Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

The zebrafish has emerged as a powerful model organism in life science owing to its remarkable biological characteristics and wide-ranging applications. This review provides a comprehensive overview of the recent advancements in research on zebrafish within the field of environmental toxicology, highlighting specific studies where this species was used to investigate various pollutants to elucidate their impacts and underlying mechanisms. The findings of these studies underscore the significant potential of zebrafish as a model to gain crucial insights into the ecological consequences of environmental contamination and toxicity pathways. By incorporating cutting-edge technologies such as artificial intelligence (AI), high-throughput screening, and omics approaches, the use of zebrafish as a model organism is poised to significantly accelerate toxicological investigations, promote environmental conservation efforts, contribute to safeguarding human health, and advance sustainable development objectives.
Animals ; Zebrafish ; Ecotoxicology/methods* ; Artificial Intelligence ; Humans ; Models, Animal ; Environmental Pollutants/toxicity*

Background/Aims: Activation of the cold receptor, transient receptor potential melastatin 8 (TRPM8) by menthol inhibits esophageal secondary peristalsis in healthy adults. Ineffective esophageal motility (IEM) is common. This study is to evaluate the effects of acute infusion of menthol on esophageal peristalsis in patients with IEM. Methods: Twenty patients with IEM (males 11, mean age 36) were studied for esophageal peristalsis using high-resolution manometry. All participant had primary peristalsis performed with 10 water swallows and secondary peristalsis generated with 10 rapid air injections of 20 mL via mid-esophageal infusion port. Two different sessions by randomly performing acute administration of placebo or menthol (3 mM) were used for testing their effects on esophageal peristalsis. Results: Menthol infusion had no effects on distal contractile integral (P = 0.471), distal latency (P = 0.58), or complete peristalsis (P = 0.251). Menthol infusion did not change basal lower esophageal sphincter pressure (P = 0.321), esophagogastric junction contractile integral (P = 0.758), or integrated relaxation pressure (P = 0.375) of primary peristalsis, but reduced upper esophageal sphincter pressure (P = 0.037). Infusion of menthol significantly reduced the frequency of secondary peristalsis for air injects of 20 mL (P = 0.002), but did not affect distal contractile integral of secondary peristalsis for air injections of 20 mL. Conclusion This work has suggested that activation of TRPM8 by menthol can attenuate mechanosensitivity of secondary peristalsis in response to rapid air distension regardless of the presence of IEM.

Background/Aims: Activation of the cold receptor, transient receptor potential melastatin 8 (TRPM8) by menthol inhibits esophageal secondary peristalsis in healthy adults. Ineffective esophageal motility (IEM) is common. This study is to evaluate the effects of acute infusion of menthol on esophageal peristalsis in patients with IEM. Methods: Twenty patients with IEM (males 11, mean age 36) were studied for esophageal peristalsis using high-resolution manometry. All participant had primary peristalsis performed with 10 water swallows and secondary peristalsis generated with 10 rapid air injections of 20 mL via mid-esophageal infusion port. Two different sessions by randomly performing acute administration of placebo or menthol (3 mM) were used for testing their effects on esophageal peristalsis. Results: Menthol infusion had no effects on distal contractile integral (P = 0.471), distal latency (P = 0.58), or complete peristalsis (P = 0.251). Menthol infusion did not change basal lower esophageal sphincter pressure (P = 0.321), esophagogastric junction contractile integral (P = 0.758), or integrated relaxation pressure (P = 0.375) of primary peristalsis, but reduced upper esophageal sphincter pressure (P = 0.037). Infusion of menthol significantly reduced the frequency of secondary peristalsis for air injects of 20 mL (P = 0.002), but did not affect distal contractile integral of secondary peristalsis for air injections of 20 mL. Conclusion This work has suggested that activation of TRPM8 by menthol can attenuate mechanosensitivity of secondary peristalsis in response to rapid air distension regardless of the presence of IEM.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: Danshensu, a phenylpropanoid compound, is derived from the dry root and rhizome of Danshen (Salvia miltiorrhiza), a traditional Chinese medicinal herb. Evidence suggests that danshensu protects isolated rat hearts against ischemia/reperfusion injury by activating the protein kinase B (Akt)/extracellular signal-regulated kinase (ERK) pathway or by inhibiting autophagy and apoptosis through the activation of mammalian target of rapamycin (mTOR) signaling. Furthermore, danshensu promotes the postischemic regeneration of brain cells by upregulating the expression of brain-derived neurotrophic factor (BDNF) in the peri-infarct region. However, basic and clinical studies are needed to investigate the antidepressant effects danshensu and determine whether brain mTOR signaling and BDNF activation mediate these effects. The aforementioned need prompted us to conduct the present study. Methods: Using a C57BL/6 mouse model, we investigated the antidepressant-like effects of danshensu and the mechanisms that mediate these effects. To elucidate the mechanisms, we analyzed the roles of Akt/ERK–mTOR signaling and BDNF activation in mediating the antidepressant-like effects of danshensu. Results: Danshensu exerted its antidepressant-like effects by activating the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) of Akt/ERK–mTOR signaling and promoting BDNF release. Treatment with danshensu increased the level of glutamate receptor 1 phosphorylation at the protein kinase A site. Conclusion Our study may be the first to demonstrate that the antidepressant effects of danshensu are dependent on the activation of the AMPAR–mTOR signaling pathway, are correlated with the elevation of BDNF level, and facilitate the insertion of AMPAR into the postsynaptic membrane. This study also pioneers in unveiling the potential of danshensu against depressive disorders.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: Danshensu, a phenylpropanoid compound, is derived from the dry root and rhizome of Danshen (Salvia miltiorrhiza), a traditional Chinese medicinal herb. Evidence suggests that danshensu protects isolated rat hearts against ischemia/reperfusion injury by activating the protein kinase B (Akt)/extracellular signal-regulated kinase (ERK) pathway or by inhibiting autophagy and apoptosis through the activation of mammalian target of rapamycin (mTOR) signaling. Furthermore, danshensu promotes the postischemic regeneration of brain cells by upregulating the expression of brain-derived neurotrophic factor (BDNF) in the peri-infarct region. However, basic and clinical studies are needed to investigate the antidepressant effects danshensu and determine whether brain mTOR signaling and BDNF activation mediate these effects. The aforementioned need prompted us to conduct the present study. Methods: Using a C57BL/6 mouse model, we investigated the antidepressant-like effects of danshensu and the mechanisms that mediate these effects. To elucidate the mechanisms, we analyzed the roles of Akt/ERK–mTOR signaling and BDNF activation in mediating the antidepressant-like effects of danshensu. Results: Danshensu exerted its antidepressant-like effects by activating the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) of Akt/ERK–mTOR signaling and promoting BDNF release. Treatment with danshensu increased the level of glutamate receptor 1 phosphorylation at the protein kinase A site. Conclusion Our study may be the first to demonstrate that the antidepressant effects of danshensu are dependent on the activation of the AMPAR–mTOR signaling pathway, are correlated with the elevation of BDNF level, and facilitate the insertion of AMPAR into the postsynaptic membrane. This study also pioneers in unveiling the potential of danshensu against depressive disorders.