ObjectiveTo investigate the effect and mechanism of modified Sini San in ameliorating intestinal mucosal barrier by observing its effects on short chain fatty acids （SCFAs） and high mobility group protein B1 （HMGB1）/receptor of advanced glycation end products （RAGE） signaling pathways in chronic stress rats. MethodsThe 50 male SD rats were randomly divided into control group，model group，low-dose modified Sini San group （7.34 g·kg^-1·d^-1），high-dose modified Sini San group （14.68 g·kg^-1·d^-1），and Fructo-oligosaccharides group （3.15 g·kg^-1·d^-1），with 10 rats in each group. Except for the control group，all other groups were subjected to chronic unpredictable stress/social isolation to create a chronic stress model for 6 weeks. After 4 weeks of modeling，each treatment group was given corresponding drugs by gavage for 2 weeks while modeling. The control group and model group were given the same volume of physiological saline. The effects of Modified Sini San on behaviors，body weight，Bristol score in feces and fecal moisture content in chronic stress rats were observed. Hematoxylin and eosin （HE） staining was used to observe the pathological changes in the cecum. The content of SCFAs in the cecal contents of rats were detected by Gas chromatography-mass spectrometry （GC-MS）. Immunohistochemistry and Western blot were used to detect the expression of HMGB1/RAGE pathway related proteins in cecal tissue. The levels of ZO-1，Occludin，and Claudin-1 in the cecal tissue were detected by enzyme linked immunosorbent assay （ELISA）. ResultsCompared with the model group，the sucrose preference rate，total distance traveled and the number of grid crossings in the open field test of rats in the low-dose modified Sini San group were obviously increased （P<0.05， P<0.01），and the immobility time in the open field test and the immobility time in the forced swimming test of rats in the low-dose and high-dose modified Sini San groups were obviously reduced （P<0.05， P<0.01）. Meanwhile，the Bristol score and fecal moisture content of rats in the low and high dose groups of modified Sini San were obviously increased （P<0.05）. The low-dose group of modified Sini San had intact mucosal layer structure in the cecal tissue and reduced infiltration of inflammatory cells. The content of SCFAs in the cecal contents increased，with a obviously increase in the content of acetic acid，propionic acid，butyric acid，and isovaleric acid （P<0.05， P<0.01） and the expression levels of HMGB1，RAGE，Toll-like receptor 2（TLR2），Toll-like receptor 4（TLR4），tumor necrosis factor-α（TNF-α），and nuclear factor kappa-B p65（NF-κB p65） proteins in cecal tissue were significantly decreased （P<0.05， P<0.01） in low-dose group of modified Sini San. Meanwhile，the contents of ZO-1，Occludin，and Claudin-1 in the cecal tissue were obviously increased （P<0.01） in low-dose group of modified Sini San. ConclusionModified Sini San can improve the function of intestinal mucosal barrier in chronic stress rats by increasing the content of SCFAs in the intestine and inhibiting the HMGB1/RAGE pathway.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

The chemical components of Carthami Flos were investigated by using macroporous resin, silica gel column chromatography, reversed-phase octadecylsilane(ODS) column chromatography, Sephadex LH-20, and semi-preparative high-performance liquid chromatography(HPLC). The planar structures of the compounds were established based on their physicochemical properties and ultraviolet-visible(UV-Vis), infrared(IR), high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), and nuclear magnetic resonance(NMR) spectroscopic technology. The absolute configurations were determined by comparing the calculated and experimental electronic circular dichroism(ECD). Six flavonoid C-glycosides were isolated from the 30% ethanol elution fraction of macroporous resin obtained from the 95% ethanol extract of Carthami Flos, and identified as saffloquinoside F(1), 5-hydroxysaffloneoside(2), iso-5-hydroxysaffloneoside(3), isosafflomin C(4), safflomin C(5), and vicenin 2(6). Among these, the compounds 1 to 3 were new chalcone C-glycosides. The compounds 1, 2, 4, and 5 could significantly increase the viability of H9c2 cardiomyocytes damaged by oxygen-glucose deprivation/reoxygenation(OGD/R) at a concentration of 50 μmol·L~(-1), showing their good cardioprotective activity.
Glycosides/pharmacology* ; Flowers/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Carthamus tinctorius/chemistry* ; Chalcones/pharmacology* ; Animals

BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiovascular diseases, affecting vital organs such as the heart, brain, and kidneys. Our goal is to predict the risk of new onset hypertension using machine learning algorithms and identify the characteristics of patients with new onset hypertension. METHODS: We analyzed data from the 2011 China Health and Nutrition Survey cohort of individuals who were not hypertensive at baseline and had follow-up results available for prediction by 2015. We tested and evaluated the performance of four traditional machine learning algorithms commonly used in epidemiological studies: Logistic Regression, Support Vector Machine, XGBoost, LightGBM, and two deep learning algorithms: TabNet and AMFormer model. We modeled using 16 and 29 features, respectively. SHAP values were applied to select key features associated with new onset hypertension. RESULTS: A total of 4,982 participants were included in the analysis, of whom 1,017 developed hypertension during the 4-year follow-up. Among the 16-feature models, Logistic Regression had the highest AUC of 0.784(0.775∼0.806). In the 29-feature prediction models, AMFormer performed the best with an AUC of 0.802(0.795∼0.820), and also scored the highest in MCC (0.417, 95%CI: 0.400∼0.434) and F1 (0.503, 95%CI: 0.484∼0.505) metrics, demonstrating superior overall performance compared to the other models. Additionally, key features selected based on the AMFormer, such as age, province, waist circumference, urban or rural location, education level, employment status, weight, WHR, and BMI, played significant roles. CONCLUSION We used the AMFormer model for the first time in predicting new onset hypertension and achieved the best results among the six algorithms tested. Key features associated with new onset hypertension can be determined through this algorithm. The practice of machine learning algorithms can further enhance the predictive efficacy of diseases and identify risk factors for diseases.
Humans ; China/epidemiology* ; Hypertension/diagnosis* ; Machine Learning ; Male ; Female ; Middle Aged ; Adult ; Nutrition Surveys ; Algorithms ; Aged ; Risk Factors

Aim To investigate the role of corylin in angiotensin Ⅱ(Ang Ⅱ)-induced cardiomyocyte hy-pertrophy and its underlying mechanisms.Methods An Ang Ⅱ-induced cardiomyocyte hypertrophy model was established and treated with corylin.Real-time PCR was employed to assess hypertrophic gene mRNA expression,and immunofluorescence was used to meas-ure cardiomyocyte surface area.Western blot and en-zyme activity assay kits were used to evaluate SIRT1 expression and activity.Results Corylin markedly mitigated Ang Ⅱ-induced hypertrophic gene expression and cardiomyocyte surface area enlargement.Moreo-ver,it prevented the Ang Ⅱ-mediated decline in SIRT1 protein levels and deacetylase activity.Further investi-gation indicated that corylin inhibited Ang Ⅱ-driven NF-κB transcriptional activity and the expression of its downstream target genes,such as TNF-α,IL-6,and IL-1β.Notably,SIRT1 silencing abolished the protective effects of corylin against cardiomyocyte hypertrophy,as well as its regulation of the SIRT1/NF-κB signaling pathway.Conclusion Corylin suppresses cardiomyo-cyte hypertrophy by modulating the SIRT1-dependent NF-κB signaling pathway.

This study predicts the quality markers(Q-markers) for the cough-relieving and phlegm-expelling effects of Kening Granules based on pharmacodynamics, plasma drug chemistry, network pharmacology, and pharmacokinetics. Strong ammonia solution spray and phenol red secretion assays were employed to evaluate the cough-relieving and phlegm-expelling effects of Kening Granules. Twentysix absorbed prototype components of Kening Granules were identified by ultra high performance liquid chromatography coupled with QExactive Plus quadrupole/Orbitrap high resolution mass spectrometry(UHPLC-Q-Exactive Plus Orbitrap HRMS). Through network pharmacology, 11 potential active components were screened out for the cough-relieving and phlegm-expelling effects of Kening Granules. The 11 components acted on 40 common targets such as IL6, TLR4, and STAT3, which mainly participated in PI3K/Akt, HIF-1, and EGFR signaling pathways. Pharmacokinetic quantitative analysis was performed for 7 prototype components. Three compounds including azelaic acid, caffeic acid, and vanillin were identified as Q-markers for the cough-relieving and phlegm-expelling effects of Kening Granules based on their effectiveness, transmissibility, and measurability. The results of this study are of great significance for clarifying the pharmacological substance basis, optimizing the quality standards, and promoting the clinical application of Kening Granules.
Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Cough/blood* ; Male ; Humans ; Animals ; Rats ; Rats, Sprague-Dawley ; Biomarkers/blood* ; Quality Control ; Chromatography, High Pressure Liquid ; Antitussive Agents/chemistry*

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

Objective To verify the accuracy of a Non-Contact Sleep Monitoring Mattress(NCSMM)based on body movement during sleep in assessing sleep quality of patients before neurosurgery in order to provide a more portable and efficient assessment tool for clinical staff.Methods A single-arm trial was conducted on 114 inpatients admitted in our department selected with convenience sampling.Sleep quality data of 1 night were collected through 5 sleep quality assessment tools,including NCSMM,polysomnography(PSG),Patient-Reported Outcome Measurement Information System(PROMIS)Sleep Disturbance scale,Richards-Campbell Sleep Scale(RCSQ),and a wearable device(smart watch for body movements and sleep quality monitoring).The sleep efficiency(≤85%)obtained by PSG was used as the diagnostic standard for sleep disorders.The area under the receiver operating characteristic curve(AUC),sensitivity,specificity,positive predictive value,negative predictive value,and Youden index were calculated for the other 4 tools to evaluate and compare their diagnostic effectiveness.Results The AUC value for NCSMM,PROMIS,RCSQ and smart watch was 0.788(95%CI:0.687～0.888,P<0.001),0.664(95%CI:0.543～0.784,P=0.02),0.723(95%CI:0.600～0.846,P=0.001)and 0.750(95%CI:0.654～0.846,P<0.001),respectively.The diagnostic accuracy rate was 0.774,0.559,0.742 and 0.602,with corresponding Youden index value of 0.488,0.321,0.456,and 0.459.NCSMM demonstrated the best AUC value,sensitivity and Youden index when compared with the other 3 tools.Conclusion NCSMM shows high accuracy in assessing sleep quality in pre-neurosurgery inpatients,and it is a viable portable and efficient assessment tool in clinical practice.

Objective:To explore the differences between the Phoenix sepsis scoring system including Phoenix sepsis score (PSS) and Phoenix-8 organ dysfunction score (hereinafter referred to as Phoenix-8) and the commonly used pediatric sepsis scores in evaluating clinical characteristics and prognostic analysis of pediatric patients with severe sepsis diagnosed under traditional standards, namely the diagnostic criteria from the 2005 International Pediatric Sepsis Consensus Conference.Methods:This study was a retrospective observational study. From December 2020 to March 2023, 202 pediatric patients with severe sepsis meeting the inclusion criteria were admitted to the Children's Hospital of Nanjing Medical University. Based on the sepsis diagnostic criteria outlined in the International Consensus Criteria for Pediatric Sepsis and Septic Shock (2024), the pediatric patients were categorized into a sepsis group and a non-sepsis group. Sepsis group was further subdivided into a death subgroup and a survival subgroup based on the outcomes. The age, hospitalization costs, disease outcome indicators (e.g., mortality rate and incidence of septic shock), major organ (e.g., heart, liver, lungs, and kidneys) damage and their correlations, as well as PSS, Phoenix-8 and commonly used pediatric sepsis scores (e.g., pediatric sequential organ failure assessment (pSOFA), pediatric risk of mortality score Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 score (PELOD-2), pediatric multiple organ dysfunction score (P-MODS), pediatric critical illness score (PCIS), and pediatric early warning score (PEWS)) were collected and compared. Receiver operating characteristic (ROC) curve and precision-recall curve were plotted to evaluate the predictive ability of PSS, Phoenix-8, and commonly used pediatric sepsis scores for mortality risk in pediatric patients with severe sepsis under traditional standards. Predictive performance was quantified using the area under the ROC curve (AUROC). Univariate logistic regression analysis was employed to quantify the odds ratios of PSS and Phoenix-8 for predicting mortality risk. Patients with severe sepsis under traditional standards were further stratified into subgroups based on complications and comorbidities, including central nervous system (CNS) diseases, multiple infections, cardiovascular system diseases, shock, and malignancies. The Hosmer-Lemeshow goodness-of-fit test was used to assess calibration of PSS and Phoenix-8, and the DeLong test was used to compare whether there were statistically significant differences in the AUROC of PSS and Phoenix-8 for predicting mortality risk among different subgroups of pediatric patients. Results:Compared with those in non-sepsis group, pediatric patients in sepsis group were significantly older ( Z=-2.92, P<0.05) with higher incidences of septic shock and mortality, hospitalization costs, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, PSS, and Phoenix-8 (with χ2 values of 21.28 and 13.64, respectively, Z values of -1.99, -5.33, -5.10, -8.55, -6.91, -10.98, and -9.93, respectively, P<0.05), and lower PCIS ( Z=-3.34, P<0.05). Compared with those in survival subgroup, hospitalization costs, PSS, Phoenix-8, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, and P-MODS of pediatric patients in death subgroup was significantly higher (with Z values of -2.50, -3.50, -2.47, -5.11, -3.84, -2.94, -3.61, and -3.04, respectively, P<0.05). Compared with those in survival subgroup, the incidences of lung damage and liver damage of pediatric patients in death subgroup were also significantly higher (with χ2 values of 6.20 and 10.94, respectively, P<0.05), and 64.7% (97/150) of patients exhibited two or more concurrent organ damage. For predicting mortality risk in pediatric patients with severe sepsis under traditional standards, the AUROC values for PRISM Ⅲ, PCIS, PEWS, pSOFA, PELOD-2, P-MODS, PSS, and Phoenix-8 were approximately 0.70, with optimal cutoff values of 17.5, 91.0, 5.5, 4.5, 2.5, 4.5, 3.5, and 4.5, respectively; PELOD-2 demonstrated the highest sensitivity (0.83); while PRISM Ⅲ, PSS, and Phoenix-8 showed high specificity (>0.80). Univariate logistic regression analysis showed that for every 1-point increase in the PSS within 24 hours of pediatric intensive care unit admission, the relative risk of mortality increased by 63.7% (with odds ratio of 1.64, 95% confidence interval of 1.34-1.99, P<0.05). Similarly, for every 1-point increase in the Phoenix-8, the relative risk of mortality increased by 37.5% (with odds ratio of 1.38, 95% confidence interval of 1.18-1.60, P<0.05). The AUROC values (around 0.80) of PSS and Phoenix-8 for predicting mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases were relatively high. In contrast, the AUROC values (0.60-0.80) for predicting mortality risk in pediatric patients with severe sepsis combined with shock or malignant tumors were moderate. All models passed the Hosmer-Lemeshow goodness-of-fit test ( P>0.05). The DeLong test indicated no statistically significant differences in predictive ability between PSS and Phoenix-8 across subgroups of pediatric patients ( P>0.05). Conclusions:PSS and Phoenix-8 exhibited higher specificity than most of the commonly used pediatric sepsis scores in predicting mortality risk under traditional standards. Both scores performed much better in predicting the mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases.