Does vitreous haemorrhage and calcification lead to increased risk of enucleation in advanced retinoblastoma?

PURPOSE: To explore whether varying degrees of vitreous haemorrhage (VH) and calcification act as risk factors for enucleation in patients with advanced retinoblastoma (RB). METHODS: Advanced RB was defined by the international classification of RB (Philadelphia version). Basic information for retinoblastoma patients diagnosed as groups D and E in our hospital between January 2017 and June 2022 was reviewed by logistics regression models. Additionally, a correlation analysis was performed, excluding variables with a VIF (variance inflation factor) >10 from the multivariate analysis. RESULTS: A total of 223 eyes diagnosed with RB were included in assessing VH and calcification; of these, 101 (45.3%) eyes experienced VH, and 182 (76.2%) eyes were found to have calcification within the tumour through computed tomography (CT) or B-scan ultrasonography. Ninety-two eyes (41.3%) were enucleated, of which 67 (72.8%) had VH and 68 (73.9%) calcification, both of which were significantly relevant to enucleation (p < 0.001*). Other clinical risk factors, such as corneal edema, anterior chamber haemorrhage, high intraocular pressure during treatment and iris neovascularization, correlated significantly with enucleation (p < 0.001*). Multivariate analysis included IIRC (intraocular international retinoblastoma classification), VH, calcification and high intraocular pressure during treatment as independent risk factors for enucleation. CONCLUSIONS: Despite identifying different potential risk factors for RB, there remains significant controversy concerning which patients require enucleation, and the degree of VH varies. Such eyes need to be evaluated carefully, and management with appropriate adjuvant therapy may improve the outcome of these patients.

Artificial intelligence-driven shimming for parallel high field nuclear magnetic resonance.

Rapid drug development requires a high throughput screening technology. NMR could benefit from parallel detection but is hampered by technical obstacles. Detection sites must be magnetically shimmed to ppb uniformity, which for parallel detection is precluded by commercial shimming technology. Here we show that, by centering a separate shim system over each detector and employing deep learning to cope with overlapping non-orthogonal shimming fields, parallel detectors can be rapidly calibrated. Our implementation also reports the smallest NMR stripline detectors to date, based on an origami technique, facilitating further upscaling in the number of detection sites within the magnet bore.

Structure, Stability, and Acidity of the Uranyl Arsenate Dimer in Aqueous Solution.

The migration of uranium (U) in the surficial environment has received considerable attention. Due to their high natural abundance and low solubility, autunite-group minerals play a key role in controlling the mobility of U. However, the formation mechanism for these minerals has yet to be understood. In this work, we took the uranyl arsenate dimer ([UO2(HAsO4)(H2AsO4)(H2O)]22-) as a model molecule and carried out a series of first-principles molecular dynamics (FPMD) simulations to explore the early stage of the formation of trögerite (UO2HAsO4·4H2O), a representative autunite-group mineral. By using the potential-of-mean-force (PMF) method and vertical energy gap method, the dissociation free energies and the acidity constants (pKa's) of the dimer were calculated. Our results show that the U in the dimer holds a 4-coordinate structure, which is consistent with the coordination environment observed in trögerite mineralogy, in contrast to the 5-coordinate U in the monomer. Furthermore, the dimerization is thermodynamically favorable in solution. The FPMD results also suggest that tetramerization and even polyreactions would occur at pH > 2, as observed experimentally. Additionally, it is found that trögerite and the dimer have very similar local structural parameters. These findings imply that the dimer could serve as an important link between the U-As complexes in solution and the autunite-type sheet of trögerite. Given the nearly identical physicochemical properties of arsenate and phosphate, our findings suggest that uranyl phosphate minerals with the autunite-type sheet may form in a similar manner. This study therefore fills a critical gap in atomic-scale knowledge of the formation of autunite-group minerals and provides a theoretical basis for regulating uranium mobilization in P/As-bearing tailing water.

A novel MYCN-YTHDF1 cascade contributes to retinoblastoma tumor growth by eliciting m6A -dependent activation of multiple oncogenes.

Retinoblastoma, the most prevalent primary intraocular tumor in children, leads to vision impairment, disability and even death. In addition to RB1 inactivation, MYCN activation has been documented as another common oncogenic alteration in retinoblastoma and represents one of the high-risk molecular subtypes of retinoblastoma. However, how MYCN contributes to the progression of retinoblastoma is still incompletely understood. Here, we report that MYCN upregulates YTHDF1, which encodes one of the reader proteins for N6-methyladenosine (m6A) RNA modification, in retinoblastoma. We further found that this MYCN-upregulated m6A reader functions to promote retinoblastoma cell proliferation and tumor growth in an m6A binding-dependent manner. Mechanistically, YTHDF1 promotes the expression of multiple oncogenes by binding to their mRNAs and enhancing mRNA stability and translation in retinoblastoma cells. Taken together, our findings reveal a novel MYCN-YTHDF1 regulatory cascade in controlling retinoblastoma cell proliferation and tumor growth, pinpointing an unprecedented mechanism for MYCN amplification and/or activation to promote retinoblastoma progression.

Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics.

Purpose: The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. Methods: We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and Disgenet databases, and the Venny was used for intersection processing. We observed the gene expression differences in the GEO database. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration, and the solvent accessible surface area. Results: Aspirin had 294 gene targets, Kawasaki disease had 416 gene targets, 42 intersecting targets were obtained, we screened 13 core targets by PPI; In the GO analysis, we learned that the biological process of Kawasaki disease involved the positive regulation of chemokine biosynthesis and inflammatory response; pathway enrichment involved PI3K-AKT signaling pathway, tumor necrosis factor signaling pathway, etc. After molecular docking, the data showed that CTSG, ELANE, and FGF1 had the best binding degree to aspirin. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, and Aspirin/ELANE combination has the strongest binding energy. Conclusion: In the treatment of Kawasaki disease, aspirin may regulate inflammatory response and vascular remodeling through CTSG, ELANE, and FGF1.

Multi-label classification of fundus images with graph convolutional network and LightGBM.

Early detection and treatment of retinal disorders are critical for avoiding irreversible visual impairment. Given that patients in the clinical setting may have various types of retinal illness, the development of multi-label fundus disease detection models capable of screening for multiple diseases is more in line with clinical needs. This article presented a composite model based on hybrid graph convolution for patient-level multi-label fundus illness identification. The composite model comprised a backbone module, a hybrid graph convolution module, and a classifier module. This article established the relationship between labels via graph convolution and then employed a self-attention mechanism to design a hybrid graph convolution structure. The backbone module extracted features using EfficientNet-B4, whereas the classifier module output multi-label using LightGBM. Additionally, this work investigated the input pattern of binocular images and the influence of label correlation on the model's identification performance. The proposed model MCGL-Net outperformed all other state-of-the-art methods on the publicly available ODIR dataset, with F1 reaching 91.60% on the test set. Ablation experiments were also performed in this paper. Experiments showed that the idea of hybrid graph convolutional structure and composite model designed in this paper promotes the model performance under any backbone CNN. The adoption of hybrid graph convolution can increase the F1 by 2.39% in trials using EfficientNet-B4 as the backbone. The composite model had a higher F1 index by 5.42% than the single EfficientNet-B4 model.

Monitoring Retinoblastoma by Machine Learning of Aqueous Humor Metabolic Fingerprinting.

The most common intraocular pediatric malignancy, retinoblastoma (RB), accounts for ≈10% of cancer in children. Efficient monitoring can enhance living quality of patients and 5-year survival ratio of RB up to 95%. However, RB monitoring is still insufficient in regions with limited resources and the mortality may even reach over 70% in such areas. Here, an RB monitoring platform by machine learning of aqueous humor metabolic fingerprinting (AH-MF) is developed, using nanoparticle enhanced laser desorption/ionization mass spectrometry (LDI MS). The direct AH-MF of RB free of sample pre-treatment is recorded, with both high reproducibility (coefficient of variation < 10%) and sensitivity (low to 0.3 pmol) at sample volume down to 40 nL only. Further, early and advanced RB patients with area-under-the-curve over 0.9 and accuracy over 80% are differentiated, through machine learning of AH-MF. Finally, a metabolic biomarker panel of 7 metabolites through accurate MS and tandem MS (MS/MS) with pathway analysis to monitor RB is identified. This work can contribute to advanced metabolic analysis of eye diseases including but not limited to RB and screening of new potential metabolic targets toward therapeutic intervention.

Controllable Subtractive Nanoimprint Lithography for Precisely Fabricating Paclitaxel-Loaded PLGA Nanocylinders to Enhance Anticancer Efficacy.

Nanoimprint lithography presents a new strategy for preparing uniform nanostructures with predefined sizes and shapes and has the potential for developing nanosized drug delivery systems. However, the current nanoimprint lithography is a type of an additive nanofabrication method that has limited potential due to its restricted template-dependent innate character. Herein, we have developed a novel subtractive UV-nanoimprint lithography (sUNL) for the scalable fabrication of PLGA nanostructures with variable sizes for the first time. sUNL can not only fabricate a variety of predefined nanostructures by simply utilizing different nanoimprint molds but also precisely prepare scalable nanocylinders with different length to diameter ratios. Particularly, sUNL can fabricate paclitaxel-loaded PLGA nanocylinders (PTX-PLGA NCs) with high drug-loading rate of 40% and long storage stability over a year. We demonstrate that PTX-PLGA NCs target clathrin- and caveolae-mediated cell transport pathways and display increased cellular uptake, in comparison to traditional PTX-loaded PLGA nanoparticles (PTX-PLGA NPs), leading to enhanced anticancer effects. Therefore, sUNL represents a promising nanofabrication method for efficiently developing predefined drug delivery systems.

The miR-186-3p/EREG axis orchestrates tamoxifen resistance and aerobic glycolysis in breast cancer cells.

Tamoxifen resistance is one of the major challenges for its medical uses in estrogen receptor (ER)-positive breast cancer. Aerobic glycolysis, an anomalous characteristic of glucose metabolism in cancer cells, has been shown to associate with the resistance to chemotherapeutic agents. It remains, however, largely unclear whether and how tamoxifen resistance contributes to aerobic glycolysis in breast cancer. Here, we report that tamoxifen resistance is associated with enhanced glycolysis in ER-positive breast cancer cells. We demonstrate that EREG, an agonist of EGFR, has an important role in enhancing glycolysis via activating EGFR signaling and its downstream glycolytic genes in tamoxifen-resistant breast cancer cells. We further show that EREG is a direct target of miR-186-3p and that downregulation of miR-186-3p by tamoxifen results in EREG upregulation in tamoxifen-resistant breast cancer cells. Importantly, systemic delivery of cholesterol-modified agomiR-186-3p to mice bearing tamoxifen-resistant breast tumors effectively attenuates both tumor growth and [18F]-fluoro-deoxyglucose ([18F]-FDG) uptake. Together, our results reveal a novel molecular mechanism of resistance to hormone therapies in which the miR-186-3p/EREG axis orchestrates tamoxifen resistance and aerobic glycolysis in ER-positive breast cancer, suggesting targeting miR-186-3p as a promising strategy for therapeutic intervention in endocrine-resistant breast tumors.

Two-dimensional photonic crystal with ring degeneracy and its topological protected edge states.

We propose a two-dimensional photonic crystal that possesses a degenerate ring in the momentum space. The photonic crystal is composed of the parallel-plate metal filled with a periodically arranged square array of metallic cylinders. Opening an air gap breaks the z-inversion symmetry, leading to the modes coupling (bi-anisotropy response) of TE and TM waves. This induced electric-magneto coupling, a similar role of the spin-orbit interaction in the condensed matters, results in a complete topological band gap around the degenerate frequency. The bulk bands below the band gap take non-zero Z2 topological invariant characterized by the evolution of the Berry phase. As a consequence, the interface of two photonic crystals with opposite bi-anisotropy supports topological protected edge states that exhibit one-way propagation and are highly resistant to disorders. Our work might be very useful for the design of topological photonic crystals and may serve as a platform for studying pseudo-spin photonics.

Realization of a three-dimensional photonic topological insulator.

Confining photons in a finite volume is highly desirable in modern photonic devices, such as waveguides, lasers and cavities. Decades ago, this motivated the study and application of photonic crystals, which have a photonic bandgap that forbids light propagation in all directions1-3. Recently, inspired by the discoveries of topological insulators4,5, the confinement of photons with topological protection has been demonstrated in two-dimensional (2D) photonic structures known as photonic topological insulators6-8, with promising applications in topological lasers9,10 and robust optical delay lines11. However, a fully three-dimensional (3D) topological photonic bandgap has not been achieved. Here we experimentally demonstrate a 3D photonic topological insulator with an extremely wide (more than 25 per cent bandwidth) 3D topological bandgap. The composite material (metallic patterns on printed circuit boards) consists of split-ring resonators (classical electromagnetic artificial atoms) with strong magneto-electric coupling and behaves like a 'weak' topological insulator (that is, with an even number of surface Dirac cones), or a stack of 2D quantum spin Hall insulators. Using direct field measurements, we map out both the gapped bulk band structure and the Dirac-like dispersion of the photonic surface states, and demonstrate robust photonic propagation along a non-planar surface. Our work extends the family of 3D topological insulators from fermions to bosons and paves the way for applications in topological photonic cavities, circuits and lasers in 3D geometries.

Uranyl Arsenate Complexes in Aqueous Solution: Insights from First-Principles Molecular Dynamics Simulations.

In this study, the structures and acidity constants (p Ka's) of uranyl arsenate complexes in solutions have been revealed by using the first principle molecular dynamics technique. The results show that uranyl and arsenate form stable complexes with the U/As ratios of 1:1 and 1:2, and the bidentate complexation between U and As is highly favored. Speciation-pH distributions are derived based on free energy and p Ka calculations, which indicate that for the 1:1 species, UO2(H2AsO4)(H2O)3+ is the major species at pH < 7, while UO2(HAsO4)(H2O)30 and UO2(AsO4)(H2O)3- dominate in acid-to-alkaline and extreme alkaline pH ranges. For the 1:2 species, UO2(H2AsO4)2(H2O)0 is dominant under acid-to-neutral pH conditions, while UO2(HAsO4)(H2AsO4)(H2O)-, UO2(HAsO4)(HAsO4)(H2O)2-, and UO2(AsO4)(HAsO4)(H2O)3- become the major forms in the pH range of 7.2-10.7, 10.7-12.1, and >12.1, respectively.

Cisplatin-induced autophagy protects breast cancer cells from apoptosis by regulating yes-associated protein.

Breast cancer is a common cause of cancer­related deaths in women. Treatment with cisplatin exhibits some therapeutic efficacy. However, treatment optimization is required, and the mechanisms underlying the cisplatin's proapoptotic effects remain unclear. In the present study, we demonstrated that cisplatin induced apoptosis and autophagy in breast cancer cells. Autophagy induced by cisplatin played a protective role in breast cancer cells, which impaired its proapoptotic effect. Mechanistically, for the first time, we found that cisplatin treatment activated the MAPK signaling pathway and promoted autophagy via the ERK signaling pathway. Notably, we found that nuclear translocation of yes-associated protein (YAP) was regulated by cisplatin-induced autophagy, and we identified YAP as a survival input that promoted survival in cisplatin-treated breast cancer cells. These findings revealed that administration of cisplatin along with an autophagy inhibitor is a promising therapeutic strategy for treating breast cancer.

Acidity constants and redox potentials of uranyl ions in hydrothermal solutions.

We report a first principles molecular dynamics (FPMD) study of the structures, acidity constants (pKa) and redox potentials (E0) of uranyl (UO22+) from ambient conditions to 573 K. It is found that UO22+ keeps five coordination up to 573 K whereas UO2+ transforms from 5 to 4-coordinate as temperature increases to 573 K. The FPMD-based vertical energy gap method is used to derive pKas and E0s. The method is validated by comparing with available experimental data (for E0 under the ambient conditions and for pKas from ambient conditions to 367 K), with an uncertainty of 1-2 pKa units and 0.2 V for pKa and E0. The encouraging results demonstrate that the method may be used to predict the pH-Eh diagrams of f-block elements under the conditions of hydrothermal solutions. The results show that the acidity constants of uranyl decrease with temperature and are lower than 3.0 when the temperature is above 473 K, indicating that hydrolytic forms are dominant for U(vi) in the near neutral pH range. The reduction potential increases with temperature, indicating that the reduced state is more significant at higher temperatures.

Structures and Acidity Constants of Silver-Sulfide Complexes in Hydrothermal Fluids: A First-Principles Molecular Dynamics Study.

In order to quantify the speciation and structures of silver-sulfide complexes in aqueous solutions, we have carried out systematic first-principles molecular dynamics (FPMD) simulations at three temperatures (25, 200, and 300 °C). It is found that monosulfide (i.e., Ag(HS)) and disulfide species (i.e., Ag(HS)2-) are the major silver-sulfide species over a wide T-P range, while Ag(HS)32- can hold stably only at ambient temperatures, and Ag(HS)43- does not exist even at the ambient conditions. Ag(H2S)+ has a tetrahedral structure up to 300 °C (i.e., Ag(H2S)(H2O)3+). Ag(H2S)2+ remains 4-coordinated to 200 °C (i.e., Ag(H2S)2(H2O)2+), but it transforms to 3-coordinated at 300 °C (i.e., Ag(H2S)2(H2O)+). All of the other mono- and disulfide species (Ag(HS)(H2O)0, Ag(HS)(OH)-, Ag(HS)(H2S)0, Ag(HS)2-, and AgS(HS)2-) have 2-fold linear structures. For their solvation structures, the H2S ligands donate weak H-bonds to water O; the HS- ligands accept weak H-bonds from water H; the dangling S2- form strong H-bonds with H of water molecules, and the OH- ligands can form strong H-bonds as donors and weak H-bonds as acceptors. We further calculated the acidity constants (i.e., pKas) of Ag(H2S)+ and Ag(H2S)2+ complexes using FPMD based vertical energy gap method. Based on the calculated pKas, the mono- and disulfide species distributions versus pH have been derived. We found that for monosulfide species, Ag(HS)(H2O)0, is the major species in near neutral pH, while Ag(H2S)(H2O)3+ and Ag(HS)(OH)- exist in the acid and alkaline pH range at T ≤ 200 °C, respectively. At 300 °C, both Ag(HS)(OH)- and Ag(HS)(H2O)0 are dominant in the neutral pH range, and Ag(H2S)(H2O)2+ only exists in acidic solutions. For disulfide species, Ag(HS)2- is dominative in near neutral pH condition at the three temperatures; Ag(HS)(H2S)0 stays in mild acidic pH range only at 25 °C; AgS(HS)2- and Ag(H2S)2(H2O)2+ (Ag(H2S)2(H2O)+ at 300 °C) are trivial at the three conditions. The results of structures and acidity constants provide quantitative and microscopic basis for understanding the behavior of silver complexes in hydrothermal fluids.

Redox potentials of aryl derivatives from hybrid functional based first principles molecular dynamics.

We report the redox potentials of a set of organic aryl molecules, including quinones, juglone, tyrosine and tryptophan, calculated using a first principles molecular dynamics (FPMD) based method. The hybrid functional HSE06 reproduces the redox potentials spanning from -0.25 V to 1.15 V within an error of 0.2 V, whereas the errors with the BLYP functional are much larger (up to 0.7 V). It is found that the BLYP functional predicts consistently lower electron affinities/ionization potentials than HSE06 both in gas phase and in an aqueous solution. In water, the ionization potentials are significantly underestimated by BLYP due to the exaggeration of the mixing between the solute states and the valence band states of liquid water. Hybrid HSE06 markedly improves both the solute levels and water band positions, leading to accurate redox potentials. This study suggests that the current FPMD based method at the level of hybrid functionals is able to accurately compute the redox potentials of a wide spectrum of organic molecules.