ObjectiveTo investigate the value of different noninvasive diagnostic models in the diagnosis of esophageal and gastric varices since there is a high risk of esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and to provide a basis for the early diagnosis of esophageal and gastric varices. MethodsA total of 108 patients with significant portal hypertension due to compensated hepatitis B cirrhosis who attended Guangdong Provincial Hospital of Traditional Chinese Medicine from November 2017 to November 2023 were enrolled， and according to the presence or absence of esophageal and gastric varices under gastroscopy， they were divided into esophageal and gastric varices group （GOV group） and non-esophageal and gastric varices group （NGOV group）. Related data were collected， including age， sex， imaging findings， and laboratory markers. The chi-square test was used for comparison of categorical data between groups； the least significant difference t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. The receiver operating characteristic （ROC） curve was plotted to evaluate the diagnostic value of five scoring models， i.e.， fibrosis-4 （FIB-4）， LOK index， LPRI， aspartate aminotransferase-to-platelet ratio index （APRI）， and aspartate aminotransferase/alanine aminotransferase ratio （AAR）. The binary logistic regression method was used to establish a combined model， and the area under the ROC curve （AUC） was compared between the combined model and each scoring model used alone. The Delong test was used to compare the AUC value between any two noninvasive diagnostic models. ResultsThere were 55 patients in the GOV group and 53 patients in the NGOV group. Compared with the NGOV group， the GOV group had a significantly higher age （52.64±1.44 years vs 47.96±1.68 years， t=0.453， P<0.05） and significantly lower levels of alanine aminotransferase ［42.00 （24.00 — 17.00） U/L vs 82.00 （46.00 — 271.00） U/L， Z=-3.065， P<0.05］， aspartate aminotransferase ［44.00 （32.00 — 96.00） U/L vs 62.00 （42.50 — 154.50） U/L，Z=-2.351， P<0.05］， and platelet count ［100.00 （69.00 — 120.00）×10⁹/L vs 119.00 （108.50 — 140.50）×10⁹/L， Z=-3.667， P<0.05］. The ROC curve analysis showed that FIB-4， LOK index， LPRI， and AAR used alone had an accuracy of 0.667， 0.681， 0.730， and 0.639， respectively， in the diagnosis of esophageal and gastric varices （all P<0.05）， and the positive diagnostic rates of GOV were 69.97%， 65.28%， 67.33%， and 58.86%， respectively， with no significant differences in AUC values （all P>0.05）， while APRI used alone had no diagnostic value （P>0.05）. A combined model （LAF） was established based on the binary logistic regression analysis and had an AUC of 0.805 and a positive diagnostic rate of GOV of 75.80%， with a significantly higher AUC than FIB-4， LOK index， LPRI， and AAR used alone （Z=-2.773，-2.479，-2.206， and-2.672， all P<0.05）. ConclusionFIB-4， LOK index， LPRI， and AAR have a similar diagnostic value for esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and APRI alone has no diagnostic value. The combined model LAF had the best diagnostic efficacy， which provides a certain reference for clinical promotion and application.

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

Objective: To explore the distribution of traditional Chinese medicine (TCM) syndromes in patients with interstitial lung disease (ILD) and its influencing factors. Methods: This cross-sectional study included 385 patients with ILD admitted to the First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine) from January 2018 to June 2022. Data on sex, age, body mass index, smoking history, respiratory rate, hospitalization time, treatment cost, whether velcro rales can be heard, comorbidities with rheumatic immune diseases, TCM four examination information, and clinical examination results, including CT imaging, D-dimer level, and lung function-related indicators, were collected. The distribution pattern of TCM syndromes in patients with ILD and the association between TCM syndromes and clinical indicators were analyzed using the cluster analysis and binary Logistic regression analysis. Results: Among the 385 patients with ILD, sticky phlegm (59.74%) and shortness of breath (56.10%) were common symptoms, while greasy tongue coating (55.32%), red tongue (52.73%), and slippery and rapid pulse (25.71%) were common tongue and pulse manifestations. The patients were divided into five syndromes using cluster analysis: syndrome of phlegm-heat stagnation in the lung (36.62%), syndrome of turbid phlegm obstructing lung (29.35%), syndrome of deficiency of both qi and yin (12.99%), syndrome of qi deficiency of lung and kidney (11.95%), and syndrome of phlegm and blood stasis obstructing lung (9.09%). The D-dimer level was lower in patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of qi deficiency of lung and kidney than in those with syndrome of phlegm and blood stasis obstructing lung (P<0.05). The percentage of predicted forced vital capacity (FVC%pred) of patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of phlegm and blood stasis obstructing lung was higher than in those with syndrome of qi deficiency of lung and kidney (P<0.05). Among patients aged 60 and above, those with syndrome of phlegm-heat stagnation in the lung, syndrome of phlegm and blood stasis obstructing lung, and syndrome of deficiency of both qi and yin containing dual pathogenic syndrome elements were more likely to experience moderate to severe pulmonary diffusion impairment than those with syndrome of turbid phlegm obstructing lung and syndrome of qi deficiency of lung and kidney containing single pathogenic syndrome elements (P<0.05). The Logistic regression showed that the FVC%pred was an influential factor for syndrome of qi deficiency of lung and kidney, and the area under the receiver operating characteristic (ROC) curve (AUC) between FVC%pred and the formation of syndrome of qi deficiency of lung and kidney was 0.676 (95%CI: 0.598-0.755), P=0.002. The sensitivity was 0.431, the specificity was 0.966, and the best threshold on the ROC curve of 0.397 was 79.1%. The D-dimer level was an influential factor in the formation of syndrome of phlegm and blood stasis obstructing lung. The AUC between D-dimer level and the formation of syndrome of phlegm and blood stasis obstructing lung was 0.729 (95%CI: 0.655-0.802), P<0.001. The sensitivity was 0.914, the specificity was 0.523, and the best threshold on the ROC curve of 0.437 was 0.675 mg/L. Conclusion syndrome of phlegm-heat stagnation in the lung and syndrome of turbid phlegm obstructing lung are common among patients with ILD. Complex pathological syndromes are more likely to exacerbate pulmonary diffusion dysfunction. The FVC%pred can assist in differentiating syndrome of qi deficiency of lung and kidney, whereas the D-dimer level can assist in differentiating syndrome of phlegm and blood stasis obstructing lung.

OBJECTIVES: To investigate the efficacy of Ag₂Se nanoparticles for eliminating intracellular Porphyromonas gingivalis (P. gingivalis) in esophageal cancer and examine the effect of P. gingivalis clearance on progression of esophageal cancer. METHODS: Ag₂Se nanoparticles were synthesized via a chemical synthesis method. The effects of Ag₂Se nanoparticles on P. gingivalis viability and colony-forming ability were assessed using fluorescence staining and colony formation assays. In a mouse model bearing subcutaneous murine esophageal cancer cell allograft with P. gingivalis infection, the effect of treatment with Ag₂Se nanoparticles on the abundance of P. gingivalis in the tumor tissues was quantified using RNAscope in situ hybridization and quantitative polymerase chain reaction (qPCR), and the changes in tumor volume were monitored. The biosafety of Ag₂Se nanoparticles was assessed by examining liver and kidney functions and pathological changes in the major organs of the mice. RESULTS: Transmission electron microscopy revealed that the synthesized Ag₂Se nanoparticles were uniformly dispersed spherical particles with a diameter around 50 nm. In vitro experiments demonstrated that exposure to Ag₂Se nanoparticles significantly reduced the viability and clonal proliferation capacity of P. gingivalis in a dose-dependent manner. In the tumor-bearing mice, treatment with Ag₂Se nanoparticles significantly reduced the abundance of P. gingivalis in tumor tissues and suppressed tumor cell proliferation. No significant damages to the liver and kidney functions or the major organs were observed in Ag₂Se nanoparticle-treated mice, demonstrating good biocompatibility of Ag₂Se nanoparticles. CONCLUSIONS Ag₂Se nanoparticles exhibit significant bactericidal and inhibitory effects against P. gingivalis, and can effectively eliminate intracellular P. gingivalis to suppress the growth of esophageal cancer allograft in mice, suggesting the potential of Ag₂Se nanoparticles in the treatment of esophageal cancer.
Animals ; Porphyromonas gingivalis/drug effects* ; Mice ; Esophageal Neoplasms/pathology* ; Nanoparticles ; Metal Nanoparticles ; Bacteroidaceae Infections ; Cell Line, Tumor

Within the prefrontal-cingulate cortex, abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions, contributing to the development of mental disorders such as depression. Despite this understanding, the neural circuit mechanisms underlying this phenomenon remain elusive. In this study, we present a biophysical computational model encompassing three crucial regions, including the dorsolateral prefrontal cortex, subgenual anterior cingulate cortex, and ventromedial prefrontal cortex. The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes. The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks. Furthermore, our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex, and network functionality was restored through intervention in the dorsolateral prefrontal cortex. This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
Prefrontal Cortex/physiology* ; Humans ; Emotions/physiology* ; Cognition/physiology* ; Gyrus Cinguli/physiology* ; Computer Simulation ; Models, Neurological ; Neural Pathways/physiology* ; Nerve Net/physiology*

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

OBJECTIVE To investigate the effects of different drying methods on the quality of Chrysanthemum morifolium， and to provide a basis for the harvesting and processing of C. morifolium. METHODS Twenty-five samples were obtained by drying the fresh products using 7 types and 25 kinds of drying methods， and the unqualified samples were removed by taking their appearance and moisture content as elimination indexes. The contents of six active ingredients （chlorogenic acid， luteoloside， 3，5- O-dicaffeoylquinic acid， quercetin， lignoceroside， baicalin） were used as indicators， and combined with principal component analysis （PCA）， partial least square method-discriminant analysis （PLS-DA）， PCA comprehensive score ranking and the best samples obtained from each drying method to select 6 experimental samples comprehensively. The quality of 6 kinds of samples was evaluated using the activities and stability of oxidation-related enzymes （polyphenol oxidase， peroxidase） and the microscopic morphology of the petal surface as evaluation indexes. RESULTS The results of PCA and PLS-DA showed significant differences in the quality of samples obtained by different drying methods， and chlorogenic acid， 3，5-O-dicaffeoylquinic acid and baicalin might be the main reasons for the differences among the samples. The herbs treated with 100 ℃ steam fixation for 1 min combined with blast drying at 50 ℃ for 4 hours had the highest comprehensive score of active ingredients. The oxidation-related enzymes in C. morifolium treated with microwave 800 W fixation for 1 minute followed by 50 ℃ air drying for 4 hours and 100 ℃ steam sterilization for 1 minute followed by 50 ℃ drying for 4 hours were completely inactivated， and the stability was better than that of samples obtained by other drying methods. The observation results of the microstructure of the petal surface showed that the sample obtained by drying at a microwave power of 400 W for 6 minutes had the highest integrity and flatness compared to the above two samples. CONCLUSIONS From the perspective of finished product quality and drying efficiency， 100 ℃ steam fixation for 1 min combined with blast drying at 50 ℃ for 4 hours is the best drying method for C. morifolium.

Atmospheric fine particulate matter (particulate matter 2.5,PM_2.5) is a major component of haze, and its potential hazards to human reproductive health have garnered widespread attention. Establishing appropriate animal models is crucial for in-depth research into the reproductive toxicity of PM_2.5 exposure and its underlying mechanisms. This paper, based on recent literature, summarizes current methods for establishing PM_2.5-exposed animal models and the evaluation criteria for reproductive toxicity research. The primary modeling methods for PM_2.5 exposure include whole-body inhalation exposure and intratracheal instillation exposure. While whole-body inhalation exposure effectively simulates real-life human inhalation environments, it requires sophisticated experimental equipment. Conversely, intratracheal instillation exposure is more cost-effective and easier to operate but faces challenges in accurately mimicking the distribution and deposition of PM_2.5 during natural inhalation. Therefore, researchers must carefully weigh these exposure methods to enhance model rigor and achieve the most realistic simulation of human exposure conditions. When summarizing the application evaluation indicators of PM_2.5-induced reproductive toxicity, this review finds that the main indicators of male reproductive toxicity include reduced sperm quality, testicular tissue damage, and hormonal imbalances. For female reproductive toxicity, the primary indicators are reduced ovarian reserve, endocrine dysfunction, endometrial damage, and adverse perinatal reactions. Additionally, this review highlights the need for detailed chemical composition analysis of PM_2.5, exploring the reproductive toxic targets and mechanisms of particles containing different chemical components, such as heavy metals and polycyclic aromatic hydrocarbons. Long-term studies are also necessary to assess the effects of PM_2.5 exposure on reproductive health and transgenerational effects, to predict potential long-term risks for humans. Additionally, interdisciplinary collaboration should be encouraged, involving cooperation between environmental science, toxicology, reproductive medicine, and other disciplines, to comprehensively assess the environmental health risks of PM_2.5 and provide scientific support for the development of integrated prevention and control strategies. This review summarizes animal modeling methods, evaluation criteria, and their applications, providing valuable methodological references for future reproductive toxicity research on PM_2.5.

ObjectiveTo identify the chemical components of Houpo Wenzhongtang in vivo and in vitro and to analyze the pharmacokinetic properties of the index components in rats with deficiency-cold of spleen and stomach. MethodThe chemical components of Houpo Wenzhongtang was analyzed and identified by ultra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS）. Six rats were randomly selected from 18 SD rats as the blank group， and the remaining rats were given lard and cold vinegar for a long time to construct a rat model with deficiency-cold of spleen and stomach. After successful modeling， the rats were randomly divided into the model group and Houpu Wenzhongtang group（13.5 g·kg^-1， calculated as crude drug）. The administration group was given the corresponding dose of Houpu Wenzhongtang by gavage， and the blank group and the model group were given the same amount of distilled water by gavage. Enzyme-linked immunosorbent assay（ELISA） were used to measure gastrin（GAS） and motilin（MTL） levels in each group. At the same time， plasma samples were collected at different time points after administration， and blood-entry prototype components and metabolites of Houpo Wenzhongtang were analyzed by UPLC-Q-TOF-MS/MS. On this basis， plasma concentrations of magnolol， honokiol， alpinetin and hesperidin in Houpo Wenzhongtang were determined by ultra performance liquid chromatography coupled with triple quadrupole/linear ion trap mass spectrometry（UPLC-QTRAP-MS/MS）， and the pharmacokinetic parameters were calculated using DAS 2.0 software. ResultA total of 79 chemical components， including 44 flavonoids and 11 lignans， were identified in Houpo Wenzhongtang. Meanwhile， 18 blood-entry prototype components and 27 metabolites were identified， the main metabolic pathways of metabolites were glucuronidation， sulfation， oxidation and hydrolysis， and phase Ⅰ and phase Ⅱ were the two primary forms of metabolism. Pharmacokinetic results showed that among the four index components， the time to peak（t_max） values of magnolol and honokiol were consistent and exhibited similar drug metabolism characteristics， the t_max of alpinetin was the shortest， and the absorption rate was the fastest， which had the earliest peak plasma concentration levels， and hesperidin had the shortest mean residence time（MRT_0-t） and the highest metabolic rate in rats. ConclusionThis study clarifies the blood-entry prototype components and their metabolites of Houpo Wenzhongtang in the rat model of deficiency-cold of spleen and stomach， and reveals the pharmacokinetic characteristics of the main active ingredients， which can provide a scientific basis for the study of pharmacodynamic material basis of this formula and its clinical application in treating the syndrome of deficiency-cold of spleen and stomach.

Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer. Methods From July 1,2020 to March 31,2022,clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hos-pital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Ex-amination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chi-nese Medicine,respectively.We obtained tongue images from patients with benign lung nod-ules and lung cancer using the TFDA-1 digital tongue diagnosis instrument,and analyzed these images with the TDAS V2.0 software.The extracted indicators included color space pa-rameters in the Lab system for both the tongue body(TB)and tongue coating(TC)(TB/TC-L,TB/TC-a,and TB/TC-b),textural parameters[TB/TC-contrast(CON),TB/TC-angular second moment(ASM),TB/TC-entropy(ENT),and TB/TC-MEAN],as well as TC parameters(perAll and perPart).The bivariate correlation of TB and TC features was analyzed using Pearson's or Spearman's correlation analysis,and the overall correlation was analyzed using canonical correlation analysis(CCA). Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values.Simple correlation analysis indi-cated that the correlation of TB-L with TC-L,TB-b with TC-b,and TB-b with perAll in lung cancer group was higher than that in benign nodules group.Moreover,the correlation of TB-a with TC-a,TB-a with perAll,and the texture parameters of the TB(TB-CON,TB-ASM,TB-ENT,and TB-MEAN)with the texture parameters of the TC(TC-CON,TC-ASM,TC-ENT,and TC-MEAN)in benign nodules group was higher than lung cancer group.CCA further demon-strated a strong correlation between the TB and TC parameters in lung cancer group,with the first and second pairs of typical variables in benign nodules and lung cancer groups indicat-ing correlation coefficients of 0.918 and 0.817(P<0.05),and 0.940 and 0.822(P<0.05),re-spectively. Conclusion Benign lung nodules and lung cancer patients exhibited differences in correla-tion in the L,a,and b values of the TB and TC,as well as the perAll value of the TC,and the texture parameters(TB/TC-CON,TB/TC-ASM,TB/TC-ENT,and TB/TC-MEAN)between the TB and TC.Additionally,there were differences in the overall correlation of the TB and TC be-tween the two groups.Objective tongue diagnosis indicators can effectively assist in the diag-nosis of benign lung nodules and lung cancer,thereby providing a scientific basis for the ear-ly detection,diagnosis,and treatment of lung cancer.