Thyroid diseases are common clinical endocrine disorders， and their pathogenesis is generally considered to be closely related to genetic predisposition factors， immune system disorders， hormone levels， etc. Xiaoyaosan is widely used in the treatment of various thyroid diseases with excellent effects. This study summarized the relevant literature on the treatment of thyroid diseases with modified Xiaoyaosan prescriptions and their active ingredients from aspects such as theoretical analysis， clinical research， and mechanism research. Theoretical analysis revealed that Xiaoyaosan could not only disperse stagnated liver qi but also replenish deficient spleen Qi， which was consistent with the etiology and pathogenesis of thyroid diseases. Clinical studies found that Xiaoyaosan and its modified prescriptions could be widely used in the treatment of multiple thyroid diseases， such as hyperthyroidism， Hashimoto's thyroiditis， and thyroid nodules. Both the use of modified Xiaoyaosan alone and in combination with medications such as methimazole， propylthiouracil， and euthyrox could effectively improve patients' clinical symptoms. In the mechanism research， this study discovered that the whole formula of Xiaoyaosan and its modified prescriptions could inhibit inflammatory reactions， regulate immune balance， and delay liver damage during the treatment of thyroid diseases. The research on Xiaoyaosan for treating thyroid diseases mainly focused on thyroid cancer， autoimmune thyroiditis， hyperthyroidism， and hypothyroidism. The mechanisms of action mainly involved promoting cell apoptosis， inhibiting cell proliferation and migration， arresting the cell cycle， and regulating thyroid hormone levels. In conclusion， this study systematically combs and summarizes the research status of Xiaoyaosan in treating thyroid diseases through literature retrieval， aiming to provide new perspectives and new ideas for the prevention and treatment of thyroid diseases with traditional Chinese medicine.

ObjectiveBy exploring the influencing factors of readmission in patients with stable angina of coronary heart disease （CHD） based on real-world clinical data， to establish a risk prediction model of integrated traditional Chinese and western medicine， in order to provide a basis for early identification of high-risk populations and reducing readmission rates. MethodsA prospective clinical study was conducted involving patients with stable angina pectoris of CHD， who were divided into a training set and a validation set at a 7∶3 ratio. General information， traditional Chinese medicine （TCM）-related data， and laboratory test results were uniformly collected. After a one-year follow-up， patients were classified into a readmission group and a non-readmission group based on whether they were readmitted. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for readmission. A risk prediction model of integrated traditional Chinese and western medicine was constructed and visualized using a nomogram. The model was validated and evaluated in terms of discrimination， calibration， and clinical decision curve analysis. ResultsA total of 682 patients were included， with 477 in the training set and 205 in the validation set， among whom 89 patients were readmitted. Multivariate logistic regression analysis identified heart failure history ［OR = 6.93， 95% CI （1.58， 30.45）］， wiry pulse ［OR = 2.58， 95% CI （1.42， 4.72）］， weak pulse ［OR = 3.97， 95% CI （2.06， 7.67）］， teeth-marked tongue ［OR = 4.38， 95% CI （2.32， 8.27）］， blood stasis constitution ［OR = 2.17， 95% CI （1.06， 4.44）］， phlegm-stasis mutual syndrome ［OR = 3.64， 95% CI （1.87， 7.09）］， and elevated non-high-density lipoprotein cholesterol ［OR = 1.30， 95% CI （1.01， 1.69）］ as influencing factors of readmission. These factors were used as predictors to construct a nomogram-based risk prediction model for readmission in patients with stable angina. The model demonstrated moderate predictive capability， with an area under the receiver operating characteristic curve （AUC） of 0.818 ［95% CI （0.781， 0.852）］ in the training set and 0.816 ［95% CI （0.779， 0.850）］ in the validation set. The Hosmer-Lemeshow test showed good calibration （χ² = 4.55， P = 0.80）， and the model's predictive ability was stable. When the threshold probability exceeded 5%， the clinical net benefit of using the model to predict readmission risk was significantly higher than intervening in all patients. ConclusionHistory of heart failure， teeth-marked tongue， weak pulse， wiry pulse， phlegm-stasis mutual syndrome， blood stasis constitution， and non-high-density lipoprotein cholesterol are influencing factors for readmission in patients with stable angina of CHD. A clinical prediction model was developed based on these factors， which showed good discrimination， calibration， and clinical utility， providing a scientific basis for predicting readmission events in patients with stable angina.

OBJECTIVES: Increasing detection of low-risk papillary thyroid carcinoma (PTC) is associated with overdiagnosis and overtreatment. N6-methyladenosine (m⁶A)-mediated microRNA (miRNA) dysregulation plays a critical role in tumor metastasis and progression. However, the functional role of m⁶A-miRNAs in PTC remains unclear. This study aims to elucidate the regulatory mechanism of m⁶A-miR-139-5p expression in PTC, determine its association with PTC metastasis, and evaluate its potential as a diagnostic biomarker for PTC metastasis, thereby providing experimental evidence for precision diagnosis and therapy. METHODS: Expression profiles of m⁶A-miRNAs were compared between the The Cancer Genome Atlas (TCGA) and GSE130512 cohorts to identify metastasis-associated candidates. Clinical specimens from 13 metastasis and 18 non-metastasis PTC patients were analyzed to assess m⁶A-miR-139-5p expression and its correlation with metastasis. Functional experiments were conducted to investigate the effect of fat mass and obesity-associated protein (FTO) on pri-miR-139 methylation and processing, clarifying its regulatory role in miR-139-5p expression. In TPC-1 cells, MTT assays were performed to evaluate whether miR-139-5p overexpression could counteract FTO-mediated cell proliferation. Transwell invasion assays were used to determine the impact of miR-139-5p on PTC cell invasion, exploring whether it functions through the ZEB1/E-cadherin axis. RESULTS: By comparing TCGA and GSE130512 cohorts, it was found that circulating m⁶A-miR-139-5p could serve as a biological indicator for detecting PTC metastasis. Detection of 13 metastatic and 18 non-metastatic clinical specimens showed that FTO inhibited the processing of pri-miR-139 by reducing its methylation level, leading to the dysregulation of miR-139-5p in PTC (P<0.05). In TPC-1 cells, MTT assay showed that overexpression of miR-139-5p could partially reverse FTO overexpression-mediated cell proliferation (P<0.05). In addition, miR-139-5p inhibited the invasive ability of PTC cells by targeting the ZEB1/E-cadherin axis, while FTO overexpression could partially weaken this inhibitory effect. CONCLUSIONS Circulating miR-139-5p can be a potential marker for evaluating PTC metastasis. FTO affects the expression and function of miR-139-5p by regulating m⁶A modification of pri-miR-139, but its clinical value needs further verification.
Humans ; MicroRNAs/metabolism* ; Thyroid Cancer, Papillary/metabolism* ; Alpha-Ketoglutarate-Dependent Dioxygenase FTO/metabolism* ; Thyroid Neoplasms/metabolism* ; Cell Line, Tumor ; Neoplasm Metastasis ; Adenosine/genetics* ; Gene Expression Regulation, Neoplastic ; Female ; Male ; Cadherins/metabolism* ; Cell Proliferation ; Zinc Finger E-box-Binding Homeobox 1/genetics*

Objective:To explore the predictive value of preoperative peripheral hematological parameters combined with clinicopathological features for cervical lymph node metastasis（CLNM） in patients with laryngeal squamous cell carcinoma（LSCC）, and to construct and validate a nomogram model for CLNM. Methods:A retrospective analysis was conducted on the clinical data of 264 LSCC patients who underwent surgical treatment and were pathologically confirmed, collected from the Second Affiliated Hospital of Shandong First Medical University and Taian 88 Hospital. Specifically, 161 patients from one hospital were allocated to the training cohort, while 103 patients from another hospital constituted the validation cohort. Based on postoperative pathological results, patients were categorized into CLNM-positive and CLNM-negative groups. The general clinical data, clinicopathological features, and hematological parameters of the two groups were analyzed and compared. A preoperative predictive model for CLNM was developed using logistic regression analysis, followed by validation and sensitivity analysis to evaluate the robustness of the model's predictive performance. Results:The results showed that there were significant differences in tumor location, tumor size, tumor differentiation, neutrophil percentage, lymphocyte count, lymphocyte percentage, c-reactive protein（CRP）, fibrinogen, neutrophil-to-lymphocyte ratio（NLR）, platelet-to-lymphocyte ratio（PLR）, systemic immune-inflammation index（SII）, systemic inflammation response index（SIRI）, and prognostic inflammatory index（PIV） between the CLNM-positive and CLNM-negative groups（P<0.05）. Lasso regression identified tumor location, clinical T stage, tumor size, tumor differentiation degree, red blood cell distribution width（RDW） -coefficient of variation（RDW-CV）, CRP, FIB, D-dimer, NLR, and lymphocyte-to-monocyte ratio（LMR） were the most predictive parameters. Multivariate logistic regression revealed that tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients（P<0.05）. A nomogram was constructed based on these five factors. The model demonstrated excellent discrimination, with a C-index of 0.837（95%CI 0.766-0.908） in the training cohort and 0.809（95%CI 0.698-0.920） in the validation cohort. Calibration curves and DCA curves in both cohorts confirmed the clinical utility of the model. Sensitivity analysis further supported the robustness of the results, showing good discrimination and calibration across different age and BMI subgroups. Conclusion:Tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients. The nomogram based on these variables exhibits strong discrimination, calibration, and clinical applicability, and may serve as a valuable tool for preoperative risk assessment and individualized treatment planning.
Humans ; Nomograms ; Laryngeal Neoplasms/blood* ; Retrospective Studies ; Lymphatic Metastasis ; Carcinoma, Squamous Cell/blood* ; Lymph Nodes/pathology* ; Male ; Female ; Middle Aged ; Neck ; C-Reactive Protein ; Aged ; Logistic Models ; Neutrophils ; Prognosis

Regenerating periodontal bone defect surrounding periodontal tissue is crucial for orthodontic or dental implant treatment. The declined osteogenic ability of periodontal ligament stem cells (PDLSCs) induced by inflammation stimulus contributes to reduced capacity to regenerate periodontal bone, which brings about a huge challenge for treating periodontitis. Here, inspired by the adhesive property of mussels, we have created adhesive and mineralized hydrogel microspheres loaded with traditional compound cordycepin (MMS-CY). MMS-CY could adhere to the surface of alveolar bone, then promote the migration capacity of PDLSCs and thus recruit them to inflammatory periodontal tissues. Furthermore, MMS-CY rescued the impaired osteogenesis and ligament-forming capacity of PDLSCs, which were suppressed by the inflammation stimulus. Moreover, MMS-CY also displayed the excellent inhibitory effect on the osteoclastic activity. Mechanistically, MMS-CY inhibited the premature senescence induced by the inflammation stimulus through the nuclear factor erythroid 2-related factor (NRF2) pathway and reducing the DNA injury. Utilizing in vivo rat periodontitis model, MMS-CY was demonstrated to enhance the periodontal bone regeneration by improving osteogenesis and inhibiting the osteoclastic activity. Altogether, our study indicated that the multi-pronged approach is promising to promote the periodontal bone regeneration in periodontitis condition by reducing the inflammation-induced stem cell senescence and maintaining bone homeostasis.
Animals ; Bone Regeneration/drug effects* ; Rats ; Periodontal Ligament/cytology* ; Microspheres ; NF-E2-Related Factor 2 ; Hydrogels ; Periodontitis/therapy* ; Osteogenesis/drug effects* ; Disease Models, Animal ; Stem Cells ; Male ; Rats, Sprague-Dawley ; Humans

OBJECTIVE: To develop a method for identifying high-risk patients among septic populations requiring mechanical ventilation, and to conduct phenotypic analysis based on this method. METHODS: Data from four sources were utilized: the Medical Information Mart for Intensive Care (MIMIC-IV 2.0, MIMIC-III 1.4), the Philips eICU-Collaborative Research Database 2.0 (eICU-CRD 2.0), and the Anhui Medical University Second Affiliated Hospital dataset. The adult patients in intensive care unit (ICU) who met Sepsis-3 and received invasive mechanical ventilation (IMV) on the first day of first admission were enrolled. The MIMIC-IV dataset with the highest data integrity was divided into a training set and a test set at a 6:1 ratio, while the remaining datasets were served as validation sets. The demographic information, comorbidities, laboratory indicators, commonly used ICU scores, and treatment measures of patients were extracted. Clinical data collected within first day of ICU admission were used to calculate the sequential organ failure assessment (SOFA) score. K-means clustering was applied to cluster SOFA score components, and the sum of squared errors (SSE) and Davies-Bouldin index (DBI) were used to determine the optimal number of disease subtypes. For clustering results, normalized methods were employed to compare baseline characteristics by visualization, and Kaplan-Meier curves were used to analyze clinical outcomes across phenotypes. RESULTS: This study enrolled patients from MIMIC-IV dataset (n = 11 166), MIMIC-III dataset (n = 4 821), eICU-CRD dataset (n = 6 624), and a local dataset (n = 110), with the four datasets showing similar median ages and male proportions exceeding 50%; using 85% of the MIMIC-IV dataset as the training set, 15% as the test set, and the rest dataset as the validation set. K-means clustering based on the six-item SOFA score was performed to determine the optimal number of clusters as 3, and patients were finally classified into three phenotypes. In the training set, compared with the patients with phenotype II and phenotype III, those with phenotype I had the more severe circulatory and respiratory dysfunction, a higher proportion of vasoactive drug usage, more obvious metabolic acidosis and hypoxia, and a higher incidence of congestive heart failure. The patients with phenotype II was dominated by respiratory dysfunction with higher visceral injury. The patients with phenotype III had relatively stable organ function. The above characteristics were consistent in both the test and validation sets. Analysis of infection-related indicators showed that the patients with phenotype I had the highest SOFA score within 7 days after ICU admission, initial decreases and later increases in platelet count (PLT), and higher counts of neutrophils, lymphocytes, and monocytes as compared with those with phenotype II and phenotype III, their blood cultures had a higher positivity rates for Gram-positive bacteria, Gram-negative bacteria and fungi as compared with those with phenotype II and phenotype III. The Kaplan-Meier curve indicated that in the training, test, and validation sets, the 28-day cumulative mortality of patients with phenotype I was significantly higher than that of patients with phenotypes II and phenotype III. CONCLUSIONS Three distinct phenotypes in septic patients receiving IMV based on unsupervised machine learning is derived, among which phenotype I, characterized by cardiorespiratory failure, can be used for the early identification of high-risk patients in this population. Moreover, this population is more prone to bloodstream infections, posing a high risk and having a poor prognosis.
Humans ; Machine Learning ; Sepsis/therapy* ; Respiration, Artificial ; Intensive Care Units ; Organ Dysfunction Scores ; Male ; Female ; Middle Aged ; Adult

ObjectiveThis study aims to observe the clinical effect of Danggui Liuhuang Tang （DGLHT） on patients with type 2 diabetes mellitus （T2DM） complicated by atherosclerotic cardiovascular disease （ASCVD） at high risk， focus on evaluating the influence of DGLHT on cardiovascular risk indicators such as flow-mediated dilation （FMD）， atherogenic index of plasma （AIP）， and triglyceride-glucose index （TyG）， and explore the regulatory effect of DGLHT on the myeloid differentiation factor 88/nuclear factor-kappa B （MyD88/NF-κB） signaling pathway. MethodsThe clinical study was a single-center， double-blind， and randomized controlled trial. A total of 68 patients with T2DM-ASCVD at high risk for cardiovascular events with Yin deficiency and fire excess syndrome were enrolled and randomly assigned to a treatment group and a control group. The treatment group was given atorvastatin calcium tablets and DGLHT， while the control group was given atorvastatin calcium tablets and placebos. The treatment course was 12 weeks， with a final study completion of 30 patients in the treatment group and 29 in the control group. Changes in cardiovascular risk indicators such as FMD， AIP， TyG， and small dense low-density lipoprotein cholesterol （sdLDL-C） index were compared. Human umbilical vein endothelial cells （HUVECs） were used to establish a vascular endothelial injury and inflammation model. The protective effect of DGLHT on endothelial injury was verified by reverse transcription polymerase chain reaction （Real-time PCR） and Western blot . ResultsAfter 12 weeks of treatment， the AIP in the treatment group significantly decreased compared with that before the treatment （P<0.05）. Compared with the control group， the treatment group showed significant improvements in FMD and TyG （P<0.05）. Additionally， the treatment group demonstrated significant reductions in two-hour postprandial glucose （2 hPG）， glycated albumin （GA）， triglycerides （TG）， apolipoprotein E （Apo E）， and sdLDL-C （P<0.05）. Analysis of traditional Chinese medicine （TCM） syndrome efficacy indicated that in the treatment group， Yin deficiency and fire excess syndromes， including dry throat and mouth （P<0.05）， excessive thirst （P<0.01）， tidal fever and night sweats （P<0.05）， and dry stools （P<0.05）， improved. Compared with the control group， the treatment group showed significant improvements in symptoms of dry throat and mouth （P<0.05） and excessive thirst （P<0.01）. TCM syndrome scores significantly decreased （P<0.01）， and the overall efficacy rate was 56.67%， significantly higher than the 10.34% observed in the control group （P<0.01）. At the cellular level， increasing concentrations of DGLHT led to decreased messenger ribonucleic acid （mRNA） levels of pro-inflammatory cytokines interleukin-6 （IL-6）， tumor necrosis factor-alpha （TNF-α）， and interleukin-1-beta （IL-1β） in lipopolysaccharide （LPS）-stimulated HUVECs （P<0.01）， with significant reductions in the high-concentration group （P<0.01）. DGLHT may inhibit the expressions of MyD88 and phosphorylated （p）-NF-κB p65 proteins in a concentration-dependent manner. ConclusionDGLHT shows significant effects in reducing cardiovascular risks and may exert an anti-inflammatory effect by inhibiting the MyD88/NF-κB signaling pathway. This finding provides a new perspective for the prevention and treatment of cardiovascular diseases in high-risk individuals with T2DM-ASCVD.

Objective To evaluate the accuracy of using HIrisPlex-S system for eye color,hair color,and skin color prediction in forensic DNA phenotyping(FDP).Methods A total of 49 unrelated individuals were enrolled.First,based on the collected facial photographs and questionnaire responses,the actual phenotypic traits,including eye color,hair color,and skin color,of the participants were manually assessed and categorized.Subsequently,peripheral blood samples were collected from the participants,and DNA was extracted.Genotyping of the HIrisPlex-S system was performed using the SNaPshot method combined with capillary electrophoresis.Single nucleotide polymorphism(SNP)sites were analyzed using the online HIrisPlex-S prediction platform(https://HIrisPlex.erasmusmc.nl/)to predict the aforementioned phenotypic traits.Two different methods were used to interpret the prediction results.In Method 1,the phenotypic trait with the highest probability value were directly selected as the predicted phenotype.In Method 2,the prediction guidelines proposed by Manfred Kayser's team was applied.The sensitivity and specificity of the predictions were calculated by comparing the prediction results with the manually interpreted actual phenotypic data,and the differences between the two interpretation methods in these performance metrics were compared.Additionally,two real case samples were included for phenotypic inference analysis to validate the system's effectiveness in practical applications.Results Among the participants,approximately 55%had"brown"eyes,while"intermediate"eye color was less common;approximately 45%had"black"hair;and approximately 39%had"pale"skin.After optimizing the concentration of single base extension(SBE)primers,the peak balance of most SNP loci in the HIrisPlex-S system improved,though inter-laboratory reproducibility remained suboptimal.In eye color prediction,the sensitivity of Method 1(0.875 0,0.000 0,and 1.000 0)was slightly higher than that of Method 2(0.812 5,0.000 0,and 0.925 9),while the specificity of Method 1(0.848 5,1.000 0,and 0.818 2)was slightly lower than that of Method 2(0.909 1,1.000 0,and 0.909 1).For hair color prediction,the two methods showed identical sensitivity(0.772 7,0.615 4,and 0.857 1),but Method 2 showed slightly better specificity(1.000 0,0.944 4,and 0.714 2)than Method 1(1.000 0,0.916 7,and 0.742 9).In skin color prediction,both the sensitivity(0.000 0,0.789 5,1.000 0,0.333 3,and 0.875 0)and specificity(1.000 0,0.966 7,0.833 3,0.976 7,and 0.878 0)of Method 2 were slightly higher than those of Method 1(sensitivity:0.000 0,0.578 9,0.923 1,0.166 7,and 0.750 0;specificity:1.000 0,0.966 7,0.694 4,0.953 5,and 0.878 0).However,overall,there was no statistically significant difference in sensitivity or specificity between the two methods(P>0.05).Additionally,the phenotypic predictions for the two real case samples were consistent with genetic ancestry analysis.Conclusion The HIrisPlex-S system can be used to predict the eye and hair colors in population samples,but its accuracy in skin color prediction needs further improvement.

Objective To establish a standardized diagnostic and treatment pathway for chronic renal failure(CRF)based on a nephrology cluster,providing a reference for the traditional Chinese medicine(TCM)diagnosis and treatment of CRF.Methods A TCM diagnostic and treatment proto-col for CRF was developed through cluster construction.A preliminary framework for the standardized diagnostic and treatment pathway of CRF was constructed through literature research.Three rounds of Delphi expert consultation were conducted among 26 experts.The experts'enthusiasm,authority,co-ordination of opinions,importance ratings,and coefficient of variation were analyzed to ultimately form the standardized diagnostic and treatment pathway for CRF.Results The active coefficients(Caj)for the first,second,and third rounds of expert consultation were 1.000,0.923,and 1.000,respectively.The expert authority coefficients(Cr)were 0.895,0.910,and 0.923,respectively.The overall Kendall's W coefficients were 0.233,0.248,and 0.293(P＜0.001).The final stand-ardized diagnostic and treatment pathway for CRF included 4 primary indicators,19 secondary indica-tors,and 77 tertiary indicators,with mean importance ratings ranging from 4.42 to 4.87 and coeffi-cients of variation ranging from 0.072 to 0.126.Conclusion The standardized diagnostic and treat-ment pathway for CRF established based on a nephrology cluster is highly scientific and reliable,with clear guidance and ease in implementation,providing good guidance for the TCM diagnosis and treat-ment of CRF.