Continuous warming drives the colonization dynamics of periphytic ciliate fauna in marine environments.

In order to evaluate the influence of global warming on the ecosystem processes in marine environments, the changes in colonization dynamics of periphytic microbiota were studied using the periphytic ciliate communities as the test organism fauna under a continuous warming gradient of 22℃ (control), 25℃, 28℃, 31℃, and 34 ℃. The results demonstrated that (1) the test ciliate communities generally showed a similar temporal pattern in within the colonization process under the water temperatures from 22 up to 28℃; however, (2) the colonization dynamics were significantly changed, and the fitness of colonization curves to the MacArthur-Wilson model equation was failed under the temperature increased by 6 ℃, and (3) the loading or assimilative capacity of the test aquatic ecosystem was decreased with the increase of water temperature. Therefore, this study suggests that continuous warming may significantly drive the colonization dynamics of periphytic ciliates in marine ecosystems.

Lattice Strain and Mott-Schottky Effect of the Charge-Asymmetry Pd1Fe Single-Atom Alloy Catalyst for Semi-Hydrogenation of Alkynes with High Efficiency.

The ideal interface design between the metal and substrate is crucial in determining the overall performance of the alkyne semihydrogenation reaction. Single-atom alloys (SAAs) with isolated dispersed active centers are ideal media for the study of reaction effects. Herein, a charge-asymmetry "armor" SAA (named Pd1Fe SAA@PC), which consists of a Pd1Fe alloy core and a semiconducting P-doped C (PC) shell, is rationally designed as an ideal catalyst for the selective hydrogenation of alkynes with high efficiency. Multiple spectroscopic analyses and density functional theory calculations have demonstrated that Pd1Fe SAA@PC is dual-regulated by lattice tensile and Schottky effects, which govern the selectivity and activity of hydrogenation, respectively. (1) The PC shell layer applied an external traction force causing a 1.2% tensile strain inside the Pd1Fe alloy to increase the reaction selectivity. (2) P doping into the C-shell layer realized a transition from a p-type semiconductor to an n-type semiconductor, thereby forming a unique Schottky junction for advancing alkyne semihydrogenation activity. The dual regulation of lattice strain and the Schottky effect ensures the excellent performance of Pd1Fe SAA@PC in the semihydrogenation reaction of phenylethylene, achieving a conversion rate of 99.9% and a selectivity of 98.9% at 4 min. These well-defined interface modulation strategies offer a practical approach for the rational design and performance optimization of semihydrogenation catalysts.

Sulfur Modified Carbon-Based Single-Atom Catalysts for Electrocatalytic Reactions.

Efficient and sustainable energy development is a powerful tool for addressing the energy and environmental crises. Single-atom catalysts (SACs) have received high attention for their extremely high atom utilization efficiency and excellent catalytic activity, and have broad application prospects in energy development and chemical production. M-N4 is an active center model with clear catalytic activity, but its catalytic properties such as catalytic activity, selectivity, and durability need to be further improved. Adjustment of the coordination environment of the central metal by incorporating heteroatoms (e.g., sulfur) is an effective and feasible modification method. This paper describes the precise synthetic methods for introducing sulfur atoms into M-N4 and controlling whether they are directly coordinated with the central metal to form a specific coordination configuration, the application of sulfur-doped carbon-based single-atom catalysts in electrocatalytic reactions such as ORR, CO2RR, HER, OER, and other electrocatalytic reaction are systematically reviewed. Meanwhile, the effect of the tuning of the electronic structure and ligand configuration parameters of the active center due to doped sulfur atoms with the improvement of catalytic performance is introduced by combining different characterization and testing methods. Finally, several opinions on development of sulfur-doped carbon-based SACs are put forward.

Sensitive remote homology search by local alignment of small positional embeddings from protein language models.

Accurately detecting distant evolutionary relationships between proteins remains an ongoing challenge in bioinformatics. Search methods based on primary sequence struggle to accurately detect homology between sequences with less than 20% amino acid identity. Profile- and structure-based strategies extend sensitive search capabilities into this twilight zone of sequence similarity but require slow pre-processing steps. Recently, whole-protein and positional embeddings from deep neural networks have shown promise for providing sensitive sequence comparison and annotation at long evolutionary distances. Embeddings are generally faster to compute than profiles and predicted structures but still suffer several drawbacks related to the ability of whole-protein embeddings to discriminate domain-level homology, and the database size and search speed of methods using positional embeddings. In this work, we show that low-dimensionality positional embeddings can be used directly in speed-optimized local search algorithms. As a proof of concept, we use the ESM2 3B model to convert primary sequences directly into the 3D interaction (3Di) alphabet or amino acid profiles and use these embeddings as input to the highly optimized Foldseek, HMMER3, and HH-suite search algorithms. Our results suggest that positional embeddings as small as a single byte can provide sufficient information for dramatically improved sensitivity over amino acid sequence searches without sacrificing search speed.

Identification and validation of hub genes expressed in ulcerative colitis with metabolic dysfunction-associated steatotic liver disease.

Objective: Ulcerative colitis (UC) and metabolic dysfunction-associated steatotic liver disease (MASLD) are closely intertwined; however, the precise molecular mechanisms governing their coexistence remain unclear. Methods: We obtained UC (GSE75214) and MASLD (GSE151158) datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired by the 'edgeR' and 'limma' packages of R. We then performed functional enrichment analysis of common DEGs. Hub genes were selected using the cytoHubba plugin and validated using GSE87466 for UC and GSE33814 for MASLD. Immunohistochemistry was employed to validate the hub genes' expression in clinical samples. Immune infiltration and gene set enrichment analyses of the hub genes were performed. Finally, we estimated the Spearman's correlation coefficients for the clinical correlation of the core genes. Results: Within a cohort of 26 differentially regulated genes in both UC and MASLD, pathways involving cytokine-mediated signaling, cell chemotaxis, and leukocyte migration were enriched. After further validation, CXCR4, THY1, CCL20, and CD2 were identified as the hub genes. Analysis of immune infiltration patterns highlighted an association between elevated pivotal gene expression and M1 macrophage activation. Immunohistochemical staining revealed widespread expression of pivotal genes in UC- and MASLD-affected tissues. Furthermore, significant correlations were observed between the increased expression of hub genes and biochemical markers, such as albumin and prothrombin time. Conclusion: This bioinformatics analysis highlights CXCR4, THY1, CCL20, and CD2 as crucial genes involved in the co-occurrence of UC and MASLD, providing insights into the underlying mechanisms of these two conditions.

A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising methods have been presented to remove noise in LDCT scans. However, existing methods cannot achieve satisfactory results due to the difficulties in (1) distinguishing the characteristics of structures, textures, and noise confused in the image domain, and (2) representing local details and global semantics in the hierarchical features. In this paper, we propose a novel denoising method consisting of (1) a 2D dual-domain restoration framework to reconstruct noise-free structure and texture signals separately, and (2) a 3D multi-depth reinforcement U-Net model to further recover image details with enhanced hierarchical features. In the 2D dual-domain restoration framework, the convolutional neural networks are adopted in both the image domain where the image structures are well preserved through the spatial continuity, and the sinogram domain where the textures and noise are separately represented by different wavelet coefficients and processed adaptively. In the 3D multi-depth reinforcement U-Net model, the hierarchical features from the 3D U-Net are enhanced by the cross-resolution attention module (CRAM) and dual-branch graph convolution module (DBGCM). The CRAM preserves local details by integrating adjacent low-level features with different resolutions, while the DBGCM enhances global semantics by building graphs for high-level features in intra-feature and inter-feature dimensions. Experimental results on the LUNA16 dataset and 2016 NIH-AAPM-Mayo Clinic LDCT Grand Challenge dataset illustrate the proposed method outperforms the state-of-the-art methods on removing noise from LDCT images with clear structures and textures, proving its potential in clinical practice.

Cascade Dual Sites Modulate Local CO Coverage and Hydrogen-Binding Strength to Boost CO2 Electroreduction to Ethylene.

Rationally modulating the binding strength of reaction intermediates on surface sites of copper-based catalysts could facilitate C-C coupling to generate multicarbon products in an electrochemical CO2 reduction reaction. Herein, theoretical calculations reveal that cascade Ag-Cu dual sites could synergistically increase local CO coverage and lower the kinetic barrier for CO protonation, leading to enhanced asymmetric C-C coupling to generate C2H4. As a proof of concept, the Cu3N-Ag nanocubes (NCs) with Ag located in partial Cu sites and a Cu3N unit center are successfully synthesized. The Faraday efficiency and partial current density of C2H4 over Cu3N-Ag NCs are 7.8 and 9.0 times those of Cu3N NCs, respectively. In situ spectroscopies combined with theoretical calculations confirm that Ag sites produce CO and Cu sites promote asymmetric C-C coupling to *COCHO, significantly enhancing the generation of C2H4. Our work provides new insights into the cascade catalysis strategy at the atomic scale for boosting CO2 to multicarbon products.

Discovery of cytosine deaminases enables base-resolution methylome mapping using a single enzyme.

Deaminases have important uses in modification detection and genome editing. However, the range of applications is limited by the small number of characterized enzymes. To expand the toolkit of deaminases, we developed an in vitro approach that bypasses a major hurdle with their toxicity in cells. We assayed 175 putative cytosine deaminases on a variety of substrates and found a broad range of activity on double- and single-stranded DNA in various sequence contexts, including CpG-specific deaminases and enzymes without sequence preference. We also characterized enzyme selectivity across six DNA modifications and reported enzymes that do not deaminate modified cytosines. The detailed analysis of diverse deaminases opens new avenues for biotechnological and medical applications. As a demonstration, we developed SEM-seq, a non-destructive single-enzyme methylation sequencing method using a modification-sensitive double-stranded DNA deaminase. The streamlined protocol enables accurate, base-resolution methylome mapping of scarce biological material, including cell-free DNA and 10 pg input DNA.

Low-Dose CT Image Super-resolution Network with Noise Inhibition Based on Feedback Feature Distillation Mechanism.

Low-dose computed tomography (LDCT) has been widely used in medical diagnosis. In practice, doctors often zoom in on LDCT slices for clearer lesions and issues, while, a simple zooming operation fails to suppress low-dose artifacts, leading to distorted details. Therefore, numerous LDCT super-resolution (SR) methods have been proposed to promote the quality of zooming without the increase of the dose in CT scanning. However, there are still some drawbacks that need to be addressed in existing methods. First, the region of interest (ROI) is not emphasized due to the lack of guidance in the reconstruction process. Second, the convolutional blocks extracting fix-resolution features fail to concentrate on the essential multi-scale features. Third, a single SR head cannot suppress the residual artifacts. To address these issues, we propose an LDCT CT joint SR and denoising reconstruction network. Our proposed network consists of global dual-guidance attention fusion modules (GDAFMs) and multi-scale anastomosis blocks (MABs). The GDAFM directs the network to focus on ROI by fusing the extra mask guidance and average CT image guidance, while the MAB introduces hierarchical features through anastomosis connections to leverage multi-scale features and promote the feature representation ability. To suppress radial residual artifacts, we optimize our network using the feedback feature distillation mechanism (FFDM) which shares the backbone to learn features corresponding to the denoising task. We apply the proposed method to the 3D-IRCADB and PANCREAS datasets to evaluate its ability on LDCT image SR reconstruction. The experimental results compared with state-of-the-art methods illustrate the superiority of our approach with respect to peak signal-to-noise (PSNR), structural similarity (SSIM), and qualitative observations. Our proposed LDCT joint SR and denoising reconstruction network has been extensively evaluated through ablation, quantitative, and qualitative experiments. The results demonstrate that our method can recover noise-free and detail-sharp images, resulting in better reconstruction results. Code is available at https://github.com/neu-szy/ldct_sr_dn_w_ffdm .

Microplastics drive community dynamics of periphytic protozoan fauna in marine environments.

The pollution of microplastics (MPs) to the marine environment has become a widespread focus of attention. To assess MP-induced ecotoxicity on marine ecosystems, periphytic protozoan communities were used as test organisms and exposed to five concentrations of MPs: 0, 1, 5, 25, and 125 mg l-1. Protozoan samples were collected using microscope slides from coastal waters of the Yellow Sea, northern China. A total of 13 protozoan species were identified and represented different tolerance to MP-induced ecotoxicity. Inhibition effects of MPs on the test protozoan communities were clearly shown in terms of both the species richness and individual abundance and followed linear relationships to MP concentrations. The community patterns were driven by MPs and significantly shifted at concentrations over 5 mg l-1. Our findings demonstrated that MPs may induce the community-level ecotoxic response of periphytic protozoan fauna and followed significant community dynamics. Thus, it is suggested that periphytic protozoan fauna may be used as useful community-based test model organisms for evaluating MP-induced ecotoxicity in marine environments.

Single-cell landscape of the cellular microenvironment in three different colonic polyp subtypes in children.

BACKGROUND: The understanding of the heterogeneous cellular microenvironment of colonic polyps in paediatric patients with solitary juvenile polyps (SJPs), polyposis syndrome (PJS) and Peutz-Jeghers syndrome (PJS) remains limited. METHODS: We conducted single-cell RNA sequencing and multiplexed immunohistochemistry (mIHC) analyses on both normal colonic tissue and different types of colonic polyps obtained from paediatric patients. RESULTS: We identified both shared and disease-specific cell subsets and expression patterns that played important roles in shaping the unique cellular microenvironments observed in each polyp subtype. As such, increased myeloid, endothelial and epithelial cells were the most prominent features of SJP, JPS and PJS polyps, respectively. Noticeably, memory B cells were increased, and a cluster of epithelial-mesenchymal transition (EMT)-like colonocytes existed across all polyp subtypes. Abundant neutrophil infiltration was observed in SJP polyps, while CX3CR1hi CD8+ T cells and regulatory T cells (Tregs) were predominant in SJP and JPS polyps, while GZMAhi natural killer T cells were predominant in PJS polyps. Compared with normal colonic tissues, myeloid cells exhibited specific induction of genes involved in chemotaxis and interferon-related pathways in SJP polyps, whereas fibroblasts in JPS polyps had upregulation of myofiber-associated genes and epithelial cells in PJS polyps exhibited induction of a series of nutrient absorption-related genes. In addition, the TNF-α response was uniformly upregulated in most cell subsets across all polyp subtypes, while endothelial cells and fibroblasts separately showed upregulated cell adhesion and EMT signalling in SJP and JPS polyps. Cell-cell interaction network analysis showed markedly enhanced intercellular communication, such as TNF, VEGF, CXCL and collagen signalling networks, among most cell subsets in polyps, especially SJP and JPS polyps. CONCLUSION: These findings strengthen our understanding of the heterogeneous cellular microenvironment of polyp subtypes and identify potential therapeutic approaches to reduce the recurrence of polyps in children.

Integrating Host Design and Tailored Electronic Effects of Yolk-Shell Zn-Mn Diatomic Sites for Efficient CO2 Electroreduction.

Modulating the surface and spatial structure of the host is associated with the reactivity of the active site, and also enhances the mass transfer effect of the CO2 electroreduction process (CO2 RR). Herein, we describe the development of two-step ligand etch-pyrolysis to access an asymmetric dual-atomic-site catalyst (DASC) composed of a yolk-shell carbon framework (Zn1 Mn1 -SNC) derived from S,N-coordinated Zn-Mn dimers anchored on a metal-organic framework (MOF). In Zn1 Mn1 -SNC, the electronic effects of the S/N-Zn-Mn-S/N configuration are tailored by strong interactions between Zn-Mn dual sites and co-coordination with S/N atoms, rendering structural stability and atomic distribution. In an H-cell, the Zn1 Mn1 -SNC DASC shows a low onset overpotential of 50 mV and high CO Faraday efficiency of 97 % with a low applied overpotential of 343 mV, thus outperforming counterparts, and in a flow cell, it also reaches a high current density of 500 mA cm-2 at -0.85 V, benefitting from the high structure accessibility and active dual sites. DFT simulations showed that the S,N-coordinated Zn-Mn diatomic site with optimal adsorption strength of COOH* lowers the reaction energy barrier, thus boosting the intrinsic CO2 RR activity on DASC. The structure-property correlation found in this study suggests new ideas for the development of highly accessible atomic catalysts.

Can salinity variability drive the colonization dynamics of periphytic protozoan fauna in marine environments?

To investigate effects of salinity variability on colonization dynamics of periphytic protozoan fauna, a 21-day study was conducted in temperature-controlled circulation systems (TCCSs). Periphytic protozoan communities were incubated using glass slides as artificial substrata in five TCCS aquaria with a large-scale salinity gradient of 9, 19, 29 (control), 39, and 49 PSU, respectively. The colonization dynamics were observed on days 3, 5, 7, 10, 14, and 21. The colonization dynamics were well fitted to the MacArthur-Wilson and logistic model equations in colonization and growth curves in all five treatments, respectively. However, the maximum species richness and abundance were reduced, and the colonization patterns were significantly shifted in four treatments with salinity changed by 20 PSU compared to the control (29 PSU). Thus, it is suggested that the large-scale salinity variability may reduce the species richness significantly and affect colonization dynamics of periphytic protozoan fauna in marine environments.

Genome-Wide Profiling of tRNA Using an Unexplored Reverse Transcriptase with High Processivity.

Monitoring the dynamic changes of cellular tRNA pools is challenging, due to the extensive post-transcriptional modifications of individual species. The most critical component in tRNAseq is a processive reverse transcriptase (RT) that can read through each modification with high efficiency. Here we show that the recently developed group-II intron RT Induro has the processivity and efficiency necessary to profile tRNA dynamics. Using our Induro-tRNAseq, simpler and more comprehensive than the best methods to date, we show that Induro progressively increases readthrough of tRNA over time and that the mechanism of increase is selective removal of RT stops, without altering the misincorporation frequency. We provide a parallel dataset of the misincorporation profile of Induro relative to the related TGIRT RT to facilitate the prediction of non-annotated modifications. We report an unexpected modification profile among human proline isoacceptors, absent from mouse and lower eukaryotes, that indicates new biology of decoding proline codons.

Symmetry-Breaking p-Block Antimony Single Atoms Trigger N-Bridged Titanium Sites for Electrocatalytic Nitrogen Reduction with High Efficiency.

The electrochemical nitrogen reduction reaction (eNRR) under mild conditions emerges as a promising approach to produce ammonia (NH3) compared to the typical Haber-Bosch process. Herein, we design an asymmetrically coordinated p-block antimony single-atom catalyst immobilized on nitrogen-doped Ti3C2Tx (Sb SA/N-Ti3C2Tx) for eNRR, which exhibits ultrahigh NH3 yield (108.3 µg h-1 mgcat-1) and excellent Faradaic efficiency (41.2%) at -0.3 V vs RHE. Complementary in situ spectroscopies with theoretical calculations reveal that the nitrogen-bridged two titanium atoms triggered by an adjacent asymmetrical Sb-N1C2 moiety act as the active sites for facilitating the protonation of the rate-determining step from *N2 to *N2H and the kinetic conversion of key intermediates during eNRR. Moreover, the introduction of Sb-N1C2 promotes the formation of oxygen vacancies to expose more titanium sites. This work presents a strategy for single-atom-decorated ultrathin two-dimensional materials with the aim of simultaneously enhancing NH3 yield and Faradaic efficiency for electrocatalytic nitrogen reduction.

Enhancing Photocatalytic-Transfer Semi-Hydrogenation of Alkynes Over Pd/C3 N4 Through Dual Regulation of Nitrogen Defects and the Mott-Schottky Effect.

The selective hydrogenation of alkynes is an important reaction; however, the catalytic activity and selectivity in this reaction are generally conflicting. In this study, ultrafine Pd nanoparticles (NPs) loaded on a graphite-like C3 N4 structure with nitrogen defects (Pd/DCN) are synthesized. The resulting Pd/DCN exhibits excellent photocatalytic performance in the transfer hydrogenation of alkynes with ammonia borane. The reaction rate and selectivity of Pd/DCN are superior to those of Pd/BCN (bulk C3 N4 without nitrogen defects) under visible-light irradiation. The characterization results and density functional theory calculations show that the Mott-Schottky effect in Pd/DCN can change the electronic density of the Pd NPs, and thus enhances the hydrogenation selectivity toward phenylacetylene. After 1 h, the hydrogenation selectivity of Pd/DCN reaches 95%, surpassing that of Pd/BCN (83%). Meanwhile, nitrogen defects in the supports improve the visible-light response and accelerate the transfer and separation of photogenerated charges to enhance the catalytic activity of Pd/DCN. Therefore, Pd/DCN exhibits higher efficiency under visible light, with a turnover frequency (TOF) of 2002 min-1 . This TOF is five times that of Pd/DCN under dark conditions and 1.5 times that of Pd/BCN. This study provides new insights into the rational design of high-performance photocatalytic transfer hydrogenation catalysts.

Construction and validation of a nomogram of risk factors and cancer-specific survival prognosis for combined lymphatic metastases in patients with early-onset colorectal cancer.

PURPOSE: This study aimed to investigate the risk and prognostic factors of lymph node metastasis (LNM) in early-onset colorectal cancer (EO-CRC) and to develop nomograms for quantitatively predicting LNM and the cancer-specific survival (CSS). METHODS: A total of 22,405 EO-CRC patients were included in this study using the SEER database from 2010 to 2017. Logistic and Cox regression were used to identify risk and the potential prognostic factors, respectively, for EO-CRC with LNM. Subsequently, nomograms regarding the risk of LNM in EO-CRC patients and its corresponding CSS were constructed based on these factors. The discriminative ability, calibration and clinical usefulness of the nomograms were assessed by the area under the receiver operating characteristic (ROC) curves (AUC), calibration curves, and decision curve analysis (DCA). RESULTS: T-stage and pathological grade were the most represented factors in the predicted LNM nomogram, while histological type and combined distant metastases were the most represented in the nomogram for CSS in EO-CRC patients with LNM (all P < 0.05). The nomogram constructed based on the prognostic factors screened by Cox regression had good performance with C-index of 0.807 and 0.802 for the training and validation cohorts, respectively. The calibration curve showed that the nomograms' predictions were in line with actual observations. Additionally, the ROC curves indicated good discrimination, and the DCA curves implied significant clinical utility of the nomograms. CONCLUSION: The nomograms we constructed have significant performance in predicting the incidence and prognosis of LNM in EO-CRC patients, which may help clinicians to make better treatment decision making.

A semiconductor-electrocatalyst nano interface constructed for successive photoelectrochemical water oxidation.

Photoelectrochemical water splitting has long been considered an ideal approach to producing green hydrogen by utilizing solar energy. However, the limited photocurrents and large overpotentials of the anodes seriously impede large-scale application of this technology. Here, we use an interfacial engineering strategy to construct a nanostructural photoelectrochemical catalyst by incorporating a semiconductor CdS/CdSe-MoS2 and NiFe layered double hydroxide for the oxygen evolution reaction. Impressively, the as-prepared photoelectrode requires an low potential of 1.001 V vs. reversible hydrogen electrode for a photocurrent density of 10 mA cm-2, and this is 228 mV lower than the theoretical water splitting potential (1.229 vs. reversible hydrogen electrode). Additionally, the generated current density (15 mA cm-2) of the photoelectrode at a given overpotential of 0.2 V remains at 95% after long-term testing (100 h). Operando X-ray absorption spectroscopy revealed that the formation of highly oxidized Ni species under illumination provides large photocurrent gains. This finding opens an avenue for designing high-efficiency photoelectrochemical catalysts for successive water splitting.

PILN: A posterior information learning network for blind reconstruction of lung CT images.

BACKGROUND AND OBJECTIVE: Computer tomography (CT) imaging technology has played significant roles in the diagnosis and treatment of various lung diseases, but the degradations in CT images usually cause the loss of detailed structural information and interrupt the judgement from clinicians. Therefore, reconstructing noise-free, high-resolution CT images with sharp details from degraded ones is of great importance for the computer-assisted diagnosis (CAD) system. However, current image reconstruction methods suffer from unknown parameters of multiple degradations in actual clinical images. METHODS: To solve these problems, we propose a unified framework, so called Posterior Information Learning Network (PILN), for blind reconstruction of lung CT images. The framework consists of two stages: Firstly, a noise level learning (NLL) network is proposed to quantify the Gaussian and artifact noise degradations into different levels. Inception-residual modules are designed to extract multi-scale deep features from the noisy image, and residual self-attention structures are proposed to refine deep features to essential representations of noise. Secondly, by taking the estimated noise levels as prior information, a cyclic collaborative super-resolution (CyCoSR) network is proposed to iteratively reconstruct the high-resolution CT image and estimate the blur kernel. Two convolutional modules are designed based on cross-attention transformer structure, named as Reconstructor and Parser. The high-resolution image is restored from the degraded image by the Reconstructor under the guidance of the predicted blur kernel, while the blur kernel is estimated by the Parser according to the reconstructed image and the degraded one. The NLL and CyCoSR networks are formulated as an end-to-end framework to handle multiple degradations simultaneously. RESULTS: The proposed PILN is applied to the Cancer Imaging Archive (TCIA) dataset and the Lung Nodule Analysis 2016 Challenge (LUNA16) dataset to evaluate its ability in reconstructing lung CT images. Compared with the state-of-the-art image reconstruction algorithms, it can provide high-resolution images with less noise and sharper details with respect to quantitative benchmarks. CONCLUSIONS: Extensive experimental results demonstrate that our proposed PILN can achieve better performance on blind reconstruction of lung CT images, providing noise-free, detail-sharp and high-resolution images without knowing the parameters of multiple degradation sources.

Universal NicE-Seq: A Simple and Quick Method for Accessible Chromatin Detection in Fixed Cells.

Genome-wide accessible chromatin sequencing and identification has enabled deciphering the epigenetic information encoded in chromatin, revealing accessible promoters, enhancers, nucleosome positioning, transcription factor occupancy, and other chromosomal protein binding. The starting biological materials are often fixed using formaldehyde crosslinking. Here, we describe accessible chromatin library preparation from low numbers of formaldehyde-crosslinked cells using a modified nick translation method, where a nicking enzyme nicks one strand of DNA and DNA polymerase incorporates biotin-conjugated dATP, dCTP, and methyl-dCTP. Once the DNA is labeled, it can be isolated for NGS library preparation. We termed this method as universal NicE-seq (nicking enzyme-assisted sequencing). We also demonstrate a single tube method that enables direct NGS library preparation from low cell numbers without DNA purification. Furthermore, we demonstrated universal NicE-seq on FFPE tissue section sample.