SESAM mode-locked Tm:Y2O3 ceramic laser

We demonstrate a widely tunable and passively mode-locked Tm:Y2O3 ceramic laser in-band pumped by a 1627-nm Raman fiber laser. A tuning range of 318 nm, from 1833 to 2151 nm, is obtained in the continuous-wave regime. The SESAM mode-locked laser produces Fourier-transform-limited pulses as short as 75 fs at ∼ 2.06 µm with an average output power of 0.26 W at 86.3 MHz. For longer pulse durations of 178 fs, an average power of 0.59 W is achieved with a laser efficiency of 29%. This is, to the best of our knowledge, the first mode-locked Tm:Y2O3 laser in the femtosecond regime. The spectroscopic properties and laser performance confirm that Tm:Y2O3 transparent ceramics are a promising gain material for ultrafast lasers at 2 µm

A stable transcription factor complex nucleated by oligomeric AML1-ETO controls leukaemogenesis.

Transcription factors are frequently altered in leukaemia through chromosomal translocation, mutation or aberrant expression(1). AML1-ETO, a fusion protein generated by the t(8;21) translocation in acute myeloid leukaemia, is a transcription factor implicated in both gene repression and activation(2). AML1-ETO oligomerization, mediated by the NHR2 domain, is critical for leukaemogenesis(3-6), making it important to identify co-regulatory factors that 'read' the NHR2 oligomerization and contribute to leukaemogenesis(4). Here we show that, in human leukaemic cells, AML1-ETO resides in and functions through a stable AML1-ETO-containing transcription factor complex (AETFC) that contains several haematopoietic transcription (co)factors. These AETFC components stabilize the complex through multivalent interactions, provide multiple DNA-binding domains for diverse target genes, co-localize genome wide, cooperatively regulate gene expression, and contribute to leukaemogenesis. Within the AETFC complex, AML1-ETO oligomerization is required for a specific interaction between the oligomerized NHR2 domain and a novel NHR2-binding (N2B) motif in E proteins. Crystallographic analysis of the NHR2-N2B complex reveals a unique interaction pattern in which an N2B peptide makes direct contact with side chains of two NHR2 domains as a dimer, providing a novel model of how dimeric/oligomeric transcription factors create a new protein-binding interface through dimerization/oligomerization. Intriguingly, disruption of this interaction by point mutations abrogates AML1-ETO-induced haematopoietic stem/progenitor cell self-renewal and leukaemogenesis. These results reveal new mechanisms of action of AML1-ETO, and provide a potential therapeutic target in t(8;21)-positive acute myeloid leukaemia

Fault Detection via 2.5D Transformer U-Net with Seismic Data Pre-Processing

Seismic fault structures are important for the detection and exploitation of hydrocarbon resources. Due to their development and popularity in the geophysical community, deep-learning-based fault detection methods have been proposed and achieved SOTA results. Due to the efficiency and benefits of full spatial information extraction, 3D convolutional neural networks (CNNs) are used widely to directly detect faults on seismic data volumes. However, using 3D data for training requires expensive computational resources and can be limited by hardware facilities. Although 2D CNN methods are less computationally intensive, they lead to the loss of correlation between seismic slices. To mitigate the aforementioned problems, we propose to predict a 2D fault section using multiple neighboring seismic profiles, that is, 2.5D fault detection. In CNNs, convolution layers mainly extract local information and pooling layers may disrupt the edge features in seismic data, which tend to cause fault discontinuities. To this end, we incorporate the Transformer module in U-net for feature extraction to enhance prediction continuity. To reduce the data discrepancies between synthetic and different real seismic datasets, we apply a seismic data standardization workflow to improve the prediction stability on real datasets. Netherlands F3 real data tests show that, when training on synthetic data labels, the proposed 2.5D Transformer U-net-based method predicts more subtle faults and faults with higher spatial continuity than the baseline full 3D U-net model

A stable transcription factor complex nucleated by oligomeric AML1-ETO controls leukaemogenesis.

Transcription factors are frequently altered in leukaemia through chromosomal translocation, mutation or aberrant expression(1). AML1-ETO, a fusion protein generated by the t(8;21) translocation in acute myeloid leukaemia (AML), is a transcription factor implicated in both gene repression and activation(2). AML1-ETO oligomerization, mediated by the NHR2 domain, is critical for leukaemogenesis(3–6), making it important to identify coregulatory factors that “read” the NHR2 oligomerization and contribute to leukaemogenesis(4). We now show that, in leukaemic cells, AML1-ETO resides in and functions through a stable protein complex (AETFC) that contains several haematopoietic transcription (co)factors. These AETFC components stabilize the complex through multivalent interactions, provide multiple DNA-binding domains for diverse target genes, colocalize genome-wide, cooperatively regulate gene expression, and contribute to leukaemogenesis. Within the AETFC complex, AML1-ETO oligomerization is required for a specific interaction between the oligomerized NHR2 domain and a novel NHR2-binding (N2B) motif in E proteins. Crystallographic analysis of the NHR2-N2B complex reveals a unique interaction pattern in which an N2B peptide makes direct contact with side chains of two NHR2 domains as a dimer, providing a novel model of how dimeric/oligomeric transcription factors create a new protein-binding interface through dimerization/oligomerization. Intriguingly, disruption of this interaction by point mutations abrogates AML1-ETO–induced haematopoietic stem/progenitor cell self-renewal and leukaemogenesis. These results reveal new mechanisms of action of AML1-ETO and a potential therapeutic target in t(8;21)(+) AML