Refine
Document Type
- Article (2) (remove)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- CAKUT (1)
- SLC20A1 (1)
- bladder exstrophy-epispadias complex (1)
- cloacal malformation (1)
- functional genetics (1)
- kidney formation (1)
- urinary tract development (1)
- zebrafish development (1)
Institute
- Medizin (2) (remove)
Previous studies in developing Xenopus and zebrafish reported that the phosphate transporter slc20a1a is expressed in pronephric kidneys. The recent identification of SLC20A1 as a monoallelic candidate gene for cloacal exstrophy further suggests its involvement in the urinary tract and urorectal development. However, little is known of the functional role of SLC20A1 in urinary tract development. Here, we investigated this using morpholino oligonucleotide knockdown of the zebrafish ortholog slc20a1a. This caused kidney cysts and malformations of the cloaca. Moreover, in morphants we demonstrated dysfunctional voiding and hindgut opening defects mimicking imperforate anus in human cloacal exstrophy. Furthermore, we performed immunohistochemistry of an unaffected 6-week-old human embryo and detected SLC20A1 in the urinary tract and the abdominal midline, structures implicated in the pathogenesis of cloacal exstrophy. Additionally, we resequenced SLC20A1 in 690 individuals with bladder exstrophy-epispadias complex (BEEC) including 84 individuals with cloacal exstrophy. We identified two additional monoallelic de novo variants. One was identified in a case-parent trio with classic bladder exstrophy, and one additional novel de novo variant was detected in an affected mother who transmitted this variant to her affected son. To study the potential cellular impact of SLC20A1 variants, we expressed them in HEK293 cells. Here, phosphate transport was not compromised, suggesting that it is not a disease mechanism. However, there was a tendency for lower levels of cleaved caspase-3, perhaps implicating apoptosis pathways in the disease. Our results suggest SLC20A1 is involved in urinary tract and urorectal development and implicate SLC20A1 as a disease-gene for BEEC.
Background: The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI proto-col contain T2-weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imag-ing (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, andT2-weighted imaging are most strongly associated with a breast cancer diagnosis.Purpose/Hypothesis: To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating Ameri-can College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2-weighted imaging, andDWI with apparent diffusion coefficient (ADC) mapping.Study Type: Retrospective.Subjects: In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwentmpMRI from December 2010 to September 2014.Field Strength/Sequence: IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBEVolume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography withstochastic Trajectories.Assessment: Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Charac-teristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2-weighted imaging accordingto BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2-weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoffvalue of ≤1.25 × 10−3mm2/sec for differentiation between benign and malignant lesions. Histopathology was the stan-dard of reference.Statistical Tests: χ2test, Fisher’s exact test, Kruskal–Wallis test, Pearson correlation coefficient, multivariate logistic regres-sion analysis, Hosmer–Lemeshow test of goodness-of-fit, receiver operating characteristics analysis.Results: In Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE(P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean(P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE(P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2-weighted imaging variables werenot included in the final models