High-performance liquid chromatography(HPLC) was used to determine the content of three major components in Citri Reticulatae Semen(CRS), including limonin, nomilin, and obacunone. The chromaticity of the CRS sample during salt processing and stir-frying was measured using a color difference meter. Next, the relationship between the color and content of the salt-processed CRS sample was investigated through correlation analysis. By integrating the oil bath technique for processing simulation with HPLC, the changes in the relative content of nomilin and its transformation products were analyzed, with its structural transformation pattern during processing identified. Additionally, RAW264.7 cells were induced with lipopolysaccharides(LPSs) to establish an inflammatory model, and the anti-inflammatory activity of nomilin and its transformation product, namely obacunone was evaluated. The results indicated that as processing progressed, E~*ab and L~* values showed a downward trend; a~* values exhibited a slow increase over a certain period, followed by no significant changes, and b~* values remained stable with no significant changes over a certain period and then started to decrease. The limonin content remained barely unchanged; the nomilin content decreased, and the obacunone increased significantly. The changing trends in content and color parameters during salt-processing and stir-frying were basically consistent. The content of nomilin and obacunone was significantly correlated with the colorimetric values(L~*, a~*, b~*, and E~*ab), while limonin content showed no significant correlation with these values. By analyzing HPLC patterns of nomylin at different heating temperatures and time, it was found that under conditions of 200-250 ℃ for heating of 5-60 min, the content of nomilin significantly decreased, while the obacunone content increased pronouncedly. The in vitro anti-inflammatory activity results indicated that compared to the model group, the group with a high concentration of nomilin and the groups with varying concentrations of obacunone showed significantly reduced release of nitric oxide(NO)(P<0.01). When both were at the same concentration, obacunone showed better performance in inhibiting NO release. In this study, the obvious correlation between the color and content of major components during the processing of CRS samples was identified, and the dynamic patterns of quality change in CRS samples during processing were revealed. Additionally, the study revealed and confirmed the transformation of nomilin into obacunone during processing, with the in vitro anti-inflammatory activity of obacunone significantly greater than that of nomilin. These findings provided a scientific basis for CRS processing optimization, tablet quality control, and its clinical application.
Mice ; Animals ; Drugs, Chinese Herbal/pharmacology* ; RAW 264.7 Cells ; Limonins/chemistry* ; Chromatography, High Pressure Liquid ; Citrus/chemistry* ; Color ; Benzoxepins/chemistry* ; Anti-Inflammatory Agents/chemistry*

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Chronic heart failure(CHF)is the end-stage of a variety of heart diseases with complex pathogenesis,which may involve myocardial fibrosis,inflammation reaction and oxidative stress.Chinese materia medica has the characteristics of multiple pathways,levels,and targets in the treatment of CHF,with significant therapeutic effects.Based on the TCM theories,this article described the research progress of TCM and its effective components,TCM compounds and Chinese patent medicines in regulating TGF-β signaling pathway in the treatment of CHF,and summarized the mechanism and target of TCM regulating TGF-β pathway in the treatment of CHF,including inhibiting myocardial fibrosis,reducing inflammatory reaction and apoptosis,so as to provide a reference for the related research of Chinese materia medica in the treatment of CHF.

Objective To explore the risk factors for 28-day mortality of sepsis-associated acute kidney injury(SA-AKI)patients and to develop a nomogram risk prediction model.Methods A retrospective cohort study was conducted,involving 184 patients with SA-AKI admitted to the intensive care unit(ICU)of the 940th Hospital of Joint Logistic Support Force of PLA between January 2017 and December 2022.Patients were categorized into survival(n=135)and non-survival(n=49)groups based on 28-day mortality.Clinical data were collected,and statistically significant risk factors were preliminarily screened.Multivariate stepwise logistic regression analysis was performed to identify independent risk factors for 28-day mortality of SA-AKI patients.A nomogram predictive model was constructed using these factors,and internally validated with the Bootstrap method.The receiver operating characteristic curve(ROC curve)was drawn,and the area under the ROC curve(AUC)was calculated to verify the predictive value and accuracy of the model.Results The 28-day mortality rate among 184 SA-AKI patients was 26.6％(49/184).Multivariate stepwise logistic regression analysis identified multiple organ dysfunction syndrome(MODS)(OR=16.393,95％CI 4.317-62.254,P＜0.001),high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(OR=1.097,95％CI 1.036-1.161,P=0.002),low oxygenation index(OR=0.992,95％CI 0.986-0.998,P=0.015),low neutrophil count(OR=0.912,95％CI 0.860-0.968,P=0.002)and low fibrinogen concentration(OR=0.733,95％CI 0.549-0.978,P=0.034)as independent risk factors.The prediction model equation was P=1/1+e-logit(P),logit(P)=-1.626+2.797×MODS+0.092×AP ACHE Ⅱ+(-0.311)×fibrinogen+(-0.092)×neutrophil count+(-0.008)×oxygenation index.Internal validation with 1000 Bootstrap resamples showed high consistency between predicted and actual values.ROC analysis showed an AUC of 0.911(95％CI 0.868-0.955,P＜0.05)for the model,with 93.9％sensitivity and 78.5％specificity at a cut-off of 0.194.The Hosmer-Lemeshow test confirmed good calibration(P=0.62),and decision-making curve analysis demonstrated clinical utility within the high-risk threshold range(0.1-0.9).Conclusions MODS,high APACHE Ⅱ score,low oxygenation index,low neutrophil count,and low fibrinogen concentration are independent risk factors for 28-day mortality in SA-AKI patients.The developed nomogram risk prediction model may provide important guidance for predicting 28-day mortality in SA-AKI patients.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

OBJECTIVE To explore the effects of meropenem exposure and degradation levels on clinical efficacy in patients with purulent meningitis （PM）. METHODS A total of 131 PM patients treated with meropenem at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2022 to June 2025 were prospectively included. Relevant data were collected and divided into a cured group （91 cases） and a non-cured group （40 cases） based on the efficacy. High-performance liquid chromatography-tandem mass spectrometry was used to determine the concentration of meropenem and its open-loop metabolites. Risk factors that affect efficacy were screened， and their predictive power and correlation were evaluated by univariate analysis， and multivariate Logistic regression analysis， receiver operating characteristic （ROC） curves， and correlation analysis. RESULTS Univariate analysis showed that serum creatinine， creatinine clearance rate， minimum inhibitory concentration of meropenem ≥16 μg/mL， cerebrospinal fluid red blood cell count， cerebrospinal fluid white blood cell count， cerebrospinal fluid glucose content， blood trough concentration， blood open-loop metabolite concentration/trough concentration ratio， and intrathecal injection were all correlated with efficacy （P＜0.05）. The results of multiple Logistic regression analysis showed that serum creatinine blood open-loop metabolite concentration/trough concentration ratio， intrathecal injection， and cerebrospinal fluid glucose content were influencing factors for suboptimal anti-infective ltt efficacy （P＜0.05）. ROC curve analysis showed that when the blood open-loop metabolite concentration/trough concentration ratio was greater than 2.854 （AUC＝0.647）， serum creatinine was less than 59.5 μmol/L （AUC＝0.647）， and cerebrospinal fluid glucose content was less than 3.37 mmol/L （AUC＝0.709）， the risk of treatment failure significantly increased （P＜0.05）. Correlation analysis showed that the blood trough concentration of meropenem was positively correlated with the concentration of its open-loop metabolites （R 2＝0.134 5， P＜0.000 1）. CONCLUSIONS Insufficient exposure level and rapid degradation of meropenem are key mechanisms affecting the anti-infective efficacy of PM. Elevated blood open-loop metabolite concentration/ trough concentration ratio， low serum creatinine level， lack of intrathecal injection， and low cerebrospinal fluid glucose content are independent risk factors for poor efficacy.

A deep learning based microwave imaging model which can directly map the scattered electric field to the dielectric property distribution image of the target object is developed,and its potential for medical applications is explored.The two-dimensional time-domain finite difference method is used for numerical simulation to obtain a dataset of scattered electric fields;a deep convolutional autoencoder based imaging model is constructed to perform imaging studies on two types of target objects;the imaging results are quantitatively evaluated using relative error,and the model's ability to distinguish different types of strokes is also analyzed.The results show that the imaging network based on deep convolutional autoencoder exhibits excellent imaging performance when processing both numerical models.For simple objects,the model can accurately locate and preliminarily reconstruct the shape of the object,with an average relative error of 0.3012,while for the stroke models,it can effectively reconstruct the location and shape of the stroke area,and preliminarily reconstruct other brain tissues,with an average relative error of 0.077 8.The microwave imaging network based on deep convolutional autoencoder has great promise for fast and accurate image reconstruction,and the numerical example of stroke detection demonstrates its significant application potential in biomedical imaging.

A deep learning based microwave imaging model which can directly map the scattered electric field to the dielectric property distribution image of the target object is developed,and its potential for medical applications is explored.The two-dimensional time-domain finite difference method is used for numerical simulation to obtain a dataset of scattered electric fields;a deep convolutional autoencoder based imaging model is constructed to perform imaging studies on two types of target objects;the imaging results are quantitatively evaluated using relative error,and the model's ability to distinguish different types of strokes is also analyzed.The results show that the imaging network based on deep convolutional autoencoder exhibits excellent imaging performance when processing both numerical models.For simple objects,the model can accurately locate and preliminarily reconstruct the shape of the object,with an average relative error of 0.3012,while for the stroke models,it can effectively reconstruct the location and shape of the stroke area,and preliminarily reconstruct other brain tissues,with an average relative error of 0.077 8.The microwave imaging network based on deep convolutional autoencoder has great promise for fast and accurate image reconstruction,and the numerical example of stroke detection demonstrates its significant application potential in biomedical imaging.

Chronic heart failure(CHF)is the end-stage of a variety of heart diseases with complex pathogenesis,which may involve myocardial fibrosis,inflammation reaction and oxidative stress.Chinese materia medica has the characteristics of multiple pathways,levels,and targets in the treatment of CHF,with significant therapeutic effects.Based on the TCM theories,this article described the research progress of TCM and its effective components,TCM compounds and Chinese patent medicines in regulating TGF-β signaling pathway in the treatment of CHF,and summarized the mechanism and target of TCM regulating TGF-β pathway in the treatment of CHF,including inhibiting myocardial fibrosis,reducing inflammatory reaction and apoptosis,so as to provide a reference for the related research of Chinese materia medica in the treatment of CHF.

Objective To construct and validate a nomogram prognostic model for elderly patients with chronic heart failure(CHF)based on echocardiographic parameters and serological indica-tors.Methods A total of 110 elderly CHF patients admitted to the First Affiliated Hospital of Guizhou University of Chinese Medicine from January 2021 to January 2023 were recruited and randomly divided into a modeling group(80 cases)and a validation group(30 cases).According to the prognosis,the patients in the modeling group were divided into good prognosis subgroup(57 cases)and poor prognosis subgroup(23 cases).Echocardiographic parameters and serological indi-cators were collected to analyze the factors affecting poor prognosis in elderly CHF patients,and then a risk-prediction nomogram model was drawn and verified.Results The patients of poor prognosis had significantly higher values of left ventricular end-diastolic diameter(LVEDD)and left ventricular end systolic diameter(LVESD)and serum levels of soluble growth stimulation ex-pressed gene 2(sST2),N-terminal pro-B-type natriuretic peptide(NT-proBNP)and cardiac tro-ponin T(cTnT),and lower left ventricular ejection fraction(LVEF)value than the good progno-sis group(P＜0.01).Multivariate logistic regression analysis showed that LVEDD,LVESD,LVEF,sST2,NT-proBNP and cTnT were all factors influencing poor prognosis in elderly CHF patients(P＜0.01).The AUC value,sensitivity and specificity of the constructed risk nomogram model based on the above influencing factors were 0.788,83.61％and 80.59％,respectively.Hosmer-Lemeshow test reveal x2=4.115,P=0.894.The results of decision curve analysis(DCA)dis-played that the benefit was higher when the threshold probability ranged from 17％-96％,and the model could select larger range of the threshold probability.Conclusion LVEDD,LVESD,LVEF,sST2,NT-proBNP and cTnT are all associated with poor prognosis in elderly CHF pa-tients.Our risk nomogram model for poor prognosis in elderly CHF patients based on the above factors has good accuracy and discriminability.