Results 281 to 290 of about 117,699 (379)

Germ cell and other tumors in individuals with differences in sex development

open access: yesCA: A Cancer Journal for Clinicians, EarlyView.
Abstract Approximately one in 3500 to one in 5100 live‐born infants have atypical external genital development, known as differences in sex development (DSD). In 2005, an expert consensus conference thoroughly reviewed aspects of health care for individuals with DSD.
Selma Feldman Witchel   +1 more
wiley   +1 more source

Diffusion Tensor Imaging (DTI) as a Non‐Invasive Tool for Assessing Pediatric Kidney Transplants: A Feasibility Study

open access: yesPediatric Transplantation, Volume 29, Issue 5, August 2025.
Our study demonstrates the feasibility of using diffusion tensor imaging (DTI) to evaluate pediatric kidney transplants. Significant differences in fractional anisotropy (FA) and track length were observed between transplanted and healthy kidneys, reflecting altered microstructural organization.
Suraj D. Serai   +5 more
wiley   +1 more source

Abnormal DNA Methylation Profile Suggests the Extension of the Clinical Spectrum of the SETD2 ‐Related Disorders to a Syndromic Multiple Tumor Phenotype

open access: yesAmerican Journal of Medical Genetics Part A, Volume 197, Issue 7, July 2025.
ABSTRACT SETD2 has an essential role in epigenetic regulation. SETD2 pathogenic variants cause neurodevelopmental disorders (SETD2‐NDDs) that most commonly include various degrees of intellectual disability and behavioral disorders, macrocephaly, brain malformations, and generalized overgrowth.
Marie Lucain   +11 more
wiley   +1 more source

Ift25 is not a cystic kidney disease gene but is required for early steps of kidney development. [PDF]

open access: yesMech Dev, 2018
Desai PB   +5 more
europepmc   +1 more source

Hybrid Support Vector Machine‐Convolutional Neural Networks Multi‐Classification Models for Detection of Kidney Stones

open access: yesInternational Journal of Imaging Systems and Technology, Volume 35, Issue 4, July 2025.
ABSTRACT The accurate and early detection of kidney stones is crucial for effective treatment and patient management. This study presents a hybrid machine learning approach combining Support Vector Machines (SVM) and Convolutional Neural Networks (CNN) for the multi‐classification of kidney stones.
Setlhabi Letlhogonolo Rapelang   +1 more
wiley   +1 more source

Primary Cilia in Cystic Kidney Disease. [PDF]

open access: yesResults Probl Cell Differ, 2017
Avasthi P, Maser RL, Tran PV.
europepmc   +1 more source

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