Combining convolutional attention mechanism and residual deformable Transformer for infarct segmentation from CT scans of acute ischemic stroke patients

BackgroundSegmentation and evaluation of infarcts on medical images are essential for diagnosis and prognosis of acute ischemic stroke (AIS). Computed tomography (CT) is the first-choice examination for patients with AIS.MethodsTo accurately segment infarcts from the CT images of patients with AIS, we proposed an automated segmentation method combining the convolutional attention mechanism and residual Deformable Transformer in this article. The method used the encoder-decoder structure, where the encoders were employed for downsampling to obtain the feature of the images and the decoder was used for upsampling and segmentation. In addition, we further applied the convolutional attention mechanism and residual network structure to improve the effectiveness of feature extraction. Our code is available at: https://github.com/XZhiXiang/AIS-segmentation/tree/master.ResultsThe proposed method was assessed on a public dataset containing 397 non-contrast CT (NCCT) images of AIS patients (AISD dataset). The symptom onset to CT time was less than 24 h. The experimental results illustrate that this work had a Dice coefficient (DC) of 58.66% for AIS infarct segmentation, which outperforms several existing methods. Furthermore, volumetric analysis of infarcts indicated a strong correlation (Pearson correlation coefficient = 0.948) between the AIS infarct volume obtained by the proposed method and manual segmentation.ConclusionThe strong correlation between the infarct segmentation obtained via our method and the ground truth allows us to conclude that our method could accurately segment infarcts from NCCT images

Late cretaceous metamorphism and anatexis of the gangdese magmatic arc, south tibet: implications for thickening and differentiation of juvenile crust

Magmatic arcs are the primary sites of growth of post-Archean continental crust; however, the mechanisms and processes for transforming primary arc crust into mature continental crust are subject to disagreement. We conducted a detailed petrologic and geochronological study on mafic and felsic migmatites from the eastern Gangdese magmatic arc, which is typical of continental arcs worldwide. The studied mafic migmatites contain amphibole, garnet, plagioclase, epidote, white mica, quartz, rutile and ilmenite in melanosomes, and plagioclase, garnet, epidote, amphibole, white mica, and quartz in leucosomes. The leucosomes occur as diffuse patches, concordant bands, or concordant and discordant networks and veins in the melanosomes. The migmatites have protolith ages between ~157 and ~86–87 Ma, and metamorphic ages of ~83–87 Ma and underwent high-pressure granulite-facies metamorphism at peak P–T conditions of ~850–880°C and 15–17 kbar. Heating, burial, and associated partial melting preceded near-isobaric cooling with residual melt crystallization. Significant melt (>16 wt.%) generated during heating and loading had a granitic composition. Compositional comparison to low-grade meta-gabbros implies that any extracted melt had adakitic affinities (high Sr/Y and highly fractionated REE patterns). The eastern Gangdese magmatic arc experienced crustal thickening during Late Cretaceous late-stage evolution of the arc due to magma loading and tectonic shortening and thrusting of the arc crust. Crustal thickening and chemical differentiation of the Gangdese arc occurred during late subduction of the Neo-Tethys, prior to the India–Asia collision. Metamorphism nearly completely erased all prior igneous mineralogy and mineral chemistry, and consequent partial melting represents a potential source for Late Cretaceous granitoids of the upper arc crust. Although prior studies demonstrate the significance of fractional crystallization, deep-seated metamorphic processes largely drove chemical differentiation to produce mature continental crust in the Gangdese arc during the late Cretaceous

A \u3cem\u3eLIN28B\u3c/em\u3e Tumor-Specific Transcript in Cancer

The diversity and complexity of the cancer transcriptome may contain transcripts unique to the tumor environment. Here, we report a LIN28B variant, LIN28B-TST, which is specifically expressed in hepatocellular carcinoma (HCC) and many other cancer types. Expression of LIN28B-TST is associated with significantly poor prognosis in HCC patients. LIN28B-TST initiates from a de novo alternative transcription initiation site that harbors a strong promoter regulated by NFYA but not c-Myc. Demethylation of the LIN28B-TST promoter might be a prerequisite for its transcription and transcriptional regulation. LIN28B-TST encodes a protein isoform with additional N-terminal amino acids and is critical for cancer cell proliferation and tumorigenesis. Our findings reveal a mechanism of LIN28B activation in cancer and the potential utility of LIN28B-TST for clinical purposes

Superior survival with allogeneic hematopoietic stem cell transplantation <i>versus</i> chemotherapy for high-risk adult acute lymphoblastic leukemia in a PDT-ALL-2016 pediatric-inspired cohort

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Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data