Mast cells (MCs) play a crucial role in mediating the establishment of networks among the circulatory, nervous and immune system at acupoints. However, the changes which occur in MCs during acupoint sensitization, i.e. the dynamic transformation of an acupoint from a "silenced" to an "activated" status, remain uncharacterized. To investigate the morphological and functional changes of MCs as an aid to understanding the cellular mechanism underlying acupoint sensitization, a rat model of knee osteoarthritis (OA) was induced by an injection of mono-iodoacetate (MIA) on day 0. On day 14, toluidine blue and immunofluorescence staining were used to observe the recruitment and degranulation of MCs and the release of mast cell co-expressed mediators: tryptase, 5-hydroxytryptamine (5-HT) and histamine (HA) at the acupoints Yanglingquan (GB34), Heding (EX-LE2) and Weizhong (BL40). Results showed that the number of MCs as well as the percentages of degranulated and extensively degranulated MCs at the acupoints GB34 and EX-LE2 in the light (A), mild (B), heavy (C) osteoarthritis groups were larger than those in the normal control (N) and normal saline (NS) groups (p < 0.01). Comparisons among the A, B and C groups suggested that the number and the degranulation extent of the MCs at the acupoints GB34 and EX-LE2 were positively correlated with the severity of the disease. Some MCs in the A, B and C group showed the release of 5-HT, HA, and tryptase in degranulation at the acupoints GB34 and EX-LE2. Such changes in MCs were not observed at the acupoint BL40. In conclusion, this study confirmed that acupoint sensitization is associated with the increase in recruitment and degranulation levels of MCs on a acupoint-specific and disease severity-dependent manner. The release of tryptase, 5-HT, and HA during MC degranulation is likely to be one of the cellular mechanisms occurring during acupoint sensitization.
Objective To investigate the effect of manual acupuncture (MA) on NLRP3 inflammasome-related proteins. Methods SAMP8 mice were randomly divided into Alzheimer's disease (AD) group, the MA group, and the medicine (M) group. Mice in the M group were treated with donepezil hydrochloride at 0.65 μg/g. In the MA group, MA was applied on Baihui (GV20) and Yintang (GV29) for 20 min and then pricked at Shuigou (GV26). The Morris water maze was applied to assess spatial learning and memory. Immunohistochemical staining and western blot analysis were used to observe the expression of NLRP3 inflammasome-related proteins. ResultsCompared with the normal (N) control group, spatial learning and the memory capabilities of the AD group significantly decreased (p < 0.01). The number of NLRP3, ASC, Caspase-1, and IL-1β positively stained cells in the AD group was higher than the N group, and the relative expression levels of the above proteins were significantly higher than those in the N group (p < 0.01). These changes were reversed by both MA and donepezil (p < 0.01). Conclusion MA can improve the learning and memory capabilities of SAMP8 mice. The negative regulation of the NLRP3/Caspase-1 pathway in the hippocampus may be a possible mechanism of MA in the treatment of AD.
Acupoints microcirculatory dynamics vary depending on the body's health status. However, the functional changes observed during acupoint sensitization, that is, the disease-induced change from a “silenced” to an “activated” status, remain elusive. In this study, the microcirculatory changes at acupoints during sensitization were characterized. Thirty SD rats were randomly divided into five groups: normal control group (N), sham osteoarthritis group (S), light osteoarthritis group (A), mild osteoarthritis group (B), and heavy osteoarthritis group (C). The obtained results showed that the blood perfusion levels at the acupoints Yanglingquan (GB34), Zusanli (ST36), and Heding (EX-LE2) in groups A, B, and C were higher than those in groups N and S on days 14, 21, and 28 (p < 0.01 or p < 0.05). A significant difference in the blood perfusion was also observed at the acupoint Weizhong (BL40) in groups B and C on days 21 and 28 (p < 0.01). In addition, remarkable differences in the level of blood perfusion at the GB34, ST36, and EX-LE2 acupoints were observed on day 28 (p < 0.01 or p < 0.05) among groups A, B, and C. No marked differences in blood perfusion levels were observed at the nonacupoint site among all groups. In conclusion, acupoint sensitization is associated with an increase in the level of local blood perfusion at specific acupoints, and this increase is positively correlated with the severity of the disease. The functional changes in microcirculation at acupoints during sensitization reflect the different physiological and pathological conditions imposed by the disease.
<p><strong>Objective</strong>: Quantitative analysis of spindle dynamics in mitosis through fluorescence microscopy requires tracking spindles elongation in noisy image sequences. Deterministic methods, which use typical microtubule detection and tracking methods, perform poorly in the case of the sophisticated background of spindles. <strong>Methods</strong>: In this paper, we present SpindlesTracker, a fully automatic and extensible workflow that can efficiently analyze time-lapse images’ dynamic spindle mechanism. First, we design a novel deep neural network: YOLOX-SP (YOLOX for spindle). It consists of double branches responsible for spindle bounding boxes and endpoints detection. Then an improved SORT algorithm is used to link the same identity in different frames. Subsequently, we pair endpoints that fall into the same spindle bounding box as the spindle poles. Finally, we introduce the minimal cost path (MCP) algorithm to extract the continuous, single-pixel spindle skeleton. <strong>Result</strong>: SpindlesTracker is evaluated in all aspects of detection, tracking, and skeleton extraction through a fission yeast dataset. It achieves 84.1% mAP in bounding box detection and over 90% accuracy in endpoint detection. And for tracking, the comparison results show that the improved SORT algorithm increases by 1.3% in multiple object tracking accuracy (MOTA) and by 6.5% in multiple object tracking precision (MOTP). In addition, the statistical result shows that the mean error of spindle length is within 1 ?m. <strong>Conclude</strong>: SpindlesTracker provides a new baseline for multiple spindles analysis. <strong>Significance</strong>: This workflow could be easily extended to other microtubule or filamentous structures. The code is released on GitHub.</p>
<p><strong>Objective</strong>: Quantitative analysis of spindle dynamics in mitosis through fluorescence microscopy requires tracking spindles elongation in noisy image sequences. Deterministic methods, which use typical microtubule detection and tracking methods, perform poorly in the case of the sophisticated background of spindles. <strong>Methods</strong>: In this paper, we present SpindlesTracker, a fully automatic and extensible workflow that can efficiently analyze time-lapse images’ dynamic spindle mechanism. First, we design a novel deep neural network: YOLOX-SP (YOLOX for spindle). It consists of double branches responsible for spindle bounding boxes and endpoints detection. Then an improved SORT algorithm is used to link the same identity in different frames. Subsequently, we pair endpoints that fall into the same spindle bounding box as the spindle poles. Finally, we introduce the minimal cost path (MCP) algorithm to extract the continuous, single-pixel spindle skeleton. <strong>Result</strong>: SpindlesTracker is evaluated in all aspects of detection, tracking, and skeleton extraction through a fission yeast dataset. It achieves 84.1% mAP in bounding box detection and over 90% accuracy in endpoint detection. And for tracking, the comparison results show that the improved SORT algorithm increases by 1.3% in multiple object tracking accuracy (MOTA) and by 6.5% in multiple object tracking precision (MOTP). In addition, the statistical result shows that the mean error of spindle length is within 1 ?m. <strong>Conclude</strong>: SpindlesTracker provides a new baseline for multiple spindles analysis. <strong>Significance</strong>: This workflow could be easily extended to other microtubule or filamentous structures. The code is released on GitHub.</p>
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