Daytime HyWFS approach for daylight adaptive optics wavefront sensing.

Bright daylight photon noise and the saturation of wavefront sensors pose challenges to high-resolution daytime imaging. In this paper, a daytime hybrid wavefront sensor (HyWFS) approach for real-time wavefront sensing in daylight adaptive optics (AO) is described. The Shack-Hartmann wavefront sensor (SHWFS) algorithm is used to efficiently compensate large-scale wavefronts, while the pyramid wavefront sensor (PyWFS) algorithm offers highly sensitive correction of small wavefronts. Daylight closed-loop AO experiments were performed using the daytime HyWFS approach with both algorithms, respectively. The experiment results indicate that the proposed approach provides accurate daylight AO correction and allows for a simple switch between the two algorithms without increasing system complexity. The daytime HyWFS approach can serve as an alternative for daylight natural guide star AO, enabling high-resolution observation of resident space objects no longer limited to dawn and dusk.

Osimertinib resistance prognostic gene signature: STRIP2 is associated with immune infiltration and tumor progression in lung adenocarcinoma.

OBJECTIVE: Although the use of osimertinib can significantly improve the survival time of lung adenocarcinoma (LUAD) patients with epithelial growth factor receptor mutation, eventually drug resistance will limit the survival benefit of most patients. This study aimed to develop a novel prognostic predictive signature based on genes associated with osimertinib resistance. METHODS: The differentially expressed genes (DEGs) associated with osimertinib resistance in LUAD were screened from Gene Expression Omnibus datasets and The Cancer Genome Atlas datasets. Multivariate cox regression was used to establish a prognostic signature, and then a nomogram was developed to predict the survival probability of LUAD patients. We used ROC curve and DCA curve to evaluate its clinical prediction accuracy and net benefit. In addition, the differentially expressed genes significantly associated with prognosis were selected for immune infiltration analysis and drug sensitivity analysis, and their roles in the progression of lung adenocarcinoma were verified by in vitro experiments. RESULTS: Our evaluation results indicated that the new nomogram had higher clinical prediction accuracy and net benefit value than the TN nomogram. Further analysis showed that patients with low STRIP2 expression had a higher level of immune response, and may be more likely to benefit from immune checkpoint inhibitors and conventional antitumor drugs. This may help to select more precise and appropriate therapy for LUAD patients with osimertinib resistance. Furthermore, in vitro experiments showed that STRIP2 promoted the LUAD cells proliferation, migration and invasion. This further demonstrates the importance of this gene signature for prognostic prediction. CONCLUSION: We developed a reliable prognostic model based on DEGs associated with osimertinib resistance and screened for biomarker that can predict the immune response in LUAD patients, which may help in the selection of treatment regimens after osimertinib resistance.

Semi-supervised heterogeneous graph contrastive learning for drug-target interaction prediction.

Identification of drug-target interactions (DTIs) is an important step in drug discovery and drug repositioning. In recent years, graph-based methods have attracted great attention and show advantages on predicting potential DTIs. However, these methods face the problem that the known DTIs are very limited and expensive to obtain, which decreases the generalization ability of the methods. Self-supervised contrastive learning is independent of labeled DTIs, which can mitigate the impact of the problem. Therefore, we propose a framework SHGCL-DTI for predicting DTIs, which supplements the classical semi-supervised DTI prediction task with an auxiliary graph contrastive learning module. Specifically, we generate representations for the nodes through the neighbor view and meta-path view, and define positive and negative pairs to maximize the similarity between positive pairs from different views. Subsequently, SHGCL-DTI reconstructs the original heterogeneous network to predict the potential DTIs. The experiments on the public dataset show that SHGCL-DTI has significant improvement in different scenarios, compared with existing state-of-the-art methods. We also demonstrate that the contrastive learning module improves the prediction performance and generalization ability of SHGCL-DTI through ablation study. In addition, we have found several novel predicted DTIs supported by the biological literature. The data and source code are available at: https://github.com/TOJSSE-iData/SHGCL-DTI.

Identification of super-enhancer-driven peptidyl arginine deiminases as potential biomarkers and therapeutic targets for osimertinib-resistant non-small cell lung cancer.

Resistance to targeted drugs is now a challenging clinical problem in the treatment of non-small cell lung cancer (NSCLC). So far, there are no approved targeted therapeutic drugs for patients with disease progression after the third-generation epidermal growth factor receptor-tyrosine kinase inhibitor osimertinib resistance (OR). Super-enhancers (SEs) are large clusters of transcriptional enhancers that drive gene expression. In this study, we aimed to explore the potential pathogenic SEs and their driven genes in OR NSCLC. OR cell line was established by exposure of H1975 cells to incremental dosing of osimertinib. RNA-sequencing and H3K27ac ChIP-sequencing were used to identify the differential expressed genes (DEGs) and SEs in parental and resistant cells. Gene ontology analysis for the OR-specific SEs-associated genes showed that histone citrullination, protein citrullination, and peptidyl-arginine modification are the top three biological processes, and the DEGs involved in these biological processes, including peptidyl arginine deiminase 1 (PADI1), PADI2, and PADI3. Realtime-PCR and western blot detections confirmed these genes were highly expressed in OR cells. SE inhibitor decreases their expression, ensuring that SEs regulate their transcriptional expressions. The PADI inhibitor inhibited OR cells' proliferation, invasion, and colony formation. This study demonstrates that SE-driven PADI family genes are potential biomarkers and targets for OR NSCLC.

Integrated RNA-sequencing and network pharmacology approach reveals the protection of Yiqi Huoxue formula against idiopathic pulmonary fibrosis by interfering with core transcription factors.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a refractory disease. Therefore, developing effective therapies for IPF is the need of the hour. PURPOSE: Yiqi Huoxue Formula (YQHX) is an herbal formula comprising three herbal medicines: Ligusticum chuanxiong Hort. (Chuanxiong Rhizoma, CR), Panax notoginseng (Burk.) F. H. Chen (Notoginseng Radix Et Rhizoma, NR) and Panax ginseng C. A. Mey. (Ginseng Radix Et Rhizoma, GR). This study aims to determine the anti-pulmonary fibrosis effect of YQHX and explore its mechanism of action. STUDY: Design and Methods: The chemical components in the GR, CR and NR extracts were identified by High Performance Liquid Chromatography. A TGF-ß1-induced myofibroblast cell model was used to test the anti-fibrosis effect of GR, CR, NR and YQHX. RNA-sequencing was used to identify the differentially expressed genes (DEGs) after YQHX treatment. Subsequently, gene enrichment analysis and key transcription factors (TFs) prediction for YQHX-regulated DEGs was performed. The active constituents of GR, CR and NR were obtained from the Traditional Chinese Medicine Database and Analysis Platform. Targets of the active constituents were predicted using the similarity ensemble approach search server and Swiss Target Prediction tool. YQHX-targeted key TFs that transcribed the DEGs were screened out. Then, the effect of YQHX on the bleomycin-induced pulmonary fibrosis mouse model was studied. Finally, one of the predicted TFs, STAT3, was selected to validate the prediction accuracy. RESULTS: Seven, two, and five compounds were identified in the GR, CR, and NR extracts, respectively. YQHX and its constituents-GR, CR and NR-inhibited the expression of fibrotic markers, including α -SMA and fibronectin, indicating that YQHX inhibited TGF-ß1-induced myofibroblast activation. RNA-sequencing identified 291 genes that were up-regulated in the TGF-ß1 group but down-regulated after YQHX treatment. In total, 55 key TFs that transcribed YQHX-regulated targets were predicted. A regulatory network of 24 active ingredients and 232 corresponding targets for YQHX was established. Among YQHX's predicted targets, 20 were TFs. On overlapping YQHX-targeted TFs and DEGs' key TFs, six key TFs, including HIF1A, STAT6, STAT3, PPARA, DDIT3 and AR, were identified as the targets of YQHX. Additionally, YQHX alleviated bleomycin-induced pulmonary fibrosis in a mouse model by inhibiting the phosphorylation of STAT3 in the lungs of pulmonary fibrosis mice. CONCLUSIONS: This study provides pharmacological support for the use of YQHX in the treatment of IPF. The potential mechanism of action of YQHX is speculated to involve the modulation of core TFs and inhibition of pathogenetic gene expressions in IPF.

Modeling Kaempferol as a Potential Pharmacological Agent for COVID-19/PF Co-Occurrence Based on Bioinformatics and System Pharmacological Tools.

Objective: People suffering from coronavirus disease 2019 (COVID-19) are prone to develop pulmonary fibrosis (PF), but there is currently no definitive treatment for COVID-19/PF co-occurrence. Kaempferol with promising antiviral and anti-fibrotic effects is expected to become a potential treatment for COVID-19 and PF comorbidities. Therefore, this study explored the targets and molecular mechanisms of kaempferol against COVID-19/PF co-occurrence by bioinformatics and network pharmacology. Methods: Various open-source databases and Venn Diagram tool were applied to confirm the targets of kaempferol against COVID-19/PF co-occurrence. Protein-protein interaction (PPI), MCODE, key transcription factors, tissue-specific enrichment, molecular docking, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to clarify the influential molecular mechanisms of kaempferol against COVID-19 and PF comorbidities. Results: 290 targets and 203 transcription factors of kaempferol against COVID-19/PF co-occurrence were captured. Epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase SRC (SRC), mitogen-activated protein kinase 3 (MAPK3), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 8 (MAPK8), RAC-alpha serine/threonine-protein kinase (AKT1), transcription factor p65 (RELA) and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) were identified as the most critical targets, and kaempferol showed effective binding activities with the above critical eight targets. Further, anti-COVID-19/PF co-occurrence effects of kaempferol were associated with the regulation of inflammation, oxidative stress, immunity, virus infection, cell growth process and metabolism. EGFR, interleukin 17 (IL-17), tumor necrosis factor (TNF), hypoxia inducible factor 1 (HIF-1), phosphoinositide 3-kinase/AKT serine/threonine kinase (PI3K/AKT) and Toll-like receptor signaling pathways were identified as the key anti-COVID-19/PF co-occurrence pathways. Conclusion: Kaempferol is a candidate treatment for COVID-19/PF co-occurrence. The underlying mechanisms may be related to the regulation of critical targets (EGFR, SRC, MAPK3, MAPK1, MAPK8, AKT1, RELA, PIK3CA and so on) and EGFR, IL-17, TNF, HIF-1, PI3K/AKT and Toll-like receptor signaling pathways. This study contributes to guiding development of new drugs for COVID-19 and PF comorbidities.

Visible pyramid wavefront sensing approach for daylight adaptive optics.

Daytime application of the pyramid wavefront sensor (PyWFS) is greatly challenged by a bright and fluctuating sky background, especially in the visible. A daytime-Py approach to apply visible pyramid wavefront sensing for real-time daylight AO is described in this paper. A field stop (FS) and a lenslet array are applied in the daylight AO system based on a visible PyWFS to separate the object signal from the background signal and improve the signal-to-noise ratio (SNR). A background elimination algorithm is proposed to extract the effective object signal. Closed-loop experiment using the daytime-Py approach is performed, which presents the first laboratory real-time daylight natural guide star AO correction of a faint object based on a visible PyWFS. SNR ranges for both the daytime-Py approach and PyWFS are reported. Furthermore, the correction results in different SNRs using both methods and with various pupil samplings using the daytime-Py approach are presented to prove that our proposal has the advantages over the PyWFS and Shack-Hartmann wavefront sensor (SHWFS) for daylight AO. This study demonstrates that the daytime-Py approach can realize the real-time object tracking and closed-loop correction in the daylight natural guide star adaptive optics (AO) system based on the visible PyWFS.

Application of the Gaussian modeling algorithm to a Shack-Hartmann wavefront sensor for daylight adaptive optics.

Daytime use of Shack-Hartmann wavefront sensor (SHWS)-based adaptive optics (AO) at a telescope is hindered by the fluctuating bright sky background. Therefore, we propose a Gaussian modeling centroid extraction algorithm that performs real-time daylight AO closed-loop corrections. The algorithm is executed in the process of modeling and updating each pixel of the consecutive SHWS images. The simulation results show that our method can provide a lower centroid estimation error (CEE) for bright sky background conditions. We also performed a field experiment on a 2 m ground-based telescope and achieved a daylight AO correction of 2.1 times diffraction limit for a star with a visual magnitude of 4.7 (HIP113116) when the elevation angle of the sun was 7.7°. This represents the first publicly reported daylight natural guide star AO correction result on a 2 m class telescope.

Identification of Potential Pathogenic Super-Enhancers-Driven Genes in Pulmonary Fibrosis.

Abnormal fibroblast differentiation into myofibroblast is a crucial pathological mechanism of pulmonary fibrosis (PF). Super-enhancers, a newly discovered cluster of regulatory elements, are regarded as the regulators of cell identity. We speculate that abnormal activation of super-enhancers must be involved in the pathological process of PF. This study aims to identify potential pathogenic super-enhancer-driven genes in PF. Differentially expressed genes (DEGs) in PF mouse lungs were identified from a GEO dataset (GDS1492). We collected super-enhancers and their associated genes in human lung fibroblasts and mouse embryonic fibroblasts from SEA version 3.0, a network database that provides comprehensive information on super-enhancers. We crosslinked upregulated DEGs and super-enhancer-associated genes in fibroblasts to predict potential super-enhancer-driven pathogenic genes in PF. A total of 25 genes formed an overlap, and the protein-protein interaction network of these genes was constructed by the STRING database. An interaction network of transcription factors (TFs), super-enhancers, and associated genes was constructed using the Cytoscape software. Gene enrichment analyses, including KEGG pathway and GO analysis, were performed for these genes. Latent transforming growth factor beta (TGF-ß) binding protein 2 (LTBP2), one of the predicted super-enhancer-driven pathogenic genes, was used to verify the predicted network's accuracy. LTBP2 was upregulated in the lungs of the bleomycin-induced PF mouse model and TGF-ß1-stimulated mouse and human fibroblasts. Myc is one of the TFs binding to the LTBP2 super-enhancer. Knockout of super-enhancer sequences with a CRISPR/Cas9 plasmid or inhibition of Myc all decreased TGF-ß1-induced LTBP2 expression in NIH/3 T3 cells. Identifying and interfering super-enhancers might be a new way to explore possible therapeutic methods for PF.

Performance analysis of 349-element adaptive optics unit for a coherent free space optical communication system.

As a continuation of our previous work [Optics Express.25, 15229(2017)] in which we have verified the performance of a coherent free space optical communication (FSOC) system with a 97-element adaptive optics (AO) system, in this paper, we evaluated the performance improvement of the coherent FSOC system using a large-scale high-speed AO system with a 349-element continuous surface deformable mirror. The mixing efficiency (ME) and bit-error-rate (BER) under different Greenwood frequency (GF) were calculated as the performance metric of coherent FSOC system. The performance of FSOC system using such a large-scale AO system was quantitatively verified for the first time. The obtained results showed that the performance was obviously improved when a larger-scale high-speed AO system is employed in coherent FSOC system. This analysis result provides a performance verification for large-scale high-speed AO systems used in FSOC system which is beneficial for coherent FSOC system parameters design.

Analysis of a holographic laser adaptive optics system using a deformable mirror.

We describe a closed-loop holographic laser adaptive optics system (HLAOS) based on a holographic wavefront sensor (HWFS) and 21-element continuous-surface piezoelectric deformable mirror (DM). The principle behind HWFSs is described, and then the response sensitivity and crosstalk effect on the lowest 12 Zernike modes of aberration are analyzed. Next, the wavefront-correction capability of the 21-element DM is analyzed. The closed-loop correction of the HLAOS to a static aberration is then numerically simulated. We report a practical implementation of the HLAOS and compare the aberration-compensation effect with a traditional adaptive optics system based on a 37-unit Shark-Hartmann sensor. The practically relevant parameters are analyzed and the experimental results show that an HLAOS using a piezoelectric DM can achieve a correction capability comparable to that of a traditional adaptive optics system.

Performance evaluation of coherent free space optical communications with a double-stage fast-steering-mirror adaptive optics system depending on the Greenwood frequency.

The Greenwood frequency (GF) is influential in performance improvement for the coherent free space optical communications (CFSOC) system with a closed-loop adaptive optics (AO) unit. We analyze the impact of tilt and high-order aberrations on the mixing efficiency (ME) and bit-error-rate (BER) under different GF. The root-mean-square value (RMS) of the ME related to the RMS of the tilt aberrations, and the GF is derived to estimate the volatility of the ME. Furthermore, a numerical simulation is applied to verify the theoretical analysis, and an experimental correction system is designed with a double-stage fast-steering-mirror and a 97-element continuous surface deformable mirror. The conclusions of this paper provide a reference for designing the AO system for the CFSOC system.

Closed-loop adaptive optics system with a single liquid crystal spatial light modulator.

We describe a closed-loop dynamic holographic adaptive optics system. This system can be realized via one liquid crystal spatial light modulator and one CCD camera. The liquid crystal spatial light modulator is used as the wavefront sensor and corrector, as well as imaging element. CCD detects the spots at holographic image plane and at focal plane of imaging channel simultaneously. The basic principle of the system is introduced first, and then the numerical analysis is presented. On this basis, we report a practical implementation of the dynamic holographic adaptive optics system. The results show that a rapid increase of Strehl ratio and improved image quality at focal plane for deliberately introduced aberrations can be achieved, verifying the feasibility of the system.

Lack of association between the dopamine transporter gene 3' VNTR polymorphism and attention deficit hyperactivity disorder in Chinese Han children: case-control and family-based studies.

Attention deficit hyperactivity disorder (ADHD) is the most common childhood onset neurodevelopment disorder. The etiology is unclear, but is suspected to involve the dopamine system. In this study we used the haplotype-based haplotype relative risk (HHRR) analysis and the transmission disequilibrium test (TDT) to investigate the potential contribution of dopamine transporter (DAT1) gene variants to ADHD. DAT1 gene polymorphisms were assessed in 54 ADHD Chinese Han children and all 108 of their parents and 66 normal child controls. No differences were found in either genotype or allele distributions. The HHRR analysis of the DAT1 polymorphisms suggests that the transmission of this polymorphism is not significantly associated with ADHD. And the TDT result showed that ADHD was not in linkage with the DAT1 gene. These findings do not support the hypothesis that DAT1 gene variants contribute to the pathogenesis of ADHD in Chinese Han population.