Single Image Super-Resolution Using a Deep Encoder-Decoder Symmetrical Network with Iterative Back Projection

Image super-resolution (SR) usually refers to reconstructing a high resolution (HR) image from a low resolution (LR) image without losing high frequency details or reducing the image quality. Recently, image SR based on convolutional neural network (SRCNN) was proposed and has received much attention due to its end-to-end mapping simplicity and superior performance. This method, however, only using three convolution layers to learn the mapping from LR to HR, usually converges slowly and leads to the size of output image reducing significantly. To address these issues, in this work, we propose a novel deep encoder-decoder symmetrical neural network (DEDSN) for single image SR. This deep network is fully composed of symmetrical multiple layers of convolution and deconvolution and there is no pooling (down-sampling and up-sampling) operations in the whole network so that image details degradation occurred in traditional convolutional frameworks is prevented. Additionally, in view of the success of the iterative back projection (IBP) algorithm in image SR, we further combine DEDSN with IBP network realization in this work. The new DEDSN-IBP model introduces the down sampling version of the ground truth image and calculates the simulation error as the prior guidance. Experimental results on benchmark data sets demonstrate that the proposed DEDSN model can achieve better performance than SRCNN and the improved DEDSN-IBP outperforms the reported state-of-the-art methods

Single Image Super-Resolution Using a Deep Encoder-Decoder Symmetrical Network with Iterative Back Projection

Image super-resolution (SR) usually refers to reconstructing a high resolution (HR) image from a low resolution (LR) image without losing high frequency details or reducing the image quality. Recently, image SR based on convolutional neural network (SRCNN) was proposed and has received much attention due to its end-to-end mapping simplicity and superior performance. This method, however, only using three convolution layers to learn the mapping from LR to HR, usually converges slowly and leads to the size of output image reducing significantly. To address these issues, in this work, we propose a novel deep encoder-decoder symmetrical neural network (DEDSN) for single image SR. This deep network is fully composed of symmetrical multiple layers of convolution and deconvolution and there is no pooling (down-sampling and up-sampling) operations in the whole network so that image details degradation occurred in traditional convolutional frameworks is prevented. Additionally, in view of the success of the iterative back projection (IBP) algorithm in image SR, we further combine DEDSN with IBP network realization in this work. The new DEDSN-IBP model introduces the down sampling version of the ground truth image and calculates the simulation error as the prior guidance. Experimental results on benchmark data sets demonstrate that the proposed DEDSN model can achieve better performance than SRCNN and the improved DEDSN-IBP outperforms the reported state-of-the-art methods

DAPK1 as an independent prognostic marker in liver cancer

The death-associated protein kinase 1 (DAPK1) can act as an oncogene or a tumor suppressor gene depending on the cellular context as well as external stimuli. Our study aims to investigate the prognostic significance of DAPK1 in liver cancer in both mRNA and protein levels. The mRNA expression of DAPK1 was extracted from the Gene Expression Omnibus database in three independent liver cancer datasets while protein expression of DAPK1 was detected by immunohistochemistry in our Chinese liver cancer patient cohort. The associations between DAPK1 expression and clinical characteristics were tested. DAPK1 mRNA expression was down-regulated in liver cancer. Low levels of DAPK1 mRNA were associated with shorter survival in a liver cancer patient cohort (n = 115; p = 0.041), while negative staining of DAPK1 protein was significantly correlated with shorter time to progression (p = 0.002) and overall survival (p = 0.02). DAPK1 was an independent prognostic marker for both time to progression and overall survival by multivariate analysis. Liver cancer with the b-catenin mutation has a lower DAPK1 expression, suggesting that DAPK1 may be regulated under the b-catenin pathway. In addition, we also identified genes that are co-regulated with DAPK1. DAPK1 expression was positively correlated with IRF2, IL7R, PCOLCE and ZBTB16, and negatively correlated with SLC16A3 in both liver cancer datasets. Among these genes, PCOLCE and ZBTB16 were significantly down-regulated, while SLC16A3 was significantly upregulated in liver cancer. By using connectivity mapping of these co-regulated genes, we have identified amcinonide and sulpiride as potential small molecules that could potentially reverse DAPK1/PCOLCE/ZBTB16/SLC16A3 expression. Our study demonstrated for the first time that both DAPK1 mRNA and protein expression levels are important prognostic markers in liver cancer, and have identified genes that may contribute to DAPK1-mediated liver carcinogenesis

Single Image Super-Resolution Using Multi-Scale Deep Encoder-Decoder with Phase Congruency Edge Map Guidance

This paper presents an end-to-end multi-scale deep encoder (convolution) and decoder (deconvolution) network for single image super-resolution (SISR) guided by phase congruency (PC) edge map. Our system starts by a single scale symmetrical encoder-decoder structure for SISR, which is extended to a multi-scale model by integrating wavelet multi-resolution analysis into our network. The new multi-scale deep learning system allows the low resolution (LR) input and its PC edge map to be combined so as to precisely predict the multi-scale super-resolved edge details with the guidance of the high-resolution (HR) PC edge map. In this way, the proposed deep model takes both the reconstruction of image pixels’ intensities and the recovery of multi-scale edge details into consideration under the same framework. We evaluate the proposed model on benchmark datasets of different data scenarios, such as Set14 and BSD100 - natural images, Middlebury and New Tsukuba - depth images. The evaluations based on both PSNR and visual perception reveal that the proposed model is superior to the state-of-the-art methods

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

DNA-Modified Polysulphone Microspheres for Endocrine Disruptors and Heavy Metal Ions Removal

Porous polysulphone (PSf) microspheres were modified by blending DNA into them and immobilizing DNA onto their surfaces. The DNA-modified microspheres, which were stable in water, were then used to remove endocrine disruptors and heavy metal ions from their aqueous solutions. Such microspheres could effectively accumulate pollutant compounds and endocrine disruptors, such as ethidium bromide, Acridine Orange, biphenyl, dibenzofuran and dibenzo- p -dioxin from their aqueous solutions. PSf microspheres without DNA also accumulated and removed endocrine disruptors due to their porosity and the hydrophobic interaction between the endocrine disruptors and PSf. Endocrine disruptors with and without a planar structure were effectively accumulated and removed by the DNA-modified PSf microspheres. In addition, PSf microspheres were found to be capable of selectively removing heavy metal ions such as Zn 2+ , Cu 2+ , Mg 2+ , Cd 2+ and Ag + from their aqueous solutions. These results show that DNA can be used to modify PSf microspheres, with the DNA-modified microspheres having a potential use in environmental applications

AMPK activation by AICAR attenuated the TSH-mediated increase in SREBP-2.

<p>(A) TSH decreased AMPK activity. HepG2 cells were synchronized overnight in serum-free EMEM and then treated with AICAR (0.5 mM) or TSH (4 μmol/L) for 24 h. AMPK activity was measured using the SAMS peptide phosphorylation assay and was calculated as picomoles per minute per milligram protein. The data are presented as the mean ± SEM (n = 4). *<i>p</i> < 0.05 compared with control (con). ^#<i>p</i> < 0.05 versus TSH. (B) HepG2 cells were pretreated with TSH (4 μM) for 24 h in the absence or presence of AICAR (0.5 mM) for 24 h. Whole cell lysates were subjected to WB using the SREBP-2 antibody. (C-D) Densitometric quantification of SREBP-2 (P) and SREBP-2 (N). The data are presented as the mean ± SEM. *<i>p</i> < 0.05 versus untreated cells; ^#<i>p</i> < 0.05 versus TSH-treated cells. (E) AICAR activated AMPK, which down-regulated the mRNA expression of HMGCR and HMGCS in TSH-treated HepG2 cells. These experiments were repeated at least three times with similar results.</p

AMPK activation by AICAR induced the threonine phosphorylation of the precursor and nuclear forms of SREBP-2.

<p>(A) HepG2 cells were transfected with pc-DNA3.1 encoding 2×flag-tagged human nuclear SREBP-2 or pcDNA empty vector or vehicle for 48 h and then were treated with or without AICAR (1 mM) for 24 h. Cell lysates were purified by immunoprecipitation (IP) with an anti-Flag antibody and were subjected to WB with antibodies against phosphorylated-Threonine (p-Thr) or phosphorylated-Serine (p-Ser). Total lysates were analyzed by WB with anti-flag and SREBP-2 antibodies as indicated. (B) HepG2 cells were treated with AICAR (1 mM) for 24 h, and the cell lysates were immunoprecipitated with an SREBP-2 antibody and subjected to WB with antibodies against p-Thr and p-Ser (data not shown). SREBP-2(P) denotes the antibody that only recognizes the SREBP-2 precursor. (C) Total protein (500 μg) from <i>Tshr</i>^<i>+/+</i> and <i>Tshr</i>^<i>-/-</i> mouse liver extracts were purified by IP with the SREBP-2 precursor antibody and subjected to WB with the p-Thr antibody. Total lysates were analyzed by WB with antibodies against p-AMPK and SREBP-2 as indicated. (D) Lysates from L02 cells treated with AICAR for 24 h were subjected to IP with an SREBP-2 antibody and then analyzed by WB with an antibody against p-Thr.</p

AICAR-activated AMPK decreased SREBP-2 protein levels.

<p>(A) HepG2 cells were treated with or without 0.5 mmol/l (0.5 mM) AICAR for 12 or 24 h and were subsequently washed with phosphate-buffered saline (PBS) and lysed. Nuclear and cytoplasmic extracts were analyzed by WB. β-actin was used as a cytoplasmic marker, and LaminB1 (LMNB1) was used as the nuclear marker. (B-C) Densitometric quantification of SREBP-2 (P) and SREBP-2 (N). The data are presented as the mean ± SEM. *<i>p</i>< 0.05 versus control (con, without AICAR). (D) AICAR-activated AMPK inhibited the expression of SREBP-2 in HepG2 cells. HepG2 cells were treated with or without 0.5 mM AICAR for 12 or 24 h and then were harvested to determine the mRNA expression of SREBP-2. β-actin was used for normalization, and the control was set to 1 in the Real-Time PCR data. All the experiments were performed in duplicate. *<i>p</i> < 0.05 versus control. (E) Immunofluoresence images of SREBP-2 (red) and nuclear staining with 4', 6-diamidino-2-phenylindole (DAPI, blue) in HepG2 cells. Magnification, ×200. Semiquantification analysis by ImageJ software of fluorescence intensity of SREBP-2 precusor and nuclear form in HepG2 cells. Bar-graph represents the results from 3 separate experiments and the fluorescence intensity of SREBP-2 from HepG2 cells without AICAR treatment was set as 1.</p