SCGB1D1

Last update 08 May 2025

Basic Info

Synonyms

LIPA, LIPHA, Lipophilin-A

+ [5]

Introduction

May bind androgens and other steroids, may also bind estramustine, a chemotherapeutic agent used for prostate cancer. May be under transcriptional regulation of steroid hormones.

100 Clinical Results associated with SCGB1D1

100 Translational Medicine associated with SCGB1D1

0 Patents (Medical) associated with SCGB1D1

Literatures (Medical) associated with SCGB1D1

01 Oct 2024·Canadian journal of veterinary research = Revue canadienne de recherche veterinaire

Review of advances in molecular structure and biological function of alpha toxin of Clostridium perfringens.

Review

Author: Xu, Chongbo ; Peng, Kun ; Xu, Chongli ; Fu, Fengyang ; She, Yuhan

Alpha toxin has become the subject of research in recent years. The objective of this article was to review and summarize recent research on the molecular structure and biological function of the alpha toxin of Clostridium perfringens. This includes the work of our research team, as well as that of other researchers. Clostridium perfringens is an anaerobic, spore-forming, Gram-positive bacillus. It can cause various intestinal diseases, such as gas gangrene, food poisoning, non-foodborne diarrhea, and enteritis. Clostridium perfringens can be classified into 5 toxinotypes A, B, C, D, and E, based on the production of major toxins. Each type of C. perfringens produces alpha toxin, which is one of the most important lethal and dermonecrotic toxins and is considered a primary virulence factor. Alpha toxin is a multifunctional metalloenzyme with phospholipase C and sphingomyelinase activities that simultaneously hydrolyze phosphatidylcholine and sphingomyelin. It can therefore destroy the integrity of cell membranes and eventually cause cell lysis. The clinical effects of alpha toxins are characterized by cytotoxicity, hemolytic activity, lethality, skin necrosis, platelet aggregation, and increased vascular permeability. Future research will concentrate on the pathogenesis of a lpha toxin exposure, clarifying the interaction between alpha toxin and the cell membrane and investigating the mechanism of activating platelet function. This research will have substantial theoretical and practical value in controlling disease progression, identifying targeted therapeutic sites, and reducing the toxic effects of vaccines.

01 Jun 2023·International Journal for Vitamin and Nutrition ResearchQ4 · MEDICINE

Low dietary protein increases vitamin A absorption and deposition into milk in periparturient rats

Q4 · MEDICINE

Article

Author: Watts, Jason S. ; Foroudi, Farhad ; Laarman, Anne H. ; Rezamand, Pedram

Abstract: Our objective was to study the effect of differing dietary crude protein and vitamin A on retinoid metabolism in a periparturient rat model. Sixty female rats, approximately 21 d before parturition, were fed rations containing either low protein (13%; LP) or high protein (22%; HP) crude protein and either low vitamin A (3 IU/g; LA) or high vitamin A (5 IU/g; HA), yielding treatments HPHA, HPLA, LPHA, and LPLA. Samples were collected at d −14, d +3, and +10 relative to parturition and analyzed for all-trans retinoid acid (RA), 13-Cis RA, and retinol. At d −14, serum all-trans RA concentrations decreased compared to baseline. At both d +3 and d +10, serum retinol increased and liver 13-Cis RA decreased. In the small intestine, 13-cis RA was higher in HPHA than HPLA pre-partum (0.93±0.12 vs. 0.40±0.12 ng/ml, P=0.04). Post-partum, 13-cis RA was lower in high vitamin HPHA and LPHA groups (0.35±0.06 and 0.38±0.06 ng/ml) than in low vitamin A HPLA and LPLA treatments (0.50±0.06 and 1.32±0.06 ng/ml, P<0.01). In rats fed LA diets, TNF-alpha expression tended to be lower in HPLA than LPLA groups on day +3 (0.69±0.34 vs 1.00±0.52, P=0.08), but not day +10 (0.56±0.25 vs. 1.00±0.49 fold change, P>0.10). Retinoids accumulated during pregnancy and were mobilized during lactation. The sequestration of retinoids was increased when dietary protein content was low. Further studies are needed to investigate how retinoid metabolism could be manipulated to improve vitamin A delivery to milk.

01 Mar 2023·IEEE/ACM Transactions on Computational Biology and BioinformaticsQ3 · ENGINEERING & TECHNOLOGY

Empirical Study of Protein Feature Representation on Deep Belief Networks Trained With Small Data for Secondary Structure Prediction

Q3 · ENGINEERING & TECHNOLOGY

Article

Author: Rashid, Shamima ; Kwoh, Chee Keong ; Sundaram, Suresh

Protein secondary structure (SS) prediction is a classic problem of computational biology and is widely used in structural characterization and to infer homology. While most SS predictors have been trained on thousands of sequences, a previous approach had developed a compact model of training proteins that used a C-Alpha, C-Beta Side Chain (CABS)-algorithm derived energy based feature representation. Here, the previous approach is extended to Deep Belief Networks (DBN). Deep learning methods are notorious for requiring large datasets and there is a wide consensus that training deep models from scratch on small datasets, works poorly. By contrast, we demonstrate a simple DBN architecture containing a single hidden layer, trained only on the CB513 dataset. Testing on an independent set of G Switch proteins improved the Q ₃ score of the previous compact model by almost 3%. The findings are further confirmed by comparison to several deep learning models which are trained on thousands of proteins. Finally, the DBN performance is also compared with Position Specific Scoring Matrix (PSSM)-profile based feature representation. The importance of (i) structural information in protein feature representation and (ii) complementary small dataset learning approaches for detection of structural fold switching are demonstrated.

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SCGB1D1

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