Insufficient expression of the survival motor neuron (SMN) protein causes spinal muscular atrophy, a neurodegenerative disease characterized by loss of motor neurons. Despite the importance of maintaining adequate SMN levels, little is known about factors that control SMN expression, particularly 3' end processing of the SMN pre-mRNA. In this study, we identify the U1A protein as a key regulator of SMN expression. U1A, a component of the U1 snRNP, is known to inhibit polyadenylation upon direct binding to mRNA. We show that U1A binds directly and with high affinity and specificity to the SMN 3'-UTR adjacent to the polyadenylation site, independent of the U1 snRNP (U1 small nuclear ribonucleoprotein). Binding of U1A inhibits polyadenylation of the SMN pre-mRNA by specifically inhibiting 3' cleavage by the cleavage and polyadenylation specificity factor. Expression of U1A in excess of U1 snRNA causes inhibition of SMN polyadenylation and decreases SMN protein levels. This work reveals a new mechanism for regulating SMN levels and provides new insight into the roles of U1A in 3' processing of mRNAs.
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http://dx.doi.org/10.1074/jbc.M113.538264 | DOI Listing |
J Natl Cancer Inst
January 2025
Division of Pediatric Hematology & Oncology, University of Minnesota, Minneapolis, MN, USA.
Purpose: It is not known whether temporal changes in childhood cancer therapy have reduced risk of subsequent malignant neoplasms (SMNs) of the central nervous system (CNS), a frequently fatal late effect of cancer therapy.
Methods: Five-year survivors of primary childhood cancers diagnosed between 1970-1999 in the Childhood Cancer Survivor Study with a subsequent CNS SMN were identified. Cumulative incidence rates and standardized incidence ratios (SIR) were compared among survivors diagnosed between 1970-1979 (N = 6223), 1980-1989 (N = 9680), and 1990-1999 (N = 8999).
Cogn Neurodyn
December 2025
Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, 730030 China.
Unlabelled: Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Metabolism, Digestion, and Reproduction, Imperial College London, London, UK.
Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple 'rules-of-thumb'. Machine learning techniques are well-suited to analyzing complex data to provide data-driven recommendations to improve decision-making.
View Article and Find Full Text PDFNeuroimage Clin
January 2025
Stroke Unit, ASST Spedali Civili, «Spedali Civili» Hospital, Brescia, Italy.
The present study investigated spatial dynamic functional network connectivity (dFNC) in patients with functional hemiparesis (i.e., functional stroke mimics, FSM).
View Article and Find Full Text PDFBrain Topogr
January 2025
Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.
Aberrant large-scale resting-state functional connectivity (rsFC) has been frequently documented in ischemic stroke. However, it remains unclear about the altered patterns of within- and across-network connectivity. The purpose of this meta-analysis was to identify the altered rsFC in patients with ischemic stroke relative to healthy controls, as well as to reveal longitudinal changes of network dysfunctions across acute, subacute, and chronic phases.
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