The loss-of-function mutations of serine protease inhibitor, Kazal type 1 (SPINK1) gene are associated with human chronic pancreatitis, but the underlying mechanisms remain unknown. We previously reported that mice lacking Spink3, the murine homologue of human SPINK1, die perinatally due to massive pancreatic acinar cell death, precluding investigation of the effects of SPINK1 deficiency. To circumvent perinatal lethality, we have developed a novel method to integrate human SPINK1 gene on the X chromosome using Cre-loxP technology and thus generated transgenic mice termed "X-SPINK1". Consistent with the fact that one of the two X chromosomes is randomly inactivated, X-SPINK1 mice exhibit mosaic pattern of SPINK1 expression. Crossing of X-SPINK1 mice with Spink3 mice rescued perinatal lethality, but the resulting Spink3;XX mice developed spontaneous pancreatitis characterized by chronic inflammation and fibrosis. The results show that mice lacking a gene essential for cell survival can be rescued by expressing this gene on the X chromosome. The Spink3;XX mice, in which this method has been applied to partially restore SPINK1 function, present a novel genetic model of chronic pancreatitis.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5109027 | PMC |
http://dx.doi.org/10.1038/srep37200 | DOI Listing |
Abdom Radiol (NY)
January 2025
Department of Radiology, Taizhou Municipal Hospital, Taizhou, Zhejiang, China.
Background: To develop and validate a clinical-radiomics model for preoperative prediction of lymphovascular invasion (LVI) in rectal cancer.
Methods: This retrospective study included data from 239 patients with pathologically confirmed rectal adenocarcinoma from two centers, all of whom underwent MRI examinations. Cases from the first center (n = 189) were randomly divided into a training set and an internal validation set at a 7:3 ratio, while cases from the second center (n = 50) constituted the external validation set.
Orv Hetil
January 2025
1 Jász-Nagykun-Szolnok Vármegyei Hetényi Géza Kórház-Rendelőintézet, Általános-Mellkassebészeti Osztály Szolnok Magyarország.
Bioinformatics
January 2025
Biocomputing Group, University of Bologna, Italy.
Motivation: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimental approaches and allow a fast screening of large datasets of variations.
Results: In this work we present DDGemb, a novel method combining protein language model embeddings and transformer architectures to predict protein ΔΔG upon both single- and multi-point variations.
Bioinformatics
January 2025
Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada.
Motivation: Understanding the associations between traits and microbial composition is a fundamental objective in microbiome research. Recently, researchers have turned to machine learning (ML) models to achieve this goal with promising results. However, the effectiveness of advanced ML models is often limited by the unique characteristics of microbiome data, which are typically high-dimensional, compositional, and imbalanced.
View Article and Find Full Text PDFBioinformatics
January 2025
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China.
Motivation: Ensuring connectivity and preventing fractures in tubular object segmentation are critical for downstream analyses. Despite advancements in deep neural networks (DNNs) that have significantly improved tubular object segmentation, existing methods still face limitations. They often rely heavily on precise annotations, hindering their scalability to large-scale unlabeled image datasets.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!