ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ （AngⅡ） and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment， AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h， and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 （CCK-8） to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay （ELISA） was used to detect the content of B-type natriuretic peptide （BNP） in cell culture supernatant， and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently， the experiment was divided into a blank group （20% blank serum）， a model group （20% blank serum + 5×10^-5 mol·L^-1 AngⅡ）， low-， medium-， and high-dose （5%， 10% and 20%） serum containing Zhenwutang groups， an autophagy inhibitor group （1×10^-4 mol·L^-1 3-MA）， and autophagy inducer group （1×10^-7 mol·L^-1 rapamycin）. The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe （Lyso Tracker） and mitochondrial probe （Mito Tracker） co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect Caspase-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， Bcl-2-related X protein （Bax）， and cytochrome C （Cyt C） in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase （Parkin）， phosphatase and tensin homolog （PTEN）-induced kinase 1 （PINK1）， and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3， cleaved Caspase-9， Bax， Bcl-2， and Cyt C in apoptosis-related pathways， phosphorylated ubiquitin ligase （p-Parkin）， phosphorylated PTEN-induced kinase 1 （p-PINK1）， p62， and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways， and the change of microtubule-associated protein 1 light chain 3 （LC3） Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10^-5 mol·L^-1， the cell activity was the lowest， and there was no cytotoxicity. At this concentration， the surface area of cardiomyocytes was significantly increased （P<0.01）， and the content of BNP in the supernatant of culture medium was significantly increased （P<0.05）. Therefore， AngⅡ with a concentration of 5×10^-5 mol·L^-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group， the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate （P<0.01） and significantly decreased mitochondrial membrane potential （P<0.01）. The results of immunofluorescence co-localization showed that compared with the blank group， the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group， the relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 in the model group was significantly up-regulated （P<0.01）， while the relative mRNA expression of Bcl-2， Parkin， and PINK1 was significantly down-regulated （P<0.01）. In addition， the relative protein expression of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 was significantly up-regulated （P<0.01）. The LC3Ⅱ/Ⅰ was significantly decreased， and the relative protein expression of Bcl-2， p-Parkin， p-PINK1， and Beclin1 was significantly down-regulated （P<0.01）. Compared with the model group， the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate （P<0.01）， and the decrease ratio of mitochondrial membrane potential is significantly lowered （P<0.01） in a dose-dependent manner. Additionally， both red and green fluorescence spots became more in these groups. In the 3-MA group， the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 was significantly down-regulated （P<0.05， P<0.01）， while that of Bcl-2， Parkin， and PINK1 was significantly up-regulated （P<0.01）. In the serum containing Zhenwutang groups， the relative protein expression levels of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 were significantly down-regulated （P<0.05，P<0.01）. The LC3Ⅱ/Ⅰ was significantly increased， and the relative protein expression levels of Bcl-2， p-Parkin， p-PINK1， and Beclin1 were significantly up-regulated （P<0.01）. ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

With the rapid development of artificial intelligence technology,small molecule generation models have emerged as a significant research direction in the field of drug discovery.These models,including Generative Adversarial Networks(GANs),Variational Autoencoders(VAEs),and diffusion models,have proven to possess remarkable capabilities in optimizing drug properties and generating complex molecular structures.This article comprehensively analyzes the application of the aforementioned advanced technologies in the drug discovery process,demonstrating how they supplement and enhance traditional drug design methods.At the same time,it addresses the challenges facing current methods in terms of data quality,model complexity,computational cost,and generalization ability,with a prospect of future research directions.