BMX deletion mitigates neuroinflammation induced by retinal ischemia/reperfusion through modulation of the AKT/ERK/STAT3 signaling cascade.

Aims: Retinal ischemia/reperfusion (I/R) injury is implicated in the etiology of various ocular disorders. Prior research has demonstrated that bone marrow tyrosine kinase on chromosome X (BMX) contributes to the advancement of ischemic disease and inflammatory reactions. Consequently, the current investigation aims to evaluate BMX's impact on retinal I/R injury and clarify its implied mechanism of action. Main methods: This study utilized male and female systemic BMX knockout (BMX-/-) mice to conduct experiments. The utilization of Western blot assay and immunofluorescence labeling techniques was employed to investigate variations in the expression of protein and tissue localization. Histomorphological changes were observed through H&E staining and SD-OCT examination. Visual function changes were assessed through electrophysiological experiments. Furthermore, apoptosis in the retina was identified using the TUNEL assay, as well as the ELISA technique, which has been utilized to determine the inflammatory factors level. Key findings: Our investigation results revealed that the knockdown of BMX did not yield a significant effect on mouse retina. In mice, BMX knockdown mitigated the negative impact of I/R injury on retinal tissue structure and visual function. BMX knockdown effectively reduced apoptosis, suppressed inflammatory responses, and decreased inflammatory factors subsequent to I/R injury. The outcomes of the current investigation revealed that BMX knockdown partially protected the retina through downregulating phosphorylation of AKT/ERK/STAT3 pathway. Significance: Our investigation showed that BMX-/- reduces AKT, ERK, and STAT3 phosphorylation, reducing apoptosis and inflammation. Thus, this strategy protected the retina from structural and functional damage after I/R injury.

Diabetic retinopathy related homeostatic dysregulation and its association with mortality among diabetes patients: A cohort study from NHANES.

AIMS: To develop a metric termed the diabetic retinopathy-related homeostatic dysregulation (DRHD) value, and estimate its association with future risk of mortality in individuals with type 2 diabetes. METHODS: With the data of the NHANES, the biomarkers associated with DR were identified from 40 clinical parameters using LASSO regression. Subsequently, the DRHD value was constructed utilizing the Mahalanobis distance approach. In the retrospective cohortof 6420 type 2 diabetes patients, we estimated the associations between DRHD values and mortality related to all-cause, cardiovascular disease (CVD) and diabetes-specific causes using Cox proportional hazards regression models. RESULTS: A set of 14 biomarkers associated with DR was identified for the construction of DRHD value. During an average of 8 years of follow-up, the multivariable-adjusted HRs and corresponding 95 % CIs for the highest quartiles of DRHD values were 2.04 (1.76, 2.37), 2.32 (1.78, 3.01), and 2.29 (1.72, 3.04) for all-cause, CVD and diabetes-specific mortality, respectively. Furthermore, we developed a web-based calculator for the DRHD value to enhance its accessibility and usability (https://dzwxl-drhd.streamlit.app/). CONCLUSIONS: Our study constructed the DRHD value as a measure to assess homeostatic dysregulation among individuals with type 2 diabetes. The DRHD values exhibited potential as a prognostic indicator for retinopathy and for mortality in patients affected by type 2 diabetes.

Association of glyphosate exposure with multiple adverse outcomes and potential mediators.

Glyphosate (GLY) is a widely used herbicide with potential adverse effects on public health. However, the current epidemiological evidence is limited. This study aimed to investigate the potential associations between exposure to GLY and multiple health outcomes. The data on urine GLY concentration and nine health outcomes, including type 2 diabetes mellitus (T2DM), hypertension, cardiovascular disease (CVD), obesity, chronic kidney disease (CKD), hepatic steatosis, cancers, chronic obstructive pulmonary disease (COPD), and neurodegenerative diseases (NGDs), were extracted from NHANES (2013-2016). The associations between GLY exposure and each health outcome were estimated using reverse-scale Cox regression and logistic regression. Furthermore, mediation analysis was conducted to identify potential mediators in the significant associations. The dose-response relationships between GLY exposure with health outcomes and potential mediators were analyzed using restricted cubic spline (RCS) regression. The findings of the study revealed that individuals with higher urinary concentrations of GLY had a higher likelihood of having T2DM, hypertension, CVD and obesity (p < 0.001, p = 0.005, p < 0.001 and p = 0.005, respectively). In the reverse-scale Cox regression, a notable association was solely discerned between exposure to GLY and the risk of T2DM (adjusted HR = 1.22, 95% CI: 1.10, 1.36). Consistent outcomes were also obtained via logistic regression analysis, wherein the adjusted OR and 95% CI for T2DM were determined to be 1.30 (1.12, 1.52). Moreover, the present investigation identified serum high-density lipoprotein cholesterol (HDL) as a mediator in this association, with a mediating effect of 7.14% (p = 0.040). This mediating effect was further substantiated by RCS regression, wherein significant dose-response associations were observed between GLY exposure and an increased risk of T2DM (p = 0.002) and reduced levels of HDL (p = 0.001). Collectively, these findings imply an association between GLY exposure and an increased risk of T2DM in the general adult population.

Association between co-exposure to phenols, phthalates, and polycyclic aromatic hydrocarbons with the risk of frailty.

The phenomenon of population aging has brought forth the challenge of frailty. Nevertheless, the contribution of environmental exposure to frailty remains ambiguous. Our objective was to investigate the association between phenols, phthalates (PAEs), and polycyclic aromatic hydrocarbons (PAHs) with frailty. We constructed a 48-item frailty index using data from the National Health and Nutrition Examination Survey (NHANES). The exposure levels of 20 organic contaminants were obtained from the survey circle between 2005 and 2016. The association between individual organic contaminants and the frailty index was assessed using negative binomial regression models. The combined effect of organic contaminants was examined using weighted quantile sum (WQS) regression. Dose-response patterns were modeled using generalized additive models (GAMs). Additionally, an interpretable machine learning approach was employed to develop a predictive model for the frailty index. A total of 1566 participants were included in the analysis. Positive associations were observed between exposure to MIB, P02, ECP, MBP, MHH, MOH, MZP, MC1, and P01 with the frailty index. WQS regression analysis revealed a significant increase in the frailty index with higher levels of the mixture of organic contaminants (aOR, 1.12; 95% CI, 1.05-1.20; p < 0.001), with MIB, ECP, COP, MBP, P02, and P01 identified as the major contributors. Dose-response relationships were observed between MIB, ECP, MBP, P02, and P01 exposure with an increased risk of frailty (both with p < 0.05). The developed predictive model based on organic contaminants exposure demonstrated high performance, with an R2 of 0.9634 and 0.9611 in the training and testing sets, respectively. Furthermore, the predictive model suggested potential synergistic effects in the MIB-MBP and P01-P02 pairs. Taken together, these findings suggest a significant association between exposure to phthalates and PAHs with an increased susceptibility to frailty.

Identification of dietary components in association with abdominal aortic calcification.

The precise impact of dietary components on vascular health remains incompletely understood. To identify the dietary components and their associations with abdominal aortic calcification (AAC), the data from NHANES was employed in this cross-sectional study. The LASSO method and logistic regression were utilized to identify dietary components that exhibited the strongest association with AAC. Grouped WQS regression analysis was employed to evaluate the combined effects of dietary components on AAC. Furthermore, principal component analysis was employed to identify the primary dietary patterns in the study population. The present analysis included 1862 participants, from whom information on 35 dietary macro- and micronutrient components was obtained through 24-hour dietary recall interviews. The assessment of AAC was performed utilizing dual-energy X-ray absorptiometry. The LASSO method identified 10 dietary components that were associated with AAC. Total protein, total fiber, vitamin A, and ß-cryptoxanthin exhibited a negative association with AAC. Compared to the first quartile, the adjusted odds ratios (95% CIs) for the highest quartile were 0.59 (0.38, 0.93), 0.63 (0.42, 0.93), 0.59 (0.41, 0.84), and 0.68 (0.48, 0.94), respectively. Grouped WQS regression demonstrated a positive association between the lipid group and AAC (aOR: 1.29; 95% CI: 1.12, 1.50), while the proteins and phytochemical group exhibited a negative association with AAC (aOR: 0.69; 95% CI: 0.58, 0.82). For the dietary pattern analysis, high adherence to the plant-based pattern (aOR: 0.62; 95% CI: 0.44, 0.88) was associated with a lower risk of AAC, whereas the caffeine and theobromine pattern (aOR: 1.73; 95% CI: 1.25, 2.41) was associated with a higher risk of AAC. The findings of this study indicate that adopting a dietary pattern characterized by high levels of protein and plant-based foods, as well as reduced levels of fat, may offers potential advantages for the prevention of AAC.

Inhibition of NOX4 with GLX351322 alleviates acute ocular hypertension-induced retinal inflammation and injury by suppressing ROS mediated redox-sensitive factors activation.

Reactive oxygen species (ROS) overproduction plays an essential role in the etiology of ischemic/hypoxic retinopathy caused by acute glaucoma. NADPH oxidase (NOX) 4 was discovered as one of the main sources of ROS in glaucoma. However, the role and potential mechanisms of NOX4 in acute glaucoma have not been fully elucidated. Therefore, the current study aims to investigate the NOX4 inhibitor GLX351322 that targets NOX4 inhibition in acute ocular hypertension (AOH)-induced retinal ischemia/hypoxia injury in mice. Herein, NOX4 was highly expressed in AOH retinas, particularly the retinal ganglion cell layer (GCL). Importantly, the NOX4 inhibitor GLX351322 reduced ROS overproduction, inhibited inflammatory factor release, suppressed glial cell activation and hyperplasia, inhibited leukocyte infiltration, reduced retinal cell senescence and apoptosis in damaged areas, reduced retinal degeneration and improved retinal function. This neuroprotective effect is at least partially associated with mediated redox-sensitive factor (HIF-1α, NF-κB, and MAPKs) pathways by NOX4-derived ROS overproduction. These results suggest that inhibition of NOX4 with GLX351322 attenuated AOH-induced retinal inflammation, cellular senescence, and apoptosis by inhibiting the activation of the redox-sensitive factor pathway mediated by ROS overproduction, thereby protecting retinal structure and function. Targeted inhibition of NOX4 is expected to be a new idea in the treatment of acute glaucoma.

Effects of heavy metal exposure on hypertension: A machine learning modeling approach.

Heavy metal exposure is a common risk factor for hypertension. To develop an interpretable predictive machine learning (ML) model for hypertension based on levels of heavy metal exposure, data from the NHANES (2003-2016) were employed. Random forest (RF), support vector machine (SVM), decision tree (DT), multilayer perceptron (MLP), ridge regression (RR), AdaBoost (AB), gradient boosting decision tree (GBDT), voting classifier (VC), and K-nearest neighbour (KNN) algorithms were utilized to generate an optimal predictive model for hypertension. Three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) methods, were integrated into a pipeline and embedded in ML for model interpretation. A total of 9005 eligible individuals were randomly allocated into two distinct sets for predictive model training and validation. The results showed that among the predictive models, the RF model demonstrated the highest performance, achieving an accuracy rate of 77.40% in the validation set. The AUC and F1 score for the model were 0.84 and 0.76, respectively. Blood Pb, urinary Cd, urinary Tl, and urinary Co levels were identified as the main influencers of hypertension, and their contribution weights were 0.0504 ± 0.0482, 0.0389 ± 0.0256, 0.0307 ± 0.0179, and 0.0296 ± 0.0162, respectively. Blood Pb (0.55-2.93 µg/dL) and urinary Cd (0.06-0.15 µg/L) levels exhibited the most pronounced upwards trend with the risk of hypertension within a specific value range, while urinary Tl (0.06-0.26 µg/L) and urinary Co (0.02-0.32 µg/L) levels demonstrated a declining trend with hypertension. The findings on the synergistic effects indicated that Pb and Cd were the primary determinants of hypertension. Our findings underscore the predictive value of heavy metals for hypertension. By utilizing interpretable methods, we discerned that Pb, Cd, Tl, and Co emerged as noteworthy contributors within the predictive model.

A Hybrid System for Automatic Identification of Corneal Layers on In Vivo Confocal Microscopy Images.

Purpose: Accurate identification of corneal layers with in vivo confocal microscopy (IVCM) is essential for the correct assessment of corneal lesions. This project aims to obtain a reliable automated identification of corneal layers from IVCM images. Methods: A total of 7957 IVCM images were included for model training and testing. Scanning depth information and pixel information of IVCM images were used to build the classification system. Firstly, two base classifiers based on convolutional neural networks and K-nearest neighbors were constructed. Second, two hybrid strategies, namely weighted voting method and light gradient boosting machine (LightGBM) algorithm were used to fuse the results from the two base classifiers and obtain the final classification. Finally, the confidence of prediction results was stratified to help find out model errors. Results: Both two hybrid systems outperformed the two base classifiers. The weighted area under the curve, weighted precision, weighted recall, and weighted F1 score were 0.9841, 0.9096, 0.9145, and 0.9111 for weighted voting hybrid system, and were 0.9794, 0.9039, 0.9055, and 0.9034 for the light gradient boosting machine stacking hybrid system, respectively. More than one-half of the misclassified samples were found using the confidence stratification method. Conclusions: The proposed hybrid approach could effectively integrate the scanning depth and pixel information of IVCM images, allowing for the accurate identification of corneal layers for grossly normal IVCM images. The confidence stratification approach was useful to find out misclassification of the system. Translational Relevance: The proposed hybrid approach lays important groundwork for the automatic identification of the corneal layer for IVCM images.

Anomalous deep-red luminescence of perylene black analogues with strong π-π interactions.

Perylene bisimide (PBI) dyes are known as red, maroon and black pigments, whose colors depend on the close π-π stacking arrangement. However, contrary to the luminescent monomers, deep-red and black PBI pigments are commonly non- or only weakly fluorescent due to (multiple) quenching pathways. Here, we introduce N-alkoxybenzyl substituted PBIs that contain close π stacking arrangement (exhibiting dπ-π ≈ 3.5 Å, and longitudinal and transversal displacements of 3.1 Å and 1.3 Å); however, they afford deep-red emitters with solid-state fluorescence quantum yields (ΦF) of up to 60%. Systematic photophysical and computational studies in solution and in the solid state reveal a sensitive interconversion of the PBI-centred locally excited state and a charge transfer state, which depends on the dihedral angle (θ) between the benzyl and alkoxy groups. This effectively controls the emission process, and enables high ΦF by circumventing the common quenching pathways commonly observed for perylene black analogues.

The Multiplicity of π-π Interactions of Fused-Ring Electron Acceptor Polymorphs on the Exciton Migration and Charge Transport.

Efficient long-range exciton migration and charge transport are the key parameters for organic photovoltaic materials, which strongly depend on the molecular stacking modes. Herein, we extracted the stacked structures of the archetype fused-ring electron acceptor molecule, ITIC, based on the information on four polymorphic crystals and investigated the relationship between molecular stacking modes and exciton migration/charge transport properties through the intermolecular Coulomb coupling and charge transfer integral calculation. Experimentally, the thin film texture is crystallized through a post-annealing treatment through grazing-incidence wide-angle X-ray scattering (GIWAXS) measurements, which lead to the enhanced exciton migration through exciton-exciton annihilation in the femtosecond transient absorption (fs-TA) measurements. This work demonstrates the relationship between the molecular arrangement and the exciton migration and electron transport and highlights the significance of optimizing molecular stacking for the development of high-performance electron acceptor materials.

An artificial intelligence approach to classify pathogenic fungal genera of fungal keratitis using corneal confocal microscopy images.

PURPOSE: Fungal keratitis is a common cause of blindness worldwide. Timely identification of the causative fungal genera is essential for clinical management. In vivo confocal microscopy (IVCM) provides useful information on pathogenic genera. This study attempted to apply deep learning (DL) to establish an automated method to identify pathogenic fungal genera using IVCM images. METHODS: Deep learning networks were trained, validated, and tested using a data set of 3364 IVCM images that collected from 100 eyes of 100 patients with culture-proven filamentous fungal keratitis. Two transfer learning approaches were investigated: one was a combined framework that extracted features by a DL network and adopted decision tree (DT) as a classifier; another was a complete supervised DL model which used DL-based fully connected layers to implement the classification. RESULTS: The DL classifier model revealed better performance compared with the DT classifier model in an independent testing set. The DL classifier model showed an area under the receiver operating characteristic curves (AUC) of 0.887 with an accuracy of 0.817, sensitivity of 0.791, specificity of 0.831, G-mean of 0.811, and F1 score of 0.749 in identifying Fusarium, and achieved an AUC of 0.827 with an accuracy of 0.757, sensitivity of 0.756, specificity of 0.759, G-mean of 0.757, and F1 score of 0.716 in identifying Aspergillus. CONCLUSION: The DL model can classify Fusarium and Aspergillus by learning effective features in IVCM images automatically. The automated IVCM image analysis suggests a noninvasive identification of Fusarium and Aspergillus with clear potential application in early diagnosis and management of fungal keratitis.

The Clinical Value of Explainable Deep Learning for Diagnosing Fungal Keratitis Using in vivo Confocal Microscopy Images.

Background: Artificial intelligence (AI) has great potential to detect fungal keratitis using in vivo confocal microscopy images, but its clinical value remains unclarified. A major limitation of its clinical utility is the lack of explainability and interpretability. Methods: An explainable AI (XAI) system based on Gradient-weighted Class Activation Mapping (Grad-CAM) and Guided Grad-CAM was established. In this randomized controlled trial, nine ophthalmologists (three expert ophthalmologists, three competent ophthalmologists, and three novice ophthalmologists) read images in each of the conditions: unassisted, AI-assisted, or XAI-assisted. In unassisted condition, only the original IVCM images were shown to the readers. AI assistance comprised a histogram of model prediction probability. For XAI assistance, explanatory maps were additionally shown. The accuracy, sensitivity, and specificity were calculated against an adjudicated reference standard. Moreover, the time spent was measured. Results: Both forms of algorithmic assistance increased the accuracy and sensitivity of competent and novice ophthalmologists significantly without reducing specificity. The improvement was more pronounced in XAI-assisted condition than that in AI-assisted condition. Time spent with XAI assistance was not significantly different from that without assistance. Conclusion: AI has shown great promise in improving the accuracy of ophthalmologists. The inexperienced readers are more likely to benefit from the XAI system. With better interpretability and explainability, XAI-assistance can boost ophthalmologist performance beyond what is achievable by the reader alone or with black-box AI assistance.

Knockdown of enhancer of rudimentary homolog expression attenuates proliferation, cell cycle and apoptosis of melanoma cells.

Early stage or localized melanoma can be surgically resected with satisfactory outcome, whereas advanced malignant melanoma responds to treatment poorly and has a negative prognosis even after surgery, radiotherapy and other comprehensive treatments. Gene therapy targeting various biological signaling pathways has become an increasingly popular area in melanoma research. However, for gene therapy success, it is important to reveal the molecular mechanisms of melanoma tumorigenesis and development. The present study examined the effects of downregulating enhancer of rudimentary homolog (ERH) expression on the proliferation, metastasis and cell cycle of melanoma cells. ERH expression levels in melanoma tissues and cells were determined. Then, ERH gene expression in melanoma cell lines was downregulated or overexpressed by the lentiviral RNA interference technique. Furthermore, we performed cell counting kit-8, clone formation, scratch, transwell migration, subcutaneous tumorigenesis and venous metastasis assays as well as carried out flow cytometry analysis to explore the effects of ERH expression on cell proliferation, cell cycle, apoptosis and metastasis. We found that ERH expression in melanoma tissues and cells was markedly higher than in normal melanin nevus. Suppressing ERH expression by RNA interference in melanoma A375, WM35 and SK28 cell lines inhibited their proliferation and induced cell apoptosis. The cell cycle was also found to be blocked in the G1 phase. However, the metastatic properties of melanoma cells in vitro and in vivo remained largely unaltered by ERH knockdown. Our results show that ERH expression is increased in melanoma. Meanwhile, the proliferation and cell cycle transformation abilities are impaired potentially by downregulating the ERH expression in melanoma cells. Therefore, targeting ERH might serve as a novel therapeutic approach for malignant melanoma.

A deep transfer learning framework for the automated assessment of corneal inflammation on in vivo confocal microscopy images.

PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in computer assisted diagnosis. This study aimed to develop deep transfer learning models for automatic detection of activated dendritic cells and inflammatory cells using in vivo confocal microscopy images. METHODS: A total of 3453 images was used to train the models. External validation was performed on an independent test set of 558 images. A ground-truth label was assigned to each image by a panel of cornea specialists. We constructed a deep transfer learning network that consisted of a pre-trained network and an adaptation layer. In this work, five pre-trained networks were considered, namely VGG-16, ResNet-101, Inception V3, Xception, and Inception-ResNet V2. The performance of each transfer network was evaluated by calculating the area under the curve (AUC) of receiver operating characteristic, accuracy, sensitivity, specificity, and G mean. RESULTS: The best performance was achieved by Inception-ResNet V2 transfer model. In the validation set, the best transfer system achieved an AUC of 0.9646 (P<0.001) in identifying activated dendritic cells (accuracy, 0.9319; sensitivity, 0.8171; specificity, 0.9517; and G mean, 0.8872), and 0.9901 (P<0.001) in identifying inflammatory cells (accuracy, 0.9767; sensitivity, 0.9174; specificity, 0.9931; and G mean, 0.9545). CONCLUSIONS: The deep transfer learning models provide a completely automated analysis of corneal inflammatory cellular components with high accuracy. The implementation of such models would greatly benefit the management of corneal diseases and reduce workloads for ophthalmologists.

Impact of air injection on subretinal fluid following successful scleral buckling surgery for macular-involving retinal detachment.

Air injection is an accessory technique during scleral buckling (SB). Subclinical subretinal fluid (SRF) may presence and persistent after SB. The impact of air injection on SRF is unclear. In the study, we retrospectively enrolled 51 patients with macular-involving RD who had undergone successful SB. They were categorized into Group A (SB without air injection) and Group B (SB with air injection). First, we found that although group B seem to be severer than group A before surgery, Kaplan-Meier graph showed that SRF absorbed more rapidly in group B after surgery, and the incidence of SRF in group B was much lower during the whole follow-up period. Moreover, the cases with superior breaks had the lowest incidence. Second, during the follow-up period, there was no significant difference about postoperative complication between two groups. Lastly, risk factors for persistent SRF were investigated with binary logistic regression, and no risk factor was found. In conclusion, air injection during the SB might accelerate SRF absorption and reduce the incidence of persistent SRF, especially for the longstanding macular-off RD with superior breaks.

Epigenetic Landscape Analysis of the Long Non-Coding RNA and Messenger RNA in a Mouse Model of Corneal Alkali Burns.

Purpose: Corneal alkali burns (CABs) are a common clinical ocular disease, presenting a poor prognosis. Although some long noncoding RNAs (lncRNAs) reportedly play a key role in epigenetic regulation associated with CABs, studies regarding the lncRNA signature in CABs remain rare and elusive. Methods: A CAB model was established in C57BL/6J mice and profiling of lncRNA expressions was performed by RNA-Seq. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to predicate the related pathological pathways and candidate genes. RT-qPCR was used to verify the expression pattern of lncRNAs and related mRNAs, both in vitro and in vivo. Data were statistically analyzed by GraphPad Prism version 6.0. Results: In all, 4436 aberrantly expressed lncRNAs were identified in CAB mice when compared with control mice. In the top 13 aberrantly expressed lncRNAs, Bc037156 and 4930511E03Rik were confirmed as the most significantly altered lncRNAs. Pathway analysis revealed that mitogen-activated protein kinase (MAPK) signaling pathway was most enriched. Following 4930511E03Rik siRNA treated, Srgn, IL-1ß and Cxcr2 were significant upregulated in corneal epithelial cells, corneal keratocytes, and bone marrow dendritic cells, with NaOH treatment. Moreover, after Bc037156 siRNA treated, expression levels of IL-1ß and Srgn were significantly downregulated in the three cell lines. Conclusions: Our study suggests that Bc037156 and 4930511E03Rik may be involved in inflammation, immune response, and neovascularization by regulating Srgn, IL-1ß, and Cxcr2 expression after CAB. These candidate lncRNAs and mRNAs may be the potential targets for the treatment strategy of the alkali injured cornea.

Coexistence of Parallel and Rotary Stackings in the Lamellar Crystals of a Perylene Bisimide Dyad for Temperature-Sensitive Bicomponent Emission.

Coexistence of rotationally π-π stacked columns and discrete slip-stacked dimers of perylene bisimide (PBI) chromophores is revealed by single crystal X-ray diffraction in the lamellar crystal of a head-to-tail linked PBI dyad. The rotary π-π stacked columnar moieties show H-type spectral character with relatively higher excitation energy, while the discrete slip-stacked π-π dimers have J-type spectral behavior with lower excitation energy. The lamellar crystals show relatively low photoluminescence efficiency of 12% at room temperature, while this dramatically increases to ∼90% at low temperature (80 K). Both of the rotary and slip-stacked moieties are emissive, and the nonradiative energy transfer processes between them are suppressed at low temperature, ensuring the highly efficient excimer-like long-lived fluorescence.

CHANGES IN THE CHOROIDAL THICKNESS AFTER MACULAR BUCKLING IN HIGHLY MYOPIC EYES.

PURPOSE: To assess changes in the choroidal thickness (CT) after macular buckling in eyes with high myopia. METHODS: Highly myopic eyes that underwent macular buckling surgery were retrospectively analyzed. Data of swept-source optical coherence tomography scanning at baseline and at 1, 3, 6, 12, and 18 months after macular buckling were collected. Subfoveal CT and CT at 750 µm superior, inferior, nasal, and temporal to the fovea were measured. The total choroidal area, vascular area, and stromal area were measured by the binarization method. The choroidal vascularity index was calculated by dividing the vascular area by the total choroidal area. RESULTS: Forty-one eyes were included in the final analysis. The subfoveal CT increased from 49.85 ± 31.23 µm preoperatively to 75.74 ± 37.89 µm 1 month after macular buckling (P < 0.001), then decreased over time, coinciding with the trends of parafoveal CT, total choroidal area, vascular area, and stromal area. The subfoveal CT was restored to the preoperative level six months postoperatively (P = 0.202) and remained stable until the end of follow-up. The choroidal vascularity index increased at 1 and 3 months postoperatively (P = 0.001 and 0.005, respectively). CONCLUSION: The choroid thickened in the early postoperative period. The compression force of the buckle implant might disturb microcirculatory drainage and contribute to the thickening. The choroid spontaneously recovered to the preoperative level over time.

A living cell-based fluorescent reporter for high-throughput screening of anti-tumor drugs.

Suppression of cellular O-linked ß-N-acetylglucosaminylation (O-GlcNAcylation) can repress proliferation and migration of various cancer cells, which opens a new avenue for cancer therapy. Based on the regulation of insulin gene transcription, we designed a cell-based fluorescent reporter capable of sensing cellular O-GlcNAcylation in HEK293T cells. The fluorescent reporter mainly consists of a reporter (green fluorescent protein (GFP)), an internal reference (red fluorescent protein), and an operator (neuronal differentiation 1), which serves as a "sweet switch" to control GFP expression in response to cellular O-GlcNAcylation changes. The fluorescent reporter can efficiently sense reduced levels of cellular O-GlcNAcylation in several cell lines. Using the fluorescent reporter, we screened 120 natural products and obtained one compound, sesamin, which could markedly inhibit protein O-GlcNAcylation in HeLa and human colorectal carcinoma-116 cells and repress their migration in vitro. Altogether, the present study demonstrated the development of a novel strategy for anti-tumor drug screening, as well as for conducting gene transcription studies.

Does Serum Vitamin D Level Affect COVID-19 Infection and Its Severity?-A Case-Control Study.

BACKGROUND: As effective medication to treat COVID-19 is currently unavailable, preventive remedies may be particularly important. OBJECTIVE: To examine the relationship between serum 25-hydroxy vitamin D (25(OH)D) level and COVID-19 infection, its severity, and its clinical case characteristics. METHODS: This case-control study compared serum 25(OH)D levels and rates of vitamin D deficiency (VDD) between 80 healthy controls and 62 patients diagnosed with COVID-19 and admitted to Guangxi People's Hospital, China, 2/16/2020-3/16/2020. Cases were categorized into asymptomatic, mild/moderate, and severe/critical disease. Logistic regression analysis was conducted to examine the associations between 25(OH)D level, or VDD, and case status/severity of COVID-19 while controlling for demographics and comorbidities. A threshold level of vitamin D for conveying COVID-19 risk was estimated. RESULTS: Severe/critical COVID-19 cases were significantly older and had higher percentages of comorbidity (renal failure) compared to mild cases. The serum 25(OH)D concentration in COVID-19 patient was much lower than that in healthy control. And 25(OH)D level was the lowest in severe/critical cases, compared with mild cases. In further, significantly higher rates of VDD were found in COVID-19 cases (41.9%) compared to healthy controls (11.1%). And VDD was the greatest in severe/critical cases (80%), compared with mild cases (36%). These statistically significant associations remained even after controlling for demographics and comorbidities. A potential threshold of 25(OH)D (41.19 nmol/L) to protect against COVID-19 was identified. CONCLUSION: Elderly and people with comorbidities were susceptible to severe COVID-19 infection. VDD was a risk factor for COVID-19, especially for severe/critical cases. While further confirmation is needed, vitamin D supplementation may have prevention or treatment potential for COVID-19 disease.