BackgroundHerpes simplex virus type 1 strain 129 (H129) has represented a promising anterograde neuronal circuit tracing tool, which complements the existing retrograde tracers. However, the current H129 derived tracers are multisynaptic, neither bright enough to label the details of neurons nor capable of determining direct projection targets as monosynaptic tracer.MethodsBased on the bacterial artificial chromosome of H129, we have generated a serial of recombinant viruses for neuronal circuit tracing. Among them, H129-G4 was obtained by inserting binary tandemly connected GFP cassettes into the H129 genome, and H129-ΔTK-tdT was obtained by deleting the thymidine kinase (TK) gene and adding tdTomato coding gene to the H129 genome. Then the obtained viral tracers were tested in vitro and in vivo for the tracing capacity.ResultsH129-G4 is capable of transmitting through multiple synapses, labeling the neurons by green florescent protein, and visualizing the morphological details of the labeled neurons. H129-ΔTK-tdT neither replicates nor spreads in neurons alone, but transmits to and labels the postsynaptic neurons with tdTomato in the presence of complementary expressed TK from a helper virus. H129-ΔTK-tdT is also capable to map the direct projectome of the specific neuron type in the given brain regions in Cre transgenic mice. In the tested brain regions where circuits are well known, the H129-ΔTK-tdT tracing patterns are consistent with the previous results.ConclusionsWith the assistance of the helper virus complimentarily expressing TK, H129-ΔTK-tdT replicates in the initially infected neuron, transmits anterogradely through one synapse, and labeled the postsynaptic neurons with tdTomato. The H129-ΔTK-tdT anterograde monosynaptic tracing system offers a useful tool for mapping the direct output in neuronal circuitry. H129-G4 is an anterograde multisynaptic tracer with a labeling signal strong enough to display the details of neuron morphology.Electronic supplementary materialThe online version of this article (doi:10.1186/s13024-017-0179-7) contains supplementary material, which is available to authorized users.

Resin embedding has been widely applied to fixing biological tissues for sectioning and imaging, but has long been regarded as incompatible with green fluorescent protein (GFP) labeled sample because it reduces fluorescence. Recently, it has been reported that resin-embedded GFP-labeled brain tissue can be imaged with high resolution. In this protocol, we describe an optimized protocol for resin embedding and chemical reactivation of fluorescent protein labeled mouse brain, we have used mice as experiment model, but the protocol should be applied to other species. This method involves whole brain embedding and chemical reactivation of the fluorescent signal in resin-embedded tissue. The whole brain embedding process takes a total of 7 days. The duration of chemical reactivation is ~2 min for penetrating 4 μm below the surface in the resin-embedded brain. This protocol provides an efficient way to prepare fluorescent protein labeled sample for high-resolution optical imaging. This kind of sample was demonstrated to be imaged by various optical micro-imaging methods. Fine structures labeled with GFP across a whole brain can be detected.

Abstract:The pH-sensitive fluorescent proteins enabling chemical reactivation in resin are useful tools for fluorescence microimaging. EGFP or EYFP is good for such applications. For simultaneous two-color imaging, a suitable red fluorescent protein is an urgent need. Here a pH-sensitive red fluorescent protein, pHuji, is selected and verified to remain pH-sensitive in HM20 resin. We observe 183% fluorescence intensity of pHuji in resin-embeded mouse brain and 29.08-fold fluorescence intensity of reactivated pHuji compared to the quenched state. pHuji and EGFP can be quenched and chemically reactivated simultaneously in resin, thus enabling simultaneous two-color micro-optical sectioning tomography of resin-embedded mouse brain. This method may greatly facilitate the visualization of neuronal morphology and neural circuits to promote understanding of the structure and function of the brain.

Objective: To analyze and compare the imaging workflow, radiation dose and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method. Materials and Methods: 127 adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time and off-center distance, of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups.Results: The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP:1.56cm±0.83 vs. MP: 4.05cm±2.40, p<0.001) and higher proportion of positioning accuracy (AP: 99% vs. MP: 92%), resulted in 16% radiation dose reduction (AP: 6.1mSv±1.3 vs. MP: 7.3mSv±1.2, p<0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas.Conclusion: The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose, optimizing imaging workflow and image quality in imaging the chest. This technique has important added clinical value in imaging COVID-19 patients to reduce the cross-infection risks.

High-resolution three-dimensional biomolecule distribution information of large samples is essential to understanding their biological structure and function. Here, we proposed a method combining large sample resin embedding with iDISCO immunofluorescence staining to acquire the profile of biomolecules with high spatial resolution. We evaluated the compatibility of plastic embedding with an iDISCO staining technique and found that the fluorophores and the neuronal fine structures could be well preserved in the Lowicryl HM20 resin, and that numerous antibodies and fluorescent tracers worked well upon Lowicryl HM20 resin embedding. Further, using fluorescence MicroOptical sectioning tomography (fMOST) technology combined with ultra-thin slicing and imaging, we were able to image the immunolabeled large-volume tissues with high resolution. Miyawaki, "Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain," Nat. Neurosci. 14(11), 1481-1488 (2011). 11. J. Sharpe, U. Ahlgren, P. Perry, B. Hill, A. Ross, J. Hecksher-Sørensen, R. Baldock, and D. Davidson, "Optical projection tomography as a tool for 3D microscopy and gene expression studies," Science 296 (

Objective To analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method. Materials and methods One hundred twenty-seven adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time, and off-center distance of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups. Results The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP 1.56 cm ± 0.83 vs. MP 4.05 cm ± 2.40, p < 0.001) and higher proportion of positioning accuracy (AP 99% vs. MP 92%), resulting in 16% radiation dose reduction (AP 6.1 mSv ± 1.3 vs. MP 7.3 mSv ± 1.2, p < 0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas. Conclusion The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose and optimizing imaging workflow and image quality in imaging the chest. Key Points • The AI-based automatic positioning (AP) operation was successful for all patients in our study. • AP method reduced the total positioning time by 28% compared with the manual positioning (MP). • AP method had less patient off-center distance and higher proportion of positioning accuracy than MP method, resulting in 16% radiation dose reduction and 9% image noise reduction in erector spinae.

Abstract:To resolve fine structures of biological systems like neurons, it is required to realize microscopic imaging with sufficient spatial resolution in three dimensional systems. With regular optical imaging systems, high lateral resolution is accessible while high axial resolution is hard to achieve in a large volume. We introduce an imaging system for high 3D resolution fluorescence imaging of large volume tissues. Selective plane illumination was adopted to provide high axial resolution. A scientific CMOS working in sub-array mode kept the imaging area in the sample surface, which restrained the adverse effect of aberrations caused by inclined illumination. Plastic embedding and precise mechanical sectioning extended the axial range and eliminated distortion during the whole imaging process. The combination of these techniques enabled 3D high resolution imaging of large tissues. Fluorescent bead imaging showed resolutions of 0.59 μm, 0.47μm, and 0.59 μm in the x, y, and z directions, respectively. Data acquired from the volume sample of brain tissue demonstrated the applicability of this imaging system. Imaging of different depths showed uniform performance where details could be recognized in either the near-soma area or terminal area, and fine structures of neurons could be seen in both the xy and xz sections.

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