ObjectiveTo investigate the effect of quercetin on acute gouty arthritis （GA） in rats by inhibiting the reactive oxygen species （ROS）/NOD-like receptor protein 3 （NLRP3）/interleukin-1β （IL-1β） signaling pathway. MethodsSixty SPF-grade male SD rats were randomized into normal， model， colchicine （0.3 mg·kg^-1）， and low-， medium-， and high-dose （25， 50， 100 mg·kg^-1， respectively） quercetin groups （n=10）. The rats in the dosing groups were administrated with the corresponding drugs （10 mL·kg^-1） by gavage once a day for one week. An equal volume of normal saline was given by gavage to rats in normal and model groups. One hour after drug administration on day 5， an acute GA model was established in other groups except the control group via intra-articular injection of monosodium urate （MSU） suspension into the right posterior ankle joint cavity. The joint swelling and gait were scored at the time points of 6， 12， 24， 48 h after modeling. Histopathological alterations in the ankle joint tissue from each group were assessed by hematoxylin-eosin （HE） staining. Malondialdehyde （MDA）， xanthine oxidase （XOD）， and total superoxide dismutase （T-SOD） assay kits were used to assess the levels of MDA， XOD， and T-SOD in the serum. The levels of tumor interleukin-6 （IL-6）， necrosis factor-α （TNF-α）， and IL-1β in the rat serum， as well as ROS in the ankle joint tissue， were measured by enzyme-linked immunosorbent assay （ELISA）. Western blot was performed to determine the protein levels of NLRP3， thioredoxin-interacting protein （TXNIP）， apoptosis-associated speck-like protein containing a CARD domain （ASC）， precursor cysteinyl aspartate-specific proteinase-1 （pro-Caspase-1）， cleaved Caspase-1 （Caspase-1 p20）， and IL-1β in the ankle joint tissue. Real-time PCR was employed to assess the mRNA levels of TXNIP， NLRP3， ASC， IL-1β， and TNF-α in the ankle joint tissue. ResultsCompared with the normal group， the model group exhibited decreased spontaneous activity， mental fatigue， increased ankle joint swelling and gait scores （P<0.01）， aggravated synovial tissue edema and inflammatory cell infiltration （P<0.01）， elevated levels of XOD， MDA， TNF-α， IL-1β， and IL-6 in the serum and ROS in the joint tissue （P<0.01）， a declined level of T-SOD （P<0.01）， up-regulated protein levels of NLRP3， TXNIP， ASC， pro-Caspase-1， Caspase-1 p20， and IL-1β in the ankle joint tissue （P<0.01）， and up-regulated mRNA levels of NLRP3， TXNIP， ASC， IL-1β， and TNF-α in the ankle joint tissue （P<0.01）. Compared with the model group， the medium- and high-dose quercetin groups showed improved general conditions， decreased gait scores （P<0.05， P<0.01）， reduced joint swelling （P<0.01）， alleviated synovial tissue edema and inflammatory cell infiltration （P<0.05， P<0.01）， lowered levels of XOD， MDA， TNF-α， IL-1β， and IL-6 in the serum and ROS in the joint tissue （P<0.01）， increased levels of T-SOD （P<0.01）， down-regulated protein levels of TXNIP， NLRP3， ASC， pro-Caspase-1， Caspase-1 p20， and IL-1β in the ankle joint tissue （P<0.05， P<0.01）， and down-regulated mRNA levels of TXNIP， NLRP3， ASC， IL-1β， and TNF-α in the ankle joint tissue （P<0.01）. Low-dose quercetin also ameliorated some of the above parameters （P<0.05， P<0.01）. ConclusionQuercetin exerts anti-GA effects by blocking the ROS/NLRP3/IL-1β signaling pathway， downregulating NLRP3 inflammasome activation， and inhibiting the production of pro-inflammatory cytokines including TNF-α， IL-1β， and IL-6.

Objective:Effects of Qingsui Xiaoyan Decoction on osteoclast differentiation of RAW264.7 cells.Methods:Receptor activator of nuclear factor kappa B ligand (RANKL) was used to induce differentiation of RAW264.7 cells into osteoclasts. CCK-8 method was used to screen experimental drug concentrations and analyze the cytotoxicity of drug intervention on RAW264.7 cells. TRAP staining method was used to quantitatively detect the effects of Qingsui Xiaoyan Decoction on osteoclast differentiation ability. RT-PCR technology was used to detect the mRNA expressions of osteoclast differentiation genes TRAP, MMP-9, CK, CTR. Western blot was used to detect osteoclast-related protein expressions of NF-κBP65, IκB-αTRAP, and TRAP.Results:After 72 hours of intervention, 0.800, 4.000, 20.000, and 100.000 mg/ml of Qingsui Xiaoyan Decoction could inhibit cell proliferation ( P<0.05). Compared with the model group, the number of TRAP-positive cells decreased ( P<0.05) in the 5, 20, 80, and 160 μg/ml Qingsui Xiaoyan Decoction groups. Additionally, the mRNA levels of TRAP, MMP-9, CK, and CTR decreased ( P<0.05), the expression of NF-κB p65 and TRAP proteins decreased ( P<0.05), and the expression of IκB-α protein increased ( P<0.05). Conclusions:Qingsui Xiaoyan Decoction can inhibit the expressions of TRAP, MMP-9, CK, CTR genes and TRAP protein, reduce the degradation of I κ B - α protein by inhibiting the NF - κ B signaling pathway, inhibit the expression of NF - κ B p65 protein, and thus inhibit the differentiation of RAW264.7 into osteoclasts.

Objective : To investigate the role and related mechanisms of IgD on the viability , proliferation , apoptosis , and other functions of Molm_13 cells. Methods: Peripheral blood serum was collected from AML patients and healthy controls. The sIgD levels were quantified by ELISA. For in vitro studies , Molm_13 cells were treated with varying concentrations of IgD. Cell viability and proliferation were assessed via CCK_8 assays , CFSE staining , and colony formation assays. Apoptosis rates were determined using an Annexin V/PI apoptosis detection kit. Preliminary exploration of the mechanisms related to IgD_induced proliferation of Molm_13 were analyzed through differential gene analysis. Results: Compared with healthy controls , the levels of sIgD in AML patients were significantly el_ evated (P < 0. 001 ) . IgD treatment dose_dependently increased Molm_13 cell viability and proliferation ( P < 0. 05) , inhibited apoptosis rates (P < 0. 001) . Conclusion IgD promotes the viability and proliferation of Molm_ 13 cells , and reduces apoptosis.

Colorectal inflammatory cancer transformation poses a major risk to patients with colitis. Patients with chronic intestinal inflammation have an approximately 2-3 folds increased risk of developing colorectal cancer (CRC). Unfortunately, there is currently no effective intervention available. Huangqin decoction (HQD), a well-known traditional Chinese medicine (TCM) formula, is frequently clinically prescribed for treating patients with colitis, and its active ingredients have effective antitumour efficacy. Nonetheless, the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear. A strategy integrating metagenomic, lipidomic, and messenger RNA (mRNA) sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome, metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation. Our study revealed that HQD suppressed colorectal inflammatory cancer transformation, which was associated with enhanced intestinal barrier function, decreased the inflammatory response, and regulation of the gut microbiome. Notably, cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis. Moreover, gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism, especially the remodeling of arachidonic acid metabolism, which was associated with the amelioration of pathological transformation. Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase (ALOX12) were affected by HQD treatment, and no obvious protective effect of HQD was observed in Alox 12 ^-/- mice, which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation. In summary, multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.

Human keratinocyte growth factor-1 (hKGF-1), a member of the fibroblast growth factor (FGF) family, plays crucial roles in organ development, cell proliferation, wound healing, and tissue repair, representing one of the most effective and specific growth factors for skin repair. However, obtaining recombinant hKGF-1 remains challenging due to its universally low expression efficiency in vitro. This study employs the Bombyx mori baculovirus expression system to establish a technological platform that utilizes the economically important insect Bombyx mori as a bioreactor for high-efficiency and low-cost expression and production of recombinant human keratinocyte growth factor 1 (hKGF-1) protein, ultimately achieving high-level expression of hKGF-1 in Bombyx mori ovary cell line (BmN). In this study, we optimized the hKGF-1 sequence based on the codon preference of baculovirus. By fusing hKGF-1 with polyhedrin (highly expressed in this system) and adding extra promoters and enhancers, we significantly improved the expreesion level of hKGF-1 in Bombyx mori cells. The results demonstrated that the aforementioned strategies significantly enhanced the expression level of hKGF-1 in Bombyx mori cells. SDS-PAGE and Western blotting results revealed that the highest hKGF-1 expression (accounting for 8.7% of total cellular protein) was achieved when the Polh promoter was combined in tandem with the P6.9 promoter and hKGF-1 was fused with a 15-residue polyhedrin fragment for co-expression. The optimal harvest time was determined to be 120 h post transfection. This study achieved the efficient expression of hKGF-1 in Bombyx mori cells, establishing an ideal technological platform for the industrial utilization of recombinant hKGF-1. The developed methodology not only provides valuable technical references for the production of other growth factors and complex proteins, but also demonstrates significant implications for employing silkworms as bioreactors for recombinant human protein expression.
Bombyx/metabolism* ; Animals ; Baculoviridae/metabolism* ; Humans ; Fibroblast Growth Factor 7/biosynthesis* ; Recombinant Proteins/genetics* ; Cell Line ; Genetic Vectors/genetics*

BACKGROUND: Previous studies have demonstrated that short-term exposure to ambient particulate matter elevates the risk of ischemic stroke in major urban areas of various countries. However, there is a notable gap in research focusing on remote areas inhabited by ethnic minorities and the cumulative effects of air pollutants. Our study conducted in the area aims to explore the potential association between ischemic stroke and air pollutants and contribute to improving health outcomes among the community. METHODS: This retrospective observational study was conducted at the Xing'an League People's Hospital in Inner Mongolia. The medical records of 4,288 patients admitted for IS between November 1, 2019, and October 31, 2020, were reviewed. Data on demographics (age and sex), air pollutants (PM₁₀, PM_2.5, NO₂, NO, CO, and O₃), and meteorological factors (daily average temperature, daily average wind speed, and daily average atmosphere pressure) were collected and analyzed. The statistical analysis included descriptive statistics, Poisson distribution analysis to evaluate the adverse effects of atmospheric pollutants on daily hospitalizations, and subgroup analysis to determine whether gender and age could modify the impact on hospitalizations. RESULTS: A substantial correlation was revealed in single-day lags model. The peak delayed effects of PM₁₀, PM_2.5, SO₂, and NO₂ were observed at lag8 (PM₁₀ (OR = 1.016, 95%CI 1.002, 1.030), PM_2.5 (OR = 1.027, 95%CI 1.007, 1.048), SO₂ (OR = 1.153, 95%CI 1.040, 279) and NO₂ (OR = 1.054, 95%CI 1.005, 1.105)) while males exhibited a consistent trend from lag0 to lag8 (PM₁₀ (OR = 1.035, 95%CI 1.018, 1.053), PM_2.5 (OR = 1.056, 95%CI 1.030, 1.082), SO₂ (OR = 1.220, 95%CI 1.072, 1.389), NO₂ (OR = 1.126, 95%CI 1.061, 1.120), CO (OR = 10.059, 95%CI 1.697, 59.638) and O₃ (OR = 0.972, 95%CI 0.946, 0.999)). When gender and age were considered, a positive impact was also observed after three days cumulative effect in males. CONCLUSIONS There is a significant cumulative effect of exposure to air pollution on IS hospital admissions, especially the males and patients under the age of 65. Our results also suggested that a notable association between CO and NO₂ in two-pollutant models.
Humans ; Male ; Female ; Air Pollution/analysis* ; China/epidemiology* ; Retrospective Studies ; Middle Aged ; Air Pollutants/analysis* ; Aged ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Adult ; Ischemic Stroke/chemically induced* ; Environmental Exposure/adverse effects* ; Aged, 80 and over

Peptide-based drugs possess several advantages, including high specificity, low immunogenicity, minimal accumulation, and fewer drug-drug interactions, making them a novel and efficient therapeutic class for various diseases. In recent years, peptide-based drugs have shown great potential and broad application prospects in the treatment of oral infectious diseases, tissue injury and repair, tumors, and complex oral mucosal disorders, acting either through direct mechanisms or indirect modulation. Oral administration remains the preferred route due to its non-invasive, painless nature and ease of management; however, gastrointestinal pH can inactivate or even degrade peptide drugs. In the treatment of oral diseases, local administration is commonly employed, avoiding gastrointestinal degradation and first-pass metabolism. Nevertheless, limitations in current theoretical research and the high cost of peptide synthesis hinder their clinical application. Future efforts should focus on advancing related studies to promote the practical application of peptide-based drugs in the field of oral medicine.
Humans ; Peptides/administration & dosage* ; Mouth Diseases/drug therapy* ; Administration, Oral

[Objective]To establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors.[Methods]Patients aged≥18 years,diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province,were continuously enrolled.Logistic regression,back propagation neural network(BPNN),and random forest(RF)algorithms were used to construct models for detecting the causative factors of coronary artery stenosis.Sensitivity(TPR),specificity(TNR),accuracy(ACC),positive predictive value(PV+),negative predictive value(PV-),area under subject operating characteristic curve(AUC),and calibration curve were used to compare the discrimination and calibration performance of the models.The best model was then employed to predict the main risk variables associated with coronary stenosis.[Results]The RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models.The TPR values for logistic regression,BPNN,and RF models were 75.76%,74.30%,and 93.70%,while ACC values were 74.05%,72.30%,and 79.49%,respectively.The AUC values were:logistic regression 0.739 9;BPNN 0.723 1;RF 0.752 2.Manifestations such as chest pains,abnormal ST segments on ECG,ventricular premature beats with hypertension,atrial fibrillation,regional wall motion abnormalities(RWMA)by color echocardiography,aortic regurgitation(AR),pulmonary insufficiency(PI),family history of cardiovascular diseases,and body mass index(BMI)were identified as top ten important variables affecting coronary stenosis according to the RF model.[Conclusions]Random forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis.The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

Objective To construct a swallowing dynamic model for simulating dysphagia caused by reduced tongue movement am-plitude.Methods A swallowing dynamic model was established based on medical imaging data from CT and videofluoroscopic swallowing study(VFSS).The finite element method was used to simulate soft tissues,while the smoothed parti-cle hydrodynamics method(SPH)was used to simulate bolus.The model's posture at each time point was com-pared with the imaging data of VFSS from twelve patients with dysphagia,and a normalization method was used for quantitative evaluation of the model's validity.By adjusting the tongue movement amplitude under different viscosity conditions,the role of tongue movement in the swallowing process was investigated,and the swallow-ing safety and efficiency were assessed.Results The tongue posture and bolus trajectory presented by the swallowing dynamic model were consistent with the VFSS imaging.The brightness in the epiglottis area in VFSS images correlated with the equivalent brightness of SPH particles in the simulation results(r=0.97).As the tongue movement amplitude reducing by 20%,the num-ber of aspirated particles,swallowing efficiency and the average velocity of bolus particles in the oropharyngeal cavity all performed well.Pudding-like fluids exhibited favorable swallowing characteristics even when tongue movement amplitude reducing significantly.Conclusion The swallowing dynamic model can simulate the human swallowing process,providing good support for re-habilitation training of patients with dysphagia and the development of specialized medical foods,demonstrating significant potential for clinical applications.

Objective:To develop and validate a 30-day readmission risk prediction model for patients with chronic obstructive pulmonary disease (COPD) using multiple machine learning algorithms.Methods:Convenience sampling was used to select 1 450 COPD patients hospitalized at Tianjin Medical University General Hospital from January 2017 to December 2023 as study subjects. Twenty-nine variables associated with readmission were included. LASSO was used to screen for primary characteristic variables associated with 30-day readmission. The 1 450 patients were divided into a training set ( n=870) and a test set ( n=580) in a 6∶4 ratio. Ten machine learning methods, including random forest, AdaBoost, extreme radient Boosting (XGB), decision tree and so on, were used for model training and testing to identify the optimal prediction model. The optimal model and SHAP were employed to analyze key features and rank characteristic importance. Results:Among 1 450 COPD patients, the 30-day readmission rate was 24.48% (355/1 450). There were no significant differences in the general information between patients in test set and training set ( P>0.05). LASSO regression analysis identified seven variables with the highest predictive value, namely regular weekly exercise, hospital stay, mean arterial pressure, forced expiratory volume in one second/forced vital capacity (FEV1/FVC), C-reactive protein, body mass index, and medication adherence. Machine learning showed that in the training set, XGB had the highest area under the receiver operating characteristic curve ( AUC), sensitivity, and F1 score of 0.943, 0.926, and 0.930, respectively. In the test set, the AUC and accuracy of XGB were 0.882 and 0.858, respectively, and XGB's various scores showed that it had good generalization and predictive performance. XGB analysis showed that medication adherence, FEV1/FVC, and regular weekly exercise were negatively correlated with the 30-day readmission risk, while body mass index, C-reactive protein, mean arterial pressure, and hospital stay were positively correlated. The characteristics ranked in order of importance were medication adherence, body mass index, C-reactive protein, mean arterial pressure, FEV1/FVC, hospital stay and regular weekly exercise. Conclusions:The XGB model has strong predictive performance and good generalization ability, which can effectively predict the 30-day readmission risk of COPD patients, assist in clinical identification of high-risk patients, implement nursing interventions, and reduce readmission rates.