AIM: To investigate the potential inhibitory effect of pterostilbene on the endothelial-to-mesenchymal transition(EndMT)induced by high glucose conditions in human retinal microvascular endothelial cells(HRMECs).METHODS: The optimal concentration of pterostilbene for treating HRMECs was determined using the CCK-8 assay, with 12.5 and 25 μmol/L concentrations selected for subsequent experiments. Four experimental groups were established: control group, high glucose group, high glucose combined with 12.5 μmol/L pterostilbene treatment group, and high glucose combined with 25 μmol/L pterostilbene treatment group. The expression levels of HDAC7 and EndMT-associated markers were detected via Western blot analysis. Cell migration ability was assessed using Transwell migration assays and scratch wound healing tests, while vasculogenic capability was evaluated through tube formation assays.RESULTS: The CCK-8 assay revealed that pterostilbene at a concentration of 22.07 μmol/L inhibited 50% of cell viability in HRMECs. Western blot analysis demonstrated that compared with the control group, the expression levels of HDAC7, ZEB1, Vimentin, and Snail were significantly upregulated in HRMECs cultured in high glucose(all P<0.01), while the expressions of VE-cadherin and CD31 were significantly reduced(all P<0.01). Compared to the high glucose group, the treatment with 12.5 and 25 μmol/L pterostilbene significantly reduced the expression of HDAC7, ZEB1, Vimentin, and Snail under high glucose conditions(all P<0.01). Notably, 25 μmol/L pterostilbene enhanced the expression of VE-cadherin and CD31(all P<0.01). Scratch wound healing tests revealed that HRMECs treated with high glucose exhibited a significantly increased cell migration rate compared to the control group(P<0.05), while the application of 25 μmol/L pterostilbene significantly suppressed HRMECs migration under high glucose conditions(P<0.01). Transwell migration assays demonstrated that the cell migration rate in the high glucose group was significantly higher than that in the control group(P<0.01), with cell migration rate markedly reduced following treatment with both of 12.5 and 25 μmol/L pterostilbene(all P<0.01). The tube formation assay revealed that the ability of HRMECs to form tubular structures was significantly enhanced under high glucose conditions(P<0.01), and both 12.5 and 25 μmol/L of pterostilbene effectively inhibited this effect(all P<0.01).CONCLUSION: Pterostilbene can inhibit HDAC7 expression, suppress EndMT-mediated migration of HRMECs, and impair tube formation under high-glucose conditions.

AIM: To investigate the potential inhibitory effect of pterostilbene on the endothelial-to-mesenchymal transition(EndMT)induced by high glucose conditions in human retinal microvascular endothelial cells(HRMECs).METHODS: The optimal concentration of pterostilbene for treating HRMECs was determined using the CCK-8 assay, with 12.5 and 25 μmol/L concentrations selected for subsequent experiments. Four experimental groups were established: control group, high glucose group, high glucose combined with 12.5 μmol/L pterostilbene treatment group, and high glucose combined with 25 μmol/L pterostilbene treatment group. The expression levels of HDAC7 and EndMT-associated markers were detected via Western blot analysis. Cell migration ability was assessed using Transwell migration assays and scratch wound healing tests, while vasculogenic capability was evaluated through tube formation assays.RESULTS: The CCK-8 assay revealed that pterostilbene at a concentration of 22.07 μmol/L inhibited 50% of cell viability in HRMECs. Western blot analysis demonstrated that compared with the control group, the expression levels of HDAC7, ZEB1, Vimentin, and Snail were significantly upregulated in HRMECs cultured in high glucose(all P<0.01), while the expressions of VE-cadherin and CD31 were significantly reduced(all P<0.01). Compared to the high glucose group, the treatment with 12.5 and 25 μmol/L pterostilbene significantly reduced the expression of HDAC7, ZEB1, Vimentin, and Snail under high glucose conditions(all P<0.01). Notably, 25 μmol/L pterostilbene enhanced the expression of VE-cadherin and CD31(all P<0.01). Scratch wound healing tests revealed that HRMECs treated with high glucose exhibited a significantly increased cell migration rate compared to the control group(P<0.05), while the application of 25 μmol/L pterostilbene significantly suppressed HRMECs migration under high glucose conditions(P<0.01). Transwell migration assays demonstrated that the cell migration rate in the high glucose group was significantly higher than that in the control group(P<0.01), with cell migration rate markedly reduced following treatment with both of 12.5 and 25 μmol/L pterostilbene(all P<0.01). The tube formation assay revealed that the ability of HRMECs to form tubular structures was significantly enhanced under high glucose conditions(P<0.01), and both 12.5 and 25 μmol/L of pterostilbene effectively inhibited this effect(all P<0.01).CONCLUSION: Pterostilbene can inhibit HDAC7 expression, suppress EndMT-mediated migration of HRMECs, and impair tube formation under high-glucose conditions.

ObjectiveA qualitative analysis method was established for the composition of Astragali Radix（AR） before and after rice stir-frying. On the basis of systematic characterization of the chemical compositions in AR and stir-fried AR with rice（ARR）， the structures of their major compounds were deduced and identified， and the differential compositions between them were analyzed. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the samples of AR and ARR in positive and negative ion modes， respectively. The compounds were analyzed and identified through self-constructed databases， literature， and reference standards， etc. And the data were analyzed by chemometrics， in order to screen for the differential components between AR and ARR. ResultsA total of 123 compounds were identified in AR and ARR， including 41 flavonoids， 19 terpenoids， 26 organic acids， 8 amino acids， 5 nucleotides， 5 carbohydrates and 19 other compounds. Among them， there were 95 common components in both， 18 unique components in AR， and 10 unique components in ARR. Principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） results both showed that there were significant differences in the chemical constituents of AR before and after rice stir-frying， and a total of 26 constituents with differences in the content were screened out， including L-canavanine， L-pyroglutamic acid， L-phenylalanine， cis-caffeic acid， and malonylastragaloside Ⅰ. Among them， 19 constituents of ARR were down-regulated and 7 constituents were up-regulated by comparing with AR. ConclusionThis study clarifies that the chemical composition of AR and ARR is mainly composed of flavonoids， terpenoids， and organic acids， and analyzes the components with significant differences in content between the two in combination with chemometrics， and the differential components are dominated by amino acids， organic acids and terpenoids， which can provide reference for the subsequent quality control and material basis research.

Objective To investigate the distribution and evolutionary patterns of traditional Chinese medicine(TCM)syndromes and syndrome elements during the malignant transformation from chronic pancreatitis(CP)to pancreatic intraepithelial neoplasia(Pan IN)and pancreatic ductal adenocarcinoma(PDAC).Methods A retrospective analysis was conducted on 710 patients(330 of CP,104 of Pan IN,276 of PDAC)diagnosed pathologically or clinically at Shanxi Institute of Traditional Chinese Medicine from January 2021 to June 2024.Data including demographics,laboratory results,and TCM diagnostic information were recorded using EpiData 3.1.Syndrome and syndrome-element patterns were determined via factor analysis and K-means clustering using SPSS 27.0.Results The study identifies seven TCM syndrome types in CP,Pan IN,and PDAC.Among CP patients,the syndrome distribution was primarily liver-gallbladder damp-heat syndrome(22.42％)and gastrointestinal excess-heat syndrome(20.91％),with excess syndromes accounting for a higher proportion(43.33％);the syndrome elements were mainly heat(51.52％)and dampness(35.15％),with the disease location in the pancreas,related to the liver,spleen,and stomach.In Pan IN patients,the syndrome distribution was mainly spleen deficiency with dampness obstruction(23.08％)and liver-gallbladder damp-heat syndrome(17.31％),with mixed deficiency-excess syndrome accounting for a higher proportion(30.00％);the syndrome elements were mainly heat(41.35％),dampness(40.38％),and qi deficiency(37.50％),with the disease location in the pancreas,related to the spleen and liver.In PDAC patients,the syndrome distribution was mainly spleen deficiency with dampness obstruction(29.71％)and qi-blood deficiency syndrome(20.29％),with deficiency syndromes accounting for a higher proportion(49.82％);the syndrome elements were mainly qi deficiency(50.00％)and dampness(36.23％),with the disease location in the pancreas,related to the spleen,kidney,and liver.Chi-square tests revealed significant differences in syndrome types(TCM syndromes:x2=100.419,P＜0.001;deficiency-excess syndromes:x2=73.722,P＜0.001),syndrome elements(x2=117.384,P＜0.001),and disease locations(x2=127.191,P＜0.001)across different stages of CP malignant transformation.During CP malignant progression,the proportion of excess syndromes gradually decreased(43.33％→12.32％),while deficiency syndromes increased(26.67％→49.82％).Excess syndrome elements(fire,heat,qi stagnation,blood stasis)decreased(53.48％→25.36％),whereas deficiency syndrome elements(qi deficiency,yin deficiency,yang deficiency,blood deficiency)increased(25.15％→49.64％).The disease location shifted from primarily the liver,spleen,and stomach in the inflammatory stage to the spleen and kidney in the cancerous stage.Conclusion The malignant transformation of CP basically involves the pancreas,is correlated early with liver and spleen-stomach and later with kidney,and exhibits a progression from excess to deficiency in the pattern of"deficiency interweaved with excess syndrome,transition from excess to deficiency,and progressive spleen deficiency".

Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pre-training.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.

Brain imaging abnormalities are present in schizophrenia (SZ) and bipolar disorder (BD), demonstrating disease-specific changes, yet they also share similarities in certain brain regions or functional characteristics, with SZ potentially exhibiting more extensive brain damage compared to BD. Structural magnetic resonance imaging (MRI) studies demonstrated widespread gray matter reductions in SZ, particularly in the prefrontal and temporal lobes. In BD, gray matter thickening was observed in the prefrontal lobes during manic episodes, while a reduction in gray matter was noted in the amygdala and hippocampus during depressive episodes. Both SZ and BD exhibited increased ventricular volume and reduced overall brain volume. Functional MRI studies revealed reduced functional connectivity in the prefrontal and temporal lobes in SZ, with decreased global and local efficiency in brain regions such as the hippocampus and cingulate gyrus. BD showed enhanced connectivity in the anterior cingulate gyrus and the default mode network (DMN). Both SZ and BD demonstrated altered functional connectivity in areas such as the striatum, salience network, central executive network and DMN. Diffusion tensor imaging studies showed decreased fractional anisotropy (FA) in the corpus callosum of SZ, with a decrease in FA in the left fronto-occipital fasciculus in BD. Both SZ and BD exhibited reduced FA in the uncinate fasciculus and corpus callosum. Magnetic resonance spectroscopy revealed decreased concentrations of glutathione, N-acetylaspartate (NAA) and inositol in the anterior cingulate gyrus of SZ. In BD, glutathione and inositol concentrations were elevated in the anterior cingulate gyrus, while NAA levels decreased during depressive episodes and increased during remission. Both SZ and BD showed increased levels of glutamate and gamma-aminobutyric acid in the prefrontal cortex. This article provides a review of the current evidence on the differences and similarities in multimodal magnetic resonance brain imaging between SZ and BD, aiming to offer a reference for future exploration of neuroimaging biomarkers and the neurobiological mechanisms of SZ and BD.

Objective:To investigate the effect and underlying mechanism of sonodynamic therapy (SDT) on inflammation-related atrial fibrillation (AF) susceptibility.Methods:Lipopolysaccharide (LPS)-stimulated mouse and HL-1 mouse atrial myocyte models were used. (1) In vivo study: experimental groups included control, LPS, LPS+SDT, and SDT groups, with 20 mice in each group. Atrial fibrillation inducibility and duration were assessed by electrical stimulation. Western blot was used to analyze atrial expression of NOD-like receptor family pyrin domain-containing protein 3 (NLRP3), interleukin (IL)-1β, and IL-18. Immunohistochemistry was used to detect calcium voltage-gated channel subunit alpha1 C (CACNA1C) expression. (2) In vitro study: cell counting kit-8 (CCK-8) and Western blot were used to determine the optimal and safe LPS concentration. The safe incubation condition for the sonosensitizer sinoporphyrin sodium was determined by CCK-8 and fluorometry. An LPS-induced inflammatory model in HL-1 atrial myocytes was used, with experimental groups including control, LPS, LPS+SDT, LPS+sinoporphyrin sodium, and LPS+ultrasound groups. NLRP3 was overexpressed using plasmid transfection, with experimental groups including control, NLRP3 plasmid, negative control plasmid, and NLRP3 plasmid+SDT groups. SDT was applied to LPS-stimulated or NLRP3-overexpressing HL-1 cells. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were used to measure mRNA and protein levels of NLRP3, apoptosis-associated speck-like protein containing a CARD (ASC), Cleaved Caspase-1, IL-1β, IL-18, and CACNA1C. The NLRP3 inhibitor MCC950 was used to validate the relationship of NLRP3 and CACNA1C. The experimental groups included control, LPS, LPS+MCC950, and MCC950 groups. Intracellular reactive oxygen species (ROS) levels were detected using the probe DCFH-DA, and the ROS scavenger N-acetyl-L-cysteine (NAC) was used to test if the effects of SDT was ROS-dependent.Results:(1) In vivo: The LPS+SDT group exhibited a lower incidence of atrial fibrillation induction and a shorter duration of atrial fibrillation compared to the LPS group(both P<0.05). Protein expression levels of NLRP3 and IL-1β were lower than those in the LPS group (all P<0.05), while the expression of CACNA1C subunit tended to increase relative to the LPS group ( P>0.05). (2) In vitro: The safe concentration of LPS for administration was ≤20 μg/ml, with an optimal pro-inflammatory concentration of 4 μg/ml. The safe concentration of sinoporphyrin sodium for administration was 0.4 μmol/L, with an optimal incubation time of 4 hours. Compared to the LPS group or NLRP3 plasmid group, the LPS+SDT group or NLRP3 plasmid+SDT group exhibited lower expression levels of NLRP3, ASC, Cleaved Caspase-1, IL-1β, and IL-18, and higher mRNA and protein levels of CACNA1C (all P<0.05). The LPS+MCC950 group had higher CACNA1C protein expression than the LPS group ( P<0.05). SDT increased intracellular ROS levels, and NAC blocked the regulatory effects of SDT on NLRP3 and CACNA1C. Conclusion:SDT reduces atrial fibrillation susceptibility in mice by inhibiting NLRP3 inflammasome activation in atrial cardiomyocytes, thereby upregulating the L-type calcium channel subunit CACNA1C.

Objective:To evaluate the preservation efficacy of 7 non-inactivating virus preservation solutions.Methods:Equal amounts of H1N1 virus were added to 7 commercially available non-inactivating virus preservation solutions, and the samples were stored at -20 ℃, 4 ℃, 25 ℃ and 37 ℃ for 1 hour, 6 hours, 1 day, 3 days, and 5 days. The viral nucleic acid in each simulated sample under different storage conditions was measured using real-time quantitative PCR. The hemagglutination (HA) titer was determined through viral isolation culture and hemagglutination assay, comparing the differences in viral growth activity across different storage solutions and conditions.Results:Except for solution E, the other solutions effectively protected viral nucleic acid at the 4 storage temperatures. In terms of viral activity, solutions A, B, C, and D effectively maintained viral viability. A and B showing the best performance, E and F showed poorer performance, and G performed the worst.Conclusions:Most non-inactivating virus preservation solutions effectively protect viral nucleic acid, but there are significant differences in their ability to maintain viral viability. To ensure optimal virus preservation, it is recommended that medical institutions evaluate the effectiveness of preservation solutions before use.

Objective To investigate the impact of sleep modes on the risk for diseases of the body systems.Methods Based on a subset of UK Biobank dataset comprising 87 617 participants,3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer,that is sleep duration and onset,sleep rhythm(relative amplitude and stability),and sleep quality(sleep efficiency and number of awakenings).Latent profile analysis(LPA)was applied to identify and classify distinct sleep modes.Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.Results LPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups,the subgroup 4 had relatively optimal levels in above sleep indicators.Compared to the subgroup 4,the other 4 subgroups exhibited variations in different sleep dimensions,with at least one indicator demonstrating an unfavorable trend.These subgroups also revealed differences in racial composition,shift work and social deprivation index.Moreover,there were notable differences in the risk of various system diseases among the subgroups(P<0.05).When compared to the subgroup 4,the other 4 subgroups exhibited an elevated risk for certain diseases(comprising a total of 126 diseases),with the diseases of the circulatory system,digestive system and musculoskeletal system most common.Among the 5 subgroups,the subgroup 2(shorter sleep duration and later sleep onset)and the subgroup 5(rhythm disorder)had the highest counts of associated risks,amounting to 85 and 91 types,respectively,but there was certain difference in their systematic composition.Conclusion There are different sleep modes within the participants,and the modes are potentially associated with an increased risk for diseases of body systems.Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.