Objective To investigate the protective mechanism of ergothioneine against oxidative stress and inflammatory damage in vascular dementia(VaD)neurons through activation of the nuclear factor erythroid 2-related factor 2/heme oxygenase-1(Nrf2/HO-1)signaling pathway.Methods A total of 15 VaD patients(VaD group)admitted in our hospital from December 2023 to April 2024 were prospectively recruited,and another 15 healthy individuals taking physical examination during same period were subjected and served as health group.Then,plasma ergothioneine levels in the two groups were quantified by liquid chromatography-tandem mass spectrometry(LC-MS/MS).In in vitro experiments,hippocampal neurons were isolated from neonatal rats,and then divided into control,oxygen-glucose deprivation model,ergothioneine,and ergothioneine+ML385 groups.The expression levels of key molecules of Nrf2/HO-1 signaling pathway,oxidative stress markers,inflammatory cytokines,and apoptosis-related proteins were detected with RT-qPCR and Western blotting.Results The VaD patients exhibited significantly reduced plasma ergothioneine level(694.71±106.87 vs 1268.84±152.87)and down-regulated mRNA levels of Nrf2(0.49±0.14 vs 1.00±0.17),HO-1(0.35±0.23 vs 1.00±0.14)and NQO1(0.39±0.16 vs 1.00±0.12)than the health group(P＜0.05,P＜0.01).Compared with the control group,the model group showed significant increases in inflammatory factor levels.Ergothioneine treatment resulted in significant decreases in malondialdehyde and reactive oxygen species contents,and neuronal apoptosis rate.The ergothioneine+ML385 group showed a significant increase in hippocampal neuronal apoptotic rate,when compared with the ergothionein group.Conclusion Ergothioneine protects VaD neurons against oxidative stress and inflammatory damage by activating the Nrf2/HO-1 signaling pathway.

Objective To investigate the protective mechanism of ergothioneine against oxidative stress and inflammatory damage in vascular dementia(VaD)neurons through activation of the nuclear factor erythroid 2-related factor 2/heme oxygenase-1(Nrf2/HO-1)signaling pathway.Methods A total of 15 VaD patients(VaD group)admitted in our hospital from December 2023 to April 2024 were prospectively recruited,and another 15 healthy individuals taking physical examination during same period were subjected and served as health group.Then,plasma ergothioneine levels in the two groups were quantified by liquid chromatography-tandem mass spectrometry(LC-MS/MS).In in vitro experiments,hippocampal neurons were isolated from neonatal rats,and then divided into control,oxygen-glucose deprivation model,ergothioneine,and ergothioneine+ML385 groups.The expression levels of key molecules of Nrf2/HO-1 signaling pathway,oxidative stress markers,inflammatory cytokines,and apoptosis-related proteins were detected with RT-qPCR and Western blotting.Results The VaD patients exhibited significantly reduced plasma ergothioneine level(694.71±106.87 vs 1268.84±152.87)and down-regulated mRNA levels of Nrf2(0.49±0.14 vs 1.00±0.17),HO-1(0.35±0.23 vs 1.00±0.14)and NQO1(0.39±0.16 vs 1.00±0.12)than the health group(P＜0.05,P＜0.01).Compared with the control group,the model group showed significant increases in inflammatory factor levels.Ergothioneine treatment resulted in significant decreases in malondialdehyde and reactive oxygen species contents,and neuronal apoptosis rate.The ergothioneine+ML385 group showed a significant increase in hippocampal neuronal apoptotic rate,when compared with the ergothionein group.Conclusion Ergothioneine protects VaD neurons against oxidative stress and inflammatory damage by activating the Nrf2/HO-1 signaling pathway.

Purpose To explore the value of deep learning ultrasound radiomics nomogram in assessing the biological characteristics of invasive metastases in invasive breast cancer.Materials and Methods A retrospective collection of ultrasound imaging data from 180 pathologically confirmed invasive breast cancer between January 2021 to December 2022 in Maoming People's Hospital was conducted,with pathological reports indicating the status of lymph node metastasis(LNM),lymphovascular space invasion(LVSI)or perineural invasion(PNI),according to the LNM/LVSI/PNI status,the three indexes were divided into the training cohort and the verification cohort by 8∶2.Based on Pyradiomics and ResNet50 deep learning extractor,1 316 radiomic features and 2 048 deep learning features were extracted,respectively.The random forest machine learning algorithm was employed to develop evaluation models,and the model scores were calculated.The deep learning radiomics nomograms were developed based on the radiomic and deep learning model scores.The receiver operating characteristic curve was used to assess the performance of the models.The Delong test was applied to analyze the performance differences between different models.Results In the evaluation of LNM,LVSI and PNI status,the area under the curve of all the nomogram in the cohorts demonstrated moderate or above assessment performance(≥0.73),with accuracies all greater than 0.70.Specifically,in the LNM evaluation,the area under the curve of the training cohort was 0.97,the accuracy was 0.93,the sensitivity was 0.88 and the specificity was 0.96.Through the Delong test,the assessment performance of the nomograms was superior to the radiomics models(LNM,Z=2.04,P=0.04;LVSI,Z=2.80,P=0.01;PNI,Z=3.52,P<0.01),and was superior to or similar to the deep learning models(LNM,Z=4.52,P<0.01;LVSI,Z=1.86,P=0.06;PNI,Z=0.31,P=0.76)in the training cohort.Conclusion The deep learning radiomics nomogram can effectively evaluate the biological characteristics of invasion and metastasis in invasive breast cancer.The nomogram improves the assessment performance by integrating the radiomic and deep learning feature information.