ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

The chemical constituents from the n-butanol fraction of ethanol extract of safflower (Carthamus tinctorius L.) were isolated and purified using chromatographic process including MCI Gel CHP-20, ODS, Sephadex LH-20 column chromatography, and semi-preparative HPLC method, and one alkyne and two phenylpropanoid derivants were obtained. Their structures were identified as (5R,E)-tetradecane-12-ene-8,10-diyne-1,5,14-triol (1), (E)-8-O-β-D-glucopyranosyl n-butyl cinnamate (2), and (7S,8S)-7-(4-hydroxy-3-methoxybenzene)-7-butyl-8,9-diol (3) by modern spectroscopy methods (1D NMR, 2D NMR, UV, IR and MS). 1-3 are all new compounds. Compounds 1-3 were screened for their anti-renal fibrosis activities in vitro, and none of them showed obvious effect.

Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

Background The positive rate of work-related musculoskeletal disorders (WMSDs) among coal mine workers remains high, which seriously affects the quality of life of the workers. Objective To estimate the prevalence of WMSDs among coal miners in Shanxi Province and analyze their influencing factors. Methods From May to December 2023, 2315 coal miners from a coal mine enterprise inShanxi Province were selected by convenience sampling, and the self-administered Basic Situation Survey Scale, Musculoskeletal Disorders Questionnaire, Effort-Reward Imbalance Questionnaire, and Pittsburgh Sleep Quality Scale were used to evaluate general demographic characteristics, work organization characteristics, living habits, sleep quality, occupational stress, and occurrence of WMSDs symptoms and the corresponding absences (sickness absence) in past 1 year. The positive rate and absenteeism rate of WMSDs were caculated, and Pearson's chi-square test was used for identify influencing factors of WMSDs, and finally a binary logistic regression method was used to further studying the factors. Results A total of 2577 questionnaires were distributed in this survey, and 2315 valid questionnaires were recovered, with an effective recovery rate of 89.9%. The positive rate of WMSDs symptoms was 48.7% (1127/2315), the absenteeism rate due to WMSDs was 22.6% (523/2315), and the waist (17.5%), neck (11.7%), and knee (9.0%) were the most common areas presenting WMSDs symptoms. The results of logistic regression showed that compared with ≤10 years of service, the risk of WMSDs was higher for those with > 20 years of service (OR=2.167, 95%CI: 1.419, 3.311). Compared with the daily working time of ≤8 h, the risk of WMSDs was higher for those >8 h daily working time (OR=1.463, 95%CI: 1.211, 1.767). A higher risk of WMSDs was reported in workers with moderate labor intensity (OR=1.247, 95%CI: 1.009, 1.542) or heavy labor intensity (OR=1.570, 95%CI: 1.215, 2.027) than those with light labor intensity. The higher the education level (OR _{high school and technical secondary school}=1.866, 95%CI: 1.435, 2.425; OR _{junior college/bachelor degree or above}=1.953, 95%CI: 1.445, 2.639), the higher the risk of WMSDs. The risk of WMSDs was higher in workers reporting smoking (OR=1.225, 95%CI: 1.021, 1.470) or alcohol consumption (OR=1.345, 95%CI: 1.122, 1.612). The risk of WMSDs in coal miners with high occupational stress (OR=1.229, 95%CI:1.030, 1.466) or those with sleep disorders (OR=3.616, 95%CI:2.824, 4.629) was higher than that in workers with low occupational stress or no sleep disorders respectively. Conclusion The positive rate of WMSDs among coal mine personnel in Shanxi Province is high, and education level, length of service, daily working hours, smoking, alcohol consumption, labor intensity, sleep disorders, and occupational stress are influencing factors for WMSDs.

BACKGROUND:Periprosthetic fracture of the femoral of the knee after total knee arthroplasty is one of the common complications,and there is a lack of biomechanical research on the periprosthetic fractures of the femoral of the knee under different bone strength conditions.The three-dimensional finite element analysis can provide a biomechanical basis for clinical practice. OBJECTIVE:To investigate the biomechanical changes of anterior femoral notching after total knee arthroplasty under different bone strengths,and to provide a mechanical basis for the clinical prevention of supracondylar femoral periprosthetic fractures after knee arthroplasty. METHODS:The femoral CT data of healthy adults were obtained,and the three-dimensional model of femoral lateral replacement of the knee joint was established by Mimics,Geomagic studio,and Solidworks software.Anterior femoral notching models of different depths were constructed,and the models were imported into ANSYS software to analyze the changes of biological stress on the femoral condyle with different bone strengths and different anterior femoral notching depths.The stress changes of the femoral anterior condyle section after and before the filling of anterior femoral notching with bone cement were analyzed. RESULTS AND CONCLUSION:(1)Under any bone strength,the supracondylar stress increased with the depth of anterior femoral notching.In normal bone conditions,there was a stress abrupt change point when the anterior femoral notching depth was between 3 mm and 4 mm.In the case of osteoporosis,there was a stress abrupt point when the anterior femoral notching depth was between 2 mm and 3 mm.(2)When anterior femoral notching occurred during knee arthroplasty and the depth exceeded the thickness of the bone cortex,the supracondylar stress of the femoral gradually increased as the bone strength decreased.(3)The stress of the anterior femoral condyle section decreased when the model with an anterior femoral notching depth of 3 mm was filled with bone cement.(4)The results show that anterior femoral notching should be avoided during knee arthroplasty,especially in patients with osteoporosis.If anterior femoral notching occurs during surgery,bone cement can be used to evenly fill the anterior femoral notching to reduce the supracondylar stress of the femur and reduce the incidence of periprosthetic fractures of the femoral joint

This article takes the award-winning traditional Chinese medicine（TCM） patents in the China Patent Award as the breakthrough point to analyze the innovative research progress and achievements of TCM in the past thirty years， such as type of patentees， geographical distribution， technology types， international layout and textual features. The China Patent Award has been selected for 24 sessions so far， with 192 patents awarded for TCM， accounting for 2.3% of the total number of awarded patents. Among the award-winning patents of TCM， the patentees are mainly enterprises， and the active geographic regions of TCM innovation include Guangdong， Shandong， Guangxi， Guizhou， Jiangsu and other provinces. The types of award-winning patents mainly focus on TCM compositions， followed by preparation methods and new applications. The main clinical applications include cardiovascular and cerebrovascular diseases， respiratory system diseases and orthopedic diseases. However， there is still much room for improvement in the international layout， and the quality of text has been steadily improving year by year. Obviously， award-winning patents represent a high level in various aspects， including patent quality， technology advancement， protection strength and social benefits. This article analyzes the overall situation of patent awards in TCM， and discusses the gold award-winning patented technologies， the preparation method of HuoXiang Zhengqi liquid oral preparation（CN911072543） and a method of preparing anti-cancer drug elemene from Curcuma wenyujin（CN200910162658.1）， as representative technologies of TCM compounds and extracts， respectively， providing references for future innovation and intellectual property protection related to TCM.

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

[Objective] To evaluate the therapeutic effect of autologous platelet-rich plasma (PRP) for chronic endometritis (CE). [Methods] A retrospective analysis was conducted on 36 patients with CE who had failed antibiotic treatment. The clinical outcomes, pregnancy rates, and early miscarriage rates were assessed following PRP treatment. Meanwhile, the CE patients of receiving first/second-line Clinical drug treatment were used as the control experiment group. [Results] Among the 36 patients treated with PRP, the effective rate was 83.33%. The clinical pregnancy rate in the treatment group was higher than that in the control group [17-36(65.38%) vs 14/27(51.85%), P>0.05], and the early miscarriage rate was lower 2/17(11.76%) vs 2/14(14.29%), P>0.05]. [Conclusion] PRP therapy is effective for CE, with no antibiotic resistance or side effects, and can be widely promoted as a treatment option.