Results 181 to 190 of about 44,278 (289)
Turner Syndrome With 45,X/46,XX Mosaicism and a Derivative X Chromosome (Xqter → Xq13?::Xp11.4 → Xqter): A Case Report. [PDF]
Jiang W, Ji T, Wu Q, Xu Z, Xia X.
europepmc +1 more source
Prolonged P-R interval in a male with 47,XYY karyotype. [PDF]
Shinichiro Nanko, J Miyawaki
openalex +1 more source
Summary Diabetes insipidus (DI) in patients with acute myeloid leukaemia (AML) and chromosome 3q alterations (EVI1/PRDM3/MECOM overexpression) constitutes a poorly understood paraneoplasia. A 44‐year‐old patient presented with clinical and morphological features of this syndrome but, surprisingly, disclosed the rare translocation t(1;2)(p36;p21), with ...
Julian List +9 more
wiley +1 more source
Telomere aggregates in amniocytes with karyotype of balanced chromosomal rearrangements
Tali Amiel +5 more
openalex +1 more source
Summary The efficacy of ciclosporin (CsA) to treat transfusion‐independent non‐severe aplastic anaemia (TI‐NSAA) has not yet been systematically evaluated. We conducted a prospective trial in patients with TI‐NSAA treated with CsA monotherapy. CsA (3.5 mg/kg/day) was administered to patients with TI‐NSAA aged ≥16.
Ken Ishiyama +14 more
wiley +1 more source
The Diagnostic Utility of Prenatal Microarray in High-Risk Pregnancies: A Single-Center Experience in Enhancing Reproductive Care and Risk Stratification. [PDF]
Bakır A +5 more
europepmc +1 more source
THE CHROMOSOMES OF ASCAPHUS TRUEI AND THE EVOLUTION OF THE ANURAN KARYOTYPES
TORSTEN WICKBOM
openalex +1 more source
Chromosomal Abnormalities in Recurrent Pregnancy Loss at a Tertiary Care Center. [PDF]
Sinha MB, Thakur P, Verma R.
europepmc +1 more source
Artificial intelligence for risk assessment and outcome prediction in malignant haematology
Machine learning models allow for dynamic and scalable risk stratification and outcome prediction. Different modalities of data such as electronic health records, patient genetics or laboratory results can be used as input. ML models autonomously select features weighing their prognostic value. Methods of model explainability in feature selection allow
Jan‐Niklas Eckardt +3 more
wiley +1 more source

