RNase T2 deficiency promotes TLR13-dependent replenishment of tissue-protective Kupffer cells.

Lysosomal stress due to the accumulation of nucleic acids (NAs) activates endosomal TLRs in macrophages. Here, we show that lysosomal RNA stress, caused by the lack of RNase T2, induces macrophage accumulation in multiple organs such as the spleen and liver through TLR13 activation by microbiota-derived ribosomal RNAs. TLR13 triggered emergency myelopoiesis, increasing the number of myeloid progenitors in the bone marrow and spleen.

TNF-α exacerbates SARS-CoV-2 infection by stimulating CXCL1 production from macrophages.

Since most genetically modified mice are C57BL/6 background, a mouse-adapted SARS-CoV-2 that causes lethal infection in young C57BL/6 mice is useful for studying innate immune protection against SARS-CoV-2 infection. Here, we established two mouse-adapted SARS-CoV-2, ancestral and Delta variants, by serial passaging 80 times in C57BL/6 mice. Although young C57BL/6 mice were resistant to infection with the mouse-adapted ancestral SARS-CoV-2, the mouse-adapted SARS-CoV-2 Delta variant caused lethal infection in young C57BL/6 mice.

Accuracy of deep learning-based attenuation correction in Tc-GSA SPECT/CT hepatic imaging.

Introduction: Attenuation correction (AC) is necessary for accurate assessment of radioactive distribution in single photon emission computed tomography (SPECT). The method of computed tomography-based AC (CTAC) is widely used because of its accuracy. However, patients are exposed to radiation during CT examination.

Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.

We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunction (CLAD) with lung ventilation single-photon emission computed tomography (SPECT) images acquired briefly using a convolutional neural network (CNN) in patients after lung transplantation and to explore the feasibility of short acquisition times. We retrospectively identified 93 consecutive lung-transplant recipients who underwent ventilation SPECT/computed tomography (CT). We employed a CNN to distinguish the images acquired in full time from those acquired in a short time.