EFNB2 (phospho-Tyr316) Antibody
- Known as:
- EFNB2 (phosphorilated-Tyr316) Antibody
- Catalog number:
- abx000386
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Abbexa
- Gene target:
- EFNB2 (phospho-Tyr316) Antibody
Related genes to: EFNB2 (phospho-Tyr316) Antibody
- Gene:
- EFNB2 NIH gene
- Name:
- ephrin B2
- Previous symbol:
- EPLG5
- Synonyms:
- LERK5, Htk-L, HTKL, MGC126226, MGC126227, MGC126228
- Chromosome:
- 13q33.3
- Locus Type:
- gene with protein product
- Date approved:
- 1995-01-17
- Date modifiied:
- 2016-10-05
Related products to: EFNB2 (phospho-Tyr316) Antibody
Related articles to: EFNB2 (phospho-Tyr316) Antibody
- Neuropathic pain affects an estimated 7%-10% of the global population and imposes an annual economic burden exceeding $600 billion in the United States alone. It lacks robust objective biomarkers; current diagnosis relies heavily on subjective reporting and heterogeneous phenotypes. Currently utilized pain assessment tools include the brief pain inventory (BPI), numerical rating scales (0-10 pain scores), and the visual analog score (VAS), which depend on patient-reported outcomes and are influenced by social, psychological and contextual factors. This subjectivity contributes to heterogeneous phenotyping and variability (>30%) towards the treatment response. Emerging transcriptomic and epitranscriptomic evidence suggests that RNA-based biomarkers may offer a biologically sound and objective approach to understanding and managing pain by capturing underlying molecular mechanisms. Therefore, the present clinical review focused on RNA biomarker classes (mRNA, miRNA, lncRNA, RNA editing, RNA modifications) and proposes a clinically deployable testing system for diagnosis, stratification, and treatment monitoring, since there are no FDA-approved RNA-based biomarkers for pain. Therefore, this review synthesizes evidence from immune-cell transcriptomic meta-analysis (TCL1A/ERAP2), dorsal root ganglion (DRG) and central nervous system gene expression patterns (EFNB2, GABBR1, NCAM1, SCN11A)/brain genetic architecture via single-cell omics integration, and atlas-driven frameworks, like iPain single-cell atlas of pain chronification and nociceptor senescence. Additional sources include studies on RNA editing mediator adenosine deaminase acting on RNA2 (ADAR2), clinical and translational evidence supporting miRNA biomarkers, and lncRNA axes (NEAT1/miR-183-5p; H19/miR-141) as tissue-specific regulatory nodes. Additionally, m6A epitranscriptomic modifications regulated by the METTL3/METTL14 writer complex and FTO/ALKBH5 erasers, with site-specific methylation of GRIN2B mRNA shown to upregulate GluN2B in dorsal horn neurons and augment central sensitization. These biomarkers also demonstrate potential utility as pharmacodynamic readouts in drug and neuro-modulation trials. Additionally, an emerging RNA workflow technology pathway leveraging rapid low-input RNA based assays was also explained. All evidence supports the idea that these biomarkers can provide complementary insight into the mechanisms underlying pain. Although current evidence supports the feasibility of RNA-based biomarkers as indicators of key biological processes, however, the current pain biology score remains at the theoretical model stage and has not been validated through , or clinical trials. - Source: PubMed
Publication date: 2026/07/16
Soin AmolKhaira MassabSoin AvirajSoin DhilenShah ShreyasTolppi SabrinaTripathi Anubhav - Nipah virus (NiV) is a highly lethal zoonotic pathogen with significant pandemic potential, for which no approved antiviral therapies are currently available. Viral entry is mediated by the interaction between the NiV attachment glycoprotein (NiV-G) and host ephrin receptors, particularly ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3), making this interface an attractive therapeutic target. In this study, we evaluated a set of structurally related flavonoids, apigenin, cynaroside, and lonicerin, as potential modulators of the EFNB2-NiV-G and EFNB3-NiV-G interactions. These compounds were selected based on their structural similarity, reported antiviral activity, chemical diversity, and favorable drug-like properties. Apigenin was employed as a reference scaffold due to its well-characterized pharmacological profile and its suitability for guiding analog-based compound selection. Apigenin served as a reference scaffold for selecting structurally related flavonoids, which were analyzed through density functional theory optimization, molecular docking, pharmacokinetic and toxicity predictions, molecular dynamics simulations, and binding free energy calculations. These flavonoids demonstrated high predicted affinity for both the EFNB2-NiV-G and EFNB3-NiV-G interfaces. According to results, these compounds consistently interacted with residues known to play a critical role in receptor recognition, with special emphasis on leucine and tryptophan residues within the G-H loop. These residues are well established as key determinants in the entry process of Nipah virus (NiV) into host cells, highlighting the potential relevance of these flavonoid-protein interactions. Molecular dynamics analyses indicated that flavonoid binding reduced the affinity and the conformational flexibility at the receptor-glycoprotein interfaces and decreased the stability of the complexes. Pharmacokinetic and toxicity predictions suggested favorable drug-like properties for the flavonoids, with apigenin displaying the most balanced profile. Collectively, these results support the potential of selected flavonoids as modulators of EFNB2-NiV-G and EFNB3-NiV-G interactions and provide a rationale for their prioritization in experimental studies aimed at developing scaffolds for the modulation of viral entry against Nipah virus. - Source: PubMed
Publication date: 2026/07/09
Vargas-Echeverría CarlosSaurith-Coronell OscarSierra-Hernandez OlimpoSantos-Rodríguez Juan FRodríguez-Macías Juan DMora José RPaz José LRómero Pájaro Breallan De JesúsIdarraga Negrete German DaríoMoura Ricardo Olimpio deNascimento Igor José Dos SantosBrazón Edgar A Márquez - Next-generation sequencing has accelerated the discovery of novel putative viruses in wildlife reservoirs, while identifying those with zoonotic potential remains challenging. In this study, we report the identification and characterization of Ailong virus, a novel putative henipavirus from previous bat metagenomes in China that utilizes human ephrin B2 (EFNB2) and EFNB3 as functional receptors. Using an integrated approach combining phylogenetic analysis, pseudotyped virus entry assays, antibody blockade assays, and structural modeling, we demonstrate that Ailong virus glycoprotein binds human EFNB2 and EFNB3 with high specificity, mediating pseudovirus entry into both human neuronal and respiratory epithelial cells. Structural analysis revealed the Ailong virus glycoprotein-EFNB2 interface closely resembling that of Nipah virus (NiV), with conservation of all critical receptor-binding residues. Moreover, AiV encodes an exceptionally large phosphoprotein, 1,033 amino acids in length, which is larger than any other known phosphoprotein in the subfamily Paramyxoviridae. Given its receptor usage, structural similarities to NiV, and efficient entry in human airway epithelia, Ailong virus is believed to pose a spillover risk. - Source: PubMed
Publication date: 2026/07/17
Dai GuiminYao ShuangChen WenjieZhang JingeDu XiaoyuZhao YanJin ZhenmingZhang Guigen - Both rare and common variants in the SRY-Box Transcription Factor 17 () locus are associated with pulmonary arterial hypertension (PAH). SOX17 dysregulation leads to pulmonary artery endothelial cell (PAEC) dysfunction and the obstructive remodelling that characterises PAH. - Source: PubMed
Publication date: 2026/05/18
Vasilaki EleniAkosman BediaSong ShanshanWalters RachelSharma YaminiPereira MandyKeles MerveMykytyuk Nadiya VMaude HannahSingh NavneetField GeorgeVentetuolo Corey EHoward Luke SAman JurjanWilkins Martin RKlinger James RZhao LanCebola InêsLiang Olin DRhodes Christopher J - Synaptogenesis-related neuron-glioma interactions are increasingly recognized in glioma, yet it remains unclear whether routine H&E morphology can capture these programs and improve prognostic stratification. We integrated H&E whole-slide images, transcriptomes, and clinical data from 434 TCGA gliomas. Deep learning and quantitative pathology yielded an integrated histomorphologic feature set of 2678 features. Synaptogenesis-related activity was quantified using ssGSEA for ninety-eight synaptogenesis-related genes. In the training cohort, Spearman analysis identified 149 correlated histomorphologic features, which were refined to thirty-five by elastic net regularization. Seventeen prognostic candidates were entered into the MIME1 framework, and the most parsimonious model, Enet[0.1], retained fourteen non-zero-coefficient features to define the synaptogenesis-associated histomorphologic signature and construct the pathology-derived risk score (PRS). Multi-omic analyses, Human Protein Atlas validation, and single-nucleus RNA-seq were used to investigate the hub gene and its cellular context. PRS robustly stratified survival in both training and validation cohorts and remained an independent prognostic factor after adjustment for age and 2021 WHO CNS grade. High-risk tumors showed increased stromal and immune scores and enrichment of immune, adhesion, and phagosome-related pathways. emerged as the hub gene and was enriched in glioblastoma, and -positive malignant cells displayed prominent communication with neurons, including EFNB2-EPHB1 signaling. Exploratory re-analysis of the myeloid compartment further showed that glioblastoma was enriched for suppressive TAM-like states relative to astrocytoma grade 2, supporting a shift toward a more tumor-associated and potentially immunosuppressive microenvironment. Routine H&E histomorphology can capture synaptogenesis-related molecular programs in glioma. The resulting PRS provides clinically relevant prognostic stratification, while -positive malignant cells may represent a candidate hub for neuron-tumor communication within a remodeled tumor ecosystem. - Source: PubMed
Publication date: 2026/05/12
Wu XiaolongLiu DongGeng HaomingZhang BinghanDiao HuantongZhou YiqiangSong GangCheng YeLiang Jiantao