Employing bibliometric methods and adhering to principles of textual research， this study systematically investigated prescription source， formula name， composition evolution， dose evolution， origin， processing， ancient and modern applications of Xiaofengsan. Xiaofengsan， also known as Renshen Xiaofengsan and Chantui Xiaofengsan， was first recorded in the Taiping Huimin Hejijufang（hereafter referred to as Jufang） of the Southern Song dynasty. The formula composition included Schizonepetae Spica， Glycyrrhizae Radix et Rhizoma， Chuanxiong Rhizoma， Notoptery Rhizoma et Radix， Bombyx Batryticatus， Saposhnikoviae Radix， Poria， Cicadae Periostracum， Pogostemonis Herba， Ginseng Radix et Rhizoma， Magnoliae Officinalis Cortex and Citri Reticulatae Pericarpium， a total of 12 medicinal materials. In terms of the evolution of formula composition， formulas across dynasties largely aligned with those recorded in Jufang， with only minor variations in application. The results of the formula dosage research indicated that one dose of medication in Jufang corresponded to the following modern dosages：Schizonepetae Spica of 82.6 g， Glycyrrhizae Radix et Rhizoma of 82.6 g， Chuanxiong Rhizoma of 82.6 g， Notoptery Rhizoma et Radix of 82.6 g， Bombyx Batryticatus of 82.6 g， Saposhnikoviae Radix of 82.6 g， Poria of 82.6 g， Cicadae Periostracum of 82.6 g， Pogostemonis Herba of 82.6 g， Ginseng Radix et Rhizoma of 82.6 g， Magnoliae Officinalis Cortex of 20.65 g and Citri Reticulatae Pericarpium of 20.65 g， the origins of all the constituent drugs were consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The results of the investigation into the decoction method indicated that the aforementioned drugs should be finely ground into powder（pass through the No.5 sieve）， and 8.26 g was taken for each dose， which was taken with the clear liquid obtained by steeping tea leaves in boiling water for several minutes. This mixture was administered three times daily， 30 min after meals. The ancient functional indications of this formula mainly involved dispelling wind-heat， eliminating pathogenic factors and regulating the middle Jiao. It primarily treated all wind-heat syndromes manifesting as skin diseases， predominantly affecting the upper body， especially the head and face. The diseases involved in modern applications were mostly dermatological diseases， including urticaria， eczema， atopic dermatitis and others. In this paper， by combing the relevant ancient literature， the key information of Xiaofengsan was textual researched， in order to provide reference for the modern application and development of this formula.

In the context of the modernization of traditional Chinese medicine （TCM）， the inheritance of the experiences of famous doctors faces significant challenges due to its complex nonlinear characteristics and dynamic evolution. There are still issues in the current inheritance system， such as the homogenization of talent cultivation models， lack of standardized mentoring practices， and monotonous evaluation method， which hinder the systematic inheritance and innovative development of famous doctors' experiences. Based on a systematic review of the current state of artificial intelligence （AI）-assisted inheritance of famous doctors' experiences， this study explores innovative pathways for deep integration of modern information technologies with famous doctors' experiences from key dimensions， including data authenticity assurance， interdisciplinary collaboration mechanisms， and the establishment of dynamic inheritance standards. It proposes a paradigm shift in the inheritance of TCM famous doctors' experiences in the AI era， aiming to build a new TCM inheritance system of "digital intelligence empowerment and cross-disciplinary innovation"， providing theoretical support and practical pathways for the inheritance of famous doctors' experiences in TCM.

ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

Background Temporal kurtosis (without frequency weighting, i.e., Z-weighted kurtosis) can evaluate noise-induced hearing loss (NIHL). However, few studies have considered the function of frequency weighting (A- or C-weighted) kurtosis on NIHL. Objective To study the significance of A- and C-weighted kurtosis adjustment for equivalent sound level (L'_{EX,8 h}) in evaluating occupational hearing loss. Methods A cross-sectional survey was used to select 973 noise-exposed workers in seven industries as the subjects. The noise exposure of all workers was assessed by distributions of A-, C-, and Z-weighted kurtosis (e.g., K_A, K_C, and K_Z) and respective adjusted equivalent sound level (e.g., L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z). The significance of A- and C-weighted kurtosis in evaluating NIHL was evaluated by correlations between three types of L'_{EX,8 h} and NIHL, and improvement of noise-induced permanent threshold shift (NIPTS) underestimation predicted by the ISO prediction model (Acoustics—Estimation of noise-induced hearing loss, ISO 1999-2013). Results The median K_A, K_C, and K_Z were 68.33, 28.22, and 19.82, respectively. The binary logistic regression showed that L_{EX, 8 h}-K_A, L_{EX, 8 h}-K_C, and L'_{EX, 8 h}-K_Z were risk factors for NIHL (OR>1, P<0.001). The receiver operating characteristic (ROC) curve showed that when the outcome variable was noise-induced hearing impairment (NIHI), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.625, 0.628, and 0.625, respectively. When the outcome variable was high-frequency noise-induced hearing loss (HFNIHL), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX, 8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.624, 0.623, and 0.622, respectively (P<0.05). The order of underestimation improvement values predicted by L'_{EX,8 h} for NIPTS₁₂₃₄ was: L'_{EX,8 h}-K_A (4.68 dB HL)>L'_{EX,8 h}-K_C (4.38 dB HL)>L'_{EX,8 h}-K_Z (4.28 dB HL) (P<0.001). The order of underestimation improvement values predicted by L'_{EX,8 h}-K for NIPTS₃₄₆ was: L'_{EX,8 h}-K_A (7.20 dB HL)>L'_{EX,8 h}-K_C (6.83 dB HL)>L'_{EX,8 h}-K_Z (6.71 dB HL) (P<0.001). Conclusion The adjustment of A- and C-weighted kurtosis to equivalent sound level L_{EX,8 h} can effectively improve the accuracy of the ISO 1999 prediction model in NIPTS prediction, and compared with the C-weighted, the A-weighted kurtosis can improve the result of the ISO 1999 prediction model in terms of underestimating NIPTS.

In this study， bibliometric methods were used to systematically investigate the name and origin， the evolution of prescription composition， dose evolution， origin and processing method， decoction method， ancient application， modified application， modern application and other information of Huoxiang Zhengqisan. After research， Huoxiang Zhengqisan， also known as Huoxiang Zhengqitang， was first recorded in Taiping Huimin Hejijufang. The original formula is composed of 41.3 g of Arecae Pericarpium， 41.3 g of Angelicae Dahuricae Radix， 41.3 g of Perilla frutescens（actually Perillae Folium）， 41.3 g of Poria， 82.6 g of Pinelliae Rhizoma， 82.6 g of Atractylodis Macrocephalae Rhizoma， 82.6 g of Citri Reticulatae Pericarpium（actually Citri Exocarpium Rubbum）， 82.6 g of Magnoliae Officinalis Cortex， 82.6 g of Platycodonis Radix， 123.9 g of Pogostemonis Herba， and 103.25 g of Glycyrrhizae Radix et Rhizoma. In this formula， Magnoliae Officinalis Cortex is processed according to the specifications for ginger-processed products， Glycyrrhizae Radix et Rhizoma is processed according to the specifications for stir-fried products， and other herbs are used in their raw products. The botanical sources of the herbs are consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The above herbs are ground into a fine powder with a particle size passing through a No. 5 sieve. For each dose， take 8.26 g of the powdered formula， add 300 mL of water， along with 3 g of Zingiberis Rhizoma Recens and 3 g of Jujubae Fructus， and decoct until reduced to 140 mL. The decoction should be administered hot， with three times daily. To induce sweating， the patient should be kept warm under a quilt， and an additional dose should be prepared and taken if needed. This formula is traditionally used to relieve the exterior and resolve dampness， regulate Qi and harmonize the middle， which is mainly used to treat a series of diseases of digestive and respiratory systems. However， potential adverse reactions， including allergies， purpura and disulfiram-like reactions， should be considered during clinical use. Huoxiang Zhengqisan features a rational composition， extensive clinical application， and strong potential for further research and development.

In this study， bibliometric methods were used to systematically investigate the name and origin， the evolution of prescription composition， dose evolution， origin and processing method， decoction method， ancient application， modified application， modern application and other information of Huoxiang Zhengqisan. After research， Huoxiang Zhengqisan， also known as Huoxiang Zhengqitang， was first recorded in Taiping Huimin Hejijufang. The original formula is composed of 41.3 g of Arecae Pericarpium， 41.3 g of Angelicae Dahuricae Radix， 41.3 g of Perilla frutescens（actually Perillae Folium）， 41.3 g of Poria， 82.6 g of Pinelliae Rhizoma， 82.6 g of Atractylodis Macrocephalae Rhizoma， 82.6 g of Citri Reticulatae Pericarpium（actually Citri Exocarpium Rubbum）， 82.6 g of Magnoliae Officinalis Cortex， 82.6 g of Platycodonis Radix， 123.9 g of Pogostemonis Herba， and 103.25 g of Glycyrrhizae Radix et Rhizoma. In this formula， Magnoliae Officinalis Cortex is processed according to the specifications for ginger-processed products， Glycyrrhizae Radix et Rhizoma is processed according to the specifications for stir-fried products， and other herbs are used in their raw products. The botanical sources of the herbs are consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The above herbs are ground into a fine powder with a particle size passing through a No. 5 sieve. For each dose， take 8.26 g of the powdered formula， add 300 mL of water， along with 3 g of Zingiberis Rhizoma Recens and 3 g of Jujubae Fructus， and decoct until reduced to 140 mL. The decoction should be administered hot， with three times daily. To induce sweating， the patient should be kept warm under a quilt， and an additional dose should be prepared and taken if needed. This formula is traditionally used to relieve the exterior and resolve dampness， regulate Qi and harmonize the middle， which is mainly used to treat a series of diseases of digestive and respiratory systems. However， potential adverse reactions， including allergies， purpura and disulfiram-like reactions， should be considered during clinical use. Huoxiang Zhengqisan features a rational composition， extensive clinical application， and strong potential for further research and development.