Quality control is a key link in the modernization process of traditional Chinese medicine(TCM). Studies have shown that the effects of active components in TCM depend on not only their chemical composition but also their suitable physical forms and states. The physical phase structures, such as micelles, vesicles, gels, and nanoparticles, can improve the solubility, delivery efficiency, and targeting precision of active components. These structures significantly enhance the pharmacological activity while reducing the toxicity and side effects, demonstrating functional activity surpassing that of active components and highlighting the key effects of "structures" on "functions" of active components. Taking the physical phase structure as a breakthrough point, this paper outlines the common types of TCM physical phase structures. Furthermore, this paper explores how to realize the quality upgrading of TCM through the precise regulation of physical phase structures based on the current applications and potential of TCM physical phase structures in processing to increase the efficacy and reduce the toxicity, compounding and decocting processes, drug delivery systems, and quality control, aiming to provide novel insights for the future quality control of TCM.
Quality Control ; Drugs, Chinese Herbal/standards* ; Medicine, Chinese Traditional/standards* ; Humans ; Drug Delivery Systems

OBJECTIVE: To evaluate the effects of Chinese patent medicine Huatuo Zaizao Pill (HTZZ) on neurological function and limb motor in ischemic stroke (IS) patients during convalescence. METHODS: This is a prospective, open-labelled, randomized controlled trial. Patients with IS were recruited from the Neurology Department of Xiyuan Hospital of China Academy of Chinese Medical Sciences from May 2021 to June 2023. Eligible participants were randomly assigned to the HTZZ (40 cases) or control group (40 cases) at a ratio of 1:1. The HTZZ group was treated with oral HTZZ (8 g, thrice daily) combined with conventional treatment, while the control group received only conventional treatment. The treatment duration was 12 weeks. The primary outcome was the change in Modified Ashworth Scale (MAS) score from baseline to week 6 and 12. Secondary outcomes included changes in scores of National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment (FM), and Barthel Index (BI) from baseline to week 6 and 12, as well as lipid indices after 12 weeks. All adverse events (AEs) were recorded and liver and kidney indices were evaluated. RESULTS: A total of 72 patients completed the study (38 in the HTZZ group and 34 in the control group). Compared with the control group, the HTZZ group demonstrated significant improvements in MAS, NIHSS, FM, and BI scores following 6 and 12 weeks of treatment in both intent-to-treat and per-protocol analyses (all P<0.05). No significant differences were noted between groups in lipid indices, AEs, and liver and kidney dysfunction after 12 weeks (P>0.05). CONCLUSIONS HTZZ alleviated spasticity and enhanced neurological function and prognosis of IS patients during convalescence. However, further evaluation of HTZZ's effect on IS outcomes is warranted in clinical trials with larger sample sizes and extended observation periods. (Trial registration No. NCT04910256).
Humans ; Drugs, Chinese Herbal/pharmacology* ; Male ; Female ; Ischemic Stroke/physiopathology* ; Middle Aged ; Aged ; Recovery of Function/drug effects* ; Convalescence ; Extremities/physiopathology* ; Treatment Outcome ; Prospective Studies

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

OBJECTIVE: This study aimed to reexplore minimum iodine excretion and to build a dietary iodine recommendation for Chinese adults using the obligatory iodine loss hypothesis. METHODS: Data from 171 Chinese adults (19-21 years old) were collected and analyzed based on three balance studies in Shenzhen, Yinchuan, and Changzhi. The single exponential equation was accordingly used to simulate the trajectory of 24 h urinary iodine excretion as the low iodine experimental diets offered (iodine intake: 11-26 μg/day) and to further deduce the dietary reference intakes (DRIs) for iodine, including estimated average requirement (EAR) and recommended nutrient intake (RNI). RESULTS: The minimum iodine excretion was estimated as 57, 58, and 51 μg/day in three balance studies, respectively. Moreover, it was further suggested as 57, 58, and 51 μg/day for iodine EAR, and 80, 81, and 71 μg/day for iodine RNI or expressed as 1.42, 1.41, and 1.20 μg/(day·kg) of body weight. CONCLUSION The iodine DRIs for Chinese adults were established based on the obligatory iodine loss hypothesis, which provides scientific support for the amendment of nutrient requirements.
Humans ; Iodine/administration & dosage* ; Male ; Female ; China ; Young Adult ; Diet ; Adult ; Nutritional Requirements ; East Asian People

Objective To investigate the age-related changes of the mandibular third molar root pulp visibility in individuals in East China,and to explore the feasibility of applying this method to deter-mine whether an individual is 18 years or older.Methods A total of 1 280 oral panoramic images were collected from the 15-30 years old East China population,and the mandibular third molar root pulp visibility in all oral panoramic images was evaluated using OLZE 0-3 four-stage method,and the age distribution of the samples at each stage was analyzed using descriptive statistics.Results Stages 0,1,2 and 3 first appeared in 16.88,19.18,21.91 and 25.44 years for males and in 17.47,20.91,22.01 and 26.01 years for females.In all samples,individuals at stages 1 to 3 were over 18 years old.Conclusion It is feasible to determine whether an individual in East China is 18 years or older based on the mandibular third molar root pulp visibility on oral panoramic images.

Objective To develop and validate a risk prediction model based on early platelet-related parameters for bronchopulmonary dysplasia(BPD)in neonates admitted to the neonatal intensive care unit(NICU),and to facilitate early identification and intervention in high-risk populations.Methods Clinical data of 291 preterm infants with a gestational age(GA)≤32 weeks or a birth weight(BW)＜1 500 g,admitted to the NICU,were retrospectively analyzed.Out of these,214 cases were selected as the modeling group.This group was further categorized into the BPD group(n=76)and the non-BPD group(n=138),based on whether they required oxygen therapy at 28 days post-birth.Perinatal data,platelet-related parameters and other indicators between the two groups.Univariate and multivariate Logistic regression analyses were conducted to identify BPD risk factors,followed by the construction of a nomogram.An additional cohort of 105 preterm infants with GA≤32 weeks or BW＜1 500 g,were used to validate the model.This cohort was divided into the BPD group(n=43)and the non-BPD(n=62)group.Receiver operating characteristic(ROC)curve and calibration curve were used to internally verify the efficiency of the prediction model.Results The Logistic regression analysis identified GA,BW,Apgar score at 5 minutes≤7,invasive ventilation,platelet count(PLT)and mean platelet volume(MPV)as significant factors in the model(P＜0.05).The constructed nomogram was formulated using R language,and the areas under the ROC curve(AUC)for the three models were 0.908,0.931 and 0.918,respectively(P＜0.05).The verification group was verified by Bootstrap.The calibration curve showed a good fit.The internal validation AUC values of the three models were 0.877,0.890 and 0.886,respectively.Conclusion GA,BW,invasive ventilation,Apgar score at 5 minutes≤7,MPV and PLT are key risk factors for BPD onset.The risk prediction model based on these indicators can effectively predict BPD,providing clinicians with a valuable tool for early detection and intervention in the development of BPD.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Fluorescence anisotropy(FA)analysis has many advantages such as no requirement of separation,high throughput and real-time detection,and thus has been widely used in many fields,including biochemical analysis,food safety detection,environmental monitoring,etc.However,due to the small volume or mass of the target,its combination with the fluorescence probe cannot produce significant signal change.To solve this issue,researchers often use nanomaterials to enhance the mass or volume of fluorophore to improve the sensitivity.Nevertheless,this FA amplification strategy also has some disadvantages.Firstly,nanomaterials are easy to quench fluorescence.As a result,the FA value is easily influenced by light scattering,which reduces the detection accuracy.Secondly,fluorescent probes in most methods require complex modification steps.Therefore,it is necessary to develop new FA probes that do not require the amplification of volume and mass or modification.As a new kind of nanomaterials,luminescent metal-organic framework(MOF)has a large volume(or mass)and strong fluorescence emission.It does not require additional signal amplification materials.As a consequence,it can be used as a potential FA probe.This study successfully synthesized a lanthanide metal organic framework(Ce-TCPP MOF)using cerium ion(Ce3+)as the central ion and 5,10,15,20-tetra(4-carboxylphenyl)porphyrin(H2TCPP)as the ligand through microwave assisted method,and used it as a novel unmodified FA probe to detect phosphate ions(Pi).In the absence of Pi,Ce-TCPP MOF had a significant FA value(r).After addition of Pi,Pi reacted with Ce3+in MOF and destroyed the structure of MOF into the small pieces,resulting in a decrease in r.The experimental results indicated that with the increase of Pi concentration,the change of the r of Ce-TCPP MOF(Δr)gradually increased.The Δr and Pi concentration showed a good linear relationship within the range of 0.5-3.5 μmol/L(0.016-0.108 mg/L).The limit of detection(LOD,3σ/k)was 0.41 μmol/L.The concentration of Pi in the Jialing River water detected by this method was about 0.078 mg/L,and the Pi value detected by ammonium molybdate spectrophotometry was about 0.080 mg/L.The two detection results were consistent with each other,and the detection results also meet the ClassⅡwater quality standard,proving that this method could be used for the detection of Pi in complex water bodies.