Designable Synthesis of Layered Silicates and Tunable Interlayer Expanded to Zeolites.

Layered zeolitic silicates and corresponding interlayer-expanded porous materials exhibit attractive application potential in wide fields. Nonetheless, designable synthesis and structure analysis of layered silicates remain challenging. Herein, two kinds of layered silicates are synthesized using different di-quaternary ammonium-type organic structure-directing agents (OSDAs). Their crystal structures are analyzed and verified by 3D electron diffraction (3D ED) and high-resolution TEM imaging. The suitable configurations of OSDA can lead to desirable interlayer states. Additionally, two new zeolite structures both with 12-membered ring (MR) channels intersected by 8 MR channels and larger interlayer spaces are constructed from layered silicate precursors by interlayer silylation. The new zeolitic material exhibits potential application in adsorption of organic pollution and catalytic reaction. This study is expected to develop versatile ways for the design and synthesis of layered silicates even zeolites and provide references in characterizing layered materials and zeolites as well.

Superhydrophilic Dendritic FeP/Cu3P Electrocatalyst for Urea Splitting via the Intramolecular Mechanism.

The electrocatalytic overall urea splitting can achieve the dual goals of urea treatment and hydrogen energy acquisition. Herein, we exploited the principle of precipitation dissolution equilibrium to obtain bimetallic phosphide FeP/Cu3P/CF for the simultaneous oxidation of urea and reduction of water and comprehensively reveal the inherent molecular thermodynamic mechanisms on the surface of catalysts. The excellent electrochemical performance can be derived from the super water affinity and synergistic effect. Especially, the theoretical calculation unveils that the synergistic effect between FeP and Cu3P can lower the activation energy required for urea electrooxidation, thereby promoting urea splitting. In situ differential electrochemical mass spectrometry (in situ DEMS) measurements further demonstrated that urea oxidation on FeP/Cu3P/CF proceeded according to the intramolecular mechanism. This work has laid the foundation for constructing highly efficient superhydrophilic bifunctional electrocatalysts.

Synergistic effect of adsorption-photocatalytic reduction of Cr(VI) in wastewater with biochar/TiO2 composite under simulated sunlight illumination.

Photocatalysis, which is an alternative technology to conventional methods, utilizes solar energy as the driving force to address environmental concerns and has attracted widespread attention from chemists worldwide. In this study, a series of photocatalytic materials composed of agricultural waste and titanium dioxide (TiO2) nanomaterial was prepared for the synergistic adsorption-photocatalytic reduction of hexavalent chromium in wastewater under mild conditions. The results showed that the TiO2 nanomaterial exhibited a higher photogenerated carrier separation efficiency and performance for the adsorption-photocatalytic reduction of Cr(VI) after loading straw biochar (BC). When the loading amount of BC was 0.025 g (i.e., TBC-3), the removal efficiency of Cr(VI) was as high as 99.9% under sunlight irradiation for 25 min, which was 2.9 and 3.5 times higher than that of pure TiO2 and BC samples, respectively. Additionally, after four cycles of experiments, the removal efficiency of Cr(VI) by TBC-3 remained at about 93.0%, proving its good chemical ability in our reaction system. Its excellent adsorption-photocatalytic performance is mainly attributed to the synergistic effect of the strong adsorption of BC and the outstanding photocatalytic performance of TiO2. Finally, the possible mechanism for the synergistic adsorption-photocatalytic reduction on BC/TiO2 to remove the highly toxic Cr(VI) in wastewater was proposed.

A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data.

In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.

Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center study.

OBJECTIVES: To develop and validate a deep learning imaging signature (DLIS) for risk stratification in patients with multiforme (GBM), and to investigate the biological pathways and genetic alterations underlying the DLIS. METHODS: The DLIS was developed from multi-parametric MRI based on a training set (n = 600) and validated on an internal validation set (n = 164), an external test set 1 (n = 100), an external test set 2 (n = 161), and a public TCIA set (n = 88). A co-profiling framework based on a radiogenomics analysis dataset (n = 127) using multiscale high-dimensional data, including imaging, transcriptome, and genome, was established to uncover the biological pathways and genetic alterations underpinning the DLIS. RESULTS: The DLIS was associated with survival (log-rank p < 0.001) and was an independent predictor (p < 0.001). The integrated nomogram incorporating the DLIS achieved improved C indices than the clinicomolecular nomogram (net reclassification improvement 0.39, p < 0.001). DLIS significantly correlated with core pathways of GBM (apoptosis and cell cycle-related P53 and RB pathways, and cell proliferation-related RTK pathway), as well as key genetic alterations (del_CDNK2A). The prognostic value of DLIS-correlated genes was externally confirmed on TCGA/CGGA sets (p < 0.01). CONCLUSIONS: Our study offers a biologically interpretable deep learning predictor of survival outcomes in patients with GBM, which is crucial for better understanding GBM patient's prognosis and guiding individualized treatment. KEY POINTS: • MRI-based deep learning imaging signature (DLIS) stratifies GBM into risk groups with distinct molecular characteristics. • DLIS is associated with P53, RB, and RTK pathways and del_CDNK2A mutation. • The prognostic value of DLIS-correlated pathway genes is externally demonstrated.

Photoredox Coupling of CO2 Reduction with Benzyl Alcohol Oxidation over Ternary Metal Chalcogenides (ZnmIn2S3+m, m = 1-5) with Regulable Products Selectivity.

Integrating photocatalytic CO2 reduction with selective benzyl alcohol (BA) oxidation in one photoredox reaction system is a promising way for the simultaneous utilization of photogenerated electrons and holes. Herein, ZnmIn2S3+m (m = 1-5) semiconductors (ZnIn2S4, Zn2In2S5, Zn3In2S6, Zn4In2S7, and Zn5In2S8) with various composition faults were synthesized via a simple hydrothermal method and used for effective selective dehydrocoupling of benzyl alcohol into high-value C-C coupling products and reduction of CO2 into syngas under visible light. The absorption edge of ZnmIn2S3+m samples shifted to shorter wavelengths as the atomic ratio of Zn/In was increased. The conduction band and valence band position can be adjusted by changing the Zn/In ratio, resulting in controllable photoredox ability for selective BA oxidation and CO2 reduction. For example, the selectivity of benzaldehyde (BAD) product was reduced from 76% (ZnIn2S4, ZIS1) to 27% (Zn4In2S7, ZIS4), while the selectivity of hydrobenzoin (HB) was increased from 22% to 56%. Additionally, the H2 formation rate on ZIS1 (1.6 mmol/g/h) was 1.6 times higher than that of ZIS4 (1.0 mmol/g/h), and the CO formation rate on ZIS4 (0.32 mmol/g/h) was three times higher than that of ZIS1 (0.13 mmol/g/h), demonstrating that syngas with different H2/CO ratios can be obtained by controlling the Zn/In ratio in ZnmIn2S3+m. This study provides new insights into unveiling the relationship of structure-property of ZnmIn2S3+m layered crystals, which are valuable for implementation in a wide range of environment and energy applications.

Genomic temporal heterogeneity of circulating tumour DNA in unresectable metastatic colorectal cancer under first-line treatment.

OBJECTIVE: Circulating tumour DNA (ctDNA) sequencing is increasingly used in the clinical management of patients with colorectal cancer. However, the genomic heterogeneity in ctDNA during treatments and its impact on clinical outcomes remain largely unknown. DESIGN: We conducted a prospective cohort study (NCT04228614) of 171 patients with unresectable metastatic colorectal cancer (mCRC) who underwent first-line treatment and prospectively collected blood samples with or without tumour samples from patients at baseline and sequentially until disease progression or last follow-up. RESULTS: The RAS/BRAF alterations in paired baseline tissue and plasma samples from 63 patients displayed a favourable concordance (81.0%, 51/63). After a period of first-line treatment (median time between baseline and last liquid biopsy, 4.67 months), 42.6% (26/61) of RAS-mutant patients showed RAS clearance and 50.0% (5/10) of BRAF-mutant patients showed BRAF clearance, while 3.6% (3/84) and 0.7% (1/135) of patients showed new RAS or BRAF mutations in ctDNA. Patients with plasma RAS/BRAF clearance showed similar progression-free survival (PFS) and overall survival (OS) with patients who remained RAS/BRAF wild-type, while much better outcomes than those who remained RAS/BRAF mutant. Patients who gained new RAS/BRAF mutations showed similar prognosis as those who maintained RAS/BRAF mutations, and shorter PFS and OS than those who remained RAS/BRAF wild-type. CONCLUSION: This prospective, serial and large-scale ctDNA profiling study reveals the temporal heterogeneity of mCRC-related somatic variants, which should be given special attention in clinical practice, as evidenced by the finding that the shift in plasma RAS/BRAF mutational status can yield a drastic change in survival outcomes.

Efficient Charge Carrier Transfer Route Induced by an S-Scheme α-Fe2O3/RP Heterojunction with Enhanced Photocatalytic Activity of Overall Water Splitting.

Photocatalytic overall water splitting simultaneously generates O2 and H2; this is a potential strategy to solve the energy shortage problem. Elemental phosphorus (RP) displays ultralow visible light performance for O2 and H2 generation; thus, a novel α-Fe2O3/RP composite is designed and prepared by a low-temperature hydrothermal method via loading a trace amount of α-Fe2O3. In the experiment, the 1.5% α-Fe2O3/RP composite showed the best overall water splitting performance, which is 6.9 times that of bare RP. Through various characterization studies, the recombination rate of charges is significantly reduced. It is largely ascribed to the matched energy band structure of the two photocatalysts and the interface contact between α-Fe2O3 and RP, which efficiently separates the photocarriers through an S-scheme mode and realizes the obvious enhancement of overall water splitting performance. Moreover, α-Fe2O3/RP maintains high activity when it is persistently irradiated for 15 cycles. The research provides insight into the exploitation of low-cost, high-activity, and stable RP-based photocatalysts to achieve visible light induced overall water splitting activity to generate O2 and H2.

Fabrication of 2D/2D BiOBr/g-C3N4 with efficient photocatalytic activity and clarification of its mechanism.

Precise regulation of photoexcited charge carriers for separation and transportation is a core requirement for practical application in the photocatalysis field. Herein, a 2D/2D BiOBr/g-C3N4 heterojunction is prepared by a self-assembly method and exhibits enhanced and stable activity for photocatalytic degradation of bisphenol A (BPA) and norfloxacin (NFA) under visible light. Compared to pure g-C3N4, the kinetic constants of BPA and NFA degradation over BiOBr/g-C3N4 are enhanced by about 14.74 and 4.01 times, respectively. The separation and transportation mechanism for the photoexcited charge carriers is clarified by electron paramagnetic resonance (EPR), in situ X-ray photoelectron spectroscopy (in situ XPS), and theoretical calculations. The results show that BiOBr/g-C3N4 exhibits the feature of a relative p-n junction, in which the charges photoexcited on BiOBr/g-C3N4 with high redox potentials can be kept and spatially separated. Moreover, the built-in electric field with the direction of g-C3N4 → BiOBr and the opportune band curvature provide the driving force for charge separation and transportation. Additionally, BPA and NFA degradation intermediates are also detected by liquid chromatography-mass spectrometry. It is of great significance to fabricate efficient photocatalysts for environmental purification and other targeted reactions.

The mutational landscape and prognostic indicators of pseudomyxoma peritonei originating from the ovary.

Pseudomyxoma peritonei (PMP) is a rare disorder with unique pathological and genetic changes. Although several studies have reported the clinical features and mutational changes of PMP that originates from the appendix, few studies on PMP originating from the ovary have been reported due to its extreme rarity. In order to characterize the somatic mutational landscape and to investigate the prognosis predicting factors of ovary-originating PMP, we examined 830 cases of PMP and identified 16 patients with PMP that originated from the ovary. Whole-exome sequencing (WES) was performed on 12 cases using formalin-fixed, paraffin-embedded (FFPE) tissue samples. We found that 25% (3/12) of the patients carried mutations in cancer driver genes, including TP53, ATM and SETD2, and 16.7% (2/12) of the patients carried mutations in cancer driver genes, including ATRX, EP300, FGFR2, KRAS, NOCR1 and RB1. The MUC16 (58.33%), BSN (41.67%), PCNT (41.67%), PPP2R5A (41.67%), PRSS36 (41.67%), PTPRK (41.67%) and SBF1 (41.67%) genes presented the highest mutational frequencies. The PI3K-Akt signaling pathway, human papillomavirus infection pathway, cell skeleton, cell adhesion, and extracellular matrix and membrane proteins were the major pathways or functions that were affected. Patients were followed up to 174 months (median: 48.26 months). The 5-year OS rate for all patients was 71.2% and the median OS was not reached. PTPRK mutations, presurgical CA199 level, completeness of cytoreduction (CCR) and peritoneal cancer index (PCI) were identified as potential predictive factors for patient survival. In conclusion, the mutational landscape for ovary-originating PMP was revealed and exhibited unique features distinct from appendix-originating PMP. PTPRK, CA199, CCR and PCI may predict patient survival.

Metastatic Low-Grade Sarcoma with CARS-ALK Fusion Dramatically Responded to Multiple ALK Tyrosine Kinase Inhibitors: A Case Report with Comprehensive Genomic Analysis.

This article reports a case of advanced metastatic low-grade sarcoma. The patient was diagnosed with an inoperable large (14 × 12 cm) lesion on his neck in September 2015 and underwent two ineffective chemotherapies in the following 4 months. Interestingly, although several pathologists could not agree on the histopathological diagnosis, the precise molecular pathological diagnosis was obtained using next-generation sequencing (NGS) and finally brought excellent therapeutic effects. The patient was detected to have CARS-ALK fusion by NGS and then was successfully treated with crizotinib orally. He received surgical resection of primary and metastatic lesions after tumor shrinkage. The combined treatment brought a durable response for 40 months. Although the tumor recurred in July 2019, the patient has been responding well to the second-line ALK tyrosine kinase inhibitor alectinib to date. We performed whole genome sequencing on the patient's primary, metastatic, and recurrent tumors and did comprehensive genomic analysis. Furthermore, our analysis results revealed that a whole genome duplication event might have happened during tumorigenesis of this case. KEY POINTS: To our best knowledge, this is the first report of a very successful treatment with first- and second-line ALK tyrosine kinase inhibitors for CARS-ALK fusion-positive metastatic low-grade sarcoma. Molecular pathological result can guide precision treatment for sarcoma, even when the exact histopathology cannot be obtained. Multiple samples from this patient were analyzed using whole genome sequencing. Results provided detailed genomic characteristics and showed tumor evolution of this low-grade sarcoma case. A whole genome duplication event might have happened during tumorigenesis of this low-grade sarcoma case.

Gencore: an efficient tool to generate consensus reads for error suppressing and duplicate removing of NGS data.

BACKGROUND: Removing duplicates might be considered as a well-resolved problem in next-generation sequencing (NGS) data processing domain. However, as NGS technology gains more recognition in clinical application, researchers start to pay more attention to its sequencing errors, and prefer to remove these errors while performing deduplication operations. Recently, a new technology called unique molecular identifier (UMI) has been developed to better identify sequencing reads derived from different DNA fragments. Most existing duplicate removing tools cannot handle the UMI-integrated data. Some modern tools can work with UMIs, but are usually slow and use too much memory. Furthermore, existing tools rarely report rich statistical results, which are very important for quality control and downstream analysis. These unmet requirements drove us to develop an ultra-fast, simple, little-weighted but powerful tool for duplicate removing and sequence error suppressing, with features of handling UMIs and reporting informative results. RESULTS: This paper presents an efficient tool gencore for duplicate removing and sequence error suppressing of NGS data. This tool clusters the mapped sequencing reads and merges reads in each cluster to generate one single consensus read. While the consensus read is generated, the random errors introduced by library construction and sequencing can be removed. This error-suppressing feature makes gencore very suitable for the application of detecting ultra-low frequency mutations from deep sequencing data. When unique molecular identifier (UMI) technology is applied, gencore can use them to identify the reads derived from same original DNA fragment. Gencore reports statistical results in both HTML and JSON formats. The HTML format report contains many interactive figures plotting statistical coverage and duplication information. The JSON format report contains all the statistical results, and is interpretable for downstream programs. CONCLUSIONS: Comparing to the conventional tools like Picard and SAMtools, gencore greatly reduces the output data's mapping mismatches, which are mostly caused by errors. Comparing to some new tools like UMI-Reducer and UMI-tools, gencore runs much faster, uses less memory, generates better consensus reads and provides simpler interfaces. To our best knowledge, gencore is the only duplicate removing tool that generates both informative HTML and JSON reports. This tool is available at: https://github.com/OpenGene/gencore.

fastp: an ultra-fast all-in-one FASTQ preprocessor.

Motivation: Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results: We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2-5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation: The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.

MutScan: fast detection and visualization of target mutations by scanning FASTQ data.

BACKGROUND: Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. RESULT: We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. CONCLUSION: MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.

AfterQC: automatic filtering, trimming, error removing and quality control for fastq data.

BACKGROUND: Some applications, especially those clinical applications requiring high accuracy of sequencing data, usually have to face the troubles caused by unavoidable sequencing errors. Several tools have been proposed to profile the sequencing quality, but few of them can quantify or correct the sequencing errors. This unmet requirement motivated us to develop AfterQC, a tool with functions to profile sequencing errors and correct most of them, plus highly automated quality control and data filtering features. Different from most tools, AfterQC analyses the overlapping of paired sequences for pair-end sequencing data. Based on overlapping analysis, AfterQC can detect and cut adapters, and furthermore it gives a novel function to correct wrong bases in the overlapping regions. Another new feature is to detect and visualise sequencing bubbles, which can be commonly found on the flowcell lanes and may raise sequencing errors. Besides normal per cycle quality and base content plotting, AfterQC also provides features like polyX (a long sub-sequence of a same base X) filtering, automatic trimming and K-MER based strand bias profiling. RESULTS: For each single or pair of FastQ files, AfterQC filters out bad reads, detects and eliminates sequencer's bubble effects, trims reads at front and tail, detects the sequencing errors and corrects part of them, and finally outputs clean data and generates HTML reports with interactive figures. AfterQC can run in batch mode with multiprocess support, it can run with a single FastQ file, a single pair of FastQ files (for pair-end sequencing), or a folder for all included FastQ files to be processed automatically. Based on overlapping analysis, AfterQC can estimate the sequencing error rate and profile the error transform distribution. The results of our error profiling tests show that the error distribution is highly platform dependent. CONCLUSION: Much more than just another new quality control (QC) tool, AfterQC is able to perform quality control, data filtering, error profiling and base correction automatically. Experimental results show that AfterQC can help to eliminate the sequencing errors for pair-end sequencing data to provide much cleaner outputs, and consequently help to reduce the false-positive variants, especially for the low-frequency somatic mutations. While providing rich configurable options, AfterQC can detect and set all the options automatically and require no argument in most cases.

Unexpected formation of scheelite-structured Ca1-xCdxWO4 (0 ≤ x ≤ 1) continuous solid solutions with tunable photoluminescent and electronic properties.

Design of a solid solution with tunable functionality is an attractive strategy toward realizing novel devices with multi-functionalities. In this work, a series of Ca1-xCdxWO4 solid solutions in the entire range 0 ≤ x ≤ 1 with tetragonal scheelite structure have been successfully prepared for the first time. X-ray diffraction (XRD), Fourier transform infrared (FT-IR) and Fourier transform Raman (FT-Raman) spectroscopies indicated that all the nanocrystals have a tetragonal scheelite structure without wolframite phase. Structural refinement data revealed that the lattice volume decreased with the replacement of Ca2+ by Cd2+ ions. UV-Vis diffuse reflectance spectra indicated that optical band gap reduced with the replacement of Ca2+ by Cd2+ ions. Scanning electron microscopic (SEM) images showed that morphologies of the nanocrystals changed with the chemical compositions. The structure evolution of the solid solutions was further investigated by high-resolution transmission electron microscopy (HRTEM). Moreover, the influence of chemical compositions on the photoluminescent and electric performance has been performed and discussed. The reported synthetic approach and findings reported here are important to understand the structure and structure-property relation of scheelite-structured tungstate and molybdate compounds, which has potential applications in the design of other kinds of novel functional materials.

What is the transfer mechanism of photogenerated carriers for the nanocomposite photocatalyst Ag3PO4/g-C3N4, band-band transfer or a direct Z-scheme?

The separation mechanisms of photoexcited carriers for composite photocatalysts are a hot point in the photocatalytic field. In this paper, the Ag3PO4/g-C3N4 nanocomposites with different main parts (Ag3PO4 or g-C3N4) were synthesized using a facile in situ precipitation method. The photocatalysts were characterized by X-ray powder diffraction, UV-vis diffuse reflection spectroscopy, transmission electron microscopy and Brunauer-Emmett-Teller methods. The photocatalytic performance was evaluated by the degradation of methylene blue under visible light irradiation. When the main part of the Ag3PO4/g-C3N4 photocatalyst is Ag3PO4, the transfer mechanism of photogenerated electron-hole takes generic band-band transfer, and the photocatalytic activity is decreased. However, when the primary part of the Ag3PO4/g-C3N4 photocatalyst is g-C3N4, the migration of photogenerated electron-hole exhibits a typical Z-scheme mechanism, and the photocatalytic activity is increased greatly. The separation mechanisms of photogenerated carriers were investigated by the electron spin resonance technology, the photoluminescence technique and the determination of reactive species in the photocatalytic reactions. It is hoped that this work could render guided information for design and application of Z-scheme photocatalysts with excellent photocatalytic performance.

Oxygen vacancies synergistic cobalt phosphide electron bridge modulated bismuth oxychloride/carbon nitride Z-scheme junction for efficient carbon dioxide reduction coupled with tetracycline oxidation.

Although great progress has been made with respect to electron bridges, the electron mobility of the state-of-the-art electron bridges is far from satisfactory because of weak electrical conductivity. To overcome the above issue, cobalt phosphide (CoP), as a model electron bridge, was modified by superficial oxygen vacancies (OVs) and embedded into a defective bismuth oxychloride/carbon nitride (BiO1-xCl/g-C3N4) Z-scheme heterojunction to obtain atomic-level insights into the effect of surface OVs on CoP electron bridges. Compared to BiO1-xCl/g-C3N4 and bismuth oxychloride/cobalt phosphide/carbon nitride (BiOCl/CoP/g-C3N4) composites, the defective bismuth oxychloride/cobalt phosphide/carbon nitride (BiO1-xCl/CoP/g-C3N4) heterojunction exhibited remarkable photocatalytic redox performance, indicating that the surface OVs-assisted CoP electron bridge effectively boosted electrical conductivity and yielded ultrafast electron transfer rates. The theoretical and experimental results demonstrate that the surface OVs play a critical role in improving the electrical conductivity of the CoP electron bridge, thereby accelerating electron mobility. This research provides insights into interfacial OVs-modified transition metal phosphide (TMP) electron bridges and their potential application in heterojunctions for energy crisis mitigation and environmental remediation.

Visualizing Large-Scale Spatial Time Series with GeoChron.

In geo-related fields such as urban informatics, atmospheric science, and geography, large-scale spatial time (ST) series (i.e., geo-referred time series) are collected for monitoring and understanding important spatiotemporal phenomena. ST series visualization is an effective means of understanding the data and reviewing spatiotemporal phenomena, which is a prerequisite for in-depth data analysis. However, visualizing these series is challenging due to their large scales, inherent dynamics, and spatiotemporal nature. In this study, we introduce the notion of patterns of evolution in ST series. Each evolution pattern is characterized by 1) a set of ST series that are close in space and 2) a time period when the trends of these ST series are correlated. We then leverage Storyline techniques by considering an analogy between evolution patterns and sessions, and finally design a novel visualization called GeoChron, which is capable of visualizing large-scale ST series in an evolution pattern-aware and narrative-preserving manner. GeoChron includes a mining framework to extract evolution patterns and two-level visualizations to enhance its visual scalability. We evaluate GeoChron with two case studies, an informal user study, an ablation study, parameter analysis, and running time analysis.

Comparison of the somatic genomic landscape between central- and peripheral-type non-small cell lung cancer.

OBJECTIVE: Lung cancer is classified into central and peripheral types based on the anatomic location. The present study aimed to explore the distinct patterns of genomic alterations between central- and peripheral-type non-small cell lung cancers (NSCLCs) with negative driver genes and identify potential driver genes and biomarkers to improve therapy strategies for NSCLC. METHODS: Whole-exome sequencing (WES) was performed with 182 tumor/control pairs of samples from 145 Chinese NSCLC patients without EGFR, ALK, or ROS1 alterations. Significantly mutated genes (SMGs) and somatic copy number alterations (SCNAs) were identified. Subsequently, tumor mutation burden (TMB), weighted genome integrity index (wGII), copy number alteration (CNA) burden, Shannon diversity index (SDI), intratumor heterogeneity (ITH), neoantigen load (NAL), and clonal variations were evaluated in central- and peripheral-type NSCLCs. Furthermore, mutational signature analysis and survival analysis were performed. RESULTS: TP53 was the most frequently mutated gene in NSCLC and more frequently mutated in central-type NSCLC. Higher wGII, ITH, and SDI were found in central-type lung adenocarcinoma (LUAD) than in peripheral-type LUAD. The NAL of central-type lung squamous cell carcinoma (LUSC) with stage III/IV was significantly higher than that of peripheral-type LUSC. Mutational signature analysis revealed that SBS10b, SBS24, and ID7 were significantly different in central- and peripheral-type NSCLCs. Furthermore, central-type NSCLC was found to evolve at a higher level with fewer clones and more subclones, particularly in central-type LUSC. Survival analysis revealed that TMB, CNA burden, NAL, subclonal driver mutations, and subclonal mutations were negatively related to the overall survival (OS) and the progression-free survival (PFS) of central-type LUAD. CONCLUSIONS: Central-type NSCLC tended to evolve at a higher level and might suggest a favorable response to immunotherapy. Our study also identified several potential driver genes and promising biomarkers for the prognosis and prediction of chemotherapy responses in NSCLC.