FastCellpose: A Fast and Accurate Deep-Learning Framework for Segmentation of All Glomeruli in Mouse Whole-Kidney Microscopic Optical Images.

Automated evaluation of all glomeruli throughout the whole kidney is essential for the comprehensive study of kidney function as well as understanding the mechanisms of kidney disease and development. The emerging large-volume microscopic optical imaging techniques allow for the acquisition of mouse whole-kidney 3D datasets at a high resolution. However, fast and accurate analysis of massive imaging data remains a challenge. Here, we propose a deep learning-based segmentation method called FastCellpose to efficiently segment all glomeruli in whole mouse kidneys. Our framework is based on Cellpose, with comprehensive optimization in network architecture and the mask reconstruction process. By means of visual and quantitative analysis, we demonstrate that FastCellpose can achieve superior segmentation performance compared to other state-of-the-art cellular segmentation methods, and the processing speed was 12-fold higher than before. Based on this high-performance framework, we quantitatively analyzed the development changes of mouse glomeruli from birth to maturity, which is promising in terms of providing new insights for research on kidney development and function.

Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy.

One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 µm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.

Cryo-fluorescence micro-optical sectioning tomography for volumetric imaging of various whole organs with subcellular resolution.

Optical visualization of complex microstructures in the entire organ is essential for biomedical research. However, the existing methods fail to accurately acquire the detailed microstructures of whole organs with good morphological and biochemical preservation. This study proposes a cryo-fluorescence micro-optical sectioning tomography (cryo-fMOST) to image whole organs in three dimensions (3D) with submicron resolution. The system comprises a line-illumination microscope module, cryo-microtome, three-stage refrigeration module, and heat insulation device. To demonstrate the imaging capacity and wide applicability of the system, we imaged and reconstructed various organs of mice in 3D, including the healthy tongue, kidney, and brain, as well as the infarcted heart. More importantly, imaged brain slices were performed sugar phosphates determination and fluorescence in situ hybridization imaging to verify the compatibility of multi-omics measurements. The results demonstrated that cryo-fMOST is capable of acquiring high-resolution morphological details of various whole organs and may be potentially useful for spatial multi-omics.

[Stable isotopes characteristics of precipitation over Shaanxi-Gansu-Ningxia and its water vapor sources.] / é™•ç”˜å®åœ°åŒºé™æ°´ç¨³å®šåŒä½ç´ ç‰¹å¾åŠæ°´æ±½æ¥æº.

Based on hydrogen and oxygen stable isotopes in precipitation and meteorological data over Shaanxi-Gansu-Ningxia provided by the Global Network of Isotopes in Precipitation (GNIP) and in previous literature, the spatial and temporal variations of oxygen stable isotopes in precipitation and their driving factors were analyzed, the local meteoric water line (LMWL) functions were established. The results showed that the slope and intercept of the LMWL changed in the order of Gansu

[Influence of below-cloud secondary evaporation on stable isotope composition in precipitation in Northwest China.] / è¥¿åŒ—åœ°åŒºé™æ°´ç¨³å®šåŒä½ç´ çš„äº‘ä¸‹äºŒæ¬¡è’¸å‘æ•ˆåº”.

The precipitation isotope data and meteorological data of eight stations provided by GNIP (Global Network for Isotopes in Precipitation) and two stations from the present study, combined with HYSPLIT model and water droplet evaporation model were used to examine the spatial and temporal distribution of precipitation δ18O and d values in Northwest China. The secondary evaporative effect of existence was evaluated and then quantitatively discussed, with the sensitive factors of secondary evaporative effect being considered. The results showed that during the summer monsoon, the δ18O and d values decreased from south to north in Xinjiang, while the δ18O value increased but d values decreased from south to north and from east to west of Shaanxi-Gansu-Ningxia region. During the winter monsoon, the δ18O value decreased from east to west in whole Northwest region, while the d value increased from south to north in Xinjiang, decreased from south to north and increased slightly from east to west in Shanxi-Gansu-Ningxia. The slope and intercept (6.80, -0.07) of the atmospheric precipitation line in the summer monsoon period was significantly lower than that of annual mean (7.27, 3.37) and winter monsoon period (7.46, 6.07), indicating that the secondary evaporation was stronger during the summer monsoon. The evaporation ratio in the summer monsoon was 4.49%, which was higher than 3.65% in the winter monsoon. However, the evaporation ratio of the winter monsoon was higher than the summer monsoon around of Loess Plateau, which might closely relate to the increasing drought of the Loess Plateau in recent years. Finally, the intensity of secondary evaporation decreased with increasing relative humidity, precipitation and vapor pressure but increased with increasing temperature (greater than 0 ℃). The influences of those factors (humidity, precipitation, temperature and vapor pressure) on the secondary evaporation were dependent on the differences of ranges.