Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

OBJECTIVES: To explore the risk factors of feeding intolerance (FI) in critically ill children receiving enteral nutrition (EN) and to construct a prediction nomogram model for FI. METHODS: A retrospective study was conducted to collect data from critically ill children admitted to the Pediatric Intensive Care Unit of Xiangya Hospital, Central South University, between January 2015 and October 2020. The children were randomly divided into a training set (346 cases) and a validation set (147 cases). The training set was further divided into a tolerance group (216 cases) and an intolerance group (130 cases). Multivariate logistic regression analysis was used to screen for risk factors for FI in critically ill children receiving EN. A nomogram was constructed using R language, which was then validated on the validation set. The model's discrimination, calibration, and clinical net benefit were evaluated using receiver operating characteristic curves, calibration curves, and decision curves. RESULTS: Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition were identified as independent risk factors for FI in critically ill children receiving EN (P<0.05). Based on these factors, a nomogram prediction model for FI in critically ill children receiving EN was developed. The area under the receiver operating characteristic curve for the training set and validation set was 0.934 (95%CI: 0.906-0.963) and 0.852 (95%CI: 0.787-0.917), respectively, indicating good discrimination of the model. The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit (χ 2=12.559, P=0.128). Calibration curve and decision curve analyses suggested that the model has high predictive efficacy and clinical application value. CONCLUSIONS Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition are independent risk factors for FI in critically ill children receiving EN. The nomogram model developed based on these factors exhibits high predictive efficacy and clinical application value.
Humans ; Critical Illness ; Enteral Nutrition/adverse effects* ; Male ; Risk Factors ; Female ; Child, Preschool ; Infant ; Nomograms ; Retrospective Studies ; Child ; Logistic Models

BACKGROUND: Quantitative flow ratio (QFR) holds significant value in guiding drug-coated balloon (DCB) treatment and enhancing outcomes. However, the predictive capability of post-angioplasty QFR for long-term clinical events in patients with de novo lesions who receive DCB treatment remains uncertain. The aim of this study was to explore the potential significance of post-angioplasty QFR measurements in predicting clinical outcomes in patients underwent DCB treatment for de novo lesions. METHODS: Patients who underwent DCB-only intervention for de novo lesions were enrolled. QFR was conducted after DCB treatment. The patients were then categorized based on post-angioplasty QFR. The primary endpoint was major adverse cardiac events (MACE), encompassing all-cause death, cardiovascular death, nonfatal myocardial infarction, stroke, and target vessel revascularization. RESULTS: A total of 553 patients with 561 lesions were included. The median follow-up period was 505 days, during which 66 (11.8%) MACEs occurred. Based on post-procedural QFR grouping, there were 259 cases in the high QFR group (QFR > 0.93) and 302 cases in the low QFR group (QFR ≤ 0.93). Kaplan-Meier analysis revealed a significantly higher cumulative incidence of MACE in the low QFR group (log-rank P = 0.004). The multivariate Cox proportional hazards model demonstrated a significant inverse correlation between QFR and the occurrence of MACEs (HR = 0.522, 95%CI: 0.289-0.942, P = 0.031). Landmark analysis indicated that high QFR had a significant reducing effect on the cumulative incidence of MACEs within 1 year (log-rank P = 0.016) and 1-5 years (log-rank P = 0.026). CONCLUSIONS In patients who underwent DCB-only treatment for de novo lesions, higher post-procedural QFR values (> 0.93) were identified as an independent protective factor against adverse prognosis.

OBJECTIVES: To explore the expression profile of circular RNAs (circRNAs) and their potential roles in prognosis and progression of Wilms' tumor (WT). METHODS: Four pairs of WT and adjacent tissues were collected for high-throughput circRNA sequencing to identify the differentially expressed circular RNAs. RT-qPCR was used to verify the expression levels of the top 6 candidate circRNAs in the clinical samples. hsa_circ_0001900 was selected for analysis of its correlation with clinicopathological features and prognosis in 34 patients with WT. Sanger sequencing and RNase R digestion experiments were used to verify the cycling site and structural stability of hsa_circ_0001900 molecule. RESULTS: A total of 23 978 circular RNA molecules were identified in WT tissues by high-throughput circular RNA sequencing, and among them 614 were differentially expressed in WT. hsa_circ_0001900 showed the highest expression level among the differentially expressed circRNAs, which was consistent with the findings in clinical tumor samples and the sequencing results. Correlation analysis showed that hsa_circ_0001900 expression level was positively correlated with WT volume, and the children with high hsa_circ_0001900 expression had a lowered recurrence-free survival rate. The results of Sanger sequencing verified the circular splice site sequence of the molecule, and Rnase R digestion assay confirmed its stable covalent structure. CONCLUSIONS This study presents a comprehensive expression profile of circular RNAs in WT, and the expression level of hsa_circ_0001900 is related to the size of WT and the patients' prognosis, suggesting its possible role as a key driving gene in WT progression.
Humans ; RNA, Circular ; Wilms Tumor/pathology* ; Prognosis ; High-Throughput Nucleotide Sequencing ; Kidney Neoplasms/genetics* ; Sequence Analysis, RNA ; Male ; Female

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Clear aligner treatment is a novel technique in current orthodontic practice. Distinct from traditional fixed orthodontic appliances, clear aligners have different material features and biomechanical characteristics and treatment efficiencies, presenting new clinical challenges. Therefore, a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique. This expert consensus discusses case selection and grading of treatment difficulty, principle of clear aligner therapy, clinical procedures and potential complications, which are crucial to the clinical success of clear aligner treatment.
Humans ; Consensus ; Orthodontic Appliance Design ; Orthodontic Appliances, Removable ; Tooth Movement Techniques/methods* ; Malocclusion/therapy* ; Orthodontics, Corrective/instrumentation*

Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans ; Malocclusion/diagnostic imaging* ; Child ; Consensus

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]