MicroRNA-522-3p promotes brain metastasis in non-small cell lung cancer by targeting Tensin 1 and modulating blood-brain barrier permeability.

Brain metastases account for more than 50% of intracranial central nervous system tumors. The blood-brain barrier (BBB) is mainly composed of endothelial cells, which exhibit low endocytosis and high efflux pumps. Although they are connected by continuous tight junctions and serve as a protective insulation, the BBB does not prevent the development of brain metastases from non-small cell lung cancer (NSCLC). Improving understanding on the mechanisms underlying the development of brain metastasis and the differential molecular characteristics relative to the primary tumor are therefore key in the treatment of brain metastases. This study evaluated the differential expression of miR-522-3p in NSCLC and brain metastases using the Gene Expression Omnibus database. NSCLC brain metastasis model was constructed to screen for cell lines that demonstrated high potential for brain metastasis; We also observed differential expression of miRNA-522-3p in the paraffin-embedded specimens of non-small cell lung cancer and brain metastases from our hospital. The molecular biological functions of miRNA-522-3p were verified using 5-ethynyl-2'-deoxyuridine (EdU) proliferation assay and Transwell invasion assays. RNA-seq was employed to identify downstream target proteins, and the dual-luciferase reporter assay confirmed Tensin 1 (TNS1), a protein that links the actin cytoskeleton to the extracellular matrix, as the downstream regulatory target protein. In vitro blood-brain barrier models and co-culture models were constructed to further identify the role of miRNA-522-3p and TNS1; the expression of BBB-related proteins (ZO-1 and OLCN) was also identified. In vivo experiments were performed to verify the effects of miRNA-522-3p on the time and incidence of NSCLC brain metastasis. The results showed significantly high expression in GSE51666; consistent results were obtained in brain metastasis cells and paraffin samples. RNA-seq combined with miRNA target protein prediction demonstrated TNS1 to be directly downstream of miR-522-3p and to be associated with cell proliferation and invasion. By regulating ZO-1 and OCLN expression, mi-522-3p/TNS1 may increase tumor cell penetration through the BBB while decreasing its permeability. In vivo, miR-522-3p was further demonstrated to significantly promote the formation of brain metastases. miR-522-3p/TNS1 can affect BBB permeability and encourage the growth of brain metastases by modifying the BBB TJ proteins. This axis offers new therapeutic targets for the prevention of brain metastasis.

A Region-Monitoring-Type Slitless Imaging Spectrometer.

In modern scientific practice, it is necessary to consistently observe predetermined zones, with the expectation of detecting and identifying emerging targets or events inside such areas. This research presents an innovative imaging spectrometer system for the continuous monitoring of specific areas. This study begins by providing detailed information on the features and optical structure of the constructed instrument. This is then followed by simulations using optical design tools. The device has an F-number of 5, a focal length of 100 mm, a field of view of 3 × 7, and a wavelength range spanning from 400 nm to 600 nm. The optical path diagram demonstrates that the system's dispersion and imaging pictures can be distinguished, hence fulfilling the system's specifications. Furthermore, the utilization of a Modulation Transfer Function (MTF) graph has substantiated that the image quality indeed satisfies the specified criteria. To evaluate the instrument's performance in the spectrum observation of fixed regions, a region-monitoring-type slitless imaging spectrometer was built. The equipment has the capability to identify a specific region and rapidly capture the spectra of objects or events that are present inside that region. The spectral data were collected effectively by the implementation of image processing techniques on the captured photos. The correlation coefficient between these data and the reference data was 0.9226, showing that the device successfully measured the target's spectrum. Therefore, the instrument that was created successfully demonstrated its ability to capture images of the observed areas and collect spectral data from the targets located within those regions.

[Clinical and genetic analysis of a child with X-linked mental retardation due to variant of SLC9A7 gene].

OBJECTIVE: To explore the clinical and genetic characteristics of a child with mental retardation, language and motor developmental delay and epilepsy. METHODS: A child who was admitted to the First Affiliated Hospital of Zhengzhou University in March 2020 for intermittent seizures for over two months was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples of the child and his parents were collected and subjected to high throughput sequencing. Candidate variants were verified by Sanger sequencing and bioinformatic analysis. RESULTS: The clinical manifestations of the child have included mental retardation, language and motor developmental delay, and seizures. High-throughput sequencing revealed that he has harbored a hemizygous splice site variant (NM_032591.3: c.1030-1G>C) of the SLC9A7 gene, which was inherited from his mother and unreported previously. CONCLUSION: The hemizygous splice site variant (NM_032591.3: c.1030-1G>C) of the SLC9A7 gene probably underlay the disease in this child. Above finding has provided a basis for clinical diagnosis and genetic counseling.

GKLF, a transcriptional activator of Txnip, drives microglia activation in kainic acid-induced murine models of epileptic seizures.

Neuroinflammation is a major component of epilepsy. Gut-enriched Kruppel-like factor (GKLF), a transcription factor of Kruppel-like factor family, has been reported to promote microglia activation and mediate neuroinflammation. However, the role of GKLF in epilepsy remains poorly characterized. This study focused on the function of GKLF in neuron loss and neuroinflammation in epilepsy and the molecular mechanism underlying microglia activation induced by GKLF upon lipopolysaccharides (LPS) treatment. An experimental epileptic model was induced by an intraperitoneal injection of 25 mg/kg kainic acid (KA). Lentivirus vectors (Lv) carrying Gklf CDS or short hairpin RNA targeting Gklf (shGKLF) was injected into the hippocampus, resulting in Gklf overexpression or knockdown in the hippocampus. BV-2 cells were co-infected with Lv-shGKLF or/and Lv carrying thioredoxin interacting protein (Txnip) CDS for 48 h and treated with 1 µg/mL LPS for 24 h. Results showed that GKLF enhanced KA-induced neuronal loss, pro-inflammatory cytokine secretion, activation of NOD-like receptor protein-3 (NLRP3) inflammasomes and microglia, and TXNIP expression in the hippocampus. GKLF inhibition showed negative effects on LPS-induced microglia activation, as evidenced by reduced pro-inflammatory cytokine secretion and activation of NLRP3 inflammasomes. GKLF bound to Txnip promoter and increased TXNIP expression in LPS-activated microglia. Interestingly, Txnip overexpression reversed the inhibitory effect of Gklf knockdown on microglia activation. These findings indicated that GKLF was involved in microglia activation via TXNIP. This study demonstrates the underlying mechanism of GKLF in the pathogenesis of epilepsy and uncovers that GKLF inhibition may be a therapeutic strategy for epilepsy treatment.

Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment.

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma. Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan-Meier (K-M) analysis was performed to determine each cohort's survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT-qPCR and IHC were used to identify the consistency of the signature in tumor tissue. Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT-PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model. Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy.

Partitionable High-Efficiency Multilayer Diffractive Optical Neural Network.

A partitionable adaptive multilayer diffractive optical neural network is constructed to address setup issues in multilayer diffractive optical neural network systems and the difficulty of flexibly changing the number of layers and input data size. When the diffractive devices are partitioned properly, a multilayer diffractive optical neural network can be constructed quickly and flexibly without readjusting the optical path, and the number of optical devices, which increases linearly with the number of network layers, can be avoided while preventing the energy loss during propagation where the beam energy decays exponentially with the number of layers. This architecture can be extended to construct distinct optical neural networks for different diffraction devices in various spectral bands. The accuracy values of 89.1% and 81.0% are experimentally evaluated for MNIST database and MNIST fashion database and show that the classification performance of the proposed optical neural network reaches state-of-the-art levels.

Corrigendum: Developing an immune-related signature for predicting survival rate and the response to immune checkpoint inhibitors in patients with glioma.

[This corrects the article DOI: 10.3389/fgene.2022.899125.].

miR-596-3p suppresses brain metastasis of non-small cell lung cancer by modulating YAP1 and IL-8.

Brain metastasis (BM) frequently occurs in advanced non-small cell lung cancer (NSCLC) and is associated with poor clinical prognosis. Due to the location of metastatic lesions, the surgical resection is limited and the chemotherapy is ineffective because of the existence of the blood brain barrier (BBB). Therefore, it is essential to enhance our understanding about the underlying mechanisms associated with brain metastasis in NSCLC. In the present study, we explored the RNA-Seq data of brain metastasis cells from the GEO database, and extracted RNA collected from primary NSCLC tumors as well as paired brain metastatic lesions followed by microRNA PCR array. Meanwhile, we improved the in vivo model and constructed a cancer stem cell-derived transplantation model of brain metastasis in mice. Our data indicated that the level of miR-596-3p is high in primary NSCLC tumors, but significantly downregulated in the brain metastatic lesion. The prediction target of microRNA suggested that miR-596-3p was considered to modulate two genes essential in the brain invasion process, YAP1 and IL-8 that restrain the invasion of cancer cells and permeability of BBB, respectively. Moreover, in vivo experiments suggested that our model mimics the clinical aspect of NSCLC and improves the success ratio of brain metastasis model. The results demonstrated that miR-596-3p significantly inhibited the capacity of NSCLC cells to metastasize to the brain. Furthermore, these finding elucidated that miR-596-3p exerts a critical role in brain metastasis of NSCLC by modulating the YAP1-IL8 network, and this miRNA axis may provide a potential therapeutic strategy for brain metastasis.

Developing an Immune-Related Signature for Predicting Survival Rate and the Response to Immune Checkpoint Inhibitors in Patients With Glioma.

Background: Glioma is one of the most aggressive cancer types affecting the central nerve system, with poor overall survival (OS) rates. The present study aimed to construct a novel immune-related signature to predict prognosis and the efficiency of immunotherapy in patients with glioma. Methods: The mRNA expression data and other clinical information of patients with glioblastoma multiforme (GBM) and low grade glioma (LGG) were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The immune-related genes were obtained from the Immunology Database and Analysis Portal database. Subsequently, an immune-related signature was created following the results obtained from the Least Absolute Shrinkage and Selection Operator regression model. To validate the predictability of the signature, Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves were created. Moreover, both univariate and multivariate analyses were carried out using the OS between this signature and other clinicopathologic factors, and a nomogram was constructed. In addition, the association between signature, immune cell infiltration, tumor mutation burden and immunophenoscore were determined. Results: Results of the present study using 118 GBM and LGG samples uncovered 15 immune-related genes that were also differently expressed in glioma samples. These were subsequently used to construct the immune-related signature. This signature exhibits the ability to predict prognosis, the infiltration of immune cells in the tumor microenvironment and the response of patients with glioma to immunotherapy. Conclusion: Results of the present study demonstrated that the aforementioned novel immune-related signature may accurately predict prognosis and the response of patients with glioma to immunotherapy.

[Clinical and genetic analysis of a child with mental retardation autosomal dominant 7].

OBJECTIVE: To analyze the clinical and genetic characteristics of a child with clinical manifestations of hypoplasia, epilepsy and abnormal face. METHODS: The clinical data of the child were collected. The peripheral blood samples of the patient and his parents were extracted for high-throughput sequencing, and Sanger sequencing verification and bioinformatics analysis were performed to detect suspected pathogenic variants. RESULTS: The clinical manifestations of the child were overall developmental backwardness, seizures, autism, and special facial appearance. High throughput sequencing showed that there was a heterozygous mutation of exon 11: c.1920_c.1927delCCTCTACC (p.Ser641Rfs*31) of the DYRK1A gene. The same variant was found in neither of her parents, suggesting that it has a denovo origin. CONCLUSION: The exon11: c.1920_c.1927delCCTCTACC (p.Ser641Rfs*31) mutation in DYRK1A gene was the genetic etiology of the case, which enriches the pathogenic gene spectrum of DYRK1A and provides the basis for clinical diagnosis and genetic counseling.

Circular RNA circBFAR promotes glioblastoma progression by regulating a miR-548b/FoxM1 axis.

Glioblastoma multiforme (GBM) is the most common and aggressive type of tumor of the primary nervous system. Treatment options for GBM include surgery, chemotherapy, and radiation therapy; however, the clinical outcomes are poor, with a high rate of recurrence. An increasing number of studies have shown that circular RNAs (circRNAs) serve important roles in several types of cancer. Gene Expression Omnibus (GEO) database was utilized to identify the differentially expressed circRNAs and their biological functions. Then, we detected the circular RNA bifunctional apoptosis regulator (circBFAR) was significantly increased in three GEO datasets. However, the role of circBFAR has not been reported in GBM. In this study, the expression of circBFAR was significantly increased both in GBM tissues or cell lines and was negatively correlated with overall survival in patients with GBM. Knockdown of circBFAR inhibited proliferation and invasion both in vitro and in vivo. Increased expression of circBFAR resulted in a reduction of miR-548b expression in glioma cells. A luciferase reporter and RIP assay indicated that miR-548b was a direct target of circBFAR, and miR-548b may negatively regulate the expression of FoxM1. Rescue experiments showed that overexpression of FoxM1 could counter the effect of circBFAR silencing on the proliferation and invasion of glioma cell lines. Moreover, we identified that circBFAR regulates FoxM1 by interacting with miR-548b in glioma cells. In conclusion, the present study demonstrated that a circBFAR/miR-548b/FoxM1 axis regulates the development of GBM and highlights potentially novel therapeutic targets for the treatment of GBM.

Optical SAR data processing configuration with simultaneous azimuth and range matching filtering.

The real-time processing of synthetic aperture radar (SAR) data has a high requirement for the processor, which is a difficult problem in SAR real-time processing. With the rapid development of optoelectronic devices, traditional electrical SAR data processing can be converted into optoelectronic processing to improve the processing speed. In this paper, a new type of optical device is proposed to improve the processing speed of SAR data. With the help of a spatial light modulator (SLM), the initial SAR signal and matched filter function are loaded on the input plane and spectrum plane of the 4f system, respectively. Using an optical lens with the function of the Fourier transform, the Fourier transform and inverse Fourier transform of the SAR signal are carried out to realize the fast imaging of SAR. In theory, the processing speed of SAR data is the speed of light. Compared with traditional methods such as the range-Doppler (RD) algorithm, it is no longer necessary to carry out a one-dimensional Fourier transform but to carry out matching filtering for the azimuth and range of the spectrum plane of 4f system at the same time. In this way, it is not necessary to introduce a cylindrical lens, only a spherical lens is needed to realize the Fourier transform imaging of SAR. Finally, a two-dimensional SAR processing optical system is built to obtain the SAR image in real time.

A High Optical Throughput Spectral Imaging Technique Using Broadband Filters.

To address the miniaturization of the spectral imaging system required by a mounted platform and to overcome the low luminous flux caused by current spectroscopic technology, we propose a method for the multichannel measurement of spectra using a broadband filter in this work. The broadband filter is placed in front of a lens, and the spectral absorption characteristics of the broadband filter are used to achieve the modulation of the incident spectrum of the detection target and to establish a mathematical model for the detection of the target. The spectral and spatial information of the target can be obtained by acquiring data using a push-broom method and reconstructing the spectrum using the GCV-based Tikhonov regularization algorithm. In this work, we compare the accuracy of the reconstructed spectra using the least-squares method and the Tikhonov algorithm based on the L-curve. The effect of errors in the spectral modulation function on the accuracy of the reconstructed spectra is analyzed. We also analyze the effect of the number of overdetermined equations on the accuracy of the reconstructed spectra and consider the effect of detector noise on the spectral recovery. A comparison between the known data cubes and our simulation results shows that the spectral image quality based on broadband filter reduction is better, which validates the feasibility of the method. The proposed method of combining broadband filter-based spectroscopy with a panchromatic imaging process for measurement modulation rather than spectroscopic modulation provides a new approach to spectral imaging.

Long-Distance Sub-Diffraction High-Resolution Imaging Using Sparse Sampling.

How to perform imaging beyond the diffraction limit has always been an essential subject for the research of optical systems. One effective way to achieve this purpose is Fourier ptychography, which has been widely used in microscopic imaging. However, microscopic imaging measurement technology cannot be directly extended to imaging macro objects at long distances. In this paper, a reconstruction algorithm is proposed to solve the need for oversampling low-resolution images, and it is successfully applied to macroscopic imaging. Compared with the traditional FP technology, the proposed sub-sampling method can significantly reduce the number of iterations in reconstruction. Experiments prove that the proposed method can reconstruct low-resolution images captured by the camera and achieve high-resolution imaging of long-range macroscopic objects.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

Optimal design of tilt carrier frequency computer-generated holograms to measure aspherics.

Computer-generated holograms (CGHs) provide an approach to high-precision metrology of aspherics. A CGH is designed under the trade-off among size, mapping distortion, and line spacing. This paper describes an optimal design method based on the parametric model for tilt carrier frequency CGHs placed outside the interferometer focus points. Under the condition of retaining an admissible size and a tolerable mapping distortion, the optimal design method has two advantages: (1) separating the parasitic diffraction orders to improve the contrast of the interferograms and (2) achieving the largest line spacing to minimize sensitivity to fabrication errors. This optimal design method is applicable to common concave aspherical surfaces and illustrated with CGH design examples.

Lactobacillus salivarius strain FDB89 induced longevity in Caenorhabditis elegans by dietary restriction.

In this study, we utilized the nematode Caenorhabditis elegans to assess potential life-expanding effect of Lactobacillus salivarius strain FDB89 (FDB89) isolated from feces of centenarians in Bama County (Guangxi, China). This study showed that feeding FDB89 extended the mean life span in C. elegans by up to 11.9% compared to that of control nematodes. The reduced reproductive capacities, pharyngeal pumping rate, growth, and increased superoxide dismutase (SOD) activity and XTT reduction capacity were also observed in FDB89 feeding worms. To probe the anti-aging mechanism further, we incorporated a food gradient feeding assay and assayed the life span of eat-2 mutant. The results demonstrated that the maximal life span of C. elegans fed on FDB89 was achieved at the concentration of 1.0 mg bacterial cells/plate, which was 10-fold greater than that of C. elegans fed on E. coli OP50 (0.1 mg bacterial cells/plate). However, feeding FDB89 could not further extend the life span of eat-2 mutant. These results indicated that FDB89 modulated the longevity of C. elegans in a dietary restriction-dependent manner and expanded the understanding of anti-aging effect of probiotics.