SORD (Human) Matched Antibody Pair ab pairs
- Known as:
- SORD (Human) Matched Antibody Pair ab pairs
- Catalog number:
- 'H00006652-AP51
- Product Quantity:
- 1 set
- Category:
- -
- Supplier:
- ACR
- Gene target:
- SORD (Human) Matched Antibody Pair pairs
Related genes to: SORD (Human) Matched Antibody Pair ab pairs
- Gene:
- SORD NIH gene
- Name:
- sorbitol dehydrogenase
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 15q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-22
- Date modifiied:
- 2016-10-05
Related products to: SORD (Human) Matched Antibody Pair ab pairs
Related articles to: SORD (Human) Matched Antibody Pair ab pairs
- Pancreatic ductal adenocarcinoma (PDAC) carries a poor prognosis largely due to lack of efficient diagnostic means. We applied mass spectrometry-based high-coverage plasma proteome analysis accompanying with machine learning to develop a 5-protein diagnostic model: SNCA, GCLC, LBP, ALAD, and SORD. For differentiating PDAC from healthy controls (HCs), this model reached an area under the curve (AUC) of 0.973 with 100% sensitivity and 85% specificity in the discovery cohort, with nested cross-validation confirming robust performance (AUC = 0.958). Further validation centered on SNCA achieved an AUC of 0.835 in an independent validation cohort. SNCA also showed good diagnostic performance in PDAC patients with low CA19-9 level (AUC = 0.868), underscoring its potential value for this subgroup. Overall, these findings indicate SNCA as a promising candidate plasma diagnostic marker for PDAC. - Source: PubMed
Publication date: 2026/06/01
Yu JiaqiLuo WenhuiZhang JianQin BaoyiWang XiaoxinYang GuoqianHou WenhaoLi ChaoyingLiu FujunSun ShijieLiu XinYing Wantao - Developer discussions particularly on programming related questions answering (Q&A) sites, contain useful information, which, if mined and analysed carefully can be transformed into insightful recommendations for developers about which software to use or prefer over others, matching with one's requirements for different software development activities. However, there is a long way to go before such a system can be realized. As a first step in this direction, we empirically explored the developers' discussions on Stack Overflow, one of the most popular Q&A sites among developers, with a particular emphasis on mining software recommendations related insights. We considered the Stack Overflow data dump published in October 2025 containing complete data of the site since 2008. The data extraction process started with the conversion of the gigantic XML files to SQL Server database table records. We then applied a keywords-based filtering approach to identify potential recommendation related queries in questions, and recommendations in answers and comments related to any aspect of software development. The set of keywords comprised of 19 keywords including the term 'recommend' along with its 14 synonyms and 4 antonyms. The extracted dataset contains 73.9k (0.31%) questions containing such terms in the question title, 1.1 M (4.69%) questions containing them in the question body, 2.2 M (6.18%) answers and 1.9 M (2.08%) comments because of exact keyword matching. The results further increase in case of substring matching. When enriched with additional metadata e.g. Users, and (which are available in the Stack Overflow data dump), the raw dataset presented in this paper can become highly useful for the empirical software engineering and machine learning research community for training models and developing recommendation systems for software engineering. The extracted answers and comments can be mined to extract implicit developer preferences from which ratings can be inferred whereas the extracted recommendation related questions with accepted answers can be transformed into a benchmark for retrieval evaluation of software recommendation systems for developers. The dataset is hosted on Figshare using DOI 10.6084/m9.figshare.30948506 and can be accessed via https://doi.org/10.6084/m9.figshare.30948506 or the GitHub repository. - Source: PubMed
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Zhang FanHan ShuaiPan DanGao LinaSong Weijie - To develop an assay to measure red blood cell (RBC) sorbitol dehydrogenase (SORD) activity for fast laboratory screening of SORD-related neuropathies, and to provide additional phenotypic arguments in case of ambiguous genetic results. - Source: PubMed
Moro NicholasFrancois StanislasGrondin ChristelBen Salem SirineRajagopal SreekanthAykut DuruArezki LouisaLarramendi José ManuelBerquet ClaireWillems MarjolaineBouchet-Séraphin CélineGauthier Lucas WKonyukh MarinaSvahn JulietteMoutereau StéphanePeoc'h KatellTard CélineFernández-Eulate GorkaStojkovic TanyaBruneel ArnaudRaynor Alexandre