The Rice Oligonucleotide Array Database: an atlas of rice gene expression

BACKGROUND: Microarray technologies facilitate high-throughput gene expression analysis. However, the diversity of platforms for rice gene expression analysis hinders efficient analysis. Tools to broadly integrate microarray data from different platforms are needed. RESULTS: In this study, we developed the Rice Oligonucleotide Array Database (ROAD,http://www.ricearray.org) to explore gene expression across 1,867 publicly available rice microarray hybridizations. The ROAD’s user-friendly web interface and variety of visualization tools facilitate the extraction of gene expression profiles using gene and microarray element identifications. The ROAD supports meta-analysis of genes expressed in different tissues and at developmental stages. Co-expression analysis tool provides information on co-regulation between genes under general, abiotic and biotic stress conditions. Additionally, functional analysis tools, such as Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthology, are embedded in the ROAD. These tools facilitate the identification of meaningful biological patterns in a list of query genes. CONCLUSIONS: The Rice Oligonucleotide Array Database provides comprehensive gene expression profiles for all rice genes, and will be a useful resource for researchers of rice and other grass species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1939-8433-5-17) contains supplementary material, which is available to authorized users

Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models

Advances in Large Language Models (LLMs) have inspired a surge of research exploring their expansion into the visual domain. While recent models exhibit promise in generating abstract captions for images and conducting natural conversations, their performance on text-rich images leaves room for improvement. In this paper, we propose the Contrastive Reading Model (Cream), a novel neural architecture designed to enhance the language-image understanding capability of LLMs by capturing intricate details typically overlooked by existing methods. Cream integrates vision and auxiliary encoders, complemented by a contrastive feature alignment technique, resulting in a more effective understanding of textual information within document images. Our approach, thus, seeks to bridge the gap between vision and language understanding, paving the way for more sophisticated Document Intelligence Assistants. Rigorous evaluations across diverse tasks, such as visual question answering on document images, demonstrate the efficacy of Cream as a state-of-the-art model in the field of visual document understanding. We provide our codebase and newly-generated datasets at https://github.com/naver-ai/crea

Динаміка та аналіз виробничого травматизму та професійних захворювань в Україні

Кожного року в Україні на виробництві травмується понад 10 тис. людей, з них гине понад 600 осіб. Оптимістична, на перший погляд, статистика, за якою травматизм на виробництві за роки незалежності України зменшився в десять разів, виявляється не такою вже й оптимістичною, коли аналізуються конкретні цифри

Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks

Multi-dimensional proteomic analyses provide different layers of protein information, including protein abundance and post-translational modifications. Here, we report an integrated analysis of protein expression, phosphorylation, and N-glycosylation by serial enrichments of phosphorylation and N-glycosylation (SEPG) from the same tissue samples. On average, the SEPG identified 142,106 unmodified peptides of 8,625 protein groups, 18,846 phosphopeptides (15,647 phosphosites), and 4,019 N-glycopeptides (2,634 N-glycosites) in tumor and adjacent normal tissues from three gastric cancer patients. The combined analysis of these data showed that the integrated analysis additively improved the coverages of gastric cancer-related protein networks; phosphoproteome and N-glycoproteome captured predominantly low abundant signal proteins, and membranous or secreted proteins, respectively, while global proteome provided abundances for general population of the proteome. Therefore, our results demonstrate that the SEPG can serve as an effective approach for multi-dimensional proteome analyses, and the holistic profiles of protein expression and PTMs enabled improved interpretation of disease-related networks by providing complementary information.1

Phenotypic and Functional Changes of Peripheral Ly6C(+) T Regulatory Cells Driven by Conventional Effector T Cells

A relatively high affinity/avidity of T cell receptor (TCR) recognition for self-peptide bound to major histocompatibility complex II (self-pMHC) ligands is a distinctive feature of CD4 T regulatory (Treg) cells, including their development in the thymus and maintenance of their suppressive functions in the periphery. Despite such high self-reactivity, however, all thymic-derived peripheral Treg populations are neither homogenous in their phenotype nor uniformly immune-suppressive in their function under steady state condition. We show here that based on the previously defined heterogeneity in the phenotype of peripheral Treg populations, Ly6C expression on Treg marks a lower degree of activation, proliferation, and differentiation status as well as functional incompetence. We also demonstrate that Ly6C expression on Treg in a steady state is either up-or downregulated depending on relative amounts of tonic TCR signals derived from its contacts with self-ligands. Interestingly, peripheral appearance and maintenance of these Ly6C-expressing Treg cells largely differed in an age-dependent manner, with their proportion being continuously increased from perinatal to young adult period but then being gradually declined with age. The reduction of Ly6C(+) Treg in the aged mice was not due to their augmented cell death but rather resulted from downregulation of Ly6C expression. The Ly6C down-regulation was accompanied by proliferation of Ly6C(+) Treg cells and subsequent change into Ly6C-effector Treg with concomitant restoration of immune-suppressive activity. Importantly, we found that this phenotypic and functional change of Ly6C(+) Treg is largely driven by conventional effector T cell population. Collectively, these findings suggest a potential cross-talk between peripheral Treg subsets and effector T cells and provides better understanding for Treg homeostasis and function on maintaining self-tolerance.110Ysciescopu

Identification of novel urinary biomarkers for assessing disease activity and prognosis of rheumatoid arthritis

To optimize treatment for rheumatoid arthritis (RA), it is ideal to monitor the disease activity on a daily basis because RA activity fluctuates over time. Urine can be collected routinely at home by patients. Recently, we identified four urinary biomarker candidates-gelsolin (GSN), orosomucoid (ORM)1, ORM2 and soluble CD14 (sCD14)-in RA patients through transcriptomic and proteomic studies. Here, we investigated the clinical significance of the aforementioned urinary biomarker candidates in a prospective manner. For the first time, we found that urinary ORM1, ORM2 and sCD14 levels, but not GSN, were elevated in RA patients and had a positive correlation with the status of the disease activity. In particular, urine tests for ORM 1, ORM 2 and sCD14 efficiently represented the presence of high RA activity without the need for measuring blood markers. In a parallel study, a more rapid radiographic progression over 3 years was observed in patients with higher ORM2 levels. Combined measurements of urinary ORM2 and serum C-reactive protein synergistically increased the predictability of the radiographic progression of RA (odds ratio: 46.5). Collectively, our data provide evidence that blood-free, urinary biomarkers are promising surrogates for assessing disease activity and prognosis of RA. We anticipate that our urinary biomarkers will provide novel candidates for patient-driven measurements of RA activity at home and can shift the paradigm from blood to urine testing in the assessment of RA activity and prognosis in hospitals.1

Transcription factor NFAT5 promotes macrophage survival in rheumatoid arthritis

Defective apoptotic death of activated macrophages has been implicated in the pathogenesis of rheumatoid arthritis (RA). However, the molecular signatures defining apoptotic resistance of RA macrophages are not fully understood. Here, global transcriptome profiling of RA macrophages revealed that the osmoprotective transcription factor nuclear factor of activated T cells 5 (NFAT5) critically regulates diverse pathologic processes in synovial macrophages including the cell cycle, apoptosis, and proliferation. Transcriptomic analysis of NFAT5-deficient macrophages revealed the molecular networks defining cell survival and proliferation. Proinflammatory M1-polarizing stimuli and hypoxic conditions were responsible for enhanced NFAT5 expression in RA macrophages. An in vitro functional study demonstrated that NFAT5-deficient macrophages were more susceptible to apoptotic death. Specifically, CCL2 secretion in an NFAT5-dependent fashion bestowed apoptotic resistance to RA macrophages in vitro. Injection of recombinant CCL2 into one of the affected joints of Nfat5+/-mice increased joint destruction and macrophage infiltration, demonstrating the essential role of the NFAT5/CCL2 axis in arthritis progression in vivo. Moreover, after intra-articular injection, NFAT5-deficient macrophages were more susceptible to apoptosis and less efficient at promoting joint destruction than were NFAT5-sufficient macrophages. Thus, NFAT5 regulates macrophage survival by inducing CCL2 secretion. Our results provide evidence that NFAT5 expression in macrophages enhances chronic arthritis by conferring apoptotic resistance to activated macrophages.clos

Elucidation of molecular basis of osteolytic bone lesions in advanced multiple myeloma

Osteolytic bone lesion is a major cause of decreased quality of life and poor prognosis in patients with multiple myeloma (MM), but molecular pathogenesis of the osteolytic process in MM remains elusive. Fms-like tyrosine kinase 3 ligand (FLT3L) was reported to be elevated in bone marrow and blood of patients with advanced MM who often show osteolysis. Here, we investigated a functional link of FLT3L to osteolytic process in MM. We recruited 86, 306 and 52 patients with MM, acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL), respectively. FLT3L levels of patients with hematologic malignancies were measured in bone marrow-derived plasma and found to be significantly elevated in MM than in AML or ALL that rarely show osteolysis. FLT3L levels were further elevated in MM patients with bone lesion compared with patients without bone lesion. In vitro cell-based assays showed that the administration of FLT3L to HEK293T, HeLa and U2OS cells led to an increase in the DKK1 transcript level through STAT3 phosphorylation at tyrosine 705. WNT reporter assay showed that FLT3L treatment reduced WNT signaling, and nuclear translocation of β-catenin. These results collectively show that FLT3L-STAT3-DKK1 pathway inhibits WNT signaling-mediated bone formation in MM, which can cause osteolytic bone lesion. Finally, transcriptomic profiles revealed that FLT3L and DKK1 were predominantly elevated in the hyperdiploidy subtype of MM. Taken together, FLT3L can serve as a promising biomarker for predicting osteolytic bone lesion and also a potential therapeutic target to prohibit the progression of osteolytic process in MM with hyperdiploidy

Segmented tomographic evaluation of structural degradation of carbon support in proton exchange membrane fuel cells

The variation of the three-dimensional (3D) structure of the membrane electrode of a fuel cell during proton exchange cycling involves the corrosion/compaction of the carbon support. The increasing degradation of the carbon structure continuously reduces the electrocatalytic performance of proton exchange membrane fuel cells (PEM-FCs). This phenomenon can be explained by performing 3D tomographic analysis at the nanoscale. However, conventional tomographic approaches which present limited experimental feasibility, cannot perform such evaluation and have not provided sufficient structural information with statistical significance thus far. Therefore, a reliable methodology is required for the 3D geometrical evaluation of the carbon structure. Here, we propose a segmented tomographic approach which employs pore network analysis that enables the visualization of the geometrical parameters corresponding to the porous carbon structure at a high resolution. This approach can be utilized to evaluate the 3D structural degradation of the porous carbon structure after cycling in terms of local surface area, pore size distribution, and their 3D networking. These geometrical parameters of the carbon body were demonstrated to be substantially reduced owing to the cycling-induced degradation. This information enables a deeper understanding of the degradation phenomenon of carbon supports and can contribute to the development of stable PEM-FC electrodes. (C) 2022 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press