OBJECTIVE To systematically analyze the compatibility stability of commonly used intravenous antibiotics in the intensive care unit （ICU）， and to provide evidence-based support for rational clinical drug use. METHODS Medication data from the ICU of Hebei General Hospital between January and December 2024 were extracted from the Prescription Automatic Screening System. Commonly used intravenous antibiotics and other intravenous drugs in the ICU were selected through consultations with critical care and pharmacy experts in Hebei province， drug package inserts and compatibility information retrieved from Micromedex， Trissel’s Injectable Drug Handbook and PubMed. The physicochemical stability of drug combinations was analyzed. In addition， Cytoscape 3.10.2 software was used to construct a drug compatibility network for identifying high-risk drugs. RESULTS &CONCLUSIONS A total of 904 pairwise drug combinations involving 16 antibacterial agents and 65 intravenous drugs were collected. Among them， 549 combinations （60.7%） were compatible， 88 combinations （9.7%） were incompatible， 82 combinations （9.1%） had conflicting evidence， and 185 combinations （20.5%） lacked valid data support. High-risk combination drugs primarily involved Amphotericin B for injection， Ceftazidime for injection， Imipenem-cilastatin for injection， Ceftriaxone sodium for injection， Vancomycin hydrochloride for injection， etc. The main risk factors for drug-drug incompatibility included drug concentration， temperature， mixing rate， pH， and chemical structure. In clinical practice， drugs and diluents should be selected rationally based on specific compatibility data， and research and monitoring of drug compatibility should be further strengthened.

Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

Objective: To investigate the factors influencing the co-prevalence of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia, so as to provide a data foundation and theoretical basis for developing targeted intervention measures. Methods: In September and October 2024, a stratified cluster random sampling method was employed to select 139 102 students from 539 schools across 12 leagues/cities and 103 banners/counties in Inner Mongolia Autonomous Region. Participants who were diagnosed with allergic rhinitis by a doctor at least once within one year and had a body mass index ≥ 28 kg/m 2 were considered to have comorbid conditions. Results: The coprevalence rate of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia was 6.4% (8 931 cases). Lasso-Logistic regression revealed that nonboarding status, higher maternal education, consuming high protein foods ≥1 time daily, occasionally or never eating breakfast, engaging in moderate to vigorous physical activity for ≥60 minutes on fewer than half of holidays, and having been exposed to second hand smoke in person within the past seven days were associated with higher odds ratios for co-prevalence of allergic rhinitis and obesity( OR = 1.23 , 1.22-1.63, 1.20, 1.19, 1.38, 1.35); being female, higher grade level, residence in flag/county/district areas, non only child status, never having consumed a full glass of alcohol, non hypertensive status, and households without pets were associated with lower co-prevalence risks ( OR =0.65, 0.67-0.77, 0.81, 0.87, 0.73, 0.41, 0.68) (all P <0.05). The ROC curve indicated an area under the curve of 0.64 for the predictive model, demonstrating satisfactory discriminatory ability. The calibration curve showed consistency between predicted and actual occurrence probabilities. Conclusions The co-prevalence of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia is closely associated with demographic characteristics, dietary behaviours, and lifestyle habits. Future prevention and control strategies should prioritize these factors to implement targeted interventions.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

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

To optimize the traditional refining process of Hydrargyrum Chloratum Compositum(HCC) and explore the change law of substances before and after refining, this study applied the hierarchical analysis method(AHP)-entropy weight method, using appearance, yield, and mercuric chloride content as evaluation indexes. The temperature and time of mild and strong fire were examined as single factors, and an L_9(3~4) orthogonal experiment was used to optimize the refining process. An infrared thermal imaging platform was set up to record the temperature changes on the surface of the tank, aiming to establish a standardized operating procedure for the refining process. Elemental changes, physical phase changes, and thermal property changes of the materials before and after refining were analyzed using atomic absorption spectrophotometry(AAS), X-ray diffraction(XRD) and differential scanning calorimetry(DSC). The results showed that the average overall score of the finished product obtained from the optimized HCC refining process(with mild fire temperature of 102 ℃, mild fire refining time of 30 min, strong fire temperature of 178 ℃, and strong fire refining time of 68 min) was 91.59, with an RSD of 0.076%, indicating that the process is stable and feasible. Combined with thermal imaging data and related research results, it was found that, at the strong fire temperature, mercury ions and nitrate ions generated mercuric chloride under the catalysis of other ions. The mercury content of mercurous chloride, mercuric chloride synthesized from nitric acid, HCC, and the pre-refined sample was 84.535%, 72.376%, 70.838%, and 41.334%, respectively. The highest intensity of the(120) diffraction peak for HCC appeared around 20.36°, but the residual fit value was larger. The synthesis of mercuric chloride from HCC and nitric acid showed an exothermic peak at 190-204 ℃, with the peak shape exhibiting a rightward trend. This study optimized the traditional refining process of HCC and analyzed the elemental changes, physical phase changes, and thermal property changes before and after refining. The findings provide experimental data for exploring the changing patterns in the refining process of HCC and its pharmacological value, as well as for standardizing the traditional refining process in clinical practice.
Drugs, Chinese Herbal/chemistry* ; X-Ray Diffraction ; Temperature ; Calorimetry, Differential Scanning ; Mercuric Chloride/chemistry*

Hongsheng Dan, historically referred to as the "surgical sacred medicine", is at risk of losing its refining technology in contemporary times. This study aimed to preserve and innovate this traditional non-heritage refining technology. By utilizing the analytic hierarchy process(AHP) combined with the entropy weight method, this study established the hierarchical structure model of refining process of Hongsheng Dan and conducted a single factor experiment and an L_9(3~4) orthogonal experiment to optimize the refining method of Hongsheng Dan. Additionally, the study employed infrared thermal imaging to monitor temperature variations of Hongsheng Dan during the refining process. The optimized refining parameters for Hongsheng Dan were established as follows: a slow fire temperature of 175 ℃ with a duration of 30 minutes, a strong fire temperature of 270 ℃ with a duration of 60 minutes, and a tail fire temperature of 180 ℃ with a duration of 15 minutes. The stability and feasibility of this optimized process were confirmed through validation tests. The research focused on the material transformation of Hongsheng Dan, starting from the material changes during the refining process of Hongsheng Dan and the synthesis of mercuric oxide from nitric acid. The study investigated elemental transformations, physical phase changes, and alterations in thermal properties. 78.98% of the mercury in Hongsheng Dan and 80.21% of the mercury in mercuric oxide from nitric acid were retained. The diffraction peak intensity of the(011) crystal plane of Hongsheng Dan was highest at approximately 30.07°, indicating that the(011) crystal plane had a preferred crystalline orientation. Furthermore, the temperature range for the alteration in thermal properties during the refining process of Hongsheng Dan was found to be between 80 ℃ and 130 ℃. This research not only optimized the refining technology of Hongsheng Dan but also pioneered the application of infrared thermal imaging to study temperature changes throughout the refining process. By exploring the material transformation patterns of Hongsheng Dan and the synthesis of mercuric oxide from nitric acid, the study provided technical support for the preservation and innovation of Hongsheng Dan.
Drugs, Chinese Herbal/standards* ; Temperature

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control