Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective To investigate the mechanism by which Yangmai Tongluo formula improves microcirculation disorders induced by high homocysteine(Hcy)levels via regulation of the acid sphingomyelinase(ASM)and endoplasmic reticulum(ER)stress pathways.Methods Fifty male C57BL/6J mice were divided randomly into a control group,Hcy model group,Yangmai Tongluo formula low-/high dose groups(5.3,10.4 g/kg,respectively),and a folic acid group(0.08 g/kg).Except for the control group,microcirculation disorders were induced in all mice using drinking water containing 1.8 g/L Hcy for 6 weeks.After modeling for 2 weeks,mice were administered the corresponding treatments by gavage for 4 weeks.Serum Hey concentrations and the blood perfusion volume of the lower extremity microvessels were measured.Protein expression levels of zonula occludens ZO-1,ZO-2,intercellular adhesion molecule-1(ICAM-1),vascular cell adhesion molecule-1(VCAM-1),ASM,glucose-regulated protein 78(GRP78),and C/EBP homologous protein(CHOP)in the cardiac microvascular endothelium were analyzed using immunofluorescence.Results Serum Hcy levels were significantly increased in the Hcy model group compared with the control group(P＜0.05).Yangmai Tongluo formula did not significantly reduce Hey levels compared with the Hey model group,but blood perfusion in the lower extremities was significantly increased(P＜0.01)and expression levels of ZO-1 and ZO-2 in the cardiac microvascular endothelium were restored(P＜0.001)in the Yangmai Tongluo formula high dose group.It also inhibited the expression of ICAM-1,VCAM-1,ASM,GRP78,and CHOP(P＜0.05),with comparable effects to folic acid.Conclusions Yangmai Tongluo formula improves Hcy-induced microcirculation disorders and endothelial dysfunction by inhibiting ASM activity and alleviating ER stress,via a mechanism closely related to the regulation of endothelial inflammation and barrier stability.These result provide experimental evidence to support the use of traditional Chinese medicine to treat microvascular diseases.

Objective To evaluate the practical application of the Media Fill Test(MFT)in assessing aseptic compounding competency of personnel in Pharmacy Intravenous Admixture Services(PIVAS).Methods A multicenter controlled study was conducted across six tertiary hospitals(center ①-⑥)in China.Participants were divided into an inexperienced group(Group A,n=118)and an experienced group(Group B,n=118),each performing five MFT operations.Positive controls validated medium efficacy.Contamination rates and pass rates were analyzed using chi-square and Fisher's exact tests.Results Valid samples included 584 for Group A and 588 for Group B.The sample pass rate was 66.78%(390/584)in Group A and 91.67%(539/588)in Group B,while personnel pass rates were 46.15%(54/117)and 80.51%(95/118),respectively,with significant intergroup differences(both P<0.01).All centers except Center ⑥ showed significantly higher pass rates in Group B(all P<0.05).Conclusion MFT effectively differentiates technical proficiency levels and is suitable for training evaluation of novice PIVAS staff.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective To evaluate the practical application of the Media Fill Test(MFT)in assessing aseptic compounding competency of personnel in Pharmacy Intravenous Admixture Services(PIVAS).Methods A multicenter controlled study was conducted across six tertiary hospitals(center ①-⑥)in China.Participants were divided into an inexperienced group(Group A,n=118)and an experienced group(Group B,n=118),each performing five MFT operations.Positive controls validated medium efficacy.Contamination rates and pass rates were analyzed using chi-square and Fisher's exact tests.Results Valid samples included 584 for Group A and 588 for Group B.The sample pass rate was 66.78%(390/584)in Group A and 91.67%(539/588)in Group B,while personnel pass rates were 46.15%(54/117)and 80.51%(95/118),respectively,with significant intergroup differences(both P<0.01).All centers except Center ⑥ showed significantly higher pass rates in Group B(all P<0.05).Conclusion MFT effectively differentiates technical proficiency levels and is suitable for training evaluation of novice PIVAS staff.

Objective To investigate the mechanism by which Yangmai Tongluo formula improves microcirculation disorders induced by high homocysteine(Hcy)levels via regulation of the acid sphingomyelinase(ASM)and endoplasmic reticulum(ER)stress pathways.Methods Fifty male C57BL/6J mice were divided randomly into a control group,Hcy model group,Yangmai Tongluo formula low-/high dose groups(5.3,10.4 g/kg,respectively),and a folic acid group(0.08 g/kg).Except for the control group,microcirculation disorders were induced in all mice using drinking water containing 1.8 g/L Hcy for 6 weeks.After modeling for 2 weeks,mice were administered the corresponding treatments by gavage for 4 weeks.Serum Hey concentrations and the blood perfusion volume of the lower extremity microvessels were measured.Protein expression levels of zonula occludens ZO-1,ZO-2,intercellular adhesion molecule-1(ICAM-1),vascular cell adhesion molecule-1(VCAM-1),ASM,glucose-regulated protein 78(GRP78),and C/EBP homologous protein(CHOP)in the cardiac microvascular endothelium were analyzed using immunofluorescence.Results Serum Hcy levels were significantly increased in the Hcy model group compared with the control group(P＜0.05).Yangmai Tongluo formula did not significantly reduce Hey levels compared with the Hey model group,but blood perfusion in the lower extremities was significantly increased(P＜0.01)and expression levels of ZO-1 and ZO-2 in the cardiac microvascular endothelium were restored(P＜0.001)in the Yangmai Tongluo formula high dose group.It also inhibited the expression of ICAM-1,VCAM-1,ASM,GRP78,and CHOP(P＜0.05),with comparable effects to folic acid.Conclusions Yangmai Tongluo formula improves Hcy-induced microcirculation disorders and endothelial dysfunction by inhibiting ASM activity and alleviating ER stress,via a mechanism closely related to the regulation of endothelial inflammation and barrier stability.These result provide experimental evidence to support the use of traditional Chinese medicine to treat microvascular diseases.

Demyelination of the central nervous system often occurs in neurodegenerative diseases， such as multiple sclerosis （MS）. The myelin sheath， a layer of myelin membrane wrapping the axon， plays a role in the rapid conduction and metabolic coupling of impulses for neurons. The exposure of the axon will lead to axonal degeneratio， and further neuronal degeneration， which is the main cause of dysfunction and even disability in patients with demyelinating neurodegenerative diseases. In addition to the demyelination of mature myelin sheath， remyelination disorder is also one of the major reasons leading to the development of the diseases. The myelin sheath is composed of oligodendrocytes （OLs） derived from oligodendrocyte progenitor cells （OPCs） which are differentiated from neural stem cells （NSCs）. The process of myelin regeneration， i.e.， remyelination， is the differentiation of NSCs into OLs. Recent studies have shown that this process is regulated by a variety of genes. MicroRNAs， as important regulators of neurodegenerative diseases， form a complex regulatory network in the process of myelin regeneration. This review summarizes the main molecular pathways of myelin regeneration and microRNAs involved in this process and classifies the mechanisms and targets. This review is expected to provide a theoretical reference for the future research on the treatment of demyelinating diseases by targeting the regulation of microRNAs.

ObjectiveTo investigate the effects of Jiaohong pills （JHP） and its prescription， Pericarpium Zanthoxyli （PZ） and Rehmanniae Radix （RR） cognitive dysfunction in scopolamine-induced Alzheimer's disease （AD） mice and its mechanism through pharmacodynamic and metabolomics study. MethodThe animal model of AD induced by scopolamine was established and treated with PZ， RG and JHP， respectively. The effects of JHP and its formulations were investigated by open field test， water maze test， object recognition test， avoidance test， cholinergic system and oxidative stress related biochemical test. Untargeted metabolomics analysis of cerebral cortex was performed by ultra-performance liquid chromatography-Quadrupole/Orbitrap high resolution mass spectrometry （UPLC Q-Exactive Orbitrap MS）. ResultThe behavioral data showed that， compared with the model group， the discrimination indexes of the high dose of JHP， PZ and RR groups was significantly increased （P<0.05）. The staging rate of Morris water maze test in the PZ， RR， high and low dose groups of JHP was significantly increased （P<0.05， P<0.01）， the crossing numbers in the PZ， JHP high and low dose groups were significantly increased （P<0.05， P<0.01）； the number of errors in the avoidance test were significantly reduced in the PZ and high-dose JHP groups （P<0.01）， and the error latencies were significantly increased in the JHP and its prescription drug groups （P<0.01）. Compared with the model group， the activities of acetylcholinesterase in the cerebral cortex of the two doses of JHP group and the PZ group were significantly increased （P<0.05， P<0.01）， and the activity of acetylcholinesterase in the high-dose JHP group was significantly decreased （P<0.05）， and the level of acetylcholine was significantly increased （P<0.01）. At the same time， the contents of malondialdehyde in the serum of the two dose groups of JHP decreased significantly （P<0.05， P<0.01）. The results of metabolomics study of cerebral cortex showed that 149 differential metabolites were identified between the JHP group and the model group， which were involved in neurotransmitter metabolism， energy metabolism， oxidative stress and amino acid metabolism. ConclusionJHP and its prescription can antagonize scopolamine-induced cognitive dysfunction， regulate cholinergic system， and reduce oxidative stress damage. The mechanism of its therapeutic effect on AD is related to the regulation of neurotransmitter， energy， amino acid metabolism， and improvement of oxidative stress.

Objective:To construct an artificial intelligence (AI)-assisted system based on deep learning for corneal in vivo confocal microscopy (IVCM) image recognition and to evaluate its value in clinical applications. Methods:A diagnostic study was conducted.A total of 18 860 corneal images were collected from 331 subjects who underwent IVCM examination at Renmin Hospital of Wuhan University and Zhongnan Hospital of Wuhan University from May 2021 to September 2022.The collected images were used for model training and testing after being reviewed and classified by corneal experts.The model design included a low-quality image filtering model, a corneal image diagnosis model, and a 4-layer identification model for corneal epithelium, Bowman membrane, stroma, and endothelium, to initially determine normal and abnormal corneal images and corresponding corneal layers.A human-machine competition was conducted with another 360 database-independent IVCM images to compare the accuracy and time spent on image recognition by three senior ophthalmologists and the AI system.In addition, 8 trainees without IVCM training and with less than three years of clinical experience were selected to recognize the same 360 images without and with model assistance to analyze the effectiveness of model assistance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2021-K148).Results:The accuracy of this diagnostic model in screening high-quality images was 0.954.Its overall accuracy in identifying normal/abnormal corneal images was 0.916 and 0.896 in the internal and external test sets, respectively.Its accuracy reached 0.983, 0.925 in the internal test sets and 0.988, 0.929 in the external test sets in identifying corneal layers of normal and abnormal images, respectively.In the human-machine competition, the overall recognition accuracy of the model was 0.878, which was similar to the average accuracy of the three senior physicians and was approximately 300 times faster than the experts in recognition speed.Trainees assisted by the system achieved an accuracy of 0.816±0.043 in identifying corneal layers of normal and abnormal images, which was significantly higher than 0.669±0.061 without model assistance ( t=6.304, P<0.001). Conclusions:A deep learning-based assistant system for corneal IVCM image recognition is successfully constructed.This system can discriminate normal/abnormal corneal images and diagnose the corresponding corneal layer of the images, which can improve the efficiency of clinical diagnosis and assist doctors in training and learning.

Objective To explore the mechanism by which puerarin alleviates the cardiotoxicity induced by doxorubicin in myocardial cells. Methods Cells in the logarithmic growth phase were divided into normal control group,model group,low-(20 mmol·L-1),medium-(40 mmol·L-1) and high-(80 mmol·L-1) dose puerarin groups,and positive control group(captopril,1 mmol·L-1). Except for the normal control group,the other groups were co-incubated with 5 mmol·L-1 doxorubicin. Cell viability was assessed using CCK-8 and lactate dehydrogenase (LDH) assays. ROS levels were detected using a ROS probe. Autophagy flux was detected by transfection with HBAD-mcherry-EGFP-LC3 adenovirus. Western Blot was used to measure the protein expression levels of Beclin-1,LC3,p62,p-AMPKα,and AMPKα. Lysosomal function was assessed using a lysosomal probe. Immunofluorescence was used to detect the relative intensity and co-localization of ASMase and LAMP1. Molecular docking analysis was performed to predict the binding capacity of PUE with ASMase. Differential gene expression was analyzed by gene set enrichment analysis. Results Compared to the normal control group,the model group showed reduced cell viability (P<0.01),increased release levels of LDH and ROS (P<0.05,P<0.01),increased number of autophagosomes (P<0.01),and decreased number of autophagic lysosomes (P<0.05). Beclin-1 protein expression and LC3-II/LC3-I ratio decreased(P<0.01),but p62 protein expression increased(P<0.01). Fluorescence intensity of lysosome decreased(P<0.01),whereas fluorescence intensity of ASMase increased(P<0.01). Immunofluorescence co-localization of ASMase and LAMP1 increased (P<0.01),the ratio of p-AMPKα/AMPKα decreased(P<0.05). Compared to the model group,the high-dose puerarin group showed a rebound in cell viability (P<0.05). The medium-and high-dose puerarin groups showed a decreasing trend in LDH level (P<0.05),and all puerarin groups showed a decreasing trend in ROS level (P<0.01). The number of autophagosomes in high-dose puerarin group reduced (P<0.01). The number of autophagic lysosomes in all puerarin groups increased (P<0.05,P<0.01). The high-dose puerarin group showed increased expression of Beclin-1 (P<0.05) and LC3-II/LC3-I ratio,and decreased p62 expression (P<0.01). All puerarin groups showed increased lysosomal fluorescence intensity (P<0.05,P<0.01). The medium-and high-dose puerarin groups showed a decrease in ASMase fluorescence intensity(P<0.05),a reduction in the immunofluorescence co-localization of ASMase with LAMP1 (P<0.01),and an increase in the p-AMPKα/AMPKα ratio (P<0.01). Molecular docking analysis discovered puerarin showed a binding energy of-8.6 kcal·mol-1 with ASMase. Gene enrichment analysis indicated that the differentially expressed genes in the doxorubicin cardiotoxicity model were related to apoptosis,autophagy,and lysosomal function. Conclusion Puerarin can alleviate doxorubicin-induced cardiotoxicity in myocardial cells and protect myocardial cells by regulating autophagy through AMPK/ASMase,as well as restoring autophagic flux.