CROST: a comprehensive repository of spatial transcriptomics.

The development of spatial transcriptome sequencing technology has revolutionized our comprehension of complex tissues and propelled life and health sciences into an era of spatial omics. However, the current availability of databases for accessing and analyzing spatial transcriptomic data is limited. In response, we have established CROST (https://ngdc.cncb.ac.cn/crost), a comprehensive repository of spatial transcriptomics. CROST encompasses high-quality samples and houses 182 spatial transcriptomic datasets from diverse species, organs, and diseases, comprising 1033 sub-datasets and 48 043 tumor-related spatially variable genes (SVGs). Additionally, it encompasses a standardized spatial transcriptome data processing pipeline, integrates single-cell RNA sequencing deconvolution spatial transcriptomics data, and evaluates correlation, colocalization, intercellular communication, and biological function annotation analyses. Moreover, CROST integrates the transcriptome, epigenome, and genome to explore tumor-associated SVGs and provides a comprehensive understanding of their roles in cancer progression and prognosis. Furthermore, CROST provides two online tools, single-sample gene set enrichment analysis and SpatialAP, for users to annotate and analyze the uploaded spatial transcriptomics data. The user-friendly interface of CROST facilitates browsing, searching, analyzing, visualizing, and downloading desired information. Collectively, CROST offers fresh and comprehensive insights into tissue structure and a foundation for understanding multiple biological mechanisms in diseases, particularly in tumor tissues.

HALL: a comprehensive database for human aging and longevity studies.

Diverse individuals age at different rates and display variable susceptibilities to tissue aging, functional decline and aging-related diseases. Centenarians, exemplifying extreme longevity, serve as models for healthy aging. The field of human aging and longevity research is rapidly advancing, garnering significant attention and accumulating substantial data in recent years. Omics technologies, encompassing phenomics, genomics, transcriptomics, proteomics, metabolomics and microbiomics, have provided multidimensional insights and revolutionized cohort-based investigations into human aging and longevity. Accumulated data, covering diverse cells, tissues and cohorts across the lifespan necessitates the establishment of an open and integrated database. Addressing this, we established the Human Aging and Longevity Landscape (HALL), a comprehensive multi-omics repository encompassing a diverse spectrum of human cohorts, spanning from young adults to centenarians. The core objective of HALL is to foster healthy aging by offering an extensive repository of information on biomarkers that gauge the trajectory of human aging. Moreover, the database facilitates the development of diagnostic tools for aging-related conditions and empowers targeted interventions to enhance longevity. HALL is publicly available at https://ngdc.cncb.ac.cn/hall/index.

NMRK2 is an efficient diagnostic indicator for Xp11.2 translocation renal cell carcinoma.

Xp11.2 translocation renal cell carcinomas (tRCC) are a rare and highly malignant type of renal cancer, lacking efficient diagnostic indicators and therapeutic targets. Through the analysis of public databases and our cohort, we identified NMRK2 as a potential diagnostic marker for distinguishing Xp11.2 tRCC from kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) due to its specific upregulation in Xp11.2 tRCC tissues. Mechanistically, we discovered that TFE3 fusion protein binds to the promoter of the NMRK2 gene, leading to its upregulation. Importantly, we established RNA- and protein-based diagnostic methods for identifying Xp11.2 tRCC based on NMRK2 expression levels, and the diagnostic performance of our methods was comparable to a dual-color break-apart fluorescence in situ hybridization assay. Moreover, we successfully identified fresh Xp11.2 tRCC tissues after surgical excision using our diagnostic methods and established an immortalized Xp11.2 tRCC cell line for further research purposes. Functional studies revealed that NMRK2 promotes the progression of Xp11.2 tRCC by upregulating the NAD+/NADH ratio, and supplementation with ß-nicotinamide mononucleotide (NMN) or nicotinamide riboside chloride (NR), effectively rescued the phenotypes induced by the knockdown of NMRK2 in Xp11.2 tRCC. Taken together, these data introduce a new diagnostic indicator capable of accurately distinguishing Xp11.2 tRCC and highlight the possibility of developing novel targeted therapeutics. © 2024 The Pathological Society of Great Britain and Ireland.

MethBank 4.0: an updated database of DNA methylation across a variety of species.

DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains.

In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Quantitative susceptibility mapping through model-based deep image prior (MoDIP).

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.

Correlation between inflammatory cytokines and the likelihood of developing multiple types of digestive system cancers: A Mendelian randomization study.

OBJECTIVE: Inflammatory cytokines have been linked to digestive system cancers, yet their exact causal connection remains uncertain. Consequently, we conducted a Mendelian randomization (MR) analysis to gauge how inflammatory cytokines are linked to the risk of five prevalent digestive system cancers (DSCs). METHODS: We collected genetic variation data for 41 inflammatory cytokines from genome-wide association studies (GWAS), and the results data for five common diseases from the Finnish database. Our primary analytical approach involved employing the inverse-variance weighted, residual sum (IVW) method, complemented by the MR-Egger method, the weighted median method, simple mode analysis, and weighted mode analysis as supplementary analytical techniques. Furthermore, we conducted multiple sensitivity analyses. RESULTS: Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), macrophage colony-stimulating factor (M-CSF), and interleukin (IL)-18 showed a negative association with the risk of hepatocellular carcinoma. Conversely, TRAIL was inversely linked to the risk of gastric cancer, while IL-16 exhibited a positive correlation with gastric cancer risk. Stem cell factor (SCF) acted as a protective factor against pancreatic cancer. For colorectal cancer, IL-7, IL-9, IL-13, and vascular endothelial growth factor (VEGF) were identified as risk factors. Notably, our results did not indicate a significant correlation between inflammatory cytokines and the risk of esophageal cancer. CONCLUSION: Our research unveils potential connections between 41 inflammatory cytokines and the risk of five common DSCs through a MR analysis. These associations offer valuable insights that could aid in the development of diagnostic biomarkers and the identification of novel therapeutic targets for DSCs.

Modular Synthesis of 1,2-Benzothiazines and 1,2-Benzothiazine 1-Imines via Palladium-Catalyzed C-H/C-C Activation Reactions.

In this study, a modular approach toward cyclic sulfoximines and sulfondiimines via palladium-catalyzed intramolecular C-H/C-C activation reactions was reported. Various 1,2-benzothiazines including bicyclic, tricyclic, highly fused ones, ones of the seven-membered ring, along with 1,2-benzothiazine 1-imines were accessed in good yields. KIE experiment demonstrated that the C-H bond cleavage at the position ortho to the sulfoximine group is not the rate-determining step in the coupling reaction.

One-pot sequential synthesis of unsymmetrical diarylmethanes using methylene chloride as a C1-synthon.

Bisindolylmethane (BIM) and its derivatives are widely used in the pharmaceutical industry due to their significant biological activities. However, most reported synthetic methods are focused on the synthesis of symmetric BIMs, while the synthesis of unsymmetrical BIMs remains a challenge. Herein, an unprecedented two-step one-pot method to afford unsymmetrically substituted 3,3'-BIM frameworks, using methylene chloride (DCM) as the C1-synthon is reported. In this protocol, the formation of two C-C bonds can be achieved via a one-pot reaction. The utility of commercially available phenols and anilines was also demonstrated in the construction of unsymmetrical diarylmethanes. This protocol provides a straightforward approach to access diverse unsymmetrical diarylmethane derivatives under simple and mild conditions. The broad substrate compatibility and good functional group tolerance of the protocol support its practical application potential.

New chromone derivatives bearing thiazolidine-2,4-dione moiety as potent PTP1B inhibitors: Synthesis and biological activity evaluation.

A series of chromone derivatives bearing thiazolidine-2,4-dione moiety (5 âˆ¼ 37) were synthesized and evaluated for their PTP1B inhibitory activity, interaction analysis and effects on insulin pathway in palmitic acid (PA)-induced HepG2 cells. The results showed that all derivatives presented potential PTP1B inhibitory activity with IC50 values of 1.40 ± 0.04 âˆ¼ 16.83 ± 0.54 µM comparing to that of positive control lithocholic acid (IC50: 9.62 ± 0.14 µM). Among them, compound 9 had the strongest PTP1B inhibitory activity with the IC50 value of 1.40 ± 0.04 µM. Inhibition kinetic study revealed that compound 9 was a reversible mixed-type inhibitor against PTP1B. CD spectra results confirmed that compound 9 changed the secondary structure of PTP1B by their interaction. Molecular docking explained the detailed binding between compound 9 and PTP1B. Compound 9 also showed 19-fold of selectivity for PTP1B over TCPTP. Moreover compound 9 could recovery PA-induced insulin resistance by increasing the phosphorylation of IRSI and AKT. CETSA results showed that compound 9 significantly increased the thermal stability of PTP1B.

Mitigating the effects of polyethylene microplastics on Pisum sativum L. quality by applying microplastics-degrading bacteria: A field study.

Polyethylene microplastics (PE-MPs) have been widely reported for their adverse effects on soil ecosystems. However, there are fewer field studies on addressing PE-MPs contamination in soil. This study investigated the effects of PE-MPs on soil properties, rhizosphere soil microorganisms, and pea (Pisum sativum L.) nutrient composition in a field experiment and mitigated the effects of PE-MPs by adding MPs-degrading bacteria. The results showed that the addition of MPs-degrading bacteria mitigated the effects of PE-MPs on the hydrolyzable nitrogen content in the soil. In addition, the introduction of MPs-degrading bacteria resulted in an increase in the Shannon indices of microorganisms in the soil. This also effectively regulates the structure of the soil microbial community to be closest to that of normal soil. Notably, the addition of MPs-degrading bacteria increased the protein, starch, cellulose, and chlorophyll contents of pea grains. This study demonstrated the ability to improve the nutrient content of peas affected by MPs by adding MPs-degrading bacteria. This study contributes to our understanding of the effects of PE-MPs on soil-microbe-plant systems and provides new insights into the bioremediation of PE-MPs in agricultural soils.

scMethBank: a database for single-cell whole genome DNA methylation maps.

Single-cell bisulfite sequencing methods are widely used to assess epigenomic heterogeneity in cell states. Over the past few years, large amounts of data have been generated and facilitated deeper understanding of the epigenetic regulation of many key biological processes including early embryonic development, cell differentiation and tumor progression. It is an urgent need to build a functional resource platform with the massive amount of data. Here, we present scMethBank, the first open access and comprehensive database dedicated to the collection, integration, analysis and visualization of single-cell DNA methylation data and metadata. Current release of scMethBank includes processed single-cell bisulfite sequencing data and curated metadata of 8328 samples derived from 15 public single-cell datasets, involving two species (human and mouse), 29 cell types and two diseases. In summary, scMethBank aims to assist researchers who are interested in cell heterogeneity to explore and utilize whole genome methylation data at single-cell level by providing browse, search, visualization, download functions and user-friendly online tools. The database is accessible at: https://ngdc.cncb.ac.cn/methbank/scm/.

EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study.

Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.

Peptides Used for Heavy Metal Remediation: A Promising Approach.

In recent years, heavy metal pollution has become increasingly prominent, severely damaging ecosystems and biodiversity, and posing a serious threat to human health. However, the results of current methods for heavy metal restoration are not satisfactory, so it is urgent to find a new and effective method. Peptides are the units that make up proteins, with small molecular weights and strong biological activities. They can effectively repair proteins by forming complexes, reducing heavy metal ions, activating the plant's antioxidant defense system, and promoting the growth and metabolism of microorganisms. Peptides show great potential for the remediation of heavy metal contamination due to their special structure and properties. This paper reviews the research progress in recent years on the use of peptides to remediate heavy metal pollution, describes the mechanisms and applications of remediation, and provides references for the remediation of heavy metal pollution.

Affine transformation edited and refined deep neural network for quantitative susceptibility mapping.

Deep neural networks have demonstrated great potential in solving dipole inversion for Quantitative Susceptibility Mapping (QSM). However, the performances of most existing deep learning methods drastically degrade with mismatched sequence parameters such as acquisition orientation and spatial resolution. We propose an end-to-end AFfine Transformation Edited and Refined (AFTER) deep neural network for QSM, which is robust against arbitrary acquisition orientation and spatial resolution up to 0.6 mm isotropic at the finest. The AFTER-QSM neural network starts with a forward affine transformation layer, followed by a Unet for dipole inversion, then an inverse affine transformation layer, followed by a Residual Dense Network (RDN) for QSM refinement. Simulation and in-vivo experiments demonstrated that the proposed AFTER-QSM network architecture had excellent generalizability. It can successfully reconstruct susceptibility maps from highly oblique and anisotropic scans, leading to the best image quality assessments in simulation tests and suppressed streaking artifacts and noise levels for in-vivo experiments compared with other methods. Furthermore, ablation studies showed that the RDN refinement network significantly reduced image blurring and susceptibility underestimation due to affine transformations. In addition, the AFTER-QSM network substantially shortened the reconstruction time from minutes using conventional methods to only a few seconds.

Stomatal conductance in rice leaves and panicles responds differently to abscisic acid and soil drought.

Improvement of photosynthesis in non-foliar green tissues is beneficial for enhancing crop yield. Recently, we have demonstrated that panicle stomatal conductance is a major limiting factor for photosynthesis. However, mechanisms underlying the responses of panicle stomatal conductance (gs,panicle) and photosynthesis (Apanicle) to environmental stimuli remain unknown. In the present study, the responses of gs,panicle and leaf stomatal conductance (gs,leaf) to exogenous application of abscisic acid and step-changes in vapor pressure deficit were investigated at the anthesis stage in pot-grown rice plants. Furthermore, the effects of drought on Apanicle and leaf photosynthesis (Aleaf) were examined. Smearing and xylem feeding of abscisic acid significantly decreased gs,leaf. In contrast, while smearing of abscisic acid substantially increased gs,panicle, its xylem feeding dramatically decreased gs,panicle. In addition, both gs,leaf and gs,panicle effectively responded to step changes in vapor pressure deficit. Furthermore, both Aleaf and Apanicle were sensitive to plant dehydration; however, given the lower sensitivity of panicle water potential than leaf water potential to drought, Apanicle was less sensitive to soil drought than Aleaf. These findings indicate that gs,panicle is hydropassively regulated, while panicle photosynthesis is less sensitive to drought.

Bicyclic Amidine-Triggered Cyclization of o-Alkynylisocyanobenzenes: Synthesis of Lactam-Derived Quinolines.

Efficient access to the synthesis of lactam-derived quinoline through a bicyclic amidine-triggered cyclization reaction from readily prepared o-alkynylisocyanobenzenes has been developed. The reaction was initiated by nucleophilic attack of the bicyclic amidines to o-alkynylisocyanobenzenes, subsequently with intramolecular cyclization to produce a DBU-quinoline-based amidinium salt, followed by hydrolysis to afford the lactam-derived quinoline in moderate to good yields.

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks.

Quantitative susceptibility mapping (QSM) is an MRI post-processing technique that produces spatially resolved magnetic susceptibility maps from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but accumulates errors. This study aims to overcome existing limitations by developing a Laplacian-of-Trigonometric-functions (LoT) enhanced deep neural network for near-instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MRI phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the proposed neural networks. The proposed iQFM and iQSM methods in healthy subjects yielded comparable results to those involving the intermediate steps while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. High susceptibility contrast between multiple sclerosis lesions and healthy tissue was also achieved using the proposed methods. Comparative studies indicated that the most significant contributor to iQFM and iQSM over conventional multi-step methods was the elimination of traditional Laplacian unwrapping. The reconstruction time on the order of minutes for traditional approaches was shortened to around 0.1 s using the trained iQFM and iQSM neural networks.

Effects of contrasting N supplies on leaf photosynthetic induction under fluctuating light in rice (Oryza sativa L.).

Nitrogen (N) is one of the most important nutrients for crop growth and yield formation, as it is an important constituent in a large amount of proteins, cell walls, and membranes related to photosynthesis. Recently, increasing studies have suggested the important roles of photosynthetic induction and stomatal movement under fluctuating light in regulating plant carbon assimilation and water use efficiency. How leaf N content affects photosynthetic induction remains uncertain. Here, we observed a significantly faster photosynthetic induction with the increasing supply of N under fluctuating light conditions. Photosynthetic induction was mainly limited by biochemical processes but not stomatal opening after a stepwise increase in irradiance across different N supplies. Higher N supply enhanced photosynthetic efficiency under constant and fluctuating light conditions but reduced leaf intrinsic water use efficiency (WUEi ). This study is mainly focused on clarifying the crucial limitation of photosynthetic induction under different N treatments, which may facilitate the improvement of photosynthetic efficiency under complicated environments in the future.

EWAS Data Hub: a resource of DNA methylation array data and metadata.

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.