ObjectiveTo explore the potential mechanism of Xiaoqinglong Decoction （小青龙汤， XD） in the treatment of allergic rhinitis. MethodsForty-five rats were randomly assigned to a control group， a model group， a loratadine group， low-， medium- and high-dose XD groups， and low-， medium- and high-dose Mahuang Decoction and Cang'erzi Powder （麻黄汤合苍耳子散， MDCP） groups. Except for the control group， rats were administered with ovalbumin （OVA） and aluminum hydroxide via intraperitoneal injection for 14 days to establish an allergic rhinitis model. After the 14th-day injection， nasal stimulation was continued with 20 μl of 10% OVA solution to maintain the model. Rats in the control group and the model group received 10 ml/（kg·d） of saline， whereas those in the loratadine group were administered with 0.9 mg/（kg·d） of loratadine. The low-， medium- and high-dose XD groups were administered XD at the dose of 2.7， 5.4， and 10.8 g/（kg·d）， respectively. The low-， medium- and high-dose MDCP groups were administered MDCP at the dose of 2.43， 4.86， and 9.72 g/（kg·d）， respectively. All treatments were administered by gavage once daily for 7 consecutive days. One hour after the final gavage， nasal symptom scores were recorded for all group of rats. The next day， serum levels of immunoglobulin E （IgE）， interleukin-4 （IL-4）， and interleukin-13 （IL-13） were measured. HE staining was used to observe the pathological morphology of the nasal mucosal tissue. Quantitative reverse transcription PCR （RT-qPCR） and Western Blot were performed to assess mRNA and protein expression of thymic stromal lymphopoietin （TSLP） and OX40 ligand （OX40L） in the nasal mucosa. ResultsCompared to the control group， total nasal symptom score in the model group significantly increased （P＜0.01）. HE staining revealed disrupted and adhered cilia， thickened basement membranes， and extensive inflammatory cell infiltration in the nasal mucosa. Serum levels of total IgE， IL-4， and IL-13， as well as TSLP and OX40L mRNA and protein expression in the nasal mucosa， were significantly elevated in the model group （P＜0.05 or P＜0.01）. Compared to the model group， the total nasal symptom scores in all drug intervention groups were significantly reduced； the serum total IgE levels in the loratadine group， the low- and medium-dose XD groups， and the low- and high-dose MDCP groups were significantly reduced； and the serum levels of IL-4 and IL-13 in the high-dose XD group and the high-dose MDCP group decreased （P＜0.05 or P＜0.01）. Nasal mucosal structure was improved. Except for the low-dose MDCP group， all other intervention groups showed a significant reduction in TSLP and OX40L mRNA expression in the nasal mucosa （P＜0.01）. All doses of XD and the medium- and high-dose MDCP groups significantly decreased the protein levels of TSLP and OX40L （P＜0.05）. The medium-dose XD group exhibited more improvement of nasal symptom scores and greater suppression of expression of TSLP and OX40L mRNA， and TSLP protein levels compared to the loratadine group （P＜0.05）. ConclusionXD may protect nasal mucosa of rats and alleviate allergic rhinitis by suppressing the TSLP/OX40L pathway， thereby attenuating Th2-mediated immune responses.

ObjectiveTo explore the potential mechanism of Xiaoqinglong Decoction （小青龙汤， XD） in the treatment of allergic rhinitis. MethodsForty-five rats were randomly assigned to a control group， a model group， a loratadine group， low-， medium- and high-dose XD groups， and low-， medium- and high-dose Mahuang Decoction and Cang'erzi Powder （麻黄汤合苍耳子散， MDCP） groups. Except for the control group， rats were administered with ovalbumin （OVA） and aluminum hydroxide via intraperitoneal injection for 14 days to establish an allergic rhinitis model. After the 14th-day injection， nasal stimulation was continued with 20 μl of 10% OVA solution to maintain the model. Rats in the control group and the model group received 10 ml/（kg·d） of saline， whereas those in the loratadine group were administered with 0.9 mg/（kg·d） of loratadine. The low-， medium- and high-dose XD groups were administered XD at the dose of 2.7， 5.4， and 10.8 g/（kg·d）， respectively. The low-， medium- and high-dose MDCP groups were administered MDCP at the dose of 2.43， 4.86， and 9.72 g/（kg·d）， respectively. All treatments were administered by gavage once daily for 7 consecutive days. One hour after the final gavage， nasal symptom scores were recorded for all group of rats. The next day， serum levels of immunoglobulin E （IgE）， interleukin-4 （IL-4）， and interleukin-13 （IL-13） were measured. HE staining was used to observe the pathological morphology of the nasal mucosal tissue. Quantitative reverse transcription PCR （RT-qPCR） and Western Blot were performed to assess mRNA and protein expression of thymic stromal lymphopoietin （TSLP） and OX40 ligand （OX40L） in the nasal mucosa. ResultsCompared to the control group， total nasal symptom score in the model group significantly increased （P＜0.01）. HE staining revealed disrupted and adhered cilia， thickened basement membranes， and extensive inflammatory cell infiltration in the nasal mucosa. Serum levels of total IgE， IL-4， and IL-13， as well as TSLP and OX40L mRNA and protein expression in the nasal mucosa， were significantly elevated in the model group （P＜0.05 or P＜0.01）. Compared to the model group， the total nasal symptom scores in all drug intervention groups were significantly reduced； the serum total IgE levels in the loratadine group， the low- and medium-dose XD groups， and the low- and high-dose MDCP groups were significantly reduced； and the serum levels of IL-4 and IL-13 in the high-dose XD group and the high-dose MDCP group decreased （P＜0.05 or P＜0.01）. Nasal mucosal structure was improved. Except for the low-dose MDCP group， all other intervention groups showed a significant reduction in TSLP and OX40L mRNA expression in the nasal mucosa （P＜0.01）. All doses of XD and the medium- and high-dose MDCP groups significantly decreased the protein levels of TSLP and OX40L （P＜0.05）. The medium-dose XD group exhibited more improvement of nasal symptom scores and greater suppression of expression of TSLP and OX40L mRNA， and TSLP protein levels compared to the loratadine group （P＜0.05）. ConclusionXD may protect nasal mucosa of rats and alleviate allergic rhinitis by suppressing the TSLP/OX40L pathway， thereby attenuating Th2-mediated immune responses.

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.

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.

This paper focuses on extreme environments and systematically analyzes sleep disorders caused by multiple pathogenesis,including circadian rhythm disorder,yin-yang imbalance and qi-blood disorder under weightlessness,emotional depression due to environmental changes,abnormal diet and excretion,and six excesses pathogenic factors,in accordance with the theory of correspondence between nature and human.It proposes harmonizing yin and yang as the core therapeutic principle and guiding framework,with specific methods including calming rebellious qi-blood,regulating qi movement,harmonizing heart and kidney,and dredging and regulating blood vessels,thus forming the"one guiding principle and four specific methods"treatment strategy.Additionally,by integrating the modified application of classic formulas,a diagnostic and therapeutic approach targeting multi-dimensional pathogenesis is established.This study aims to promote the in-depth integration of Traditional Chinese Medicine(TCM)in extreme environmental medicine through TCM theories and innovative application of prescriptions,provide TCM-characterized solutions for health management of workers in extreme environments,and facilitate the transformation of extreme environmental medicine toward the modern medical model of"prevention-treatment integration".

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.