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.