A new asymmetrical corner detector(ACD) for a semi-automatic image co-registration scheme

Co-registration of multi-sensor and multi-temporal images is essential for remote sensing applications. In the image co-registration process, automatic Ground Control Points (GCPs) selection is a key technical issue and the accuracy of GCPs localization largely accounts for the final image co-registration accuracy. In this thesis, a novel Asymmetrical Corner Detector (ACD) algorithm based on auto-correlation is presented and a semi-automatic image co-registration scheme is proposed. The ACD is designed with the consideration of the fact that asymmetrical corner points are the most common reality in remotely sensed imagery data. The ACD selects points more favourable to asymmetrical points rather than symmetrical points to avoid incorrect selection of flat points which are often highly symmetrical. The experimental results using images taken by different sensors indicate that the ACD has obtained excellent performance in terms of point localization and computation efficiency. It is more capable of selecting high quality GCPs than some well established corner detectors favourable to symmetrical corner points such as the Harris Corner Detector (Harris and Stephens, 1988). A semi-automatic image co-registration scheme is then proposed, which employs the ACD algorithm to extract evenly distributed GCPs across the overlapped area in the reference image. The scheme uses three manually selected pairs of GCPs to determine the initial transformation model and the overlapped area. Grid-control and nonmaximum suppression methods are used to secure the high quality and spread distribution of GCPs selected. It also involves the FNCC (fast normalised crosscorrelation) algorithm (Lewis, 1995) to refine the corresponding point locations in the input image and thus the GCPs are semi-automatically selected to proceed to the polynomial fitting image rectification. The performance of the proposed coregistration scheme has been demonstrated by registering multi-temporal, multi-sensor and multi-resolution images taken by Landsat TM, ETM+ and SPOT sensors. Experimental results show that consistent high registration accuracy of less than 0.7 pixels RMSE has been achieved. Keywords: Asymmetrical corner points, image co-registration, AC

Sno/scaRNAbase: a curated database for small nucleolar RNAs and cajal body-specific RNAs

Small nucleolar RNAs (snoRNAs) and Cajal body-specific RNAs (scaRNAs) are named for their subcellular localization within nucleoli and Cajal bodies (conserved subnuclear organelles present in the nucleoplasm), respectively. They have been found to play important roles in rRNA, tRNA, snRNAs, and even mRNA modification and processing. All snoRNAs fall in two categories, box C/D snoRNAs and box H/ACA snoRNAs, according to their distinct sequence and secondary structure features. Box C/D snoRNAs and box H/ACA snoRNAs mainly function in guiding 2′-O-ribose methylation and pseudouridilation, respectively. ScaRNAs possess both box C/D snoRNA and box H/ACA snoRNA sequence motif features, but guide snRNA modifications that are transcribed by RNA polymerase II. Here we present a Web-based sno/scaRNA database, called sno/scaRNAbase, to facilitate the sno/scaRNA research in terms of providing a more comprehensive knowledge base. Covering 1979 records derived from 85 organisms for the first time, sno/scaRNAbase is not only dedicated to filling gaps between existing organism-specific sno/scaRNA databases that are focused on different sno/scaRNA aspects, but also provides sno/scaRNA scientists with an opportunity to adopt a unified nomenclature for sno/scaRNAs. Derived from a systematic literature curation and annotation effort, the sno/scaRNAbase provides an easy-to-use gateway to important sno/scaRNA features such as sequence motifs, possible functions, homologues, secondary structures, genomics organization, sno/scaRNA gene's chromosome location, and more. Approximate searches, in addition to accurate and straightforward searches, make the database search more flexible. A BLAST search engine is implemented to enable blast of query sequences against all sno/scaRNAbase sequences. Thus our sno/scaRNAbase serves as a more uniform and friendly platform for sno/scaRNA research. The database is free available at

Single-cell RNA analysis to identify five cytokines signaling in immune-related genes for melanoma survival prognosis

Melanoma is one of the deadliest skin cancers. Recently, developed single-cell sequencing has revealed fresh insights into melanoma. Cytokine signaling in the immune system is crucial for tumor development in melanoma. To evaluate melanoma patient diagnosis and treatment, the prediction value of cytokine signaling in immune-related genes (CSIRGs) is needed. In this study, the machine learning method of least absolute selection and shrinkage operator (LASSO) regression was used to establish a CSIRG prognostic signature of melanoma at the single-cell level. We discovered a 5-CSIRG signature that was substantially related to the overall survival of melanoma patients. We also constructed a nomogram that combined CSIRGs and clinical features. Overall survival of melanoma patients can be consistently predicted with good performance as well as accuracy by both the 5-CSIRG signature and nomograms. We compared the melanoma patients in the CSIRG high- and low-risk groups in terms of tumor mutation burden, infiltration of the immune system, and gene enrichment. High CSIRG-risk patients had a lower tumor mutational burden than low CSIRG-risk patients. The CSIRG high-risk patients had a higher infiltration of monocytes. Signaling pathways including oxidative phosphorylation, DNA replication, and aminoacyl tRNA biosynthesis were enriched in the high-risk group. For the first time, we constructed and validated a machine-learning model by single-cell RNA-sequencing datasets that have the potential to be a novel treatment target and might serve as a prognostic biomarker panel for melanoma. The 5-CSIRG signature may assist in predicting melanoma patient prognosis, biological characteristics, and appropriate therapy

Knock-down of glutaminase 2 expression decreases glutathione, NADH, and sensitizes cervical cancer to ionizing radiation

AbstractPhosphate-activated mitochondrial glutaminase (GLS2) is suggested to be linked with elevated glutamine metabolism. It plays an important role in catalyzing the hydrolysis of glutamine to glutamate. The present study was to investigate the potent effect of GLS2 on radioresistance of cervical carcinoma. GLS2 was examined in 144 cases of human cervical cancer specimens (58 radioresistant specimens, 86 radiosensitive specimens) and 15 adjacent normal cervical specimens with immunohistochemistry. HeLa cells were treated with a cumulative dose of 50Gy X-rays, over 6months, yielding the resistant sub-line HeLaR. The expressions of GLS2 were measured by Western blot. Radioresistance was tested by colony survival assay. Apoptosis was determined by flow cytometry. The levels of glutathione (GSH), reactive oxygen species (ROS), NAD+/NADH ratio and NADP+/NADPH ratio were detected by quantization assay kit. Xenografts were used to confirm the effect of GLS2 on radioresistance in vivo. The expressions of GLS2 were significantly enhanced in tumor tissues of radioresistant patients compared with that in radiosensitive patients. In vitro, the radioresistant cell line HeLaR exhibited significantly increased GLS2 levels than its parental cell line HeLa. GLS2 silenced radioresistant cell HeLaR shows substantially enhanced radiosensitivity with lower colony survival and higher apoptosis in response to radiation. In vivo, xenografts with GLS2 silenced HeLaR were more sensitive to radiation. At the molecular level, knock-down of GLS2 increased the intracellular ROS levels of HeLaR exposed to irradiation by decreasing the productions of antioxidant GSH, NADH and NADPH. GLS2 may have an important role in radioresistance in cervical cancer patients

Templated-Construction of Hollow MoS2 Architectures with Improved Photoresponses

: Despite the outstanding optoelectronic properties of MoS2 and its analogues, synthesis of such materials with desired features including fewer layers, arbitrary hollow structures, and particularly specifically customized morphologies, via inorganic reactions has always been challenging. Herein, using predesigned lanthanide-doped upconversion luminescent materials (e.g., NaYF4:Ln) as templates, arbitrary MoS2 hollow structures with precisely defined morphologies, widely variable dimensions, and very small shell thickness (≈2.5 nm) are readily constructed. Most importantly, integration of the near-infrared-responsive template significantly improves the photoresponse of up to 600 fold in device made of NaYF4:Yb/Er@MoS2 compared with that of MoS2 nanosheets under 980 nm laser illumination. Multichannel optoelectronic device is further fabricated by simply changing luminescent ions in the template, e.g., NaYF4:Er@MoS2, operating at 1532 nm light excitation with a 276-fold photoresponse enhancement. The simple chemistry, easy operation, high reliability, variable morphologies, and wide universality represent the most important advantages of this novel strategy that has not been accessed before

Novel Y-chromosomal microdeletions associated with non-obstructive azoospermia uncovered by high throughput sequencing of sequence-tagged sites (STSs)

Y-chromosomal microdeletion (YCM) serves as an important genetic factor in non-obstructive azoospermia (NOA). Multiplex polymerase chain reaction (PCR) is routinely used to detect YCMs by tracing sequence-tagged sites (STSs) in the Y chromosome. Here we introduce a novel methodology in which we sequence 1,787 (post-filtering) STSs distributed across the entire male-specific Y chromosome (MSY) in parallel to uncover known and novel YCMs. We validated this approach with 766 Chinese men with NOA and 683 ethnically matched healthy individuals and detected 481 and 98 STSs that were deleted in the NOA and control group, representing a substantial portion of novel YCMs which significantly influenced the functions of spermatogenic genes. The NOA patients tended to carry more and rarer deletions that were enriched in nearby intragenic regions. Haplogroup O2* was revealed to be a protective lineage for NOA, in which the enrichment of b1/b3 deletion in haplogroup C was also observed. In summary, our work provides a new high-resolution portrait of deletions in the Y chromosome.National Key Scientific Program of China [2011CB944303]; National Nature Science Foundation of China [31271244, 31471344]; Promotion Program for Shenzhen Key Laboratory [CXB201104220045A]; Shenzhen Project of Science and Technology [JCYJ20130402113131202, JCYJ20140415162543017]SCI(E)[email protected]; [email protected]; [email protected]

Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research

Cancer is a complex disease, the understanding and treatment of which are being aided through increases in the volume of collected data and in the scale of deployed computing power. Consequently, there is a growing need for the development of data-driven and, in particular, deep learning methods for various tasks such as cancer diagnosis, detection, prognosis, and prediction. Despite recent successes, however, designing high-performing deep learning models for nonimage and nontext cancer data is a time-consuming, trial-and-error, manual task that requires both cancer domain and deep learning expertise. To that end, we develop a reinforcement-learning-based neural architecture search to automate deep-learning-based predictive model development for a class of representative cancer data. We develop custom building blocks that allow domain experts to incorporate the cancer-data-specific characteristics. We show that our approach discovers deep neural network architectures that have significantly fewer trainable parameters, shorter training time, and accuracy similar to or higher than those of manually designed architectures. We study and demonstrate the scalability of our approach on up to 1,024 Intel Knights Landing nodes of the Theta supercomputer at the Argonne Leadership Computing Facility.Comment: SC '19: IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis, November 17--22, 2019, Denver, C

The Extra Domain A of Fibronectin Increases VEGF-C Expression in Colorectal Carcinoma Involving the PI3K/AKT Signaling Pathway

The extra domain A (EDA)-containing fibronectin (EDA-FN), an alternatively spliced form of the extracellular matrix protein fibronectin, is predominantly expressed in various malignancies but not in normal tissues. In the present study, we investigated the potential pro-lymphangiogenesis effects of extra domain A (EDA)-mediated vascular endothelial growth factor-C (VEGF-C) secretion in colorectal carcinoma (CRC). We detected the expressions of EDA and VEGF-C in 52 human colorectal tumor tissues and their surrounding mucosae by immunohistochemical analysis, and further tested the correlation between the expressions of these two proteins in aforementioned CRC tissues. Both EDA and VEGF-C were abundantly expressed in the specimens of human CRC tissues. And VEGF-C was associated with increased expression of EDA in human CRC according to linear regression analysis. Besides, EDA expression was significantly correlated with lymph node metastasis, tumor differentiation and clinical stage by clinicopathological analysis of tissue microarrays containing tumor tissues of 115 CRC patients. Then, human CRC cell SW480 was transfected with lentivectors to elicit expression of shRNA against EDA (shRNA-EDA), and SW620 was transfected with a lentiviral vector to overexpress EDA (pGC-FU-EDA), respectively. We confirmed that VEGF-C was upregulated in EDA-overexpressed cells, and downregulated in shRNA-EDA cells. Moreover, a PI3K-dependent signaling pathway was found to be involved in EDA-mediated VEGF-C secretion. The in vivo result demonstrated that EDA could promote tumor growth and tumor-induced lymphangiogenesis in mouse xenograft models. Our findings provide evidence that EDA could play a role in tumor-induced lymphangiogenesis via upregulating autocrine secretion of VEGF-C in colorectal cancer, which is associated with the PI3K/Akt-dependent pathway