9H10 Smac / Diablo
- Known as:
- 9H10 Smac / Diablo
- Catalog number:
- mc-280
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Kamiya biomedical company
- Gene target:
- 9H10 Smac / Diablo
Related genes to: 9H10 Smac / Diablo
- Gene:
- DIABLO NIH gene
- Name:
- diablo IAP-binding mitochondrial protein
- Previous symbol:
- -
- Synonyms:
- SMAC, DIABLO-S, FLJ25049, FLJ10537, DFNA64
- Chromosome:
- 12q24.31
- Locus Type:
- gene with protein product
- Date approved:
- 2003-10-27
- Date modifiied:
- 2018-05-03
Related products to: 9H10 Smac / Diablo
Related articles to: 9H10 Smac / Diablo
- Cancer care is highly interdependent, but optimal timing and sequencing is challenging. Teamwork is a promising approach to optimize care timing and sequencing. We previously showed that the 4R Oncology model fostered a high-functioning team and enabled interdependent care optimizations in lung and breast cancers in a community health system. Herein, we evaluated whether the optimizations and 4R clinic implementation resulted in actual timing/sequencing improvements. - Source: PubMed
Publication date: 2026/05/30
Trosman Julia RWeldon Christine BLinehan ElizabethVelotta Jeffery BHennings MartiNg ChunTomita MegumiJames HenieKatzel JedLan Cynthia TSakoda Lori CAbbe TheaWei JennyOssowski StephanieRapkin BruceSuga Jennifer MarieRavelo ArlieneYu ElaineLiu Raymond - Methylomics has emerged as a central framework for understanding gene regulation in development and disease, yet the rapid expansion of profiling technologies, computational integration methods, and clinical applications has outpaced comprehensive synthesis. This review addresses that gap by systematically examining current advances across the full methylomics pipeline, from data generation to clinical translation. We draw on evidence from large-scale consortium datasets and benchmarking studies of multi-omics integration methods including MOFA, DIABLO, and deep learning architectures, single-cell and spatial methylomic technologies, long-read sequencing platforms (Oxford Nanopore, PacBio HiFi), and cell-free DNA (cfDNA) liquid biopsy approaches. The review further surveys methylation dysregulation across major disease domains, including cancer, cardiovascular disease, neurological disorders, and autoimmune conditions. Integrating methylomic data with transcriptomic and chromatin accessibility layers, particularly in spatial and single-cell contexts, substantially improves the resolution of disease-associated regulatory mechanisms. cfDNA methylation profiling emerges as a cross-disease, non-invasive monitoring platform with broad diagnostic potential, supported by machine learning-based deconvolution. We conclude that while technological barriers are diminishing, standardization of analytical workflows, population diversity in reference datasets, and regulatory alignment remain the principal challenges for translating methylomics advances into broadly accessible precision medicine. - Source: PubMed
Publication date: 2026/05/14
Kinzhebay AimanZhanymbetova AinaYerkos AinurZhetpisbay ZhibekImanbek RustemSalybekov Amankeldi A - There is a lack of studies focusing on caprellid amphipods along the coasts of Uruguay. So far, only three species, , , and , have been recorded from Uruguay. Sampling was carried out for one year (from April 2022 to March 2023) along the Uruguayan coast between latitudes 34°02'43.4"S and 34°55'05.7"S at rocky outcrops in the localities of Piriápolis, Punta Ballena, La Barra, La Paloma, La Pedrera, and Punta del Diablo. At each sampling point, scraping was performed in intertidal and shallow waters up to a depth of 10 m by snorkeling and SCUBA. All substrata, consisting mainly of algae and bryozoans, were collected within a 50 × 50 cm grid. Additionally, in Punta del Diablo, buoyant material stranded on the beach was also collected. This work represents the first record of the species , , , and Paracaprella aff. pusilla for Uruguay, increasing the number of known species in the country to seven. Herein, an illustrated key to the seven species known to occur in Uruguay is presented. The low caprellid diversity in Uruguay could be related to the highly variable abiotic characteristics of the Uruguayan coast, mainly due to the freshwater input from the Río de la Plata, and to other biotic factors such as the low diversity of macroalgae. The taxonomical impediment (lack of taxonomists and scarce sampling in the area) could also cause an underestimation of species richness. Therefore, additional sampling efforts, especially in deeper waters and sediment habitats, are still necessary to properly characterize this amphipod group in Uruguay. - Source: PubMed
Publication date: 2026/05/11
Ramos TaiaraVerdi AnaGuerra-García José M - Most previous studies aimed to establish etiological signatures of thyroid tumors compared sporadic papillary thyroid carcinomas (sPTC) and PTC that develop in individuals exposed to ionizing radiation during childhood. However, such approaches may lead to a biased signature combining exposure markers independent of the carcinogenic process and markers of radiation-induced carcinogenesis. We analyzed the miRNome (Affymetrix) and transcriptome (RNA sequencing) of a series of normal thyroid tissues and PTC from Ukrainian individuals contaminated with iodine-131 released by the Chornobyl Nuclear Power Plant in 1986 at high (> 0.5 Gy; N = 9) or low (< 50 mGy; N = 12) thyroid radiation doses, and from unexposed Ukrainian individuals (N = 28). First, the six sample groups were analyzed jointly using partial least squares discriminant analysis (sPLS-DA) to assess whether normal tissues and PTC shared common multi-omic signatures associated with exposure history, independent of carcinogenesis. Next, we applied a multiblock sPLS-DA (DIABLO) to isolate markers associated with exposure in the three normal tissue groups. Then, using the remaining miR and genes from the datasets not associated with exposure, we searched for a multi-omics signature associated with a difference in the carcinogenic process. sPLS-DA analysis of the six sample groups showed that normal tissues and PTC from exposed individuals shared a common multi-omics signature (58 miR/snoRNA, 50 genes) compared to unexposed samples. Our DIABLO analysis identified 44 miR/snoRNA and 45 genes exposure signatures distinguishing exposed from unexposed normal tissues. These signatures, when applied to PTC groups, supported that PTC developed after radiation exposure exibited exposure markers independent of any carcinogenic process. In addition to this exposure signature, we identified 39 miR/snoRNA and 64 genes signatures that identified the PTC developed after radiation exposure which deviated significantly from the sPTC profile. Normal tissues and PTC from exposed individuals exhibit a common molecular long-term memory of exposure history. Furthermore, PTC developed after radiation exposure display dose-dependent molecular specificities compared to sPTC. As PTC associated with low doses are mainly subclinical sPTC revealed by screening in the post-Chornobyl population, the proposed multi-omic signature could be attributable to sPTC developed in an exposed thyroid gland. - Source: PubMed
Publication date: 2026/05/18
Ory CatherineJouannet CharlinePanunzi LeonardoNouira AsmaBenderitter MarcLe Guen BernardSchlumberger Martinde Vathaire FlorentDeleuze Jean-FrançoisBogdanova Tetiana ITronko MykolaPushkarev Victor VMasiuk SergiiSouidi MaâmarBenadjaoud Mohamed Amine - Psoriasis is a chronic immune-mediated disease driven by genetic susceptibility and environmental factors, including microbial exposure. While HLA-C-linked variants represent the strongest genetic risk factors, their relationship with the cutaneous microbiome remains incompletely understood. This study aimed to investigate host-microbiome interactions in psoriasis through integrative multi-omics analysis. Skin microbiome profiling using 16S rRNA sequencing and targeted genotyping of psoriasis-associated single-nucleotide polymorphisms (SNPs) was performed in lesional and non-lesional skin from patients with plaque psoriasis and in healthy controls. Integrated analysis was conducted using supervised multivariate modeling (DIABLO) to identify coordinated genetic and microbial features associated with disease status. Combined genetic and microbial signatures differentiated lesional, non-lesional, and healthy skin. Variants within the HLA-C susceptibility region, including rs12191877, rs10484554, and rs4406273, showed contributions to group separation and demonstrated positive associations with . Associations involving ERAP1 variants linked antigen-processing pathways with inflammation-associated microbial taxa in lesional skin. Importantly, genotype-microbiome correlations were also detected in clinically non-lesional skin, where an increased psoriasis risk allele dosage co-varied with a higher relative abundance of and . In contrast, commensal-associated taxa were enriched in healthy controls and formed genotype-linked clusters only in non-lesional skin. These findings suggest that psoriasis is characterized by coordinated host genetic and microbial interaction patterns centered on antigen presentation pathways. The presence of a genotype-microbiome coupling in non-lesional skin may indicate that genetically determined immune configurations could shape microbial community structure prior to visible lesion development. Rather than reflecting uniform dysbiosis, psoriasis may represent a dynamic host-microbe ecosystem in which genetic susceptibility influences microbial persistence and inflammatory readiness. - Source: PubMed
Publication date: 2026/05/04
Seifert OliverAssarsson MalinManoharan LokeshwaranSöderman Jan