and dynamic contrast-enhanced magnetic resonance imaging analyses that 40 Hz light flickering enhanced glymphatic influx and efflux independently of anesthesia and sleep, an effect attributed to increased astrocytic aquaporin-4 polarization and enhanced vasomotion. Adenosine-A2A receptor (A2AR) signaling emerged as the neurochemical underpinning of 40 Hz flickering-induced enhancement of glymphatic flow, based on increased cerebrofluid adenosine levels, the abolishment of enhanced glymphatic flow by pharmacological or genetic inactivation of equilibrative nucleotide transporters-2 or of A2AR, and by the physical and functional A2AR-aquaporin-4 interaction in astrocytes. These findings establish 40 Hz light flickering as a novel non-invasive strategy of enhanced glymphatic flow, with translational potential to relieve brain disorders.

Exome-wide association study identifies KDELR3 mutations in extreme myopia.

Extreme myopia (EM), defined as a spherical equivalent (SE) ≤ -10.00 diopters (D), is one of the leading causes of sight impairment. Known EM-associated variants only explain limited risk and are inadequate for clinical decision-making. To discover risk genes, we performed a whole-exome sequencing (WES) on 449 EM individuals and 9606 controls. We find a significant excess of rare protein-truncating variants (PTVs) in EM cases, enriched in the retrograde vesicle-mediated transport pathway. Employing single-cell RNA-sequencing (scRNA-seq) and a single-cell polygenic burden score (scPBS), we pinpointed PI16 + /SFRP4+ fibroblasts as the most relevant cell type. We observed that KDELR3 is highly expressed in scleral fibroblast and involved in scleral extracellular matrix (ECM) organization. The zebrafish model revealed that kdelr3 downregulation leads to elongated ocular axial length and increased lens diameter. Together, our study provides insight into the genetics of EM in humans and highlights KDELR3's role in EM pathogenesis.

Effect of anionic groups in zwitterionic hydrophilic stationary phases on their chromatographic characteristics.

The structure of zwitterion has great impact on the separation properties of zwitterionic hydrophilic stationary phases. To better understand the role of anionic groups of zwitterions, a novel carboxybetaine-based zwitterionic monolithic column was first prepared through thermo-initiated copolymerization of functional monomer (3-acrylamidopropyl)-dimethyl-(2-carboxymethyl) ammonium (CBAA) and crosslinker ethylene dimethacrylate (EDMA) within 100 µm ID capillary. The optimal poly(CBAA-co-EDMA) monolithic column exhibited satisfactory mechanical and chemical stability, good repeatability, high column efficiency (96,000 plates/m), and excellent separation performance for different classes of polar compounds (i.e., phenols, monophosphate nucleotides, urea and allantoin). A comparative study was then performed among three zwitterionic hydrophilic stationary phases containing different anionic groups, i.e. poly(CBAA-co-EDMA) (carboxybetaine), poly(2-{2-(methacryloyloxy) ethyldimethylammonium}ethyl n-butyl phosphate-co-EDMA) (phosphocholine), and poly(N,N-dimethyl-N-(3-methacrylamidopropyl)-N-(3-sulfopropyl) ammonium betaine-co-EDMA) (sulfobetaine) using benzoic acid derivatives, amine compounds, nucleobases and nucleosides as model analytes. The carboxybetaine-based monolithic column exhibited much higher positive zeta-potential and hydrophilicity, which endows it with a stronger retention capacity for acidic and neutral compounds, but sulfobetaine-based monolithic column exhibited much higher selectivity and retention capacity for the amines. Moreover, their enrichment efficiencies for N-glycopeptides were also evaluated based on their different hydrophilicity, and it was observed that the poly(CBAA-co-EDMA) monolithic material captured 4-8 times more N-glycopeptides compared to the other two materials.

Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction.

Increasing research has shown that the abnormal expression of microRNA (miRNA) is associated with many complex diseases. However, biological experiments have many limitations in identifying the potential disease-miRNA associations. Therefore, we developed a computational model of Three-Layer Heterogeneous Network based on the Integration of CircRNA information for MiRNA-Disease Association prediction (TLHNICMDA). In the model, a disease-miRNA-circRNA heterogeneous network is built by known disease-miRNA associations, known miRNA-circRNA interactions, disease similarity, miRNA similarity, and circRNA similarity. Then, the potential disease-miRNA associations are identified by an update algorithm based on the global network. Finally, based on global and local leave-one-out cross validation (LOOCV), the values of AUCs in TLHNICMDA are 0.8795 and 0.7774. Moreover, the mean and standard deviation of AUC in 5-fold cross-validations is 0.8777+/-0.0010. Especially, the two types of case studies illustrated the usefulness of TLHNICMDA in predicting disease-miRNA interactions.