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The protection of telomere ends by the shelterin complex prevents DNA damage signalling and promiscuous repair at chromosome ends. Evidence suggests that the 3' single-stranded telomere end can assemble into a lasso-like t-loop configuration.sup.1,2, which has been proposed to safeguard chromosome ends from being recognized as DNA double-strand breaks.sup.2. Mechanisms must also exist to transiently disassemble t-loops to allow accurate telomere replication and to permit telomerase access to the 3' end to solve the end-replication problem. However, the regulation and physiological importance of t-loops in the protection of telomere ends remains unknown. Here we identify a CDK phosphorylation site in the shelterin subunit at Ser365 of TRF2, whose dephosphorylation in S phase by the PP6R3 phosphatase provides a narrow window during which the RTEL1 helicase can transiently access and unwind t-loops to facilitate telomere replication. Re-phosphorylation of TRF2 at Ser365 outside of S phase is required to release RTEL1 from telomeres, which not only protects t-loops from promiscuous unwinding and inappropriate activation of ATM, but also counteracts replication conflicts at DNA secondary structures that arise within telomeres and across the genome. Hence, a phospho-switch in TRF2 coordinates the assembly and disassembly of t-loops during the cell cycle, which protects telomeres from replication stress and an unscheduled DNA damage response. A phospho-switch is identified in the shelterin subunit TRF2 that regulates transient recruitment of the RTEL1 helicase to, and release from, telomeres, and provides a narrow window during which RTEL1 can unwind t-loops to facilitate telomere replication., Author(s): Grzegorz Sarek [sup.1] , Panagiotis Kotsantis [sup.1] , Phil Ruis [sup.1] , David Van Ly [sup.2] [sup.3] , Pol Margalef [sup.1] , Valerie Borel [sup.1] , Xiao-Feng Zheng [sup.4] [...]

Objective To analyze the data on the disease burden of ALD in China from 1990 to 2019, so as to provide a reference for the prevention and control of ALD. Methods The data on the morbidity, mortality, and DALY rate of ALD in China from 1990 to 2019 were collected from the GBD 2019 to describe the disease burden, Joinpoint regression model was used to analyze the time trend of ALD morbidity and mortality, and APC model was used to investigate the effects of age, period and cohort on ALD morbidity and mortality. Results From 1990 to 2019, the standardized morbidity of ALD in China showed an upward trend ( AAPC = 0. 12% ), and the standardized mortality and DALY rate showed a downward trend ( AAPC = -2. 43%, AAPC = -2. 65% ). The morbidity, mortality, and DALY rates of males were higher than those of females. The results of the age effect showed that the risk of ALD in males was the highest at the age of 45 -49, with an RR of 8. 01. The risk of disease in females was the highest at the age of 50 - 54, with an RR of 12. 07. The risk of death increases with age. The period effect results showed that the incidence risk and mortality risk of ALD was gradually reduced, the birth cohort effect showed that the incidence risk of ALD generally increased with the birth cohort, and the mortality risk generally decreased with the birth cohort. Conclusion As a whole the morbidity of ALD in China is on the rise, and the mortality and DALY rate are on the decline. There are gender and age differences in the risk of morbidity and mortality. [ABSTRACT FROM AUTHOR]

TOR and FRAP are novel protein kinases whose kinase domains are necessary for the functioning of TOR2, the G1 cell cycle and other cellular processes. The kinase activity of TOR is not inhibited by FKBP 12-rapamycin but the phosphorylation of G1 effectors is hindered.

Concrete confinement effect plays a pivotal role in augmenting the strength and ductility of concrete structures. However, traditional models are often proven to be time‐consuming and occasionally yield unreliable predictions. In this paper, the evaluation of traditional models is performed by deconstructing the derivation process into critical steps: determination of confining pressure, calculation of confinement effectiveness coefficient, and the assessment of confined strength and strain. Each step undergoes rigorous scrutiny with the predictions being compared against experimental results and numerical simulations. Subsequently, data‐driven analysis is conducted leveraging a database comprising 466 specimens spanning across a wide spectrum of material strengths and geometric configurations. The power of six machine learning (ML) models is harnessed to unveil the correlations between input parameters and the confinement degree. After that, the interpretability analysis is undertaken to further evaluate the feasibility of the trained ML models. In comparison to traditional semi‐empirical models, ML techniques present a promising alternative for quantifying the confinement effect rapidly and efficiently, opening new avenues for advancing concrete structural analysis. [ABSTRACT FROM AUTHOR]