Ask about this productRelated genes to: SCIN antibody
- Gene:
- SCIN NIH gene
- Name:
- scinderin
- Previous symbol:
- -
- Synonyms:
- KIAA1905
- Chromosome:
- 7p21.3
- Locus Type:
- gene with protein product
- Date approved:
- 2003-07-10
- Date modifiied:
- 2015-06-02
Related products to: SCIN antibody
Related articles to: SCIN antibody
- Numerous research endeavors have reported altered expression of Scinderin () in various cancer types. Single Nucleotide Polymorphisms (SNPs) represent the most prevalent form of genetic variation within the human genome which can have significant functional consequences, including cancer predisposition. - Source: PubMed
Vaghefinezhad NedaAzadeh MansourehTafrihi MajidHosseinzadeh Colagar Abasalt - Following their domestication, chickens were translocated around the world to novel environments. Through a combination of natural and artificial selection, chickens adapted to these local conditions, creating significant genetic diversity across populations worldwide. Studying this diversity in the context of local environmental conditions may offer insights into mechanisms of adaptation to environmental stressors. In this study, we analyzed genomic data from the Chicken Genomic Diversity Consortium, applying multiple statistical approaches, including fixation index (F), nucleotide diversity (π), Tajima’s D, and runs of homozygosity (ROH), to identify selective sweeps among indigenous chickens from Afghanistan, China, Indonesia, Iran and Pakistan, compared with White Leghorn chickens. We identified sweeps in 14 genes related to heat tolerance, associated with relevant gene ontology (GO) terms and located within ROH regions. These genes, such as , , , , , , , , , , , , , , and play crucial roles in calcium signaling pathways, thermal sensation, and the plasticity of neurodevelopmental processes. These findings illustrate the significant role of selection in shaping genomic differentiation across chicken populations and provide insights into the genetic basis of adaptation to environmental stressors. - Source: PubMed
Publication date: 2026/04/07
Hosseinzadeh SevdaRafat Seyed AbbasJavanmard ArashHasanpur KarimBardou PhilippeCharles MathieuKlopp ChristopheSmith Adrian LFiddaman Steven R - Staphylococcus aureus biofilms are major contributors to chronic and recurrent infections due to their intrinsic tolerance to antibiotics and host immune clearance, highlighting the urgent need for safe and effective antibiofilm strategies. This study evaluated the inhibitory effects and underlying mechanisms of betulinic acid (BA), the principal active constituent of the traditional Chinese medicine Liquidambaris fructus, against S. aureus biofilms. In vitro assays demonstrated that the minimum biofilm inhibitory concentration (MBIC) of BA was 32 μg/mL, which was markedly lower than its minimum inhibitory concentration (MIC, 512 μg/mL), indicating preferential activity against biofilm formation. Serial passage experiments revealed no detectable induction of drug resistance. Mechanistic studies revealed that BA suppressed early biofilm adhesion and aggregation, downregulated the expression of adhesion-related genes (clfA, clfB, fnbpA and fnbpB), and reduced the production of extracellular polysaccharide (EPS) and extracellular DNA (eDNA). BA further disrupted mature biofilm architecture, promoted macrophage infiltration, enhanced bacterial clearance and attenuated the expression of immune evasion factors (scin, chip, lukE and nuc). In vivo, BA significantly alleviated implant-associated infections, mitigated local inflammatory responses and facilitated tissue repair. Collectively, these findings reveal that BA inhibits S. aureus biofilms through multiple coordinated mechanisms, with a low propensity for resistance development and favourable biosafety, supporting its potential as a promising lead compound for the development of novel antibiofilm therapeutics. - Source: PubMed
Guo DongbinTao YeSun LuanbiaoLiu XinyaoGao YuanJiang PeitongGao HanWang BingmeiWang Li - Immune protection by the complement system depends on C3 cleavage by C3 convertases that is critical to all three activation pathways. Structural data on convertase formation in the classical pathway and on C3-substrate binding to convertases is lacking. We present the cryo-EM structures of the proconvertase (C4b2), convertase (C4b2b), and convertase-substrate complex (C4b2b-C3) of the classical pathway. The data show that C2 and C4b form proconvertases and convertases like factor B and C3b of the alternative pathway. Substrate C3 binds C4b of the convertase through two interfaces: one also found in the SCIN-inhibited C3bBb dimer, and another facilitated by conformational changes in C3. Bending of C3 and swinging of the C2 protease bring the C3-scissile loop into the active site. The second, charged, C4b-interaction site favors C3- substrate binding, but upon cleavage repels product C3b. Thus, a charge switch-over mechanism effects the catalytic turnover of the convertases producing opsonin C3b. - Source: PubMed
Publication date: 2025/12/18
De la O Becerra Karla IBrondijk T Harma CSerna Martin ItziarGros Piet - Dermatological diseases are prevalent globally and provide significant challenges in diagnosis and treatment. Dermatology has changed due to developments in high-resolution digital photography and medical imaging, making it possible to document and analyze skin, nail, and hair diseases in great detail. With more than 10,000 photos, the Skin Condition Image Network (SCIN) dataset has become an essential tool in this area. In dermatological image analysis, image segmentation is essential because it makes it easier to identify and classify areas of interest for use, including automated disease diagnosis, lesion identification, and measurement. However, because skin textures vary, lighting varies, and skin disorders appear differently individually, it is difficult to achieve reliable segmentation in dermatological images. While segmentation techniques are now helpful for broad image analysis jobs, they are frequently insufficient for dermatological images from datasets such as SCIN. Reliable and consistent segmentation results are hampered by problems such as uneven lighting, different lesion scales, and image artifacts. Therefore, particular optimization algorithms that can adapt to the unique characteristics of dermatological images are needed to increase segmentation accuracy. This work is designed explicitly for SCIN dermatological images, suggesting an enhanced multilevel image segmentation optimization method. Opposition-Based Learning (OBL) and Orthogonal Learning (OL) are two improvements that the Enhanced Secretary Bird Optimization Algorithm (mSBOA) uses to increase segmentation accuracy, robustness to image artifacts, and computational efficiency. This study aims to improve optimization algorithms for robust multilevel feature segmentation in SCIN dataset dermatological images, mitigate problems such as overlapping textures and variable illumination, increase computational efficiency without sacrificing accuracy, and investigate possible clinical benefits of higher segmentation accuracy in automated dermatological diagnostics. Accurate segmentation can help create personalized treatment approaches, enhance patient outcomes, and lower diagnostic errors. Dermatologists gain from the wider adoption of AI-based healthcare solutions made possible by strong segmentation algorithms, especially in distant or underdeveloped areas. By increasing the potential for automated dermatological evaluations and enhancing diagnostic capacities, the study's findings advance the field of dermatological image analysis. - Source: PubMed
Publication date: 2025/11/05
Khurma Ruba AbuEmam Marwa MChakraborty FalguniMohamed SaherAl-Betar Mohammed Azmi