The surface plasmon resonance (SPR) biosensor is a very powerful tool for studying binding mechanisms between all kinds of biomolecular species without the need of any tagging or labeling. However, application of SPR at present is largely confined to the laboratory environment and SPR biosensors are yet to be widely accepted by the point-of-care diagnostics industry. Despite its attractive label-free and real time measurement capabilities, the lack of sensitivity as compared to conventional fluorescence based techniques has been the main barrier. It has largely accepted that when the sensitivity issue is resolved, enormous commercialisation opportunities will follow as label-free detection techniques are just too attractive for the end-user who wants to quickly get to the identification of those target biomolecules.
Abstract Genomic Knowledgebase (GenomicKB) is a graph database for researchers to explore and investigate human genome, epigenome, transcriptome, and 4D nucleome with simple and efficient queries. The database uses a knowledge graph to consolidate genomic datasets and annotations from over 30 consortia and portals, including 347 million genomic entities, 1.36 billion relations, and 3.9 billion entity and relation properties. GenomicKB is equipped with a web-based query system (https://gkb.dcmb.med.umich.edu/) which allows users to query the knowledge graph with customized graph patterns and specific constraints on entities and relations. Compared with traditional tabular-structured data stored in separate data portals, GenomicKB emphasizes the relations among genomic entities, intuitively connects isolated data matrices, and supports efficient queries for scientific discoveries. GenomicKB transforms complicated analysis among multiple genomic entities and relations into coding-free queries, and facilitates data-driven genomic discoveries in the future.
A modified alloy (Al-0.7Mn) was designed and fabricated with an increased Mn content up to 0.7wt.% and a controlled Fe content of 0.1wt.% and compared with the conventional Al3102 (Al-0.3Mn) alloy using the air-slip casting process. Both alloys were homogenized at 510°C for 10 hours and then air-cooled. The microstructure, corrosion resistance, and mechanical properties of these materials were investigated. In the modified Al-0.7Mn alloy, the Mn/Fe ratios were found to be higher in both the α-Al matrix and the intermetallic compound of Al6(Mn, Fe) compared to those of the Al3102 alloy. Additionally, the size and volume fraction of the Al6(Mn, Fe) phase were relatively larger and higher in the modified Al-0.7Mn alloy, while the grain size of the α-Al matrix was significantly smaller. The galvanic corrosion test results indicated that the corrosion potential (Ecorr) of the conventional Al3102 alloy was higher than that of the modified Al-0.7Mn alloy (Al-0.7Mn: -682.1mV, Al3102: -652.4mV). In contrast, the corrosion current (Icorr) and corrosion rate were measured to be 49.86 μA and 0.541 mm/year for the Al-0.7Mn alloy, and 53.91 μA and 0.585 mm/year for the Al3102 alloy, respectively. Thus, it was confirmed that the corrosion rate of the Al-0.7Mn alloy was slower compared to the conventional alloy, indicating better corrosion resistance. Room temperature tensile results showed that the tensile strengths of the modified and conventional alloys were 92.55 MPa and 78.39 MPa, respectively, demonstrating that the modified Al-0.7Mn alloy achieved higher strength without a significant decrease in ductility. This improvement is attributed to the higher Mn/Fe wt.% ratio in the Al6(Mn, Fe) phase of the modified Al-0.7Mn alloy, which can reduce the detrimental effect of Fe element and enhance the corrosion resistance. Additionally, the larger size and higher volume fraction of Al6(Mn, Fe) in the modified alloy, along with the smaller grain size, may contribute to the higher tensile strength. Based on these results, the corrosion mechanisms and deformation behavior of the modified Al-0.7Mn alloy were also discussed.
Life-expectancy is increasing in the western-world. Unfortunately, increasing lifespan does not coincide with increasing health-span. Older people (≥60 years) are living longer with chronic illnesses such as asthma. Increasing age is associated with profound changes in the immune system including immunosenescence and inflammageing resulting in increased incidence and severity of infections, as well as other diseases. Yet despite these dramatic changes in immunity, the impact of increasing age on severe asthma phenotype and immune function is not well understood. The majority of clinical and research studies to-date have focussed on younger patients, often actively excluding older participants, despite the 2014 National Review of Asthma Deaths that showed mortality from asthma in older adults has not improved over 30 years, in contrast to younger patients.
Aim
The aim of this project is to dissect how the combination of old age and asthmatic disease changes the immune system and to dissect the implications for antigen-specific immunity.
Methods
Peripheral blood was collected after full informed written consent. Whole blood high dimensional spectral flow analysis was performed using a 27 colour panel and the Cytek Aurora. PBMCs were isolated and cryopreserved and subsequently stimulated with peptides from common respiratory pathogens including RSV, Influenza, SARs-CoV-2 and Aspergillus. Antigen-specific immunity was assessed by flow cytometric assessment of activation markers and proliferation using Celltrace Violet.
Results
In this study, we observed that there was an increase in senescent CD4+ and CD8+ T cells (termed EMRA) in older asthma patients as compared to age-matched controls. The T cells present in older asthma patients are more exhausted with increased expression of exhaustion markers PD-1 and CD57. This increase in immunosenescence and immune exhaustion correlated with reduced antigen-specific immunity in vitro to common respiratory pathogens.
Discussion
We conclude that older severe asthma patients have increased immunosenescence and immune exhaustion which leads to a reduced antigen-specific immunity. This could explain in part why older asthma patients are more susceptible to respiratory infections, themselves a trigger of asthma exacerbations.
Organic light-emitting device (OLED) is regarded as the potential application for future display. However, one of the bottlenecks is the OLED package issue, which results in short term device lifetime. Currently, a new laser bonding package process is proposed. In this paper, the investigation of transient temperature field analysis for the laser bonding process is presented. Finite element model is applied in ANSYS and compiled by subroutine of APDL. Moving heat flux and birth-death element method are both adopted in order to achieve the complicated bonding process. The laser bonding process comes to quasi-steady state after a short time of initial transient stage. Through a series parameters simulation, parameters as moving velocity, laser power and laser beam radius show a significant effect on bonding process. Furthermore, by case study, the optimization of the bonding parameters was carried out for future experimental investigation and validation.
Knowledge graphs have recently emerged as a powerful data structure to organize biomedical knowledge with explicit representation of nodes and edges. The knowledge representation is in a machine-learning ready format and supports explainable AI models. However, PubMed, the largest and richest biomedical knowledge repository, exists as free text, limiting its utility for advanced machine learning tasks. To address the limitation, we present LiteralGraph, a computational framework that rigorously extracts biomedical terms and relationships from PubMed literature. Using this framework, we established Genomic Literature Knowledge Base (GLKB), a knowledge graph that consolidates 263,714,413 biomedical terms, 14,634,427 biomedical relationships, and 10,667,370 genomic events from 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that make it accessible to researchers for various usages, including machine learning using the semantic knowledge in PubMed articles, reducing hallucination of large language models (LLM), and helping experimental scientists explore their data using vast PubMed evidence.
How ubiquitous transcription factors (TFs) coordinate temporal inputs from broadly expressed epigenetic factors to control cell fate remains poorly understood. Here, we uncover a molecular relationship between p53, an abundant embryonic TF, and WDR5, an essential member of the MLL chromatin modifying complex, that regulates mouse embryonic stem cell fate. Wild-type Wdr5 or transient Wdr5 knockout promotes a distinct pattern of global chromatin accessibility and spurs neuroectodermal differentiation through an RbBP5-dependent process in which WDR5 binds to, and activates transcription of, neural genes. Wdr5 rescue after its prolonged inhibition targets WDR5 to mesoderm lineage-specifying genes, stimulating differentiation toward mesoderm fates in a p53-dependent fashion. Finally, we identify a direct interaction between WDR5 and p53 that enables their co-recruitment to, and regulation of, genes known to control cell proliferation and fate. Our results unmask p53-dependent mechanisms that temporally integrate epigenetic WDR5 inputs to drive neuroectoderm and mesoderm differentiation from pluripotent cells.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)